237 resultados para physical models
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Aim Physical activity (PA) patterns of retirement village residents were investigated using self-report and objective measures. Methods Residents (n = 323) from retirement villages in Perth, Australia, were surveyed on PA behaviour and various demographic, residency, health-related and mobility factors. Most participants wore accelerometers for 7 days. Retirement village managers (n = 32) were surveyed on village descriptive characteristics, including the provision of amenities and facilities. Logistic regression models examined village and resident characteristics associated with PA. Results Based on objective measurement, only 27.1% of participants were sufficiently active (n = 288). Walking was one of the most popular PA modes. Few village characteristics were associated with PA; however, villages located in more walkable neighbourhoods increased participants’ odds of transport walking. Travelling outside the village daily also increased PA odds. Conclusions Most residents were insufficiently active to gain health benefits. Considering individual and environmental factors, within the retirement village and neighbourhood settings, and associations with PA, warrants attention.
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Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.
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Aim To develop and psychometrically test the Barriers to Nurses’ use of Physical Assessment Scale. Background There is growing evidence of failure to recognise hospitalised patients at risk of clinical deterioration, in part due to inadequate physical assessment by nurses. Yet, little is known about the barriers to nurses’ use of physical assessment in the acute hospital setting and no validated scales have been published. Design Instrument development study. Method Scale development was based on a comprehensive literature review, focus groups, expert review and psychometric evaluation. The scale was administered to 434 acute care registered nurses working at a large Australian teaching hospital between June and July 2013. Psychometric analysis included factor analysis, model fit statistics and reliability testing. Results The final scale was reduced to 38 items representing seven factors, together accounting for 57.7% of the variance: (1) reliance on others and technology, (2) lack of time and interruptions, (3) ward culture, (4) lack of confidence, (5) lack of nursing role models, (6) lack of influence on patient care, and; (7) specialty area. Internal reliability ranged from .70 to .86. Conclusion Findings provide initial evidence for the validity and reliability of the Barriers to Nurses’ use of Physical Assessment Scale and point to the importance of understanding the organisational determinants of nurses’ assessment practices. The new scale has potential clinical and research applications to support nursing assessment in acute care settings.
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Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.
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Objective To evaluate a conceptual model linking parent physical activity (PA) orientations, parental support for PA, and PA behavior in preschool children. Methods Participants were 156 parent-child dyads from 13 child care centers in Queensland, Australia. Parents completed a questionnaire measuring parental PA, parental enjoyment of PA, perceived importance of PA, parental support for PA, parents' perceptions of competence, and child PA at home. MVPA while attending child care was measured via accelerometry. Data were collected between May and August of 2003. The relationships between the study variables and child PA were tested using observed variable path analysis. Results Parental PA and parents' perceptions of competence were positively associated with parental support for PA (β= 0.23 and 0.18, respectively, p<0.05). Parental support, in turn, was positively associated with child PA at home (β= 0.16, p<0.05), but not at child care (β= 0.01, p= 0.94). Parents' perceptions of competence was positively associated with both home-based and child care PA (β= 0.20 and 0.28, respectively, p<0.05). Conclusions Family-based interventions targeting preschoolers should include strategies to increase parental support for PA. Parents who perceive their child to have low physical competence should be encouraged to provide adequate support for PA. © 2009 Elsevier Inc.
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Background There are few theoretically derived questionnaires of physical activity determinants among youth, and the existing questionnaires have not been subjected to tests of factorial validity and invariance, The present study employed confirmatory factor analysis (CFA) to test the factorial validity and invariance of questionnaires designed to be unidimensional measures of attitudes, subjective norms, perceived behavioral control, and self-efficacy about physical activity. Methods Adolescent girls in eighth grade from two cohorts (N = 955 and 1,797) completed the questionnaires at baseline; participants from cohort 1 (N = 845) also completed the questionnaires in ninth grade (i.e., 1-year follow-up). Factorial validity and invariance were tested using CFA with full-information maximum likelihood estimation in AMOS 4.0, Initially, baseline data from cohort 1 were employed to test the fit and, when necessary, to modify the unidimensional models. The models were cross-validated using a multigroup analysis of factorial invariance on baseline data from cohorts 1 and 2, The models then were subjected to a longitudinal analysis of factorial invariance using baseline and follow-up data from cohort i, Results The CFAs supported the fit of unidimensional models to the four questionnaires, and the models were cross-validated, as indicated by evidence of multigroup factorial invariance, The models also possessed evidence of longitudinal factorial invariance. Conclusions Evidence was provided for the factorial validity and the invariance of the questionnaires designed to be unidimensional measures of attitudes, subjective norms, perceived behavioral control, and self-efficacy about physical activity among adolescent girls, (C) 2000 American Health Foundation and academic Press.
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This thesis investigates the use of building information models for access control and security applications in critical infrastructures and complex building environments. It examines current problems in security management for physical and logical access control and proposes novel solutions that exploit the detailed information available in building information models. The project was carried out as part of the Airports of the Future Project and the research was modelled based on real-world problems identified in collaboration with our industry partners in the project.
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A discrete agent-based model on a periodic lattice of arbitrary dimension is considered. Agents move to nearest-neighbor sites by a motility mechanism accounting for general interactions, which may include volume exclusion. The partial differential equation describing the average occupancy of the agent population is derived systematically. A diffusion equation arises for all types of interactions and is nonlinear except for the simplest interactions. In addition, multiple species of interacting subpopulations give rise to an advection-diffusion equation for each subpopulation. This work extends and generalizes previous specific results, providing a construction method for determining the transport coefficients in terms of a single conditional transition probability, which depends on the occupancy of sites in an influence region. These coefficients characterize the diffusion of agents in a crowded environment in biological and physical processes.
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Background Physical activity (PA) has a positive association with health-related quality of life (HRQL) in the general population. The association between PA and HRQL in those with poor mental health is less clear. Purpose To examine the concurrent and prospective dose-response relationships between total physical activity (TPA) and walking only with HRQL in women aged 50-55 with depressive symptoms in 2001. Methods Participants were 1904 women born in 1946-1951 who completed mailed surveys for the Australian Longitudinal Study on Women's Health in 2001, 2004, 2007 and 2010 and who, in 2001, reported depressive symptoms. At each time point, they reported their weekly minutes of walking, moderate PA, and vigorous PA. A summary TPA score was created that accounted for differences in energy expenditure among the three PA types. Mixed models were used to examine associations between TPA and HRQL (SF-36 component and subscale scores) and between walking and HRQL, for women who reported walking as their only PA. Analyses were conducted in 2013-2014. Results Concurrently, higher levels of TPA and walking were associated with better HRQL (p<0.05). The strongest associations were found for physical functioning, vitality, and social functioning subscales. In prospective models, associations were attenuated, yet compared with women doing no TPA or walking, women doing “sufficient” TPA or walking had significantly better HRQL over time for most SF-36 scales. Conclusions This study extends previous work by demonstrating trends between both TPA and walking and HRQL in women reporting depressive symptoms.
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Background Musculoskeletal conditions and insufficient physical activity have substantial personal and economic costs among contemporary aging societies. This study examined the age distribution, comorbid health conditions, body mass index (BMI), self-reported physical activity levels, and health-related quality of life of patients accessing ambulatory hospital clinics for musculoskeletal disorders. The study also investigated whether comorbidity, BMI, and self-reported physical activity were associated with patients’ health-related quality of life after adjusting for age as a potential confounder. Methods A cross-sectional survey was undertaken in three ambulatory hospital clinics for musculoskeletal disorders. Participants (n=224) reported their reason for referral, age, comorbid health conditions, BMI, physical activity levels (Active Australia Survey), and health-related quality of life (EQ-5D). Descriptive statistics and linear modeling were used to examine the associations between age, comorbidity, BMI, intensity and duration of physical activity, and health-related quality of life. Results The majority of patients (n=115, 51.3%) reported two or more comorbidities. In addition to other musculoskeletal conditions, common comorbidities included depression (n=41, 18.3%), hypertension (n=40, 17.9%), and diabetes (n=39, 17.4%). Approximately one-half of participants (n=110, 49.1%) self-reported insufficient physical activity to meet minimum recommended guidelines and 150 (67.0%) were overweight (n=56, 23.2%), obese (n=64, 28.6%), severely obese (n=16, 7.1%), or very severely obese (n=14, 6.3%), with a higher proportion of older patients affected. A generalized linear model indicated that, after adjusting for age, self-reported physical activity was positively associated (z=4.22, P<0.001), and comorbidities were negatively associated (z=-2.67, P<0.01) with patients’ health-related quality of life. Conclusion Older patients were more frequently affected by undesirable clinical attributes of comorbidity, obesity, and physical inactivity. However, findings from this investigation are compelling for the care of patients of all ages. Potential integration of physical activity behavior change or other effective lifestyle interventions into models of care for patients with musculoskeletal disorders is worthy of further investigation.
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We learn from the past that invasive species have caused tremendous damage to native species and serious disruption to agricultural industries. It is crucial for us to prevent this in the future. The first step of this process is to identify correctly an invasive species from native ones. Current identification methods, relying on mainly 2D images, can result in low accuracy and be time consuming. Such methods provide little help to a quarantine officer who has time constraints to response when on duty. To deal with this problem, we propose new solutions using 3D virtual models of insects. We explain how working with insects in the 3D domain can be much better than the 2D domain. We also describe how to create true-color 3D models of insects using an image-based 3D reconstruction method. This method is ideal for quarantine control and inspection tasks that involve the verification of a physical specimen against known invasive species. Finally we show that these insect models provide valuable material for other applications such as research, education, arts and entertainment. © 2013 IEEE.
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Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity - past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control. © 2014 Nguyen et al.
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Background Child sexual abuse is considered a modifiable risk factor for mental disorders across the life course. However the long-term consequences of other forms of child maltreatment have not yet been systematically examined. The aim of this study was to summarise the evidence relating to the possible relationship between child physical abuse, emotional abuse, and neglect, and subsequent mental and physical health outcomes. Methods and Findings A systematic review was conducted using the Medline, EMBASE, and PsycINFO electronic databases up to 26 June 2012. Published cohort, cross-sectional, and case-control studies that examined non-sexual child maltreatment as a risk factor for loss of health were included. All meta-analyses were based on quality-effects models. Out of 285 articles assessed for eligibility, 124 studies satisfied the pre-determined inclusion criteria for meta-analysis. Statistically significant associations were observed between physical abuse, emotional abuse, and neglect and depressive disorders (physical abuse [odds ratio (OR) = 1.54; 95% CI 1.16–2.04], emotional abuse [OR = 3.06; 95% CI 2.43–3.85], and neglect [OR = 2.11; 95% CI 1.61–2.77]); drug use (physical abuse [OR = 1.92; 95% CI 1.67–2.20], emotional abuse [OR = 1.41; 95% CI 1.11–1.79], and neglect [OR = 1.36; 95% CI 1.21–1.54]); suicide attempts (physical abuse [OR = 3.40; 95% CI 2.17–5.32], emotional abuse [OR = 3.37; 95% CI 2.44–4.67], and neglect [OR = 1.95; 95% CI 1.13–3.37]); and sexually transmitted infections and risky sexual behaviour (physical abuse [OR = 1.78; 95% CI 1.50–2.10], emotional abuse [OR = 1.75; 95% CI 1.49–2.04], and neglect [OR = 1.57; 95% CI 1.39–1.78]). Evidence for causality was assessed using Bradford Hill criteria. While suggestive evidence exists for a relationship between maltreatment and chronic diseases and lifestyle risk factors, more research is required to confirm these relationships. Conclusions This overview of the evidence suggests a causal relationship between non-sexual child maltreatment and a range of mental disorders, drug use, suicide attempts, sexually transmitted infections, and risky sexual behaviour. All forms of child maltreatment should be considered important risks to health with a sizeable impact on major contributors to the burden of disease in all parts of the world. The awareness of the serious long-term consequences of child maltreatment should encourage better identification of those at risk and the development of effective interventions to protect children from violence.
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Background Women with young children (<5 years) are an important group for physical activity intervention. Purpose To evaluate the feasibility, acceptability and efficacy of MobileMums- a physical activity intervention for women with young children. Methods Women were randomized to MobileMums (n=133) or a control group (n=130). MobileMums was delivered primarily via individually-tailored text messages. Moderate to vigorous physical activity (MVPA) was measured by self-report and accelerometer at baseline, end of the intervention (13-weeks) and 6-months later (9-months). Changes were analyzed using repeated measures models. Results MobileMums was feasible to deliver and acceptable to women. Self-reported MVPA duration (minutes/week) and frequency (days/week) increased significantly post intervention (13-week intervention effect 48.5 min/week, 95%CI [13.4, 82.9] and 1.6 days/week, 95%CI [0.6, 2.6]). Intervention effects were not maintained 6-months later. No effects observed in accelerometer-derived MVPA. Conclusions MobileMums increased women’s self-reported MVPA immediately post intervention. Future investigations need to target sustained physical activity improvements.