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Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Background and Purpose: Insufficient documentation of artificial intelligence (AI) models remains a widespread issue, which hampers reproducibility in research environments and safe integration in clinical departments. O...

The emergence of metasurfaces has enabled lightweight, compact imaging with degrees of freedom which previously required complex optical setups to achieve, such as polarization, wave vector, and spectrum. To date, most m...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...

The next-generation network technology is an intelligent information technology with the characteristics of collaborative perception, ubiquitous communication, and computer assistance. It is highly related to the industr...

Abstract The rapid growth of biological resources and associated research outputs has increased the complexity of resource discovery, access, and reuse across heterogeneous repositories. However, fragmented metadata sche...

Tripartite motif (TRIM)7 is an E3 ubiquitin ligase that was first identified through its interaction with glycogenin-1 (GN1), the autoglucosyltransferase that initiates glycogen biosynthesis. A growing body of evidence i...

Abstract Background Reliable identification of protein‑protein interactions (PPIs) is crucial for deciphering cellular functional networks. Current research models still face limitations in aligning heterogeneous featu...

Abstract Satellite Image Classification is a process in remote sensing that aims at classifying pixels of satellite imagery into usable information of land use and land cover. This information is not only limited to seve...

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

Abstract What is the fundamental economic function of the firm under radical uncertainty? This paper advances a theory of the firm centered on economies of cognition: the systematic reduction in the costs of perception, ...

Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...

Fast and accurate identification of skin lesions is important for the outcome of patients. The evaluation of lesions is subjective, and poor quality images may limit accuracy. Deep learning models can be an alternative; ...

The low visual contrast between dermatological lesions and normal skin, coupled with the masking effect of surface artefacts, presents two major obstacles to precise automated skin lesion segmentation. In order to addres...

Abstract Brain-computer interfaces (BCIs) were initially created to help individuals with disabilities control devices and communicate without muscle movement. Today, BCIs are used for prosthetic control, cognitive enhan...

Optical encryption systems have great potential for flexible and high-performance data protection, making them an area of rapid development. However, most approaches present two main issues, namely, the presence of speck...

ABSTRACT Graph contrastive learning (GCL) has emerged as a dominant paradigm for self‐supervised representation learning for attributed graph data. However, existing GCL methods heavily rely on empirical graph data aug...

BackgroundBoth insulin and glucagon have been extensively studied due to their critical roles in glucose metabolism, development, and disease. However, there is limited information about the molecular characteristics of ...

Abstract Neoadjuvant chemotherapy (NAC) induces critical morphological and vascular changes in breast cancer tumors, yet existing deep learning techniques in medical imaging tend to neglect these longitudinal changes thr...

In recent years, large language models and agent systems based on them have been considered a promising tool for the digital transformation of public administration. However, the practical effectiveness of such systems i...

Controlling nonlinear pulse propagation in optical fibers is paramount for applications spanning spectroscopy and optical communication networks. However, the inherent complexity of laser pulse evolution in matter, shape...

Remote sensing enables urban planners to gain macroscopic insights into urban structures and issues. Pan-sharpening plays a key role by merging multispectral and panchromatic images, combining high spatial resolution wit...

This paper addresses the challenge of packet-based information routing in large-scale communication networks. The problem is framed as a constrained statistical learning task, where each network node operates using only ...

Gain-dissipative systems of various physical origin have recently shown the ability to act as analogue minimisers of hard combinatorial optimisation problems. Whether or not these proposals will lead to any advantage in ...