nils-herrmann/clean_scirepeval huggingface dataset:
Rule-governed behavior: teaching a preliminary repertoire of rule-following to children with autism.

Rule-governed behavior is generally considered an integral component of complex verbal repertoires but has rarely been the subject of empirical research. In particular, little or no previous research has attempted to establish rule-governed behavior in individuals who do not already display the repertoire. This study consists of two experiments that evaluated multiple exemplar training procedures for teaching a simple component skill, which may be necessary for developing a repertoire of rule-governed behavior. In both experiments, children with autism were taught to respond to simple rules that specified antecedents and the behaviors that should occur in their presence. In the first study, participants were taught to respond to rules containing "if/then" statements, where the antecedent was specified before the behavior. The second experiment was a replication and extension of the first. It involved a variation on the manner in which rules were presented. Both experiments eventually demonstrated generalization to novel rules for all participants; however variations to the standard procedure were required for several participants. Results suggest that rule-following can be analyzed and taught as generalized operant behavior and implications for future research are discussed.
Finding All Justifications of OWL DL Entailments

Finding the justifications of an entailment (that is, all the minimal set of axioms sufficient to produce an entailment) has emerged as a key inference service for the Web Ontology Language (OWL). Justifications are essential for debugging unsatisfiable classes and contradictions. The availability of justifications as explanations of entailments improves the understandability of large and complex ontologies. In this paper, we present several algorithms for computing all the justifications of an entailment in an OWL-DL Ontology and show, by an empirical evaluation, that even a reasoner independent approach works well on real ontologies.
Lane following and lane departure using a linear-parabolic model

This paper proposes a technique for unwanted lane departure detection. Initially, lane boundaries are detected using a combination of the edge distribution function and a modified Hough transform. In the tracking stage, a linear-parabolic lane model is used: in the near vision field, a linear model is used to obtain robust information about lane orientation; in the far field, a quadratic function is used, so that curved parts of the road can be efficiently tracked. For lane departure detection, orientations of both lane boundaries are used to compute a lane departure measure at each frame, and an alarm is triggered when such measure exceeds a threshold. Experimental results indicate that the proposed system can fit lane boundaries in the presence of several image artifacts, such as sparse shadows, lighting changes and bad conditions of road painting, being able to detect in advance involuntary lane crossings.
Reconstruction of the mandible with osseous free flaps: a 10-year experience with 150 consecutive patients.

Osseous free flaps have become the preferred method for reconstructing segmental mandibular defects. Of 457 head and neck free flaps, 150 osseous mandible reconstructions were performed over a 10-year period. This experience was retrospectively reviewed to establish an approach to osseous free flap mandible reconstruction. There were 94 male and 56 female patients (mean age, 50 years; range 3 to 79 years); 43 percent had hemimandibular defects, and the rest had central, lateral, or a combination defect. Donor sites included the fibula (90 percent), radius (4 percent), scapula (4 percent), and ilium (2 percent). Rigid fixation (up to five osteotomy sites) was used in 98 percent of patients. Aesthetic and functional results were evaluated a minimum of 6 months postoperatively. The free flap success rate was 100 percent, and bony union was achieved in 97 percent of the osteotomy sites. Osseointegrated dental implants were placed in 20 patients. A return to an unrestricted diet was achieved in 45 percent of patients; 45 percent returned to a soft diet, and 5 percent were on a liquid diet. Five percent of patients required enteral feeding to maintain weight. Speech was assessed as normal (36 percent), near normal (27 percent), intelligible (28 percent), or unintelligible (9 percent). Aesthetic outcome was judged as excellent (32 percent), good (27 percent), fair (27 percent), or poor (14 percent). This study demonstrates a very high success rate, with good-to-excellent functional and aesthetic results using osseous free flaps for primary mandible reconstruction. The fibula donor site should be the first choice for most cases, particularly those with anterior or large bony defects requiring multiple osteotomies. Use of alternative donor sites (i.e., radius and scapula) is best reserved for cases with large soft-tissue and minimal bone requirements. The ilium is recommended only when other options are unavailable. Thoughtful flap selection and design should supplant the need for multiple, simultaneous free flaps and vein grafting in most cases.
GPLOM: The Generalized Plot Matrix for Visualizing Multidimensional Multivariate Data

Scatterplot matrices (SPLOMs), parallel coordinates, and glyphs can all be used to visualize the multiple continuous variables (i.e., dependent variables or measures) in multidimensional multivariate data. However, these techniques are not well suited to visualizing many categorical variables (i.e., independent variables or dimensions). To visualize multiple categorical variables, 'hierarchical axes' that 'stack dimensions' have been used in systems like Polaris and Tableau. However, this approach does not scale well beyond a small number of categorical variables. Emerson et al.  extend the matrix paradigm of the SPLOM to simultaneously visualize several categorical and continuous variables, displaying many kinds of charts in the matrix depending on the kinds of variables involved. We propose a variant of their technique, called the Generalized Plot Matrix (GPLOM). The GPLOM restricts Emerson et al.'s technique to only three kinds of charts (scatterplots for pairs of continuous variables, heatmaps for pairs of categorical variables, and barcharts for pairings of categorical and continuous variable), in an effort to make it easier to understand. At the same time, the GPLOM extends Emerson et al.'s work by demonstrating interactive techniques suited to the matrix of charts. We discuss the visual design and interactive features of our GPLOM prototype, including a textual search feature allowing users to quickly locate values or variables by name. We also present a user study that compared performance with Tableau and our GPLOM prototype, that found that GPLOM is significantly faster in certain cases, and not significantly slower in other cases.
High linearity SPDT switch for dual band wireless LAN applications

This paper presents a high linear and power-handling single-pole double-throw (SPDT) switch for WLAN 802.11 a/b/g applications. The switch circuit has asymmetric and stacked topology to have high power-handling and linearity for the Tx path. This SPDT switch has been implemented with 0.25 /spl mu/m GaAs pHEMT process by ETRI. The designed SPDT switch has the measured insertion loss of better than 1dB and isolation of better than 40dB for the Tx path and 25dB for the Rx path and the high power handling capability with P/sub 1dB/ of about 23dBm with control voltage of -3/0 V. The fabricated SPDT switch chip size is 1.8 mm /spl times/ 1.8 mm.
A Survey of Scheduling and Interference Mitigation in LTE

Among the goals of 3GPP LTE networks are higher user bit rates, lower delays, increased spectrum efficiency, support for diverse QoS requirements, reduced cost, and operational simplicity. Resource scheduling and interference mitigation are two functions which are key to achieving these goals. This paper provides a survey of related techniques which have been proposed and shown to be promising. A brief discussion of the challenges for LTE-Advanced, the next step in the evolution, is also provided.
Exploring Content-based Artwork Recommendation with Metadata and Visual Features

Compared to other areas, artwork recommendation has received lile aention, despite the continuous growth of the artwork market. Previous research has relied on ratings and metadata to make artwork recommendations, as well as visual features extracted with deep neural networks (DNN). However, these features have no direct interpretation to explicit visual features (e.g. brightness, texture) which might hinder explainability and user-acceptance. In this work, we study the impact of artwork metadata as well as visual features (DNN-based and aractiveness-based) for physical artwork recommendation, using images and transaction data from the UGallery online artwork store. Our results indicate that: (i) visual features perform beer than manually curated data, (ii) DNN-based visual features perform beer than aractiveness-based ones, and (iii) a hybrid approach improves the performance further. Our research can inform the development of new artwork recommenders relying on diverse content data.
FinBrain: When Finance Meets AI 2.0

Artificial intelligence (AI) is the core technology of technological revolution and industrial transformation. As one of the new intelligent needs in the AI 2.0 era, financial intelligence has elicited much attention from the academia and industry. In our current dynamic capital market, financial intelligence demonstrates a fast and accurate machine learning capability to handle complex data and has gradually acquired the potential to become a "financial brain". In this work, we survey existing studies on financial intelligence. First, we describe the concept of financial intelligence and elaborate on its position in the financial technology field. Second, we introduce the development of financial intelligence and review state-of-the-art techniques in wealth management, risk management, financial security, financial consulting, and blockchain. Finally, we propose a research framework called FinBrain and summarize four open issues, namely, explainable financial agents and causality, perception and prediction under uncertainty, risk-sensitive and robust decision making, and multi-agent game and mechanism design. We believe that these research directions can lay the foundation for the development of AI 2.0 in the finance field.
Model Compression Applied to Small-Footprint Keyword Spotting

Several consumer speech devices feature voice interfaces that perform on-device keyword spotting to initiate user interactions. Accurate on-device keyword spotting within a tight CPU budget is crucial for such devices. Motivated by this, we investigated two ways to improve deep neural network (DNN) acoustic models for keyword spotting without increasing CPU usage. First, we used low-rank weight matrices throughout the DNN. This allowed us to increase representational power by increasing the number of hidden nodes per layer without changing the total number of multiplications. Second, we used knowledge distilled from an ensemble of much larger DNNs used only during training. We systematically evaluated these two approaches on a massive corpus of far-field utterances. Alone both techniques improve performance and together they combine to give significant reductions in false alarms and misses without increasing CPU or memory usage.
Applying a ThinkLet- and ThinXel-Based Group Process Modeling Language: A Prototype of a Universal Group Support System

Group Support Systems (GSS) can improve the productivity of Group Work by offering a variety of tools to assist a virtual group across geographical distances. Experience shows that the value of a GSS depends on how purposefully and skillfully it is used. We present a framework for a universal GSS based on a thinkLet- and thinXel-based Group Process Modeling Language (GPML). Our framework approach uses the GPML to describe different kinds of group processes in an unambiguous and compact representation and to guide the participants automatically through these processes. We assume that a GSS based on this GPML can provide the following advantages: to support the user by designing and executing a collaboration process and to increase the applicability of GSSs for different kinds of group processes. We will present a prototype and use different kinds of group processes to illustrate the application of a GPML for a universal GSS.
Rendered Insecure: GPU Side Channel Attacks are Practical

Graphics Processing Units (GPUs) are commonly integrated with computing devices to enhance the performance and capabilities of graphical workloads. In addition, they are increasingly being integrated in data centers and clouds such that they can be used to accelerate data intensive workloads. Under a number of scenarios the GPU can be shared between multiple applications at a fine granularity allowing a spy application to monitor side channels and attempt to infer the behavior of the victim. For example, OpenGL and WebGL send workloads to the GPU at the granularity of a frame, allowing an attacker to interleave the use of the GPU to measure the side-effects of the victim computation through performance counters or other resource tracking APIs. We demonstrate the vulnerability using two applications. First, we show that an OpenGL based spy can fingerprint websites accurately, track user activities within the website, and even infer the keystroke timings for a password text box with high accuracy. The second application demonstrates how a CUDA spy application can derive the internal parameters of a neural network model being used by another CUDA application, illustrating these threats on the cloud. To counter these attacks, the paper suggests mitigations based on limiting the rate of the calls, or limiting the granularity of the returned information.
Comparison of immunoglobulin ( IgM ) from four fish species

Immunoglobulin (IgM) was isolated from the serum of four fish species, Atlantic salmon (Salmo salar L.), halibut (Hippoglossus hippoglossus L.), haddock (Melanogrammus aeglefinus L.) and cod (Gadus morhua L.) and a comparison made of some physical and biochemical properties. The molecular weight of IgM varied between the different species and between the different analytical methods used. IgM from all four species was tetrameric in serum although a proportion of the molecule was held together by noncovalent forces. Salmon and haddock IgM were composed of two IgM types as regards the overall charge whereas halibut and cod IgM were homogeneous in this respect. The molecular weight of the heavy and light chains was similar for all four species. The oligosaccharide moiety, which was N-linked and associated with the heavy chain varied from 7.8 to 11.4% of the total molecular weight. Lectin analysis indicated variable composition of the carbohydrate moiety between species. The sensitivity to PNGase and trypsin varied between the four species.
Phase 2 Placebo-Controlled Trial of Two Vaccines to Prevent Ebola in Liberia.

The safety and efficacy of vaccines to prevent Ebola virus disease (EVD) were unknown when the incidence of EVD was peaking in Liberia.



We initiated a randomized, placebo-controlled, phase 3 trial of the chimpanzee adenovirus 3 vaccine (ChAd3-EBO-Z) and the recombinant vesicular stomatitis virus vaccine (rVSV∆G-ZEBOV-GP) in Liberia. A phase 2 subtrial was embedded to evaluate safety and immunogenicity. Because the incidence of EVD declined in Liberia, the phase 2 component was expanded and the phase 3 component was eliminated.



A total of 1500 adults underwent randomization and were followed for 12 months. The median age of the participants was 30 years; 36.6% of the participants were women. During the week after the administration of vaccine or placebo, adverse events occurred significantly more often with the active vaccines than with placebo; these events included injection-site reactions (in 28.5% of the patients in the ChAd3-EBO-Z group and 30.9% of those in the rVSV∆G-ZEBOV-GP group, as compared with 6.8% of those in the placebo group), headache (in 25.1% and 31.9%, vs. 16.9%), muscle pain (in 22.3% and 26.9%, vs. 13.3%), feverishness (in 23.9% and 30.5%, vs. 9.0%), and fatigue (in 14.0% and 15.4%, vs. 8.8%) (P<0.001 for all comparisons); these differences were not seen at 1 month. Serious adverse events within 12 months after injection were seen in 40 participants (8.0%) in the ChAd3-EBO-Z group, in 47 (9.4%) in the rVSV∆G-ZEBOV-GP group, and in 59 (11.8%) in the placebo group. By 1 month, an antibody response developed in 70.8% of the participants in the ChAd3-EBO-Z group and in 83.7% of those in the rVSV∆G-ZEBOV-GP group, as compared with 2.8% of those in the placebo group (P<0.001 for both comparisons). At 12 months, antibody responses in participants in the ChAd3-EBO-Z group (63.5%) and in those in the rVSV∆G-ZEBOV-GP group (79.5%) remained significantly greater than in those in the placebo group (6.8%, P<0.001 for both comparisons).



A randomized, placebo-controlled phase 2 trial of two vaccines that was rapidly initiated and completed in Liberia showed the capability of conducting rigorous research during an outbreak. By 1 month after vaccination, the vaccines had elicited immune responses that were largely maintained through 12 months. (Funded by the National Institutes of Allergy and Infectious Diseases and the Liberian Ministry of Health; PREVAIL I ClinicalTrials.gov number, NCT02344407 .).
AIDS-defining illnesses: a comparison between before and after commencement of highly active antiretroviral therapy (HAART).

Attempts to address the significant impact of HAART on medical variables on the Malaysian HIV/AIDS population have yet to be evaluated. This study aims to analyze the proportions of AIDS-defining illnesses (ADIs) before and after HAART. A retrospective study was carried out on 128 new cases of HIV infected patients who first commenced HAART in 2004 at the national HIV reference center. Before commencement of HAART, 76 clinical episodes of ADIs were recorded in 52 patients. Most common being pulmonary Mycobacterium tuberculosis (28.9%), PCP (27.6%) and disseminated and extrapulmonary Mycobacterium tuberculosis (11.8%). During HAART, 8 clinical episodes of ADIs were documented in 7 patients with a median time of onset of 10 weeks after initiation of HAART (range, 4-36 weeks). The median CD4 count at the time of the commencement of HAART for these patients was 11 cells/mm(3). ADIs reported include PCP (2 episodes), disseminated and extrapulmonary Mycobacterium tuberculosis (2 episodes), extrapulmonary cryptococcosis (1 episode), esophageal candidiasis (1 episode), recurrent pneumonia (1 episode) and disseminated or extrapulmonary histoplasmosis (1 episode). Three (37.5%) of these occurred despite a reduction of viral load by at least 2 log(10) and an increased in the CD4 cell count. In conclusion, ADIs can still present after the initiation of successful HAART especially in those with CD4 counts below 100 cells/mm(3). In Malaysia, ADIs are the major causes of HIV/AIDS associated morbidity and mortality, thus increased awareness on the management of these illnesses is warranted especially in the months following HAART.
Diseases as network perturbations.

The tremendous amount of the data obtained from the study of complex biological systems changes our view on the pathogenesis of human diseases. Instead of looking at individual components of biological processes, we focus our attention more on the interaction and dynamics of biological systems. A network representation and analysis of the physiology and pathophysiology of biological systems is an effective way to study their complex behavior. Specific perturbations can trigger cascades of failures, which lead to the malfunctioning of cellular networks and as a result to the development of specific diseases. In this review we discuss recent developments in the field of disease network analysis and highlight some of the topics and views that we think are important for understanding network-based disease mechanisms.
Review Typology: The Basic Types of Reviews for Synthesizing Evidence for the Purpose of Knowledge Translation.

With advances in medical practice and fields of research, reviews occupy a key position for summarizing existing knowledge. Due to the differences and overlap in terminology, the full potential for reviews may be lost due to confusion of indistinct approaches. The main objective of this study was to provide a descriptive outline of each of the common review types with their characteristics and examples in a health care system. Ascoping search was conducted using the keywords associated with the literature review typology. The SALSA(Search, Appraisal, Synthesis and Analysis) analytical framework was used to identify and distinguish each type of review. Nine common types of reviews and associated methodologies were evaluated against the already established SALSA framework. Their description, strengths and weaknesses are presented. The results provided a basic idea of different types of reviews based on the intended level of knowledge synthesis by which researchers can identify the appropriate type of review based on their intended audience.
Towards a model of understanding social search

Search engine researchers typically depict search as the solitary activity of an individual searcher. In contrast, results from our critical-incident survey of 150 users on Amazon's Mechanical Turk service suggest that social interactions play an important role throughout the search process. Our main contribution is that we have integrated models from previous work in sensemaking and information seeking behavior to present a canonical social model of user activities before, during, and after search, suggesting where in the search process both explicitly and implicitly shared information may be valuable to individual searchers.
Regulation of GABA(A) receptor membrane trafficking and synaptic localization.

Synaptic inhibition plays a key role in regulating neuronal excitability and information processing in the brain. The strength of synaptic inhibition is therefore an important determinant of both cellular and network activity levels in the central nervous system (CNS). gamma-aminobutyric acid type A (GABA(A)) receptors are the major sites for fast inhibitory neurotransmission in the CNS and alterations in their trafficking, synaptic accumulation and function play a key role in regulating neuronal excitability. Synaptic receptor number is determined by the trafficking of GABA(A) receptors to and away from inhibitory synapses and by their stability and localization at the inhibitory postsynaptic domain. Here we discuss advances that have led to an improved understanding of the mechanisms that regulate the delivery and stabilization of GABA(A) receptors at inhibitory synapses and address the role of GABA(A) receptor trafficking, GABA(A) receptor associated proteins and post-translational modifications in regulating this process.
PM synchronous machine PMSM Performance Improvement

Due to the importance of PM synchronous machine in many categories like in industrial, mechatronics, automotive, energy storage flywheel, centrifugal compressor, vacuum pump and robotic applications moreover in smart power grid applications, this paper is presented. It reviews the improvement of permanent magnet synchronous machines performance researches. This is done depending on many researchers' papers as samples for many aspects like: modelling, control, optimization and design to present a satisfied literature review