Interlocking directorates and conflicts of interest: The Rotterdamsche Bankvereeniging, Müller & Co. and the Dutch financial crisis of the 1920s

How can interlocking directorates cause financial instability for universal banks? A detailed history of the Rotterdamsche Bankvereeninging in the 1920s answers this question in a case study. This large commercial bank adopted a new German-style universal banking business model from the early 1910s, sharing directors with the firms it financed as a means of controlling its interests. Then, in 1924, it required assistance from the Dutch state in order to survive a bank run brought on by public concerns over its close ties with Müller & Co., a trading conglomerate that suffered badly in the economic downturn of the early 1920s. Using a new narrative history combined with an interpretive model, this article shows how the interlocking directorates between the bank and this major client, and in particular the direction of influence of these interlocks, resulted in a conflict of interest that could not be easily overcome.

Analyzing Intergenerational Influences on Income Poverty & Economic Vulnerability with EU-SILC

The European Union Statistics of Income and Living Conditions
(EU-SILC) 2005 wave includes a special module on inter-generational
transmission of poverty. In addition to the standard data relating to income
and material deprivation, information relating to parental background and
childhood circumstances was collected for all household members aged over
24 and less than 66 at the end of the income reference period. In principle,
the module provides an unprecedented opportunity to apply a welfare regime
perspective to a comparative European analysis of the relationship between
poverty and social exclusion and parental characteristics and childhood
economic circumstances. In this paper, we seek to exploit such potential. In
pursuing this objective, it is necessary to take into account some of the
limitations of the data. We do by restricting our attention to a set of
countries where data issues seem less extreme. Finally, we compare findings
from one dimensional and multidimensional approaches to poverty and social
exclusion in order to provide an assessment of the extent to which our
analysis of welfare regime variation provides a coherent account of the
intergenerational transmission of disadvantage.

TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Autonomic management of non-functional concerns in distributed & parallel application programming

An approach to the management of non-functional concerns in massively parallel and/or distributed architectures that marries parallel programming patterns with autonomic computing is presented. The necessity and suitability of the adoption of autonomic techniques are evidenced. Issues arising in the implementation of autonomic managers taking care of multiple concerns and of coordination among hierarchies of such autonomic managers are discussed. Experimental results are presented that demonstrate the feasibility of the approach.