Effects of Switching Barriers on Satisfaction, Repurchase Intentions and Attitudinal Loyalty

The positive effect of customer satisfaction on repurchase intentions and attitudinal loyalty has been shown in numerous studies. The effect of switching barriers on these variables, however, has been subject to much less attention from researchers. In this study we propose that switching barriers can be seen as either positive or negative, and we examine their effects on customer satisfaction, repurchase intentions and attitudinal loyalty. A LISREL analysis of the empirical data shows that negative switching barriers have negative effects on customer satisfaction and attitudinal loyalty, but a positive effect on repurchase intentions. Positive switching barriers impinge positively on customer satisfaction, repurchase intentions and attitudinal loyalty.switching barriers; loyalty; satisfaction; repurchase intentions

Big Game Range Management

RANGE management has been generally considered in the past as the administration of domestic livestock grazing land. Only in recent years have big game species come definitely into the range management picture. On some areas they are now the main consideration in the plan of proper range management. Proper management of livestock range has to do essentially with maintaining a proper balance between forage and livestock so that the range will be kept at its maximum permanent production. This is also true of big game range management

How Poetry Saved Nostradamus From the Pope

I came across the work of Nostradamus as part of a curatorial team working with books housed in special collections. Instantly, I was intrigued by the background of the man who\u27s most enduring work is an attempt to calculate the events of the future based off the mathematics of astrology. Nostradamus was a doctor and astrologist living in France from 1503 to 1566. He wrote his first prophesies in 1550 after a visit to Italy sparked his interest in the occult. In order to keep his predictions from seeming to close to biblical prophecies, they were written using poetic forms.https://digitalcommons.usu.edu/fsrs2022/1069/thumbnail.jp

Predictive and Prescriptive Analytics for Minimizing the Cost of Recidivism

A problem faced by the United States is the ever increasing prison population. There are inmates serving long sentences, new inmates being sentenced for the first time, and those who have previously served prison sentences that reoffend. The third group and the reduction of recidivism are the focus this dissertation. It is estimated that over 80% of inmates released from prison will reoffend within the next ten years. Is there an optimal sentence length that reduces that chance of an ex-convict reoffending? Are there programs or opportunities that some inmates have while incarcerated that reduce the probability they will return to prison? Prison units in states such as Texas can afford inmates the opportunity to receive a high school education, job training, and sometimes work in positions that allow the inmate to acquire career skills for reentry into society. A few of these programs, such as the Texas Corrections Industries and work release, can earn money for not only the inmate but the state. Others help fulfill societal needs such as training service animals and picking up trash on the road side; however, many programs do not benefit the state in a direct monetary sense but can benefit the state by reducing the chance that inmates will reoffend once they are released. A general hypothesis for this research is that optimized sentencing, and spending on education and training of inmates will significantly reduce the overall cost to society. For the purpose of this dissertation, the term recidivism refers to re-incarceration after release from prison. This dissertation begins by comparing methods to predict recidivism including logistic regression and classification trees. Then, the second stage uses those results to minimize the overall cost of incarceration considering sentence lengths, opportunities provided to the inmate during their time in prison, and expected cost of possible future crimes. If education or training lowers the lifetime cost, then the final step assigns them to serve in one of the units which has the suggested program. Empirical analysis on the data resulted in logistic regression being one of the most accurate predictors of recidivism. When assessed on the test data subset the accuracy was near 75%. Two hundred thirteen of the inmate cohorts were sentenced to some education, the model predicts that education will save the Texas Department of Corrections over $1,585,000,000 over time

An Examination of External Influences Imbedded in the Historical Snow Data of Utah

Snowpack data collection has a long and storied history in Utah as well as the western United States. Many researchers use historical snow course data for various applications ranging from water supply forecasting to climate change. These data are far from a perfect data set and data users should know the errors and limitations within them. In the current setting, only those collecting the data have access to the raw data and the site biographical information. In Utah, records extend back to at least 1912. Systematic measurements began in the mid 1920\u27s with many long term snow courses established at that time. In an extremely fortuitous circumstance, Mr. George D. Clyde (former Governor of Utah) was responsible for the Snow Survey Program during the 1930\u27s in Utah and had foresight to document each existing Snow Course in the year 1936. Each site was meticulously mapped, described and most important, photographed from several angles. Comparisons are made between the 1936 photographs, maps and descriptions and current conditions, specifically with regard to vegetation and sample point location. General conclusions are made regarding the impact that vegetation change has had on snow accumulation at each course. Changes in sampling technique and data processing are documented, particularly with regard to sample density and the re-sampling (or lack thereof in the record up to the 1950\u27s) of individual sample points when density thresholds are exceeded. With the advent of weather modification programs, changes in snow accumulation could reasonably be expected. Utah began a relatively small test weather modification program in the 1950\u27s in central Utah. The Utah cloud seeding act was passed in 1973 and the seeding program has continued since that time. Snow Courses affected by this program are identified and the potential impact on historical data. Finally, recommendations for individual snow course suitability for long term study based on consistency are made for each of the courses examined. SNOTEL sites, the automated version of the snow courses began to be installed in the late 1970\u27s and early 1980\u27s. These sites to a lesser degree due to the shorter historical time of data collection, have been impacted by vegetation change as well. They also have data impacted by sensor changes and weather modification. Because snow course data are often used to extrapolate the SNOTEL data set to a longer time frame, it is important that external influences in this data set are quantified as well

Soil moisture data collection and water supply forecasting

Presented during the USCID water management conference held on October 13-16, 2004 in Salt Lake City, Utah. The theme of the conference was "Water rights and related water supply issues."Includes bibliographical references.Extreme deviations in hydroclimatic conditions are a source of considerable error in statistical water supply forecast models. Much attention has been given over the past years to the relationship between snowpack, precipitation and streamflow (Martinec, 1975, Hawley, et al. 1980, McCuen, 1993). These relationships tend to vary in strength, but in large part have been satisfactory for water supply forecasting purposes. Increased demands on water resources have led to crises in water management and ways are being sought to improve water supply forecasting. Many other hydroclimatic variables such as soil moisture are implicit in these statistical relationships. As long as these variables (soil moisture) remain proportional to the independent variables (snowpack, precipitation, etc.) in the forecasting relationship, then the model will be stable. If there is some amount of disproportion, then the model will most likely produce significant error. Such a case in northern Utah is presented with a limited database. The success of this instrumentation has led to a broader scale application with the goal of complete soil moisture and temperature sensor installations at all SNOTEL sites system wide. Currently, soil moisture data are being incorporated into water supply forecasting in an analog method with some success.Proceedings sponsored by the U.S. Department of the Interior, Central Utah Project Completion Act Office and the U.S. Committee on Irrigation and Drainage

Interview with Dr. Phyllis Perrin Wilcox: The Accreditation Process

Dr. Phyllis Perrin Wilcox, professor emerita, taught the first sign language class at the University of New Mexico (UNM) in 1971 when eight students were enrolled in a one-credit class. Many years and many students later, the University of New Mexico offers a Bachelor of Science in Signed Language Interpreting (SLI), and Dr. Wilcox headed the faculty as they sought accreditation by the Commission on Collegiate Interpreter Education (CCIE; see http://ccie-accreditation.org/). In this interview, Dr. Wilcox describes the experience of preparing for review and becoming accredited, as well as the impacts accreditation, has had on the program. Her insights and advice will help support other SLI programs considering CCIE accreditation. Anita Nelson-Julander, a graduate student in the Master’s Interpreting Pedagogy program at the University of North Florida, who has worked at the Sorenson VRS Interpreting Institute for 7 years, interviewed Dr. Wilcox

Broad Spectrum Antiviral Activity of Favipiravir (T-705): Protection from Highly Lethal Inhalational Rift Valley Fever

Background:Development of antiviral drugs that have broad-spectrum activity against a number of viral infections would be of significant benefit. Due to the evolution of resistance to currently licensed antiviral drugs, development of novel anti-influenza drugs is in progress, including Favipiravir (T-705), which is currently in human clinical trials. T-705 displays broad-spectrum in vitro activity against a number of viruses, including Rift Valley Fever virus (RVFV). RVF is an important neglected tropical disease that causes human, agricultural, and economic losses in endemic regions. RVF has the capacity to emerge in new locations and also presents a potential bioterrorism threat. In the current study, the in vivo efficacy of T-705 was evaluated in Wistar-Furth rats infected with the virulent ZH501 strain of RVFV by the aerosol route.Methodology/Principal Findings:Wistar-Furth rats are highly susceptible to a rapidly lethal disease after parenteral or inhalational exposure to the pathogenic ZH501 strain of RVFV. In the current study, two experiments were performed: a dose-determination study and a delayed-treatment study. In both experiments, all untreated control rats succumbed to disease. Out of 72 total rats infected with RVFV and treated with T-705, only 6 succumbed to disease. The remaining 66 rats (92%) survived lethal infection with no significant weight loss or fever. The 6 treated rats that succumbed survived significantly longer before succumbing to encephalitic disease.Conclusions/Significance:Currently, there are no licensed antiviral drugs for treating RVF. Here, T-705 showed remarkable efficacy in a highly lethal rat model of Rift Valley Fever, even when given up to 48 hours post-infection. This is the first study to show protection of rats infected with the pathogenic ZH501 strain of RVFV. Our data suggest that T-705 has potential to be a broad-spectrum antiviral drug. © 2014 Caroline et al

Health and behavioral findings with a Worksite Wellness Program

Participants (n=176) from three Midwest companies completed a worksite health risk appraisal (HRA). Mean age was 40 years (range 20-76) with fairly equal distribution by gender. Weight status was assessed by Bioelectrical Impedance Analysis (BIA), Body Mass Index (BMI), and waist-to-hip ratio (W-H Ratio) and categorized participants as underweight/low risk (N = 2 vs. 3 vs. 39, respectively); healthy/normal/moderate risk (28 vs. 35 vs. 61); overweight/high risk (45 vs. 57 vs. 44); and obese/very high risk (100 vs. 78 vs. 31), respectively. Categorization methods were significantly different (p Each method detected differences in four health status indicators (non-HDL, left and right flexibility, and MET scores) by weight category. Detection of differences in the remaining eight health status indicators (cholesterol, HDL, LDL, HDL/LDL ratio, triglycerides, glucose, diastolic blood pressure, and endurance) varied by weight categorization method. These differences also varied by gender. Results confirm previous findings that increasing adiposity negatively impacts health status indicators. Findings suggest the use of multiple body adiposity measures may be warranted to screen for various chronic diseases. Use of weight status measures should be tailored to gender, age, and disease risk; however, this topic should be further explored. Health risk appraisals (HRA) were conducted at three Midwest companies as part of a worksite wellness program (WWP). The HRA was comprised of a series of validated surveys regarding basic demographics, self-efficacy, dietary intake, and physical activity, anthropometrics, and biochemical measures. Employees (n = 105) ranged in age from 20-76 years (mean age = 40) with fairly equal distribution by gender. Employees at each worksite were randomly assigned to either the control (N = 47) or intervention group (N = 45) after completing the HRA. Increasing health care costs, concerns regarding employee productivity, and research suggesting a significant Return on Investment (ROI) drive the increasing employer interest in WWP\u27s. Onsite WWP\u27s can provide access to 65% of the adult population with targeted strategies to modify poor health behaviors. WWP\u27s have been shown to improve health status including increased self-efficacy. Self-efficacy is the belief of having control, knowledge, skills, capability, and surroundings conducive to achieving one\u27s goal. Higher self-efficacy has been linked to positive health behaviors: increased fruit, vegetable, fiber, and dairy intake along with increased activity, performance, weight loss, smoking cessation, lowered body mass index (BMI), as well as reduced dietary and saturated fat intake 131. Current findings suggest self-efficacy diminishes with age and increases with education level. Health status indicators were shown to vary by gender. Designing a program to control for outside factors and tailoring programming to gender, age, and education status may provide the foundation for significant improvements in self-efficacy and health behaviors. Findings suggest education has the strongest influence on self-efficacy which should be taken into account during program development