The Basalt Vista community, nestled high in the mountains in Basalt, Colorado, is about to get a whole lot smarter in the pursuit of energy efficiency and renewable energy integration.
The National Renewable Energy Laboratory (NREL) is installing its R&D 100 Award-winning foresee™ software in local homes to field-test smart energy management and community-level energy aggregation and coordination as part of its Smart Community project. The software will leverage physics-based modeling, machine-learning algorithms, and advanced data analytics to provide Basalt homeowners whole-home energy cost savings balanced with comfort, convenience, and grid benefits.
The concept of digital twins is a leading trend in enterprise strategy. It gets its name from the way that companies are building virtual equivalents, or twins, of physical objects. These digital copies are increasingly popular because they can be used to drive important simulations that haven’t been possible until now.
Researchers at Michigan State University are collecting data on how Great Lakes shoreline, including how residents view coastlines and the impact of high water levels.
Assistant professor Erin Bunting said the goal is to empower local communities, which is important to the future of the lakeshores and future research.
Life is full of nervous reactions — a head snaps towards a voice, leg muscles tense at the sound of a starting gun and thirsty mice scamper towards a squirt of water when trained to respond to a certain tone.
The mechanisms behind such reward-related behaviours are notoriously difficult to unpick. Nerve cells often snake through multiple brain areas, and their long axons and dense, tree-like dendrites can spark cellular conversations with thousands upon thousands of neighbours. Neural filaments can be exceptionally fine, and their positioning is crucial: disruptions in neural networks can lead to a range of neurological conditions. Yet, “If you want to label more than a few neurons at the same time and then trace where their axons go, it’s really difficult”, says Xiaoyin Chen, a neuroscientist at the Allen Institute for Brain Science in Seattle, Washington.
Still, researchers are slowly creating the tools to untangle that complexity, harnessing the power of sequencing, optogenetics and protein engineering to trace neuronal connections, record their activity, measure their inputs and outputs and map their networks.
The Conversation; Simon Coghlan, Jeannie Marie Paterson, Shaanan Cohney, Tim Miller
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Our recent research paper explored the ethics of automated proctoring. We found the promise of the software alluring, but it carries substantial risks.
Some educational institutions claim proctoring technologies are needed to prevent cheating. Some other institutions and students are concerned about hidden dangers.
Indeed, students have launched protests, petitions and lawsuits. They condemn online proctoring as discriminatory and intrusive, with overtones of Big Brother. Some proctoring companies have responded with attempts to stifle protest, which include suing their critics.
As the world has learned to its cost, the Delta variant of the pandemic coronavirus is more than twice as infectious as previous strains. Just what drives Delta’s ability to spread so rapidly hasn’t been clear, however. Now, a new lab strategy that makes it possible to quickly and safely study the effects of mutations in SARS-CoV-2 variants has delivered one answer: a little-noticed mutation in Delta that allows the virus to stuff more of its genetic code into host cells, thus boosting the chances that each infected cell will spread the virus to another cell.
That discovery, published today in Science, is “a big deal,” says Michael Summers, a structural biologist at the University of Maryland, Baltimore County—not just because it helps explain Delta’s ravages. The new system, developed by Nobel Prize winner Jennifer Doudna of the University of California (UC), Berkeley, and her colleagues, is a powerful tool for understanding current SARS-CoV-2 variants and exploring how future variants might affect the pandemic, he says. “The system she has developed allows you to look at any mutation and its influence on key parts of viral replication. … That can now be studied in a much easier way by a lot more scientists.”
Although the channel won’t likely have much to fear from corporate espionage, the US Clarifying Lawful Overseas Use of Data (CLOUD) Act may yet increase costs and complexity, especially in the face of post-Brexit GDPR reform.
Nigel Seddon, vice president of EMEA West at IT services management vendor Ivanti, says the act will probably increase complexity in relationships and global supply chains already struggling with different data handling regimes from the EU to Singapore and beyond.
“You’ve got the dynamics of the UK now being separate from Europe, and here is yet another country, creating its own specific rules and regulations,” Seddon points out.
Proceedings of the National Academy of Sciences; Andrew C. Eggers, Haritz Garro, and Justin Grimmer
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After the 2020 US presidential election Donald Trump refused to concede, alleging widespread and unparalleled voter fraud. Trump’s supporters deployed several statistical arguments in an attempt to cast doubt on the result. Reviewing the most prominent of these statistical claims, we conclude that none of them is even remotely convincing. The common logic behind these claims is that, if the election were fairly conducted, some feature of the observed 2020 election result would be unlikely or impossible. In each case, we find that the purportedly anomalous fact is either not a fact or not anomalous. [full text]
Most algorithms that power neuromorphic chips only care about the contribution of each artificial neuron—that is, how strongly they connect to one another, dubbed “synaptic weight.” What’s missing—yet tantamount to our brain’s inner working—is timing.
This month, a team affiliated with the Human Brain Project, the European Union’s flagship big data neuroscience endeavor, added the element of time to a neuromorphic algorithm. The results were then implemented on physical hardware—the BrainScaleS-2 neuromorphic platform—and pitted against state-of-the-art GPUs and conventional neuromorphic solutions.
NVIDIA has launched a follow-up to the Jetson AGX Xavier, its $1,100 AI brain for robots that it released back in 2018. The new module, called the Jetson AGX Orin, has six times the processing power of Xavier even though it has the same form factor and can still fit in the palm of one’s hand. NVIDIA designed Orin to be an “energy-efficient AI supercomputer” meant for use in robotics, autonomous and medical devices, as well as edge AI applications that may seem impossible at the moment.
Like a canary in a coal mine, the MarineCanary (MC) is an early warning system designed to detect waterborne issues like hazardous algal blooms, pollutants, high water temperatures and hypoxic conditions, before they hurt marine life. Each unit is created as a stand-alone, drop-and-go system that is suspended in the water column between its float and anchor mooring system. Within the MC unit lives a set of mussels. When a significant number of them close their shells, a warning is sent to the user’s mobile device.
The original MC unit was designed almost 25 years ago by IntegraSEE co-founder, Ulrich Lobsiger, and was based on recording and analysing live mussel behaviour using timelapse film technology, but – as machine learning, deep learning and AI weren’t readily available – there wasn’t a lot of incentive to commercialise a product that required manual image processing.
That all changed last July when Karan Kharecha, our computer science team member, and I, deployed our first prototype in Halifax Harbour on COVE Ocean’s Stella Maris platform.
Google AI Blog, Michael Dixon and Reena Singhal Lee
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Earlier this year, we launched Contactless Sleep Sensing in Nest Hub, an opt-in feature that can help users better understand their sleep patterns and nighttime wellness. While some of the most critical sleep insights can be derived from a person’s overall schedule and duration of sleep, that alone does not tell the complete story. The human brain has special neurocircuitry to coordinate sleep cycles — transitions between deep, light, and rapid eye movement (REM) stages of sleep — vital not only for physical and emotional wellbeing, but also for optimal physical and cognitive performance. Combining such sleep staging information with disturbance events can help you better understand what’s happening while you’re sleeping.
Today we announced enhancements to Sleep Sensing that provide deeper sleep insights. While not intended for medical purposes1, these enhancements allow better understanding of sleep through sleep stages and the separation of the user’s coughs and snores from other sounds in the room.
A $2,949,109 award from the National Science Foundation will help University of Maryland researchers explore the “rules of life” of networks of neurons in the brain—a project that could one day lead to better computing tools.
The researchers will bring together recent technological advances in patterning, electrical recording, optical stimulation and genetic manipulation of neurons to study how to nurture the cultured cells while continuously observing and stimulating them at fine scale. They hope to uncover how the individual parts of a single neuron contribute to the overall learning and computation of the neural network.
Electrical and computer engineering Professor Pamela Abshire, an affiliate of the Institute for Systems Research (ISR) is the principal investigator
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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
Having talked to many established academics and students, it is often unclear what digitally marketing yourself means. I am defining digitally marketing yourself as reaching your personal marketing goals through the application of digital technologies and media. Digitally marketing yourself starts with the understanding of your online presence. Developing a strong online presence may reinforce your online identity and what you offer to others.
A first-ever database compiling movement of the largest rivers in the world over time could become a crucial tool for urban planners to better understand the deltas that are home to these rivers and a large portion of Earth’s population.
The database, created by researchers at The University of Texas at Austin, uses publicly available remote sensing data to show how the river centerlines of the world’s 48 most threatened deltas have moved during the past 40 years. The data can be used to predict how rivers will continue to move over time and help governments manage population density and future development.
