Results 91 to 100 of about 21,944 (260)

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

First-principles real-space embedding theory of the superconducting proximity effect

Physical Review Research
When a superconductor is placed in contact with a normal material, Cooper pairs penetrate the latter and induce superconductivity via the proximity effect. Despite its central role in quantum materials, superconducting devices, and topological platforms,
Nicolas Baù, Mitra Dowlatabadi, Tommaso Chiarotti, Massimo Capone, Antimo Marrazzo   +4 more
doaj   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source

Robust distance protection for cross-country faults in power grids with high penetration of inverter- based resources

e-Prime: Advances in Electrical Engineering, Electronics and Energy
Cross-country faults can adversely affect the operation of protection devices. Relays whose pickup is based on overcurrent or impedance elements are more likely to fail during cross-country faults.
Jose de Jesus Chavez, Marjan Popov, David López, Vladimir Terzija, Sadegh Azizi   +4 more
doaj   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Uncovering renewable energy policy impact channels on land values, the local farm structure, and farmland heterogeneity

American Journal of Agricultural Economics, EarlyView.
Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt, Stefan Seifert, Saskia Wolff, Tobia Lakes, Marten Graubner, Axel Werwatz, Silke Hüttel   +6 more
wiley   +1 more source

Negotiating contested spaces and places: Narratives of social suffering and resistance in racialized Cape Town communities

American Journal of Community Psychology, EarlyView.
Abstract This study employs a schizocartographic approach to explore community narratives of space, memory, and violence in Kraaifontein, Cape Town. Through participants' accounts, ordinary places—gardens, shops, blocks, sports grounds, and streets—emerge as ambivalent geographies where trauma, resilience, and belonging intersect.
Guido Veronese, Chiara Fiscone, Ashraf Kagee   +2 more
wiley   +1 more source

Stability control of adsorption robot considering external disturbance and parameter uncertainty using RMPC

Measurement + Control
This paper mainly studies the stability of a sea cucumber adsorption robot (SCAR) under external disturbances and parameter uncertainty. As a fishing robot with a suction effect, a dynamic model of its vertical operation is established, taking into ...
Changbin Wang, Dalei Song, Chong Li, Qianli Jiang, Weicheng Sun   +4 more
doaj   +1 more source

Optimizing hydropower scheduling through accurate power load prediction: A practical case study

Heliyon
Hydropower stations that are part of the grid system frequently encounter challenges related to the uneven distribution of power generation and associated benefits, primarily stemming from delays in obtaining timely load data.
Guangqin Huang, Ming Tan, Zhihang Meng, Jiaqi Yan, Jin Chen, Qiang Qu   +5 more
doaj   +1 more source

Navigating AI with pedagogical purpose: Toward an anatomy‐centered framework for AI‐enhanced learning

Anatomical Sciences Education, EarlyView.
Abstract Artificial Intelligence (AI) has emerged as a transformative force in medical education, enabling customized, feedback‐rich, and immersive learning experiences. Anatomy education, as a discipline that is simultaneously visual, spatial, and clinically foundational, occupies a distinctive position within this technological landscape.
Rachel Jayasekhar, Gok Kandasamy
wiley   +1 more source