861 resultados para multiple data sources


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Objectives: To systematically review radiofrequency ablation (RFA) for treating liver tumors. Data Sources: Databases were searched in July 2003. Study Selection: Studies comparing RFA with other therapies for hepatocellular carcinoma (HCC) and colorectal liver metastases (CLM) plus selected case series for CLM. Data Extraction: One researcher used standardized data extraction tables developed before the study, and these were checked by a second researcher. Data Synthesis: For HCC, 1.3 comparative studies were included, 4 of which were randomized, controlled trials. For CLM, 13 studies were included, 2 of which were nonrandomized comparative studies and 11 that were case series. There did not seem to be any distinct differences in the complication rates between RFA and any of the other procedures for treatment of HCC. The local recurrence rate at 2 years showed a statistically significant benefit for RFA over percutaneous ethanol injection for treatment of HCC (6% vs 26%, 1 randomized, controlled trial). Local recurrence was reported to be more common after RFA than after laser-induced thermotherapy, and a higher recurrence rate and a shorter time to recurrence were dassociated with RFA compared with surgical resection (1 nonrandomized study each). For CLM, the postoperative complication rate ranged from 0% to 33% (3 case series). Survival after diagnosis was shorter in the CLM group treated with RFA than in the surgical resection group (1 nonrandomized study). The CLM local recurrence rate after RFA ranged from 4% to 55% (6 case series). Conclusions: Radiofrequency ablation may be more effective than other treatments in terms of less recurrence of HCC and may be as sale, although the evidence is scant. There was not enough evidence to determine the safety or efficacy of RFA for treatment of CLM.

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An emerging issue in the field of astronomy is the integration, management and utilization of databases from around the world to facilitate scientific discovery. In this paper, we investigate application of the machine learning techniques of support vector machines and neural networks to the problem of amalgamating catalogues of galaxies as objects from two disparate data sources: radio and optical. Formulating this as a classification problem presents several challenges, including dealing with a highly unbalanced data set. Unlike the conventional approach to the problem (which is based on a likelihood ratio) machine learning does not require density estimation and is shown here to provide a significant improvement in performance. We also report some experiments that explore the importance of the radio and optical data features for the matching problem.

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In 2001/02 five case study communities in both metropolitan and regional urban locations in Australia were chosen as test sites to develop measures of community strength on four domains: natural capital; produced economic capital; human capital; and social and institutional capital. Secondary data sources were used to develop measures on the first three domains. For the fourth domain social and institutional capital primary data collection was undertaken through sample surveys of households. A structured approach was devised. This involved developing a survey instrument using scaled items relating to four elements: formal norms; informal norms; formal structures; and informal structures which embrace the concepts of trust, reciprocity, bonds, bridges, links and networks in the interaction of individuals with their community inherent in the notion social capital. Exploratory principal components analysis was used to identify factors that measure those aspects of social and institutional capital, with confirmatory analysis conducted using Cronbach's Alpha. This enabled the construction of four primary scales and 15 sub-scales as a tool for measuring social and institutional capital. Further analyses reveals that two measures anomie and perceived quality of life and wellbeing relate to certain primary scales of social capital.

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The developments of models in Earth Sciences, e.g. for earthquake prediction and for the simulation of mantel convection, are fare from being finalized. Therefore there is a need for a modelling environment that allows scientist to implement and test new models in an easy but flexible way. After been verified, the models should be easy to apply within its scope, typically by setting input parameters through a GUI or web services. It should be possible to link certain parameters to external data sources, such as databases and other simulation codes. Moreover, as typically large-scale meshes have to be used to achieve appropriate resolutions, the computational efficiency of the underlying numerical methods is important. Conceptional this leads to a software system with three major layers: the application layer, the mathematical layer, and the numerical algorithm layer. The latter is implemented as a C/C++ library to solve a basic, computational intensive linear problem, such as a linear partial differential equation. The mathematical layer allows the model developer to define his model and to implement high level solution algorithms (e.g. Newton-Raphson scheme, Crank-Nicholson scheme) or choose these algorithms form an algorithm library. The kernels of the model are generic, typically linear, solvers provided through the numerical algorithm layer. Finally, to provide an easy-to-use application environment, a web interface is (semi-automatically) built to edit the XML input file for the modelling code. In the talk, we will discuss the advantages and disadvantages of this concept in more details. We will also present the modelling environment escript which is a prototype implementation toward such a software system in Python (see www.python.org). Key components of escript are the Data class and the PDE class. Objects of the Data class allow generating, holding, accessing, and manipulating data, in such a way that the actual, in the particular context best, representation is transparent to the user. They are also the key to establish connections with external data sources. PDE class objects are describing (linear) partial differential equation objects to be solved by a numerical library. The current implementation of escript has been linked to the finite element code Finley to solve general linear partial differential equations. We will give a few simple examples which will illustrate the usage escript. Moreover, we show the usage of escript together with Finley for the modelling of interacting fault systems and for the simulation of mantel convection.

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Purpose – The purpose of this paper is to explore the role and relevance of external standards in demonstrating the value and impact of academic library services to their stakeholders. Design/methodology/approach – Two UK standards, Charter Mark and Customer Service Excellence, are evaluated via an exploratory case study, employing multiple data collection techniques. Methods and results of phases 1-2 of a three phase research project are outlined. Findings – Despite some limitations, standards may assist the manager in demonstrating the value, impact and quality of academic libraries in a recessional environment. Active engagement and partnership with customers is imperative if academic libraries are to be viewed as vital to their parent organisations and thus survive. Originality/value – This paper provides a systematic evaluation of the role of external accreditation standards in measuring academic library service value and impact.

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Purpose – The purpose of this paper is to analyze the way in which the knowledge competitiveness of regions is measured and further introduces the World Knowledge Competitiveness Index (WKCI) benchmarking tool. Design/methodology/approach – The methodology consists of an econometric analysis of key indicators relating to the concept of knowledge competitiveness for 125 regions from across the globe consisting of 55 representatives from North America, 45 from Europe and 25 from Asia and Oceania. Findings – The key to winning the super competitive race in the knowledge-based economy is investment in the future: research and development, and education and training. It is found that the majority of the high-performing regional economies in the USA have a knowledge competitive edge over their counterparts in Europe and Asia. Research limitations/implications – To an extent, the research is limited by the availability of comparable indicators and metrics at the regional level that extend across the globe. Whilst comparative data are often accessible at the national level, regional data sources remain underdeveloped. Practical implications – The WKCI has become internationally recognized as an important instrument for economic development policymakers and regional investment promotion agents as they create and refine their strategies and targets. In particular, it has provided a benchmark that allows regions to compare their knowledge competitiveness with other regions for around the world and not only their own nation or continent. Originality/value – The WKCI is the first composite and relative measure of the knowledge competitiveness of the globe's best performing regions.

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Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources and Web services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial mashups to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and correlation of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. Spatial entropy index HSu for the ScankOO analysis of the hypothetical dataset using a vicinity which is fixed by the number of points without distinction between their labels. (The size of the labels is proportional to the inverse of the index) In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

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This thesis, set within an Action Research framework, details the development and validation of a writer-centred model of the writing process. The model was synthesised within the boundaries of a writers’ group for MA students. The initial data collected, and analysed using the principles of grounded theory, were retrospective descriptions of group members’ writing processes. After initial analysis, additional data, from group members’ writing, and from audio recordings, were used for further analysis, and to form a model of the writing process. To ascertain whether the model had value outside the specific context in which it was made, it was validated from three different perspectives. Firstly, the retrospective descriptions of other writers were collected and analysed, using the model as a framework. Secondly, the model was presented at academic conferences; comments about the model, made by members of the audience, were collected and analysed. Finally, the model was used in writing courses for PhD students. Comments from these students, along with questionnaire responses, were collected and the content analysed. Upon examination of all data sources, the model was updated to reflect additional insights arising from the analysis. Analysis of the data also indicated that the model is useable outside its original context. Potential uses for the model are 1) raising awareness of the process of writing, 2) putting writers at ease, 3) serving as a starting point for individuals or groups to design their own models of the writing process, and 4) as a tool to help writers take control of their writing processes.

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Context: The cognitive side effects of medications with anticholinergic activity have been documented among older adults in a variety of clinical settings. However, there has been no systematic confirmation that acute or chronic prescribing of such medications lead to transient or permanent adverse cognitive outcomes. Objective: Evaluate the existing evidence regarding the effects of anticholinergic medications on cognition in older adults. Data sources: We searched the MEDLINE, OVID, and CINAHL databases from January, 1966 to January, 2008 for eligible studies. Study selection: Studies were included if the anticholinergic activity was systematically measured and correlated with standard measurements of cognitive performance. Studies were excluded if they reported case studies, case series, editorials, and review articles. Data extraction: We extracted the method used to determine anticholinergic activity of medications and its association with cognitive outcomes. Results: Twenty-seven studies met our inclusion criteria. Serum anticholinergic assay was the main method used to determine anticholinergic activity. All but two studies found an association between the anticholinergic activity of medications and either delirium, cognitive impairment or dementia. Conclusions: Medications with anticholinergic activity negatively affect the cognitive performance of older adults. Recognizing the anticholinergic activity of certain medications may represent a potential tool to improve cognition.

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Objective: To determine the efficacy of cholinesterase inhibitors (ChEIs) in improving the behavioral and psychological symptoms of dementia (BPSD) in patients with Alzheimer’s disease (AD). Data sources: We searched MEDLINE, Cochrane Registry, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) from 1966 to 2007. We limited our search to English Language, full text, published articles and human studies. Data extraction: We included randomized, double-blind, placebo-controlled trials evaluating the efficacy of donepezil, rivastigmine, or galantamine in managing BPSD displayed by AD patients. Using the United States Preventive Services Task Force (USPSTF) guidelines, we critically appraised all studies and included only those with an attrition rate of less than 40%, concealed measurement of the outcomes, and intention to treat analysis of the collected data. All data were imputed into pre-defined evidence based tables and were pooled using the Review Manager 4.2.1 software for data synthesis. Results: We found 12 studies that met our inclusion criteria but only nine of them provided sufficient data for the meta-analysis. Among patients with mild to severe AD and in comparison to placebo, ChEIs as a class had a beneficial effects on reducing BPSD with a standard mean difference (SMD) of -0.10 (95% confidence interval [CI]; -0.18, -0.01) and a weighted mean difference (WMD) of -1.38 neuropsychiatry inventory point (95% CI; -2.30, -0.46). In studies with mild AD patients, the WMD was -1.92 (95% CI; -3.18, -0.66); and in studies with severe AD patients, the WMD was -0.06 (95% CI; -2.12, +0.57). Conclusion: Cholinesterase inhibitors lead to a statistical significant reduction in BPSD among patients with AD, yet the clinical relevance of this effect remains unclear.

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Objectives: Are behavioural interventions effective in reducing the rate of sexually transmitted infections (STIs) among genitourinary medicine (GUM) clinic patients? Design: Systematic review and meta-analysis of published articles. Data sources: Medline, CINAHL, Embase, PsychINFO, Applied Social Sciences Index and Abstracts, Cochrane Library Controlled Clinical Trials Register, National Research Register (1966 to January 2004). Review methods: Randomised controlled trials of behavioural interventions in sexual health clinic patients were included if they reported change to STI rates or self reported sexual behaviour. Trial quality was assessed using the Jadad score and results pooled using random effects meta-analyses where outcomes were consistent across studies. Results: 14 trials were included; 12 based in the United States. Experimental interventions were heterogeneous and most control interventions were more structured than typical UK care. Eight trials reported data on laboratory confirmed infections, of which four observed a greater reduction in their intervention groups (in two cases this result was statistically significant, p<0.05). Seven trials reported consistent condom use, of which six observed a greater increase among their intervention subjects. Results for other measures of sexual behaviour were inconsistent. Success in reducing STIs was related to trial quality, use of social cognition models, and formative research in the target population. However, effectiveness was not related to intervention format or length. Conclusions: While results were heterogeneous, several trials observed reductions in STI rates. The most effective interventions were developed through extensive formative research. These findings should encourage further research in the United Kingdom where new approaches to preventing STIs are urgently required.

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Markets are dynamic by nature, and marketing efforts can be directed to stimulate, reduce, or to utilize these dynamics. The field of marketing dynamics aims at modeling the effects of marketing actions and policies on short-term performance (“lift”) and on long-term performance (“base”). One of the core questions within this field is: “How do marketing efforts affect outcome metrics such as revenues, profits, or shareholder value over time?” Developments in statistical modeling and new data sources allow marketing scientists to provide increasingly comprehensive answers to this question. We present an outlook on developments in modeling marketing dynamics and specify research directions.

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Purpose: Current conceptualisations of strategic flexibility and its antecedents are theory-driven, which has resulted in a lack of consensus. To summarise this domain the paper aims to develop and present an a priori conceptual model of the antecedents and outcomes of strategic flexibility. Discussion and insights into the conceptual model, and the relationships specified, are made through a novel qualitative empirical approach. The implications for further research and a framework for further theoretical development are presented. Design/methodology/approach: An exploratory qualitative research design is used applying multiple data collection techniques in a branch network of a large regional retailer in the UK. The development of strategic options and the complex relationship to strategic flexibility is investigated. Findings: The number and type of strategic options developed by managers impact on the degree of strategic flexibility and also on the ability of the firm to achieve competitive differentiation. Additionally, the type of strategic option implemented by managers is dependent on the competitive situation faced at a local level. Evidence of managers' limited perception of competition was identified based on their spatial embeddedness. Research limitations/implications: A single, in-depth case study was used. The data gathered is rich and appropriate for the exploratory approach adopted here. However, generalisability of the findings is limited. Practical implications: Strategic flexibility is rooted in the ability of front-line mangers to develop and implement strategic options; this in turn facilitates competitive differentiation. Originality/value: The research presented is unique in this domain on two accounts. First, theory is developed by presenting an a priori conceptual model, and testing through in-depth qualitative data gathering. Second, insights into strategic flexibility are presented through an examination of managerial cognition, resources and strategic option generation using cognitive mapping and laddering technique. © Emerald Group Publishing Limited.

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Purpose – This paper aims to focus on developing critical understanding in human resource management (HRM) students in Aston Business School, UK. The paper reveals that innovative teaching methods encourage deep approaches to study, an indicator of students reaching their own understanding of material and ideas. This improves student employability and satisfies employer need. Design/methodology/approach – Student response to two second year business modules, matched for high student approval rating, was collected through focus group discussion. One module was taught using EBL and the story method, whilst the other used traditional teaching methods. Transcripts were analysed and compared using the structure of the ASSIST measure. Findings – Critical understanding and transformative learning can be developed through the innovative teaching methods of enquiry-based learning (EBL) and the story method. Research limitations/implications – The limitation is that this is a single case study comparing and contrasting two business modules. The implication is that the study should be replicated and developed in different learning settings, so that there are multiple data sets to confirm the research finding. Practical implications – Future curriculum development, especially in terms of HE, still needs to encourage students and lecturers to understand more about the nature of knowledge and how to learn. The application of EBL and the story method is described in a module case study – “Strategy for Future Leaders”. Originality/value – This is a systematic and comparative study to improve understanding of how students and lecturers learn and of the context in which the learning takes place.

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In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our proposal includes a merging algorithm that aggregates, combines and filters ontology-based search results and three different ranking algorithms that sort the final answers according to different criteria such as popularity, confidence and semantic interpretation of results. An experimental evaluation on a large scale corpus indicates improvements in the quality of the search results with respect to a scenario where the merging and ranking algorithms were not applied. These collective methods for merging and ranking allow to answer questions that are distributed across ontologies, while at the same time, they can filter irrelevant answers, fuse similar answers together, and elicit the most accurate answer(s) to a question.