Optimal Selection of the Reference Potential Probe Point in DCPD Real-Time Monitoring of Crack Growth Rate by He Xue, Siyu Gou, Chenqiang Ni, Liang Zhang, Shuai Wang, Youjun Zhao

“…Finite element method is used to analyze the electric potential field of the compact tensile sample, a mathematical model of the measurability and crack independence of the reference potential difference are constructed, genetic algorithm is used to find the optimal reference potential difference (RPD) probe point position, and finally, the crack monitoring experiments are performed to evaluate the feasibility of algorithm optimization results. …”
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Exploring the relationship between sepsis and Golgi apparatus dysfunction: bioinformatics insights and diagnostic marker discovery by Wanli Ma, Xinyi Liu, Ran Yu, Jiannan Song, Lina Hou, Ying Guo, Hongwei Wu, Dandan Feng, Qi Zhou, Haibo Li

“…Subsequently, functional enrichment analyses, including GO, KEGG, and GSEA, were performed to explore the biological significance of the GARGs.A PPI network was constructed to identify core genes, and immune infiltration analysis was performed using the ssGSEA algorithm. To further evaluate immune microenvironmental features, unsupervised clustering was applied to identify immunological subgroups. …”
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Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing by Hoang-Anh T. Vo, Sang Nguyen, Ai-Quynh T. Tran, Han Nguyen, Hai Bich Ho, Philip W. Fowler, Timothy M. Walker, Thuy Thi Nguyen

“…Automated Mycobacterial Growth Detection Algorithm (AMyGDA) is a software package that uses image processing techniques to read plates, but struggles with plates that exhibit low growth or images of low quality. …”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…Our research introduces a novel multisensor dataset designed to support the creation and evaluation of advanced multisensor fall detection algorithms. …”
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Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model by Tingting Hu, Liheng Zhao, Xueling Zhao, Lin He, Xiaoli Zhong, Zhe Yin, Junjie Chen, Yanting Han, Ka Li

“…Abstract Objective The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery. …”
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All-Digital Timing Recovery for Free Space Optical Communication Signals With a Large Dynamic Range and Low OSNR by Yunfeng Gu, Sheng Cui, Changjian Ke, Keji Zhou, Deming Liu

“…As timing recovery is indispensable for DCRs, the development of a timing recovery algorithm (TRA) capable of processing such FSOC signals is of particular interest in FSOC field. …”
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Comparison of proposed National Institute of Child Health and Human Development panel recommendations with newborn sepsis risk calculator in term neonates exposed to maternal chori... by Arpit Gupta, Julia Youssef, Nidhi Arora, Emad Ghaly, Alexander Shilkrut

“…The same cohort of newborns was evaluated using SRC and NICHD algorithm to determine whether treatment with antibiotics could have been avoided in some patients. …”
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Assessing water clarity in the Chesapeake Bay using satellite-derived Secchi disk depth by Seunghyun Son, Nikolay P. Nezlin, Veronica P. Lance

“…A semi-analytical SDD algorithm (hereafter called CB-SDD algorithm) proposed for turbid coastal waters was extensively evaluated in the Chesapeake Bay. …”
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Ranking Assisted Unsupervised Morphological Disambiguation of Turkish by Hayri Volkan Agun, Ozkan Aslan

“…Furthermore, to reduce ambiguity in sentences from different genres with scarce samples, the proposed method is easily adaptable.…”
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AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development by Petar Radanliev

“…These tools allow for a visual and systematic evaluation of the ethical principles guiding AI development across different jurisdictions. …”
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Comparative Analysis of Biomechanical Variables in Marker-based and Markerless Motion Capture Systems by D. I. Guseinov

“…Markerless motion capture systems have incomparable advantages over marker-based ones.In particular, significantly reduced time costs for the registration and data processing procedures, since registration is represented by filming a video from different angles, and processing is accompanied by the use of software algorithms for tracking the silhouette of an athlete using a presetted computer avatar. …”
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Key gene screening and diagnostic model establishment for acute type a aortic dissection by Yue Pan, Zhiming Yu, Xiaoyu Qian, Xuesong Zhang, Qun Xue, Weizhang Xiao

“…External dataset validation and PCR testing of clinical samples (n = 9) were conducted to confirm gene expression differences. A nomogram diagnostic model was constructed and evaluated for predictive accuracy.ResultsSix core genes were identified: Ccl2, Cdh8, Hk2, Tph1, Npy1r, and Slc24a4, with four (Ccl2, Hk2, Tph1, and Npy1r) showing significant differential expression in clinical validation. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…Additionally, we evaluated the performance of these models using different optimization techniques, including Adadelta, SGD, RMSprop, and Adam, to determine the most effective optimization strategy for improving classifica-tion accuracy. …”
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Exploring the role of alternative lengthening of telomere-related genes in diagnostic modeling for non-alcoholic fatty liver disease by Nan Zhu, Xiaoliang Wang, Huiting Zhu, Yue Zheng

“…This study employed a support vector machine algorithm and least absolute shrinkage and selection operator regression analysis to identify key genes for constructing a diagnostic model. …”
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Electronic nose and machine learning for modern meat inspection by Ivan Shtepliuk, Guillem Domènech-Gil, Viktor Almqvist, Arja Helena Kautto, Ivar Vågsholm, Sofia Boqvist, Jens Eriksson, Donatella Puglisi

“…Based on the consensus of preliminary decisions from each individual sensor element, the algorithm effectively determined the final status of the meat. …”
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An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments by Zhenling Dai, Ziqun Gu, Rongrong Shen, Jingshuai Wang

“…Notably, this 11-gene signature also predicted the sensitivity of breast cancer to both conventional and immune therapies, aligning closely with predictions from the OncoPredict algorithm. Further, in-vitro experiments confirmed the regulatory role of HOXC13, one of the 11 genes, in the cGAS-STING pathway. …”
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THE RELATIONSHIP BETWEEN THE INDIVIDUAL GENETICALLY DETERMINED FACIAL PROFILE OF PATIENTS WITH A DISTAL OCCLUSION (ENGLE CLASS II) AND THE TYPE OF GROWTH OF THEIR FACIAL SKULL AND... by S.I. Doroshenko, O.Y. Opekha, V.V. Volkova

“…Jarabak methods has enabled a more detailed diagnosis of distal occlusion (Class II malocclusion) and the development of a comprehensive treatment algorithm with improved outcome prediction. …”
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Asynchronous layerwise deep learning with MCMC on low-power devices by Francois M., Gay P., Lebeaud S., Loustau S., Palafox J., Sow F.K., Tirel N.

“…The learning process is tested on two different environments and the electricity consumption is evaluated on several epochs, based on a homemade open source library using standard softwares and performance counters, and compared with a physical power meter. …”
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Optimizing axial length estimation for intraocular lens power calculation in phacovitrectomy for macula-off retinal detachment by Sukhum Silpa-archa, Chitchanok Samanwongthai, Variya Nganthavee, Korawin Charoensuk

“…The lowest MAE was achieved using the simple algorithm (0.31 ± 0.55 mm), followed by the AL of the fellow eye measured via IOL Master (0.34 ± 0.60 mm), and the advanced algorithm (0.36 ± 0.62 mm). …”
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A THREE-TERM CONJUGATE GRADIENT METHOD FOR LARGE-SCALE MINIMIZATION IN ARTIFICIAL NEURAL NETWORKS by Umar A Omesa, Muhammad Y. Waziri, Issam A. R. Moghrabi, Sulaiman M. Ibrahim, Gudu E B, Fakai S L, Rabiu Bashir Yunus, Elissa Nadia Madi

“…To evaluate the performance of the new method we considered some standard test problems for unconstrained optimization and applied the proposed method to train different ANNs on some benchmark data sets contained in the NN toolbox. …”
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