Extreme wind storms over Europe in present and future climate: a cluster analysis approach

Boreal winter wind storm situations over Central Europe are investigated by means of an objective cluster analysis. Surface data from the NCEP-Reanalysis and ECHAM4/OPYC3-climate change GHG simulation (IS92a) are considered. To achieve an optimum separation of clusters of extreme storm conditions, 55 clusters of weather patterns are differentiated. To reduce the computational effort, a PCA is initially performed, leading to a data reduction of about 98 %. The clustering itself was computed on 3-day periods constructed with the first six PCs using "k-means" clustering algorithm. The applied method enables an evaluation of the time evolution of the synoptic developments. The climate change signal is constructed by a projection of the GCM simulation on the EOFs attained from the NCEP-Reanalysis. Consequently, the same clusters are obtained and frequency distributions can be compared. For Central Europe, four primary storm clusters are identified. These clusters feature almost 72 % of the historical extreme storms events and add only to 5 % of the total relative frequency. Moreover, they show a statistically significant signature in the associated wind fields over Europe. An increased frequency of Central European storm clusters is detected with enhanced GHG conditions, associated with an enhancement of the pressure gradient over Central Europe. Consequently, more intense wind events over Central Europe are expected. The presented algorithm will be highly valuable for the analysis of huge data amounts as is required for e.g. multi-model ensemble analysis, particularly because of the enormous data reduction.

Opportunities for magnetospheric research with coordinated cluster and ground-based observations

ESA’s first multi-satellite mission Cluster is unique in its concept of 4 satellites orbiting in controlled formations. This will give an unprecedented opportunity to study structure and dynamics of the magnetosphere. In this paper we discuss ways in which ground-based remote-sensing observations of the ionosphere can be used to support the multipoint in-situ satellite measurements. There are a very large number of potentially useful configurations between the satellites and any one ground-based observatory; however, the number of ideal occurrences for any one configuration is low. Many of the ground-based instruments cannot operate continuously and Cluster will take data only for a part of each orbit, depending on how much high-resolution (‘burst-mode’) data are acquired. In addition, there are a great many instrument modes and the formation, size and shape of the cluster of the four satellites to consider. These circumstances create a clear and pressing need for careful planning to ensure that the scientific return from Cluster is maximised by additional coordinated ground-based observations. For this reason, ESA established a working group to coordinate the observations on the ground with Cluster. We will give a number of examples how the combined spacecraft and ground-based observations can address outstanding questions in magnetospheric physics. An online computer tool has been prepared to allow for the planning of conjunctions and advantageous constellations between the Cluster spacecraft and individual or combined ground-based systems. During the mission a ground-based database containing index and summary data will help to identify interesting datasets and allow to select intervals for coordinated studies. We illustrate the philosophy of our approach, using a few important examples of the many possible configurations between the satellite and the ground-based instruments.

GALAXY EVOLUTION IN A COMPLEX ENVIRONMENT: A MULTI-WAVELENGTH STUDY OF HCG 7

The environment where galaxies are found heavily influences their evolution. Close groupings, like the ones in the cores of galaxy clusters or compact groups, evolve in ways far more dramatic than their isolated counterparts. We have conducted a multi-wavelength study of Hickson Compact Group 7 (HCG 7), consisting of four giant galaxies: three spirals and one lenticular. We use Hubble Space Telescope (HST) imaging to identify and characterize the young and old star cluster populations. We find young massive clusters (YMCs) mostly in the three spirals, while the lenticular features a large, unimodal population of globular clusters (GCs) but no detectable clusters with ages less than a few Gyr. The spatial and approximate age distributions of the similar to 300 YMCs and similar to 150 GCs thus hint at a regular star formation history in the group over a Hubble time. While at first glance the HST data show the galaxies as undisturbed, our deep ground-based, wide-field imaging that extends the HST coverage reveals faint signatures of stellar material in the intragroup medium (IGM). We do not, however, detect the IGM in H I or Chandra X-ray observations, signatures that would be expected to arise from major mergers. Despite this fact, we find that the H I gas content of the individual galaxies and the group as a whole are a third of the expected abundance. The appearance of quiescence is challenged by spectroscopy that reveals an intense ionization continuum in one galaxy nucleus, and post-burst characteristics in another. Our spectroscopic survey of dwarf galaxy members yields a single dwarf elliptical galaxy in an apparent stellar tidal feature. Based on all this information, we suggest an evolutionary scenario for HCG 7, whereby the galaxies convert most of their available gas into stars without the influence of major mergers and ultimately result in a dry merger. As the conditions governing compact groups are reminiscent of galaxies at intermediate redshift, we propose that HCGs are appropriate for studying galaxy evolution at z similar to 1-2.

Multi-objective clustering ensemble for gene expression data analysis

In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a special crossover operator, which uses clustering validation measures as objective functions. The algorithm proposed can deal with data sets presenting different types of clusters, without the need of expertise in cluster analysis. its result is a concise set of partitions representing alternative trade-offs among the objective functions. We compare the results obtained with our algorithm, in the context of gene expression data sets, to those achieved with multi-objective Clustering with automatic K-determination (MOCK). the algorithm most closely related to ours. (C) 2009 Elsevier B.V. All rights reserved.

Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study

Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.

Assessing sport management journals : a multi-dimensional examination

The rating of refereed journals has become important for academics and institutions as well as for sport management as a field of study. This paper argues that the dearth of a rating system in sport management works against the best interests of the development of the field. This paper presents a rating scheme for sport management journals, which replicates an earlier study of marketing journals, using weighted multi-dimensional perceptual ratings (Polonsky & Whitelaw, 2006). Forty-five senior sport management academics evaluated 13 journals on four criteria: journal prestige, contribution to theory, contribution to practice and contribution to teaching. Using the weighted scores of the four criteria for each journal and a supporting cluster analysis, four categories of journals were identified. The results of this study will assist academics as they argue the case for the quality of journals in which they publish. Further it facilitates evaluation of sport management journals in relation to one another on the basis of their overall ranking and their scores on the four individual criteria.

Multi-dimensional examination of marketing journal rankings by North American academics

This paper extends the journal ranking debate by developing weighted multi-dimensional perceptual rankings based on respondents' evaluation of a journals' prestige, contribution to theory, contribution to practice and contribution to teaching. Spearman correlations indicate that journal rankings based on each of the evaluative criteria are statistically significantly correlated for all pairs of criteria, other than teaching and theory. The multi-dimensional evaluation is also statistically significantly correlated to all individual criteria, other than the teaching dimension. A cluster analysis of the journals using the four evaluative criteria identified that there are three groupings of journals: A, B, and C. In most cases, A journals are evaluated as performing better than B journals on each of evaluative criteria other than for the contribution to teaching where there are no difference in perceptions between groups. B journals are viewed to perform better than C journals on prestige, contribution to practice and contribution to teaching, but not based on their prestige of weighted evaluation. This suggests that there are differences in how academics view each group of journals, although these differences do seem to vary based on the grouping being considered (i.e., A, B, or C).

A grouping journals using multi-dimensional perceptual criteria of North American marketing academics

This paper seeks to develop groupings of journals (A, B, C) using multi-dimensional perceptual rankings, based on North American respondents’ evaluation of a journal’s prestige, contribution to theory, contribution to practice and contribution to teaching. Nonparametric comparisons of criterion mean values indicate that there are generally statistically significant correlations between criteria. Cluster analysis identifies A, B, and C 'categorisations' of journals are different in regards to all four evaluative criteria.

Clustering based multi-label classification for image annotation and retrieval

This paper presents a novel multi-label classification framework for domains with large numbers of labels. Automatic image annotation is such a domain, as the available semantic concepts are typically hundreds. The proposed framework comprises an initial clustering phase that breaks the original training set into several disjoint clusters of data. It then trains a multi-label classifier from the data of each cluster. Given a new test instance, the framework first finds the nearest cluster and then applies the corresponding model. Empirical results using two clustering algorithms, four multi-label classification algorithms and three image annotation data sets suggest that the proposed approach can improve the performance and reduce the training time of standard multi-label classification algorithms, particularly in the case of large number of labels.

Clusters driven implementation of a brain inspired model for multi-view pattern identifications

The human brain processes information in both unimodal and multimodal fashion where information is progressively captured, accumulated, abstracted and seamlessly fused. Subsequently, the fusion of multimodal inputs allows a holistic understanding of a problem. The proliferation of technology has produced various sources of electronic data and continues to do so exponentially. Finding patterns from such multi-source and multimodal data could be compared to the multimodal and multidimensional information processing in the human brain. Therefore, such brain functionality could be taken as an inspiration to develop a methodology for exploring multimodal and multi-source electronic data and further identifying multi-view patterns. In this paper, we first propose a brain inspired conceptual model that allows exploration and identification of patterns at different levels of granularity, different types of hierarchies and different types of modalities. Secondly, we present a cluster driven approach for the implementation of the proposed brain inspired model. Particularly, the Growing Self Organising Maps (GSOM) based cross-clustering approach is discussed. Furthermore, the acquisition of multi-view patterns with clusters driven implementation is demonstrated with experimental results.

Cluster randomized controlled trial of a peer support program for people with diabetes: study protocol for the Australasian peers for progress study

Background
Well managed diabetes requires active self-management in order to ensure optimal glycaemic control and appropriate use of available clinical services and other supports. Peer supporters can assist people with their daily diabetes self-management activities, provide emotional and social support, assist and encourage clinical care and be available when needed.
Methods
A national database of Australians diagnosed with type 2 diabetes is being used to invite people in pre-determined locations to participate in community-based peer support groups. Peer supporters are self-identified from these communities. All consenting participants receive diabetes self-management education and education manual prior to randomization by community to a peer support intervention or usual care. This multi-faceted intervention comprises four interconnected components for delivering support to the participants. (1) Trained supporters lead 12 monthly group meetings. Participants are assisted to set goals to improve diabetes self-management, discuss with and encourage each other to strengthen linkages with local clinical services (including allied health services) as well as provide social and emotional support. (2) Support through regular supporter-participant or participant-participant contact, between monthly sessions, is also promoted in order to maintain motivation and encourage self-improvement and confidence in diabetes self-management. (3) Participants receive a workbook containing diabetes information, resources and community support services, key diabetes management behaviors and monthly goal setting activity sheets. (4) Finally, a password protected website contains further resources for the participants. Supporters are mentored and assisted throughout the intervention by other supporters and the research team through attendance at a weekly teleconference. Data, including a self-administered lifestyle survey, anthropometric and biomedical measures are collected on all participants at baseline, 6 and 12 months. The primary outcome is change in cardiovascular disease risk using the UKPDS risk equation. Secondary outcomes include biomedical, quality of life, psychosocial functioning, and other lifestyle measures. An economic evaluation will determine whether the program is cost effective.
Discussion
This manuscript presents the protocol for a cluster randomized controlled trial of group-based peer support for people with type 2 diabetes in a community setting. Results from this trial will contribute evidence about the effectiveness of peer support in achieving effective self-management of diabetes.

Factors influencing participation in a vascular disease prevention lifestyle program among participants in a cluster randomized trial

Background
Previous research suggests that lifestyle intervention for the prevention of diabetes and cardiovascular disease (CVD) are effective, however little is known about factors affecting participation in such programs. This study aims to explore factors influencing levels of participation in a lifestyle modification program conducted as part of a cluster randomized controlled trial of CVD prevention in primary care.

Methods
This concurrent mixed methods study used data from the intervention arm of a cluster RCT which recruited 30 practices through two rural and three urban primary care organizations. Practices were randomly allocated to intervention (n = 16) and control (n = 14) groups. In each practice up to 160 eligible patients aged between 40 and 64 years old, were invited to participate. Intervention practice staff were trained in lifestyle assessment and counseling and referred high risk patients to a lifestyle modification program (LMP) consisting of two individual and six group sessions over a nine month period. Data included a patient survey, clinical audit, practice survey on capacity for preventive care, referral and attendance records at the LMP and qualitative interviews with Intervention Officers facilitating the LMP. Multi-level logistic regression modelling was used to examine independent predictors of attendance at the LMP, supplemented with qualitative data from interviews with Intervention Officers facilitating the program.

Results
A total of 197 individuals were referred to the LMP (63% of those eligible). Over a third of patients (36.5%) referred to the LMP did not attend any sessions, with 59.4% attending at least half of the planned sessions. The only independent predictors of attendance at the program were employment status - not working (OR: 2.39 95% CI 1.15-4.94) and having high psychological distress (OR: 2.17 95% CI: 1.10-4.30). Qualitative data revealed that physical access to the program was a barrier, while GP/practice endorsement of the program and flexibility in program delivery facilitated attendance.

Conclusion
Barriers to attendance at a LMP for CVD prevention related mainly to external factors including work commitments and poor physical access to the programs rather than an individuals’ health risk profile or readiness to change. Improving physical access and offering flexibility in program delivery may enhance future attendance. Finally, associations between psychological distress and attendance rates warrant further investigation.

Reducing office workers' sitting time: rationale and study design for the Stand Up Victoria cluster randomized trial

Background
Excessive time spent in sedentary behaviours (sitting or lying with low energy expenditure) is associated with an increased risk for type 2 diabetes, cardiovascular disease and some cancers. Desk-based office workers typically accumulate high amounts of daily sitting time, often in prolonged unbroken bouts. The Stand Up Victoria study aims to determine whether a 3-month multi-component intervention in the office setting reduces workplace sitting, particularly prolonged, unbroken sitting time, and results in improvements in cardiometabolic biomarkers and work-related outcomes, compared to usual practice.

Methods/design
A two-arm cluster-randomized controlled trial (RCT), with worksites as the unit of randomization, will be conducted in 16 worksites located in Victoria, Australia. Work units from one organisation (Department of Human Services, Australian Government) will be allocated to either the multi-component intervention (organisational, environmental [heightadjustable workstations], and individual behavioural strategies) or to a usual practice control group. The recruitment target is 160 participants (office-based workers aged 18–65 years and working at least 0.6 full time equivalent) per arm. At each assessment (0- [baseline], 3- [post intervention], and 12-months [follow-up]), objective measurement via the activPAL3 activity monitor will be used to assess workplace: sitting time (primary outcome); prolonged sitting time (sitting time accrued in bouts of ≥30 minutes); standing time; sit-to-stand transitions; and, moving time. Additional outcomes assessed will include: non-workplace activity; cardio-metabolic biomarkers and health indicators (including fasting glucose, lipids and insulin; anthropometric measures; blood pressure; and, musculoskeletal symptoms); and, work-related outcomes (presenteeism, absenteeism, productivity, work performance). Incremental cost-effectiveness and identification of both workplace and individual-level mediators and moderators of change will also be evaluated.

Iterative development of Stand Up Australia : a multi-component intervention to reduce workplace sitting

Sitting, particularly in prolonged, unbroken bouts, is widespread within the office workplace, yet few interventions have addressed this newly-identified health risk behaviour. This paper describes the iterative development process and resulting intervention procedures for the Stand Up Australia research program focusing on a multi-component workplace intervention to reduce sitting time. The development of Stand Up Australia followed three phases. 1) Conceptualisation: Stand Up Australia was based on social cognitive theory and social ecological model components. These were operationalised via a taxonomy of intervention strategies and designed to target multiple levels of influence including: organisational structures (e.g. via management consultation), the physical work environment (via provision of height-adjustable workstations), and individual employees (e.g. via face-to-face coaching). 2) Formative research: Intervention components were separately tested for their feasibility and acceptability. 3) Pilot studies: Stand Up Comcare tested the integrated intervention elements in a controlled pilot study examining efficacy, feasibility and acceptability. Stand Up UQ examined the additional value of the organisational- and individual-level components over height-adjustable workstations only in a three-arm controlled trial. In both pilot studies, office workers’ sitting time was measured objectively using activPAL3 devices and the intervention was refined based on qualitative feedback from managers and employees. Results and feedback from participants and managers involved in the intervention development phases suggest high efficacy, acceptance, and feasibility of all intervention components. The final version of the Stand Up Australia intervention includes strategies at the organisational (senior management consultation, representatives consultation workshop, team champions, staff information and brainstorming session with information booklet, and supportive emails from managers to staff), environmental (height-adjustable workstations), and individual level (face-to-face coaching session and telephone support). Stand Up Australia is currently being evaluated in the context of a cluster-randomised controlled trial at the Department of Human Services (DHS) in Melbourne, Australia. Stand Up Australia is an evidence-guided and systematically developed workplace intervention targeting reductions in office workers’ sitting time.

INTroducing a care bundle to prevent pressure injury (INTACT) in at-risk patients: a protocol for a cluster randomised trial

BACKGROUND: Pressure injuries are a significant clinical and economic issue, affecting both patients and the health care system. Many pressure injuries in hospitals are facility acquired, and are largely preventable. Despite growing evidence and directives for pressure injury prevention, implementation of preventative strategies is suboptimal, and pressure injuries remain a serious problem in hospitals. OBJECTIVES: This study will test the effectiveness and cost-effectiveness of a patient-centred pressure injury prevention care bundle on the development of hospital acquired pressure injury in at-risk patients. DESIGN: This is a multi-site, parallel group cluster randomised trial. The hospital is the unit of randomisation. METHODS: Adult medical and surgical patients admitted to the study wards of eight hospitals who are (a) deemed to be at risk of pressure injury (i.e. have reduced mobility), (b) expected to stay in hospital for ≥48h, (c) admitted to hospital in the past 36h; and (d) able to provide informed consent will be eligible to participate. Consenting patients will receive either the pressure injury prevention care bundle or standard care. The care bundle contains three main messages: (1) keep moving; (2) look after your skin; and (3) eat a healthy diet. Nurses will receive education about the intervention. Patients will exit the study upon development of a pressure injury, hospital discharge or 28 days, whichever comes first; transfer to another hospital or transfer to critical care and mechanically ventilated. The primary outcome is incidence of hospital acquired pressure injury. Secondary outcomes are pressure injury stage, patient participation in care and health care costs. A health economic sub-study and a process evaluation will be undertaken alongside the trial. Data will be analysed at the cluster (hospital) and patient level. Estimates of hospital acquired pressure injury incidence in each group, group differences and 95% confidence interval and p values will be reported. DISCUSSION: To our knowledge, this is the first trial of an intervention to incorporate a number of pressure injury prevention strategies into a care bundle focusing on patient participation and nurse-patient partnership. The results of this study will provide important information on the effectiveness and cost-effectiveness of this intervention in preventing pressure injuries in at-risk patients. If the results confirm the utility of the developed care bundle, it could have a significant impact on clinical practice worldwide. TRIAL REGISTRATION: This trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12613001343796.