Ecosystem-Driven Design of In-Home Terminals Based on Open Platform for the

Abstract—In-home healthcare services based on the Internet-of-Things (IoT) have great business potentials. To turn it into reality, a business ecosystem should be established first. Technical solutions should therefore aim for a cooperative ecosystem by meeting the interoperability, security, and system integration requirements. In this paper, we propose an ecosystem-driven design strategy and apply it in the design of an open-platform-based in-home healthcare terminal. A cooperative business ecosystem is formulated by merging the traditiona

Biliary Neuroendocrine Neoplasms: Clinical Profiles, Management, and Analysis of Prognostic Factors

Biliary neuroendocrine neoplasms (NENs) represent <1% of all NENs. The aim of this retrospective study is to present the clinical characteristics, management and prognosis profiles of 28 biliary NEN patients from a large tertiary center, and identify factors related to prognosis. Nine tumors originated from the gallbladder, two from the extrahepatic bile duct and 17 from the ampulla of Vater. One patient was classified as neuroendocrine tumor (NET) Grade 1, three patients were classified as NET Grade 2, 18 were graded neuroendocrine carcinoma (NEC) Grade 3 and six were classified as mixed adenoneuroendocrine carcinoma (MANEC). The overall survival rate and disease-free survival rate did not have statistically significant differences between tumors of different locations or different grading. Recurrence of disease correlated with poor prognosis (p < 0.001). Lymphovascular invasion and invasion beyond the submucosa were related to higher risk of local lymph node metastases. Multivariate analysis identified patient age (p = 0.021) and R0 resection margin (p = 0.027) as independent prognostic factors associated with overall survival. Our study included relatively large numbers of biliary tract NENs with intact follow-up information. Patients with biliary neuroendocrine tumors showed different clinical outcomes according to tumor locations and tumor grades. Achieving R0 resection is important for better prognosis

Discovery and structural characterization of a therapeutic antibody against coxsackievirus A10

9月20日，《科学》子刊《科学•进展》（Science Advances）刊出了我校夏宁邵教授团队发表的题为“Discovery and structural characterization of a therapeutic antibody against coxsackievirus A10”的研究论文。该研究首次发现手足口病重要病原体柯萨奇病毒A组10型（CVA10）不同类型病毒颗粒共有的优势中和表位，揭示了病毒颗粒及其与优势中和抗体复合物的精确三维结构，阐明了中和抗体的功能与作用机制，为新型疫苗和治疗药物的研制提供了重要的理论基础。 该研究首次揭示并描绘了CVA10的病毒颗粒及其优势中和表位的精确特征，发现了具有良好应用潜能的治疗性中和抗体，为新型疫苗和特异性治疗药物的研究提供了关键基础。 我校夏宁邵教授、程通副教授和美国加州大学洛杉矶分校纳米系统研究所Z. Hong Zhou（周正洪）教授、美国加州大学圣地亚哥分校颜晓东博士为该论文的共同通讯作者。我校博士生朱瑞、徐龙发博士后、郑清炳工程师、李少伟教授和美国加州大学洛杉矶分校崔彦祥博士后为该论文共同第一作者。【Abstract】Coxsackievirus A10 (CVA10) recently emerged as a major pathogen of hand, foot, and mouth disease and herpangina in children worldwide, and lack of a vaccine or a cure against CVA10 infections has made therapeutic antibody identification a public health priority. By targeting a local isolate, CVA10-FJ-01, we obtained a potent antibody, 2G8, against all three capsid forms of CVA10. We show that 2G8 exhibited both 100% preventive and 100% therapeutic efficacy against CVA10 infection in mice. Comparisons of the near-atomic cryo–electron microscopy structures of the three forms of CVA10 capsid and their complexes with 2G8 Fab reveal that a single Fab binds a border region across the three capsid proteins (VP1 to VP3) and explain 2G8’s remarkable cross-reactivities against all three capsid forms. The atomic structures of this first neutralizing antibody of CVA10 should inform strategies for designing vaccines and therapeutics against CVA10 infections.This work was supported by grants from the National Science and Technology Major Projects for Major New Drugs Innovation and Development (2018ZX09711003-005-003), the National Science and Technology Major Project of Infectious Diseases (2017ZX10304402-002-003), the National Natural Science Foundation of China (31670933 and 81801646), and the National Institutes of Health (R37-GM33050, GM071940, DE025567, and AI094386). We acknowledge the use of instruments at the Electron Imaging Center for Nanomachines supported by the University of California, Los Angeles and by instrumentation grants from NIH (1S10RR23057 and 1U24GM116792) and NSF (DBI-1338135 and DMR-1548924). 该研究获得了国家自然科学基金、新药创制国家科技重大专项、传染病防治国家科技重大专项和美国国立卫生研究院基金的资助

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

International Comparison, Regional Characteristics and Regulatory Management of Structural Rise in the Prices of Chinese Industrial and Agricultural Products

China's price fluctuations increasingly exhibit significant structural characteristics, and since 2003, there have been several rounds of significant structural price rise. The degree of structural rise in the prices of industrial and agricultural products in China is not only higher than in the general developed countries and developing countries, but also more prominent than in other transition economies. And the structural rise in the prices of Chinese industrial and agricultural products exhibits significant economic zone differences: the structural fluctuations are the greatest in the central and western regions, significantly higher than in the eastern regions as well as the national average. From the perspective of causes of structural rise in the prices of Chinese industrial and agricultural products, the government must aim to coordinate the industrial and agricultural investments and bridge the gap in the industrial and agricultural technologies and supply capacity

A state metrics compressed decoding technique for energy-efficient turbo decoder

Abstract In the energy resource-constrained wireless applications, turbo codes are frequently employed to guarantee reliable data communication. To both reduce the power dissipation of the turbo decoder and the probability of data frame retransmission in the physical layer, memory capacity reduced near optimal turbo decoder is of special importance from the perspective of practical implementation. In this regard, a state metrics compressed decoding technique is proposed. By inserting two modules in the conventional turbo decoding architecture, a smaller quantization scheme can be applied to the compressed state metrics. Furthermore, structure of the inserted modules is described in detail. We demonstrate that one or two rounds of compression/decompression are performed in most cases during the iterative decoding process. At the cost of limited dummy decoding complexity, the state metrics cache (SMC) capacity is reduced by 53.75%. Although the proposed technique is a lossy compression strategy, the introduced errors only have tiny negative influence on the decoding performance as compared with the optimal Log-MAP algorithm

Migrating Gis Big Data Computing From Hadoop To Spark: An Exemplary Study Using Twitter

Recent research has demonstrated that social media could provide valuable spatio-temporal data about users activities. However, information extraction and computation from big amount of data pose various challenges. To effectively process massive datasets, several platforms have been developed. Our previous study [20] explored Hadoop-based cloud computing for processing big amount of social media data [9] to study geographic distributions of social media users. In this paper, we investigate an emerging system named Spark and present a timely pilot experience on geospatial big data research. In our study, Spark has been utilized to perform some classic geospatial analyses like K-Nearest Neighbors (KNN), geographic mean and median points, and the distribution of the median points. Our design is tested on an Amazon EC2 cluster. An exemplary study using 60GB, 120GB and 180GB Twitter data has demonstrated the performance achievements by migrating computing tasks from Hadoop to Spark. In our experiments, the Spark-based solution can be up to 2.3x faster than the Hadoop-based solution due to its in-memory processing and coarse-grained resource allocation strategy. In the paper, we also discuss optimization strategies on using Spark for different geospatial computing tasks