A Low Power Error Detection in the Syndrome Calculator Block for Reed-Solomon Codes: RS(204,188)

Reed-Solomon (RS) codes have been widely adopted in many modern communication systems. This paper describes a new method for error detection in the syndrome calculator block of RS decoders. The main feature of this method is to prove that it is possible to compute only a few syndrome coeffi-cients — less than half — to detect whether the codeword is correct. The theoretical estimate of the prob-ability that the new algorithm failed is shown to depend on the number of syndrome coefficients computed. The algo...     

A survey of expressed genes in Caenorhabditis elegans.

As an adjunct to the genomic sequencing of Caenorhabditis elegans, we have investigated a representative cDNA library of 1,517 clones. A single sequence read has been obtained from the 5' end of each clone, allowing its characterization with respect to the public databases, and the clones are being localized on the genome map. The result is the identification of about 1,200 of the estimated 15,000 genes of C. elegans. More than 30% of the inferred protein sequences have significant similarity to existing sequences in the databases, providing a route towards in vivo analysis of known genes in the nematode. These clones also provide material for assessing the accuracy of predicted exons and splicing patterns and will lead to a more accurate estimate of the total number of genes in the organism than has hitherto been available.     

A CLUSTERING ALGORITHM FOR MIXED NUMERIC AND CATEGORICAL DATA

Most of the earlier work on clustering mainly focused on numeric data whose inherent geometric properties can be exploited to naturally define distance functions between data points. However, data mining applications frequently involve many datasets that also consists of mixed numeric and categorical attributes. In this paper we present a clustering algorithm which is based on the k-means algorithm. The algorithm clusters objects with numeric and categorical attributes in a way similar to k-means. The object similarity measure is derived from both numeric and categorical attributes. When applied to numeric data, the algorithm is identical to the k-means. The main result of this paper is to provide a method to update the “cluster centers“ of clustering objects described by mixed numeric and categorical attributes in the clustering process to minimise the clustering cost function. The clustering performance of the algorithm is demonstrated with the two well known data sets, namely credit approval and abalone databases.     

Chromosome-wide SNPs reveal an ancient origin for Plasmodium falciparum

The Malaria's Eve hypothesis, proposing a severe recent population bottleneck (about 3,000-5,000 years ago) of the human malaria parasite Plasmodium falciparum, has prompted a debate about the origin and evolution of the parasite. The hypothesis implies that the parasite population is relatively homogeneous, favouring malaria control measures. Other studies, however, suggested an ancient origin and large effective population size. To test the hypothesis, we analysed single nucleotide polymorphisms (SNPs) from 204 genes on chromosome 3 of P. falciparum. We have identified 403 polymorphic sites, including 238 SNPs and 165 microsatellites, from five parasite clones, establishing chromosome-wide haplotypes and a dense map with one polymorphic marker per approximately 2.3 kilobases. On the basis of synonymous SNPs and non-coding SNPs, we estimate the time to the most recent common ancestor to be approximately 100,000-180,000 years, significantly older than the proposed bottleneck. Our estimated divergence time coincides approximately with the start of human population expansion, and is consistent with a genetically complex organism able to evade host immunity and other antimalarial efforts.     

Modeling the Knowledge Creation Process of Graduate Research

Graduate students who are beginning academic research want to learn how to create and verify new knowledge in their research. Their supervisors, on the other hand, are seeking appropriate research environments including effective research guidance methods. In order to meet these demands, this paper proposes a knowledge creation model that supports the objectives of both graduate students and their supervisors. This is an academic knowledge creation model for individuals supported by a group and its origin can be traced back to a famous organizational knowledge creation model. Since this type of model is constructed from empirical knowledge, it is not easy to prove its objective significance. But, this paper tries to show the effectiveness of the proposed model as an initial stage of model validation based on a questionnaire survey of students in a graduate school in China.     

Macrophage migration inhibitory factor (MIF) modulates trophic signaling through interaction with serine protease HTRA1

Macrophage migration inhibitory factor (MIF), a small conserved protein, is abundant in the immune- and central nervous system (CNS). MIF has several receptors and binding partners that can modulate its action on a cellular level. It is upregulated in neurodegenerative diseases and cancer although its function is far from clear. Here, we report the finding of a new binding partner to MIF, the serine protease HTRA1. This enzyme cleaves several growth factors, extracellular matrix molecules and is implicated in some of the same diseases as MIF. We show that the function of the binding between MIF and HTRA1 is to inhibit the proteolytic activity of HTRA1, modulating the availability of molecules that can change cell growth and differentiation. MIF is therefore the first endogenous inhibitor ever found for HTRA1. It was found that both molecules were present in astrocytes and that the functional binding has the ability to modulate astrocytic activities important in development and disease of the CNS.