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The present work focuses on the computational modelling of fluid flow in a mixing stirred reactor to describe the flow pattern in two‐dimensional (2D) detail, which can be useful for optimizing the parameters of electr...

The RAG1 and RAG2 genes encode proteins essential for initiating V(D)J recombination in T cell receptor and immunoglobulin gene loci. Biallelic pathogenic variants in these genes are implicated in a spectrum of immunodef...

Distinguishing between the left- and right-handed versions of a chiral molecule (enantiomers) is vital, but also inherently difficult. Traditional optical methods using elliptically/circularly polarized light rely on lin...

Abstract This paper presents a digital model for the powder metallurgical (PM) production chain of high-performance sintered gears based on an integrated computational materials engineering (ICME) platform. Discrete and ...

A novel full-atom multiscale method, combining different computational approaches and aimed to describe diffusion of multiple ions in anion exchange membranes (AEM), is presented. The method is used to evaluate diffusion...

In the present study, the transmission error (TE) behaviour of an identical involute spur gear pair dynamically coupled with an attached subsystem is investigated through numerical modelling. The surrounding mechanical s...

Pain after surgery is of major perioperative concern because it is associated with substantial complications, including chronic post-surgical pain (CPSP) development. The CPSP incidence is high, and its accurate predicti...

Salinity distribution is a critical determinant in the management of water resources and the protection of ecological integrity in coastal regions, drawing particular concerns in the context of increasing saltwater intru...

Plant disease diagnosis in field settings is challenged by subtle symptomology, high inter-class visual similarity, and class imbalance, making automated detection particularly difficult. While deep learning models achie...

Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive me...

The reliability of oil and gas transportation depends heavily on weld quality during pipeline construction. This study investigates the effect of gas metal arc welding (GMAW) current on API 5 L GrB pipeline weld joint. W...

Abstract The rapid growth of distributed energy resources (DERs) is reshaping the operational landscape of transmission and distribution networks, creating new challenges for maintaining system‐wide security, economic ...

We develop an analytical framework to predict the one-point probability distribution function (PDF) of dispersion measures (DMs) for fast radio bursts (FRBs) within the baryonification (BFC) model. BFC provides a computa...

Prediction invariance of causal models under heterogeneous settings has been exploited by a number of recent methods for causal discovery, typically focussing on recovering the causal parents of a target variable of inte...

Traditional metasurface design is limited by the computational cost of full-wave simulations, preventing thorough exploration of complex configurations. Data-driven approaches have emerged as a solution to this bottlenec...

Abstract This paper analyses the results of the computational analysis between a single planar and a wrap-around fin mounted on a semi-cylindrical body. A free-stream Computational Fluid Dynamics (CFD) model was simula...

Anaerobic co-digestion of livestock waste presents a viable approach for addressing environmental challenges and reducing greenhouse gas emissions in semi-urban and rural contexts. This study focuses on the development o...

In a complex information environment, Russia’s invasion of Ukraine presents a major challenge to the communication of political leaders throughout the world. The objective of this article is to analyse the frames and s...

Purpose. This research examines how the expansion of Indian Premier League Franchises into foreign leagues contributes to India’s global image and soft power influence in international cricket. Methodology. Using a mix...

The article is devoted to modelling the growth of thin films on the surfaces of crystals having a similar crystal structure with a small parameter of mismatch of the lattice of substances from which the film and the crys...

Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated ...

The central building block of convolutional neural networks (CNNs) is the convolution operator, which enables networks to construct informative features by fusing both spatial and channel-wise information within local re...

Subjects / keywords: psychiatric function, psychiatry dysfunction, cognition, mental dysfunction, computational modelling; Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Medicine: Internal medicine: Neu...