Current Approaches to the Treatment of Traumatic Shock (Review) by D. A. Ostapchenko, A. I. Gutnikov, L. A. Davydova

“…The use of a comprehensive multicomponent intensive care strategy matching the pathophysiological changes is a difficult challenge for a critical care physician.The aim of the review is to demonstrate the specific features and sequence of events occurring in the body during the development of traumatic shock, the pattern of manifestations of clinical signs, and potential use of intensive therapy methods tailored to the pathophysiological responses in traumatic shock.Material. …”
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The effect application of nitrogen levels and intercropping ratios of pea (Pisum sativum) and lettuce (Lactuca sativa) by Elham Raftari, Ali Nakhzari Moghaddam, Mehdi Mollashahi, Hossein Hosseini Moghaddam

“…Introduction    The practice of growing two or more crops simultaneously in the same field is called intercropping and it is a common feature in traditional farming of small landholders. …”
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Defect Detection and Correction in OpenMP: A Static Analysis and Machine Learning-Based Solution by Norah A. Al-Johany, Fathy E. Eassa, Sanaa A. Sharaf, Eynas H. Balkhair, Sara M. Assiri

“…To enhance predictive accuracy, the tool incorporates machine learning classifiers—Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), and Linear Support Vector Machine (LSVM)—trained on various feature combinations, including Abstract Features (AF), Halstead Features (HF), and Semantic Features (SF). …”
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Improved YOLOv8-Based Method for the Carapace Keypoint Detection and Size Measurement of Chinese Mitten Crabs by Ke Chen, Zhuquan Chen, Changbo Wang, Zhifan Zhou, Maohua Xiao, Hong Zhu, Dongfang Li, Weimin Liu

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Deep learning identification of reward-related neural substrates of preadolescent irritability: A novel 3D CNN application for fMRI by Johanna C. Walker, Conner Swineford, Krupali R. Patel, Lea R. Dougherty, Jillian Lee Wiggins

“…The recent emergence of deep learning methods, particularly convolutional neural networks (CNNs), applied to fMRI data presents a promising avenue in psychiatry research, offering advantages over traditional analyses by requiring minimal assumptions and enabling detection of higher-level patterns and intricate, nonlinear relationships within inherently complex fMRI data. …”
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Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neura... by Mizuho Nishio, Osamu Sugiyama, Masahiro Yakami, Syoko Ueno, Takeshi Kubo, Tomohiro Kuroda, Kaori Togashi

“…We developed a computer-aided diagnosis (CADx) method for classification between benign nodule, primary lung cancer, and metastatic lung cancer and evaluated the following: (i) the usefulness of the deep convolutional neural network (DCNN) for CADx of the ternary classification, compared with a conventional method (hand-crafted imaging feature plus machine learning), (ii) the effectiveness of transfer learning, and (iii) the effect of image size as the DCNN input. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…However, dense planting patterns and complex environments within greenhouses present challenges for accurately detecting growth stages. …”
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A review of the FIVA project: Novel windows employing vacuum glazing products by Ulrich J. Pont, Peter Schober, Magdalena Wölzl, Matthias Schuss, Jakob Haberl

“…Four different designs were developed that not only integrated vacuum glass products, but also featured unusual opening patterns, the latest generation of electrically driven fitting products, and specific seals. …”
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Self-Adaptive Deep Learning Framework for Non-Intrusive Load Monitoring: Addressing Aging Appliance Challenges With Transfer Learning and Pseudo Labeling by W. A. Yasodya, S. M. L. Arampola, M. S. K. Nisakya, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

“…Unlike traditional NILM models, this approach incorporates a unique self-adaptive feature that enables the model to automatically adapt to changing power patterns resulting from aging appliances. …”
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Applications of gene pair methods in clinical research: advancing precision medicine by Changchun Wu, Xueqin Xie, Xin Yang, Mengze Du, Hao Lin, Jian Huang

“…To bridge methodological development with practical implementation, we establish a reproducible analytical pipeline incorporating feature selection, classifier construction, and model evaluation modules using real-world benchmark datasets from pulmonary tuberculosis studies. …”
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Sensor-Based Monitoring Data from an Industrial System of Centrifugal Pumps by Angelo Martone, Alessia D’Ambrosio, Michele Ferrucci, Assuntina Cembalo, Gianpaolo Romano, Gaetano Zazzaro

“…<b>Conclusions</b>: This dataset supports advanced methodologies in feature extraction, multivariate signal analysis, unsupervised pattern discovery, vibration analysis, and the development of digital twins and soft sensing models for predictive maintenance optimization.…”
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Structural Fault Detection and Diagnosis for Combine Harvesters: A Critical Review by Haiyang Wang, Liyun Lao, Honglei Zhang, Zhong Tang, Pengfei Qian, Qi He

“…Subsequently, it details the core steps of data-driven methods, including the acquisition of operational data from various sensors (e.g., vibration, acoustic, strain), signal preprocessing methods, signal processing and feature extraction techniques covering time-domain, frequency-domain, time–frequency domain combination, and modal analysis among others, and the use of machine learning and artificial intelligence models for fault pattern learning and diagnosis. …”
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Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023) by Jian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song, Wen-hua Xiong

“…“deep learning,” “magnetic resonance imaging,” and “stroke” emerged as the most attention-gathering keywords among researchers. The development in this field is marked by a coexisting pattern of interdisciplinary integration and refinement within major disciplinary branches.ConclusionThe application of machine learning in the early prediction and personalized medical plans for stroke patients using neuroimaging characteristics offers significant value. …”
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Variations in Global Soil Moisture During the Past Decades: Climate or Human Causes? by Yangxiaoyue Liu, Yaping Yang, Jia Song

“…Here, we investigate the evolutionary pattern of SM and then carry out an attribution analysis from climate and human perspectives. …”
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Spatial Characterization of Channeling in Sheared Rough‐Walled Fractures in the Transition to Nonlinear Fluid Flow by Robert Egert, Fabian Nitschke, Maziar Gholami Korzani, Thomas Kohl

“…In contrast, parallel to the shearing, a complex pattern of individual tortuous channels emerges, with flow occurring in 22% of the void space. …”
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Phonological category resolution: a study of handshapes in younger and older sign languages by Assaf Israel, Wendy Sandler

“…Our methodology measures the degree of cross-signer consensus with respect to each meaningless phonetic feature of handshape as well as the number of variants (indicating the range of variation), and reveals a consistent pattern across the three languages: The largest amount of variation is found in ABSL; ISL is next; and ASL shows the least amount of cross-signer variation in production of the handshape category. …”
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Permanent and seasonally specific surface heat island structure in urban and non-urban areas in mid-latitude polycentric agglomeration based on Landsat images by Aleksandra Renc, Ewa Łupikasza

“…Permanent non-urban SHI was scattered throughout the GZM without any clear pattern and covered only 0.4% of the entire GZM, and 75% of its area was covered by non-irrigated arable land and pastures. …”
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Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…By understanding the meaning of each Toraja carving, both tourists and the local community can gain knowledge about Toraja culture, thereby preserving and maintaining the culture amidst modern developments. Image processing approaches, particularly the development of Convolutional Neural Networks (CNN), offer a solution for extracting information from the diverse and intricate patterns of Toraja wood carvings. …”
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Carbon use efficiency of alpine grasslands affected by grazing exclusion and local environmental context in Tibet, China by Yunfei Feng, Jianshuang Wu, Meng Li, Ben Chen, Minyahel Tilahun, Xianzhou Zhang

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An Approach for Predicting the Shape and Size of a Buried Basic Object on Surface Ground Penetrating Radar System by Nana Rachmana Syambas

“…GPR data of many basic objects (with circular, triangular, and rectangular cross-section) are classified and extracted to generate data training model as a unique template for each type of basic object. The pattern of object under test will be known by comparing its data with the training data using a decision tree method. …”
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