DEVELOPMENT OF NONPARAMETRIC PATH FUNCTION USING HYBRID TRUNCATED SPLINE AND KERNEL FOR MODELING WASTE-TO-ECONOMIC VALUE BEHAVIOR by Usriatur Rohma, Adji Achmad Rinaldo Fernandes, Suci Astutik, Solimun Solimun

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Mothers’ intention to vaccinate their daughters against human papillomavirus in NorthWest Ethiopia, using the theory of planned behavior by Samrawit Tilahun, Habtamu Wondiye, Zeamanuel Anteneh Yigzaw

“…The study participants were selected using a multi-stage random sampling technique. Data was collected using an interview-administered questionnaire. …”
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Effect of fracture energy estimation on the predictions of mode II behavior of bonded joints using cohesive zone models by Michele Perrella, Enrico Armentani, Giuseppe Lamanna, Valentino Paolo Berardi

“…The mode II cohesive traction-separation law was identified by numerical differentiation of SERR and best fit equation systems were adopted for an analytical description of cohesive interface behavior. Moreover, the obtained CZM laws were used for predicting the decohesion process by finite element analyses. …”
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Relationship between the Health Literacy and Intention to Conduct Diabetes Testing in At-risk Individuals using the Theory of Planned Behavior by Narges Abdolmaleki, Afshin Bahmani, Sayran Nili, Arezoo Fallahi

“…Data were analyzed using the SPSS (version 23) software, descriptive tests (mean and standard deviation), and analytical tests (chi-square, Pearson correlation, and multiple regressions). …”
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Detecting Anomalies in CPU Behavior Using Clustering Algorithms from the Scikit-Learn Library in Python Programming Language by Artem Turashev, Vladimir Sukhomlin

“…This article examines the problem of detecting anomalies in central processing unit (CPU) operation using time series clustering algorithms. The central processing unit is the main computing component responsible for executing instructions and processing data. …”
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Effect of fracture energy estimation on the predictions of mode II behavior of bonded joints using cohesive zone models by Michele Perrella, Enrico Armentani, Giuseppe Lamanna, Valentino Paolo Berardi

“…The mode II cohesive traction-separation law was identified by numerical differentiation of SERR and best fit equation systems were adopted for an analytical description of cohesive interface behavior. Moreover, the obtained CZM laws were used for predicting the decohesion process by finite element analyses. …”
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Identification of Subtypes of Post-Stroke and Neurotypical Gait Behaviors Using Neural Network Analysis of Gait Cycle Kinematics by Andrian Kuch, Nicolas Schweighofer, James M. Finley, Alison McKenzie, Yuxin Wen, Natalia Sanchez

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The thermal and Pasternak foundation effect on the transient behaviors of the rectangular plate using a novel semi-analytical method by Xu Liang, Zeng Cao, Yu Deng, Xue Jiang, Xing Zha, Jianxing Leng

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Prediction of stress-strain behavior of rock materials under biaxial compression using a deep learning approach. by Changsheng Li, Xinsong Zhang

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Exploring the influence of media and social factors on altruistic behavior using the general learning model and norm activation theory by Chi-Horng Liao

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Addressing racial disparities in COVID-19 compliance: A community-driven approach using the theory of planned behavior by Florent Nkouaga

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The trust paradox: An exploration of consumer psychology and behavior in cross-border shopping using E-commerce mobile applications by Kuo-Jui Liu, Shang-Liang Chen, Ho-Chuan Huang, Mon-Long Gan

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Longitudinal analysis of behavioral factors and techniques used to identify vaccine hesitancy among Twitter users: Scoping review by Sulaiman Khan, Md. Rafiul Biswas, Zubair Shah

“…This scoping review aims to identify the community and individual factors that longitudinally influence public behavior toward vaccination. The secondary aim is to gain insight into techniques and methodologies used to extract these factors from Twitter data. …”
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Virtual assessment: using in-game behaviors during immersive role-play for contextually relevant assessment of fear of intimacy by Yijun Qian, Luoying Lin, Yaning Li, Yaning Li, Zhimeng Wang, Meng Li, Xin Tong, RAY LC

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Application of Behavior-Based Safety to Reduce Unsafe Actions in Preventive Maintenance Work Using the JSA and DO IT Methods by Aura Irsyaf Putri, Muhammad Nur, Misra Hartati, Anwardi, M. Isnaini Hadiyul Umam

“…This study aims to reduce unsafe actions during PM activities by implementing the Job Safety Analysis (JSA) method and the DO IT (Define, Observe, Intervene, and Test) approach within the Behavior Based Safety (BBS) framework. The research was conducted using field observations, interviews with workers, and accident data collected from 2023. …”
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Modeling study of the magnetocaloric behavior of La₀.₆₇Ca₀.₃₃Mn₀.₉₈Ni₀.₀₂O₃ alloys using artificial neural networks by Kawther Laajimi, Emna Ammar Elhadjamor, Radhouane Laajimi, Mehdi Rahmani, Mohamed Hichem Gazzah

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Thermal Multi-Sensor Assessment of the Spatial Sampling Behavior of Urban Landscapes Using 2D Turbulence Indicators by Gabriel I. Cotlier, Drazen Skokovic, Juan Carlos Jimenez, José Antonio Sobrino

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Predicting Breast Cancer Screening Behaviors Using Protective Motivation Theory: A Structural Equation Modeling Approach by Yizheng Gao, Jianwei Yu, Hairuo Wang, Binhao Liu, Shunhua Zhang

“…Methods: This cross-sectional study included 895 women from eastern China. Data were collected using an online questionnaire that included sociodemographic information, PMT theoretical construction, and breast cancer screening behavior. …”
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Classification of overweight/obesity among Saudi adolescents relative to lifestyle behaviors using the IOTF or WHO reference standards by Hazzaa M. Al-Hazzaa, Hazzaa M. Al-Hazzaa, Amal Alhakami, Ahlam M. Alotaibi, Ahlam M. Alotaibi

“…PurposeTo compare two BMI classifications (the IOTF and WHO references) in assessing overweight/obesity prevalence among Saudi adolescents and to evaluate the ability of the two standards to detect risks of unhealthy lifestyle behaviors.MethodsHealthy Saudi adolescents (15–19 years) were drawn from two data sets (n = 2,263) collected previously in 2009 and 2019, using a random multistage stratified cluster sampling technique. …”
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Discovering action insights from large-scale assessment log data using machine learning by Minyoung Yun, Minjeong Jeon, Heyoung Yang

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