Results 81 to 90 of about 8,902 (235)

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

Generalized Zagreb index of some dendrimer structures

Universal Journal of Mathematics and Applications, 2018
Chemical graph theory, is a branch of mathematical chemistry which deals with the nontrivial applications of graph theory to solve molecular problem. A chemical graph is represent a molecule by considering the atoms as the vertices and bonds between them
Anita Pal, Prosanta Sarkar, İsmail Naci Cangül, Nilanjan De   +3 more
doaj   +1 more source

Streptococcal Mannose Phosphotransferase System Component IID Is a Novel RANK‐Binding Osteoclastogenic Factor

Advanced Science, EarlyView.
Streptococcal mannose phosphotransferase system component IID (Man‐PTSIID) is identified as a novel RANK‐binding osteoclastogenic factor. By directly binding to RANK and activating NF‐κB independently of TLR2, Man‐PTSIID drives osteoclastogenesis and inflammatory bone destruction, uncovering an unexpected microbial mechanism underlying streptococcal ...
Chaeyeon Park, Yeongkag Kwon, Yeonjin Lim, Jeong Woo Park, Hyun Jung Ji, Dongwook Lee, Jueun Lee, Sung‐Ho Yun, Sungho Jeong, Ho Seong Seo, Kun Cho, Cheol‐Heui Yun, Ok‐Jin Park, Seung Hyun Han   +13 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Record Dissymmetry in Vibrational Optical Activity: Combining Vibronic Coupling and Aggregation in Cobalt(II) Camphorate Complexes

Angewandte Chemie, EarlyView.
The cobalt(II) bis(trifluoroacetylcamphorate) scaffold exhibits versatile coordination chemistry with solvent‐driven ligand exchange and geometrical rearrangements, associated with unique chiroptical properties. Microcrystalline suspension of [Co(tfc)2(CH3CN)2] revealed the largest VCD dissymmetry factor ever reported (g ≈ 0.2 at 1600 cm−1), arising ...
Gianmarco Papi, Massimo Guelfi, Stefano Zacchini, Fabio Marchetti, Gennaro Pescitelli   +4 more
wiley   +2 more sources

Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?

Agribusiness, EarlyView.
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Programmable Flocks: Hierarchical Swarm Control via Dynamic Parameter Injection

Advanced Intelligent Systems, EarlyView.
We present a method for the control of robot swarms which allows the shaping and the translation of patterns of simple robots (“smart particles”), using two types of devices. These two types represent a hierarchy: a larger group of simple, oblivious robots (which we call the workers) that is governed by simple local attraction forces and a smaller ...
Vivek Shankar Varadharajan, Giovanni Beltrame   +1 more
wiley   +1 more source