New Delhi, May 10: Troops of India and China were involved in a fierce face-off and many of them sustained minor injuries in the clash near Naku La in the Sikkim sector along the Sino-Indo border on Saturday, official sources

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Troops of India and China were involved in a fierce face-off and many of them sustained minor injuries in the clash near Naku La in the Sikkim sector along the Sino-Indo border on Saturday. The troops disengaged after dialogue at the local level. "Troops resolve such issues mutually as per established protocols. Such an incident occurred after a long time," said a source.

The troops disengaged after dialogue at the local level

The Trump administration is tightening visa guidelines for Chinese journalists in response to the treatment of US journalists in China, as tensions flare between the two nations over the coronavirus.

Hong Kong: Trump administration tightens visas for Chinese reporters - Times of India

The clashes took place during the usual routine of patrolling by the forces from the two countries, according to Zee News

Many of them sustained minor injuries in the clash near Naku La in the Sikkim sector along the Sino-Indo border on Saturday

Single-wavelength X-ray anomalous diffraction (SAD) is a frequently employed technique to solve the phase problem in X-ray crystallography. The precision and accuracy of recovered anomalous differences are crucial for determining the correct phases. Continuous rotation (CR) and inverse-beam geometry (IBG) anomalous data collection methods have been performed on tetragonal lysozyme and monoclinic survivin crystals and analysis carried out of how correlated the pairs of Friedel's reflections are after scaling. A multivariate Bayesian model for estimating anomalous differences was tested, which takes into account the correlation between pairs of intensity observations and incorporates the a priori knowledge about the positivity of intensity. The CR and IBG data collection methods resulted in positive correlation between I(+) and I(−) observations, indicating that the anomalous difference dominates between these observations, rather than different levels of radiation damage. An alternative pairing method based on near simultaneously observed Bijvoet's pairs displayed lower correlation and it was unsuccessful for recovering useful anomalous differences when using the multivariate Bayesian model. In contrast, multivariate Bayesian treatment of Friedel's pairs improved the initial phasing of the two tested crystal systems and the two data collection methods.

By simulating the environment when corn was first exploited by people and then domesticated, Smithsonian scientists discovered that corn’s ancestor; a wild grass called teosinte, […]

The post Greenhouse “time machine” sheds light on corn domestication appeared first on Smithsonian Insider.

Simon L. Bullock
Apr 6, 2020; 133:jcs245134-jcs245134
Meeting Report

Full Text:

Machine learning algorithms can sometimes do a great job with a little help from human expertise, at least in the field of materials science. In many specialized areas of science, engineering and medicine, researchers are turning to machine learning algorithms to analyze data sets that have grown too large for humans to understand. In materials science, success with this effort could accelerate the design of next-generation advanced functional materials, where development now usually depends on old-fashioned trial and error. By themselves, however, data analytics techniques borrowed from other research areas often fail to provide the insights needed to help materials scientists and engineers choose which of many variables to adjust -- and the techniques can't account for dramatic changes such as the introduction of a new chemical compound into the process. In a new study, researchers explain a technique known as dimensional stacking, which shows that human experience still has a role to play in the age of machine intelligence. The machines gain an edge at solving a challenge when the data to be analyzed are intelligently organized based on human knowledge of what factors are likely to be important and related. "When your machine accepts strings of data, it really does matter how you are putting those strings together," said Nazanin Bassiri-Gharb, the paper's corresponding author and a scientist at the Georgia Institute of Technology. "We must be mindful that the organization of data before it goes to the algorithm makes a difference. If you don't plug the information in correctly, you will get a result that isn't necessarily correlated with the reality of the physics and chemistry that govern the materials."

Image credit: Rob Felt/Georgia Tech

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How do galaxies such as our Milky Way come into existence? How do they grow and change over time? The science behind galaxy formation has long been a puzzle, but a University of Arizona-led team of scientists is one step closer to finding answers, thanks to supercomputer simulations. Observing real galaxies in space can only provide snapshots in time, so researchers who study how galaxies evolve over billions of years need to use computer simulations. Traditionally, astronomers have used simulations to invent theories of galaxy formation and test them, but they have had to proceed one galaxy at a time. Peter Behroozi of the university's Steward Observatory and colleagues overcame this hurdle by generating millions of different universes on a supercomputer, each according to different physical theories for how galaxies form. The findings challenge fundamental ideas about the role dark matter plays in galaxy formation, the evolution of galaxies over time and the birth of stars. The study is the first to create self-consistent universes that are exact replicas of the real ones -- computer simulations that each represent a sizeable chunk of the actual cosmos, containing 12 million galaxies and spanning the time from 400 million years after the Big Bang to the present day. The results from the "UniverseMachine," as the authors call their approach, have helped resolve the long-standing paradox of why galaxies cease to form new stars even when they retain plenty of hydrogen gas, the raw material from which stars are forged. The research is partially funded by NSF's Division of Physics through grants to UC Santa Barbara's Kavli Institute for Theoretical Physics and the Aspen Center for Physics.

Image credit: NASA/ESA/J. Lotz and the HFF Team/STScI

UATP has partnered the payment technology company

Chef Chun Lei (l.) and restaurant owner Charles Lu (r.) in the kitchen of Shanghailander Palace in Arcadia.; Credit: Josie Huang/KPCC

This content is from Southern California Public Radio. View the original story at SCPR.org.

Full Text:

Machine learning algorithms can sometimes do a great job with a little help from human expertise, at least in the field of materials science. In many specialized areas of science, engineering and medicine, researchers are turning to machine learning algorithms to analyze data sets that have grown too large for humans to understand. In materials science, success with this effort could accelerate the design of next-generation advanced functional materials, where development now usually depends on old-fashioned trial and error. By themselves, however, data analytics techniques borrowed from other research areas often fail to provide the insights needed to help materials scientists and engineers choose which of many variables to adjust -- and the techniques can't account for dramatic changes such as the introduction of a new chemical compound into the process. In a new study, researchers explain a technique known as dimensional stacking, which shows that human experience still has a role to play in the age of machine intelligence. The machines gain an edge at solving a challenge when the data to be analyzed are intelligently organized based on human knowledge of what factors are likely to be important and related. "When your machine accepts strings of data, it really does matter how you are putting those strings together," said Nazanin Bassiri-Gharb, the paper's corresponding author and a scientist at the Georgia Institute of Technology. "We must be mindful that the organization of data before it goes to the algorithm makes a difference. If you don't plug the information in correctly, you will get a result that isn't necessarily correlated with the reality of the physics and chemistry that govern the materials."

Image credit: Rob Felt/Georgia Tech

Full Text:

How do galaxies such as our Milky Way come into existence? How do they grow and change over time? The science behind galaxy formation has long been a puzzle, but a University of Arizona-led team of scientists is one step closer to finding answers, thanks to supercomputer simulations. Observing real galaxies in space can only provide snapshots in time, so researchers who study how galaxies evolve over billions of years need to use computer simulations. Traditionally, astronomers have used simulations to invent theories of galaxy formation and test them, but they have had to proceed one galaxy at a time. Peter Behroozi of the university's Steward Observatory and colleagues overcame this hurdle by generating millions of different universes on a supercomputer, each according to different physical theories for how galaxies form. The findings challenge fundamental ideas about the role dark matter plays in galaxy formation, the evolution of galaxies over time and the birth of stars. The study is the first to create self-consistent universes that are exact replicas of the real ones -- computer simulations that each represent a sizeable chunk of the actual cosmos, containing 12 million galaxies and spanning the time from 400 million years after the Big Bang to the present day. The results from the "UniverseMachine," as the authors call their approach, have helped resolve the long-standing paradox of why galaxies cease to form new stars even when they retain plenty of hydrogen gas, the raw material from which stars are forged. The research is partially funded by NSF's Division of Physics through grants to UC Santa Barbara's Kavli Institute for Theoretical Physics and the Aspen Center for Physics.

Image credit: NASA/ESA/J. Lotz and the HFF Team/STScI

A recent study has analysed risks to European renewable industries from the Chinese supply of critical raw materials. The offshore wind sector was found to be the most vulnerable of the renewable industries to supply risks. EU and industry strategies should be able to deal with these supply risks in the short term, but there are potential long-term risks to solar and wind sectors. The development of alternative technologies less reliant on these raw materials, and methods to recycle these materials is, therefore, a priority.

The headcount has now come down from more than 1,000 employees a year ago, with the majority of job cuts in the wake of Covid-19 outbreak that forced shutdowns in the February-April period. The headcount comprises staff on the company’s rolls as well as those on contract and outsourced manpower.

Tiny plastic particles from laundry wastewater are being washed into the marine environment, according to recent research. The plastic, from synthetic clothes cleaned in domestic washing machines, is a significant source of contamination and, unless measures are taken to address the problem, growing coastal populations will only exacerbate the situation.

The group has been very active during the last five years, especially in 2019-20.

Google has announced machine images, a new type of Compute Engine resource that contains all the information people need to create, backup or restore a virtual machine, reducing the amount of time people spend managing their Cloud environment.

The group has been very active during the last five years, especially in 2019-20.

The headcount has now come down from more than 1,000 employees a year ago, with the majority of job cuts in the wake of Covid-19 outbreak that forced shutdowns in the February-April period. The headcount comprises staff on the company’s rolls as well as those on contract and outsourced manpower.

Oil spills can decimate seabird populations. Some birds can be saved, if the oil is washed from their feathers in time; however, this long process is stressful for the birds and requires numerous volunteers. Researchers have now developed a ‘bird-washing machine’ which reduces the washing time from two hours to four minutes. When trialled on oiled birds rescued from the Caspian Sea this resulted in a substantial increase in survival: 88.5% survival after seven days compared to 50% survival with current washing techniques.

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Scientists at NTU Singapore, MIT and Brown University have developed new approaches that significantly improve the accuracy of an important material testing technique by harnessing the power of machine learning....

As construction begins on a 32-story prefab tower here in the U.S., Broad Sustainable Building Corp. is preparing for a similar project in China that will resul

Chessboard-like grid patterns that cover sand dunes in China are explained as attempts at mining nickel in the deserts.

The Shenzhou 10, along with its three crewmembers, returned safely after 15 days of space travel.

'Where the River Runs' is a pop-up meadow with a deep environmental message.

In June 2012, a network of 16,000 computers trained itself to recognize a cat by looking at 10 million images from YouTube videos.

Sweatshops filled with robots could bring manufacturing of smartphones, computers and TVs to the United States, as well.

After debuting in Nottingham, England, the big-hearted concept catering to 'rough sleepers' is coming to America.

The rainforest as a living machine, is quite possibly the most sophisticated technology on the planet.

To meet China's insatiable demand for pork, Shuanghui International is turning to an American company to help 'bring home the bacon.'

Chengdu's wild plan involves a reflective satellite or "moon" that would beam down a "dusk-like glow" within city limits.

Support small companies with good products though kickstarter.com! The following two companies have great products to back.

The Porsche 918 Spyder and Ferrari F70 offer split personalities: voracious performance on tap, but eco-driving if you tread lightly. Is it a new era of Dr. Gre

The Monkey's Paw book store in Toronto has a Biblio-Mat that distributes random rare books to customers for only a few dollars.

In an effort to save money and labor, a farm in Germany has begun selling fresh, local produce from vending machines.

Xenobots are hybrids of living frog cells and machinery — a unique hybrid of organic and inorganic parts that can power themselves.

Dr. Don Milton's Gesundheit machine collects the breath exhaled by a sick person so researchers can study how viruses are spread.

Food delivery services and high-tech appliances could be a boon for boomers, especially if kitchens disappear.

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