Results 131 to 140 of about 175,760 (266)

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Uncertainty Quantification of Central Canal Stenosis Deep Learning Classifier From Lumbar Sagittal T2-Weighted MRI. [PDF]

JOR Spine
Brenzikofer A, Monzon M, Galbusera F, Manjaly ZM, Cina A, Jutzeler CR.   +5 more
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Socio-psychological predictors of school dropout intention among Italian adolescents: evidence from a large-scale study. [PDF]

Front Psychol
Ruzzante F, Loconte R, Romeo M, Sesso G, D'Arcangelo S, Maggi F, Ricciardi E, Pietrini P.   +7 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Rethinking the prediction and prevention of dropout in digital mental health. [PDF]

World Psychiatry
Linardon J.
europepmc   +1 more source

Do Universal Free School Meals Improve the Dietary Quality of Food‐At‐Home Purchases?

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Since 2014, the number of schools offering universal free meals to all enrolled children without requiring annual meal applications has increased meaningfully. Using USDA's Purchase to Plate Crosswalk, a difference‐in‐differences framework, and a nationwide consumer panel, the effect of universal‐free‐meal exposure on the diet quality of food ...
Xueying Ma, Andres Cuadros‐Meñaca, Michael R. Thomsen   +2 more
wiley   +1 more source

Blockchain‐Based Smart Contracts in US Specialty Crop Marketing: Grower Preferences and Adoption Potential

Agribusiness, EarlyView.
ABSTRACT Using survey and discrete choice experiment data, we examined US specialty crop growers' preferences for marketing contract attributes in the context of emerging blockchain‐based technologies and expanding traceability initiatives. Results show that farmers preferred traditional written contracts but might be willing to accept digital ...
Elizabeth Canales, Alba J. Collart, Matthew G. Interis, Esther Mmenaa Agyemang‐Duah   +3 more
wiley   +1 more source

Immunization continuity failures and measles vaccine dropout in a fragile urban setting: Evidence from Mogadishu, Somalia. [PDF]

Public Health Pract (Oxf)
Hussein AS, Osman AN, Ahmed GD, Ibrahim LA, Mohamed SH, Mohamed SJ, Abdullahi AA.   +6 more
europepmc   +1 more source