Investigating sexual strategies in a social community website

In this exploratory study we tried to corroborate existing findings of Sexual Strategies Theory (SST, Buss & Schmitt, 1993) by using data collected from an online community. A random sample of N = 460 German user profiles was drawn from Myspace, a social networking website. Sexual interests reported by the users were analyzed separately for men and women: “Dating” served as an indicator of short-term and interest in “Serious Relationship” as an indicator of long-term sexual strategy. Consistent with SST, a higher percentage of male than female users was interested in dating. However, men were also more interested in serious relationships, indicating that online partner search itself might be a short-term sexual strategy

Fostering Economic Development in Sub-Saharan African: What Role for Reforming Business Regulations?

Unternehmensregulierung; Reform; Strukturwandel; Entwicklung; Afrika südlich der Sahara

A PAUC-based Estimation Technique for Disease Classification and Biomarker Selection.

The partial area under the receiver operating characteristic curve (PAUC) is a well-established performance measure to evaluate biomarker combinations for disease classification. Because the PAUC is defined as the area under the ROC curve within a restricted interval of false positive rates, it enables practitioners to quantify sensitivity rates within pre-specified specificity ranges. This issue is of considerable importance for the development of medical screening tests. Although many authors have highlighted the importance of PAUC, there exist only few methods that use the PAUC as an objective function for finding optimal combinations of biomarkers. In this paper, we introduce a boosting method for deriving marker combinations that is explicitly based on the PAUC criterion. The proposed method can be applied in high-dimensional settings where the number of biomarkers exceeds the number of observations. Additionally, the proposed method incorporates a recently proposed variable selection technique (stability selection) that results in sparse prediction rules incorporating only those biomarkers that make relevant contributions to predicting the outcome of interest. Using both simulated data and real data, we demonstrate that our method performs well with respect to both variable selection and prediction accuracy. Specifically, if the focus is on a limited range of specificity values, the new method results in better predictions than other established techniques for disease classification

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multi-armed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low RKHS norm. We resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for GP optimization. We analyze GP-UCB, an intuitive upper-confidence based algorithm, and bound its cumulative regret in terms of maximal information gain, establishing a novel connection between GP optimization and experimental design. Moreover, by bounding the latter in terms of operator spectra, we obtain explicit sublinear regret bounds for many commonly used covariance functions. In some important cases, our bounds have surprisingly weak dependence on the dimensionality. In our experiments on real sensor data, GP-UCB compares favorably with other heuristical GP optimization approaches

Auswirkung intracerebroventrikulärer Baclofenapplikation auf Glutamat-, Aspartat- und Glycinfreisetzung und das Dopaminerge System im Ncl. paraventricularis hypothalami der Ratte

Eine Studie über den Einfluß intracerebroventrikulärer Baclofenapplikation auf Glutamat-, Aspartat- und Glycinfreisetzung und das Dopaminerge System im Ncl. paraventricularis hypothalami der Ratte. Tierxperimentelle Arbeit am Zentrum für Neurochirurgie

Preimage resistance beyond the birthday bound: Double-length hashing revisited

Security proofs are an essential part of modern cryptography. Often the challenge is not to come up with appropriate schemes but rather to technically prove that these satisfy the desired security properties. We provide for the first time techniques for proving asymptotically optimal preimage resistance bounds for block cipher based double length, double call hash functions. More precisely, we consider for some \keylength>\blocklength compression functions H:\{0,1\}^{\keylength+\blocklength} \rightarrow \{0,1\}^{2\blocklength} using two calls to an ideal block cipher with an \blocklength-bit block size. Optimally, an adversary trying to find a preimage for $H$ should require \Omega(2^{2\blocklength}) queries to the underlying block cipher. As a matter of fact there have been several attempts to prove the preimage resistance of such compression functions, but no proof did go beyond the \Omega(2^{\blocklength}) barrier, therefore leaving a huge gap when compared to the optimal bound. In this paper, we introduce two new techniques on how to lift this bound to \Omega(2^{2\blocklength}). We demonstrate our new techniques for a simple and natural design of $H$, being the concatenation of two instances of the well-known Davies-Meyer compression function

STUDIES IN THE EVALUATION OF A DOMAIN-INDEPENDENT NATURAL LANGUAGE QUERY SYSTEM

There is growing consensus that some of the most crucial questions concerning the feasibility and desirability of natural language interfaces to databases can only be resolved by empirical research. This paper reports the results of several empirical studies which investigated the same domain-independent natural language query system, using various applications in two different natural languages - English and German. Taken together, these experiments involved about 100 subjects and over 12,000 queries, constituting the bulk of empirical evaluations of natural query language systems reported to date. Some definitive results are derived from the combined experience, and plans are outlined to resolve several of the remaining issues.Information Systems Working Papers Serie

RAMSSES – Realisation and Demonstration of Advanced Material Solutions for Sustainable and Efficient Ships

The RAMSSES project aims to show the benefits of advanced materials in maritime applications by implementing 13 market driven demo cases. The entire process chain and a wide range of applications (structural components, equipment, ship integration, repair) are covered. Installation and assessment of demonstrators on shore or on board will reveal the high technology readiness. The test program, based on risk assessment and supervised by rule making bodies, targets on ensuring relevance for commercial approval beyond the project. While demonstrators will support commercialisation of specific products, RAMSSES is also engaged strategically in enabling more rapid and agile material innovation in the European Maritime industry. The first key element is a knowledge repository for test data and best practice procedures, allowing reuse of such information for similar future cases. Secondly, standardised risk scenarios will help easing approval processes in the future, and finally a new materials innovation platform will enhance continuous technology transfer within the maritime sector and beyond