Culture

A recent study has shown that it may be possible to dampen the workings of the subconscious brain to prevent alcohol relapse, the results leading to a world-first trial of a personalised smartphone app called "SWiPE".

Cognitive Bias Modification, a new form of computerised brain-training, is focused on training the brain to automatically avoid alcohol cues, with findings showing that early relapse was reduced by 17 percent after four sessions of CBM, compared to those who received a "control" (placebo) version of the task.

Regular drinkers have a 'cognitive bias' to alcohol cues such as places, sights, smells, and social situations that remind them of drinking, subconsciously capturing attention, driving impulses to seek out and drink alcohol. When these cues become less attention-grabbing and less rewarding, our subconscious brain has less influence on our behaviour, leaving more room for our conscious brain to drive decision-making.

Published in JAMA Psychiatry and led by researchers from Turning Point, Monash University and Deakin University, the study has resulted in researchers developing a CBM smartphone app called "SWiPE" where people can upload alcoholic beverages or brands they wish to train their subconscious brain to avoid, while at the same time 'approaching' images of more positive, healthy activities they want to do more of.

Associate Professor Victoria Manning, Head of Research and Workforce Development, Turning Point and Associate Professor in Addiction Studies, Monash University says "preventing relapse in the period following alcohol detox is really important because that is when people engage in psychological treatments and peer support groups that have shown to help people recover from alcohol problems."

"A lot of the time, people wanting to quit or take a break from alcohol experience a form of internal conflict - they know it's important not to drink, but at the same time, they really want to have a drink".

Our conscious brain allows us to think about the things we'll gain by not drinking - saving money, better sleep, better health, better relationships - and it enables us to focus on some of the positive, healthier things we can do instead. The problem is that there is also the subconscious brain at work saying "go on... have one, it will relax you, make you feel better, you deserve it", even if those benefits are not entirely- true or just short-lived. Unfortunately, all too often, the subconscious brain wins the battle.

The researchers are really encouraged by these results: "Being easy-to-implement, safe and requiring only a laptop and joystick, we'd love to see CBM routinely offered as an adjunctive intervention during inpatient withdrawal, to optimise patient outcomes" says Associate Professor Victoria Manning.

"We know only a small percentage of people with alcohol problems seek treatment. Therefore, having low-cost, widely-available, evidence-based interventions available outside of traditional treatment settings will mean more people have access to anonymous and convenient, easy to use support tools when they most need them."

The team is currently examining SWiPE's feasibility, acceptability and effectiveness at reducing alcohol consumption and cravings and preliminary findings suggests app-delivered CBM is also looking very promising.

Researchers from Beijing Normal University, Peking University and National Astronomical Observatories of the Chinese Academy of Sciences (NAOC) found that there is weak correlation between fast radio bursts(FRBs) and soft gamma-ray repeater J1935+2154(SGRs). The study was published in Nature on Nov. 4.

The detection of FRB 200428 associated with the galactic magnetar SGR J1935+2154 provides crucial clues to the generation of FRBs.

They used the Five-hundred-meter Aperture Spherical radio Telescope (FAST) to conduct multi-band joint observations of the Milky Way magnetar SGR J1935+2154.

In April, Dr. LIN Lin from Beijing Normal University, first author of the study, proposed monitoring SGR J1935+2154, a soft gamma-ray repeater showing FRB like pulses, to explore the origin of FRBs. FAST detected no pulse during the campaign, particularly around the arrival time of 29 high-energy bursts.

Combined with CHIME and STARE-2 detections, FAST's results cover eight orders of magnitude on the brightness scale, thus providing the most stringent limit to the radio flux of this Galactic fast radio burst (FRB) sources.

"The weak correlation could be explained by special geometry and/or limited bandwidth of FRBs," said Prof. ZHANG Bing from University of Nevada, corresponding author of the study. "The observations of SGR J1935 start to reveal the magnetar origin of FRBs, although other possibilities still exist."

While continuing the monitoring of SGR J1935+2154, the unprecedented sensitivity of FAST has potential for revolutionizing our understanding of radio transients. In May of this year, Prof. ZHU Weiwei from NAOC, co-author of the study, published the first new FRB discovered by FAST.

According to Prof. LI Di, co-corresponding author of the study, FAST's chief scientist, "FAST has discovered more than five new FRBs and has detected more than 1,600 pulses from known repeating sources. FAST is and will be making unique contributions to this young and active field."

In the vast universe, some extremely strong radio waves occasionally blink, with duration of only milliseconds. Such fast radio bursts were discovered by astronomers in 2007. Puzzling questions arise: Who sent them? What information is conveyed by these radio bursts?

The Five-hundred-meter Aperture Spherical Radio Telescope (FAST) has revealed some mystery of the fast radio bursts, according to a study published in Nature on Oct. 28.

More than 30 burst sources have been found until last year. These bursts randomly emerge in the sky, which implies that most of them are not from the Milky Way but outside.

In 2017, astronomers finally caught a repeating FRB source from that several bursts emerge in a few hours. The burst source is found to come from a galaxy 3 billion light years away in the deep Universe.

The large collecting area makes FAST the most sensitive telescope over the world and the precisely controlled adopt reflectors enables it to make excellent focus and track on celestial targets.

In the trial open semester in 2019, Dr. LUO Rui, first author of the study, a PhD student from Peking University, hoped to use FAST to see if a radio burst FRB 180301 repeats or not. Fortunately, four bursts were detected during the two-hour observation session on July 16, 2019. This is an exciting result, but no bursts were detected in the four-hour observation on September 11, 2019.

Considering the position uncertainty of originally reported from the first discovery by the Australian telescope, a research team led by Prof. LI Kejia from Peking University, Prof. HAN Jinlin from National Astronomical Observatories of Chinese Academy of Sciences (NAOC), and Prof. ZHANG Bing from University of Las Vegas discussed and changed the observations strategy by monitoring the target by using the central beam of 19-beam receiver of the FAST and made the full-polarization data recorded.

On October 6 and 7, FAST detected 11 bursts in six hours. Totally, FAST detected 15 bursts in 12 hours. The intensity profiles of these bursts are quite different from each other, but definitely they come from one source, similar to the repeating burst source astronomers previously found, with a similar distance of three billion light-years away, and a similar burst rate but much less luminous.

The most intriguing results come from the careful analysis on the polarization signals of the 11 radio bursts recorded by FAST. Among the 11 bursts detected by FAST, the polarization properties of seven bursts could be well-measured, which showed not only interesting swings of polarization, but also the diversity of swings.

Such a diverse polarization behavior had never been seen in any radio bursts previously. It means that the bursts are produced in the magnetosphere of compact stars with extremely magnetic fields, such as neutron stars, and disfavors the shock models produced by jets of plasma as proposed by many scientists.

In the past, polarization signals from only a few of some 30 bursts have been recorded, either showing flat polarization angle swing, i.e. constant polarization direction of radio waves, or variable position angle in one-off bursts. The significance results obtained by FAST observations settle down the debates between the two schools of theoretical models.

As of today, FAST has conducted intense astronomical observations to many celestial objects, and has discovered more than 230 new pulsars in the last few years.

Fishermen working on Lake Tanganyika in eastern Congo experience a lack of safety and want better enforcement of existing regulations. They also report a decline in the lake's fish stocks. These are some of the findings of a large international study led by KU Leuven (Belgium) based on 1018 interviews with stakeholders in the area. The study was published in the Journal of Great Lakes Research.

Lake Tanganyika is the second largest freshwater lake in the world and is located in four countries: the Democratic Republic of the Congo, Tanzania, Burundi, and Zambia. The fisheries on the lake play a vital role in providing food to eastern Congo, one of the poorest regions in the world.

Exploitation of natural resources and pollution put the fish stocks under pressure. Researchers now show that fishermen experience a lack of safety on the lake and there is a reported decline in fishery yield. Fishermen and other stakeholders ask for protection, access to safety gear, and better enforcement of existing fisheries legislation. The team consisted of researchers from, among others, the Royal Belgian Institute of Natural Sciences, the Belgian Royal Museum of Central Africa and the Congolese Centre de Recherche en Hydrobiologie (CRH).

Outdated regulations

Fishermen working on Lake Tanganyika mainly catch three species: perch and two species of sardines. The fish are sold on the beaches to saleswomen, who then sell them on markets. Regulation of fishing is limited. Government employees collect catch statistics on the beaches and check if any illegal materials, such as beach seines or mosquito nets, are being used. To ensure that fish stocks are not depleted, good management is indispensable. However, the current regulations are four decades old, and no longer relevant for the situation today, since the number of fishermen has increased exponentially. In order to adapt the regulations to the needs of fisheries stakeholders, it is important to have insight into their opinions and views.

The researchers conducted and analysed 1018 interviews with fishermen, salespeople, government employees and other stakeholders of the fisheries. Fishermen, salespeople, and officials indicate that the catches of the three target species are decreasing and that fish are also getting smaller over time. These could be indications of overfishing of the system. "However, the study participants did not attribute this to overfishing or overpopulation", says Maarten Van Steenberge, who coordinated the study. As a result, fishermen and others are not in favor of stricter regulations, as they do not see the benefit.

Illegal practices

A stricter fisheries policy has little chance of succeeding if the local population does not support it. "We do notice that although the fishermen are not open to tightening the regulations, they do demand a stricter application of the existing rules, for example to prevent unfair competition from fishermen who fish with illegal materials", says Pascal Masilya Mulungula, researcher at CRH in Uvira, Congo.

Illegal fishing practices like catching juvenile fish near the shore with mosquito nets, has detrimental effects on the stocks. However, these illegal fishing practices are mostly carried out by impoverished women, who lack any other source of food and income, and this income to support their families. Strict application of the rules, which forbid this type of fishing, should thus go together with alternatives sources of income for these people.

Unsafe

The interviews with fishermen also revealed that their main concern is a lack of security. "Fishermen report dangerous conditions on the lake, such as high waves and strong winds. They are also regularly attacked by gangs or extorted by soldiers or security officers", says Els De Keyzer, who carried out the research. The fishermen ask for more security equipment, such as lifejackets, and strict action against gangs and corruption.

This was the first time that stakeholders of the Lake Tanganyika fisheries were interviewed about these issues on such big scale, providing unique insight into the problems and needs related to these fisheries. The authors handed over their findings to the local administration in a policy brief. "We hope that this study will be used as a starting point for policymakers who want to adapt the regulations to current conditions. Since the stocks are shared between four countries, future research should focus on how much willingness there is for collaboration between stakeholders around the lake," concludes De Keyzer.

Since the dawn of space exploration, humankind has been fascinated by survival of terrestrial life in outer space. Outer space is a hostile environment for any form of life, but some extraordinarily resistant microorganisms can survive. Such extremophiles may migrate between planets and distribute life across the Universe, underlying the panspermia hypothesis or interplanetary transfer of life.

The extremophilic bacterium Deinococcus radiodurans withstands the drastic influence of outer space: galactic cosmic and solar UV radiation, extreme vacuum, temperature fluctuations, desiccation, freezing, and microgravity. A recent study examined the influence of outer space on this unique microbe on a molecular level. After 1 year of exposure to low Earth orbit (LEO) outside the International Space Station during the Tanpopo space Mission, researches found that D. radiodurans escaped morphological damage and produced numerous outer membrane vesicles. A multifaceted protein and genomic responses were initiated to alleviate cell stress, helping the bacteria to repair DNA damage and defend against reactive oxygen species. Processes underlying transport and energy status were altered in response to space exposure. D. radiodurans used a primordial stress molecule polyamine putrescine as a reactive oxygen species scavenger during regeneration from space exposure.

"These investigations help us to understand the mechanisms and processes through which life can exist beyond Earth, expanding our knowledge how to survive and adapt in the hostile environment of outer space. The results suggest that survival of D. radiodurans in LEO for a longer period is possible due to its efficient molecular response system and indicate that even longer, farther journeys are achievable for organisms with such capabilities" says Tetyana Milojevic, a head of Space Biochemistry group at the University of Vienna and a corresponding author of the study.

Together with the colleagues from Tokyo University of Pharmacy and Life Science (Japan), Research Group Astrobiology at German Aerospace Center (DLR, Cologne), Vienna Metabolomics Centre (ViMe) at the University of Vienna and Center for Microbiome Research at Medical University Graz, researches answered the question not only till which extend but how extremophilic microbes can tolerate drastic space conditions.

Today, a multitude of industries, including optics, electronics, water purification, and drug delivery, innovate at an unprecedented scale with nanometer-wide rolls of honeycomb-shaped graphite sheets called carbon nanotubes (CNTs). Features such as light weight, convenient structure, immense mechanical strength, superior thermal and electrical conductivities, and stability put CNTs a notch above other material alternatives. However, to supply their rising industrial demand, their production must be constantly scaled up, and therein lies the main challenge to using CNTs.

While scientists have been able to grow individual CNTs approximately 50 cm in length, when they attempt arrays, or forests, they hit a ceiling at around 2 cm. This is because the catalyst, which is key to CNT growth occurring, deactivates and/or runs out before CNTs in a forest can grow any longer, driving up monetary and raw-material costs of CNT production and threatening to cap its industrial use.

Now, a ceiling-breaking strategy has been devised by a team of scientists from Japan. In their study published in Carbon, the team presents a novel approach to a conventional technique that yields CNT forests of record length: ~14 cm--7 times greater than the previous maximum. Hisashi Sugime, Assistant Professor at Waseda University, who led the team, explains, "In the conventional technique, the CNTs stop growing due to a gradual structural change in the catalyst, so we focused on developing a new technique that suppresses this structural change and allows the CNTs to grow for a longer period."

The team created a catalyst based on their findings in a previous study to begin with. They added a gadolinium (Gd) layer to the conventional iron-aluminum oxide (Fe/Al2Ox) catalyst coated onto a silicon (Si) substrate. This Gd layer prevented the deterioration of the catalyst to a certain extent, allowing the forest to grow up to around 5 cm in length.

To further prevent catalyst deterioration, the team placed the catalyst in their original chamber called the cold-gas chemical vapor deposition (CVD) chamber. There, they heated it to 750°C and supplied it with small concentrations (parts-per-million) of room temperature Fe and Al vapors.

This kept the catalyst going strong for 26 hours, in which time a dense CNT forest could grow to 14 cm. Various analyses to characterize the grown CNTs showed that they were of high purity and competitive strength.

This achievement not only overcomes hurdles to the widespread industrial application of CNTs but it opens doors in nanoscience research. "This simple but novel method that drastically prolongs catalyst lifetime by supplying ppm-level vapor sources is insightful for catalyst engineering in other fields such as petrochemistry and nanomaterial crystal growth," Sugime says. "The knowledge herein could be pivotal to making nanomaterials a ubiquitous reality."

Coronavirus has infected more than 40 million people around the world and has caused more than a million deaths in less than a year. Moreover, it is still not clear why some people who contract the virus show no symptoms whereas others may die or suffer very severe consequences. Although age, illnesses and previous treatments can be used to give a prognosis in some cases, it is still not possible to state for certain how each case of coronavirus will evolve. One of the treatments that have been discussed in regard to their role in the evolution of COVID-19 has been statins. This drug helps to reduce cholesterol in the blood and thus prevent cardiovascular diseases. It is currently taken by one in four people and is the most widely used medicine among the general public. Now, a research by the Universitat Rovira i Virgili (URV) and Pere Virgili Institut (IISPV) led by Lluís Masana has found that people who are being treated with statins have a 22% to 25% lower risk of dying from COVID-19. The research results have been published in the European Heart Journal - Cardiovascular Pharmacotherapy.

The study was carried out through the Network of Lipid and Arteriosclerosis Units of Catalonia and collected information from 2,159 patients infected with SARS-COv-2 from 19 hospitals in Catalonia during the first wave of the pandemic from March to May. The researcher evaluated one hundred clinical variables per patient such as age, sex, previous illnesses, cholesterol levels, evolution of the virus, treatments used for COVID-19, and so on. The researchers then compared death rates of patients being treated with statins with death rates among those who were not and they also analysed the effect of withdrawing statins when the patient was admitted to hospital. "In our comparison, we adjusted the groups so that they were comparable in terms of age, sex and the existence of earlier illnesses", explained Masana, who has coordinated the study from the Lipid and Arteriosclerosis Research Unit at the URV's Department of Medicine and Surgery, which is a member of the CIBERDEM Network bringing together research groups working on diabetes and metabolism in Spain. Masana is also a researcher at the Sant Joan University Hospital in Reus.

The percentage of patients who died in the group not treated with statins was 25.4%, whereas it was 19.8% among those who were, that is to say 22% lower. "The data indicate that treatment with statins prevents one in five deaths", indicated Masana. Furthermore, if treatment with this medicine continued during hospitalization, mortality fell by up to 25%, thus preventing one in four deaths.

Consequently, Lluís Masana went on to say that "not only do these findings demonstrate that treatment with statins has no negative on the evolution of COVID-19, they also show that it significantly reduces patient mortality".

One of the indirect effects of the pandemic is that some people have stopped taking preventive measures aimed at combatting chronic diseases or maintaining general health, and this has been the case with statins. "Some health professionals have even advised their withdrawal in the belief that they could worsen the effects of COVID-19", said Masana. In this regard, in addition the virus to directly causing death in some patients, complications and overall mortality can increase due to the withdrawal of these drugs and regular monitoring of the use of this medicine. "In the case of statins, we have demonstrated that fear of the pandemic should never be used as an excuse to suspend treatment", concluded the researcher.

Although the research was never intended to demonstrate that administering statins to COVID-19 patients would reduce the risk of death, it does open the way for studies that may confirm this finding.

A rise in negative health behaviours - such as lack of sleep, exercise and an unhealthy diet - is connected to poorer mental health during the tightest restrictions of Scotland's COVID-19 lockdown, a new study has confirmed.

Research conducted on 20 May 2020 and led by University of the West of Scotland (UWS), in partnership with Glasgow Caledonian University (GCU), has concluded that these changes contributed to a higher negative mood and that maintaining, or even improving, health behaviours in a lockdown situation is key to sustaining positive mental health.

The study, funded by the Chief Scientist Office (CSO), also found a link between increased alcohol consumption when living with children, and a poorer diet if the person's working status had been affected by COVID-19.

Dr Joanne Ingram, Lecturer in the School of Education and Social Sciences at UWS, said: "When the Scottish Government instigated the initial societal lockdown in response to the COVID-19 pandemic, many subsequently experienced significant lifestyle changes, alongside the stresses of potentially catching the virus or experiencing bereavement.

"We know that stressful situations and poorer health behaviours, such as higher alcohol consumption, unhealthy diet, poorer sleep quality and physical inactivity are frequently linked to poor mental health; however, our objective was to examine changes in health behaviours and their relationship with negative mood during the COVID-19 lockdown."

The study found that:

Increased alcohol consumption was linked to living with children, but not to negative mood.

Poorer diet was linked to more-negative mood, and to changes to working status. Those who had changed their work status due to the COVID-19 pandemic reported that their diet had become unhealthier.

Poorer sleep quality was linked with more-negative mood, and with 'shielding' from the virus. Shielding was the only COVID-19-related factor which was associated with changes in sleep quality.

Being less physically active was related to more-negative mood and student status, with those studying full-time seeing a greater reduction in their physical activity.

Being more physically active was linked to having or suspecting COVID-19 infection within the household.

Households where COVID-19 had been experienced or suspected were associated with increasing their physical activity.

Dr Joanne Ingram added: "This study adds to reports on poor mental health during lockdown and identifies lifestyle restrictions and changes to health behaviours which may be responsible for higher negative mood. Our data suggests that it is advisable to maintain or improve health behaviours during pandemic-associated restrictions, which is important to highlight whilst restrictions are on-going."

Dr Christopher Hand from the Department of Psychology at Glasgow Caledonian University, said: "While we found a relationship between negative change in health behaviours and higher negative mood, our results weren't all doom-and-gloom. We saw that large numbers of people were able to make healthy changes during lockdown, and these positive changes were associated with better mental health outcomes.

Though we may not always realize it, photodetectors contribute greatly to the convenience of modern life. Also known as photosensors, photodetectors convert light energy into electrical signals to complete tasks such as opening automatic sliding doors and automatically adjusting a cell phone's screen brightness in different lighting conditions.

A new paper, published by a team of Penn State researchers in ACS Nano, seeks to further advance photodetectors' use by integrating the technology with durable Gorilla glass, the material used for smart phone screens that is manufactured by Corning Incorporated.

The integration of photodetectors with Gorilla glass could lead to the commercial development of "smart glass," or glass equipped with automatic sensing properties. Smart glass has a number of applications ranging from imaging to advanced robotics, according to the researchers.

"There are two problems to address when attempting to manufacture and scale photodetectors on glass," said principal investigator Saptarshi Das, assistant professor of engineering science and mechanics (ESM).?"It must be done using relatively low temperatures, as the glass degrades at high temperatures, and must ensure the photodetector can operate on glass using minimal energy."

To overcome the first challenge, Das, along with ESM doctoral student Joseph R. Nasr, determined that the chemical compound molybdenum disulfide was the best material to use as a coating on the glass.

Then, Joshua Robinson, professor of materials science and engineering (MatSE) and MatSE doctoral student Nicholas Simonson used a chemical reactor at 600 degrees Celsius -- a low enough temperature so as not to degrade the Gorilla glass - to fuse together the compound and glass. The next step was to turn the glass and coating into a photodetector by patterning it using a conventional electron beam lithography tool.

"We then tested the glass using green LED lighting, which mimics a more natural lighting source unlike laser lighting, which is commonly used in similar optoelectronics research," Nasr said.

The ultra-thin body of the molybdenum disulfide photodetectors allows for better electrostatic control, and ensures it can operate with low power -- a critical need for the smart glass technology of the future.

"The photodetectors need to work in resource-constrained or inaccessible locations that by nature do not have access to sources of unrestricted electricity," Das said. "Therefore, they need to rely on pre-storing their own energy in the form of wind or solar energy."

If developed commercially, smart glass could lead to technology advances in wide-ranging sectors of industry including in manufacturing, civil infrastructure, energy, health care, transportation and aerospace engineering, according to the researchers. The technology could be applied in biomedical imaging, security surveillance, environmental sensing, optical communication, night vision, motion detection and collision avoidance systems for autonomous vehicles and robots.

"Smart glass on car windshields could adapt to oncoming high-beam headlights when driving at night by automatically shifting its opacity using the technology," Robinson said. "And new Boeing 757 planes could utilize the glass on their windows for pilots and passengers to automatically dim sunlight."

UNIVERSITY PARK, Pa. -- Fake news detectors, which have been deployed by social media platforms like Twitter and Facebook to add warnings to misleading posts, have traditionally flagged online articles as false based on the story's headline or content. However, recent approaches have considered other signals, such as network features and user engagements, in addition to the story's content to boost their accuracies.

However, new research from a team at Penn State's College of Information Sciences and Technology shows how these fake news detectors can be manipulated through user comments to flag true news as false and false news as true. This attack approach could give adversaries the ability to influence the detector's assessment of the story even if they are not the story's original author.

"Our model does not require the adversaries to modify the target article's title or content," explained Thai Le, lead author of the paper and doctoral student in the College of IST. "Instead, adversaries can easily use random accounts on social media to post malicious comments to either demote a real story as fake news or promote a fake story as real news."

That is, instead of fooling the detector by attacking the story's content or source, commenters can attack the detector itself.

The researchers developed a framework -- called Malcom -- to generate, optimize, and add malicious comments that were readable and relevant to the article in an effort to fool the detector. Then, they assessed the quality of the artificially generated comments by seeing if humans could differentiate them from those generated by real users. Finally, they tested Malcom's performance on several popular fake news detectors.

Malcom performed better than the baseline for existing models by fooling five of the leading neural network based fake news detectors more than 93% of the time. To the researchers' knowledge, this is the first model to attack fake news detectors using this method.

This approach could be appealing to attackers because they do not need to follow traditional steps of spreading fake news, which primarily involves owning the content. The researchers hope their work will help those charged with creating fake news detectors to develop more robust models and strengthen methods to detect and filter-out malicious comments, ultimately helping readers get accurate information to make informed decisions.

"Fake news has been promoted with deliberate intention to widen political divides, to undermine citizens' confidence in public figures, and even to create confusion and doubts among communities," the team wrote in their paper, which will be presented virtually during the 2020 IEEE International Conference on Data Mining.

Added Le, "Our research illustrates that attackers can exploit this dependency on users' engagement to fool the detection models by posting malicious comments on online articles, and it highlights the importance of having robust fake news detection models that can defend against adversarial attacks."

Scientists worldwide have been working flat out on research into infectious diseases in the wake of the global outbreak of the COVID-19 disease, caused by the new coronavirus SARS-CoV-2. This concerns not only virologists, but also physicists, who are developing mathematical models to describe the spread of epidemics. Such models are important for testing the effects of various measures designed to contain the disease - such as face masks, closing public buildings and businesses, and the familiar one of social distancing. These models often serve as a basis for political decisions and underline the justification for any measures taken.

Physicists Michael te Vrugt, Jens Bickmann and Prof. Raphael Wittkowski from the Institute of Theoretical Physics and the Center for Soft Nanoscience at the University of Münster have developed a new model showing the spread of infectious diseases. The working group led by Raphael Wittkowski is studying Statistical Physics, i.e. the description of systems consisting of a large number of particles. In their work, the physicists also use dynamical density functional theory (DDFT), a method developed in the 1990s which enables interacting particles to be described.

At the beginning of the corona pandemic, they realised that the same method is useful for describing the spread of diseases. "In principle, people who observe social distancing can be modelled as particles which repel one another because they have, for example, the same electrical charge," explains lead author Michael te Vrugt. "So perhaps theories describing particles which repel one another might be applicable to people keeping their distance from one another," he adds. Based on this idea, they developed the so-called SIR-DDFT model, which combines the SIR model (a well-known theory describing the spread of infectious diseases) with DDFT. The resulting theory describes people who can infect one another but who keep their distance. "The theory also makes it possible to describe hotspots with infected people, which improves our understanding of the dynamics of so-called super-spreader events earlier this year such as the carnival celebrations in Heinsberg or the après-ski in Ischgl," adds co-author Jens Bickmann. The results of the study have been published in the journal "Nature Communications".

The extent of the social distancing being practised is then defined by the strength of the repulsive interactions. "As a result," explains Raphael Wittkowski, the leader of the study, "this theory can also be used to test the effects of social distancing by simulating an epidemic and varying the values for the parameters defining the strength of the interactions." The simulations show that the infection rates do indeed show a marked decrease that is a result of social distancing. The model thus reproduces the familiar "flattening the curve" effect, in which the curve depicting the development of the number of infected people over time becomes much flatter as a result of social distancing. In comparison with existing theories, the new model has the advantage that the effects of social interactions can be explicitly modelled.

In March 2020, New York City, an icon of America, was unfortunately named an early epicenter of the novel coronavirus. Now seven months later, America faces a new surge in coronavirus cases and researchers at Texas A&M University hope to provide information and context to help with the battle ahead.

Rich Whittle, a doctoral student at Texas A&M, cites in a recent study that by April 2020, New York City accounted for more than a third of the nation's confirmed cases, with a transmission rate five times higher than the rest of the country.

Whittle wanted to look at these early stages of the pandemic spread in New York neighborhoods to discover if there were any socioeconomic factors that could be associated with the high positivity rate of COVID-19.

"The world is waking up to the first global pandemic in a while, but it's not going to be the last, so understanding the contact patterns and socioeconomic factors that lead to high-detected case numbers is important for public health," said Whittle.

The study, published in BMC Medicine, identified four significant predictors of COVID-19 cases in New York City: neighborhoods with higher population densities led to an increase in the positivity rate; neighborhoods with younger populations (under 18 years old) also led to an increase; households with a higher income led to a decrease; and race showed a significant association with detected COVID-19 cases - both a lower percentage of white population and higher percentage of Black population led to increased positivity rates.

"From what is available in the early stages, this is what we're seeing from the data, and we know those early stages are really important to keep this and future pandemics under control," said Dr. Ana Diaz Artiles, assistant professor in the Department of Aerospace Engineering at Texas A&M and co-author of the study.

The study used spatial modeling techniques to look at data from roughly 60,000 cases during the first month of the pandemic in New York City.

"I'm really interested in spatial statistics. When I was in the military, I worked in geospatial intelligence so I have a background interest in that," said Whittle. "And I was taking Dr. Diaz Artiles' stats class at the time, so I thought I could combine those two interests and have a look at an ecological study related to COVID-19."

Whittle initiated the study as his final class project for Diaz Artiles' spring Design of Experiments and Statistical Methods course (AERO 689).

"This class gives the opportunity to solve problems that the students are interested in," said Diaz Artiles. "These classes are really useful for students not only in terms of learning statistical tools, but to apply them in practical applications that could even lead to impactful results and publications."

In addition to academic interest, Whittle was motivated to pursue the study because of the value the results could provide, both now and in the future.

"There's a need to understand the beginning stage of the pandemic," said Whittle. "And I think in America, certainly now, there's a lot of discontent. There's a definite public interest in understanding the response in the initial stages of the pandemic."

Whittle and Diaz Artiles emphasize that understanding the early factors and influences of past pandemics, such as the H1N1 pandemic of 2009 and the one we face today, is important in helping to inform future management.

"Hopefully our study will provide a better understanding of the main factors that impact the spread of the disease, thus improving future decision making in the early stages of a pandemic," said Diaz Artiles.

The majority of people infected with SARS-CoV-2 appear to actively shed infectious virus for about 8 days, but there is a wide range of variability from person to person. Understanding how long people can remain actively infected is important, because it provides new details about a disease and a virus that are still not well understood and informs public health decisions. Researchers report November 4 in the journal Cell an unusual case of one woman with leukemia and a low antibody count who was infected with the coronavirus for at least 105 days, and infectious for at least 70, while remaining asymptomatic the entire time.

"At the time we started this study, we really didn't know much about the duration of virus shedding," says senior author Vincent Munster, a virologist at the National Institute of Allergy and Infectious Diseases. "As this virus continues to spread, more people with a range of immunosuppressing disorders will become infected, and it's important to understand how SARS-CoV-2 behaves in these populations."

Munster, an expert in emerging infectious diseases, began publishing research on SARS-CoV-2 in January. He was contacted in April by infectious disease specialist Francis Riedo, a study co-author, about a patient in Kirkland, Washington, who had been infected very early in the COVID-19 pandemic. Riedo's patient had had numerous positive PCR tests for the virus over a period of weeks, and he wanted to know if she was still shedding virus.

The patient, a 71-year-old woman, was immunocompromised due to chronic lymphocytic leukemia and acquired hypogammaglobulinemia. She never showed any symptoms of COVID-19. She was found to be infected with the virus when she was screened after being admitted to the hospital for severe anemia and her doctors recognized that she had been a resident of a rehabilitation facility experiencing a large outbreak.

Munster's lab at NIAID's Rocky Mountain Laboratories in Hamilton, Montana, began studying samples that were regularly collected from the patient's upper respiratory tract. They found that infectious virus continued to be present for at least 70 days after the first positive test, and the woman didn't fully clear the virus until after day 105. "This was something that we expected might happen, but it had never been reported before," Munster says.

The investigators believe the patient remained infectious for so long because her compromised immune system never allowed her to mount a response. Blood tests showed that her body was never able to make antibodies. At one point she was treated with convalescent plasma, but Munster doesn't think the treatment had an effect because of its low concentration of antibodies. Despite her inability to mount an antibody response, she never went on to develop COVID-19.

The team performed deep sequencing on all the virus samples obtained from the patient to see how the virus might have changed over the course of the patient's infection. Samples collected at various times displayed different dominant gene variants. However, the investigators don't think that these mutations played a role in how long the virus persisted, because they saw no evidence of natural selection. Selection would have been implicated if one of the variants had appeared to provide the virus with a survival benefit and had become the dominant variant, but none of them did. They also tested whether or not the mutations affected the ability or speed of the virus to replicate and found no differences.

Munster says that as far as he knows, this is the longest case of anyone being actively infect-ed with SARS-CoV-2 while remaining asymptomatic. "We've seen similar cases with influenza and with Middle East respiratory syndrome, which is also caused by a coronavirus," he notes. "We expect to see more reports like ours coming out in the future."

Microbes and other microscopic organisms could serve as sustainable "factories" to create many types of industrial materials because they naturally convert nutrients such as sugars into byproducts. However, creating industrial amounts of organic acids from renewable resources poses a challenge, because not many organisms can grow in highly acidic environments. With the help of gene editing and computational modeling tools, a team of researchers explored one type of yeast that could survive in the harsh environment created by acidic products.

The team, which includes Penn State, the University of Illinois at Urbana-Champaign and Princeton University researchers, studied the yeast strain Issatchenkia orientalis, considered to be a "non-model" yeast because it has not been researched extensively. After reconstructing the yeast's metabolism into a network model, the team examined its growth on different feedstock and subsequent byproducts. This strain was able to produce succinic acid, which is a precursor for industrial polymer production. The team reported its results in Metabolic Engineering Communications.

The researchers used a combination of genetic sequencing, gene editing, and sophisticated computational modeling to pinpoint which metabolic activities could be changed to maximize production of succinic acid without detriment to the yeast.

"The emergence of efficient CRISPR-Cas tools for making multiple genetic interventions in a single pass has emphasized the need for the development of predictive models and algorithms for suggesting which multiple genetic modifications to implement," said Costas Maranas, the Donald B. Broughton Professor of chemical engineering and Institute for Computational and Data Sciences associate, Penn State, who co-led this study.

The computation-heavy approach, which ran on Penn State's Roar supercomputer, was important in helping to refine the research direction, according to the researchers. The I. orientalis model covers 850 genes and contains 1,826 metabolic reactions, so identifying the right combination of genes and reactions to modify in order to produce succinic acid becomes a needle-in-a-haystack type of problem. Running thousands of computer simulations sifts through the hay and provides a much narrower set of experiments to test in a lab.

"With this approach, we can rank redesign hypotheses much faster than relying on a purely experimentalist approach," said Patrick Suthers, postdoctoral scholar in chemical engineering, Penn State. "Our collaborators worked on developing genetic tools specifically for this organism, but even with their tools, it takes much longer to make modifications."

The team's analysis uses OptKnock, an optimization framework previously developed by the Maranas group, as part of the computational modeling.

Combining the computational techniques with traditional experiments not only informed the models with phenotypic measurements, but it also allowed the researchers to ensure their model was accurate in its predictions.

"One critical part of creating models is being able to say, yes, our predictions do make sense," said Suthers. "In this case, our group focused on taking information from the genome in the organism, which our collaborators had sequenced. Then we take the genome and convert it into the functions that can take place in the cell."

The result is a yeast model that can be used in any number of ways.

"Now that we have this comprehensive genome-scale model, we can look at things like the rates of organism growth and fluxes, and we can nail down key reactions in the metabolic system," said Suthers. "We can also add in new genes to make new types of products."

An earthquake of magnitude 8.0 or larger will almost always cause strong shaking, but a new study suggests that smaller earthquakes--those around magnitude 5.5 or so--are the cause of most occurrences of strong shaking at a 60-kilometer (37-mile) distance.

Small earthquakes are expected to produce relatively weak shaking, and for the most part that's true, said Sarah Minson of the U.S. Geological Survey. However, ground motion is highly variable, and there are always outlier earthquakes at every size that generate more shaking than expected.

Combine that with the fact that there are more smaller magnitude earthquakes than large magnitude earthquakes, and most shaking comes from these "little earthquakes with ambition," Minson and her colleagues report in Seismological Research Letters.

The researchers found that for all distances and for all levels of shaking, "the earthquakes that cause that level of shaking are systematically smaller magnitude than the earthquakes that should cause that level of shaking," said Minson, noting that this makes these smaller earthquakes a significant source of earthquake damage.

The findings could change how people think about and prepare for the "Big One," the large magnitude earthquakes that loom large in the imaginations of people from California to Chile, said Minson.

A future magnitude 8.0 San Andreas Fault earthquake will cause more total damage across the Los Angeles Basin than a smaller, local earthquake like the 1933 magnitude 6.4 Long Beach earthquake, simply because the larger earthquake causes shaking over a wider area. But that just means that there will be more overall shaking, not that the shaking will necessarily be stronger in any particular locality, she explained.

While waiting for the Big One, places like Long Beach are likely to have multiple damaging medium earthquakes, "and thus most damage at any location is probably coming from smaller earthquakes with ambition," Minson added.

The 1969 Santa Rosa, California earthquakes, around magnitude 6, caused about $50 million damage in today's dollars, while the magnitude 5.7 Magna, Utah earthquake earlier this year caused similar amounts of damage just to 100 government buildings, the researchers noted.

"For a lot of us, if we do look back over our personal experiences, the earthquake that we had the greatest amount of damage from is not the largest magnitude earthquake that we've felt at all," Minson said.

It's a "sharks versus cows" concept, she added. "Sharks are scary, and cows are not, but cows kill more people every year than sharks do."

The researchers began with calculations of the variation of expected ground acceleration from an earthquake of a certain magnitude and distance away from the shaking, along with the well-known Gutenberg-Richter magnitude-frequency relationship. The relationship demonstrates how the frequency of earthquakes decreases as the magnitude grows, so that for each magnitude 8 earthquake that occurs within a given region and time period, there will be 10 magnitude 7 earthquakes, 100 magnitude 6 earthquakes, and so on.

Together, these two factors suggest that most shaking should come from smaller earthquakes that are "ambitious outliers" in terms of the amount of ground acceleration they cause. "The probability of any of these small earthquakes producing shaking is tiny, but there are many of them," Minson said.

Minson and colleagues confirmed this hypothesis after examining three data sets of earthquakes from across the globe, ranging from magnitude 0.5 to 8.3.

Ambitious little earthquakes may cause difficulty for some earthquake early warning systems, which alert users to potential damaging shaking after an earthquake begins, the researchers write. The closer users are to the earthquake source, the less likely it is that the alert arrives before they feel the shaking.

"If it turns that most of our shaking is coming from smaller magnitude earthquakes, well, smaller magnitude earthquakes are spatially more compact," Minson said, who noted that some systems also may not send out an alert at all for small earthquakes that aren't expected to produce damaging shaking.

The findings do not change the total amount of earthquake hazard calculated for a region, Minson stressed. "All we did is say, ok, when that shaking comes, what is it likely to come as? And it's much more likely to come as little earthquakes with ambition than a big earthquake doing what big earthquakes do."

This means, as Minson's UGGS co-author Sara McBride says, that "it's time to talk about the medium ones." Surveys and studies show that people often are demotivated by efforts to prepare for the Big One, overwhelmed by fatalism in the face of such an event. Focusing on smaller but significant events could encourage people to devote more time and effort to earthquake preparedness, the researchers suggest.

"If we talk about earthquakes like Loma Prieta and Northridge, and ask people to be prepared for that, it's more tractable," Minson said. "Those are the earthquakes that people have experienced and know how to prepare for and survive."