Description:
In recent decades there has been a shift in labor market public policy from a culture of early retirement to one centered on hiring older workers, i.e., those aged over 50. The culture of early exit flourished in most major industrialized economies until the 1990s. Previously, older workers who left the workforce prematurely were regarded to be early retirees rather than unemployed. Their joblessness ended not with their reentering the workforce but transferring to pensions (Casey and Laczko 1989). Subsequently, there has been a policy shift towards prolonging working lives that has been generated by population aging in general as well as the aging of workforces in specific industry sectors, such as nursing and teaching.
Description:
Brittleness of rock is one of the most critical features for design of underground excavation project. Therefore, proper assessing of rock brittleness can be very useful for designers and evaluators of geotechnical applications. In this study, feasibility of genetic programming (GP) model and non-linear multiple regression (NLMR) in predicting brittleness of intact rocks is examined. For this purpose, a dataset developed by conducting various rock tests including uniaxial compressive strength, Brazilian tensile strength, unit weight and brittleness via punch penetration on rock samples gathered from 48 tunnels projects around the world is utilized herein. Considering multiple inputs, several GP models were constructed to estimate brittleness index of the rock and finally, the best GP model was selected. Note that, GP can make an equation for predicting output of the system using model inputs. To show applicability of the developed GP model, non-linear multiple regression (NLMR) was also applied and developed. Considering some model performance indices, performance prediction of the GP and NLMR models were evaluated and it was found that the GP model is superior to NLMR one. Based on coefficient of determination (R (2)) of testing datasets, by proposing GP model, it can be improved from 0.882 (obtained by NLMR model) to 0.904. It is worth mentioning that the proposed predictive models in this study should be planned and used for the similar types of rock and the established inputs ranges.
Description:
Biotic stress is one of the major environmental factors affecting plants. Viruses, fungi, bacteria, weeds, insects, and other pests and pathogens represent a major constraint to agricultural productivity and a serious threat to vegetable and grain crops. Plant protection against pathogens and pests is a commercially important issue and one of the main directions of researches. Almost half of new infectious diseases identified in plants during the past 10 years have a viral nature. The number and distribution areas of some plant viruses in Europe have been increasing rapidly during the past 35 years that caused big problems from an economic point of view. Viral diseases have also become a real threat for different cultivars of vegetables, grains, and other agricultural crops in our country. It causes extensive leaf yellowing, stem and leaf deformation, reducing the fruit quality, substantial yield loss, and shortening the lifecycle of crops. The probable cause of decay of virus-infected plants is not only the virus activity itself but also reduced tolerance to unfavorable environmental conditions. The identification of the viruses affecting plants and the study of the plant responses are very important for the better understanding of the plant–virus interactions and for developing the tendency to reduce the plant virus-associated risks in Azerbaijan. Therefore, the main goal of the present study is to identify the most widespread plant viruses in Azerbaijan using different molecular techniques and to evaluate some characteristics of plant response to viral stress
Description:
We consider problems of vector optimization with preferences that are not necessarily a pre-order relation. We introduce the class of functions which can serve for a scalarization of these problems and consider a scalar duality based on recently developed methods for non-linear penalization scalar problems with a single constraint.
Description:
This book collects multiple disciplinary voices which explore current research and perspectives to discuss how sprirituality is understood, interpreted and applied in a range of contexts. It addresses sprirituality in combination with such topics as Christian mysiticism, childhood and adolescent education, midwifery, and sustainability. It links spirituality to a variety of disciplines, including cognitive neuroscience, sociology, and psychology. Finally, it discusses the application of spirituality within the context of social work, teaching, health care, and occupational therapy. A final chapter provides an analytical discussion of the different voices that appear in the book and offers a holistic description of spirituality which has the potential to bring some unity to the meaning, expression and practice of spirituality across a variety of disciplines as well as across cultural, religious and secular worldviews.
Description:
In this paper a novel feature selection technique based on mutual dependency modelling between genes is proposed for multiclass microarray gene expression classification. Several studies on analysis of gene expression data has shown that the genes (whether or not they belong to the same gene group) get co-expressed via a variety of pathways. Further, a gene may participate in multiple pathways that may or may not be co-active for all samples. It is therefore biologically meaningful to simultaneously divide genes into functional groups and samples into co-active categories. This can be done by modeling gene profiles for multiclass microarray gene data sets based on mutual dependency models, which model complex gene interactions. Most of the current works in multiclass microarray gene expression studies are based on statistical models with little or no consideration of gene interactions. This has led to lack of robustness and overly optimistic estimates of accuracy and noise reduction. In this paper, we propose multivariate analysis techniques which model the mutual dependency between the features and take into account complex interactions for extracting a subset of genes. The two techniques, the cross modal factor analysis (CFA) and canonical correlation analysis(CCA) show a significant reduction in dimensionality and class-prediction error, and improvement in classification accuracy for multiclass microarray gene expression datasets.
Description:
In this paper, we propose a new algorithm for global minimization of functions represented as a difference of two convex functions. The proposed method is a derivative free method and it is designed by adapting the extended cutting angle method. We present preliminary results of numerical experiments using test problems with difference of convex objective functions and box-constraints. We also compare the proposed algorithm with a classical one that uses prismatical subdivisions.
Description:
Confirmatory factor analysis was used to model a multitrait (ADHD-inattention and hyperactivity/impulsivity) by multi-source (teachers and parents) design across a 3-month interval in a sample of 360 Australian elementary school children. The purpose was to evaluate the convergent and discriminant validity of the ADHD-inattention (IN) and hyperactivity/ impulsivity (H/I) measures. Although similar traits and similar sources showed stronger correlations across time than dissimilar traits and dissimilar sources, the amount of source variance in the ADHD-IN and ADHD-H/I measures was substantial and consistent across the interval (M = 59%; range = 35-84%). This large amount of source variance raises the possibility that the correlations of the IN and H/I rating scales with other constructs (e.g., social competence, conduct problems) represent mostly source rather than trait effects. Multitrait by multisource analyses provide a means to answer this question and further advance understanding of ADHD.
Description:
Clusterwise linear regression consists of finding a number of linear regression functions each approximating a subset of the data. In this paper, the clusterwise linear regression problem is formulated as a nonsmooth nonconvex optimization problem and an algorithm based on an incremental approach and on the discrete gradient method of nonsmooth optimization is designed to solve it. This algorithm incrementally divides the whole dataset into groups which can be easily approximated by one linear regression function. A special procedure is introduced to generate good starting points for solving global optimization problems at each iteration of the incremental algorithm. The algorithm is compared with the multi-start Spath and the incremental algorithms on several publicly available datasets for regression analysis.
Description:
This paper presents a canonical duality theory for solving general nonconvex/discrete constrained minimization problems. By using the canonical dual transformation, these challenging problems can be reformulated as a unified canonical dual problem (i.e., with zero duality gap) in continuous space, which can be solved easily to obtain global optimal solution. Some basic concepts and general theory in canonical systems are reviewed. Applications to Boolean least squares problems are illustrated.
Description:
Cultural studies in science education have been gaining more attention in recent years. One much-debated theme in this area is teaching culturally related knowledge in modern school science. Within the context of science education, “culturally related knowledge” refers to the knowledge that can be treated as science, but has different cultural origins from that of Western Modern Science (WMS) or Euro-centric science (Aikenhead and Ogawa 2007). Different points of view about the nature of science and the relationship between science education and culture have a direct influence on people’s opinions of the content and pedagogy of science teaching in school. "From introduction"
Description:
Abandoned historical gold mining wastes often exist as geographically extensive, unremediated, and poorly contained deposits that contain elevated levels of As and other potentially toxic elements (PTEs). One of the key variables governing human exposure to PTEs in mine waste is particle size. By applying a size-resolved approach to mine waste characterisation, this study reports on the proportions of mine waste relevant to human exposure and mobility, as well as their corresponding PTE concentrations, in four distinct historical mine wastes from the gold province in Central Victoria, Australia. To the best of our knowledge, such a detailed investigation and comparison of historical mining wastes has not been conducted in this mining-affected region. Mass distribution analysis revealed notable proportions of waste material in the readily ingestible size fraction (aecurrency sign250 A mu m; 36.1-75.6 %) and the dust size fraction (aecurrency sign100 A mu m; 5.9-45.6 %), suggesting a high potential for human exposure and dust mobilisation. Common to all mine waste types were statistically significant inverse trends between particle size and levels of As and Zn. Enrichment of As in the finest investigated size fraction (aecurrency sign53 A mu m) is of particular concern as these particles are highly susceptible to long-distance atmospheric transport. Human populations that reside in the prevailing wind direction from a mine waste deposit may be at risk of As exposure via inhalation and/or ingestion pathways. Enrichment of PTEs in the finer size fractions indicates that human health risk assessments based on bulk contaminant concentrations may underestimate potential exposure intensities.
Description:
The effectiveness of vocational education and training (VET) systems depends upon their teachers. The teachers are regarded as “dual professionals,” requiring expertise in both their background industry areas and in VET pedagogy itself. This chapter uses Australia as a case study of what happens when the accepted regime of qualifications for VET teachers alters. In Australia full-time VET teachers were, until recently, required to undertake degree level qualifications in VET pedagogy, taught at universities, either before or, more usually, after entering the occupation. The required level has now reduced to the regulatory minimum of a Certificate IV level qualification, taught by training providers not universities, and often provided to their own teachers. The qualification contains only 300 nominal hours of training. It has been recognized as a particularly poorly taught qualification, requiring the introduction of a high degree of regulation and most recently a special compliance framework for training providers wishing to deliver it. In this chapter, the historical path of the decline in VET teacher professionalism in Australia is charted, including research evidence from a national project managed by the author, about the effects of higher-level qualifications on VET teacher practices and quality and teachers’ propensity to engage in professional development. A conceptual model of the attributes of professional VET teachers with regard to qualifications and professional development is presented. The chapter concludes with some recommendations for change and implications for other countries.