Article
Mathematical & Computational Biology
Hongxiang Qiu, Andrea J. Cook, Jennifer F. Bobb
Summary: Generalized linear mixed models (GLMM) are widely used for analyzing clustered data, but standard statistical tests may have elevated type I error rates when the number of clusters is small to moderate. It remains unknown which tests are appropriate for count outcomes or covariate-adjusted models.
STATISTICS IN MEDICINE
(2023)
Article
Nutrition & Dietetics
Nick Birk, Mika Matsuzaki, Teresa T. Fung, Yanping Li, Carolina Batis, Meir J. Stampfer, Megan Deitchler, Walter C. Willett, Wafaie W. Fawzi, Sabri Bromage, Sanjay Kinra, Shilpa N. Bhupathiraju, Erin Lake
Summary: The study developed a predictive tool using machine learning and statistical methods to screen for prediabetes. Results showed that GLMM, GLM, LASSO, and random forest models performed well, with the fully adjusted GLMM achieving slightly superior results in cluster-correlated data.
JOURNAL OF NUTRITION
(2021)
Article
Mathematical & Computational Biology
Rakesh Kumar Saroj, Pawan Kumar Yadav, Rajneesh Singh, Obvious N. Chilyabanyama
Summary: This study used machine learning models and multivariate logistic regression to predict under-five mortality and identify important factors. The results showed that the neural network model was the best predictive model, with an accuracy of 95.29% to 95.96%, recall of 71.51% to 81.03%, precision of 36.64% to 51.83%, F1 score of 50.46% to 62.68%, Cohen's Kappa value of 0.48 to 0.60, AUROC range of 93.51% to 96.22%, and precision-recall curve range of 99.52% to 99.73%. Additionally, logistic regression also performed well in predicting under-five mortality, with an accuracy of 94% to 95%, AUROC range of 93.4% to 94.8%, and precision-recall curve range of 99.5% to 99.6%. Important factors influencing under-five mortality included the number of living children, survival time, wealth index, child size at birth, birth in the last five years, the total number of children ever born, mother's education level, and birth order.
Article
Multidisciplinary Sciences
Hyeon-Kyoung Koo, Jinsoo Min, Hyung Woo Kim, Yousang Ko, Jee Youn Oh, Yun-Jeong Jeong, Hyeon Hui Kang, Ji Young Kang, Sung-Soon Lee, Minseok Seo, Edwin K. Silverman, Ju Sang Kim, Jae Seuk Park
Summary: This study identified five phenotypes of pulmonary tuberculosis through cluster analysis and compared their initial symptomatic, microbiological and radiographic characteristics. This helps to better understand and diagnose pulmonary tuberculosis.
SCIENTIFIC REPORTS
(2022)
Article
Pediatrics
Obvious Nchimunya Chilyabanyama, Roma Chilengi, Michelo Simuyandi, Caroline C. Chisenga, Masuzyo Chirwa, Kalongo Hamusonde, Rakesh Kumar Saroj, Najeeha Talat Iqbal, Innocent Ngaruye, Samuel Bosomprah
Summary: This study used machine learning algorithms to predict stunting among children under the age of five in Zambia, and found that calibrating predicted probabilities improved the performance of the models, with random forest algorithm performing the best.
Article
Ecology
Alena Foerster, Christophe David, Benjamin Dumont, Linda-Maria Dimitrova Martensson, Frank Rasche, Christoph Emmerling
Summary: This study analyzed the impact of annual crops and perennial intermediate wheatgrass on earthworm communities and diversity from Southern to Northern Europe. The results showed that earthworms were more abundant, had higher biomass, and greater diversity under perennial wheat, following a South to North gradient.
EUROPEAN JOURNAL OF SOIL BIOLOGY
(2023)
Article
Agricultural Engineering
Elaissi Ameur, Moumni Essahli Sarra, Khtatfa Takoua, Kouja Mariem, Abid Nabil, Frederic Lynen, Khouja Mohamed Larbi
Summary: This study investigated the chemical composition and antibacterial activity of Pinus essential oils from five Tunisian species, finding that blends of oils extracted from certain species showed the highest antibacterial activity. These oil blends may serve as promising alternatives for the treatment of otitis media.
INDUSTRIAL CROPS AND PRODUCTS
(2022)
Article
Physics, Mathematical
Antonio Blanca, Reza Gheissari
Summary: The study proves rapid mixing of the random-cluster Glauber dynamics on random Delta-regular graphs for all q >= 1 and p = 2, but undergoes an exponential slowdown at a certain threshold. By analyzing sharp bounds on the shattering time, it demonstrates the tree uniqueness region under certain conditions.
COMMUNICATIONS IN MATHEMATICAL PHYSICS
(2021)
Article
Mathematics, Applied
Rui-Ray Zhang
Summary: This paper studies the probability of linearity of random hypergraphs, provides more precise asymptotics through cluster expansion, and improves existing results when r = 3 and p = o(n(-7/5)).
ADVANCES IN APPLIED MATHEMATICS
(2022)
Article
Physics, Mathematical
Hugo Duminil-Copin, Christophe Garban, Vincent Tassion
Summary: In this paper, we investigate the behavior of statistical physics models on a book with pages that are isomorphic to half-planes. We prove that even for models undergoing a continuous phase transition on Z(2), the phase transition becomes discontinuous as soon as the number of pages is sufficiently large. Our work confirms predictions in theoretical physics and provides further evidence for the analysis of certain quantum spin systems.
COMMUNICATIONS IN MATHEMATICAL PHYSICS
(2023)
Article
Construction & Building Technology
Shuqin Chen, Yinyan Lv, Zhichao Wang, Yuhang Ma, Yurui Huang, Yichao Wang, Yuxuan Cai, Zhiqin Rao
Summary: This study collects real-time occupancy data and develops a Monte Carlo-based model to simulate and compare the building heating and cooling load differences caused by fixed occupancy schedules and random occupancy time series. The results show that using random occupancy schedules can accurately predict and assess the building loads.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Mathematics
Luiz Paulo Favero, Joseph E. Hair, Rafael de Freitas Souza, Matheus Albergaria, Talles Brugni
Summary: The article introduces a less commonly used mathematical analytical method in social sciences - mixed modeling. By extending the application of mixed models in a corruption database, the results demonstrate the importance of considering zero inflation and country-level random effects.
Article
Engineering, Industrial
Fen Li, Zhenzhou Lu, Kaixuan Feng
Summary: An improved chance index (ICI) is proposed to quantify the safety degree of structures with twofold random uncertainty, taking into account bilateral information of statistical distribution of failure probability function. The ICI utilizes the average of upper and lower bilateral fractiles of the failure probability function as the index.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Environmental
Wenli Liu, Yexin He, Zihan Liu, Hanbin Luo, Tianxiang Liu
Summary: This paper proposes a framework of global sensitivity analysis (GSA) to identify the most sensitive indicators for sewer deposit prediction. By developing a data-driven bilevel model and employing three different GSA methods, the study identifies the likelihood of combined sewer overflow occurrences (LCSOO), pipe age (PA), and pipe material (PM) as influential parameters for deposit thickness.
Article
Materials Science, Multidisciplinary
Yifan Chen, Biyang Sheng, Shijie Xie, Rihong Cao, Yixian Wang, Yanlin Zhao, Hang Lin
Summary: This paper investigates fracture propagation and scale effect in random fractured rock samples under compression-shear condition. The samples are produced with rock-like materials, and the mechanical responses are studied by controlling the compression-shear angle. The strain field evolution is analyzed using digital image processing technology, and the influence of compression-shear angle on failure mode is revealed.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2023)
Article
Computer Science, Interdisciplinary Applications
Denis Ndanguza, Isambi S. Mbalawata, Heikki Haario, Jean M. Tchuenche
MATHEMATICS AND COMPUTERS IN SIMULATION
(2017)
Article
Public, Environmental & Occupational Health
Kenji Takehara, Togoobaatar Ganchimeg, Akihito Kikuchi, Lkagvasuren Gundegmaa, Lkagvasuren Altantsetseg, Ai Aoki, Takemune Fukuie, Kazuya Suwabe, Shagdar Bat-Erdene, Masashi Mikami, Rintaro Mori, Hideaki Soya
Article
Public, Environmental & Occupational Health
Kasahun Takele, Temesgen Zewotir, Denis Ndanguza
Article
Pediatrics
Kasahun Takele, Temesgen Zewotir, Denis Ndanguza
Article
Engineering, Multidisciplinary
Denis Ndanguza, Angelique Nyirahabinshuti, Consolee Sibosiko
ALEXANDRIA ENGINEERING JOURNAL
(2020)
Article
Multidisciplinary Sciences
Kasahun Takele, Temesgen Zewotir, Denis Ndanguza
Summary: This study aims to investigate the correlation and coexistence of child malnutrition and morbidity in Ethiopia. The findings indicate that children born to well-nourished mothers, from middle to high-income households, and with higher levels of maternal education are less affected by malnutrition and illness. Breastfeeding and appropriate birth spacing also indirectly impact child morbidity.
SCIENTIFIC REPORTS
(2023)
Article
Meteorology & Atmospheric Sciences
Danny Parsons, David Stern, Denis Ndanguza, Mouhamadou Bamba Sylla
Summary: The study assesses the performance of CHIRTS-daily dataset in Africa and finds that it outperforms ERA5 and ERA5-Land in estimating daily, annual mean, and annual extreme maximum temperatures. Although there are biases in the estimation of minimum temperatures, they could potentially be corrected.
Article
Remote Sensing
Aboma Temesgen Sebu, Kasahun Takele Genati, Daniel Biftu Bekalo, Teshome Kebede Deressa
SPATIAL INFORMATION RESEARCH
(2020)
Article
Mathematics
D. Ndanguza, J. M. Tchuenche, H. Haario