Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated. However, one cannot easily address this task without observing ground truth annotation for the training data. To address this problem, we propose a novel deep learning model of Cross-Domain Representation Disentangler (CDRD). By observing fully annotated source-domain data and unlabeled target-domain data of interest, our model bridges the information across data domains and transfers the attribute information accordingly. Thus, cross-domain joint feature disentanglement and adaptation can be jointly performed. In the experiments, we provide qualitative results to verify our disentanglement capability. Moreover, we further confirm that our model can be applied for solving classification tasks of unsupervised domain adaptation, and performs favorably against state-of-the-art image disentanglement and translation methods.Comment: CVPR 2018 Spotligh

XRCC1, but not APE1 and hOGG1 gene polymorphisms is a risk factor for pterygium.

PurposeEpidemiological evidence suggests that UV irradiation plays an important role in pterygium pathogenesis. UV irradiation can produce a wide range of DNA damage. The base excision repair (BER) pathway is considered the most important pathway involved in the repair of radiation-induced DNA damage. Based on previous studies, single-nucleotide polymorphisms (SNPs) in 8-oxoguanine glycosylase-1 (OGG1), X-ray repair cross-complementing-1 (XRCC1), and AP-endonuclease-1 (APE1) genes in the BER pathway have been found to affect the individual sensitivity to radiation exposure and induction of DNA damage. Therefore, we hypothesize that the genetic polymorphisms of these repair genes increase the risk of pterygium.MethodsXRCC1, APE1, and hOGG1 polymorphisms were studied using fluorescence-labeled Taq Man probes on 83 pterygial specimens and 206 normal controls.ResultsThere was a significant difference between the case and control groups in the XRCC1 genotype (p=0.038) but not in hOGG1 (p=0.383) and APE1 (p=0.898). The odds ratio of the XRCC1 A/G polymorphism was 2.592 (95% CI=1.225-5.484, p=0.013) and the G/G polymorphism was 1.212 (95% CI=0.914-1.607), compared to the A/A wild-type genotype. Moreover, individuals who carried at least one C-allele (A/G and G/G) had a 1.710 fold increased risk of developing pterygium compared to those who carried the A/A wild type genotype (OR=1.710; 95% CI: 1.015-2.882, p=0.044). The hOGG1 and APE1 polymorphisms did not have an increased odds ratio compared with the wild type.ConclusionsXRCC1 (Arg399 Glu) is correlated with pterygium and might become a potential marker for the prediction of pterygium susceptibility

Pathway Detection from Protein Interaction Networks and Gene Expression Data Using Color-Coding Methods and A∗ Search Algorithms

With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73GHz and 1GB main memory running under windows operating system

Single deep ultraviolet light emission from boron nitride nanotube film

Light in deep ultraviolet DUV region has a wide range of applications and the demand for finding DUV light emitting materials at nanoscale is increasingly urgent as they are vital for building miniaturized optic and optoelectronic devices. We discover that boron nitride nanotubes BNNTs with a well-crystallized cylindrical multiwall structure and diameters smaller than 10 nm can have single DUV emission at 225 nm 5.51 eV. The measured BNNTs are grown on substrate in the form of a thin film. This study suggests that BNNTs may work as nanosized DUV light sources for various applications. © 20

SNP-RFLPing 2: an updated and integrated PCR-RFLP tool for SNP genotyping

<p>Abstract</p> <p>Background</p> <p>PCR-restriction fragment length polymorphism (RFLP) assay is a cost-effective method for SNP genotyping and mutation detection, but the manual mining for restriction enzyme sites is challenging and cumbersome. Three years after we constructed SNP-RFLPing, a freely accessible database and analysis tool for restriction enzyme mining of SNPs, significant improvements over the 2006 version have been made and incorporated into the latest version, SNP-RFLPing 2.</p> <p>Results</p> <p>The primary aim of SNP-RFLPing 2 is to provide comprehensive PCR-RFLP information with multiple functionality about SNPs, such as SNP retrieval to multiple species, different polymorphism types (bi-allelic, tri-allelic, tetra-allelic or indels), gene-centric searching, HapMap tagSNPs, gene ontology-based searching, miRNAs, and SNP500Cancer. The RFLP restriction enzymes and the corresponding PCR primers for the natural and mutagenic types of each SNP are simultaneously analyzed. All the RFLP restriction enzyme prices are also provided to aid selection. Furthermore, the previously encountered updating problems for most SNP related databases are resolved by an on-line retrieval system.</p> <p>Conclusions</p> <p>The user interfaces for functional SNP analyses have been substantially improved and integrated. SNP-RFLPing 2 offers a new and user-friendly interface for RFLP genotyping that can be used in association studies and is freely available at <url>http://bio.kuas.edu.tw/snp-rflping2</url>.</p

Knowledge Sharing and Business Matching in Advertising and Public Relations Services Using Semantic Peer Technology

We develop semantic peer network aiming at knowledge sharing and business matching for the domain of advertisement and public relations. We top up a knowledge-based layer upon the peer to peer network to make it knowledge base peer. The knowledge base consists of ontology for the application domain and domain instances. We develop user services for resource sharing and business matching based on the knowledge-based layer. A trust management mechanism is built into the knowledge-based layer for making trustable resource sharing and business match making. Also we develop an RDF-based streaming mechanism for automatically pushing newly matched information to appropriate nodes. We made experiment to test the performance of search for the prototype system. The result shows that the addition of knowledge-based layer upon the peer-to-peer network would not result in the decrease of performance. We also investigate future work after the prototype researc