Results 191 to 200 of about 403,145 (258)

Learning Health Systems Symposium: Charting the Future of Saskatchewan Healthcare. [PDF]

Learn Health Syst
Haver C, Azizian AR, Weise C, Cary M, King M, Shaw S, Avis K, Bomfim E, Osman BA, Groot G.   +9 more
europepmc   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

Stranded assets in European agriculture during food system transformations. [PDF]

Nat Food
Kortleve AJ, Mogollón JM, Harwatt H, Bruckner M, Liu B, Behrens P.   +5 more
europepmc   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source

Optimising regional care delivery systems targeting adults with heart failure and mental health interconnected conditions: a participatory action research study protocol. [PDF]

BMJ Open
Philip S, Dahrouge S, Valade RL, Hammond E, Aomreore A, Hosseini M, Archibald D, Bandk K, Antunes P, Assaouré J, Benoit P, Plourde D, Sabbagh R, Skaff E, Seguin J, Tanguay E, Welch V, Liu P, Kehoe MacLeod K.   +18 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Women's empowerment as a driver to household food security in the Eastern Cape Province, South Africa: a structural equation model approach. [PDF]

Front Sociol
Katiyatiya CLF, Ncanywa T.
europepmc   +1 more source

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

Implementation and evaluation of the Y-Check comprehensive adolescent health check-up intervention in Zimbabwe: a pre-post mixed-methods study. [PDF]

Nat Med
Doyle AM, Nzvere F, Manyau S, Simms V, Li Lin I, Kandiye FR, Nyamayaro CA, Takawira M, Chingono RMS, Tembo M, Manhibi R, Dauya E, Dziva Chikwari C, Greco G, Bernays S, Baltag V, Maisiri H, Kasu T, Nyamayaro W, Bandason T, Mackworth-Young CRS, Banati P, Weiss HA, Ross DA, Ferrand RA.   +24 more
europepmc   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source