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Driving on an approach to a signalized intersection while distracted is relatively risky, as potential vehicular conflicts and resulting angle collisions tend to be relatively more severe compared to other locations. Given the prevalence and importance of this particular scenario, the objective of this study was to examine the decisions and actions of distracted drivers during the onset of yellow lights. Driving simulator data were obtained from a sample of 69 drivers under baseline and handheld cell phone conditions at the University of Iowa – National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examinations have been conducted from a traditional regression-based approach, which do not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that the probability of yellow light running increases with the increase in driving speed at the onset of yellow. Both young (18–25 years) and middle-aged (30–45 years) drivers reveal reduced propensity for yellow light running whilst distracted across the entire speed range, exhibiting possible risk compensation during this critical driving situation. The propensity for yellow light running for both distracted male and female older (50–60 years) drivers is significantly higher. Driver experience captured by age interacts with distraction, resulting in their combined effect having slower physiological response and being distracted particularly risky.

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The LiteSteel beam (LSB) is a cold-formed high strength steel channel section made of two torsionally rigid closed flanges and a slender web. Due to its mono-symmetric characteristics, its centroid and shear centre do not coincide. The LSBs can be used in floor systems as joists or bearers and in these applications they are often subjected to transverse loads that are applied away from the shear centre. Hence they are often subjected to combined bending and torsion actions. Previous researches on LSBs have concentrated on their bending or shear behaviour and strengths, and only limited research has been undertaken on their combined bending and torsion behaviour. Therefore in this research a series of nine experiments was first conducted on LSBs subject to combined bending and torsion. Three LSB sections were tested to failure under eccentric loading at mid-span, and appropriate results were obtained from seven tests. A special test rig was used to simulate two different eccentricities and to provide accurate simple boundary conditions at the supports. Finite element models of tested LSBs were developed using ANSYS, and the ultimate strengths, failure modes, and load–displacement curves were obtained and compared with corresponding test results. Finite element analyses agreed well with test results and hence the developed models were used in a parametric study to investigate the effects of load locations, eccentricities, and spans on the combined bending and torsion behaviour of LSBs. The interaction between the ultimate bending and torsional moment capacities was studied and a simple design rule was proposed. This paper presents the details of the tests, finite element analyses, and parametric study of LSBs subject to combined bending and torsion, and the results.

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Ankylosing spondylitis (AS) is a common inflammatory arthritis predominantly affecting the axial skeleton. Susceptibility to the disease is thought to be oligogenic. To identify the genes involved, we have performed a genomewide scan in 185 families containing 255 affected sibling pairs. Two-point and multipoint nonparametric linkage analysis was performed. Regions were identified showing "suggestive" or stronger linkage with the disease on chromosomes 1p, 2q, 6p, 9q, 10q, 16q, and 19q. The MHC locus was identified as encoding the greatest component of susceptibility, with an overall LOD score of 15.6. The strongest non-MHC linkage lies on chromosome 16q (overall LOD score 4.7). These results strongly support the presence of non-MHC genetic-susceptibility factors in AS and point to their likely locations.

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Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

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The social economy as a regional development actor is gaining greater attention given its purported ability to address social and environmental problems. This growth in interest is occurring within a global environment that is calling for a more holistic understanding of development compared to traditionally economic-centric conceptions. While regional development policies and practices have long considered for-profit businesses as agents for regional growth, there is a relatively limited understanding of the role of the social economy as a development actor. The institutional environment is a large determinant of all kinds of entrepreneurial activity, and therefore understanding the relationships between the social economy and broader regional development processes is warranted. This paper moves beyond suggestions of an economic-centric focus of regional development by utilising institutional logics as a theoretical framework for understanding the role of social enterprise in regional development. A multiple case study of ten social enterprises in two regional locations in Australia suggests that social enterprise can represent competing logics to economic-centric institutional values and systems. The paper argues that dominant institutional logics can constrain or promote the inter-play between the social and the economic aspects of development, in the context of social enterprise.

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Background Resources to help the older aged (≥65 year olds) manage their medicines should probably target those in greatest need. The older-aged have many different types of living circumstances. There are different locations (urban, rural), different types of housing (in the community or in retirement villages), different living arrangements (living alone or with others), and different socioeconomic status (SES) circumstances. However, there has been limited attention to whether these living circumstances affect adherence to medicines in the ≥65 year olds. Aim of the review The aim was to determine whether comparative studies, including logistic regression studies, show that living circumstances affect adherence to medicines by the ≥65 year olds. Methods A literature search of Medline, CINAHL and the Internet (Google) was undertaken. Results Four comparative studies have not shown differences in adherence to medicines between the ≥65 year olds living in rural and urban locations, but one study shows lower adherence to medicines for osteoporosis in rural areas compared to metropolitan, and another study shows greater adherence to antihypertensive medicines in rural than urban areas. There are no comparative studies of adherence to medicines in the older-aged living in indigenous communities compared to other communities. There is conflicting evidence as to whether living alone, being unmarried, or having a low income/worth is associated with nonadherence. Preliminary studies have suggested that the older-aged living in rental, low SES retirement villages or leasehold, middle SES retirement villages have a lower adherence to medicines than those living in freehold, high SES retirement villages. Conclusions The ≥65 year olds living in rural communities may need extra help with adherence to medicines for osteoporosis. The ≥65 year olds living in rental or leasehold retirement villages may require extra assistance/resources to adhere to their medicines. Further research is needed to clarify whether living under certain living circumstances (e.g. living alone, being unmarried, low income) has an effect on adherence, and to determine whether the ≥65 year olds living in indigenous communities need assistance to be adherent to prescribed medicines.

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PURPOSE: To compare pressures generated by 2 different cement pressurisers at various locations in the proximal femur. METHODS: Two groups of 5 synthetic femurs were used, and 6 pressure sensors were placed in the femur at 20-mm intervals proximally to distally. Cement was filled into the femoral canal retrogradely using a cement gun with either the half-moon pressuriser or the femoral canal pressuriser. Maximum pressures and pressure time integrals (cumulative pressure over time) of the 2 pressurisers were compared. RESULTS: At all sensors, the half-moon pressuriser produced higher maximum pressures and pressure time integrals than the femoral canal pressuriser, but the difference was significant only at sensor 1 (proximal femur). This may result in reduced cement interdigitation in the proximal femur. CONCLUSION: The half-moon pressuriser produced higher maximum cementation pressures and pressure time integrals than the femoral canal pressuriser in the proximal femur region, which is critical for rotational stability of the implant and prevention of implant fracture. KEYWORDS: arthroplasty, replacement, hip; bone cements; femur

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Background Bloodstream infections resulting from intravascular catheters (catheter-BSI) in critical care increase patients' length of stay, morbidity and mortality, and the management of these infections and their complications has been estimated to cost the NHS annually £19.1–36.2M. Catheter-BSI are thought to be largely preventable using educational interventions, but guidance as to which types of intervention might be most clinically effective is lacking. Objective To assess the effectiveness and cost-effectiveness of educational interventions for preventing catheter-BSI in critical care units in England. Data sources Sixteen electronic bibliographic databases – including MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, Cumulative Index to Nursing and Allied Health Literature (CINAHL), NHS Economic Evaluation Database (NHS EED), EMBASE and The Cochrane Library databases – were searched from database inception to February 2011, with searches updated in March 2012. Bibliographies of systematic reviews and related papers were screened and experts contacted to identify any additional references. Review methods References were screened independently by two reviewers using a priori selection criteria. A descriptive map was created to summarise the characteristics of relevant studies. Further selection criteria developed in consultation with the project Advisory Group were used to prioritise a subset of studies relevant to NHS practice and policy for systematic review. A decision-analytic economic model was developed to investigate the cost-effectiveness of educational interventions for preventing catheter-BSI. Results Seventy-four studies were included in the descriptive map, of which 24 were prioritised for systematic review. Studies have predominantly been conducted in the USA, using single-cohort before-and-after study designs. Diverse types of educational intervention appear effective at reducing the incidence density of catheter-BSI (risk ratios statistically significantly < 1.0), but single lectures were not effective. The economic model showed that implementing an educational intervention in critical care units in England would be cost-effective and potentially cost-saving, with incremental cost-effectiveness ratios under worst-case sensitivity analyses of < £5000/quality-adjusted life-year. Limitations Low-quality primary studies cannot definitively prove that the planned interventions were responsible for observed changes in catheter-BSI incidence. Poor reporting gave unclear estimates of risk of bias. Some model parameters were sourced from other locations owing to a lack of UK data. Conclusions Our results suggest that it would be cost-effective and may be cost-saving for the NHS to implement educational interventions in critical care units. However, more robust primary studies are needed to exclude the possible influence of secular trends on observed reductions in catheter-BSI.

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Purpose To determine neuroretinal function with multifocal electroretinogram (mfERG) in diabetic subjects without retinopathy. Methods Multifocal electroretinogram (mfERG) was performed in 18 eyes of 18 diabetic subjects without retinopathy and 17 eyes of 17 age and gender-matched healthy control participants. Among 18 diabetic subjects, two had type 1 and 16 had type 2 diabetes. MfERG responses were averaged by the retinal areas of six concentric rings and four quadrants, and 103 retinal locations; N1–P1 amplitude and P1-implicit time were analysed. Results Average mfERG N1–P1 amplitude (in nv/deg2) of 103 retinal locations was 56.3 ± 17.2 (mean ± SD) in type 1 diabetic subjects, 47.2 ± 9.3 in type 2 diabetic subjects and 71.5 ± 12.7 in controls. Average P1-implicit time (in ms) was 43.0 ± 1.3 in type 1 diabetic subjects, 43.9 ± 2.3 in type 2 diabetic subjects and 41.9 ± 2.1 in controls. There was significant reduction in average N1–P1 amplitude and delay in P1-implicit time in type 2 diabetic subjects in comparison to controls. mfERG amplitude did not show any significant correlation with diabetes duration and blood sugar level. However, implicit time showed a positive correlation with diabetes duration in type 2 diabetic subjects with diabetes duration ≥5 years. Conclusions This is the first study in a Nepalese population with diabetes using multifocal electroretinography. We present novel findings that mfERG N1–P1 amplitude is markedly reduced along with delay in P1-implicit time in type 2 diabetic subjects without retinopathy. These findings indicate that there might be significant dysfunction of inner retina before the development of diabetic retinopathy in the study population, which have higher prevalence of diabetes than the global estimate and uncontrolled blood sugar level.

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Increasing epidemiological studies have shown that a rapid temperature change within 1 day is an independent risk factor for human health. This paper aimed to systematically review the epidemiological evidence on the relationship between diurnal temperature range (DTR) and human health and to propose future research directions. A literature search was conducted in October 2013 using the databases including PubMed, ScienceDirect, and EBSCO. Empirical studies regarding the relationship between DTR and mortality and morbidity were included. Twenty-five relevant studies were identified, among which, 11 investigated the relationship between DTR and mortality and 14 examined the impact of DTR on morbidity. The majority of existing studies reported that DTR was significantly associated with mortality and morbidity, particularly for cardiovascular and respiratory diseases. Notably, compared with adults, the elderly and children were more vulnerable to DTR effects. However, there were some inconsistencies regarding the susceptible groups, lag time, and threshold of DTR. The impact of DTR on human health may be confounded or modified by season, socioeconomic, and educational status. Further research is needed to further confirm the adverse effects of DTR in different geographical locations; examine the effects of DTR on the health of children aged one or under; explore extreme DTR effects on human health; analyze the difference of DTR effects on human health in different locations and the modified effects of potential confounding factors; and develop detailed preventive measures against large DTR, particularly for susceptible groups

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Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

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Acoustic recordings play an increasingly important role in monitoring terrestrial environments. However, due to rapid advances in technology, ecologists are accumulating more audio than they can listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings by calculating acoustic indices. These are statistics which describe the temporal-spectral distribution of acoustic energy and reflect content of ecological interest. We combine spectral indices to produce false-color spectrogram images. These not only reveal acoustic content but also facilitate navigation. An additional analytic challenge is to find appropriate descriptors to summarize the content of 24-hour recordings, so that it becomes possible to monitor long-term changes in the acoustic environment at a single location and to compare the acoustic environments of different locations. We describe a 24-hour ‘acoustic-fingerprint’ which shows some preliminary promise.

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AIMS: To examine changes in illicit drug consumption between peak holiday season (23 December-3 January) in Australia and a control period two months later in a coastal urban area, an inland semi-rural area and an island populated predominantly by vacationers during holidays. DESIGN: Analysis of representative daily composite wastewater samples collected from the inlet of the major wastewater treatment plant in each area. SETTING: Three wastewater treatment plants. PARTICIPANTS: Wastewater treatment plants serviced approximately 350, 000 persons in the urban area, 120,000 in the semi-rural area and 1100-2400 on the island. MEASUREMENTS: Drug residues were analysed using liquid chromatography coupled to a tandem mass spectrometer. Per capita drug consumption was estimated. Changes in drug use were quantified using Hedges' g. FINDINGS: During the holidays, cannabis consumption in the semi-rural area declined (g = -2.8) as did methamphetamine (-0.8), whereas cocaine (+1.5) and ecstasy (+1.6) use increased. In the urban area, consumption of all drugs increased during holidays (cannabis +1.6, cocaine +1.2, ecstasy +0.8 and methamphetamine +0.3). In the vacation area, methamphetamine (+0.7), ecstasy (+0.7) and cocaine (+1.1) use increased, but cannabis (-0.5) use decreased during holiday periods. CONCLUSIONS: While the peak holiday season in Australia is perceived as a period of increased drug use, this is not uniform across all drugs and areas. Substantial declines in drug use in the semi-rural area contrasted with substantial increases in urban and vacation areas. Per capita drug consumption in the vacation area was equivalent to that in the urban area, implying that these locations merit particular attention for drug use monitoring and harm minimisation measures.

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Introduction and Aims: Holiday periods are potentially a time for increased substance use as social events and private parties are more common. Data on community illicit drug consumption during holiday periods are limited. Besides existing methods for determining drug use, such as population surveys, one emerging method is to measure illicit drugs and/or their metabolites in wastewater samples. This study examined the change in consumption of cannabis, methamphetamine, cocaine and 3,4- methylenedioxymethamphetamine in three different types of areas (an inland semi-rural area, a coastal urban area and a vacation island) with respect to holiday times. Design and Methods: Samples were collected at the inlet of the major wastewater treatment plant in each area during a key annual holiday (i.e. the summer holiday including Christmas and New Year) and control period. Illicit drug residues in the daily composited samples were measured by liquid chromatography coupled with tandem mass spectrometry. Results: Drug use varied substantially among the three areas within each monitoring period as well as between the holiday and control period within each area. Use consistently increased and peaked over New Year particularly for cocaine and 3,4-methylenedioxymethamphetamine whereas cannabis and methamphetamine were relatively less subjected to holiday times in all the areas. Discussion and Conclusions: Wastewater sampling and analysis provides higher spatio-temporal resolution than national surveys and supplements drug epidemiology studies originating primary in metropolitan locations. Such data is essential for policy makers to plan potential intervention strategies associated with these illicit substances in regional areas and other settings besides urban areas in the future.

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With recent economic growth in Oman there is increased use of heavy vehicles, presenting an increase in heavy vehicle crashes, associated fatalities and injuries. Vehicle defects cause a significant number of heavy vehicle crashes in Oman and increase the likelihood of fatalities. The aim of this study is to explore factors contributing to driving with vehicle defects in the Omani heavy vehicle industry. A series of qualitative participants observations were conducted in Oman with 49 drivers. These observations also involved discussion and interviews with drivers. The observations occurred at two road-side locations where heavy vehicle drivers gather for eating, resting, vehicle check-up, etc. Data collection was conducted over a three week period. The data was analysed using thematic analysis. A broad number of factors were identified as contributing to the driving of vehicles with defects. Participants indicated that tyres and vehicle mechanical faults were a common issue in the heavy vehicle industry. Participants regularly reported that their companies use cheap, poor quality standards parts and conducted minimal maintenance. Drivers also indicated that they felt powerless to resist company pressure to drive vehicles with known faults. In addition, drivers reported that traffic police were generally in effective and lacked skill to appropriately conduct roadside inspection on trucks. Further, participants stated that it was possible for companies to avoid being fined during annual or roadside vehicle inspections if members of the company knew the traffic police officer conducting the inspection. Moreover, fines issued by police are generally directed to the individual driver rather than being applied to the company, thus providing no incentive for companies to address vehicle faults. The implications of the findings are discussed.