Spatiotemporal data consisting of measurements gathered at different times and locations is challenging to analyse due to variability and noise impact across different scales. The authors propose a statistical approach that delivers models of large-scale spatiotemporal datasets applicable to data-analysis tasks of forecasting and interpolation.
Noncanonical amino acids are efficiently incorporated into proteins by optimizing mRNA codon usage.
The principles of thermodynamics are cornerstones of our understanding of physics. But they were discovered in the era of steam-driven technology, long before anyone dreamed of quantum mechanics. In this episode, the theoretical physicist Nicole Yunger Halpern talks to host Steven Strogatz about how physicists today are reinterpreting concepts such as work, energy and information for a quantum world.
Listen on Apple Podcasts, Spotify, TuneIn or your favorite podcasting app, or you can stream it from Quanta.
The AI scene is electrified with groundbreaking advancements this month, keeping us all at the edge of our seats. A mind-blowing AI robot with human-like intelligence has the world in shock. Google DeepMind’s JEST AI learns at an astonishing 13x faster pace. OpenAI’s SearchGPT and CriticGPT, the force behind ChatGPT’s prowess, are disrupting industries. STRAWBERRY, their most powerful AI yet, takes center stage. GPT4ALL 3.0 is the AI sensation causing a frenzy, while OpenAI’s AI Health Coach promises personalized wellness solutions. Llama 3.1 emerges as a contender, and NeMo AI boasts a massive 128k context capacity, running locally and free. Microsoft’s new AI Search could redefine how we navigate information, while OpenAI’s latest unnamed model has the tech world buzzing with anticipation.
Become a Member of the channel and Supporter of AI Revolution → / @airevolutionx.
However, the yeast should be treated to rid compounds that can increase the risk of gout if consumed excessively. Even so, treated yeast still meets 41% of the daily protein requirement, comparable to traditional protein sources.
This technology aims to address several global challenges: environmental conservation, food security, and public health. Running on clean energy and CO2, the system reduces carbon emissions in food production. It uncouples land use from farming, freeing up space for conservation.
Angenent also stresses that it will not outcompete farmers. Instead, the technology will help farmers concentrate on producing vegetables and crops sustainably. The team’s yeast may also help developing nations overcome food scarcity and nutritional deficiencies by delivering protein and vitamin B9.
Researchers at Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology at the University of Nottingham have developed ultra-thin soft robots, designed for exploring narrow spaces in challenging built environments. The research is published in the journal Nature Communications.
These advanced robots, featuring multimodal locomotion capabilities, are set to transform the way industries, such as power plants, bridges and aero engines, conduct inspections and maintenance.
The innovative robots, known as Thin Soft Robots (TS-Robots), boast a thin thickness of just 1.7mm, enabling them to access and navigate in confined spaces, such as millimeter-wide gaps beneath doors or within complex machinery.
Wenn wir unsere Augen öffnen, dann fällt es uns ganz leicht, die verschiedene Objekte, Menschen und Tiere um uns herum zu sehen. Bisher war die weitreichende Forschungsmeinung, dass ein ganz wesentliches Ziel unserer Wahrnehmung ist, Objekte zu erkennen und verschiedenen Kategorien zuzuordnen – zum Beispiel, ob dieses Objekt vor uns ein Hund ist und ob ein Hund zur Kategorie der Tiere zählt. Forschende vom Max-Planck-Institut für Kognitions-und Neurowissenschaften in Leipzig und der Justus-Liebig-Universität Gießen in Zusammenarbeit mit den National Institutes of Health in den USA konnte nun zeigen, dass dieses Bild unvollständig ist. In einer aktuellen Studie im Fachjournal Nature Human Behaviour schreiben sie, dass sich die Hirnaktivität beim Sehen von Objekten viel besser mit einer Vielzahl verhaltensrelevanter Dimensionen erklären lässt.
Bisher dachte man, dass das visuelle System in unserem Gehirn die gesehenen Objekte in sehr grundlegende Merkmale zerlegt und dann nach und nach wieder zusammensetzt, mit dem Ziel, deren Erkennen zu ermöglichen. „Unsere Ergebnisse haben gezeigt, dass Erkennen und Kategorisieren zwar wichtige Ziele unseres Sehens sind, aber bei weitem nicht die einzigen.“, sagt Letztautor Martin Hebart, Gruppenleiter am MPI CBS und Professor an der Justus-Liebig-Universität. „Tatsächlich finden wir verhaltensrelevante Signale an allen Verarbeitungsstufen im visuellen System. Dies konnten wir aus der Analyse der von uns entdeckten verhaltensrelevanten Dimensionen ableiten.” Im Vorfeld hatten die Forscher mit einem Computermodell aus Verhaltensdaten von über 12.000 Studienteilnehmer*innen 66 Objektdimensionen identifiziert.
Given the right conditions, certain types of cells are able to self-assemble into new lifeforms after the organism they were once part of has died.
In polymers, the competition between the folding and aggregation of chains, both at an individual level and between chains, can determine the mechanical, thermal, and conductive properties of such materials. Understanding the interplay of folding and aggregation presents a significant opportunity for the development and discovery of polymeric materials with tailored properties and functionalities.
Google researchers have created an innovative AI model called Health Acoustic Representations (HeAR), designed to identify acoustic biomarkers for diseases like tuberculosis.
It can listen to human sounds and flag early signs of disease.
Continue reading “New AI model helps researchers detect disease based on coughs” »
