990 resultados para Borch, Gerard ter, 1617-1681.
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Injury is the fourth leading cause of death in Australia. Injury rates in Queensland are amongst the highest in Australia and 21.5% of people surveyed for this research reported that their lifestyle or that of an immediate family member had been permanently affected by injury. Injury results in over 40,000 hospital admissions and 200,000 attendances at hospital Emergency Departments in Queensland each year. Queensland's death rate from injuries is higher than the national average, with consistently higher rates of deaths related to transport injuries. Queensland statistics also show higher than national average rates of injuries due to falls, homicide and accidental drowning. (Pike, Muller, Baade & Ward, 2000) In 2000-01 injuries represented over $4 billion (or 8%) of total health system expenditure, and 185,000 disability-adjusted life years (DALYs), or 7% of the total morbidity burden of disease and injury in Australia in 2003. (Begg, Vos, Barker, Stevenson, Stanley & Lopez, 2007). Injury is one of seven key health areas identified by the Commonwealth, state and territory governments for priority attention as National Health Priority Areas
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Principal Topic: It is well known that most new ventures suffer from a significant lack of resources, which increases the risk of failure (Shepherd, Douglas and Shanley, 2000) and makes it difficult to attract stakeholders and financing for the venture (Bhide & Stevenson, 1999). The Resource-Based View (RBV) (Barney, 1991; Wernerfelt, 1984) is a dominant theoretical base increasingly drawn on within Strategic Management. While theoretical contributions applying RBV in the domain of entrepreneurship can arguably be traced back to Penrose (1959), there has been renewed attention recently (e.g. Alvarez & Busenitz, 2001; Alvarez & Barney, 2004). This said, empirical work is in its infancy. In part, this may be due to a lack of well developed measuring instruments for testing ideas derived from RBV. The purpose of this study is to develop a measurement scales that can serve to assist such empirical investigations. In so doing we will try to overcome three deficiencies in current empirical measures used for the application of RBV to the entrepreneurship arena. First, measures for resource characteristics and configurations associated with typical competitive advantages found in entrepreneurial firms need to be developed. These include such things as alertness and industry knowledge (Kirzner, 1973), flexibility (Ebben & Johnson, 2005), strong networks (Lee et al., 2001) and within knowledge intensive contexts, unique technical expertise (Wiklund and Shepard, 2003). Second, the RBV has the important limitations of being relatively static and modelled on large, established firms. In that context, traditional RBV focuses on competitive advantages. However, newly established firms often face disadvantages, especially those associated with the liabilities of newness (Aldrich & Auster, 1986). It is therefore important in entrepreneurial contexts to expand to an investigation of responses to competitive disadvantage through an RBV lens. Conversely, recent research has suggested that resource constraints actually have a positive effect on firm growth and performance under some circumstances (e.g., George, 2005; Katila & Shane, 2005; Mishina et al., 2004; Mosakowski, 2002; cf. also Baker & Nelson, 2005). Third, current empirical applications of RBV measured levels or amounts of particular resources available to a firm. They infer that these resources deliver firms competitive advantage by establishing a relationship between these resource levels and performance (e.g. via regression on profitability). However, there is the opportunity to directly measure the characteristics of resource configurations that deliver competitive advantage, such as Barney´s well known VRIO (Valuable, Rare, Inimitable and Organized) framework (Barney, 1997). Key Propositions and Methods: The aim of our study is to develop and test scales for measuring resource advantages (and disadvantages) and inimitability for entrepreneurial firms. The study proceeds in three stages. The first stage developed our initial scales based on earlier literature. Where possible, we adapt scales based on previous work. The first block of the scales related to the level of resource advantages and disadvantages. Respondents were asked the degree to which each resource category represented an advantage or disadvantage relative to other businesses in their industry on a 5 point response scale: Major Disadvantage, Slight Disadvantage, No Advantage or Disadvantage, Slight Advantage and Major Advantage. Items were developed as follows. Network capabilities (3 items) were adapted from (Madsen, Alsos, Borch, Ljunggren & Brastad, 2006). Knowledge resources marketing expertise / customer service (3 items) and technical expertise (3 items) were adapted from Wiklund and Shepard (2003). flexibility (2 items), costs (4 items) were adapted from JIBS B97. New scales were developed for industry knowledge / alertness (3 items) and product / service advantages. The second block asked the respondent to nominate the most important resource advantage (and disadvantage) of the firm. For the advantage, they were then asked four questions to determine how easy it would be for other firms to imitate and/or substitute this resource on a 5 point likert scale. For the disadvantage, they were asked corresponding questions related to overcoming this disadvantage. The second stage involved two pre-tests of the instrument to refine the scales. The first was an on-line convenience sample of 38 respondents. The second pre-test was a telephone interview with a random sample of 31 Nascent firms and 47 Young firms (< 3 years in operation) generated using a PSED method of randomly calling households (Gartner et al. 2004). Several items were dropped or reworded based on the pre-tests. The third stage (currently in progress) is part of Wave 1 of CAUSEE (Nascent Firms) and FEDP (Young Firms), a PSED type study being conducted in Australia. The scales will be tested and analysed with a random sample of approximately 700 Nascent and Young firms respectively. In addition, a judgement sample of approximately 100 high potential businesses in each category will be included. Findings and Implications: The paper will report the results of the main study (stage 3 – currently data collection is in progress) will allow comparison of the level of resource advantage / disadvantage across various sub-groups of the population. Of particular interest will be a comparison of the high potential firms with the random sample. Based on the smaller pre-tests (N=38 and N=78) the factor structure of the items confirmed the distinctiveness of the constructs. The reliabilities are within an acceptable range: Cronbach alpha ranged from 0.701 to 0.927. The study will provide an opportunity for researchers to better operationalize RBV theory in studies within the domain of entrepreneurship. This is a fundamental requirement for the ability to test hypotheses derived from RBV in systematic, large scale research studies.
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Background The accurate measurement of Cardiac output (CO) is vital in guiding the treatment of critically ill patients. Invasive or minimally invasive measurement of CO is not without inherent risks to the patient. Skilled Intensive Care Unit (ICU) nursing staff are in an ideal position to assess changes in CO following therapeutic measures. The USCOM (Ultrasonic Cardiac Output Monitor) device is a non-invasive CO monitor whose clinical utility and ease of use requires testing. Objectives To compare cardiac output measurement using a non-invasive ultrasonic device (USCOM) operated by a non-echocardiograhically trained ICU Registered Nurse (RN), with the conventional pulmonary artery catheter (PAC) using both thermodilution and Fick methods. Design Prospective observational study. Setting and participants Between April 2006 and March 2007, we evaluated 30 spontaneously breathing patients requiring PAC for assessment of heart failure and/or pulmonary hypertension at a tertiary level cardiothoracic hospital. Methods SCOM CO was compared with thermodilution measurements via PAC and CO estimated using a modified Fick equation. This catheter was inserted by a medical officer, and all USCOM measurements by a senior ICU nurse. Mean values, bias and precision, and mean percentage difference between measures were determined to compare methods. The Intra-Class Correlation statistic was also used to assess agreement. The USCOM time to measure was recorded to assess the learning curve for USCOM use performed by an ICU RN and a line of best fit demonstrated to describe the operator learning curve. Results In 24 of 30 (80%) patients studied, CO measures were obtained. In 6 of 30 (20%) patients, an adequate USCOM signal was not achieved. The mean difference (±standard deviation) between USCOM and PAC, USCOM and Fick, and Fick and PAC CO were small, −0.34 ± 0.52 L/min, −0.33 ± 0.90 L/min and −0.25 ± 0.63 L/min respectively across a range of outputs from 2.6 L/min to 7.2 L/min. The percent limits of agreement (LOA) for all measures were −34.6% to 17.8% for USCOM and PAC, −49.8% to 34.1% for USCOM and Fick and −36.4% to 23.7% for PAC and Fick. Signal acquisition time reduced on average by 0.6 min per measure to less than 10 min at the end of the study. Conclusions In 80% of our cohort, USCOM, PAC and Fick measures of CO all showed clinically acceptable agreement and the learning curve for operation of the non-invasive USCOM device by an ICU RN was found to be satisfactorily short. Further work is required in patients receiving positive pressure ventilation.
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This paper reports the initial steps of research on planning of rural networks for MV and LV. In this paper, two different cases are studied. In the first case, 100 loads are distributed uniformly on a 100 km transmission line in a distribution network and in the second case, the load structure become closer to the rural situation. In case 2, 21 loads are located in a distribution system so that their distance is increasing, distance between load 1 and 2 is 3 km, between 2 and 3 is 6 km, etc). These two models to some extent represent the distribution system in urban and rural areas, respectively. The objective function for the design of the optimal system consists of three main parts: cost of transformers, and MV and LV conductors. The bus voltage is expressed as a constraint and should be maintained within a standard level, rising or falling by no more than 5%.
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- This paper presents a validation proposal for development of diagnostic and prognostic algorithms for SF6 puffer circuit-breakers reproduced from actual site waveforms. The re-ignition/restriking rates are duplicated in given circuits and the cumulative energy dissipated in interrupters by the restriking currents. The targeted objective is to provide a simulated database for diagnosis of re-ignition/restrikes relating to the phase to earth voltage and the number of re-ignition/restrikes as well as estimating the remaining life of SF6 circuit-breakers. The model-based diagnosis of a tool will be useful in monitoring re-ignition/restrikes as well as predicting a nozzle’s lifetime. This will help ATP users with practical study cases and component data compilation for shunt reactor switching and capacitor switching. This method can be easily applied with different data for the different dielectric curves of circuit breakers and networks. This paper presents modelling details and some of the available cases, required project support, the validation proposal, the specific plan for implementation and the propsed main contributions.
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This paper presents a database ATP (Alternative Transient Program) simulated waveforms for shunt reactor switching cases with vacuum breakers in motor circuits following interruption of the starting current. The targeted objective is to provide multiple reignition simulated data for diagnostic and prognostic algorithms development, but also to help ATP users with practical study cases and component data compilation for shunt reactor switching. This method can be easily applied with different data for the different dielectric curves of circuit-breakers and networks. This paper presents design details, discusses some of the available cases and the advantages of such simulated data.
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In this paper, the stability of an autonomous microgrid with multiple distributed generators (DG) is studied through eigenvalue analysis. It is assumed that all the DGs are connected through Voltage Source Converter (VSC) and all connected loads are passive. The VSCs are controlled by state feedback controller to achieve desired voltage and current outputs that are decided by a droop controller. The state space models of each of the converters with its associated feedback are derived. These are then connected with the state space models of the droop, network and loads to form a homogeneous model, through which the eigenvalues are evaluated. The system stability is then investigated as a function of the droop controller real and reac-tive power coefficients. These observations are then verified through simulation studies using PSCAD/EMTDC. It will be shown that the simulation results closely agree with stability be-havior predicted by the eigenvalue analysis.
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This paper describes the operation of a microgrid that contains a custom power park (CPP). The park may contain an unbalanced and/or nonlinear load and the microgrid may contain many dis-tributed generators (DGs). One of the DGs in the microgrid is used as a compensator to achieve load compensation. A new method is proposed for current reference generation for load compensation, which takes into account the real and reactive power to be supplied by the DG connected to the compensator. The real and reactive power from the DGs and the utility source is tightly regulated assuming that dedicated communication channels are available. Therefore this scheme is most suitable in cases where the loads in CPP and DGs are physically located close to each other. The proposal is validated through extensive simulation studies using EMTDC/PSCAD software package (version 4.2).