Results 171 to 180 of about 2,052,393 (261)

Modeling surgeon belief updating under bias: a Bayesian simulation in shoulder arthroplasty. [PDF]

JSES Int
Menendez ME, Moverman MA, Namdari S, Matsen FA, Ring D.   +4 more
europepmc   +1 more source

Pyrazole‐Derived Antibacterial Compounds Effectively Treat Methicillin‐Resistant Staphylococcus Aureus Infections by Inhibiting Aspartate Transcarbamoylase

Advanced Science, EarlyView.
This study unveils a novel antibacterial mechanism against MRSA, in which the compound Py‐27 selectively targets and inhibits aspartate transcarbamoylase (ATCase), a key enzyme in pyrimidine synthesis. This inhibition disrupts DNA replication, induces oxidative damage, leading to potent bactericidal activity.
Xiaorong Yang, Xinyuan Cao, Lixia Dai, Feng Yang, Jing Wang, Yudong Ma, Tong Bu, Zile Gong, Xueyan Liu, Changcai Bai, Xiaolou Miao, Xiaofei Shang   +11 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Neural correlates of Bayesian social belief updating in the medial prefrontal cortex. [PDF]

Cereb Cortex
Hofmans L, van den Bos W.
europepmc   +1 more source

Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations

Advanced Electronic Materials, EarlyView.
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka, Akito Tateyama, Hina Kitano, Takashi Nakanishi, Kazuya Terabe, Takashi Tsuchiya   +5 more
wiley   +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

Similar network compositions, but distinct neural dynamics underlying belief updating in environments with and without explicit outcomes. [PDF]

Neuroimage, 2022
Fiore VG, Gu X.
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

The narrow search effect and how broadening search promotes belief updating. [PDF]

Proc Natl Acad Sci U S A
Leung E, Urminsky O.
europepmc   +1 more source