Deep Learning Methods for Inferring Industrial CO₂ Hotspots from Co-Emitted NO₂ Plumes by Erchang Sun, Shichao Wu, Xianhua Wang, Hanhan Ye, Hailiang Shi, Yuan An, Chao Li

“…The trained model performed well on the test set, with most samples achieving an identification accuracy above 80% and more than half exceeding 94%. …”
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Genomic Prediction in a Self-Fertilized Progenies of <i>Eucalyptus</i> spp. by Guilherme Ferreira Melchert, Filipe Manoel Ferreira, Fabiana Rezende Muniz, Jose Wilacildo de Matos, Thiago Romanos Benatti, Itaraju Junior Baracuhy Brum, Leandro de Siqueira, Evandro Vagner Tambarussi

“…These results highlight the potential of genomic selection for use in the genetic improvement of <i>Eucalyptus</i> through inbred lines. In addition, our model facilitates the identification of promising individuals and the acceleration of breeding cycles, one of the major challenges in <i>Eucalyptus</i> breeding programs. …”
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Deep Learning Approaches for Continuous Sign Language Recognition: A Comprehensive Review by Asma Khan, Seyong Jin, Geon-Hee Lee, Gul E. Arzu, L. Minh Dang, Tan N. Nguyen, Woong Choi, Hyeonjoon Moon

“…It critically analyzes numerous studies, organizing them into a comprehensive taxonomy covering aspects such as sign language, data collection, input method, gesture signals, identification methods, applied data collections, and comprehensive efficiency. …”
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ggClusterNet 2: An R package for microbial co‐occurrence networks and associated indicator correlation patterns by Tao Wen, Yong‐Xin Liu, Lanlan Liu, Guoqing Niu, Zhexu Ding, Xinyang Teng, Jie Ma, Ying Liu, Shengdie Yang, Penghao Xie, Tianjiao Zhang, Lei Wang, Zhanyuan Lu, Qirong Shen, Jun Yuan

“…To address emerging challenges, including multi‐factor experimental designs, multi‐treatment conditions, and multi‐omics data, we present a comprehensive upgrade with four key components: (1) A microbial co‐occurrence network pipeline integrating network computation (Pearson/Spearman/SparCC correlations), visualization, topological characterization of network and node properties, multi‐network comparison with statistical testing, network stability (robustness) analysis, and module identification and analysis; (2) Network mining functions for multi‐factor, multi‐treatment, and spatiotemporal‐scale analysis, including Facet.Network() and module.compare.m.ts(); (3) Transkingdom network construction using microbiota, multi‐omics, and other relevant data, with diverse visualization layouts such as MatCorPlot2() and cor_link3(); and (4) Transkingdom and multi‐omics network analysis, including corBionetwork.st() and visualization algorithms tailored for complex network exploration, including model_maptree2(), model_Gephi.3(), and cir.squ(). …”
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Application of Deep Learning in Food Safety Detection and Risk Early Warning by DING Haohan, WANG Long, HOU Haoke, XIE Zhenqi, HAN Yu, CUI Xiaohui

“…Although deep learning performs well in improving the efficiency and accuracy of food safety detection, its practical application still faces challenges such as poor data quality, weak privacy protection capacity and lack of model interpretability. …”
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Region-Wise Recognition and Classification of Arabic Dialects and Vocabulary: A Deep Learning Approach by Fawaz S. Al–Anzi, Bibin Shalini Sundaram Thankaleela

“…This article presents a unique approach to Arabic dialect identification using a pre-trained speech classification model. …”
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ABOUT THE ESSENCE AND CONTENT OF MOTIVATION OF NEW MEMBERS OF A PROFESSIONAL GROUP: THE THEORETICAL REVIEW by Valentyna V. Pashchenko

“…Adams, expectation theory by V. Vrum, Porter-Lawler model, theory X, Y D. McGregor, theory Z (participative management) by V. …”
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An Ensemble Approach for Detection of Malicious URLs Using SOM and Tabu Search Optimization by Simar Preet Singh, Abhilash Maroju, Mohammad Kamrul Hasan, Karan Tejpal

“…Our model performs better than other models in a variety of malicious URL attack scenarios. …”
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A machine vision approach for classification and dimensional design of furniture panels using GMM-SVM by Yuan Tian, Li Zhao, Haoxin Li

“…This method combines Gaussian mixture model (GMM) and support vector machine (Support vector machine, SVM) to effectively identify classification. …”
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Forecasting of Socio-Economic Development of Regions in Kazakhstan: Principles, Features and Disadvantages by L. A. Balgarina, S. A. Jumabayev, Y. K. Shokamanov

“…The result of the study was the identification of limitations affecting the quality and efficiency of the use of the developed forecasts, and ways to reduce them are proposed. …”
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INFLUENCE OF TYPE OF ORGANIZATIONAL CULTURE IN INSTITUTE OF EDUCATION ON LEVEL OF PROFESSIONAL DEFORMATION OF TEACHERS by Katsiaryna I. Sapeha

“…The greatest development of deformation of teachers is observed on elements of authoritativeness and rigidity, the smallest – on noncriticality of self-perception.Scientific novelty of material is presented for the first time applied sociocultural-interdeterministic dialogical approach to research of professional deformation of personality, that psychological interdeterminant of deformation are allocated, one of structural components of model of ecocultural educational environment – open type of organizational culture in institute of education are described.Practical significance of results consists in detection of opportunities and criteria of formation in institute of formation of ecocultural dialogical environment and its structural component for purpose of timely prevention and overcoming of professional deformation of personality of teachers, to creation of prerequisites for increase of efficiency of interaction among participants of educational process.…”
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Functional control of the technical condition method for aircraft control system sensors under complete parametric uncertainty by J. V. Bondarenko, E. Yu. Zybin

“…The efficiency of the method is shown on the Boeing 747–100/200 longitudinal model example. …”
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Klasifikasi Penyakit pada Tanaman Berdasarkan Citra Daun Menggunakan Metode Convolutional Neural Network by Denis Aji Pangestu, Okta Qomaruddin Aziz, Cahyo Crysdian

“…This research aims to develop a plant disease classification model using Convolutional Neural Network (CNN) to assist farmers in identifying diseases in rice, corn, tomato, and potato plants based on leaf images. …”
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A Habitat-Template Approach to Green Wall Design in Mediterranean Cities by Miriam Patti, Carmelo Maria Musarella, Giovanni Spampinato

“…In this context, the careful selection of plant species is essential to ensure ecological efficiency, resilience, and low maintenance. This study presents a model for selecting plant species suitable for natural green walls in Mediterranean cities, with a focus on habitats protected under Directive 92/43/EEC. …”
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Simulation of Natural Gas Pipeline Networks Based on Roughness Optimization Algorithm and Global Mesh Refinement by Yi Yang

“…The roughness identification problem is then transformed into an optimization problem by minimizing the error between measured and simulated values. …”
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Decoding AGN Feedback with X-arithmetic: From Morphology to Physical Mechanisms by Hannah McCall, Irina Zhuravleva, Eugene Churazov, Congyao Zhang, William Forman, Christine Jones, Yuan Li

“…This technique decomposes perturbations in feedback-dominated regions into images excluding either (1) weak shocks and sound waves, (2) bubbles inflated by jets, or (3) cooling and slow gas motions (isobaric perturbations), enabling efficient spatial identification of these features without involving spectroscopic analysis. …”
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Kernel to computation: identifying optimal feature set for red rice classification by Suma D, Narendra V G, Darshan Holla M, Shreyas, Raviraja Holla M

“…Feature selection was performed using Recursive Feature Elimination and Backward Feature Elimination to enhance model efficiency. Hyperparameter tuning was applied to optimize classification performance, and k-fold cross-validation with statistical significance testing was used to assess generalization and validate model performance differences. …”
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Improving Satellite Imagery Masking Using Multitask and Transfer Learning by Rangel Daroya, Luisa Vieira Lucchese, Travis Simmons, Punwath Prum, Tamlin Pavelsky, John Gardner, Colin J. Gleason, Subhransu Maji

“…Our models provide a 9% <inline-formula><tex-math notation="LaTeX">$F1$</tex-math></inline-formula> score improvement compared to previous work on water pixel identification. …”
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RF-PSignal: The Smart Home Gesture Recognition System Based on Channel-Wise Topology and Self-Adaptive Attention by Xiaohang Zhang, Chunhong Yue, Yajun Zhang, Kun Liang, Yanxiang Li

“…Unlike most existing studies that rely on time-series signals for feature extraction and pattern recognition, the system achieves outstanding performance and computational efficiency through a time-series-to-image transformation algorithm and lightweight model design. …”
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Opportunities and challenges of digital twin applications in the Middle East construction industry by Diala Barham, Sandra T. Matarneh, Algan Tezel, Saed Hasan, Wajdi Mereb

“…Purpose – Over the years, the Middle East (ME) has experienced significant advancements in technology, particularly in the digital realm, initiated by Dubai’s 2013 Building Information Modeling (BIM) mandate. However, there are ongoing questions regarding how digital twins (DTs) have been adopted and awareness within the region’s construction industry. …”
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