Results 191 to 200 of about 95,777 (258)

Using physics‐informed neural networks to quantify submarine groundwater discharge under high‐frequency tidal dynamics using heat as a tracer

Limnology and Oceanography: Methods, Volume 24, Issue 2, February 2026.
Abstract Estimating exchange rates of submarine groundwater discharge (SGD) at high temporal resolution over extended periods remains challenging, particularly when using heat as a tracer in highly dynamic environments such as tidal systems. Currently available heat transport models struggle to accurately quantify SGD exchange rates in these settings ...
S. Frei, M. U. Munir, A. M. Seiverth, B. S. Gilfedder   +3 more
wiley   +1 more source

An adaptive, energy-efficient and secure routing protocol for zone-related mobile Ad-hoc networks using reinforcement learning. [PDF]

Sci Rep
Singh SB, Rizvi MA, Saxena K, Gupta R, Tripathi AN, Dewangan NK.   +5 more
europepmc   +1 more source

A tandem reinforcement learning framework for localized prostate cancer treatment planning and machine parameter optimization

Medical Physics, Volume 53, Issue 2, February 2026.
Abstract Background Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) is a complex, high‐dimensional problem typically solved with inverse planning solutions that are both temporally and computationally expensive. While machine learning techniques have been explored to automate this process, they often supplement rather than ...
Nathan Shaffer, Avinash Reddy Mudireddy, Joel St‐Aubin   +2 more
wiley   +1 more source

Research on reliability of capacitors and transistors based on BP neural network and Icepak simulation. [PDF]

Sci Rep
He Y, Yang X, Zhai X.
europepmc   +1 more source

Deep Neural Network With a Smooth Monotonic Output Layer for Dynamic Risk Prediction

Statistics in Medicine, Volume 45, Issue 3-5, February 2026.
ABSTRACT Risk prediction is a key component of survival analysis across various fields, including medicine, public health, economics, engineering, and others. The fundamental concern of risk prediction lies in the joint distribution of risk factors and the time to event.
Zhiyang Zhou, Yu Deng, Lei Liu, Hongmei Jiang, Yifan Peng, Xiaoyun Yang, Yun Zhao, Hongyan Ning, Norrina B. Allen, John T. Wilkins, Kiang Liu, Donald M. Lloyd‐Jones, Lihui Zhao   +12 more
wiley   +1 more source

Decision-Support for Restorative Dentistry: Hybrid Optimization Enhances Detection on Panoramic Radiographs. [PDF]

Healthcare (Basel)
Ateş G, Türk F, Akçın ET, Güngör M.   +3 more
europepmc   +1 more source

Bayesian Inference via GeTex‐OTS Based Stochastic Synapse for Uncertainty‐Aware Medical Diagnostics

SmartMat, Volume 7, Issue 1, February 2026.
This work reports a GeTex ovonic threshold switch integrated into a compact 1S1T1R stochastic synapse that directly realizes an MC‐Dropconnect Bayesian neural network. Tunable probabilistic switching enables uncertainty‐aware COVID‐19 diagnosis and MNIST recognition while remaining compatible with conventional 1T1R CIM architectures, highlighting a ...
Xinyu Wen, Lun Wang, Kuan Wang, Vivian Zhao, Zixuan Liu, Kexun He, Jianguo Yang, Hao Tong, Xiangshui Miao, Yuhui He   +9 more
wiley   +1 more source

Hybrid quantum-classical photonic neural networks. [PDF]

Npj Unconv Comput
Austin T, Bilodeau S, Hayman A, Rotenberg N, Shastri BJ.   +4 more
europepmc   +1 more source

Impacts of Climate Change and Human Activities on Global Mountain Grasslands: Insights Into the Last Two Decades and Future Climate Scenarios

Earth's Future, Volume 14, Issue 2, February 2026.
Abstract Mountain grasslands are vital ecosystems providing critical services such as carbon sequestration, water regulation, and biodiversity conservation. However, these ecosystems are increasingly threatened by climate change and human activities. This study evaluates vegetation dynamics in global mountain grasslands (2000–2021) using remote sensing
Mulun Na, Giulia Zuecco, Paolo Tarolli
wiley   +1 more source