Computer-Modeling System of Agronomist’s Labor Functions by I. E. Bystrenina

“…Among the main objectives of the research is the study of the essence of computer modeling as a teaching method in the works of domestic scientists, as well as the construction of models and their implementation using high-level programming languages in order to obtain an information system for the labor functions of an agronomist.Materials and methods. …”
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ADVERTISEMENT AS A MEANS OF COMMUNICATION: THE CONTENT AND PECULIARITIES OF TRANSLATION by Inna M. Anataichuk, Olena V. Rutz, Viktoriya S. Sazonova

“…Therefore, after the analysis of the abovementioned methods of translating English advertising texts, we can conclude that the translator has a large variety of translation transformations. …”
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Instance-Level Weighted Contrast Learning for Text Classification by Xinhui Liu, Jifa Chen, Qiubo Huang

“…Contrastive learning has become a key research focus aimed at improving classification performance by learning the similarities and differences between samples using models. However, existing contrastive learning methods have notable shortcomings, primarily concerning insufficient data utilization. …”
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DB-Net: A Dual-Branch Hybrid Network for Stroke Lesion Segmentation on Non-Contrast CT Images by Xiao Jia, He Dong, Jiashu Xu, Yanhong Zhang, Yihua Lan

“…To address these challenges, this study proposes a two-branch hybrid network combining a convolutional neural network (CNN) with a Transformer framework. The proposed architecture features the aforementioned dual-branch encoder, as well as a spatial channel difference learning module and parallel attention module. …”
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Adoption of business intelligence in Jordanian hospitals: Examining moderating effects of support, readiness, compatibility, and user satisfaction by Mohammad Mahmoud Saleem Alzubi

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The Application of Deep Learning for Lymph Node Segmentation: A Systematic Review by Jingguo Qu, Xinyang Han, Man-Lik Chui, Yao Pu, Simon Takadiyi Gunda, Ziman Chen, Jing Qin, Ann Dorothy King, Winnie Chiu-Wing Chu, Jing Cai, Michael Tin-Cheung Ying

“…Despite the advancements, it still confronts challenges like the shape diversity of lymph nodes, the scarcity of accurately labeled datasets, and the inadequate development of methods that are robust and generalizable across different imaging modalities. …”
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Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Met... by Amir Moslemi, Laurentius Oscar Osapoetra, Archya Dasgupta, Schontal Halstead, David Alberico, Maureen Trudeau, Sonal Gandhi, Andrea Eisen, Frances Wright, Nicole Look-Hong, Belinda Curpen, Michael Kolios, Gregory J. Czarnota

“…We determined features from CT images in different level of frequencies using wavelet transform. …”
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Dagestan national clothes as an attribute of rural everyday life. 1920–1960s by Madina Magomedovna Amirkhanova

“…In national clothes, the values of the time, consonant with the era, are objectively fixed.The national costume is comprehensively considered in the context of socio-historical processes, using the principle of historicism and interdisciplinary, comparative, historical, logical, problem-chronological methods. The purpose of the research is to show the spatial and temporal processes of distribution, development of traditional clothes of Dagestan, general and special in cut, the way of wearing clothes among different nationalities, to analyze the transformation of the national costume in the specified chronological framework. …”
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Robust Prediction of Wildfire Spread in Australia by Michael Palk, Katharina Knappmann, Stefan Voss, Raka Jovanovic

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Multistep photovoltaic power forecasting based on multi-timescale fluctuation aggregation attention mechanism and contrastive learning by Liang Yuan, Xiangting Wang, Yao Sun, Xubin Liu, Zhao Yang Dong

“…Despite the superior performance of Transformer-based time series methods, their application to PV power prediction remains suboptimal. …”
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Arabic Cyberbullying Detection: A Comprehensive Review of Datasets and Methodologies by Huda Aljalaoud, Kia Dashtipour, Ahmed Y. Al-Dubai

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Hierarchical Multi-Scale Decomposition and Deep Learning Ensemble Framework for Enhanced Carbon Emission Prediction by Yinuo Sun, Zhaoen Qu, Zhuodong Liu, Xiangyu Li

“…We integrate complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose carbon emission time series into intrinsic mode functions (IMFs) capturing different frequency bands. Each IMF is processed through a hybrid convolutional neural network (CNN)–Transformer architecture: CNNs extract local features and transformers model long-range dependencies via multi-head attention. …”
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Multi-scale attention patching encoder network: a deployable model for continuous estimation of hand kinematics from surface electromyographic signals by Chuang Lin, Qiong Xiao, Penghui Zhao

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Investments in Renewable Energy in Rural Communes: An Analysis of Regional Disparities in Poland by Agnieszka Kozera, Aldona Standar, Joanna Stanisławska, Anna Rosa

“…Therefore, this study extends the existing literature resources with a view to bridging that gap by assessing rural communes’ investment activity in the context of the Polish energy transformation, with particular emphasis on regional differences in RES investments financed with Union funds. …”
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Study of Recent Image Restoration Techniques: A Comprehensive Survey by Nikita Singhal, Anup Kadam, Pravesh Kumar, Hritik Singh, Aaryan Thakur, Pranay

“…This article provides an all-inclusive review of state-of-the-art (SOTA) methods in image restoration, covering traditional methods as well as modern techniques like deep learning and transformer-based models. …”
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MtAD-Net: Multi-Threshold Adaptive Decision Net for Unsupervised Synthetic Aperture Radar Ship Instance Segmentation by Junfan Xue, Junjun Yin, Jian Yang

“…Therefore, exploring the use of unsupervised instance segmentation methods to convert BBox-level annotations into pixel-level GT holds great significance in the SAR field. …”
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Anesthesia depth prediction from drug infusion history using hybrid AI by Liang Wang, Yiqi Weng, Wenli Yu

“…Methods The proposed model combines multiple deep learning techniques to address different aspects of anesthesia prediction. …”
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Linguistic-stylistic analysis of the language of leadership in the political arena and the business world by Oremire J. Ehibor, Joy Eyisi, Jonathan A. Odukoya, Charles U. Ogbulogo, C. U. C. Ugorji, Onyekachi Odo, Lily Chimuanya, Eugenia Abiodun-Eniayekan, Edith Awogu-Maduagwu, Rebecca U. Adesiyan

“…The research underscores the importance of recognsing these differences to enhance communication and understanding across different sectors, advocating against broad generalisations.…”
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Semantic Tokenization-Based Mamba for Hyperspectral Image Classification by Ri Ming, Na Chen, Jiangtao Peng, Weiwei Sun, Zhijing Ye

“…Recently, the Mamba-based methods have shown even stronger spatial context modeling ability than Transformer for HSIC. …”
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Evaluating large language models and agents in healthcare: key challenges in clinical applications by Xiaolan Chen, Jiayang Xiang, Shanfu Lu, Yexin Liu, Mingguang He, Danli Shi

“…Second, we analyzed key medical task scenarios: closed-ended tasks, open-ended tasks, image processing tasks, and real-world multitask scenarios involving LLM agents, thereby offering guidance for further research across different medical applications. Third, we compared evaluation methods and dimensions, covering both automated metrics and human expert assessments, while addressing traditional accuracy measures alongside agent-specific dimensions, such as tool usage and reasoning capabilities. …”
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