A NOVEL OCCLUSION SIGN LANGUAGE RECOGNITION

[[abstract]]Sign language plays an important role in communicate with changers that hearing improved. However, the sign language in many countries and areas different and auto recognition system became the research way in recent year. In this paper, we devise a novel method for occlusion processing in Taiwan Sign Language recognition system. Our method employs adxl345 and Kinect to extract the feature of signer. Then the features are regulated by the dictionary of sparse coding. In final, the HMM model and result signs are recognized from the features that corrected by our method. In experimental result, we present the data that our employ. Then we describe closing test result and future work.[[sponsorship]]National Taipei University[[conferencetype]]國際[[conferencedate]]20150718~20150719[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tokyo, Japa

A systematic approach to detecting transcription factors in response to environmental stresses

Abstract Background Eukaryotic cells have developed mechanisms to respond to external environmental or physiological changes (stresses). In order to increase the activities of stress-protection functions in response to an environmental change, the internal cell mechanisms need to induce certain specific gene expression patterns and pathways by changing the expression levels of specific transcription factors (TFs). The conventional methods to find these specific TFs and their interactivities are slow and laborious. In this study, a novel efficient method is proposed to detect the TFs and their interactivities that regulate yeast genes that respond to any specific environment change. Results For each gene expressed in a specific environmental condition, a dynamic regulatory model is constructed in which the coefficients of the model represent the transcriptional activities and interactivities of the corresponding TFs. The proposed method requires only microarray data and information of all TFs that bind to the gene but it has superior resolution than the current methods. Our method not only can find stress-specific TFs but also can predict their regulatory strengths and interactivities. Moreover, TFs can be ranked, so that we can identify the major TFs to a stress. Similarly, it can rank the interactions between TFs and identify the major cooperative TF pairs. In addition, the cross-talks and interactivities among different stress-induced pathways are specified by the proposed scheme to gain much insight into protective mechanisms of yeast under different environmental stresses. Conclusion In this study, we find significant stress-specific and cell cycle-controlled TFs via constructing a transcriptional dynamic model to regulate the expression profiles of genes under different environmental conditions through microarray data. We have applied this TF activity and interactivity detection method to many stress conditions, including hyper- and hypo- osmotic shock, heat shock, hydrogen peroxide and cell cycle, because the available expression time profiles for these conditions are long enough. Especially, we find significant TFs and cooperative TFs responding to environmental changes. Our method may also be applicable to other stresses if the gene expression profiles have been examined for a sufficiently long time.</p

MixNet: Toward Accurate Detection of Challenging Scene Text in the Wild

Detecting small scene text instances in the wild is particularly challenging, where the influence of irregular positions and nonideal lighting often leads to detection errors. We present MixNet, a hybrid architecture that combines the strengths of CNNs and Transformers, capable of accurately detecting small text from challenging natural scenes, regardless of the orientations, styles, and lighting conditions. MixNet incorporates two key modules: (1) the Feature Shuffle Network (FSNet) to serve as the backbone and (2) the Central Transformer Block (CTBlock) to exploit the 1D manifold constraint of the scene text. We first introduce a novel feature shuffling strategy in FSNet to facilitate the exchange of features across multiple scales, generating high-resolution features superior to popular ResNet and HRNet. The FSNet backbone has achieved significant improvements over many existing text detection methods, including PAN, DB, and FAST. Then we design a complementary CTBlock to leverage center line based features similar to the medial axis of text regions and show that it can outperform contour-based approaches in challenging cases when small scene texts appear closely. Extensive experimental results show that MixNet, which mixes FSNet with CTBlock, achieves state-of-the-art results on multiple scene text detection datasets

The iNOS/Src/FAK axis is critical in Toll-like receptor-mediated cell motility in macrophages

AbstractThe Toll-like receptors (TLRs) play a pivotal role in innate immunity for the detection of highly conserved, pathogen-expressed molecules. Previously, we demonstrated that lipopolysaccharide (LPS, TLR4 ligand)-increased macrophage motility required the participation of Src and FAK, which was inducible nitric oxide synthase (iNOS)-dependent. To investigate whether this iNOS/Src/FAK pathway is a general mechanism for macrophages to mobilize in response to engagement of TLRs other than TLR4, peptidoglycan (PGN, TLR2 ligand), polyinosinic–polycytidylic acid (polyI:C, TLR3 ligand) and CpG-oligodeoxynucleotides (CpG, TLR9 ligand) were used to treat macrophages in this study. Like LPS stimulation, simultaneous increase of cell motility and Src (but not Fgr, Hck, and Lyn) was detected in RAW264.7, peritoneal macrophages, and bone marrow-derived macrophages exposed to PGN, polyI:C and CpG. Attenuation of Src suppressed PGN-, polyI:C-, and CpG-elicited movement and the level of FAK Pi-Tyr861, which could be reversed by the reintroduction of siRNA-resistant Src. Besides, knockdown of FAK reduced the mobility of macrophages stimulated with anyone of these TLR ligands. Remarkably, PGN-, polyI:C-, and CpG-induced Src expression, FAK Pi-Tyr861, and cell mobility were inhibited in macrophages devoid of iNOS, indicating the importance of iNOS. These findings corroborate that iNOS/Src/FAK axis occupies a central role in macrophage locomotion in response to engagement of TLRs

The Effectiveness of Traditional Chinese Medicine in Treating Patients with Leukemia

Leukemia is the most common malignancy among all childhood cancers and is associated with a low survival rate in adult patients. Since 1995, the National Health Insurance (NHI) program in Taiwan has been offering insurance coverage for Traditional Chinese Medicine (TCM), along with conventional Western medicine (WM). This study analyzes the status of TCM utilization in Taiwan, in both pediatric and adult patients with leukemia. A retrospective cohort study was conducted using population-based National Health Insurance Research Database of Registry of Catastrophic Illness, involving patient data from 2001 to 2010 and follow-up data through 2011. The effectiveness of TCM use was evaluated. Relevant sociodemographic data showed that both pediatric and adult patients who were TCM users one year prior to leukemia diagnosis were more likely to utilize TCM services for cancer therapy. A greater part of medical expenditure of TCM users was lower than that of TCM nonusers, except little discrepancy in drug fee of adult patients. The survival rate is also higher in TCM users. Altogether, these data show that TCM has the potential to serve as an adjuvant therapy when combined with conventional WM in the treatment of patients with leukemia

Sequence variants of the aging gene CISD2 and the risk for Alzheimer's disease

Background/PurposeThe CISD2 gene has been related to life span control and mitochondrial dysfunction in animals. In addition, inhibition of mitochondrial enzymes due to an accumulation of beta-amyloid peptide has been related to Alzheimer's disease (AD). This study aimed to explore the association between sequence variants of the CISD2 gene and risk for AD, which has not been explored previously.MethodsThis was a case–control study involving a total of 276 patients with AD who were recruited from three teaching hospitals in Taiwan from 2007 to 2010; 460 controls were recruited from elderly individuals attending for health check-ups and volunteers in the hospital during the same period of time. All participants were aged 60 years or older. Two haplotype-tagging single nucleotide polymorphisms (htSNPs), rs223330 and rs223331, were selected from the CISD2 gene to test the association between their polymorphisms and the risk for dementia, and how ApoE ɛ4 status, sex, hypertension, and type 2 diabetes mellitus might modify this association.Resultsrs223330 variant carriage was not associated with risk for AD [TT versus CC: adjusted odds ratio (AOR) = 0.98, 95% confidence interval (CI) = 0.59–1.62; TC versus CC: AOR = 0.72, 95% CI = 0.47–1.11]. Similar findings were observed for rs223331 (AA versus TT: AOR = 1.12; AT versus TT: AOR = 0.99). In addition, hypertension significantly modified the association between rs223331 and risk for AD (p = 0.005).Three common haplotypes (with a frequency of 99.8%) were observed for CISD2. Common CISD2 haplotypes were not associated with the risk for AD.ConclusionOur findings suggested that CISD2 htSNPs are not associated with AD risk