10,702 research outputs found

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Phylogeographic investigation of the bladder grasshopper Bullacris unicolor (Orthoptera Pneumoroidea) in South Africa

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    There are several factors, such as genetic drift, gene flow and migration that affect the population genetic structure and phylogeographic distribution of genetic lineages within single species. Previous studies of the bladder grasshoppers, Bullacris unicolor of South Africa, showed divergence in mitochondrial CO1 (cytochrome c oxidase subunit 1) haplotype diversity and significant genetic structure. In this study, we revisit these findings adding more samples from different locations and using mitochondrial CO1 and Internal transcribed spacer (ITS) gene sequences. We tested the hypothesis that the western, northern and eastern distribution ranges of B. unicolor show different population genetic patterns, corresponding with isolation-by-distance. Mitochondrial CO1 and ITS data were collected for 99 individuals from 12 localities across the Western, Northern and Eastern sides of South Africa. Overall, significant variation in genetic structure was found across the localities as indicated by FST analyses

    The Bayesian Regularized Quantile Varying Coefficient Model

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    The quantile varying coefficient (VC) model can flexibly capture dynamical patterns of regression coefficients. In addition, due to the quantile check loss function, it is robust against outliers and heavy-tailed distributions of the response variable, and can provide a more comprehensive picture of modeling via exploring the conditional quantiles of the response variable. Although extensive studies have been conducted to examine variable selection for the high-dimensional quantile varying coefficient models, the Bayesian analysis has been rarely developed. The Bayesian regularized quantile varying coefficient model has been proposed to incorporate robustness against data heterogeneity while accommodating the non-linear interactions between the effect modifier and predictors. Selecting important varying coefficients can be achieved through Bayesian variable selection. Incorporating the multivariate spike-and-slab priors further improves performance by inducing exact sparsity. The Gibbs sampler has been derived to conduct efficient posterior inference of the sparse Bayesian quantile VC model through Markov chain Monte Carlo (MCMC). The merit of the proposed model in selection and estimation accuracy over the alternatives has been systematically investigated in simulation under specific quantile levels and multiple heavy-tailed model errors. In the case study, the proposed model leads to identification of biologically sensible markers in a non-linear gene-environment interaction study using the NHS data

    Insight into the population dynamics of pathogenic bacteria causing grapevine crown gall in snowfall areas: snow cover protects the proliferation of pathogenic bacteria

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    Grapevine crown gall (GCG) is a significant bacterial disease caused by tumorigenic Allorhizobium vitis (TAV) and is prevalent worldwide. TAV infects grapevines through wounds such as freezing injuries. Although grapevines typically avoid being wounded under snow cover, GCG occurs in many commercial vineyards in snowy regions. This study investigated the TAV population in GCG gall tissues, grapevine skins, and snow on grapevine skins from six infected vineyards located in Hokkaido, Japan, an area known for heavy snowfall. TAV was isolated not only from gall tissues but also from skins and snow on skins throughout the year. Hierarchical Bayesian model (HBM) analysis revealed that the number of TAV cells in gall tissues was affected by cultivar and low temperature, while those in skins were affected by location and low temperature. Additionally, Bayesian changepoint detection (BCD) showed that the number of TAV cells in gall and skin tissues increased during winter, including the snowfall season. Furthermore, the TAV population in grapevine skins under the snow was significantly higher than those above the snow, indicating that TAV under the snow is protected by the snow and can survive well during the snowfall season. This study highlights the ability of TAV to overwinter on/in galls and skins under the snow and act as inoculum for the next season

    GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies

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    Phylogenetic inference, grounded in molecular evolution models, is essential for understanding the evolutionary relationships in biological data. Accounting for the uncertainty of phylogenetic tree variables, which include tree topologies and evolutionary distances on branches, is crucial for accurately inferring species relationships from molecular data and tasks requiring variable marginalization. Variational Bayesian methods are key to developing scalable, practical models; however, it remains challenging to conduct phylogenetic inference without restricting the combinatorially vast number of possible tree topologies. In this work, we introduce a novel, fully differentiable formulation of phylogenetic inference that leverages a unique representation of topological distributions in continuous geometric spaces. Through practical considerations on design spaces and control variates for gradient estimations, our approach, GeoPhy, enables variational inference without limiting the topological candidates. In experiments using real benchmark datasets, GeoPhy significantly outperformed other approximate Bayesian methods that considered whole topologies.Comment: 23 pages, 5 figure

    Behavioural ecology of the greater bilby (Macrotis lagotis) and conservation tool development in a semi-wild sanctuary

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    Conservation translocations are becoming an increasingly necessary tool to stem the decline of threatened species globally. The greater bilby (Macrotis lagotis) is a nationally threatened species in Australia. While bilby translocations are expected to contribute to the species’ persistence, the scarcity of information on their behaviour and ecology prevents informed-management. By intensively studying a population of bilbies both prior to, and following reintroduction, and subsequent reinforcements to a fenced sanctuary, I aimed to (1) advance knowledge of bilby behaviour and examine behaviours potentially relevant to fitness (i.e. survival and breeding success), (2) improve ecological knowledge of bilbies within understudied (temperate) climates, and (3) use this knowledge to suggest and develop effective tools for their conservation. Chapter 1 describes the current state of research in applied conservation research, and how increased behavioural data could help address some of the current knowledge gaps for bilby conservation. In Chapter 2, I examined patterns in bilby resource selection, finding that selection changed between seasons and years due to the environmental conditions and resources available. I also found that resource requirements are likely to be behavioural-state dependent and sex-specific. In Chapter 3, I constructed social networks to examine nocturnal proximity of bilbies and concurrent burrow sharing and found that associations were non-random. Expanding on this, in Chapter 4, I found that burrow sharing was likely to help describe breeding strategies, as males strongly avoided other males, and mixed-sex dyads exhibited kin-avoidance when mate choice was more limited. In Chapter 5, I developed a test to screen personality traits in bilbies, finding links between male response to handling and relative breeding success post-release. Lastly, in Chapter 6, I described a method to collect detailed movement data on the bilby, and discussed some of the practical and animal welfare constraints for its application. My thesis provides new insights into the behavioural ecology of the bilby with potential implications for future management of the species. With further translocations necessary for long-term persistence of the bilby, this research is highly relevant to current and future management of this ecologically important species, with potential applications to other similarly at-risk species

    A stratified decision-making model for long-term planning: application in flood risk management in Scotland

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    In a standard decision-making model for a game of chance, the best strategy is chosen based on the current state of the system under various conditions. There is however a shortcoming of this standard model, in that it can be applicable only for short-term decision-making periods. This is primarily due to not evaluating the dynamic characteristics and changes in status of the system and the outcomes of nature towards an a priori target or ideal state, which can occur in longer periods. Thus, in this study, a decision-making model based on the concept of stratification (CST), game theory and shared socio-economic pathway (SSP) is developed and its applicability to disaster management is shown. The game of chance and CST have been integrated to incorporate the dynamic nature of the decision environment for long-term disaster risk planning, while accounting for various states of the system and an ideal state. Furthermore, an interactive web application with dynamic user interface is built based on the proposed model to enable decision makers to identify the best choices in their model by a predictive approach. The Monte Carlo simulation is applied to experimentally validate the proposed model. Then, it is demonstrated how this methodology can suitably be applied to obtain ad hoc models, solutions, and analysis in the strategic decision-making process of flooding risk strategy evaluation. The model's applicability is shown in an uncertain real-world decision-making context, considering dynamic nature of socio-economic situations and flooding hazards in the Highland and Argyll Local Plan District in Scotland. The empirical results show that flood forecasting and awareness raising are the two most beneficial mitigation strategies in the region followed by emergency plans/response, planning policies, maintenance, and self help

    Advances in Methane Production from Coal, Shale and Other Tight Rocks

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    This collection reports on the state of the art in fundamental discipline application in hydrocarbon production and associated challenges in geoengineering activities. Zheng et al. (2022) report an NMR-based method for multiphase methane characterization in coals. Wang et al. (2022) studied the genesis of bedding fractures in Ordovician to Silurian marine shale in the Sichuan basin. Kang et al. (2022) proposed research focusing on the prediction of shale gas production from horizontal wells. Liang et al. (2022) studied the pore structure of marine shale by adsorption method in terms of molecular interaction. Zhang et al. (2022) focus on the coal measures sandstones in the Xishanyao Formation, southern Junggar Basin, and the sandstone diagenetic characteristics are fully revealed. Yao et al. (2022) report the source-to-sink system in the Ledong submarine channel and the Dongfang submarine fan in the Yinggehai Basin, South China Sea. There are four papers focusing on the technologies associated with hydrocarbon productions. Wang et al. (2022) reported the analysis of pre-stack inversion in a carbonate karst reservoir. Chen et al. (2022) conducted an inversion study on the parameters of cascade coexisting gas-bearing reservoirs in coal measures in Huainan. To ensure the safety CCS, Zhang et al (2022) report their analysis of available conditions for InSAR surface deformation monitoring. Additionally, to ensure production safety in coal mines, Zhang et al. (2022) report the properties and application of gel materials for coal gangue control
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