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

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

Die chinesisch-amerikanische Schauspielerin Anna May Wong als Schwellen- und Kippfigur des transnationalen Kinos

Die vorliegende Arbeit setzt sich mit dem Zusammenhang von „Rasse“- und Geschlechterdiskursen in den USA, Deutschland und England entlang der Schauspielerin Anna May Wong (1905-1961) auseinander. Anna May Wongs mehrere Jahrzehnte umspannende Karriere ist insofern außergewöhnlich, als dass sie als chinesisch-amerikanische Schauspielerin in der US-amerikanischen und europäischen Filmbranche erfolgreich war, dabei jedoch auf Widerstände stieß und sich mit diesen auf ambivalente Weise auseinandersetzte. Die Arbeit geht Anna May Wong als Kristallisationspunkt für Verhandlungen über rassifizierte und vergeschlechtlichte Grenzziehungen nach. Im Mittelpunkt stehen die Inszenierung Wongs in den Filmen, die sie von 1922-1937 in den jeweiligen Ländern gedreht hat, und ihrer Wahrnehmung durch sich selbst und das Publikum. In der Untersuchung ihrer Inszenierung und Wahrnehmung werden diskursive Verflechtungen, Unterschiede und Brüche sichtbar. Im Untersuchungszeitraum verändern sich zudem geopolitische Machtrelationen zwischen Europa, den USA und China signifikant, die auf die Konstruktion von Differenzfiguren erheblichen Einfluss haben und die in der vorliegenden Arbeit herausgearbeitet werden. Zugleich nimmt sie auch Wongs eigene Subjektivierungsstrategien in den Blick und fragt danach, in welchem Verhältnis Leben und Werk zueinander stehen. Anhand einer Mikrogeschichte entlang der Person Anna May Wong wird eine Geschichte der Abgrenzungs- und Aneignungsbewegungen zwischen Europa, USA und China erzählt. Die Untersuchung von Anna May Wong als Ausnahmephänomen verweist zum einen auf die diskursiven Regeln rassifizierter und vergeschlechtlichter Abgrenzung. Zum anderen bringt sie den spannungsreichen Überschuss zum Vorschein, der zeigt, dass das Andere im Eigenen immer schon enthalten ist.This dissertation examines the life and work of the actress Anna May Wong (1905-1961) through the lens of discourse on race and gender in the USA, Germany, and England. Vice versa: it interrogates the discourse of race and gender by engaging the figure of Wong and her work both on screen and off. Wong’s decades-long career is extraordinary in the sense that, as a Chinese American, she achieved success in the American and European film industry in spite of gendered and racially-based resistance, an experience that her films explore in ambivalent ways. Wong serves as a prism in this dissertation to explore the ways in which racial and gendered boundaries were drawn during the span of her career, but with a specific focus on the films that she made between 1922-1937, which were shot in the United States and Europe. An interrogation of the manner in which Wong appears in these films, as well as the films’ reception(s), reveals a web of complex interweavings, intersections, and ruptures along sexual, gendered, and racialized lines. During the period on which this dissertation focuses, geopolitical power relations between Europe, China, and the United States shifted significantly with dramatic effects on the construction of difference, which the following project explores. The dissertation interrogates, therefore, the relationship between her life and the global context of her work. Her micro-history serves as a fulcrum for examining the larger history of bordering, appropriation, and identity negotiation(s) between Europe, the United States, and China. The investigation of Anna May Wong as a unique phenomenon reveals, on the one hand, a discursive and material history of raced and gendered constructions of difference. On the other hand, her work consistently engages a suspenseful type of excess, which demonstrates the ways in which the “other” is always already embedded in the “self”

Analysis of Transient Flow Field and Rock Cuttings Trajectory in Large-Diameter Reaming Drilling

This paper investigates the transient flow field characteristics and rock cuttings trajectory during large-diameter reaming drilling, aiming to address the issue of low debris removal efficiency. By establishing a liquid-solid two-phase flow numerical model, the flow field of a bundled down-the-hole hammer for 830mm reaming drilling was simulated, and the flow velocity, pressure distribution, and rock cuttings movement trajectory within the hole bottom and return channel were analyzed. The study found that the bit rotation significantly influences the flow field, increasing the area of high-speed regions at the hole bottom, enhancing the average flow velocity of the flow field, and facilitating the removal of rock cuttings. Simultaneously, the pressure difference in the flow field at the hole bottom is crucial for transporting rock cuttings to the debris removal pipe, and there exists an optimal critical value of bit rotation speed to achieve the best reverse circulation effect of the flow field. The analysis of rock cuttings trajectory shows that the flow field at the hole bottom can be divided into three stages, with different characteristics of rock cuttings distribution at each stage. Increasing the diameter of the debris removal hole helps enlarge the area of high-speed regions for rock cuttings, improving debris removal efficiency. This study provides theoretical guidance for enhancing debris removal efficiency in large-diameter reaming drilling

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

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

Research on Pattern Classification Based on Double Pseudo-Inverse Extreme Learning Machine

Abstract This research aims to address the limitations inherent in the traditional Extreme Learning Machine (ELM) algorithm, particularly the stochastic determination of input-layer weights and hidden-layer biases, which frequently leads to an excessive number of hidden-layer neurons and inconsistent performance. To augment the neural network’s efficacy in pattern classification, Principal Component Analysis (PCA) is employed to reduce the dimensionality of the input matrix and alleviate multicollinearity issues during the computation of the input weight matrix. This paper introduces an enhanced ELM methodology, designated the PCA-DP-ELM algorithm, which integrates PCA with Double Pseudo-Inverse Weight Determination (DP). The PCA-DP-ELM algorithm proposed in this study consistently achieves superior average classification accuracy across various datasets, irrespective of whether assessed through longitudinal or cross-sectional experiments. The results from both experimental paradigms indicate that the optimized algorithm not only enhances accuracy but also improves stability. These findings substantiate that the proposed methodology exerts a positive influence on pattern classification.Abstract This research aims to address the limitations inherent in the traditional Extreme Learning Machine (ELM) algorithm, particularly the stochastic determination of input-layer weights and hidden-layer biases, which frequently leads to an excessive number of hidden-layer neurons and inconsistent performance. To augment the neural network’s efficacy in pattern classification, Principal Component Analysis (PCA) is employed to reduce the dimensionality of the input matrix and alleviate multicollinearity issues during the computation of the input weight matrix. This paper introduces an enhanced ELM methodology, designated the PCA-DP-ELM algorithm, which integrates PCA with Double Pseudo-Inverse Weight Determination (DP). The PCA-DP-ELM algorithm proposed in this study consistently achieves superior average classification accuracy across various datasets, irrespective of whether assessed through longitudinal or cross-sectional experiments. The results from both experimental paradigms indicate that the optimized algorithm not only enhances accuracy but also improves stability. These findings substantiate that the proposed methodology exerts a positive influence on pattern classification

Using Granule to Search Privacy Preserving Voice in Home IoT Systems

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

Efficient Premature Ventricular Contraction Detection Based on Network Dynamics Features

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