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If smoke indicates a fire, nitric oxide signals inflammation. The chemical mediator promotes inflammation, but researchers suspect it can do its job too well after anterior cruciate ligament (ACL) ruptures and related injuries and initiate early onset osteoarthritis. Typically, the degenerative disease is only diagnosed after progressive symptoms, but it potentially could be identified much earlier through nitric oxide monitoring, according to Huanyu “Larry” Cheng, James E. Henderson Jr. Memorial Associate Professor of Engineering Science and Mechanics at Penn State.

Cheng and his student, Shangbin Liu, who earned a master’s degree in engineering science and mechanics at Penn State this year, collaborated with researchers based in China to develop a flexible biosensor capable of continuous and wireless nitric detection in rabbits. They published their approach in the Proceedings of the National Academy of Sciences.

“Real-time assessment of biomarkers associated with inflammation, such as nitric oxide in the joint cavity, could indicate pathological evolution at the initial development of osteoarthritis, providing essential information to optimize therapies following traumatic knee injury,” Cheng said.

U.S. and European physicists have demonstrated a new method for predicting whether metallic compounds are likely to host topological states that arise from strong electron interactions.

Physicists from Rice University, leading the research and collaborating with physicists from Stony Brook University, Austria’s Vienna University of Technology (TU Wien), Los Alamos National Laboratory, Spain’s Donostia International Physics Center and Germany’s Max Planck Institute for Chemical Physics of Solids, unveiled their new design principle in a study published online today in Nature Physics.

The team includes scientists at Rice, TU Wien and Los Alamos who discovered the first strongly correlated topological semimetal in 2017. That system and others the new design principle seeks to identify are broadly sought by the quantum computing industry because topological states have immutable features that cannot be erased or lost to .

A novel hormone combination has been created by a research team from Helmholtz Munich, the German Center for Diabetes Research (DZD), and Novo Nordisk for the potential treatment of type 2 diabetes in the future. The researchers combined the blood sugar-lowering actions of the medications tesaglitazar and GLP-1 (Glucagon-like peptide-1) to create a new and extremely effective drug.

The benefit of combining Tesaglitazar with GLP-1 is that the Tesaglitazar only penetrates the tissue with GLP-1 receptors. This increases the effects on sugar metabolism while lessening the side effects of tesaglitazar. Scientists have already successfully tested the new drug in animal studies. The study was recently published in the journal Nature Metabolism.

Tesaglitazar enhances glucose and fat metabolism in type 2 diabetic patients. It increases insulin sensitivity by acting on two receptors inside the cell nucleus. This was demonstrated in phase 3 clinical trials. However, tesaglitazar has side effects such as kidney damage.

A team of scientists at King Abdullah University of Science and Technology, in Saudi Arabia, says they already have a solution in the works: before land-based lithium runs out, shift lithium mining to the ocean. The team claims they’ve created an affordable method for extracting lithium from the seawater, potentially unlocking a practically infinite supply of lithium.

The challenge: Land-based lithium mining is incredibly damaging to the environment, and it wastes huge amounts of water — up to 500,000 gallons of water per ton of lithium extracted.

Seawater contains 5,000 times the amount of lithium found on land, but only in very low concentrations, which has made previous attempts to extract lithium from the ocean ineffective.

Futuristic China | Business Documentary from 2018.

Hear from the leaders of Baidu, China’s equivalent to Google. The smart home is being advanced at Iflytech, robots for business use are developed at UBTECH, while Tiandi demonstrates their latest advances in surveillance technology.
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Artificial General Intelligence or short AGI was commonly referred as Strong AI. The continues advancements in robotics are also spurring the development of AGI. Currently we only have narrow AI or weak AI. But robots are paving the way for strong AI. In the future, robots might possibly become smarter than us or at least, reach human level intelligence. The field of robotics has seen many improvements over the years, as artificial intelligence systems continue to get better. Machine intelligence is a trendy topic among computer scientists and other relevant researchers on the field. As robots continue to get better, concerns for the rise of a superintelligence or an artificial general intelligence that could have different goals from ours, is increasingly getting the attention of computer scientists and lay people alike. We have often seen works of science fiction where robots and AGI have malicious intent. However, things could go really bad fur us even if initially these intelligent machines are programmed to obey human orders and follow our values. As a machine continues to improve itself by modifying it’s own source code, it could lead to an intelligence explosion. A point of time often referred as a technological singularity. Where it becomes hard if not impossible to predict future trajectories of the AI in question. As of the year 2017, there are over 40 organizations focused on the development of AGI. As we’ve said many times before, today’s AI is narrow. However the field of robotics is accelerating the rise of AGI and we will possibly witness a truly general AI in our lifetimes.

#AGI #AI #Artificialintelligence.

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Sources: Boston Dynamics’Big Dog: https://www.youtube.com/watch?v=cNZPRsrwumQ&t=126s.

Yoshua Bengio (MILA), Irina Higgins (DeepMind), Nick Bostrom (FHI), Yi Zeng (Chinese Academy of Sciences), and moderator Joshua Tenenbaum (MIT) discuss possible paths to artificial general intelligence.

The Beneficial AGI 2019 Conference: https://futureoflife.org/beneficial-agi-2019/

After our Puerto Rico AI conference in 2015 and our Asilomar Beneficial AI conference in 2017, we returned to Puerto Rico at the start of 2019 to talk about Beneficial AGI. We couldn’t be more excited to see all of the groups, organizations, conferences and workshops that have cropped up in the last few years to ensure that AI today and in the near future will be safe and beneficial. And so we now wanted to look further ahead to artificial general intelligence (AGI), the classic goal of AI research, which promises tremendous transformation in society. Beyond mitigating risks, we want to explore how we can design AGI to help us create the best future for humanity.

We again brought together an amazing group of AI researchers from academia and industry, as well as thought leaders in economics, law, policy, ethics, and philosophy for five days dedicated to beneficial AI. We hosted a two-day technical workshop to look more deeply at how we can create beneficial AGI, and we followed that with a 2.5-day conference, in which people from a broader AI background considered the opportunities and challenges related to the future of AGI and steps we can take today to move toward an even better future.

In nature, evolutionary chromosomal changes may take a million years, but scientists have recently reported a novel technique for programmable chromosome fusion that has successfully created mice with genetic changes that occur on a million-year evolutionary scale in the laboratory. The findings might shed light on how chromosomal rearrangements – the neat bundles of structured genes provided in equal numbers by each parent, which align and trade or mix characteristics to produce offspring – impact evolution.

In a study published in the journal Science, the researchers show that chromosome level engineering is possible in mammals. They successfully created a laboratory house mouse with a novel and sustainable karyotype, offering crucial insight into how chromosome rearrangements may influence evolution.

“The laboratory house mouse has maintained a standard 40-chromosome karyotype — or the full picture of an organism’s chromosomes — after more than 100 years of artificial breeding,” said co-first author Li Zhikun, researcher in the Chinese Academy of Sciences (CAS) Institute of Zoology and the State Key Laboratory of Stem Cell and Reproductive Biology. “Over longer time scales, however, karyotype changes caused by chromosome rearrangements are common. Rodents have 3.2 to 3.5 rearrangements per million years, whereas primates have 1.6.”