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The purpose of this paper is to analyze the inelastic buckling of a rectangular thin flat isotropic plate subjected to uniform uniaxial in-plane compression using a work principle, a deformation plasticity theory and Taylor–Maclaurin series formulation.

The non-loaded longitudinal edges of the rectangular plate are clamped, whereas the loaded edges are simply supported (CSCS). Total work error function is applied to Stowell’s plasticity theory in the derivation of the inelastic buckling equation. Mathematical formulation of the Taylor–Maclaurin series deflection function satisfied the boundary conditions of the CSCS rectangular plate. The critical inelastic load of the plate is then derived by applying variational principles.

Values of the plate buckling coefficient are calculated using various values of moduli ratio for aspect ratios ranging from 0.1 to 1.0, in intervals of 0.1. The accuracy of the proposed technique is validated by comparing the results obtained in the present study with solutions from a previous investigation. The percentage differences in the values of the buckling coefficient ranged from −0.122 to −4.685 per cent.

The results indicate that the work principle approach can be used as an alternative approximate method for analyzing inelastic buckling of rectangular thin flat isotropic plates under uniform in-plane compressive loads.

The paper presents a new technique for a compatible transition from a h‐refined to a p‐refined finite element mesh. At one or more faces of particularly designed pNh‐transition elements a low order h‐discretization may be combined with a usual p‐mesh in the other parts of the elements. The pNh‐elements are conform finite elements which can be applied in an adaptive scheme controlled by a residue based error estimate. Typical applications which require strongly a local mesh refinement within a p‐finite element mesh are, e.g. the approximation of high gradients and the determination of contact areas. Numerical examples demonstrate the efficiency of the pNh‐element technique for such problems.

This paper aims to examine the effect of audit quality of consolidated financial statements on the accuracy of analysts’ earnings forecasts from the viewpoint of users of financial statements.

This paper investigates the effect of dependence on the work of other auditors on error in analysts’ earnings forecasts based on samples from 2011 to 2012 (the period since implementation of the International Financial Reporting Standards in Korea). In addition, this paper examines the effects of use of Big 4 auditors, use of auditors with industry expertise and the proportion of overseas subsidiaries in relation to all subsidiaries on the association between dependence on the work of other auditors and error in analysts’ earnings forecasts.

This paper finds a positive relation between dependence on the work of other auditors and error in analysts’ earnings forecasts, suggesting that more dependence on the work of other auditors decreases the quality of the audit of consolidated financial statements; thus, to the extent that low-quality audits decrease reporting reliability, analysts’ forecasts are less likely to be accurate. This paper also finds that the positive relationship between dependence on the work of other auditors and error in analysts’ earnings forecasts is weakened when the principal auditor is a Big 4 auditor or one with industry expertise, because such auditors provide higher-quality audit services. However, the positive relationship between dependence on the work of other auditors and error in analysts’ earnings forecasts is further strengthened in cases where the proportion of overseas subsidiaries to all subsidiaries is higher. These results suggest that the complexity of the consolidation process increases as the proportion of overseas subsidiaries increases.

The findings are useful in analyzing the effects of adoption of the New ISA, implemented in 2014, which does not allow the division of audit responsibilities between principal auditors and other auditors. This paper also provides insights for regulators and practitioners to improve the auditor appointment system in the future.

Laboratory data are extensively used in medical practice; consequently, laboratory errors have a tremendous impact on patient safety. Therefore, programs designed to identify and reduce laboratory errors, as well as, setting specific strategies are required to minimize these errors and improve patient safety. The purpose of this paper is to identify part of the commonly encountered laboratory errors throughout our practice in laboratory work, their hazards on patient health care and some measures and recommendations to minimize or to eliminate these errors.

Recording the encountered laboratory errors during May 2008 and their statistical evaluation (using simple percent distribution) have been done in the department of laboratory of one of the private hospitals in Egypt. Errors have been classified according to the laboratory phases and according to their implication on patient health.

Data obtained out of 1,600 testing procedure revealed that the total number of encountered errors is 14 tests (0.87 percent of total testing procedures). Most of the encountered errors lay in the pre- and post-analytic phases of testing cycle (representing 35.7 and 50 percent, respectively, of total errors). While the number of test errors encountered in the analytic phase represented only 14.3 percent of total errors. About 85.7 percent of total errors were of non-significant implication on patients health being detected before test reports have been submitted to the patients. On the other hand, the number of test errors that have been already submitted to patients and reach the physician represented 14.3 percent of total errors. Only 7.1 percent of the errors could have an impact on patient diagnosis.

The findings of this study were concomitant with those published from the USA and other countries. This proves that laboratory problems are universal and need general standardization and bench marking measures.

Original being the first data published from Arabic countries that evaluated the encountered laboratory errors and launch the great need for universal standardization and bench marking measures to control the laboratory work.

The purpose is to introduce a safety planning and control (SPC) model that has been integrated into the production planning and control process. The paper is concerned with the impact of this model on human error control, since both workers' and managers' errors are major contributing factors in accident causation.

The analysis of this impact was based on two stages: the analysis of the main types of human errors detected in five sites in which the model has been implemented and a discussion on how the model contributes to the design of safe work systems from a cognitive engineering perspective.

The main conclusion is that six elements of the model (safety planning, near miss reporting, training, percentage of safe work packages indicator, participatory cycle, and planning and control diffusion) contribute to make both the boundaries of safe work visible and respected. Safety planning also helps to make the production system error‐tolerant to some extent. However, the analysis of causes of safety failures in the empirical studies pointed out a high incidence of violations of the boundaries (on average, 43.5 percent of the total safety failures), mostly by workers.

Although improvement in the existing mechanisms might make the model more behavior‐oriented, a broader set of measures is necessary to achieve excellence in dealing with human errors. Also, additional empirical data are necessary to clarify the nature and frequency of the human errors that have impact in construction safety.

The model may help in devising more effective tools to reduce errors in construction.

WE were astonished, surely with reason, to read in the July issue of Management Services that they were seeking help from a “large number of organisations” for a survey to offset what it describes as “the lack of current information” to provide a salary survey in the management services field.

This chapter introduces demographic variables in empirical regression to help find whether demographic changes have an impact on economic growth. There is evidence from estimated values in this chapter to suggest that there is no impact that demographic changes in Hong Kong is affecting the economic growth. The population growth has purely a transition impact where the fertility rate was low in early 2000 up to 2015 as the size of the dependency ratio increases. Besides testing demographic variables the government emphasises better education for all people of ages for prosperous growth but in fact has a negative response on educational investment on the growth of the economy. A well-educated country individual does not suggest a higher productivity in economy growth. An important implication is that there has been no single variable as yet that has seriously impacted the economy growth, but there will be changes in the coming years and has to be attended in result to avoid a diminishing economy.

Outlines previous research on company failure prediction and discusses some of the methodological issues involved. Extends an earlier study (Tan 1997) using artificial neural networks (ANN) to predict financial distress in Australian credit unions by extending the forecast period of the models, presents the results and compares them with probit model results. Finds the ANN models generally at least as good as the probit, although both types improved their accuracy rates (for Type I and Type II errors) when early warning signals were included. Believes ANN “is a promising technique” although more research is required, and suggests some avenues for this.

This paper seeks to provide researchers and librarians with an overview of the US Census Bureau's American Community Survey (ACS), with a specific focus on practical issues that users must face when choosing and using ACS datasets.

Each of the following issues are explored subsequent to a general overview of the ACS: choosing among census datasets from different census programs, interpreting and choosing between the different ACS period estimates, selecting census geography, understanding and recalculating margins of error, and accessing the data. Samples of ACS tables and formulas for creating derived estimates are used to illustrate how to interpret and work with the data.

The ACS datasets are fundamentally different from the decennial census as they are period estimates created from rolling sample surveys. The ACS has a steeper learning curve; this complexity is due in part to the number of choices users must make between datasets, but the primary challenge is learning how to understand and work with estimates as opposed to population counts.

While other papers have discussed the benefits and challenges of the ACS, this paper is structured around the practical issues that researchers must face when using it. Special consideration is given to calculating derived estimates using spreadsheet formulas, as this is a key task that many users will need to perform and spreadsheets are the most likely tool users will employ to manipulate the data.

A Study in Organisation. Under the non‐committal title “Construction of Esso Refinery, Fawley; A Study in Organisation”, A. P. Gray and Mark Abrams tell the story of how this vast £37½ million venture was constructed in little more than two years—thanks to outstandingly efficient management both at the planning and construction stages.