MARKETING ANALYSIS FOR BEIJING TONGRENTANG GROUP CO. LTD.

BEIJING TONGRENTANG GROUP CO.LTD is a legally registered enterprise, with independent legal personality of a comprehensive Traditional Chinese Medicine(TCM) enterprise management. The main business is TCM production and sales, pharmaceutical research and development, import and export trade of Chinese medicinal materials and cooperating with hospitals of TCM to build special clinics. The objective of the study was exploring how to enlarge the market of BEIJING TONGRENTANG GROUP CO.LTD. to improve the development of the enterprise. The main things in research process were based on the case of the enterprise to analyze the market competitiveness and market environment of TCM to enlarge the market of the enterprise. The theoretical part of the thesis report refers to some contents, including external and internal marketing environment, the SWOT analysis of market situation, methods of enlarging the market of the company. All of the contents are premised on the case of the company. The empirical research of the thesis report is divided into two parts, which are qualitative research and quantitative research. The qualitative research was an interview of a sales manager of the company by Skype conversation and e-mail communication. The quantitative research was based on the questionnaire for customers who enter the store of TONGRENTANG to buy products or services in TONGRENTANG stores. From the conclusion of the thesis, the researcher presents that challenges and opportunities are coexisting on the future development of the company. In the end, three suggestions are given for development of the company in the future

Rosavin exerts an antitumor role and inactivates the MAPK/ERK pathway in small-cell lung carcinoma in vitro

This study attempts to explore the function and mechanism of action of rosavin in small-cell lung cancer (SCLC) in vitro. The viability and clone formation of SCLC cells were assessed using cell counting kit-8 and colony formation assays, respectively. Apoptosis and cell cycle were detected using flow cytometry and cell cycle analysis, respectively. Wound healing and transwell assays were performed to evaluate the migration and invasion of SCLC cells. Besides, protein levels of p-ERK, ERK, p-MEK and MEK were determined using western blot analysis. Rosavin repressed the viability and clone formation of SCLC cells, and promoted apoptosis and G0/G1 arrest of SCLC cells. At the same time, rosavin suppressed migration and invasion of SCLC cells. Moreover, protein levels of p-ERK/ERK and p-MEK/MEK were decreased after rosavin addition in SCLC cells. Rosavin impaired malignant behaviors of SCLC cells, which may be associated with inhibition of the MAPK/ERK pathway in vitro

Aerodynamic Characterization of a Fan Array Wind Generator

Experimental assessment of safe and precise flight control algorithms for unmanned aerial vehicles (UAVs) under gusty wind conditions requires the capability to generate a large range of velocity profiles. In this study, we employ a small fan array wind generator which can generate flows with large spatial and temporal variability. We perform a thorough aerodynamic characterization operating the fans uniformly from a low to the maximum level. PIV and hot-wire measurements indicate a jet-like flow with nearly uniform core which monotonously contracts in streamwise direction and surrounding growing unsteady shear-layers. These complex dynamics results in a limited region with desired flow profile and turbulence level. The experimental results shed light on the flow generated by a full-scale fan array wind generator, and indicate the need for further improvements via properly designed add-ons and dedicated control algorithms.Comment: 22 page

DAGC: Data-Volume-Aware Adaptive Sparsification Gradient Compression for Distributed Machine Learning in Mobile Computing

Distributed machine learning (DML) in mobile environments faces significant communication bottlenecks. Gradient compression has emerged as an effective solution to this issue, offering substantial benefits in environments with limited bandwidth and metered data. Yet, they encounter severe performance drop in non-IID environments due to a one-size-fits-all compression approach, which does not account for the varying data volumes across workers. Assigning varying compression ratios to workers with distinct data distributions and volumes is thus a promising solution. This study introduces an analysis of distributed SGD with non-uniform compression, which reveals that the convergence rate (indicative of the iterations needed to achieve a certain accuracy) is influenced by compression ratios applied to workers with differing volumes. Accordingly, we frame relative compression ratio assignment as an $n$-variables chi-square nonlinear optimization problem, constrained by a fixed and limited communication budget. We propose DAGC-R, which assigns the worker handling larger data volumes the conservative compression. Recognizing the computational limitations of mobile devices, we DAGC-A, which are computationally less demanding and enhances the robustness of the absolute gradient compressor in non-IID scenarios. Our experiments confirm that both the DAGC-A and DAGC-R can achieve better performance when dealing with highly imbalanced data volume distribution and restricted communication

Short-Video Marketing in E-commerce: Analyzing and Predicting Consumer Response

This study analyzes and predicts consumer viewing response to e-commerce short-videos (ESVs). We first construct a large-scale ESV dataset that contains 23,001 ESVs across 40 product categories. The dataset consists of the consumer response label in terms of average viewing durations and human-annotated ESV content attributes. Using the constructed dataset and mixed-effects model, we find that product description, product demonstration, pleasure, and aesthetics are four key determinants of ESV viewing duration. Furthermore, we design a content-based multimodal-multitask framework to predict consumer viewing response to ESVs. We propose the information distillation module to extract the shared, special, and conflicted information from ESV multimodal features. Additionally, we employ a hierarchical multitask classification module to capture feature-level and label-level dependencies. We conduct extensive experiments to evaluate the prediction performance of our proposed framework. Taken together, our paper provides theoretical and methodological contributions to the IS and relevant literature

Elucidating the roles of the mammary and gut microbiomes in breast cancer development

The mammary microbiome is a newly characterized bacterial niche that might offer biological insight into the development of breast cancer. Together with in-depth analysis of the gut microbiome in breast cancer, current evidence using next-generation sequencing and metabolic profiling suggests compositional and functional shifts in microbial consortia are associated with breast cancer. In this review, we discuss the fundamental studies that have progressed this important area of research, focusing on the roles of both the mammary tissue microbiome and the gut microbiome. From the literature, we identified the following major conclusions, (I) There are unique breast and gut microbial signatures (both compositional and functional) that are associated with breast cancer, (II) breast and gut microbiome compositional and breast functional dysbiosis represent potential early events of breast tumor development, (III) specific breast and gut microbes confer host immune responses that can combat breast tumor development and progression, and (IV) chemotherapies alter the microbiome and thus maintenance of a eubiotic microbiome may be key in breast cancer treatment. As the field expectantly advances, it is necessary for the role of the microbiome to continue to be elucidated using multi-omic approaches and translational animal models in order to improve predictive, preventive, and therapeutic strategies for breast cancer