5,297 research outputs found

    PLACING THE EVOLUTIONARY HISTORY OF \u3ci\u3eDESMOGNATHUS\u3c/i\u3e SALAMANDERS IN CONTEXT: A PHYLOGEOGRAPHIC APPROACH

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    Patterns of genetic variation do not arise in a vacuum but are instead shaped by the interplay between evolutionary forces and ecological constraints. Here, I use a phylogeographic approach to examine the role that ecology played in lineage divergence in the Desmognathus quadramaculatus species complex (Family: Plethodontidae), which consists of three nominal species: D. quadramaculatus, D. marmoratus, and D. folkertsi. Previous phylogenetic studies have shown that individuals from these species do not form clades based on phenotype. My approach to reconciling phylogenetic discordance was two-fold, using (1) genome-wide markers to provide insight into the relationships among lineages and (2) geographic and climate data to provide context for patterns of genetic diversity. First, I obtained genome-wide nuclear markers using double-digest restriction-site associated DNA sequencing (ddRAD) to examine whether two morphologically divergent species, D. marmoratus and D. quadramaculatus, represent independently evolving lineages. Phylogenetic, population structure, and model testing analyses all confirmed that D. marmoratus and D. quadramaculatus do not group based on phenotype. Instead, I found that there were two cryptic genetic lineages (Nantahala and Pisgah) that each contained both phenotypes. Additionally, ecological niche modeling showed that the two genetic lineages primarily occupy geographic areas with significantly different climates, suggesting that climate may have played a role in divergence. Next, I assembled loci from publicly available sequencing data using a draft transcriptome of Desmognathus fuscus as a reference to assess the three nominal species in the quadramaculatus species complex across their entire range. I used phylogenetic and population structure analyses, alongside haplowebs and conspecificity matrices, to determine if the loci supported the hypothesis that the phenotypes represent multiple independently evolving lineages within the broader genetic clades found in the previous chapter. I found that the loci were not informative enough to determine whether the phenotypes had a genetic basis in Pisgah, but did support genetic divergence between phenotypes in Nantahala. Finally, I used ecological niche models (ENMs) and resistance modeling to place the genetic results and phenotypic diversity within the context of time and space. I found that though the quadramaculatus and marmoratus phenotypes were nearly indistinguishable in niche space in the present day, they were projected to occupy different geographic areas in the past and future. The southern portion of the study area had areas of high habitat suitability from the Last Glacial Maximum (~22 kya) to the present, which aligns with the higher genetic divergence between groups in Nantahala. Anthropogenic land use changes reduced habitat availability but likely did not drive genetic divergence in the past, and may be of more consequence to genetic diversity than climate change over the next 50 years. Like many taxa that underwent adaptive radiations, the evolutionary history of Desmognathus has been obfuscated by high rates of within-species phenotypic diversity and shared morphology between distantly related lineages. My findings emphasize the importance of interrogating complex patterns of genetic variation within the context of the dynamic, heterogeneous landscapes in which they arise

    Self-efficacy Facilitated Sleep, Physical Activity, Towards Regulating BMI of Permanent 12-hour shift Registered Nurses

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    Shift workers with obesity-related comorbidities have reduced health and lifespan. Registered nurses (RNs) are ranked fifth among the most obese professionals in the United States, according to recent studies. Researchers have not examined the relationship between self-efficacy, physical activity, sleep, and 12-hour night shift RNs despite demonstrating that self-efficacy inspires confident health habits in the general population. For this quantitative study, the social cognitive theory was applied to study the interrelationships among the independent variables, sleep self-efficacy, self-efficacy for physical activity, and body mass index (BMI), with multiple dependent demographic variables, quality and quantity of sleep, and the level and quantity of exercise. How much does BMI affect the connection between sleep self-efficacy and the amount and quality of sleep for RNs who work 12-hour shifts? Additionally, can sleep self-efficacy and the shift worked predict the amount and quality of sleep, and can self-efficacy for physical activity and shift worked predict participation in physical activity among RNs? Using a cross-sectional, correlational design, a survey generated valid responses from 266 largely African American RNs. Regression results showed that self-efficacy alone does not ensure compliance with health regimens within this population. Significant negative relationships were discovered between sleep self-efficacy and quality of sleep, exercise self-efficacy and exercise adherence, and exercise self-efficacy and BMI. The insights gained from this investigation can help individuals and organizations promote healthy habits among night shift nurses

    Short-term forecast techniques for energy management systems in microgrid applications

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    A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Doctor of Philosophy in Sustainable Energy Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyIn the 2015 Paris Agreement, 195 countries adopted a global climate agreement to limit the global average temperature rise to less than 2°C. Achieving the set targets involves increasing energy efficiency and embracing cleaner energy solutions. Although advances in computing and Internet of Things (IoT) technologies have been made, there is limited scientific research work in this arena that tackles the challenges of implementing low-cost IoT-based Energy Management System (EMS) with energy forecast and user engagement for adoption by a layman both in off-grid or microgrid tied to a weak grid. This study proposes an EMS approach for short-term forecast and monitoring for hybrid microgrids in emerging countries. This is done by addressing typical submodules of EMS namely: load forecast, blackout forecast, and energy monitoring module. A short-term load forecast model framework consisting of a hybrid feature selection and prediction model was developed. Prediction error performance evaluation of the developed model was done by varying input predictors and using the principal subset features to perform supervised training of 20 different conventional prediction models and their hybrid variants. The proposed principal k-features subset union approach registered low error performance values than standard feature selection methods when it was used with the ‘linear Support Vector Machine (SVM)’ prediction model for load forecast. The hybrid regression model formed from a fusion of the best 2 models (‘linearSVM’ and ‘cubicSVM’) showed improved prediction performance than the individual regression models with a reduction in Mean Absolute Error (MAE) by 5.4%. In the case of the EMS blackout prediction aspect, a hybrid Adaptive Similar Day (ASD) and Random Forest (RF) model for short-term power outage prediction was proposed that predicted accurately almost half of the blackouts (49.16%), thereby performing slightly better than the stand-alone RF (32.23%), and ASD (46.57%) models. Additionally, a low-cost EMS smart meter was developed to realize the implemented energy forecast and offer user engagement through monitoring and control of the microgrid towards the goal of increasing energy efficiency

    Expectations and expertise in artificial intelligence: specialist views and historical perspectives on conceptualisation, promise, and funding

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    Artificial intelligence’s (AI) distinctiveness as a technoscientific field that imitates the ability to think went through a resurgence of interest post-2010, attracting a flood of scientific and popular expectations as to its utopian or dystopian transformative consequences. This thesis offers observations about the formation and dynamics of expectations based on documentary material from the previous periods of perceived AI hype (1960-1975 and 1980-1990, including in-between periods of perceived dormancy), and 25 interviews with UK-based AI specialists, directly involved with its development, who commented on the issues during the crucial period of uncertainty (2017-2019) and intense negotiation through which AI gained momentum prior to its regulation and relatively stabilised new rounds of long-term investment (2020-2021). This examination applies and contributes to longitudinal studies in the sociology of expectations (SoE) and studies of experience and expertise (SEE) frameworks, proposing a historical sociology of expertise and expectations framework. The research questions, focusing on the interplay between hype mobilisation and governance, are: (1) What is the relationship between AI practical development and the broader expectational environment, in terms of funding and conceptualisation of AI? (2) To what extent does informal and non-developer assessment of expectations influence formal articulations of foresight? (3) What can historical examinations of AI’s conceptual and promissory settings tell about the current rebranding of AI? The following contributions are made: (1) I extend SEE by paying greater attention to the interplay between technoscientific experts and wider collective arenas of discourse amongst non-specialists and showing how AI’s contemporary research cultures are overwhelmingly influenced by the hype environment but also contribute to it. This further highlights the interaction between competing rationales focusing on exploratory, curiosity-driven scientific research against exploitation-oriented strategies at formal and informal levels. (2) I suggest benefits of examining promissory environments in AI and related technoscientific fields longitudinally, treating contemporary expectations as historical products of sociotechnical trajectories through an authoritative historical reading of AI’s shifting conceptualisation and attached expectations as a response to availability of funding and broader national imaginaries. This comes with the benefit of better perceiving technological hype as migrating from social group to social group instead of fading through reductionist cycles of disillusionment; either by rebranding of technical operations, or by the investigation of a given field by non-technical practitioners. It also sensitises to critically examine broader social expectations as factors for shifts in perception about theoretical/basic science research transforming into applied technological fields. Finally, (3) I offer a model for understanding the significance of interplay between conceptualisations, promising, and motivations across groups within competing dynamics of collective and individual expectations and diverse sources of expertise

    Communicating linguistics: language, community and public engagement

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    Increasingly, academics are called upon to demonstrate the value of linguistics and explain their research to the wider public. In support of this agenda, Communicating Linguistics: Language, Community and Public Engagement provides an overview of the wide range of public engagement activities currently being undertaken in linguistics, as well as practically focused advice aimed at helping linguists to do public engagement well. From podcasts to popular writing, from competitions to consultancy, from language creation to community projects, there are many ways in which linguists can share their research with the public. Bringing together insights from leading linguists working in academia as well as non-university professions, this unique collection:- Provides a forum for the discussion of challenges and opportunities of public engagement in linguistics in order to shape best practice- Documents best practice through a summary of some of the many excellent public engagement projects currently taking place internationally- Celebrates the long tradition of public engagement in linguistics, a discipline which is often misunderstood despite its direct and fundamental importance to everyday lifeBreaking down long-standing divisions between universities and the wider community, this book will be of significant value to academics in linguistics but also teachers, policy makers and anyone interested in better understanding the nature and use of language in society

    Essays in High Frequency Trading and Market Structure

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    High Frequency Trading (HFT) is the use of algorithmic trading technology to gain a speed advantage when operating in financial markets. The increasing gap between the fastest and the slowest players in financial markets raises questions around the efficiency of markets, the strategies players must use to trade effectively and the overall fairness of markets which regulators must maintain. This research explores markets affected by HFT activity from three perspectives. Firstly an updated microstructure model is proposed to allow for empirical exploration of current levels of noise in financial markets, this illustrates current noise levels are not disruptive to dominant trading strategies. Second, a ARCH type model is used to de-compose market data into a series of traders working price levels to demonstrate that in cases of suspected market abuse, regulators can assess the impact individual traders make on price even in fast markets. Finally, a review of various HFT control measures are examined in terms of effectiveness and in light of an ordoliberal benchmark of fairness. The work illustrates the extents to which HFT activity is not yet disruptive, but also shows where HFT can be a conduit for market abuse and provides a series of recommendations around use of circuit breakers, algorithmic governance standards and additional considerations where assets are dual listed in different countries
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