83 resultados para Caesium 137, standard deviation


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The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

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The experiences of the loss reduction projects in electric power distribution companies (EPDCs) of Iran are presented. The loss reduction methods, which are proposed individually by 14 EPDCs, corresponding energy saving (ES), Investment costs (IC), and loss rate reductions are provided. In order to illustrate the effectiveness and performance of the loss reduction methods, three parameters are proposed as energy saving per investment costs (ESIC), energy saving per quantity (ESPQ), and investment costs per quantity (ICPQ). The overall ESIC of 14 EPDC as well as individual average and standard deviation of the EISC for each method is presented and compared. In addition, the average and standard deviation of the ESPQs and ICPQs for the loss reduction methods, individually, are provided and investigated. These parameters are useful for EPDCs that intend to reduce the electric losses in distribution networks as a benchmark and as a background in the planning purposes.

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This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

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Used frequently in food contact materials, bisphenol A (BPA) has been studied extensively in recent years, and ubiquitous exposure in the general population has been demonstrated worldwide. Characterising within- and between-individual variability of BPA concentrations is important for characterising exposure in biomonitoring studies, and this has been investigated previously in adults, but not in children. The aim of this study was to characterise the short-term variability of BPA in spot urine samples in young children. Children aged ≥2-<4 years (n = 25) were recruited from an existing cohort in Queensland Australia, and donated four spot urine samples each over a two day period. Samples were analysed for total BPA using isotope dilution online solid phase extraction-liquid chromatography-tandem mass spectrometry, and concentrations ranged from 0.53–74.5 ng/ml, with geometric mean and standard deviation of 2.70 ng/ml and 2.94 ng/ml, respectively. Sex and time of sample collection were not significant predictors of BPA concentration. The between-individual variability was approximately equal to the within-individual variability (ICC = 0.51), and this ICC is somewhat higher than previously reported literature values. This may be the result of physiological or behavioural differences between children and adults or of the relatively short exposure window assessed. Using a bootstrapping methodology, a single sample resulted in correct tertile classification approximately 70% of the time. This study suggests that single spot samples obtained from young children provide a reliable characterization of absolute and relative exposure over the short time window studied, but this may not hold true over longer timeframes.

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Perflurooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) have been used for a variety of applications including fluoropolymer processing, fire-fighting foams and surface treatments since the 1950s. Both PFOS and PFOA are polyfluoroalkyl chemicals (PFCs), man-made compounds that are persistent in the environment and humans; some PFCs have shown adverse effects in laboratory animals. Here we describe the application of a simple one compartment pharmacokinetic model to estimate total intakes of PFOA and PFOS for the general population of urban areas on the east coast of Australia. Key parameters for this model include the elimination rate constants and the volume of distribution within the body. A volume of distribution was calibrated for PFOA to a value of 170ml/kgbw using data from two communities in the United States where the residents' serum concentrations could be assumed to result primarily from a known and characterized source, drinking water contaminated with PFOA by a single fluoropolymer manufacturing facility. For PFOS, a value of 230ml/kgbw was used, based on adjustment of the PFOA value. Applying measured Australian serum data to the model gave mean+/-standard deviation intake estimates of PFOA of 1.6+/-0.3ng/kgbw/day for males and females >12years of age combined based on samples collected in 2002-2003 and 1.3+/-0.2ng/kg bw/day based on samples collected in 2006-2007. Mean intakes of PFOS were 2.7+/-0.5ng/kgbw/day for males and females >12years of age combined based on samples collected in 2002-2003, and 2.4+/-0.5ng/kgbw/day for the 2006-2007 samples. ANOVA analysis was run for PFOA intake and demonstrated significant differences by age group (p=0.03), sex (p=0.001) and date of collection (p<0.001). Estimated intake rates were highest in those aged >60years, higher in males compared to females, and higher in 2002-2003 compared to 2006-2007. The same results were seen for PFOS intake with significant differences by age group (p<0.001), sex (p=0.001) and date of collection (p=0.016).

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Introduction Older people recovering from cardiac events requiring an acute hospital admission may experience a decline in physical function limiting their ability to return home to their previous accommodation. Subacute inpatient rehabilitation therapies have potential to assist recovery of physical functioning. However, it is unknown whether age influences the length of stay or physical functioning at discharge from subacute inpatient rehabilitation for this population. Objectives This study examined the outcomes of a cohort of older patients recovering from a cardiac event requiring hospitalisation to investigate the association between age and physical function at discharge, as well as age and length of rehabilitation stay. Methods Participants included 145 consecutive inpatient admissions to a subacute geriatric assessment and rehabilitation unit with a cardiac condition as their primary reason for hospital admission. Participants were required to complete a multi-disciplinary physical functioning assessment within 72 hours of admission to the unit, and again within 72 hours prior to discharge from the unit. The primary outcome measure was the Functional Independence Measure motor score. Demographic and clinical information, including length of stay and discharge destination, were also recorded. Results A total n=126 (87%) participants, with a mean (standard deviation) age of 79 (10) years, had both assessments completed and were included in analyses. Participants who had passed away (n=4, 3%), or did not have both assessments completed per protocol were excluded from analyses. Discharge destinations included home (n=101, 80%), residential aged care (n=17, 13%) and another hospital (n=8, 6%). The (median, interquartile range) Functional Independence Measure motor score was higher at discharge (79, 71 to 84) than admission (61, 48 to 71); z=7.75 p<0.001. Age was not associated with Functional Independence Measure motor score at discharge (t= -0.18, p=0.86), or length of stay in the rehabilitation unit (t= -0.52, 0.60). Conclusion Any perception that age may be associated with longer lengths of stay and reduced physical function outcomes among patients with cardiac conditions admitted for subacute inpatient rehabilitation for older adults is not supported data from this investigation. Older age should not be considered a disincentive when considering the suitability of patients with cardiac diagnoses for this type of inpatient rehabilitation or their potential physical functioning outcome.

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Introduction The benefits of physical activity are established and numerous; not the least of which is reduced risk of negative cardiovascular events. While sedentary lifestyles are having negative impacts across populations, people with musculoskeletal disorders may face additional challenges to becoming physically active. Unfortunately, interventions in ambulatory hospital clinics for people with musculoskeletal disorders primarily focus on their presenting musculoskeletal complaint with cursory attention given to lifestyle risk factors; including physical inactivity. This missed opportunity is likely to have both personal costs for patients and economic costs for downstream healthcare funders. Objectives The objective of this study was to investigate the presence of obesity, diabetes, diagnosed cardiac conditions, and previous stroke (CVA) among insufficiently physically active patients accessing (non-surgical) ambulatory hospital clinics for musculoskeletal disorders to indicate whether a targeted risk-reducing intervention is warranted. Methods A sub-group analysis of patients (n=110) who self-reported undertaking insufficient physical activity level to meet national (Australian) minimum recommended guidelines was conducted. Responses to the Active Australia Survey were used to identify insufficiently active patients from a larger cohort study being undertaken across three (non-surgical) ambulatory hospital clinics for musculoskeletal disorders. Outcomes of interest included body mass index, Type-II diabetes, diagnosed cardiac conditions, previous CVA and patients’ current health-related quality of life (Euroqol-5D). Results The mean (standard deviation) age of inactive patients was 56 (14) years. Body mass index values indicated that n=80 (73%) were overweight n=26 (24%), or obese n=45 (49%). In addition to their presenting condition, a substantial number of patients reported comorbid diabetes n=23 (21%), hypertension n=25 (23%) or an existing heart condition n=14 (13%); 4 (3%) had previously experienced a CVA as well as other comorbid conditions. Health-related quality of life was also substantially impacted, with a mean (standard deviation) multi-attribute utility score of 0.51 (0.32). Conclusion A range of health conditions and risk factors for further negative health events, including cardiovascular complications, consistent with physically inactive lifestyles were evident. A targeted risk-reducing intervention is warranted for this high risk clinical group.

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This paper reports on the use of a local order measure to quantify the spatial ordering of a quantum dot array (QDA). By means of electron ground state energy analysis in a quantum dot pair, it is demonstrated that the length scale required for such a measure to characterize the opto-electronic properties of a QDA is of the order of a few QD radii. Therefore, as local order is the primary factor that affects the opto-electronic properties of an array of quantum dots of homogeneous size, this order was quantified through using the standard deviation of the nearest neighbor distances of the quantum dot ensemble. The local order measure is successfully applied to quantify spatial order in a range of experimentally synthesized and numerically generated arrays of nanoparticles. This measure is not limited to QDAs and has wide ranging applications in characterizing order in dense arrays of nanostructures.

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Due to significant increase in vehicular accident and traffic congestions, vehicle to vehicle (V2V) communication based on the intelligent transport system (ITS) was introduced. However, to carry out efficient design and implementation of a reliable vehicular communication systems,a deep knowledge of the propagation channel characteristics in different environments is crucial, in particular the Doppler and pathloss parameters. Therefore, this paper presents an empirical V2V channel characterization and measurement performed under realistic urban, suburban and highway driving conditions in Brisbane, Australia. Based on Lin Cheng statistical Doppler Model (LCDM), values for the RMS Doppler spread and coherence time due to time selective nature of V2V channels were presented. Also, based on Log-distance power law model, values for the mean pathloss exponent and the standard deviation of shadowing were reported for urban, suburban and highway environments. The V2V channel parameters can be useful to system designers for the purpose of evaluating, simulating and developing new protocols and systems.

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In this paper, we present a pathloss characterization for vehicle-to-vehicle (V2V) communications based on empirical data collected from extensive measurement campaign performed under line-of-sight (LOS), non-line-of-sight (NLOS) and varying traffic densities. The experiment was conducted in three different V2V propagation environments: highway, suburban and urban at 5.8GHz. We developed pathloss models for each of the three different V2V environments considered. Based on a log-distance power law model, the values for the pathloss exponent and the standard deviation of shadowing were reported. The average pathloss exponent ranges from 1.77 for highway, 1.68 for the urban to 1.53 for the suburban environment. The reported results can contribute to vehicular network (VANET) simulators and can be used by system designers to develop, evaluate and validate new protocols and system designs under realistic propagation conditions.

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Objectives: To develop a new measure of dysfunctional thoughts for family caregivers of people living with dementia. These thoughts can contribute to negative outcomes, but they may be modifiable. Method: A stepwise process was used to develop the Thoughts Questionnaire, commencing with item generation, concept mapping, and pilot testing in a sample of professional and nonprofessional caregivers of people with dementia (n = 18). Next, an independent sample of 35 family caregivers of people with dementia (30 female; M age = 64.30, standard deviation = 10.65) completed: (a) the Thoughts Questionnaire; (b) an existing measure of dysfunctional thoughts, the Dementia Thoughts Caregivers Questionnaire; and (c) separate validated measures of depressive symptoms, caregiver stress, and coping, respectively. Results: The level of agreement with dysfunctional thought statements from the Dementia Thoughts Caregivers Questionnaire and Thoughts Questionnaire was low. However, a small number of Thoughts Questionnaire statements were strongly endorsed by over 85% of the sample. Both dysfunctional thought measures had adequate reliability, but total scores were not significantly intercorrelated (r = .287, p = .095). Only the Thoughts Questionnaire was significantly, positively correlated with most caregiver stress measures. Thoughts Questionnaire items required a much lower reading level than the Dementia Thoughts Caregivers Questionnaire items. Discussion: This study provides preliminary data on a tool for assessing the negative role-related thoughts that family caregivers of people with dementia may experience. Given that these thoughts are implicated in depression but they may be modified, the capacity to identify dysfunctional thoughts may prove useful in caregiver support programs.

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The estimation of the critical gap has been an issue since the 1970s, when gap acceptance was introduced to evaluate the capacity of unsignalized intersections. The critical gap is the shortest gap that a driver is assumed to accept. A driver’s critical gap cannot be measured directly and a number of techniques have been developed to estimate the mean critical gaps of a sample of drivers. This paper reviews the ability of the Maximum Likelihood technique and the Probability Equilibrium Method to predict the mean and standard deviation of the critical gap with a simulation of 100 drivers, repeated 100 times for each flow condition. The Maximum Likelihood method gave consistent and unbiased estimates of the mean critical gap. Whereas the probability equilibrium method had a significant bias that was dependent on the flow in the priority stream. Both methods were reasonably consistent, although the Maximum Likelihood Method was slightly better. If drivers are inconsistent, then again the Maximum Likelihood method is superior. A criticism levelled at the Maximum Likelihood method is that a distribution of the critical gap has to be assumed. It was shown that this does not significantly affect its ability to predict the mean and standard deviation of the critical gaps. Finally, the Maximum Likelihood method can predict reasonable estimates with observations for 25 to 30 drivers. A spreadsheet procedure for using the Maximum Likelihood method is provided in this paper. The PEM can be improved if the maximum rejected gap is used.

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Purpose Musculoskeletal conditions can impair people’s ability to undertake physical activity as they age. The purpose of this qualitative study was to investigate perceived barriers and facilitators to undertaking physical activity reported by patients accessing ambulatory hospital clinics for musculoskeletal disorders. Patients and methods A questionnaire with open-ended items was administered to patients (n=217, 73.3% of 296 eligible) from three clinics providing ambulatory services for nonsurgical treatment of musculoskeletal disorders. The survey included questions to capture the clinical and demographic characteristics of the sample. It also comprised two open-ended questions requiring qualitative responses. The first asked the participant to describe factors that made physical activity more difficult, and the second asked which factors made it easier for them to be physically active. Participants’ responses to the two open-ended questions were read, coded, and thematically analyzed independently by two researchers, with a third researcher available to arbitrate any unresolved disagreement. Results The mean (standard deviation) age of participants was 53 (15) years; n=113 (52.1%) were male. A total of 112 (51.6%) participants reported having three or more health conditions; n=140 (64.5%) were classified as overweight or obese. Five overarching themes describing perceived barriers for undertaking physical activity were "health conditions", "time restrictions", "poor physical condition", "emotional, social, and psychological barriers", and "access to exercise opportunities". Perceived physical activity facilitators were also aligned under five themes, namely "improved health state", "social, emotional, and behavioral supports", "access to exercise environment", "opportunities for physical activities", and "time availability". Conclusion It was clear from the breadth of the data that meaningful supports and interventions must be multidimensional. They should have the capacity to address a variety of physical, functional, social, psychological, motivational, environmental, lifestyle, and other perceived barriers. It would appear that for such interventions to be effective, they should be flexible enough to address a variety of specific concerns.

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Objectives Shift workers are prone to obesity and associated co-morbidities such as diabetes and cardiovascular disease. Sleep restriction associated with shift work results in dramatic endocrine and metabolic effects that predispose shift workers to these adverse health consequences. While sleep restriction has been associated with increased caloric intake, food preference may also play a key role in weight gain associated with shift work. This study examined the impact of an overnight simulated night shift on food preference. Methods Sixteen participants [mean 20.1, standard deviation (SD) 1.4 years; 8 women] underwent a simulated night shift and control condition in a counterbalanced order. On the following morning, participants were provided an opportunity for breakfast that included high- and low-fat food options (mean 64.8% and 6.4% fat, respectively). Results Participants ate significantly more high-fat breakfast items after the simulated night shift than after the control condition [167.3, standard error of the mean (SEM 28.7) g versus 211.4 (SEM 35.6) g; P=0.012]. The preference for high-fat food was apparent among the majority of individuals following the simulated night shift (81%), but not for the control condition (31%). Shift work and control conditions did not differ, however, in the total amount of food or calories consumed. Conclusions A simulated night shift leads to preference for high-fat food during a subsequent breakfast opportunity. These results suggest that food choice may contribute to weight-related chronic health problems commonly seen among night shift workers.

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This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.