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The human brain is less accessible than other organs because it is covered by a thick, hard skull. As a result, researchers have been limited to low-resolution imaging or analysis of brain signals measured outside the skull. This has proved to be a major hindrance in brain research, including research on developmental stages, causes of diseases, and their treatments. Recently, studies have been performed using primary neurons from rats or human-derived induced pluripotent stem cells (iPSCs) to create artificial brain models that have been applied to investigate brain developmental processes and the causes of brain diseases. These studies are expected to play a key role to unlocking the mysteries of the brain.

In the past, artificial models were created and studied in 2D; however, in 2017, a research team from KIST developed a 3D artificial brain model that more closely resembled the real brain. Unfortunately, due to the absence of an analytical framework for studying signals in a 3D brain model, studies were limited to analyses of surface signals or had to reform the 3D structure to a flat shape. As such, tracking in a complex, interconnected artificial network remained a challenge.

The Korea Institute of Science and Technology (KIST) announced that the research teams of Doctors Il-Joo Cho and Nakwon Choi have developed a that can apply precise non-destructive stimuli to a 3D artificial neural circuit and measure neural signals in real-time from multiple locations inside the model at the cellular level.

Elementary school-age children who get less than nine hours of sleep per night have significant differences in certain brain regions responsible for memory, intelligence and well-being compared to those who get the recommended nine to 12 hours of sleep per night, according to a new study led by University of Maryland School of Medicine (UMSOM) researchers. Such differences correlated with greater mental health problems, like depression, anxiety, and impulsive behaviors, in those who lacked sleep. Inadequate sleep was also linked to cognitive difficulties with memory, problem solving and decision making. The findings were published today in the journal The Lancet Child & Adolescent Health.

The American Academy of Sleep Medicine recommends that aged six to 12 years of age sleep 9 to 12 hours per night on a regular basis to promote optimal health. Up until now, no studies have examined the long-lasting impact of insufficient sleep on the neurocognitive development of pre-teens.

To conduct the study, the researchers examined data that were collected from more than 8,300 children aged nine to 10 years who were enrolled in the Adolescent Brain Cognitive Development (ABCD) study. They examined MRI images, , and surveys completed by the participants and their parents at the time of enrollment and at a two-year follow-up visit at 11 to 12 years of age. Funded by the National Institutes of Health (NIH), the ABCD study is the largest long-term study of brain development and child health in the U.S.

Presently available in France, the “Electric As You Go” program is for private customers who wish to change their old vehicle to an affordable, sustainable one. Trying to break through ‘” the cost is too much to invest in an EV” scenario (which becomes more disputable each hour of each day), Stellantis introduced “Electric As You Go” and is promoting a more affordable long-term rental program dedicated to battery electric vehicles (BEVs).

The program claims it is efficiently designed to offer breakthrough competitive prices to Stellantis customers. The offer is starting in France and looks hopeful.

There is the customary but “limited” initial down payment and a monthly fee that starts from €110 per month plus a cost of 7 cents per kilometer with a 500 km minimum per month. This new offer frames itself as a breakthrough project. “The main goal of the program is to offer the opportunity to better adapt the total cost of the vehicle to its real use.”

Living organisms offer extensive diversity in terms of their phenotypes, metabolic processes, and adaptation to various niches. However, the basic building blocks that create this diversity are remarkably similar. How can we advance our understanding of the fascinating mechanisms that drive biological complexity and how can we harness biological components to build entirely new materials and devices?

A new Special Issue from ACS Synthetic Biology will focus on this dynamic topic, including contributions that deconstruct as well as build up and mimic biological systems. The resulting work serves both to test our scientific understanding and to extend known biology to develop new concepts and applications. The issue will be led by Associate Editor Michael Jewett with Guest Editors Kate Adamala, Marileen Dogterom, and Neha Kamat.

The table also shows the average normalized rank of transfer learning approaches. Hyperparameter transfer learning uses evaluation data from past HPO tasks in order to warmstart the current HPO task, which can result in significant speed-ups in practice.

Syne Tune supports transfer-learning-based HPO via an abstraction that maps a scheduler and transfer learning data to a warmstarted instance of the former. We consider the bounding-box and quantile-based ASHA, respectively referred to as ASHA-BB and ASHA-CTS. We also consider a zero-shot approach (ZS), which greedily selects hyperparameter configurations that complement previously considered ones, based on historical performances; and RUSH, which warmstarts ASHA with the best configurations found for previous tasks. As expected, we find that transfer learning approaches accelerate HPO.

Our experiments show that Syne Tune makes research on automated machine learning more efficient, reliable, and trustworthy. By making simulation on tabulated benchmarks a first-class citizen, it makes hyperparameter optimization accessible to researchers without massive computation budgets. By supporting advanced use cases, such as hyperparameter transfer learning, it allows better problem solving in practice.

What would happen if you fell into a black hole? Join James Beacham, particle physicist at the Large Hadron Collider at CERN, as he explores what happens when the fabric of reality – physical or societal – gets twisted beyond recognition.

Watch the Q&A with James here: https://youtu.be/Q37oEB4bNSI
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James Beacham searches for answers to the biggest open questions of physics using the largest experiment ever, the Large Hadron Collider at CERN. He hunts for dark matter, gravitons, quantum black holes, and dark photons as a member of the ATLAS collaboration, one of the teams that discovered the Higgs boson in 2012.

In addition to his research, he is a frequent keynote speaker about science, innovation, the future of technology, and art at events and venues around the world, including the American Museum of Natural History, the Royal Institution, SXSW, and the BBC, as well as private events for companies and corporations, including KPMG, Bain, Dept Agency, and many others.

Why is there something rather than nothing? And what does ‘nothing’ really mean? More than a philosophical musing, understanding nothing may be the key to unlocking deep mysteries of the universe, from dark energy to why particles have mass. Journalist John Hockenberry hosts Nobel laureate Frank Wilczek, esteemed cosmologist John Barrow, and leading physicists Paul Davies and George Ellis as they explore physics, philosophy and the nothing they share.

This program is part of the Big Ideas Series, made possible with support from the John Templeton Foundation.

The World Science Festival gathers great minds in science and the arts to produce live and digital content that allows a broad general audience to engage with scientific discoveries. Our mission is to cultivate a general public informed by science, inspired by its wonder, convinced of its value, and prepared to engage with its implications for the future.

Visit our Website: http://www.worldsciencefestival.com/