480 research outputs found
Open Data and Big Data Programs in Local Government Policy Analysis
This paper examines the development of policy around the open data programs for local government. Through a literature review, a survey of large municipalities in Ontario, and in-depth interviews, the research attempts to identify if there are factors that ensure whether the policy development process is more likely to be implemented along with the program or if there is a lack of policy development as a result of it. The findings reveal a definite lack of policy development with the open data program, which is likely due to the challenge for policy makers to ensure appropriate access and privacy protection, as technology makes information more accessible, and there are also emerging social issues that result from different generational expectations and values
Economic analysis of current and potential Muscatine melon market
The Muscatine melon traditionally has been one of Iowa\u27s best known produce items. As the number of acres and producers decline, melon producers are looking for ways to make their product a more attractive economic production option, and place-based marketing may be helpful. Melon producers, however, need to ask themselves if they are willing to cooperatively develop and market a place-based product in order to achieve higher prices and profitability
Muscatine Melon: A Case Study of a Place-based Food in Iowa
This special project of the Leopold Center\u27s Marketing and Food Systems Initiative (2004-MSP09) looks at the 120-year history of melon production in southeast Iowa and potential for promotion
The Effect of University Marketing Efforts on Students’ Academic Decision-Making: An Empirical Study
This study examines the influence that university marketing tools focusing on certain demographics (i.e., gender and age) have on students’ academic decision-making. The marketing students sampled rated their decision-making process in regards to college selection, selection of a Business Administration major, and selection of an option within that Business Administration major. The findings indicate that university marketing efforts are more influential for younger students already enrolled regarding their choice of a college or school. Refined university outreach programs are necessary to better inform and direct students’ post-enrollment decision-making
Ethics in community nursing
The purpose of this theoretical paper is to explore the ethics in a community nursing. Nursing, a practice discipline recognizes caring, morals, and values as integral to the practice of all nurses. The ethical principles of beneficence, autonomy, advocacy, and social justice will be discussed from the lens of caring. Caring nursing theorists, such as Jean Watson, Ann Boykin, and Savina Schoenhofer, articulate the importance of understanding communities and individuals as whole and autonomous. These theorists and others challenge nursing to engage in a responsive, ethical and philosophical discourse when the community is viewed as autonomous
Child's play: Harnessing play and curiosity motives to improve child handwashing in a humanitarian setting.
In humanitarian emergency settings there is need for low cost and rapidly deployable interventions to protect vulnerable children, in- and out-of-school, from diarrhoeal diseases. Handwashing with soap can greatly reduce diarrhoea but interventions specifically targeting children's handwashing behaviour in humanitarian settings have not been tested. Traditional children's handwashing promotion interventions have been school-focused, resource-intensive and reliant on health-based messaging. However, recent research from non-humanitarian settings and targeting adults suggests that theory-based behaviour change interventions targeting specific motives may be more effective than traditional handwashing interventions. In this proof-of-concept study we test, for the first time, the distribution of a modified soap bar, designed to appeal to the motives of play and curiosity, in a household-level, rapidly deployable, handwashing promotion intervention for older children in a humanitarian setting - an internally displaced persons camp in Iraqi Kurdistan. Out of five total blocks within the camp, one was assigned to intervention and one to control. 40 households from each assigned block were then randomly chosen for inclusion in the study and the practice of handwashing with soap at key times was measured at baseline and four weeks after intervention delivery. Children in intervention households received transparent soaps with embedded toys, delivered within a short, fun, and interactive household session with minimal, non-health-based, messaging. The control group received plain soap delivered in a short standard, health-based, hygiene promotion session. At the 4-week follow-up, children in the intervention group were 4 times more likely to wash their hands with soap after key handwashing occasions than expected in the counterfactual (if there had been no intervention) based on the comparison to children in the control group (adjusted RR = 3.94, 95% CI 1.59-9.79). We show that distributing soaps with toys embedded inside, in a rapidly deployable intervention, can improve child handwashing behaviour in a humanitarian emergency context. Further studies are needed to determine the longer-term behavioural and health impact of such an intervention when delivered at a greater scale in a humanitarian context
Eating Smart and Moving More for Head Start: A Pilot Study
Our study examined the relationship between improved personal health behaviors of Head Start teachers’ and the promotion of positive health behaviors in their classroom. Thirty-three Head Start teachers across 7 centers received six 30-minute nutrition education lessons. Dietary intake, physical activity, and self-efficacy for promoting positive health behaviors in the classroom were measured at baseline and post-intervention. Significant improvements were observed for dietary intake and physical activity. Self-efficacy for promoting health behaviors in the classroom did not significantly improve. Additional education is needed to improve health promotion practices. Lessons learned contributed to program refinement. Implications for Extension are discussed
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Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.
How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing
Phase Transitions in Chemisorbed Systems
Contains reports on six research projects.Joint Services Electronics Program (Contract DAAG29-83-K-0003
Identifying Documents In-Scope of a Collection from Web Archives
Web archive data usually contains high-quality documents that are very useful
for creating specialized collections of documents, e.g., scientific digital
libraries and repositories of technical reports. In doing so, there is a
substantial need for automatic approaches that can distinguish the documents of
interest for a collection out of the huge number of documents collected by web
archiving institutions. In this paper, we explore different learning models and
feature representations to determine the best performing ones for identifying
the documents of interest from the web archived data. Specifically, we study
both machine learning and deep learning models and "bag of words" (BoW)
features extracted from the entire document or from specific portions of the
document, as well as structural features that capture the structure of
documents. We focus our evaluation on three datasets that we created from three
different Web archives. Our experimental results show that the BoW classifiers
that focus only on specific portions of the documents (rather than the full
text) outperform all compared methods on all three datasets.Comment: 10 page
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