Fusing Data with Correlations

Many applications rely on Web data and extraction systems to accomplish knowledge-driven tasks. Web information is not curated, so many sources provide inaccurate, or conflicting information. Moreover, extraction systems introduce additional noise to the data. We wish to automatically distinguish correct data and erroneous data for creating a cleaner set of integrated data. Previous work has shown that a na\"ive voting strategy that trusts data provided by the majority or at least a certain number of sources may not work well in the presence of copying between the sources. However, correlation between sources can be much broader than copying: sources may provide data from complementary domains (\emph{negative correlation}), extractors may focus on different types of information (\emph{negative correlation}), and extractors may apply common rules in extraction (\emph{positive correlation, without copying}). In this paper we present novel techniques modeling correlations between sources and applying it in truth finding.Comment: Sigmod'201

Expression of GPR17 receptor in a murine model of perinatal brain neuroinflammation and its possible interaction with Wnt pathway

Oligodendrocyte precursor cells (OPCs) are generated in specific germinal regions and progressively maturate to myelinating cells. Oligodendrocytes (OLs) differentiation is regulated by a complex interplay of intrinsic, epigenetic and extrinsic factors, including Wnt and the G protein-coupled receptor referred to as GPR17 (Mitew et al., 2014). This receptor responds to both extracellular nucleotides (UDP, UDP-glucose) and cysteinyl-leukotrienes (Ciana et al., 2006), endogenous signaling molecules involved in inflammatory response and in the repair of brain lesions. GPR17 is highly expressed in OPCs during the transition to immature OLs, but it is down-regulated in mature cells. Accordingly, GPR17-expressing OPCs are already present in mice at birth, increase over time, reach a peak at P10, before the peak of myelination, and then decline in the adult brain (Boda et al., 2011). Of note, in cultured OPCs, early GPR17 silencing has been shown to profoundly affect their ability to generate mature OLs (Fumagalli et al., 2011, 2015). Myelination defects characterize many brain disorders, including perinatal brain injury caused by systemic inflammation (Favrais et al., 2011), which is a leading cause of preterm birth. It has already been suggested that an imbalance in the Wnt/\u3b2-catenin/TCF4 pathway could be involved in the maturation arrest of OLs that is observed in premature infants (Yuen et al., 2014). No data are currently available on GPR17 in perinatal brain injury and on its possible interaction with Wnt pathway. Based on these premises, the aim of this work was to assess if the maturational blockade of OLs due to mild systemic perinatal inflammation, induced by intraperitoneal injections of interleukin-1\u3b2 (IL- 1\u3b2), is accompanied by defects in GPR17 expression and whether the Wnt pathway is involved in the regulation of GPR17. Data showed that in newborn mice exposed to IL-1\u3b2, which induces a blockade of oligodendrocyte maturation, GPR17 expression is not affected at early time point (P5), but it is downregulated at P10, when its expression should be maximal. Moreover, in vitro studies revealed that the maturation blockade of the oligodendroglial cell line Oli-Neu, after treatment with a Wnt Agonist II, is accompanied by a severe inhibition of GPR17 expression. In conclusion, our data have shown that myelination defects observed in perinatal brain injury are associated with defects in GPR17 expression; further studies are needed to characterize the molecular link between Wnt pathway and GPR17 receptor

Altered Auditory Feedback In-The-Ear Devices

Purpose: This study examined objective and subjective measures of the effect of a self-contained ear-level device delivering altered auditory feedback (AAF) for those who stutter 12 months following initial fitting with and without the device. Method: Nine individuals with developmental stuttering participated. In Experiment 1, the proportion of stuttering was examined during reading and monologue. A self-report inventory inquiring about behavior related to struggle, avoidance and expectancy associated with stuttering was examined in Experiment 2. In Experiment 3, naive listeners rated the speech naturalness of speech produced by the participants during reading and monologue. Results: The proportions of stuttering events were significantly (p < 0.05) reduced at initial fitting and remained so 12 months post follow-up. After using the device for 12 months, self- reported perception of struggle, avoidance and expectancy were significantly (p < 0.05) reduced relative to pre-fitting. Naive listeners rated the speech samples produced by those who stutter while wearing the device significantly more natural sounding than those produced without the device for both reading and monologue (p < 0.0001). Conclusions: These findings support the notion that a device delivering AAF is a viable therapeutic alternative in the treatment of stuttering

Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

<p>Abstract</p> <p>Background</p> <p>Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this research was to form a partnership of healthcare providers, managers, and researchers to review randomized controlled trials assessing the effects of computerized decision support for six clinical application areas: primary preventive care, therapeutic drug monitoring and dosing, drug prescribing, chronic disease management, diagnostic test ordering and interpretation, and acute care management; and to identify study characteristics that predict benefit.</p> <p>Methods</p> <p>The review was undertaken by the Health Information Research Unit, McMaster University, in partnership with Hamilton Health Sciences, the Hamilton, Niagara, Haldimand, and Brant Local Health Integration Network, and pertinent healthcare service teams. Following agreement on information needs and interests with decision-makers, our earlier systematic review was updated by searching Medline, EMBASE, EBM Review databases, and Inspec, and reviewing reference lists through 6 January 2010. Data extraction items were expanded according to input from decision-makers. Authors of primary studies were contacted to confirm data and to provide additional information. Eligible trials were organized according to clinical area of application. We included randomized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a computerized clinical decision support system compared with patient care without such a system.</p> <p>Results</p> <p>Data will be summarized using descriptive summary measures, including proportions for categorical variables and means for continuous variables. Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates. When reporting results from individual studies, we will cite the measures of association and p-values reported in the studies. If appropriate for groups of studies with similar features, we will conduct meta-analyses.</p> <p>Conclusion</p> <p>A decision-maker-researcher partnership provides a model for systematic reviews that may foster knowledge translation and uptake.</p

The feasibility of psychomotor therapy in acute mental health services for adults with intellectual disability

Background. Psychomotor therapy enables people to reflect on the relationship between experiences and feelings by starting from awareness of bodily responses rather than from awareness of emotion. In this study we examine PsyMot (ID), an assessment that directs this psychological therapy. Method. Twelve suitable consecutive admissions were recruited from a specialist intellectual disability (ID) assessment and treatment unit for adults. Video-recordings of PsyMot (ID) allowed assessment of interrater reliability (IRR). Treatment goals indicated by PsyMot (ID) were addressed using psychomotor therapy as part of a comprehensive program of interventions. Results. Psychomotor therapy was both feasible and popular with patients who participated without any adverse effects. Nine patients completed PsyMot (ID). IRR of the treatment goals identified by all 3 raters was good to excellent in 81% cases, but there were discrepancies for individual items. Conclusions. PsyMot (ID) and psychomotor therapy is feasible within this context, and enriched the clinical team's formulation. Further studies of reliability and efficacy should be undertaken

You call it ‘Self-Exuberance,’ I call it ‘Bragging.’ Miscalibrated Predictions of Emotional Responses to Self-Promotion

People engage in self-promotional behavior because they want others to hold favorable images of them. Self-promotion, however, entails a tradeoff between conveying one’s positive attributes and being seen as bragging. We propose that people get this tradeoff wrong because they erroneously project their own feelings onto their interaction partners. As a consequence, people overestimate the extent to which recipients of their self-promotion will feel proud of and happy for them, and underestimate the extent to which recipients will feel annoyed (Experiment 1 and 2). Because people tend to self-promote excessively when trying to make a favorable impression on others, such efforts often backfire, causing targets of the self-promotion to view the self-promoter as less likeable and as a braggart (Experiment 3)

Evaluating the End-User Experience of Private Browsing Mode

Nowadays, all major web browsers have a private browsing mode. However, the mode's benefits and limitations are not particularly understood. Through the use of survey studies, prior work has found that most users are either unaware of private browsing or do not use it. Further, those who do use private browsing generally have misconceptions about what protection it provides. However, prior work has not investigated \emph{why} users misunderstand the benefits and limitations of private browsing. In this work, we do so by designing and conducting a three-part study: (1) an analytical approach combining cognitive walkthrough and heuristic evaluation to inspect the user interface of private mode in different browsers; (2) a qualitative, interview-based study to explore users' mental models of private browsing and its security goals; (3) a participatory design study to investigate why existing browser disclosures, the in-browser explanations of private browsing mode, do not communicate the security goals of private browsing to users. Participants critiqued the browser disclosures of three web browsers: Brave, Firefox, and Google Chrome, and then designed new ones. We find that the user interface of private mode in different web browsers violates several well-established design guidelines and heuristics. Further, most participants had incorrect mental models of private browsing, influencing their understanding and usage of private mode. Additionally, we find that existing browser disclosures are not only vague, but also misleading. None of the three studied browser disclosures communicates or explains the primary security goal of private browsing. Drawing from the results of our user study, we extract a set of design recommendations that we encourage browser designers to validate, in order to design more effective and informative browser disclosures related to private mode

Testing for Differentially-Expressed MicroRNAs with Errors-in-Variables Nonparametric Regression

MicroRNA is a set of small RNA molecules mediating gene expression at post-transcriptional/translational levels. Most of well-established high throughput discovery platforms, such as microarray, real time quantitative PCR, and sequencing, have been adapted to study microRNA in various human diseases. The total number of microRNAs in humans is approximately 1,800, which challenges some analytical methodologies requiring a large number of entries. Unlike messenger RNA, the majority of microRNA (60%) maintains relatively low abundance in the cells. When analyzed using microarray, the signals of these low-expressed microRNAs are influenced by other non-specific signals including the background noise. It is crucial to distinguish the true microRNA signals from measurement errors in microRNA array data analysis. In this study, we propose a novel measurement error model-based normalization method and differentially-expressed microRNA detection method for microRNA profiling data acquired from locked nucleic acids (LNA) microRNA array. Compared with some existing methods, the proposed method significantly improves the detection among low-expressed microRNAs when assessed by quantitative real-time PCR assay

Overestimating Outcome Rates: Statistical Estimation When Reliability Is Suboptimal

To demonstrate how failure to account for measurement error in an outcome (dependent) variable can lead to significant estimation errors and to illustrate ways to recognize and avoid these errors. Data Sources . Medical literature and simulation models. Study Design/Data Collection . Systematic review of the published and unpublished epidemiological literature on the rate of preventable hospital deaths and statistical simulation of potential estimation errors based on data from these studies. Principal Findings . Most estimates of the rate of preventable deaths in U.S. hospitals rely upon classifying cases using one to three physician reviewers (implicit review). Because this method has low to moderate reliability, estimates based on statistical methods that do not account for error in the measurement of a “preventable death” can result in significant overestimation. For example, relying on a majority rule rating with three reviewers per case (reliability ∼0.45 for the average of three reviewers) can result in a 50–100 percent overestimation compared with an estimate based upon a reliably measured outcome (e.g., by using 50 reviewers per case). However, there are statistical methods that account for measurement error that can produce much more accurate estimates of outcome rates without requiring a large number of measurements per case. Conclusion . The statistical principles discussed in this case study are critically important whenever one seeks to estimate the proportion of cases belonging to specific categories (such as estimating how many patients have inadequate blood pressure control or identifying high-cost or low-quality physicians). When the true outcome rate is low (<20 percent), using an outcome measure that has low-to-moderate reliability will generally result in substantially overestimating the proportion of the population having the outcome unless statistical methods that adjust for measurement error are used.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74896/1/j.1475-6773.2006.00661.x.pd