Improved response surface method for anti-slide reliability analysis of gravity dam based on weighted regression

The aim of this study was to design and construct an improved response surface method （RSM） based on weighted regression for the anti-slide reliability analysis of concrete gravity dam. The limitation and lacuna of the traditional RSM were briefly analyzed. Firstly, based on small experimental points, research was devoted to an improved RSM with singular value decomposition techniques. Then, the method was used on the basis of weighted regression and deviation coefficient correction to reduce iteration times and experimental points and improve the calculation method of checking point. Finally, a test example was given to verify this method. Compared with other conventional algorithms, this method has some strong advantages： this algorithm not only saves the arithmetic operations but also greatly enhances the calculation efficiency and the storage efficiency.     

<Emphasis Type="Italic">Minerva</Emphasis> and the Development of Science (Policy) Studies

This article analyzes the transformation of Minerva from an intellectual towards a scholarly journal by making use of bibliometric methods. The aim is to provide some empirical insights that help to understand what properties of the journal changed in the course of this transformation process. Minerva was one of the first journals that reflected on science and its role in society and science policy in particular. Analyzing the development of the journal sheds light on the emergence of science (policy) studies and on Minerva’s role as a forerunner in this field. In a first step, the methods will be described. The second section provides some empirical results of the publication output of Minerva and its relations to other journals in the field. The empirical findings are put into a broader perspective in the concluding third section.     

The Congress for Cultural Freedom, <Emphasis Type="Italic">Minerva</Emphasis>, and the Quest for Instituting “Science Studies” in the Age of Cold War

The Congress for Cultural Freedom is remembered as a paramount example of the “cultural cold wars.” In this paper, I discuss the ways in which this powerful transnational organization sought to promote “science studies” as a distinct – and politically relevant – area of expertise, and part of the CCF broader agenda to offer a renewed framework for liberalism. By means of its Study Groups, international conferences and its periodicals, such as Minerva, the Congress developed into an influential forum for examining the ways Big Science impacted the relations between science, society, and politics, thus constituting a semi-institutional niche for Science Studies before its professionalization within academia during the 1970s. I argue that the Congress contributed to the construction of public space in which the relations between science, society and politics were debated, and science was reconceptualized as a social activity. The vision of “science studies” the CCF-associated intellectuals promulgated was different from the science studies we know today. Yet, this alternative vision, in which the issues of science politics appeared inseparable from those of science policy, science organization, and science governance, constituted the “pre-history” of science studies today.     

Newborns' face recognition: role of inner and outer facial features

Existing data indicate that newborns are able to recognize individual faces, but little is known about what perceptual cues drive this ability. The current study showed that either the inner or outer features of the face can act as sufficient cues for newborns' face recognition (Experiment 1), but the outer part of the face enjoys an advantage over the inner part (Experiment 2). Inversion of the face stimuli disrupted recognition when only the inner portion of the face was shown, but not when the whole face was fully visible or only the outer features were presented (Experiment 3). The results enhance our picture of what information newborns actually process and encode when they discriminate, learn, and recognize faces.     

The Middle East Books Market: a Personal Overview

A concise review is presented of the essential elements of the book publishing and bookselling business in a complex and diverse market. Demographics create the diversity while Arabic is the one language spoken across a multitude of different countries. Three features are common to all of these countries and they are: the dominance of English as the second language, education has and will remain to be a priority, and economic pressures cause price sensitivity to be a major challenge especially in the educational market segments. It is the price sensitivity as a key factor for the lack of respect for intellectual property and copyright regulations. A review of distribution and retail stores is a very important topic in relation to this complex collection of countries. The emergence of e-books is discussed especially in the educational, professional and reference market segments. Finally, there is a review of the Arabic language publishers and local book fairs to bring this article to closure.     

Finding related sentence pairs in MEDLINE

We explore the feasibility of automatically identifying sentences in different MEDLINE abstracts that are related in meaning. We compared traditional vector space models with machine learning methods for detecting relatedness, and found that machine learning was superior. The Huber method, a variant of Support Vector Machines which minimizes the modified Huber loss function, achieves 73% precision when the score cutoff is set high enough to identify about one related sentence per abstract on average. We illustrate how an abstract viewed in PubMed might be modified to present the related sentences found in other abstracts by this automatic procedure.     

Statistical query expansion for sentence retrieval and its effects on weak and strong queries

The retrieval of sentences that are relevant to a given information need is a challenging passage retrieval task. In this context, the well-known vocabulary mismatch problem arises severely because of the fine granularity of the task. Short queries, which are usually the rule rather than the exception, aggravate the problem. Consequently, effective sentence retrieval methods tend to apply some form of query expansion, usually based on pseudo-relevance feedback. Nevertheless, there are no extensive studies comparing different statistical expansion strategies for sentence retrieval. In this work we study thoroughly the effect of distinct statistical expansion methods on sentence retrieval. We start from a set of retrieved documents in which relevant sentences have to be found. In our experiments different term selection strategies are evaluated and we provide empirical evidence to show that expansion before sentence retrieval yields competitive performance. This is particularly novel because expansion for sentence retrieval is often done after sentence retrieval (i.e. expansion terms are mined from a ranked set of sentences) and there are no comparative results available between both types of expansion. Furthermore, this comparison is particularly valuable because there are important implications in time efficiency. We also carefully analyze expansion on weak and strong queries and demonstrate clearly that expanding queries before sentence retrieval is not only more convenient for efficiency purposes, but also more effective when handling poor queries.