308 research outputs found
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Negotiating intimacies in China's online social milieux
This is a cultural study into Chinaâs cyberspace focussing on romantic relationships. The research asks: how does culture influence the ways Chinese Internet users conduct romantic relationships online; and how might these relationships be seen to reproduce, extend and/or challenge the Confucian tradition governing social and familial practices, and the communist party-stateâs ideologies? While the first question explores the issue of how culture may shape the ways the Internet is used in China and impact on usersâ experiences of online romance, the second question examines how Chinese cultural traditions may in turn be shaped by the Internet. The aims are to understand: (1) how Chinese define and make sense of their online romantic relationships; and (2) the significance of the Internet in influencing the ways Chinese negotiate their intimacies in relation to wider familial relations, the party-stateâs paternalism and the social climate of growing individualism in the society
Efficient algorithms for finding disjoint paths in grids
The reconfiguration problem on VLSI/WSI processor arrays in the presence of faulty processors can be stated as the following integral multi-source routing problem: Given a set of N nodes (faulty processors or sources) in an mĂn rectangular grid where m, nâ€N, the problem to be solved is to connect the N nodes to distinct nodes at the grid boundary using a set of `disjoint' paths. This problem can be referred to as an escape problem which can be solved trivially in O(mnN) time. By exploiting all the properties of the network, planarity and regularity of a grid, integral flow, and unit capacity source/sink/flow, we can optimally compress the size of the grid from O(mn) to O(âmnN) and solve the problem in O(dâmnN), where d is the maximum number of disjoint paths found, for both the edge-disjoint and vertex-disjoint cases. In the worst case, d, m, n are O(N) and the result is O(N2.5). Note that this routing problem can also be solved with the same time complexity even if the disjoint paths have to be ended at another set of N nodes (sinks) in the grid instead of the grid boundary.published_or_final_versio
Escaping a grid by edge-disjoint paths
We study the edge-disjoint escape problem in grids: Given a set of n sources in a two-dimensional grid, the problem is to connect all sources to the grid boundary using a set of n edge-disjoint paths. Different from the conventional approach that reduces the problem to network flow problem, we solve the problem by ensuring that no rectangles in the grid contain more sources than outlets, a necessary and sufficient condition for the existence of a solution. Based on this condition, we give a greedy algorithm which finds the paths in O(n2) time, which is faster than the previous approaches. This problem has applications in point-to-point delivery, VLSI reconfiguration and package routing.published_or_final_versio
Optimal simulation of full binary trees on faulty hypercubes
The problem of operating full binary tree based algorithms on a hypercube with faulty nodes was investigated. Developing a method for embedding a full binary tree into the faulty hypercube is the solution to this problem. Two outcomes for embedding an (n-1)-tree into an n-cube with unit dilation and load, that were based on a new embedding technique, were presented. For the problem where the root can be mapped to any nonfaulty hypercube node, the optimum toleration of faults was shown. Moreover, it was demonstrated that the algorithm for the variable root embedding problem is maximal within a class algorithms called recursive embedding algorithms as far as the number of tolerable faults is concerned. Lastly, it was demonstrated that when an O(1/ân) fraction of nodes in the hypercube are faulty, a O(1)-load variable root embedding is not always possible regardless of the significance of the dilation.published_or_final_versio
Herpes zoster and its neurological complications
Ninety-three Chinese patients with cutaneous herpes zoster were seen during a 4-year period. Thoracic zoster occurred most commonly, followed by ophthalmic, cervical and lumbosacral zoster. Neurological complications were present in eleven patients (11.8%), the commonest being Ramsay-Hunt syndrome and segmental limb paresis. The clinical picture, pathogenesis, treatment and outcome of segmental limb paresis, myelitis and delayed contralateral hemiparesis following zoster ophthalmicus are discussed. Nine immunocompromised patients received intravenous adenine arabinoside (vidarabine) or acycloguanosine (acyclovir), and no cutaneous or visceral spread occurred in these patients.published_or_final_versio
Finding optimal threshold for correction error reads in DNA assembling
Background: DNA assembling is the problem of determining the nucleotide sequence of a genome from its substrings, called reads. In the experiments, there may be some errors on the reads which affect the performance of the DNA assembly algorithms. Existing algorithms, e.g. ECINDEL and SRCorr, correct the error reads by considering the number of times each length-k substring of the reads appear in the input. They treat those length-k substrings appear at least M times as correct substring and correct the error reads based on these substrings. However, since the threshold M is chosen without any solid theoretical analysis, these algorithms cannot guarantee their performances on error correction. Results: In this paper, we propose a method to calculate the probabilities of false positive and false negative when determining whether a length-k substring is correct using threshold M. Based on this optimal threshold M that minimizes the total errors (false positives and false negatives). Experimental results on both real data and simulated data showed that our calculation is correct and we can reduce the total error substrings by 77.6% and 65.1% when compared to ECINDEL and SRCorr respectively. Conclusion: We introduced a method to calculate the probability of false positives and false negatives of the length-k substring using different thresholds. Based on this calculation, we found the optimal threshold to minimize the total error of false positive plus false negative. © 2009 Chin et al; licensee BioMed Central Ltd.published_or_final_versio
Experience of adapting learning for practical electrical engineering laboratory experiments under remote teaching circumstances
The NRG1 gene is frequently silenced by methylation in breast cancers and is a strong candidate for the 8p tumour suppressor gene.
Neuregulin-1 (NRG1) is both a candidate oncogene and a candidate tumour suppressor gene. It not only encodes the heregulins and other mitogenic ligands for the ERBB family, but also causes apoptosis in NRG1-expressing cells. We found that most breast cancer cell lines had reduced or undetectable expression of NRG1. This included cell lines that had translocation breaks in the gene. Similarly, expression in cancers was generally comparable to or less than that in various normal breast samples. Many non-expressing cell lines had extensive methylation of the CpG island at the principal transcription start site at exon 2 of NRG1. Expression was reactivated by demethylation. Many tumours also showed methylation, whereas normal mammary epithelial fragments had none. Lower NRG1 expression correlated with higher methylation. Small interfering RNA (siRNA)-mediated depletion of NRG1 increased net proliferation in a normal breast cell line and a breast cancer cell line that expressed NRG1. The short arm of chromosome 8 is frequently lost in epithelial cancers, and NRG1 is the most centromeric gene that is always affected. NRG1 may therefore be the major tumour suppressor gene postulated to be on 8p: it is in the correct location, is antiproliferative and is silenced in many breast cancers
Genome maps across 26 human populations reveal population-specific patterns of structural variation.
Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2âkb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60âMb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome
Identification of disease-causing genes using microarray data mining and gene ontology
Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes.
Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results.
Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth.
Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers
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