Human rights violations are associated with forcibly displaced population’s mental health—a systematic review and meta-analysis by Felix Sisenop, Pallavi Chatarajupalli, Paul A. Bain, Hanna Kaade, Jutta Lindert

“…For anxiety, the prevalence rate was greater with random sampling compared to convenience sampling (44.71% vs. 36.87%). …”
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Ensemble learning to predict short birth interval among reproductive-age women in Ethiopia: evidence from EDHS 2016–2019 by Jenberu Mekurianew Kelkay, Deje Sendek Anteneh, Henok Dessie Wubneh, Abraham Dessie Gessesse, Gebeyehu Fassil Gebeyehu, Kalkidan Kassahun Aweke, Mikiyas Birhanu Ejigu, Mathias Amare Sendeku, Kirubel Adrissie Barkneh, Hasset Girma Demissie, Wubshet D. Negash, Birku Getie Mihret

“…Region, residency, age of women, sex of child, respondent education, distance health facility, husband education and religion were top predicting factors of short birth interval among women in Ethiopia. Conclusion Random forest was best predictive models with improved performance. …”
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Asymptotic Behavior of the Kirchhoff Type Stochastic Plate Equation on Unbounded Domains by Xiaobin Yao, Zhang Zhang

“…We first prove the uniform estimates of solutions and then establish the existence and upper semicontinuity of random attractors.…”
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𝑞-Gaussian Distributions: Simplifications and Simulations by Paweł J. Szabłowski

“…We also present an algorithm for simulating i.i.d. sequences of random variables having 𝑞-Gaussian distribution.…”
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Management of Melaleuca by Residents in South Florida by Katherine Carter-Finn, Alan W. Hodges, Donna J. Lee, Michael T. Olexa

“…Olexa, describes the results of a survey of a random sample of households in the 10 southernmost counties of Florida. …”
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n-Digit Benford Converges to Benford by Azar Khosravani, Constantin Rasinariu

“…Using the sum invariance property of Benford random variables, we prove that an n-digit Benford variable converges to a Benford variable as n approaches infinity.…”
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A thirty-year prospective study of children in residential care in the 1970s by Howard Meltzer, Daniel Guinea-Martin, Bryce Millard, Louisa Blackwell

“…In this paper, we examine the 30-year outcomes of a random one percent sample of children residing in care homes in 1971 in a prospective study based on linked census and vital event data (deaths and live births) and we compare these outcomes with children not in care at that time.…”

A feature selection and scoring scheme for dimensionality reduction in a machine learning task by PHILEMON UTEN EMMOH, christopher ifeanyi Eke, Timothy Moses

“…The experimental results of the proposed technique on lung cancer dataset shows that logistic regression, decision tree, adaboost, gradient boost and random forest produced a predictive accuracy of 0.919%, 0.935%, 0.919%, 0.935% and 0.935% respectively, and that of happiness classification dataset produced a predictive accuracy of 0.758%, 0.689%, 0.724%, 0.655% and 0.689% on random forest, k-nearest neighbor, decision tree, gradient boost and cat boost respectively, which outperformed the existing techniques. …”
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Monitoring Cortical and Neuromuscular Activity: Six-month Insights into Knee Joint Position Sense Following ACL Reconstruction by Aglaja Busch, Lorena R. R. Gianotti, Frank Mayer, Heiner Baur

“…Linear mixed models were performed with group (ACL or controls), the measurement time point, and respective limb as fixed effect and each grouping per subject combination as random effect with random intercept. # Results Significantly higher beta-2 power over the frontal region of interest was observed at the first measurement time point in the non-involved limb of the ACL group in comparison to the control group (p = 0.03). …”
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Analysis of the structural reliability of communication networks supporting protective switching mechanisms for one protected section and one backup section by K. А. Batenkov, A. B. Fokin

“…The following methods are used: theory of random graphs, matrices, probabilities and computer modeling.Results. …”
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Prediction of aerodynamic coefficients for twisting shapes of buildings and structures based on machine learning and CFD-modelling by S. G. Saiyan, V. B. Shelepina

“…The best-performing machine learning model (random forest) was verified by comparing it to the results of numerical modelling.Conclusions. …”
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The Efficacy and Treatment Fidelity of Kinesiology Taping in Conjunction With Conservative Treatment Interventions Among Individuals With Shoulder Pain: A Systematic Review with M... by Paul A Salamh, Christopher S Cory, William J Hanney, Haley E Condon, Xinliang Liu, Morey J Kolber

“…Overall effect size (pooled random effects) was estimated for studies with acceptable clinical homogeneity…”
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Self-adaptive bare-bones differential evolution based on bi-mutation strategy by Hui-yu LIU, Ji-hong HAN, Lin YUAN, Bo YU

“…Bare-bones differentia1 evo1ution（BBDE）can e1egant1y so1ve the se1ection prob1em of contro1 parameters and mutation strategy in differentia1 evo1ution（DE）.MGBDE is a c1assica1 BBDE based on bi-mutation strategy.However，it random1y assigns a mutation strategy to each individua1，not considering their differences during evo1ution process，meanwhi1e it may suffer from premature convergence.To overcome these drawbacks，a modified a1gorithm based on MGBDE was proposed.A mutation strategy choice factor that guided the individua1 to choose a preferab1e mutation strategy at each mutation operation was introduced，avoiding the evo1ution b1indness brought by the random se1ection of mutation strategy.To retain the a1most parameter-free characteristic of bare-bones a1gorithm，the tuning of choice factor to be adapted was invo1ved in the individua1 evo1ution，inspired by the concept of se1f-adaptive DE.The a1gorithm a1so inc1uded a we11-designed stagnation perturbation mechanism to reduce the risk of trapping into the 1oca1 optima1.Experimenta1 resu1ts on 18 benchmark functions show that the proposed a1gorithm genera11y achieves better performance than state-of-the-art BBDE variants and severa1 we11-known DE a1gorithms in terms of convergence and robustness.…”
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Pregnant Women with Type 2 Diabetes Mellitus and Hypertension: A Physiological Overview by Muhsin Hmeadi Ubeid

“…High significance correlation exists between HTN and random blood glucose levels.…”
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Association between Atrial Fibrillation and Risk of Alzheimer’s Disease and Vascular Dementia: A Systematic Review and Meta-analysis by Yi Zheng, Guangping Li

“…Similarly, a significant association was found between AF and an increased risk of VaD, using a random effects model (OR/RR: 1.80, 95% CI: 1.57–2.07, I2 = 82.1%, P < 0.001). …”
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Machine learning prediction of combat basic training injury from 3D body shape images. by Steven Morse, Kevin Talty, Patrick Kuiper, Michael Scioletti, Steven B Heymsfield, Richard L Atkinson, Diana M Thomas

“…Predictions were made using logistic regression, random forest, and artificial neural network (ANN) models. …”
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Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages by Sijin Lee, Hyun Ji Park, Jumi Hwang, Sung Woo Lee, Kap Su Han, Won Young Kim, Jinwoo Jeong, Hyunggoo Kang, Armi Kim, Chulung Lee, Su Jin Kim

“…This study aims to develop ML-based models for predicting critical illness in the community, paramedic, and hospital stages using Korean National Emergency Department Information System (NEDIS) data. Random forest and light gradient boosting machine (LightGBM) were applied to develop predictive models. …”
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Predicting the hub interactome of COVID-19 and oral squamous cell carcinoma: uncovering ALDH-mediated Wnt/β-catenin pathway activation via salivary inflammatory proteins by Pradeep Kumar Yadalam, Deepavalli Arumuganainar, Prabhu Manickam Natarajan, Carlos M. Ardila

“…The random forest model achieved the highest accuracy (93%) and class accuracy (84%). …”
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A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement by Xiaomeng Shi, Zhirui Ye, Nirajan Shiwakoti, Offer Grembek

“…Further, considering the hierarchy of movement complexity, we decomposed the externally governed movements of pedestrian traffic into several unique movement patterns including straight line, turning, egress and ingress, opposing, weaving, merging, diverging, and random flows. Analysis of the literature showed that empirical data were highly rich in straight line and egress flow while medium rich in turning, merging, weaving, and opposing flows, but poor in ingress, diverging, and random flows. …”
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