990 resultados para Unit Groups


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The first data set contains the mean and cofficient of variation (standard deviation divided by mean) of a multi-frequency indicator I derived from ER60 acoustic information collected at five frequencies (18, 38, 70, 120, and 200 kHz) in the Bay of Biscay in May of the years 2006, 2008, 2009 and 2010 (Pelgas surveys). The multi-frequency indicator was first calculated per voxel (20 m long × 5 m deep sampling unit) and then averaged on a spatial grid (approx. 20 nm × 20 nm) for five 5-m depth layers in the surface waters (10-15m, 15-20m, 20-25m, 25-30m below sea surface); there are missing values in particular in the shallowest layer. The second data set provides for each grid cell and depth layer the proportion of voxels for which the multi-frequency indicator I was indicative of a certain group of organisms. For this the following interpretation was used: I < 0.39 swim bladder fish or large gas bubbles, I = 0.39-0.58 small resonant bubbles present in gas bearing organisms such as larval fish and phytoplankton, I = 0.7-0.8 fluidlike zooplankton such as copepods and euphausiids, and I > 0.8 mackerel. These proportions can be interpreted as a relative abundance index for each of the four organism groups.

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Optimum conditions were selected for chromatographic separation of model mixtures of C12-C40 n-alkanes. For one of samples of hydrothermal deposits extraction conditions of hydrocarbons were studied and a sample preparation procedure was selected. The procedure was proposed to determine n-alkanes in samples of hydrothermal deposits by means of gas chromatography - mass spectrometry (GC-MS). Detection limit for n-alkanes was 3x10**-9 to 10**-8% depending on components. On the basis of the proposed procedure composition of n-alkanes was studied in samples of hydrothermal deposits collected at the Mid-Atlantic Ridge (Broken Spur, Lost City, and Rainbow hydrothermal fields). Analyses showed that samples contained C14-C35 n-alkanes. Concentrations of the n-alkanes were rather low and varied from 0.002 to 0.038 µg/g. Hypotheses concerning genesis of identified n-alkanes were offered.

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The objective of the study was to evaluate whether the introduction of patient-focused nursing care affected the number of seclusions and the length of time patients spent in seclusion, in an acute psychiatric unit. The study used a pre-intervention–post-intervention design and was conducted in an eight-bed locked unit within a large regional general hospital in Queensland, Australia. The medical records of all people who were secluded as part of their management while in hospital, during two 6-month periods, were retrospectively reviewed. Changes to the ways in which nurses conducted their daily activities were implemented during the time between the data collection periods. There were no differences between the groups with respect to the number of times a patient was secluded. However, following implementation of patient-focused care, there was a reduction in the length of time for which patients were secluded. The only change in medication administration was that post-implementation, Haloperidol was used in fewer seclusion episodes. The findings indicate that changes to nursing practice may result in closer monitoring of patients and a reduction in the time patients spend secluded in acute inpatient psychiatric settings.

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Background: In mental health, policy-makers and planners are increasingly being asked to set priorities. This means that health economists, health services researchers and clinical investigators are being called upon to work together to define and measure costs. Typically, these researchers take available service utilisation data and convert them to costs, using a range of assumptions. There are inefficiencies, as individual groups of researchers frequently repeat essentially similar exercises in achieving this end. There are clearly areas where shared or common investment in the development of statistical software syntax, analytical frameworks and other resources could maximise the use of data. Aims of the Study: This paper reports on an Australian project in which we calculated unit costs for mental health admissions and community encounters. In reporting on these calculations, our purpose is to make the data and the resources associated with them publicly available to researchers interested in conducting economic analyses, and allow them to copy, distribute and modify them, providing that all copies and modifications are available under the same terms and conditions (i.e., in accordance with the 'Copyleft' principle), Within this context, the objectives of the paper are to: (i) introduce the 'Copyleft' principle; (ii) provide an overview of the methodology we employed to derive the unit costs; (iii) present the unit costs themselves; and (iv) examine the total and mean costs for a range of single and comorbid conditions, as an example of the kind of question that the unit cost data can be used to address. Method: We took relevant data from the Australian National Survey of Mental Health and Wellbeing (NSMHWB), and developed a set of unit costs for inpatient and community encounters. We then examined total and mean costs for a range of single and comorbid conditions. Results: We present the unit costs for mental health admissions and mental health community contacts. Our example, which explored the association between comorbidity and total and mean costs, suggested that comorbidly occurring conditions cost more than conditions which occur on their own. Discussion: Our unit costs, and the materials associated with them, have been published in a freely available form governed by a provision termed 'Copyleft'. They provide a valuable resource for researchers wanting to explore economic questions in mental health. Implications for Health Policies: Our unit costs provide an important resource to inform economic debate in mental health in Australia, particularly in the area of priority-setting. In the past, such debate has largely, been based on opinion. Our unit costs provide the underpinning to strengthen the evidence-base of this debate. Implications for Further Research: We would encourage other Australian researchers to make use of our unit costs in order to foster comparability across studies. We would also encourage Australian and international researchers to adopt the 'Copyleft' principle in equivalent circumstances. Furthermore, we suggest that the provision of 'Copyleft'-contingent funding to support the development of enabling resources for researchers should be considered in the planning of future large-scale collaborative survey work, both in Australia and overseas.

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To examine the effect of an algorithm-based sedation guideline developed in a North American intensive care unit (ICU) on the duration of mechanical ventilation of patients in an Australian ICU. The intervention was tested in a pre-intervention, post-intervention comparative investigation in a 14-bed adult intensive care unit. Adult mechanically ventilated patients were selected consecutively (n =322) The pre-intervention and post-intervention groups were similar except for a higher number of patients with a neurological diagnosis in the pre-intervention group. An algorithm-based sedation guideline including a sedation scale was introduced using a multifaceted implementation strategy. The median duration of ventilation was 5.6 days in the post-intervention group, compared with 4.8 days for the pre-intervention group (P = 0.99). The length of stay was 8.2 days in the post-intervention group versus 7.1 days in the pre-intervention group (P = 0.04). There were no statistically significant differences for the other secondary outcomes, including the score on the Experience of Treatment in ICU 7 item questionnaire, number of tracheostomies and number of self-extubations. Records of compliance to recording the sedation score during both phases revealed that patients were slightly more deeply sedated when the guideline was used. The use of the algorithm-based sedation guideline did not reduce duration of mechanical ventilation in the setting of this study.

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This exploratory paper, developing a conceptual model of owner-manager characteristics and access to finance, aims to investigate whether the concept of strategic groups plays a role in the process of small and medium-sized enterprises (SMEs) accessing finance. Strategic groups are groups of firms making similar patterns of investments in order to achieve their goals. This paper explores how strategic groups, which represent a classification of SMEs based upon their realised strategies, helps to provide an understanding of the success of SMEs in raising finance. The data, from a representative survey of 400 SMEs conducted by the Barclays Bank Telephone Research Unit, were subject to two-stage cluster analysis, thus codified into strategic groups using the natural rhythm of the data, rather than any subjective and value-laden categories being imposed by the authors. The findings show clear differentiation between strategic groups of SMEs, the characteristics of their owner-managers, and the financing strategies adopted. As such, the paper develops a novel typology of strategic groups of SMEs which, therefore, informs their financing strategies, as well as advising other stakeholders.