Results 41 to 50 of about 1,125,987 (281)

Precipitation Regulates the Assembly Processes of Rare Species in Phytoplankton Communities in River Ecosystems

Diversity
Phytoplankton communities typically comprise a few dominant species and numerous rare ones, but their responses to seasonal precipitation changes remain poorly understood.
Enze Xiao, Xiaofeng Liu, Tian Lou, Yimin Zhu, Yiou Wang, Xinxin Lu, Yawen Fan, Xiang Tan, Yan Liu   +8 more
doaj   +1 more source

Network Reliability Modeling Based on a Geometric Counting Process

Mathematics, 2018
In this paper, we investigate the reliability and stochastic properties of an n-component network under the assumption that the components of the network fail according to a counting process called a geometric counting process (GCP).
Somayeh Zarezadeh, Somayeh Ashrafi, Majid Asadi   +2 more
doaj   +1 more source

Stochastic Light-Cone CTMRG: a new DMRG approach to stochastic models

, 2002
We develop a new variant of the recently introduced stochastic transfer-matrix DMRG which we call stochastic light-cone corner-transfer-matrix DMRG (LCTMRG).
A Gendiar, A Kemper, A Schadschneider, Bursill R J, de Oliveira S M, Enss T, Essam J W, GNU multiprecision library (GMP), J Zittartz, Kemper A, Kinzel W, Kinzel W, Marro J, Nishino T, Nishino T, Nishino T, Nishino T, Peschel I, Schütz G M, T Nishino, Trotter H F   +20 more
core   +2 more sources

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

Molecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix, Daniel Samaga, Katharina Gehr, Benedek Dankó, Mohamed Schumann, Guido Drexler, Ahmed Alnatsha, Georg Beyer, Ujjwal Mahajan, Martin Selmansberger, Julia Mayerle, Claus Belka, Horst Zitzelsberger, Kirsten Lauber   +13 more
wiley   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Sensorless Speed Estimation of Induction Motors through Signal Analysis Based on Chaos Using Density of Maxima

Entropy
Three-phase induction motors are widely used in various industrial sectors and are responsible for a significant portion of the total electrical energy consumed.
Marlio Antonio Silva, Jose Anselmo Lucena-Junior, Julio Cesar da Silva, Francisco Antonio Belo, Abel Cavalcante Lima-Filho, Jorge Gabriel Gomes de Souza Ramos, Romulo Camara, Alisson Brito   +7 more
doaj   +1 more source

Characterization of Noise Signatures of Involuntary Head Motion in the Autism Brain Imaging Data Exchange Repository

Frontiers in Integrative Neuroscience, 2018
The variability inherently present in biophysical data is partly contributed by disparate sampling resolutions across instrumentations. This poses a potential problem for statistical inference using pooled data in open access repositories.
Carla Caballero, Sejal Mistry, Joe Vero, Elizabeth B Torres, Elizabeth B Torres, Elizabeth B Torres   +5 more
doaj   +1 more source