nils-herrmann/clean_scirepeval huggingface dataset:
Salicylate intolerance: pathophysiology, clinical spectrum, diagnosis and treatment.

Acetylic salicylic acid (aspirin) intolerance relates to altered generation and metabolism of arachidonic acid and eicosanoids, and prostaglandins and leukotrienes ingestion of salicylates or COX-inhibitors.



Selective review of literature in PubMed and the Cochrane Library.



Rhinitis, asthma and nasal polyposis are typical presentations, but urticaria and gut inflammation are also described. The mechanism involves a specific reaction to COX inhibitor substances in analgesics, cosmetics or plants resulting in an abnormal pattern of eicosanoids (prostaglandins and leucotrienes). The diagnosis is based on symptoms occurring immediately following ingestion of these substances or on refractory polyp formation. Blood tests may be helpful in unclear cases. Avoidance of triggering agents is helpful. Corticosteroids are the mainstay of pharmacological treatment. Biological, desensitization treatment involving the administration of increasing amounts of acetylic salicylic acid may also be used.



Asthma, rhinitis and nasal polyps, as well as chronic gastrointestinal irritation and urticaria following acetylic salicylic acid ingestion may suggest intolerance.
Visual word recognition in the left and right hemispheres: anatomical and functional correlates of peripheral alexias.

According to a simple anatomical and functional model of word reading, letters displayed in one hemifield are first analysed through a cascade of contralateral retinotopic areas, which compute increasingly abstract representations. Eventually, an invariant representation of letter identities is created in the visual word form area (VWFA), reproducibly located within the left occipito-temporal sulcus. The VWFA then projects to structures involved in phonological or lexico-semantic processing. This model yields detailed predictions on the reading impairments that may follow left occipitotemporal lesions. Those predictions were confronted to behavioural, anatomical and functional MRI data gathered in normals and in patients suffering from left posterior cerebral artery infarcts. In normal subjects, alphabetic stimuli activated both the VWFA and the right-hemispheric symmetrical region (R-VWFA) relative to fixation, but only the VWFA showed a preference for alphabetic strings over simple chequerboards. The comparison of normalized brain lesions with reading-induced activations showed that the critical lesion site for the classical syndrome of pure alexia can be tightly localized to the VWFA. Reading impairments resulting from deafferentation of an intact VWFA from right- or left-hemispheric input were dissected using the same methods, shedding light on the connectivity of the VWFA. Finally, the putative role of right-hemispheric processing in the letter-by-letter reading strategy was clarified. In a letter-by-letter reader, the R-VWFA assumed some of the functional properties normally specific to the VWFA. These data corroborate our initial model of normal word perception and underline that an alternative right-hemispheric pathway can underlie functional recovery from alexia.
Antenna miniaturization techniques for wireless applications

In wireless communication, antenna miniaturization is a vital issue these days. This paper presents the simulation analysis of small planar antennas using different antenna miniaturization techniques. They have brought to define miniaturization methods by which we can estimate the use of micro strip antennas. Various govt. and private sector organizations made use of these techniques to solve the problem of antenna fabrication in mobiles, satellites, missiles, radar navigational aids and military applications. These techniques are used to reduce the physical size but to increase the bandwidth and efficiency of antenna. Some approaches for antenna miniaturization are introduction of slots, slits, short meandering and novel geometries like fractals or by using higher dielectrics constant. The effect of miniaturization in various antenna parameters like, radiation efficiency, gain and bandwidth are discussed. Finally the paper reports a brief description of miniaturization of antenna by using suitable and efficient methods that includes use of double layered substrate structure in microstrip patch antenna.
Bringing Together BPM and Social Software

Traditional BPM approaches are well understood for hierarchical organizations that cope with highly repetitive and well-defined processes. Unfortunately, they do not work well for the most prevalent types of processes and exclude most of the employees from participation. Especially collaborative adhoc processes in a team-based organization are not covered by BPM methods. Social software is a widely accepted and promising approach to support participation but lacks mechanisms for controlling processes. The paper presents a novel approach using roles. Based on a systematic literature review, this paper contributes a solution-architecture for collaborative BPM and presents collaboration patterns expressed through role models. This helps overcoming the model-reality-divide and lost innovation in the business process modeling area. Furthermore, role-model based collaboration patterns can be used to monitor and control collaborative ad-hoc processes.
Efficacy of robot-assisted fingers training in chronic stroke survivors: a pilot randomized-controlled trial

While constraint-induced movement therapy (CIMT) is one of the most promising techniques for upper limb rehabilitation after stroke, it requires high residual function to start with. Robotic device, on the other hand, can provide intention-driven assistance and is proven capable to complement conventional therapy. However, with many robotic devices focus on more proximal joints like shoulder and elbow, recovery of hand and fingers functions have become a challenge. Here we propose the use of robotic device to assist hand and fingers functions training and we aim to evaluate the potential efficacy of intention-driven robot-assisted fingers training. Participants (6 to 24 months post-stroke) were randomly assigned into two groups: robot-assisted (robot) and non-assisted (control) fingers training groups. Each participant underwent 20-session training. Action Research Arm Test (ARAT) was used as the primary outcome measure, while, Wolf Motor Function Test (WMFT) score, its functional tasks (WMFT-FT) sub-score, Fugl-Meyer Assessment (FMA), its shoulder and elbow (FMA-SE) sub-score, and finger individuation index (FII) served as secondary outcome measures. Nineteen patients completed the 20-session training (; eighteen of them came back for a 6-month follow-up. Significant improvements (p < 0.05) were found in the clinical scores for both robot and control group after training. However, only robot group maintained the significant difference in the ARAT and FMA-SE six months after the training. The WMFT-FT score and time post-training improvements of robot group were significantly better than those of the control group. This study showed the potential efficacy of robot-assisted fingers training for hand and fingers rehabilitation and its feasibility to facilitate early rehabilitation for a wider population of stroke survivors; and hence, can be used to complement CIMT.
Learning Computer Networking on Open Paravirtual Laboratories

Learning practical information communication technology skills such as network configuration and security planning requires hands-on experience with a number of different devices which may be unavailable or too costly to provide, especially for institutions under tight budget constraints. This paper describes how a specific open software technology, paravirtualization, can be used to set up open source virtual networking labs (VNLs) easily and at virtually no cost. The paper highlights how paravirtual labs can be adopted jointly by partner organizations, e.g., when the institution hosting the virtual lab provides hands-on training and students' skill evaluation as a service to partner institutions overseas. A practical VNL implementation, the open virtual lab (OVL), is used to describe the added value that open source VNLs can give to e-Learning frameworks, achieving a level of students' performance comparable or better than the one obtained when students directly interact with physical networking equipment.
Test effort estimation in regression testing

Software test effort estimation has always been a challenge for the software practitioners, because it consumes approximately half of the overall development costs of any software project. In order to provide effective software maintenance it is necessary to carry out the regression testing of the software. Hence, this research work aims to propose a measure for the estimation of the software test effort in regression testing. Since, the effort required developing or test software shall depend on various major contributing factors like, therefore, the proposed measure first estimates the change type of any software, make test cases for any software, then calculate execution complexity of any software and tester rank. In general, the regression testing takes more time and cost to perform it. Therefore, the effort estimation in regression testing is utmost required in order to compute man-hour for any software. In order to analyze the validity of the proposed test effort estimation measure, the measure is compared for various ranges of problem from small, mid and large size program to real life software projects. The result obtained shows that, the proposed test measure is a comprehensive one and compares well with other prevalent measures proposed in the past.
A study of Monte Carlo localization on robot operating system

Localization is one of the problems that often appears in the world of robotics. Monte Carlo Localization (MCL) are the one of the popular algorithms in localization because easy to implement on issues Global Localization. This algorithm using particles to represent the robot position. MCL can simulated by Robot Operating System (ROS) using robot type is Pioneer3-dx. In this paper we will discuss about this algorithm on ROS, by analyzing the influence of the number particle that are used for localization of the actual robot position.
Hip and Knee Strengthening Is More Effective Than Knee Strengthening Alone for Reducing Pain and Improving Activity in Individuals With Patellofemoral Pain: A Systematic Review With Meta-analysis.

Systematic review with meta-analysis.  The addition of hip strengthening to knee strengthening for persons with patellofemoral pain has the potential to optimize treatment effects. There is a need to systematically review and pool the current evidence in this area.  To examine the efficacy of hip strengthening, associated or not with knee strengthening, to increase strength, reduce pain, and improve activity in individuals with patellofemoral pain.  A systematic review of randomized and/or controlled trials was performed. Participants in the reviewed studies were individuals with patellofemoral pain, and the experimental intervention was hip and knee strengthening. Outcome data related to muscle strength, pain, and activity were extracted from the eligible trials and combined in a meta-analysis.  The review included 14 trials involving 673 participants. Random-effects meta-analyses revealed that hip and knee strengthening decreased pain (mean difference, -3.3; 95% confidence interval [CI]: -5.6, -1.1) and improved activity (standardized mean difference, 1.4; 95% CI: 0.03, 2.8) compared to no training/placebo. In addition, hip and knee strengthening was superior to knee strengthening alone for decreasing pain (mean difference, -1.5; 95% CI: -2.3, -0.8) and improving activity (standardized mean difference, 0.7; 95% CI: 0.2, 1.3). Results were maintained beyond the intervention period. Meta-analyses showed no significant changes in strength for any of the interventions.  Hip and knee strengthening is effective and superior to knee strengthening alone for decreasing pain and improving activity in persons with patellofemoral pain; however, these outcomes were achieved without a concurrent change in strength.
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

In this work, we propose “global style tokens” (GSTs), a bank of embeddings that are jointly trained within Tacotron, a state-of-the-art end-toend speech synthesis system. The embeddings are trained with no explicit labels, yet learn to model a large range of acoustic expressiveness. GSTs lead to a rich set of significant results. The soft interpretable “labels” they generate can be used to control synthesis in novel ways, such as varying speed and speaking style – independently of the text content. They can also be used for style transfer, replicating the speaking style of a single audio clip across an entire long-form text corpus. When trained on noisy, unlabeled found data, GSTs learn to factorize noise and speaker identity, providing a path towards highly scalable but robust speech synthesis.
A New Inequality-Based Obstacle-Avoidance MVN Scheme and Its Application to Redundant Robot Manipulators

This paper proposes a new inequality-based criterion/constraint with its algorithmic and computational details for obstacle avoidance of redundant robot manipulators. By incorporating such a dynamically updated inequality constraint and the joint physical constraints (such as joint-angle limits and joint-velocity limits), a novel minimum-velocity-norm (MVN) scheme is presented and investigated for robotic redundancy resolution. The resultant obstacle-avoidance MVN scheme resolved at the joint-velocity level is further reformulated as a general quadratic program (QP). Two QP solvers, i.e., a simplified primal-dual neural network based on linear variational inequalities (LVI) and an LVI-based numerical algorithm, are developed and applied for online solution of the QP problem as well as the inequality-based obstacle-avoidance MVN scheme. Simulative results that are based on PA10 robot manipulator and a six-link planar robot manipulator in the presence of window-shaped and point obstacles demonstrate the efficacy and superiority of the proposed obstacle-avoidance MVN scheme. Moreover, experimental results of the proposed MVN scheme implemented on the practical six-link planar robot manipulator substantiate the physical realizability and effectiveness of such a scheme for obstacle avoidance of redundant robot manipulator.
The WebNLG Challenge: Generating Text from RDF Data

The WebNLG challenge consists in mapping sets of RDF triples to text. It provides a common benchmark on which to train, evaluate and compare “microplanners”, i.e. generation systems that verbalise a given content by making a range of complex interacting choices including referring expression generation, aggregation, lexicalisation, surface realisation and sentence segmentation. In this paper, we introduce the microplanning task, describe data preparation, introduce our evaluation methodology, analyse participant results and provide a brief description of the participating systems.
GUS fusions: beta-glucuronidase as a sensitive and versatile gene fusion marker in higher plants.

We have used the Escherichia coli beta-glucuronidase gene (GUS) as a gene fusion marker for analysis of gene expression in transformed plants. Higher plants tested lack intrinsic beta-glucuronidase activity, thus enhancing the sensitivity with which measurements can be made. We have constructed gene fusions using the cauliflower mosaic virus (CaMV) 35S promoter or the promoter from a gene encoding the small subunit of ribulose bisphosphate carboxylase (rbcS) to direct the expression of beta-glucuronidase in transformed plants. Expression of GUS can be measured accurately using fluorometric assays of very small amounts of transformed plant tissue. Plants expressing GUS are normal, healthy and fertile. GUS is very stable, and tissue extracts continue to show high levels of GUS activity after prolonged storage. Histochemical analysis has been used to demonstrate the localization of gene activity in cells and tissues of transformed plants.
Cancrum Oris: A case report.

Cancrum Oris is acute gangrenous stomatitis of oral and para-oral structures in age group between 2 to 16 years particularly in sub-Saharan Africa with high morbidity and mortality. Exact bacteriology is uncertain. Acute necrotising gingivitis and oral herpetic ulcers are considered to be antecedent lesions. The treatment of cancrum oris is penicillin, tetracycline, metronidazol and clindamycin. second step of management includes reconstructive surgery for the treatment of the functional and cosmetic problems. The authors are reporting a case of cancrum oris in a 1.5-year-old child.
Stochastic Optimization for Large-scale Optimal Transport

Optimal transport (OT) defines a powerful framework to compare probability distributions in a geometrically faithful way. However, the practical impact of OT is still limited because of its computational burden. We propose a new class of stochastic optimization algorithms to cope with large-scale OT problems. These methods can handle arbitrary distributions (either discrete or continuous) as long as one is able to draw samples from them, which is the typical setup in highdimensional learning problems. This alleviates the need to discretize these densities, while giving access to provably convergent methods that output the correct distance without discretization error. These algorithms rely on two main ideas: (a) the dual OT problem can be re-cast as the maximization of an expectation; (b) the entropic regularization of the primal OT problem yields a smooth dual optimization which can be addressed with algorithms that have a provably faster convergence. We instantiate these ideas in three different setups: (i) when comparing a discrete distribution to another, we show that incremental stochastic optimization schemes can beat Sinkhorn’s algorithm, the current state-of-the-art finite dimensional OT solver; (ii) when comparing a discrete distribution to a continuous density, a semidiscrete reformulation of the dual program is amenable to averaged stochastic gradient descent, leading to better performance than approximately solving the problem by discretization ; (iii) when dealing with two continuous densities, we propose a stochastic gradient descent over a reproducing kernel Hilbert space (RKHS). This is currently the only known method to solve this problem, apart from computing OT on finite samples. We backup these claims on a set of discrete, semi-discrete and continuous benchmark problems.
Specification of Graph Translators with Triple Graph Grammars

Data integration is a key issue for any integrated set of software tools where each tool has its own data structures (at least on the conceptual level), but where we have many interdependencies between these private data structures. A typical CASE environment, for instance, offers tools for the manipulation of requirements and software design documents and provides more or less sophisticated assistance for keeping these documents in a consistent state. Up to now almost all of these data consistency observing or preserving integration tools are hand-crafted due to the lack of generic implementation frameworks and the absence of adequate specification formalisms. Triple graph grammars, a proper superset of pair grammars, are intended to fill this gap and to support the specification of interdependencies between graph-like data structures on a very high level. Furthermore, they form a solid fundament of a new machinery for the production of batch-oriented as well as incrementally working data integration tools.
Letter Recognition Using Holland-Style Adaptive Classifiers

Machine rule induction was examined on a difficult categorization problem by applying a Holland-style classifier system to a complex letter recognition task. A set of 20,000 unique letter images was generated by randomly distorting pixel images of the 26 uppercase letters from 20 different commercial fonts. The parent fonts represented a full range of character types including script, italic, serif, and Gothic. The features of each of the 20,000 characters were summarized in terms of 16 primitive numerical attributes. Our research focused on machine induction techniques for generating IF-THEN classifiers in which the IF part was a list of values for each of the 16 attributes and the THEN part was the correct category, i.e., one of the 26 letters of the alphabet. We examined the effects of different procedures for encoding attributes, deriving new rules, and apportioning credit among the rules. Binary and Gray-code attribute encodings that required exact matches for rule activation were compared with integer representations that employed fuzzy matching for rule activation. Random and genetic methods for rule creation were compared with instance-based generalization. The strength/specificity method for credit apportionment was compared with a procedure we call “accuracy/utility.”
Modular Production Networks : A New American model of Industrial Organization

This paper uses the case of contract manufacturing in the electronics industry to illustrate an emergent American model of industrial organization, the modular production network. Lead firms in the modular production network concentrate on the creation, penetration, and defense of markets for end products—and increasingly the provision of services to go with them—while manufacturing capacity is shifted out-of-house to globally-operating turn-key suppliers. The modular production network relies on codified inter-firm links and the generic manufacturing capacity residing in turn-key suppliers to reduce transaction costs, build large external economies of scale, and reduce risk for network actors. I test the modular production network model against some of the key theoretical tools that have been developed to predict and explain industry structure: Joseph Schumpeter's notion of innovation in the giant firm, Alfred Chandler's ideas about economies of speed and the rise of the modern corporation, Oliver Williamson's transaction cost framework, and a range of other production network models that appear in the literature. I argue that the modular production network yields better economic performance in the context of globalization than more spatially and socially embedded network models. I view the emergence of the modular production network as part of a historical process of industrial transformation in which nationally-specific models of industrial organization co-evolve in intensifying rounds of competition, diffusion, and adaptation.
Design of a high voltage pulse circuit for exciting ultrasonic transducers

Ultrasonic nondestructive testing with characters of fine resolution and low cost has well been developed and widely applied in modern industrial world. The generation of high voltage pulse to excite the transducer has been a critical challenge in an ultrasonic testing system. In this paper a DC/DC converting circuit with an input of 12V and an output of 300V and -300V independently is introduced, so is a pulse generator with pulse width configured by a FPGA with parameters transmitted through a PCI bus by VC++ program. With different connection of the circuit, a positive unipolar pulse, a negative unipolar pulse, a monocycle bipolar pulse and a 2-cycle bipolar pulse can be generated respectively. Finally some pulse characters which may influence the excitation of the ultrasonic transducer are analyzed, the spectrum signature of each type is presented in the later part of this paper.