991 resultados para Counties
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Farmer and business directory for the counties of Haldimand, Halton, Lincoln, Norfolk, and Welland for the year 1895.
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Farmer and business directory of Haldimand, Lincoln, Welland, and Wentworth for the year 1902.
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Farmers and business directory for the counties of Haldimand, Lincoln, Welland, and Wentworth for the years 1917 - 1918.
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Farmers and business directory for the counties of Haldimand, Lincoln, Welland, and Wentworth for the years 1923 - 1924.
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List (4 pages, handwritten) of lands in the counties of Lincoln and Welland for which the Sherriff has made new deeds, n.d.
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According to estimates released by the Bureau of the Census in August, 2009, Nebraska’s total housing stock increased by 5,529 units between July 1, 2007 and July 1, 2008, an increase of 0.7 percent for the year. This represented an estimated rate of growth in housing stock slightly below the state’s estimated rate of population growth, which was 0.8 percent for the same time period.
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In writing this report, two objects were kept in mind, (1) to explain, if possible, the origin of the chromite deposits found in Sweetgrass and Stillwater Counties, and (2) to bring up to date all information on these deposits which had thus far been available. The work done consisted of study of the rocks and ores of the area under the microscope, both as thin sections and as polished sections, practically all of which was done at the Montana State School of Mines, during the school year of 1928 - 1929. The rock specimens and much information as to their locations and probable compositions were obtained from Mr. P. F. Minister, of the East Butte Copper Company. United States Geological Survey Bulletin 725-A, Deposits of Chromite in California, Oregon, Washington, and Montana, and the unpublished report on the Chromite deposits of the Boulder River, prepared by Prof. C. H. Clapp of the University of Montana, were frequently referred to and considerable material was drawn from them. The map of the Boulder River area is from Clapp's report.
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Background Accidental poisoning is one of the leading causes of injury in the United States, second only to motor vehicle accidents. According to the Centers for Disease Control and Prevention, the rates of accidental poisoning mortality have been increasing in the past fourteen years nationally. In Texas, mortality rates from accidental poisoning have mirrored national trends, increasing linearly from 1981 to 2001. The purpose of this study was to determine if there are spatiotemporal clusters of accidental poisoning mortality among Texas counties, and if so, whether there are variations in clustering and risk according to gender and race/ethnicity. The Spatial Scan Statistic in combination with GIS software was used to identify potential clusters between 1980 and 2001 among Texas counties, and Poisson regression was used to evaluate risk differences. Results Several significant (p < 0.05) accidental poisoning mortality clusters were identified in different regions of Texas. The geographic and temporal persistence of clusters was found to vary by racial group, gender, and race/gender combinations, and most of the clusters persisted into the present decade. Poisson regression revealed significant differences in risk according to race and gender. The Black population was found to be at greatest risk of accidental poisoning mortality relative to other race/ethnic groups (Relative Risk (RR) = 1.25, 95% Confidence Interval (CI) = 1.24 – 1.27), and the male population was found to be at elevated risk (RR = 2.47, 95% CI = 2.45 – 2.50) when the female population was used as a reference. Conclusion The findings of the present study provide evidence for the existence of accidental poisoning mortality clusters in Texas, demonstrate the persistence of these clusters into the present decade, and show the spatiotemporal variations in risk and clustering of accidental poisoning deaths by gender and race/ethnicity. By quantifying disparities in accidental poisoning mortality by place, time and person, this study demonstrates the utility of the spatial scan statistic combined with GIS and regression methods in identifying priority areas for public health planning and resource allocation.