Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic Review and Meta-Analysis of Randomised Trials to Ascertain Fatal Gastrointestinal Bleeding Events Attributable to Preventive Low-Dose Aspirin: No Evidence of Increased Risk

Background Aspirin has been shown to lower the incidence and the mortality of vascular disease and cancer but its wider adoption appears to be seriously impeded by concerns about gastrointestinal (GI) bleeding. Unlike heart attacks, stroke and cancer, GI bleeding is an acute event, usually followed by complete recovery. We propose therefore that a more appropriate evaluation of the risk-benefit balance would be based on fatal adverse events, rather than on the incidence of bleeding. We therefore present a literature search and meta-analysis to ascertain fatal events attributable to low-dose aspirin. Methods In a systematic literature review we identified reports of randomised controlled trials of aspirin in which both total GI bleeding events and bleeds that led to death had been reported. Principal investigators of studies in which fatal events had not been adequately described were contacted via email and asked for further details. A meta-analyses was then performed to estimate the risk of fatal gastrointestinal bleeding attributable to low-dose aspirin. Results Eleven randomised trials were identified in the literature search. In these the relative risk (RR) of ‘major’ incident GI bleeding in subjects who had been randomised to low-dose aspirin was 1.55 (95% CI 1.33, 1.83), and the risk of a bleed attributable to aspirin being fatal was 0.45 (95% CI 0.25, 0.80). In all the subjects randomised to aspirin, compared with those randomised not to receive aspirin, there was no significant increase in the risk of a fatal bleed (RR 0.77; 95% CI 0.41, 1.43). Conclusions The majority of the adverse events caused by aspirin are GI bleeds, and there appears to be no valid evidence that the overall frequency of fatal GI bleeds is increased by aspirin. The substantive risk for prophylactic aspirin is therefore cerebral haemorrhage which can be fatal or severely disabling, with an estimated risk of one death and one disabling stroke for every 1,000 people taking aspirin for ten years. These adverse effects of aspirin should be weighed against the reductions in vascular disease and cancer.
A Constructive Epistemic Logic with Public Announcement (Non-Predetermined Possibilities)

We argue that the notion of epistemic \emph{possible worlds} in constructivism (intuitionism) is not as the same as it is in classic view, and there are possibilities, called non-predetermined worlds, which are ignored in (classic) Epistemic Logic. Regarding non-predetermined possibilities, we propose a constructive epistemic logic and prove soundness and completeness theorems for it. We extend the proposed logic by adding a public announcement operator. To declare the significance of our work, we formulate the well-known Surprise Exam Paradox, $\mathbf{SEP}$, via the proposed constructive epistemic logic and then put forward a solution for the paradox. We clarify that the puzzle in the $\mathbf{SEP}$ is because of students'(wrong) assumption that the day of the exam is necessarily predetermined.
Improved Block Kalman Filter for Degraded Image Restoration

This paper is mainly concerned with the problem of how to set the initial conditions of two-dimensional(2-D) block Kalman filter on degraded image for image restoration. The proposed approach incorporates layering and interpolation process into the degraded image that has been corrupted by blur and additive noise. The innovation of this paper are setting reasonable filtering initial conditions which are associated with image information and increase interpolation operation with edge protection function. Compared with the reported paper, the presented method gives a sharper restored image, especially, which has little ringing distortions near the boundaries.
Content-boosted maximum margin matrix factorization for Flickr group recommendation

Recommending groups or communities to users can greatly improve the browsing experience in online photo sharing sites, e.g. Flickr. However, directly applying collaborative filtering techniques to group recommendation will suffer from "cold start" problem since many users do not affiliate to any groups. In this paper, we propose a hybrid recommendation method named Content-boosted Maximum Margin Matrix Factorization (CM3F), which combines collaborative user-group information with user similarity obtained from their uploaded images. Therefore, CM3F not only inherits the advantages of the state-of-the-art Maximum Margin Matrix Factorization (MMMF) method, but also owns the merits of the content-based graph regularization. The experiments conducted on our crawled dataset with 2196 users, 985 groups and 334467 images from Flickr demonstrate the effectiveness of our framework.
A Practical Approach Towards Validating HIL Simulation of a Safety-Critical System

In order to perform efficient testing of software intensive safety-critical products, organisations often utilise hardware-in-the-loop simulation of the system under test surrounding environment. This way, the system could be invoked and its behaviour could be observed in a controlled setting rather than in the field. However, what effect simulation quality might have on the effectiveness of the testing process still remains an open question. An answer to such a question is rather critical for organisations who are obliged to safety certify their products.In this paper, we are presenting an approach used by Bombardier Transportation to validate their hardware-in-the-loop simulation of a safety-critical system, by executing test cases both in the control setting (lab) and on the real product (train). The process is intended to be used when certifying the simulation which is a necessary step in order to certify the complete system. In addition, we are also presenting some observations from the pilot study and lessons learned.
Compressed Domain Moving Object Detection based on H.264/AVC Macroblock Types

This paper introduces a low complexity frame-based object detection algorithm for H.264/AVC video streams. The method solely parses and evaluates H.264/AVC macroblock types extracted from the video stream, which requires only partial decoding. Different macroblock types indicate different properties of the video content. This fact is used to segment a scene in foreand background or, more precisely, to detect moving objects within the scene. The main advantage of this algorithm is that it is most suitable for massively parallel processing, because it is very fast and combinable with several other preand post-processing algorithms, without decreasing their performance. The actual algorithm is able to process about 3600 frames per second of video streams in CIF resolution, measured on an Intel R CoreTM i5-2520M CPU @ 2.5 GHz with 4 GB RAM.
Integrating Antisocial Children into Prosocial Groups at Summer Camp: A Three-Year Study

This manuscript reviews the results of a three-year project involving the integration of twenty-nine antisocial children, as defined by professionals using a variety of measures, into a summer camp primarily composed of prosocial children. Each year a selected number of children was integrated into prosocial groups. Behavioral measurements were derived for all three years and for both antisocial and prosocial children. These yielded mean proportions of observed prosocial, nonsocial, and antisocial behavior per unit time. In addition, for the last two years of the study children and their group counselors completed various inventories posited to measure antisocial behavior. The data indicate that antisocial children can be incorporated into a regular summer-camp setting with minimal difficulties. Significant differences on behavior and on the inventories occurred during certain years of the project; however, the differences between behavioral and inventory data did not correspond with each other. The results are discussed in terms of their relevance for social work practice with antisocial children.
Factors impacting the knowing-doing gap in sexual harassment training

We examined the gaps between research-based sexual harassment training practices human resource (HR) managers believe their organization should use and the practices their organizations actually use (knowing-doing gaps). We studied individual (attitudes about academics) and organizational predictors (senior management support, managerial rewards, and organizational resources) of gaps at the pre-training, training design and delivery, and post-training stages. Organizational factors generally reduced gaps at the pre-training and post-training stages, while the individual factor marginally increased the gap at the pre-training stage. The knowing-doing gap for training design and delivery practices was not predicted by any of the individual or organizational variables.
Performance Tuning on Multicore Systems for Feature Matching within Image Collections

Parallel programming is the mainstream for today's HPC applications. Programmers need to parallelize their programs to achieve better performance on multicore systems. However, due to a lack of good understanding of parallelism in algorithms, scheduling policy in runtime systems, and multicore architectures, programmers usually find it very hard to write high-performance, scalable programs on these parallel platforms. Although using a parallelized library written by experts can reduce the amount of work for coding, it does not automatically guarantee good performance according to our study. A better understanding of parallelism in algorithms, the OS/runtime systems, and hardware architectures is necessary if programmers wish to further improve performance. In this paper, we use SIFT-based feature matching within large-scale image collections to show the importance of three factors-the level of parallelism, scheduling policy, and memory architecture-that affect the performance of large-scale feature matching on multicore systems. We demonstrate experimental results using programs based on OpenCV and OpenMP, which are executed on both 16-core and 64-core machines. From our experimental results, we find that images with a large number of features achieve poor scalability on the 64-core machine due to a poor cache utilization. To address this issue of cache performance, we propose a Divide-and-Merge algorithm that divides the feature space into several small sub-spaces so that they fit within the cache. Our experiments show that the performance tuning addressing all of the three factors improves the speedup of feature matching from 10.6× to 21.5× on the 64-core machine. While the speedup is improved by 103%, the scalability of the feature matching algorithm is improved by up to 6.45 times on the 64-core machine with our performance tuning. Our study indicates that performance tuning on multicore systems is very challenging even for a simple image processing algorithm.
A novel transmit optimization scheme for MIMO spatial multiplexing systems

In this paper, we propose a new kind of adaptive MIMO signaling scheme. Compared with other adaptive scheme, our approach utilize both the channel state information (CSI) and the constellation of the information streams. We also find that some precoders can be greatly enhanced by the constellation rotation, while others achieve nearly no improvement. We analyze this phenomenon and therefore develop some criteria to generalize the combination of them. Numerical simulations are presented and verify our results.
On the Admission of Dependent Flows in Powerful Sensor Networks

In this paper, we define and study a new problem, referred to as the Dependent Unsplittable Flow Problem (D-UFP). We present and discuss this problem in the context of large-scale powerful (radar/camera) sensor networks, but we believe it has important applications on the admission of large flows in other networks as well. In order to optimize the selection of flows transmitted to the gateway, D-UFP takes into account possible dependencies between flows. We show that D-UFP is more difficult than NP-hard problems for which no good approximation is known. Then, we address two special cases of this problem: the case where all the sensors have a shared channel and the case where the sensors form a mesh and route to the gateway over a spanning tree.
Salmonella Type III Secretion Effector SlrP Is an E3 Ubiquitin Ligase for Mammalian Thioredoxin*

Salmonella enterica encodes two virulence-related type III secretion systems in Salmonella pathogenicity islands 1 and 2, respectively. These systems mediate the translocation of protein effectors into the eukaryotic host cell, where they alter cell signaling and manipulate host cell functions. However, the precise role of most effectors remains unknown. Using a genetic screen, we identified the small, reduction/oxidation-regulatory protein thioredoxin as a mammalian binding partner of the Salmonella effector SlrP. The interaction was confirmed by affinity chromatography and coimmunoprecipitation. In vitro, SlrP was able to mediate ubiquitination of ubiquitin and thioredoxin. A Cys residue conserved in other effectors of the same family that also possess E3 ubiquitin ligase activity was essential for this catalytic function. Stable expression of SlrP in HeLa cells resulted in a significant decrease of thioredoxin activity and in an increase of cell death. The physiological significance of these results was strengthened by the finding that Salmonella was able to trigger cell death and inhibit thioredoxin activity in HeLa cells several hours post-infection. This study assigns a functional role to the Salmonella effector SlrP as a binding partner and an E3 ubiquitin ligase for mammalian thioredoxin.
Planning compensates for the mechanical limitations of articulation

We explore a simple model of speech articulation. The model consists of an articulator combined with the ability to remember and improve the neural drive signal for the articulator. Over many productions, the system learns a neural drive signal that provides an accurate match for acoustically-defined targets. In fact, the match can be better than expected, yielding narrower regions of coarticulation than the intrinsic muscle response time. Further, despite the time delay introduced by the muscle, the articulatory response has no time delay, because the learned neural drive signal occurs in advance of changes in the acoustic targets. Finally, we test the model against tonal production data from Mandarin conversation, and show that it can represent non-trivial surface intonation patterns with simple and linguistically reasonable targets.
UQAM-NTL: Named entity recognition in Twitter messages

This paper describes our system used in the 2nd Workshop on Noisy User-generated Text (WNUT) shared task for Named Entity Recognition (NER) in Twitter, in conjunction with Coling 2016. Our system is based on supervised machine learning by applying Conditional Random Fields (CRF) to train two classifiers for two evaluations. The first evaluation aims at predicting the 10 fine-grained types of named entities; while the second evaluation aims at predicting no type of named entities. The experimental results show that our method has significantly improved Twitter NER performance.
NEET youth in Austria: a typology including socio-demography, labour market behaviour and permanence

Due to the limited relevance of traditional labour market indicators for youth unemployment, researchers and policy-makers focus on an indicator known as not in employment, education or training (‘NEET’). The underlying assumption is that NEET indicates young people with a high risk of social exclusion. For political solutions, it is necessary to consider the heterogeneity of the NEET group. This paper examines the socio-structural attributes that characterise NEET youth in Austria, the main reasons for the NEET situation and whether NEET status, once assigned to an individual, is permanent or temporary. Latent cluster analyses identify seven subgroups of NEET youth, all of which face different challenges. The data source used is the Austrian Labour Force Survey (micro census) from the years 2008–2010, and young people between 16 and 24 years old are analysed. A panel data-set is created to analyse NEET permanence. Drawing on the identified reasons for a permanent NEET situation, this paper argues for more job and training opportunities that fit the needs of young people, especially those with illnesses. Finally, this study asks whether the definition of NEET should be adapted to exclude young mothers with care responsibilities who are not actively looking for a job.
Roseomonas Spinal Epidural Abscess Complicating Instrumented Posterior Lumbar Interbody Fusion

ABSTRACT The first case of a spinal epidural abscess caused by Roseomonas mucosa following instrumented posterior lumbar fusion is presented. Although rare, because of its highly resistant profile, Roseomonas species should be included in the differential diagnosis of epidural abscesses in both immunocompromised and immunocompetent hosts.
Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury

Brain computer interfaces (BCIs) are devices that measure brain activities and translate them into control signals used for a variety of applications. Among them are systems for communication, environmental control, neuroprostheses, exoskeletons, or restorative therapies. Over the last years the technology of BCIs has reached a level of matureness allowing them to be used not only in research experiments supervised by scientists, but also in clinical routine with patients with neurological impairments supervised by clinical personnel or caregivers. However, clinicians and patients face many challenges in the application of BCIs. This particularly applies to high spinal cord injured patients, in whom artificial ventilation, autonomic dysfunctions, neuropathic pain, or the inability to achieve a sufficient level of control during a short-term training may limit the successful use of a BCI. Additionally, spasmolytic medication and the acute stress reaction with associated episodes of depression may have a negative influence on the modulation of brain waves and therefore the ability to concentrate over an extended period of time. Although BCIs seem to be a promising assistive technology for individuals with high spinal cord injury systematic investigations are highly needed to obtain realistic estimates of the percentage of users that for any reason may not be able to operate a BCI in a clinical setting.
Pyramidal parametrics

The mapping of images onto surfaces may substantially increase the realism and information content of computer-generated imagery. The projection of a flat source image onto a curved surface may involve sampling difficulties, however, which are compounded as the view of the surface changes. As the projected scale of the surface increases, interpolation between the original samples of the source image is necessary; as the scale is reduced, approximation of multiple samples in the source is required. Thus a constantly changing sampling window of view-dependent shape must traverse the source image. To reduce the computation implied by these requirements, a set of prefiltered source images may be created. This approach can be applied to particular advantage in animation, where a large number of frames using the same source image must be generated. This paper advances a “pyramidal parametric” prefiltering and sampling geometry which minimizes aliasing effects and assures continuity within and between target images. Although the mapping of texture onto surfaces is an excellent example of the process and provided the original motivation for its development, pyramidal parametric data structures admit of wider application. The aliasing of not only surface texture, but also highlights and even the surface representations themselves, may be minimized by pyramidal parametric means.
Self-concept and peer status among gifted program youth

The authors examined the relation between self-concept and peer status among 465 high-ability youth (Grades 5-11) attending a university summer enrichment program. The differential relation of 4 facets of self-concept (social, academic, athletic, and physical appearance) was investigated in both an academic and a nonacademic peer group setting
Loss of penicillin tolerance by inactivating the carbon catabolite repression determinant CcpA in Streptococcus gordonii.

OBJECTIVES Antibiotic tolerance is a phenomenon allowing bacteria to withstand drug-induced killing. Here, we studied a penicillin-tolerant mutant of Streptococcus gordonii (Tol1), which was shown to be deregulated in the expression of the arginine deiminase operon (arc). arc was not directly responsible for tolerance, but is controlled by the global regulator CcpA. Therefore, we sought whether CcpA might be implicated in tolerance. METHODS The ccpA gene was characterized and subsequently inactivated by PCR ligation mutagenesis in both the susceptible wild-type (WT) and Tol1. The minimal inhibitory concentration and time-kill curves for the strains were determined and the outcome of penicillin treatment in experimental endocarditis assessed. RESULTS ccpA sequence and expression were similar between the WT and Tol1 strains. In killing assays, the WT lost 3.5 +/- 0.6 and 5.3 +/- 0.6 log(10) cfu/mL and Tol1 lost 0.4 +/- 0.2 and 1.4 +/- 0.9 log(10) cfu/mL after 24 and 48 h of penicillin exposure, respectively. Deletion of ccpA almost totally restored Tol1 kill susceptibility (loss of 2.5 +/- 0.7 and 4.9 +/- 0.7 log(10) cfu/mL at the same endpoints). In experimental endocarditis, penicillin treatment induced a significant reduction in vegetation bacterial densities between Tol1 (4.1 log(10) cfu/g) and Tol1DeltaccpA (2.4 log(10) cfu/g). Restitution of ccpA re-established the tolerant phenotype both in vitro and in vivo. CONCLUSIONS CcpA, a global regulator of the carbon catabolite repression system, is implicated in penicillin tolerance both in vitro and in vivo. This links antibiotic survival to bacterial sugar metabolism. However, since ccpA sequence and expression were similar between the WT and Tol1 strains, other factors are probably involved in tolerance.
Validity of an Arterial System Model: A Quantitative Evaluation

The purpose of this investigation was to validate an arterial system model in a quantitative fashion. The model is based on a finite difference solution to the Navier¿Stokes equations and retains certain nonlinear features of the system. Rather than apply standard error measures that test waveform correlation, the validation method used relies on the quantification of differences between the model and animals over a wide range of parametric changes. A series of functions was used to define the difference between the dependent variables of the model and corresponding hemodynamic variables of the animals. These functions were displayed as a family of three-dimensional difference surfaces which related the function value to parametric changes of the independent variables. Experimental data from three dogs were compared with model predictions. Regions of validity for the independent variables were then assessed by examining the difference surfaces.