Since the devastating hurricane seasons of 2004, 2005, and 2008, the stability and serviceability of coastal bridges during and following hurricane events have become a main public concern. Twenty coastal bridges, critical for hurricane evacuation and recovery efforts, in Texas have been identified as vulnerable to hurricane surge and wave action. To accurately assess extreme surges at these bridges, a dimensionless surge response function methodology was adopted. The surge response function defines maximum surge in terms of hurricane meteorological parameters such as hurricane size, intensity, and landfall location. The advantage of this approach is that, given a limited set of discrete hurricane surge data (either observed or simulated), all possible hurricane surges within the meteorological parameter space may be described. In this thesis, we will first present development of the surge response function methodology optimized to include the influence of regional continental shelf geometry. We will then demonstrate surge response function skill for surge prediction by comparing results with surge observations for Hurricanes Carla (1961) and Ike (2008) at several stations along the coast. Finally, we apply the improved surge response function methodology to quantify extreme surges for Texas coastal bridge probability and vulnerability assessment.

Runoff from road construction and maintenance sites is responsible for erosion and deposition of sediments in the receiving water bodies. In addition to soil particles from erosion, runoff also transports other pollutants such as rubber, toxic metals, automobile fluids, car exhausts (which settle with the rain), pesticides, fertilizers, and other debris. Compost has been used effectively as a valuable soil amendment to aid plant growth. Berms (mounds) of compost placed at the top or bottom of steep slopes can be used to slow the velocity of water and provide additional protection for receiving waters. However, a downside of the application of composted organic material is the potential degradation of runoff water quality. Overloading with nitrogen and phosphorus causes eutrophication, which reduces the suitability of waterways for beneficial uses. A field testing of the berms coupled with a laboratory analysis of the testing water will provide a basis for the impact of the compost berms on the runoff water quality. The study of the impact of compost on the runoff water quality was investigated. The objective of this study was to evaluate the performance of berms made from various materials such as dairy manure compost, yard waste compost and composted bio-solids mixed with wood chips in a ratio of 50:50 on the runoff water quality, as well as, the sediment removal efficiencies. Field tests were performed on the berms to simulate conventional rainfall runoff and the tested water was collected as time-weighted samples and analyzed in the laboratory. Several variables were investigated during this study. Results of this investigation demonstrated that the effectiveness of this application was hampered by the structural instability of the berm. A 100% failure rate was observed in the berms tested. Optimum performance was observed in yard waste compost berms, which introduced the least amount of contaminants into the water. However, some masking effect could be present due to berm failures. In fact, the actual sediment removal by the berms could not be determined. The study of compost filter berms showed some evidence of the existence of first flush effect.

A high-volume air sampler (PS-1) was used to measure the concentrations of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere of Kaohsiung coast, PAHs diagnostic ratios,Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) were employed to determine the potential sources of PAHs. The results show that the lowest concentrations of PAHs occurred in May (2.62 ngm-3), while the highest occurred in December (36.4 ngm-3). The nighttime concentrations of PAHs are higher than daytime with average night / day ratio of 1.65. The PAHs was more distributed in gas phase with proportions between 64.1 to 93.7 %. The 2, 3-Ring PAHs were mostly present in the gaseous phase (96.2 and 96.5 % respectively), 4-Ring also present dominantly in the gaseous phase (73.0 %), 5-Ring present mostly in the particle phase (80.2 %), 6, 7-Ring PAHs were mostly present in particulate phase (97.4 and 97.7 % respectively). During the Ghost Festiva and Asian dust storm events, atmospheric concentrations of PAHs and PAHs/TSP ratios were both found increased. It is found that gaseous and particulate PAHs correlate negatively with ambient temperature(r=-0.62, -0.57). Results from analyses of diagnostic ratios, HCA and PCA, the major sources of pollution include gasoline, diesel exhaust and industrial emission.

With increasing demands on environmental protection in recent years, the Government agency concerned has recently proposed the strategies for shore protection and management, which aim for prevention and mitigation of coastal disaster and reduction in coastal erosion, as well as the creation of an environment with focus on landscape, ecology and community recreation. Soft and quasi-natural approach will be implemented to restore the glory of a stable coast. Based on the consideration of disaster prevention, this study investigates the beach profile changes, which include beach berm erosion and bar formation resulting from storm waves with different return periods. The SBEACH model is used to estimate the beach changes subject to variable conditions of beach berm width, medium sand grain diameter, beach slope and design water level etc. Regression analysis is then applied to establish a relationship between the storm beach buffer width and relevant physical parameters. Prior to this, the results of large wave tank tests on beach profile changes conducted by Coastal Engineering Research Center in the United States are used to calibrate the two main parameters K and £` used in SBEACH model. Beach profile changes can now be estimated systematically using a set of modified K and £` values. After having performed a series numerical studies, we may conclude that: (1) With storms of different return periods but identical non-dimensional fall velocity (H0/£sT), berm erosion increases and the location of the bar becomes further offshore as storm return period increases ; (2) With different sand grain sizes subject to identical storm wave conditions, beach berm erosion increases as grain size increased, but shoreline retreat decreases; and location of bar is further offshore for a beach consisting smaller sand grains; (3) Under the same storm return period and sand grain diameter (i.e., similar non-dimensional fall velocity), berm erosion increases as storm intensity and design water level increase, but shoreline retreat decreases and bar is located nearer; and vice versa; (4) from a series of calculations based on different sand grains and storm beach buffer width, it is found that larger buffer is required for beach with smaller grain size, in order to absorb the storm wave energy.

The collapse of subprime loan markets in the United States in 2007 sparked a global financial crisis. With the fallout of subprime loan storm, the global economy has been in serious recession. In addition to the financial stagnation, other industries have been also affected. According to the estimation by International Labor Organization (ILO), the global unemployment population in 2009 will be more than 200 millions. The continued rising of misery index and losing confidence among the public become the motivation for inspiring the researcher to explore this issue. The research aims to understand the financial storm and explore the cause of the subprime financial storm through the reviews and reorganization of literature. In light of the cyclical and repetitive nature of financial crisis, if we could find the leverage solution to the subprime loan storm, it will be a useful reference for dealing with possible financial crises in future. This research adopted literature analysis method and history study to collect data and explain the feedback viewpoint of the operation of the subprime loan storm through casual loop diagram (CLD). Through the reorganization of related literature, this research found the historical cause of the subprime loan storm. We also constructed a causal feedback diagram of the formation of subprime loan storm by the archetypes. Furthermore, we found out the leverage solution that might effectively curb subprime loan storm in the causal feedback diagram. This research presents three conclusions: 1) three reasons for the formation of the structure of subprime loan storm: a. the building-up of Black-Scholes Model; b. the regulations on the capital adequacy rates and commodity derivatives in Basel Agreement; c. the domination of performance; 2) the policy factors for the formation of the structure of subprime loan storm: the over-adjustment of rate policy by Fed; 3) the implicit factors for the formation of the structure of subprime loan storm: the effects of moral decline. In the last part, the research recommends six fundamental solutions for the subprime loan problem according to the leverage solution to the subprime loan storm: 1) the de-leverage of commodity derivatives; 2) the strict self-management of internal control and audit system in banks; 3) the adjustment of performance-dominated culture; 4) the promotion of moral education; 5) the pace of adjustment of rate policy by Fed should be slowed down; 6) the governments should adopt fiscal policy as much as they can.

Recently the labor dispute, by the laborer requested the employer pays the retirement pension, discharges with severance pay, the wages event for the most large amount, in the human resources management reduces staff the dismissal for the employer to express on own initiative behavior of the termination labor contract, is because the employer folk remedy meaning expressed occurs, is really big rights and interests of influence regarding the laborer.Therefore, this article has the dismissal jurisdiction, gets employed the protection with the laborer the contradiction and the conflict discussion, by home four big industry practice utilization in, regarding employer and laborer during divergent interest, obtains during the suitable balance the thorough discussion. The research goal in the financial storm occurrence, the industrial structure change and the whole employment environmental variation, grows the question which the enterprise reduces staff, causes unemployed's ratio to climb.Speaking of the enterprise, reduces staff the benefit which in the cost reduces, relative also has in the management strategy negative management the influence, and remains in office the staff the intrinsic psychological concealed worry which initiates after the event.Do take the mean value difference examination ¢wt test and the mean value variation analysis ¢wANOVA concept and the statistical analytic method as the analysis tool, when organizes front to consider must pick the line to reduce staff, should consider the staff innermost feelings, the enterprise completes the properly necessary measure, assists these the laborer who reduces staff, with remains in office staff's psychology, more promotes to the organization centripetal force.

Thesis (Ph. D.)--Oregon State University, 2009. / Printout. Includes bibliographical references. Also available on the World Wide Web.

Thesis (M.S.)--Rutgers University, 2009. / "Graduate Program in Ecology, Evolution and Natural Resources." Includes bibliographical references (p. 41-47).

Thesis (M.S.)--University of Wisconsin--Stevens Point, 2002. / Includes bibliographical references (leaves 62-65).

Creating an accurate hurricane location forecasting model is of the utmost importance because of the safety measures that need to occur in the days and hours leading up to a storm's landfall. Hurricanes can be incredibly deadly and costly, but if people are given adequate warning, many lives can be spared. This thesis seeks to develop an accurate model for predicting storm location based on previous location, previous wind speed, and previous pressure. The models are developed using hurricane data from 1980-2009.