879 resultados para General allocation model


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Since policy-makers usually pursue several conflicting objectives, policy-making can be understood as a multicriteria decision problem. Following the methodological proposal by André and Cardenete (2005) André, F. J. and Cardenete, M. A. 2005. Multicriteria Policy Making. Defining Efficient Policies in a General Equilibrium Model, Seville: Centro de Estudios Andaluces. Working Paper No. E2005/04, multi-objective programming is used in connection with a computable general equilibrium model to represent optimal policy-making and to obtain so-called efficient policies in an application to a regional economy (Andalusia, Spain). This approach is applied to the design of subsidy policies under two different scenarios. In the first scenario, it is assumed that the government is concerned just about two objectives: ensuring the profitability of a key strategic sector and increasing overall output. Finally, the scope of the exercise is enlarged by solving a problem with seven policy objectives, including both general and sectorial objectives. It is concluded that the observed policy could have been Pareto-improved in several directions.

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Libraries since their inception 4000 years ago have been in a process of constant change. Although, changes were in slow motion for centuries, in the last decades, academic libraries have been continuously striving to adapt their services to the ever-changing user needs of students and academic staff. In addition, e-content revolution, technological advances, and ever-shrinking budgets have obliged libraries to efficiently allocate their limited resources among collection and services. Unfortunately, this resource allocation is a complex process due to the diversity of data sources and formats required to be analyzed prior to decision-making, as well as the lack of efficient integration methods. The main purpose of this study is to develop an integrated model that supports libraries in making optimal budgeting and resource allocation decisions among their services and collection by means of a holistic analysis. To this end, a combination of several methodologies and structured approaches is conducted. Firstly, a holistic structure and the required toolset to holistically assess academic libraries are proposed to collect and organize the data from an economic point of view. A four-pronged theoretical framework is used in which the library system and collection are analyzed from the perspective of users and internal stakeholders. The first quadrant corresponds to the internal perspective of the library system that is to analyze the library performance, and costs incurred and resources consumed by library services. The second quadrant evaluates the external perspective of the library system; user’s perception about services quality is judged in this quadrant. The third quadrant analyses the external perspective of the library collection that is to evaluate the impact of the current library collection on its users. Eventually, the fourth quadrant evaluates the internal perspective of the library collection; the usage patterns followed to manipulate the library collection are analyzed. With a complete framework for data collection, these data coming from multiple sources and therefore with different formats, need to be integrated and stored in an adequate scheme for decision support. A data warehousing approach is secondly designed and implemented to integrate, process, and store the holistic-based collected data. Ultimately, strategic data stored in the data warehouse are analyzed and implemented for different purposes including the following: 1) Data visualization and reporting is proposed to allow library managers to publish library indicators in a simple and quick manner by using online reporting tools. 2) Sophisticated data analysis is recommended through the use of data mining tools; three data mining techniques are examined in this research study: regression, clustering and classification. These data mining techniques have been applied to the case study in the following manner: predicting the future investment in library development; finding clusters of users that share common interests and similar profiles, but belong to different faculties; and predicting library factors that affect student academic performance by analyzing possible correlations of library usage and academic performance. 3) Input for optimization models, early experiences of developing an optimal resource allocation model to distribute resources among the different processes of a library system are documented in this study. Specifically, the problem of allocating funds for digital collection among divisions of an academic library is addressed. An optimization model for the problem is defined with the objective of maximizing the usage of the digital collection over-all library divisions subject to a single collection budget. By proposing this holistic approach, the research study contributes to knowledge by providing an integrated solution to assist library managers to make economic decisions based on an “as realistic as possible” perspective of the library situation.

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This paper identifies a number of critical infrastructure applications that are reliant on location services from cooperative location technologies such as GPS and GSM. We show that these location technologies can be represented in a general location model, such that the model components can be used for vulnerability analysis. We perform a vulnerability analysis on these components of GSM and GPS location systems as well as a number of augmentations to these systems.

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In this paper we examine the dynamics of the link between inequality and inflation from a political economy perspective. We consider a simple dynamic general equilibrium model in which agents vote over the desired inflation rate in each period, and inequality is persistent. Inflation in our model is a mechanism of redistribution, and we find that the link between inequality and inflation within any period or over time depends on institutional and preference related parameters. Furthermore, we find that differences in the initial distributions of wealth can yield a diverse set of patterns for the evolution of the inflation and inequality link. Relative to existing literature, our model leads to more precise predictions about the inflation-inequality correlation. To that end, results in the extant empirical literature on the inflation and inequality link need to be interpreted with caution.

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A persistent question in the development of models for macroeconomic policy analysis has been the relative role of economic theory and evidence in their construction. This paper looks at some popular strategies that involve setting up a theoretical or conceptual model (CM) which is transformed to match the data and then made operational for policy analysis. A dynamic general equilibrium model is constructed that is similar to standard CMs. After calibration to UK data it is used to examine the utility of formal econometric methods in assessing the match of the CM to the data and also to evaluate some standard model-building strategies. Keywords: Policy oriented economic modeling; Model evaluation; VAR models

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The stylized facts that motivate this thesis include the diversity in growth patterns that are observed across countries during the process of economic development, and the divergence over time in income distributions both within and across countries. This thesis constructs a dynamic general equilibrium model in which technology adoption is costly and agents are heterogeneous in their initial holdings of resources. Given the households‟ resource level, this study examines how adoption costs influence the evolution of household income over time and the timing of transition to more productive technologies. The analytical results of the model constructed here characterize three growth outcomes associated with the technology adoption process depending on productivity differences between the technologies. These are appropriately labeled as „poverty trap‟, „dual economy‟ and „balanced growth‟. The model is then capable of explaining the observed diversity in growth patterns across countries, as well as divergence of incomes over time. Numerical simulations of the model furthermore illustrate features of this transition. They suggest that that differences in adoption costs account for the timing of households‟ decision to switch technology which leads to a disparity in incomes across households in the technology adoption process. Since this determines the timing of complete adoption of the technology within a country, the implications for cross-country income differences are obvious. Moreover, the timing of technology adoption appears to be impacts on patterns of growth of households, which are different across various income groups. The findings also show that, in the presence of costs associated with the adoption of more productive technologies, inequalities of income and wealth may increase over time tending to delay the convergence in income levels. Initial levels of inequalities in the resources also have an impact on the date of complete adoption of more productive technologies. The issue of increasing income inequality in the process of technology adoption opens up another direction for research. Specifically increasing inequality implies that distributive conflicts may emerge during the transitional process with political- economy consequences. The model is therefore extended to include such issues. Without any political considerations, taxes would leads to a reduction in inequality and convergence of incomes across agents. However this process is delayed if politico-economic influences are taken into account. Moreover, the political outcome is sub optimal. This is essentially due to the fact that there is a resistance associated with the complete adoption of the advanced technology.

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The reduction of CO2 emissions and social exclusion are two key elements of UK transport strategy. Despite intensive research on each theme, little effort has so far been made linking the relationship between emissions and social exclusion. In addition, current knowledge on each theme is limited to urban areas; little research is available on these themes for rural areas. This research contributes to this gap in the literature by analysing 157 weekly activity-travel diary data collected from three case study areas with differential levels of area accessibility and area mobility options, located in rural Northern Ireland. Individual weekly CO2 emission levels from personal travel diaries (both hot exhaust emission and cold-start emission) were calculated using average speed models for different modes of transport. The socio-spatial patterns associated with CO2 emissions were identified using a general linear model whereas binary logistic regression analyses were conducted to identify mode choice behaviour and activity patterns. This research found groups that emitted a significantly lower level of CO2 included individuals living in an area with a higher level of accessibility and mobility, non-car, non-working, and low-income older people. However, evidence in this research also shows that although certain groups (e.g. those working, and residing in an area with a lower level of accessibility) emitted higher levels of CO2, their rate of participation in activities was however found to be significantly lower compared to their counterparts. Based on the study findings, this research highlights the need for both soft (e.g. teleworking) and physical (e.g. accessibility planning) policy measures in rural areas in order to meet government’s stated CO2 reduction targets while at the same time enhancing social inclusion.

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Many drivers in highly motorised countries believe that aggressive driving is increasing. While the prevalence of the behaviour is difficult to reliably identify, the consequences of on-road aggression can be severe, with extreme cases resulting in property damage, injury and even death. This research program was undertaken to explore the nature of aggressive driving from within the framework of relevant psychological theory in order to enhance our understanding of the behaviour and to inform the development of relevant interventions. To guide the research a provisional ‘working’ definition of aggressive driving was proposed encapsulating the recurrent characteristics of the behaviour cited in the literature. The definition was: “aggressive driving is any on-road behaviour adopted by a driver that is intended to cause physical or psychological harm to another road user and is associated with feelings of frustration, anger or threat”. Two main theoretical perspectives informed the program of research. The first was Shinar’s (1998) frustration-aggression model, which identifies both the person-related and situational characteristics that contribute to aggressive driving, as well as proposing that aggressive behaviours can serve either an ‘instrumental’ or ‘hostile’ function. The second main perspective was Anderson and Bushman’s (2002) General Aggression Model. In contrast to Shinar’s model, the General Aggression Model reflects a broader perspective on human aggression that facilitates a more comprehensive examination of the emotional and cognitive aspects of aggressive behaviour. Study One (n = 48) examined aggressive driving behaviour from the perspective of young drivers as an at-risk group and involved conducting six focus groups, with eight participants in each. Qualitative analyses identified multiple situational and person-related factors that contribute to on-road aggression. Consistent with human aggression theory, examination of self-reported experiences of aggressive driving identified key psychological elements and processes that are experienced during on-road aggression. Participants cited several emotions experienced during an on-road incident: annoyance, frustration, anger, threat and excitement. Findings also suggest that off-road generated stress may transfer to the on-road environment, at times having severe consequences including crash involvement. Young drivers also appeared quick to experience negative attributions about the other driver, some having additional thoughts of taking action. Additionally, the results showed little difference between males and females in the severity of behavioural responses they were prepared to adopt, although females appeared more likely to displace their negative emotions. Following the self-reported on-road incident, evidence was also found of a post-event influence, with females being more likely to experience ongoing emotional effects after the event. This finding was evidenced by ruminating thoughts or distraction from tasks. However, the impact of such a post-event influence on later behaviours or interpersonal interactions appears to be minimal. Study Two involved the quantitative analysis of n = 926 surveys completed by a wide age range of drivers from across Queensland. The study aimed to explore the relationships between the theoretical components of aggressive driving that were identified in the literature review, and refined based on the findings of Study One. Regression analyses were used to examine participant emotional, cognitive and behavioural responses to two differing on-road scenarios whilst exploring the proposed theoretical framework. A number of socio-demographic, state and trait person-related variables such as age, pre-study emotions, trait aggression and problem-solving style were found to predict the likelihood of a negative emotional response such as frustration, anger, perceived threat, negative attributions and the likelihood of adopting either an instrumental or hostile behaviour in response to Scenarios One and Two. Complex relationships were found to exist between the variables, however, they were interpretable based on the literature review findings. Factor analysis revealed evidence supporting Shinar’s (1998) dichotomous description of on-road aggressive behaviours as being instrumental or hostile. The second stage of Study Two used logistic regression to examine the factors that predicted the potentially hostile aggressive drivers (n = 88) within the sample. These drivers were those who indicated a preparedness to engage in direct acts of interpersonal aggression on the road. Young, male drivers 17–24 years of age were more likely to be classified as potentially hostile aggressive drivers. Young drivers (17–24 years) also scored significantly higher than other drivers on all subscales of the Aggression Questionnaire (Buss & Perry, 1992) and on the ‘negative problem orientation’ and ‘impulsive careless style’ subscales of the Social Problem Solving Inventory – Revised (D’Zurilla, Nezu & Maydeu-Olivares, 2002). The potentially hostile aggressive drivers were also significantly more likely to engage in speeding and drink/drug driving behaviour. With regard to the emotional, cognitive and behavioural variables examined, the potentially hostile aggressive driver group also scored significantly higher than the ‘other driver’ group on most variables examined in the proposed theoretical framework. The variables contained in the framework of aggressive driving reliably distinguished potentially hostile aggressive drivers from other drivers (Nagalkerke R2 = .39). Study Three used a case study approach to conduct an in-depth examination of the psychosocial characteristics of n = 10 (9 males and 1 female) self-confessed hostile aggressive drivers. The self-confessed hostile aggressive drivers were aged 24–55 years of age. A large proportion of these drivers reported a Year 10 education or better and average–above average incomes. As a group, the drivers reported committing a number of speeding and unlicensed driving offences in the past three years and extensive histories of violations outside of this period. Considerable evidence was also found of exposure to a range of developmental risk factors for aggression that may have contributed to the driver’s on-road expression of aggression. These drivers scored significantly higher on the Aggression Questionnaire subscales and Social Problem Solving Inventory Revised subscales, ‘negative problem orientation’ and ‘impulsive/careless style’, than the general sample of drivers included in Study Two. The hostile aggressive driver also scored significantly higher on the Barrett Impulsivity Scale – 11 (Patton, Stanford & Barratt, 1995) measure of impulsivity than a male ‘inmate’, or female ‘general psychiatric’ comparison group. Using the Carlson Psychological Survey (Carlson, 1982), the self-confessed hostile aggressive drivers scored equal or higher scores than the comparison group of incarcerated individuals on the subscale measures of chemical abuse, thought disturbance, anti-social tendencies and self-depreciation. Using the Carlson Psychological Survey personality profiles, seven participants were profiled ‘markedly anti-social’, two were profiled ‘negative-explosive’ and one was profiled as ‘self-centred’. Qualitative analysis of the ten case study self-reports of on-road hostile aggression revealed a similar range of on-road situational factors to those identified in the literature review and Study One. Six of the case studies reported off-road generated stress that they believed contributed to the episodes of aggressive driving they recalled. Intense ‘anger’ or ‘rage’ were most frequently used to describe the emotions experienced in response to the perceived provocation. Less frequently ‘excitement’ and ‘fear’ were cited as relevant emotions. Notably, five of the case studies experienced difficulty articulating their emotions, suggesting emotional difficulties. Consistent with Study Two, these drivers reported negative attributions and most had thoughts of aggressive actions they would like to take. Similarly, these drivers adopted both instrumental and hostile aggressive behaviours during the self-reported incident. Nine participants showed little or no remorse for their behaviour and these drivers also appeared to exhibit low levels of personal insight. Interestingly, few incidents were brought to the attention of the authorities. Further, examination of the person-related characteristics of these drivers indicated that they may be more likely to have come from difficult or dysfunctional backgrounds and to have a history of anti-social behaviours on and off the road. The research program has several key theoretical implications. While many of the findings supported Shinar’s (1998) frustration-aggression model, two key areas of difference emerged. Firstly, aggressive driving behaviour does not always appear to be frustration driven, but can also be driven by feelings of excitation (consistent with the tenets of the General Aggression Model). Secondly, while the findings supported a distinction being made between instrumental and hostile aggressive behaviours, the characteristics of these two types of behaviours require more examination. For example, Shinar (1998) proposes that a driver will adopt an instrumental aggressive behaviour when their progress is impeded if it allows them to achieve their immediate goals (e.g. reaching their destination as quickly as possible); whereas they will engage in hostile aggressive behaviour if their path to their goal is blocked. However, the current results question this assertion, since many of the hostile aggressive drivers studied appeared prepared to engage in hostile acts irrespective of whether their goal was blocked or not. In fact, their behaviour appeared to be characterised by a preparedness to abandon their immediate goals (even if for a short period of time) in order to express their aggression. The use of the General Aggression Model enabled an examination of the three components of the ‘present internal state’ comprising emotions, cognitions and arousal and how these influence the likelihood of a person responding aggressively to an on-road situation. This provided a detailed insight into both the cognitive and emotional aspects of aggressive driving that have important implications for the design of relevant countermeasures. For example, the findings highlighted the potential value of utilising Cognitive Behavioural Therapy with aggressive drivers, particularly the more hostile offenders. Similarly, educational efforts need to be mindful of the way that person-related factors appear to influence one’s perception of another driver’s behaviour as aggressive or benign. Those drivers with a predisposition for aggression were more likely to perceive aggression or ‘wrong doing’ in an ambiguous on-road situation and respond with instrumental and/or hostile behaviour, highlighting the importance of perceptual processes in aggressive driving behaviour.

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Purpose: The purpose of this study was to improve the retention of primary healthcare (PHC) nurses through exploring and assessing their quality of work life (QWL) and turnover intention. Design and methods: A cross-sectional survey design was used in this study. Data were collected using a questionnaire comprising four sections (Brooks’ survey of Quality of Nursing Work Life [QNWL], Anticipated Turnover Intention, open-ended questions and demographic characteristics). A convenience sample was recruited from 143 PHC centres in Jazan, Saudi Arabia. A response rate of 87% (n = 508/585) was achieved. The SPSS v17 for Windows and NVivo 8 were used for analysis purposes. Procedures and tests used in this study to analyse the quantitative data were descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression, and hierarchical multiple regression. Qualitative data obtained from responses to the open-ended questions were analysed using the NVivo 8. Findings: Quantitative findings suggested that PHC nurses were dissatisfied with their work life. Respondents’ scores ranged between 45 and 218 (mean = 139.45), which is lower than the average total score on Brooks’ Survey (147). Major influencing factors were classified under four dimensions. First, work life/home life factors: unsuitable working hours, lack of facilities for nurses, inability to balance work with family needs and inadequacy of vacations’ policy. Second, work design factors: high workload, insufficient workforce numbers, lack of autonomy and undertaking many non-nursing tasks. Third, work context factors: management practices, lack of development opportunities, and inappropriate working environment in terms of the level of security, patient care supplies and unavailability of recreation room. Finally, work world factors: negative public image of nursing, and inadequate payment. More positively, nurses were notably satisfied with their co-workers. Conversely, 40.4% (n = 205) of the respondents indicated that they intended to leave their current employment. The relationships between QWL and demographic variables of gender, age, marital status, dependent children, dependent adults, nationality, ethnicity, nursing tenure, organisational tenure, positional tenure, and payment per month were significant (p < .05). The eta squared test for these demographics indicates a small to medium effect size of the variation in QWL scores. Using the GLM univariate analysis, education level was also significantly related to the QWL (p < .05). The relationships between turnover intention and demographic variables including gender, age, marital status, dependent children, education level, nursing tenure, organisational tenure, positional tenure, and payment per month were significant (p < .05). The eta squared test for these demographics indicates a small to moderate effect size of the variation in the turnover intention scores. Using the GLM univariate analysis, the dependent adults’ variable was also significantly related to turnover intention (p < .05). Turnover intention was significantly related to QWL. Using standard multiple regression, 26% of the variance in turnover intention was explained by the QWL F (4,491), 43.71, p < .001, with R² = .263. Further analysis using hierarchical multiple regression found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, F (17.433) = 12.04, p < .001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables, R squared change =.19, F change (4, 433) = 30.190, p < .001. The work context variable makes the strongest unique contribution (-.387) to explain the turnover intention, followed by the work design dimension (-.112). The qualitative findings reaffirmed the quantitative findings in terms of QWL and turnover intention. However, the home life/work life and work world dimensions were of great important to both QWL and turnover intention. The qualitative findings revealed a number of new factors that were not included in the survey questionnaire. These included being away from family, lack of family support, social and cultural aspects, accommodation facilities, transportation, building and infrastructure of PHC, nature of work, job instability, privacy at work, patients and community, and distance between home and workplace. Conclusion: Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes. Improving these factors could lead to a higher QWL and increase retention rates and therefore reinforcing the stabilisation of the nursing workforce. Significance of the research: Many countries are examining strategies to attract and retain the health care workforce, particularly nurses. This study identified factors that influence the QWL of PHC nurses as well as their turnover intention. It also determined the significant relationship between QWL and turnover intention. In addition, the present study tested Brooks’ survey of QNWL on PHC nurses for the first time. The qualitative findings of this study revealed a number of new variables regarding QWL and turnover intention of PHC nurses. These variables could be used to improve current survey instruments or to develop new research surveys. The study findings could be also used to develop and appropriately implement plans to improve QWL. This may help to enhance the home and work environments of PHC nurses, improve individual and organisational performance, and increase nurses’ commitment. This study contributes to the existing body of research knowledge by presenting new data and findings from a different country and healthcare system. It is the first of its kind in Saudi Arabia, especially in the field of PHC. It has examined the relationship between QWL and turnover intention of PHC nurses for the first time using nursing instruments. The study also offers a fresh explanation (new framework) of the relationship between QWL and turnover intention among PHC nurses, which could be used or tested by researchers in other settings. Implications for further research: Review of the extant literature reveals little in-depth research on the PHC workforce, especially in terms of QWL and organisational turnover in developing countries. Further research is required to develop a QWL tool for PHC nurses, taking into consideration the findings of the current study along with the local culture. Moreover, the revised theoretical framework of the current study could be tested in further research in other regions, countries or healthcare systems in order to identify its ability to predict the level of PHC nurses’ QWL and their intention to leave. There is a need to conduct longitudinal research on PHC organisations to gain an in-depth understanding of the determents of and changes in QWL and turnover intention of PHC nurses at various points of time. An intervention study is required to improve QWL and retention among PHC nurses using the findings of the current study. This would help to assess the impact of such strategies on reducing turnover of PHC nurses. Focusing on the location of the current study, it would be valuable to conduct another study in five years’ time to examine the percentage of actual turnover among PHC nurses compared with the reported turnover intention in the current study. Further in-depth research would also be useful to assess the impact of the local culture on the perception of expatriate nurses towards their QWL and their turnover intention. A comparative study is required between PHC centres and hospitals as well as the public and private health sector agencies in terms of QWL and turnover intention of nursing personnel. Findings may differ from sector to sector according to variations in health systems, working environments and the case mix of patients.

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This study was designed to determine the Intraocular Pressure (IOP) response to differing levels of dehydration. Seven males participated in a 90 minute treadmill walk (5 km/h and 1 % grade) in both a cool (22 °C) and hot (43 °C) climate. At Baseline and at 30 minute intervals measurements of IOP, by tonometery, and indicators of hydration status (nude weight and plasma osmolality (Posm)) were taken. Body temperature and heart rate were also measured at these time points. Statistically significant interactions (time point (4) by trial (2)) were observed for IOP (F = 10.747, p = 0.009) and body weight loss (F = 50.083, p < 0.001) to decrease, and Posm (F = 34.867, p < 0.001) to increase, by a significantly greater amount during the hot trial compared to the cool. A univariate general linear model showed a significant relationship between IOP and body weight loss (F = 37.63, p < 0.001) and Posm (F = 38.53, p < 0.001). A significant interaction was observed for body temperature (F = 20.908, p < 0.001) and heart rate (F = 25.487, p < 0.001) between the trials and time points, but there was negligible association between these variables and IOP (Pearson correlation coefficient < ±0.5). The present study provides evidence to suggest that IOP is influenced by hydration status.

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Aggressive driving is considered an important road-safety concern for drivers in highly motorised countries. However, understanding of the causes and maintenance factors fundamental to aggressive driving is limited. In keeping with theoretical advances from general aggression research such as the General Aggression Model (GAM), research has begun to examine the emotional and cognitive antecedents of aggressive driving in order to better understand the underlying processes motivating aggressive driving. Early findings in the driving area have suggested that greater levels of aggression are elicited in response to an intentionally aggressive on-road event. In contrast, general aggression research suggests that greater levels of aggression are elicited in response to an ambiguous event. The current study examined emotional and cognitive responses to two hypothetical driving scenarios with differing levels of aggressive intent (intentional versus ambiguous). There was also an interest in whether factors influencing responses were different for hostile aggression (that is, where the action is intended to harm the other) versus instrumental aggression (that is, where the action is motivated by an intention to remove an impediment or attain a goal). Results were that significantly stronger negative emotion and negative attributions, as well as greater levels of threat were reported in response to the scenario which was designed to appear intentional in nature. In addition, participants were more likely to endorse an aggressive behavioural response to a situation that appeared deliberately aggressive than to one where the intention was ambiguous. Analyses to determine if greater levels of negative emotions and cognitions are able to predict aggressive responses provided different patterns of results for instrumental aggression from those for hostile aggression. Specifically, for instrumental aggression, negative emotions and negative attributions were significant predictors for both the intentional and the ambiguous scenarios. In addition, perceived threat was also a significant predictor where the other driver’s intent was clearly aggressive. However, lower rather than higher, levels of perceived threat were associated with greater endorsement of an aggressive response. For hostile aggressive behavioural responses, trait aggression was the strongest predictor for both situations. Overall the results suggest that in the driving context, instrumental aggression is likely to be a much more common response than hostile aggression. Moreover, aggressive responses are more likely in situations where another driver’s behaviour is clearly intentional rather than ambiguous. The results also support the conclusion that there may be different underlying mechanisms motivating an instrumental aggressive response to those motivating a hostile one. In addition, understanding the emotions and cognitions underlying aggressive driving responses may be helpful in predicting and intervening to reduce driving aggression. The finding that drivers appear to regard tailgating as an instrumental response is of concern since this behaviour has the potential to result in crashes.

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Background Quality of work life (QWL) has been found to influence the commitment of health professionals including nurses. However, reliable information on the QWL and turnover intention of primary health care (PHC) nurses is limited. The aim of this study was to examine the relationship between QWL and turnover intention of PHC nurses in Saudi Arabia. Methods A cross-sectional survey was used in this study. Data were collected using Brooks’ survey of Quality of Nursing Work life (QNWL), the Anticipated Turnover Scale and demographic data questions. A total of 508 PHC nurses in the Jazan region, Saudi Arabia completed the questionnaire (RR = 87%). Descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression (SMR), and hierarchical multiple regression (HMR) were applied for analysis using SPSS v17 for Windows. Results Findings suggested that the respondents were dissatisfied with their work life, with almost 40% indicating a turnover intention from their current PHC centres. Turnover intention was significantly related to QWL. Using SMR, 26% of the variance in turnover intention was explained by the QWL, p < 0.001, with R² = .263. Further analysis using HMR found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, p < 0.001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables. Conclusions Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes.

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A general electrical model of a piezoelectric transducer for ultrasound applications consists of a capacitor in parallel with RLC legs. A high power voltage source converter can however generate significant voltage stress across the transducer that creates high leakage currents. One solution is to reduce the voltage stress across the piezoelectric transducer by using an LC filter, however a main drawback is changing the piezoelectric resonant frequency and its characteristics. Thereby it reduces the efficiency of energy conversion through the transducer. This paper proposes that a high frequency current source converter is a suitable topology to drive high power piezoelectric transducers efficiently.

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The application of different EMS current thresholds on muscle activates not only the muscle but also peripheral sensory axons that send proprioceptive and pain signals to the cerebral cortex. A 32-channel time-domain fNIRS instrument was employed to map regional cortical activities under varied EMS current intensities applied on the right wrist extensor muscle. Eight healthy volunteers underwent four EMS at different current thresholds based on their individual maximal tolerated intensity (MTI), i.e., 10 % < 50 % < 100 % < over 100 % MTI. Time courses of the absolute oxygenated and deoxygenated hemoglobin concentrations primarily over the bilateral sensorimotor cortical (SMC) regions were extrapolated, and cortical activation maps were determined by general linear model using the NIRS-SPM software. The stimulation-induced wrist extension paradigm significantly increased activation of the contralateral SMC region according to the EMS intensities, while the ipsilateral SMC region showed no significant changes. This could be due in part to a nociceptive response to the higher EMS current intensities and result also from increased sensorimotor integration in these cortical regions.