Miracle-dz/UniFAR-FTUs huggingface dataset:
Realising context-oriented information filtering

The notion of information overload is an increasing factor in modern information service environments where information is ‘pushed’ to the user. As increasing volumes of information are presented to computing users in the form of email, web sites, instant messaging and news feeds, there is a growing need to filter and prioritise the importance of this information. ‘Information management’ needs to be undertaken in a manner that not only prioritises what information we do need, but to also dispose of information that is sent, which is of no (or little) use to us. The development of a model to aid information filtering in a context-aware way is developed as an objective for this thesis. A key concern in the conceptualisation of a single concept is understanding the context under which that concept exists (or can exist). An example of a concept is a concrete object, for instance a book. This contextual understanding should provide us with clear conceptual identification of a concept including implicit situational information and detail of surrounding concepts. Existing solutions to filtering information suffer from their own unique flaws: textbased filtering suffers from problems of inaccuracy; ontology-based solutions suffer from scalability challenges; taxonomies suffer from problems with collaboration. A major objective of this thesis is to explore the use of an evolving community maintained knowledge-base (that of Wikipedia) in order to populate the context model from prioritise concepts that are semantically relevant to the user’s interest space. Wikipedia can be classified as a weak knowledge-base due to its simple TBox schema and implicit predicates, therefore, part of this objective is to validate the claim that a weak knowledge-base is fit for this purpose. The proposed and developed solution, therefore, provides the benefits of high recall filtering with low fallout and a dependancy on a scalable and collaborative knowledge-base. A simple web feed aggregator has been built using the Java programming language that we call DAVe’s Rss Organisation System (DAVROS-2) as a testbed environment to demonstrate specific tests used within this investigation. The motivation behind the experiments is to demonstrate that the combination of the concept frame-
Needs-based planning: the case of Manitoba.

OBJECTIVE To illustrate the use of needs-based planning in the identification of physician surpluses and deficits and of resource misallocations within a provincial medical system at a time when provincial governments and medical associations across the country are faced with funding constraints for physician services. DESIGN For each of 4 regions in Manitoba, the authors analysed residents' rates of physician visits (whether within the resident's own or another region). Residents' need for physician contact was estimated by means of a statistical analysis of the data on contacts in relation to age, sex and health-related indicators, and the rates of visits needed and actually made were compared. PARTICIPANTS All Manitoba residents. OUTCOME MEASURES Numbers of generalist physicians (general practitioners, family physicians, general internists and general pediatricians) needed to serve each region, and the extent of physician surplus and deficit in each region. RESULTS There appeared to be a surplus of physicians in most of urban Manitoba but deficits in northern Manitoba and some parts of the rural south. General internists and general pediatricians in Winnipeg provide a significant part of the ambulatory care that is provided by general practitioners in other parts of the province. The provincial government currently spends more per resident to provide physician services in areas of physician surplus than in areas of physician deficit, although the patterns are inconsistent. CONCLUSIONS Needs-based planning is possible. If provinces are intent on controlling physician numbers and expenditures, it makes sense to manage the implications of doing so.
Embedding Propagators in a Concurrent Constraint Language

Solving large and hard discrete combinatorial problems often requires the design of new constraints. Current constraint systems focus on either highlevel modeling or efficient implementation technology. While each approach lacks the advantages of the other one, this paper describes the combination of them in the high-level concurrent constraint language Oz. We describe an interface to Oz providing abstractions to program new efficient constraints in C++, preserving the benefits of Oz for problem modeling. While constraints and the Oz runtime system are linked through the interface, and adequate interface abstractions are supplied to implement advanced algorithmic techniques. In particular, it provides the means to reflect the validity of a constraint and to control and inspect the state of a constraint. This allows the user to solve demanding combinatorial problems, such as hard scheduling problems. It is desirable to execute concurrent constraint programs in parallel to profit from multiprocessor architectures. We discuss how the proposed interface can be adapted to parallel execution, avoiding the recoding of constraint implementations for sequential solvers.
Effects of Dexamethasone on Fetal Doppler Indices

Objective: To assess the impacts of dexamethasone given to the mother on fetal Doppler flow velocity waveforms of both umbilical and fetal middle cerebral arteries in pregnancies with normal fetoplacental vascular resistance. Study Design: Prospective Study. Patients and Methods: Pregnant women between 28 weeks and 34 weeks gestation at risk of preterm labour, Preterm birth was anticipated on the basis of: History of previous preterm birth, dilating cervix, antepartum hemorrhage, Preterm premature rupture of the membranes, increased amniotic fluid volume, Patients with possible need for early termination of pregnancy including those with history of previous uterine rupture and hysterotomy. Intramuscular dexamethasone was given as 4 doses dexamethasone (6mg/12 hours for 48 hrs), Doppler ultrasound assessment of umbilical artery (UA), middle cerebral artery (MCA) both resistive index (RI) and pulsatility index (PI) were done as baseline, day 2 and day 4. Results: There was no significant variation noted in UA or MCA PI or RI throughout dexamethasone therapy. Conclusion: Dexamethasone treatment was not associated with significant changes in the mean values of the pulsatility, resistive indices in umbilical artery and fetal middle cerebral artery, Awareness of this drug-induced effect might prevent unnecessary iatrogenic delivery of preterm fetuses.
Enhanced oil recovery using silica nanoparticles in the presence of salts for wettability alteration

Abstract This study focuses on the performance of nanosilica particles in the injected brine with different salt concentrations. For investigating the effect of SiO2-water-salt nanofluid in improving oil recovery, a set of experiment was conducted in both static and dynamic conditions. Interfacial Tension (IFT) measurement, contact angle measurements on glass surfaces, adhesion tests on sandstone grains and micromodel flooding tests were conducted. IFT results showed that although presence of nanoparticles can decrease the interfacial tension between injected brine and oil, but this change is not significant. The effect of nanofluid and salt concentration on the surface/fluid interaction was investigated by contact angle tests and new adhesion tests using grains of rocks. Both tests confirm that presence of nanofluid and salt can shift the wettability of rock surfaces towards more water wet condition. A glass micromodel was constructed for conducting flooding test to compare the capability of the nanofluid solution with/without salt, for improving oil recovery in dynamic conditions. The obtained results of all experiments demonstrated that silica nanoparticles are able to improve the wettability of both glass and sandstone surfaces towards more water-wet conditions. Wettability alteration by electrical double layer (EDL) and multicomponent ion exchange (MIE) are the dominant mechanisms in glass and sandstone surfaces during LSW injection and disjoining pressure is the major mechanism during nanofluid flooding. The presence of salts in the nanolfuids also showed to have a pronounced positive effect on the level of wettability alteration due to more adsorption of nanoparticles on the rock surface. Graphical Abstract
Visualization Cockpit: Orchestration of Multiple Visualizations for Knowledge-Exploration

Semantic-Web technologies and ontology-based information processing systems are established techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies, so they work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The customization of the presentation itself and the interaction techniques with these presentation artifacts is a key question for gainful and effective work with semantic information. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps.
Finite-element modeling for the design optimization of microwave filters

This paper outlines an electromagnetic optimization technique dedicated to the design of microwave bandpass filters. The purpose is to determine the optimal dimensions of the electromagnetic model. Applying this technique, the geometrical dimensions of the distributed structure are accurately determined, and no experimental readjustment is necessary. The optimization procedure combines an electromagnetic analysis and a parameter extraction. The analysis method is a finite-element modeling coupled with a frequency parameterization technique for improving the computation time. The parameter extraction method is based on the approximation of the simulated scattering matrix and on the synthesis of the equivalent electrical network. The comparison between extracted and ideal networks enables to converge the optimal dimensions. The procedure is applied to design a dual-mode waveguide filter. In this case, within the electromagnetic model, the screws are taken into account using lumped elements which may be adjusted independently.
Long-Term Treatment of Obsessive-Compulsive Disorder After an Acute Response: A Comparison of Fluoxetine Versus Placebo

Few controlled studies have evaluated the long-term continuation of pharmacotherapy for relapse prevention in patients with obsessive-compulsive disorder (OCD). This study assessed efficacy and safety of fluoxetine versus placebo in preventing relapse of OCD during a 52-week period in responders to short-term administration of fluoxetine. Patients who met DSM-IV criteria for OCD and had a Yale-Brown Obsessive Compulsive Scale score ≥19 were treated with single-blind fluoxetine 20, 40, or 60 mg/day (based on physician assessment of response and tolerability). After 20 weeks, responders were randomly assigned to receive continued treatment with fluoxetine or placebo and were monitored for relapse for up to 52 weeks. Of 130 patients who entered the study, 71 (55%) were randomly assigned to receive fluoxetine (N = 36) or placebo (N = 35). Patients who received fluoxetine had numerically lower relapse rates compared with those who received placebo, although the difference was not significant (Kaplan-Meier 1-year relapse rates: fluoxetine, 20.6%; placebo, 31.9%; one-tailed p value = 0.137). In additional analyses evaluating patients on the basis of fluoxetine dose at randomization, patients who continued treatment with fluoxetine 60 mg/day (N = 52) had significantly lower rates of relapse than those who were switched to placebo (Kaplan-Meier 1-year relapse rates: fluoxetine, 17.5%; placebo, 38.0%; one-tailed p value = 0.041). Those who responded to the acute treatment phase with 40 (N = 18) or 20 (N = 1) mg/day had low overall rates of relapse, and the difference between continued fluoxetine and placebo treatment for these patients was not significant. For responders to the 60 mg/day dosage, those patients who continued treatment with fluoxetine were provided greater protection against relapse than those patients switched to placebo.
Automatic clustering of eye gaze data for machine learning

Eye gaze patterns or scanpaths of subjects looking at art while answering questions related to the art have been used to decode those tasks with the use of certain classifiers and machine learning techniques. Some of these techniques require the artwork to be divided into several Areas or Regions of Interest. In this paper, two ways of clustering the static visual stimuli - k-means and the density based clustering algorithm called OPTICS - were used for this purpose. These algorithms were used to cluster the gaze points before classification. The classification success rates were then compared. While it was observed that both k-means and OPTICS gave better success rates than manual clustering, which is itself higher than chance level, OPTICS consistently gave higher success rates than k-means given the right parameter settings. OPTICS also formed clusters that look more intuitive and consistent with the heat map readings than k-means, which formed clusters that look unintuitive and less consistent with the heat map.
Doris: A Tool for Interactive Exploration of Historic Corpora

Insights into social phenomenon can be gleaned from trends and patterns in corpora of documents associated with that phenomenon. Recent years have witnessed the use of computational techniques, mostly based on keywords, to analyze large corpora for these purposes. In this paper, we extend these techniques to incorporate semantic features. We introduce Doris, an interactive exploration tool that combines semantic features with information retrieval techniques to enable exploration of document corpora corresponding to the social phenomenon. We discuss the semantic techniques and describe an implementation on a corpus of United States (US) presidential speeches. We illustrate, with examples, how the ability to combine syntactic and semantic features in a visualization helps researchers more easily gain insights into the underlying phenomenon.
On Effective Dynamic Search in Specialized Domains

Dynamic search in specialized domains is a challenging task, in which systems must learn about the user's need from his or her interactive exploration. Despite recent initiatives to advance the state-of-the-art for this task, limited progress has been achieved, with the best performing dynamic search systems only marginally improving upon vanilla ad-hoc search systems. In this paper, we perform a comprehensive analysis of the impact of several components of a prototypical dynamic search system on the effectiveness of the entire system. Through a series of simulations, we discuss the impact of: producing an initial ranking of candidate documents, modeling the possible aspects underlying the user's query given his or her feedback, leveraging the modeled aspects to improve the initial ranking, and deciding when to stop the interactive process. Our results using data from the TREC 2015-2016 Dynamic Domain track shed light on these components and provide directions for the design of effective dynamic search systems for specialized domains.
Variables Partner Violence : Associations With Psychological and Relational Informal Social Reactions to College Women ' s Disclosure of Intimate

This researchers assessed informal (e.g., friends, family) social reactions to college women’s (N = 139) disclosure of intimate partner violence (IPV) within their current romantic relationships and associated psychological (i.e., posttraumatic stress symptoms [PTSS] and global psychological distress symptoms) and relational (i.e., intentions to leave the abusive relationship) variables. Women completed confidential surveys, which assessed current partner abuse, psychological and relational variables, and three types of social reactions from informal supports to disclosure of IPV: positive (e.g., believing, validating the victim), negative (e.g., disbelieving, blaming the victim), and leaving (i.e., being told to end the relationship) reactions. At the bivariate level, negative social reactions to women’s disclosure were related to increases in global psychological distress, PTSS, and leaving intentions; positive social reactions to disclosure related only to increases in PTSS; and 1University of New Hampshire, Durham, USA 2Ohio University, Athens, USA Corresponding Author: Katie M. Edwards, Department of Psychology, University of New Hampshire, 10 Library Way, Durham, NH 03824, USA. Email: katie.edwards@unh.edu 532524 JIVXXX10.1177/0886260514532524Cross-Cultural ResearchEdwards et al. research-article2014 by guest on December 1, 2014 jiv.sagepub. com Downloaded from 26 Journal of Interpersonal Violence 30(1) being told to leave the relationship related to increases in PTSS and leaving intentions. In the regression analyses, after controlling for abuse severity, negative social reactions were significantly related to global psychological distress and PTSS, and being told to leave significantly related to leaving intentions and PTSS. Mechanisms for these relationships and implications are discussed.
Distributed Macro Calibration via Output Synchronization in Lossy Sensor Networks

In this paper a novel distributed algorithm for blind macro calibration in sensor networks based on output synchronization is proposed. The algorithm is formulated as a set of gradient-type recursions for estimating parameters of sensor calibration functions, starting from local criteria dened as weighted sums of mean square dierences between the outputs of neighboring sensors. It is proved, on the basis of an originally developed methodology for treating higher-order consensus (or output synchronization) schemes, that the algorithm achieves asymptotic agreement for sensor gains and osets, in the mean square sense and with probability one. In the case of additive measurement noise, additive inter-agent communication noise, and communication outages, a modication of the original algorithm based on instrumental variables is proposed. It is proved using stochastic approximation arguments that the modied
Negative HCV-RNA 2 weeks after initiation of treatment predicts sustained virological response to pegylated interferon alfa-2a and ribavirin in patients with chronic hepatitis C

Abstract Objective. The aim of this study was to examine the early viral kinetics as predictor for sustained virological response (SVR) during hepatitis C treatment. Materials and methods. We included patients with biopsy-proven chronic hepatitis C and ALT above the upper limit of normal, who received a standard treatment of pegylated interferon alfa-2a and ribavirin. The HCV–RNA concentration (limit of detection 20 IU/mL) was determined at days 0, 1, 2, 3, 4, 7, 14, 21 and monthly thereafter. Results. Among 46 patients who completed the trial, 30 (65%) had SVR. Low baseline viral load, IL28B genotype CC and absence of cirrhosis were statistically associated with SVR. In multivariate analysis only absence of cirrhosis and HCV–RNA negativity at day 14 were independent predictors for SVR. Eight patients who became HCV–RNA negative on day 14 as well as 13 of 14 patients (93%) with HCV–RNA levels of <1000 IU/mL at day 7 obtained a SVR. Among 8 of 18 (44%) genotype 1 and 4 patients with more than a one log drop in HCV–RNA titer at day 7, 75% achieved SVR. Conclusions. We observed a correlation between low HCV–RNA titers in week 2 and SVR during pegylated interferon/ribavirin-based treatment. This may help identify a group of patients for whom SVR may be obtained without the addition of directly acting antivirals, and thereby save the patients for unnecessary side effects and the health care system for additional costs.
IoT Assisted Kernel Linear Discriminant Analysis Based Gait Phase Detection Algorithm for Walking With Cognitive Tasks

Gait phase detection is an important procedure in the application of many lower limb auxiliary robots. The gait phase detection algorithms that utilize surface electromyography (sEMG) signals have been developed to overcome unnatural walking. However, traditional studies mostly consider precise gait walking events when the subject is focusing only on walking, and the accuracy of traditional algorithms is susceptible to more realistic gait scenarios, such as walking with cognitive tasks. In this paper, the gait phase detection is considered in more realistic and challenging scenarios, in which the subject is walking while performing cognitive tasks. A kernel linear discriminant analysis (LDA)-based nonlinear fusion model is proposed for gait recognition, which can effectively reduce the error caused by cognitive tasks, making it an ideal model for gait phase detection while cognitive tasks are performed in the process of walking. Furthermore, the Internet of Things (IoT) framework is incorporated to reduce the gait phase detection algorithm’s process time by offloading the data from local sEMG sensors to the IoT server with powerful computation capability. The experiments have been conducted to validate our proposed algorithms, demonstrating that the boundaries between the stance period and swing period are more blurred when walking with cognitive tasks.
Cellular activating properties and morphology of membrane-bound and purified meningococcal lipopolysaccharide

Neisseria meningitidis, the cause of epidemic meningitis and acute lethal sepsis, synthesizes surplus lipopolysaccharides (LPSs) during growth, which are released as outer membrane vesicles (OMV) or `blebs'. Meningococcal disease severity is related to plasma LPS levels. We have compared the biological activities of native outer membrane vesicles (nOMV) to those of purified Nm-LPS (Nm-LPS) and LPS-depleted OMV (dOMV) prepared from N. meningitidis. The LPS content of nOMV was determined spectrophotometrically by quantifying KDO and by silver-stained SDS-PAGE gels. The morphology of the preparations was studied by transmission electron microscopy. The Limulus amoebocyte lysate (LAL) assay was used to quantify LPS in the plasma solutions. The preparations were diluted in endotoxin-free heparin plasma to equal amounts of LPS (w/w) in the range 50—5000 pg/ml. The biological reactivity was tested by: (i) a monocyte target-assay (monocyte purity ≥ 96%); and (ii) a whole blood model, measuring the secretion of TNF-α and IL-6 induction of procoagulant activity in monocytes (PCA). In both models, nOMV induced dose-dependent cell responses (TNF-α, IL-6, PCA) similar to purified Nm-LPS, whereas dOMV induced minimal responses. However, LAL activity was significantly higher for nOMV than for purified Nm-LPS and dOMV. The cellular responses of purified Nm-LPS and nOMV were reduced (>95%) by a specific anti-CD 14-antibody.