Development of a Laboratory Experiment to Simulate Upper-Stage Rocket Explosions

This report is a summary of the senior project entitled Development of a Laboratory Experiment to Simulate Upper-Stage Rocket Explosions. The goal of the experiment was to recreate a NASA experiment which used aluminum soft drink cans to approximate the shape of an Ariane third stage rocket. The cans were placed in a vacuum chamber and fired upon with a projectile from a light gas gun. The resulting debris was collected and analyzed allowing several conclusions to be made regarding the behavior or rocket breakups and the formation of space debris. In lieu of a light gas gun, energy drink cans, fitted with a one-way valve from a bicycle inner tube and filled with a hydrogen and oxygen mixture, are detonated with an Estes model rocket motor igniter. The cans were successfully detonated and aluminum debris was formed in a manner consistent with the predictions of the original experiment. This report describes in detail the preliminary experiments and testing leading to the development of the final apparatus and procedure implemented in the Aerospace Engineering Department’s Spacecraft Environment Laboratory

BRAF Mutation and Its Importance in Colorectal Cancer

BRAF mutation is seen in nearly one in ten patients with advanced colorectal cancer. Despite major improvements in survival for advanced colorectal cancer overall, patients with BRAF mutation continue to have a very poor prognosis often with median survival of less than 12 months. It is important for clinicians to be aware of this subgroup as the treatment approach should be different. Treatment options beyond standard chemotherapy are crucial to achieve better outcomes and the role of anti-EGFR therapy alone remains controversial. Current trials assessing combinations of molecular targeted agents have seen some promise. This chapter explores the background of BRAF mutation and current treatment strategies

A surface water flooding impact library for flood risk assessment

The growing demand for improved risk-based Surface Water Flooding (SWF) warning systems is evident in EU directives and in the UK Government’s Pitt Review of the 2007 summer floods. This paper presents a novel approach for collating receptor and vulnerability datasets via the concept of an Impact Library, developed by the Health and Safety Laboratory as a depository of pre-calculated impact information on SWF risk for use in a real-time SWF Hazard Impact Model (HIM). This has potential benefits for the Flood Forecasting Centre (FFC) as the organisation responsible for the issuing of flood guidance information for England and Wales. The SWF HIM takes a pixel-based approach to link probabilistic surface water runoff forecasts produced by CEH’s Grid-to-Grid hydrological model with Impact Library information to generate impact assessments. These are combined to estimate flood risk as a combination of impact severity and forecast likelihood, at 1km pixel level, and summarised for counties and local authorities. The SWF HIM takes advantage of recent advances in operational ensemble forecasting of rainfall by the Met Office and of SWF by the Environment Agency and CEH working together through the FFC. Results are presented for a case study event which affected the North East of England during 2012. The work has been developed through the UK’s Natural Hazards Partnership (NHP), a group of organisations gathered to provide information, research and analysis on natural hazards for civil contingencies, government and responders across the UK

MULTIVARIATE STATISTICAL ANALYSIS OF TERRESTRIAL INVERTEBRATE INDEX OF BIOTIC INTEGRITY

The Index of Biotic Integrity (IBI) is designed to measure the changes in ecological and environmental conditions as affected by human disturbances. In practice, the IBI is used in various ecological applications to detect divergence in biological integrity attributable to human actions. Last year during this conference, methodologies for developing an Avian Index of Biotic Integrity (A-IBI) were presented and discussed. The objective of this paper is to demonstrate the construction and statistical evaluation of a multi-metric terrestrial Invertebrate Index of Biotic Integrity (I-IBI) using the same multivariate statistical techniques. Canonical correlation analyses were utilized to select pertinent invertebrate metrics as impacted by vegetation and hydrology variables. The resulting invertebrate metrics were then ranked, according to a pre-specified scale of human disturbance, and the I-IBI scores were subsequently computed. The multivariate model, as well as the final I-IBI scores were statistically validated using independent temporal data sets. Furthermore, the sensitivity of I-IBI values was determined in order to access their reliability. The techniques are demonstrated using five years of invertebrate survey data collected from the terrestrial environments within the historic fifty-year floodplain of the Kootenai River in Northern Idaho

A Benefit-Cost Analysis of Tulsa Pre-K, Based on Effects on High School Graduation and College Attendance

This paper presents new benefit-cost estimates for the Tulsa universal preschool program. These calculations are based on estimated effects from previous papers of Tulsa pre-K on high school graduation rates and college attendance rates of students who were enrolled in kindergarten in Tulsa Public Schools in the fall of 2006. In this paper, educational effects from these prior papers are used to infer lifetime earnings effects and are compared with program costs. Our conservative estimates of earnings effects suggest that per pre-K participant, the present value of earnings effects in 2021 dollars is $25,533, compared with program costs of$9,628, for a benefit-cost ratio of 2.65. Compared to prior benefit-cost studies of Tulsa pre-K, this benefit-cost ratio is below what was predicted from Tulsa pre-K’s estimated effects on kindergarten test scores, but above what was predicted from Tulsa pre-K’s estimated effects on grade retention by ninth grade. This fading and recovery of predicted pre-K effects as children go through K–12 and then enter adulthood is consistent with prior research. It attests to the importance of the “soft skill” effects of pre-K and reminds us that short-term studies of pre-K provide useful information for public-policy decisions

MODELING DISPERSAL OF YELLOW STARTHISTLE IN THE CANYON GRASSLANDS OF NORTH CENTRAL IDAHO

Yellow starthistle is an invasive plant species that reduces productivity and plant diversity within the canyon grasslands of Idaho. Early detection of yellow starthistle and predicting its spread have important managerial implications that could greatly reduce the economic/environmental losses due to this weed. The spread of an invasive plant species depends on its ability to reproduce and disperse seed into new areas. Typically, information on the factors that directly affect a plant’s ability to reproduce and subsequently disperse seed is not available or difficult to obtain. Alternatively, topographic factors, such as slope and aspect as well as competitive correlates such as vegetation indices related to plant community biomass could be used to model plant survival and seed movement. In this research, several spatial network models incorporating these variables were considered for the prediction of yellow starthistle dispersal. Models will differed in their assessment of plant movement costs, which can be separated into two processes, survival to reproduction and seed dispersal. The candidate models were evaluated based on their predictive ability and biological relevance. Topographical variables, slope and aspect, were found to be significant contributors to yellow starthistle dispersal models, whereas vegetation indices did not improve the prediction process. The optimal model was applied to an area in central Idaho for predicting the dispersal of yellow starthistle in 1987 given a known 1981 infestation

Whole-genome sequencing shows that patient-to-patient transmission rarely accounts for acquisition of Staphylococcus aureus in an intensive care unit

BACKGROUND  Strategies to prevent Staphylococcus aureus infection in hospitals focus on patient-to-patient transmission. We used whole-genome sequencing to investigate the role of colonized patients as the source of new S. aureus acquisitions, and the reliability of identifying patient-to-patient transmission using the conventional approach of spa typing and overlapping patient stay. METHODS Over 14 months, all unselected patients admitted to an adult intensive care unit (ICU) were serially screened for S. aureus. All available isolates (n = 275) were spa typed and underwent whole-genome sequencing to investigate their relatedness at high resolution. RESULTS Staphylococcus aureus was carried by 185 of 1109 patients sampled within 24 hours of ICU admission (16.7%); 59 (5.3%) patients carried methicillin-resistant S. aureus (MRSA). Forty-four S. aureus (22 MRSA) acquisitions while on ICU were detected. Isolates were available for genetic analysis from 37 acquisitions. Whole-genome sequencing indicated that 7 of these 37 (18.9%) were transmissions from other colonized patients. Conventional methods (spa typing combined with overlapping patient stay) falsely identified 3 patient-to-patient transmissions (all MRSA) and failed to detect 2 acquisitions and 4 transmissions (2 MRSA). CONCLUSIONS Only a minority of S. aureus acquisitions can be explained by patient-to-patient transmission. Whole-genome sequencing provides the resolution to disprove transmission events indicated by conventional methods and also to reveal otherwise unsuspected transmission events. Whole-genome sequencing should replace conventional methods for detection of nosocomial S. aureus transmission

PREDICTION OF YELLOW STARTHISTLE SURVIVAL AND MOVEMENT OVER TIME AND SPACE

Yellow starthistle is a noxious weed that has become a serious plant pest with devastating impact on ranching operation and natural resources in western states. Early detection of yellow starthistle and predicting its spread has important managerial implications and greatly reduce the economic losses due to this weed. The dispersal of yellow starthistle consists of two main components, plant survival and seed movement. Resources and direct factors relating to these components are not typically available or are difficult to obtain. Alternatively, topographic factors, such as slope, aspect and elevation, are readily available and can be related to plant survival and seed movement. In this study, several GIS network models incorporating these topographic factors are considered for the prediction of yellow starthistle spread. The models differed in their assessment of the costs of movement derived from these factors. Models were evaluated based on their predictive ability and residual analysis. The optimal model gave an accurate estimate of the dispersal boundary for the study area. Further validation of the estimated model using an independent data set from a larger area also verified its predictive capability