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Salvaging the school year depends on quickly vaccinating teachers, lower infection rates

Los Angeles Times

Saving the Los Angeles school year has become a race against the clock -- as campuses are unlikely to reopen until teachers are vaccinated against COVID-19 and infection rates decline at least three-fold, officials said Monday. The urgency to salvage the semester in L.A. and throughout the state was underscored by new research showing the depth of student learning loss and by frustrated parents who organized statewide to pressure officials to bring back in-person instruction. A rapid series of developments Monday -- involving the governor, L.A. Unified School District, the teachers union and the county health department -- foreshadowed the uncertainties that will play out in the high-stakes weeks ahead for millions of California students. "We're never going to get back if teachers can't get vaccinated," said Assemblyman Patrick O'Donnell (D-Long Beach), who chairs the state's Assembly Education Committee and has two high schoolers learning from home. He expressed frustration that educators are not being prioritized by the L.A. County Health Department even as teachers in Long Beach are scheduled for vaccines this week. Although Long Beach is part of L.A. County, it operates its own independent health agency.



Learn how to build a video game with this Unity and Blender course

Mashable

TL;DR: The Build The Legend of Zelda Clone in Unity3D and Blender course is on sale for £25.56 as of Jan. 26, saving you 82% on list price. If you're curious to know what makes Zelda a hit among gamers, you may want to consider finding out how it was created in the first place. The Build The Legend of Zelda Clone in Unity3D and Blender course will show what makes a game like Zelda tick, and give you an intro to game development and design to boot. You'll get a shot at recreating The Legend of Zelda -- a Nintendo classic. Taught by John Bura, a seasoned game programmer and educator, this course is designed to help you develop a game from scratch using Unity (a game engine) and Blender (an open-source 3D computer graphics software toolset).


Competition among human females likely contributed to concealed ovulation

Daily Mail - Science & tech

Competition for mates between prehistoric human women may have contributed to'concealed ovulation' – a lack of any notable physical clues that a woman is fertile, experts say. Using computational models, US researchers found evidence that concealed ovulation in humans – which is unusual in the animal kingdom – evolved to allow women to hide their fertility status from other females. This would have helped avoid female conflict, perhaps driven by aggression towards potential rivals for male mates. Previously, scientists have thought women evolved to conceal ovulation from males to encourage them to help with looking after children. The new research shows that the origin of concealed ovulation might have actually have been much more female-oriented than previously thought. 'The study of human evolution has tended to look at things from a male perspective,' said senior study author Athena Aktipis, associate professor of psychology at Arizona State University in the US.


New Algorithms Could Reduce Racial Disparities in Health Care

WIRED

Researchers trying to improve healthcare with artificial intelligence usually subject their algorithms to a form of machine med school. Software learns from doctors by digesting thousands or millions of x-rays or other data labeled by expert humans until it can accurately flag suspect moles or lungs showing signs of Covid-19 by itself. A study published this month took a different approach--training algorithms to read knee x-rays for arthritis by using patients as the AI arbiters of truth instead of doctors. The results revealed radiologists may have literal blind spots when it comes to reading Black patients' x-rays. The algorithms trained on patients' reports did a better job than doctors at accounting for the pain experienced by Black patients, apparently by discovering patterns of disease in the images that humans usually overlook.


Fukushima College robot wins top prize for nuclear decommissioning

The Japan Times

Fukushima – A robot created by a team from a technology college in northeastern Japan recently won the top prize in a robotics competition that had the theme of decommissioning the Fukushima No. 1 nuclear power plant. The Mehikari robot of Fukushima College earned praise for its speed as well as ability to employ different methods to retrieve mock debris similar in size to that at the plant, the site of a nuclear disaster triggered by a massive earthquake and tsunami on March 11, 2011. The robot completed the set task in about 2 minutes, the fastest time, in the annual competition aimed at fostering future engineers that was attended by students from 13 colleges belonging to the National Institute of Technology. Sunday's competition was the fifth of its kind. Students in 14 teams from the colleges across the country such as in Osaka and Kumamoto prefectures were tasked this year with developing robots to remove fuel debris from the plant, organizers said.


Flutter Artificial Intelligence Course - Build 15+ AI Apps

#artificialintelligence

We will develop 15 AI Apps with Flutter using TensorFlow Machine Learning and Deep Learning Concepts. In this course you will also learn how to train a model/machine for your apps. And how to import and use these trained models after training in your flutter app (android iOS app). This is a complete step by step course. At the end of this course you will be able to make your own Ai, Deep Learning and Machine Learning Apps for the Android Smart Phones and iOS [iPhones] using Flutter SDK with TensorFlow Lite.


Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data

#artificialintelligence

High-throughput sequencing technologies have rapidly developed during the past years and have become an essential tool in plant sciences. However, the analysis of genomic data remains challenging and relies mostly on the performance of automatic pipelines. Frequently applied pipelines involve the alignment of sequence reads against a reference sequence and the identification of sequence variants. Since most benchmarking studies of bioinformatics tools for this purpose have been conducted on human datasets, there is a lack of benchmarking studies in plant sciences. In this study, we evaluated the performance of 50 different variant calling pipelines, including five read mappers and ten variant callers, on six real plant datasets of the model organism Arabidopsis thaliana. Sets of variants were evaluated based on various parameters including sensitivity and specificity. We found that all investigated tools are suitable for analysis of NGS data in plant research. When looking at different performance metrics, BWA-MEM and Novoalign were the best mappers and GATK returned the best results in the variant calling step.


Waymo CEO dismisses Tesla self-driving plan: "This is not how it works"

#artificialintelligence

Many Tesla fans view the electric carmaker as a world leader in self-driving technology. CEO Elon Musk himself has repeatedly claimed that the company is less than two years away from perfecting fully self-driving technology. But in an interview with Germany's Manager magazine, Waymo CEO John Krafcik dismissed Tesla as a Waymo competitor and argued that Tesla's current strategy was unlikely to ever produce a fully self-driving system. "For us, Tesla is not a competitor at all," Krafcik said. "We manufacture a completely autonomous driving system. Tesla is an automaker that is developing a really good driver assistance system."


Growing up in bilingual home 'provides lasting cognitive benefits'

Daily Mail - Science & tech

Growing up in a bilingual home can provide unexpected cognitive benefits later in life – especially if exposed to two or more languages from birth. UK experts found that adults who were exposed earlier to two languages in their lives were the highest performers in cognitive tests. 'Early bilinguals' – those who learn a second language as an infant or young child – have cognitive advantages over those who learn a second language later, suggesting the earlier we're exposed to two languages, the better for our brains. In the experiments, early bilinguals were found to be quicker at shifting attention and detecting visual changes compared to adults who learnt their second language later in life (late bilinguals). Both early and late bilinguals performed better than those people who spent their early lives in single-language homes.