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Bayesiantheory, etc ; data analysis; regression analysis; shrinkage; Show all 4 Subjects
Abstract:
... Multiple Bayesian approaches have been explored for variable selection in the multinomial regression framework. While there are a number of studies considering variable selection in the regression paradigm with a numerical response, the research is limited for a categorical response variable. The proposed approach develops a method for leveraging the features of the global-local shrinkage framewor ...
Bayesiantheory, etc ; Internet; apples; cultivars; decision support systems; diagnostic techniques; fruits; streams; Show all 8 Subjects
Abstract:
... Post-harvest diseases of apple can cause considerable economic losses. Thus, we developed DSSApple, an interactive web-based decision support system, that helps users to diagnose post-harvest diseases of domesticated apple based on observed macroscopic symptoms on fruit. Specifically, DSSApple is designed as a two-stream hybrid diagnostic tool, that can be effectively used by both expert and non-e ...
Bayesiantheory, etc ; agricultural management; agronomy; climate; model uncertainty; phenology; prediction; rice; simulation models; Show all 9 Subjects
Abstract:
... Crop simulation models play an increasingly important role in agricultural management. Therefore, improving crop models’ accuracy and reliability has become a key issue. Previous studies have shown that multi-model ensembles (MMEs) perform better than individual models and are capable of assessing model uncertainty. Here, we study the use of the Bayesian model averaging (BMA) method to improve the ...
Bayesiantheory, etc ; data collection; electroencephalography; models; spectral analysis; time series analysis; wind speed; California; Show all 8 Subjects
Abstract:
... Spectral analysis discovers trends, periodic and other characteristics of a time series by representing these features in the frequency domain. However, when multivariate time series are considered, and the number of components increases, the size of the spectral density matrix grows quadratically, making estimation and inference rather challenging. The proposed novel Bayesian framework considers ...
Bayesiantheory, etc ; cheesemaking; cheeses; dairy goats; farms; food chemistry; goat milk; milk; prediction; spectroscopy; Show all 10 Subjects
Abstract:
... The objectives of this study were to explore the use of Fourier-transform infrared (FITR) spectroscopy on 458 goat milk samples for predicting cheese-making traits, and to test the effect of the farm variability on their prediction accuracy. Calibration equations were developed using a Bayesian approach with three different scenarios: i) a random cross-validation (CV) [80% calibration (CAL); 20% v ...
Bayesiantheory, etc ; Weibull statistics; chlorogenic acid; color; cumulative distribution; cysteine; decolorization; glutathione; models; pH; thiols; Show all 11 Subjects
Abstract:
... Thiols (cysteine and glutathione) were explored as potential decolorization agents to mitigate green pigment formation in chlorogenic acid quinone-lysine solutions. Reparameterizations of the Weibull cumulative distribution function were applied to describe the time-dependence of greening under varying pH conditions. Repeated fitting of 3-parameter models (RMSE = 0.0111, CVRMSE = 1.55%) indicated ...
Bayesiantheory, etc ; case studies; data collection; ecosystems; environment; freshwater; lakes; models; phosphorus; poisonous algae; spring; uncertainty; Lake Erie; Show all 13 Subjects
Abstract:
... Ecological models help provide forecasts of ecosystem responses to natural and anthropogenic stresses. However, their ability to create reliable predictions requires forecasts with track records sufficiently long to build confidence, skill assessments, and treating uncertainty quantitatively. We use Lake Erie harmful algal blooms as a case study to help formalize ecological forecasting. Key challe ...
Bayesiantheory, etc ; childhood; data analysis; insulin resistance; lymphocytic leukemia; models; obesity; radiotherapy; regression analysis; relative risk; sample size; Show all 11 Subjects
Abstract:
... Mediation analysis with a binary outcome is notoriously more challenging than with a continuous outcome. A new Bayesian approach for performing causal mediation with a binary outcome and a binary mediator, named the t-link approach, is introduced. This approach relies on the Bayesian multivariate logistic regression model introduced by O'Brien and Dunson (2004) and its Student-t approximation. By ...
... Few studies have investigated the adverse effects of preconception phthalate (PAE) exposure on birth weight in couples receiving assisted reproductive technology (ART) compared to naturally conceived newborns. We examined the association between parental preconception/prenatal urinary phthalate exposure and low birth weight (LBW) risk in couples who conceived using ART or naturally. From the Jiang ...
Bayesiantheory, etc ; air; air pollutants; air pollution; biomarkers; blood lipids; blood pressure; coagulation; environment; enzymes; high density lipoprotein cholesterol; homeostasis; inflammation; lipogenesis; metabolomics; triacylglycerols; Show all 16 Subjects
Abstract:
... The cardiometabolic effects of air pollution in the context of mixtures and the underlying mechanisms remain not fully understood. This study aims to investigate the joint effect of air pollutant mixtures on a broad range of cardiometabolic parameters, examine the susceptibility of obese individuals, and determine the role of circulating fatty acids. In this panel study, metabolically healthy norm ...
Bayesiantheory, etc ; Lutjanus argentimaculatus; aquaculture; cluster analysis; gene flow; genetic resources; genetic structure; genetic variation; marine fish; microsatellite repeats; multidimensional scaling; Arabian Sea; Bay of Bengal; Show all 13 Subjects
Abstract:
... The mangrove red snapper, Lutjanus argentimaculatus, is a marine fish of key economic and cultural importance in the Indo-Pacific region. It is now considered much more of an important aquaculture species than capture fisheries. The present study aimed to reveal the genetic structure of this candidate species from the Arabian Sea and Bay of Bengal using microsatellite markers. Twelve microsatellit ...
... Evidence from in vitro and rodent studies suggests that organophosphate esters (OPEs) may disrupt sex steroid hormone homeostasis, but no human studies, to date, have examined the effects of in utero exposure to OPEs on offspring reproductive development. Anogenital distance (AGD) is a sensitive biomarker of fetal hormonal milieu and has been used to assess reproductive toxicity. We evaluated the ...
... Even though the monophyletic status of Achiridae has been supported by morphological and molecular data, the interrelationships within the representatives of this family are poorly resolved. In the present study, we carried out the most complete molecular phylogenetic analysis of this group, encompassing all genera and employing both nuclear (Rhodopsin, Recombination activator [Rag 1], Mixed – lin ...
... To assess the source characteristics of coastal aerosols and evaluate the contribution of atmospheric deposition to particulate organic matter in surface seawater, total suspended particulates (TSP) were collected at a shore-based site on the south coast of North Yellow Sea from December 2019 through November 2020. The samples were analyzed for total organic carbon (TOC) and nitrogen (TN) as well ...
... Bayesian network is a powerful algorithm to diagnose the faults in building energy systems based on incomplete and uncertain diagnostic information. In practice, it is very challenging to construct Bayesian networks for large-scale and complex systems. Inspired by the object oriented programming technology, a hierarchical object oriented Bayesian network-based method is proposed in this study. Its ...
... Predicting countries’ energy consumption and pollution levels precisely from socioeconomic drivers will be essential to support sustainable policy-making in an effective manner. Current predictive models, like the widely used STIRPAT equation, are based on rigid mathematical expressions that assume constant elasticities. Using a Bayesian approach to symbolic regression, here we explore a vast amou ...
... Agent-based models (ABMs) are an increasingly popular choice for simulating large systems of interacting components, and have been applied across a wide variety of natural and environmental systems. However, ABMs can be incredibly disparate and often opaque in their formulation, implementation, and analysis. This can impede critical assessment and re-implementation, and jeopardize the reproducibil ...
... The present study investigates the environmental benefits of phasing-in autonomous ships in global maritime transportation along major dry bulk and tanker routes using Bayesian probabilistic forecasting algorithm. The focus is on the simulations and calibrations on the navigational behavior of autonomous ships at both port and high-sea, as well as the potential emission abatement of atmospheric po ...
Bayesiantheory, etc ; phylogeny; phylogeography; Bulgaria; Show all 4 Subjects
Abstract:
... HIV-1 subtype C is the most abundant strain of HIV-1 infections worldwide and was found in the first known patients diagnosed with HIV/AIDS in Bulgaria in 1986. However, there is limited information on the molecular-epidemiological characteristics of this strain in the epidemic of the country. In this study, we analyze the evolutionary history of the introduction and dissemination of HIV-1 subtype ...
... Gaussian processes (GPs) are common components in Bayesian non‐parametric models having a rich methodological literature and strong theoretical grounding. The use of exact GPs in Bayesian models is limited to problems containing several thousand observations due to their prohibitive computational demands. We develop a posterior sampling algorithm using H‐matrix approximations that scales at O(nlog ...