Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Concurrency Testing for Weak Memory Programs

The Probabilistic Concurrency Testing (PCT) algorithm that provides theoretical guarantees on the probability of detecting concurrency bugs does not apply to weak memory programs. The PCT algorithm builds on the interleaving semantics of sequential consistency, which does not hold for weak memory concurrency. It is because weak memory concurrency allows additional behaviors that cannot be produced by any interleaving execution. In this paper, we generalize PCT to address weak memory concurrency and present Probabilistic Concurrency Testing for Weak Memory (PCTWM). We empirically evaluate PCTWM on a set of well-known weak memory program benchmarks in comparison to the state-of-the-art weak memory testing tool C11Tester. Our results show that PCTWM can detect concurrency bugs more frequently than C11Tester.
Multi-Objective Optimization and Multi-Criteria Decision Making For FDM Using Evolutionary Approaches

In this paper, we describe a systematic multi-objective pro blem solving approach, simulataneosly minimizing two conflicting goals average surface roughnes s ‘Ra’ and build time ‘T ’, for object manufacturing in FDM process by usage of evolutionary algorithm s. Popularly used multi-objective genetic algorithm NSGA-II and recently proposed multi-objective p article swarm optimization (MOPSO) algorithms, are employed for the optimization purposes. Stat istically significant performance measures are employed to compare the two algorithms and means to arriv e at approximate Pareto-optimal fronts are also suggested. To refine the solutions obtained by the op timizers, a mutation driven hill climbing local search is also proposed. Several suggestions and thre e new proposals pertaining to the issue of decision making in presence of trade-off solutions are also made. The overall procedure is integrated into aMORPEMulti-objective Rapid Prototyping Engine. Several sampl e objects are considered for simulation to demonstrate the working of MORPE. Finally, a careful study of optimal build directions for several components considered indicates a trend, provi ding an insight into the FDM processes and can be considered useful for various practical RP applicati ons. Multi-objective Optimization, Decision Making, Genetic A lgorithms, Particle Swarm Optimization and FDM rapid prototyping process.
Tapering and discontinuation of methotrexate in patients with RA treated with TNF inhibitors: data from the DREAM registry

Objectives To study the number of patients that taper or discontinue concomitant methotrexate (MTX) in daily practice in patients with rheumatoid arthritis (RA) treated with tumour necrosis factor inhibitor (TNFi) and to analyse the effects of that adaption on disease activity and drug survival. Methods Data were collected from the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry. Patients who started their first TNFi were included in the study. Treatment effectiveness after MTX tapering or discontinuation was analysed using Disease Activity Score of 28 joints (DAS28). Drug survival of the TNFi was analysed using the Cox proportional hazard model with a time-dependent covariate. Results In 458 patients (34%), MTX was tapered, 126 patients (10%) discontinued MTX and 747 patients (56%) continued MTX at the same dose. On average, DAS28 improved after tapering MTX (−0.40, −0.45) and after stopping MTX (−0.28, −0.12) at 6 and 12 months. In the taper group, 21% of the patients relapsed (DAS28 increase >0.6), and in the discontinuation group this was 21% and 24% at 6 and 12 months, respectively. Patients who taper and discontinue MTX have a similar DAS28 score over time as patients who continue MTX. Moreover, there was no influence of tapering or discontinuation of MTX on long-term drug survival of TNFi. Conclusions In daily practice, tapering or discontinuation of concomitant MTX in patients with RA treated with TNFi frequently occurs and it does not seem to influence the average DAS28 over time or the long-term TNFi drug survival. It appears that in daily clinical practice the correct patients are selected to taper or discontinue MTX.
Modelization and experimental validation of CHB inverters for EVs and eﬃciency comparison with IGBT and SiC inverters on realistic driving cycles

—Electric Vehicles (EVs) based on Cascaded H Bridge (CHB) promise reduced consumption and improved modularity, repairability, resilience, and versatility. This study focuses on evaluating the efficiency of CHB inverters utilizing low-voltage Si MOSFETs to improve EV performance and range. Through a comprehensive system-level approach and modeling, a simulation of the CHB-based powertrain is developed and experimentally validated. Electrical and mechanical simulations are conducted separately and finally combined to streamline computation times. Subsequently, CHB-based EV is compared with two-level inverters (2LI) across different driving cycles, considering multiple sources of losses from the battery to the road. Despite increased battery losses, CHB proves reduction of consumption during urban driving cycles, making it a compelling choice for sustainable commuter vehicles.
Large-scale hierarchical classification with rare categories and inconsistencies

Structuring data is crucial for managing massive amount of available data. Hierarchy (taxonomy) provides a natural and convenient way to organize the information. It has been extensively used in several domains, such as gene taxonomy for organizing gene sequences, international patent hierarchy for easy browsing and retrieval of patent documents, DMOZ taxonomy for web-pages categorization, and ImageNet database for indexing millions of images according to WordNet hierarchy. Given, a hierarchy containing thousands of classes (categories) and millions of instances (examples), there is an essential need to develop an efficient and automated approaches to categorize unlabeled test instances. This problem is referred to as Hierarchical Classification (HC) task. HC is an important machine learning problem that has been researched and explored extensively in the past few years (Silla Jr & Freitas, 2011). The popularity of large-scale HC problem is evident from various HC competitions organized in the past few years such as LSHTC1, BioASQ2 and ILSVRC3. HC poses several challenges due to the following reasons: (i) Data imbalance with large number of classes having very few positive examples for training (rare categories), (ii) Multi-label classification, (iii) Feature selection, (iv) Inconsistent hierarchy due to domain experts manual design, and (v) Scalability due to large number of examples, features and classes. Several approaches that address these issues individually (or multiple issues together) have been developed over the years (Gopal & Yang, 2013; Babbar et al., 2013), however there are many possibilities of improving the existing methods. Specifically, we have developed the methods for handling rare categories and inconsistent hierarchy problem.
Ultra-Early Hemostatic Therapy for Intracerebral Hemorrhage

Background— Intracerebral hemorrhage (ICH) causes higher morbidity and mortality than other forms of stroke and has no proven effective treatment. Hematoma volume is a powerful predictor of outcome after ICH. Summary of Review— Historically, ICH bleeding was considered to be a monophasic event that stopped quickly as a result of clotting and tamponade by surrounding brain tissue. More recently, prospective and retrospective CT-based studies have demonstrated that hematoma growth occurs in up to 38% of patients initially scanned within 3 hours of onset and in 16% scanned between 3 and 6 hours, even in the absence of coagulopathy. Progressive bleeding of this type has been associated with contrast extravasation on CT angiography and poor outcome after early (<4 hours) surgical clot evacuation. On the basis of these observations, it is plausible that ultra-early hemostatic therapy given in the emergency setting might reduce ICH volume in some patients and improve outcome. Among candidate agents for this indication, the most promising is recombinant activated factor VIIa, which promotes local hemostasis at sites of vascular injury in both coagulopathic and normal patients. Conclusions— Ultra-early hemostatic therapy, given within 3 to 4 hours of onset, may potentially arrest ongoing bleeding and minimize hematoma growth after ICH. Given the current lack of effective therapy for ICH, clinical trials testing this treatment approach are justified.
Attract me!: how could end-users identify interesting resources?

Recently, the interest in semantic web technologies increased in various domains, e.g., software engineering or biology. Since this technologies address the long tail of information domains with missing content types, the number of linked datasets will grow even more rapidly. Tech-savvy users and scientists benefit from this trend as they have the knowledge to created complex queries, and thus, to retrieve interesting subsets and answers. However, end-users have difficulties to understand the data's paradigm and need appropriate tool support to slice and dice the data to understandable parts or particular resources. In this paper, we propose a novel approach to enable end-users to browse huge semantic datasets, to detect, and to select interesting resources according to their specific tasks. Based on our evaluation results of two user studies using a web-based prototype we explain, which visualization and interaction techniques in combination with automatic filters are well-suited for novices.
A Comparison of the Performance of Six Machine Learning Algorithms for Fake News

INTRODUCTION : This research focuses on the increasing importance of social media websites as versatile platforms for entertainment, work, communication, commerce, and accessing global news. However, it emphasizes the need to use this power responsibly. OBJECTIVES : The objective of the study is to evaluate the performance of artificial intelligence algorithms in detecting fake news. METHODS : Through a comparison of six machine learning algorithms and the use of natural language processing techniques, RESULTS : The study identifies four algorithms with a 99% accuracy rate in detecting fake news. CONCLUSION : The results demonstrate the effectiveness of the proposed method in enhancing the performance of artificial intelligence algorithms in addressing the problem of fake news detection.
The effect of social network site use on the psychological well‐being of cancer patients

Social network sites (SNSs) are growing in popularity and social significance. Although researchers have attempted to explain the effect of SNS use on users' psychological well‐being, previous studies have produced inconsistent results. In addition, most previous studies relied on healthy students as participants; other cohorts of SNSs users, in particular people living with serious health conditions, have been neglected. In this study, we carried out semistructured interviews with users of the Ovarian Cancer Australia (OCA) Facebook to assess how and in what ways SNS use impacts their psychological well‐being. A theoretical model was proposed to develop a better understanding of the relationships between SNS use and the psychological well‐being of cancer patients. Analysis of data collected through a subsequent quantitative survey confirmed the theoretical model and empirically revealed the extent to which SNS use impacts the psychological well‐being of cancer patients. Findings showed the use of OCA Facebook enhances social support, enriches the experience of social connectedness, develops social presence and learning and ultimately improves the psychological well‐being of cancer patients.
An Exploration of the Experience of Lesbians with Chronic Illness

An exploration of the challenges facing lesbians with chronic conditions and their coping strategies was investigated by examining the experiences of participants who were clients of a volunteer organization serving chronically ill lesbians. This article reports the results associated with those challenges, with its ultimate goal being and to assess the effectiveness of current services. Using the participant observation method, as employed by O'Toole (2000), the analysis was based on multiple data sources and 10 years experience within the volunteer organization, including 3 years in direct client support. A qualitative method served as the primary focus for the study. The quantitative method preceded the qualitative method and provided limited supporting data. The total number of participants included all past and current clients, but the number participating in each data source varied. Qualitative sources included archival structured interviews (n = 69), taped interviews (n = 5-6), and extensive comments written in response to the quantitative surveys (n = 14). The quantitative measures (n = 14) included the researcher-developed Chronic Conditions Challenges Checklist (C4) and the Short Form of the McGill Pain Questionnaire ([SF-MPQ]; Melzack, 1998 ). A content analysis of all data sources found a number of challenges that met the criteria of being identified in at least two data sources and across multiple participants. Challenges included those related to the disease process (i.e., pain, fatigue, and decreases in mobility) to impacts of the condition (financial security, ability to participate, support from family of origin and independence, loneliness, and issues related to mental health). Challenges were discussed in terms of those that are similar to and different from other women suffering from chronic illness, as well as their relevance to related literature.
Short-Term Environmental Enrichment Rescues Adult Neurogenesis and Memory Deficits in APPSw,Ind Transgenic Mice

Epidemiological studies indicate that intellectual activity prevents or delays the onset of Alzheimer's disease (AD). Similarly, cognitive stimulation using environmental enrichment (EE), which increases adult neurogenesis and functional integration of newborn neurons into neural circuits of the hippocampus, protects against memory decline in transgenic mouse models of AD, but the mechanisms involved are poorly understood. To study the therapeutic benefits of cognitive stimulation in AD we examined the effects of EE in hippocampal neurogenesis and memory in a transgenic mouse model of AD expressing the human mutant β-amyloid (Aβ) precursor protein (APPSw,Ind). By using molecular markers of new generated neurons (bromodeoxiuridine, NeuN and doublecortin), we found reduced neurogenesis and decreased dendritic length and projections of doublecortin-expressing cells of the dentate gyrus in young APPSw,Ind transgenic mice. Moreover, we detected a lower number of mature neurons (NeuN positive) in the granular cell layer and a reduced volume of the dentate gyrus that could be due to a sustained decrease in the incorporation of new generated neurons. We found that short-term EE for 7 weeks efficiently ameliorates early hippocampal-dependent spatial learning and memory deficits in APPSw,Ind transgenic mice. The cognitive benefits of enrichment in APPSw,Ind transgenic mice were associated with increased number, dendritic length and projections to the CA3 region of the most mature adult newborn neurons. By contrast, Aβ levels and the total number of neurons in the dentate gyrus were unchanged by EE in APPSw,Ind mice. These results suggest that promoting the survival and maturation of adult generated newborn neurons in the hippocampus may contribute to cognitive benefits in AD mouse models.
Getting the most from search-based refactoring

Object-oriented systems that undergo repeated addition of functionality commonly suffer a loss of quality in their underlying design. This problem must often be remedied in a costly refactoring phase before further maintenance programming can take place. Recently search-based approaches to automating the task of softwarere factoring, based on the concept of treating object-oriented designas a combinatorial optimisation problem, have been proposed. However, because search-based refactoring is a novel approach it has yet to be established which search techniques are most suitable forthe task. In this paper we report the results of an empirical comparison of simulated annealing, genetic algorithm and multiple ascent hill-climbing in search-based refactoring. A prototype automated refactoring tool is employed, capable of making radical changes to the design of an existing program in order that it conform more closely to a contemporary quality model. Results show multiple-ascent hill climbing to outperform both simulated annealing and genetic algorithm over a set of four input programs.
Auditory and Nonauditory Effects of Ultrasonic Scaler Use and Its Role in the Development of Permanent Hearing Loss.

PURPOSE To evaluate the negative auditory and non-auditory effects developed immediately after using ultrasonic scalers and their potential role in the development of permanent hearing loss. MATERIALS AND METHODS The auditory functions of 60 dental clinicians were evaluated with the pure tone audiometry test (PTA), tympanogram and the otoacoustic emission test (OAE) before and immediately after using ultrasonic scalers. The paired t-test was used to evaluate the difference in the pre- and post-exposure recordings for all three tests. RESULTS There was a significant increase in the PTA and tympanogram test results, along with reduced OAE values immediately after using ultrasonic scalers. Hearing ability dropped by 63% to 66% immediately after using ultrasonic scalers. The maximum hearing disability was noted for low-frequency thresholds. The reduction was greater in the left than in the right ear. CONCLUSIONS Noise-emitting devices such as ultrasonic scalers produce significant immediate auditory and non-auditory changes. It is important that dentists recognise the initial signs of hearing damage and adopt appropriate measures while working to prevent the development of permanent hearing impairment in future.
Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases

We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an objective function suitable for the user’s objective. An objective function is usually defined in terms of the distribution of a given target attribute. Our goal is to find association rules that split databases into two subsets, optimizing the value of an objective function. The problem is intractable for general objective functions, because letting N be the number of records of a given database, there are 2N possible binary segmentations, and we may have to exhaustively examine all of them. However, when the objective function is convex, there are feasible algorithms for finding nearly optimal binary segmentations, and we prove that typical criteria, such as “entropy (mutual information),” “x2 (correlation) ,” and “gini index (mean squared error) ,” are actually convex. We propose practical algorithms that use computational geometry techniques to handle Permission to copy without fee all or part of this material is gmnted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 24th VLDB Conference New York, USA, 1998 cases where a target attribute is not binary, in which conventional approaches cannot be used directly.
Dissociation : An Insufficiently Recognized Major Feature of Complex PTSD

The role of dissociation in (complex) PTSD has been insufficiently recognized for at least two reasons: the view that dissociation is a peripheral, not a central feature of PTSD, and existing confusion regarding the nature of dissociation. This conceptual paper addresses both issues by postulating that traumatization essentially involves some degree of division or dissociation of psychobiological systems that constitute personality. One or more dissociative parts of the personality avoid traumatic memories and perform functions in daily life, while one or more other parts remain fixated in traumatic experiences and defensive actions. Dissociative parts manifest in negative and positive dissociative symptoms that should be distinguished from alterations of consciousness. Complex PTSD involves a more complex structural dissociation than simple PTSD.
Towards tsunami early-warning with Distributed Acoustic Sensing: Expected seaﬂoor strains induced by tsunamis

Tsunami wave observations far from the coast remain challenging due to the logistics and cost of deploying and operating oﬀshore instrumentation on a long-term basis with suﬃcient spatial coverage and density. Distributed Acoustic Sensing (DAS) on submarine ﬁber optic cables now enables real-time seaﬂoor strain observations over distances exceeding 100 km at a relatively low cost. Here, we evaluate the potential contribution of DAS to tsunami warning by assessing theoretically the sensitivity required by a DAS instrument to record tsunami waves. Our analysis includes signals due to two eﬀects induced by the hydrostatic pressure perturbations arising from tsunami waves: the Poisson’s eﬀect of the submarine cable and the compliance eﬀect of the seaﬂoor. It also includes the eﬀect of seaﬂoor shear stresses and temperature transients induced by the horizontal ﬂuid ﬂow associated with tsunami waves. The analysis is supported by fully coupled 3-D physics-based simulations of earthquake rupture, seismo-acoustic waves and tsunami wave propagation. The strains from seismo-acoustic waves and static deformation near the earthquake source are orders of magnitude larger than the tsunami strain signal. We illustrate a data processing procedure to discern the tsunami signal. With enhanced low-frequency sensitivity on DAS interrogators (strain sensitivity [? ] 2 × 10 -10 at mHz frequencies), we ﬁnd that, on seaﬂoor cables located above or near the earthquake source area, tsunamis are expected to be observable with a suﬃcient signal-to-noise ratio within a few minutes of the earthquake onset. These encouraging results pave the way towards faster tsunami warning enabled by seaﬂoor DAS.