Development of endothelial dysfunction at an obliterating atherosclerosis of vessels of the lower extremities and markers of prediction of a course of a disease by S. S. Dunaevskaya, Yu. S. Vinnik

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Personality predicts internalizing symptoms and quality of life in police cadets: a comparison of artificial intelligence and parametric approaches by Macià Buades-Rotger, Ana Martínez Catena, Guillermo Recio, Mireia Cano Gallent, Jordi Niñerola i Maymí, Anna Figueras Masip, David Gallardo-Pujol

“…Abstract Background Police cadets undergo persistent and elevated stress due to continuous training and evaluation. …”
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Prediction and reliability analysis of rigid pipeline response in soft soil using improved particle swarm neural network by Laifu Song, Shun Zhang, Jun Wang, Hongtao Fu, Jiayu Cai

“…An improved PSO-BPNN method for predicting the dynamic response of pipelines is proposed, and the accuracy and applicability of the method are verified. …”
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An equipment behavioral study in fluidic production processes using data for an optimized predictive maintenance: Application to pneumatic valves in biopharmaceutical Industry by Wadel Florent, Tighazoui Ayoub, Houssin Remy, Coulibaly Amadou

“…Predictive maintenance of production equipment is gaining increasing interest in the biopharmaceutical industry in the context of Industry 4.0, where reliability is essential to ensure product quality, equipment availability, and compliance with strict standards. …”
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Training Load and Current Soreness Predict Future Delayed Onset Muscle Soreness in Collegiate Female Soccer Athletes by Brett S. Pexa, Christopher J. Johnston, Jeffrey B Taylor, Kevin R. Ford

“…# Background Delayed onset muscles soreness (DOMS) is an indication of muscle stress and trauma that develops from excessive musculoskeletal loads. …”
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Predicting damage in notched functionally graded materials plates through extended finite element method based on computational simulations by Hakim Siguerdjidjene, Amin Houari, Kouider Madani, Salah Amroune, Mohamed Mokhtari, Barhm Mohamad, Chellil Ahmed, Abdelkrim Merah, Raul D.S.G. Campilho

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Growth Differentiation Factor 15 May Predict Mortality of Peripheral and Coronary Artery Diseases and Correlate with Their Risk Factors by Lung-An Hsu, Semon Wu, Jyh-Ming Jimmy Juang, Fu-Tien Chiang, Ming-Sheng Teng, Jeng-Feng Lin, Hsuan-Li Huang, Yu-Lin Ko

“…We further enrolled 86 patients with PAD and 481 patients with CAD, who received endovascular intervention and coronary angiography, respectively, to examine the role of GDF15 level in predicting all-cause mortality. Significant associations were found between GDF15 genotypes/haplotypes and GDF15 levels. …”
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Medium-Chain Acyl-CoA Deficiency: Outlines from Newborn Screening, In Silico Predictions, and Molecular Studies by Serena Catarzi, Anna Caciotti, Janita Thusberg, Rodolfo Tonin, Sabrina Malvagia, Giancarlo la Marca, Elisabetta Pasquini, Catia Cavicchi, Lorenzo Ferri, Maria A. Donati, Federico Baronio, Renzo Guerrini, Sean D. Mooney, Amelia Morrone

“…The functional and pathogenic characterization of genetic variants presented here is required to predict their medical consequences in newborns.…”
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Predicting Job Burnout of Medical Staff of Karaj Government Hospitals by Ego Strength: Mediating Role of Emotion Regulation and Alexithymia by Jamil Mansouri, Mina Mohammadi, Mohammad Ali Besharat, Nazila Amani

“…The indirect path analysis results indicated that the relationship between ego strength and job burnout is substantially mediated by emotion regulation and alexithymia. Considering the stressful environment of hospitals and considering the findings of the research, it is possible to design and implement educational and intervention programs based on ego strength with more emphasis on emotional dimensions, including emotion regulation and alexithymia, in order to reduce the burnout of medical staff.…”
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Predicting the strength of 3D-printed conductive composite under tensile load: A probabilistic modeling and experimental study by Nassima Naboulsi, Fatima Majid, Taoufik Hachimi, Soufyan Dadoun, Najoua Barhoumi, Kaouther Khlifi

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A Compressor - System Digital Twin for Performance Prediction Under a Wide Range of Flow and Operating Conditions by Alberto Serena, Lars E. Bakken

“…The model under study is vital in the definition of the actual surge margin and of a suitable recovery strategy; an early detection is needed to safeguard stable operation and avoid unnecessary stresses. The main focus is the validation of the system model at the boundary of the operating envelope, and, in particular, the study and prediction of the trip trajectory, caused by disturbances in the power input, or variations in inlet composition, or downstream equipment pressure build-up. …”
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Optimal design of a hybrid ship energy management system under various sea conditions using Model Predictive Control. by Rafia Mushtaq, Muhammad Iqbal, Abdul Khaliq, Jamshed Iqbal

“…This paper introduces an optimal design and control approach for a hybrid ship energy management system under various sea conditions by employing model predictive control. Ship reliability and environmental sustainability can be enhanced by reducing emissions and ecological impact. …”
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Evaluating Predictive Value of Plasma Free Hemoglobin (PFH) in ECMO for COVID-19, Non-COVID-19 Pulmonary, and Cardiac Patients by Wasiq Rashid, Varshith Paduchuri, Joby Chandy, John Hodgson, Enrico Camporesi

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Econometric predictive model for assessing the functional state of students during the examination period: a cross-sectional exploratory pilot study by I. S. Knyazhev, L. V. Karaulova, O. V. Reztsov, A. P. Spitsin

“…The values in adaptive potential exceeded 2.0 points, indicating the stress of the cardiovascular adaptation. The correlation regression analysis showed the greatest significance of the multiple linear regression model developed by the authors for predicting the adaptive potential of the cardiovascular system.…”
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Evaluation of PINK1 protein expression as a predictive marker for the efficacy of adjuvant chemotherapy in colorectal cancer: a retrospective study by Takatsugu Fujii, Masataka Hirasaki, Yasuo Kamakura, Tomonori Kawasaki, Satoshi Yamasaki, Yasuhiro Ishiyama, Chikashi Hiranuma, Tetsuya Hamaguchi, Yasumitsu Hirano, Shinichi Sakuramoto

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Mindfulness-based stress reduction intervention during pregnancy changes maternal brain by Yvan Gomez, Ayako Nakaki, Allegra Conti, Sara Castro-Barquero, Benedetta Gambosi, Irene Casas, Mariona Genero, Lina Youssef, Leticia Benitez, Noelia Encabo, Rosa Casas, Andrés Martín-Asuero, Teresa Oller-Guzmán, Ivette Morilla, Anabel Martínez-Àran, Nuria Bargallo, Nicola Toschi, Ramon Estruch, Eduard Vieta, Fàtima Crispi, Eduard Gratacos, Francesca Crovetto

Subjects: “…Mindfulness-based stress reduction…”
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Psychological characteristics of educational stress of modern students by Halina Dubczak

“… The article presents the results of the empirical research of psychological characteristics of stress reactions that occur during educational activities of modern Ukrainian students. …”
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Machine Learning-Based Prediction of Fatigue Fracture Locations in 7075-T651 Aluminum Alloy Friction Stir Welded Joints by Guangming Mi, Guoqin Sun, Shuai Yang, Xiaodong Liu, Shujun Chen, Wei Kang

“…In this study, we investigate fatigue fracture location prediction in 7075-T651 aluminum alloy FSW joints by applying four machine learning methods—decision tree, logistic regression, a three-layer back-propagation artificial neural network (BP ANN), and a novel Quadratic Classification Neural Network (QCNN)—using maximum stress, stress amplitude, and stress ratio as input features. …”
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Predicting high anger intensity using ecological momentary assessment and wearable-derived physiological data in a trauma-affected sample by Olivia Metcalf, Karen E. Lamb, David Forbes, Meaghan L. O’Donnell, Tianchen Qian, Tracey Varker, Sean Cowlishaw, Sophie Zaloumis

“…However, no prediction models have been built in trauma-exposed populations that leverage real-world data.Objective: This project aimed to determine if wearable-derived physiological data can predict anger intensity in trauma-exposed adults.Method: Heart rate variability (i.e. a commercial wearable stress score) was combined with ecological momentary assessment (EMA) data collected over 10 days (n = 84). …”
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Design of an Optimized Feature Driven Severity Stage Classifier for Parkinson’s Disease Prediction Using Deep Learning by K. Shyamala, T. M. Navamani

“…We proposed a Parkinson’s Speech Stage-Net model (PSS-Net) for the prediction of the severity of PD that includes Isolation Forest-based outlier detection and removal, KMeansSMOTE data balancing, and Optimized Dimensionality Reduction techniques. …”
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