Information provenance for open distributed collaborative system

In autonomously managed distributed systems for collaboration, provenance can facilitate reuse of information that are interchanged, repetition of successful experiments, or to provide evidence for trust mechanisms that certain information existed at a certain period during collaboration. In this paper, we propose domain independent information provenance architecture for open collaborative distributed systems. The proposed system uses XML for interchanging information and RDF to track information provenance. The use of XML and RDF also ensures that information is universally acceptable even among heterogeneous nodes. Our proposed information provenance model can work on any operating systems or workflows.

Modeling relevant legal information for consumer disputes

Accessing relevant legal information found in text excerpts from heterogeneous sources is essential to the decision making process in consumer disputes. The Ontology of Relevant Legal Information in Consumer Disputes (ric) is the domain-independent ontology modeling this relevant legal information comprising rights, their requisites, exceptions, constraints, enforcement procedures, legal sources. Its use is exemplified with one extension thereof, the Air Transport Passenger Incidents Ontology (ric-atpi), representing both the possible incidents triggered by a complaint in the air transport passenger domain and the related legal information that might be applicable. The Ontology models the key provisions found in the hard law, and those in soft law, comprising heterogeneous sources in a structured manner. An ontology-based system provides the knowledge embedded in the legal sources and their relation to the specific scenario.

The performance of solarscan : an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma

Objective To describe the diagnostic performance of SolarScan (Polartechnics Ltd, Sydney, Australia), an automated instrument for the diagnosis of primary melanoma.

Design Images from a data set of 2430 lesions (382 were melanomas; median Breslow thickness, 0.36 mm) were divided into a training set and an independent test set at a ratio of approximately 2:1. A diagnostic algorithm (absolute diagnosis of melanoma vs benign lesion and estimated probability of melanoma) was developed and its performance described on the test set. High-quality clinical and dermoscopy images with a detailed patient history for 78 lesions (13 of which were melanomas) from the test set were given to various clinicians to compare their diagnostic accuracy with that of SolarScan.

Setting Seven specialist referral centers and 2 general practice skin cancer clinics from 3 continents. Comparison between clinician diagnosis and SolarScan diagnosis was by 3 dermoscopy experts, 4 dermatologists, 3 trainee dermatologists, and 3 general practitioners.

Patients Images of the melanocytic lesions were obtained from patients who required either excision or digital monitoring to exclude malignancy.

Main Outcome Measures Sensitivity, specificity, the area under the receiver operator characteristic curve, median probability for the diagnosis of melanoma, a direct comparison of SolarScan with diagnoses performed by humans, and interinstrument and intrainstrument reproducibility.

Results The melanocytic-only diagnostic model was highly reproducible in the test set and gave a sensitivity of 91% (95% confidence interval [CI], 86%-96%) and specificity of 68% (95% CI, 64%-72%) for melanoma. SolarScan had comparable or superior sensitivity and specificity (85% vs 65%) compared with those of experts (90% vs 59%), dermatologists (81% vs 60%), trainees (85% vs 36%; P =.06), and general practitioners (62% vs 63%). The intraclass correlation coefficient of intrainstrument repeatability was 0.86 (95% CI, 0.83-0.88), indicating an excellent repeatability. There was no significant interinstrument variation (P = .80).

Conclusions SolarScan is a robust diagnostic instrument for pigmented or partially pigmented melanocytic lesions of the skin. Preliminary data suggest that its performance is comparable or superior to that of a range of clinician groups. However, these findings should be confirmed in a formal clinical trial.

Stability and convergence analysis of transform-domain LMS adaptive filters with second-order autoregressive process

In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.

What's wrong with me? Concerns about online medical self-diagnosis

Self-service technologies (SSTs) are becoming increasingly commonplace in healthcare. However, research on the customer (patient) experience in this context is rare. This paper focuses on online medical self-diagnosis, a type of e-health service. This SST can provide customers with benefits such as greater convenience and control, yet we argue that this form of do-it-yourself doctoring also raises concerns for customers. This paper contributes to the service domain by presenting research propositions on the potential negative implications for customers, and their antecedents, of online medical self-diagnosis. We propose that this form of self-diagnosis is related to harms, such as customer anxiety, customer willingness to bypass healthcare professionals, and self-medication. Future research opportunities are discussed, along with implications for policy and practice.

Independent functions of yeast Pcf11p in pre-mRNA 3´ end processing and in transcription termination

Pcf11p, an essential subunit of the yeast cleavage factor IA, is required for pre-mRNA 3' end processing, binds to the C-terminal domain (CTD) of the largest subunit of RNA polymerase II (RNAP II) and is involved in transcription termination. We show that the conserved CTD interaction domain (CID) of Pcf11p is essential for cell viability. Interestingly, the CTD binding and 3' end processing activities of Pcf11p can be functionally uncoupled from each other and provided by distinct Pcf11p fragments in trans. Impaired CTD binding did not affect the 3' end processing activity of Pcf11p and a deficiency of Pcf11p in 3' end processing did not prevent CTD binding. Transcriptional run-on analysis with the CYC1 gene revealed that loss of cleavage activity did not correlate with a defect in transcription termination, whereas loss of CTD binding did. We conclude that Pcf11p is a bifunctional protein and that transcript cleavage is not an obligatory step prior to RNAP II termination.

Application of an adaptive neural network with symbolic rule extraction to fault detection and diagnosis in a power generation plant

Artificial neural networks have a good potential to be employed for fault diagnosis and condition monitoring problems in complex processes. In this paper, the applicability of the fuzzy ARTMAP (FAM) neural network as an intelligent learning system for fault detection and diagnosis in a power generation plant is described. The process under scrutiny is the circulating water (CW) system, with specific attention to the conditions of heat transfer and tube blockage in the CW system. A series of experiments has been conducted systematically to investigate the effectiveness of FAM in fault detection and diagnosis tasks. In addition, a set of domain rules has been extracted from the trained FAM network so that its predictions can be explained and justified. The outcomes demonstrate the benefits of employing FAM as an intelligent fault detection and diagnosis tool with an explanatory capability for monitoring and diagnosing complex processes in power generation plants.

Multitasking: multiple, domain-specific cognitive functions in a virtual environment

Multitasking among three or more different tasks is a ubiquitous requirement of everyday cognition, yet rarely is it addressed in research on healthy adults who have had no specific training in multitasking skills. Participants completed a set of diverse subtasks within a simulated shopping mall and office environment, the Edinburgh Virtual Errands Test (EVET). The aim was to investigate how different cognitive functions, such as planning, retrospective and prospective memory, and visuospatial and verbal working memory, contribute to everyday multitasking. Subtasks were chosen to be diverse, and predictions were derived from a statistical model of everyday multitasking impairments associated with frontal-lobe lesions (Burgess, Veitch, de Lacy Costello, & Shallice, 2000b). Multiple regression indicated significant independent contributions from measures of retrospective memory, visuospatial working memory, and online planning, but not from independent measures of prospective memory or verbal working memory. Structural equation modelling showed that the best fit to the data arose from three underlying constructs, with Memory and Planning having a weak link, but with both having a strong directional pathway to an Intent construct that reflected implementation of intentions. Participants who followed their preprepared plan achieved higher scores than those who altered their plan during multitask performance. This was true regardless of whether the plan was efficient or poor. These results substantially develop and extend the Burgess et al. (2000b) model to healthy adults and yield new insight into the poorly understood area of everyday multitasking. The findings also point to the utility of using virtual environments for investigating this form of complex human cognition.

An empirical comparison of classification algorithms for diagnosis of depression from brain sMRI scans

To be diagnostically effective, structural magnetic resonance imaging (sMRI) must reliably distinguish a depressed individual from a healthy individual at individual scans level. One of the tasks in the automated diagnosis of depression from brain sMRI is the classification. It determines the class to which a sample belongs (i.e., depressed/not depressed, remitted/not-remitted depression) based on the values of its features. Thus far, very limited works have been reported for identification of a suitable classification algorithm for depression detection. In this paper, different types of classification algorithms are compared for effective diagnosis of depression. Ten independent classification schemas are applied and a comparative study is carried out. The algorithms are: Naïve Bayes, Support Vector Machines (SVM) with Radial Basis Function (RBF), SVM Sigmoid, J48, Random Forest, Random Tree, Voting Feature Intervals (VFI), LogitBoost, Simple KMeans Classification Via Clustering (KMeans) and Classification Via Clustering Expectation Minimization (EM) respectively. The performances of the algorithms are determined through a set of experiments on sMRI brain scans. An experimental procedure is developed to measure the performance of the tested algorithms. A classification accuracy evaluation method was employed for evaluation and comparison of the performance of the examined classifiers.

Diagnose lernabhängiger veränderung mentaler modelle

Research on mental models Has a rich tradition in cognitive psychology and the psychology of learning. Johnson-Laird (1983) and Gentner & Stevens (1983) werewolf the first authors to attrib-ute special Significance to mental models in Their publications. Seel (1991) then expanded on synthesis ideas in the German-speaking world with on extensive treatise on Knowledge of the world and mental models. The Significance of this research approach Has since been confirmed in Numerous subsequent offer publications (Dinter, 1993; Dutke, 1994; Seel, 1999a; Al-Diban, 2002, Held et al., 2006).In the present study, I would like to Contribute to this discussion from a Methodological per-Spective. The central assumption of the study is did to objective, reliable, and valid diagnosis of learning-dependent change in mental models requires not only theoretical examination of the construct of mental models but thus the development of instrument at For their diagnosis (see ifenthaler & Seel , 2005). The newly developed SMD technology Enables the automated and com-puter-aided diagnosis of externalized models independent of content domain. The externalized models are Diagnosed on three levels, each with a different focus.The central research question as to Whether, and if so how, mental models change in the course of the learning process is Investigated in three experimental studies (N = 106). The longi-tudinal design of the studies Enables a precise diagnosis across a total of seven points of meas-urement. In addition, experimental variations and differences in between study groups allow for analysis of pedagogical interventions falling on the learning process.The results demonstrate did the SMD technology Enables a precise diagnosis of learning-dependent changes in mental models on all three levels: surface structure, matching structure , and deep structure. It was Possible in the three experimental studies to detect a learning-dependent change in mental models on the relational and the structural level. Additionally, the semantic structure of the externalized models Proved to be more Closely similar to the explanation model than to the expert model.The study Concludes with a discussion of the empirical findings and a research outlook Which CLEARLY demarcates Their Range of application. Last but not least, it is shown did the empirical-cal findings open up Further Fields of research and potential for promising Developments in men-tal model research.

Cancer risk factors, diagnosis and sexual identity in the Australian longitudinal study of women's health

PURPOSE: We sought to examine cancer diagnosis, cancer treatment, and related risk factors among Australian, middle-aged, exclusively heterosexual women compared with sexual minority women (SMW; mainly heterosexual, bisexual, mainly lesbian, and lesbian). METHODS: Secondary data analysis of the Australian Longitudinal Study of Women's Health for women born in 1946 through 1951 (n = 10,451) included bivariate tests (i.e., contingency table analyses, independent t tests). RESULTS: SMW did not have significantly higher cancer diagnoses compared with exclusively heterosexual women, although they were more likely to report never having had a mammogram or pap smear. SMW were also significantly more likely to be high-risk drinkers (11.1% vs. 6.8%; p < .05), current smokers (15.1% vs. 8.3%; p < .001), report significantly higher rates of depression (mean ± SD; 6.4 ± 5.5 vs. 5.4 ± 5.1; p < .01.), have experienced physical abuse (10.2% vs. 5.1%; p < .001), and been in a violent relationship (27.2% vs. 12.8%; p < .001). CONCLUSION: SMW had higher rates of several known cancer risk factors, ostensibly placing them at higher risk of cancer as well as chronic health conditions. Further research is needed to determine whether increased risk results in increased cancer as these women age, and to inform the development of interventions to reduce the risk of disease for SMW.

A domain-specific approach for assessing physical activity efficacy in adolescents: from scale conception to predictive validity

Objective: To develop and test the utility of a domain-specific physical activity efficacy scale in adolescents for predicting physical activity behaviour. Design: Two independent studies were conducted. Study 1 examined the psychometric properties of a newly constructed Domain-Specific Physical Activity Efficacy Questionnaire (DSPAEQ) and study 2 tested the utility of the scale for predicting leisure- and school-time physical activity. Methods: In study 1, descriptive physical activity data were used to generate scale items. The scales factor structure and internal consistency were tested in a sample of 272 adolescents. A subsequent sample of Canadian (N = 104) and New Zealand (N = 29) adolescents, was recruited in study 2 to explore the scale's predictive validity using a subjective measure of leisure- and school-time physical activity. Results: A principle axis factor analysis in study 1 revealed a 26-item, five-factor coherent and interpretable solution; representative of leisure and recreation, household, ambulatory, transportation, and school physical activity efficacy constructs, respectively. The five-factor solution explained 81% of the response variance. In study 2 the domain-specific efficacy model explained 16% and 1% of leisure- and school-time physical activity response variance, respectively, with leisure time physical activity efficacy identified as a unique and significant contributor of leisure-time physical activity. Conclusion: Study 1 provides evidence for the tenability of a five factor DSPEAQ, while study 2 shows that the DSPEAQ has utility in predicting domain-specific physical activity. This latter finding underscores the importance of scale correspondence between the behavioural elements (leisure-time physical activity) and cognitive assessment of those elements (leisure-time physical activity efficacy).

Targeting CD44, ABCG2 and CD133 markers using aptamers: in silico analysis of CD133 extracellular domain 2 and its aptamer

The application of nucleic acid aptamers for the diagnosis and therapy of cancer stem cells (CSCs) is expanding. The current study truncated and probed various existing aptamers against CSC markers CD44, ABCG2 and CD133 in retinoblastoma (RB) primary cells, cell lines, a breast cancer cell line and MCF7-sphere. Truncated CD44 aptamer retained its specific binding to cancer cells, ABCG2+ve MCF7-spheres and CD133+ve RB cells. Similarly, ABCG2 and CD133 aptamers showed higher affinity to ABCG2+ve, CD133+ve cells than the negative population and cell lines. All aptamers appreciably reduced viability of up to 50% and 32% of the primary RB tumor cells and cell lines, respectively. Colony formation of MCF7, RB cell lines and MCF7-sphere growth were inhibited significantly. Structure prediction, simulation of CD133 extracellular domain 2 (ExD2) and A15 followed by docking to comprehend the potential interaction revealed hydrogen bonds and non bonded interactions between them. This information could be used to improve the A15 aptamer to gain more interactions with CD133. Thus approaches undertaken here can be applied universally for cell-specific targeting, and the aptamers studied against CSC markers deserve further in vivo studies.