Results 171 to 180 of about 29,182 (301)

An operational target trial emulation framework for causal inference using electronic health record data. [PDF]

NPJ Digit Med
Wang Y, Li Y, Lin T, Guo Y.
europepmc   +1 more source

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

Data-driven discovery of digital twins in biomedical research. [PDF]

Brief Bioinform
Métayer C, Ballesta A, Martinelli J.
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

Modeling the Phillips curve with unobserved components

The relationship between in.ation and the output gap can be modeled simply and effectively by including an unobserved random walk component in the model.
Harvey, A.
core  

Irreversible Effects of Affiliation With Delinquent Peers on Cyberbullying Perpetration Among Adolescents in Hong Kong: Moderating Effect of Student-Teacher Relationships. [PDF]

Behav Sci Law
Han Y, Chen JK.
europepmc   +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

Epidemiological and antigenic inferences from serological cross-reactivity among arboviruses. [PDF]

Sci Transl Med
O'Driscoll M, Hozé N, Lefrancq N, Ribeiro Dos Santos G, Hoinard D, Rahman MZ, Paul KK, Naser Titu AM, Alam MS, Hossain ME, Vanhomwegen J, Cauchemez S, Gurley ES, Salje H.   +13 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

An Overview and Recent Developments in the Analysis of Multistate Processes. [PDF]

Stat Med
Gorfine M, Cook RJ, Kragh Andersen P, Therneau TM, Joly P, Putter H, Pohar Perme M, Abrahamowicz M, Topic Group 8 “Survival Analysis” of the STRATOS Initiative.   +8 more
europepmc   +1 more source