Today’s globally networked society places great demand on the dissemination and sharing of information. While in the past released information was mostly in tabular and statistical form, many situations call today for the release of specific data (microdata). In order to protect the anonymity

Molluscs, comprising one of the most successful phyla, lack clear evidence of adaptive immunity and yet thrive in the oceans, which are rich in viruses. There are thought to be nearly 120,000 species of Mollusca, most living in marine habitats. Despite the extraordinary abundance of viruses in oceans, molluscs often have very long life spans (10 to 100 years). Thus, their innate im-munity must be highly effective at countering viral infections. Antiviral compounds are a crucial component of molluscan de-fenses against viruses and have diverse mechanisms of action against a wide variety of viruses, including many that are human pathogens. Antiviral compounds found in abalone, oyster, mussels, and other cultured molluscs are available in large supply, providing good opportunities for future research and development. However, most members of the phylumMollusca have not been examined for the presence of antiviral compounds. The enormous diversity and adaptations of molluscs imply a potential source of novel antiviral compounds for future drug discovery. Mollusca is the second-most-diverse phylum, with nearly85,000 described species (1, 2) and a total world estimate of 120,000 to 200,000 species (3). Molluscs are characterized into eight classes, including Gastropoda, Bivalvia, Scaphopoda, Cephalopoda, Polyplacophora, Monoplacophora, Caudofoveata, and Solenogastres, which can be found in a wide range of ecolog-ical niches frommarine (52,525 described species) and freshwater

. It then elaborates on the phase-wise development of cultures and organizational structures. Managing corporate improvement by building cultures of trust is the central focus of this contribution. By showing the cultural dimensions of Great Places to Work and their workplace practices, worthwhile experiences leading

This paper presents a new algorithm for mobile robot localization, called Monte Carlo Localization (MCL). MCL is a version of Markov localization, a family of probabilistic approaches that have recently been applied with great practical success. However, previous approaches were either

partitioning of the object space and if features were independently displayed within a category. This Bayesian analysis is placed within an incremental categorization algorithm. The resulting rational model accounts for effects of central tendency of categories, effects of specific instances, learning

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in higher education imhe

institutional management in higher education imhe

As software becomes more and more complex, it is more and more important to structure it well. Well-structured software is easy to write, easy to debug, and provides a collection of modules that can be re-used to reduce future programming costs. Conventional languages place conceptual limits

this paper. Let us place it within the neural network perspective, and particularly that of learning. The area of neural networks has greatly benefited from its unique position at the crossroads of several diverse scientific and engineering disciplines including statistics and probability theory