Forecasting inflation, industrial output and exchange rates : a template study for India

This paper reports results from a forecasting study for inflation, industrial output and exchange rates for India. We cannot reject the null hypothesis for linearity for all series used except for the growth rate of the foreign exchange series and our analysis is based on linear models, ARIMA and bivariate transfer functions and restricted VAR. Forecasting performance is evaluated using the models’ root mean-squared error differences and Theil’s inequality coefficients from recursive origin static, fixed origin dynamic and rolling origin dynamic forecasts. For models based on weekly data, based on RMSEs, we find that the bivariate models improve upon the forecasts of the ARIMA model while for models based on monthly data the ARIMA model has almost always better performance. In choosing between the two bivariate models on the basis of RMSEs, our overall results tend to support the use of a restricted VAR, as this model had the best forecasting performance more frequently than the transfer function model.

Dynamic output feedback control of single-link flexible manipulators

This paper presents an efficient technique to design dynamic feedback control scheme for single-link flexible manipulators.  A linear model can be derived for the robotic system using the assumed-mode method.  Conventional techniques such as pole-placement or LQR require physical measurements of all systme states,  posing a stringent requirement for its implementation.  To overcome this problem, a low-order state functional observer is proposed here for reconstruction of the state feedback control action.  The observer design involves solving an optimisation problem with the objective to generate a feedback gain that is as close as possible to that of the required feedback controller.  A condition for robust stability of the closed-loop system under the observer-based control scheme is given.  The attractive features of the propsed technique are the resulted functional state observer is of a very low order and it requires only sensor measurements of only the output- the tip position of the arm.

Attitudes about work practices, time allocation and publication output: profiles of U.S. marketing academics

This study examines attitudes of U.S.-based Academy of Marketing Science members toward teaching, research, participation in administration (including service), and academic promotional issues. Individuals were grouped using Ward’s and K-means clustering procedures, which revealed four groups—established academics, research-focused academics, less satisfied midcareer academics, and satisfied teachers. Clusters were further profiled according to the amount of time spent on teaching, research, and administration; research output; and individual demographic and institutional characteristics. Overall, clusters were generally dissatisfied with a range of work-related issues, with workload stress appearing as an issue that needs to be addressed within marketing academia.

Attitudes about work practices, time allocation and publication output : profiles of Australasian marketing academics

The Australasian tertiary education sector has undergone significant organizational and cultural changes, which have increased pressures on academics to undertake a range of additional activities while at the same time improving research performance. These pressures impact on individuals in different ways, although there may be some groups or clusters of individuals within institutions with common characteristics. Managers may need to develop different sets of management strategies and policies to assist each group of academics to deal better with these pressures and improve their individual performance. The paper examines Australasian marketing academics’ perceptions of their work environments and whether these perceptions result in differing clusters of individuals who might also vary based on their research performance, time allocated to different academic roles, and their professional and demographic characteristics. Sixty-eight members of the Australian and New Zealand Academy of Marketing responded to a survey using a modified version of an instrument developed by Diamantopoulos et al. (1992). K-means clustering procedure identified four groups of academics – “Traditional Academics,” “Satisfied Professors,” “Newer Academics,” and “Satisfied Researchers.” While only a few significant differences among clusters were identified in relation to time allocated to academic activities and research performance, it appears that clusters differ on several professional and demographic characteristics.

A comparison of methods to calculate the optimal load for maximal power output in the power clean

The aim of this study was to compare three calculation methods to determine the load that maximises power output in the power clean. Five male athletes (height=179.8 10.5cms, weight 91 .8 8.8kg, power dean 1RM = 117.0 20.5kg) performed two per cleans at 10% increments from 50% to 100% of 1RM. Bar displacement data was collected using a Ballistic Measurement System (BMS) and vertical ground reaction force (VGRF) data was measured by a Kistler 9287B Force Plate. Power output was calculated for BMS (system mass), BMS (bar mass) and VGRF/BMS system mass. Optimal load was determined to be 70% for the BMS (system mass) and VGRF BMS (system mass) methods and 90% for the BMS (bar mass) method. Sports scientists should be aware of the technical issues underlying these findings due to the practical ramifications for athlete testing and training.

Performances of three minimally invasive cardiac output monitoring systems

We evaluated cardiac output (CO) using three new methods – the auto-calibrated FloTrac–Vigileo (CO_ed), the non-calibrated Modelflow (CO_mf ) pulse contour method and the ultra-sound HemoSonic system (CO_hs) – with thermodilution (CO_td) as the reference. In 13 postoperative cardiac surgical patients, 104 paired CO values were assessed before, during and after four interventions: (i) an increase of tidal volume by 50%; (ii) a 10 cm H₂O increase in positive end-expiratory pressure; (iii) passive leg raising and (iv) head up position. With the pooled data the difference (bias (2SD)) between CO_ed and CO_td, CO_mf and CO_td and CO_hs and CO_td was 0.33 (0.90), 0.30 (0.69) and −0.41 (1.11) l.min⁻¹, respectively. Thus, Modelflow had the lowest mean squared error, suggesting that it had the best performance. CO_ed significantly overestimates changes in cardiac output while CO_mf and CO_hs values are not significantly different from those of CO_td. Directional changes in cardiac output by thermodilution were detected with a high score by all three methods.

Using input-output data in life cycle inventory analysis

The impacts on the environment from human activities are of increasing concern. The need to consider the reduction in energy consumption is of particular interest, especially in the construction and operation of buildings, which accounts for between 30 and 40% of Australia's national energy consumption. Much past and more recent emphasis has been placed on methods for reducing the energy consumed in the operation of buildings. With the energy embodied in these buildings having been shown to account for an equally large proportion of a building's life cycle energy consumption, there is a need to look at ways of reducing the embodied energy of buildings and related products. Life cycle assessment (LCA) is considered to be the most appropriate tool for assessing the life cycle energy consumption of buildings and their products. The life cycle inventory analysis (LCIA) step of a LCA, where an inventory of material and energy inputs is gathered, may currently suffer from several limitations, mainly concerned with the use of incomplete and unreliable data sources and LCIA methods. These traditional methods of LCIA include process-based and input-output-based LCIA. Process-based LCIA uses process specific data, whilst input-output-based LCIA uses data produced from an analysis of the flow of goods and services between sectors of the Australian economy, also known as input-output data. With the incompleteness and unreliability of these two respective methods in mind, hybrid LCIA methods have been developed to minimise the errors associated with traditional LCIA methods, combining both process and input-output data. Hybrid LCIA methods based on process data have shown to be incomplete. Hybrid LCIA methods based on input-output data involve substituting available process data into the input-output model minimising the errors associated with process-based hybrid LCIA methods. However, until now, this LCIA method had not been tested for its level of completeness and reliability. The aim of this study was to assess the reliability and completeness of hybrid life cycle inventory analysis, as applied to the Australian construction industry. A range of case studies were selected in order to apply the input-output-based hybrid LCIA method and evaluate the subsequent results as obtained from each case study. These case studies included buildings: two commercial office buildings, two residential buildings, a recreational building; and building related products: a solar hot water system, a building integrated photovoltaic system and a washing machine. The range of building types and products selected assisted in testing the input-output-based hybrid LCIA method for its applicability across a wide range of product types. The input-output-based hybrid LCIA method was applied to each of the selected case studies in order to obtain their respective embodied energy results. These results were then evaluated with the use of a number of evaluation methods. These evaluation methods included an analysis of the difference between the process-based and input-output-based hybrid LCIA results as an evaluation of the completeness of the process-based LCIA method. The second method of evaluation used was a comparison between equivalent process and input-output values used in the input-output-based hybrid LCIA method as a measure of reliability. It was found that the results from a typical process-based LCIA and process-based hybrid LCIA have a large gap when compared to input-output-based hybrid LCIA results (up to 80%). This gap has shown that the currently available quantity of process data in Australia is insufficient. The comparison between equivalent process-based and input-output-based LCIA values showed that the input-output data does not provide a reliable representation of the equivalent process values, for material energy intensities, material inputs and whole products. Therefore, the use of input-output data to account for inadequate or missing process data is not reliable. However, as there is currently no other method for filling the gaps in traditional process-based LCIA, and as input-output data is considered to be more complete than process data, and the errors may be somewhat lower, using input-output data to fill the gaps in traditional process-based LCIA appears to be better than not using any data at all. The input-output-based hybrid LCIA method evaluated in this study has shown to be the most sophisticated and complete currently available LCIA method for assessing the environmental impacts associated with buildings and building related products. This finding is significant as the construction and operation of buildings accounts for a large proportion of national energy consumption. The use of the input-output-based hybrid LCIA method for products other than those related to the Australian construction industry may be appropriate, especially if the material inputs of the product being assessed are similar to those typically used in the construction industry. The input-output-based hybrid LCIA method has been used to correct some of the errors and limitations associated with previous LCIA methods, without the introduction of any new errors. Improvements in current input-output models are also needed, particularly to account for the inclusion of capital equipment inputs (i.e. the energy required to manufacture the machinery and other equipment used in the production of building materials, products etc.). Although further improvements in the quantity of currently available process data are also needed, this study has shown that with the current available embodied energy data for LCIA, the input-output-based hybrid LCIA appears to provide the most reliable and complete method for use in assessing the environmental impacts of the Australian construction industry.

Scholarly journal output : a regional perspective

This paper presents the findings of an investigation designed to reveal the destination of the refereed journal research output of accounting and finance faculty members across their entire academic careers. A geographic approach was adopted with the intention of providing a historical data-set to inform the development of a region-centric model of academic research productivity. The study focuses on publication careers of accounting and finance academics from one particular geographic region, New Zealand. The data were collected through a detailed examination of electronic databases of journal holdings and research reports of tertiary institutions. The results of this study provide evidence that, across their careers, New Zealand's academics have published a significant number of papers in journals located in two regions, Australia-New Zealand and the United Kingdom, and that this academic community has attained publication success in international journals generally regarded as high quality.

Are output fluctuations transitory? New evidence from twenty four Chinese provinces

The fact that an occurrence of a unit root in real output is inconsistent with the notion that business cycles are stationary fluctuations around a deterministic trend makes this an important topic for empirical investigation. We examine this issue for 24 Chinese provinces using the recently developed Lagrange multiplier panel unit root test which allows for a structural break. Our main finding is that real gross domestic product (GDP) and real GDP per capita for Chinese provinces are stationary fluctuations around a deterministic trend.

Intravenous AICAR administration reduces hepatic glucose output and inhibits whole body lipolysis in type 2 diabetic patients

Aims/hypothesis: The 5′-AMP-activated protein kinase (AMPK) pathway is intact in type 2 diabetic patients and is seen as a target for diabetes treatment. In this study, we aimed to assess the impact of the AMPK activator 5-aminoimidazole-4-carboxamide riboside (AICAR) on both glucose and fatty acid metabolism in vivo in type 2 diabetic patients.

Methods: Stable isotope methodology and blood and muscle biopsy sampling were applied to assess blood glucose and fatty acid kinetics following continuous i.v. infusion of AICAR (0.75 mg kg−1 min−1) and/or NaCl (0.9%) in ten male type 2 diabetic patients (age 64 ± 2 years; BMI 28 ± 1 kg/m2).
Results Plasma glucose rate of appearance (R a) was reduced following AICAR administration, while plasma glucose rate of disappearance (R d) was similar in the AICAR and control test. Consequently, blood glucose disposal (R d expressed as a percentage of R a) was increased following AICAR infusion (p < 0.001). Accordingly, a greater decline in plasma glucose concentration was observed following AICAR infusion (p < 0.001). Plasma NEFA R a and R d were both significantly reduced in response to AICAR infusion, and were accompanied by a significant decline in plasma NEFA concentration. Although AMPK phosphorylation in skeletal muscle was not increased, we observed a significant increase in acetyl-CoA carboxylase phosphorylation (p < 0.001).

Conclusions/interpretation: The i.v. administration of AICAR reduces hepatic glucose output, thereby lowering blood glucose concentrations in vivo in type 2 diabetic patients. Furthermore, AICAR administration stimulates hepatic fatty acid oxidation and/or inhibits whole body lipolysis, thereby reducing plasma NEFA concentration.