Chapter 40R School Cost Analysis and Proposed Smart Growth School Cost Insurance Supplement

Analyzes the effects of insuring local communities against having to absorb school costs above the increased property and excise tax revenue generated by new housing units. Calls for supplements as a way to encourage the construction of moderate housing

VALUE OF BEEF STEAK BRANDING: HEDONIC ANALYSIS OF RETAIL SCANNER DATA

Replaced with revised version of paper 07/18/10.beef steak, brand premium, hedonic modeling, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries, Marketing,

Broadcast News: Writing, Reporting and Producing -5/E.

Broadcast News: Writing, Reporting and Producing examines the skills, technologies, and chalenges of broadcast jurnalism. Beginning with an introduction chapter of ethical considerations, you Learn how to find the news, develop sources and collect information from both real and virtual document. The book then delves into an in depth analysis on writing the news and choosing news writing styles. The third seaction expands on writing the news in to merging video and audio into e news report.and the final seaction show how to produce and seliver the news in a Comprehensive newscast, whether it is designed for televison, radio, internet and others

Value of Beef Steak Branding: Hedonic Analysis of Retail Scanner Data

Consumers rely on experience and credence attributes when purchasing beef from retailers. It is essential for all beef industry sectors to recognize the complexity of consumer buying behavior. A hedonic model is estimated to determine if there are incentives to brand beef steaks, the types of brands that entertain price premiums, and the level of existing premiums. Most branded steaks garnered premiums along with organic claims, religious processing claims, and premium cuts. Factors influencing brand value were new brands targeting emerging consumer trends, brands with regional prominence, and brands positioned as special label, program/breed specific production, and store labels

Spacelab Flight Operations

This paper will cover the primary activities involved in conducting Spacelab flight operations. Spacelab flight operations are characterized by a unique partnership between the operators of the Space Transportation System (STS) and the Mission Management organization. This partnership involves both the activities of the flight control personnel and the flight crew and must exist as an integrated team in order to be able to successfully complete a Spacelab flight. This paper will discuss an overview of how this partnership functions from the initial planning phase though the actual flight conduct. The responsibilities and functions of the flight crew members will be discussed as well as the make up of the flight control team. A typical flight scenario describing the basic operation of the Spacelab will be covered. A description of the Mission Control Center (MCC) and Payload Operations Control Center-(POCC) capabilities wiH be given

Identifying Significant Environmental Features Using Feature Recognition

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, including those relating to historic preservation, archaeology, endangered species habitat, and geology. LIDAR Analyst and Feature Analyst are a pair of geoprocessing software packages that have been developed by Textron Systems. Using this software, users can use LIDAR data to identify finely-scaled user-specified features. The software’s automated feature extraction saves time that might otherwise be spent manually analyzing images and digitizing features. This report explores the capabilities and accuracy of this software by using LIDAR data to identify sinkholes throughout a small area in Kentucky. This report also discusses an alternative LIDAR-based geoprocessing methodology developed by the Kentucky Geological Society. The method relies on ArcGIS and Python scripting to identify sinkholes. The feasibility and applicability of these methodologies are compared, the workflow for each method is outlined, and the capabilities and limitations of each are noted. Sample results—the identification of sinkholes—from each methodology are presented. The research team found the batch processing capability built into LIDAR and Feature Analyst adequate and beneficial for smaller projects, such as projects that prioritize the extraction of buildings, trees, and forest regions

Drivers and trajectories of resistance to new first-line drug regimens for tuberculosis.

BACKGROUND: New first-line drug regimens for treatment of tuberculosis (TB) are in clinical trials: emergence of resistance is a key concern. Because population-level data on resistance cannot be collected in advance, epidemiological models are important tools for understanding the drivers and dynamics of resistance before novel drug regimens are launched. METHODS: We developed a transmission model of TB after launch of a new drug regimen, defining drug-resistant TB (DR-TB) as resistance to the new regimen. The model is characterized by (1) the probability of acquiring resistance during treatment, (2) the transmission fitness of DR-TB relative to drug-susceptible TB (DS-TB), and (3) the probability of treatment success for DR-TB versus DS-TB. We evaluate the effect of each factor on future DR-TB prevalence, defined as the proportion of incident TB that is drug-resistant. RESULTS: Probability of acquired resistance was the strongest predictor of the DR-TB proportion in the first 5 years after the launch of a new drug regimen. Over a longer term, however, the DR-TB proportion was driven by the resistant population's transmission fitness and treatment success rates. Regardless of uncertainty in acquisition probability and transmission fitness, high levels (>10%) of drug resistance were unlikely to emerge within 50 years if, among all cases of TB that were detected, 85% of those with DR-TB could be appropriately diagnosed as such and then successfully treated. CONCLUSIONS: Short-term surveillance cannot predict long-term drug resistance trends after launch of novel first-line TB regimens. Ensuring high treatment success of drug-resistant TB through early diagnosis and appropriate second-line therapy can mitigate many epidemiological uncertainties and may substantially slow the emergence of drug-resistant TB

Modeling of Novel Diagnostic Strategies for Active Tuberculosis – A Systematic Review: Current Practices and Recommendations

Introduction: The field of diagnostics for active tuberculosis (TB) is rapidly developing. TB diagnostic modeling can help to inform policy makers and support complicated decisions on diagnostic strategy, with important budgetary implications. Demand for TB diagnostic modeling is likely to increase, and an evaluation of current practice is important. We aimed to systematically review all studies employing mathematical modeling to evaluate cost-effectiveness or epidemiological impact of novel diagnostic strategies for active TB. Methods: Pubmed, personal libraries and reference lists were searched to identify eligible papers. We extracted data on a wide variety of model structure, parameter choices, sensitivity analyses and study conclusions, which were discussed during a meeting of content experts. Results & Discussion From 5619 records a total of 36 papers were included in the analysis. Sixteen papers included population impact/transmission modeling, 5 were health systems models, and 24 included estimates of cost-effectiveness. Transmission and health systems models included specific structure to explore the importance of the diagnostic pathway (n = 4), key determinants of diagnostic delay (n = 5), operational context (n = 5), and the pre-diagnostic infectious period (n = 1). The majority of models implemented sensitivity analysis, although only 18 studies described multi-way sensitivity analysis of more than 2 parameters simultaneously. Among the models used to make cost-effectiveness estimates, most frequent diagnostic assays studied included Xpert MTB/RIF (n = 7), and alternative nucleic acid amplification tests (NAATs) (n = 4). Most (n = 16) of the cost-effectiveness models compared new assays to an existing baseline and generated an incremental cost-effectiveness ratio (ICER). Conclusion: Although models have addressed a small number of important issues, many decisions regarding implementation of TB diagnostics are being made without the full benefits of insight from mathematical models. Further models are needed that address a wider array of diagnostic and epidemiological settings, that explore the inherent uncertainty of models and that include additional epidemiological data on transmission implications of false-negative diagnosis and the pre-diagnostic period