Na Zhang

Background: The three-dimensional model of nurses’ moral sensitivity has typically been studied using a variable-centered rather than a person-centered approach, preventing a more complete understanding of how these forms of moral sensitivity are expressed as a whole. Latent profile analysis is a person-centered approach that classifies individuals from a heterogeneous population into homogeneous subgroups, helping identify how different subpopulations of nurses use distinct combinations of different moral sensitivities to affect their service behaviors. Objective: Latent profile analysis was used to identify three distinct profiles of nurses’ moral sensitivity. Associations of the profiles with service behaviors were then examined. Methods: Five hundred twenty-five nurses from three tertiary hospitals in China were investigated with Moral Sensitivity Questionnaire and Nurses’ Service Behavior Scale. Latent profile analysis was used to analyze the data. Ethical considerations: Approval was obtained from the Ethics committee for biomedical research of Medical College, the Hebei University of Engineering. Results: A three-profile moral sensitivity model provided the best fit to the data. The resulting profiles were low moral sensitivity, moderate moral sensitivity, and high moral sensitivity. There were significant differences in service behaviors among different profiles of moral sensitivity. Conclusion: The results provide a new and expanded view of nurses’ moral sensitivity, which may be used to monitor nurses’ service behaviors comprehensively and to evaluate nursing ethics management strategies.

As a promising method with excellent characteristics in terms of resilience and dependability, distributed methods are gradually used in the field of energy management of microgrid. However, these methods have more stringent requirements on the working conditions, which will make the system more sensitive to communication failures and cyberattacks. As a result, it is both theoretical merits and practical values to investigate the malicious effect of cyber attacks on microgrid. This paper studies the distributed economic dispatch problem under denial-of-service attacks for the microgrid, in which each generator can communicate with its neighbors and has the computational capability to implement local operation. Firstly, a DoS attack model is proposed, in which the DoS attacker intentionally jams the communication channel to deteriorate the performance of the microgrid. Then, the evolution mechanism of the dispatch system of the microgrid under different attack scenarios is adequately discussed. On this basis, an optimal attack strategy based on enumerating-search algorithm is presented to allocate the limited attack resources reasonably, so as to maximize the effect of DoS attacks. Finally, the validity of the theoretical studies about the attack effect under different scenarios and the effectiveness of the proposed enumerating-search-based optimal attack strategy are illustrated through the simulation examples on the IEEE 57-bus system and IEEE 39-bus system, respectively.

As the first stage of the formation of a collaborative new product innovation team, member selection is crucial for the effective operation of the CNPI team and the achievement of new product innovation goals. Considering comprehensively the individual and collaborative attributions, the individual knowledge competence, knowledge complementarity, and collaborative performance among candidates are chosen as the criteria to select CNPI team members in this paper. Moreover, using the fuzzy set and social network analysis method, the quantitative methods of the above criteria are proposed correspondingly. Then, by integrating the above criteria, a novel multiobjective decision model for member selection of the CNPI team is built from the view of individual and collaborative attributions. Since the proposed model is NP-hard, a double-population adaptive genetic algorithm is further developed to solve it. Finally, a real case is provided to illustrate the application and effectiveness of the proposed model and method in this paper.

Background: Malaria around the China-Myanmar border is a serious health problem in the countries of South-East Asia. An. minimus is a principle malaria vector with a wide geographic distribution in this area. Malaria is endemic along the boundary between Yunnan province in China and the Kachin State of Myanmar where the local Anopheles community and the malaria transmission vectors have never been clarified. Methods. Adult Anopheles specimens were collected using CDC light traps in four villages along the border of China and Myanmar from May 2012 to April 2013. Morphological and molecular identification of mosquito adults confirmed the species of Anopheles. Blood-meal identification using the female abdomens was conducted using multiplex PCR. For sporozoite detection in An. minimus, sets of 10 female salivary glands were pooled and identified with SSU rDNA using nested PCR. Monthly abundance of An. minimus populations during the year was documented. The diversity of Anopheles and the role of An. minimus on malaria transmission in this border area were analyzed. Results: 4,833 adult mosquitoes in the genus Anopheles were collected and morphologically identified to species or species complex. The Anopheles community is comprised of 13 species, and 78.83% of our total specimens belonged to An. minimus s.l., followed by An. maculatus and the An. culicifacies complex. The quantity of trapped An. minimus in the rainy season of malaria transmission was greater than during the non-malarial dry season, and a peak was found in May 2012. An. minimus fed on the blood of four animals: humans, cattle, pigs and dogs. 1,500 females of An. minimus were pooled into 150 samples and tested for sporozoites: only 1 pooled sample was found to have sporozoites of Plasmodium vivax. Conclusion: Anopheles is abundant with An. minimus being the dominant species and having a high human blood index along the China-Myanmar border. The sporozoites in An. minimus were determined to be Plasmodium vivax with a 0.07-0.7% infection rate. © 2013Yu et al.; licensee BioMed Central Ltd.