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string(54) "Chronic pain associated with poor health — and COVID"
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string(82) "https://coolnspicy.com/science/chronic-pain-associated-with-poor-health-and-covid/"
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string(15) "Michael Steiner"
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["pubdate"]=>
string(31) "Fri, 04 Nov 2022 00:22:03 +0000"
["category"]=>
string(33) "scienceChronicCOVIDhealthpainpoor"
["guid"]=>
string(29) "https://coolnspicy.com/?p=311"
["description"]=>
string(880) "Journal Reference: David G. Blanchflower, Alex Bryson. Chronic pain: Evidence from the national child development study. PLOS ONE, 2022; 17 (11): e0275095 DOI: 10.1371/journal.pone.0275095 Chronic pain — pain lasting at least three months — is a serious problem affecting a large number of people: according to the National Academies of Science, Engineering and Medicine, more ... Read more
The post Chronic pain associated with poor health — and COVID first appeared on .
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Journal Reference:
- David G. Blanchflower, Alex Bryson. Chronic pain: Evidence from the national child development study. PLOS ONE, 2022; 17 (11): e0275095 DOI: 10.1371/journal.pone.0275095
Chronic pain — pain lasting at least three months — is a serious problem affecting a large number of people: according to the National Academies of Science, Engineering and Medicine, more than 100 million Americans suffer from chronic pain.
In the new work, the researchers studied people enrolled in the National Child Development Survey, a study following all those born in one week in March 1958 in England, Scotland and Wales. The main pain data used were from the Bio-Medical Survey conducted in 2003, when most of the 12,037 respondents were age 44. Additional health data was collected in 2008, 2013 and 2021.
Overall, two-fifths of those in their 40s reported suffering chronic pain. The study pinpointed multiple factors predicting pain at this age, including a person’s father’s social class at birth as well as pain in childhood. Both short-term and chronic pain at age 44 were associated with pain and poor health in later decades of life, with associations strongest for chronic pain. Among those reporting chronic pain at age 44, for example, 84% still reported “very severe” pain at age 50. Chronic pain, but not short-term pain, was also associated with poor mental health outcomes, lower life satisfaction, pessimism about the future, poor sleep and joblessness at age 55. Additionally, the researchers found that pain at age 44 predicts whether a respondent had been infected with COVID-19 in the 2021 survey, at age 62, suggesting that pain is associated with broader health vulnerabilities.
The authors conclude that chronic pain shows persistence across the life-course and is, in part, passed between generations.
The authors add: “Tracking a birth cohort across their life-course we find chronic pain is highly persistent. It is associated with poor mental health outcomes later in life including depression, as well as leading to poorer general health and joblessness. We hope the study highlights the need for academics and policy makers to focus more attention on the problems of chronic pain.”
Chronic pain associated with poor health — and COVID-19 infection — decades later
The post Chronic pain associated with poor health — and COVID first appeared on .
"
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string(880) "Journal Reference: David G. Blanchflower, Alex Bryson. Chronic pain: Evidence from the national child development study. PLOS ONE, 2022; 17 (11): e0275095 DOI: 10.1371/journal.pone.0275095 Chronic pain — pain lasting at least three months — is a serious problem affecting a large number of people: according to the National Academies of Science, Engineering and Medicine, more ... Read more
The post Chronic pain associated with poor health — and COVID first appeared on .
"
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Journal Reference:
- David G. Blanchflower, Alex Bryson. Chronic pain: Evidence from the national child development study. PLOS ONE, 2022; 17 (11): e0275095 DOI: 10.1371/journal.pone.0275095
Chronic pain — pain lasting at least three months — is a serious problem affecting a large number of people: according to the National Academies of Science, Engineering and Medicine, more than 100 million Americans suffer from chronic pain.
In the new work, the researchers studied people enrolled in the National Child Development Survey, a study following all those born in one week in March 1958 in England, Scotland and Wales. The main pain data used were from the Bio-Medical Survey conducted in 2003, when most of the 12,037 respondents were age 44. Additional health data was collected in 2008, 2013 and 2021.
Overall, two-fifths of those in their 40s reported suffering chronic pain. The study pinpointed multiple factors predicting pain at this age, including a person’s father’s social class at birth as well as pain in childhood. Both short-term and chronic pain at age 44 were associated with pain and poor health in later decades of life, with associations strongest for chronic pain. Among those reporting chronic pain at age 44, for example, 84% still reported “very severe” pain at age 50. Chronic pain, but not short-term pain, was also associated with poor mental health outcomes, lower life satisfaction, pessimism about the future, poor sleep and joblessness at age 55. Additionally, the researchers found that pain at age 44 predicts whether a respondent had been infected with COVID-19 in the 2021 survey, at age 62, suggesting that pain is associated with broader health vulnerabilities.
The authors conclude that chronic pain shows persistence across the life-course and is, in part, passed between generations.
The authors add: “Tracking a birth cohort across their life-course we find chronic pain is highly persistent. It is associated with poor mental health outcomes later in life including depression, as well as leading to poorer general health and joblessness. We hope the study highlights the need for academics and policy makers to focus more attention on the problems of chronic pain.”
Chronic pain associated with poor health — and COVID-19 infection — decades later
The post Chronic pain associated with poor health — and COVID first appeared on .
"
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string(73) "Researchers encourage retailers to embrace AI to better service customers"
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string(105) "https://coolnspicy.com/science/researchers-encourage-retailers-to-embrace-ai-to-better-service-customers/"
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["creator"]=>
string(15) "Michael Steiner"
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["pubdate"]=>
string(31) "Thu, 03 Nov 2022 20:21:06 +0000"
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string(59) "sciencecustomersembraceencourageResearchersretailersservice"
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string(991) "Journal Reference: Kien Nguyen, Minh Le, Brett Martin, Ibrahim Cil, Clinton Fookes. When AI meets store layout design: a review. Artificial Intelligence Review, 2022; 55 (7): 5707 DOI: 10.1007/s10462-022-10142-3 In research published in Artificial Intelligence Review, the team propose an AI-powered store layout design framework for retailers to best take advantage of recent advances in ... Read more
The post Researchers encourage retailers to embrace AI to better service customers first appeared on .
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Journal Reference:
- Kien Nguyen, Minh Le, Brett Martin, Ibrahim Cil, Clinton Fookes. When AI meets store layout design: a review. Artificial Intelligence Review, 2022; 55 (7): 5707 DOI: 10.1007/s10462-022-10142-3
In research published in Artificial Intelligence Review, the team propose an AI-powered store layout design framework for retailers to best take advantage of recent advances in AI techniques, and its sub-fields in computer vision and deep learning to monitor the physical shopping behaviours of their customers.
Any shopper who has retrieved milk from the farthest corner of a shop knows well that an efficient store layout presents its merchandise to both attract customer attention to items they had not intended to buy, increase browsing time, and easily find related or viable alternative products grouped together.
A well thought out layout has been shown to positively correlate with increased sales and customer satisfaction. It is one of the most effective in-store marketing tactics which can directly influence customer decisions to boost profitability.
QUT researchers Dr Kien Nguyen and Professor Clinton Fookes from the School of Electrical Engineering & Robotics and Professor Brett Martin, QUT Business Schoolteamed up with researchers Dr Minh Le, from the University of Economics, Ho Chi Minh city, Vietnam, and Professor Ibrahim Cil from Sakarya University, Serdivan, Turkey, to conduct a comprehensive review on existing approaches to in store layout design.
Dr Nguyen says improving supermarket layout design — through understanding and prediction — is a vital tactic to improve customer satisfaction and increase sales.
“Most importantly this paper proposes a comprehensive and novel framework to apply new AI techniques on top of the existing CCTV camera data to interpret and better understand customers and their behaviour in store,” Dr Nguyen said.
“CCTV offers insights into how shoppers travel through the store; the route they take, and sections where they spend more time. This research proposes drilling down further, noting that people express emotion through observable facial expressions such as raising an eyebrow, eyes opening or smiling.”
Understanding customer emotion as they browse could provide marketers and managers with a valuable tool to understand customer reactions to the products they sell.
“Emotion recognition algorithms work by employing computer vision techniques to locate the face, and identify key landmarks on the face, such as corners of the eyebrows, tip of the nose, and corners of the mouth,” Dr Nguyen said.
“Understanding customer behaviours is the ultimate goal for business intelligence. Obvious actions like picking up products, putting products into the trolley, and returning products back to the shelf have attracted great interest for the smart retailers.
“Other behaviours like staring at a product and reading the box of a product are a gold mine for marketing to understand the interest of customers in a product,” Dr Nguyen said.
Along with understanding emotions through facial cues and customer characterisation, layout managers could employ heatmap analytics, human trajectory tracking and customer action recognition techniques to inform their decisions. This type of knowledge can be assessed directly from the video and can be helpful to understand customer behaviour at a store-level while avoiding the need to know about individual identities.
Professor Clinton Fookes said the team had proposed the Sense-Think-Act-Learn (STAL) framework for retailers.
“Firstly, ‘Sense’ is to collect raw data, say from video footage from a store’s CCTV cameras for processing and analysis. Store managers routinely do this with their own eyes; however, new approaches allow us to automate this aspect of sensing, and to perform this across the entire store,” Professor Fookes said.
“Secondly, ‘Think’ is to process the data collected through advanced AI, data analytics, and deep machine learning techniques, like how humans use their brains to process the incoming data.
“Thirdly, ‘Act’ is to use the knowledge and insights from the second phase to improve and optimise the supermarket layout. The process operates as a continuous learning cycle.
“An advantage of this framework is that it allows retailers to evaluate store design predictions such as the traffic flow and behaviour when customers enter a store, or the popularity of store displays placed in different areas of the store,” Professor Fookes said.
“Stores like Woolworths and Coles already routinely use AI empowered algorithms to better serve customer interests and wants, and to provide personalised recommendations. This is particularly true at the point-of-sale system and through loyalty programs. This is simply another example of using AI to provide better data-driven store layouts and design, and to better understand customer behaviour in physical spaces.”
Dr Nguyen said data could be filtered and cleaned to improve quality and privacy and transformed into a structural form. As privacy was a key concern for customers, data could be de-identified or made anonymous, for example, by examining customers at an aggregate level.
“Since there is an intense data flow from the CCTV cameras, a cloud-based system can be considered as a suitable approach for supermarket layout analysis in processing and storing video data,” he said.
“The intelligent video analytic layer in the THINK phase plays the key role in interpreting the content of images and videos.”
Dr Nguyen said layout managers could consider store design variables (for example space design, point-of-purchase displays, product placement, placement of cashiers), employees (for example: number, placement) and customers (for example: crowding, visit duration, impulse purchases, use of furniture, waiting queue formation, receptivity to product displays).
Researchers encourage retailers to embrace AI to better service customers
The post Researchers encourage retailers to embrace AI to better service customers first appeared on .
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string(991) "Journal Reference: Kien Nguyen, Minh Le, Brett Martin, Ibrahim Cil, Clinton Fookes. When AI meets store layout design: a review. Artificial Intelligence Review, 2022; 55 (7): 5707 DOI: 10.1007/s10462-022-10142-3 In research published in Artificial Intelligence Review, the team propose an AI-powered store layout design framework for retailers to best take advantage of recent advances in ... Read more
The post Researchers encourage retailers to embrace AI to better service customers first appeared on .
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Journal Reference:
- Kien Nguyen, Minh Le, Brett Martin, Ibrahim Cil, Clinton Fookes. When AI meets store layout design: a review. Artificial Intelligence Review, 2022; 55 (7): 5707 DOI: 10.1007/s10462-022-10142-3
In research published in Artificial Intelligence Review, the team propose an AI-powered store layout design framework for retailers to best take advantage of recent advances in AI techniques, and its sub-fields in computer vision and deep learning to monitor the physical shopping behaviours of their customers.
Any shopper who has retrieved milk from the farthest corner of a shop knows well that an efficient store layout presents its merchandise to both attract customer attention to items they had not intended to buy, increase browsing time, and easily find related or viable alternative products grouped together.
A well thought out layout has been shown to positively correlate with increased sales and customer satisfaction. It is one of the most effective in-store marketing tactics which can directly influence customer decisions to boost profitability.
QUT researchers Dr Kien Nguyen and Professor Clinton Fookes from the School of Electrical Engineering & Robotics and Professor Brett Martin, QUT Business Schoolteamed up with researchers Dr Minh Le, from the University of Economics, Ho Chi Minh city, Vietnam, and Professor Ibrahim Cil from Sakarya University, Serdivan, Turkey, to conduct a comprehensive review on existing approaches to in store layout design.
Dr Nguyen says improving supermarket layout design — through understanding and prediction — is a vital tactic to improve customer satisfaction and increase sales.
“Most importantly this paper proposes a comprehensive and novel framework to apply new AI techniques on top of the existing CCTV camera data to interpret and better understand customers and their behaviour in store,” Dr Nguyen said.
“CCTV offers insights into how shoppers travel through the store; the route they take, and sections where they spend more time. This research proposes drilling down further, noting that people express emotion through observable facial expressions such as raising an eyebrow, eyes opening or smiling.”
Understanding customer emotion as they browse could provide marketers and managers with a valuable tool to understand customer reactions to the products they sell.
“Emotion recognition algorithms work by employing computer vision techniques to locate the face, and identify key landmarks on the face, such as corners of the eyebrows, tip of the nose, and corners of the mouth,” Dr Nguyen said.
“Understanding customer behaviours is the ultimate goal for business intelligence. Obvious actions like picking up products, putting products into the trolley, and returning products back to the shelf have attracted great interest for the smart retailers.
“Other behaviours like staring at a product and reading the box of a product are a gold mine for marketing to understand the interest of customers in a product,” Dr Nguyen said.
Along with understanding emotions through facial cues and customer characterisation, layout managers could employ heatmap analytics, human trajectory tracking and customer action recognition techniques to inform their decisions. This type of knowledge can be assessed directly from the video and can be helpful to understand customer behaviour at a store-level while avoiding the need to know about individual identities.
Professor Clinton Fookes said the team had proposed the Sense-Think-Act-Learn (STAL) framework for retailers.
“Firstly, ‘Sense’ is to collect raw data, say from video footage from a store’s CCTV cameras for processing and analysis. Store managers routinely do this with their own eyes; however, new approaches allow us to automate this aspect of sensing, and to perform this across the entire store,” Professor Fookes said.
“Secondly, ‘Think’ is to process the data collected through advanced AI, data analytics, and deep machine learning techniques, like how humans use their brains to process the incoming data.
“Thirdly, ‘Act’ is to use the knowledge and insights from the second phase to improve and optimise the supermarket layout. The process operates as a continuous learning cycle.
“An advantage of this framework is that it allows retailers to evaluate store design predictions such as the traffic flow and behaviour when customers enter a store, or the popularity of store displays placed in different areas of the store,” Professor Fookes said.
“Stores like Woolworths and Coles already routinely use AI empowered algorithms to better serve customer interests and wants, and to provide personalised recommendations. This is particularly true at the point-of-sale system and through loyalty programs. This is simply another example of using AI to provide better data-driven store layouts and design, and to better understand customer behaviour in physical spaces.”
Dr Nguyen said data could be filtered and cleaned to improve quality and privacy and transformed into a structural form. As privacy was a key concern for customers, data could be de-identified or made anonymous, for example, by examining customers at an aggregate level.
“Since there is an intense data flow from the CCTV cameras, a cloud-based system can be considered as a suitable approach for supermarket layout analysis in processing and storing video data,” he said.
“The intelligent video analytic layer in the THINK phase plays the key role in interpreting the content of images and videos.”
Dr Nguyen said layout managers could consider store design variables (for example space design, point-of-purchase displays, product placement, placement of cashiers), employees (for example: number, placement) and customers (for example: crowding, visit duration, impulse purchases, use of furniture, waiting queue formation, receptivity to product displays).
Researchers encourage retailers to embrace AI to better service customers
The post Researchers encourage retailers to embrace AI to better service customers first appeared on .
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["title"]=>
string(77) "Double trouble when 2 disasters strike electrical transmission infrastructure"
["link"]=>
string(109) "https://coolnspicy.com/science/double-trouble-when-2-disasters-strike-electrical-transmission-infrastructure/"
["dc"]=>
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["creator"]=>
string(15) "Michael Steiner"
}
["pubdate"]=>
string(31) "Thu, 03 Nov 2022 16:19:44 +0000"
["category"]=>
string(71) "sciencedisastersDoubleelectricalinfrastructurestriketransmissiontrouble"
["guid"]=>
string(29) "https://coolnspicy.com/?p=307"
["description"]=>
string(1064) "Journal Reference: Ashkan B. Jeddi, Abdollah Shafieezadeh, Jieun Hur, Jeong‐Gon Ha, Daegi Hahm, Min‐Kyu Kim. Multi‐hazard typhoon and earthquake collapse fragility models for transmission towers: An active learning reliability approach using gradient boosting classifiers. Earthquake Engineering & Structural Dynamics, 2022; DOI: 10.1002/eqe.3735 Researchers at The Ohio State University have developed a machine learning model for ... Read more
The post Double trouble when 2 disasters strike electrical transmission infrastructure first appeared on .
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Journal Reference:
- Ashkan B. Jeddi, Abdollah Shafieezadeh, Jieun Hur, Jeong‐Gon Ha, Daegi Hahm, Min‐Kyu Kim. Multi‐hazard typhoon and earthquake collapse fragility models for transmission towers: An active learning reliability approach using gradient boosting classifiers. Earthquake Engineering & Structural Dynamics, 2022; DOI: 10.1002/eqe.3735
Researchers at The Ohio State University have developed a machine learning model for predicting how susceptible overhead transmission lines are to damage when natural hazards like hurricanes or earthquakes happen in quick succession.
An essential facet of modern infrastructure, steel transmission towers help send electricity across long distances by keeping overhead power lines far off the ground. After severe damage, failures in these systems can disrupt networks across affected communities, taking anywhere from a few weeks to months to fix.
The study, published in the journal Earthquake Engineering and Structural Dynamics, uses simulations to analyze what effect prior damage has on the performance of these towers once a second hazard strikes. Their findings suggest that previous damage has a considerable impact on the fragility and reliability of these networks if it can’t be repaired before the second hazard hits, said Abdollah Shafieezadeh, co-author of the study and an associate professor of civil, environmental and geodetic engineering.
“Our work aims to answer if it’s possible to design and manage systems in a way that not only minimizes their initial damage but enables them to recover faster,” said Shafieezadeh.
The machine learning model not only found that a combination of an earthquake and hurricane could be particularly devastating to the electrical grid, but that the order of the disasters may make a difference. The researchers found that the probability of a tower collapse is much higher in the event of an earthquake followed by a hurricane than the probability of failure when the hurricane comes first and is followed by an earthquake.
That means while communities would certainly suffer some setbacks in the event that a hurricane precedes an earthquake, a situation wherein an earthquake precedes a hurricane could devastate a region’s power grid. Such conclusions are why Shafieezadeh’s research has large implications for disaster recovery efforts.
“When large-scale power grid systems are spread over large geographic areas, it’s not possible to carefully inspect every inch of them very carefully,” said Shafieezadeh. “Predictive models can help engineers or organizations see which towers have the greatest probability of failure and quickly move to improve those issues in the field.”
After training the model for numerous scenarios, the team created “fragility models” that tested how the structures would hold up under different characteristics and intensities of natural threats. With the help of these simulations, researchers concluded that tower failures due to a single hazardous event were vastly different from the pattern of failures caused by multi-hazard events. The study noted that many of these failings occurred in the leg elements of the structure, a segment of the tower that helps bolt the structure to the ground and prevents collapse.
Overall, Shafieezadeh said his research shows a need to focus on re-evaluating the entire design philosophy of these networks. Yet to accomplish such a task, much more support from utilities and government agencies is needed.
“Our work would be greatly beneficial in creating new infrastructure regulations in the field,” Shafieezadeh said. “This along with our other research shows that we can substantially improve the entire system’s performance with the same amount of resources that we spend today, just by optimizing their allocation.”
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy of the Republic of Korea (MOTIE).
Double trouble when 2 disasters strike electrical transmission infrastructure
The post Double trouble when 2 disasters strike electrical transmission infrastructure first appeared on .
"
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string(1064) "Journal Reference: Ashkan B. Jeddi, Abdollah Shafieezadeh, Jieun Hur, Jeong‐Gon Ha, Daegi Hahm, Min‐Kyu Kim. Multi‐hazard typhoon and earthquake collapse fragility models for transmission towers: An active learning reliability approach using gradient boosting classifiers. Earthquake Engineering & Structural Dynamics, 2022; DOI: 10.1002/eqe.3735 Researchers at The Ohio State University have developed a machine learning model for ... Read more
The post Double trouble when 2 disasters strike electrical transmission infrastructure first appeared on .
"
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Journal Reference:
- Ashkan B. Jeddi, Abdollah Shafieezadeh, Jieun Hur, Jeong‐Gon Ha, Daegi Hahm, Min‐Kyu Kim. Multi‐hazard typhoon and earthquake collapse fragility models for transmission towers: An active learning reliability approach using gradient boosting classifiers. Earthquake Engineering & Structural Dynamics, 2022; DOI: 10.1002/eqe.3735
Researchers at The Ohio State University have developed a machine learning model for predicting how susceptible overhead transmission lines are to damage when natural hazards like hurricanes or earthquakes happen in quick succession.
An essential facet of modern infrastructure, steel transmission towers help send electricity across long distances by keeping overhead power lines far off the ground. After severe damage, failures in these systems can disrupt networks across affected communities, taking anywhere from a few weeks to months to fix.
The study, published in the journal Earthquake Engineering and Structural Dynamics, uses simulations to analyze what effect prior damage has on the performance of these towers once a second hazard strikes. Their findings suggest that previous damage has a considerable impact on the fragility and reliability of these networks if it can’t be repaired before the second hazard hits, said Abdollah Shafieezadeh, co-author of the study and an associate professor of civil, environmental and geodetic engineering.
“Our work aims to answer if it’s possible to design and manage systems in a way that not only minimizes their initial damage but enables them to recover faster,” said Shafieezadeh.
The machine learning model not only found that a combination of an earthquake and hurricane could be particularly devastating to the electrical grid, but that the order of the disasters may make a difference. The researchers found that the probability of a tower collapse is much higher in the event of an earthquake followed by a hurricane than the probability of failure when the hurricane comes first and is followed by an earthquake.
That means while communities would certainly suffer some setbacks in the event that a hurricane precedes an earthquake, a situation wherein an earthquake precedes a hurricane could devastate a region’s power grid. Such conclusions are why Shafieezadeh’s research has large implications for disaster recovery efforts.
“When large-scale power grid systems are spread over large geographic areas, it’s not possible to carefully inspect every inch of them very carefully,” said Shafieezadeh. “Predictive models can help engineers or organizations see which towers have the greatest probability of failure and quickly move to improve those issues in the field.”
After training the model for numerous scenarios, the team created “fragility models” that tested how the structures would hold up under different characteristics and intensities of natural threats. With the help of these simulations, researchers concluded that tower failures due to a single hazardous event were vastly different from the pattern of failures caused by multi-hazard events. The study noted that many of these failings occurred in the leg elements of the structure, a segment of the tower that helps bolt the structure to the ground and prevents collapse.
Overall, Shafieezadeh said his research shows a need to focus on re-evaluating the entire design philosophy of these networks. Yet to accomplish such a task, much more support from utilities and government agencies is needed.
“Our work would be greatly beneficial in creating new infrastructure regulations in the field,” Shafieezadeh said. “This along with our other research shows that we can substantially improve the entire system’s performance with the same amount of resources that we spend today, just by optimizing their allocation.”
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy of the Republic of Korea (MOTIE).
Double trouble when 2 disasters strike electrical transmission infrastructure
The post Double trouble when 2 disasters strike electrical transmission infrastructure first appeared on .
"
["date_timestamp"]=>
int(1667492384)
}
[3]=>
array(11) {
["title"]=>
string(16) "500 million year"
["link"]=>
string(48) "https://coolnspicy.com/science/500-million-year/"
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string(15) "Michael Steiner"
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["pubdate"]=>
string(31) "Thu, 03 Nov 2022 12:18:31 +0000"
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string(7) "science"
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string(29) "https://coolnspicy.com/?p=305"
["description"]=>
string(700) "Journal Reference: Guangxu Zhang, Luke A. Parry, Jakob Vinther, Xiaoya Ma. Exceptional soft tissue preservation reveals a cnidarian affinity for a Cambrian phosphatic tubicolous enigma. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1623 The first animals to build hard and robust skeletons appear suddenly in the fossil record in a ... Read more
The post 500 million year first appeared on .
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Journal Reference:
- Guangxu Zhang, Luke A. Parry, Jakob Vinther, Xiaoya Ma. Exceptional soft tissue preservation reveals a cnidarian affinity for a Cambrian phosphatic tubicolous enigma. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1623
The first animals to build hard and robust skeletons appear suddenly in the fossil record in a geological blink of an eye around 550-520 million years ago during an event called the Cambrian Explosion. Many of these early fossils are simple hollow tubes ranging from a few millimetres to many centimetres in length. However, what sort of animals made these skeletons was almost completely unknown, because they lack preservation of the soft parts needed to identify them as belonging to major groups of animals that are still alive today.
The new collection of 514 million year old fossils includes four specimens of Gangtoucunia aspera with soft tissues still intact, including the gut and mouthparts. These reveal that this species had a mouth fringed with a ring of smooth, unbranched tentacles about 5 mm long. It’s likely that these were used to sting and capture prey, such as small arthropods. The fossils also show that Gangtoucunia had a blind-ended gut (open only at one end), partitioned into internal cavities, that filled the length of the tube.
These are features found today only in modern jellyfish, anemones and their close relatives (known as cnidarians), organisms whose soft parts are extremely rare in the fossil record. The study shows that these simple animals was among the first to build the hard skeletons that make up much of the known fossil record.
According to the researchers, Gangtoucunia would have looked similar to modern scyphozoan jellyfish polyps, with a hard tubular structure anchored to the underlying substrate. The tentacle mouth would have extended outside the tube, but could have been retracted inside the tube to avoid predators. Unlike living jellyfish polyps however, the tube of Gangtoucunia was made of calcium phosphate, a hard mineral that makes up our own teeth and bones. Use of this material to build skeletons has become more rare among animals over time.
Corresponding author Dr Luke Parry, Department of Earth Sciences, University of Oxford, said: ‘This really is a one-in-million discovery. These mysterious tubes are often found in groups of hundreds of individuals, but until now they have been regarded as ‘problematic’ fossils, because we had no way of classifying them. Thanks to these extraordinary new specimens, a key piece of the evolutionary puzzle has been put firmly in place.’
The new specimens clearly demonstrate that Gangtoucunia was not related to annelid worms (earthworms, polychaetes and their relatives) as had been previously suggested for similar fossils. It is now clear that Gangtoucunia’s body had a smooth exterior and a gut partitioned longitudinally, whereas annelids have segmented bodies with transverse partitioning of the body.
The fossil was found at a site in the Gaoloufang section in Kunming, eastern Yunnan Province, China. Here, anaerobic (oxygen-poor) conditions limit the presence of bacteria that normally degrade soft tissues in fossils.
PhD student Guangxu Zhang, who collected and discovered the specimens, said: ‘The first time I discovered the pink soft tissue on top of a Gangtoucunia tube, I was surprised and confused about what they were. In the following month, I found three more specimens with soft tissue preservation, which was very exciting and made me rethink the affinity of Gangtoucunia. The soft tissue of Gangtoucunia, particularly the tentacles, reveals that it is certainly not a priapulid-like worm as previous studies suggested, but more like a coral, and then I realised that it is a cnidarian.’
Although the fossil clearly shows that Gangtoucunia was a primitive jellyfish, this doesn’t rule out the possibility that other early tube-fossil species looked very different. From Cambrian rocks in Yunnan province, the research team have previously found well-preserved tube fossils that could be identified as priapulids (marine worms), lobopodians (worms with paired legs, closely related to arthropods today) and annelids.
Co-corresponding author Xiaoya Ma (Yunnan University and University of Exeter) said: ‘A tubicolous mode of life seems to have become increasingly common in the Cambrian, which might be an adaptive response to increasing predation pressure in the early Cambrian. This study demonstrates that exceptional soft-tissue preservation is crucial for us to understand these ancient animals.’
500 million year-old fossils reveal answer to evolutionary riddle
The post 500 million year first appeared on .
"
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string(700) "Journal Reference: Guangxu Zhang, Luke A. Parry, Jakob Vinther, Xiaoya Ma. Exceptional soft tissue preservation reveals a cnidarian affinity for a Cambrian phosphatic tubicolous enigma. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1623 The first animals to build hard and robust skeletons appear suddenly in the fossil record in a ... Read more
The post 500 million year first appeared on .
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Journal Reference:
- Guangxu Zhang, Luke A. Parry, Jakob Vinther, Xiaoya Ma. Exceptional soft tissue preservation reveals a cnidarian affinity for a Cambrian phosphatic tubicolous enigma. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1623
The first animals to build hard and robust skeletons appear suddenly in the fossil record in a geological blink of an eye around 550-520 million years ago during an event called the Cambrian Explosion. Many of these early fossils are simple hollow tubes ranging from a few millimetres to many centimetres in length. However, what sort of animals made these skeletons was almost completely unknown, because they lack preservation of the soft parts needed to identify them as belonging to major groups of animals that are still alive today.
The new collection of 514 million year old fossils includes four specimens of Gangtoucunia aspera with soft tissues still intact, including the gut and mouthparts. These reveal that this species had a mouth fringed with a ring of smooth, unbranched tentacles about 5 mm long. It’s likely that these were used to sting and capture prey, such as small arthropods. The fossils also show that Gangtoucunia had a blind-ended gut (open only at one end), partitioned into internal cavities, that filled the length of the tube.
These are features found today only in modern jellyfish, anemones and their close relatives (known as cnidarians), organisms whose soft parts are extremely rare in the fossil record. The study shows that these simple animals was among the first to build the hard skeletons that make up much of the known fossil record.
According to the researchers, Gangtoucunia would have looked similar to modern scyphozoan jellyfish polyps, with a hard tubular structure anchored to the underlying substrate. The tentacle mouth would have extended outside the tube, but could have been retracted inside the tube to avoid predators. Unlike living jellyfish polyps however, the tube of Gangtoucunia was made of calcium phosphate, a hard mineral that makes up our own teeth and bones. Use of this material to build skeletons has become more rare among animals over time.
Corresponding author Dr Luke Parry, Department of Earth Sciences, University of Oxford, said: ‘This really is a one-in-million discovery. These mysterious tubes are often found in groups of hundreds of individuals, but until now they have been regarded as ‘problematic’ fossils, because we had no way of classifying them. Thanks to these extraordinary new specimens, a key piece of the evolutionary puzzle has been put firmly in place.’
The new specimens clearly demonstrate that Gangtoucunia was not related to annelid worms (earthworms, polychaetes and their relatives) as had been previously suggested for similar fossils. It is now clear that Gangtoucunia’s body had a smooth exterior and a gut partitioned longitudinally, whereas annelids have segmented bodies with transverse partitioning of the body.
The fossil was found at a site in the Gaoloufang section in Kunming, eastern Yunnan Province, China. Here, anaerobic (oxygen-poor) conditions limit the presence of bacteria that normally degrade soft tissues in fossils.
PhD student Guangxu Zhang, who collected and discovered the specimens, said: ‘The first time I discovered the pink soft tissue on top of a Gangtoucunia tube, I was surprised and confused about what they were. In the following month, I found three more specimens with soft tissue preservation, which was very exciting and made me rethink the affinity of Gangtoucunia. The soft tissue of Gangtoucunia, particularly the tentacles, reveals that it is certainly not a priapulid-like worm as previous studies suggested, but more like a coral, and then I realised that it is a cnidarian.’
Although the fossil clearly shows that Gangtoucunia was a primitive jellyfish, this doesn’t rule out the possibility that other early tube-fossil species looked very different. From Cambrian rocks in Yunnan province, the research team have previously found well-preserved tube fossils that could be identified as priapulids (marine worms), lobopodians (worms with paired legs, closely related to arthropods today) and annelids.
Co-corresponding author Xiaoya Ma (Yunnan University and University of Exeter) said: ‘A tubicolous mode of life seems to have become increasingly common in the Cambrian, which might be an adaptive response to increasing predation pressure in the early Cambrian. This study demonstrates that exceptional soft-tissue preservation is crucial for us to understand these ancient animals.’
500 million year-old fossils reveal answer to evolutionary riddle
The post 500 million year first appeared on .
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string(76) "This simple material could scrub carbon dioxide from power plant smokestacks"
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string(108) "https://coolnspicy.com/science/this-simple-material-could-scrub-carbon-dioxide-from-power-plant-smokestacks/"
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string(995) "Journal Reference: Hayden A. Evans, Dinesh Mullangi, Zeyu Deng, Yuxiang Wang, Shing Bo Peh, Fengxia Wei, John Wang, Craig M. Brown, Dan Zhao, Pieremanuele Canepa, Anthony K. Cheetham. Aluminum formate, Al(HCOO) 3 An earth-abundant, scalable, and highly selective material for CO 2 capture. Science Advances, 2022; 8 (44) DOI: 10.1126/sciadv.ade1473 The team’s object of study ... Read more
The post This simple material could scrub carbon dioxide from power plant smokestacks first appeared on .
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Journal Reference:
- Hayden A. Evans, Dinesh Mullangi, Zeyu Deng, Yuxiang Wang, Shing Bo Peh, Fengxia Wei, John Wang, Craig M. Brown, Dan Zhao, Pieremanuele Canepa, Anthony K. Cheetham. Aluminum formate, Al(HCOO) 3 An earth-abundant, scalable, and highly selective material for CO 2 capture. Science Advances, 2022; 8 (44) DOI: 10.1126/sciadv.ade1473
The team’s object of study is aluminum formate, one of a class of substances called metal-organic frameworks (MOFs). As a group, MOFs have exhibited great potential for filtering and separating organic materials — often the various hydrocarbons in fossil fuels — from one another. Some MOFs have shown promise at refining natural gas or separating the octane components of gasoline; others might contribute to reducing the cost of plastics manufacturing or cheaply converting one substance to another. Their capacity to perform such separations comes from their inherently porous nature.
Aluminum formate, which the scientists refer to as ALF, has a talent for separating carbon dioxide (CO2) from the other gases that commonly fly out of the smokestacks of coal-fired power plants. It also lacks the shortcomings that other proposed carbon filtration materials have, said NIST’s Hayden Evans, one of the lead authors of the team’s research paper, published today in the peer-reviewed journal Science Advances.
“What makes this work exciting is that ALF performs really well relative to other high-performing CO2 adsorbents, but it rivals designer compounds in its simplicity, overall stability and ease of preparation,” said Evans, a chemist at the NIST Center for Neutron Research (NCNR). “It is made of two substances found easily and abundantly, so creating enough ALF to use widely should be possible at very low cost.”
The research team includes scientists from the National University of Singapore; Singapore’s Agency for Science, Technology and Research; the University of Delaware; and the University of California, Santa Barbara.
Coal-fired power plants account for roughly 30% of global CO2 emissions. Even as the world embraces other energy sources such as solar and wind power that do not generate greenhouse gases, finding a way to reduce the carbon output of existing plants could help mitigate their effects while they remain in operation.
Scrubbing the CO2 from flue gas before it reaches the atmosphere in the first place is a logical approach, but it has proved challenging to create an effective scrubber. The mixture of gases that flows up the smokestacks of coal-fired power plants is typically fairly hot, humid and corrosive — characteristics that have made it difficult to find an economical material that can do the job efficiently. Some other MOFs work well but are made of expensive materials; others are less costly in and of themselves but perform adequately only in dry conditions, requiring a “drying step” that reduces the gas humidity but raises the overall cost of the scrubbing process.
“Put it all together, you need some kind of wonder material,” Evans said. “Here, we’ve managed to tick every box except stability in very humid conditions. However, using ALF would be inexpensive enough that a drying step becomes a viable option.”
ALF is made from aluminum hydroxide and formic acid, two chemicals that are abundant and readily available on the market. It would cost less than a dollar per kilogram, Evans said, which is up to 100 times less expensive than other materials with similar performance. Low cost is important because carbon capture at a single plant could require up to tens of thousands of tons of filtration material. The amount needed for the entire world would be enormous.
On a microscopic scale, ALF resembles a three-dimensional wire cage with innumerable small holes. These holes are just large enough to allow CO2 molecules to enter and get trapped, but just small enough to exclude the slightly larger nitrogen molecules that make up the majority of flue gas. Neutron diffraction work at the NCNR showed the team how the individual cages in the material collect and fill with CO2, revealing that the gas molecules fit inside certain cages within ALF like a hand in a glove, Evans said.
Despite its potential, ALF is not ready for immediate use. Engineers would need to design a procedure to create ALF at large scales. A coal-fired plant would also need a compatible process to reduce the humidity of the flue gas before scrubbing it. Evans said that a great deal is already understood about how to address these issues, and that they would not make the cost of using ALF prohibitive.
What to do with the CO2 afterward is also a major question, he said, though this is a problem for all carbon-capture materials. There are research efforts underway to convert it to formic acid — which is not only a naturally occurring organic material but also one of the two constituents of ALF. The idea here is that ALF could become part of a cyclic process where ALF removes CO2 from the exhaust streams, and that captured CO2 is used to create more formic acid. This formic acid would then be used to make more ALF, further reducing the overall impact and cost of the material cycle.
“There is a great deal of research going on nowadays into the problem of what to do with all the captured CO2,” Evans said. “It seems possible that we could eventually use solar energy to split hydrogen from water, and then combine that hydrogen with the CO2 to make more formic acid. Combined with ALF, that’s a solution that would help the planet.”
This simple material could scrub carbon dioxide from power plant smokestacks
The post This simple material could scrub carbon dioxide from power plant smokestacks first appeared on .
"
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["summary"]=>
string(995) "Journal Reference: Hayden A. Evans, Dinesh Mullangi, Zeyu Deng, Yuxiang Wang, Shing Bo Peh, Fengxia Wei, John Wang, Craig M. Brown, Dan Zhao, Pieremanuele Canepa, Anthony K. Cheetham. Aluminum formate, Al(HCOO) 3 An earth-abundant, scalable, and highly selective material for CO 2 capture. Science Advances, 2022; 8 (44) DOI: 10.1126/sciadv.ade1473 The team’s object of study ... Read more
The post This simple material could scrub carbon dioxide from power plant smokestacks first appeared on .
"
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Journal Reference:
- Hayden A. Evans, Dinesh Mullangi, Zeyu Deng, Yuxiang Wang, Shing Bo Peh, Fengxia Wei, John Wang, Craig M. Brown, Dan Zhao, Pieremanuele Canepa, Anthony K. Cheetham. Aluminum formate, Al(HCOO) 3 An earth-abundant, scalable, and highly selective material for CO 2 capture. Science Advances, 2022; 8 (44) DOI: 10.1126/sciadv.ade1473
The team’s object of study is aluminum formate, one of a class of substances called metal-organic frameworks (MOFs). As a group, MOFs have exhibited great potential for filtering and separating organic materials — often the various hydrocarbons in fossil fuels — from one another. Some MOFs have shown promise at refining natural gas or separating the octane components of gasoline; others might contribute to reducing the cost of plastics manufacturing or cheaply converting one substance to another. Their capacity to perform such separations comes from their inherently porous nature.
Aluminum formate, which the scientists refer to as ALF, has a talent for separating carbon dioxide (CO2) from the other gases that commonly fly out of the smokestacks of coal-fired power plants. It also lacks the shortcomings that other proposed carbon filtration materials have, said NIST’s Hayden Evans, one of the lead authors of the team’s research paper, published today in the peer-reviewed journal Science Advances.
“What makes this work exciting is that ALF performs really well relative to other high-performing CO2 adsorbents, but it rivals designer compounds in its simplicity, overall stability and ease of preparation,” said Evans, a chemist at the NIST Center for Neutron Research (NCNR). “It is made of two substances found easily and abundantly, so creating enough ALF to use widely should be possible at very low cost.”
The research team includes scientists from the National University of Singapore; Singapore’s Agency for Science, Technology and Research; the University of Delaware; and the University of California, Santa Barbara.
Coal-fired power plants account for roughly 30% of global CO2 emissions. Even as the world embraces other energy sources such as solar and wind power that do not generate greenhouse gases, finding a way to reduce the carbon output of existing plants could help mitigate their effects while they remain in operation.
Scrubbing the CO2 from flue gas before it reaches the atmosphere in the first place is a logical approach, but it has proved challenging to create an effective scrubber. The mixture of gases that flows up the smokestacks of coal-fired power plants is typically fairly hot, humid and corrosive — characteristics that have made it difficult to find an economical material that can do the job efficiently. Some other MOFs work well but are made of expensive materials; others are less costly in and of themselves but perform adequately only in dry conditions, requiring a “drying step” that reduces the gas humidity but raises the overall cost of the scrubbing process.
“Put it all together, you need some kind of wonder material,” Evans said. “Here, we’ve managed to tick every box except stability in very humid conditions. However, using ALF would be inexpensive enough that a drying step becomes a viable option.”
ALF is made from aluminum hydroxide and formic acid, two chemicals that are abundant and readily available on the market. It would cost less than a dollar per kilogram, Evans said, which is up to 100 times less expensive than other materials with similar performance. Low cost is important because carbon capture at a single plant could require up to tens of thousands of tons of filtration material. The amount needed for the entire world would be enormous.
On a microscopic scale, ALF resembles a three-dimensional wire cage with innumerable small holes. These holes are just large enough to allow CO2 molecules to enter and get trapped, but just small enough to exclude the slightly larger nitrogen molecules that make up the majority of flue gas. Neutron diffraction work at the NCNR showed the team how the individual cages in the material collect and fill with CO2, revealing that the gas molecules fit inside certain cages within ALF like a hand in a glove, Evans said.
Despite its potential, ALF is not ready for immediate use. Engineers would need to design a procedure to create ALF at large scales. A coal-fired plant would also need a compatible process to reduce the humidity of the flue gas before scrubbing it. Evans said that a great deal is already understood about how to address these issues, and that they would not make the cost of using ALF prohibitive.
What to do with the CO2 afterward is also a major question, he said, though this is a problem for all carbon-capture materials. There are research efforts underway to convert it to formic acid — which is not only a naturally occurring organic material but also one of the two constituents of ALF. The idea here is that ALF could become part of a cyclic process where ALF removes CO2 from the exhaust streams, and that captured CO2 is used to create more formic acid. This formic acid would then be used to make more ALF, further reducing the overall impact and cost of the material cycle.
“There is a great deal of research going on nowadays into the problem of what to do with all the captured CO2,” Evans said. “It seems possible that we could eventually use solar energy to split hydrogen from water, and then combine that hydrogen with the CO2 to make more formic acid. Combined with ALF, that’s a solution that would help the planet.”
This simple material could scrub carbon dioxide from power plant smokestacks
The post This simple material could scrub carbon dioxide from power plant smokestacks first appeared on .
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string(39) "How ancient fish colonized the deep sea"
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string(71) "https://coolnspicy.com/science/how-ancient-fish-colonized-the-deep-sea/"
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string(31) "Thu, 03 Nov 2022 08:15:56 +0000"
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string(34) "scienceancientcolonizeddeepfishsea"
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string(846) "Journal Reference: Elizabeth Christina Miller, Christopher M. Martinez, Sarah T. Friedman, Peter C. Wainwright, Samantha A. Price, Luke Tornabene. Alternating regimes of shallow and deep-sea diversification explain a species-richness paradox in marine fishes. Proceedings of the National Academy of Sciences, 2022; 119 (43) DOI: 10.1073/pnas.2123544119 “It’s easy to look at shallow habitats like coral reefs, ... Read more
The post How ancient fish colonized the deep sea first appeared on .
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Journal Reference:
- Elizabeth Christina Miller, Christopher M. Martinez, Sarah T. Friedman, Peter C. Wainwright, Samantha A. Price, Luke Tornabene. Alternating regimes of shallow and deep-sea diversification explain a species-richness paradox in marine fishes. Proceedings of the National Academy of Sciences, 2022; 119 (43) DOI: 10.1073/pnas.2123544119
“It’s easy to look at shallow habitats like coral reefs, which are very diverse and exciting, and assume that they’ve always been that way,” said Miller, who completed the study as a postdoctoral researcher in the UW School of Aquatic and Fishery Sciences and is now a postdoctoral fellow at the University of Oklahoma. “These results really challenge that assumption, and help us understand how fish species have adapted to major changes to the climate.”
The deep sea is typically defined as anything below about 650 feet, the depth at which there is no longer enough sunlight for photosynthesis to occur. That means there is far less food and warmth than in the shallows, making it a difficult place to live. But by analyzing the relationships of fish using their genetic records going back 200 million years, Miller was able to identify a surprising evolutionary pattern: the speciation rates — that is, how quickly new species evolved — flip-flopped over time. There were periods lasting tens of millions of years when new species were evolving faster in the deep sea than in more shallow areas.
In some ways, this discovery raised more questions than it answered. What was causing fish to prefer one habitat over another? What made some fish able to move into the deep sea more easily than others? And how did these ancient shifts help create the diversity of species we have today?
When Miller mapped these flip-flopping speciation rates onto a timeline of Earth’s history, she was able to identify three major events that likely played a role.
“The first was the breakup of Pangea, which occurred between 200 and 150 million years ago,” said Miller. “That created new coastlines and new oceans, which meant there were more opportunities for fishes to move from shallow to deep water. There were suddenly a lot more access points.”
Next was the Cretaceous Hot Greenhouse period, which occurred approximately 100 million years ago and marked one of the warmest eras in Earth’s history. During this time, many continents were flooded due to sea-level rise, creating a large number of new, shallow areas across the earth.
“It was around this period that we really see shallow-water fishes take off and diversify,” said Miller. “We can trace a lot of the species diversity we see in the shallows today to this time.”
The third event was yet another major climatic change about 15 million years ago, known as the middle Miocene climatic transition. This was caused by further shifting of the continents, which caused major changes in ocean circulation and cooled the planet — all the way down to the deep sea.
“Around this time we see deep-sea speciation rates really speed up,” Miller said. “This was especially driven by cold-water fishes. A lot of the species you see today off the coasts of Washington and Alaska diversified during this time.”
But climate changes alone don’t explain how fish came to colonize the deep sea in the first place. Not every species has the right combination of traits to survive in deeper water and make use of the relatively limited resources beyond the reach of sunlight.
“To evolve into a new species in the deep sea, first you have to get there,” said Miller. “What we found was that not only were the speciation rates flip-flopping through time, but what the deep-sea fishes looked like was as well.”
The earliest fish that were able to transition into the deep sea tended to have large jaws. These likely gave them more opportunities to catch food, which can be scarce at depth. The researchers found that much later in history, fish that had longer, tapered tails tended to be most successful at making the transition to deep water. This allowed them to conserve energy by scooting along the seafloor instead of swimming in the water column.
“If you look at who lives in the deep sea today, some species have a tapered body and others have big, scary, toothy jaws,” Miller said. “Those two body plans represent ancestors that colonized the deep sea millions of years apart.”
While these events might seem like ancient history, they may be able to teach us about how today’s changing climate will affect life in our oceans. Miller hopes that future research can build on these findings and investigate how modern deep-sea fish will respond to climate change, and potentially inform conservation efforts.
“What we learned from this study is that deep-sea fishes tend to do well when oceans are colder, but with climate change, oceans are getting warmer,” she said. “We can expect that this is really going to impact fish in the deep-sea in the coming years.”
Co-authors are Luke Tornabene at the UW; Christopher Martinez at UC Irvine; Sarah Friedman at the NOAA Alaska Fisheries Science Center; Peter Wainwright at UC Davis; and Samantha Price at Clemson University.
This research was funded by the National Science Foundation.
Journal Reference:
- Elizabeth Christina Miller, Christopher M. Martinez, Sarah T. Friedman, Peter C. Wainwright, Samantha A. Price, Luke Tornabene. Alternating regimes of shallow and deep-sea diversification explain a species-richness paradox in marine fishes. Proceedings of the National Academy of Sciences, 2022; 119 (43) DOI: 10.1073/pnas.2123544119
“It’s easy to look at shallow habitats like coral reefs, which are very diverse and exciting, and assume that they’ve always been that way,” said Miller, who completed the study as a postdoctoral researcher in the UW School of Aquatic and Fishery Sciences and is now a postdoctoral fellow at the University of Oklahoma. “These results really challenge that assumption, and help us understand how fish species have adapted to major changes to the climate.”
The deep sea is typically defined as anything below about 650 feet, the depth at which there is no longer enough sunlight for photosynthesis to occur. That means there is far less food and warmth than in the shallows, making it a difficult place to live. But by analyzing the relationships of fish using their genetic records going back 200 million years, Miller was able to identify a surprising evolutionary pattern: the speciation rates — that is, how quickly new species evolved — flip-flopped over time. There were periods lasting tens of millions of years when new species were evolving faster in the deep sea than in more shallow areas.
In some ways, this discovery raised more questions than it answered. What was causing fish to prefer one habitat over another? What made some fish able to move into the deep sea more easily than others? And how did these ancient shifts help create the diversity of species we have today?
When Miller mapped these flip-flopping speciation rates onto a timeline of Earth’s history, she was able to identify three major events that likely played a role.
“The first was the breakup of Pangea, which occurred between 200 and 150 million years ago,” said Miller. “That created new coastlines and new oceans, which meant there were more opportunities for fishes to move from shallow to deep water. There were suddenly a lot more access points.”
Next was the Cretaceous Hot Greenhouse period, which occurred approximately 100 million years ago and marked one of the warmest eras in Earth’s history. During this time, many continents were flooded due to sea-level rise, creating a large number of new, shallow areas across the earth.
“It was around this period that we really see shallow-water fishes take off and diversify,” said Miller. “We can trace a lot of the species diversity we see in the shallows today to this time.”
The third event was yet another major climatic change about 15 million years ago, known as the middle Miocene climatic transition. This was caused by further shifting of the continents, which caused major changes in ocean circulation and cooled the planet — all the way down to the deep sea.
“Around this time we see deep-sea speciation rates really speed up,” Miller said. “This was especially driven by cold-water fishes. A lot of the species you see today off the coasts of Washington and Alaska diversified during this time.”
But climate changes alone don’t explain how fish came to colonize the deep sea in the first place. Not every species has the right combination of traits to survive in deeper water and make use of the relatively limited resources beyond the reach of sunlight.
“To evolve into a new species in the deep sea, first you have to get there,” said Miller. “What we found was that not only were the speciation rates flip-flopping through time, but what the deep-sea fishes looked like was as well.”
The earliest fish that were able to transition into the deep sea tended to have large jaws. These likely gave them more opportunities to catch food, which can be scarce at depth. The researchers found that much later in history, fish that had longer, tapered tails tended to be most successful at making the transition to deep water. This allowed them to conserve energy by scooting along the seafloor instead of swimming in the water column.
“If you look at who lives in the deep sea today, some species have a tapered body and others have big, scary, toothy jaws,” Miller said. “Those two body plans represent ancestors that colonized the deep sea millions of years apart.”
While these events might seem like ancient history, they may be able to teach us about how today’s changing climate will affect life in our oceans. Miller hopes that future research can build on these findings and investigate how modern deep-sea fish will respond to climate change, and potentially inform conservation efforts.
“What we learned from this study is that deep-sea fishes tend to do well when oceans are colder, but with climate change, oceans are getting warmer,” she said. “We can expect that this is really going to impact fish in the deep-sea in the coming years.”
Co-authors are Luke Tornabene at the UW; Christopher Martinez at UC Irvine; Sarah Friedman at the NOAA Alaska Fisheries Science Center; Peter Wainwright at UC Davis; and Samantha Price at Clemson University.
This research was funded by the National Science Foundation.
How ancient fish colonized the deep sea
The post How ancient fish colonized the deep sea first appeared on .
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The post How ancient fish colonized the deep sea first appeared on .
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Journal Reference:
- Elizabeth Christina Miller, Christopher M. Martinez, Sarah T. Friedman, Peter C. Wainwright, Samantha A. Price, Luke Tornabene. Alternating regimes of shallow and deep-sea diversification explain a species-richness paradox in marine fishes. Proceedings of the National Academy of Sciences, 2022; 119 (43) DOI: 10.1073/pnas.2123544119
“It’s easy to look at shallow habitats like coral reefs, which are very diverse and exciting, and assume that they’ve always been that way,” said Miller, who completed the study as a postdoctoral researcher in the UW School of Aquatic and Fishery Sciences and is now a postdoctoral fellow at the University of Oklahoma. “These results really challenge that assumption, and help us understand how fish species have adapted to major changes to the climate.”
The deep sea is typically defined as anything below about 650 feet, the depth at which there is no longer enough sunlight for photosynthesis to occur. That means there is far less food and warmth than in the shallows, making it a difficult place to live. But by analyzing the relationships of fish using their genetic records going back 200 million years, Miller was able to identify a surprising evolutionary pattern: the speciation rates — that is, how quickly new species evolved — flip-flopped over time. There were periods lasting tens of millions of years when new species were evolving faster in the deep sea than in more shallow areas.
In some ways, this discovery raised more questions than it answered. What was causing fish to prefer one habitat over another? What made some fish able to move into the deep sea more easily than others? And how did these ancient shifts help create the diversity of species we have today?
When Miller mapped these flip-flopping speciation rates onto a timeline of Earth’s history, she was able to identify three major events that likely played a role.
“The first was the breakup of Pangea, which occurred between 200 and 150 million years ago,” said Miller. “That created new coastlines and new oceans, which meant there were more opportunities for fishes to move from shallow to deep water. There were suddenly a lot more access points.”
Next was the Cretaceous Hot Greenhouse period, which occurred approximately 100 million years ago and marked one of the warmest eras in Earth’s history. During this time, many continents were flooded due to sea-level rise, creating a large number of new, shallow areas across the earth.
“It was around this period that we really see shallow-water fishes take off and diversify,” said Miller. “We can trace a lot of the species diversity we see in the shallows today to this time.”
The third event was yet another major climatic change about 15 million years ago, known as the middle Miocene climatic transition. This was caused by further shifting of the continents, which caused major changes in ocean circulation and cooled the planet — all the way down to the deep sea.
“Around this time we see deep-sea speciation rates really speed up,” Miller said. “This was especially driven by cold-water fishes. A lot of the species you see today off the coasts of Washington and Alaska diversified during this time.”
But climate changes alone don’t explain how fish came to colonize the deep sea in the first place. Not every species has the right combination of traits to survive in deeper water and make use of the relatively limited resources beyond the reach of sunlight.
“To evolve into a new species in the deep sea, first you have to get there,” said Miller. “What we found was that not only were the speciation rates flip-flopping through time, but what the deep-sea fishes looked like was as well.”
The earliest fish that were able to transition into the deep sea tended to have large jaws. These likely gave them more opportunities to catch food, which can be scarce at depth. The researchers found that much later in history, fish that had longer, tapered tails tended to be most successful at making the transition to deep water. This allowed them to conserve energy by scooting along the seafloor instead of swimming in the water column.
“If you look at who lives in the deep sea today, some species have a tapered body and others have big, scary, toothy jaws,” Miller said. “Those two body plans represent ancestors that colonized the deep sea millions of years apart.”
While these events might seem like ancient history, they may be able to teach us about how today’s changing climate will affect life in our oceans. Miller hopes that future research can build on these findings and investigate how modern deep-sea fish will respond to climate change, and potentially inform conservation efforts.
“What we learned from this study is that deep-sea fishes tend to do well when oceans are colder, but with climate change, oceans are getting warmer,” she said. “We can expect that this is really going to impact fish in the deep-sea in the coming years.”
Co-authors are Luke Tornabene at the UW; Christopher Martinez at UC Irvine; Sarah Friedman at the NOAA Alaska Fisheries Science Center; Peter Wainwright at UC Davis; and Samantha Price at Clemson University.
This research was funded by the National Science Foundation.
Journal Reference:
- Elizabeth Christina Miller, Christopher M. Martinez, Sarah T. Friedman, Peter C. Wainwright, Samantha A. Price, Luke Tornabene. Alternating regimes of shallow and deep-sea diversification explain a species-richness paradox in marine fishes. Proceedings of the National Academy of Sciences, 2022; 119 (43) DOI: 10.1073/pnas.2123544119
“It’s easy to look at shallow habitats like coral reefs, which are very diverse and exciting, and assume that they’ve always been that way,” said Miller, who completed the study as a postdoctoral researcher in the UW School of Aquatic and Fishery Sciences and is now a postdoctoral fellow at the University of Oklahoma. “These results really challenge that assumption, and help us understand how fish species have adapted to major changes to the climate.”
The deep sea is typically defined as anything below about 650 feet, the depth at which there is no longer enough sunlight for photosynthesis to occur. That means there is far less food and warmth than in the shallows, making it a difficult place to live. But by analyzing the relationships of fish using their genetic records going back 200 million years, Miller was able to identify a surprising evolutionary pattern: the speciation rates — that is, how quickly new species evolved — flip-flopped over time. There were periods lasting tens of millions of years when new species were evolving faster in the deep sea than in more shallow areas.
In some ways, this discovery raised more questions than it answered. What was causing fish to prefer one habitat over another? What made some fish able to move into the deep sea more easily than others? And how did these ancient shifts help create the diversity of species we have today?
When Miller mapped these flip-flopping speciation rates onto a timeline of Earth’s history, she was able to identify three major events that likely played a role.
“The first was the breakup of Pangea, which occurred between 200 and 150 million years ago,” said Miller. “That created new coastlines and new oceans, which meant there were more opportunities for fishes to move from shallow to deep water. There were suddenly a lot more access points.”
Next was the Cretaceous Hot Greenhouse period, which occurred approximately 100 million years ago and marked one of the warmest eras in Earth’s history. During this time, many continents were flooded due to sea-level rise, creating a large number of new, shallow areas across the earth.
“It was around this period that we really see shallow-water fishes take off and diversify,” said Miller. “We can trace a lot of the species diversity we see in the shallows today to this time.”
The third event was yet another major climatic change about 15 million years ago, known as the middle Miocene climatic transition. This was caused by further shifting of the continents, which caused major changes in ocean circulation and cooled the planet — all the way down to the deep sea.
“Around this time we see deep-sea speciation rates really speed up,” Miller said. “This was especially driven by cold-water fishes. A lot of the species you see today off the coasts of Washington and Alaska diversified during this time.”
But climate changes alone don’t explain how fish came to colonize the deep sea in the first place. Not every species has the right combination of traits to survive in deeper water and make use of the relatively limited resources beyond the reach of sunlight.
“To evolve into a new species in the deep sea, first you have to get there,” said Miller. “What we found was that not only were the speciation rates flip-flopping through time, but what the deep-sea fishes looked like was as well.”
The earliest fish that were able to transition into the deep sea tended to have large jaws. These likely gave them more opportunities to catch food, which can be scarce at depth. The researchers found that much later in history, fish that had longer, tapered tails tended to be most successful at making the transition to deep water. This allowed them to conserve energy by scooting along the seafloor instead of swimming in the water column.
“If you look at who lives in the deep sea today, some species have a tapered body and others have big, scary, toothy jaws,” Miller said. “Those two body plans represent ancestors that colonized the deep sea millions of years apart.”
While these events might seem like ancient history, they may be able to teach us about how today’s changing climate will affect life in our oceans. Miller hopes that future research can build on these findings and investigate how modern deep-sea fish will respond to climate change, and potentially inform conservation efforts.
“What we learned from this study is that deep-sea fishes tend to do well when oceans are colder, but with climate change, oceans are getting warmer,” she said. “We can expect that this is really going to impact fish in the deep-sea in the coming years.”
Co-authors are Luke Tornabene at the UW; Christopher Martinez at UC Irvine; Sarah Friedman at the NOAA Alaska Fisheries Science Center; Peter Wainwright at UC Davis; and Samantha Price at Clemson University.
This research was funded by the National Science Foundation.
How ancient fish colonized the deep sea
The post How ancient fish colonized the deep sea first appeared on .
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["title"]=>
string(56) "Ambrosia beetles breed and maintain their own food fungi"
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string(88) "https://coolnspicy.com/science/ambrosia-beetles-breed-and-maintain-their-own-food-fungi/"
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string(15) "Michael Steiner"
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string(31) "Thu, 03 Nov 2022 08:11:06 +0000"
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string(44) "scienceAmbrosiabeetlesbreedfoodfungimaintain"
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string(915) "Journal Reference: Janina M. C. Diehl, Vienna Kowallik, Alexander Keller, Peter H. W. Biedermann. First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1458 Fungal coatings in wooden tunnels Ambrosia beetles feed on special fungal coatings that ... Read more
The post Ambrosia beetles breed and maintain their own food fungi first appeared on .
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Journal Reference:
- Janina M. C. Diehl, Vienna Kowallik, Alexander Keller, Peter H. W. Biedermann. First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1458
Fungal coatings in wooden tunnels
Ambrosia beetles feed on special fungal coatings that grow in the tunnels they bore into old wood. To early naturalists, these coverings seemed like divine ambrosia, which is how the beetles got their name. Due to their social and hygienic behavior, it has long been assumed that they actively care for their fungi, but so far, such agricultural abilities have only been demonstrated in some termites and leafcutter ants.
Genetic analysis of fungus gardens
Diehl has now also succeeded in doing this for ambrosia beetles: In the laboratory, she had mother beetles of the little wood borer establish nests with offspring, in which the typical fungal gardens formed. She then removed the nurturing individuals from some of the nests and left them in others. Genetic analysis of bacterial and fungal communities of the fungal gardens after 40 days showed that the presence of the beetles had greatly altered the fungal community.
“You might have expected there to be fewer food fungi in the nests with beetles because they were being eaten, but in fact, the opposite was true; here the fungal composition was clearly shifted toward food fungi,” says Diehl. In the nests without nurturing beetles, on the other hand, the proportion of weed fungi was significantly higher. The composition of the bacteria also differed.
Beetles probably use antibiotic-forming bacteria
“These results support the existence of active farming in ambrosia beetles, although the exact mechanisms controlling the fungal community need further investigation,” adds Biedermann. He says there is evidence that the beetles use specific bacteria that produce antibiotic substances. These, in turn, could inhibit the growth of the weed fungi.
Social behavior probably also plays an important role; the entire group of beetles in the nest, including the larvae, work together to care for the fungi. This creates a close symbiosis between beetles and fungi: “Each ambrosia beetle species has its own food fungus. Neither can survive without the other.”
60 million years of experience
Economically relevant bark beetles, such as the spruce bark beetle (Ips typographus), also have similar symbioses with fungi, and understanding them could help control the beetles better in the future. Further research into how exactly ambrosia beetles suppress the growth of weed fungi could also provide worthwhile insights for human agriculture, which is struggling with resistance, for example, says Biedermann. “It’s highly exciting for us to see how nature has been doing this for 60 million years. Presumably, we humans can still learn something from these mechanisms.”
Journal Reference:
- Janina M. C. Diehl, Vienna Kowallik, Alexander Keller, Peter H. W. Biedermann. First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1458
Fungal coatings in wooden tunnels
Ambrosia beetles feed on special fungal coatings that grow in the tunnels they bore into old wood. To early naturalists, these coverings seemed like divine ambrosia, which is how the beetles got their name. Due to their social and hygienic behavior, it has long been assumed that they actively care for their fungi, but so far, such agricultural abilities have only been demonstrated in some termites and leafcutter ants.
Genetic analysis of fungus gardens
Diehl has now also succeeded in doing this for ambrosia beetles: In the laboratory, she had mother beetles of the little wood borer establish nests with offspring, in which the typical fungal gardens formed. She then removed the nurturing individuals from some of the nests and left them in others. Genetic analysis of bacterial and fungal communities of the fungal gardens after 40 days showed that the presence of the beetles had greatly altered the fungal community.
“You might have expected there to be fewer food fungi in the nests with beetles because they were being eaten, but in fact, the opposite was true; here the fungal composition was clearly shifted toward food fungi,” says Diehl. In the nests without nurturing beetles, on the other hand, the proportion of weed fungi was significantly higher. The composition of the bacteria also differed.
Beetles probably use antibiotic-forming bacteria
“These results support the existence of active farming in ambrosia beetles, although the exact mechanisms controlling the fungal community need further investigation,” adds Biedermann. He says there is evidence that the beetles use specific bacteria that produce antibiotic substances. These, in turn, could inhibit the growth of the weed fungi.
Social behavior probably also plays an important role; the entire group of beetles in the nest, including the larvae, work together to care for the fungi. This creates a close symbiosis between beetles and fungi: “Each ambrosia beetle species has its own food fungus. Neither can survive without the other.”
60 million years of experience
Economically relevant bark beetles, such as the spruce bark beetle (Ips typographus), also have similar symbioses with fungi, and understanding them could help control the beetles better in the future. Further research into how exactly ambrosia beetles suppress the growth of weed fungi could also provide worthwhile insights for human agriculture, which is struggling with resistance, for example, says Biedermann. “It’s highly exciting for us to see how nature has been doing this for 60 million years. Presumably, we humans can still learn something from these mechanisms.”
original title
The post Ambrosia beetles breed and maintain their own food fungi first appeared on .
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string(915) "Journal Reference: Janina M. C. Diehl, Vienna Kowallik, Alexander Keller, Peter H. W. Biedermann. First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1458 Fungal coatings in wooden tunnels Ambrosia beetles feed on special fungal coatings that ... Read more
The post Ambrosia beetles breed and maintain their own food fungi first appeared on .
"
["atom_content"]=>
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Journal Reference:
- Janina M. C. Diehl, Vienna Kowallik, Alexander Keller, Peter H. W. Biedermann. First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1458
Fungal coatings in wooden tunnels
Ambrosia beetles feed on special fungal coatings that grow in the tunnels they bore into old wood. To early naturalists, these coverings seemed like divine ambrosia, which is how the beetles got their name. Due to their social and hygienic behavior, it has long been assumed that they actively care for their fungi, but so far, such agricultural abilities have only been demonstrated in some termites and leafcutter ants.
Genetic analysis of fungus gardens
Diehl has now also succeeded in doing this for ambrosia beetles: In the laboratory, she had mother beetles of the little wood borer establish nests with offspring, in which the typical fungal gardens formed. She then removed the nurturing individuals from some of the nests and left them in others. Genetic analysis of bacterial and fungal communities of the fungal gardens after 40 days showed that the presence of the beetles had greatly altered the fungal community.
“You might have expected there to be fewer food fungi in the nests with beetles because they were being eaten, but in fact, the opposite was true; here the fungal composition was clearly shifted toward food fungi,” says Diehl. In the nests without nurturing beetles, on the other hand, the proportion of weed fungi was significantly higher. The composition of the bacteria also differed.
Beetles probably use antibiotic-forming bacteria
“These results support the existence of active farming in ambrosia beetles, although the exact mechanisms controlling the fungal community need further investigation,” adds Biedermann. He says there is evidence that the beetles use specific bacteria that produce antibiotic substances. These, in turn, could inhibit the growth of the weed fungi.
Social behavior probably also plays an important role; the entire group of beetles in the nest, including the larvae, work together to care for the fungi. This creates a close symbiosis between beetles and fungi: “Each ambrosia beetle species has its own food fungus. Neither can survive without the other.”
60 million years of experience
Economically relevant bark beetles, such as the spruce bark beetle (Ips typographus), also have similar symbioses with fungi, and understanding them could help control the beetles better in the future. Further research into how exactly ambrosia beetles suppress the growth of weed fungi could also provide worthwhile insights for human agriculture, which is struggling with resistance, for example, says Biedermann. “It’s highly exciting for us to see how nature has been doing this for 60 million years. Presumably, we humans can still learn something from these mechanisms.”
Journal Reference:
- Janina M. C. Diehl, Vienna Kowallik, Alexander Keller, Peter H. W. Biedermann. First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes. Proceedings of the Royal Society B: Biological Sciences, 2022; 289 (1986) DOI: 10.1098/rspb.2022.1458
Fungal coatings in wooden tunnels
Ambrosia beetles feed on special fungal coatings that grow in the tunnels they bore into old wood. To early naturalists, these coverings seemed like divine ambrosia, which is how the beetles got their name. Due to their social and hygienic behavior, it has long been assumed that they actively care for their fungi, but so far, such agricultural abilities have only been demonstrated in some termites and leafcutter ants.
Genetic analysis of fungus gardens
Diehl has now also succeeded in doing this for ambrosia beetles: In the laboratory, she had mother beetles of the little wood borer establish nests with offspring, in which the typical fungal gardens formed. She then removed the nurturing individuals from some of the nests and left them in others. Genetic analysis of bacterial and fungal communities of the fungal gardens after 40 days showed that the presence of the beetles had greatly altered the fungal community.
“You might have expected there to be fewer food fungi in the nests with beetles because they were being eaten, but in fact, the opposite was true; here the fungal composition was clearly shifted toward food fungi,” says Diehl. In the nests without nurturing beetles, on the other hand, the proportion of weed fungi was significantly higher. The composition of the bacteria also differed.
Beetles probably use antibiotic-forming bacteria
“These results support the existence of active farming in ambrosia beetles, although the exact mechanisms controlling the fungal community need further investigation,” adds Biedermann. He says there is evidence that the beetles use specific bacteria that produce antibiotic substances. These, in turn, could inhibit the growth of the weed fungi.
Social behavior probably also plays an important role; the entire group of beetles in the nest, including the larvae, work together to care for the fungi. This creates a close symbiosis between beetles and fungi: “Each ambrosia beetle species has its own food fungus. Neither can survive without the other.”
60 million years of experience
Economically relevant bark beetles, such as the spruce bark beetle (Ips typographus), also have similar symbioses with fungi, and understanding them could help control the beetles better in the future. Further research into how exactly ambrosia beetles suppress the growth of weed fungi could also provide worthwhile insights for human agriculture, which is struggling with resistance, for example, says Biedermann. “It’s highly exciting for us to see how nature has been doing this for 60 million years. Presumably, we humans can still learn something from these mechanisms.”
original title
The post Ambrosia beetles breed and maintain their own food fungi first appeared on .
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[7]=>
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["title"]=>
string(73) "Glowing fossils: Fluorescence reveals color patterns of earliest scallops"
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string(104) "https://coolnspicy.com/science/glowing-fossils-fluorescence-reveals-color-patterns-of-earliest-scallops/"
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string(31) "Thu, 03 Nov 2022 08:09:49 +0000"
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string(1000) "Journal Reference: Klaus Wolkenstein. Fluorescent colour patterns in the basal pectinid Pleuronectites from the Middle Triassic of Central Europe: origin, fate and taxonomic implications of fluorescence. Palaeontology, 2022; 65 (5) DOI: 10.1111/pala.12625 In fossils from the Mesozoic Era, traces of colour patterns are very rarely observed. However, the investigation with UV light of scallops from ... Read more
The post Glowing fossils: Fluorescence reveals color patterns of earliest scallops first appeared on .
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Journal Reference:
- Klaus Wolkenstein. Fluorescent colour patterns in the basal pectinid Pleuronectites from the Middle Triassic of Central Europe: origin, fate and taxonomic implications of fluorescence. Palaeontology, 2022; 65 (5) DOI: 10.1111/pala.12625
In fossils from the Mesozoic Era, traces of colour patterns are very rarely observed. However, the investigation with UV light of scallops from the Triassic period — right from the beginning of the Mesozoic Era — shows that colour patterns are preserved much more frequently than previously thought. UV light, which is invisible to the human eye, excites organic compounds in the fossils causing them to glow. This reveals a surprising variety of colour patterns: different variations of stripes, zigzags and flame patterns. The diversity of colour patterns is similar to those of today’s seashells found on a beach.
However, the colour patterns of today’s scallops do not show any fluorescence. “In the case of the Triassic shells, fluorescent compounds were only formed in the course of fossilisation through oxidation of the original pigments,” explains Dr Klaus Wolkenstein from the Geosciences Centre at the University of Göttingen, who is currently carrying out research at the University of Bonn. Surprisingly, the fossil shells show different fluorescent colours, depending on the region where they were found. “The colour spectrum ranges from yellow to red with all the transitions in between, which suggests that there were clear regional differences in the fossilisation of these scallops,” adds Wolkenstein.
Journal Reference:
- Klaus Wolkenstein. Fluorescent colour patterns in the basal pectinid Pleuronectites from the Middle Triassic of Central Europe: origin, fate and taxonomic implications of fluorescence. Palaeontology, 2022; 65 (5) DOI: 10.1111/pala.12625
In fossils from the Mesozoic Era, traces of colour patterns are very rarely observed. However, the investigation with UV light of scallops from the Triassic period — right from the beginning of the Mesozoic Era — shows that colour patterns are preserved much more frequently than previously thought. UV light, which is invisible to the human eye, excites organic compounds in the fossils causing them to glow. This reveals a surprising variety of colour patterns: different variations of stripes, zigzags and flame patterns. The diversity of colour patterns is similar to those of today’s seashells found on a beach.
However, the colour patterns of today’s scallops do not show any fluorescence. “In the case of the Triassic shells, fluorescent compounds were only formed in the course of fossilisation through oxidation of the original pigments,” explains Dr Klaus Wolkenstein from the Geosciences Centre at the University of Göttingen, who is currently carrying out research at the University of Bonn. Surprisingly, the fossil shells show different fluorescent colours, depending on the region where they were found. “The colour spectrum ranges from yellow to red with all the transitions in between, which suggests that there were clear regional differences in the fossilisation of these scallops,” adds Wolkenstein.
Source link
The post Glowing fossils: Fluorescence reveals color patterns of earliest scallops first appeared on .
"
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string(1000) "Journal Reference: Klaus Wolkenstein. Fluorescent colour patterns in the basal pectinid Pleuronectites from the Middle Triassic of Central Europe: origin, fate and taxonomic implications of fluorescence. Palaeontology, 2022; 65 (5) DOI: 10.1111/pala.12625 In fossils from the Mesozoic Era, traces of colour patterns are very rarely observed. However, the investigation with UV light of scallops from ... Read more
The post Glowing fossils: Fluorescence reveals color patterns of earliest scallops first appeared on .
"
["atom_content"]=>
string(4549) "
Journal Reference:
- Klaus Wolkenstein. Fluorescent colour patterns in the basal pectinid Pleuronectites from the Middle Triassic of Central Europe: origin, fate and taxonomic implications of fluorescence. Palaeontology, 2022; 65 (5) DOI: 10.1111/pala.12625
In fossils from the Mesozoic Era, traces of colour patterns are very rarely observed. However, the investigation with UV light of scallops from the Triassic period — right from the beginning of the Mesozoic Era — shows that colour patterns are preserved much more frequently than previously thought. UV light, which is invisible to the human eye, excites organic compounds in the fossils causing them to glow. This reveals a surprising variety of colour patterns: different variations of stripes, zigzags and flame patterns. The diversity of colour patterns is similar to those of today’s seashells found on a beach.
However, the colour patterns of today’s scallops do not show any fluorescence. “In the case of the Triassic shells, fluorescent compounds were only formed in the course of fossilisation through oxidation of the original pigments,” explains Dr Klaus Wolkenstein from the Geosciences Centre at the University of Göttingen, who is currently carrying out research at the University of Bonn. Surprisingly, the fossil shells show different fluorescent colours, depending on the region where they were found. “The colour spectrum ranges from yellow to red with all the transitions in between, which suggests that there were clear regional differences in the fossilisation of these scallops,” adds Wolkenstein.
Journal Reference:
- Klaus Wolkenstein. Fluorescent colour patterns in the basal pectinid Pleuronectites from the Middle Triassic of Central Europe: origin, fate and taxonomic implications of fluorescence. Palaeontology, 2022; 65 (5) DOI: 10.1111/pala.12625
In fossils from the Mesozoic Era, traces of colour patterns are very rarely observed. However, the investigation with UV light of scallops from the Triassic period — right from the beginning of the Mesozoic Era — shows that colour patterns are preserved much more frequently than previously thought. UV light, which is invisible to the human eye, excites organic compounds in the fossils causing them to glow. This reveals a surprising variety of colour patterns: different variations of stripes, zigzags and flame patterns. The diversity of colour patterns is similar to those of today’s seashells found on a beach.
However, the colour patterns of today’s scallops do not show any fluorescence. “In the case of the Triassic shells, fluorescent compounds were only formed in the course of fossilisation through oxidation of the original pigments,” explains Dr Klaus Wolkenstein from the Geosciences Centre at the University of Göttingen, who is currently carrying out research at the University of Bonn. Surprisingly, the fossil shells show different fluorescent colours, depending on the region where they were found. “The colour spectrum ranges from yellow to red with all the transitions in between, which suggests that there were clear regional differences in the fossilisation of these scallops,” adds Wolkenstein.
Source link
The post Glowing fossils: Fluorescence reveals color patterns of earliest scallops first appeared on .
"
["date_timestamp"]=>
int(1667462989)
}
[8]=>
array(11) {
["title"]=>
string(76) "Unveiling the dimensionality of complex networks through hyperbolic geometry"
["link"]=>
string(108) "https://coolnspicy.com/science/unveiling-the-dimensionality-of-complex-networks-through-hyperbolic-geometry/"
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string(15) "Michael Steiner"
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["pubdate"]=>
string(31) "Thu, 03 Nov 2022 08:09:34 +0000"
["category"]=>
string(63) "sciencecomplexdimensionalitygeometryhyperbolicnetworksUnveiling"
["guid"]=>
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["description"]=>
string(996) "Journal Reference: Pedro Almagro, Marián Boguñá, M. Ángeles Serrano. Detecting the ultra low dimensionality of real networks. Nature Communications, 2022; 13 (1) DOI: 10.1038/s41467-022-33685-z Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá, from the Faculty of Physics and the Institute of Complex Systems of the UB (UBICS), and ... Read more
The post Unveiling the dimensionality of complex networks through hyperbolic geometry first appeared on .
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Journal Reference:
- Pedro Almagro, Marián Boguñá, M. Ángeles Serrano. Detecting the ultra low dimensionality of real networks. Nature Communications, 2022; 13 (1) DOI: 10.1038/s41467-022-33685-z
Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá, from the Faculty of Physics and the Institute of Complex Systems of the UB (UBICS), and Pedro Almargo, from the Higher Technical School of Engineering of the University of Sevilla. The research study provides a multidimensional hyperbolic model of complex networks that reproduces its connectivity, with an ultra-low and customizable dimensionality for each specific network. This enables a better characterization of its structure — e.g. at a community scale — and the improvement of its predictive capability.
The study reveals unexpected regularities, such as the extremely low dimensions of molecular networks associated with biological tissues; the slightly higher dimensionality required by social networks and the Internet; and the discovery that brain connectomes are close to three dimensions in their automatic organisation.
Hyperbolic versus Euclidean geometry
The intrinsic geometry of data sets or complex networks is not obvious, which becomes an obstacle in determining the dimensionality of real networks. Another challenge is that the definition of distance has to be established according to their relational and connectivity structure, and this also requires sophisticated models.
Now, the new approach is based on the geometry of complex networks, and more specifically, on the configurational geometric model or SD model. “This model, which we have developed in previous work, describes the structure of complex networks based on fundamental principles,” says the lecturer M. Ángeles, ICREA researcher at the Department of Condensed Matter Physics of the UB.
“More specifically — he continues — , the model postulates a law of interconnection of the network elements (or nodes) that is gravitational, so nodes that are closer in a similarity space — of spherical geometry in D dimensions — and with more popularity — an extra dimension corresponding to the importance of the node — are more likely to establish connections.”
In the study, the similarity and popularity variables are combined to give rise to the hyperbolic geometry of the model, which emerges as the natural geometry representing the hierarchical architecture of complex networks.
In previous studies, the team had applied the simplest version of the one-dimensional SD model — the S1 model — to explain many typical features of real-world networks: the small-world property (the six degrees of separation), the heterogeneous distributions of the number of neighbours per node, and the high levels of transitive relationships (triangle connections that can be illustrated with the expression my friend’s friend is also my friend).
“In addition, the application of statistical inference techniques allows us to obtain real network maps in the hyperbolic plan that are congruent with the established model,” she says. “Beyond visualisation, these representations have been used in a multitude of tasks, including efficient navigation methods, the detection of self-similarity patterns, the detection of strongly interacting communities of nodes, and the implementation of a network renormalisation procedure that reveals hidden symmetries in the multi-scale organisation of complex networks and allows the production of network replicas at reduced or enlarged scales.”
Now, the team infers the dimensionality of the hyperbolic space underlying the real networks from properties that relate to the dimension of their geometry. In particular, the work measures the statistics of higher-order cycles (triangles, squares, pentagons) associated with the connections.
A methodology applicable to all complex networks
In computer science, the applied techniques are based on data that typically make definitions of similarity distance between their elements, an approach that involves the construction of graphs that are mapped onto a latent space of Euclidean features.
“Our estimates of the dimensionality of complex networks are well below our estimates based on Euclidean space, since hyperbolic space is better suited to represent the hierarchical structure of real complex networks. For example, the Internet only requires D = 7 dimensions to be mapped into the hyperbolic space of our model, whereas this name is multiplied by six and scales to D = 47 in one of the most recent techniques using Euclidean space,” says Professor Marián Boguñá.
In addition, techniques for mapping complex data usually assume a latent space, with a predetermined name of dimensions, or implement heuristic techniques to find a suitable value. Thus, the new method is based on a model that does not need the spatial mapping of the network to determine the dimension of its geometry.
In the field of network science, many methodologies use the shortest distances to study the connectivity structure of the network (shortest paths) as a metric space. However, these distances are strongly affected by the small-world property and do not provide a wide range of distance values.
“Our model uses a completely different definition of distance based on an underlying hyperbolic space, and we do not need to map the network. Our methodology is applicable to any real network or data series with complex structure and with a size that is typically thousands or tens of thousands of nodes but can reach hundreds of thousands in a reasonable computational time,” says M. Ángeles Serrano.
What is the real dimensionality of social networks and the Internet?
ocial networks and the Internet is higher (between 6 and 9) compared to networks in other domains, according to the study’s findings. However, it is still very low — 6 to 7 times lower — compared to that obtained by other methods. This reflects the fact that interactions in these systems are more complex and determined by a greater variety of factors.
On the other hand, friendship-based social networks are at the top of the dimensionality ranking. “This is an unexpected result, since one might think that friendship is a freer type of affective relationship, but our results link to the fact that homophily in human interactions is determined by a multitude of sociological factors such as age, gender, social class, beliefs, attitudes or interests,” says M. Ángeles Serrano.
In the case of the Internet, even though it is a technological network, its greater dimensionality reflects the fact that for an autonomous system, connecting does not mean only accessing the system, as one might think at first. On the contrary, many different factors influence the formation of these connections, and as a consequence, a variety of other relationships may be present (e.g., supplier-client, peer-to-peer, exchange-based peering, etc.).
“What is really surprising, both for social networks and the internet, is that our theoretical framework — which does not use any annotations about connections beyond their existence — is able to capture this multidimensional reality that is not explicit in our data,” concludes the team, which is currently working on constructing hyperbolic multidimensional maps of complex networks that are congruent with the theoretical framework established by the SD model.
Journal Reference:
- Pedro Almagro, Marián Boguñá, M. Ángeles Serrano. Detecting the ultra low dimensionality of real networks. Nature Communications, 2022; 13 (1) DOI: 10.1038/s41467-022-33685-z
Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá, from the Faculty of Physics and the Institute of Complex Systems of the UB (UBICS), and Pedro Almargo, from the Higher Technical School of Engineering of the University of Sevilla. The research study provides a multidimensional hyperbolic model of complex networks that reproduces its connectivity, with an ultra-low and customizable dimensionality for each specific network. This enables a better characterization of its structure — e.g. at a community scale — and the improvement of its predictive capability.
The study reveals unexpected regularities, such as the extremely low dimensions of molecular networks associated with biological tissues; the slightly higher dimensionality required by social networks and the Internet; and the discovery that brain connectomes are close to three dimensions in their automatic organisation.
Hyperbolic versus Euclidean geometry
The intrinsic geometry of data sets or complex networks is not obvious, which becomes an obstacle in determining the dimensionality of real networks. Another challenge is that the definition of distance has to be established according to their relational and connectivity structure, and this also requires sophisticated models.
Now, the new approach is based on the geometry of complex networks, and more specifically, on the configurational geometric model or SD model. “This model, which we have developed in previous work, describes the structure of complex networks based on fundamental principles,” says the lecturer M. Ángeles, ICREA researcher at the Department of Condensed Matter Physics of the UB.
“More specifically — he continues — , the model postulates a law of interconnection of the network elements (or nodes) that is gravitational, so nodes that are closer in a similarity space — of spherical geometry in D dimensions — and with more popularity — an extra dimension corresponding to the importance of the node — are more likely to establish connections.”
In the study, the similarity and popularity variables are combined to give rise to the hyperbolic geometry of the model, which emerges as the natural geometry representing the hierarchical architecture of complex networks.
In previous studies, the team had applied the simplest version of the one-dimensional SD model — the S1 model — to explain many typical features of real-world networks: the small-world property (the six degrees of separation), the heterogeneous distributions of the number of neighbours per node, and the high levels of transitive relationships (triangle connections that can be illustrated with the expression my friend’s friend is also my friend).
“In addition, the application of statistical inference techniques allows us to obtain real network maps in the hyperbolic plan that are congruent with the established model,” she says. “Beyond visualisation, these representations have been used in a multitude of tasks, including efficient navigation methods, the detection of self-similarity patterns, the detection of strongly interacting communities of nodes, and the implementation of a network renormalisation procedure that reveals hidden symmetries in the multi-scale organisation of complex networks and allows the production of network replicas at reduced or enlarged scales.”
Now, the team infers the dimensionality of the hyperbolic space underlying the real networks from properties that relate to the dimension of their geometry. In particular, the work measures the statistics of higher-order cycles (triangles, squares, pentagons) associated with the connections.
A methodology applicable to all complex networks
In computer science, the applied techniques are based on data that typically make definitions of similarity distance between their elements, an approach that involves the construction of graphs that are mapped onto a latent space of Euclidean features.
“Our estimates of the dimensionality of complex networks are well below our estimates based on Euclidean space, since hyperbolic space is better suited to represent the hierarchical structure of real complex networks. For example, the Internet only requires D = 7 dimensions to be mapped into the hyperbolic space of our model, whereas this name is multiplied by six and scales to D = 47 in one of the most recent techniques using Euclidean space,” says Professor Marián Boguñá.
In addition, techniques for mapping complex data usually assume a latent space, with a predetermined name of dimensions, or implement heuristic techniques to find a suitable value. Thus, the new method is based on a model that does not need the spatial mapping of the network to determine the dimension of its geometry.
In the field of network science, many methodologies use the shortest distances to study the connectivity structure of the network (shortest paths) as a metric space. However, these distances are strongly affected by the small-world property and do not provide a wide range of distance values.
“Our model uses a completely different definition of distance based on an underlying hyperbolic space, and we do not need to map the network. Our methodology is applicable to any real network or data series with complex structure and with a size that is typically thousands or tens of thousands of nodes but can reach hundreds of thousands in a reasonable computational time,” says M. Ángeles Serrano.
What is the real dimensionality of social networks and the Internet?
ocial networks and the Internet is higher (between 6 and 9) compared to networks in other domains, according to the study’s findings. However, it is still very low — 6 to 7 times lower — compared to that obtained by other methods. This reflects the fact that interactions in these systems are more complex and determined by a greater variety of factors.
On the other hand, friendship-based social networks are at the top of the dimensionality ranking. “This is an unexpected result, since one might think that friendship is a freer type of affective relationship, but our results link to the fact that homophily in human interactions is determined by a multitude of sociological factors such as age, gender, social class, beliefs, attitudes or interests,” says M. Ángeles Serrano.
In the case of the Internet, even though it is a technological network, its greater dimensionality reflects the fact that for an autonomous system, connecting does not mean only accessing the system, as one might think at first. On the contrary, many different factors influence the formation of these connections, and as a consequence, a variety of other relationships may be present (e.g., supplier-client, peer-to-peer, exchange-based peering, etc.).
“What is really surprising, both for social networks and the internet, is that our theoretical framework — which does not use any annotations about connections beyond their existence — is able to capture this multidimensional reality that is not explicit in our data,” concludes the team, which is currently working on constructing hyperbolic multidimensional maps of complex networks that are congruent with the theoretical framework established by the SD model.
Source link
The post Unveiling the dimensionality of complex networks through hyperbolic geometry first appeared on .
"
}
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string(996) "Journal Reference: Pedro Almagro, Marián Boguñá, M. Ángeles Serrano. Detecting the ultra low dimensionality of real networks. Nature Communications, 2022; 13 (1) DOI: 10.1038/s41467-022-33685-z Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá, from the Faculty of Physics and the Institute of Complex Systems of the UB (UBICS), and ... Read more
The post Unveiling the dimensionality of complex networks through hyperbolic geometry first appeared on .
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Journal Reference:
- Pedro Almagro, Marián Boguñá, M. Ángeles Serrano. Detecting the ultra low dimensionality of real networks. Nature Communications, 2022; 13 (1) DOI: 10.1038/s41467-022-33685-z
Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá, from the Faculty of Physics and the Institute of Complex Systems of the UB (UBICS), and Pedro Almargo, from the Higher Technical School of Engineering of the University of Sevilla. The research study provides a multidimensional hyperbolic model of complex networks that reproduces its connectivity, with an ultra-low and customizable dimensionality for each specific network. This enables a better characterization of its structure — e.g. at a community scale — and the improvement of its predictive capability.
The study reveals unexpected regularities, such as the extremely low dimensions of molecular networks associated with biological tissues; the slightly higher dimensionality required by social networks and the Internet; and the discovery that brain connectomes are close to three dimensions in their automatic organisation.
Hyperbolic versus Euclidean geometry
The intrinsic geometry of data sets or complex networks is not obvious, which becomes an obstacle in determining the dimensionality of real networks. Another challenge is that the definition of distance has to be established according to their relational and connectivity structure, and this also requires sophisticated models.
Now, the new approach is based on the geometry of complex networks, and more specifically, on the configurational geometric model or SD model. “This model, which we have developed in previous work, describes the structure of complex networks based on fundamental principles,” says the lecturer M. Ángeles, ICREA researcher at the Department of Condensed Matter Physics of the UB.
“More specifically — he continues — , the model postulates a law of interconnection of the network elements (or nodes) that is gravitational, so nodes that are closer in a similarity space — of spherical geometry in D dimensions — and with more popularity — an extra dimension corresponding to the importance of the node — are more likely to establish connections.”
In the study, the similarity and popularity variables are combined to give rise to the hyperbolic geometry of the model, which emerges as the natural geometry representing the hierarchical architecture of complex networks.
In previous studies, the team had applied the simplest version of the one-dimensional SD model — the S1 model — to explain many typical features of real-world networks: the small-world property (the six degrees of separation), the heterogeneous distributions of the number of neighbours per node, and the high levels of transitive relationships (triangle connections that can be illustrated with the expression my friend’s friend is also my friend).
“In addition, the application of statistical inference techniques allows us to obtain real network maps in the hyperbolic plan that are congruent with the established model,” she says. “Beyond visualisation, these representations have been used in a multitude of tasks, including efficient navigation methods, the detection of self-similarity patterns, the detection of strongly interacting communities of nodes, and the implementation of a network renormalisation procedure that reveals hidden symmetries in the multi-scale organisation of complex networks and allows the production of network replicas at reduced or enlarged scales.”
Now, the team infers the dimensionality of the hyperbolic space underlying the real networks from properties that relate to the dimension of their geometry. In particular, the work measures the statistics of higher-order cycles (triangles, squares, pentagons) associated with the connections.
A methodology applicable to all complex networks
In computer science, the applied techniques are based on data that typically make definitions of similarity distance between their elements, an approach that involves the construction of graphs that are mapped onto a latent space of Euclidean features.
“Our estimates of the dimensionality of complex networks are well below our estimates based on Euclidean space, since hyperbolic space is better suited to represent the hierarchical structure of real complex networks. For example, the Internet only requires D = 7 dimensions to be mapped into the hyperbolic space of our model, whereas this name is multiplied by six and scales to D = 47 in one of the most recent techniques using Euclidean space,” says Professor Marián Boguñá.
In addition, techniques for mapping complex data usually assume a latent space, with a predetermined name of dimensions, or implement heuristic techniques to find a suitable value. Thus, the new method is based on a model that does not need the spatial mapping of the network to determine the dimension of its geometry.
In the field of network science, many methodologies use the shortest distances to study the connectivity structure of the network (shortest paths) as a metric space. However, these distances are strongly affected by the small-world property and do not provide a wide range of distance values.
“Our model uses a completely different definition of distance based on an underlying hyperbolic space, and we do not need to map the network. Our methodology is applicable to any real network or data series with complex structure and with a size that is typically thousands or tens of thousands of nodes but can reach hundreds of thousands in a reasonable computational time,” says M. Ángeles Serrano.
What is the real dimensionality of social networks and the Internet?
ocial networks and the Internet is higher (between 6 and 9) compared to networks in other domains, according to the study’s findings. However, it is still very low — 6 to 7 times lower — compared to that obtained by other methods. This reflects the fact that interactions in these systems are more complex and determined by a greater variety of factors.
On the other hand, friendship-based social networks are at the top of the dimensionality ranking. “This is an unexpected result, since one might think that friendship is a freer type of affective relationship, but our results link to the fact that homophily in human interactions is determined by a multitude of sociological factors such as age, gender, social class, beliefs, attitudes or interests,” says M. Ángeles Serrano.
In the case of the Internet, even though it is a technological network, its greater dimensionality reflects the fact that for an autonomous system, connecting does not mean only accessing the system, as one might think at first. On the contrary, many different factors influence the formation of these connections, and as a consequence, a variety of other relationships may be present (e.g., supplier-client, peer-to-peer, exchange-based peering, etc.).
“What is really surprising, both for social networks and the internet, is that our theoretical framework — which does not use any annotations about connections beyond their existence — is able to capture this multidimensional reality that is not explicit in our data,” concludes the team, which is currently working on constructing hyperbolic multidimensional maps of complex networks that are congruent with the theoretical framework established by the SD model.
Journal Reference:
- Pedro Almagro, Marián Boguñá, M. Ángeles Serrano. Detecting the ultra low dimensionality of real networks. Nature Communications, 2022; 13 (1) DOI: 10.1038/s41467-022-33685-z
Among the authors of the study are the researchers M. Ángeles Serrano and Marián Boguñá, from the Faculty of Physics and the Institute of Complex Systems of the UB (UBICS), and Pedro Almargo, from the Higher Technical School of Engineering of the University of Sevilla. The research study provides a multidimensional hyperbolic model of complex networks that reproduces its connectivity, with an ultra-low and customizable dimensionality for each specific network. This enables a better characterization of its structure — e.g. at a community scale — and the improvement of its predictive capability.
The study reveals unexpected regularities, such as the extremely low dimensions of molecular networks associated with biological tissues; the slightly higher dimensionality required by social networks and the Internet; and the discovery that brain connectomes are close to three dimensions in their automatic organisation.
Hyperbolic versus Euclidean geometry
The intrinsic geometry of data sets or complex networks is not obvious, which becomes an obstacle in determining the dimensionality of real networks. Another challenge is that the definition of distance has to be established according to their relational and connectivity structure, and this also requires sophisticated models.
Now, the new approach is based on the geometry of complex networks, and more specifically, on the configurational geometric model or SD model. “This model, which we have developed in previous work, describes the structure of complex networks based on fundamental principles,” says the lecturer M. Ángeles, ICREA researcher at the Department of Condensed Matter Physics of the UB.
“More specifically — he continues — , the model postulates a law of interconnection of the network elements (or nodes) that is gravitational, so nodes that are closer in a similarity space — of spherical geometry in D dimensions — and with more popularity — an extra dimension corresponding to the importance of the node — are more likely to establish connections.”
In the study, the similarity and popularity variables are combined to give rise to the hyperbolic geometry of the model, which emerges as the natural geometry representing the hierarchical architecture of complex networks.
In previous studies, the team had applied the simplest version of the one-dimensional SD model — the S1 model — to explain many typical features of real-world networks: the small-world property (the six degrees of separation), the heterogeneous distributions of the number of neighbours per node, and the high levels of transitive relationships (triangle connections that can be illustrated with the expression my friend’s friend is also my friend).
“In addition, the application of statistical inference techniques allows us to obtain real network maps in the hyperbolic plan that are congruent with the established model,” she says. “Beyond visualisation, these representations have been used in a multitude of tasks, including efficient navigation methods, the detection of self-similarity patterns, the detection of strongly interacting communities of nodes, and the implementation of a network renormalisation procedure that reveals hidden symmetries in the multi-scale organisation of complex networks and allows the production of network replicas at reduced or enlarged scales.”
Now, the team infers the dimensionality of the hyperbolic space underlying the real networks from properties that relate to the dimension of their geometry. In particular, the work measures the statistics of higher-order cycles (triangles, squares, pentagons) associated with the connections.
A methodology applicable to all complex networks
In computer science, the applied techniques are based on data that typically make definitions of similarity distance between their elements, an approach that involves the construction of graphs that are mapped onto a latent space of Euclidean features.
“Our estimates of the dimensionality of complex networks are well below our estimates based on Euclidean space, since hyperbolic space is better suited to represent the hierarchical structure of real complex networks. For example, the Internet only requires D = 7 dimensions to be mapped into the hyperbolic space of our model, whereas this name is multiplied by six and scales to D = 47 in one of the most recent techniques using Euclidean space,” says Professor Marián Boguñá.
In addition, techniques for mapping complex data usually assume a latent space, with a predetermined name of dimensions, or implement heuristic techniques to find a suitable value. Thus, the new method is based on a model that does not need the spatial mapping of the network to determine the dimension of its geometry.
In the field of network science, many methodologies use the shortest distances to study the connectivity structure of the network (shortest paths) as a metric space. However, these distances are strongly affected by the small-world property and do not provide a wide range of distance values.
“Our model uses a completely different definition of distance based on an underlying hyperbolic space, and we do not need to map the network. Our methodology is applicable to any real network or data series with complex structure and with a size that is typically thousands or tens of thousands of nodes but can reach hundreds of thousands in a reasonable computational time,” says M. Ángeles Serrano.
What is the real dimensionality of social networks and the Internet?
ocial networks and the Internet is higher (between 6 and 9) compared to networks in other domains, according to the study’s findings. However, it is still very low — 6 to 7 times lower — compared to that obtained by other methods. This reflects the fact that interactions in these systems are more complex and determined by a greater variety of factors.
On the other hand, friendship-based social networks are at the top of the dimensionality ranking. “This is an unexpected result, since one might think that friendship is a freer type of affective relationship, but our results link to the fact that homophily in human interactions is determined by a multitude of sociological factors such as age, gender, social class, beliefs, attitudes or interests,” says M. Ángeles Serrano.
In the case of the Internet, even though it is a technological network, its greater dimensionality reflects the fact that for an autonomous system, connecting does not mean only accessing the system, as one might think at first. On the contrary, many different factors influence the formation of these connections, and as a consequence, a variety of other relationships may be present (e.g., supplier-client, peer-to-peer, exchange-based peering, etc.).
“What is really surprising, both for social networks and the internet, is that our theoretical framework — which does not use any annotations about connections beyond their existence — is able to capture this multidimensional reality that is not explicit in our data,” concludes the team, which is currently working on constructing hyperbolic multidimensional maps of complex networks that are congruent with the theoretical framework established by the SD model.
Source link
The post Unveiling the dimensionality of complex networks through hyperbolic geometry first appeared on .
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["title"]=>
string(48) "Good sleep can increase women’s work ambitions"
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string(831) "Journal Reference: Leah D. Sheppard, Teng Iat Loi, Julie A. Kmec. Too Tired to Lean In? Sleep Quality Impacts Women’s Daily Intentions to Pursue Workplace Status. Sex Roles, 2022; DOI: 10.1007/s11199-022-01321-1 The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well ... Read more
The post Good sleep can increase women’s work ambitions first appeared on .
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Journal Reference:
- Leah D. Sheppard, Teng Iat Loi, Julie A. Kmec. Too Tired to Lean In? Sleep Quality Impacts Women’s Daily Intentions to Pursue Workplace Status. Sex Roles, 2022; DOI: 10.1007/s11199-022-01321-1
The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well they had slept and the quality of their current mood, and then later in the day how they felt about striving for more status and responsibility at work.
“When women are getting a good night’s sleep and their mood is boosted, they are more likely to be oriented in their daily intentions toward achieving status and responsibility at work,” said lead author Leah Sheppard, an associate professor in WSU’s Carson College of Business. “If their sleep is poor and reduces their positive mood, then we saw that they were less oriented toward those goals.”
For the study published in the journal Sex Roles, Sheppard and co-authors Julie Kmec of WSU and Teng Iat Loi of University of Minnesota-Duluth surveyed full-time employees twice a day for two consecutive work weeks for a total of more than 2,200 observations. The participants answered questions about their previous night’s sleep and current mood around noon every day and in the evenings answered questions about their intentions to pursue more responsibility, status, and influence at work.
Both men and women reported good and bad sleep quality over the course of the study, notably with no gender difference in reported sleep quality. However, women more often reported lowered intentions to pursue more status at work on days following a night of poor sleep.
The researchers can only speculate about exactly why sleep’s impact on mood effects women’s aspirations and not men’s, but they suspect it may have to do with gender differences in emotion regulation as well as societal expectations — or some combination of these forces.
Neuroscience research has shown that women tend to experience greater emotional re-activity and less emotion regulation than men, and this can be reinforced by cultural stereotypes of women as more emotional. At the same time, stereotypes of men as being more ambitious than women likely add more pressure for them to scale the corporate ladder, so perhaps poor sleep quality would be less likely to deter men from their work aspirations.
These findings hold some good news for women who want to advance their careers, though, Sheppard said. For instance, they might take some practical steps to improve work aspirations, ranging from practicing meditation to help with both sleep and emotion regulation to putting better boundaries on work hours — and of course, simply striving to get better sleep.
“It’s important to be able to connect aspirations to something happening outside the work environment that is controllable,” she said. “There are lots of things that anyone can do to have a better night’s sleep and regulate mood in general.”
Journal Reference:
- Leah D. Sheppard, Teng Iat Loi, Julie A. Kmec. Too Tired to Lean In? Sleep Quality Impacts Women’s Daily Intentions to Pursue Workplace Status. Sex Roles, 2022; DOI: 10.1007/s11199-022-01321-1
The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well they had slept and the quality of their current mood, and then later in the day how they felt about striving for more status and responsibility at work.
“When women are getting a good night’s sleep and their mood is boosted, they are more likely to be oriented in their daily intentions toward achieving status and responsibility at work,” said lead author Leah Sheppard, an associate professor in WSU’s Carson College of Business. “If their sleep is poor and reduces their positive mood, then we saw that they were less oriented toward those goals.”
For the study published in the journal Sex Roles, Sheppard and co-authors Julie Kmec of WSU and Teng Iat Loi of University of Minnesota-Duluth surveyed full-time employees twice a day for two consecutive work weeks for a total of more than 2,200 observations. The participants answered questions about their previous night’s sleep and current mood around noon every day and in the evenings answered questions about their intentions to pursue more responsibility, status, and influence at work.
Both men and women reported good and bad sleep quality over the course of the study, notably with no gender difference in reported sleep quality. However, women more often reported lowered intentions to pursue more status at work on days following a night of poor sleep.
The researchers can only speculate about exactly why sleep’s impact on mood effects women’s aspirations and not men’s, but they suspect it may have to do with gender differences in emotion regulation as well as societal expectations — or some combination of these forces.
Neuroscience research has shown that women tend to experience greater emotional re-activity and less emotion regulation than men, and this can be reinforced by cultural stereotypes of women as more emotional. At the same time, stereotypes of men as being more ambitious than women likely add more pressure for them to scale the corporate ladder, so perhaps poor sleep quality would be less likely to deter men from their work aspirations.
These findings hold some good news for women who want to advance their careers, though, Sheppard said. For instance, they might take some practical steps to improve work aspirations, ranging from practicing meditation to help with both sleep and emotion regulation to putting better boundaries on work hours — and of course, simply striving to get better sleep.
“It’s important to be able to connect aspirations to something happening outside the work environment that is controllable,” she said. “There are lots of things that anyone can do to have a better night’s sleep and regulate mood in general.”
Source link
The post Good sleep can increase women’s work ambitions first appeared on .
"
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string(831) "Journal Reference: Leah D. Sheppard, Teng Iat Loi, Julie A. Kmec. Too Tired to Lean In? Sleep Quality Impacts Women’s Daily Intentions to Pursue Workplace Status. Sex Roles, 2022; DOI: 10.1007/s11199-022-01321-1 The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well ... Read more
The post Good sleep can increase women’s work ambitions first appeared on .
"
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Journal Reference:
- Leah D. Sheppard, Teng Iat Loi, Julie A. Kmec. Too Tired to Lean In? Sleep Quality Impacts Women’s Daily Intentions to Pursue Workplace Status. Sex Roles, 2022; DOI: 10.1007/s11199-022-01321-1
The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well they had slept and the quality of their current mood, and then later in the day how they felt about striving for more status and responsibility at work.
“When women are getting a good night’s sleep and their mood is boosted, they are more likely to be oriented in their daily intentions toward achieving status and responsibility at work,” said lead author Leah Sheppard, an associate professor in WSU’s Carson College of Business. “If their sleep is poor and reduces their positive mood, then we saw that they were less oriented toward those goals.”
For the study published in the journal Sex Roles, Sheppard and co-authors Julie Kmec of WSU and Teng Iat Loi of University of Minnesota-Duluth surveyed full-time employees twice a day for two consecutive work weeks for a total of more than 2,200 observations. The participants answered questions about their previous night’s sleep and current mood around noon every day and in the evenings answered questions about their intentions to pursue more responsibility, status, and influence at work.
Both men and women reported good and bad sleep quality over the course of the study, notably with no gender difference in reported sleep quality. However, women more often reported lowered intentions to pursue more status at work on days following a night of poor sleep.
The researchers can only speculate about exactly why sleep’s impact on mood effects women’s aspirations and not men’s, but they suspect it may have to do with gender differences in emotion regulation as well as societal expectations — or some combination of these forces.
Neuroscience research has shown that women tend to experience greater emotional re-activity and less emotion regulation than men, and this can be reinforced by cultural stereotypes of women as more emotional. At the same time, stereotypes of men as being more ambitious than women likely add more pressure for them to scale the corporate ladder, so perhaps poor sleep quality would be less likely to deter men from their work aspirations.
These findings hold some good news for women who want to advance their careers, though, Sheppard said. For instance, they might take some practical steps to improve work aspirations, ranging from practicing meditation to help with both sleep and emotion regulation to putting better boundaries on work hours — and of course, simply striving to get better sleep.
“It’s important to be able to connect aspirations to something happening outside the work environment that is controllable,” she said. “There are lots of things that anyone can do to have a better night’s sleep and regulate mood in general.”
Journal Reference:
- Leah D. Sheppard, Teng Iat Loi, Julie A. Kmec. Too Tired to Lean In? Sleep Quality Impacts Women’s Daily Intentions to Pursue Workplace Status. Sex Roles, 2022; DOI: 10.1007/s11199-022-01321-1
The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well they had slept and the quality of their current mood, and then later in the day how they felt about striving for more status and responsibility at work.
“When women are getting a good night’s sleep and their mood is boosted, they are more likely to be oriented in their daily intentions toward achieving status and responsibility at work,” said lead author Leah Sheppard, an associate professor in WSU’s Carson College of Business. “If their sleep is poor and reduces their positive mood, then we saw that they were less oriented toward those goals.”
For the study published in the journal Sex Roles, Sheppard and co-authors Julie Kmec of WSU and Teng Iat Loi of University of Minnesota-Duluth surveyed full-time employees twice a day for two consecutive work weeks for a total of more than 2,200 observations. The participants answered questions about their previous night’s sleep and current mood around noon every day and in the evenings answered questions about their intentions to pursue more responsibility, status, and influence at work.
Both men and women reported good and bad sleep quality over the course of the study, notably with no gender difference in reported sleep quality. However, women more often reported lowered intentions to pursue more status at work on days following a night of poor sleep.
The researchers can only speculate about exactly why sleep’s impact on mood effects women’s aspirations and not men’s, but they suspect it may have to do with gender differences in emotion regulation as well as societal expectations — or some combination of these forces.
Neuroscience research has shown that women tend to experience greater emotional re-activity and less emotion regulation than men, and this can be reinforced by cultural stereotypes of women as more emotional. At the same time, stereotypes of men as being more ambitious than women likely add more pressure for them to scale the corporate ladder, so perhaps poor sleep quality would be less likely to deter men from their work aspirations.
These findings hold some good news for women who want to advance their careers, though, Sheppard said. For instance, they might take some practical steps to improve work aspirations, ranging from practicing meditation to help with both sleep and emotion regulation to putting better boundaries on work hours — and of course, simply striving to get better sleep.
“It’s important to be able to connect aspirations to something happening outside the work environment that is controllable,” she said. “There are lots of things that anyone can do to have a better night’s sleep and regulate mood in general.”
Source link
The post Good sleep can increase women’s work ambitions first appeared on .
"
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string(9) "
hourly "
["updatefrequency"]=>
string(4) "
1 "
}
["generator"]=>
string(28) "https://wordpress.org/?v=6.1"
["tagline"]=>
NULL
}
["textinput"]=>
array(0) {
}
["image"]=>
array(0) {
}
["feed_type"]=>
string(3) "RSS"
["feed_version"]=>
string(3) "2.0"
["encoding"]=>
string(5) "UTF-8"
["_source_encoding"]=>
string(0) ""
["ERROR"]=>
string(0) ""
["WARNING"]=>
string(0) ""
["_CONTENT_CONSTRUCTS"]=>
array(6) {
[0]=>
string(7) "content"
[1]=>
string(7) "summary"
[2]=>
string(4) "info"
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string(5) "title"
[4]=>
string(7) "tagline"
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string(9) "copyright"
}
["_KNOWN_ENCODINGS"]=>
array(3) {
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string(5) "UTF-8"
[1]=>
string(8) "US-ASCII"
[2]=>
string(10) "ISO-8859-1"
}
["stack"]=>
array(0) {
}
["inchannel"]=>
bool(false)
["initem"]=>
bool(false)
["incontent"]=>
bool(false)
["intextinput"]=>
bool(false)
["inimage"]=>
bool(false)
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bool(false)
["last_modified"]=>
string(31) "Fri, 04 Nov 2022 00:22:03 GMT
"
["etag"]=>
string(41) ""9739775aec895d60d67b702f42ea05ce-gzip"
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}