Marine sentinels using eDNA to track Physalia sp. in the Gulf of Thailand. by Thanaporn Suebsuya, Panagiotis Madesis, Chatmongkon Suwannapoom, Maslin Osathanunkul

“…Traditional survey methods such as trawling and netting are time-consuming, potentially disruptive to marine ecosystems, and often lack the precision needed for effective monitoring. …”
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Genetic diversity and population structure of 288 potato (Solanum tuberosum L.) germplasms revealed by SSR and AFLP markers by Jian WANG, Lu HOU, Ruo-yu WANG, Miao-miao HE, Qing-chang LIU

“…In general, the results obtained from Bayesian statistical analysis, cluster analysis and principal coordinate analysis consistently revealed the lack of geographical differentiation among country-wide collections, indicating germplasm introduction was common for the countries out of potato origin center. …”
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Metagenomic source tracking after microbiota transplant therapy by Susan L. Hoops, Daphne Moutsoglou, Byron P. Vaughn, Alexander Khoruts, Dan Knights

“…Recent methods for measuring donor engraftment use whole-genome sequencing and reference databases or metagenome-assembled genomes (MAGs) to track individual bacterial strains but lack the ability to disambiguate DNA that matches both donor and patient microbiota. …”
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Poor oral health is associated with social vulnerability in critically ill trauma patients by Lillian S Kao, Charles E Wade, Erin E Fox, Gabrielle E Hatton, Mokunfayo O Fajemisin, Stephanie Martinez Ugarte, Chelsea J Guy-Frank, Kayli A Quinton, Sophia Syed, Kimberly A Mankiewicz

“…Social factors associated with poor oral health from Bayesian analysis (PP OR>1) included lack of social support (99%), housing instability (99%), divorced marital status (87%), and non-English primary language (86%). …”
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Embedding a Choice Experiment in an Online Decision Aid or Tool: Scoping Review by Nyantara Wickramasekera, Phil Shackley, Donna Rowen

“…Four proof-of-concept embedding methods were identified: scenario analysis, known preference phenotypes, Bayesian collaborative filtering, and penalized multinomial logit model. …”
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Uncertainty-aware traction force microscopy. by Adithan Kandasamy, Yi-Ting Yeh, Ricardo Serrano, Mark Mercola, Juan C Del Alamo

“…This information is passed on to a hierarchical Bayesian TFM framework with spatially adaptive regularization that propagates the uncertainty to the traction stress readouts (TFM-UQ). …”
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Association of urine parabens with liver function in US adolescents based on NHANES 2007–2016 by Linfei Li, Gunchu Hu, Xiong Luo, Zuxing Wei, Jun He

“…Then, we applied the weighted quantile sum (WQS) analysis and the Bayesian kernel machine regression (BKMR) to examine the associations between parabens and liver function indicators. …”
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A comparison between general linear regression and quantitative robust regression (data for kidney patients as an example) by أسامة عبد العزيز كاظم القريشي, سما سعدي علي الهاشمي

“…The research problem was the presence of outliers in the data of the dependent variable and this leads to the inefficiency of the linear regression model estimated using general linear regression due to the failure to meet the conditions for using Ordinary least squares method (OLS), and thus a lack of confidence in its estimated and predictive accuracy, The aim of the research is to use quantitative robust regression on a sample divided into three quartiles (0.25, 0.50, 0.75) represented by (74) male kidney patients in Al-Kadhimiya Hospital for the period (1/2024-3/2024) and compare it with general linear regression and choose the best model using Comparison standards (Hannan & Quinn, Schwartz Bayesian, Akaike Information), to determine the extent of the effect of independent variables (Diabetes, Hypertension, triglycerides, age) on the increase in blood urea, and the researcher reached the advantage of quantitative robust regression (first quartile and second quartile) compared to general linear regression, While general linear regression appeared better than quantitative robust regression (third quartile), All independent variables have a significant effect on the increase in blood urea levels in all three models. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Furthermore, the predictive models typically lack interpretability. To address these issues, this study proposes a hybrid prediction model for the residual strength of defective pipelines based on Bayesian optimization (BO) and eXtreme Gradient Boosting (XGBoost). …”
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Phase Diagram of Extensive-Rank Symmetric Matrix Denoising beyond Rotational Invariance by Jean Barbier, Francesco Camilli, Justin Ko, Koki Okajima

“…In this paper, we make progress toward the understanding of Bayesian matrix denoising when the hidden signal is a factored matrix XX^{⊺} that is not rotationally invariant. …”
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Knowledge-based and Expert Systems in Prognostics and Health Management: a Survey by Kalil Bouhadra, Florent Forest

“…One major issue is that data-driven methods often lack transparency in their reasoning, which is crucial for understanding fault occurrences and diagnostics. …”
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Primates decline rapidly in unprotected forests: evidence from a monitoring program with data constraints. by Francesco Rovero, Arafat Mtui, Amani Kitegile, Philipo Jacob, Alessandro Araldi, Simone Tenan

“…Yet monitoring schemes in these countries often suffer from logistic constraints and/or poor rigor in data collection, and a lack of consideration of sources of bias in analysis. …”
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Bridging language gaps: The role of NLP and speech recognition in oral english instruction by Parul Dubey, Pushkar Dubey, Rohit Raja, Sapna Singh Kshatri

“…These technologies facilitate personalized and adaptive learning, making pronunciation and fluency improvement more efficient. Traditional methods lack real-time speech assessment and individualized feedback, limiting learners' progress. …”
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Practical and effective diagnosis of animal anthrax in endemic low-resource settings. by Olubunmi R Aminu, Tiziana Lembo, Ruth N Zadoks, Roman Biek, Suzanna Lewis, Ireen Kiwelu, Blandina T Mmbaga, Deogratius Mshanga, Gabriel Shirima, Matt Denwood, Taya L Forde

“…Field-prepared blood smears (n = 152) were tested by microscopy using four staining techniques as well as polymerase chain reaction (PCR) followed by Bayesian latent class analysis. Median sensitivity (91%, CI 95% [84-96%]) and specificity (99%, CI 95% [96-100%]) of microscopy using azure B were comparable to those of the recommended standard, polychrome methylene blue, PMB (92%, CI 95% [84-97%] and 98%, CI 95% [95-100%], respectively), but azure B is more available and convenient. …”
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Factors Influencing the Severity of Urinary and Defecatory Dysfunction Among the Middle-Aged and Older Adult Chinese Population: Longitudinal Study of a 5-Wave Survey Cohort by Haoran Zhu, Xiaoming Li, Liwei Jing, Jingli Kou, Lichao Gong, Rui Wang, Guangtian Liu, Chao Zhang, Jiayi Zhao, Jing Zhang

“…MethodsA longitudinal cohort of over 10,000 participants from the China Health and Retirement Longitudinal Study was analyzed across 5 waves using Bayesian logistic regression. This analysis examined associations between UDD severity and factors including demographic, lifestyle, and health-related factors, including comorbidities, BMI, and handgrip strength. …”
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Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006-2009. by Victor A Alegana, Jim A Wright, Sami M Nahzat, Waqar Butt, Amad W Sediqi, Naeem Habib, Robert W Snow, Peter M Atkinson, Abdisalan M Noor

“…<h4>Background</h4>Identifying areas that support high malaria risks and where populations lack access to health care is central to reducing the burden in Afghanistan. …”
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The latency time of SARS-CoV- 2 Delta variant in infection- and vaccine-naive individuals from Vietnam by Vera H. Arntzen, Manh Nguyen Duc, Marta Fiocco, Lan Truong Thi Thanh, Tam Nguyen Hoai Thao, Buu Mai Thanh, Tu-Anh Nguyen, Nhat Le Thanh Hoang, Marc Choisy, Lam Phung Khanh, Nga Le Hong, Ronald B. Geskus

“…Estimates of the SARS-CoV- 2 latency time are sparse due to lack of appropriate and representative data. Infection time is rarely known exactly and exposure information may be subject to several biases. …”
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Adverse events associated with amlodipine: a pharmacovigilance study using the FDA adverse event reporting system by Jiazhen Jiang, Qian Zhong, Xinyu Zhou, Lisi Zhou, Jiyuan Zheng, Bingshuo Liu, Xingwei Di

“…Four risk signal detection methods were employed: Ratio of Odds Ratio, Proportional Reporting Ratio, Bayesian Confidence Propagation Neural Network, and Empirical Bayes Geometric Mean, to conduct a comprehensive analysis of amlodipine-related ADRs. …”
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Allergic-related skin diseases: Global disease burden from 1990 to 2021 and future trends by Xiao Tang, MD, Li Lin, MD, Fangning Yu, MD, Yizhao Ma, MM, Zeyu Liu, MM, Xuying Xu, MD

“…Currently, there is a lack of systematic analysis of allergic-related skin diseases globally. …”
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Multiple lifestyle behaviour mHealth intervention targeting Swedish college and university students: protocol for the Buddy randomised factorial trial by Hanna Henriksson, Pontus Henriksson, Marie Löf, Preben Bendtsen, Marcus Bendtsen, Katarina Åsberg, Oskar Lundgren

“…A Bayesian group sequential design will be employed to periodically make decisions to continue or stop recruitment, with simulations suggesting that between 1500 and 2500 participants will be required. …”
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