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Researchers at NIMTE have turned metal corrosion into a tool for efficient biomass upgrading, achieving high HMF-to-BHMF conversion rates with a CoCuMW/CF electrode. Their findings offer a low-cost, sustainable solution for bio-based chemical production.

A research team led by Prof. Jian Zhang from the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS) has harnessed metal corrosion to develop high-performance electrodes, facilitating the efficient and cost-effective upgrading of bio-based 5-hydroxymethylfurfural (HMF). Their findings were published in Chem Catalysis.

While corrosion is typically associated with material degradation and economic loss, researchers are now investigating its potential for advantageous applications, particularly in biomass upgrading.

A strange molecular pattern, first mistaken for an error, led researchers to an unexpected discovery: molecules forming non-repeating structures similar to the einstein tiling problem.

This phenomenon, driven by chirality and energy balance, could pave the way for novel insights into molecular physics.

At the crossroads of mathematics and tiling lies the einstein problem—a puzzle that, despite its name, has nothing to do with Albert Einstein. The question is simple yet profound: Can a single shape tile an infinite surface without ever creating a repeating pattern? In 2022, English amateur mathematician David Smith discovered such a shape, known as a “proto-tile.”

Startlingly thorough discussion of the changes underway in spaceflight.


This week on NewsNight, the Trump administration’s shake-up of government leads to changes at NASA. The panel looks at the president’s call for an expedited timetable for getting astronauts to Mars, and how cuts to federal spending might affect the space agency. Plus, Governor DeSantis floats relocating NASA headquarters to Florida.

#florida #nasa #space #artemis #trump #spacex.

MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.

Re relying on a weather app to predict next week’s temperature. How do you know you can trust its forecast? Scientists use statistical and physical models to make predictions about everything from weather to air pollution. But checking whether these models are truly reliable is trickier than it seems—especially when the locations where we have validation data don Traditional validation methods struggle with this problem, failing to provide consistent accuracy in real-world scenarios. In this work, researchers introduce a new validation approach designed to improve trust in spatial predictions. They define a key requirement: as more validation data becomes available, the accuracy of the validation method should improve indefinitely. They show that existing methods don’t always meet this standard. Instead, they propose an approach inspired by previous work on handling differences in data distributions (known as “covariate shift”) but adapted for spatial prediction. Their method not only meets their strict validation requirement but also outperforms existing techniques in both simulations and real-world data.

By refining how we validate predictive models, this work helps ensure that critical forecasts—like air pollution levels or extreme weather events—can be trusted with greater confidence.


A new evaluation method assesses the accuracy of spatial prediction techniques, outperforming traditional methods. This could help scientists make better predictions in areas like weather forecasting, climate research, public health, and ecological management.

Technically this year we have a global pandemic but with 11 different viruses that have evolved.


For the first time the pandemic began, deaths from influenza have outpaced deaths from COVID-19 in 22 states, plus New York City and Washington, D.C. Dr. Jon LaPook has the latest numbers.