Saturday, January 14, 2023

Plant-based diets: What are they, and how do you start?

by Kirstie Ganobsik

As Americans struggle to eat better, plant-based diets have become the rage, but exactly what are those and how hard are they to follow?

A growing number of people have turned to plant-based eating, as evidenced by the fact that the plant-based foods market increased by 29% in recent years, according to the U.S. National Library of Medicine.

Still, even though the Physicians Committee for Responsible Medicine says there are many health benefits to plant-based eating patterns, making the switch from consuming a diet rich in meat to one that centers on plants can be a challenge.

What is a plant-based diet?

"When we talk about a whole foods, plant-based diet, we mean the majority (at least 80% to 90%) of the food should be unprocessed plant-based foods—things like legumes, fruits, vegetables, seeds, whole grains and nuts," Dr. Urvi Shah, a hematologist oncologist at Memorial Sloan Kettering Cancer Center, said in a recent blog post.

"Some people may end up eating minimal amounts of processed plant foods or animal-based foods like dairy or meat occasionally, but not on a regular basis," she added.

Fruits, vegetables, grains, dairy, seeds, fish and meat that contain a variety of micronutrients (vitamins and minerals) and macronutrients (protein, carbohydrates and fat) should be included in a plant-based diet, according to a perspective published in the journal Advances in Nutrition.

The key is to ensure that the largest proportion of your food comes from plants, Harvard Health notes.

Plant-based vs. vegan vs. vegetarian: What's the difference?

The United States Department of Agriculture (USDA) names different levels of vegetarian eating patterns, including vegan, lacto-ovo vegetarian and pescatarian diets. The key difference between all these eating plans and a plant-based diet is that only the latter includes small amounts of meat.

"I tell patients that vegan means zero animal products and is grounded in ethical or environmental or health reasons for a person who has decided very clearly what they want. A vegetarian diet may have similar reasons, but allows dairy or eggs in varying proportions," said Shah.

"A whole foods, plant-based diet can be similar to a Mediterranean diet or other diets that include eating meat rarely. Again, the majority (90%) of foods should be whole plant-based foods," she added.

Plant-based diet health benefits

A review published in the journal JAMA Oncology by Shah and her colleague at Sloan Kettering, medical oncologist Dr. Neil Iyengar, found that evidence supports plant-based diets for reducing cancer risk and improving metabolic disorders.

Better heart health may be another benefit of plant-centered eating. The American Heart Association (AHA) recently published a study in the Journal of the American Heart Association that revealed that young people who eat a plant-centered diet reduced their risk for stroke, heart attack, and other cardiovascular conditions in middle age.

"A nutritionally rich, plant-centered diet is beneficial for cardiovascular health," study author Yuni Choi, a postdoctoral researcher at the University of Minnesota School of Public Health, said about the study.

Plant-based diets have also been shown to help control type 2 diabetes and obesity, and were linked to lower mortality risk, according to a study published recently in JAMA Internal Medicine.

How to start a plant-based diet

The plant-based eating plans that are recommended by the AHA in its 2021 Dietary Guidance Scientific Statement include the Mediterranean diet and the Dietary Approaches to Stop Hypertension (DASH) diet.

The USDA also recommends these two plant-based eating patterns to meet its daily dietary nutritional recommendations.

"We hope Americans can find ways to "Start Simple' and incorporate modest changes each day," Sonny Perdue, then Secretary of the USDA, and Alex Azar, then Secretary of the U.S. Department of Health and Human Services, said in the forward to the 2020-2025 USDA Dietary Guidelines for Americans.

Here are key foods that are part of these plant-based diets:

Green leafy vegetables like spinach, turnips, green leaf lettuce and kale
Red, orange and starchy vegetables, including bell peppers, carrots, corn, and whole potatoes
Whole grains such as brown rice, barley, wheat and oats
Whole fruits like bananas, berries, oranges and raisins
Dairy, including yogurt, dairy milk, and low-fat sour cream
Unsaturated oil, including olive and sunflower oils
A variety of plant-based proteins, including beans, legumes, seeds, soy, mushrooms, nuts and broccoli
Limited amounts of protein from meat, fish, eggs, cheese and low-fat poultry

Journal information: JAMA Oncology\
, Journal of the American Heart Association , JAMA Internal Medicine

What could a plant-based diet do for you?

Preterm birth linked to chemicals found in the vagina

by Columbia University Irving Medical Center

Chemicals that accumulate in the vagina, potentially originating from personal care products, may contribute to spontaneous preterm birth, according to a new study by researchers at Columbia University Vagelos College of Physicians and Surgeons.

The study of 232 pregnant women found that a handful of non-biological chemicals previously found in cosmetics and hygiene products are strongly associated with preterm birth.

"Our findings suggest that we need to look more closely at whether common environmental exposures are in fact causing preterm births and, if so, where these exposures are coming from," says study co-leader Tal Korem, Ph.D., assistant professor in the Program for Mathematical Genomics and the Departments of Systems Biology and Obstetrics and Gynecology at Columbia. "The good news is that if these chemicals are to blame, it may be possible to limit these potentially harmful exposures."

The study was published January 12 in Nature Microbiology.

Preterm birth, childbirth before 37 weeks of pregnancy, is the number one cause of neonatal death and can lead to a variety of lifelong health issues. Two-thirds of preterm births occur spontaneously, but despite extensive research, there are no methods for predicting or preventing spontaneous preterm birth.

Several studies have suggested that imbalances in the vaginal microbiome play a role in preterm birth and other problems during pregnancy. However, researchers have not been able to reproducibly link specific populations of microorganisms with adverse pregnancy outcomes.

The research team, co-led by Korem and Maayan Levy, Ph.D., of the University of Pennsylvania, decided to take a more expansive view of the vaginal microenvironment by looking at its metabolome. The metabolome is the complete set of small molecules found in a particular biological niche, including metabolites produced by local cells and microorganisms and molecules that come from external sources. "The metabolome can be seen as a functional readout of the ecosystem as a whole," Korem says. "Microbiome profiling can tell us who the microbes are; metabolomics gets us close to understanding what the microbes are doing."

In the current study, the researchers measured over 700 different metabolites in the second-trimester metabolome of 232 pregnant women, including 80 pregnancies that ended prematurely.

The study found multiple metabolites that were significantly higher in women who had delivered early than in those who delivered at full term.

"Several of these metabolites are chemicals that are not produced by humans or microbes—what we call xenobiotics," says Korem. "These include diethanolamine, ethyl-beta glucoside, tartrate, and ethylenediaminetetraacetic acid. While we did not identify the source of these xenobiotics in our participants, all could be found in cosmetics and hygiene products."

Algorithm predicts preterm birth

Using machine learning models, the team also developed an algorithm based on metabolite levels that can predict preterm birth with good accuracy, potentially paving the way for early diagnostics.

Though the predictions were more accurate than models based on microbiome data and maternal characteristics (such as age, BMI, race, preterm birth history, and prior births), the new model still needs improvement and further validation before it could be used in the clinic.

Despite the current limitations, Korem says, "our results demonstrate that vaginal metabolites have the potential to predict, months in advance, which women are likely to deliver early."

More information: William F. Kindschuh et al, Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome, Nature Microbiology (2023). DOI: 10.1038/s41564-022-01293-8

Journal information: Nature Microbiology

Provided by Columbia University Irving Medical Center

Hormonal treatment in pregnancy won't lower odds for preterm birth

https://libcom.org/article/our-synthetic-environment-murray-bookchin

Our Synthetic Environment - Murray Bookchin - Libcom.org

Our Synthetic Environment was one of the first books of the modern period in which an author espoused an ecological and environmentalist worldview. It predates ...

Adopting pediatric readiness standards found to improve survival in hospital emergency departments

by NIH/Eunice Kennedy Shriver National Institute of Child Health and Human Development

emergency room — Credit: Pixabay/CC0 Public Domain

Emergency departments that have the highest levels of coordination of health care, personnel, procedures and medical equipment needed to care for ill and injured children have far higher rates of survival than hospitals with low readiness, according to a new study.

Researchers found that more than 1,400 children's deaths may have been prevented if hospital emergency departments had adopted national pediatric care readiness standards as laid out by the National Pediatric Readiness Project. The six-year study of 983 emergency departments in 11 states followed nearly 800,000 children.

The National Pediatric Readiness Project was established to ensure that all emergency departments have the coordination of health care, personnel, procedures and medical equipment needed to care for ill and injured children. According to the project's checklist, standards include specifications for physician and nurse certification, patient assessment, triage, medication administration, and trauma resuscitation and stabilization.

In the current study, researchers sought to determine if adopting the readiness standards would lower the death rate among children admitted to emergency departments for serious injury or illness. They ranked the emergency departments into four segments (quartiles) according to the extent they had implemented the readiness standards.

Compared to children cared for in low-readiness departments, children with injuries cared for in high-readiness departments had a 60% lower chance of dying in the hospital; and children with medical illness had a 76% lower chance of dying while they were in the hospital. Similarly, among roughly 545,000 children in six states, injured children in the highest quartile had a 41% lower chance of dying within a year and children with medical issues had a 66% lower chance of dying within a year, compared to children cared for in hospitals in the lowest readiness quartile.

The study was conducted by Craig D. Newgard, M.D., of Oregon Health & Science University, Portland, and colleagues. It appears in JAMA Network Open.

More information: Craig D. Newgard et al, Emergency DepartmentPediatricReadiness and Short-term and Long-termMortality Among ChildrenReceiving Emergency Care, JAMA Network Open (2023). DOI: 10.1001/jamanetworkopen.2022.50941

Journal information: JAMA Network Open Provided by NIH/Eunice Kennedy Shriver National Institute of Child Health and Human Development Child death rate linked to hospital preparedness for pediatric emergencies

U$ Health insurance drives medical advances, claims new study

by International Institute for Applied Systems Analysis

A new study argues that expanding health insurance coverage can drive medical progress, support well-being, and even extend lifespan in the United States.

There is a long-standing debate on whether rolling out health insurance toward high levels of coverage is desirable. For countries with non-existent or only patchy coverage, expanding health insurance would certainly be beneficial. However, in high-income settings where basic coverage is already granted the question remains open.

In a collaborative effort, IIASA Economic Frontiers Program Director, Michael Kuhn, and Ivan Frankovic, now an economist at the Deutsche Bundesbank, analyzed the macroeconomic impact of health insurance expansion in the United States between 1965 and 2005. The study, which has been published in the Journal of Health Economics, used an overlapping generations model of an economy looking at three sectors: final goods production, health care, and medical research and development (R&D).

"This work is the first to tackle the link between health insurance expansion, medical progress, and well-being in a coherent and rigorous analytical model for the United States," says Kuhn. "Our model allows for a thorough integrated assessment of the underlying mechanisms and, as the first of its kind, an assessment of the implications for well-being when individuals do not only care about consumption, but also about their health and longevity."

The authors found that the expansion of health insurance explains about 63% of the increase in health care expenditure and that it was also responsible for a 57% boost to the growth rate of medical patent registrations. Moreover, the expansion of health insurance increased life expectancy by an extra 1.2 years in 2005, mainly due to the stimulation of medical progress.

"The knock-on effects of health insurance on medical progress are relevant both in terms of magnitude and their significant positive impact on well-being," explains Frankovic. "Such effects should be taken into account during policymaking, for example, in the form of an extended cost-benefit analysis."

A side effect of health insurance expansion is that generous health insurance coverage may stimulate the excessive consumption of health care beyond what is really needed, especially by the elderly generation to the detriment of the younger, working-age generation. However, the researchers found that these losses were compensated by the gains in life expectancy and productivity in the younger generations.

"Our analysis demonstrates the importance of taking a broader well-being-oriented and systemic stance when evaluating health care policies," says Kuhn. "One needs to look beyond what might be short-term losses due to excessive consumption and consider the stimulus a high demand for medical care creates for R&D, resulting in new medical treatments."

More information: Ivan Frankovic et al, Health insurance, endogenous medical progress, health expenditure growth, and welfare, Journal of Health Economics (2023). DOI: 10.1016/j.jhealeco.2022.102717

Journal information: Journal of Health Economics

Provided by International Institute for Applied Systems Analysis

Medicaid expansion linked to gains in insurance coverage

All-out drone war in Ukraine points to future

by W.G. Dunlop

*A Turkish-made Bayraktar -- a type of drone used extensively by Ukrainian forces.*

Deployed on a scale never seen before to carry out both surveillance and strikes, drones ranging from small commercially-available models to larger aircraft have become a defining feature of the Ukraine conflict.

Drones have been a part of warfare for years, employed extensively by the United States during the "War on Terror," and they have played important roles in conflicts including in Iraq and in the Nagorno-Karabakh region.

But the degree to which they are being used by both sides in Ukraine—and the benefits they bring, as well as the threats they pose—highlights the importance for militaries to be ready to employ and to counter drones in future conflicts.

"The size and the scale of drone use in Ukraine supersedes all the previous conflicts," said Samuel Bendett, a researcher in uncrewed military systems who is an analyst with the CNA Russia Studies Program.

Bendett stressed the "absolutely unprecedented use of commercial-type drones" for both surveillance and combat in Ukraine, and said the war has shown that "small... tactical drones are absolutely essential—at every unit, every platoon level, every company level."

"Because these are basically expendable with a very short shelf life, they have to be provided to the forces in very large quantities," he said.

*A drone approaches for an attack in Kyiv in October 2022.*

'Accessible and cheap'

Drones have played key roles from the earliest days of the conflict, with Ukrainian forces using Turkish-made Bayraktars to carry out strikes on Moscow's troops as they unsuccessfully sought to seize Kyiv.

Both sides are using drones to locate and track enemy forces as well as to direct artillery fire, and both are also employing "loitering munitions"—uncrewed aircraft equipped with explosive charges that detonate on impact.

Lauren Kahn, a research fellow at the Council on Foreign Relations, said the Ukraine war came at a time when "a lot of these technologies are maturing and coming of age" and are "accessible and cheap."

This allows for more experimentation, she said.

"Because they're so affordable, they're being used in a way that they're treated (as) much less precious," said Kahn, who focuses on the impact of emerging technologies on international security.

And it poses a challenge for defenders when drones are less expensive than the means used to bring them down, she said, citing Russian strikes on Ukrainian energy infrastructure with waves of drones provided by Iran.

"Better and more effective ways of countering drones, I think, is going to be... the next phase and next focus of development," Khan said, adding that there "needs to be a more economically feasible solution" to match the "cheapness of the offensive technology."

A Ukrainian serviceman poses with a drone on the outskirts of Bakhmut in December 2022 — *A Ukrainian serviceman poses with a drone on the outskirts of Bakhmut in*

'Absolutely paramount'

The war in Ukraine has served as a proving ground for counter-drone measures, and the United States has provided options to Kyiv ranging from machine guns to dedicated air defense systems.

Drones can be used in "creative and unique ways on the battlefield" and defending against them requires continued effort, Pentagon Press Secretary Brigadier General Pat Ryder said.

Bendett said electronic countermeasures are playing an important role for both sides in Ukraine.

"Both Russians and Ukrainians are now saying publicly that there are parts of the front where their military drones cannot operate, where their commercial drones can be jammed and rendered inoperable," he said.

While drones used to carry out strikes draw more popular attention, the surveillance capabilities of uncrewed aircraft can have a wider-reaching impact, making it more difficult for troops to escape notice by their enemies.

The conflict has shown that counter-drone "systems, technologies and training is absolutely paramount," Bendett said.

"Militaries have to adapt," he said. "They have to adapt to the fact that any belligerent right now and... in future wars may be equipped with the types of drones that we're seeing in Ukraine."

Ukraine war: Drones are transforming the conflict, bringing Russia on to the frontline

Computers that power self-driving cars could be a huge driver of global carbon emissions

by Massachusetts Institute of Technology

In the future, the energy needed to run the powerful computers on board a global fleet of autonomous vehicles could generate as many greenhouse gas emissions as all the data centers in the world today.

That is one key finding of a new study from MIT researchers that explored the potential energy consumption and related carbon emissions if autonomous vehicles are widely adopted.

The data centers that house the physical computing infrastructure used for running applications are widely known for their large carbon footprint: They currently account for about 0.3 percent of global greenhouse gas emissions, or about as much carbon as the country of Argentina produces annually, according to the International Energy Agency. Realizing that less attention has been paid to the potential footprint of autonomous vehicles, the MIT researchers built a statistical model to study the problem. They determined that 1 billion autonomous vehicles, each driving for one hour per day with a computer consuming 840 watts, would consume enough energy to generate about the same amount of emissions as data centers currently do.

The researchers also found that in over 90 percent of modeled scenarios, to keep autonomous vehicle emissions from zooming past current data center emissions, each vehicle must use less than 1.2 kilowatts of power for computing, which would require more efficient hardware. In one scenario—where 95 percent of the global fleet of vehicles is autonomous in 2050, computational workloads double every three years, and the world continues to decarbonize at the current rate—they found that hardware efficiency would need to double faster than every 1.1 years to keep emissions under those levels.

"If we just keep the business-as-usual trends in decarbonization and the current rate of hardware efficiency improvements, it doesn't seem like it is going to be enough to constrain the emissions from computing onboard autonomous vehicles. This has the potential to become an enormous problem. But if we get ahead of it, we could design more efficient autonomous vehicles that have a smaller carbon footprint from the start," says first author Soumya Sudhakar, a graduate student in aeronautics and astronautics.

Sudhakar wrote the paper with her co-advisors Vivienne Sze, associate professor in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Research Laboratory of Electronics (RLE); and Sertac Karaman, associate professor of aeronautics and astronautics and director of the Laboratory for Information and Decision Systems (LIDS). The research appears in the January-February issue of IEEE Micro.

Modeling emissions

The researchers built a framework to explore the operational emissions from computers on board a global fleet of electric vehicles that are fully autonomous, meaning they don't require a back-up human driver.

The model is a function of the number of vehicles in the global fleet, the power of each computer on each vehicle, the hours driven by each vehicle, and the carbon intensity of the electricity powering each computer.

"On its own, that looks like a deceptively simple equation. But each of those variables contains a lot of uncertainty because we are considering an emerging application that is not here yet," Sudhakar says.

For instance, some research suggests that the amount of time driven in autonomous vehicles might increase because people can multitask while driving and the young and the elderly could drive more. But other research suggests that time spent driving might decrease because algorithms could find optimal routes that get people to their destinations faster.

In addition to considering these uncertainties, the researchers also needed to model advanced computing hardware and software that doesn't exist yet.

To accomplish that, they modeled the workload of a popular algorithm for autonomous vehicles, known as a multitask deep neural network because it can perform many tasks at once. They explored how much energy this deep neural network would consume if it were processing many high-resolution inputs from many cameras with high frame rates, simultaneously.

When they used the probabilistic model to explore different scenarios, Sudhakar was surprised by how quickly the algorithms' workload added up.

For example, if an autonomous vehicle has 10 deep neural networks processing images from 10 cameras, and that vehicle drives for one hour a day, it will make 21.6 million inferences each day. One billion vehicles would make 21.6 quadrillion inferences. To put that into perspective, all of Facebook's data centers worldwide make a few trillion inferences each day (1 quadrillion is 1,000 trillion).

"After seeing the results, this makes a lot of sense, but it is not something that is on a lot of people's radar. These vehicles could actually be using a ton of computer power. They have a 360-degree view of the world, so while we have two eyes, they may have 20 eyes, looking all over the place and trying to understand all the things that are happening at the same time," Karaman says.

Autonomous vehicles would be used for moving goods, as well as people, so there could be a massive amount of computing power distributed along global supply chains, he says. And their model only considers computing—it doesn't take into account the energy consumed by vehicle sensors or the emissions generated during manufacturing.

Keeping emissions in check

To keep emissions from spiraling out of control, the researchers found that each autonomous vehicle needs to consume less than 1.2 kilowatts of energy for computing. For that to be possible, computing hardware must become more efficient at a significantly faster pace, doubling in efficiency about every 1.1 years.

One way to boost that efficiency could be to use more specialized hardware, which is designed to run specific driving algorithms. Because researchers know the navigation and perception tasks required for autonomous driving, it could be easier to design specialized hardware for those tasks, Sudhakar says. But vehicles tend to have 10- or 20-year lifespans, so one challenge in developing specialized hardware would be to "future-proof" it so it can run new algorithms.

In the future, researchers could also make the algorithms more efficient, so they would need less computing power. However, this is also challenging because trading off some accuracy for more efficiency could hamper vehicle safety.

Now that they have demonstrated this framework, the researchers want to continue exploring hardware efficiency and algorithm improvements. In addition, they say their model can be enhanced by characterizing embodied carbon from autonomous vehicles—the carbon emissions generated when a car is manufactured—and emissions from a vehicle's sensors.

While there are still many scenarios to explore, the researchers hope that this work sheds light on a potential problem people may not have considered.

"We are hoping that people will think of emissions and carbon efficiency as important metrics to consider in their designs. The energy consumption of an autonomous vehicle is really critical, not just for extending the battery life, but also for sustainability," says Sze.

More information: Soumya Sudhakar et al, Data Centers on Wheels: Emissions From Computing Onboard Autonomous Vehicles, IEEE Micro (2022). DOI: 10.1109/MM.2022.3219803

Provided by Massachusetts Institute of Technology

This story is republished courtesy of MIT News (web.mit.edu/newsoffice/), a popular site that covers news about MIT research, innovation and teaching.

Bolstering the safety of self-driving cars with a deep learning-based object detection system

New technique to turn abandoned mines into batteries

by International Institute for Applied Systems Analysis

Turning abandoned mines into batteries — Underground Gravity Energy Storage system: a schematic of different system

A novel technique called Underground Gravity Energy Storage turns decommissioned mines into long-term energy storage solutions, thereby supporting the sustainable energy transition.

Renewable energy sources are central to the energy transition toward a more sustainable future. However, as sources like sunshine and wind are inherently variable and inconsistent, finding ways to store energy in an accessible and efficient way is crucial. While there are many effective solutions for daily energy storage, the most common being batteries, a cost-effective long-term solution is still lacking.

In a new International Institute for Applied Systems Analysis (IIASA)-led study, an international team of researchers has developed a novel way to store energy by transporting sand into abandoned underground mines. The new technique, called Underground Gravity Energy Storage (UGES), proposes an effective long-term energy storage solution while also making use of now-defunct mining sites, which likely number in the millions globally.

The work is published in the journal Energies.

UGES generates electricity when the price is high by lowering sand into an underground mine and converting the potential energy of the sand into electricity via regenerative braking, and then lifting the sand from the mine to an upper reservoir using electric motors to store energy when electricity is cheap. The main components of UGES are the shaft, motor/generator, upper and lower storage sites, and mining equipment. The deeper and broader the mineshaft, the more power can be extracted from the plant, and the larger the mine, the higher the plant's energy storage capacity.

"When a mine closes, it lays off thousands of workers. This devastates communities that rely only on the mine for their economic output. UGES would create a few vacancies as the mine would provide energy storage services after it stops operations," says Julian Hunt, a researcher in the IIASA Energy, Climate, and Environment Program and the lead author of the study. "Mines already have the basic infrastructure and are connected to the power grid, which significantly reduces the cost and facilitates the implementation of UGES plants."

Other energy storage methods, like batteries, lose energy via self-discharge over long periods. The energy storage medium of UGES is sand, meaning that there is no energy lost to self-discharge, enabling ultra-long time energy storage ranging from weeks to several years.

The investment costs of UGES are about 1 to 10 USD/kWh and power capacity costs are about 2 USD/kW. The technology is estimated to have a global potential of 7 to 70 TWh, with most of this potential concentrated in China, India, Russia, and the U.S.

"To decarbonize the economy, we need to rethink the energy system based on innovative solutions using existing resources. Turning abandoned mines into energy storage is one example of many solutions that exist around us, and we only need to change the way we deploy them," concludes Behnam Zakeri, study co-author and a researcher in the IIASA Energy, Climate, and Environment Program.

More information: Julian David Hunt et al, Underground Gravity Energy Storage: A Solution for Long-Term Energy Storage, Energies (2023). DOI: 10.3390/en16020825

Provided by International Institute for Applied Systems Analysis

Researchers introduce new energy storage concept to turn high-rise buildings into batteries

SCIENCTIFICTION (SCI-FI)

Using cosmic rays to generate and distribute random numbers and boost security for local devices and networks

by University of Tokyo

Introducing COSMOCAT — *When both sender and receiver have identical random numbers, they can share*

State-of-the-art methods of information security are likely to be compromised by emerging technologies such as quantum computers. One of the reasons they are vulnerable is that both encrypted messages and the keys to decrypt them must be sent from sender to receiver.

A new method—called COSMOCAT—is proposed and demonstrated, which removes the need to send a decryption key since cosmic rays transport it for us, meaning that even if messages are intercepted, they could not be read using any theorized approach. COSMOCAT could be useful in localized various bandwidth applications, as there are limitations to the effective distance between sender and receiver.

In the field of information communication technology, there is a perpetual arms race to find ever more secure ways to transfer data, and ever more sophisticated ways to break them. Even the first modern computers were essentially code-breaking machines used by the U.S. and European Allies during World War II. And this race is about to enter a new regime with the advent of quantum computers, capable of breaking current forms of security with ease. Even security methods which use quantum computers themselves might be susceptible to other quantum attacks.

"Basically, the problem with our current security paradigm is that it relies on encrypted information and keys to decrypt it both being sent along a network from sender to receiver," said Professor Hiroyuki Tanaka from Muographix at the University of Tokyo.

"Regardless of the way messages are encrypted, in theory someone eavesdropping could use the keys to decode the secure messages eventually. Quantum computers just make this process faster. If we dispense with this idea of sharing keys and could instead find some way of using unpredictable random numbers to encrypt information, then it should lead to a system immune to interception. And I happen to work often with a source capable of generating truly random unpredictable numbers: cosmic rays from outer space."

Various random number generators have been tried over time, but the problem is how to share these random numbers while avoiding interception. Cosmic rays may hold the answer, as one of their byproducts, muons, are statistically random in their arrival times at the ground. Muons also travel close to the speed of light and penetrate solid matter easily.

This means that as long as we know the distance between the sender's detector and the receiver's detector, the time required for muons to travel from the sender to the receiver can be precisely calculated. And providing that a pair of devices are sufficiently synchronized, the muons' arrival time could serve as a secret key for both encoding and decoding a packet of data. But this key never has to leave the sender's device, as the receiving machine should automatically have it as well. This would plug the security hole presented by sending shared keys.

"I call the system Cosmic Coding and Transfer, or COSMOCAT," said Tanaka. "It could be used alongside or in place of current wireless communications technologies such as Wi-Fi, Bluetooth, near-field communication (NFC), and more. And it can exceed speeds possible with current encrypted Bluetooth standards. However, the distance it can be used at is limited; hence, it's ideally kept to small local networks, for example, within a building. I believe COSMOCAT is ready to be adopted by commercial applications."

At present, the muon-detecting apparatus are relatively large and require more power than other local wireless communication components. But as technology improves and the size of this apparatus can be reduced, it might soon be possible to install COSMOCAT in high-security offices, data centers and other local area networks

The work is published in the journal iScience.

More information: Hiroyuki K.M. Tanaka, Cosmic Coding and Transfer (COSMOCAT) for Ultra High Security Near-Field Communications, iScience (2023). DOI: 10.1016/j.isci.2022.105897

Journal information: iScience

Provided by University of Tokyo

Explore further

Measurement-device-independent quantum communication without encryption

Provided by University of Tokyo Measurement-device-independent quantum communication without encryption

AI improves detail, estimate of urban air pollution

by Blaine Friedlander, Cornell University

Using artificial intelligence, Cornell engineers have simplified and reinforced models that accurately calculate the fine particulate matter (PM2.5)—the soot, dust and exhaust emitted by trucks and cars that get into human lungs—contained in urban air pollution.

Now, city planners and government health officials can obtain a more precise accounting about the well-being of urban dwellers and the air they breathe, from new research published December 2022 in Transportation Research Part D.

"Infrastructure determines our living environment, our exposure," said senior author Oliver Gao, the Howard Simpson Professor of Civil and Environmental Engineering in the College of Engineering. "Air pollution impact due to transportation—put out as exhaust from the cars and trucks that drive on our streets—is very complicated. Our infrastructure, transportation and energy policies are going to impact air pollution and hence public health."

Previous methods to gauge air pollution were cumbersome and reliant on extraordinary amounts of data points. "Older models to calculate particulate matter were computationally and mechanically consuming and complex," said Gao, a faculty fellow at the Cornell Atkinson Center for Sustainability. "But if you develop an easily accessible data model, with the help of artificial intelligence filling in some of the blanks, you can have an accurate model at a local scale."

Lead author Salil Desai '20, M.Eng. '21 and visiting scientist Mohammad Tayarani, together with Gao, published "Developing Machine Learning Models for Hyperlocal Traffic Related Particulate Matter Concentration Mapping," to offer a leaner, less data-intensive method for making accurate models.

Ambient air pollution is a leading cause of premature death around the world. Globally, more than 4.2 million annual fatalities—in the form of cardiovascular disease, ischemic heart disease, stroke and lung cancer—were attributed to air pollution in 2015, according to a Lancet study cited in the Cornell research.

In this work, the group developed four machine learning models for traffic-related particulate matter concentrations in data gathered in New York City's five boroughs, which have a combined population of 8.2 million people and a daily-vehicle miles traveled of 55 million miles.

The equations use few inputs such as traffic data, topology and meteorology in an AI algorithm to learn simulations for a wide range of traffic-related, air-pollution concentration scenarios.

Their best performing model was the Convolutional Long Short-term Memory, or ConvLSTM, which trained the algorithm to predict many spatially correlated observations.

"Our data-driven approach—mainly based on vehicle emission data—requires considerably fewer modeling steps," Desai said. Instead of focusing on stationary locations, the method provides a high-resolution estimation of the city street pollution surface. Higher resolution can help transportation and epidemiology studies assess health, environmental justice and air quality impacts.

More information: Salil Desai et al, Developing Machine learning models for hyperlocal traffic related particulate matter concentration mapping, Transportation Research Part D: Transport and Environment (2022). DOI: 10.1016/j.trd.2022.103505

Journal information: The Lancet

Provided by Cornell University New approach better predicts air pollution models' performance in health studies

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