SN 2012ec: mass of the progenitor from PESSTO follow-up of the photospheric phase

We present the results of a photometric and spectroscopic monitoring campaign of SN 2012ec, which exploded in the spiral galaxy NGC 1084, during the photospheric phase. The photometric light curve exhibits a plateau with luminosity L = 0.9 x 10(42) erg s(-1) and duration similar to 90 d, which is somewhat shorter than standard Type II-P supernovae (SNe). We estimate the nickel mass M(Ni-56) = 0.040 +/- 0.015 M-circle dot from the luminosity at the beginning of the radioactive tail of the light curve. The explosion parameters of SN 2012ec were estimated from the comparison of the bolometric light curve and the observed temperature and velocity evolution of the ejecta with predictions from hydrodynamical models. We derived an envelope mass of 12.6 M-circle dot, an initial progenitor radius of 1.6 x 10(13) cm and an explosion energy of 1.2 foe. These estimates agree with an independent study of the progenitor star identified in pre-explosion images, for which an initial mass of M = 14-22 M-circle dot was determined. We have applied the same analysis to two other Type II-P SNe (SNe 2012aw and 2012A), and carried out a comparison with the properties of SN 2012ec derived in this paper. We find a reasonable agreement between the masses of the progenitors obtained from pre-explosion images and masses derived from hydrodynamical models. We estimate the distance to SN 2012ec with the standardized candle method (SCM) and compare it with other estimates based on other primary and secondary indicators. SNe 2012A, 2012aw and 2012ec all follow the standard relations for the SCM for the use of Type II-P SNe as distance indicators.

A cluster-randomised intervention trial against Schistosoma japonicum in the Peoples' Republic of China: bovine and human transmission

Background Zoonotic schistosomiasis japonica is a major public health problem in China. Bovines, particularly water buffaloes, are thought to play a major role in the transmission of schistosomiasis to humans in China. Preliminary results (1998–2003) of a praziquantel (PZQ)-based pilot intervention study we undertook provided proof of principle that water buffaloes are major reservoir hosts for S. japonicum in the Poyang Lake region, Jiangxi Province. Methods and Findings Here we present the results of a cluster-randomised intervention trial (2004–2007) undertaken in Hunan and Jiangxi Provinces, with increased power and more general applicability to the lake and marshlands regions of southern China. The trial involved four matched pairs of villages with one village within each pair randomly selected as a control (human PZQ treatment only), leaving the other as the intervention (human and bovine PZQ treatment). A sentinel cohort of people to be monitored for new infections for the duration of the study was selected from each village. Results showed that combined human and bovine chemotherapy with PZQ had a greater effect on human incidence than human PZQ treatment alone. Conclusions The results from this study, supported by previous experimental evidence, confirms that bovines are the major reservoir host of human schistosomiasis in the lake and marshland regions of southern China, and reinforce the rationale for the development and deployment of a transmission blocking anti-S. japonicum vaccine targeting bovines.

Bayesian versus frequentist statistical inference for investi gating a one-off cancer cluster reported to a health department

Background The problem of silent multiple comparisons is one of the most difficult statistical problems faced by scientists. It is a particular problem for investigating a one-off cancer cluster reported to a health department because any one of hundreds, or possibly thousands, of neighbourhoods, schools, or workplaces could have reported a cluster, which could have been for any one of several types of cancer or any one of several time periods. Methods This paper contrasts the frequentist approach with a Bayesian approach for dealing with silent multiple comparisons in the context of a one-off cluster reported to a health department. Two published cluster investigations were re-analysed using the Dunn-Sidak method to adjust frequentist p-values and confidence intervals for silent multiple comparisons. Bayesian methods were based on the Gamma distribution. Results Bayesian analysis with non-informative priors produced results similar to the frequentist analysis, and suggested that both clusters represented a statistical excess. In the frequentist framework, the statistical significance of both clusters was extremely sensitive to the number of silent multiple comparisons, which can only ever be a subjective "guesstimate". The Bayesian approach is also subjective: whether there is an apparent statistical excess depends on the specified prior. Conclusion In cluster investigations, the frequentist approach is just as subjective as the Bayesian approach, but the Bayesian approach is less ambitious in that it treats the analysis as a synthesis of data and personal judgements (possibly poor ones), rather than objective reality. Bayesian analysis is (arguably) a useful tool to support complicated decision-making, because it makes the uncertainty associated with silent multiple comparisons explicit.

The bereavement response : a cluster analysis

BACKGROUND: Literature and clinical experience suggest that some people experience atypical, complicated or pathological bereavement reactions in response to a major loss. METHOD: Three groups of community-based bereaved subjects--spouses (n = 44), adult children (n = 40), and parents (n = 36)--were followed up four times in the 13 months after a loss. A 17-item scale of core bereavement times was developed and used to investigate the intensity of the bereavement response over time. RESULTS: Cluster analysis revealed a pattern of bereavement-related symptoms approximating a syndrome of chronic grief in 11 (9.2%) of the 120 subjects. None of the respondents displayed a pattern consistent with delayed or absent grief. CONCLUSIONS: In a non-clinical community sample of bereaved people, delayed or absent grief is infrequently seen, unlike chronic grief, which is demonstrated in a minority.

Creative clusters and universities : the cluster concept in economics and geography

This paper considers the history of the cluster concept in urban economic geography, and its relationship to recent debates about creative cities. It then looks at the role that universities can play in the development of a creative cluster, as well as some of the potential pitfalls.

Up the junction? Exploiting knowledge-based development through supply chain and SME cluster interactions

Maximisation of Knowledge-Based Development (KBD) benefits requires effective dissemination and utilisation mechanisms to accompany the initial knowledge creation process. This work highlights the potential for interactions between Supply Chains (SCs) and Small and Medium sized Enterprise Clusters (SMECs), (including via ‘junction’ firms which are members of both networks), to facilitate such effective dissemination and utilisation of knowledge. In both these network types there are firms that readily utilise their relationships and ties for ongoing business success through innovation. The following chapter highlights the potential for such beneficial interactions between SCs and SMECs in key elements of KBD, particularly knowledge management, innovation and technology transfer. Because there has been little focus on the interactions between SCs and SMECs, particularly when firms simultaneously belong to both, this chapter examines the conduits through which information and knowledge can be transferred and utilised. It shows that each network type has its own distinct advantages in the types of information searched for and transferred amongst network member firms. Comparing and contrasting these advantages shows opportunities for both networks to leverage the knowledge sharing strengths of each other, through these ‘junctions’ to address their own weaknesses, allowing implications to be drawn concerning new ways of utilising relationships for mutual network gains.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Cluster-based network model for time-course gene expression data

We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.

Case management educational intervention with public health nurses : cluster randomized controlled trial

Aim: This paper is a report of a study conducted to determine the effectiveness of a community case management collaborative education intervention in terms of satisfaction, learning and performance among public health nurses. Background: Previous evaluation studies of case management continuing professional education often failed to demonstrate effectiveness across a range of outcomes and had methodological weaknesses such as small convenience samples and lack of control groups. Method: A cluster randomised controlled trial was conducted between September 2005 and February 2006. Ten health centre clusters (5 control, 5 intervention) recruited 163 public health nurses in Taiwan to the trial. After pre-tests for baseline measurements, public health nurses in intervention centres received an educational intervention of four half-day workshops. Post-tests for both groups were conducted after the intervention. Two-way repeated measures analysis of variance was performed to evaluate the effect of the intervention on target outcomes. Results: A total of 161 participants completed the pre- and post-intervention measurements. This was almost a 99% response rate. Results revealed that 97% of those in the experimental group were satisfied with the programme. There were statistically significant differences between the two groups in knowledge (p = 0.001), confidence in case management skills (p = 0.001), preparedness for case manager role activities (p = 0.001), self-reported frequency in using skills (p = 0.001), and role activities (p = 0.004). Conclusion: Collaboration between academic and clinical nurses is an effective strategy to prepare nurses for rapidly-changing roles.