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

Automated verification of shape, size and bag properties.

In recent years, separation logic has emerged as a contender for formal reasoning of heap-manipulating imperative programs. Recent works have focused on specialised provers that are mostly based on fixed sets of predicates. To improve expressivity, we have proposed a prover that can automatically handle user-defined predicates. These shape predicates allow programmers to describe a wide range of data structures with their associated size properties. In the current work, we shall enhance this prover by providing support for a new type of constraints, namely bag (multi-set) constraints. With this extension, we can capture the reachable nodes (or values) inside a heap predicate as a bag constraint. Consequently, we are able to prove properties about the actual values stored inside a data structure

EveTAR: Building a Large-Scale Multi-Task Test Collection over Arabic Tweets

This article introduces a new language-independent approach for creating a large-scale high-quality test collection of tweets that supports multiple information retrieval (IR) tasks without running a shared-task campaign. The adopted approach (demonstrated over Arabic tweets) designs the collection around significant (i.e., popular) events, which enables the development of topics that represent frequent information needs of Twitter users for which rich content exists. That inherently facilitates the support of multiple tasks that generally revolve around events, namely event detection, ad-hoc search, timeline generation, and real-time summarization. The key highlights of the approach include diversifying the judgment pool via interactive search and multiple manually-crafted queries per topic, collecting high-quality annotations via crowd-workers for relevancy and in-house annotators for novelty, filtering out low-agreement topics and inaccessible tweets, and providing multiple subsets of the collection for better availability. Applying our methodology on Arabic tweets resulted in EveTAR , the first freely-available tweet test collection for multiple IR tasks. EveTAR includes a crawl of 355M Arabic tweets and covers 50 significant events for which about 62K tweets were judged with substantial average inter-annotator agreement (Kappa value of 0.71). We demonstrate the usability of EveTAR by evaluating existing algorithms in the respective tasks. Results indicate that the new collection can support reliable ranking of IR systems that is comparable to similar TREC collections, while providing strong baseline results for future studies over Arabic tweets

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

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

Evaluating the feasibility of complex interventions in mental health services: standardised measure and reporting guidelines

Aims: To develop a) an empirically-based standardised measure of the feasibility of complex interventions for use within mental health services and b) reporting guidelines to facilitate feasibility assessment. Method: A focussed narrative review of studies assessing implementation blocks and enablers was conducted with thematic analysis and vote counting used to determine candidate items for the measure. Twenty purposively sampled studies (15 trial reports, 5 protocols) were included in the psychometric evaluation, spanning different interventions types. Cohen’s Kappa was calculated for inter-rater reliability and test-retest reliability. Results: 95 influences on implementation were identified from 299 reviewed references. The final measure - Structured Assessment of Feasibility (SAFE) - comprises 16 items rated on a Likert scale. SAFE demonstrated excellent inter-rater (kappa 0.84, 95% CI 0.79 - 0.89) and test re-test reliability (kappa 0.89, 95% CI 0.85 - 0.93). Cost information and training time were the two influences least likely to be reported in intervention papers. SAFE Reporting Guidelines include 16 items organised into 3 categories (Intervention, Resource consequences, Evaluation). Conclusion: SAFE is a novel approach to evaluating interventions, and supplements efficacy and health economic evidence. SAFE Reporting Guidelines will allow feasibility of an intervention to be systematically assessed

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