Motivic integral of K3 surfaces over a non-archimedean field

We prove a formula expressing the motivic integral (\cite{ls}) of a K3 surface over \bC((t)) with semi-stable reduction in terms of the associated limit Hodge structure. Secondly, for every smooth variety over a non-archimedean field we define an analogue of the monodromy pairing, constructed by Grothendieck in the case of Abelian varieties, and prove that our monodromy pairing is a birational invariant of the variety. Finally, we propose a conjectural formula for the motivic integral of maximally degenerated K3 surfaces over an arbitrary non-archimedean field and prove this conjecture for Kummer K3 surfaces.Comment: Erratum adde

On the center of the ring of differential operators on a smooth variety over \bZ/p^n\bZ

We compute the center of the ring of PD differential operators on a smooth variety over \bZ/p^n\bZ confirming a conjecture of Kaledin. More generally, given an associative algebra $A_0$ over \bF_p and its flat deformation $A_n$ over \bZ/p^{n+1}\bZ we prove that under a certain non-degeneracy condition the center of $A_n$ is isomorphic to the ring of length $n+1$ Witt vectors over the center of $A_0$.Comment: 16 page

Increasing Software Reliability using Mutation Testing and Machine Learning

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. The goal of mutation testing was to reduce complex program errors by preventing the related simple errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This dissertation used machine learning for the selection of mutation operators that reduced the computational cost of testing and improved test suite effectiveness. The goals were to produce mutations that were more resistant to test cases, improve test case evaluation, validate then improve the test suite’s effectiveness, realize cost reductions by generating fewer mutations for testing and improving software reliability by detecting more errors. To accomplish these goals, experiments were conducted using sample programs to determine how well the reinforcement learning based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. One key result from this research was the development of a reinforcement algorithm to identify mutation operator combinations that resulted in live mutants. During experimentation, the reinforcement learning algorithm identified the optimal mutation operator selections for various programs and test suite scenarios, as well as determined that by using parallel processing and multiple cores the reinforcement learning process for mutation operator selection was practical. With reinforcement learning the mutation operators utilized were reduced by 50 – 100%.In conclusion, these improvements created a ‘live’ mutation testing process that evaluated various mutation operators and generated mutants to perform real-time mutation testing while dynamically prioritizing mutation operator recommendations. This has enhanced the software developer’s ability to improve testing processes. The contributions of this paper’s research supported the shift-left testing approach, where testing is performed earlier in the software development cycle when error resolution is less costly

An ecological assessment of neighborhood, family, peer, and individual characteristics in predicting violence: a multilevel analysis of African-American families

This study used epidemic, cultural deviance, and social learning perspectives to examine the extent to which exposure to various forms of violence predicted violent behavior among 867 African-American youth. The study examined the following macro-level predictors of childhood violence: neighborhood violence, neighborhood SES, neighborhood subculture of violence, and percent African American. The following micro-level predictors were examined: street code, associating with violent peers, corporal punishment, parental violence, and warm/supportive parenting. Using hierarchical linear modeling techniques (HLM), the results showed that neighborhood SES was the only macro-level variable to exert a significant influence on violence. Furthermore, childhood violence was significantly related to street code, violent peers, parental violent behavior, and warm/supportive parenting. Overall, the results indicated that micro-level variables explained 27% of the variance, and macro-level variables explained an additional 3%. These findings demonstrate the importance of micro-level factors in predicting violence. It was concluded that simply living in a violent neighborhood does not produce violent children, but that family, peer, and individual characteristics at the micro-level play a large role in predicting violence in children

The cartel system

https://stars.library.ucf.edu/prism/1176/thumbnail.jp

The Present Evil Age : The Origin and Persistence of Evil in Galatians

This dissertation investigates the origin and persistence of evil in Galatians within the context of Second Temple Judaism and early Christianity. The focus of investigation is narrative explanation(s) for evil. What story and/or stories were told to explain the original cause of evil and why it persists in the present? The study begins with a history of research that separates current scholarly accounts of Paul’s view of evil into two broad categories, Adamic template and Christological novum. According to the Adamic template, evil originates in Adam’s sin and persists in human rebellion in the likeness of the Protoplast. According to the Christological novum, Paul’s view of evil is merely a reflex of his Christology. My research challenges both categories.I make four claims about evil in Paul, Second Temple Judaism, and early Christianity. First, Paul’s argument in Galatians, especially Gal 3:19–4:11, is informed by Enochic tradition (chapters two and five). In Galatians Paul’s view of evil is based on the Enochic narrative of rebellious angels. Second, among first century Jews, Adamic and Enochic traditions were not separated as inherently incompatible narrative explanations of evil (chapter three). Jewish authors commonly cited multiple traditions to articulate their theology of evil, producing a mixed template. Third, the function of Adamic and Enochic traditions are determined by the contexts in which they appear (chapters three and four). Adamic tradition, for example, does not indicate that evil is an essentially human problem from start to finish that absolves God (chapter three). Likewise, Enochic tradition does not blame superhuman forces for evil and abdicate human responsibility (chapter four). These traditions do not conform to strict patterns of meaning in the ways that modern scholarship often assumes. Fourth, an Enochic reading of Galatians 3:19–4:11 is supported by the early reception of Paul (chapter six). Among second century Christian apologists, especially Justin Martyr, Paul’s arguments in Galatians are redeployed and explicitly combined with an Enochic narrative

The American Negro

https://stars.library.ucf.edu/prism/1837/thumbnail.jp

Caregivers\u27 Relationship Satisfaction and Perception of Competency as Predictors of Quality of Life for ALS Patients

In addition to the physiological impact of Amyotrophic Lateral Sclerosis (ALS), patients and spousal caregivers experience significant emotional and psychological reactions to the disease and its course. As there is no effective treatment and no cure for this debilitating, fatal neuromuscular disease, treatment should include psychological interventions to improve patients\u27 disease experience. External factors impacting psychological well-being of patients must be identified to allow for effective and relevant intervention. The current study examined the relationships between level of care provided to patients, caregivers\u27 relationship satisfaction, and caregivers\u27 perceived competence, and whether these factors predict patient quality of life (QOL). It was hypothesized that spousal caregivers\u27 satisfaction in their relationships with patients, as well as their competence as caregivers, would predict ALS patients\u27 QOL beyond level of care required and after various aspects of QOL (within five domains of functioning) were considered. Fifty three spousal ALS patient-caregiver dyads at a predominantly rural university hospital provided data during a multidisciplinary clinic. Caregivers completed the Dyadic Satisfaction Subscale of the Dyadic Adjustment Scale (DAS), Perceived Caregiving Competence Questionnaire, and Level of Care Index. Patients completed the McGill Quality of Life Questionnaire (MQOL), including the Single Item Scale (MSIS) to assess subjectively rated QOL. Correlational and hierarchical multiple regression analyses did not identify a predictive relationship between the hypothesized variables, but did indicate that patients\u27 total MQOL score predicted 32.5 percent of the variance in self-reported QOL, and was the best predictor of this patient variable, as assessed by the MSIS [F (1, 47) = 24.06, p \u3c .05]. This finding suggests that patients, when asked to do so subjectively, accurately represent their QOL, as assessed more indirectly and by varied experiences. Further, QOL is more broadly defined for patients than is solely represented by the MQOL, and not largely dependent on caregivers. Additional research is needed to more accurately understand factors contributing to ALS patients\u27 QOL and means to more precisely measure this construct. Future studies should aim to identify caregiver variables that may influence patient illness experience to justify additional intervention for both members of the spousal dyad in coping with ALS

Disarmament and the American economy: A symposium

https://stars.library.ucf.edu/prism/1229/thumbnail.jp

Perceived Effect of Personal Use of Managerial Workstations on Individual Productivity

The purpose of this research was to determine the extent of penetration of managerial workstations into the management ranks; and whether age, education and exposure to automation do affect perceptions and subsequent productivity gains from workstation utilization. Are the attitudes and beliefs of older managers the key factor in slowing progress in implementing change and reaping the benefits of productivity? Or, are companies failing in their implementation strategies and participative management approaches? A descriptive-survey design was utilized. The cover letter and three-page questionnaire were circulated to 490 companies in the five-county metropolitan Atlanta area. Represented in this sample was a cross section of public and private sector organizations. Variables addressed in the six hypotheses were: nature of workstation use; involvement in planning; perception of benefit to productivity; and preferred method of training. Data was entered into a data base for query manipulation. Statistical Package for the Social Sciences, (SPSS), software was utilized for analysis, using chi-square, Cramer\u27s V and correlation analysis. Findings support exposure to automation and the length of time the manager has been using the workstation in the daily setting, to be more influential than age. Communication with other workers via the workstation did not prove to be as strong a determinant of whether the manager perceived the workstation to be beneficial to his/her productivity. Fully supported was the positive effect of having the manager participate in the initial planning for implementation of automation. Self-study was the preferred method of training. Further research is needed on the effect of automation on decision-making and the most effective training strategies for this unique and critical population. Top managers cannot afford to ignore the value-added benefit potential to productivity afforded by managerial workstations