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Examines two aspects of a new system being installed by BP engineering. First, the measurement of corrosion in hot, dangerous and inaccessible locations, both within process plants and on remote pipelines and, second, the automatic collection of data from widely separated measurement points at a single location for monitoring and assessment. Discusses recent advances in ultrasonic non‐destructive test instruments and low frequency electro‐magnetic communication techniques, showing how these have made this project possible.

Female labour force participation (FLFP) is undeniably critical for both developing and developed countries. This study aims to investigate the impact of economic risk on FLFP, controlling economic well-being, fertility rate and education, considering the asymmetric relationship among the indicators in Turkey.

Time series data covering years from 1988Q1 to 2019Q4 is deployed for the empirical analysis to identify the long-run asymmetric link. Empirical analysis of the study starts with the employment of the Augmented Dickey-Fuller unit root test with the breakpoint to test for the order of integration of time series and to capture the breakpoints. The Brock-Dechert-Scheibkman test is applied to determine if or not the econometric model is correctly identified. Nonlinear autoregressive distributed lag (NARDL) bounds test is used to examine the existence of an asymmetric link between FLFP and economic well-being. The empirical analysis follows the investigation of the determinants of FLFP through the employment of the NARDL model.

The existence of long-run link among the time series is confirmed through the results obtained from the NARDL bounds test. Furthermore, long-run NARDL estimations confirm that (i) positive shocks in economic well-being increases FLFP; (ii) positive shock in education negatively impacts FLFP; (iii) FLFP is negatively affected by economic risk; and (iv) finally, increased fertility rate increases FLFP in Turkey.

This paper is checked from turnitin for the plagiarism which is estimated to be less than 20%. It is an original paper that fills the gap in literature and provides meaningful insight both for the policymakers and academics.

The dissolving trade barriers, financial deregulation, hyper‐mobility of capital and the rapid diffusion of new information technologies have ushered the Australian economy into the borderless world. The orthodoxy that states that centralised wage‐fixing in Australia has impeded wage flexibility and resulted in high unemployment is unconvincing. Partly, this is because in the 1980s Australian labour market institutions have been decentralised and decollectivised in response to pressures from the borderless world. The insights garnered from cross‐sectional comparative statics that, first, skill‐biased Schumpeterian technological change was the major cause of labour immiserisation and, second, adverse Stolper‐Samuelson trade played an insignificant effect need to be reviewed. Parsimonious dynamic time‐series models of trade and technology have been formulated using general‐to‐specific methods after taking account of stochastic trends through unit root and cointegration tests. Granger causality and non‐nested tests applied to these models support the contention that both trade and technology contributed to increasing wage disparity during the borderless era. Moreover the supply side factors such as female participation, immigration and institutional factors such as deunionisation have also increased wage disparity. The deregulation of the Australian labour market by the Workplace Relations Act, whilst an inevitable response to achieve competitiveness in the borderless world market, would exacerbate wage inequality. Policies aimed at skill accumulation on the one hand, and social welfare policies involving negative income taxes on the other may have to be implemented to mitigate the deleterious social effects of rising wage inequality.

The purpose of this paper is to enlarge the exposure of the Theil–Sen (TS) methodology to the academic, analyst and practitioner communities using an earnings forecast setting. The study includes an appendix that describes the TS model in very basic terms and SAS code to assist readers in the implementation of the TS model. The study also presents an alternative approach to deflating or scaling variables.

Archival in nature using a combination of regression analysis and binomial tests.

The binomial test results support the hypothesis that the forecasting performance of the naïve no-change model is at least equal to or better than the ordinary least squares (OLS) model when earnings volatility is low. However, the results do not support the same hypothesis for the TS model nor do the results support the hypothesis that the OLS and TS models will outperform the naïve no-change model when cash flow volatility is high. Nevertheless, the study makes notable contributions to the literature, as the results indicate that the performance of the naïve model is at least as good as the OLS and TS models across 18 of the 20 binomial tests. Moreover, the results indicate that the performance of the TS model is always superior to the OLS model.

The results are generalizable to US firms and may not extend to non-US firms.

The TS methodology is advantageous to OLS in that the results are robust to outlier observations, and there is no heteroscedasticity. Researchers will find this study to be useful given the use of a model (i.e. TS) which has to date received little attention, and the provision of the details for the mechanics of the model. A bonus for researchers is that the study includes SAS code for implementing the procedure.

Awareness of alternative forecast methodologies could lead to improved forecasting results in certain contexts. The study also helps the financial community in general, as improved forecasting abilities are important for all capital market participants as they improve market efficiency.

Although a healthy literature exists for examining out-of-sample forecasts for earnings, the literature lacks an answer for a simple question before pursuing additional analyses: Are the results any better than those from a naive no-change forecast? The current study emphasizes the idea that the naïve no-change forecast is the most elementary model possible, and the researcher must first establish the superiority of a more complex model before conducting further analyses.

Provides a framework for understanding the relationships between alternative cointegrating estimators with special attention given to single equation procedures. The approach consists of augmenting the long‐run model with general short‐run dynamic specifications and identifying the specific assumptions implied by each of these estimators about the short‐run dynamics. Understanding this hierarchical structure between estimators is important since it shows the conditions when consistent and asymptotically efficient parameter estimates may be obtained from standard econometric packages. Since the alternative estimators are shown to be nested in a general framework, this suggests that general‐to‐specific methodology may be adopted to test between these alternative specifications. To highlight the salient characteristics of the alternative estimators, the framework is related to two theoretical economic models: stock prices and money demand; and applied to the demand for imports and testing of the crowding out hypothesis.

As the global community increasingly directs its attention towards sustainable urban development, integrating artificial intelligence (AI) into circular economy (CE) management within smart cities has become a potent strategy. This study aims to examine the potential influence of AI-based technologies on optimizing resources and minimizing waste, which constitute critical components of the principles underpinning the CE. The focus is mainly on applying these technologies within smart city environments. Artificial Intelligence can significantly enhance the processes of gathering, analyzing and decision-making by integrating internet of things (IoT) sensors, data analytics, machine learning algorithms and predictive analytics. This chapter explores the potential of AI in predicting trends, optimizing circular supply chains, improving waste management and recycling practices, facilitating sustainable product design, fostering citizen engagement and aiding policy development. The current research presents a comprehensive examination of the interrelated connection between the principles of CE and the advanced technology of AI. Doing so contributes significantly to our holistic comprehension of how these advancements might collectively influence the development of a more sustainable and resilient future for urban populations.

If additional evidence were needed of the connection between food supply and the spread of infectious disease, it would be found in a report recently presented to the Finsbury Borough Council by its Medical Officer of Health, Dr. GEORGE NEWMAN. It appears that in the early part of May a number of cases of scarlet fever were notified to Dr. NEWMAN, and upon inquiry being made it was ascertained that nearly the whole of these cases had partaken of milk from a particular dairy. A most pains‐taking investigation was at once instituted, and the source of the supply was traced to a farm in the Midlands, where two or three persons were found recovering from scarlet fever. The wholesale man in London, to whom the milk was consigned, at first denied that any of this particular supply had been sent to shops in the Finsbury district, but it was eventually discovered that one, or possibly two, churns had been delivered one morning, with the result that a number of persons contracted the disease. One of the most interesting points in Dr. NEWMAN'S report is that three of these cases, occurring in one family, received milk from a person who was not a customer of the wholesale dealer mentioned above. It transpired on the examination of this last retailer's servants that on the particular morning on which the infected churn of milk had been sent into Finsbury, one of them, running short, had borrowed a quart from another milkman, and had immediately delivered it at the house in which these three cases subsequently developed. The quantity he happened to borrow was a portion of the contents of the infected churn.

Uses parametric Granger causality techniques to test whether trade acted as an engine of growth during the period 1971(2)‐1994(2) in Australia. The causality tests were performed on time‐series data that were filtered after unit root and cointegration testing. During the study period there was a dramatic shift from a protectionist to a more liberal trading regime in Australia. Superexogeneity tests were applied to the conditional growth and the marginal trade policy models derived by the application of general to specific methodology. The superexogeneity tests examined whether the shift from a protectionist to a more liberal trading regime in the mid‐1980s undermined the structure of Australian trade growth dynamics as foreshadowed in the Lucas critique. Reviews the macropolicy implications of the trade policy regime shift.

Internationalisation of the Australian economy is profoundly changing the macroeconomic fabric of the Australian labour market. This study aims to shed light on both trade and technology effects on the Australian labour market during the study period 1983(4)‐1995(3). The study uses unit root and multicointegration econometrics, general to specific modelling and encompassing tests to test how trade liberalisation and technical progress have immiserised Australian labour by increasing unemployment or through the widening of skill differentiated wage disparity. The study concludes with some policy perspectives on labour market deregulation in Australia.

People with lived experience of mental health problems (MHPs) are often marginalised and have difficulty achieving community inclusion. Citizenship, a relatively novel concept in mental health, provides a means of understanding what is necessary for marginalised individuals and groups to gain a sense of belonging within their communities. By exploring the “what, why, how and who” of citizenship, the purpose of this paper is to provide a rationale for the inclusion of citizenship as part of a person-centred and holistic mental health strategy.

A community-based participatory research (CBPR) approach, with peer researchers, was adopted to develop a model of citizenship within a Scottish context. The aim of the model is to link the concept of citizenship with specific strategies that systems, agencies and individuals can use within mental health policy and practice to promote greater inclusion and participation. Concept mapping was used as part of a mixed-methods participatory methodology and data were then analysed using multivariate statistical methods of multidimensional scaling and hierarchical cluster analysis.

It is argued that using a CBPR approach, utilising concept mapping, encourages the development of a model of citizenship that is entirely grounded in the perspectives and lived experiences of people with MHPs. The need for adequate resources, preparatory work, training, research management and reflexive practice are key to the success of a CBPR approach with peer researchers.

Working with peer researchers and key stakeholder groups is central to a CBPR approach and the implementation of a model of citizenship within mental health policy and practice. Developing a model of citizenship derived specifically from the experiences of people with lived experience is likely to promote their inclusion. It provides a means of challenging the structural deficits and inequalities that cause distress and prevent people with lived experience of MHPs of recovering their citizenship.