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Researchers from Lero, the Science Foundation Ireland Research Centre for Software, hosted at University of Limerick (UL), are lending support to Arnold Palmer's famous assertion that golf is predominantly played in "the six inches between the ears".

According to research by Lero and UL, kinaesthetic ability, which is an individual's ability to feel an action without actually performing it, may improve their golf game. Niall Ramsbottom, a researcher at Lero and UL, explained that recent research carried out by the team indicates that with mental practice, golfers can improve their putting.

"Our results indicate that a form of mental practice, i.e. the combination of action observation and motor imagery, may enhance the golf putting ability of experienced golfers," he said, "and that could well mean a reduction in a golfer's handicap".

The research was carried out at the Physical Education and Sports Sciences Department at University of Limerick, in conjunction with Lero. The findings for the work carried out by Mr Ramsbottom and his fellow researchers, Eoghan McNeill, Dr Adam Toth and Dr Mark Campbell, show that golfers who already had a good 'feel" for putting, may benefit the most from this mental practice.

"We found, kinaesthetic imagery ability - an individual's ability to imagine the feel of an action without actually performing it - may have an important role in determining the effectiveness of the exercise on putting performance. Putting is a feel-based motor skill and our research suggests that those with good kinaesthetic imagery ability may perform better following this mental practice technique," explained Mr Ramsbottom.

"The findings suggest that simply viewing a video of another performing an action may bolster one's ability to imagine and subsequently perform that action," he said.

Putting ability is crucial in golf as approximately 40% of golf strokes are taken with the putter.

"Furthermore, golf putting ability was found to be one of the most important skills in determining earnings on the Professional Golf Association (PGA) Tour," the report, published in Psychology of Sport and Exercise, states, citing previously conducted research.

In undertaking the research, 44 right-handed, skilled male golfers from the Limerick area were recruited. Each of the participants was required to hold a current Golfing Union of Ireland handicap, and could not have participated on any such research previously. In a laboratory environment, the golfers completed 40 putts with instructions to 'make the ball stop as close to the target as possible'. A three-dimensional ultrasound camera was used to record the putting and statistical analysis was conducted, using specialised software.

"A subset of golfers looked at an action observation video which consisted of an expert golfer performing the putting task in the same lab environment. They did so while listening to a motor imagery script consisting of short sentences describing key visual and kinaesthetic feelings associated with performing the putting the task. Having completed these simple exercises, the golfers who were found to have better kinaesthetic imagery (KI) ability benefited more from the mental practice intervention than those with poorer KI ability," explained Mr Ramsbottom.

Appropriately selected anticoagulation therapy can help to reduce the medical costs of patients suffering from atrial fibrillation. A new study from the University of Eastern Finland shows that direct oral anticoagulants can be a more cost-effective alternative than traditional warfarin therapy when the patient's place of residence is taken into consideration. Published in Geospatial Health, the study used GIS data to create a geospatial model comparing the costs of different anticoagulant therapies. The patient's travel, time-loss and medication costs were used parameters to determine the overall costs of therapy.

Most atrial fibrillation patients need anticoagulation management to reduce the risk of thromboembolic events and stroke. Currently, two major drug therapies are available: warfarin and direct oral anticoagulants (DOACs).

Patients receiving warfarin therapy require regular INR monitoring. As a result, warfarin therapy is more cost-effective than DOACs only when the patient lives near the INR sample collection point, due to higher costs of travel and greater loss of leisure or working time. The study found that DOACs are a more cost-effective alternative also in situations where the patient requires INR monitoring more frequently than normal.

The researchers developed a geospatial model that determines market areas DOAC and warfarin therapy, taking into consideration the costs of travel, time-loss caused by INR monitoring, different modes of travel and the patient's assumed working or retirement status. Using this data, they calculated distance limits for each market area by mode of transport, making is possible to compare the spatial costs of warfarin therapy also when using different modes of travel. The study compared the costs of warfarin and DOAC therapy in a hospital district in the eastern part of Finland.

The data used in the study included the regional sample collection point locations, the Finnish National Road and Street Database, and recent travel and medical cost parameters from the study area. The costs were looked at from the patient's perspective, taking into consideration possible national reimbursements of medical costs and costs of using a taxi.

"Our model pertains to Finland, but it is possible to create a similar geospatial model for other countries as well, provided that road data and the required parameters are available. It is also possible to use this model to compare other drugs that have a treatment setting that is similar to anticoagulant therapy," Project Researcher and lead author of the study Mikko Pyykönen from the University of Eastern Finland notes.

Researchers from Tohoku University and Tohoku University Hospital have revealed why some existing cancer treatments are ineffective in tackling the early-stages of lung cancer. A team led by Professor Tetsuya Kodama investigated the ability of anti-cancer agents to affect early-stage lung metastatic tumors.

The team developed a mouse model of lung metastasis that can produce lesions (less than 100 μm), which current clinical imaging had been unable to detect. Micro X-ray CT and histopathology were used to analyze the lungs. The small arteries were shown to be obstructed by tumor cells, which significantly reduces the total vessel length, volume, and number of vessel branches in the lung. The compromised arteries prevent anti-cancer agents with low-molecular weights from being sufficiently administered to a tumor.

Past animal experiments have shown that the enhanced permeability and retention (EPR) effect occurs when new tumor blood vessels are formed. This then enables the extravasation of certain size molecules (100-200 nm) to accumulate in tumors, more so than normal tissue. Experiments undertaken by Professor Kodama's team indicate that fluorescent dye encapsulated liposome (diameter 145 mm) are not present around lesions at the early stage of tumor development. This means that high-molecular weight anti-cancer agents also cannot be considered an effective hematogenous drug delivery method for the treatment of lung cancer at the early stage.

Surgery followed by a course of chemotherapy has been the mainstream treatment for early-stage lung cancer for some time. However, based on this research, Professor Kodama suggests that "these findings indicate the need for new drug delivery methods to replace conventional systemic chemotherapy and the development of new therapies for lung cancer."

Boston, MA -- HIV infection among infants remains an enormous global health challenge. Each day, 300 to 500 infants in sub-Saharan Africa become infected with the virus. HIV progresses much faster in infants than in adults because of their weaker immune systems. While antiretroviral drugs are highly effective at suppressing HIV in newborns and infants, these drugs are typically not administered immediately after birth, at least not in most countries hardest hit by the HIV epidemic. In 2010, an infant with HIV born in Mississippi was given antiretroviral therapy (ART) within 30 hours of her birth. This infant was then able to maintain spontaneous viral control for several months after stopping antiretroviral therapy, raising the possibility that early treatment might make a critical difference for newborns. The Early Infant Treatment (EIT) Study, led by Roger Shapiro, MD, MPH, from the Harvard T.H. Chan School of Public Health and Mathias Lichterfeld, MD, PhD, and Daniel Kuritzkes, MD, both from Brigham and Women's Hospital, sought to further investigate this possibility in newborns from Botswana. As part of an international collaborative effort, investigators from the Brigham conducted immunological and virological testing, finding that initiating ART immediately, rather than waiting a few weeks, provided measurable benefits for infants born with HIV. The team's results are published in Science Translational Medicine.

"Our study suggests that strategies to test and treat infants immediately after birth may improve outcomes. We find that ART initiation within hours after birth is doable and translates into multiple benefits for the infants -- lower frequencies of reservoir cells and improved immune responses," said Lichterfeld, the corresponding author and an associate physician in the Division of Infectious Diseases at the Brigham. Lichterfeld is also an associate member of the Ragon Institute of MGH, MIT and Harvard; and an associate nember of the Broad Institute of MIT and Harvard. "What excites me most about this work is that making a comparatively small change in the timing of treatment may have a large impact on long-term treatment outcomes."

The EIT study is a prospective clinical trial that enrolled infants from two major maternity
hospitals in the Francistown and Gaborone regions of Botswana, a country with the third highest HIV-1 prevalence in the world. Infants enrolled in the study began ART in the first days (frequently, within hours) immediately following their births. The team compared their results to those of infants not in the study who received ART later (within a median of four months after birth). Infants were then followed for two years with blood sampling at regular intervals.

Investigators focused on 10 infants enrolled in the EIT study who were HIV positive at birth. They measured the number of virally infected cells (typically called viral reservoir cells) and many different types of innate and adaptive immune responses. The team observed that the number of reservoir cells was extremely small (significantly smaller than in adults who were on ART for a median of 16 years). The number of reservoir cells was also significantly smaller than in infected infants who started treatment later. The team also identified specific types of innate immune cells (NK cells and monocytes) that were on the rise while the viral reservoir size shrank, suggesting that these cells may influence or modulate viral reservoir cells.

Birds of a feather may flock together, but the feathers of birds differ altogether.

New research from an international team led by USC scientists set out to learn how feathers developed and helped birds spread across the world. Flight feathers, in particular, are masterpieces of propulsion and adaptation, helping penguins swim, eagles soar and hummingbirds hover.

Despite such diversity, the feather shares a common core design: a one-style-fits-all model with option trims for specialized performance. This simplicity and flexibility found in nature holds promise for engineers looking for better ways to build drones, wind turbines, medical implants and other advanced materials.

Those findings, published today in Cell, offer an in-depth look at the form and function of a feather based on a comparative analysis of their physical structure, cellular composition and evolution. The study compares feathers of 21 bird species from around the world.

"We've always wondered how birds can fly in so many different ways, and we found the difference in flight styles is largely due to the characteristics of their flight feathers," said Cheng-Ming Chuong, the study's lead author and a developmental biologist in the Department of Pathology at the Keck School of Medicine of USC. "We want to learn how flight feathers are made so we can better understand nature and learn how biological architecture principles can benefit modern technology."

To gain a comprehensive understanding of the flight feather, Chuong formed a multi-disciplinary international team with Wen Tau Juan, a biophysicist at the Integrative Stem Cell Center, China Medical University in Taiwan. The work involved experts in stem cells, molecular biology, anatomy, physics, bio-imaging, engineering, materials science, bioinformatics and animal science. The bird species studied include ostrich, sparrow, eagle, chickens, ducks, swallow, owl, penguin, peacock, heron and hummingbird, among others.

They compared feathers using fossils, stem cells and flight performance characteristics. They focused on the feather shaft, or rachis, that supports the feather much like a mast holds a sail, bearing the stress between wind and wing. They also focused on the vane, the lateral branches astride the shaft that give the feather its shape to flap the air. And they examined how evolution shaped the barbs, ridges and hooks that help a feather hold its form and lock with adjacent feathers like Velcro to form a wing. The goal was to understand how a simple filament appendage on dinosaurs transformed into a three-level branched structure with different functions.

For birds such as ducks, eagles and sparrows that fly in different modes, the scientists noted significant differences in the feather shaft compared to ground-hugging birds. On the rigid exterior, the shaft cortex was thinner and lightweight, while the interior was filled with porous cells resembling bubble wrap, aligned into bands of various orientations and reinforced with ridges that operate like tiny lateral beams. Together, it forms a light, hollow and buoyant structure to enable flight. Cross-sections of feather shafts of different birds show highly specialized shapes and orientations of the inner core and outer cortex.

"The flight feather is made of two highly adaptable architectural modules, light and strong materials that can develop into highly adaptable configurations," Chuong said.

The researchers discovered two different molecular mechanisms guiding feather growth. Cortex thickness was governed by bone morphogenetic proteins, which are molecular signals for tissue growth. The porous feather interior, or medulla, relied upon a different mechanism known as transforming growth factor beta (TGF-b). Both components originate as stem cells in the bird's skin.

By contrast, feathers in flightless birds were simpler, consisting of a dense cortex exterior that is more rigid and sturdy with fewer internal struts and cells found in flying birds. The features were especially pronounced for penguins, which use wings as paddles under the water.

As part of the study, the researchers looked at nearly 100 million-year-old feathers, found embedded in amber in Myanmar. These fossils show early feathers lacked one key feature that modern birds have. Specifically, the researchers report how fossil feathers had barb branches and barbules, which form a feather vane by overlapping, but not hooklets. The hooklets, which act like clasps to turn fluffy feathers into a tight flat plane for high-performance flight, evolved later. The scientists also identified WNT2B, another growth factor, as the agent that controls hooklet formation. These also originated from epidermal stem cells.

Taken together, the findings show how feathered dinosaurs and early birds could form a primitive vane by overlapping barbule plates, although that wasn't aerodynamically fit to carry much load. As more complex composite features occurred in the wing, it got heavier, so feather shafts became stronger yet more lightweight, which led to stiffer feathers and sturdy wings that powered flight to carry birds around the world.

"Our findings suggest the evolutionary trends of feather shaft and vane are balanced for the best flight performance of an individual bird and become part of the selective basis of speciation," the study says. "The principles of functional architectures we studied here may also stimulate bio-inspired designs and fabrication of future composite materials for architectures of different scales, including wind turbines, artificial tissues, flying drones."

For species trying to boost their chances of avoiding predation, it could be a classic case of 'it's not what you know, it's who you know that matters,' according to new research.

Seeing groups of different wild animals hanging out together on the plains of Africa is not unusual, but why and how these social groups form has puzzled ecologists for many years.

For four years, a team of zoologists from the universities of Liverpool and York has been studying the formation of mixed groups of herbivore species on the African savannahs in Masai Mara, Kenya.

Their findings, published in Ecology Letters, show that herbivores seek out the company of species with the most informative alarm calls who can alert them to the threat of nearby predators.

"Often ecologists focus simply on the location of food and predators to understand how animals distribute themselves in nature, but we've shown that animals choose to live alongside other species who can provide them with valuable information, in this case about predation risk," explains University of Liverpool researcher Dr Jakob Bro-Jorgensen.

To carry out the study, the researchers created a theoretical model that predicts which combinations of characteristics cause species to join in mixed groups in a multi-species community. They then tested their model's predictions in a community-wide field study of African savannah herbivores using multi-layered network analysis.

In addition to informative alarm calls, vigilance and vulnerability were also found to be driving factors of social group formation. Species who are not themselves very vigilant were found to be more likely to join mixed groups, presumably to compensate for their lower ability to spot predators. Similarly, species deemed to be more vulnerable to predators were also more likely to seek out the security provided by being in a mixed group.

Dr Jakob Bro-Jorgensen said: "Our study points to an intriguing complex social world where social relations between species range from mutually beneficial to parasitic.

"The impact of communication between species on social attraction and survival highlights the importance of taking behavioural links between species into account in order to understand how the natural world operates.

"This, in turn is crucial to uncovering how animal communities respond to current environmental changes and could help conservationists better predict the risk of extinction faced by endangered species who rely on information from others."

Short term exposure to fine particulate matter in the air (known as PM2.5) is associated with several newly identified causes of hospital admissions, even at levels below international air quality guidelines, finds a US study published by The BMJ today.

The study also confirms several previously established causes of hospital admission associated with short term exposure to PM2.5 including heart and lung diseases, diabetes, Parkinson's disease, and diabetes.

As such, the researchers suggest that the World Health Organization (WHO) air quality guidelines need revising.

A research team at the Harvard Chan School of Public Health analysed more than 95 million Medicare hospital insurance claims for adults aged 65 or older in the United States from 2000 to 2012.

Causes of hospital admission were classified into 214 mutually exclusive disease groups and these were linked with estimated daily exposure to PM2.5 based on data from the US Environmental Protection Agency.

The researchers then estimated the increased risk of admission and the corresponding costs associated with a 1 ug/m3 increase in short term exposure to PM2.5 for each disease group.

They found that each 1 ug/m3 increase in PM2.5 was associated with 2,050 extra hospital admissions, 12,216 days in hospital, and $31m (£24m, €28m) in care costs for diseases not previously associated with PM2.5 including sepsis, kidney failure, urinary tract and skin infections.

What's more, these associations remained even when the analysis was restricted to days when the PM2.5concentration was below the WHO air quality guideline, suggesting that they need updating, say the researchers.

The researchers point to some study limitations, such as being unable to fully capture costs after discharge, or take account of other factors that could trigger hospital admission, such as smoking, alcohol consumption, and drug use.

However, strengths include the large sample size over a 13-year period and results that remained similar after further analyses, suggesting that they are robust.

As such, they say this study "discovered several new causes of hospital admissions associated with short term exposure to PM2.5 and confirmed several already known associations, even at daily PM2.5 concentrations below the current WHO guideline."

Economic analysis suggests that "even a small increase in short term exposure to PM2.5 is associated with substantial economic effect," they add.

"Our knowledge of the health effects of PM is still lacking in many areas," say researchers at the University of Southampton in a linked editorial.

However, they explain that these newly associated diseases represent around a third (31-38%) of the total PM2.5 associated effect, suggesting that current figures for PM2.5 associated illness "might be considerable underestimates."

They call for more research to uncover new disease associations and explore potential causative mechanisms. "Clearly, there is still much to learn, but we should not mistake knowledge gaps for paucity of evidence," they write. "The sooner we act, the sooner the world's population will reap the benefits."

Researchers from the Netherlands Institute for Neuroscience have shown how it is possible that objects stand out less when they are surrounded by similar objects. This surround-suppression effect is caused by feedback from higher visual brain areas. The results of this research are important for a better understanding of the way in which the brain transforms incoming light into a cohesive image. The paper has been published in the scientific journal Current Biology.

The brain area responsible for processing vision is located at the back of the brain. One of the most important parts of this area, the primary visual cortex, is the area where a visual stimulus first reaches the cortex. Nerve cells in this area are sensitive to perceiving objects within a very small field of vision. So when you look at a specific object, the nerve cells in the primary cortex are activated and you see this object. "But when this object is surrounded by similar objects, the cells are less active. So really what happens is that you don't see the trees for the wood," says Alexander Heimel, group leader at the Netherlands Institute.

SURROUND-SUPPRESSION EFFECT

"The theory had previously yielded the idea that this surround-suppression effect was the result of signals from higher visual brain areas. But until recently there was not much scientific evidence for this," says principal researcher Joris Vangeneugden, aios at Maastricht University. In order to find out whether it really was a matter of higher visual brain areas signaling, the researchers measured mouse brain activity while the mouse was looking at images of different sizes. At the same time, the researchers managed to pause the higher visual areas for a couple of seconds. It turned out that the activity in the primary visual cortex remained high for the larger images when these higher visual areas were paused, while this did not happen when they were active. The suppression of the surroundings thus decreased. This shows that the higher areas do indeed provide some sort of feedback to the primary visual cortex. "They tell the primary visual cortex that it should focus on a small individual object, not on everything there is to see," says Heimel.

VISUAL PROTHESIS

Understanding this step is necessary to understand, eventually, how the brain transforms the light that enters via our eyes into a perception that makes us understand what we see. "An understanding of how our brain does this is essential for the development of prosthetics that will make blind people see again. Merely ensuring that light reaches the brain does not always suffice; what happens after that is even more important," says Vangeneugden.

Animals evolved from single-celled ancestors, before diversifying into 30 or 40 distinct anatomical designs. When and how animal ancestors made the transition from single-celled microbes to complex multicellular organisms has been the focus of intense debate.

Until now, this question could only be addressed by studying living animals and their relatives, but now the research team has found evidence that a key step in this major evolutionary transition occurred long before complex animals appear in the fossil record, in the fossilised embryos that resemble multicellular stages in the life cycle of single-celled relatives of animals.

The team discovered the fossils named Caveasphaera in 609 million-year old rocks in the Guizhou Province of South China. Individual Caveasphaera fossils are only about half a millimeter in diameter, but X-ray microscopy revealed that they were preserved all the way down to their component cells.

Kelly Vargas, from the University of Bristol's School of Earth Sciences, said: "X-Ray tomographic microscopy works like a medical CT scanner, but allows us to see features that are less than a thousandth of a millimeter in size. We were able to sort the fossils into growth stages, reconstructing the embryology of Caveasphaera."

Co-author Zongjun Yin, from Nanjing Institute of Geology and Palaeontology in China, added: "Our results show that Caveasphaera sorted its cells during embryo development, in just the same way as living animals, including humans, but we have no evidence that these embryos developed into more complex organisms."

Co-author Dr John Cunningham, also from University of Bristol, said: "Caveasphaera had a life cycle like the close living relatives of animals, which alternate between single-celled and multicellular stages. However, Caveasphaera goes one step further, reorganising those cells during embryology."

Co-author Stefan Bengtson, from the Swedish Museum of Natural History, said "Caveasphaera is the earliest evidence of this most important step in the evolution of animals, which allowed them to develop distinct tissue layers and organs".

Co-author Maoyan Zhu, also from Nanjing Institute of Geology and Palaeontology, said he is not totally convinced that Caveasphaera is an animal. He added: "Caveasphaera looks a lot like the embryos of some starfish and corals - we don't find the adult stages simply because they are harder to fossilise

Co-author Dr Federica Marone from the Paul Scherrer Institute in Switzerland said "this study shows the amazing detail that can be preserved in the fossil record but also the power of X-ray microscopes in uncovering secrets preserved in stone without destroying the fossils."

Co-author Professor Philip Donoghue, also from the University of Bristol's School of Earth Sciences, said "Caveasphaera shows features that look both like microbial relatives of animals and early embryo stages of primitive animals. We're still searching for more fossils that may help us to decide.

"Either way, fossils of Caveasphaera tell us that animal-like embryonic development evolved long before the oldest definitive animals appear in the fossil record."

The choices we make in large group settings -- such as in online forums and social media -- might seem fairly automatic to us. But our decision-making process is more complicated than we know. So, researchers have been working to understand what's behind that seemingly intuitive process.

Now, new University of Washington research has discovered that in large groups of essentially anonymous members, people make choices based on a model of the "mind of the group" and an evolving simulation of how a choice will affect that theorized mind.

Using a mathematical framework with roots in artificial intelligence and robotics, UW researchers were able to uncover the process for how a person makes choices in groups. And, they also found they were able to predict a person's choice more often than more traditional descriptive methods. The results were published Wednesday, Nov. 27, in Science Advances.

"Our results are particularly interesting in light of the increasing role of social media in dictating how humans behave as members of particular groups," said senior author Rajesh Rao, the CJ and Elizabeth Hwang professor in the UW's Paul G. Allen School of Computer Science & Engineering and co-director of the Center for Neurotechnology.

"In online forums and social media groups, the combined actions of anonymous group members can influence your next action, and conversely, your own action can change the future behavior of the entire group," Rao said.

The researchers wanted to find out what mechanisms are at play in settings like these.

In the paper, they explain that human behavior relies on predictions of future states of the environment -- a best guess at what might happen -- and the degree of uncertainty about that environment increases "drastically" in social settings. To predict what might happen when another human is involved, a person makes a model of the other's mind, called a theory of mind, and then uses that model to simulate how one's own actions will affect that other "mind."

While this act functions well for one-on-one interactions, the ability to model individual minds in a large group is much harder. The new research suggests that humans create an average model of a "mind" representative of the group even when the identities of the others are not known.

To investigate the complexities that arise in group decision-making, the researchers focused on the "volunteer's dilemma task," wherein a few individuals endure some costs to benefit the whole group. Examples of the task include guarding duty, blood donation and stepping forward to stop an act of violence in a public place, they explain in the paper.

To mimic this situation and study both behavioral and brain responses, the researchers put subjects in an MRI, one by one, and had them play a game. In the game, called a public goods game, the subject's contribution to a communal pot of money influences others and determines what everyone in the group gets back. A subject can decide to contribute a dollar or decide to "free-ride" -- that is, not contribute to get the reward in the hopes that others will contribute to the pot.

If the total contributions exceed a predetermined amount, everyone gets two dollars back. The subjects played dozens of rounds with others they never met. Unbeknownst to the subject, the others were actually simulated by a computer mimicking previous human players.

"We can almost get a glimpse into a human mind and analyze its underlying computational mechanism for making collective decisions," said lead author Koosha Khalvati, a doctoral student in the Allen School. "When interacting with a large number of people, we found that humans try to predict future group interactions based on a model of an average group member's intention. Importantly, they also know that their own actions can influence the group. For example, they are aware that even though they are anonymous to others, their selfish behavior would decrease collaboration in the group in future interactions and possibly bring undesired outcomes."

In their study, the researchers were able to assign mathematical variables to these actions and create their own computer models for predicting what decisions the person might make during play. They found that their model predicts human behavior significantly better than reinforcement learning models -- that is, when a player learns to contribute based on how the previous round did or didn't pay out regardless of other players -- and more traditional descriptive approaches.

Given that the model provides a quantitative explanation for human behavior, Rao wondered if it may be useful when building machines that interact with humans.

"In scenarios where a machine or software is interacting with large groups of people, our results may hold some lessons for AI," he said. "A machine that simulates the 'mind of a group' and simulates how its actions affect the group may lead to a more human-friendly AI whose behavior is better aligned with the values of humans."

Analysis of the impact craters on Ryugu using the spacecraft Hayabusa 2's remote sensing image data has illuminated the geological history of the Near-Earth asteroid.

A research group led by Assistant Professor Naoyuki Hirata of the Department of Planetology at Kobe University's Graduate School of Science revealed 77 craters on Ryugu. Through analyzing the location patterns and characteristics of the craters, they determined that the asteroid's eastern and western hemispheres were formed at different periods of time.

It is hoped that the collected data can be used as a basis for future asteroid research and analysis.

These results were first published in the American Scientific Journal 'Icarus' on November 5 2019.

Introduction

The Japan Space Agency (JAXA)'s Hayabusa 2 has been used to carry out various missions to increase our understanding of the spinning top-shaped, Near-Earth asteroid Ryugu. Since arriving in June 2018, the unmanned spacecraft has taken samples and a great number of images of the asteroid. It is hoped that these can reveal more about Ryugu's formation and history.

This research group focused on using the image data to determine the number and location of impact craters on the asteroid. Impact craters are formed when a smaller asteroid or a comet hits the surface of the asteroid. Analyzing the spatial distribution and the number of impact craters can reveal the frequency of collisions and aid researchers in determining the age of different surface areas.

Research Methodology

First of all, the image data from Hayabusa 2 was analyzed. Hayabusa 2 has many different types of camera including Optical Navigation Cameras (ONC). The ONC team has been able to take around 5000 images of Ryugu, which have revealed many surface features- including impact craters. For this study, image data obtained from the 'ONC-T' camera between July 2018 and February 2019 was utilized. The research group had to determine which of these images showed craters. 340 images were used for crater counting, with stereopair images making it easier to identify the craters. A global image mosaic map was constructed from the ONC images and rendered onto the computer model of Ryugu's shape. Small Body Mapping Tool software was then used to measure the size, latitude and longitude of the craters. A LiDAR (Light Detection and Ranging pulsed laser) was also utilized to determine the overall size of Ryugu.

The depressions identified on Ryugu were divided into four categories- depending on how evident their circular appearance was. Category I to III depressions were classified as distinct craters. Category IV depressions only had quasi-circular features, therefore it was hard to determine whether they were craters or not. Many craters were filled with boulders or lacked a distinct shape. Depressions that were too vague to determine were left out of the results.

Research Results

The research team were able to identify all impact craters over 10 to 20m in diameter on Ryugu's entire surface- a total of 77 craters. Furthermore, a pattern was discovered in their distribution. The section of the eastern hemisphere near the meridian was found to have the most craters. This is the area near the large crater named Cendrillon - which is one of Ryugu's biggest. In contrast, there are hardly any craters in the western hemisphere- suggesting that this part of the asteroid was formed later. The analysis also revealed that there are more craters at lower latitudes than at higher latitudes on Ryugu. In other words, there are very few craters in Ryugu's polar regions.

The equatorial ridge in the eastern hemisphere was determined to be a fossil structure. When asteroids like Ryugu rotate at high speeds, this can alter their shape. It is thought that this ridge formed in the distant past during a period when it only took Ryugu 3 hours to rotate. As the eastern hemisphere and western hemisphere were formed at different periods of the asteroid's history- this suggests that there have been at least two instances where Ryugu's rotational speed has increased.

Further Research

The results of this study were compiled into a global impact crater catalogue for Ryugu. It is hoped that this database can be used as a basis for future research and that comparing these results with those of a similar asteroid will lead to greater understanding about these astronomical objects.

Hayabusa2 is scheduled to drop the capsule containing samples of Ryugu's surface into Earth's atmosphere in late 2020. Analysis of these samples should provide further insight into the asteroid and how it was formed.

A new study proposed a scheme to achieve ultrahigh reduced transition temperature, up to Tc/TF ~ 1, in two-component atomic Fermi gases, a system that mimic high Tc superconductors, via a tunable pairing interaction strength, using mixed dimensions where one component is in a deep one-dimensional (1D) optical lattice with a large lattice spacing, while the other remains in 3D free space. Quantum atomic Fermi gases have provided an ideal prototype for studying the physics of high Tc superconductivity, including the underlying pairing mechanism and the unusual pseudogap phenomena, which have been at the heart of debate in the field of high Tc superconductivity.

In a Letter published in SCIENCE CHINA Physics, Mechanics & Astronomy, theorists from Zhejiang University, Sun Yat-Sen University, and Zhejiang University of Technology, as well as the Synergetic Innovation Center of Quantum Information and Quantum Physics, report that by tuning the lattice spacing to be large in a mixed dimensional setting, the reduced superfluid transition temperature, Tc/TF, can be made extremely high, higher than that for any known systems.

It has been a long-term goal in the field of superconductivity to achieve a high transition temperature Tc, ideally up to room temperature (about 300 K) and above. Given that the typical electron kinetic energy, represented by its Fermi temperature TF, is of the order of 10000 K in a solid, this is only a small fraction. Conventional superconductors in metals and alloys have a transition temperature of a few Kelvins, usually below 20 K. The high Tc cuprate superconductors, discovered in 1986, has a Tc up to 95 K at the optimal oxygen doping concentration under ambient pressure, and up to 164 K under high pressure, has a relatively low TF due to strong electron correlations, which pushes the reduced temperature Tc/TF up to about 0.05. This ratio does not exceed this value for other families of superconductors, either, including iron-based superconductors, heavy fermion superconductors, organic superconductors, the monolayer FeSe/SrTiO3 superconductors, and the newly discovered magic angle twisted bilayer graphene, as well as the Tc record holder, H2S under high pressure. A higher ratio is made possible in ultracold atomic Fermi gases, with Tc/TF up to 0.218 in the BEC limit in the 3D homogeneous case. This ratio can be further raised to 0.518 in a harmonic trap in the BEC limit, utilizing the enhanced local Fermi energy at the trap center. This enhancement led to the idea of using mixed dimensions to tune the Fermi energy as a function of lattice spacing.

The idea of enhancing Tc/TF via mixed dimensions is illustrated in Figure 1. One of the two pairing components, referred to as spin down atoms, remain in 3D free space, occupying an isotropic Fermi sphere in momentum space. On the contrary, the spin up atoms are subject to a deep 1D optical lattice potential (in the z direction) with a large band gap and a large lattice spacing d so that the fermions occupies a thin disc of thickness 2p/d and radius kF?, so that the Fermi energy EF? for the spin up atoms increases with increasing d. The lattice may be so deep that the spin-up atoms are essentially localized in their respective lattice sites in the absence of pairing interaction. Then, when the pairing interaction is turned on and tuned to be large via Feshbach resonance, the Fermi sphere of the spin down atoms will be deformed into a disc to match that of the spin up atoms. As a result, both components now acquire a large Fermi energy (in comparison with the non-interacting 3D value, EF) and thus led to a high Tc/TF. As pointed out by the authors, despite that the spin up atoms are highly localized in the absence of pairing interaction, the atomic pairs acquire high mobility due to the spin down components. This is somewhat similar to the case of superconductivity in a flat band, where individual electrons are localized whereas Cooper pairs acquire mobility via the pairing interaction. The enhancement of Tc/TF is largely governed by the ratio EF? /EF. The result is shown in Figure 2, where Tcmax is the maximum Tc as a function of pairing strength for a given lattice spacing d. The ratio reaches about unity for kFd = 55, higher than any known systems. (Note here EF=KBTF=?2K2F/2m , where kB is the Boltzmann constant, ? the Planck constant h divided by 2p, m the mass of atoms, and kF and EF the Fermi momentum and Fermi energy, respectively, for the system in the absence of lattice potential and pairing interaction.)

As emphasized by the authors, the above idea of enhancing Tc/TF is independent of specific details of their theory and works equally well for rival theories. The proposed scheme may be realized experimentally with isotopic atoms such as 161Dy and 163Dy, once a proper Feshbach resonance is identified.

Ultracold atomic systems have been widely studied for their capability of quantum simulation and quantum engineering. An important goal of the atomic Fermi gas community is to simulate and help to understand the mechanism of high Tc superconductivity. A proper understanding will certainly be critical in the search for and design of new superconductors of higher Tc.

Ludwig-Maximilians-Universitaet (LMU) in Munich biologists Marcel Dann and Dario Leister have demonstrated for the first time that cyanobacteria and plants employ similar mechanisms and key proteins to regulate cyclic electron flow during photosynthesis.

Cyclic electron flow (CEF) is a crucial component of photosynthesis in both plants and cyanobacteria. However, up to now, it was not clear how it differs from, and what components it shares with, the related electron-transport process of linear electron flow (LEF) or how it is regulated. LMU biologists Marcel Dann and Dario Leister have now shown that two specific proteins, called PGRL1 und PGR5, mediate the control of CEF in plants. These proteins had been identified as important elements in photosynthesis in recent years, both in Leister's laboratory and by a group of researchers in Japan. In plants, the amount of biologically useful energy (in the form of ATP) generated by the LEF pathway is insufficient for the synthesis of sugars from carbon dioxide. The ATP produced by cyclic electron flow makes up for this shortfall, and is vital for carbon fixation. This becomes obvious when plants are exposed to stress, have to repair damage caused by high light levels, or are confronted with other deleterious environmental changes. "When CEF is defective, plants very quickly get very sick," Leister says.

Since cyclic electron flow is extremely difficult to measure directly in plants, Dann and Leister turned to cyanobacteria, which also possess a CEF pathway. Cyanobacteria are a very useful model system because the organelles known as chloroplasts - the sites of photosynthesis in plants - were actually derived from them during evolution. The molecular mechanisms that regulate CEF in cyanobacteria are therefore similar to, but significantly less complex than those used by plants, Leister explains. "These are systems that utilize a simpler form of photosynthesis." In their study, which appears in the online journal Nature Communications, the authors introduced the genes that code for the two plant proteins PGRL1 und PGR5 into various mutant strains of these bacteria and analyzed their effects on photosynthesis. "We were quite surprised to find that we could in fact measure something that looked very like cyclic electron transport," says Leister. This finding clearly proves that these two proteins indeed play a key role in cyclic electron flow. In addition, it emerged that they are sufficient to re-establish CEF in mutant cyanobacteria.

This is particularly notable, because cyanobacteria lack PGRL1, although they do have a PGR5-like protein. For this reason, researchers have long wondered why these cells manage to implement CEF with the aid of this PGR5 homolog alone, while the plant pathway requires both PGR5 and PGRL1. The two researchers also found a possible answer to this riddle. They showed that cyanobacteria have a second protein, called Sll1217, which apparently has a function analogous to that of PGRL1 in plants. Although Sll1217 displays only a very low level of structural (i.e. amino-acid sequence) similarity to plant PGRL1, it interacts with PGR5 from both plants and cyanobacteria. Dann and Leister are the first to suggest a function in CEF for Sll1217.

Dario Leister plans to make practical use of these new insights. His latest project, "PhotoRedesign", for which he recently received a Synergy Grant from the European Research Council (ERC), sets out to improve photosynthetic performance and develop ways to enable plants to make better use of sunlight. "We are attempting to beat nature by combining the best elements of different systems of photosynthesis," says Leister. In this respect, the genetically altered cyanobacteria provide new opportunities for further experimentation. "In bacteria, we can experimentally alter the plant version of cyclic electron transport by genetic manipulation within a few weeks," Leister points out. "The altered cyanobacterial strain is like a living laboratory, which allows us to play around with the process of CEF. Such experiments would take years in plants." - And solutions that work in cyanobacteria can then be tried out in plants. "That not only saves lots of time, it allows us to carry out experiments that would be impossible to do in plants."

Clown fish are unable to genetically adapt to changes in their environment. Such is the conclusion of a study, unprecedented in the field of submarine environmental research, by a group of CNRS scientists* and their Australian, Saudi, Chilean, and American colleagues. Their findings are published in Ecology Letters (26 November 2019). For over ten years, the researchers observed clown fish in the lagoons of Kimbe Island, a hot spot of biodiversity in Papua New Guinea. After having pieced together genealogies spanning four generations for each family of these fish, they demonstrated a lack of genetic variation to boost reproductive success and replenish the population. Hence the reproductive success of the clown fish depends almost entirely on their environment, and especially their sea anemones. Clown fish are at the mercy of their habitat, whose daily deterioration has already been documented. Efforts to preserve the quality of their habitat will primarily determine whether they are able to continue living in the lagoons.

The automatic identification of complex features in images has already become a reality thanks to artificial neural networks. Some examples of software exploiting this technique are Facebook's automatic tagging system, Google's image search engine and the animal and plant recognition system used by iNaturalist. We know that these networks are inspired by the human brain, but their working mechanism is still mysterious. New research, conducted by SISSA in association with the Technical University of Munich and published for the 33rd Annual NeurIPS Conference, proposes a new approach for studying deep neural networks and sheds new light on the image elaboration processes that these networks are able to carry out.

Similar to what happens in the visual system, neural networks used for automatic image recognition analyse the content progressively, through a chain of processing stages. However, to date, it is not completely clear which mechanisms allow deep networks to reach their extraordinary levels of accuracy.

"We have developed an innovative method to systematically measure the level of complexity of the information encoded in the various layers of a deep network - the so-called intrinsic dimension of image representations" say Davide Zoccolan and Alessandro Laio, respectively neuroscientist and physicist at SISSA. "Thanks to a multidisciplinary work that has involved the collaboration of experts in physics, neurosciences and machine learning, we have succeeded in exploiting a tool originally developed in another area to study the functioning of deep neural networks".

SISSA scientists, in association with Jakob Macke, of the Technical University of Munich, have examined how the information acquired from neural networks used for image classification is processed: "We have found that image representations undergo a progressive transformation. In the early processing stages, image information is faithfully and exhaustively represented, giving rise to rich and complex representations. In the final processing stages, the information is radically simplified, producing image representations that are supported by a few dozen parameters" explain the two scientists. "Surprisingly we found that the classification accuracy of a neural network tightly depends on its ability to simplify: the more it simplifies the information, the more accurate it is."

This is an especially important result for SISSA that has recently launched a new research program in Data Science, with the goal of studying and developing innovative algorithms for the processing of complex and large data sets.