Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

<p>Abstract</p> <p>Background</p> <p>Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns.</p> <p>Methods</p> <p>In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender.</p> <p>Results</p> <p>Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships.</p> <p>Conclusions</p> <p>Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services.</p

The Leverage of Demographic Dynamics on Carbon Dioxide Emissions: Does Age Structure Matter?

This article provides a methodological contribution to the study of the effect of changes in population age structure on carbon dioxide (CO2) emissions. First, I propose a generalization of the IPAT equation to a multisector economy with an age-structured population and discuss the insights that can be obtained in the context of stable population theory. Second, I suggest a statistical model of household consumption as a function of household size and age structure to quantitatively evaluate the extent of economies of scale in consumption of energy-intensive goods, and to estimate age-specific profiles of consumption of energy-intensive goods and of CO2 emissions. Third, I offer an illustration of the methodologies using data for the United States. The analysis shows that per-capita CO2 emissions increase with age until the individual is in his or her 60s, and then emissions tend to decrease. Holding everything else constant, the expected change in U.S. population age distribution during the next four decades is likely to have a small, but noticeable, positive impact on CO2 emissions

Rural-to-Urban Labor Migration, Household Livelihoods, and the Rural Environment in Chongqing Municipality, Southwest China

Rural migration and its relationship to the rural environment have attracted increasing research interest in recent decades. Rural migration constitutes a key component of human population movement, while rural areas contain most of the world’s natural resources such as land and forests. This study empirically evaluates a conceptual framework incorporating rural household livelihoods as an integrative mediating factor between rural migration and the rural environment in the context of rural-to-urban labor migration in Chongqing Municipality, Southwest China. The analysis draws on data collected through household surveys and key informant interviews from four villages. Results confirm the hypothesis that labor-migrant and non-labor-migrant households differ significantly in livelihood activities including agricultural production, agricultural technology use, income and consumption, and resource use and management. Implications for the subsequent environmental outcomes of rural labor out-migration and corresponding natural resource management and policy in rural origin areas are discussed

Vanadate-stimulated NADH oxidation in plasma membrane

The rate of NADH oxidation with oxygen as the acceptor is very low in mouse liver plasma membrane and erythrocyte membrane. When vanadate is added, this rate is stimulated 10- to 20-fold. The absorption spectrum of vanadate does not change with the disappearance of NADH. The reaction is inhibited by superoxide dismutase, and there is no activity under an argon atmosphere. This indicates that oxygen is the electron acceptor and the reaction is mediated by superoxide. The vanadate stimulation is not limited to plasma membrane. Golgi apparatus and endoplasmic reticulum show similar increase in NADH oxidase activity when vanadate is added. The endomembranes have significant vanadate-stimulated activity with both NADH and NADPH. The vanadate-stimulated NADH oxidase in plasma membrane is inhibited by compounds, which inhibit NADH dehydrogenase activity: catechols, anthracycline drugs and manganese. This activity is stimulated by high phosphate and sulfate anion concentrations

Generation of hydrogen peroxide on oxidation of NADH by hepatic plasma membranes

The oxidation of NADH by mouse liver plasma membranes was shown to be accompanied by the formation of H2O2. The rate of H2O2 formation was less than one-tenth the rate of oxygen uptake and much slower than the rate of reduction of artificial electron acceptors. The optimum pH for this reaction was 7.0 and theK m value for NADH was found to be 3×10–6 M. The H2O2-generating system of plasma membranes was inhibited by quinacrine and azide, thus distinguishing it from similar activities in endoplasmic reticulum and mitochondria. Both NADH and NADPH served as substrates for plasma membrane H2O2 generation. Superoxide dismutase and adriamycin inhibited the reaction. Vanadate, known to stimulate the oxidation of NADH by plasma membranes, did not increase the formation of H2O2. In view of the growing evidence that H2O2 can be involved in metabolic control, the formation of H2O2 by a plasma membrane NAD(P)H oxidase system may be pertinent to control sites at the plasma membrane

Sharing, Households and Sustainable Consumption

[Abstract]: The problem of gene specific co-regulation discovery is that, for a particular gene of interest, identify its closely co-regulated genes and the associated subsets of experimental conditions in which such co-regulations occur. The co-regulations are local in the sense that they occur in some subsets of full experimental conditions. In this paper, we propose an innovative method for finding gene specific co-regulations using genetic algorithm (GA). Two novel ad hoc GAs, the single-stage and two-stage progressive GA, are proposed. They are called progressive because the initial population for the GA in a window position inherits the top-ranked individuals obtained in the preceding window position, enabling them to achieve better accuracy than the non-progressive algorithm. Experimental results with real-life gene expression data demonstrate the efficiency and effectiveness of our technique in discovering gene specific co-regulations