Menu

Blog

Page 3205

Nov 1, 2022

Efficiency and stability best practices for solar water splitting to make hydrogen

Posted by in categories: chemistry, solar power, sustainability

Scientists from the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) and Lawrence Berkeley National Laboratory (Berkeley Lab) are providing researchers with a guide to how to best measure the efficiency of producing hydrogen directly from solar power.

Photoelectrochemical (PEC) water-splitting, which relies on sunlight to split water into its component elements—oxygen and hydrogen—stands out as potentially one of the most sustainable routes to clean energy. Measurements of how efficient the PEC process is on an identical system can vary wildly from different laboratories, however, from a lack of standardized methods. The newly developed best-practices guide published in Frontiers in Energy Research is intended to provide confidence in comparing results obtained at different sites and by different groups.

The publication provides a road map for the PEC community as researchers continue to refine the technology. These were verified by both laboratories via round-robin testing using the same testing hardware, PEC photoelectrodes, and measurement procedures. Research into photovoltaics has allowed a certification of cell efficiencies, but PEC water-splitting efficiency measurements do not yet have a widely accepted protocol.

Nov 1, 2022

New study links suffering from long-lasting severe depression to reduction in brain volume

Posted by in categories: biotech/medical, neuroscience

A study on a large sample of patients found chronic, long-lasting depression to be associated with reduced brain volume. The reduced volume was found in brain regions relevant for planning one’s behavior, focusing attention, thinking, learning and remembering and also in regions relevant for regulating emotions. The study was published in Neurobiology and Treatment of Depression.

Depression, also called major depressive disorder, is a mood disorder that causes a persistent feeling of sadness and loss of interest. It changes the way a person feels, thinks and behaves. For many people suffering from it, depressive episodes become a recurring event. More than half of patients with depression experience a relapse after 2 years and the probability of recurrent depressive episodes rises to 90% after 3–4 episodes. Studies have indicated that recurring depressive episodes might be linked to structural changes in the brain, but the existing results are not uniform.

Ms. Hannah Lemke and her colleagues analyzed the data of 681 patients from the Marburg-Muenster-Affective-Cohort Study (MACS) in order to better link properties of the course of depressive disorder with specific changes in the brain structure. Patient data were collected at two sites in Germany – Muenster and Marburg.

Nov 1, 2022

New computational method builds detailed maps of human tissues

Posted by in categories: biotech/medical, computing

Weill Cornell Medicine researchers have developed a computational method to map the architecture of human tissues in unprecedented detail. Their approach promises to accelerate studies on organ-scale cellular interactions and could enable powerful new diagnostic strategies for a wide range of diseases.

The method, published Oct. 31 in Nature Methods, grew out of the scientists’ frustration with the gap between classical microscopy and modern single-cell molecular analysis. “Looking at tissues under the microscope, you see a bunch of cells that are grouped together spatially—you see that organization in images almost immediately,” said lead author Junbum Kim, a graduate student in physiology and biophysics at Weill Cornell Medicine.

“Now, have gained the ability to examine in tremendous detail, down to which genes each cell is expressing, so they’re focused on the cells instead of focusing on the tissue structure,” he said.

Nov 1, 2022

Scientists Engineered Super Bacteria That Are Alien to All Life on Earth

Posted by in categories: bioengineering, genetics

On the other, because organisms share the same universal code, they’re vulnerable to outside attacks from viruses and other pathogens—and can transfer their new capabilities to natural organisms, even if it kills them.

Why not build a genetic firewall?

A recent study in Science did just that. The team partially reworked the existing genetic code into a “cipher” that normal organisms can’t comprehend. Similarly, the engineered bacteria lost its ability to read the natural genetic code. The tweaks formed a powerful language barrier between the engineered bacteria and natural organisms, isolating each from sharing genetic information with the other.

Nov 1, 2022

Flowers for Algernon — science fiction by Daniel Keyes (Audiobook)

Posted by in category: futurism

Is a science fiction short story and subsequent novel written by Daniel Keyes.

Nov 1, 2022

Ted Chiang Understand Audiobook

Posted by in category: futurism

Sci fiction Audiobooks Ted Chiang Understand.

Nov 1, 2022

Hyperbolic Propagation: Columbia Physicists See Light Waves Moving Through a Metal

Posted by in categories: materials, quantum physics

New research finds evidence of waveguiding in a unique quantum material. These findings counter expectations about how metals conduct light and may push imaging beyond optical diffraction limits.

We perceive metals as shiny when we encounter metals in our day-to-day lives. That’s because common metallic materials are reflective at visible light wavelengths and will therefore bounce back the light that strikes them. Although metals are well suited to conducting electricity and heat, they aren’t typically thought of as a means to conduct light.

However, scientists are increasingly finding examples that challenge expectations about how things should behave in the burgeoning field of quantum materials. New research describes a metal capable of conducting light through it. Conducted by a team of researchers led by Dmitri Basov, Higgins Professor of Physics at Columbia University.

Nov 1, 2022

Supernova Explosions Reveal Precise Details of Dark Energy and Dark Matter

Posted by in categories: cosmology, evolution, physics

An analysis of more than two decades’ worth of supernova explosions convincingly boosts modern cosmological theories and reinvigorates efforts to answer fundamental questions.

A powerful new analysis has been performed by astrophysicists that places the most precise limits ever on the composition and evolution of the universe. With this analysis, dubbed Pantheon+, cosmologists find themselves at a crossroads.

Pantheon+ convincingly finds that the cosmos is made up of about two-thirds dark energy and one-third matter — predominantly in the form of dark matter — and is expanding at an accelerating pace over the last several billion years. However, Pantheon+ also cements a major disagreement over the pace of that expansion that has yet to be solved.

Nov 1, 2022

Japan records over 10,000 syphilis cases for first time

Posted by in category: biotech/medical

The number of syphilis cases in Japan this year has exceeded 10,000 for the first time since comparable data became available in 1999.

Japan’s National Institute of Infectious Diseases says 10,141 cases were reported as of October 23. That is about 1.7 times the figure for the same period last year, which was a record high.

Syphilis is a bacterial infection transmitted mainly through sexual contact. Symptoms may quickly disappear, or not appear at all. So, infected people could spread the disease without knowing.

Nov 1, 2022

Learning at the Speed of Light

Posted by in category: robotics/AI

Of course running a state of the art machine learning model, with billions of parameters, is not exactly easy when memory is measured in kilobytes. But with some creative thinking and a hybrid approach that leverages the power of the cloud and blends it with the advantages of tinyML, it may just be possible. A team of researchers at MIT has shown how this may be possible with their method called Netcast that relies on heavily-resourced cloud computers to rapidly retrieve model weights from memory, then transmit them nearly instantaneously to the tinyML hardware via a fiber optic network. Once those weights are transferred, an optical device called a broadband “Mach-Zehnder” modulator combines them with sensor data to perform lightning-fast calculations locally.

The team’s solution makes use of a cloud computer with a large amount of memory to retain the weights of a full neural network in RAM. Those weights are streamed to the connected device as they are needed through an optical pipe with enough bandwidth to transfer an entire full feature-length movie in a single millisecond. This is one of the biggest limiting factors that prevents tinyML devices from executing large models, but it is not the only factor. Processing power is also at a premium on these devices, so the researchers also proposed a solution to this problem in the form of a shoe box-sized receiver that performs super-fast analog computations by encoding input data onto the transmitted weights.

This scheme makes it possible to perform trillions of multiplications per second on a device that is resourced like a desktop computer from the early 1990s. In the process, on-device machine learning that ensures privacy, minimizes latency, and that is highly energy efficient is made possible. Netcast was test out on image classification and digit recognition tasks with over 50 miles separating the tinyML device and cloud resources. After only a small amount of calibration work, average accuracy rates exceeding 98% were observed. Results of this quality are sufficiently good for use in commercial products.