nils-herrmann/clean_scirepeval huggingface dataset:
EULAR evidence-based recommendations for the management of fibromyalgia syndrome.

To develop evidence-based recommendations for the management of fibromyalgia syndrome.



A multidisciplinary task force was formed representing 11 European countries. The design of the study, including search strategy, participants, interventions, outcome measures, data collection and analytical method, was defined at the outset. A systematic review was undertaken with the keywords "fibromyalgia", "treatment or management" and "trial". Studies were excluded if they did not utilise the American College of Rheumatology classification criteria, were not clinical trials, or included patients with chronic fatigue syndrome or myalgic encephalomyelitis. Primary outcome measures were change in pain assessed by visual analogue scale and fibromyalgia impact questionnaire. The quality of the studies was categorised based on randomisation, blinding and allocation concealment. Only the highest quality studies were used to base recommendations on. When there was insufficient evidence from the literature, a Delphi process was used to provide basis for recommendation.



146 studies were eligible for the review. 39 pharmacological intervention studies and 59 non-pharmacological were included in the final recommendation summary tables once those of a lower quality or with insufficient data were separated. The categories of treatment identified were antidepressants, analgesics, and "other pharmacological" and exercise, cognitive behavioural therapy, education, dietary interventions and "other non-pharmacological". In many studies sample size was small and the quality of the study was insufficient for strong recommendations to be made.



Nine recommendations for the management of fibromyalgia syndrome were developed using a systematic review and expert consensus.
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning

The risks and perils of overfitting in machine learning are well known. However most of the treatment of this, including diagnostic tools and remedies, was developed for the supervised learning case. In this work, we aim to offer new perspectives on the characterization and prevention of overfitting in deep Reinforcement Learning (RL) methods, with a particular focus on continuous domains. We examine several aspects, such as how to define and diagnose overfitting in MDPs, and how to reduce risks by injecting sufficient training diversity. This work complements recent findings on the brittleness of deep RL methods and offers practical observations for RL researchers and practitioners.
A Miniaturized Absorptive Frequency Selective Surface

A miniaturized absorptive frequency selective surface (MAFSS) is presented in this letter, composed of a layer of miniaturized resistive surface placed above a metallic bandpass FSS. The MAFSS performs as a bandpass filter at operation band around 0.92 GHz, and acts as an absorber over a wide out-of-band 3-9 GHz. Moreover, due to its miniaturized elements, the MAFSS exhibits the property of eliminating the grating lobe in absorption band when illuminated by oblique incident wave. Numerical and experimental results have been given.
The roles of body and mind in abstract thought.

How are people able to think about things they have never seen or touched? We demonstrate that abstract knowledge can be built analogically from more experience-based knowledge. People's understanding of the abstract domain of time, for example, is so intimately dependent on the more experience-based domain of space that when people make an air journey or wait in a lunch line, they also unwittingly (and dramatically) change their thinking about time. Further, our results suggest that it is not sensorimotor spatial experience per se that influences people's thinking about time, but rather people's representations of and thinking about their spatial experience.
Enchancing effect of patented whey protein isolate (Immunocal) on cytotoxicity of an anticancer drug.

To determine the enhancing effect of a whey protein isolate on the cytotoxicity of a potential anticancer drug, baicalein, the human hepatoma cell line Hep G2 was assigned to grow in different media for four days, and cell growth and apoptosis were investigated. The control group was grown in normal medium; the other three groups were grown in whey protein isolate (Immunocal) medium, baicalein medium, and a combination of Immunocal and baicalein. As indicated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, survival rate was significantly lower in cells grown in baicalein + Immunocal than in cells grown in baicalein alone. In contrast, there was no significant difference in survival rate of the cells grown in Immunocal. In the investigation of apoptosis, cells grown in baicalein + Immunocal showed a higher phosphatidylserine exposure, lower mitochondrial transmembrane potential, and nearly 13 times more cells undergoing apoptosis than cells grown in baicalein alone. We also demonstrated that Immunocal reduced glutathione (GSH) in Hep G2 cells by 20-40% and regulated the elevation of GSH, which was in response to baicalein. In conclusion, Immunocal seemed to enhance the cytotoxicity of baicalein by inducing more apoptosis; this increase in apoptotic cells may be associated with the depletion of GSH in Hep G2 cells. This is the first study to demonstrate, in vitro, that Immunocal may function as an adjuvant in cancer treatments.
Video games as a tool to train visual skills.

Adult brain plasticity, although possible, is often difficult to elicit. Training regimens in adults can produce specific improvements on the trained task without leading to general enhancements that would improve quality of life. This paper considers the case of playing action video games as a way to induce widespread enhancement in vision.



We review the range of visual skills altered by action video game playing as well as the game components important in promoting visual plasticity. Further, we discuss what these results might mean in terms of rehabilitation for different patient populations.
Security for Ubiquitous Computing

Ubiquitous computing, over a decade in the making, has finally graduated from whacky buzzword through fashionable research topic to something that is definitely and inevitably happening. This will mean revolutionary changes in the way computing affects our society: changes of the same magnitude and scope as those brought about by the World Wide Web. When throw-away computing capabilities are embedded in shoes, drink cans and postage stamps, security and privacy take on entirely new meanings. Programmers, engineers and system designers will have to learn to think in new ways. Ubiquitous computing is not just a wireless version of the Internet with a thousand times more computers, and it would be a naive mistake to imagine that the traditional security solutions for distributed systems will scale to the new scenario. Authentication, authorization, and even concepts as fundamental as ownership require thorough rethinking. At a higher level still, even goals and policies must be revised. One question we should keep asking is simply “Security for whom?” The owner of a device, for example, is no longer necessarily the party whose interests the device will attempt to safeguard. Ubiquitous computing is happening and will affect everyone. By itself it will never be “secure” (whatever this means) if not for the dedicated efforts of people like us who actually do the work. We are the ones who can make the difference. So, before focusing on the implementation details, let’s have a serious look at the big picture. C. Park and S. Chee (Eds.): ICISC 2004, LNCS 3506, p. 2, 2005.
Understanding agile project management methods using Scrum

This paper seeks to define and describe agile project management using the Scrum methodology as a method for more effectively managing and completing projects.  This paper provides a general overview and introduction to the concepts of agile project management and the Scrum methodology in particular.  Agile project management using the Scrum methodology allows project teams to manage digital library projects more effectively by decreasing the amount of overhead dedicated to managing the project. Using an iterative process of continuous review and short-design time frames, the project team is better able to quickly adapt projects to rapidly evolving environments in which systems will be used.  This paper fills a gap in the digital library project management literature by providing an overview of agile project management methods.
Mining Fix Patterns for FindBugs Violations

Several static analysis tools, such as Splint or FindBugs, have been proposed to the software development community to help detect security vulnerabilities or bad programming practices. However, the adoption of these tools is hindered by their high false positive rates. If the false positive rate is too high, developers may get acclimated to violation reports from these tools, causing concrete and severe bugs being overlooked. Fortunately, some violations are actually addressed and resolved by developers. We claim that those violations that are recurrently fixed are likely to be true positives, and an automated approach can learn to repair similar unseen violations. However, there is lack of a systematic way to investigate the distributions on existing violations and fixed ones in the wild, that can provide insights into prioritizing violations for developers, and an effective way to mine code and fix patterns which can help developers easily understand the reasons of leading violations and how to fix them. In this paper, we first collect and track a large number of fixed and unfixed violations across revisions of software. The empirical analyses reveal that there are discrepancies in the distributions of violations that are detected and those that are fixed, in terms of occurrences, spread and categories, which can provide insights into prioritizing violations. To automatically identify patterns in violations and their fixes, we propose an approach that utilizes convolutional neural networks to learn features and clustering to regroup similar instances. We then evaluate the usefulness of the identified fix patterns by applying them to unfixed violations. The results show that developers will accept and merge a majority (69/116) of fixes generated from the inferred fix patterns. It is also noteworthy that the yielded patterns are applicable to four real bugs in the Defects4J major benchmark for software testing and automated repair.
MOBMAS: A methodology for ontology-based multi-agent systems development

Ontologies offer significant benefits to multi-agent systems: interoperability, reusability, support for multi-agent system (MAS) development activities (such as system analysis and agent knowledge modeling) and support for MAS operation (such as agent communication and reasoning). This paper presents an ontology-based methodology, MOBMAS, for the analysis and design of multi-agent systems. MOBMAS is the first methodology that explicitly identifies and implements the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In this paper, we present comprehensive documentation and validation of MOBMAS.
Child sexual abuse in the etiology of anxiety disorders: a systematic review of reviews.

There is considerable controversy about the role of child sexual abuse in the etiology of anxiety disorders. Although a growing number of research studies have been published, these have produced inconsistent results and conclusions regarding the nature of the associations between child sexual abuse and the various forms of anxiety problems as well as the potential effects of third variables, such as moderators, mediators, or confounders. This article provides a systematic review of the several reviews that have investigated the literature on the role of child sexual abuse in the etiology of anxiety disorders. Seven databases were searched, supplemented with hand search of reference lists from retrieved papers. Four meta-analyses, including 3,214,482 subjects from 171 studies, were analyzed. There is evidence that child sexual abuse is a significant, although general and nonspecific, risk factor for anxiety disorders, especially posttraumatic stress disorder, regardless of gender of the victim and severity of abuse. Additional biological or psychosocial risk factors (such as alterations in brain structure or function, information processing biases, parental anxiety disorders, family dysfunction, and other forms of child abuse) may interact with child sexual abuse or act independently to cause anxiety disorders in victims in abuse survivors. However, child sexual abuse may sometimes confer additional risk of developing anxiety disorders either as a distal and indirect cause or as a proximal and direct cause. Child sexual abuse should be considered one of the several risk factors for anxiety disorders and included in multifactorial etiological models for anxiety disorders.
Enforcing temporal logic specifications via reinforcement learning

We consider the problem of controlling a system with unknown, stochastic dynamics to achieve a complex, time-sensitive task. An example of this problem is controlling a noisy aerial vehicle with partially known dynamics to visit a pre-specified set of regions in any order while avoiding hazardous areas. In particular, we are interested in tasks which can be described by signal temporal logic (STL) specifications. STL is a rich logic that can be used to describe tasks involving bounds on physical parameters, continuous time bounds, and logical relationships over time and states. STL is equipped with a continuous measure called the robustness degree that measures how strongly a given sample path exhibits an STL property [4, 3]. This measure enables the use of continuous optimization problems to solve learning [7, 6] or formal synthesis problems [9] involving STL.
Named Entity Resources - Overview and Outlook

Recognition of real-world entities is crucial for most NLP applications. Since its introduction some twenty years ago, named entity processing has undergone a significant evolution with, among others, the definition of new tasks (e.g. entity linking) and the emergence of new types of data (e.g. speech transcriptions, micro-blogging). These pose certainly new challenges which affect not only methods and algorithms but especially linguistic resources. Where do we stand with respect to named entity resources? This paper aims at providing a systematic overview of named entity resources, accounting for qualities such as multilingualism, dynamicity and interoperability, and to identify shortfalls in order to guide future developments.
The Basic AI Drives

One might imagine that AI systems with harmless goals will be harmless. This paper instead shows that intelligent systems will need to be carefully designed to prevent them from behaving in harmful ways. We identify a number of “drives” that will appear in sufficiently advanced AI systems of any design. We call them drives because they are tendencies which will be present unless explicitly counteracted. We start by showing that goal-seeking systems will have drives to model their own operation and to improve themselves. We then show that self-improving systems will be driven to clarify their goals and represent them as economic utility functions. They will also strive for their actions to approximate rational economic behavior. This will lead almost all systems to protect their utility functions from modification and their utility measurement systems from corruption. We also discuss some exceptional systems which will want to modify their utility functions. We next discuss the drive toward self-protection which causes systems try to prevent themselves from being harmed. Finally we examine drives toward the acquisition of resources and toward their efficient utilization. We end with a discussion of how to incorporate these insights in designing intelligent technology which will lead to a positive future for humanity.
Online tuning fuzzy PID controller using robust extended Kalman filter

Fuzzy PID controllers have been developed and applied to many fields for over a period of 30 years. However, there is no systematic method to design membership functions (MFs) for inputs and outputs of a fuzzy system. Then optimizing the MFs is considered as a system identification problem for a nonlinear dynamic system which makes control challenges. This paper presents a novel online method using a robust extended Kalman filter to optimize a Mamdani fuzzy PID controller. The robust extended Kalman filter (REKF) is used to adjust the controller parameters automatically during the operation process of any system applying the controller to minimize the control error. The fuzzy PID controller is tuned about the shape of MFs and rules to adapt with the working conditions and the control performance is improved significantly. The proposed method in this research is verified by its application to the force control problem of an electro-hydraulic actuator. Simulations and experimental results show that proposed method is effective for the online optimization of the fuzzy PID controller.
Recurrent Neural Network Predictions in Sentiment Analysis

Recently, a technique called Layer-wise Relevance Propagation (LRP) was shown to deliver insightful explanations in the form of input space relevances for understanding feed-forward neural network classification decisions. In the present work, we extend the usage of LRP to recurrent neural networks. We propose a specific propagation rule applicable to multiplicative connections as they arise in recurrent network architectures such as LSTMs and GRUs. We apply our technique to a word-based bi-directional LSTM model on a five-class sentiment prediction task, and evaluate the resulting LRP relevances both qualitatively and quantitatively, obtaining better results than a gradient-based related method which was used in previous work.
BabelRelate! A Joint Multilingual Approach to Computing Semantic Relatedness

We present a knowledge-rich approach to computing semantic relatedness which exploits the joint contribution of different languages. Our approach is based on the lexicon and semantic knowledge of a wide-coverage multilingual knowledge base, which is used to compute semantic graphs in a variety of languages. Complementary information from these graphs is then combined to produce a ‘core’ graph where disambiguated translations are connected by means of strong semantic relations. We evaluate our approach on standard monolingual and bilingual datasets, and show that: i) we outperform a graph-based approach which does not use multilinguality in a joint way; ii) we achieve uniformly competitive results for both resource-rich and resource-poor languages.
Depression in late life: review and commentary.

Depression is perhaps the most frequent cause of emotional suffering in later life and significantly decreases quality of life in older adults. In recent years, the literature on late-life depression has exploded. Many gaps in our understanding of the outcome of late-life depression have been filled. Intriguing findings have emerged regarding the etiology of late-onset depression. The number of studies documenting the evidence base for therapy has increased dramatically. Here, I first address case definition, and then I review the current community- and clinic-based epidemiological studies. Next I address the outcome of late-life depression, including morbidity and mortality studies. Then I present the extant evidence regarding the etiology of depression in late life from a biopsychosocial perspective. Finally, I present evidence for the current therapies prescribed for depressed elders, ranging from medications to group therapy.
Spring Framework : A Companion to JavaEE

This paper present the ideas of the Spring framework which is widely used in making enterprise applications .Considering the present situation where applications are developed using the traditional EJB model, Spring framework insists that ordinary java beans can be used with slight modifications. This framework can be used with J2EE to make it easier to develop application. This paper presents the architecture overview of spring along with the features of the framework that have made the framework useful. The integration of various frameworks for an E-commerce system has also been discussed in this paper. The Spring MVC framework is also discussed. This paper also proposes architecture for a website based on Spring, Hibernate and struts framework. KeywordsSpring, IoC, AOP, E-commerce, MVC
Lactate kinetics and individual anaerobic threshold.

Exercise with stepwise increasing work loads until exhaustion leads to a curvilinear increase of lactate in blood and typical lactate kinetics in the post-exercise period. Lactate kinetics in blood during exercise and recovery results from diffusion along gradients between muscle and blood and simultaneous elimination. Therefore, a general diffusion-elimination model is presented from which maximal rate of elimination (Em), individual anaerobic threshold (IAT), gradient between muscle and blood (deltaC-deltaCEm), muscle volume working above the IAT (Vm), individual membrane constant (Mc), quantity of lactate accounting for lactate gradient (Agrad), and whole body lactate (Anet) can be obtained. For demonstration purpose, this model was applied to a highly trained athlete. In this example, all constants and variables mentioned above as well as an equation reflecting individual lactate kinetics were calculated. Furthermore, the IAT was determined in 61 athletes participating in different events. In general, it can be demonstrated that with increasing aerobic capacity the lactate concentration at the IAT decreases. The lactate concentration at the IAT varies interindividually within broad limits, thus emphasizing the need for individual assessment.
Adoption of Vehicular Ad Hoc Networking Protocols by Networked Robots

This paper focuses on the utilization of wireless networkin g in the robotics domain. Many researchers have already equipped their robot s with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterpa r s. Typically, this integration of wireless communication is tackled in a quite pragmat ic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) prot oc ls that were designed specifically with robotic use cases in mind. This is in harp contrast with the domain of vehicular ad hoc networks (VANET). This observati on is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progre ss in the field of networked robots. To investigate this possibility, this paper rovides a thorough overview of the related work in the domain of robotic and vehicular ad h oc networks. Based on this information, an exhaustive list of requirements is d efined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while R ANET protocols have to support high throughput media streaming as well. Althoug h not always with equal importance, all other defined requirements are valid for bot h protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this pap er concludes with the definition of an appropriate working plan.