Review of the Research on Underwater Explosion Ice-Breaking Technology by Xiao Huang, Zi-Xian Zhong, Xiao Luo, Yuan-Dong Wang

“…Future advancements require multiscale fluid–structure interaction models integrating brine migration effects, enhanced experimental diagnostics for transient processes, and optimized numerical algorithms to enable reliable predictions for engineering applications.…”
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MicroRNA-dependent mechanisms of taxane resistance in breast cancer by V. S. Apollonova, E. I. Sidina, E. V. Tkachenko, A. V. Malek

“…However, currently used algorithms of taxan-based regimens application do not always provide with desire effect. …”
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A comprehensive review on smart manufacturing using machine learning applicable to fused deposition modeling by Swapnil Deokar, Narendra Kumar, Ravi Pratap Singh

“…This study focuses on the use of ML algorithms for predicting part quality of AM parts, such as tensile strength, wear strength, detection of defect, geometric accuracy and minimizing the material waste.…”
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An Analysis of Semi-Supervised Machine Learning in Electrical Machines by V. Raju Arvind, S. Shyamsharan, Poorvajaa Gurunathan, Krishna Kumba, Nawin Ra

“…The research investigates important SSML algorithms such as self-training, co-training, generative models, and graph-based methods, highlighting their particular uses in fault diagnosis, condition monitoring, and predictive maintenance of electrical machines. …”
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Climate change is expected to reduce the potential distribution of Ceiba glaziovii in Caatinga, the largest area of dry tropical forest in South America by Débora de Melo Almeida, Sara Sebastiana Nogueira, Emanuel Araújo Silva, João Matheus Ferreira de Souza, Antonio Leandro Chaves Gurgel, Alex Nascimento de Sousa

“…Ecological niche modeling is a widely used tool to predict species distribution considering current, past, or future climate change scenarios across different geographic areas. …”
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Cystic Fibrosis Newborn Screening: A Systematic Review-Driven Consensus Guideline from the United States Cystic Fibrosis Foundation by Meghan E. McGarry, Karen S. Raraigh, Philip Farrell, Faith Shropshire, Karey Padding, Cambrey White, M. Christine Dorley, Steven Hicks, Clement L. Ren, Kathryn Tullis, Debra Freedenberg, Q. Eileen Wafford, Sarah E. Hempstead, Marissa A. Taylor, Albert Faro, Marci K. Sontag, Susanna A. McColley

“…Newborn screening for cystic fibrosis (CF) has been universal in the US since 2010; however, there is significant variation among newborn screening algorithms. Systematic reviews were used to develop seven recommendations for newborn screening program practices to improve timeliness, sensitivity, and equity in diagnosing infants with CF: (1) The CF Foundation recommends the use of a floating immunoreactive trypsinogen (IRT) cutoff over a fixed IRT cutoff; (2) The CF Foundation recommends using a very high IRT referral strategy in CF newborn screening programs whose variant panel does not include all CF-causing variants in CFTR2 or does not have a variant panel that achieves at least 95% sensitivity in all ancestral groups within the state; (3) The CF Foundation recommends that CF newborn screening algorithms should not limit <i>CFTR</i> variant detection to the F508del variant or variants included in the American College of Medical Genetics-23 panel; (4) The CF Foundation recommends that CF newborn screening programs screen for all CF-causing <i>CFTR</i> variants in CFTR2; (5) The CF Foundation recommends conducting <i>CFTR</i> variant screening twice weekly or more frequently as resources allow; (6) The CF Foundation recommends the inclusion of a <i>CFTR</i> sequencing tier following IRT and <i>CFTR</i> variant panel testing to improve the specificity and positive predictive value of CF newborn screening; (7) The CF Foundation recommends that both the primary care provider and the CF specialist be notified of abnormal newborn screening results. …”
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Genetic Subtype‐Based International Prognostic Index Prognostic Model in Diffuse Large B‐Cell Lymphoma by Lan Mi, Jili Deng, Jiayue Qin, Chen Zhang, Lixia Liu, Shunli Yang, Libin Chen, Hua‐Jun Wu, Haojie Wang, Jun Zhu, Hong Chen, Feng Lou, Shanbo Cao, Yuqin Song, Weiping Liu

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COOPERATIVE MODEL FOR OPTIMIZATION OF EXECUTION OF THREADS ON MULTI-CORE SYSTEM by A. A. Prihozhy, O. N. Karasik

“…It optimizes the execution order of the  computational operations and the operations of data exchange, decreases the overall time of the multithread application  execution by means of the reduction of the critical path in the concurrent algorithm graph, increases the application throughput at the growth of the number of threads, and excludes the competition among threads that is specific for preemptive multitasking...............................…”
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Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China by Ao Zhang, Xin-wen Zhao, Xing-yuezi Zhao, Xiao-zhan Zheng, Min Zeng, Xuan Huang, Pan Wu, Tuo Jiang, Shi-chang Wang, Jun He, Yi-yong Li

“…RF and XGB models were superior to LR and SVM models, indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.©2024 China Geology Editorial Office.…”
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Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review by Hesameddin Akbarein, Mohammad Hussein Taaghi, Mahyar Mohebbi, Parham Soufizadeh

“…It also examines the primary machine learning algorithms used in relevant studies, highlighting emerging trends in the field. …”
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Finite-element analysis of contact characteristics and friction modes of the "valve-guide" of the internal combustion engine by K.E. Holenko, A.A. Vychavka, M.O. Dykha, V.O. Dytyniuk

“…Modeling the performance of the "valve-guide" engine pair using modern software is an effective tool both for identifying weak points in the design and for predicting the behavior of the friction unit in operation. …”
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Self-organizing maps to evaluate optimal strategies for balancing binary class distributions: a methodological approach by Alberto Nogales, Diego Guadalupe, Álvaro J. García-Tejedor

“…Abstract Since machine learning algorithms rely on data, the way datasets are collected significantly impacts their performance. …”
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Use of Neural Networks for Stable, Accurate and Physically Consistent Parameterization of Subgrid Atmospheric Processes With Good Performance at Reduced Precision by Janni Yuval, Paul A. O'Gorman, Chris N. Hill

“…Abstract A promising approach to improve climate‐model simulations is to replace traditional subgrid parameterizations based on simplified physical models by machine learning algorithms that are data‐driven. However, neural networks (NNs) often lead to instabilities and climate drift when coupled to an atmospheric model. …”
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Automated CATS system for distance learning by Yu. B. Popova

“…These mathematical methods made it possible to develop adaptability algorithms, their software implementation and testing in the educational process. …”
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Tailoring orthotropic mechanical and thermal properties in nonlinear contact, vibration and thermal problems via kriging-based optimization by Yicong Zhou, Jinyan Duan, Guoxin Mao, Jun Hong

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PointNet++ (MSG-DSLS): A Classification Framework With Dynamic Step-Size Loop-Sampling for High-Density Tree Point Clouds by Zhen Liu, Ying Quan, Bin Wang, Jianyang Liu, Mingze Li

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Detection of platelet-associated immunoglobulins and complement system components in patients with aplastic anemia and hemoblastosis by A. F. Rakhmani, E. A. Mikhaylova, I. V. Galtseva, Yu. O. Davidova, N. M. Kapranov, I. V. Dubinkin, S. M. Kulikov, T. V. Gaponova, Z. T. Fidarova, V. V. Troitskaya, E. N. Parovichnikova, V. G. Savchenko

“…In addition to application of a certain transfusion therapy algorithm it is also necessary to detect PAIg (G, M, A) and PAC3 / C4 for prediction of severe refractoriness to donor's platelet transfusions.…”
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Phase diagram from nonlinear interaction between superconducting order and density: toward data-based holographic superconductor by Sejin Kim, Kyung Kiu Kim, Yunseok Seo

“…We introduce positional embedding layers to improve the learning process in our algorithm, and the Adam optimization is used to predict the critical temperature data via holographic calculation with appropriate accuracy. …”
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A Semi-Supervised Attention-Temporal Ensembling Method for Ground Penetrating Radar Target Recognition by Li Liu, Dajiang Yu, Xiping Zhang, Hang Xu, Jingxia Li, Lijun Zhou, Bingjie Wang

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Sparse sensing data–based participant selection for people finding by Ye Tian, Zhirong Tang, Jian Ma

“…Simulation results demonstrate that the proposed mechanism outperforms the other algorithms both in accuracy of positioning and quality of uploaded sensing data.…”
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