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Using data on electromagnetic (EM) waves and plasma particles measured simultaneously via multiple satellites, an international collaborative research group has discovered the existence of invisible “propagation path” of EM waves and elucidated the mechanism by which EM waves propagate to the ground.

It is known that various kinds of EM occur naturally in geospace and cause variations in the plasma environment that surrounds the Earth via a known as wave–particle interaction. In particular, when geospace storms occur due to disturbances of sun and solar wind, EM waves become more active, and variations of geospace environment sometimes, may cause damage to spacecrafts, expose astronauts to radiation, and cause terrestrial power grid failures. To understand variation in the plasma environment caused by EM waves in , in-situ measurement has been performed in space using spacecrafts, such as the Japanese geospace satellite Arase.

As EM waves in space propagate far away from their origin, to correctly understand the effects of EM waves, it is crucial to understand where in space the EM waves are generated and how they are propagated. However, it has been difficult to unravel the origin of EM waves and the mysteries of how EM waves spread spatially using only single-point observation. “Electromagnetic ion cyclotron waves (EMIC waves),” which are the focus of this study, are an important class of EM wave in geospace that control variations in the geospace plasma environment. The source region of ion mode waves has a finite spatial extent, and generated EMIC waves are considered to propagate north to south along the geomagnetic field lines. The specific spatial size of the EMIC wave source region and the 3D aspect of how the propagation path is formed from space to ground are yet to be elucidated.

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The hunt is on for leptoquarks, particles beyond the limits of the standard model of particle physics —the best description we have so far of the physics that governs the forces of the Universe and its particles. These hypothetical particles could prove useful in explaining experimental and theoretical anomalies observed at particle accelerators such as the Large Hadron Collider (LHC) and could help to unify theories of physics beyond the standard model, if researchers could just spot them.

A new paper published in Nuclear Physics B by Anirban Karan, Priyotosh Bandyopadhyay, and Saunak Dutta, of the Indian Institute of Technology Hyderabad, Kandi, together with Mahesh Jakkapu, Graduate University for Advanced Studies (SOKENDAI), Kanagawa, Japan, examines the potential signatures of leptoquarks at the LHC to see how they could arise from for the possible mass ranges of these particles.

The main objective of this research is how to distinguish the signatures of different leptoquarks at proton-proton colliders like LHC or its proposed successor, Karan says.

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Clip during an interview made by Nicholas Singh, Senior Product Manager at Novos Labs to Kris Verburgh, CSO and Co-Founder of Novos Lab.

The clip shows the answer made by Kris Verburgh to a question made by José Cordeiro, PhD, MBA, Vice-Chairman of Humanity Plus, about the prediction made by Ray Kurzweil on the availability of full body human biological rejuvenation by 2045.

The episode took place during the webinar “Why Do We Age (And What Can We Do About It)?” organized by Novos Labs that took place on December 9, 2021.

To watch the entire webinar clic here: https://zoom.us/rec/play/lF-M5nVdYmXSiHQUAwC2YfrtaiUBfXUQP0N…pN068ViIHM

Continue reading “Kris Verburgh — CSO of Novos Labs views on Longevity Escape Velocity (con S/T en Español)” | >

The accelerated growth in ecommerce and online marketplaces has led to a surge in fraudulent behavior online perpetrated by bots and bad actors alike. A strategic and effective approach to online fraud detection will be needed in order to tackle increasingly sophisticated threats to online retailers.

These market shifts come at a time of significant regulatory change. Across the globe, new legislation is coming into force that alters the balance of responsibility in fraud prevention between users, brands, and the platforms that promote them digitally. For example, the EU Digital Services Act and US Shop Safe Act will require online platforms to take greater responsibility for the content on their websites, a responsibility that was traditionally the domain of brands and users to monitor and report.

Can AI find what’s hiding in your data? In the search for security vulnerabilities, behavioral analytics software provider Pasabi has seen a sharp rise in interest in its AI analytics platform for online fraud detection, with a number of key wins including the online reviews platform, Trustpilot. Pasabi maintains its AI models based on anonymised sets of data collected from multiple sources.

Using bespoke models and algorithms, as well as some open source and commercial technology such as TensorFlow and Neo4j, Pasabi’s platform is proving itself to be advantageous in the detection of patterns in both text and visual data. Customer data is provided to Pasabi by its customers for the purposes of analysis to identify a range of illegal activities — - illegal content, scams, and counterfeits, for example — - upon which the customer can then act.

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Continue reading “Why AI is the future of fraud detection” | >

A new computational simulator can help predict whether changes to materials or design will improve performance in new photovoltaic cells.

In the ongoing race to develop ever-better materials and configurations for solar cells, there are many variables that can be adjusted to try to improve performance, including material type, thickness, and geometric arrangement. Developing new solar cells has generally been a tedious process of making small changes to one of these parameters at a time. While computational simulators have made it possible to evaluate such changes without having to actually build each new variation for testing, the process remains slow.

Now, researchers at MIT and Google Brain have developed a system that makes it possible not just to evaluate one proposed design at a time, but to provide information about which changes will provide the desired improvements. This could greatly increase the rate for the discovery of new, improved configurations.

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The system could help physicians select the least risky treatments in urgent situations, such as treating sepsis.

Sepsis claims the lives of nearly 270,000 people in the U.S. each year. The unpredictable medical condition can progress rapidly, leading to a swift drop in blood pressure, tissue damage, multiple organ failure, and death.

Prompt interventions by medical professionals save lives, but some sepsis treatments can also contribute to a patient’s deterioration, so choosing the optimal therapy can be a difficult task. For instance, in the early hours of severe sepsis, administering too much fluid intravenously can increase a patient’s risk of death.

To help clinicians avoid remedies that may potentially contribute to a patient’s death, researchers at MIT and elsewhere have developed a machine-learning model that could be used to identify treatments that pose a higher risk than other options. Their model can also warn doctors when a septic patient is approaching a medical dead end — the point when the patient will most likely die no matter what treatment is used — so that they can intervene before it is too late.

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Continue reading “Machine-learning system flags remedies that might do more harm than good” | >

Strategy accelerates the best algorithmic solvers for large sets of cities.

Waiting for a holiday package to be delivered? There’s a tricky math problem that needs to be solved before the delivery truck pulls up to your door, and MIT researchers have a strategy that could speed up the solution.

The approach applies to vehicle routing problems such as last-mile delivery, where the goal is to deliver goods from a central depot to multiple cities while keeping travel costs down. While there are algorithms designed to solve this problem for a few hundred cities, these solutions become too slow when applied to a larger set of cities.

The solver algorithms work by breaking up the problem of delivery into smaller subproblems to solve — say, 200 subproblems for routing vehicles between 2,000 cities. Wu and her colleagues augment this process with a new machine-learning algorithm that identifies the most useful subproblems to solve, instead of solving all the subproblems, to increase the quality of the solution while using orders of magnitude less compute.

Their approach, which they call “learning-to-delegate,” can be used across a variety of solvers and a variety of similar problems, including scheduling and pathfinding for warehouse robots, the researchers say.

Continue reading “Machine learning speeds up vehicle routing” | >

The possibility of space mining in future was thrown into sharp relief this weekend as a Near Earth Asteroid (NEA) called 4,660 Nereus passed our planet.

Worth an estimated $5 billion in precious metals and measuring 330 meters across, Nereus at no point came anywhere near being dangerous, getting no closer than 2.4 million miles/3.9 million kilometers at 13:51 UTC on Saturday, December 11, 2021.

That’s about 10 times the distance between the Earth and the Moon.

So why so much attention on Nereus?

There seemed to be a lot of misunderstanding about how dangerous—or otherwise—Nereus could be to Earth.

Continue reading “Asteroid Nereus Cruised Past Earth Today. In 39 Years It Could Be Mined For Billion In Precious Metals” | >

The predicted existence of an exotic particle made up of six elementary particles known as quarks by RIKEN researchers could deepen our understanding of how quarks combine to form the nuclei of atoms.

Quarks are the fundamental building blocks of matter. The nuclei of atoms consist of protons and neutrons, which are in turn made up of three quarks each. Particles consisting of three quarks are collectively known as baryons.

Scientists have long pondered the existence of systems containing two baryons, which are known as dibaryons. Only one dibaryon exists in nature—deuteron, a hydrogen nucleus made up of a proton and a neutron that are very lightly bound to each other. Glimpses of other dibaryons have been caught in nuclear-physics experiments, but they had very fleeting existences.

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