Decoding the Microbial Spectrum: Bioinformatic Approaches for Viruses, Bacteria and Fungi by Marius SURLEAC, Ilda CZOBOR-BARBU, Simona PARASCHIV, Irina GHEORGHE-BARBU, Liviu-Iulian ROTARU, Dan OŢELEA, Mariana Carmen CHIFIRIUC

“…C. auris) and other particularities such as carrying specific traits (e.g. copy number variations) with yet unknown roles due to scarce annotation data. Some of the methods used involve quality control filtering and trimming performed with HTStream and Trimmomatic, de novo assembly and reference mapping with tools like shovill or Snippy, antibiotic resistance predicted with ResFinder or CARD, pangenome analysis with Roary, taxonomy profiling with Metaxa2 or huge phylogenetic analyses on fungi performed with Pathogenwatch. …”
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Advancing dendrochronology with R: an overview of packages and future perspectives by Jan Altman, Jan Altman, Jan Altman, Nela Altmanova, Nela Altmanova, Pavel Fibich, Pavel Fibich, Kirill Korznikov, Patrick Fonti

“…Beyond managing traditional tasks like data processing, analysis, and results visualization, R is pivotal in integrating innovative techniques, such as multi-proxy datasets, artificial intelligence or machine learning, to address emerging challenges in tree-ring research. …”
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Automating Monte Carlo simulations in nuclear engineering with domain knowledge-embedded large language model agents by Zavier Ndum Ndum, Jian Tao, John Ford, Yang Liu

“…Yet, traditional workflows for Monte Carlo simulations like FLUKA are labor-intensive and error-prone, relying on manual input file generation and post-processing. …”
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InMemQK: A Product Quantization Based MatMul Module for Compute-in-Memory Attention Macro by Pengcheng Feng, Yihao Chen, Jinke Yu, Hao Yue, Zhelong Jiang, Yi Xiao, Wan’ang Xiao, Huaxiang Lu, Gang Chen

“…Large Language Models (LLMs), based on transformer architecture, have demonstrated remarkable capabilities in natural language processing tasks, enabling machines to generate human-like text and engage in meaningful dialogues. …”
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A Lightweight Neural Network for Denoising Wrapped-Phase Images Generated with Full-Field Optical Interferometry by Muhammad Awais, Younggue Kim, Taeil Yoon, Wonshik Choi, Byeongha Lee

“…However, these maps are often degraded by noise, such as speckle and Gaussian, which reduces the measurement accuracy and complicates phase reconstruction. Denoising such data is a fundamental problem in computer vision and plays a critical role in biomedical imaging modalities like Full-Field Optical Interferometry. …”
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Printed Optoelectronic Memories Using Gr/WS2 Nanostructured Composite Ink for Retina‐Inspired Vision Persistent Synapses by Jiahui Bai, Qiuyan Wang, Qiaoqiao Zheng, Dong Liu, Hongbing Zhan, Renjing Xu, Jiajie Pei

“…Abstract The rapid advancement of neuromorphic computing and machine vision drives the need for optoelectronic memories that mimic neural and visual systems, integrating optical sensing, data storage, and processing. Traditional fabrication methods are often complex, multistep processes that struggle to achieve lightweight, scalable, and flexible designs. …”
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Deep Learning-Based Prediction of Pitch Response for Floating Offshore Wind Turbines by Ruifeng Chen, Ke Zhang, Min Luo, Ye An, Lixiang Guo

“…The comprehensive framework, which encompasses feature selection, data processing, deep learning model construction, and interpretation, demonstrates significant potential for addressing a broad range of engineering problems through deep learning methodologies.…”
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A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images by Mishmala Sushith, A. Sathiya, V. Kalaipoonguzhali, V. Sathya

“…Abstract Recent advancements in deep learning have significantly impacted medical image processing domain, enabling sophisticated and accurate diagnostic tools. …”
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Beyond boundaries a hybrid cellular potts and particle swarm optimization model for energy and latency optimization in edge computing by Dinesh Sahu, Nidhi, Shiv Prakash, Priyanshu Sinha, Tiansheng Yang, Rajkumar Singh Rathore, Lu Wang

“…Abstract The need to compute data in real-time and manage resources in environments with distributed computing has given edge computing significant importance. …”
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SAVE: Self-Attention on Visual Embedding for Zero-Shot Generic Object Counting by Ahmed Zgaren, Wassim Bouachir, Nizar Bouguila

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On-Device Automatic Speech Recognition for Low-Resource Languages in Mixed Reality Industrial Metaverse Applications: Practical Guidelines and Evaluation of a Shipbuilding Applicat... by Anton Valladares-Poncela, Paula Fraga-Lamas, Tiago M. Fernandez-Carames

“…The system prioritizes data privacy and security by eliminating the need for Internet connectivity or external processing. …”
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GENDER ANALYSIS OF PROBLEMS AND PROSPECTS OF RURAL HOUSEHOLD-BASED ENTERPRISES IN OSUN STATE, NIGERIA by Docas Lola ALABI, Michael FAMAKINWA, Sunday Idowu OGUNJIMI

“…Snow ball sampling procedure was employed to select 100 male and 100 female entrepreneurs for the study from four LGAs of the state. Data were described with frequency counts, percentages, means and standard deviation while ANOVA was used for inferential purpose. …”
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Trends in digitalization of financial and economic activities of companies in Ukraine by A.Yu., M.Р., S.М., I.V., O.А.

“…The information base of the study was the data of the State Statistics Service of Ukraine, National Bank of Ukraine, research of international organizations, scientific papers and other open sources. …”
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Sky images based photovoltaic power forecasting: A novel approach with optimized VMD and Vision Mamba by Chenhao Cai, Leyao Zhang, Jianguo Zhou, Luming Zhou

“…In the third step, exogenous variables, including meteorological and image data, are introduced and processed through Variate Embedding combined with cross-attention mechanisms to capture the intricate interactions between these variables. …”
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Level of knowledge among the population of radiation safety basic issues by S. A. Zelencova, G. V. Arhangel'skaja, N. M. Vishnjakova, I. A. Zykova, V. S. Repin

“…The goal of research was to determine the level of knowledge among the population on issues like sources of ionising radiation, methods of ionising radiation measurement, measures of self-protection in case of threating or actual radioactive pollution in the district, and to study self-estimation by the population of their knowledge of radiation safety issues. …”
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THE ARTISTIC POTENTIAL OF CHORAL CONDUCTING IN CONTEMPORARY UKRAINE by Lyudmyla SHUMSKA, Yuliia PUCHKO-KOLESNYK, Lyudmyla KOSTENKO, Oleksandr VILA-BOTSMAN, Olha MARTYNOVSKA

“…As part of the methodological approach to the study, a comparative and structural analysis was applied, including the processing of statistical data on choral performances on the YouTube platform, as well as an analysis of the use of modern technologies in Ukrainian music institutions based on open sources. …”
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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability by Abdennabi Morchid, Abdennacer Elbasri, Zahra Oughannou, Hassan Qjidaa, Rachid El Alami, Badre Bossoufi, Saleh Mobayen, Pawel Skruch

“…Using ML algorithms like linear regression algorithms to model the relationships between environmental factors and crop water requirements, enabling accurate prediction of required irrigation levels based on data collected by sensors. …”
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The large language model diagnoses tuberculous pleural effusion in pleural effusion patients through clinical feature landscapes by Chaoling Wu, Wanyi Liu, Pengfei Mei, Yunyun Liu, Jian Cai, Lu Liu, Juan Wang, Xuefeng Ling, Mingxue Wang, Yuanyuan Cheng, Manbi He, Qin He, Qi He, Xiaoliang Yuan, Jianlin Tong

“…While various machine learning and statistical models have been proposed for TPE diagnosis, these methods are typically limited by complexities in data processing and difficulties in feature integration. …”
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Observing air quality in Egypt’s Alexandria port based on the consequences of the COVID-19 lockdown by Mona Kaamoush, Mohi El-Sayeh, Mohamed Y. Omar

“…The aim was to assess the effect of the COVID-19 preventive measures on air quality in the vicinity of Alexandria Port, using satellite data provided by the European Space Agency’s geospatial processing engine. …”
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Advancing Underwater Vision: A Survey of Deep Learning Models for Underwater Object Recognition and Tracking by Mahmoud Elmezain, Lyes Saad Saoud, Atif Sultan, Mohamed Heshmat, Lakmal Seneviratne, Irfan Hussain

“…For tracking tasks, transformer-based models like SiamFCA and FishTrack leverage hierarchical attention mechanisms and convolutional neural networks (CNNs) to achieve high accuracy and robustness in dynamic underwater environments. …”
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