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Population Projection is essential to policy planning, especially to social welfare. The cohort component method is the most popular method for population projection. The future trends of fertility, mortality, and immigration are often determined by the experts' opinions, which are also known as scenario forecasts, and then plugged into the cohort component method. However, the projections derived via the experts' opinions are deterministic and do not have implications in probability. To let the population projections possess the meaning of probability by renovating the scenario forecasts, researchers have developed three types of probabilistic forecasting methods, including the stochastic forecast method, random scenario method, and ex post method. In this paper, we study the block bootstrap method, a computer simulation method and also a stochastic forecast method, and evaluate the possibility of applying this method in population projection. Specifically, employing data from Taiwan, the U.S., Japan, and France, we use cross-validation and computer simulation to explore the limitations of the block bootstrap, and check if this method can produce reasonable projections. Based on the empirical results, we found that the block bootstrap is a feasible method and can produce stable population projections. In addition, we also study the ex post method proposed by Stoto (1983) and give the probability implications to projections from the Council for Economic Planning and Development (a scenario forecast). [ABSTRACT FROM AUTHOR]

To investigate the effects of arsenic exposure on porphyrins excretion profiles in human, porphyrins were measured by HPLC and total arsenic by HG-AAS in urine samples collected from arsenicosis-endemic areas and control sites in Guizhou Province. Analytical data showed that urinary uroporphyrin-III and coproporphyrin-III were significantly elevated in arsenic-exposed group compared with those in control group, while urinary coproporphyrin-I was not significantly higher in arsenic-exposed group than that in control group. Not any significant difference was found in porphyrins between the male and female except for 20-40 years age group. As far as age was concerned, arsenic-exposed group of <20 years showed significant increases in uroporphyrin-III and coproporphyrin-III compared with the control group of <20 years. Similarly, arsenic-exposed groups of 20-40 years and >40 years also showed significant increases in coproporphyrin-III compared with corresponding age groups of control. Besides, there were positive correlations between the urinary arsenic and total coproporphyrin, and total porphyrin. The effects of arsenic exposure were associated with increased porphyrins excretion, which was suggested that porphyrins were possible to be used as biomarkers of early health effect due to arsenicosis.