Nanoengineering of amino - functionalized mesoporous silica nanospheres as nanoreactors

Selective functionalization of mesoporous silica nanospheres (MSNs) is crucial for nanoengineering of MSNs. Herein, we have combined “surface-protected etching strategy” and “cationic surfactant assisted etching strategy” to prepare functionalized MSNs with externally attached amino groups. The externally attached NH2 groups endow the catalysts with excellent catalytic performance for nitroaldol reaction between nitromethane and benzaldehyde. In addition, those NH2-MSNs can also be used to support gold nanoparticles, which display very good catalytic performance for reduction of 4-nitrophenol. It can be envisioned that the synthesis protocol developed in this work could also be extended to nanoengineered MSNs, which provides opportunities for nanoreactors design.     

优化快速流程模式对直肠癌患者手术效果的影响

目的分析快速流程模式(FT)对直肠癌手术效果的影响.方法选择100例符合条件的患者,随机分成两组,观察组进行FT,对照组应用传统模式(TC),对比研究两组患者的康复效果并统计两组出现并发症的例数.结果观察组患者的术后住院天数、首次排气时间、首次下床活动时间、首次经口进食时间、首次拔除胃管以及尿管时间均短于TC组,其差异具有统计学意义(P0.05);两组之间首次拔除引流管的时间差异无统计学意义(P0.05);两组患者在吻合口瘘、肠梗阻、切口感染的发生率及总发生率的差异均无统计学意义(P0.05).结论对直肠癌患者围手术期实施快速流程模式,手术效果显著,且并不增加术后并发症,是一种安全有效的方法.     

A two-dimensional improvement for Farr-Gao algorithm

Farr-Gao algorithm is a state-of-the-art algorithm for reduced Gröbner bases of vanishing ideals of finite points, which has been implemented in Maple as a build-in command. This paper presents a two-dimensional improvement for it that employs a preprocessing strategy for computing reduced Gröbner bases associated with tower subsets of given point sets. Experimental results show that the preprocessed Farr-Gao algorithm is more efficient than the classical one.     

基于PHP的科研管理系统设计与实现

文中分析并设计出了高校科研管理系统,并使用PHP编程语言进行了系统的实现.     

对传媒类艺术学生开展挫折教育的思考

传媒类艺术生由于成长环境相对良好,成长道路较为顺利,具有纪律意识较差、文化基础不牢、自我认知缺乏、容易冲动、过于自信等自身显著的个性特征。日益激烈的竞争对传媒类艺术生的心理素质提出了更高的要求,因此,应通过开展挫折教育,提高他们的受挫能力,促进他们健康成长成才。     

Privacy Quantification Model Based on the Bayes Conditional Risk in Location-Based Services

The widespread use of Location-Based Services(LBSs),which allows untrusted service providers to collect large quantities of information regarding users’locations,has raised serious privacy concerns.In response to these issues,a variety of LBS Privacy Protection Mechanisms(LPPMs)have been recently proposed.However,evaluating these LPPMs remains problematic because of the absence of a generic adversarial model for most existing privacy metrics.In particular,the relationships between these metrics have not been examined in depth under a common adversarial model,leading to a possible selection of the inappropriate metric,which runs the risk of wrongly evaluating LPPMs.In this paper,we address these issues by proposing a privacy quantification model,which is based on Bayes conditional privacy,to specify a general adversarial model.This model employs a general definition of conditional privacy regarding the adversary’s estimation error to compare the different LBS privacy metrics.Moreover,we present a theoretical analysis for specifying how to connect our metric with other popular LBS privacy metrics.We show that our privacy quantification model permits interpretation and comparison of various popular LBS privacy metrics under a common perspective.Our results contribute to a better understanding of how privacy properties can be measured,as well as to the better selection of the most appropriate metric for any given LBS application.     

省级公共医疗卫生供给绩效评估实证研究——基于全面绩效管理的视角

为了研究安徽省公共医疗卫生供给绩效及其影响因素,从公共服务供给压力、状态和响应3个维度筛选了15个相关指标,构建了评估指标体系,利用最新数据和熵值-Tobit模型对安徽省公共医疗卫生供给绩效及其影响因素进行综合评估,认为样本考察期内安徽省公共医疗卫生供给绩效呈现"快速-平稳-快速-平稳"的动态波动趋势,且供给压力依然较大,供给状态不容乐观,但供给响应指数提升明显; Tobit回归显示,安徽省财政医疗支出占比呈现规模报酬递减效应,人口密度与公共医疗卫生供给绩效呈现负相关关系,而人均地区生产总值、城镇化水平和财政自给率与公共医疗卫生供给绩效呈现正相关关系,但财政自给率的影响不显著,据此,提出了促进省级公共医疗卫生供给绩效提升的相关对策建议。     

Secure pairing with wearable devices by using ambient sound and light

Wearable devices usually work together with smart phones. To ensure only legitimate smart phones can read the data, they must conduct pairing to establish a shared key. Traditional pairing methods require that the pairing devices have a keyboard or screen for user interaction. However, due to the size limitation, keyboards or screens are hard to be installed in the wearable devices. To solve this problem, we propose a novel pairing method by using ambient sound and light. In this new scheme, any pairing request from smart phone will trigger wearable device vibration. Only after users press the confirm key on the device can the pairing process continues. Then pairing devices collect ambient sound and light at the predetermined time and establish a shared key by using the Diffie-Hellman protocol. To protect against potential man-in-the-middle attacks in the key establishment process, an improved interlock protocol with sound and light comparison is conducted to authenticate the key. If both the sound and light collected by the pairing devices are similar enough, the key is accepted. Otherwise, it is rejected. Compared with current context based pairing methods, our scheme does not impose strict synchronization on devices to collect ambient context data. Moreover, our scheme need not collect and exchange contextual information for multiple times to resist offline brute force attacks. The experimental results and security analysis prove the effectiveness of our scheme.     

面向无人自主平台的战场地理环境模型研究

战场环境模型是复杂战场环境面向特定需求的抽象和描述,用以支撑战场环境特性和演变规律的研究和应用。现有的战场环境模型主要面向人类战争活动来描述战场环境,缺乏以无人自主平台为认知主体的设计。提出了一种耦合人机各自优势的多层次战场地理环境模型结构,充分发挥机器在特征层面的快速计算能力,以及人在要素和关系层面的认知经验。提出了一种集环境观测、模型构建和空间决策为一体的建模方法,支撑无人自主平台根据任务和环境实现自主空间决策。