Results 201 to 210 of about 211,590 (248)

Model‐Inversion‐Resistant Physical Unclonable Neural Network Using Vertical NAND Flash Memory

Advanced Science, EarlyView.
Schematic and key features of the proposed forward‐forward physical unclonable neural network (FF‐PUNN), incorporating a concealable physical unclonable function (PUF) layer and forward‐forward (FF) learning. ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and ...
Sung‐Ho Park, Ryun‐Han Koo, Jonghyun Ko, Jiseong Im, Yeongheon Yang, Mingyun Oh, Dongbeen Shin, Gyuweon Jung, Jong‐Ho Lee   +8 more
wiley   +1 more source

Livestock Tango: U.S. and Latin America Dance Together, but Who Will Lead?

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT This study examines the competitiveness between Latin American and U.S. livestock and meat sectors. We employ a computable general equilibrium modeling framework to evaluate two scenarios: coordinated improvements in Latin American productivity, transport efficiency, and market access (Scenario I), and the minimum productivity gains required ...
Taís C. Menezes, Amanda M. Countryman, Dustin L. Pendell   +2 more
wiley   +1 more source

An infant case of double-chambered left ventricle with extensive non-compaction revealed by intraoperative endoscopy. [PDF]

J Cardiol Cases
Ifuku T, Okada N, Irisa H, Oshima Y.
europepmc   +1 more source

Effects of Environmental and Health Information on Willingness to Pay for Local and Organic Foods in Taiwan

Agribusiness, EarlyView.
ABSTRACT Using a lab‐in‐the‐field experiment, we investigate how providing information about food miles and pesticide residue influences willingness to pay (WTP) for potatoes among 407 shoppers in Taiwan, split between a supermarket and a farmers market.
Chiu‐Lin Huang, Edward C. Jaenicke, Martina Vecchi, Sheng‐Jang Sheu   +3 more
wiley   +1 more source

Timbre perception in violins: spectral and formant influences of string materials in a controlled study. [PDF]

Sci Rep
Asakura T.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Performance of Acoustic, Electro-Acoustic and Optical Sensors in Precise Waveform Analysis of a Plucked and Struck Guitar String. [PDF]

Sensors (Basel)
Jasiński J, Pluta M, Trojanowski R, Grygiel J, Wiciak J.   +4 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

A novel absorbable string-loop suturing device for closing a large colonic defect spanning anastomosis after endoscopic submucosal dissection. [PDF]

Endoscopy
Song S, Rao X, Cai Y, Guo X, Rong L.
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source