Neuro-Fuzzy Model Evaluation for Enhanced Prediction of Mechanical Properties in AM Specimens by Emmanouil-Marinos Mantalas, Vasileios D. Sagias, Paraskevi Zacharia, Constantinos I. Stergiou

“…Experimental data collected from AM processes are used to train the ANFIS model, allowing it to predict outputs such as stress, strain, and Young’s modulus under various printing parameters values. …”
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Risk Factor Analysis and Prediction Model Construction and Validation of Depression During Pregnancy by Huiling Qu, Yanna Zhou, Yi Yu

“…Conclusions: A nomogram model, which incorporates indicators such as spousal and parental disharmony, changes in sleep and dietary habits, work-study stress, adverse maternal history, unsatisfactory living environment, assisted reproduction, unplanned pregnancy, interference from adverse life events, and lack of maternity knowledge, can effectively predict depression during pregnancy.…”
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Research on Accelerated Degradation Test Design and Life Prediction for Aluminum Electrolytic Capacitor by YANG Tao, WANG Xu, XIAO Jianglin

“…Starting from the structure and degradation mechanism of aluminum electrolytic capacitor, this paper designs an accelerated degradation test with temperature as the accelerated sensitive stress, uses the accelerated degradation data for life prediction, and gives a top-down design direction for extending the life of aluminum electrolytic capacitors. …”
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Do Depressive Traits and Hostility Predict Age-Related Decline in General Intelligence? by Erik Lykke Mortensen, John Calvin Barefoot, Kirsten Avlund

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Harmful algal blooms are preceded by a predictable and quantifiable shift in the oceanic microbiome by Miranda C. Mudge, Michael Riffle, Gabriella Chebli, Deanna L. Plubell, Tatiana A. Rynearson, William S. Noble, Emma Timmins-Schiffman, Julia Kubanek, Brook L. Nunn

“…Abstract Harmful algal blooms (HABs) have become a worldwide environmental and human health problem, stressing the urgent need for a reliable forecasting tool. …”
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Mindfulness for Teachers: Strategies to Manage Stress and Improve Learning Quality in Madrasah by Imam Gojali, Fathi Hidayah, Ana Aniati, Hasan Baharun

“…This study focuses on the effectiveness of mindfulness training in reducing stress and improving the mental well-being of Islamic Religious Education (PAI) teachers at school. …”
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Comparison of hemodynamic effects and negative predictive value of normal adenosine gated myocardial perfusion scan with or without caffeine abstinence by Maseeh uz Zaman, Nosheen Fatima, Areeba Zaman, Unaiza Zaman, Rabia Tahseen

“…The aim of this study was to compare the hemodynamic changes and negative predictive value (NPV) of normal MPIs with adenosine stress performed with or without caffeine abstinence. …”
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MODIFIABLE AND NON-MODIFIABLE RISK FACTORS IN PREDICTING THE RECURRENCE OF ATRIAL FIBRILLATION IN PATIENTS WITH ARTERIAL HYPERTENSION by M. S. Arakelyan, N. G. Poteshkina, P. A. Mogutova

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ADAPTATION OF INTERNATIONAL STUDENTS TO THE RUSSIAN EDUCATIONAL SYSTEM by L.I. Khasanova

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Advancements in predicting soil liquefaction susceptibility: a comprehensive analysis of ensemble and deep learning approaches by Divesh Ranjan Kumar, Warit Wipulanusat

“…The BI-LSTM model has the highest accuracy, with 0.9791 in training and 0.8889 in testing, indicating strong predictive ability and good generalizability. LSTM follows closely with training and testing accuracies of 0.9433 and 0.8750, respectively, offering consistent performance. …”
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Techno-Stress of the Faculty Members in a Higher Education Institution: Basis for a Faculty Development Program by Cecile de Mesa Espiritu

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Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

“…In order to accurately predict the rockburst intensity level of the railway tunnel, the rock stress coefficient σθ/σc, rock brittleness coefficient σc/σt, and elastic energy index Wet are used as evaluation indexes of rockburst intensity, and a BP neural network rockburst prediction model based on hybrid particle swarm optimization algorithm is proposed. …”
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Study on the Prediction of the Height of Two Zones in the Overlying Strata under a Strong Shock by Xingping Lai, Bowei Liu, Pengfei Shan, Feng Cui, Yun Zhang, Xudong Zhang, Rui Bai, Xuan Wu

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Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation by Pascal B. Meyre, Stefanie Aeschbacher, Steffen Blum, Tobias Reichlin, Moa Haller, Nicolas Rodondi, Andreas S. Müller, Alain Bernheim, Jürg Hans Beer, Giorgio Moschovitis, André Ziegler, Bianca Wahrenberger, Elia Rigamonti, Giulio Conte, Philipp Krisai, Leo H. Bonati, Stefan Osswald, Michael Kühne, David Conen

“…We identify 5 biomarkers including D-dimer, growth differentiation factor 15 (GDF-15), interleukin-6 (IL-6), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and high-sensitivity troponin T (hsTropT) that independently predict cardiovascular death, stroke, myocardial infarction, and systemic embolism, significantly enhancing predictive accuracy. …”
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Prediction method of surface deformation around soft base dump based on viscoelastic theory by Dong WANG, Li YIN, Lanzhu CAO, Yiming FU, Liguo ZHANG, Chunhui ZHANG, Chunjian DING

“…A series of quantitative data is obtained through calculations and predictions of surface deformation on layered viscoelastic substrates under pile load actions in the discharging yard. …”
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Optimizing corn yield prediction: Integrating multi-temporal UAS data and machine learning by Huihui Zhang, Yuting Zhou, Shengfang Ma, Kevin Yemoto

“…The integration of VNIR and LWIR imagery improves yield prediction accuracy, particularly in water-stressed conditions, highlighting the importance of advanced sensing technologies and complex models such as RF and GB. …”
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Multi‐trait multi‐environment genomic prediction of preliminary yield trial in pulse crop by Rica Amor Saludares, Sikiru Adeniyi Atanda, Lisa Piche, Hannah Worral, Francoise Dariva, Kevin McPhee, Nonoy Bandillo

“…Multi‐trait multi‐environment enabled genomic prediction (MTME‐GP) offers a valuable alternative to predict missing phenotypes of selection candidates for multiple traits and diverse environments. …”
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Unveiling postpartum PTSD: predicting risk factors using decision trees and logistic regression in Chinese women by Xiao Fei Nie, Lan Lan Xu, Wen Ping Guo, Jin Hui Li, Li Cheng, Tao Tao Zhang, Jun-Yan Li

“…However, no studies have yet integrated both approaches to investigate postpartum posttraumatic stress disorder (PP-PTSD). This study aims to explore the factors associated with postpartum posttraumatic stress disorder (PP-PTSD) in Chinese women using decision tree and logistic regression models, while also comparing the predictive performance of both approaches. …”
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Suicidal ideation and thoughts of self-harm during the COVID-19 pandemic among Swedish employees: a cohort study on the role of job instability and job insecurity by Sandra Blomqvist, Hugo Westerlund, Linda L. Magnusson Hanson

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Novel insights into the genetic basis and transcriptomic elucidation of virulence attenuation in Pseudomonas syringae pv. actinidiae variants by Muhammad Asif, Renjian Hu, Ting Xie, Rong Fan, Youhua Long, Yong Wang, Shiping Wu, Zhibo Zhao, Lili Huang

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