A Push-Pull System to Reduce House Entry of Malaria Mosquitoes.

Mosquitoes are the dominant vectors of pathogens that cause infectious diseases such as malaria, dengue, yellow fever and filariasis. Current vector control strategies often rely on the use of pyrethroids against which mosquitoes are increasingly developing resistance. Here, a push-pull system is presented, that operates by the simultaneous use of repellent and attractive volatile odorants. Experiments were carried out in a semi-field set-up: a traditional house which was constructed inside a screenhouse. The release of different repellent compounds, para-menthane-3,8-diol (PMD), catnip oil e.o. and delta-undecalactone, from the four corners of the house resulted in significant reductions of 45% to 81.5% in house entry of host-seeking malaria mosquitoes. The highest reductions in house entry (up to 95.5%), were achieved by simultaneously repelling mosquitoes from the house (push) and removing them from the experimental set-up using attractant-baited traps (pull). The outcome of this study suggests that a push-pull system based on attractive and repellent volatiles may successfully be employed to target mosquito vectors of human disease. Reductions in house entry of malaria vectors, of the magnitude that was achieved in these experiments, would likely affect malaria transmission. The repellents used are non-toxic and can be used safely in a human environment. Delta-undecalactone is a novel repellent that showed higher effectiveness than the established repellent PMD. These results encourage further development of the system for practical implementation in the field

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Modelling the Effect of Temperature on Respiration Rate of Fresh Cut Papaya (Carica papaya L.) Fruits.

A respiration rate (RR) model based on Peleg’s equation was developed for predicting RRs of fresh cut papaya. Respiration data for fresh cut papaya at 3/4 maturity were generated at temperatures 5, 10, 15, 20, 25 and 30°C using a closed system. RRs was found to be significantly influenced by storage temperature and increased from 0.021 to 0.289 mL[O2]/kg·h and 0.063 to 0.393 mL[CO2]/kg·h as a function of O2 and CO2 gas concentrations, respectively. Peleg’s constant K 1 and K 2 were obtained from linear regression analysis using GraphPad Prism 5.0 software and regression coefficients have good fit with values close to unity. The model was verified to assess the capability of its predictability of the RRs over the temperatures. There was good agreement with the experimentally estimated RRs. Information derived from the model can contribute in the design of successful modified atmospheric systems for storage of fresh cut papaya

The diffusion of a new service: Combining service consideration and brand choice

We propose an individual-level model of a two-stage service diffusion process. In the first stage, customers decide whether to "consider" joining the service. This (Consideration) stage is modeled by a hazard model. Customers who decide to consider the service move on to the Choice stage, wherein they choose among the service alternatives and an outside No Choice option. This stage is modeled by a conditional Multinomial Logit model. The service provider does not observe the transition in the first stage of potential customers who have yet to choose a brand. Such potential customers may have started to consider joining the service, yet chose the outside alternative in each period thereafter. One of the main contributions of the model is its ability to distinguish between these two non-adopter types. We estimated the model using data on the adoption process of newly introduced service plans offered by a commercial bank. We employed the hierarchical Bayes Monte Carlo Markov Chain procedure to estimate individual as well as population parameters. The empirical results indicate that the model outperforms competing models in breadth of analysis, model fit, and prediction accuracy

Psychometric Evaluation of the HIV Stigma Scale in a Swedish Context

Background HIV-related stigma has negative consequences for infected people's lives and is a barrier to HIV prevention. Therefore valid and reliable instruments to measure stigma are needed to enable mapping of HIV stigma. This study aimed to evaluate the psychometric properties of the HIV stigma scale in a Swedish context with regard to construct validity, data quality, and reliability. Methods The HIV stigma scale, developed by Berger, Ferrans, and Lashley (2001), was distributed to a cross-sectional sample of people living with HIV in Sweden (n = 194). The psychometric evaluation included exploratory factor analysis together with an analysis of the distribution of scores, convergent validity by correlations between the HIV stigma scale and measures of emotional well-being, and an analysis of missing items and floor and ceiling effects. Reliability was assessed using Cronbach's α. Results The exploratory factor analysis suggested a four-factor solution, similar to the original scale, with the dimensions personalised stigma, disclosure concerns, negative self-image, and concerns with public attitudes. One item had unacceptably low loadings and was excluded. Correlations between stigma dimensions and emotional well-being were all in the expected direction and ranged between −0.494 and −0.210. The instrument generated data of acceptable quality except for participants who had not disclosed their HIV status to anybody. In line with the original scale, all subscales demonstrated acceptable internal consistency with Cronbach's α 0.87–0.96. Conclusion A 39-item version of the HIV stigma scale used in a Swedish context showed satisfactory construct validity and reliability. Response alternatives are suggested to be slightly revised for items assuming the disclosure of diagnosis to another person. We recommend that people that have not disclosed should skip all questions belonging to the dimension personalised stigma. Our analysis confirmed construct validity of the instrument even without this dimension

Malaria, anemia and invasive bacterial disease: a neutrophil problem?

Invasive bacterial disease is well described in immunocompromised hosts, including those with malaria infection. One bacterial infection frequently observed in children with Plasmodium falciparum infection is non-Typhoidal salmonella (NTS) infection, in which a typically intestinal infection becomes systemic with serious, often fatal, consequences. In this review, we consider the role of malaria-induced immunoregulatory responses in tipping the balance from tissue homeostasis during malaria infection to risk of invasive NTS. Also, neutrophils are crucial in the clearance of NTS but their ability to mount an oxidative burst and kill intracellular Salmonella is severely compromised during, and for some time after, an acute malaria infection. Here, we summarize the evidence linking malaria and invasive NTS infections, describe the role of neutrophils in clearing NTS infections, review evidence for neutrophil dysfunction in malaria infections, and explore the roles of heme oxygenase-1, interleukin-10, and complement in mediating this dysfunction. Finally, given the epidemiological evidence that low density, subclinical malaria infections pose a risk for invasive NTS infections, we consider whether the high prevalence of such infections might underlie the very high incidence of invasive bacterial disease across much of sub-Saharan Africa

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

This is the final version of the article. Available from the publisher via the DOI in this record.Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways

Regulation of microRNA biogenesis and turnover by animals and their viruses

Item does not contain fulltextMicroRNAs (miRNAs) are a ubiquitous component of gene regulatory networks that modulate the precise amounts of proteins expressed in a cell. Despite their small size, miRNA genes contain various recognition elements that enable specificity in when, where and to what extent they are expressed. The importance of precise control of miRNA expression is underscored by functional studies in model organisms and by the association between miRNA mis-expression and disease. In the last decade, identification of the pathways by which miRNAs are produced, matured and turned-over has revealed many aspects of their biogenesis that are subject to regulation. Studies in viral systems have revealed a range of mechanisms by which viruses target these pathways through viral proteins or non-coding RNAs in order to regulate cellular gene expression. In parallel, a field of study has evolved around the activation and suppression of antiviral RNA interference (RNAi) by viruses. Virus encoded suppressors of RNAi can impact miRNA biogenesis in cases where miRNA and small interfering RNA pathways converge. Here we review the literature on the mechanisms by which miRNA biogenesis and turnover are regulated in animals and the diverse strategies that viruses use to subvert or inhibit these processes

Validazione di Piani di Disaster Recovery mediante Simulatore

Contribution published online at: http://www.mimos.it/nuovo/contenuto_view.asp?check=10

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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