Results 81 to 90 of about 139,608 (260)

Systematic Review and Meta‐Analysis of Short‐ and Long‐Term Outcomes Following Natural Orifice Specimen Extraction for Colon Cancer

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Natural orifice specimen extraction (NOSE) in colon cancer surgery raises concerns about intra‐abdominal infection, peritoneal seeding, and local recurrence due to possible tumor cell implantation. This systematic review and meta‐analysis compares complete intracorporeal resection with NOSE versus conventional laparoscopic colon ...
Daichi Kitaguchi   +4 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

open access: yesAdvanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour   +5 more
wiley   +1 more source

Arrovian Aggregation in Economic Environments: How Much Should We Know About Indifference Surfaces? [PDF]

open access: yes
Arrow's celebrated theorem of social choice shows that the aggregation of individual preferences into a social ordering cannot make the ranking of any pair of alternatives depend only on individual preferences over that pair, unless the fundamental weak ...
Fleurbaey, Marc   +2 more
core   +3 more sources

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

open access: yesAdvanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar   +3 more
wiley   +1 more source

A Noisy Model of Individual Behaviour. [PDF]

open access: yes
This paper develops a model of individual adjustment subject to mistakes. In this case when mistakes are assumed i.i.d., this process produces a probability distribution of agents decision whose evolution is determined by Fokker-Planck equation.
Basov, S.
core  

Counting Combinatorial Choice Rules [PDF]

open access: yes, 2004
I count the number of combinatorial choice rules that satisfy certain properties: Kelso-Crawford substitutability, and independence of irrelevant alternatives.
Echenique, Federico
core  

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

open access: yesAdvanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia   +3 more
wiley   +1 more source

Horizontal Mergers with Free Entry in Differentiated Oligopolies [PDF]

open access: yes
Antitrust authorities view the possibility of entry as a key determinant of whether a proposed merger will be harmful to society. This paper examines the effects of horizontal mergers in models of non-localized, differentiated Bertrand oligopoly that ...
Daniel Piccinin, Nisvan Erkal
core  

Modeling industrial location decisions in U.S. counties [PDF]

open access: yes, 2002
Given its sound theoretical underpinnings, the RandomUtilityMaximizationbased conditional logit model (CLM) serves as the principal method for applied research on industrial location decisions.
Figueiredo, Octávio   +2 more
core  

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

open access: yesAdvanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee   +3 more
wiley   +1 more source

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