REST API技术及在移动通信网络管理中的应用

介绍了目前最炙手可热的REST架构风格，该风格顺应Web2.0的兴起，完美的匹配了云计算时代来临的可扩展要求，在各种应用场景中都得到了充分的表现。根据其技术特点，分析了该风格的API在移动通信网络管理中的应用，从网管系统内部、网管系统之间以及网管系统与上层APP应用之间等多方面对是否适用于REST风格以及如何在合适的位置使用REST API进行了分析。     

基于LotusNotes的文档ID应用剖析

介绍了文档数据库Lotus Domino／Notes的特点．对其文档处理的核心，即Notes文档的ID构成机制作了系统剖析．并在此基础上分析了如何在文档复制中运用ID的不同组件以及如何运用API程序访问文档ID等。     

基于Native Mode ATM API的应用系统模型及关键技术

ＡＴＭ技术作为Ｂ－ＩＳＤ的基础，在传输包括话音、图像、数据的综合业务环境中具有现有其它网络技术所不具备的技术优势，然而目前真正基于ＡＴＭＮａｔｉｖｅＭｏｄｅ的应用还很少，而大量基于Ｏｖｅｒｌａｙ Ｍｏｄｅ的ＡＴＭ应用不能充分发挥ＡＴＭ技术的优势。随着信息技术的发展，将会有大量的综合业务应用出现，它具有和传统数据通信安全不同的业务特性，必须通过一种灵活，高效的应用程序接口给予支持，本文提出基于Ｎａｔ     

VC实现串行通讯的三种途径

介绍了串行通讯的基本原理，以及在Win98，Win2000环境下实现串行通讯的三种方法，并给出了用Visual C 6.0编写的相应的应用程序。     

本地应用服务交付平台的功能架构要求研究

着眼提升有线电视网络服务能力,针对智慧家庭生活需要,研究了家庭网络本地应用服务交付平台(LASDP)的功能架构要求.在分析市场需要对家庭网络平台能力要求的基础上,以面向服务的架构(SOA)思想为指导,研究并给出了LASDP的功能架构要求.研究所推进的LASDP的标准化工作,对提升有线电视网络融合智能电视业务和智慧家庭服务水平、满足用户需求和构建家庭服务生态链等方面,有着积极的意义.     

You cannot fight the pressure: Structural rearrangements of active pharmaceutical ingredients under magic angle spinning

Although solid-state nuclear magnetic resonance (NMR) is a versatile analytical tool to study polymorphs and phase transitions of pharmaceutical molecules and products, this work summarizes examples of spontaneous and unexpected (and unwanted) structural rearrangements and phase transitions (amorphous-to-crystalline and crystalline-to-crystalline) under magic angle spinning (MAS) conditions, some of them clearly being due to the pressure experienced by the samples. It is widely known that such changes can often be detected by X-ray powder diffraction (XRPD); here, the capability of solid-state NMR experiments with a special focus on ¹H-¹³C frequency-switched Lee–Goldburg heteronuclear correlation (FSLG HETCOR)/MAS NMR experiments to detect even subtle changes on a molecular level not observable by conventional 1D NMR experiments or XRPD is presented. Furthermore, it is shown that a polymorphic impurity combined with MAS can induce a crystalline-to-crystalline phase transition. This showcases that solid-state NMR is not always noninvasive and such changes upon MAS should be considered in particular when compounds are studied over longer time spans.     

Analysis of impurities in pharmaceuticals by LC‐MS with cold electron ionization

Pharmaceuticals require careful and precise determination of their impurities that might harm the user upon consumption. Although today, the most common technique for impurities identification is liquid chromatography‐mass spectrometry (LC‐MS/MS), it has several downsides due to the nature of the ionization method. Also, the analyses in many cases are targeted thus despite being present, some of the compounds will not be revealed. In this paper, we propose and show a new method for untargeted analysis and identification of impurities in active pharmaceutical ingredients (APIs). The instrument used for these analyses is a novel electron ionization (EI) LC‐MS with supersonic molecular beams (SMB). The EI‐LC‐MS‐SMB was implemented for analyses of several drug samples spiked with an impurity. The instrument provides EI mass spectra with enhanced molecular ions, named Cold EI, which increases the identification probabilities when the compound is identified with the aid of an EI library like National Institute of Standards and Technology (NIST). We analyzed ibuprofen and its impurities, and both the API and the expected impurity were identified with names and structures by the NIST library. Moreover, other unexpected impurities were found and identified proving the ability of the EI‐LC‐MS‐SMB system for truly untargeted analysis. The results show a broad dynamic range of four orders of magnitude at the same run with a signal‐to‐noise ratio of over 10 000 for the API and almost uniform response.     

Deep Hierarchical Ensemble Model for Suicide Detection on Imbalanced Social Media Data

As a serious worldwide problem, suicide often causes huge and irreversible losses to families and society. Therefore, it is necessary to detect and help individuals with suicidal ideation in time. In recent years, the prosperous development of social media has provided new perspectives on suicide detection, but related research still faces some difficulties, such as data imbalance and expression implicitness. In this paper, we propose a Deep Hierarchical Ensemble model for Suicide Detection (DHE-SD) based on a hierarchical ensemble strategy, and construct a dataset based on Sina Weibo, which contains more than 550 thousand posts from 4521 users. To verify the effectiveness of the model, we also conduct experiments on a public Weibo dataset containing 7329 users’ posts. The proposed model achieves the best performance on both the constructed dataset and the public dataset. In addition, in order to make the model applicable to a wider population, we use the proposed sentence-level mask mechanism to delete user posts with strong suicidal ideation. Experiments show that the proposed model can still effectively identify social media users with suicidal ideation even when the performance of the baseline models decrease significantly.     

The effect of H2S concentration on the corrosion behavior of API 5L X-70 steel

This work presents electrochemical data measured during the corrosion of API 5L X-70 pipeline steel immersed in aqueous environments containing dissolved H₂S. Three different electrolyte were used: a 3 wt% NaCl solution containing 100, 650 and 2,550 ppm of H₂S respectively. The corrosion of steel is described by means of electrochemical impedance spectroscopy. The electrochemical data obtained from the steel monitoring are presented in terms of Nyquist plots. The influence of the total H₂S concentration as well as the effect of temperature on the corrosion of API 5L X-70 steel were also studied. In the presence of H₂S the R_ct values decrease as the H₂S concentration increases.     

基于非功能特性的Parlay SCF 发现机制

为满足客户应用精确发现SCF（service capability feanlre）的需求，提出了一种基于SCF多个非功能特性来进行SCF发现的机制。该机制提出了SCF非功能特性的度量方法，将多目标决策方法用于基于多个非功能特性的SCF选择过程，并改进了Parlay的接口和流程以实现基于非功能特性的SCF发现机制。