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Abstract In order to improve the operation efficiency and impact resistance of the robotic arm in unstructured environments such as orchards, this paper proposes an online trajectory planning method for multi-index compr...

Abstract Early small fires in coal mines are of critical importance for mine safety, as most incidents begin as small fire sources. These fires essentially constitute a task of small-object detection. Detecting such targ...

In this paper, we chart an emerging academic terrain: cultural evolution of the arts, which is a theory-driven exploration of artistic dynamics, often done with large datasets of music, literature, movies, paintings, or ...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Abstract Recently, numerous lightweight image super-resolution methods with low computational complexity have been proposed, achieving a promising trade-off between reconstruction quality and efficiency. However, most ex...

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...

The purpose of this study is to justify the design parameters of spiral-vortex equipment ensuring energy-efficient desulfurization of flue gases from autonomous medium-capacity gas-piston power plants (GPPPs). The study ...

Abstract Energy activities are the primary source of carbon dioxide emissions. Real-time and accurate monitoring of their carbon emission dynamics is a crucial foundation for governments and enterprises in formulating ca...

Abstract Wireless Sensor Networks comprise low-cost, low-power, lightweight, and multifunctional sensor nodes capable of sensing and transmitting data from remote or hazardous environments to a central base station. Thes...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

Abstract Preterm birth (PTB) affects an estimated 15 million infants worldwide each year, raising an enormous challenge in the field of maternal-fetal medicine. This work explores machine learning approaches for disting...

The main objectives of the study are to develop a new adaptive geometric method for real-time monitoring of industrial electricity consumption schedules to ensure timely detection of structural imbalances and minimizatio...

Context. Astronomical environments are governed by a complex interplay of physical processes, including gravitational dynamics, radiative transfer, stellar evolution, chemistry, and hydrodynamics. These processes span a ...

Federated Learning (FL) has emerged as a privacy-preserving distributed learning paradigm that enables collaborative model training without sharing raw data. Despite its advantages, ensuring trustworthy FL deployment rem...

Galaxy is a widely used open-source platform for accessible, reproducible, transparent and scalable data analysis in the life sciences and beyond. Despite its growing adoption across domains, several misconceptions persi...

Mathematics and computer science play a pivotal role in modern biology. Dynamical models based on differential equations are particularly adapted to describe dynamic behaviors of many biological processes. However, tradi...

Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical ...

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-...

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic a...

Although much biological research depends upon species diagnoses, taxonomic expertise is collapsing. We are convinced that the sole prospect for a sustainable identification capability lies in the construction of systems...

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression...

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method ...

The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing...

We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence...