Relevant biochar characteristics influencing compressive strength of biochar-cement mortars by Julia Hylton, Aaron Hugen, Steven M. Rowland, Michael Griffin, Lori E. Tunstall

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Mechanism and relevance of necroptosis to immune microenvironment of periodontitis: A pilot study by ZHENG Zhanglong, LI Jia, JIANG Jirui, SHAN Zhengnan, LI Shengjiao

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Social Media as a New Communication Platform in the Context of the Information Eco Strategy by Halyna Bryikhanova, Veronika Zaitseva, Iryna Gamova, Diana Fayvishenko

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Criteria for Psychological Evaluation of Legally Relevant Emotional States of Defendants: Methodological Recommendations by F. S. Safuanov, O. F. Savina, M. V. Morozova, I. V. Isaeva

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PANoptosis-Relevant Subgroups Predicts Prognosis and Characterizes the Tumour Microenvironment in Ovarian Cancer by Chen Y, Deng Z, Chen J, Lin J, Zou J, Li S, Sun Y

“…However, its prognostic relevance in OC remains unclear.Methods: Utilizing data from The Cancer Genome Atlas (TCGA), we analyzed transcriptomic and clinical signatures of OC patients. …”
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Time Series measurements of White Blood Cells (WBC) and plasma Cancer Antigen 15-3 (CA 15-3) in a patient with metastatic breast cancer, serving as a reference for assessing the clinical relevance of different clustering algorithms. by Alexandros CLOUVAS

“…The present study marks a significant advancement, as the time-series measurements of White Blood Cells (WBC) and plasma CA 15-3 from the same patient served as a reference for assessing the clinical relevance of various clustering algorithms. The time-series measurements of WBC are particularly noteworthy because the specific therapy administered to the patient has clearly defined all clustering parameters, including the number of clusters and their boundaries. …”
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İlgi Sıralamalarının Artırımlı Olarak Geliştirilmesi: Pennant Erişimle Desteklenen Yeni Bir Yöntem Önerisi by Yaşar Tonta, Müge Akbulut

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Predictive analysis of solubility data with pressure and temperature in assessing nanomedicine preparation via supercritical carbon dioxide by Hashem O. Alsaab, Yusuf S. Althobaiti

“…Three models, namely Automatic Relevance Determination Regression (ARD), Gaussian process regression (GPR), and Linear Regression (LR) were designed and tuned to build predictive models. …”
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Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO by Sheng-wei Fei, Yong He

“…In this paper, Cauchy kernel relevance vector machine with stochastic inertia weight particle swarm optimization algorithm (SIWPSO-CauchyRVM) is proposed to fault diagnosis for bearing. …”
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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

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Clinical relevance and druggability of sole reciprocal kinase fusions: A large‐scale study by Jiao Feng, Tonghui Ma, Chunyang Wang, Baoming Wang, Qian Liu, Zhengchuang Liu, Houquan Tao, Zaiyuan Ye

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The method of increasing the efficiency of the man-machine system functioning by improving the quality of decision support system software by О.В. Турінський, М.А. Павленко, Г.В. Пєвцов, С.В. Осієвський

“…The time complexity of the algorithms implementing the relevance tree tasks was evaluated. …”
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A multi-label classification method for disposing incomplete labeled data and label relevance by Lina ZHANG, Lingpeng DAI, Tai KUANG

“…Multi-label classification methods have been applied in many real-world fields，in which the labels may have strong relevance and some of them even are incomplete or missing.However，existing multi-label classification algorithms are unable to handle both issues simultaneously.A new probabilistic model that can automatically learn and exploit multi-label relevance was proposed on label relevance and missing label classification simultaneously.By integrating out the missing information，it also provides a disciplined approach to handle missing labels.Experiments on a number of real world data sets with both complete and incomplete labels demonstrated that the proposed method can achieve higher classification and prediction evaluation scores than the existing multi-label classification algorithms.…”
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Maximizing Nash Social Welfare Based on Greedy Algorithm and Estimation of Distribution Algorithm by Weizhi Liao, Youzhen Jin, Zijia Wang, Xue Wang, Xiaoyun Xia

“…It is proven that the proposed algorithm aligns with the previous greedy algorithm when all agents possess identical valuations. …”
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Enhancing Algorithmic Literacy: Experimental Study on Communication Students’ Awareness of Algorithm-Driven News by Jose Manuel Noguera-Vivo, María del Mar Grandío-Pérez

“…The relevance of digital information dissemination theories such as incidental consumption, news-finds-me perception, echo chambers and filter bubbles is highlighted in understanding algorithm-driven news selection. …”
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Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions. by Sergio Rojas-Galeano, Emily Hsieh, Dan Agranoff, Sanjeev Krishna, Delmiro Fernandez-Reyes

“…Our method combines a weighted-kernel discriminant with an iterative stochastic probability estimation algorithm to discover the relevance distribution over the set of variables. …”
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Control-Relevant Adaptive Personalized Modeling From Limited Clinical Data for Precise Warfarin Management by Affan Affan, Jacek M. Zurada, Tamer Inanc

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Prediction of Graduate Career Relevance Based on Academic and Non-Academic Aspects using Machine Learning by Muhammad Yusuf Luthfi Ijlal, Arif Setiawan, Diana Laily Fithri

“…However, not all graduates succeed in securing employment in fields relevant to their area of study. This study aims to analyze the influence of academic and non-academic factors on career alignment and to develop a predictive model using machine learning algorithms. …”
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Higher glass transition temperatures reduce thermal stress cracking in aqueous solutions relevant to cryopreservation by Soheil Kavian, Ronald Sellers, Gabriel Arismendi Sanchez, Crysthal Alvarez, Guillermo Aguilar, Matthew J. Powell-Palm

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An Algorithm for Forecasting Future Trends by Aleksandr Borzov, Viktor Sorokin, Vitaly Mityazov, Daria Shimanova

“…Considering this context, this work aims to develop an algorithm to identify and analyse topics that would be relevant in the future using autoregression methods. …”
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