Results 131 to 140 of about 9,149 (290)

“Intrapericardial Approach” for Venous Outflow Reconstruction in Living‐Donor Liver Transplantation for Budd‐Chiari Syndrome: Surgical Techniques and LongTerm Outcomes

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Unlike deceased‐donor liver transplantation, living‐donor liver transplantation (LDLT) for Budd‐Chiari Syndrome (BCS) presents distinctive challenges in hepatic venous (HV)‐outflow reconstruction because diseased HV–inferior vena cava (IVC) cannot be entirely replaced with healthy donor vessels.
Koichiro Hata   +4 more
wiley   +1 more source

Young children's perspectives of time: New directions for co‐constructing understandings of quality in ECEC

open access: yesBritish Educational Research Journal, EarlyView., 2023
Abstract Children's relationship with time in preschools is an under‐researched area. Young children rarely know how to measure time using a clock, but their experiences of time may contribute to understanding children's well‐being and debates about quality in preschools.
Kristín Dýrfjörð   +3 more
wiley   +1 more source

Challenges and enablers in fluidization technology

open access: yesAIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

Stability analysis of a two-class system with constant retrial rate and unreliable server

open access: yes
In this paper we find stability conditions of a two-class retrial system with unreliable server, in which the new customer joins a class-dependent orbit queue regardless of the state of the server.
Efrosinin Dmitry   +3 more
core   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Unreliable Queueing System with Backup Server

open access: yes, 2016
SECTION 6 COMPUTER DATA ANALYSIS AND MODELING IN ...
openaire   +1 more source

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

open access: yesAdvanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang   +3 more
wiley   +1 more source

Distributed learning over unreliable networks

open access: yes, 2019
Most of today's distributed machine learning systems assume reliable networks: whenever two machines exchange information (e.g., gradients or models), the network should guarantee the delivery of the message.
Liu, Ji   +7 more
core   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah   +3 more
wiley   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Home - About - Disclaimer - Privacy