Application of artificial intelligence in the materials science, with a special focus on fuel cells and electrolyzers by Mariah Batool, Oluwafemi Sanumi, Jasna Jankovic

“…This review begins by explaining the fundamental concepts of artificial intelligence and introducing commonly used artificial intelligence-based algorithms in a simplified and clearly comprehensible way, establishing a foundational knowledge base for further discussion. …”
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MODELING OF A DUPLEX MILLER AND CONDITIONS OF FORMATION OF TREATMENT OF WHEEL PAIRS OF MAIN ELECTRIC CARDS, DUAL CARS, ELECTRO SECTIONS by Victor Shapovalov, Alexandr Permyakov, Alexander Klochko

“…The following results were obtained: the design of a "duplex" milling cutter with a predicted increase in resistance and increase in processing productivity due to modeling of forming processes with a decrease in the sliding angle by three to five times, which was not previously taken into account when designating and selecting cutting parameters, is provided. …”
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Secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks by Shayla Islam, S.M. Topazal, Mohammad Kamrul Hasan, Raenu AL Kolandaisamy, Huda Saleh Abbas, Nguyen Vo, Rahul Thakkar, Muhammad Attique Khan, Deepak Gupta, Dina Abdulaziz AlHammadi

“…The predictive algorithm anticipates device movement and pre-allocates resources at the target Base Station (BS), reducing HO latency by 20–30 % in 5 G and up to 40 % in 6 G. …”
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Signature verification by geometry and image processing by Jaber Ebaa Abdulsattar, Ataei Alireza, Tavakoli Ali

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Etude on Recursion Elimination by Nikolay Shilov

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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Objective:</b> This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. …”
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A lightweight spatiotemporal classification framework for tree species with entropy-based change resistance filter using satellite imagery by Biao Zhang, Zhichao Wang, Boyi Liang, Liguo Dong, Zebang Feng, Mingyang He, Zhongke Feng

“…To improve the stability and accuracy of the classification results, this study proposes a lightweight spatiotemporal classification framework, with the core algorithm being the Spatiotemporal Entropy-based Change Resistance Filter (STECR-F) algorithm. …”
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Peculiarities of Clinical Indices, Duration and Complication of Acute Pancreatitis in Patients With Comorbid Obesity by Kebkalo A., Tkachuk O., Reiti A.

“…In addition, obese patients are provided with a higher bed-day in-patient and in-patient-care settings, which increases the total cost of treatment and requires a cost-effective algorithm in the future. A high mortality rate in obese patients requires improved treatment algorithm.…”
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Identification and validation of glycolysis-related diagnostic signatures in diabetic nephropathy: a study based on integrative machine learning and single-cell sequence by Xiaoyin Wu, Xiaoyin Wu, Buyu Guo, Buyu Guo, Xingyu Chang, Xingyu Chang, Yuxuan Yang, Yuxuan Yang, Qianqian Liu, Qianqian Liu, Jiahui Liu, Jiahui Liu, Yichen Yang, Yichen Yang, Kang Zhang, Yumei Ma, Songbo Fu, Songbo Fu, Songbo Fu

“…The current lack of reliable predictive biomarkers hinders early diagnosis and personalized therapy.MethodsTranscriptomic profiles of DN samples and controls were extracted from GEO databases. …”
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Evaluation of a content-based image retrieval system for radiologists in high-resolution CT of interstitial lung diseases by Benjamin Böttcher, Marly van Assen, Roberto Fari, Philipp L. von Knebel Doeberitz, Eun Young Kim, Eugene A. Berkowitz, Felix G. Meinel, Carlo N. De Cecco

“…A CBIR application provides condensed information about similar HRCT cases reducing time for ILD assessment. CBIR algorithms benefit from the input of multiple regions of interest per ILD case. …”
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Rehabilitation training method for motor dysfunction based on video stream matching by Hong Yanyan

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A novel machine learning models for meteorological drought forecasting in the semi-arid climate  region by Chaitanya Baliram Pande, Dinesh Kumar Vishwakarma, Aman Srivastava, Kanak N. Moharir, Fahad Alshehri, Norashidah Md Din, Lariyah Mohd Sidek, Bojan Đurin, Abebe Debele Tolche

“…The study aims to assess the accuracy of the developed models in predicting future drought events and gain insights into meteorological droughts in tropical climates using the Standardized Precipitation Index (SPI)-SPI-3 and SPI-6. …”
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Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study by P. A. Makar, P. Cheung, C. Hogrefe, A. Akingunola, U. Alyuz, J. O. Bash, M. D. Bell, R. Bellasio, R. Bianconi, T. Butler, H. Cathcart, O. E. Clifton, O. E. Clifton, A. Hodzic, I. Kioutsioukis, R. Kranenburg, A. Lupascu, A. Lupascu, J. A. Lynch, K. Momoh, J. L. Perez-Camanyo, J. Pleim, Y.-H. Ryu, R. San Jose, D. Schwede, D. Schwede, T. Scheuschner, M. W. Shephard, R. S. Sokhi, S. Galmarini

“…If model–measurement fusion is only applied to some but not all of the fields contributing to the total deposition of sulfur or nitrogen, the corrections may result in greater variability between models or less accurate results for an ensemble of models, for those cases where an unobserved or unused observed component contributes significantly to predicted total deposition.</p> <p>Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH<span class="inline-formula">₃</span> bidirectional fluxes. …”
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GRAVITY ANOMALIES OF THE CRUST AND UPPER MANTLE FOR CENTRAL AND SOUTH ASIA by V. N. Senachin, A. A. Baranov

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System architecture and key technologies of intelligent, safe and efficient mining for rockburst coal seams by Zhigang DENG, Yunpeng LI, Shankun ZHAO, Yin WANG, Shaogang LI, Linghai KONG, Junjun JIANG, Zhenguo SU, Yizhe LI, Kai QIN

“…At the same time, the real-time data of various monitoring systems in the well and underground are combined with the dynamic update and calculation of the mine digital model, which can not only review and analyze the historical engineering effects, but also predict and deduce the impact of future engineering activities. …”
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Constructing a tumor immune microenvironment-driven prognostic model in acute myeloid leukemia using bioinformatics and validation data by Amir Abbas Navidinia, Ali Keshavarz, Bentol Hoda Kuhestani Dehaghi, Reza Khayami, Najibe Karami, Vahid Amiri, Mehdi Allahbakhshian Farsani

“…ROC analysis demonstrated predictive accuracy (AUC: 63.38–68.5% for 1–5-year survival). …”
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Daily time-use compositions of physical behaviours and its association with evaluative and experienced wellbeing: a multilevel compositional analysis by Anantha Narayanan, Scott Duncan, Conal Smith, Flora Le, Lisa Mackay, Julia McPhee, Basile Chaix, Tom Stewart

“…We investigated these associations by reallocating time among behaviours and assessing the predicted impact on wellbeing outcomes. Methods Time-use behaviours were obtained from 211 adults who wore Axivity AX3 accelerometers on their wrists for seven days. …”
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Identifying Data-Driven Clinical Subgroups for Cervical Cancer Prevention With Machine Learning: Population-Based, External, and Diagnostic Validation Study by Zhen Lu, Binhua Dong, Hongning Cai, Tian Tian, Junfeng Wang, Leiwen Fu, Bingyi Wang, Weijie Zhang, Shaomei Lin, Xunyuan Tuo, Juntao Wang, Tianjie Yang, Xinxin Huang, Zheng Zheng, Huifeng Xue, Shuxia Xu, Siyang Liu, Pengming Sun, Huachun Zou

“…ObjectiveThis study aimed to identify subgroups with differential cervical precancer or cancer risks using machine learning, validate subgroup predictions across datasets, and propose a computational phenomapping strategy to enhance global CCP efforts. …”
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The Prognostic Significance of Sleep and Circadian Rhythm for Myocardial Infarction Outcomes: Case-Control Study by Wei-Chih Chin, Pao-Hsien Chu, Lung-Sheng Wu, Kuang-Tso Lee, Chen Lin, Chien-Te Ho, Wei-Sheng Yang, I-Hang Chung, Yu-Shu Huang

“…The use of actigraphy with different algorithms to evaluate sleep and circadian rhythm after acute MI has the potential for predicting outcomes and preventing future disease progression. …”
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Prospective Applications of Artificial Intelligence In Fetal Medicine: A Scoping Review of Recent Updates by Miskeen E, Alfaifi J, Alhuian DM, Alghamdi M, Alharthi MH, Alshahrani NA, Alosaimi G, Alshomrani RA, Hajlaa AM, Khair NM, Almuawi AM, Al-Jaber KH, Elrasheed FE, Elhassan K, Abbas M

“…The selected works were analyzed for common themes, AI methodologies applied, and the scope of AI’s integration into fetal medicine practice.Results: The review identified several key areas where AI applications are making strides in fetal medicine, including prenatal screening, diagnosis of congenital anomalies, and predicting pregnancy complications. AI-driven algorithms have been developed to analyze complex fetal ultrasound data, enhancing image quality and interpretative accuracy. …”
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