全自动血细胞分离机版本升级前后的用户体会

目的:对目前血液中心使用的全自动血细胞分离机版本升级前后的操作者使用体会、献血者使用体验进行比较。方法:通过远程管理软件,记录两台血细胞分离机在2019年度~2021年度版本升级前后的采集数据,作分析比较。结果:经统计,版本升级前后的处理血量、预计使用时间、采集时间、采后计数、复方枸橼酸钠溶液用量,差异分析P<0.05,版本升级后的处理血量、复方枸橼酸钠溶液用量高于升级前;而升级后的预计使用时间、采集时间、采后计数低于升级前;对报警情况,差异分析P<0.05,升级后各类报警低于升级前;在80人使用的体验分析中,版本时间,差异分析P<0.05,升级可以使采集时间缩短;对版本舒适度使用体验,差异分析P<0.05,升级后无不适率高于升级前。结论:升级后的版本程序相对升级前的版本程序更加细化单采血小板采集程序;提高血细胞分离机的性能:低抽血速度恢复、缩短采集时间、减少抗凝剂预冲失败报警;优化细节体验,确保献血者在采集过程中的安全、舒适,保障献血者的健康;确保血液安全和血液质量。

静脉留置针在儿科护理中的应用及体会

静脉留置针,也称为套管针,其特征在于其操作简单方便、所用材质相对柔软、插管留置时间长,并且难以刺穿血管,因此在临床医学中得到了广泛使用。静脉留置针可有效减轻儿科患者在使用过程中的疼痛感,并在一定程度上减轻相关医务人员的工作量,提高其工作效率,从而保证了输液及抢救的需要。近年来,静脉留置针的出现及其在临床医学中的广泛应用可以避免反复穿刺引起的不适,并且可以保护血管。同时,静脉留置针的使用使得临床用药更加方便,这使得留置针逐渐成为儿科输液的主要工具。

Resource Allocation and User Association for HTTP Adaptive Streaming in Heterogeneous Cellular Networks with Small Cells

Video streaming,especially hypertext transfer protocol based(HTTP) adaptive streaming(HAS) of video,has been expected to be a dominant application over mobile networks in the near future,which brings huge challenge for the mobile networks.Although some works have been done for video streaming delivery in heterogeneous cellular networks,most of them focus on the video streaming scheduling or the caching strategy design.The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users is largely ignored.In this paper,the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied,we model the optimization problem as a mixed integer programming problem.And to reduce the computational complexity,an optimal rate allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved.Then we use the many-to-one matching model to analyze the user association problem,and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed.Finally,extensive simulation results are illustrated to demonstrate the performance of the proposed scheme.

A User Participation Behavior Prediction Model of Social Hotspots Based on Influence and Markov Random Field

Hotspot topic trends can be captured by analyzing user attributes and historical behavior in social network. In this paper, we propose a user participation behavior prediction model for social hotspots, based on user behavior and relationship data, to predict user participation behavior and topic development trends. Firstly, for the complex factors of user behavior, three dynamic influence factor functions are defined, including individual, peer and community influence. These functions take timeliness into account using a time discretization method. Secondly, to determine laws of individual behavior and group behavior within a social topic, a hotspot user participation behavior prediction model is proposed and associated with the basic concepts of randora field and Markov property in information diffusion. The experimental results show that the model can not only dynamically predict the individual behavior, but also grasp the development trends of topics.

Techno-psychological Aspects of Social Media Behaviors

Social media has become an inevitable part of our lives in the age of network society. People establish multiple identities for themselves, with or without references to the real world, and behave according to those identities. Self-made components of virtual presence are not limited to identities only; many users also create hyper-personalities for themselves with the help of new technologies. Then, the fundamental question becomes： Why do people create self-made identities and hyper-personalities to portray or hide themselves in social media environments？ The answer to this question has certain connections and implications for behaviors of social media users. Therefore, researchers have investigated why some people find social media attractive and attend whenever possible, while others are afraid of social media and hesitate to attend. Positive and negative behaviors of social media users can be classified as braggadocian and preventative. Braggadocian behaviors are related to courageously taking advantage of social media, whereas preventative behaviors are concerned with avoidance of social media. The dominant behavioral pattern of a user depends on what one can achieve through attending or preventing social media. This paper first discusses basic elements of human behavior that drive social media such as altruism, hedonism, connectionism, homophily, multiple identities, memetics, narcissism, and tribalism. Then, it focuses on precautionary elements of human behavior such as avoidance, escape, blocking, fear, hiding, removal, and protectionism. Whether they are attentive or not, one thing is clear： People refrain or enrich their own lives in social media rather than being abused or watching others in industrial media.

Social Media Is the New Punk User Experience, Social Music and DIY Culture

In the digital convergence culture （Jenkins, 2006） and in the network society （Castells, 1996）, the theories of personal branding, social identity, and the two-step flow of communication have become intertwined to create a model through which individuals and musicians share and embrace music. This paper examines the rise of social network for music involving both the practices of use and consumption and those of creation, sharing and distribution of innovative and independents musical reality. Social media have introduced radical changes in social and musical practices increasing the ability of creation from the bottom in contrast to mainstream. Moreover, thanks to performativity, collaboration and participation offering by Web 2.0, fit fully in culture ＂DIY 2.0＂ offering an interesting chance for the emerging underground music.

A probe into social media users- Based on the ＂Actual Man＂ theory of Marxism

Social media users attracted the attention of scholars at home and abroad.This paper conducted a detailed literature review and prposed an analytical framework to define and conceptualize social media users on the ＂Actual Man＂ theory of Marxism.Furthermore, the paper generalizes three research levels, including the individual level,the gruop level and the materialism level.This study can improve understanding of the users＇ behavior in the social media virtue world as well as provide references for advanced researehe~

Microblog User Recommendation Based on Particle Swarm Optimization

Considering that there exists a strong similarity between behaviors of users and intelligence of swarm of agents,in this paper we propose a novel user recommendation strategy based on particle swarm optimization(PSO)for Microblog network. Specifically,a PSO-based algorithm is developed to learn the user influence,where not only the number of followers is incorporated,but also the interactions among users(e.g.,forwarding and commenting on other users' tweets). Three social factors,the influence and the activity of the target user,together with the coherence between users,are fused to improve the performance of proposed recommendation strategy. Experimental results show that,compared to the well-known Page Rank-based algorithm,the proposed strategy performs much better in terms of precision and recall and it can effectively avoid a biased result caused by celebrity effect and zombie fans effect.

Enterprise Content Management with Information Architecture： Guidelines to Structure the Information Assets

CM （contelat management） is a strategic discipline that should support the information assets of a company. Although there are some technological instruments structuring this work, the methods that have been used must have improvement to a better use. In this sense, IA （information architecture）, as a process that helps users to manage and find information, can collaborate with the organization of this assets allowing the best identification and categorization of information, as well as providing improvements in the website navigation in Intranets and Internet. This article introduces part of a research that deals with the use of IA for developing and structuring the project of Dataprev about the content management for Brazilian social security system.

Users’Participation in Community Forest Management:A Comparative Study

Local community participation in forest management is pivotal since they are familiar with the forest environment.In the successful management of community forestry(CF),both males and females along with the representation of poor and disadvantaged groups are of vital importance.This research compares the users’perception in community forest management(CFM)activities,and socio-economic variables influencing participation in studied community forestry user groups(CFUGs).Primary data were collected through reconnaissance surveys,interviewing key informants,focus group discussions,and household surveys.Secondary data were collected from the division forest office,CFUGs’operational plan(OP)and Constitution,internet,and authenticated websites.The chi-square(χ^(2))test was applied to test separately association variables like gender,caste,age class,education level,and wealth ranking with participation.Using ordered logit regression,the variables affecting participation in OP and constitution-making,Silvicultural activities,Forest products collection,and CF fund mobilization were quantified.Gender and Education were found to be the most promising factor influencing participation in Jagriti CFUG and Jhankrikhola CFUG respectively.In general,higher caste,older age,and rich people dominate the major decision-making activities.However,lower caste and poor people have been involved comparatively more in Forest product collection.