Results 101 to 110 of about 167,467 (260)
Machine Learning for Green Solvents: Assessment, Selection and Substitution
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta +4 more
wiley +1 more source
In contemporary artificial intelligence research, overfitting is typically regarded as a pathological failure mode that leads to poor generalization. This paper challenges that prevailing view by reinterpreting overfitting not as a defect to be eliminated, but as a necessary condition for the formation of a self-consistent internal model, namely, the ...
openaire +1 more source
Dissecting the Ecological Structure of Health and Disease in the Global Gut Microbiome
We introduce Wiredancer, a framework that identifies three continuous ecological factors of the gut microbiota. These factors exhibit distinct patterns across health and disease, jointly capturing disrupted ecological stability and offering a new perspective for precision diagnostics and therapeutic strategies.
Baoyuan Zhu +19 more
wiley +1 more source
This study constructed the first spatiotemporal multi‐omics map of peach fruit and discovered a key candidate gene that synergistically regulates trichome development and drought tolerance through the jasmonic acid signaling pathway, providing insights into the coupling mechanism between development and stress resistance.
Zhixin Liu +9 more
wiley +1 more source
Research on Surrogate Model of Dam Structural Behavior for Multi‐Output Problem
The establishment efficiency of the surrogate model is often affected by the multi‐output problem during the establishment process. It is an urgent issue to solve how to establish a multi‐output joint surrogate model more quickly while ensuring a certain
Yuan Qiao +3 more
doaj +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
High‐throughput single‐cell analysis of resuscitating bacteria reveals a starvation‐history‐dependent transiently tolerant subpopulation that survives β$\beta$‐lactam exposure by temporarily reducing growth. Distinct from classical persisters, these actively growing yet dynamically modulated cells dominate survival across clinically relevant antibiotic
Kieran Abbott +5 more
wiley +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
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
This study achieves anisotropic thermal expansion tuning in Nd2(Co1‐xFex)17‐yCry compounds via a magnetoelastic strategy. Variable‐temperature synchrotron X‐ray diffraction reveals that increased Fe content induces switchable lattice responses. Compositional control reduces the volume expansion coefficient αV by 20% (x═0.7) and modulates TC (442–625 K),
Jiayuan Li +8 more
wiley +1 more source

