South Carolina Statistical Abstract 1993

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract 1994

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract 2000-2001

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract '96

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract '97

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract '98

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract 1999

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

South Carolina Statistical Abstract 2001-2002

The South Carolina Budget and Control Board, Office of Research and Statistics annually published Statistical Abstracts, a comprehensive, single-source reference of demographic and economic data pertinent to the state. This publication is now an online publication by the South Carolina Revenue and Fiscal Affairs Office.

Conhecer as razões da desistência nos Centros de Novas Oportunidades

Trabalho de projecto de mestrado, Ciências da Educação (Formação de Adultos - Educação e formação de jovens e adultos pouco escolarizados), Universidade de Lisboa, Instituto de Educação, 2011

Long-term and Short-term Forecast Models for Poaceae (Grass) Pollen in Poznan, Poland, Constructed Using Regression Analysis

Airborne concentrations of Poaceae pollen have been monitored in Poznań for more than ten years and the length of the dataset is now considered sufficient for statistical analysis. The objective of this paper is to produce long-range forecasts that predict certain characteristics of the grass pollen season (such as the start, peak and end dates of the grass pollen season) as well as short-term forecasts that predict daily variations in grass pollen counts for the next day or next few days throughout the main grass pollen season. The method of forecasting was regression analysis. Correlation analysis was used to examine the relationship between grass pollen counts and the factors that affect its production, release and dispersal. The models were constructed with data from 1994-2004 and tested on data from 2005 and 2006. The forecast models predicted the start of the grass pollen season to within 2 days and achieved 61% and 70% accuracy on a scale of 1-4 when forecasting variations in daily grass pollen counts in 2005 and 2006 respectively. This study has emphasised how important the weather during the few weeks or months preceding pollination is to grass pollen production, and draws attention to the importance of considering large-scale patterns of climate variability (indices of the North Atlantic Oscillation) when constructing forecast models for allergenic pollen.

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150

Investigating and Predicting Atmospheric Concentrations of Allergenic Fungal Spores (Alternaria, Cladosporium, Didymella and Ganoderma)

Air quality is an increasing concern of the European Union, local authorities, scientists and most of all inhabitants that become more aware of the quality of the surrounding environment. Bioaerosols may be consisted of various elements, and the most important are pollen grains, fungal spores, bacteria, viruses. More than 100 genera of fungal spores have been identified as potential allergens that cause immunological response in susceptible individuals. Alternaria and Cladosporium have been recognised as the most important fungal species responsible for respiratory tract diseases, such as asthma, eczema, rhinitis and chronic sinusitis. While a lot of attention has been given to these fungal species, a limited number of studies can be found on Didymella and Ganoderma, although their allergenic properties were proved clinically. Monitoring of allergenic fungal spore concentration in the air is therefore very important, and in particular at densely populated areas like Worcester, UK. In this thesis a five year spore data set was presented, which was collected using a 7-day volumetric spore trap, analysed with the aid of light microscopy, statistical tests and geographic information system techniques. Although Kruskal-Wallis test detected statistically significant differences between annual concentrations of all examined fungal spore types, specific patterns in their distribution were also found. Alternaria spores were present in the air between mid-May/mid-June until September-October with peak occurring in August. Cladosporium sporulated between mid-May and October, with maximum concentration recorded in July. Didymella spores were seen from June/July up to September, while peaks were found in August. Ganoderma produced spores for 6 months (May-October), and maximum concentration could be found in September. With respect to diurnal fluctuations, Alternaria peaked between 22:00h and 23:00h, Cladosporium 13:00-15:00h, Didymella 04:00-05:00h and 22:00h-23:00h and Ganoderma from 03:00h to 06:00h. Spatial analysis showed that sources of all fungal species were located in England, and there was no evidence for a long distance transport from the continent. The maximum concentration of spores was found several hours delayed in comparison to the approximate time of the spore release from the crops. This was in agreement with diurnal profiles of the spore concentration recorded in Worcester, UK. Spores of Alternaria, Didymella and Ganoderma revealed a regional origin, in contrast to Cladosporium, which sources were situated locally. Hence, the weather conditions registered locally did not exhibit strong statistically significant correlations with fungal spore concentrations. This has had also an impact on the performance of the forecasting models. The best model was obtained for Cladosporium with 66% of the accuracy.

Evolution of the rbcS gene family in Solanaceae: concerted evolution and gain and loss of introns, with a description of new statistical guidelines for determining the number of unique gene copies.

Thesis (Ph.D.)--University of Washington, 2014

Applications of Statistical Modeling in Iterative CT Image Reconstruction

Thesis (Master's)--University of Washington, 2015