Behind the Rise: Chinese Hip-hop History Research

While hip hop music is considerably one of the most popular music genres in the United States, the hip-hop industry in China is only slowly merging to public starting from the late 2000s. The main purpose for this paper is to discover the history for hip hop industry in China and especially analyze reasons behind the rapid climb in the industry beginning from late 2017. There will include not only detailed historical data for Chinese hip-hop, but also promotion strategy and commercial operation analysis involved along the whole journey. The author collects the research data through multiple online sources like online traffic reports, social media, searching engine, etc...and gets in touch with many rising local artists to capture their opinions for the “Rising of Chinese hip-hop” as objectively as possible. This is the first time those history has been documented in English, and the author hopes to give readers outside the mandarin world a glimpse of what Chinese hip-hop industry has been developed so far.https://remix.berklee.edu/graduate-studies-production-technology/1234/thumbnail.jp

Exploring Users’ Adoption of MOOCs from the Perspective of the Institutional theory

MOOCs, which stands for Massive Open Online Courses, have attracted millions of users around the world and it has a promise to be a very important part of future education. However, there is little research on users’ adoption of MOOCs. This paper aims to improve the understanding of users’ behavior intention to use MOOCs. The proposed research model is an extension of technology acceptance model with three factors from the institutional theory. And an empirical study with 247 subjects was conducted to test this model. The results indicate that both perceived usefulness and perceived ease of use directly affect users’ behavior intention to use MOOCs significantly. Another interesting finding is that mimetic pressures also have a significant positive influence on users’ behavior intention to use MOOCs

An Examination of the Determinants of Customer Loyalty in Online Group-buying Context in China

With the rapidly development of e-commerce, online shopping becomes very popular among Chinese customers. In the past few years, online group-buying has experienced big rise and fall, thus, how to retain customers and improve customer loyalty should be considered by the practitioners. This study aims to explore potential factors which contribute to customer loyalty in the online group-buying context. Based on the literature review, we proposed a research model included five factors which directly or indirectly affect customer loyalty of online group-buying. The model was empirically evaluated using survey data collected from 352 users, and the data was analyzed by the structural equation modeling technology. Six research hypotheses were proposed in the study. Four research hypotheses were positively significant supported, while two research hypotheses were rejected in this study. The result shows that both customer satisfaction and switching costs have positive effects on customer loyalty in the online group-buying context, and the effect from switching costs is stronger. Furthermore, structural assurances in the process of online group-buying have strong effect on customers’ trust, while customer satisfaction is directly affected by trust. In addition, both theoretical and practical implications of this study are discussed at last

LSTM-TrajGAN: A Deep Learning Approach to Trajectory Privacy Protection

The prevalence of location-based services contributes to the explosive growth of individual-level trajectory data and raises public concerns about privacy issues. In this research, we propose a novel LSTM-TrajGAN approach, which is an end-to-end deep learning model to generate privacy-preserving synthetic trajectory data for data sharing and publication. We design a loss metric function TrajLoss to measure the trajectory similarity losses for model training and optimization. The model is evaluated on the trajectory-user-linking task on a real-world semantic trajectory dataset. Compared with other common geomasking methods, our model can better prevent users from being re-identified, and it also preserves essential spatial, temporal, and thematic characteristics of the real trajectory data. The model better balances the effectiveness of trajectory privacy protection and the utility for spatial and temporal analyses, which offers new insights into the GeoAI-powered privacy protection

IL-15 enhances HIV-1 infection by promoting survival and proliferation of CCR5+CD4+ T cells

HIV-1 usually utilizes CCR5 as its coreceptor and rarely switches to a CXCR4-tropic virus until the late stage of infection. CCR5+CD4+ T cells are the major virus-producing cells in viremic individuals as well as SIV-infected nonhuman primates. The differentiation of CCR5+CD4+ T cells is associated with the availability of IL-15, which increases during acute HIV-1 infection. Here, we report that CCR5 was expressed by CD4+ T cells exhibiting effector or effector memory phenotypes with high expression levels of the IL-2/IL-15 receptor common β and γ chains. IL-15, but not IL-7, improved the survival of CCR5+CD4+ T cells, drove their expansion, and facilitated HIV-1 infection in vitro and in humanized mice. Our study suggests that IL-15 plays confounding roles in HIV-1 infection, and future studies on the IL-15-based boosting of anti-HIV-1 immunity should carefully examine the potential effects on the expansion of HIV-1 reservoirs in CCR5+CD4+ T cells

Mitigating Cosmological Tensions via Momentum-Coupled Dark Sector Model

In this paper, we investigate the momentum coupling between early dark energy (EDE) and cold dark matter to alleviate cosmological tensions. EDE has exhibited promising efficacy in addressing the Hubble tension, but it exacerbates the large-scale structure tension. We consider the interaction between EDE and cold dark matter, introducing a pure momentum exchange between them to alleviate the large-scale structure tension introduced by the EDE model. We find that this coupling model is consistent with the EDE model, yielding a higher value for $H_0$, which can resolve the Hubble tension. Additionally, the new model exhibits a suppressive effect on structure growth, contributing to the alleviation of the large-scale structure tension. By utilizing the Markov Chain Monte Carlo method and incorporating various cosmological data, the coupling model constrains the best-fit values for $H_0$ to be $72.23$ km/s/Mpc and for $S_8$ to be 0.8192. Compared to the $\Lambda$CDM model, the new models have not fully resolved the large-scale structure tension. However, in contrast to the best-fit value of 0.8316 for $S_8$ obtained from the EDE model, the new model alleviates the negative impact of the EDE model.Comment: 10 pages, 6 figure