Information retrieval of mass encrypted data over multimedia networking with N-level vector model-based relevancy ranking

With an explosive growth in the deployment of networked applications over the Internet, searching the encrypted information that the user needs becomes increasingly important. However, the information search precision is quite low when using Vector space model for mass information retrieval, because long documents having poor similarity values are poorly represented in the vector space model and the order in which the terms appear in the document is lost in the vector space representation with intuitive weighting. To address the problems, this study proposed an N-level vector model (NVM)-based relevancy ranking scheme with an introduction of a new formula of the term weighting, taking into account the location of the feature term in the document to describe the content of the document properly, investigated into ways of ranking the encrypted documents using the proposed scheme, and conducted realistic simulation of information retrieval of mass encrypted data over multimedia networking. Results indicated that the timing of the index building, the most costing part of the relevancy ranking scheme, increased with the increase in both the document size and the multimedia content of the document being searched, which is in agreement with the expected. Performance evaluation demonstrated that our specially designed NVM-based encrypted information retrieval system is effective in ranking the encrypted documents transmitted over multimedia networks with large recall ratio and great retrieval precision

Association between Polymorphisms of ERCC1 and Response in Patients with Advanced Non-small Cell Lung Cancer Receiving Cisplatin-based Chemotherapy

Background and objective Results of studies on genetic polymorphisms of ERCC1 gene in DNA repair pathway which may affect response to platinum-based chemotherapy and survival in patients with non-small cell lung cancer are conflicting. The aim of this study is to prospectively assess the association between single nucleotide polymorphisms of C8092A and codon118 in ERCC1 and drug response in 90 patients with advanced non-small cell lung cancer treated with cisplatin-based chemotherapy. Methods All patients were treated with cisplatin-based chemotherapy. Genotypes of ERCC1 C8092A and codon118 were examined by sequencing, and the association between genotypes and response was evaluated. Results Genotype frequencies of ERCC1 C8092A were CC 40.0% (36/90), CA 48.9% (44/90) and AA 11.1% (10/90), frequencies of codon118 were CC 58.9% (53/90), CT 34.4% (31/90) and TT 6.7% (6/90). There was no significant difference in response rate of patients carrying with CC, compared with CA plus AA in C8092A (33.3% vs 29.6%, P=0.71). Response rate of patients carrying with CC in ERCC1 118 was 32.1%, 24.3% with CT plus CC (P=0.43). There was no difference in progression free survival between patients carrying with CC and CT plus TT in C8092A (5.2 months vs 5.4 months, P=0.62). There was no difference in progression free survival between patients carrying with CC and CA plus AA (5.5 months vs 5.3 months, P=0.59). Conclusion The results suggest that there is no association between polymorphisms in ERCC1 C8092A and codon118 and response in patients with advanced non-small cell lung cancer receiving cisplatin-based chemotherapy

Impact of a Pandemic on Attitudes towards Immigrants

Immigration control is an issue that figures prominently in public policy discussions and election campaigns throughout the world. Immigrants can be perceived as posing both realistic and symbolic threats to the host society. During the current global pandemic, these threats are amplified. This research investigated how attitudes towards immigrants were likely to be more negative when the impact of the pandemic was made salient. Based on intergroup threat theory (Rios et al., 2018) and uncertainty identity theory (Hogg, 2021a), two empirical studies investigated the effect of realistic and symbolic threats from the COVID-19 pandemic on people’s attitudes towards immigrants. Study 1 (N =303) tested if priming pandemic induced symbolic threats increased social identity uncertainty and found that pandemic-related symbolic but not realistic threats increased social identity uncertainty. Study 2 (N =363) again primed the two types of threat induced by the pandemic, measured their effects on attitudes towards immigrants, and examined if the effects could be explained by social identity uncertainty and collective angst. Results showed that people who perceived more COVID-19 related symbolic threat than COVID-19 related realistic threat experienced more COVID-19 related national identity uncertainty and collective angst, which predicted less positive attitudes towards immigrants. People who perceived more COVID-19 related realistic threat than COVID-19 related symbolic threat experienced less COVID-19 specific national identity uncertainty and collective angst, which predicted their more positive attitudes towards immigrants

Substitution of Ni for Fe in superconducting Fe0.98_{0.98}Te0.5_{0.5}Se0.5_{0.5} depresses the normal-state conductivity but not the magnetic spectral weight

We have performed systematic resistivity and inelastic neutron scattering measurements on Fe$_{0.98-z}$Ni$_z$Te$_{0.5}$Se$_{0.5}$ samples to study the impact of Ni substitution on the transport properties and the low-energy ($\le$ 12 meV) magnetic excitations. It is found that, with increasing Ni doping, both the conductivity and superconductivity are gradually suppressed; in contrast, the low-energy magnetic spectral weight changes little. Comparing with the impact of Co and Cu substitution, we find that the effects on conductivity and superconductivity for the same degree of substitution grow systematically as the atomic number of the substituent deviates from that of Fe. The impact of the substituents as scattering centers appears to be greater than any contribution to carrier concentration. The fact that low-energy magnetic spectral weight is not reduced by increased electron scattering indicates that the existence of antiferromagnetic correlations does not depend on electronic states close to the Fermi energy.Comment: 6 pages, 5 figure

Spin-glass ground state in a triangular-lattice compound YbZnGaO4_4

We report on comprehensive results identifying the ground state of a triangular-lattice structured YbZnGaO$_4$ to be spin glass, including no long-range magnetic order, prominent broad excitation continua, and absence of magnetic thermal conductivity. More crucially, from the ultralow-temperature a.c. susceptibility measurements, we unambiguously observe frequency-dependent peaks around 0.1 K, indicating the spin-glass ground state. We suggest this conclusion to hold also for its sister compound YbMgGaO$_4$, which is confirmed by the observation of spin freezing at low temperatures. We consider disorder and frustration to be the main driving force for the spin-glass phase.Comment: Version as accepted to PR

A novel retinoblastoma therapy from genomic and epigenetic analyses.

Retinoblastoma is an aggressive childhood cancer of the developing retina that is initiated by the biallelic loss of RB1. Tumours progress very quickly following RB1 inactivation but the underlying mechanism is not known. Here we show that the retinoblastoma genome is stable, but that multiple cancer pathways can be epigenetically deregulated. To identify the mutations that cooperate with RB1 loss, we performed whole-genome sequencing of retinoblastomas. The overall mutational rate was very low; RB1 was the only known cancer gene mutated. We then evaluated the role of RB1 in genome stability and considered non-genetic mechanisms of cancer pathway deregulation. For example, the proto-oncogene SYK is upregulated in retinoblastoma and is required for tumour cell survival. Targeting SYK with a small-molecule inhibitor induced retinoblastoma tumour cell death in vitro and in vivo. Thus, retinoblastomas may develop quickly as a result of the epigenetic deregulation of key cancer pathways as a direct or indirect result of RB1 loss

Methods for Comparing a DNA Sequence with a Protein Sequence

We describe two methods for constructing an optimal global alignment of, and an optimal local alignment between, a DNA sequence and a protein sequence. The alignment model of the methods addresses the problems of frameshifts and introns in the DNA sequence. The methods require computer memory proportional to the sequence lengths, so they can rigorously process very huge sequences. The simplified versions of the methods were implemented as computer programs named NAP and LAP. The experimental results demonstrate that the programs are sensitive and powerful tools for finding genes by DNA-protein sequence homology