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Attitudes and Perceptions of Sex Offenders Amongst Rural Populationns
Get PDFThe current study aims to examine rural residents’ attitudes regarding sex offenders and their perceptions of the recidivism rates of these types of individuals. Data from qualitative interviews of rural Illinois residents (N=24) will be used. This archival data will be coded with NVivo software to determine the prevalence of certain responses indicating positive or negative attitudes as well as perceptions of both adult and juvenile recidivism rates. Through the examination and analyses of the coded data, this study will help determine what kind of attitudes rural residents in southern Illinois harbor towards sex offenders and how that may correlate with perceived recidivism rates of both adults and juveniles with sex offenses
Neural Activation Patterns during Socially Transmitted Aggression
Get PDFChildren who experience abuse or witness it are at an elevated risk of becoming either victims themselves or engaging in violent behavior later in life, possibly due to the observed behavior of the abuser or the abused. However, socially transmitted aggression remains understudied due to the absence of a suitable behavioral paradigm. This study addresses this gap by introducing a novel social transmission paradigm combined with fiber photometry to explore the brain regions implicated in socially transmitted aggression in mice, given the conservation of their circuity and impact on aggressive behavior. This study addresses this gap by introducing a novel social transmission paradigm combined with fiber photometry to explore the brain regions implicated in socially transmitted aggression in mice. It was imperative to acquire an in-depth comprehension of aggression models utilized in preceding investigations. A thorough examination of multiple publications in the Morris Library database focusing on socially transmitted aggression and early-life stress, specifically employing fiber photometry techniques, was conducted. This literature review facilitated the formulation of a robust model to attain the anticipated outcomes. Notably, the database encompassed articles previously disseminated by the Nordman Lab, serving as pivotal resources for elucidating social transmission models utilized in their prior research. This comprehension was instrumental in devising an animal model capable of representing the nuances of human experiences after instances of aggression and abuse. Through utilization of the resources offered by the Morris Library database, we adeptly devised a rodent model to execute the project with optimal efficiency and effectiveness
Ready, Set, Train!: Strategies to Incorporate Self-directed and Embodied Learning into Training and Development Programs
Get PDFOffering training and development programs to employees is one strategy to help companies maintain a competitive advantage in industry. In order to be beneficial for employees and companies, training and development programs must be effective. Learning activities are one strategy to incorporate into training and development programs to keep participants engaged. This article highlights how the adult learning theories of self-directed learning and embodied learning can be incorporated into training and development programs. An overview of self-directed learning and embodied learning theories and examples of related learning activities are highlighted that could be incorporated into other training programs and curriculums
Cognitive Impairment in the Primary Care Clinic.
Get PDFCognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment
Alignments and Tree files for Mexican Gyrinicola Description
No full textThis data set contains the .tree and .nxs files used for the phylogenetic inference portion of a paper for submission
Genetic Distance Matrices for Mexican Gyrinicola Description
No full textThe data set contains .csv files for a paper describing various Gyrinicola for future publication
Rural Elementary Teachers’ Perceptions of STEM Education Following STEM Kits Intervention
No full textThis study served to enhance STEM education in rural areas elementary classrooms, where schools often contend with limited resources. The literature called attention to a gap in students not exposed to STEM instruction until they reached secondary school. This gap was revealed in the literature to show a decline in students pursuing a career in STEM fields. This action research study was carried out using a theory of change approach and was viewed via the constructivist lens. The data was collected by having elementary teachers complete a questionnaire after integrating STEM lesson kits in their classrooms throughout the intervention. Findings showed that students who received early STEM instruction in elementary school developed an early interest in the subject and went on to continue STEM throughout their education and pursue professions in those disciplines. These findings have implications that elementary teachers may teach STEM education in the classroom and see success and excellence in their students’ academic areas if given practical hands-on materials and a mentor to guide them. The STEM lesson kits are the essential resources for this research, but resources alone cannot educate, mentorship is required to complement the kits. This dissertation suggests that STEM education become part of elementary school curricula aligned with Next Generation Science Standards (NGSS) and that appropriate mentors be available to teachers
Occupational Stressors and Their Moderators in the Academic Research Workforce
No full textRecent literature regarding occupational stress in higher education has predominantly focused on students or student-facing activities such as teaching and advising, overlooking stress in research creation, research production, and research administration. Guided by the Job Demands-Resources model and Organizational Support theory, this dissertation used a mixed methods approach to address this gap through an examination of stressors and stress moderators among U.S. tenure-track faculty, tenured faculty, and university research administrators. Results from this dissertation study showed that members of the academic research workforce encounter a variety of occupational stressors that impact their job performance and overall well-being. Quantitative results revealed a link between perceived occupational support and perceived organizational support and that perceived stress was highest among early career faculty members. Qualitative results identified operational intensity, organizational complexity, negative workplace climates (such as bullying, racism, and sexism), and interpersonal factors as job demand stressors. Identified job resources that moderated stress included institutional support, social resources, talent management, and well-being resources. These findings suggest that institutions can enhance employee well-being and research creation, production, and administration through implementation of support systems that facilitate positive work climates
Comparison of Conventional Methods to Multiwell Microfluidic Device for Rapid Antibiotic Susceptibility Testing
No full textAntibiotic resistance in bacteria is currently one of the greatest threats to health and safety. Antibiotic-resistant infections are on the rise due to the overuse and misuse of antibiotics, allowing for more bacteria to gain resistance to them. Antimicrobial susceptibility testing (AST) determines the minimum amount of antibiotic the bacteria is susceptible to, but this process can take days to provide results. A solution to this problem would be rapid AST methods that could provide clinicians with results in a timely manner which would allow for personalized antibiotic treatment strategies during the patient’s visit. Microfluidic devices have been proposed to be a viable alternative, allowing for the bacteria to be captured, monitored, and analyzed at the single-cell level. In this thesis, a microfluidic device is designed and developed to implement single-cell analysis. This allows for the measurement of bacterial growth in response to the applied antibiotics and the quantification of the bacterial resistance profiles within a few cell cycles, all in a period of hours. This prototype device is evaluated by testing the antibiotic resistance of Escherichia coli (E. coli), a commonly found urinary tract infection agent, in response to first-line antibiotics. The results obtained from the microfluidic device correspond with the standard broth microdilution method, suggesting its clinical feasibility. Finally, the future development directions are discussed to improve the device design and possibly facilitate its deployment in the future
PREDICTING YOLO MISDETECTION USING FEATURE MAP ACTIVATIONS
No full textThis research proposes a novel method to identify the YOLO object detection network failures. The proposed method employs a secondary neural network to predict misdetections (localization and classification error) based on the features extracted from the YOLO network. Moreover, to make the secondary network lightweight by selecting important features for a target class, a recursive feature elimination-based method is proposed. As a result, the computational cost is reduced without compromising the accuracy. Four of the most frequently occurring classes in the COCO dataset were taken into consideration when training the secondary network for the experimental evaluation. When a single class was taken into consideration, the proposed failure detection approach attained an accuracy of 89.79%; this is a 16% improvement in accuracy over the existing method. A 52% reduction in inference time and an accuracy of 88.90% were obtained with the feature selection approach. Additionally, the proposed failure detection framework was assessed by taking into account several classes at once, and excellent accuracy was noted