U.S. Agriculture, Biofuel Markets, and Trade: Challenges and Opportunities
ABSTRACT Using an enhanced Computable General Equilibrium (CGE) model (GTAP‐BIO), this study assesses how the expansion in demand for Electric Vehicles (EVs) and the reduction in exports of agricultural products induced by trade disputes negatively affect US agriculture.
Rayan Wolf, Farzad Taheripour
wiley +1 more source
Autonomous AI‐Driven Design for Skin Product Formulations
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang +5 more
wiley +1 more source
An Optimized Particle Swarm Algorithm for High-Precision Camera Calibration with Enhanced Wide-Angle Distortion Correction. [PDF]
Ji Q +7 more
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti +6 more
wiley +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source
Differentiable Forward and Back-Projector for Rigid Motion Estimation in X-Ray Imaging. [PDF]
Jiang X +4 more
europepmc +1 more source
Behaviorally Adaptive and Inclusive Advanced Driver‐Assistance Systems
Advanced driver‐assistance systems (ADASs) are mapped as evolving human‐centered, adaptive technologies linking sensing, driver monitoring, AR/HUD interfaces, patents, regulation, and inclusive design. The review identifies gaps in real‐world evidence, diverse‐driver validation, gaze metrics, and governance, outlining a roadmap for safer, behaviorally ...
Jana Skirnewskaja +2 more
wiley +1 more source
Motion artifacts in electrocardiographic signals, conventionally dismissed as noise, are shown to encode discriminative activity information. A smart t‐shirt fusing textile strain sensors with textile ECG electrodes, processed through a complex‐valued residual network, recognizes 12 sport activities.
Nada Al‐azzawi +4 more
wiley +1 more source
Exposure-Midpoint Temporal Alignment and Risk-Aware Adaptive Feature Tracking for Stereo Visual-Inertial Odometry. [PDF]
Yang S, Liu Q, Zhuang Z, Shen X.
europepmc +1 more source

