Concluding Reflection: \u27Where Do We Go From Here?\u27

Women and Men in Theological Education

Development of an innovative technology based youth passenger safety program - an evidence-based approach

Young drivers are overrepresented in motor vehicle crash rates, and their risk increases when carrying similar aged passengers. Graduated Driver Licensing strategies have demonstrated effectiveness in reducing fatalities among young drivers, however complementary approaches may further reduce crash rates. Previous studies conducted by the researchers have shown that there is considerable potential for a passenger focus in youth road safety interventions, particularly involving the encouragement of young passengers to intervene in their peers’ risky driving (Buckley, Chapman, Sheehan & Davidson, 2012). Additionally, this research has shown that technology-based applications may be a promising means of delivering passenger safety messages, particularly as young people are increasingly accessing web-based and mobile technologies. This research describes the participatory design process undertaken to develop a web-based road safety program, and involves feasibility testing of storyboards for a youth passenger safety application. Storyboards and framework web-based materials were initially developed for a passenger safety program, using the results of previous studies involving online and school-based surveys with young people. Focus groups were then conducted with 8 school staff and 30 senior school students at one public high school in the Australian Capital Territory. Young people were asked about the situations in which passengers may feel unsafe and potential strategies for intervening in their peers’ risky driving. Students were also shown the storyboards and framework web-based material and were asked to comment on design and content issues. Teachers were also shown the material and asked about their perceptions of program design and feasibility. The focus group data will be used as part of the participatory design process, in further developing the passenger safety program. This research describes an evidence-based approach to the development of a web-based application for youth passenger safety. The findings of this research and resulting technology will have important implications for the road safety education of senior high school students

A study of selected families to determine their knowledge and their use of existing public health nursing services

Thesis (M.S.)--Boston Universit

Alien Registration- Sheehan, Mary (Waterville, Kennebec County)

https://digitalmaine.com/alien_docs/15123/thumbnail.jp

Modulation of cardiac muscle contractility by phosphorylation, HCM and DCM causing mutations and small molecules

Mutations in sarcomeric proteins that cause familial hypertrophic cardiomyopathy and dilated cardiomyopathy have been shown to abolish the coupled relationship between troponin I phosphorylation and myofilament Ca2+-sensitivity, a phenomenon referred to as uncoupling. In normal heart, PKA phosphorylation of troponin I Ser22 and 23 leads to a 2-fold decrease in Ca2+-sensitivity and a corresponding increase in the rate of Ca2+ release from TnC and is essential for the lusitropic response to adrenergic stimulation. Therefore, uncoupling results in a blunted response to β1-adrenergic activation and has been demonstrated in animal models with hypertrophic cardiomyopathy and dilated cardiomyopathy mutations at a cellular, tissue and whole animal level. However, the molecular mechanisms and physiological relevance of uncoupling as a common phenomenon in cardiomyopathy-associated sarcomeric mutations are not well-understood. In this study, I have employed a multidisciplinary approach to probe for the presence of troponin uncoupling in mutation-containing cardiomyopathy models at an atomistic, molecular and cellular level. I have employed molecular dynamics simulation to elucidate how the structure and dynamics of troponin can give rise to physiological properties of cardiomyopathy. Additionally, I have investigated small molecules analogues of EGCG and silybin for recoupling properties that can restore the abolished relationship between troponin I phosphorylation and myofilament Ca2+-sensitivity in vitro, identifying a number of promising recoupling agents via in vitro motility assay. Moreover, I have demonstrated uncoupling at the cellular level as a blunting of the time to relaxation in intact cardiomyocytes following β-adrenergic stimulation and have developed a methodology that is capable of distinguishing cellularly-active recoupling molecules from candidates that are toxic. I have identified two promising recoupling agents, silybin B and resveratrol, using the contractile study presented herein, demonstrated by a reversal of the blunted phenotype. My investigation has demonstrated the feasibility of small molecules as recoupling agents and their therapeutic potential.Open Acces

Collaborating for Better Outcomes: Exploring the Link Between Nurse-Nurse Collaboration and Nurse Job Satisfaction

As Registered Nurses (RNs) are crucial to delivering care, it is important to determine the factors which contribute to a healthy work environment for nurses and positive outcomes for patients. Past research has focused on the benefits of nurse-physician collaboration including improved nurse/ patient satisfaction and lower patient mortality. The few studies which have explored nurse-nurse collaboration have linked it with positive outcomes. To determine whether there is a relationship between nurse-nurse collaboration and nurse job satisfaction in the hospital setting, this correlational study involved a convenience/ snowball sample of RNs working in hospitals, who completed the two study instruments (Dougherty-Larson Nurse-Nurse Collaboration Instrument [DLNNCI] and McCloskey Mueller Satisfaction Scale [MMSS]). The results indicated a significant, positive correlation between nurse-nurse collaboration and nurse job satisfaction (r = .569, p<.01). Collaboration between nurses is associated with nurse job satisfaction and may contribute to the development of a healthy work environmen

Unifying metric approach to the triple parity

AbstractThe even-odd parity problem is a tough one for neural networks to handle because they assume a finite dimensional vector space. Typically, the size of the neural network increases as the size of the problem increases. The triple parity problem is even tougher. In this paper, a method is proposed for supervised and unsupervised learning to classify bit strings of arbitrary length in terms of their triple parity. The learner is modeled by two formal concepts, transformation system and stability optimization. Even though a small set of short examples were used in the training stage, all bit strings of any length were classified correctly in the online recognition stage. The proposed learner has successfully learned to devise a way by means of metric calculations to classify bit strings of any length according to their triple parity. The system was able to acquire the concept of counting, dividing, and then taking the remainder, by autonomously evolving a set of string-editing rules along with their appropriate weights to solve the difficult problem

Assessing Crash Risks on Curves

In Queensland, curve related crashes contributed to 63.44% of fatalities, and 25.17% required hospitalisation. In addition, 51.1% of run-off-road crashes occurred on obscured or open-view road curves (Queensland Transport, 2006). This paper presents a conceptual framework for an in-vehicle system, which assesses crash risk when a driver is manoeuvring on a curve. Our approach consists of using Intelligent Transport Systems (ITS) to collect information about the driving context. The driving context corresponds to information about the environment, driver, and vehicle gathered from sensor technology. Sensors are useful to detect drivers’ high-risk situations such as curves, fogs, drivers’ fatigue or slippery roads. However, sensors can be unreliable, and therefore the information gathered from them can be incomplete or inaccurate. In order to improve the accuracy, a system is built to perform information fusion from past and current driving information. The integrated information is analysed using ubiquitous data mining techniques and the results are later used in a Coupled Hidden Markov Model (CHMM), to learn and classify the information into different risk categories. CHMM is used to predict the probability of crash on curves. Based on the risk assessment, our system provides appropriate intervention to the driver. This approach could allow the driver to have sufficient time to react promptly. Hence, this could potentially promote safe driving and decrease curve related injuries and fatalities

Leveraging Epidemiology to Improve Risk Assessment.

The field of environmental public health is at an important crossroad. Our current biomonitoring efforts document widespread exposure to a host of chemicals for which toxicity information is lacking. At the same time, advances in the fields of genomics, proteomics, metabolomics, genetics and epigenetics are yielding volumes of data at a rapid pace. Our ability to detect chemicals in biological and environmental media has far outpaced our ability to interpret their health relevance, and as a result, the environmental risk paradigm, in its current state, is antiquated and ill-equipped to make the best use of these new data. In light of new scientific developments and the pressing need to characterize the public health burdens of chemicals, it is imperative to reinvigorate the use of environmental epidemiology in chemical risk assessment. Two case studies of chemical assessments from the Environmental Protection Agency Integrated Risk Information System database are presented to illustrate opportunities where epidemiologic data could have been used in place of experimental animal data in dose-response assessment, or where different approaches, techniques, or studies could have been employed to better utilize existing epidemiologic evidence. Based on the case studies and what can be learned from recent scientific advances and improved approaches to utilizing human data for dose-response estimation, recommendations are provided for the disciplines of epidemiology and risk assessment for enhancing the role of epidemiologic data in hazard identification and dose-response assessment