Artificial beach nourishment, the most common method to mitigate coastal erosion in the United States, is also considered the most ecologically friendly alternative for shoreline stabilization. However, this habitat alteration has the potential to impact nesting marine turtles and developing hatchlings. The first objective of this study was to determine how nourishing beaches with two different design templates affects loggerhead (Caretta caretta) and green turtle (Chelonia mydas) nesting success, the ratio of nests to the total number of nests and non-nesting emergences, and reproductive success, the ratio of hatched and emerged hatchlings to the total number of eggs deposited. Two types of restoration designs exist along the southern Brevard County, FL coastline, which supports some of the highest density loggerhead and green turtle nesting worldwide. Since 2005, approximately 35 kilometers of beach have undergone 1) fullscale restoration (typically called nourishment), where sand was added above and below the mean high tide line (2005, 2010) or 2) dune restoration, where sand was placed on the dune (2005, 2006, 2008, 2009). To quantify the effects of these restoration types, we used a Before-After-ControlImpact-Paired Series (BACIPS) model, which tests for significance between the difference in nesting success rates at the impact (engineered) and control sites (natural beach) before and after restoration ( ). For loggerheads, there was a significant difference in after dune restoration during the years of construction (2005, 2006, 2008, and 2009; p

No description available.

No description available.

<p>A critical factor in transit mode share analysis is the level of accessibility to transit services. The objective of this study is to investigate the relationships between accessibility and the built environment, and the use of transit. To do so, the proportion of transit users is modeled as a function of socio-economic characteristics, transit level of service, and built environment characteristics. While accessibility to transit has been the object of previous research, accessibility <em>by</em> transit is a factor that has received only limited attention in prior transit modal share research. The case study is the city of Hamilton, and the geographic unit of analysis is the Dissemination Area. A logistic model for proportions with a spatial filter (for spatial autocorrelation) and an over-dispersion parameter is found to provide the best fit and statistical properties. The results of analysis at the meso-scale show that accessibility by transit contributes positively to usage of transit. The possibility that factors at the micro-scale may also influence use of transit, suggests the development of a methodology, based on the use of spatial filtering, to systematically select walkability audit sites. The proposed methodology is demonstrated by means of a case study of neighborhoods in Hamilton. Statistical analysis of walkability audit information shows that the proposed selection strategy can be used to better target limited resources for field-based work, and produce valuable insights into the micro-level factors that may affect transit use.</p> / Master of Arts (MA)

Environmental Impact Assessment stands as a crucial tool in the realm of sustainable development, serving to evaluate the potential environmental implications of proposed projects. While Environmental Impact Assessment processes are widely adopted across nations, their efficacy continually evolves in response to contemporary challenges. This study delves into the effectiveness of EIA procedures, focusing on the Environmental Impact Assessment report of the Mullikulam on-shore wind farm project in Sri Lanka. Initially, the research scrutinizes the criteria for assessing the effectiveness of EIA through desk review and content analysis. Subsequently, it employs a comprehensive checklist to evaluate the effectiveness of the Environmental Impact Assessment report of the said wind farm project, analyzing its adherence to key effectiveness criteria. This evaluation extends to comparative analysis, encompassing two additional Environmental Impact Assessment reports concerning on-shore wind farms in other countries. While the study's objective is to critically evaluate the effectiveness of the Environmental Impact Assessment report of the Mullikulam wind farm project, findings indicate notable deficiencies, particularly concerning site selection, mitigation strategies, and stakeholder engagement. By highlighting these shortcomings, the research underscores the imperative for improvements in EIA practices to enhance effectiveness. The study contributes valuable insights for policymakers, practitioners, and stakeholders involved in EIA processes, advocating for enhancements to ensure stronger environmental assessments in future projects.

Land, water and natural resources are under increasing pressure due to rising demands for food and energy from the rapidly growing global population. Across a catchment there can be multiple stakeholders with conflicting opinions over how space and resources should be used and managed. Consequently, it is important to consider the suitability of a catchment for a particular purpose to optimise use of the area and minimise potential conflicts and impacts on the wider environment. Aquaculture is a significant contributor to world food supply and as fisheries are unlikely to increase it is expected that the industry will continue to grow and expand in the future to help meet food security requirements. As a result, it is essential that the sector aims for sustainable development within the most suitable locations. However, it can be difficult to assess the suitability of multiple large catchments and some issues may not be immediately apparent. This project aimed to show how spatial models could be used as decision support tools to evaluate the suitability of large catchments for sustainable aquaculture. Four large areas of importance to aquaculture were selected; covering 10,148km2, 26,225km2, 48,319km2 and 66,283km2 in Bangladesh, China, Thailand and Vietnam respectively. Asia is by far the most dominant aquaculture region in the world and each of the four study areas contribute to local, regional and global food supplies. The study area in Bangladesh was located in Khulna region in the south west of the country and the main species of focus were prawn and shrimp. The Chinese study area was located in the south eastern province of Guangdong and the main species covered were tilapia and shrimp. Similarly, in Thailand, the main species evaluated were tilapia and shrimp whilst the study area extended across the Central region. Finally, the largest study area was the Mekong Delta in Vietnam and the main species of focus in this area were pangasius catfish and shrimp. One of the challenges in modelling large catchments is model applicability and data availability. Often, the required data are not available (or accessible) and it would be difficult, time consuming and expensive to collect new information. Furthermore, when assessing multiple areas is it vital that a representative and unbiased approach is used where no one catchment is favoured over the other due to higher quality data. Therefore, this study used data that are available for almost any area in the world; allowing future application of the models and enabling effective and unbiased decision support. Four modelling stages were employed in this study to evaluate the suitability of large catchments for sustainable aquaculture development. The first stage was the classification of seasonal land use models from satellite imagery. This provides information on what the land is used for and how aquaculture could impact or be impacted by the wider environment. The second step was the development of seasonal models of site suitability using optimal values within a GIS-based multi-stage framework. These models identify which locations are best for culture and can also be used to estimate the availability of areas for food production. The next stage investigated the use of Maxent as a novel approach in site suitability modelling to evaluate the conditions experienced by existing farms. The information from Maxent can be used to identify trends, opportunities and concerns related to sustainable management and farm locations. Finally, qualitative models of non-point source pollution (NPSP) were developed which assess the risk of NPSP within a catchment. NPSP is an issue which can impact both aquaculture and the wider environment. Thus, it is important to understand the areas within a catchment where NPSP risk is higher enabling the establishment of monitoring and/or mitigation procedures. The models support the ecosystem approach to aquaculture (EAA) and enable objective planning and management strategies to enhance productivity across large catchments without negatively impacting the environment. In order to meet growing food requirements, large areas will need to be used for agriculture and aquaculture; therefore, analysis at a wider catchment level, which complements assessment at a local scale, is required as it allows a holistic view of the situation. The work presented here illustrates the potential use of spatial models across large catchments and considers the suitability of the areas for aquaculture development.

Alternative splicing is one of the mechanisms how to regulate gene expression. Under different conditions, different mRNAs encoding proteins with different function, localization or stability can be made from one cellular transcript. The human hSlu7 protein affects the alternative splicing of some genes through alternative 3'splice site (3'SS) selection. Although it was thought that alternative splicing is absent from Saccharomyces cerevisiae, recent results argue against such conclusion. We therefore decided to characterize the function of the yeast Slu7 protein, which participates in the second step of splicing and is closely associated with the 3'SS selection. We focused on a highly conserved uncharacterized motif in the essential part of the Slu7 protein named the RED motif. Mutations in this motif caused second step splicing defects with some substrates and altered the alternative 3'SS usage ratio of some splicing constructs. Our results implicate a role for the RED motif in selecting proper 3'splice sites, especially the distal ones. Genetic interactions of slu7 mutations with PRP22 and PRP45 mutant alelles add to the intricate interaction network of splicing factors and suggest a possible role of Slu7p in facilitating the Prp22p association with the spliceosome.

Beekeepers in Appalachia market varietal honeys derived from particular species of deciduous trees; however, finding places in a mountainous landscape to locate new beeyards is difficult. Site selection is hindered by the high up-front costs of negotiating access to remote areas with limited knowledge of the available forage. Remotely sensed data and species distribution modeling (SDM) of trees important to beekeepers could aid in locating apiary sites at the landscape scale. The objectives of this study are i) using publicly available forest inventory data, to model the spatial distribution of three native tree species that are important to honey producers in eastern Kentucky: American Basswood, Sourwood and Tulip Poplar, and to assess the accuracy of the models, ii) to incorporate a method for discounting the value of a nectar resource as a function of distance based on an energetic model of honeybee foraging, and iii) to provide an example by ranking potential apiary locations around the perimeter of a mine site in the study area based on their proximity to probable species habitat using a GIS model. Logistic regression models were trained using presence-absence records from 1,059 USFS Forest Inventory and Analysis (FIA) sub-plots distributed throughout a 9,000 km2 portion of the Kentucky River watershed. The models were evaluated by applying them to a separate dataset, 950 forest inventory sub-plots distributed over a 40.5 km2 research forest maintained by the University of Kentucky. Weights derived from an energic model of honeybee foraging were then applied to the probabilities of tree species occurrence predicted by the SDM. As an example, 24 potential apiary locations around the perimeter of a reclaimed mine site were selected and then ranked according to a site suitability index. Three tributary areas corresponding to different honeybee flight ranges were considered: 500m, 700m, and 1,200m. Results confirm that rankings are dependent on the foraging range considered, suggesting that the number of colonies at an apiary location would be an important factor to consider when choosing a site. However, the methodology makes assumptions that are only anecdotally supported, notably i) that colonies will forage preferentially at the target species when it is in bloom and, ii) that foragers will exhaust resources closest to the hive first, regardless of patch size. Additional study of how bees deplete the nectar resources surrounding an apiary is needed to verify the usefulness of SDM in site selection for varietal honey production.

近年來由於政府實施無紙化及金融業者推行電子帳單的成效卓越，使得國內郵件的收寄量逐年下滑，郵局如何與民營業者競爭國內物流市場並達成盈餘目標，成為營運中不可忽視之因素。 傳統的郵局設點多依據公司規定與配合政府政策需求，甚少採用涉及複雜因素之區位分析進行選址。因此，如何有效且公正地評選郵局新設據點以提高收益，成為亟待解決之問題。 本研究目的在於提供高收益之郵局設點建議，我們提出一種評估中華郵政公司設點效益的方法，以國內郵局實際設點位置與相關空間資料來建置實驗模型。研究結果顯示，以本研究方法建立之預測模型可成功的提供中華郵政公司建議於何處新增據點可收最大功效。 我們首先蒐集中華郵政公司設點之鄰近區域資料，如競爭者設點數、人口因素、重要交通路口、郵件收寄量等。其次導入資料探勘技術分析影響郵件收寄量之因素，建立中華郵政公司設點收寄量預測模型。然後依照建立預測模型時所得到之區辨力分數，判斷採用何種資料探勘技術建立預測模型較適當。最後將所選定的預測模型套用於台北縣市各村里建物重心，透過環域資料分析以計算預估之收寄量，再整合各資料探勘技術之預測結果後推論出最佳設點建議。 實作中，以台北縣市資料來測試我們的方法。實驗數據顯示，我們的方法成功地找出十一個建議設點的村里，可提供給中華郵政公司作為高收益的設點建議。 / The amount of postal mail declines in recent years due to the efforts of paper-reduce policies implemented by the government, the industries, and the general publics. It becomes one of the important issues of the Chunghwa Post Company, to compete with other companies in domestic freight and mail services and to achieve the desired profits. Traditionally, the location of post offices were decided according to the government policies as well as the company regulations. The issues involved in the site selection analysis were seldom considered. Hence, developing an effective and fair mechanism to find the new post office locations that could improve the company’s surplus becomes an important problem to be solved. The purpose of this thesis is to provide recommendations to the post office site selection which will yield high profit to the company. We proposed a method to evaluate the effective profits that could be produced by a particular post office through the data mining techniques and the related GIS information. We first collect various data, such as neighborhood population, traffic flow, postal mail received at particular post office, competitor’s information, etc., and analyze these data using data mining techniques in order to establish prediction models. The most appropriate model was chosen to find the new post office sites. The Metropolitan Taipei area was chosen to illustrate our idea. The best sites for new post offices were selected through the buffering analysis as well as the data mining techniques. The experimental results show that our method can successfully find eleven locations which could generate most profit to Chunghwa Post Company if the new post offices were located in these places.

近年來台灣連鎖咖啡店消費人口的穩定成長，提升了連鎖咖啡店的市場規模與消費產值，傳統利潤導向的市場經營方式，使得連鎖咖啡店的競爭更趨激烈，如何訂定正確的選址與經營策略，成為在高度競爭市場中存活的重要關鍵。 傳統的選址問題需要投入大量的人力與時間進行相關資訊的蒐集、訪查與評估，故而在新設營業點時，較少運用複雜的因素進行區位選址的分析與評估。因此能透過較多的因素，從區位選址與營利效應等觀點進行分析，協助投資者獲得更好的利潤，提高決策成功的機率，是極為重要的問題。 本論文的目的，在於為連鎖咖啡店之選址決策，提出能增加成功機率之設點建議。我們依據連鎖咖啡市場雙雄在訂定選址決策的成功經驗，透過相關係數進行人口與經濟活動因素之統計分析，以找出其成功選址之關鍵因素。同時運用資料探勘的分類技術，建構成功選址之分類模型，並經由地理資訊系統提供的圖層資料，對連鎖咖啡市場雙雄之競爭關係進行分析與評估，以提供正確選址及設點之建議。 實作中我們採用台北市出租店面之空間資料，以探討並評估本研究建議模型之實際效益。實驗結果顯示，透過本研究之選址分類模型進行設點類型之預測，有七成以上之達成率，顯示本研究提出之模型能有效增加選址的成功機率，同時經由競爭對手設點空間關係之分析，亦能提供有利選址決策之建議。 / The number of customers of coffee shop chains has grown steadily in recent years that cause the market size as well as the total consumption value increase rapidly and continuously. The competition among the chain coffee stores get even worse under the traditional profit oriented management style. In such case, it is crucial to make the correct decisions when selecting the coffee shop locations as well as making operation strategies in opening new coffee shops. Traditionally, it takes a great amount of time and human resources in collecting relevant information, conducting field visits as well as site evaluations when making coffee shop site selections. One seldom considers complex factors of site evaluation or field analyzing in selecting the location of new coffee shop. Hence, it will be one of the major contributions if one can find a mechanism in analyzing the site selection as well as profit evaluation to help the investors to produce better profit and to improve the chance of success. The goal of this thesis is to provide recommendations to improve the success rate of chain coffee shop site selection strategy. Based on the coffee market leaders’ success experiences in formulating the site selection strategies, we analyzed the correlation coefficients of the population as well as economy activities in order to identify the key factors in successful site selection strategies. We also used data mining techniques to construct the classification models of successful site selection. In addition, we analyzed and evaluated competition relations between the two leading chain coffee brands using the geographic information systems to obtain appropriate recommendations in new site selections. The shop rental information of Taipei City was used to explore and to evaluate the models recommended in our mechanism. The experimental results showed that the prediction through the classification models for site selections can achieve 70% of success rate. This indicates our mechanism effectively improve the successful rate of site selections. Moreover, the experimental results also show that the spatial analysis of site selections between the competitors is helpful in providing appropriate site selection strategies.