Development of a numerical model to predict impact forces on a North Atlantic right whale during collision with a vessel

The North Atlantic right whale is under a great deal of public and private concern due to their endangered status and shrinking numbers. Of the 40 animals examined post-mortem (1970-2006), 21 deaths (52.5%) were caused by vessel-whale collision injuries, such as skull fractures. Several methods have been proposed to help reduce the number of fatalities. One such method is to place restrictions on ship speed within right whale critical habitats. However, no quantitative data exist regarding the effect of reduced vessel speed on the likelihood of fatality. The objective of this study is to develop a numerical model of the collision event to determine forces acting on the whale during impact. This will provide data on the mechanics of a ship-whale collision needed to form a basis for informed decisions regarding regulation of shipping traffic. A representative three-dimensional finite element model of a whale has been developed using inputs from various sources. The mechanical properties of bone material and soft tissue were assigned based on experimental work and published data. The external geometry was created based on data available from necropsy findings. A simplified skeleton containing the major components was estimated based on the size of the external whale geometry. A surface model of a very large crude carrier was created as the representative hull model for the simulations. Since mandible fracture is assumed to be a fatal endpoint of collision, the relative positions of the whale and ship were chosen such that direct impact occurs on the mandible. Numerical simulations were performed for vessel approach speeds of 5, 8, 10, 12, and 15 knots. From the simulation results, the impact forces as a function of time and the overall collision dynamics can be determined. The resultant transient load curves can be applied to a detailed mandible model to predict what impact velocities result in mandible fracture

Autophagy in the proximal tubule cell and its role in the progression of chronic kidney disease

Chronic kidney disease is a substantial health problem effecting a large portion of the US population. Presence of excess protein, particularly albumin, in the urine of patients with chronic kidney disease is an independent risk factor for cardiovascular disease and progression to end stage renal disease. In addition, excess protein reabsorption in the proximal tubule is sufficient to cause damage to the proximal tubule independent of the initial condition that lead to chronic disease. In the last decade, excess protein reabsorption by the proximal tubule as a result of chronic kidney damage has been shown to cause oxidative and ER stress, cell death, as well as tubule inflammation and fibrosis in the proximal tubule cell. Only recently have two studies investigated the role of autophagy in protein-induced tubule damage. Autophagy is a dynamic catabolic mechanism used to degrade cytosolic elements in times of cell starvation and is an important process in the cell's response to stress. The results of the studies by Wei Jin Liu et al. and Yamahara et. al. provide important first steps to determine whether autophagy of excess protein in proteinuric states prevents proximal tubule cell toxicity and potentially slow the progression of chronic kidney disease (CKD). This thesis will explore the results of these two studies in the context of proximal tubule damage in chronic kidney disease, and discuss the potential for protein autophagy to improve our understanding and treatment of chronic kidney disease

EVOLUTION OF INVESTMENT FLOWS IN U.S. MANUFACTURING:A SPATIAL PANEL APPROACH

The paper starts with a discussion of a conceptual model of location factors in U.S. manufacturing investment at the state level. The purpose of the paper is to test the relative importance of growth factors influencing investment and whether or not they have changed in importance over time. These factors include agglomeration, market structure, labor, infrastructure, and fiscal policy. A better understanding of investment flows in the manufacturing sector will help determine how growth factors have changed over time and which economic development policies may be most appropriate at targeting the sector. The analysis covers the time period 1994 to 2006 for the 48 contiguous states, with data taken from the Annual Survey of Manufactures, the Bureau of Economic Analysis, and the Bureau of Labor Statistics. Panel methods are used to test for fixed effects due to heterogeneity across states. Spatial panel methods with time effects are used for determination and specification of spatial and temporal effects. Empirical results are consistent across the empirical models put forth. Results suggest that market demand remains one of the most important location factors of manufacturing investment. Investment also goes to states with more productive labor and localized agglomeration of manufacturing activity.manufacturing, investment, location factors

DETERMINANTS OF INVESTME??T FLOWS IN U.S. MANUFACTURING

The purpose of the paper is to test the long-run steady state of growth factors hypothesized to influence U.S. manufacturing investment flows. These factors include agglomeration, market structure, labor, infrastructure, and fiscal policy. Spatial cross-regressive and spatial Durbin models are used to measure the spatial interaction of investment flows. Spatial spillovers are found to be of a competitive nature at the state level, implying that a factor which attracts more investment to a particular state is associated with lower investments in neighboring states. Investment flows to states with higher market demand, more productive labor, and more localized agglomeration of manufacturing activity.manufacturing, investment, spatial Durbin model

A TWO-STEP ESTIMATOR FOR A SPATIAL LAG MODEL OF COUNTS: THEORY, SMALL SAMPLE PERFORMANCE AND AN APPLICATION

Several spatial econometric approaches are available to model spatially correlated disturbances in count models, but there are at present no structurally consistent count models incorporating spatial lag autocorrelation. A two-step, limited information maximum likelihood estimator is proposed to fill this gap. The estimator is developed assuming a Poisson distribution, but can be extended to other count distributions. The small sample properties of the estimator are evaluated with Monte Carlo experiments. Simulation results suggest that the spatial lag count estimator achieves gains in terms of bias over the aspatial version as spatial lag autocorrelation and sample size increase. An empirical example deals with the location choice of single-unit start-up firms in the manufacturing industry in the US between 2000 and 2004. The empirical results suggest that in the dynamic process of firm formation, counties dominated by firms exhibiting (internal) increasing returns to scale are at a relative disadvantage even if localization economies are presentcount model, location choice, manufacturing, Poisson, spatial econometrics

Manufacturing Transition in Local Economies: A Regional Adjustment Model

This paper addresses changes in capital formation by testing the importance of location factors with respect to the rate of establishment births and deaths in U.S. manufacturing, 2000–2004. A theoretical concept called “localized creative destruction” is tested as a mechanism to explain the dynamics impacting the spatial distribution of manufacturing establishment birth and death rates. While no support of this process was found, results identify a convergence process occurring where counties with high initial birth/death rates have smaller changes in firm birth and death rates. The interpretation is that counties become more equally competitive in terms of firm formation dynamics in lieu of successful counties increasing their lead in the short run. This is potentially relevant to policymakers and economic development practitioners who are concerned with business retention and the impact of new manufacturing establishments on their existing base.location determinants, manufacturing, adjustment models, Community/Rural/Urban Development, L60, R11, R12,

Firm Birth and Death in U.S. Manufacturing: A Regional Adjustment Model

Attracting manufacturing investment is a frequently used rural development policy. Previous research in the location literature has informed policymakers which factors are most important for attracting new firm investment. Far less is known about the interaction of birth and death of establishments. A conceptual model of county-level investment in the U.S. manufacturing sector is developed from location theory and subsequent literature. Specifically, we test the relative importance of location factors influencing firm investment, and if these factors influence firm birth and death differently. Local factors include agglomeration due to localization, urbanization, and internal economies, market structure, labor quality, availability, and cost, market conditions, , infrastructure, and fiscal policy. This study covers the time period 2000 to 2004 for U.S. counties in the lower 48 states. Counts of establishments are from the U.S. Census Bureau’s Dynamic Firm Data Series, which links establishments across space and time. Negative binomial models containing spatially lagged endogenous variables are estimated in a regional adjustment framework to show how ceteris paribus changes in location factors affect the conditional number of establishment births and deaths in a county.location determinants, manufacturing, count models, Community/Rural/Urban Development, Research Methods/ Statistical Methods, L60, R11, R12,

Issue Brief: African Americans and Social Welfare

This issue brief focuses on social welfare and how it relates to African Americans in the United States. More specifically it discusses the racial aspect of social welfare how African Americans are perceived in regards to it