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How can machine learning help determine the best times and ways to use solar energy? This is what a recent study published in Advances in Atmospheric Sciences hopes to address as a team of researchers from the Karlsruhe Institute of Technology investigated how machine learning algorithms can be used to predict and forecast weather patterns to enable more cost-effective approaches for using solar energy. This study has the potential to help enhance renewable energy technologies by fixing errors that are often found in current weather prediction models, leading to more efficient use of solar power by predicting when weather patterns will enable the availability of the Sun for solar energy needs.

For the study, the researchers used a combination of statistical methods and machine learning algorithms to help predict the most efficient times of day that photovoltaic (PV) power generation will achieve maximum production output. Their methods used what’s known as post-processing, which involves correcting weather forecasting errors before that data enters PV models, resulting in changing PV model predictions, resulting in establishing more accurate weather forecasting from machine learning algorithms.

“One of our biggest takeaways was just how important the time of day is,” said Dr. Sebastian Lerch, who is a professor at the Karlsruhe Institute of Technology and a co-author on the study. “We saw major improvements when we trained separate models for each hour of the day or fed time directly into the algorithms.”

What can a moon’s tidal friction teach us about its formation and evolution? This is what a recent study published in Science Advances hopes to address as a team of researchers at the University of California Santa Cruz investigated a connection between the spin rate and tidal energy on Saturn’s moon, Titan, to determine more about Titan’s interior. This study has the potential to help researchers better understand the internal processes of Titan, leading to better constraints on the existence of a subsurface ocean.

For the study, the researchers used a combination of data obtained by NASA’s now-retired Cassini spacecraft and a series of mathematical calculations to determine Titan’s tidal dissipation, which is the amount of tidal energy lost in an object from friction and other processes, and for which the only moons in the solar system this has been successfully been accomplished being the Earth’s Moon and Jupiter’s volcanic moon, Io. Better understanding a moon’s tidal dissipation helps researchers better understand its formation and evolution, which the researchers successfully estimated for Titan.

“Tidal dissipation in satellites affects their orbital and rotational evolution and their ability to maintain subsurface oceans,” said Dr. Brynna Downey, who is a postdoctoral researcher at the Southwest Research Institute in Colorado and lead author of the study. “Now that we have an estimate for the strength of tides on Titan, what does it tell us about how quickly the orbit is changing? What we discovered is that it’s changing very quickly on a geologic timescale.”

Researchers have been working for decades to understand the architecture of the subatomic world. One of the knottier questions has been where the proton gets its intrinsic angular momentum, otherwise referred to as its spin.

Nuclear physicists surmise that the proton’s spin most likely comes from its constituents: quarks bound together by gluons carrying the strong force. But the details of the quark and gluon contributions have remained elusive.

Now, a new investigation from an international collaboration of physicists compiles evidence from observational results and analysis using lattice quantum chromodynamics (QCD) to present a compelling argument regarding how much of the proton’s spin comes from its gluons.

Join Jay Leno in this exclusive episode of Jay Leno’s Garage as we take a first drive and an in-depth tour of the revolutionary 2026 Tesla Model Y! Packed with cutting-edge features, including matrix headlights, improved aerodynamics, and a luxurious, all-new interior, this is Tesla’s most advanced SUV yet. Learn directly from Tesla’s lead designers and engineers about the innovations that make this Model Y a game-changer.

Don’t miss this exciting ride-along packed with performance stats, unique design elements, and behind-the-scenes stories. Buckle up for a closer look at the future of electric vehicles!

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Excitons, encountered in technologies like solar cells and TVs, are quasiparticles formed by an electron and a positively charged “hole,” moving together in a semiconductor. Created when an electron is excited to a higher energy state, excitons transfer energy without carrying a net charge. While their behavior in traditional semiconductors is well understood, excitons act differently in organic semiconductors.

Recent research led by condensed matter physicist Ivan Biaggio focuses on understanding the mechanisms behind dynamics, quantum entanglement, and dissociation in organic molecular crystals.

The paper is published in the journal Physical Review Letters.

Altilium has filed a patent application for its proprietary EcoCathode™ recycling process, underlining its technical leadership in the UK and its commitment to establishing a national champion for EV battery recycling.

The patent provides a process, apparatus and system for recovering battery metals (such as cobalt, manganese, nickel and lithium) and graphite, and the production of battery precursors and battery-ready cathode active materials (CAM), from black mass (comprising a mixed feed of critical compounds or elements).

Through microstructure reengineering, Altilium’s EcoCathode™ process represents a significant stride in clean technology and sustainable EV battery recycling in the UK. Recovering over 95% of crucial metals from old EV batteries, the technology will contribute to a sustainable domestic supply of battery raw materials, reducing carbon emissions by over 50% and reducing the cost of CAM by more than 20% compared to conventional virgin mining practices.

Evolution is traditionally associated with a process of increasing complexity and gaining new genes. However, the explosion of the genomic era shows that gene loss and simplification is a much more frequent process in the evolution of species than previously thought, and may favor new biological adaptations that facilitate the survival of living organisms.

This evolutionary driver, which seems counter-intuitive—” less is more” in genetic terms—now reveals a surprising dimension that responds to the new evolutionary concept of “less, but more,” i.e., the phenomenon of massive gene losses followed by large expansions through gene duplications.

This is one of the main conclusions of an article published in the journal Molecular Biology and Evolution, led by a team from the Genetics Section of the Faculty of Biology and the Institute for Research on Biodiversity (IRBio) of the University of Barcelona, in which teams from the Okinawa Institute of Science and Technology (OIST) have also participated.

Synaptic vesicles (SVs) store and transport neurotransmitters to the presynaptic active zone for release by exocytosis. After release, SV proteins and excess membrane are recycled via endocytosis, and new SVs can be formed in a clathrin-dependent manner. This process maintains complex molecular composition of SVs through multiple recycling rounds. Previous studies explored the molecular composition of SVs through proteomic analysis and fluorescent microscopy, proposing a model for an average SV. However, the structural heterogeneity and molecular architecture of individual SVs are not well described. Here, we used cryoelectron tomography to visualize molecular details of SVs isolated from mouse brains and inside cultured neurons. We describe several classes of small proteins on the SV surface and long proteinaceous densities inside SVs.