Tech

Severe space weather could be forecast with greater accuracy and reliability than ever before, according to a new study, which presents a physics-based method for predicting imminent large solar flares. Solar flares - massive explosions of electromagnetic radiation, plasma and charged particles in the Sun's outer atmosphere - are triggered by the sudden release of energy stored in the twisted magnetic fields that occur around visible sunspots. The X-ray light emitted by a flare, and the ejection of material from the Sun that often accompanies them, can produce powerful space weather effects on Earth. These can pose hazards to astronauts, spacecraft, and technological systems on the ground, such as electric power grids and radio communications. As global society becomes more dependent on these technologies, there is increasing need for reliable methods to predict imminent solar events and improve warning times when they occur. Despite decades of study and near-continuous monitoring of the Sun's magnetic activity, the specific conditions and mechanisms that produce flares remain unknown, making them particularly difficult to forecast. Kanya Kusano and colleagues present the "κ-scheme" (kappa-scheme), a predictive model that can forecast large solar flares more reliably than previous methods. Using a physics-based scheme to derive critical thresholds of a magnetohydrodynamic instability, Kusano et al.'s approach predicts when a large solar flare is imminent using routine magnetic observations of the Sun. It also identifies where the flare will occur, and how much energy could be released. To test their model, the authors analyzed data from NASA's Solar Dynamics Observatory from 2008 to 2019, finding that the κ-scheme was able to identify the occurrence, location and size of most large flares, up to 20 hours in advance. In a related Perspective, Astrid Veronig discusses how the method improves our understanding of how and why solar flares occur.

Washington, DC: COVID-19 has led to a global economic slowdown that is affecting all four pillars of food security - availability, access, utilization, and stability - according to a new article from researchers at the International Food Policy Research Institute (IFPRI), published in the journal Science. Agricultural and food markets are facing continuous disruptions due to labor shortages caused by lockdowns, as well as large shifts in food demand arising from income losses and the closure of schools and restaurants. The key findings highlight the impact of COVID-19 on food systems, the global economy, poverty, health, and trade.

"The most important impact of the pandemic on food security is through income declines that put food access at risk", said article co-author and IFPRI Director-General Johan Swinnen. "This is especially a concern for the extreme poor, who spend on average about 70 percent of their total income on food."

The International Monetary Fund (IMF) projects a 5% decline in the world economy in 2020, a deeper global recession than during 2008-2009 financial crisis. Model-based simulations by IFPRI suggest that such a deep recession would push 150 million more people into extreme poverty; an increase of 24% from current levels. Most of the rise in poverty will be concentrated in sub-Saharan Africa and South Asia. "Disruptions in food systems both contribute to increases in poverty, by affecting a critical source of income for many of the world's poor, and also exacerbate the impacts of poverty by reducing access to food, particularly nutritious foods," said Swinnen.

The researchers note that income declines will particularly affect consumption of nutrition-rich foods, such as fruits, vegetables, and animal-source products. New evidence from Ethiopia confirms this impact and further indicates that it is expected to increase micronutrient deficiencies among its population, contributing to poor health and greater susceptibility to COVID-19.

Governments all over the world have made attempts to ensure availability of staple foods and these supply chains have generally held up well, even in countries with strict social distancing requirements. But food supply chains differ across countries and crops, as do the impacts of COVID-19 on supplies. Capital-intensive food value chains that are highly mechanized (predominant in rich countries for staple crops such as wheat, maize and soybeans) have continued functioning with few disruptions. In contrast, food production in poor countries tends to be more labor-intensive; and production of many non-staples, such as fruits and vegetables, worldwide requires workers be in close proximity. These food value chains have shown more supply disruptions owing to the risk of disease transmission, labor shortages, and disruptions in transportation and logistics. Parts of food processing sectors in rich countries have also been susceptible to such disruptions, as evident in the case of United States and Europe, where 30,000 workers in meat processing tested positive for COVID-19, causing many plant closures.

"It is critical to exempt agricultural practices and actors from COVID-19 lockdown measures to ensure the adequate flow of food from farm to fork", said IFPRI's Markets, Trade and Institutions Division Director Rob Vos. The researchers point to the "green lanes" the Chinese government created to ease the transport, production processes, and distribution of agricultural inputs and food products as an example.

Trade is also essential to address issues of availability and stability. It ensures diversification of supplies, reduces gaps in production and helps stabilize of world markets. Export restrictions on staple foods including rice and wheat, imposed by 21 countries in the early months of the pandemic, created volatility and upward pressure on world prices for food staples. "Fortunately, many of these export restrictions have since been lifted, and world market prices for rice, for instance, declined after the end of Vietnam's export ban," said article co-author and IFPRI Senior Research Fellow David Laborde. The researchers recommend governments avoid further use of disruptive policies like export restrictions on food, keep policies consistent with rules agreed at the WTO and maintain open trade channels.

Fiscal challenges facing low- and middle-income countries could create strong international spillover effects for the economic consequences of COVID-19. Support and response from high-income countries and international organizations is crucial for poor countries with limited fiscal space. "Such support would not only aid global economic recovery but also mitigate the enormous humanitarian costs associated with the health tragedy of COVID-19 and the consequent food crisis," said article co-author and IFPRI Senior Research Fellow Will Martin.

Older Americans may be receiving cancer screenings not recommended by the U.S. Preventive Services Task Force, according to Penn State College of Medicine researchers.

The task force recommends routine screening for colorectal, cervical and breast cancers. These recommendations end for people at upper ages or who develop a condition that decreases their life expectancy. A routine screening above the recommended age is called overscreening.

"There are two reasons why people should stop screening for cancer," Jennifer Moss, assistant professor of family and community medicine and public health sciences, said. "First, when they 'age-out' of the recommended screening age, or second, when their life expectancy is too low. As with any clinical procedure, there are risks from the cancer screening tests. These risks are even higher for people who have aged-out or who have a low life expectancy."

To determine the extent of overscreening nationally, the researchers analyzed data from the Center for Disease Control and Prevention's 2018 Behavioral Risk Factor Surveillance System. This survey collects data about a variety of health behaviors, including cancer screening. In total, researchers reviewed data for 20,937 men and 34,244 women for colorectal cancer, 82,811 women for cervical cancer and 38,356 women for breast cancer. Researchers identified overscreened patients as those over age 75 for colorectal cancer screening, and women over 65 for cervical and over 75 for breast cancer screenings. The researchers also determined patient location and whether the patient lived in or near a city.

"We can never exactly know a person's life expectancy, but my co-authors and I used a scientifically-accepted index to calculate estimated risk of death over the next 10 years," Moss said. "We hypothesized that people who are older or who have lower life expectancies would be less likely to report having received their cancer screenings recently, but we didn't see strong evidence of this. This pattern shows us that too many people are getting screened after a point when the screening is probably not going to provide benefit and may cause harm."

Researchers found overscreening of 59.3% of men and 56.2% of women for colorectal cancer; 45.8% of women for cervical cancer and 73% of women for breast cancer. Research results appear in the journal JAMA Network Open.

"This pattern emphasizes the need for additional research to identify risks and benefits of screening in older adults and determine who may benefit from screening after the recommended upper-age limits," the researchers reported.

Overscreening was higher for women who live in or near cities. Researchers offer several reasons this may be. First, women who live in more rural areas may have longer and more trusting relationships with their healthcare providers, allowing for conversations about stopping cancer screenings. Second, rural women may have less access to screening facilities, reducing the number overscreened. Third, women who live in or near cities may receive automated screening reminders from more technologically-advanced healthcare facilities. Lastly, beliefs about cancer differ between rural and city populations. Those who live in or near a city may be more open to screening. Why men do not have the same overscreening difference is not known.

Preventing screenings that are not recommended is challenging, said the researchers. One reason is that life expectancy estimates are not always accurate. Another reason is that doctors and patients may not be comfortable discussing life expectancy and using it to make medical decisions. A third reason is that the healthcare system often encourages screening. A fourth reason is that awareness campaigns often do not highlight that screenings are not recommended for all ages.

"Guidelines for cancer screening must balance risks with benefits," the researchers reported. "Individuals with limited life expectancy can anticipate fewer benefits of cancer screening, particularly for colonoscopy."

This research helps inform the general healthcare system. Patients should discuss their individual health decisions, including cancer screening, with their healthcare providers.

Origami principles can unlock the potential of the smallest robots, enhancing speed, agility and control in machines no more than a centimeter in size.

University of Michigan researchers have demonstrated that behavioral rules underpinning the Japanese art of folding can expand the capabilities of these machines, creating potential for greater use in fields as diverse as medical equipment and infrastructure sensing.

"We've come up with a new way to design, fabricate and actuate microbots," said Evgueni Filipov, U-M assistant professor of civil and environmental engineering. "We've been the first to bring advanced origami folding capabilities into one integrated microbot system."

Their bots can form one shape, complete a task, then reconfigure into a second shape for an additional task, and so on.

The latest research from the team, which includes Kenn Oldham, a U-M professor of mechanical engineering, Ph.D. student Yi Zhu and graduate research assistant Mayur Birla, appears in Advanced Functional Materials.

To date, most microbots have limited movements, which hampers their ability to perform useful tasks. To increase their range of motion, they need to be able to fold at large angles. U-M's team has created microbots that can fold as far as 90 degrees and more. Larger folds allow microbots to form more complex shapes.

U-M's unique approach enables its microbots to complete their range of motion up to 80 times per second, a faster pace than most can operate.

Microbots using origami principles often require an outside stimulus to activate, such as heat inside a body or a magnetic field applied to the microbot. U-M's utilize a layer of gold and a layer of polymer that act as an onboard actuator--meaning no outside stimulus is needed.

While the microbots are currently controlled by a tether, eventually, an onboard battery and a microcontroller will apply an electric current in the systems.

"When current passes through the gold layer, it creates heat, and we use heat to control the motions of the microbot," Filipov said. "We drive the initial fold by heating the system, then we unfold by letting it cool down.

"To get something to fold and stay folded, we overheat the system. When we overheat, we can program the fold--change where it comes to rest."

These capabilities allow microbots to function elastically and plastically--giving them the ability to recover their original shape.

The research was supported by the Defense Advanced Research Projects Agency and the U-M College of Engineering Dean's Fellowship.

Video: https://www.youtube.com/watch?v=8nLdhHnMIME

Photos: https://www.flickr.com/photos/michigan-engineering/albums/72157715276516223

Study abstract: Elastically and Plastically Foldable Electrothermal Micro?Origami for Controllable and Rapid Shape Morphing

Evgueni Filipov

The Deployable and Reconfigurable Structures Laboratory

With millions of COVID-19 cases reported across the globe, people are turning to antibody tests to find out whether they have been exposed to the coronavirus that causes the disease. But what are antibodies? Why are they important? If we have them, are we immune to COVID-19? And if not, why not?

Antibody tests look for the presence of antibodies, which are specific proteins made in response to infections. Antibodies are disease specific. For example, measles antibodies will protect you from getting measles if you are exposed to it again, but they won't protect you from getting mumps if you are exposed to mumps.

"Antibodies are important because they prevent infection and heal patients affected by diseases," said Victor Padilla-Sanchez, a researcher at The Catholic University of America in Washington D.C. "If we have antibodies, we are immune to disease, as long as they are in your system, you are protected. If you don't have antibodies, then infection proceeds and the pandemic continues."

This form of foreign-antibody-based protection is called passive immunity -- short-term immunity provided when a person is given antibodies to a disease rather than producing these antibodies through their own immune system.

"We're at the initial steps of this now, and this is where I'm hoping my work might help," Padilla-Sanchez said. Padilla-Sanchez specializes in viruses. Specifically, he uses computer models to understand the structure of viruses on the molecular level and uses this information to try to figure out how the virus functions.

Severe acute respiratory syndrome (SARS) was the first new infectious disease identified in the 21st century. This respiratory illness originated in the Guangdong province of China in November 2002. The World Health Organization identified this new coronavirus (SARS-CoV) as the agent that caused the outbreak.

Now we're in the middle of yet another new coronavirus (SARS-CoV-2), which emerged in Wuhan, China in 2019. COVID-19, the disease caused by SARS-CoV-2, has become a rapidly spreading pandemic that has reached most countries in the world. As of July 2020, COVID-19 has infected more than 15.5 million people worldwide with more than 630,000 deaths.

To date, there are not any vaccines or therapeutics to fight the illness.

Since both illnesses (SARS-CoV and SARS-CoV-2) share the same spike protein, the entry key that allows the virus into the human cells, Padilla-Sanchez's idea was to take the antibodies found in the first outbreak in 2002 -- 80R and m396 -- and reengineer them to fit the current COVID-19 virus.

A June 2020 study in the online journal, Research Ideas and Outcomes, describes efforts by Padilla-Sanchez to unravel this problem using computer simulation. He discovered that sequence differences prevent 80R and m396 from binding to COVID-19.

"Understanding why 80R and m396 did not bind to the SARS-CoV-2 spike protein could pave the way to engineering new antibodies that are effective," Padilla-Sanchez said. "Mutated versions of the 80r and m396 antibodies can be produced and administered as a therapeutic to fight the disease and prevent infection."

His docking experiments showed that amino acid substitutions in 80R and m396 should increase binding interactions between the antibodies and SARS-CoV-2, providing new antibodies to neutralize the virus.

"Now, I need to prove it in the lab," he said.

For his research, Padilla-Sanchez relied on supercomputing resources allocated through the Extreme Science and Engineering Discovery Environment (XSEDE). XSEDE is a single virtual system funded by the National Science Foundation used by scientists to interactively share computing resources, data, and expertise.

The XSEDE-allocated Stampede2 and Bridges systems at the Texas Advanced Computing Center (TACC) and Pittsburgh Supercomputer Center supported the docking experiments, macromolecular assemblies, and large-scale analysis and visualization.

"XSEDE resources were essential to this research," Padilla-Sanchez said.

He ran the docking experiments on Stampede2 using the Rosetta software suite, which includes algorithms for computational modeling and analysis of protein structures. The software virtually binds the proteins then provides a score for each binding experiment. "If you find a good docking position, then you can recommend that this new, mutated antibody should go to production."

TACC's Frontera supercomputer, the 8th most powerful supercomputer in the world and the fastest supercomputer on a university campus, also provided vital help to Padilla-Sanchez. He used the Chimera software on Frontera to generate extremely high-resolution visualizations. From there, he transferred the work to Bridges because of its large memory nodes.

"Frontera has great performance when importing a lot of big data. We're usually able to look at just protein interactions, but with Frontera and Bridges, we were able to study full infection processes in the computer," he said.
Padilla-Sanchez's findings will be tested in a wet lab. Upon successful completion of that stage, his work can proceed to human trials.

Currently, various labs across the world are already testing vaccines.

"If we don't find a vaccine in the near term we still have passive immunity, which can prevent infection for several months as long as you have the antibodies," Padilla-Sanchez said. "Of course, a vaccine is the best outcome. However, passive immunity may be a fast track in providing relief for the pandemic."

Florida is one of several states in the Southeast where wind energy is virtually nonexistent, which is one reason wind farms have not been an economically viable energy source in the region. But a new study from the FAMU-FSU College of Engineering shows how upcoming technological advances could make wind energy a hot commodity in the Sunshine State.

Sean Martin, a researcher in the Department of Civil and Environmental Engineering from Florida State University, is working with an interdisciplinary team of scientists to examine wind resource characteristics at nine different locations in Florida. Their analysis will help the wind industry and policymakers know how viable wind energy production using developing technologies could be.

Sean Martin, a researcher in the Department of Civil and Environmental Engineering

Their work was published in the journal Applied Energy.

"With advances in turbine technology, taller towers, larger rotor diameter and new control systems, we will be able to provide low-cost wind power to low-wind regions, such as Florida and the Southeast," Martin said. "The increased hub heights and taller turbines can take advantage of greater wind speeds that occur higher up to harvest more wind power."

Compared to states like Texas or Iowa, the wind in Florida is not something wind farms can profitably capture at the moment. Wind speeds are slower because of increased surface friction and turbulence caused by buildings, trees and other obstructions. Most utility-scale turbines installed in the United States are west of the Mississippi River, where more favorable wind speeds, greater than 13 miles per hour, are prevalent.

But using new tools that can capture wind energy at higher elevations, where wind speeds are faster, might make wind energy feasible.

Arda Vanli, associate professor in the Department of Industrial and Manufacturing Engineering

So how tall are these turbines? The average height of most existing on-shore turbines from the ground to the top of the blades is more than 380 feet, similar to a 32-story building. The new, taller turbines are almost twice the height at 660 feet, close to the height of a 55-story building, and are the kind of wind turbines that will be most useful in Florida.

Martin is collaborating with Arda Vanli, an associate professor of industrial and manufacturing engineering, and Sungmoon Jung, an associate professor of civil and environmental engineering.

"I don't think anybody can predict the timing for wind energy," Jung said. "We almost had it a few years ago. There was a private company that proposed a wind farm in Florida, but the company withdrew the plan because the technology at the time was not economical enough. I hope we will see wind energy in the future as technology improves."

Sungmoon Jung, associate professor in the Department of Civil and Environmental Engineering

One of the things the researchers are looking at is the capacity of wind turbines to operate at different sites. Wind speed varies, so turbines must be able to spin at different velocities. Researchers want to know what percentage of time in a year that the turbine can operate at full capacity. In general, turbines that generate at least 30 percent of their total capacity are more economical for utility-scale wind power. The data will be able to predict the best areas in Florida to place the new turbines based on their ability to produce wind energy at specific sites.

"The key is finding and identifying characteristic patterns in the wind data," Martin said. "Once we establish the patterns, the data can assist in site selection and can improve energy estimation measures to help industry and policymakers make decisions on where wind farms are most profitable."

There are other factors the researchers must consider when choosing a site for a wind farm. Safety for birds, noise from rotors and the fact that some people may find wind turbines unsightly are all considerations.

When including some of these elements with wind speed data, the scientists found that the best locations for wind farms appear to be in rural areas of northwest, central and southern Florida.

"Site selection is an important decision, especially in low-wind power areas," Vanli said. "Transporting huge wind turbines to these locations is a significant investment and having good data can eventually determine whether the investment will be successful or not."

Wind energy is gaining significant attention both from academia and in industry. New, affordable methods for generating renewable energy are on the horizon. Wind farms could be viable in Florida within this decade, and turbines even taller than the ones used for this research could be more prevalent in the future.

"The real question is whether factors such as public perception, acceptance and environmental factors will prevent this resource from being developed," Martin said. "We hope the research will add additional renewables to the U.S. energy portfolio and can offset our reliance on a single fuel source, adding energy security to meet a growing need."

As the COVID-19 pandemic continues, officials across the country have had to make decisions about opening and closing schools, businesses and community facilities. They have relied in large part on information about the pandemic -- from hospitalization statistics to test results -- to inform these decisions. But different facts and figures about COVID-19 can paint different pictures of the pandemic, according to Adrian Raftery, a professor of statistics and sociology at the University of Washington.

"The COVID-19 pandemic is generating many different types of data about this disease in communities -- ¬things like the number of confirmed cases or the number of deaths in a particular area," said Raftery. "None of these data sources on their own are perfect in terms of capturing a complete and accurate summary of the prevalence of COVID-19 and the risks of doing certain things like opening businesses or schools. All have their own strengths and weaknesses."

Raftery is lead author of a new guide published June 11 by the National Academies of Sciences, Engineering and Medicine that is intended to help officials nationwide make sense of these different COVID-19 data sources when making public health decisions.

Officials looking for COVID-19 statistics have plenty to choose from: confirmed cases, deaths, hospitalizations, intensive care unit occupancy, emergency room visits, antibody tests, nasal-swab tests and the ratio of positive test results - to name a few of the more common data points collected and distributed by hospitals and public health agencies. But officials don't necessarily have all of these statistics on hand when making decisions, or have enough information to interpret them.

"We intend for this guide to help these decision-makers and their advisors interpret the data on COVID-19 and understand the upsides and downsides of each data source," said Raftery.

For example, the number of positive test results for the novel coronavirus is likely an underestimate of its true prevalence in a community. Many people who have the virus are asymptomatic and aren't likely to seek out a test, and even people with symptoms may not have access to tests and medical care, according to Raftery. As another example, the number of COVID-19 deaths in a region does not reflect the disease's current prevalence because the number of deaths lag behind the number of cases by several weeks. In addition, some deaths may be misattributed to COVID-19, Raftery said.

The guide highlights some criteria for officials to take into account when assessing the usefulness of particular COVID-19 data points, including:

Assessing how representative the data are for a community or region

Whether there may be systemic biases in some data sources

Thinking about the types of uncertainties in data sources, due to factors like sample size, how data were collected and the population surveyed

Whether there's a time lag due to delays in reporting data, the course of the disease and other factors

"There are no perfect data sources, but all of these data sources are still useful for making decisions that directly impact public health," said Raftery.

Raftery has worked extensively on statistical methods to measure and estimate the prevalence of other viruses, including HIV in Africa. Though HIV and the novel coronavirus cause different types of diseases, there are similarities in how the two viruses spread among susceptible populations, as well as how types of social distancing -- condom use for HIV and physical distancing and mask usage for the novel coronavirus -- can decrease transmission. COVID-19 is also generating the same types of data sources, with the same limitations, as HIV/AIDS, such as test results, hospitalization rates and deaths.

Over time, it may be possible to collect more revealing data about COVID-19 from what are known as "representative random samples" within a population. In representative sampling, people are surveyed at random for a disease, and certain populations can be more heavily sampled than others based on what scientists and officials have learned about a disease's prevalence and susceptibility. Representative sampling avoids biases and can more accurately estimate the disease's prevalence in a region, according to Raftery.

"As we learn more about COVID-19, how it spreads, how different populations are more or less susceptible, we may be able to move more in the direction of representative sampling," said Raftery. "The State of Indiana has already done a survey of this kind, and others should follow suit. But there is also a lot that officials can do with the statistics and data sources that hospitals and agencies are providing right now -- provided that officials can be made aware of the strengths and weaknesses of each piece of data."

The guide is the first completed by the National Academies' Societal Experts Action Network -- or SEAN -- an eight-member committee tasked by the National Academies to provide rapid expert assistance on issues related to the social and behavioral sciences during the pandemic. Raftery is a member of the SEAN and spearheaded this inaugural project.

NASA-NOAA's Suomi NPP satellite provided visible imagery of the development and movement of Tropical Storm Isaias is it moved into the eastern Caribbean Sea. NASA's Aqua satellite provided temperature information that gave insight into Isaias' rainmaking potential.

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard Suomi NPP provided a visible image of Potential Tropical Cyclone 9 on July 28. The storm developed into Tropical Storm Isaias on July 29. The imagery showed the broader circulation of the disturbance had become slightly better defined but at the time of the July 29 image, Air Force Reserve reconnaissance aircraft was still unable to find a well-defined circulation.

Later in the day, by 5 p.m. EDT, deep convection continued to increase and a band of thunderstorms developed over the southwestern portion of the broad circulation. By 11 p.m., the storm had developed into a tropical storm. The National Hurricane center noted, "Observations from recent scatterometer passes over the system show that it now has a sufficiently well-defined center to be designated as a tropical cyclone."

Many Warnings and Watches in Effect

The National Hurricane Center (NHC) posted many watches and warnings as Isaias moved through the Caribbean Sea on July 30.

A Tropical Storm Warning is in effect for Puerto Rico, Vieques, Culebra; the U.S. Virgin Islands; the Dominican Republic entire southern and northern coastlines; the north coast of Haiti from Le Mole St. Nicholas eastward to the northern border with the Dominican Republic; Turks and Caicos Islands; the southeastern Bahamas including the Acklins, Crooked Island, Long Cay, the Inaguas, Mayaguana, the Ragged Islands; the Central Bahamas, including Cat Island, the Exumas, Long Island, Rum Cay, and San Salvador.

A Tropical Storm Watch is in effect for the northwestern Bahamas including Andros Island, New Providence, Eleuthera, Abacos Islands, Berry Islands, Grand Bahamas Island, and Bimini.

NASA Infrared Data Reveals a Heavy Rainmaker

The AIRS instrument aboard NASA's Aqua satellite captured a look at cloud top temperatures in Isaias and gave insight into the size of the large storm and its rainfall potential.

Cloud top temperatures provide information to forecasters about where the strongest storms are located within a tropical cyclone. Tropical cyclones do not always have uniform strength, and some sides have stronger sides than others. The stronger the storms, the higher they extend into the troposphere, and the colder the cloud temperatures. NASA provides that data to forecasters at NOAA's National Hurricane Center or NHC so they can incorporate in their forecasting.

On July 30 at 2:35 a.m. EDT (0635 UTC) NASA's Aqua satellite analyzed the storm using the Atmospheric Infrared Sounder or AIRS instrument. AIRS found coldest cloud top temperatures as cold as or colder than minus 63 degrees Fahrenheit (minus 53 degrees Celsius). NASA research has shown that cloud top temperatures that cold indicate strong storms that have the capability to create heavy rain.

Rainfall Forecast from NHC

NASA's AIRS data, combined with other data is used by NHC in their forecasts. NHC said Isaias is expected to produce the following rain accumulations:

In Puerto Rico, the Dominican Republic and northern Haiti: 4 to 8 inches, with isolated maximum totals of 10 inches.

In the Bahamas, Turks and Caicos: 4 to 8 inches.

In Cuba: 1 to 2 inches, with isolated maximum totals of 4 inches.

These rainfall amounts will lead to life-threatening flash flooding and mudslides, as well as river flooding. Urban and small stream flooding is expected for the U.S. Virgin Islands, eastern and southwestern Puerto Rico, and Hispaniola. Heavy rains associated with Isaias may begin to affect South Florida Saturday morning. This rain could result in isolated flash and urban flooding, especially in low-lying and poorly drained areas.

Isaias' Status on July 30

By 11 a.m. EDT on July 30, Isaias had moved northwest and was bringing heavy rain and gusty winds to Puerto Rico. The rainfall was producing life-threatening flash flooding. Heavy rains and gusty winds were also spreading over the Dominican Republic.

The center of Tropical Storm Isaias was located near latitude 18.1 degrees north and longitude 68.9 degrees west. That is 50 miles (75 km) southwest of Punta Cana, Dominican Republic. Isaias was moving toward the northwest near 20 mph (31 kph), and a west-northwestward to northwestward motion with some decrease in forward speed is expected over the next couple of days.

Maximum sustained winds are near 60 mph (95 kph) with higher gusts. Some slight weakening is possible as Isaias moves over Hispaniola today. Re-strengthening is forecast on Friday into Friday night. Tropical-storm-force winds extend outward up to 310 miles (500 km) primarily to the north of the center. Tropical-storm-force winds are occurring along the southern coast of Puerto Rico. The estimated minimum central pressure is 1003 millibars.

Forecast for Isaias

On the forecast track, the center of Isaias will move over Hispaniola today, July 30, and move near the Southeastern Bahamas by tonight or early Friday. Isaias is forecast to be near the Central Bahamas Friday night and approach the Northwest Bahamas or southern Florida Friday night and Saturday, August 1.

The atlas features close to 250 structurally distinct areas, each one based on the analysis of 10 brains. More than 24000 extremely thin brain sections were digitized, assembled in 3D and mapped by experts. As part of the new EBRAINS infrastructure of the European Human Brain Project, the atlas serves as an interface to link different information about the brain in a spatially precise way. German researchers led by Prof. Katrin Amunts have now presented the new brain atlas in the renowned journal Science.

Under the microscope, it can be seen that the human brain is not uniformly structured, but divided into clearly distinguishable areas. They differ in the distribution and density of nerve cells and in function. With the Julich-Brain, researchers led by Katrin Amunts now present the most comprehensive digital map of the cellular architecture and make it available worldwide via the EBRAINS research infrastructure.

"On the one hand, the digital brain atlas will help to interpret the results of neuroimaging studies, for example of patients, more accurately", says Katrin Amunts, Director at the German Research Center Juelich and Professor at the University of Duesseldorf. "On the other hand, it is becoming the basis for a kind of 'Google Earth' of the brain - because the cellular level is the best interface for linking data about very different facets of the brain.

A Google Earth of the Brain

In this way, the researchers are making a significant contribution to the Human Brain Project (HBP), for which the European Commission just approved 150 million Euro until 2023. "Together with many partners in this project, we are building EBRAINS as a novel high-tech research infrastructure for the neurosciences," says Amunts, who is also the Scientific Research Director of the project.

More than a quarter century of research has gone into the 3D atlas. Dozens of experts have used image analysis and mathematical algorithms to evaluate the tissue sections over the years and determine the boundaries between brain areas, which together make up a length of almost 2000 meters.

Regions vary in their difference

Mapping showed that areas vary between different brains, for example in terms of size and location. The Julich-Brain therefore displays the position and shape of individual regions as "probability maps". The researchers found particularly large differences in the Broca region, which is involved in language. In contrast, the primary visual area appeared much more uniform.

As part of EBRAINS, the Julich Brain Atlas is the starting point for bringing structure and function together. The atlas is already helping to link data on gene expression, connectivity and functional activity, for example, to better understand brain functions and the mechanisms of diseases. "EBRAINS also enables us to use the maps for simulations or to apply artificial intelligence to explore the division of labor between brain areas. The huge amounts of data generated from this are processed using the EBRAINS computing platform." The computational power comes from the new European supercomputing network FENIX, which is formed by five leading centres for High Performance Computing, including the Julich Supercomputing Centre (JSC).

Digital brain science

"It is exciting to see how far the combination of brain research and digital technologies has progressed," says Amunts. "Many of these developments converge in the Julich-Brain-Atlas and on EBRAINS. They help us - and more and more researchers worldwide - to better understand the complex organization of the brain and to jointly uncover how things are connected."

WHAT

The 2020 Joint Statistical Meetings will bring together statisticians and data scientists from around the world - this year, for the first time, in a virtual format. This tip sheet from the American Statistical Association highlights interesting presentations from the upcoming JSM 2020.

WHEN

Sunday, August 2 - Thursday, August 6, 2020

WHERE

Online venue https://ww2.amstat.org/meetings/jsm/2020/

Complementary press registration is open, courtesy of the ASA. Information on how to receive press credentials is at the bottom of this release.

FEATURED RESEARCH (SYNOPSES BELOW)

**ASTERISKS IDENTIFY CORONAVIRUS/COVID-19-RELEVANT RESEARCH

MONDAY HIGHLIGHTS

1. Improving NCAA football rankings with data science

2. Precision medicine for stem cell transplants

3. Statistical analysis of footprints in forensic science

4. The role of uncertain infection status in controlling epidemics **

5. Deep Learning AI neural networks for climate change

TUESDAY HIGHLIGHTS

6. Which emoticon personality are you? ;-)

7. Undercounting invisible immigrant communities in the census

8. How do algorithmic tools affect fairness and quality of decision making?

9. Mathematical model for re-opening businesses during COVID-19 **

WEDNESDAY HIGHLIGHTS

10. Analyzing the fairness of a pre-trial risk algorithm

11. Data science tools for monitoring patient safety during clinical trials

12. "Nowcasting" and Forecasting COVID-19 **

13. Text-mining news articles to predict stock returns

THURSDAY HIGHLIGHTS

14. Group testing for COVID-19: What is it, and how could it be implemented more effectively? **

15. Panel on statistical significance and P-values

16. COVID-19 Infectious disease modeling and statistics: myths, maxims and mobilization **

17. New model for contact tracing and disease spread **

18. Who are the scientific grant gatekeepers?

19. Statistical models for comparing state opioid policies

MONDAY HIGHLIGHTS

1) Improving NCAA football rankings with data science

In US college football, declaring a national champion hasn't been easy. Prior to 2014, the statistical rating method used was plagued with criticisms, and currently a 13-member committee selects and seeds teams for playoffs. But some fans still wonder if there's a better way. In this presentation, Shane Reese of Brigham Young University will present a new statistical rating system, called Ratings Using Score Histories, developed with colleagues to help select playoff teams. Its novel feature: it uses data from a game's score process - that is, the score for each point in time throughout a game - for an entire season. Unlike previous methods, this new system treats teams from weaker and stronger conferences more fairly and also makes use of all available data. The presentation will demonstrate how the rating system can be used, including results from the 2019-2020 season.

The presentation, "RUSH: An Evolutionary Approach to Ranking College Football Teams," will take place Monday, August 3, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309359

2) Precision medicine for stem cell transplants

Treating blood cancers like leukemia sometimes calls for the aggressive approach of transplanting stem cells from a healthy donor into a patient's bone marrow. To help prepare the patient's body for the transplant, a drug called busulfan is injected directly into the veins. It's tricky to get its exact dosage correct, however - too much can lead to toxicity or even death, while too little can make it easier for the cancer to return. In this presentation, Peter Thall from the MD Anderson Cancer Center at the University of Texas will describe the new "precision medicine" statistical model that he and colleagues created to determine the right dosage, resulting in a method that be easily used by any transplant doctor. By switching from the current "one-size-fits-all" strategy to the new method, the researchers calculate that doctors can extend many patients' lives dramatically - by an average of 10 to 14 months, for example, for 40 to 60-year-olds in complete remission, which is an improvement of up to 290%.

The presentation, "Bayesian Nonparametric Survival Regression for Optimizing Precision Dosing of Intravenous Busulfan in Allogeneic Stem Cell Transplantation," will take place Monday, August 3, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=308042

3) Statistical analysis of footprints in forensic science

Using footprints in forensic science to link a suspect to a crime scene is statistically complicated. All shoe soles have some kind of random markings - stray holes and scratches acquired during normal use - which investigators can use to compare a suspect's shoe with a crime scene print. But first investigators need to mathematically understand how these random markings accumulate in the first place. In this presentation, Naomi Kaplan-Damary at the University of California, Irvine and the Hebrew University of Jerusalem will present work with colleagues that involved the analysis of nearly 400 shoes. Using the same equations that can describe the distribution of trees in a forest or stars in the Milky Way, the researchers pinpointed the areas on the soles that are more likely to pick up distinguishing blemishes, which will help determine their importance as evidence.

The presentation, "A Step Forward in Estimating the Probability of Accidental Mark Locations on a Shoe Sole," will take place Monday, August 3, 2020 : 1:00 PM to 2:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309225

4) The role of uncertain infection status in controlling epidemics **

During an epidemic, public health officials ideally would know exactly who was infected at any moment so they could quickly intervene to stop the spread (by quarantining the infected individuals, for example). In real life, of course, there's usually a lot of uncertainty around who's infected and who's not. This uncertainty means that some uninfected people will be needlessly quarantined, disrupting families and workplaces, while some infected people will be allowed to mix freely and spread the disease faster. Jessica Hoffman from University of Texas at Austin will present theoretical results with colleagues showing that even a tiny uncertainty has a dramatic impact on the amount of time and resources (such as quarantining) needed to contain the epidemic. This work implies that a community should invest in knowing exactly who is infected - through contact tracing, for example - or else it will pay the price tenfold later.

The presentation, "The Cost of Uncertainty in Curing Epidemics," will take place Monday, August 3, 2020 : 1:00 PM to 2:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=312849

5) Deep Learning AI neural networks for climate change

Deep Learning is a powerful type of machine learning artificial intelligence that has been used with extraordinary success in fields such as computer vision, speech recognition, and language translation. But its use in climate change science is new. Prabhat from Lawrence Berkeley National Laboratory and colleagues have worked on using Deep Learning for the problem of detecting extreme weather events such as hurricanes and severe weather fronts. In this presentation, Prabhat will describe their work training a state-of-the-art deep learning network to find extreme weather patterns in complex "ground-truth" climate datasets. He will also show how they can now apply the trained network to new climate datasets and use this to understand how extreme weather patterns will change in the future.

The presentation, "Deep Learning for Extreme Weather Detection," will take place Monday, August 3, 2020 : 1:00 PM to 2:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309281

TUESDAY HIGHLIGHTS

6) Which emoticon personality are you? ;-)

Before emojis there were emoticons - primitive emoji pictographs that conveyed emotion through plain-text characters. Users could choose between different styles - a smiley of :-) or :D, for example, instead of :). Do people choose different emoticon styles at random, or do patterns exist that reveal something about a person? To investigate, Juha Alho from the University of Helsinki analyzed discussions between 2001 and 2015 on suomi24, a large Reddit-style social-networking site in Finland, for a total of 48 million individual posts. Using a statistical method called correspondence analysis, Alho uncovered four distinct emoticon user "personalities": the Classics, the Noses, the D-Grins, and the Multi-Mouths. In this talk Alho will describe these personality groups, discuss daily emoticon usage patterns, show trends over time, and reveal which sports forums - from golf to ice swimming to parkour - had the largest relative shares of each of the four emoticon personalities.

The presentation, "What Authors Reveal of Themselves in Internet Discussions?," will take place Tuesday, August 4, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=308134

7) Undercounting invisible immigrant communities in the census

It's been estimated that almost 11 million undocumented immigrants currently live in the US. This number, and their potential exclusion on the census, has become a hotly debated political issue. How do researchers even estimate the number of undocumented immigrants, and what happens if they are not counted? In this presentation, Nadia Flores-Yeffal of Texas Tech University will answer these questions and provide context around the counting of invisible communities of immigrants. She estimates that the undercount in the 2020 Census of both undocumented immigrants and their US-born family members could be up to 8% of the entire population, due in part to the prevalence of "mixed-status families."

The presentation, "How Are Invisible Communities of Immigrants in the United States Counted? What Happens If They're Undercounted?," will take place Tuesday, August 4, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=312361

8) How do algorithmic tools affect fairness and quality of decision making?

In today's data-rich society, many of our decisions are guided partly by machine recommendations, from online shopping to movie recommendations. Judges often use algorithm recommendations as well, for example when weighing the risks of releasing an arrestee on bail before a trial. Much of the debate around these pretrial risk-assessment instruments has focused on accuracy and fairness of the algorithms themselves, however, not on how the algorithms influence and shape their users' behavior. Kosuke Imai from Harvard University and colleagues have developed a statistical framework for experimentally evaluating the impact of machine recommendations on human decisions, including whether or not they improve the fairness of decisions or lead to decisions with better outcomes. This presentation will illustrate the new methods with an example from the criminal justice system, showing how the use of a risk-assessment algorithm influenced judges' decisions and whether it resulted in racial or gender bias in results.

The presentation, "Experimental Evaluation of Computer-Assisted Human Decision Making: Application to Pretrial Risk Assessment Instrument," will take place Tuesday, August 4, 2020 : 1:00 PM to 2:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309356

9) Mathematical model for re-opening businesses during COVID-19 **

How can leaders decide how to reopen the economy safely while the coronavirus is still circulating in the population? In this presentation, Hongyu Miao of the University of Texas Health Science Center at Houston will describe work with colleagues in developing a mathematical model that considers both profit and infection risk from a business entity's perspective. They propose an algebraic equation that describes the net profit a business can generate by reopening and also shouldering the costs associated with virus suppression and worker protection. The presentation will illustrate the model with case studies, discuss what role personal protective equipment should play in the workplace, and show how a business could control infection rates in a workplace while also generating a positive net profit.

The presentation, "Modeling of Business Reopening when Facing SARS-CoV-2 Pandemic: Protection, Cost and Risk," will take place Tuesday, August 4, 2020 : 1:00 PM to 2:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=313328

WEDNESDAY HIGHLIGHTS

10) Analyzing the fairness of a pre-trial risk algorithm

Judges often use algorithms to help categorize the risk that an arrested person will commit another crime before their trial or fail to appear for court dates. The fairness of these of these pre-trial risk assessment tools has been called into question in recent years, however. In this presentation, Megan Price from the Human Rights Data Analysis Group will present work with colleagues that investigated the fairness of such a tool in San Francisco. Their work looked at the algorithm's sensitivity to "overbooking," where a defendant is booked on more serious charges that are ultimately dropped, sometimes in exchange for a guilty plea to lesser charges. Their results showed that in more than a quarter of the cases, overbooking was associated with the defendants receiving stricter pre-trial recommendations than they would have received otherwise. The researchers say this raises questions about the appropriateness of these tools for high-stakes situations.

The presentation, "Assessing Risk Assessment in San Francisco," will take place Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309351

11) Data science tools for monitoring patient safety during clinical trials

Clinical trials that study the effectiveness of new drugs - including potential COVID-19 treatments - need to keep careful watch on a multitude of patient health measurements to make sure the regimen is safe. Traditionally, this data has been reported to clinicians in pages of static tables and lists, which makes it hard to spot important patterns. In this presentation, James Buchanan from Covilance and his colleagues from a multidisciplinary working group will present a new, free visualization tool designed to address this problem. The Hepatic Explorer is an interactive open-source web-based data science application for monitoring liver toxicity that allows a researcher to both visualize data as a whole and also explore red-flag areas. This tool could be of particular help during the current pandemic, Buchanan says, because COVID-19 patients often show abnormal liver readings that need to be distinguished from the study drug's effects.

The presentation, "Improved Signal Detection and Evaluation Using New Open-Source Interactive Safety Graphics," will take place Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309756

12) "Nowcasting" and Forecasting COVID-19 **

Modeling the spread of COVID-19 typically takes one of two approaches: mathematical models such as SIR/SEIR that focus on the theoretical mechanisms driving the spread, and statistical models more driven by data actually being observed. Lily Wang from Iowa State University and collaborators have developed a modeling approach that combines the advantages of mathematical and statistical models to conduct short-term and long-term forecasts. Their "spatio-temporal epidemic model" (STEM) also allows researchers to take into account the particular characteristics of each county that affect both disease spread and fatalities, such as the mobility, age distributions, health infrastructure, and racial and ethnic demographics. In this presentation, Wang will demonstrate the online dashboard they developed based on STEM, which allows users to visualize, track, and predict COVID-19 infections and deaths. Wang will also reveal the model's latest projections for August through December, and show how they compare with the CDC's reported projections.

The presentation, "Spatiotemporal Dynamics, Nowcasting and Forecasting COVID-19 in the United States," will take place Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309454

13) Text-mining news articles to predict stock returns

Advances in data science and machine learning have made it possible to mine enormous sets of news articles and other text data to capture subtleties and sentiments of the language within. This power of this methodology, however, has yet to be fully applied to the field of finance. Zheng Tracy Ke from Harvard University, Dacheng Xiu from University of Chicago, and their colleagues have developed a natural language processing method that's specifically designed to mine text documents to predict stock returns. In this talk, the researchers will present results from applying the new methodology to 6.7 million articles from the Dow Jones Newswires, one of the most actively monitored financial news streams. They will show that their approach can be used to investigate how stock prices respond to the news, and also has value for practical asset management.

The presentation, "Predicting Returns with Text Data," will take place Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309567

THURSDAY HIGHLIGHTS

14) Group testing for COVID-19: What is it, and how could it be implemented more effectively? **

Everyone agrees that COVID-19 testing is the key to containing the coronavirus, saving lives, and reopening the economy. The problem: There simply aren't enough tests for all the people we would like to screen. The solution? "Just group it," says Chris Bilder of the University of Nebraska-Lincoln. His work with colleagues on "group testing," also known as "specimen pooling" and "pooled testing," has shown that this clever statistical strategy is technically feasible and could make available testing resources go a lot further. In this introductory overview lecture, Bilder will explain what group testing is, discuss its history and challenges, show how it is being used, and explain how it could be implemented more effectively.

The presentation, "JUST GROUP IT. Group Testing for Identification," will take place Thursday, August 6, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=314408

15) Panel on statistical significance and P-values

In this session organized by Deborah Mayo of Virginia Tech, four panelists will revisit the debate around statistical significance and P-values, including the presuppositions of criticisms that have been raised, the ramifications of reforms that have been proposed, and an appraisal of alternative methods.

The session, "P-Values and "Statistical Significance": Deconstructing the Arguments," will take place Thursday, August 6, 2020 : 10:00 AM to 11:50 AM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309634

16) COVID-19 Infectious disease modeling and statistics: myths, maxims and mobilization **

In this 40-minute ASA Public Lecture, noted epidemiologist Britta Jewell from the MRC Centre for Global Disease Analysis at Imperial College London and noted statistician Nick Jewell from the London School of Hygiene & Tropical Medicine will discuss facts and myths surrounding the COVID-19 pandemic in the US. They will also share insights that can be gleaned from mathematical models and statistical information and will explain what the country needs to do next around collecting and interpreting data.

The presentation, "COVID-19: Infectious Disease Modeling and Statistics-Myths, Maxims and Mobilization," will take place Thursday, August 6, 2020: 12:00 PM - 1:00 PM EDT. Details: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/ActivityDetails.cfm?SessionID=220178

17) New model for contact tracing and disease spread **

Traditional infectious disease models assume that people mix randomly in a population, and that everyone is equally likely to come into contact everyone else. In reality, however, we each have our own network of contacts that we're more likely to mix with, which is why contact tracing is so important during pandemics. Fan Bu at Duke University and colleagues set out to develop a new method combining both approaches and also improving on past models. Their method can account for how our networks evolve during an epidemic as our behavior changes, and how this in turn affects disease spread. The model can also handle real-world situations with only partial data and where uncertainty is important. In this presentation, Bu will use real data from a 2013 flu transmission to show how the new method can incorporate high-tech contact tracing data to improve modeling and forecasting.

The presentation, "Likelihood-Based Inference for Partially Observed Epidemics on Dynamic Networks," will take place Thursday, August 6, 2020 : 1:00 PM to 2:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309898

18) Who are the scientific grant gatekeepers?

The progress of scientific research relies heavily on grant peer review - a process in which scientists agree to spend significant amounts of time anonymously evaluating grant applications submitted by other researchers. Despite its importance, there has been very little data on characteristics of scientists doing the reviews, so a comprehensive survey of scientists was developed and administered to learn more. Stephen Gallo of the American Institute of Biological Sciences will present results showing an uneven distribution of grant peer review participation, with nearly half of all reported reviews done by less than a quarter of all respondents, and most reporting that they were working at maximum capacity. Implications for the future of science will be discussed.

The presentation, "The Participation and Motivations of Grant Peer Reviewers," will take place Thursday, August 6, 2020 : 3:00 PM to 4:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309505

19) Statistical models for comparing state opioid policies

To address the U.S. opioid crisis, public health experts in different states are trying out a number of policy approaches, such as educating physicians, monitoring prescriptions, and making opioid overdose medication available. Published studies that evaluate these different approaches have increased more than ten-fold in the past 15 years, but it's still difficult to statistically compare the success of different programs across states. In this presentation, Beth Ann Griffin from the RAND Corporation will discuss work with colleagues that examined these statistical methods, especially when a state's particular opioid problems influence the policies it chooses. Simulation results from real-world data will be presented.

The presentation, "Evaluating Methods to Estimate the Effect of State Laws on Opioid-Related Outcomes in the Presence of Selection Bias," will take place Thursday, August 6, 2020 : 3:00 PM to 4:50 PM EDT. Abstract: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/AbstractDetails.cfm?abstractid=309239

Scientists from the Shanghai Institute of Organic Chemistry of the Chinese Academy of Sciences (CAS) have developed the first copper-catalyzed enantioselective trifluoromethylation of benzylic radicals via a copper-catalyzed radical relay strategy.

The incorporation of trifluoromethyl (CF3) groups into biologically active molecules has a significant effect on their physical and biological properties, and optically pure CF3-containing organic molecules broadly exist in pharmaceuticals and agrochemicals. Thus, exploration of efficient asymmetric trifluoromethylation methods is highly demand. Recently, radical trifluoromethylation coupling presents one of most efficient method for their synthesis. However, so far, there are no reports of asymmetric radical trifluoromethylations to date.

As their ongoing research interest in asymmetric radical transformations, LIU Guosheng and his colleagues have recently developed a copper-catalyzed radical relay strategy for the enantioselective cyanation and arylation of sp3 C-H bonds, including benzylic and allylic C-H bonds, which provide efficient method for later-stage modification of drugs and bioactive molecules. They devoted large efforts to mechanism studies, and found that the benzylic radical was enantioselectively trapped by (Box)Cu(CN)2 or (Box)Cu-Ar species.

Inspired by the recent progress on the radical trifluoromethylation, they envisioned that the asymmetric trifluoromethylation of secondary alkyl radicals forging chiral C-CF3 bonds might be possible by introducing chiral ligands.

The copper-catalyzed asymmetric trifluoromethylation of cyclopropanols successfully afforded the optically pure β-CF3 ketones in good yields and excellent enantioselectivities under very mild conditions. Critical to the success of this reaction is that a benzylic radical intermediate can be enantioselectively trapped by reactive (L*)CuIICF3.

n addition, a novel quinolinyl-containing bisoxazoline ligand (Bn-BoxQu) plays a significant role in the asymmetric trifluoromethylation.

This study enables to synthesize diverse optically pure β-CF3 ketones efficiently, which can serve as versatile building blocks for the synthesis of a (R)-CF3-modified analogue of drug Cinacalcet.

What The Study Did: The delivery of radiotherapy in 209 patients with cancer during the COVID-19 outbreak in Wuhan, China, is evaluated in this case series.

Authors: Conghua Xie, M.D., Ph.D., of Zhongnan Hospital of Wuhan University in Wuhan, China, and Melvin L. K. Chua, M.B.B.S., Ph.D., of the National Cancer Centre Singapore in Singapore, are the corresponding authors.

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/

(doi:10.1001/jamaoncol.2020.2783)

Editor's Note: The article contains funding/support disclosures. Please see the articles for additional information, including other authors, author contributions and affiliations, conflicts of interest and financial disclosures, and funding and support.

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Media advisory: The full article is linked to this news release.

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The electron is an elementary particle, a building block on which other systems evolve. With specific properties such as spin, or angular momentum, that can be manipulated to carry information, electrons are primed to advance modern information technology. An international collaboration of researchers has now developed a way to extend and stabilize the lifetime of the electron's spin to more effectively carry information.

They published their results on June 15 in Physical Review B.

"We found the new way to use spin degree of freedom as electron spin wave," said Makoto Kohda, paper author and associate professor in the Department of Materials Science at Tohoku University.

The spin property serves as a tiny magnet, which allows it to store information. Spin can also hold quantum mechanical information, a critical tool for quantum computing. Electron spin as a nature of wave function, however, is new, according to Kohda. This is different from the magnetic spin wave, which carries information in a different way.

The electron spin wave, a term coined by Kohda and the research team, carries information, as well. The problem is that the spin wave could only propagate for so long before losing its information.

"We theoretically found a way to enhance the electron spin wave's lifetime by choosing the proper crystal orientations," Kohda said.

In a simulated experiment, the electron spin is confined in a quantum well with various crystal orientations. When the researchers adjusted the orientation of the crystal to allow the spin orientation to sit perpendicularly, the crystal structure partially protected the electron spin wave from relaxing too much. The protection allowed the spin to persist for up to 30% longer than normal.

"We will use this new information carrier, the electron spin wave, for future electronic devices and quantum information advancements," Kohda said. "The next step is to demonstrate how information can be transferred, processed and stored based on the electron spin wave in semiconductor devices."

The first disease-modifying Alzheimer's disease treatments are on the horizon, but health systems in the United States and Europe would have to take a number of steps to ensure they are ready to provide those treatments to the millions of people who need them, according to two USC reports presented this week at the Alzheimer's Association International Conference.

Soeren Mattke, a USC research professor of economics at the Center for Economic and Social Research (CESR) at the USC Dornsife College of Letters, Arts and Sciences, assessed the hurdles to providing these treatments to people with Alzheimer's disease in the United States, as well as in France, Germany, Italy, Spain and the United Kingdom.

"As the COVID-19 pandemic has taught us, even the most sophisticated healthcare systems can be overwhelmed by sudden surges in the demand for services," Mattke wrote. "The arrival of a disease-modifying treatment for Alzheimer's disease may result in a similar scenario, in which current health system capacity is insufficient to cope with the expected influx of patients who will seek diagnosis and treatment."

He and co-author Mo Wang, a research assistant at USC Dornsife, found that the countries have various gaps in their healthcare systems that, if unaddressed, make it difficult for many patients to access treatments once they have been approved for use. Mattke, a physician and health services researcher who directs the CESR Center for Improving Chronic Disease Care, focused on problems in the countries' healthcare systems, as well as in their capacity and their capabilities to deliver treatment.

While these countries' systems differ in many ways, they have some problems in common, including a lack of funding for memory testing that would help identify people who have Alzheimer's disease and, with the exception of Germany, a shortage of specialists trained in cognitive testing.

Mattke gathered the information for the reports by conducting 30 expert interviews and examining multiple databases, research published in peer-reviewed journals and technical reports.

Some of the health system barriers likely to impede access to treatment include:

Funding: While all countries have or are in the process of developing national dementia strategies, none have devoted funding to implement the recommendations. Further, several diagnostic tests that are part of the patient journey are not or not fully covered by health systems. It is assumed, but by no means guaranteed, that the approval of a treatment would lead to coverage of the necessary tests.

Workforce: Primary care physicians in all countries remain reluctant to assess cognitive function, because of incompatibility with their workflows, lack of training and tools, and a perceived lack of therapeutic consequences. Dementia specialists are in short supply in all countries, leading to lengthy wait times in the diagnostic process. The United States has 8.8 such specialists per 100,000 people and France has the fewest in the group with 6.5 per 100,000. While Germany leads the pack with 24 specialists per 100,000 people, incentives are lacking for those clinicians to increase patient volume. see more patients.

Technology: Countries have limited capacity to conduct PET brain scans to diagnose Alzheimer's disease. Not even the United States, with five PET scanners per 1 million people, would have sufficient capacity and many patients in rural areas would face geographic obstacles. Countries like France, Germany and Spain have only about two scanners per 1 million people and the U.K. only 0.5.

While these findings point to a need to devote additional resources to memory care, engage primary care physicians in case finding and triage and leverage scarce dementia specialists' time more effectively, there are encouraging initiatives in all six countries.

A simple blood test for Alzheimer's disease could become available soon, which would greatly improve the diagnostic process. diagnostics. France has set up a national network of memory clinics for routine care and for research. Germany introduced an annual comprehensive geriatric assessment including cognitive decline. Italy launched a program, the "Interceptor Project," to track patients with early stage Alzheimer's disease with the objective that doctors could identify patients at risk of faster progression. In Spain, an expert group formed a group to conduct regional assessment of system readiness for memory care and provide recommendations. The U.K. initiated an accreditation scheme to standardize memory services. In the U.S., Project ECHO is experimenting with telehealth models to empower primary care clinicians to provide memory care.

"Alzheimer's disease poses a unique challenge because so many different clinicians and planners must work together to prepare for the advent of a disease-modifying treatment," Mattke said. "A concerted effort of stakeholders will be needed to raise awareness for this challenge and work on solutions. Unlike in the COVID-19 pandemic, there is still time for healthcare systems to prepare. But, the work needs to start now."

Researchers have solved a major problem for optical wireless communications - the process by which light carries information between cell phones and other devices. Light-emitting diodes (LEDs) pulse their light in a coded message that recipient devices can understand.

Now, a team of researchers based in Japan has married the two options into the ideal combination of long lasting and fast LEDs. They published their results on July 22 in Applied Physics Letters.

“A key technology for faster modulation is to decrease the device size,” said paper author Kazunobu Kojima, associate professor at the Institute of Multidisciplinary Research for Advanced Materials at Tohoku University. “However, this tactic creates a dilemma: although smaller LEDs can be modulated faster, they have lower power.”

Another issue is that both visible and infrared optical wireless communications can have significant solar interference, according to Kojima. To avoid confusion with visible and infrared solar light, the researchers aimed to improve LEDs that specifically communicate via deep ultraviolet light, which can be detected without solar interference.

"Deep ultraviolet LEDs are currently mass produced in factories for applications related to COVID-19," Kojima said, noting that deep ultraviolet light is used for sterilization processes as well as in solar-blind optical wireless communications. "So, they're cheap and practical to use."

The researchers fabricated the deep ultraviolet LEDs on sapphire templates, which are considered an inexpensive substrate, and measured their transmission speed. They found that the deep ultraviolet LEDs were smaller and much quicker in their communications than traditional LEDs at that speed.

"The mechanism underlying this speed is in how a lot of tiny LEDs self-organize in a single deep ultraviolet LED," Kojima said. "The tiny LED ensemble helps with both power and speed."

The researchers want to use the deep ultraviolet LEDs in 5G wireless networks. Many technologies are currently under testing to contribute 5G, and Li-Fi, or light fidelity, is one of the candidate technologies.

"Li-Fi's critical weakness is its solar dependency," Kojima said. "Our deep ultraviolet LED-based optical wireless technology can compensate for this problem and contribute to society, I hope."