论严修与直隶教育近代化

严修是中国近代著名教育理论家和实践家,其教育主张及教育实践极大促进了直隶教育的近代化。他提出了改革进而废除科举制的主张,这为直隶教育向近代化方向迈进清除了最大的障碍;在学部主政期间他创立新的教育体制,为直隶教育近代化奠定了制度基础;此外,他兴办了各级各类的新式学堂,形成了直隶近代教育体系的雏形。     

Scenarios in Europe—Who uses them and why?

The authors of this article describe a study of European companies the aim of which was to review the extent of multiple scenario analysis in company planning. They describe the differences in planning between users and non-users of the system, and analyse the benefits and drawbacks of using the system.     

A new approach in vocational rehabilitation in Iceland: preliminary report

The lack of vocational rehabilitation in Iceland inspired the Janus Rehabilitation initiative in the year 2000. The team currently consists of two occupational therapists, a social worker, a physiotherapist, a psychologist, and a physician. Janus uses resources from local education establishments and is located at the Reykjavík Technical School. A client-centred approach is used, enabling a flexible rehabilitation timeframe. The aim is to help the client back to employment/education. Advantage is taken of the facilities of the school where integration between education and rehabilitation takes place. Forty individuals have been admitted, with a mean time from work of 2.9 years, (range: 0-11 years). Seventeen (43%) have returned to employment/education. Twenty-three of those entering the programme are still on invalidity pension. The Canadian Occupational Performance Measurement (COPM) shows improvement in occupational performance and satisfaction. The Icelandic Quality of Life measurement also shows improvement. The results have been promising. However, a larger group is needed in order to draw clear unequivocal conclusions.     

Multivariate log-Birnbaum–Saunders regression models

In this paper, we present a multivariate version of the skewed log-Birnbaum–Saunders regression model. This new family of distributions holds good properties such as marginal variables following univariate skewed log-Birnbaum–Saunders distributions, besides presenting the usual log-Birnbaum–Saunders distribution as a particular case. Furthermore, the model parameters are estimated through maximum-likelihood methods, a closed-form expression for the Fisher’s information matrix is presented, and testing hypothesis for model parameters is performed. Two real datasets are analyzed and results are discussed.     

Welfare State Development in Latin America and the Caribbean (1970s–2000s): Multidimensional Welfare Index,Its Methodology and Results

There is an ongoing debate between focalization and universalization on welfare policies as the best way to develop the welfare state in Latin America and the Caribbean. However, there is a need to develop a measure that exhibits the multidimensional nature of the welfare state, instead of focusing on the social spending dimension. Segura-Ubiergo (The political economy of the welfare state in Latin America: globalization, democracy and development. Cambridge University Press, New York, 2007) constructed a welfare effort index (WEI) to facilitate understand the relative degrees of welfare state development among Latin American countries. The WEI focuses mainly on social spending and ignores the other dimensions of welfare. Based on a comparative analysis of 17 Latin American countries and following the methodology of Segura-Ubiergo, a new index that aims at enriching the WEI was constructed. The new index is multidimensional in that it has eight indicators relating to three dimensions of welfare: social spending, coverage of welfare programs and outcome of welfare institutions. Principal component analysis was used for reducing the indicators into three indexes that represent three proposed dimensions of welfare. The combination of these three indexes gives the multidimensional welfare index. The results of the index account for more than 75 % of the data variance.     

An ant colony optimization approach for the proportionate multiprocessor open shop

Multiprocessor open shop makes a generalization to classical open shop by allowing parallel machines for the same task. Scheduling of this shop environment to minimize the makespan is a strongly NP-Hard problem. Despite its wide application areas in industry, the research in the field is still limited. In this paper, the proportionate case is considered where a task requires a fixed processing time independent of the job identity. A novel highly efficient solution representation is developed for the problem. An ant colony optimization model based on this representation is proposed with makespan minimization objective. It carries out a random exploration of the solution space and allows to search for good solution characteristics in a less time-consuming way. The algorithm performs full exploitation of search knowledge, and it successfully incorporates problem knowledge. To increase solution quality, a local exploration approach analogous to a local search, is further employed on the solution constructed. The proposed algorithm is tested over 100 benchmark instances from the literature. It outperforms the current state-of-the-art algorithm both in terms of solution quality and computational time.

     

Environmental and social supply chain management sustainability practices: construct development and measurement

The purpose of this paper is to conceptualise and operationalise the concept of supply chain management sustainability practices. Based on a multi-stage procedure involving a literature review, expert Q-sort and pre-test process, pilot test and survey of 156 supply chain directors and managers in Ireland, we develop a multidimensional conceptualisation and measure of social and environmental supply chain management sustainability practices. The research findings show theoretically sound constructs based on four underlying sustainable supply chain management practices: monitoring, implementing systems, new product and process development and strategy redefinition. A two-factor model is then identified as the most reliable: comprising process-based and market-based practices.     

A comparison of classification models to identify the Fragile X Syndrome

The main models of machine learning are briefly reviewed and considered for building a classifier to identify the Fragile X Syndrome (FXS). We have analyzed 172 patients potentially affected by FXS in Andalusia (Spain) and, by means of a DNA test, each member of the data set is known to belong to one of two classes: affected, not affected. The whole predictor set, formed by 40 variables, and a reduced set with only nine predictors significantly associated with the response are considered. Four alternative base classification models have been investigated: logistic regression, classification trees, multilayer perceptron and support vector machines. For both predictor sets, the best accuracy, considering both the mean and the standard deviation of the test error rate, is achieved by the support vector machines, confirming the increasing importance of this learning algorithm. Three ensemble methods - bagging, random forests and boosting - were also considered, amongst which the bagged versions of support vector machines stand out, especially when they are constructed with the reduced set of predictor variables. The analysis of the sensitivity, the specificity and the area under the ROC curve agrees with the main conclusions extracted from the accuracy results. All of these models can be fitted by free R programs.