一部近代中国的百科全书：未完成的中西文化之桥

上个世纪之交，一种新的文化现象出现在中国东部沿海城市——即中文的现代西式百科全书问世。这些新式教育工具以简洁的语言为现代社会文化中的众多问题提供了简明而有序的信息，其创新意义，远非彼时中国所使用的“工具书”一词所能概括。本文考察了黄摩西1911年出版的《普通百科新大辞典》，它被视为1903-1911年间中国出版的同类著作中最先进的一部。我们特别关注这部著作之成为“现代”工具书的那些特征，以此勾勒出这部辞书的现代的、世界主义的特质，同时也展示出学者黄摩西的学术成就；并从一个特定角度，呈现已成为晚清社会风格标志的西学东渐的过程。     

An integrated closed-loop product lifecycle management approach for reverse logistics design

Nowadays, reverse logistics is gaining importance for many companies in different industries. This importance is rooted in the fact that it generates profit and decreases the environmental impacts of products. Even though the decrease of environmental impacts is an indispensable requisite, reverse logistics design is only driven by cost indicators. The main reason behind this high cost is access to environmental information is difficult and is directly linked to data all along the lifecycle of the product. This paper presents a method by which reverse logistics design integrates environmental impacts based on the management of closed-loop product lifecycle. This method is divided into two processes: from beginning of life to end of life and from end of life to beginning of life. The first process integrates product data in order to calculate environmental impacts of the potential reverse logistics networks, whereas the second process selects the most appropriate reverse logistics network before optimising the product based on this particular network. The proposition is illustrated by a case study on a recycled aluminium automotive part.     

A novel feature selection scheme for high-dimensional data sets: four-Staged Feature Selection

Classification of high-dimensional data set is a big challenge for statistical learning and data mining algorithms. To effectively apply classification methods to high-dimensional data sets, feature selection is an indispensable pre-processing step of learning process. In this study, we consider the problem of constructing an effective feature selection and classification scheme for data set which has a small number of sample size with a large number of features. A novel feature selection approach, named four-Staged Feature Selection, has been proposed to overcome high-dimensional data classification problem by selecting informative features. The proposed method first selects candidate features with number of filtering methods which are based on different metrics, and then it applies semi-wrapper, union and voting stages, respectively, to obtain final feature subsets. Several statistical learning and data mining methods have been carried out to verify the efficiency of the selected features. In order to test the adequacy of the proposed method, 10 different microarray data sets are employed due to their high number of features and small sample size.     

MARS as an alternative approach of Gaussian graphical model for biochemical networks

The Gaussian graphical model (GGM) is one of the well-known modelling approaches to describe biological networks under the steady-state condition via the precision matrix of data. In literature there are different methods to infer model parameters based on GGM. The neighbourhood selection with the lasso regression and the graphical lasso method are the most common techniques among these alternative estimation methods. But they can be computationally demanding when the system's dimension increases. Here, we suggest a non-parametric statistical approach, called the multivariate adaptive regression splines (MARS) as an alternative of GGM. To compare the performance of both models, we evaluate the findings of normal and non-normal data via the specificity, precision, F-measures and their computational costs. From the outputs, we see that MARS performs well, resulting in, a plausible alternative approach with respect to GGM in the construction of complex biological systems.     

An Examination of Factors Affecting Economic Status and Finances Satisfaction of Families: A Comparison of Metropolitan and Rural Areas

Research on the family financial management behavior has gained a great impetus over 30 years. There has been a growing interest in the question of how families organize or manage their economic resources and financial satisfaction. The main purpose of this study is to examine factors affecting financial behaviors and financial satisfaction of families who live in metropolitan and rural areas. Participants in the study consist of women who are married and dwelling in Ankara and Karabuk cities of Turkey. A total of 3,046 female (with an approximate 87 % participation rate) are participated in the study on a voluntary (Ankara n = 1,300; Karabuk n = 1,746). Results indicated that 45.4 % of females have determined that economic decision making are always shared by couples (Ankara 41.9 %; Karabuk 47.9 %). Among women who lived in Ankara (62.3 %) have not saving their income, while the group of Karabuk (51.4 %) have sometimes saving. Similar results have been found in terms of the expenditure behaviors among the families who are living in both of the metropolitan and rural areas. The rates of the families living both in Ankara and Karabuk who state that they have become indebted due to various reasons (Ankara 56.5 %; Karabuk 72.9 %) is higher compared to those who state they have not become indebted. Among the females who stated that they are “very dissatisfied” from their savings behavior, “satisfied” with their expenditure behaviors and “dissatisfied” with their debt behaviors are higher percentage (50.6 %, 47.9 %, and 48.3 % respectively).     

Factors Motivating Individuals to Take Precautionary Action for an Expected Earthquake in Istanbul

Istanbul is expected to experience an earthquake in the near future, but individuals show limited interest in preparing for it. This study aims to identify the factors associated with taking action to prepare for an earthquake and mitigate its effects at the individual level. A field survey was carried out in 2007 in two districts of Istanbul with different levels of earthquake risk. Within these districts, three socioeconomic levels were considered. A total of 1,123 people were interviewed face to face. Analysis indicated that the educational level of the respondents was the leading factor associated with taking at least three measures, followed by living in a higher earthquake risk area, having participated in rescue and solidarity activities in previous earthquakes, a higher level of knowledge about earthquakes, home ownership, a higher score for action‐stimulating attitudes, being younger, and a higher general safety score, in that order. The findings pointed to the role of knowledge about earthquakes and possible mitigation/preparedness measures, and thus the importance of developing effective awareness programs. Such programs should also consider the characteristics of different groups in the population. Motivated individuals, such as those who have participated in rescue and solidarity activities in previous earthquakes, could be involved in reaching other people.     

Teachers as risk and resource factors in minority students’ school adjustment: an integrative review of qualitative research on acculturation

ABSTRACT

The present study is embedded in the contextual approach of acculturation research. It examines teachers’ attitudes and behaviors, teachers’ expectations as well as their teaching practices as risk and resource factors in minority students’ school adjustment. The study applies the method of content analysis and uses a deductively developed and inductively enriched system of categories. The results of the study provide an integrative review of qualitative research on the role teachers play in the acculturation process of minority youth and their adjustment outcomes in the school context.