Results 91 to 100 of about 31,545 (295)

Contemporary Regional Disparities in Robotic‐Assisted Rectal Resection in Japan: A Nationwide Population‐Based Study Using the National Database Open Data

Annals of Gastroenterological Surgery, EarlyView.
Robotic‐assisted rectal resection in Japan increased markedly after national insurance reimbursement in 2018, with a concurrent decline in open surgery. Using NDB Open Data, we found substantial inter‐prefectural heterogeneity in surgical volume and robotic utilization that persisted after age and sex standardization (SCR). Urban–rural differences were
Ryo Ohta, Takeshi Yamada, Key Uehara, Hiromichi Sonoda, Akihisa Matsuda, Seiichi Shinji, Yasuyuki Yokoyama, Goro Takahashi, Nobuhiko Taniai, Hiroshi Yoshida   +9 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Weather based forewarning model for cotton pests using zero-inflated and hurdle regression models

Journal of Agrometeorology
Early forewarning of crop pest based on weather variables provides lead time to manage impending pest attacks that minimize crop loss, decrease the cost of pesticides and enhance the crop yield.
N. NARANAMMAL, S.R. KRISHNA PRIYA
doaj   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Bayesian Regularisation in Structured Additive Regression Models for Survival Data [PDF]

, 2008
During recent years, penalized likelihood approaches have attracted a lot of interest both in the area of semiparametric regression and for the regularization of high-dimensional regression models.
Konrath, Susanne, Kneib, Thomas, Fahrmeir, Ludwig   +2 more
core   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Poisson Autoregression [PDF]

This paper considers geometric ergodicity and likelihood based inference for linear and nonlinear Poisson autoregressions. In the linear case the conditional mean is linked linearly to its past values as well as the observed values of the Poisson process.
Dag Tjøstheim, Anders Rahbek, Konstantinos Fokianos   +2 more
core  

Bias of Maximum-Likelihood estimates in logistic and Cox regression models: A comparative simulation study [PDF]

, 2003
Parameter estimates of logistic and Cox regression models are biased for finite samples. In a simulation study we investigated for both models the behaviour of the bias in relation to sample size and further parameters.
Lenz-Tönjes, Rebecca, Blettner, Maria, Küchenhoff, Helmut, Bender, R., Lenz-Tönjes, R., Langner, Ingo, Langner, I., Bender, Ralf   +7 more
core   +1 more source