850 research outputs found

    Intercultural Communication on China’s We Media–WeChat Public Platform as an Example.

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    To explore the deep associations between diversified culture communication modes and the new tendencies of China’s social media, this thesis focuses on the development patterns of intercultural communication on China’s we media. Symbolized by WeChat Public Platform, China’s we media has achieved a tremendous development in recent years. In Chapter 1, the background introduction of we media highlights the essential connotation and the basic methodology of this thesis. And by interpreting the rise of China’s we media in Chapter 2, the unique evolution process of social media in China is revealed logically. Besides, as specific case studies, the two cultural WeChat official accounts: EatPrayLove and Shameless in Chapter 3 comprehensively present a macroscopic cognition as well as the detailed descriptions of intercultural communication on China’s we media. In addition, based on a series of analyses and demonstrations on the developments and prospects of China’s we media in Chapter 4, the further exploration and interpretation on how to promote intercultural communication is concluded concisely and precisely in Chapter 5

    Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

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    Using Granule to Search Privacy Preserving Voice in Home IoT Systems

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    The Home IoT Voice System (HIVS) such as Amazon Alexa or Apple Siri can provide voice-based interfaces for people to conduct the search tasks using their voice. However, how to protect privacy is a big challenge. This paper proposes a novel personalized search scheme of encrypting voice with privacy-preserving by the granule computing technique. Firstly, Mel-Frequency Cepstrum Coefficients (MFCC) are used to extract voice features. These features are obfuscated by obfuscation function to protect them from being disclosed the server. Secondly, a series of definitions are presented, including fuzzy granule, fuzzy granule vector, ciphertext granule, operators and metrics. Thirdly, the AES method is used to encrypt voices. A scheme of searchable encrypted voice is designed by creating the fuzzy granule of obfuscation features of voices and the ciphertext granule of the voice. The experiments are conducted on corpus including English, Chinese and Arabic. The results show the feasibility and good performance of the proposed scheme

    miR-181a Post-Transcriptionally Downregulates Oncogenic RalA and Contributes to Growth Inhibition and Apoptosis in Chronic Myelogenous Leukemia (CML)

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    MicroRNAs (miRNAs) are a class of short RNAs that regulate gene expression through either translational repression or mRNA cleavage. miRNA-181a (miR-181a), one of the many miRNAs conserved among vertebrates, is differentially expressed in a variety of leukemia. However, its function in leukemia, particularly chronic myelogenous leukemia (CML), is poorly understood. Here we have reported the identification of miR-181a targets by combining TargetScan software prediction and expression profiling through overexpression of miR-181a mimic in leukemic K562 cells. Four overlapping genes were found to be the likely targets of miR-181a. Among the four genes, RalA is a downstream molecule of bcr-abl fusion protein in ras signaling pathway. However, its role in CML remains elusive. Luciferase reporter and Western blot assays confirmed that RalA is a direct target of miR-181a. overexpression of miR-181a effectively suppresses cell growth and induces G2-phase arrest and apoptosis partially by targeting RalA in leukemic K562 cells. Using the KEGG database combined with recent publications, downstream signaling pathway of RalA was graphed by cytoscape software. Therefore, our study is the first to report that RalA is directly regulated by miR-181a and plays an important role in CML. The approach of computational prediction combined with expression profiling might be valuable for the identification of miRNA targets in animal

    Fluid Dynamics of Biomimetic Pectoral Fin Propulsion Using Immersed Boundary Method

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    Numerical simulations are carried out to study the fluid dynamics of a complex-shaped low-aspect-ratio pectoral fin that performs the labriform swimming. Simulations of flow around the fin are achieved by a developed immersed boundary (IB) method, in which we have proposed an efficient local flow reconstruction algorithm with enough robustness and a new numerical strategy with excellent adaptability to deal with complex moving boundaries involved in bionic flow simulations. The prescribed fin kinematics in each period consists of the power stroke and the recovery stroke, and the simulations indicate that the former is mainly used to provide the thrust while the latter is mainly used to provide the lift. The fin wake is dominated by a three-dimensional dual-ring vortex wake structure where the partial power-stroke vortex ring is linked to the recovery-stroke ring vertically. Moreover, the connection of force production with the fin kinematics and vortex dynamics is discussed in detail to explore the propulsion mechanism. We also conduct a parametric study to understand how the vortex topology and hydrodynamic characteristics change with key parameters. The results show that there is an optimal phase angle and Strouhal number for this complicated fin. Furthermore, the implications for the design of a bioinspired pectoral fin are discussed based on the quantitative hydrodynamic analysis

    Efficient Premature Ventricular Contraction Detection Based on Network Dynamics Features

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    Automatic detection of premature ventricular contractions (PVCs) is essential for early identification of cardiovascular abnormalities and reduction of clinical workload. As the most prevalent arrhythmia, PVCs can cause cardiac failure or sudden death. The difficulty resides in extracting features that effectively reflect the electrocardiogram (ECG) signals. Transition networks (TN), which represent the transition relationships between various phases of a time series, are advantageous for capturing temporal dynamics. Therefore, in order to recognize PVCs, each heartbeat was firstly split into serval segments; then their statistical properties were calculated for the sequence construction; finally, network topology related features were extracted from TN constructed by these sequences of statistical properties, and input into decision trees-based Gentleboost for PVC recognition. The algorithm was trained on MIT-BIH arrhythmia database (MIT-BIH-AR), and tested on St. Petersburg Institute of Cardiological Technics 12-lead arrhythmia database (INCART), wearable ECG database (WECG), and noise stress test database by four evaluation metrics: sensitivity, positive predictivity, F1-score (F1) and area under the curve (AUC). The proposed algorithm achieved an average F1 of 0.9784 and AUC of 0.9975 on MIT-BIH-AR, and proved good generalization ability on INCART and WECG with F1=0.9633 and 0.9467, AUC=0.9887 and 0.9755, respectively. The algorithm also exhibited robustness and noise immunity as evidenced by tests on sensitivity of R-wave peak offset and noise, and real-world daily life conditions. Overall, the proposed PVC detection algorithm based on TN theory offered high classification accuracy, strong robustness, and good generalization ability, with great potential for wearable mobile applications

    Global gene expression analysis reveals reduced abundance of putative microRNA targets in human prostate tumours

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    <p>Abstract</p> <p>Background</p> <p>Recently, microRNAs (miRNAs) have taken centre stage in the field of human molecular oncology. Several studies have shown that miRNA profiling analyses offer new possibilities in cancer classification, diagnosis and prognosis. However, the function of miRNAs that are dysregulated in tumours remains largely a mystery. Global analysis of miRNA-target gene expression has helped illuminate the role of miRNAs in developmental gene expression programs, but such an approach has not been reported in cancer transcriptomics.</p> <p>Results</p> <p>In this study, we globally analysed the expression patterns of miRNA target genes in prostate cancer by using several public microarray datasets. Intriguingly, we found that, in contrast to global mRNA transcript levels, putative miRNA targets showed a reduced abundance in prostate tumours relative to benign prostate tissue. Additionally, the down-regulation of these miRNA targets positively correlated with the number of types of miRNA target-sites in the 3' untranslated regions of these targets. Further investigation revealed that the globally low expression was mainly driven by the targets of 36 specific miRNAs that were reported to be up-regulated in prostate cancer by a miRNA expression profiling study. We also found that the transcript levels of miRNA targets were lower in androgen-independent prostate cancer than in androgen-dependent prostate cancer. Moreover, when the global analysis was extended to four other cancers, significant differences in transcript levels between miRNA targets and total mRNA backgrounds were found.</p> <p>Conclusion</p> <p>Global gene expression analysis, along with further investigation, suggests that miRNA targets have a significantly reduced transcript abundance in prostate cancer, when compared with the combined pool of all mRNAs. The abnormal expression pattern of miRNA targets in human cancer could be a common feature of the human cancer transcriptome. Our study may help to shed new light on the functional roles of miRNAs in cancer transcriptomics.</p
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