农村进城务工女性社会网络构建分析——以北京地区家政服务员为例

改革开放以来,大量农民依靠社会网络进城务工,但以家政服务员为代表的农村进城务工女性在社会网络构建方面相对处于不利地位。虽然农村进城务工女性多渠道努力构建社会网络,但基础依然是乡土社会网络,在社会变迁中出现内生性关系网络和外延性关系网络交替并行的融合状态。她们的社会网络以初级群体为主,选择有限。因此,还需要从外部环境和内部条件等方面优化农村进城务工女性的社会网络构建。

浙江省台州市男男性行为者艾滋病病毒／性传播感染的危险行为与性关系网络调查

目的了解浙江省台州市男男性行为者（MSM）艾滋病病毒／性传播感染（HIV／STI）及相关危险行为，初步了解其性关系网络。方法采用横断面研究设计，在台州市区2个MSM聚集地点以方便抽样法招募研究对象，知情同意后进行问卷调查，并采集血样检测HIV／STI感染。结果共调查106名MSM，收获有效问卷97份；25．0％（23／92）的对象有过1名女性性伴，47．8％（44／92）有过≥2名女性性伴；14．3％（13／91）有过1名男性肛交性伴，80．2％（73／91）有过≥2名肛交性伴；22．1％（19／86）有过群交行为，62．5％（55／88）肛交时没有100％使用安全套；15．1％（14／93）有过1名男性口交性伴，75．3％（70／93）有≥2名男性口交性伴；38．9％（37／95）曾向女性买过性；35．5％（33／93）曾向男性买过性，15．3％（13／85）曾向男性卖过性。HIV抗体阳性率为3．9％（3／77），梅毒抗体阳性率为24．7％（18／73），Ⅱ-型单纯疱疹病毒抗体阳性率为15．1％（11／73），HCV抗体检测均为阴性。46名对象报告MSM认识关系个体中心网络，平均联结度数5．91，平均网络密度0．548；43名对象报告性关系个体中心网络，平均联结度数2．70，平均网络密度0．246。结论台州地区MSM人群中存在多性伴、安全套使用率低、商业性服务等危险行为，HIV／STI感染率较高。MSM群体内部性关系紧密，可能存在一些高风险的疏离个体，仍需进一步研究其性关系网络与HIV／STI传播间的关系。

上海市闵行区商业性女性性服务者HSV-2感染率及性关系网络

目的了解上海市闵行区商业性女性性服务者（FSWs）II型单纯疱疹病毒（HSV-2）感染现状及其影响因素、阳性感染者性行为及其性网络特征。方法运用横断面研究设计和以场所为基础的抽样方法,从上海市闵行区江川、颛桥、古美、莘庄4个街道招募478名FSWs,通过问卷调查了解该人群特征及性行为情况并进行HSV-2和艾滋病病毒（HIV）抗体检测,运用SPSS 17.0软件进行数据统计分析。采用logistic单因素和多因素回归分析HSV-2感染相关的社会人口学特征,HSV-2感染者性行为比较采用χ2检验,P〈0.05为差异有统计学意义。结果 139名研究对象HSV-2抗体检测阳性,HSV-2感染率为29.1%。多因素logistic回归分析显示＂三小场所＂（服务人员20人以下提供商业性性服务的小场所,例如：小发廊、小足浴室、小浴室等）（OR=1.91,95%CI：1.12~3.25）、现住址居住时间≤6个月（OR=1.99,95%CI：1.24~3.19）及月收入≥3 001元（OR=3.90,95%CI：1.30~11.65）为FSWs人群HSV-2感染的关联因素。未发现HIV阳性者。HSV-2感染者过去一个月的性关系网络较广,安全套使用率较低,其中C型性关系网络（无固定性伴,但有商业性伴或非固定非商业性伴）商业性行为平均联结度4.50,非固定非商业性行为平均联结度4.11。D型性关系网络（既有固定性伴,也有商业性或非固定非商业性伴）的商业性行为平均联结度7.94,非固定非商业性行为平均联结度5.32。结论上海市闵行区FSWs人群尤其是＂三小场所＂、流动性大及收入高的FSWs中HSV-2感染率较高。应加强对FSWs的宣传教育和防治工作,控制HSV-2感染及传播。

基于网络社交的中青年男男性行为者性行为及性关系网络特征

目的了解中青年男男性行为者(men have sex with men,MSM)基于网络社交感染性传播疾病的高危行为及性关系网络特征。方法通过Blued(B组)、微信(V组)和线下场所(C组)招募MSM开展横断面问卷调查,分析各组MSM的高危行为及性关系网络异同点。结果共有197人(B、V、C组分别有85人、66人和46人)参加调查,年龄中位数(四分位数)M(P25,P75)为35(30,42)岁。三组对象年龄、文化程度、婚姻状态、职业、户籍差异均无统计学意义。过去6个月,B、V和C组男性性伴人数中位数(四分位数)分别是6(3,10)人、5(2,8)人和5(2,9)人(P>0.05);男性性行为人次数中位数(四分位数)分别是7(4,17)人次、6(3,13)人次和6(3,15)人次(P>0.05),坚持用安全套比例分别为38.8%、47.0%和30.4%(P>0.05);B、V和C组分别有95.2%、92.4%和89.1%的对象曾通过线上途径寻找性伴(P<0.05);B、V和C组各有45.9%、16.7%和26.1%的对象非常担心感染HIV(P<0.001),54.1%、75.8%和60.9%的对象在过去一年主动检测过HIV(P<0.05)。B、V和C组分别有44人、30人及23人报告性关系个体中心网络;各组应答者与未应答者相比,人口学及性行为等特征因素差异均无统计学意义。B、V和C组的平均网络密度分别为0.193、0.245、0.241。同为网络社交的B组和V组对象的性关系网络特征存在明显差异,其中V组对象网络特征与C组较为接近;B组平均相对入度、平均入接近中心度和平均中介中心度均低于V、C组对象,且平均相对出度、平均出接近中心度均高于V、C组对象。结论MSM表现为多性伴、安全套使用率较低等特点,不同的网络社交形成的MSM者性关系网络特征存在差异,需开展进一步研究。

理想或幻想:外聘督导者能做什么?

自20世纪90年代新管理主义盛行后,对机构督导者职能之要求,集中在绩效表现和风险控管。在此背景下,诸多学者建议,应聘请机构外的专家协助发挥督导的教育与支持功能。外聘督导者成为现行许多地区用以协助提升专业服务质量之机制。然而,聘请外聘督导者提供协助,对机构和社会工作者有其优点和限制。本文以台湾中部地区儿少福利机构社会工作为研究对象,探讨其对外聘督导角色功能的期望与实际情況。研究结果发现,社会工作者普遍认为外聘督导的实际功能是低于期望的,其中不论是期望的或实际的角色功能,都是教育与品管性功能高于支持与调节性功能。至于督导关系则是权威遵从度较高,社会工作者对外聘督导者有权威和亲近的关系时,才能发挥较大督导功能。外聘督导必须了解组织中的网络关系,及其对督导效能之影响。本文建议,应认识机构聘请外聘督导者之目标与其功能发挥程度息息相关,並發展较长期聘用制度。

Decentralized Control Based on FNNSMC for Interconnected Uncertain Nonlinear Systems

A new type controller, fuzzy neural networks sliding mode controller (FNNSMC), is developed for a class of large scale systems with unknown bounds of high order interconnections and disturbances. Although sliding mode control is simple and insensitive to uncertainties and disturbances, there are two main problems in the sliding mode controller (SMC): control input chattering and the assumption of known bounds of uncertainties and disturbances. The FNNSMC, which incorporates the fuzzy neural networks (FNN) and the SMC, can eliminate the chattering by using the continuous output of the FNN to replace the discontinuous sign term in the SMC. The bounds of uncertainties and disturbances are also not required in the FNNSMC design. The simulation results show that the FNNSMC has more robustness than the SMC.

Response of tilt and strain meters in Hubei province to the 2011 Mw9. 0 Japan earthquake

Tih and strain meters of the deformation-observation network in Hubei Province all responded to the Mw9.0 Japan earthquake on March 11,2011. By analyzing the co-seismic responses,we found that firstly there was essentially a linear correlation between response time and epicentral distance. Secondly, there was some correlation between maximum response amplitude and earthquake magnitude as well as between the duration and earthquake magnitude. Thirdly, the response amplitudes and decay rates were different for different types of instruments. Due to less data-sampling frequency, the deformation instruments, could not display the first motion of P and S waves, but responded mainly to far-field surface waves. Before the earthquake, the NS earthtide component recorded by the cave stainmeter at Yichang was distorted for nearly eight hours. While digital deformation observation did not show complete information about the earthquake source, it still reflected some key features of seismic-wave propagation.

Estimation of half-wave potential of anabolic androgenic steroids by means of QSER Approach

The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.

Digital Soil Mapping Using Artificial Neural Networks and Terrain-Related Attributes

Detailed soil surveys involve costly and time-consuming work and require expert knowledge. Since soil surveys provide information to meet a wide range of needs, new methods are necessary to map soils quickly and accurately. In this study, multilayer perceptron artificial neural networks(ANNs) were developed to map soil units using digital elevation model(DEM) attributes. Several optimal ANNs were produced based on a number of input data and hidden units. The approach used test and validation areas to calculate the accuracy of interpolated and extrapolated data. The results showed that the system and level of soil classification employed had a direct effect on the accuracy of the results. At the lowest level, smaller errors were observed with the World Reference Base(WRB)classification criteria than the Soil Taxonomy(ST) system, but more soil classes could be predicted when using ST(7 soils in the case of ST vs. 5 with WRB). Training errors were below 11% for all the ANN models applied, while the test error(interpolation error) and validation error(extrapolation error) were as high as 50% and 70%, respectively. As expected, soil prediction using a higher level of classification presented a better overall level of accuracy. To obtain better predictions, in addition to DEM attributes, data related to landforms and/or lithology as soil-forming factors, should be used as ANN input data.