Results 101 to 110 of about 111,792 (225)
Advanced Science, EarlyView.A neural network‐enabled permittivity engineering paradigm is introduced, transcending traditional trial‐and‐error design. By decoupling electromagnetic parameters and screening a high‐throughput feature space, an ultrathin (1.0 mm) magnetic absorber is inversely designed, experimentally achieving a superior and customizable 5.1 GHz bandwidth and ...
Chenxi Liu +9 more
wiley +1 more source
MathematicsStock price forecasting remains challenging due to the nonlinear, volatile, multi-scale dynamics of financial time series. This study addresses two core limitations of existing models: incomplete capture of full-spectrum multi-scale temporal dependencies
Zhizhe Lin +5 more
doaj +1 more source
Advanced Science, EarlyView.Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen +9 more
wiley +1 more source
Fine-Tuning LLMs for E-Commerce Sentiment Analysis: Proprietary Versus Open-Source Approaches
IEEE AccessThe increasing volume of online product reviews presents both opportunities and challenges for e-commerce platforms seeking to leverage customer sentiment for strategic decision-making.
Pawanjit Singh Ghatora +3 more
doaj +1 more source
Advanced Science, EarlyView.A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng +8 more
wiley +1 more source
Applied SciencesMachine learning makes significant contributions in many areas of the applied sciences. One of these is the field of education, in the form of predicting students’ academic success and developing educational policies.
Bahar Demirtürk, Tuba Harunoğlu
doaj +1 more source
Mechanistic Analysis of Large Atomic Models of Molten Salt
Advanced Science, EarlyView.This work uncovers the physical mechanism of large atomic models for molten salts by linking atomic contribution to electronic structure features. We demonstrate that energy predictions are physically determined by the local occupancy of frontier orbitals.
Yuliang Guo +3 more
wiley +1 more source
Advanced Science, EarlyView.Fabrication‐induced variability remains a fundamental limitation in the scalable design of soft biomaterials. In this work, a stochastic machine learning approach based on Gaussian processes modeling is employed to establish quantitative links between biofabrication parameters, material properties, and their intrinsic variability.
Maria Alexaki +8 more
wiley +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Forecasting Root Rot Disease through Predictive Microbial Functional Profiling
Advanced Science, EarlyView.Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy.
Chuan You +11 more
wiley +1 more source