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Rising anthropogenic CO2 in the atmosphere and oceanic uptake of CO2 have led to a gradual decrease in seawater pH and ocean acidification, but pH changes in estuaries and coastal systems are more complicated due to a multitude of global and regional environmental drivers. Increasing global fertilizer use due to agricultural production has led to a doubling of riverine nutrient loading since the 1950s, leading to widespread eutrophication in estuarine and coastal waters. Excessive nutrient loading stimulates primary production in the surface euphotic layer, which consumes CO2 and elevates pH, but unassimilated organic matter sinks and decomposes in bottom waters, producing CO2 and reducing pH. In the meantime, human-accelerated chemical weathering, such as acid rain and mining, has resulted in rising alkalinity in many rivers and basification in estuarine and coastal waters. To discern how these environmental drivers influence long-term pH trends in coastal waters, a coupled hydrodynamic-biogeochemical-carbonate chemistry model was used to conduct hindcast simulations of the Chesapeake Bay between 1951 and 2010. The model reproduced the observed chlorophyll increase and hypoxia expansion due to the increased nutrient loading. In contrast, low-pH bottom waters and acidic volume shrank from 1950 to 1980. GAM analysis of long-term pH trends in different regions of Chesapeake Bay revealed increasing pH in the upper Bay driven by the river alkalinization, a peak pH in the mid-Bay in the 1980s coincident with the peak nutrient loading and decreasing pH in the lower Bay driven by ocean acidification. Four scenario runs were performed to assess the individual effects of rising pCO2, river alkalinization, riverine nutrient loading, and climate change (warming and sea-level rise) on long-term pH changes in the Chesapeake Bay. The model results suggested that river alkalinization was more important than ocean acidification in driving the long-term pH changes in the estuary.

The performance optimization of UAV communication systems requires the joint design of UAV trajectory and communication efficiently. To tackle the challenge of infinite design variables arising from the continuous-time UAV trajectory optimization, a commonly adopted approach is by approximating the UAV trajectory with piecewise-linear path segments in three-dimensional (3D) space. However, this approach may still incur prohibitive computational complexity in practice when the UAV flight period/distance becomes long, as the distance between consecutive waypoints needs to be kept sufficiently small to retain high approximation accuracy. To resolve this fundamental issue, we propose in this paper a new and general framework for UAV trajectory and communication co-design. First, we propose a flexible path discretization scheme that optimizes only a number of selected waypoints (designable waypoints) along the UAV path for complexity reduction, while all the designable and non-designable waypoints are used in calculating the approximated communication utility along the UAV trajectory for ensuring high trajectory discretization accuracy. Next, given any number of designable waypoints, we propose a novel path compression scheme where the UAV 3D path is first decomposed into three one-dimensional (1D) sub-paths and each sub-path is then approximated by superimposing a number of selected basis paths weighted by their corresponding path coefficients, thus further reducing the path design complexity. Finally, we provide a case study on UAV trajectory design for aerial data harvesting from distributed ground sensors, and numerically show that the proposed schemes can significantly reduce the UAV trajectory design complexity yet achieve favorable rate performance as compared to conventional path/time discretization schemes., Comment: 30 pages. This paper proposed a novel UAV trajectory design framework with flexible path discretization and path compression to significantly reduce the design complexity based on conventional path/time discretization schemes

Current knowledge about the evolutionary history of donkeys is still incomplete due to the lack of archeological and whole-genome diversity data. To fill this gap, we have de novo assembled a chromosome-level reference genome of one male Dezhou donkey and analyzed the genomes of 126 domestic donkeys and seven wild asses. Population genomics analyses indicate that donkeys were domesticated in Africa and conclusively show reduced levels of Y chromosome variability and discordant paternal and maternal histories, possibly reflecting the consequences of reproductive management. We also investigate the genetic basis of coat color. While wild asses show diluted gray pigmentation (Dun phenotype), domestic donkeys display non-diluted black or chestnut coat colors (non-Dun) that were probably established during domestication. Here, we show that the non-Dun phenotype is caused by a 1 bp deletion downstream of the TBX3 gene, which decreases the expression of this gene and its inhibitory effect on pigment deposition.

Full Text, Thesis (PhD Doctorate), Doctor of Philosophy (PhD), School of Languages and Linguistics, Arts, Education and Law, Meaning and meaning transfer is central to consecutive interpreting, both pragmatically and theoretically. Therefore, a comprehensive and sophisticated understanding of meaning components, and the process, major influencing factors and patterns of meaning transfer is fundamental not only to consecutive interpreting practice, quality assessment, teaching and training, but also to theoretical studies of consecutive interpreting. To date, however, there has been little comprehensive and systematic study of meaning transfer in consecutive interpreting. Meaning transfer is a multi-dimensional and multi-componential process. For this reason, a multidisciplinary approach is taken, integrating concepts and theories from descriptive translation studies, the interpretive theory of translation, and M.A.K Halliday’s systemic functional linguistics (SFL) with added support from a thorough empirical investigation. In specific, this takes the form of an analysis and description of Chinese government press conference interpreting, following a top-down order. First, drawing on documentary data, we analyse and describe the Social Institutional Context and Situational Context. Second, through analysing and comparing three authentic Chinese government press conference interpreting cases, we investigate the patterns of transferring Experiential, Interpersonal and Textual Meaning and their influencing variables, and explore the possible motivation for the given pattern. With reference to the Social Institutional and Situational Context, we examine and evaluate the meaning transfer patterns and identify the norms for transferring the three types of meaning. Third, various relevant influencing variables are categorized into different contexts which are used for the construction of a meaning transfer model for Experiential, Interpersonal and Textual Meaning, respectively. Finally, these three meaning transfer models are integrated into a comprehensive meaning transfer model for consecutive

Meaning and meaning transfer is central to consecutive interpreting, both pragmatically and theoretically. Therefore, a comprehensive and sophisticated understanding of meaning components, and the process, major influencing factors and patterns of meaning transfer is fundamental not only to consecutive interpreting practice, quality assessment, teaching and training, but also to theoretical studies of consecutive interpreting. To date, however, there has been little comprehensive and systematic study of meaning transfer in consecutive interpreting. Meaning transfer is a multi-dimensional and multi-componential process. For this reason, a multidisciplinary approach is taken, integrating concepts and theories from descriptive translation studies, the interpretive theory of translation, and M.A.K Halliday’s systemic functional linguistics (SFL) with added support from a thorough empirical investigation. In specific, this takes the form of an analysis and description of Chinese government press conference interpreting, following a top-down order. First, drawing on documentary data, we analyse and describe the Social Institutional Context and Situational Context. Second, through analysing and comparing three authentic Chinese government press conference interpreting cases, we investigate the patterns of transferring Experiential, Interpersonal and Textual Meaning and their influencing variables, and explore the possible motivation for the given pattern. With reference to the Social Institutional and Situational Context, we examine and evaluate the meaning transfer patterns and identify the norms for transferring the three types of meaning. Third, various relevant influencing variables are categorized into different contexts which are used for the construction of a meaning transfer model for Experiential, Interpersonal and Textual Meaning, respectively. Finally, these three meaning transfer models are integrated into a comprehensive meaning transfer model for consecutive, Thesis (PhD Doctorate), Doctor of Philosophy (PhD), School of Languages and Linguistics, Arts, Education and Law, Full Text