Impact of Women’s Land Ownership Patterns on Intimate Partner Violence in Tanzania by Laurent Joseph

“…"The study aimed at analysing the lonely, joint, and title deed land ownership by women on intimate partner violence (IPV) they experience in region population variability in the Tanzanian context. This quantitative explanatory study used ANOVA and multi-linear regression to analyse secondary data from 2015-16 and 2022 TDHS-MIS reports and population and women who own land alone, each having a census in 2022 and its estimation in 2015 based on the 2012 census. …”
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Exposure–response relationship of household air pollution on body mass index among women in rural areas of Guatemala, India, Peru and Rwanda: household air pollution intervention n... by Adolphe Ndikubwimana, William Checkley, Yunyun Chen, Thomas Clasen, Carmen Lucía Contreras, Anaite Diaz-Artiga, Ephrem Dusabimana, Lisa de las Fuentes, Shirin Jabbarzadeh, Michael Johnson, Egide Kalisa, Patrick Karakwende, Miles Kirby, Amy E. Lovvorn, John P. McCracken, Florien Ndagijimana, Theoneste Ntakirutimana, Jean Dieu Ntivuguruzwa, Jennifer L. Peel, Ajay Pillarisetti, Victor G. Dávila-Román, Ghislaine Rosa, Sarada S. Garg, Lisa Thompson, Lance A. Waller, Jiantong Wang, Maggie L. Clark, Bonnie N. Young, the HAPIN investigators

“…Results We observed mixed evidence of associations between household air pollution and BMI in linear regression. There was no association with BMI and PM₂.₅ (1-unit increase in log-transformed PM₂.₅ estimate 0.02 kg/m2 [95% CI: -0.51, 0.54]) or CO (1-unit increase in log-transformed CO estimate 0.42 kg/m2 [95% CI -0.31, 1.14]). …”
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Understanding tinnitus symptom dynamics and clinical improvement through intensive longitudinal data by Milena Engelke, Jorge Piano Simões, Laura Basso, Nina Wunder, Berthold Langguth, Thomas Probst, Rüdiger Pryss, Winfried Schlee

“…Clinical improvement was associated with linear declines in tinnitus-related thoughts, jaw tension, tinnitus loudness, increases in happiness, and variability changes in tinnitus loudness and distress. …”
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Metabolomics Profiling of Epicardial Adipose Tissue: MESA and the Rotterdam Study by Ian J. Neeland, Fang Zhu, Goncalo Graca, Anastasios Lymperopoulos, Gianluca Iacobellis, Ali Farzaneh, Daniel Bos, Mohsen Ghanbari, Jeffrey J. Goldberger, Maryam Kavousi, Philip Greenland

“…Associations between fasting serum metabolites and EAT volume were assessed using cross‐sectional linear regression of individual‐level data in MESA and validated in Rotterdam. …”
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Incorporating gene expression and environment for genomic prediction in wheat by Jia Liu, Jia Liu, Andrew Gock, Kerrie Ramm, Sandra Stops, Tanya Phongkham, Adam Norman, Russell Eastwood, Eric Stone, Shannon Dillon

“…We evaluated the performance of different model scenarios based on linear (GBLUP) and Gaussian/nonlinear (RKHS) regression in the Bayesian analytical framework. …”
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An Adaptive Prediction Framework of Ship Fuel Consumption for Dynamic Maritime Energy Management by Ya Gao, Yanghui Tan, Dingyu Jiang, Peisheng Sang, Yunzhou Zhang, Jie Zhang

“…The effectiveness of the proposed approach was validated using a real-world dataset from an LPG carrier, where it was benchmarked against conventional machine learning models, including Random Forest (RF), Linear Regression (LR), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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Correlation of global and gene-specific DNA methylation in maternal-infant pairs. by Molly L Kile, Andrea Baccarelli, Letizia Tarantini, Elaine Hoffman, Robert O Wright, David C Christiani

“…Positive correlations were observed between maternal and umbilical cord blood at p16, LINE-1, and Alu but not p53. Multiple linear regression models observed a significant association between maternal and umbilical cord blood at LINE-1 and Alu (LINE-1: β = 0.63, p<0.0001; Alu: β = 0.28, p = 0.009). …”
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Predictors of Quality of Life in Psoriasis Patients: Insights from a Cross-Sectional Study by Walniczek P, Ponikowska M, Kolarczyk EB, Spaleniak P, Mróz-Kijowska K, Czapla M, Uchmanowicz I

“…The analysis included demographic, clinical, and psychological variables to evaluate their impact on quality of life.Results: The multivariate linear regression model revealed that significant independent predictors of quality of life included age (p=0.001), duration of disease (p=0.004), and nutritional status (p=0.002). …”
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A comparative analysis of five land surface temperature downscaling methods in plateau mountainous areas by Ju Wang, Ju Wang, Ju Wang, Bo-Hui Tang, Bo-Hui Tang, Bo-Hui Tang, Bo-Hui Tang, Xinming Zhu, Xinming Zhu, Xinming Zhu, Dong Fan, Dong Fan, Dong Fan, Menghua Li, Menghua Li, Menghua Li, Junyi Chen, Junyi Chen, Junyi Chen

“…Three machine learning models, including Back Propagation (BP) Neural Network, random forest (RF), and extreme gradient boosting (XGBoost), and two classic single-factor linear regression models (DisTrad and TsHARP) were compared. …”
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Influence of submarine groundwater discharge on the nutrient dynamics of a fringing-reef lagoon by Zoe Ruben, Dorina Murgulet, Cody V. Lopez, Ismael Marino-Tapia, Arnoldo Valle-Levinson, Kathleen E. Matthews

“…Inputs vary with SGD magnitudes and sources and by proximity to active spring discharges. Groundwater multi-tracer analysis and multiple linear regression identify 226Ra as explaining NH4+ variability due to long-term groundwater processes, while 223Ra predicts NOx-, HSiO3-, and urea due to short-term inputs. …”
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Enhanced wind power forecasting using machine learning, deep learning models and ensemble integration by T. A. Rajaperumal, C. Christopher Columbus

“…A wide range of ML models—Random Forest (RF), Decision Trees, Linear Regression, K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and Gradient Boosting—alongside DL models such as Multi-Layer Perceptron (MLP) and Long Short-Term Memory (LSTM) were evaluated. …”
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The 5-year outcomes of a health-empowerment program on low-income children’s behaviors and quality of life by Fangcao Lu, Carlos King Ho Wong, Emily Tsui Yee Tse, Amy Pui Pui Ng, Lanlan Li, Laura Bedford, Daniel Yee Tak Fong, Patrick Ip, Cindy Lo Kuen Lam

“…Multiple linear regressions were conducted to identify changes in outcome variables as the effect of the HEP. …”
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Quantitative electroencephalography predicts postoperative delirium in adult cardiac surgical patients from a prospective observational study by Zhibao Guo, Wang Wan, Wenxue Liu, Ling Liu, Yi Yang, Congshan Yang, Xingran Cui

“…Linear regression was performed to quantify associations among EEG findings, delirium, and clinical outcomes. …”
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Trajectories of mHealth-Tracked Mental Health and Their Predictors in Female Chronic Pelvic Pain Disorders by Leventhal EL, Nukavarapu N, Elhadad N, Bakken SR, Elovitz MA, Hirten RP, Rodrigues J, Danieletto M, Landell K, Ensari I

“…Additionally, this study demonstrates the potential of ambulatory mHealth-based data combined with functional models for delineating inter-individual and temporal variability.Keywords: chronic pelvic pain, digital health, functional data modeling, global mental health…”
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Comprehensive Analysis of Phenotypic Traits in Chinese Cabbage Using 3D Point Cloud Technology by Chongchong Yang, Lei Sun, Jun Zhang, Xiaofei Fan, Dongfang Zhang, Tianyi Ren, Minggeng Liu, Zhiming Zhang, Wei Ma

“…Based on the plant spread and plant height, a linear regression prediction of Chinese cabbage weights was conducted, yielding an R² value of 0.76. …”
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Long-term health related quality of life in adult extracorporeal membrane oxygenation survivors: a single-centre, cross-sectional study by Xiaoting Zeng, Fuxun Yang, Xiaoxiu Luo, Jiajia Li, Yunping Lan, Fan Zeng, Yu Lei, Chun Pan, Rongan Liu, Xiaobo Huang

“…Statistical analyses included the two-sample rank sum test, multi-sample Kruskal-Wallis test, Spearman correlation analysis, and multiple linear regression to assess relationships between health-related quality of life and various factors. …”
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Assessment of pan coefficient performance: A comparative study of empirical and model-driven approaches using a hill-climbing-based alternating model tree and MOORA by Saad Javed Cheema, Aitazaz A. Farooque, Mehdi Jamei, Khabat Khasravi, Farhat Abbas, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal

“…However, this is quite challenging due to variations in climate change and the deep non-linearity of meteorological data. Intensive experiments for pan evaporation (Epan) were conducted to develop a model, which includes hill-climbing based BestFirst-ClassifierSubsetEval (BF), alternating model tree (AMT), and multi-objective optimization by ratio analysis (MOORA). …”
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Surface distributions and vertical profiles of trace gases (CO, O₃, NO, NO₂) in the Arctic wintertime boundary layer using low-cost sensors during ALPACA-2022 by B. Barret, P. Medina, N. Brett, R. Pohorsky, K. S. Law, S. Bekki, G. J. Fochesatto, J. Schmale, S. R. Arnold, A. Baccarini, M. Busetto, M. Cesler-Maloney, B. D'Anna, S. Decesari, J. Mao, G. Pappaccogli, J. Savarino, F. Scoto, W. R. Simpson

“…For NO, NO<span class="inline-formula">₂</span>, and O<span class="inline-formula">₃</span>, the best agreements for the prediction datasets were obtained with an artificial neural network, the multi-layer perceptron. For these three gases, the correlation coefficients are higher than 0.95, and the slopes of linear regressions with the reference data are in the range 0.93–1.04. …”
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