Results 161 to 170 of about 215,422 (309)

Preventing a dropout [PDF]

British Dental Journal, 2007
openaire   +2 more sources

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

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

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

Construction and validation of an instrument to assess the university dropout intention formation process UDIFP-29. [PDF]

PLoS One
Angulo YL, Muñoz-Inostroza K, Sáez-Delgado F, Mella-Norambuena J, Zalaquett CP.   +4 more
europepmc   +1 more source

Science Dropouts [PDF]

Science, 1964
openaire   +2 more sources

Factors Affecting Recollapse of the Augmented Vertebrae After Percutaneous Vertebral Augmentation: A Prospective Study

AGING MEDICINE, EarlyView.
To investigate the relevant factors of augmented vertebrae recollapse after percutaneous vertebral augmentation (PVA) for the treatment of osteoporotic vertebral compression fractures (OVCFs). Intervertebral cleft (IVC) and those with PVP intervention are at higher risk of recollapse.
Yawen Zhang, Junchuan Liu, Maoyu Zhao, Yudian Qiu, Quan Ji, Nan Min, Qiang Wang   +6 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

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

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source