Computers Math

Artificial intelligence that enhances remote monitoring of water bodies — highlighting quality shifts due to climate change or pollution — has been developed by researchers at the University of Stirling.
A new algorithm — known as the ‘meta-learning’ method — analyses data directly from satellite sensors, making it easier for coastal zone, environmental and industry managers to monitor issues such as harmful algal blooms (HABs) and possible toxicity in shellfish and finfish.
Environmental protection agencies and industry bodies currently monitor the ‘trophic state’ of water — its biological productivity — as an indicator of ecosystem health. Large clusters of microscopic algae, or phytoplankton, is called eutrophication and can turn into HABs, an indicator of pollution and which pose risk to human and animal health.
HABs are estimated to cost the Scottish shellfish industry £1.4 million per year, and a single HAB event in Norway killed eight million salmon in 2019, with a direct value of over £74 million.
Lead author Mortimer Werther, a PhD Researcher in Biological and Environmental Sciences at Stirling’s Faculty of Natural Sciences, said: “Currently, satellite-mounted sensors, such as the Ocean and Land Instrument (OLCI), measure phytoplankton concentrations using an optical pigment called chlorophyll-a. However, retrieving chlorophyll-a across the diverse nature of global waters is methodologically challenging.
“We have developed a method that bypasses the chlorophyll-a retrieval and enables us to estimate water health status directly from the signal measured at the remote sensor.”
Eutrophication and hypereutrophication is often caused by excessive nutrient input, for example from agricultural practices, waste discharge, or food and energy production. In impacted waters, HABs are common, and cyanobacteria may produce cyanotoxins which affect human and animal health. In many locations, these blooms are of concern to the finfish and shellfish aquaculture industries.
Mr Werther said: “To understand the impact of climate change on freshwater aquatic environments such as lakes, many of which serve as drinking water resources, it is essential that we monitor and assess key environmental indicators, such as trophic status, on a global scale with high spatial and temporal frequency.
“This research, funded by the European Union’s Horizon 2020 programme, is the first demonstration that trophic status of complex inland and nearshore waters can be learnt directly by machine learning algorithms from OLCI reflectance measurements. Our algorithm can produce estimates for all trophic states on imagery acquired by OLCI over global water bodies.
“Our method outperforms a comparable state-of-the-art approach by 5-12% on average across the entire spectrum of trophic states, as it also eliminates the need to choose the right algorithm for water observation. It estimates trophic status with over 90% accuracy for highly affected eutrophic and hypereutrophic waters.”
The collaborative study was carried out with five external partners from research and industry: Dr. Stefan G.H. Simis from Plymouth Marine Laboratory; Harald Krawczyk from the German Aerospace Center; Dr. Daniel Odermatt from the Swiss Federal Institute of Aquatic Science and Technology; Kerstin Stelzer from Brockmann Consult and Oberon Berlage from Appjection (Amsterdam).
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Materials provided by University of Stirling. Note: Content may be edited for style and length. More

A year into the COVID-19 pandemic, mass vaccinations have begun to raise the tantalizing prospect of herd immunity that eventually curtails or halts the spread of SARS-CoV-2. But what if herd immunity is never fully achieved — or if the mutating virus gives rise to hyper-virulent variants that diminish the benefits of vaccination?
Those questions underscore the need for effective treatments for people who continue to fall ill with the coronavirus. While a few existing drugs show some benefit, there’s a pressing need to find new therapeutics.
Led by The University of New Mexico’s Tudor Oprea, MD, PhD, scientists have created a unique tool to help drug researchers quickly identify molecules capable of disarming the virus before it invades human cells or disabling it in the early stages of the infection.
In a paper published this week in Nature Machine Intelligence, the researchers introduced REDIAL-2020, an open source online suite of computational models that will help scientists rapidly screen small molecules for their potential COVID-fighting properties.
“To some extent this replaces (laboratory) experiments, says Oprea, chief of the Translational Informatics Division in the UNM School of Medicine. “It narrows the field of what people need to focus on. That’s why we placed it online for everyone to use.”
Oprea’s team at UNM and another group at the University of Texas at El Paso led by Suman Sirimulla, PhD, started work on the REDIAL-2020 tool last spring after scientists at the National Center for Advancing Translational Sciences (NCATS) released data from their own COVID drug repurposing studies. More

The human world is, increasingly, an urban one — and that means elevators. Hong Kong, the hometown of physicist Zhijie Feng (Boston University),* adds new elevators at the rate of roughly 1500 every year…making vertical transport an alluring topic for quantitative research.
“Just in the main building of my undergraduate university, Hong Kong University of Science and Technology,” Feng reflects, “there are 37 elevators, all numbered so we can use them to indicate the location of hundreds of classrooms. There is always a line outside each elevator lobby, and if they are shut down, we have to hike for 30 minutes.”
Feng and Santa Fe Institute Professor Sidney Redner saw this as an opportunity to explore the factors that determine elevator transport capabilities. In their new paper in the Journal of Statistical Mechanics, they begin by making a deliberately simple “toy” model.
“Engineers have already developed computational models for simulating elevators as realistically as possible,” says Feng. “Instead, we wanted insight into basic mechanisms, using just enough parameters to describe what we see in a way we can fully understand.”
Their minimum-variable simulation makes six key assumptions: unoccupied buildings, first-come-first-served transport, identical elevators traveling to uniformly distributed destination floors, 2.5 seconds to enter or exit elevators, and one second to travel from one floor to the next.
For a 100-story building with one idealized infinite-capacity elevator, Feng and Redner find that waiting times typically fall between five and seven minutes. With elevators that can carry 20 people each, and buildings that hold 100 workers per floor, this cycle requires 500 trips over 2 hours — or 21 elevators — to get everyone to work on time.
“If the elevators are uncorrelated,” the authors write, wait time “should equal the single elevator cycle time divided by the number of elevators, which is roughly 15 seconds.” However, this efficient spacing of elevators doesn’t last: as passenger demand increases, elevators start to move in lockstep, creating traffic jams in the lobby below until multiple elevators arrive back on the ground floor at the same time.
These nonlinear dynamics stymie any easy answer to the question of how long a person has to wait. But to Feng and Redner this is just the entry-level to a bigger inquiry. “I hope our work could be a ‘pocket version’ model to extend from,” Feng remarks. She credits Redner’s textbook, which she read in her early undergraduate days, for inspiring her love of breaking down complex problems into simple models.
Some of the further questions they identify include, “If a building tapers with height, is there a taper angle that minimizes waiting time but optimizes office space?”; and, “What if some elevators only service certain floors, and others service different floors?”
Food for thought next time you’re waiting in the lobby…
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Materials provided by Santa Fe Institute. Note: Content may be edited for style and length. More

Social media may make it easier for people to engage online, but I does not provide certain benefits of real-life human interactions, says a Michigan State University researcher.
“Problematic social media use has been associated with depression, anxiety and social isolation, and having a good social support system helps insulate people from negative mental health,” said Dar Meshi, an assistant professor in the Department of Advertising and Public Relations at MSU. “We wanted to compare the differences between real-life support and support provided over social media to see if the support provided over social media could have beneficial effects.”
The research was published online April 29 in the journal Addictive Behaviors.
While social media support did not negatively impact mental health, it did not positively affect it either.
“Only real-life social support was linked to better overall mental health,” Meshi said. “Typical interactions over social media are limited. We theorize that they don’t allow for more substantial connection, which may be needed to provide the type of support that protects against negative mental health.”
Meshi and Morgan Ellithorpe, an assistant professor in the Department of Communication at the University of Delaware and a co-author on this paper, conducted a survey of 403 university students to identify how problematic their social media use was and their degree of social support in real-life and on social media.
By also using the PROMIS, or Patient-reported Outcomes Measurement Information System, scales for measuring depression, anxiety and social isolation, the researchers could see how the students’ social media use and social support related to their mental health.
Problematic social media use is not a recognized addictive disorder, but there are similarities in the symptoms of someone with a substance use disorder and a person displaying excessive social media use. Examples include preoccupation with social media and signs of withdrawal, such as irritability, when prevented from using social media.
“It appears that the more excessive one’s social media use is, the less social support that person gets in real life, which leads to poor mental health,” Ellithorpe said.
Meshi and Ellithorpe encourage people who are using too much social media to reach out to people in real life for social support.
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Materials provided by Michigan State University. Original written by Emilie Lorditch. Note: Content may be edited for style and length. More

“Image” is everything in the $20 billion market for AR/VR glasses. Consumers are looking for glasses that are compact and easy to wear, delivering high-quality imagery with socially acceptable optics that don’t look like “bug eyes.”
University of Rochester researchers at the Institute of Optics have come up with a novel technology to deliver those attributes with maximum effect. In a paper in Science Advances, they describe imprinting freeform optics with a nanophotonic optical element called “a metasurface.”
The metasurface is a veritable forest of tiny, silver, nanoscale structures on a thin metallic film that conforms, in this advance, to the freeform shape of the optics — realizing a new optical component the researchers call a metaform.
The metaform is able to defy the conventional laws of reflection, gathering the visible light rays entering an AR/VR eyepiece from all directions, and redirecting them directly into the human eye.
Nick Vamivakas, a professor of quantum optics and quantum physics, likened the nanoscale structures to small-scale radio antennas. “When we actuate the device and illuminate it with the right wavelength, all of these antennas start oscillating, radiating a new light that delivers the image we want downstream.”
“Metasurfaces are also called ‘flat optics’ so writing metasurfaces on freeform optics is creating an entirely new type of optical component,” says Jannick Rolland, the Brian J. Thompson Professor of Optical Engineering and director of the Center for Freeform Optics. More

According to Michael Twidale, professor in the School of Information Sciences at the University of Illinois Urbana-Champaign, bad usability can be an irritation for everyone but “especially awful” for the underprivileged. In “Everyone Everywhere: A Distributed and Embedded Paradigm for Usability,” which was recently published in the Journal of the Association for Information Science and Technology (JASIST), Twidale and coauthors David M. Nichols (University of Waikato, New Zealand) and Christopher P. Lueg (Bern University of Applied Sciences, Switzerland) present a new paradigm to address the persistence of difficulties that people have in accessing and using information.
Twidale points to the COVID vaccination rollout as one recent example of bad usability. In many places, people have to book their vaccine appointments online, which can be difficult for the especially vulnerable elderly population.
“When hard to use software means a vulnerable elderly person cannot book a vaccination, that’s a social justice issue,” he said. “If you can’t get things to work, it can further exclude you from the benefits that technology is bringing to everyone else. Making a computer system easier to use is a tiny fraction of the cost of making the computer system work at all. So why aren’t things fixed? Because people put up with bad interfaces and blame themselves. We want to say, ‘No, it’s not your fault! It is bad design.'”
Twidale and his coauthors propose expanding awareness of usability and distributing the topic across disciplines, beyond the “tiny elite” of usability professions. In turn, this increased emphasis on usability could lead to improvements in other disciplines such as politics (e.g., better ballot design) and medicine (e.g., user-friendly medical devices).
“A wider usability movement would remind members of any profession that regardless of their domain and efforts in making the world a better place, bad usability makes everything worse. In contrast, reducing bad usability is often a relatively low-cost way of contributing to improvements within these professions.”
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Materials provided by University of Illinois School of Information Sciences. Note: Content may be edited for style and length. More

In 2018, industry and academic researchers revealed a potentially devastating hardware flaw that made computers and other devices worldwide vulnerable to attack.
Researchers named the vulnerability Spectre because the flaw was built into modern computer processors that get their speed from a technique called “speculative execution,” in which the processor predicts instructions it might end up executing and preps by following the predicted path to pull the instructions from memory. A Spectre attack tricks the processor into executing instructions along the wrong path. Even though the processor recovers and correctly completes its task, hackers can access confidential data while the processor is heading the wrong way.
Since Spectre was discovered, the world’s most talented computer scientists from industry and academia have worked on software patches and hardware defenses, confident they’ve been able to protect the most vulnerable points in the speculative execution process without slowing down computing speeds too much.
They will have to go back to the drawing board.
A team of University of Virginia School of Engineering computer science researchers has uncovered a line of attack that breaks all Spectre defenses, meaning that billions of computers and other devices across the globe are just as vulnerable today as they were when Spectre was first announced. The team reported its discovery to international chip makers in April and will present the new challenge at a worldwide computing architecture conference in June.
The researchers, led by Ashish Venkat, William Wulf Career Enhancement Assistant Professor of Computer Science at UVA Engineering, found a whole new way for hackers to exploit something called a “micro-op cache,” which speeds up computing by storing simple commands and allowing the processor to fetch them quickly and early in the speculative execution process. Micro-op caches have been built into Intel computers manufactured since 2011. More

Researchers have developed a brain-like computing device that is capable of learning by association.
Similar to how famed physiologist Ivan Pavlov conditioned dogs to associate a bell with food, researchers at Northwestern University and the University of Hong Kong successfully conditioned their circuit to associate light with pressure.
The research will be published April 30 in the journal Nature Communications.
The device’s secret lies within its novel organic, electrochemical “synaptic transistors,” which simultaneously process and store information just like the human brain. The researchers demonstrated that the transistor can mimic the short-term and long-term plasticity of synapses in the human brain, building on memories to learn over time.
With its brain-like ability, the novel transistor and circuit could potentially overcome the limitations of traditional computing, including their energy-sapping hardware and limited ability to perform multiple tasks at the same time. The brain-like device also has higher fault tolerance, continuing to operate smoothly even when some components fail.
“Although the modern computer is outstanding, the human brain can easily outperform it in some complex and unstructured tasks, such as pattern recognition, motor control and multisensory integration,” said Northwestern’s Jonathan Rivnay, a senior author of the study. “This is thanks to the plasticity of the synapse, which is the basic building block of the brain’s computational power. These synapses enable the brain to work in a highly parallel, fault tolerant and energy-efficient manner. In our work, we demonstrate an organic, plastic transistor that mimics key functions of a biological synapse.”
Rivnay is an assistant professor of biomedical engineering at Northwestern’s McCormick School of Engineering. He co-led the study with Paddy Chan, an associate professor of mechanical engineering at the University of Hong Kong. Xudong Ji, a postdoctoral researcher in Rivnay’s group, is the paper’s first author. More