Two non-synonymous markers in PTPN21, identified by genome-wide association study data-mining and replication, are associated with schizophrenia

We conducted data-mining analyses of genome wide association (GWA) studies of the CATIE and MGS-GAIN datasets, and found 13 markers in the two physically linked genes, PTPN21 and EML5, showing nominally significant association with schizophrenia. Linkage disequilibrium (LD) analysis indicated that all 7 markers from PTPN21 shared high LD (r(2)>0.8), including rs2274736 and rs2401751, the two non-synonymous markers with the most significant association signals (rs2401751, P=1.10 × 10(-3) and rs2274736, P=1.21 × 10(-3)). In a meta-analysis of all 13 replication datasets with a total of 13,940 subjects, we found that the two non-synonymous markers are significantly associated with schizophrenia (rs2274736, OR=0.92, 95% CI: 0.86-0.97, P=5.45 × 10(-3) and rs2401751, OR=0.92, 95% CI: 0.86-0.97, P=5.29 × 10(-3)). One SNP (rs7147796) in EML5 is also significantly associated with the disease (OR=1.08, 95% CI: 1.02-1.14, P=6.43 × 10(-3)). These 3 markers remain significant after Bonferroni correction. Furthermore, haplotype conditioned analyses indicated that the association signals observed between rs2274736/rs2401751 and rs7147796 are statistically independent. Given the results that 2 non-synonymous markers in PTPN21 are associated with schizophrenia, further investigation of this locus is warranted.

The formal specification of abstract data types and their implementation in Fortran 90: Implementation issues concerning the use of pointers

In this paper we continue our investigation into the development of computational-science software based on the identification and formal specification of Abstract Data Types (ADTs) and their implementation in Fortran 90. In particular, we consider the consequences of using pointers when implementing a formally specified ADT in Fortran 90. Our aim is to highlight the resulting conflict between the goal of information hiding, which is central to the ADT methodology, and the space efficiency of the implementation. We show that the issue of storage recovery cannot be avoided by the ADT user, and present a range of implementations of a simple ADT to illustrate various approaches towards satisfactory storage management. Finally, we propose a set of guidelines for implementing ADTs using pointers in Fortran 90. These guidelines offer a way gracefully to provide disposal operations in Fortran 90. Such an approach is desirable since Fortran 90 does not provide automatic garbage collection which is offered by many object-oriented languages including Eiffel, Java, Smalltalk, and Simula.

“Signal, image and video processing” special issue: Semantic representations for social behavior analysis in video surveillance systems

No abstract available

Cases, Materials and Text on National, Supranational and International Non-Discrimination Law

This casebook, the result of the collaborative efforts of a panel of experts from various EU Member States, is the latest in the Ius Commune Casebook series developed at the Universities of Maastricht and Leuven. The book provides a comprehensive and skilfully designed resource for students, practitioners, researchers, public officials, NGOs, consumer organisations and the judiciary. In common with earlier books in the series, this casebook presents cases and other materials (legislative materials, international and European materials, excerpts from books or articles). As non-discrimination law is a comparatively new subject, the chapters search for and develop the concepts of discrimination law on the basis of a wide variety of young and often still emerging case law and legislation. The result is a comprehensive textbook with materials from a wide variety of EU Member States. The book is entirely in English (i.e. materials are translated where not available in English). At the end of each chapter a comparative overview ties the material together, with emphasis, where appropriate, on existing or emerging general principles in the legal systems within Europe.
The book illustrates the distinct relationship between international, European and national legislation in the field of non-discrimination law. It covers the grounds of discrimination addressed in the Racial Equality and Employment Equality Directives, as well as non-discrimination law relating to gender. In so doing, it covers the law of a large number of EU Member States, alongside some international comparisons.
The Ius Commune Casebook on Non-Discrimination Law
- provides practitioners with ready access to primary and secondary legal material needed to assist them in crafting test case strategies.
- provides the judiciary with the tools needed to respond sensitively to such cases.
- provides material for teaching non-discrimination law to law and other students.
- provides a basis for ongoing research on non-discrimination law.
- provides an up-to-date overview of the implementation of the Directives and of the state of the law.
This Casebook is the result of a project which has been supported by a grant from the European Commission's Anti-Discrimination Programme.

Assessment of Atomic Data: Problems and Solutions

For the reliable analysis and modeling of astrophysical, laser-produced, and fusion plasmas, atomic data are required for a number of parameters, including energy levels, radiative rates, and electron impact excitation rates. Such data are desired for a range of elements (H to W) and their many ions. However, measurements of atomic data, mainly for radiative and excitation rates, are not feasible for many species, and therefore, calculations are needed. For some ions (such as of C, Fe, and Kr), there is a variety of calculations available in the literature, but often, they differ significantly from one another. Therefore, there is a great demand from the user community to have data "assessed" for accuracy so that they can be confidently applied to the modeling of plasmas. In this paper we highlight the difficulties in assessing atomic data and offer some solutions for improving the accuracy of calculated results.

Data Cleaning and Outlier Removal: Application in Human Skin Detection

An outlier removal based data cleaning technique is proposed to
clean manually pre-segmented human skin data in colour images.
The 3-dimensional colour data is projected onto three 2-dimensional
planes, from which outliers are removed. The cleaned 2 dimensional
data projections are merged to yield a 3D clean RGB data. This data
is finally used to build a look up table and a single Gaussian classifier
for the purpose of human skin detection in colour images.