Predictors of job seekers’ self-disclosure on social media

Social media-based screening is a well-known practice to both recruiters and job seekers. Little is known, however, about how job seekers present themselves on social media, i.e. ‘self-disclosure’, for employment purposes. This study builds on the theories of hyperpersonal computer-mediated communication, self-efficacy and social exchange to examine job seekers’ professional online image concerns, social media self-efficacy, and perceptions of social media effectiveness in the job search as predictors of inappropriate and career-oriented self-disclosures on these media. Findings from a sample of 3374 Italian respondents showed that career-oriented self-disclosure was predicted by all three factors, whereas inappropriate self-disclosure was only predicted by social media self-efficacy. Furthermore, the relationship between professional online image concerns and inappropriate self-disclosure was moderated by age, education and work experience, but not by gender. Theoretical and practical implications are discussed, and directions for future research are suggested.     

Micro- and macroergonomic changes in mental workload and medication safety following the implementation of new health IT

Health information technology (IT) is a promising way to achieve safer medication management in the delivery of healthcare. However, human factors/ergonomics dictates that in order to make the complex, cognitive work of healthcare delivery safer, health IT must properly support human cognition. This means, for example, that new health IT must reduce, not increase, workload during safety-critical tasks. The present study was the first to quantitatively assess the short- and long-term impact of bar coded medication administration (BCMA) IT on nurses' mental workload as well as on perceived medication safety. One-hundred seventy registered nurses across 3 dissimilar clinical units at an academic, freestanding pediatric hospital in the Midwest US participated in surveys administered before, 3 months after, and 12 months after the hospital implemented BCMA. Nurses rated their external mental workload (interruptions, divided attention, being rushed) and internal mental workload (concentration, mental effort) during medication administration tasks as well as the likelihood of each of three medication safety events: medication administration errors, medication errors on the clinical unit, and clinical unit-level adverse drug events. Clinical unit differences were assessed. Findings generally confirmed the hypothesis that external but not internal mental workload was associated with the perceived likelihood of a medication safety event. Comparisons of mental workload from pre- to post-BCMA revealed statistically significant changes in the critical care unit only. Medication safety appeared to improve over the long term in the hematology/oncology unit only. In the critical care and medical/surgical units, medication safety exhibited short-term improvements that were eliminated over time. Changes in mental workload and medication safety, two classically microergonomic constructs, were deeply embedded in macroergonomic phenomena. These included the fit between the BCMA system and the nature of nursing work, the process of BCMA implementation, and BCMA interactions with concurrent changes occurring in the hospital. Findings raise questions about achieving sustainable performance improvement with health IT as well as the balance between micro- and macroergonomic approaches to studying technology change.Relevance to industryDesigners must consider how technology changes cognitive work, including mental workload. Hospitals and other implementers of technology must ensure that new technology fits its users, their tasks, and the context of use, which may entail tailoring implementation, for example, to specific clinical units. Evaluators must look over time to assess both changes in cognitive work and implementation issues. Healthcare practitioners must also recognize that new technology means a complex transformation to an already complex sociotechnical system, which calls for a macroergonomic approach to design and analysis.     

电信运营商信息安全管控架构及集中策略研究

本文对运营商信息安全集中管控架构演进和信息安全管控策略面临的问题进行了深入分析，提出了信息安全集中管控架构的演进方向建议及对信息安全监控策略工作优化的若干意见。     

Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology

This work intends to develop an online experimental system for screening of deoxynivalenol (DON) contamination in whole wheat meals by visible/near-infrared (Vis/NIR) spectroscopy and computer vision coupling technology. Spectral and image information of samples with various DON levels was collected at speed of 0.15 m s⁻¹ on a conveyor belt. The two-type data were then integrated and subjected to chemometric analysis. Discriminant analysis showed that samples could be classified by setting 1000 μg kg⁻¹ as the cut-off value. The best correct classified rate obtained in prediction was 93.55% based on fusion of spectral and image features, with reduced prediction uncertainty as compared to single feature. However, quantification of DON by quantitative analysis was not successful due to poor model performance. These results indicate that, although not accurate enough to provide conclusive result, this coupling technology could be adopted for rapid screening of DON contamination in cereals and feeds during processing.     

Design and synthesis of side-chain optimized poly(2,6-dimethyl-1,4-phenylene oxide)-g-poly(styrene sulfonic acid) as proton exchange membrane for fuel cell applications: Balancing the water-resistance and the sulfonation degree

Side-chain optimized poly (2,6-dimethyl-1,4-phenylene oxide)-g-poly (styrene sulfonic acid) (PPO-g-PSSA) is designed with balanced water-resistance and sulfonation degree. The PPO-g-PSSA is synthesized by controlled atom-transfer radical polymerization (ATRP) from brominated poly (2,6-dimethyl-1,4-phenylene oxide) (PPO-xBr) and ethyl styrene-4-sulfonate and followed by hydrolysis. A series of PPO-g-PSSA are prepared possessing different bromination degree (x) of PPO-xBr and polymerization degree (m) of the side-chains and the water-resistances of the fabricated membranes are investigated. The results show that a PPO-g-PSSA at relatively low x (x < 0.2) and high m (m > 4) exhibits good balance between the water-resistance and the sulfonation degree. Namely, it displays suitable proton conductivity with compromised water-resistance. Moreover, a maximum ion exchange capacity (IEC) of 3.24 mmol g^?1 is reached without the sacrifice of water-resistance. In addition, PPO-g-0.08PSSA-13 and PPO-g-0.14PSSA-4 are chosen characterized by thermogravimetric analysis, proton conductivities and mechanical properties. At 90% RH, the optimized PPO-g-0.08PPSA-13 possesses a proton conductivity of 37.9 mS cm^?1 at 40 °C and 45.5 mS cm^?1 at 95 °C, respectively.     

Investigation on sulphonated zinc oxide nanorod incorporated sulphonated poly (1,4-phenylene ether ether sulfone) nanocomposite membranes for improved performance of microbial fuel cell

Hydrothermally prepared zinc oxide nanorods are sulphonated (S–ZnO NR) and incorporated into 15% Sulphonated Poly (1,4-Phenylene Ether Ether Sulfone) (SPEES) to improve the hydrophilicity, water uptake and ion transfer capacity. Water uptake and ion transfer capacity increased to 34.6 ± 0.6% and 2.0 ± 0.05 meq g^?1 from 29.8 ± 0.3% and 1.4 ± 0.04 meq g^?1 by adding 7.5 wt% S–ZnO NR to SPEES. Morphological studies show the prepared S–ZnO NR is well dispersed in the polymer matrix. SPEES +7.5 wt% S–ZnO NR membrane exhibits optimum performance after three-weeks of continual operation in a fabricated microbial fuel cell (MFC) to produce a maximum power density of 142 ± 1.2 mW m^?2 with a reduced biofilm compared to plain SPEES (59 ± 0.8 mW m^?2), unsulphonated filler incorporated SPEES (SPEES + 7.5 wt% ZnO, 68 ± 1.1 mW m^?2) and Nafion (130 ± 1.5 mW m^?2) thereby suggesting its suitability as a sustainable and improved cation exchange membrane (CEM) for MFCs.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

采用信息增益率的混合入侵检测模型设计

针对现有混合入侵检测模型仅定性选取特征而导致检测精度较低的问题，同时为了充分结合误用检测模型和异常检测模型的优势，提出一种采用信息增益率的混合入侵检测模型.首先，利用信息增益率定量地选择特征子集，最大程度地保留样本信息；其次，采用余弦时变粒子群算法确定支持向量机参数构建误用检测模型，使其更好地平衡粒子在全局和局部的搜索能力，然后，选取灰狼算法确定单类支持向量机参数构建异常检测模型，以此来提高对最优参数的搜索效率和精细程度，综合提高混合入侵检测模型对攻击的检测效果；最后，通过两种数据集进行仿真实验，验证了所提混合入侵检测模型具有较好的检测性能.