nils-herrmann/clean_scirepeval huggingface dataset:
Team vs . Team : Success Factors in a Multiplayer Online Battle Arena Game

There is a small but growing body of research investigating how teams form and how that affects how they perform. Much of that research focuses on teams that seek to accomplish certain tasks such as writing an article or performing a Broadway musical. There has been much less investigation of the relative performance of teams that form to directly compete against another team. In this study, we report on team-vs-team competitions in the multiplayer online battle arena game Dota 2. Here, the teams’ overall goal is to beat the opponent. We use this setting to observe multilevel factors influence the relative performance of the teams. Those factors include compositional factors or attributes of the individuals comprising a team, relational factors or prior relations among individuals within a team and ecosystem factors or overlapping prior membership of team members with others within the ecosystem of teams. We also study how these multilevel factors affect the duration of a match. Our results show that advantages at the compositional, relational and ecosystem levels predict which team will succeed in short or medium duration matches. Relational and ecosystem factors are particularly helpful in predicting the winner in short duration matches, whereas compositional factors are more important predicting winners in medium duration matches. However, the two types of relations have opposite effects on the duration of winning. None of the three multilevel factors help explain which team will win in long matches.
Prevalence, pathogenesis, and causes of chronic cough

Cough is a reflex action of the respiratory tract that is used to clear the upper airways. Chronic cough lasting for more than 8 weeks is common in the community. The causes include cigarette smoking, exposure to cigarette smoke, and exposure to environmental pollution, especially particulates. Diseases causing chronic cough include asthma, eosinophilic bronchitis, gastro-oesophageal reflux disease, postnasal drip syndrome or rhinosinusitis, chronic obstructive pulmonary disease, pulmonary fibrosis, and bronchiectasis. Doctors should always work towards a clear diagnosis, considering common and rare illnesses. In some patients, no cause is identified, leading to the diagnosis of idiopathic cough. Chronic cough is often associated with an increased response to tussive agents such as capsaicin. Plastic changes in intrinsic and synaptic excitability in the brainstem, spine, or airway nerves can enhance the cough reflex, and can persist in the absence of the initiating cough event. Structural and inflammatory airway mucosal changes in non-asthmatic chronic cough could represent the cause or the traumatic response to repetitive coughing. Effective control of cough requires not only controlling the disease causing the cough but also desensitisation of cough pathways.
Estudo de avaliação da efi cácia do ácido tranexâmico tópico e injetável no tratamento do melasma Study evaluating the effi cacy of topical and injected tranexamic acid in treatment of melasma

Melasma is an acquired hypermelanosis of multifactorial etiology. It is a great therapeutic chalenge. Tranexamic acid (TA) has been reported as an alternative therapy.  To evaluate the effi cacy and safety of TA in treatment of melasma, comparing the use of localized microinjection versus topical therapy.  Eighteen women with melasma were selected and divided into 2 groups. Group A: At-home topical application of TA 3% twice a day. Group B: 12 applications of intradermal injections of TA (4 mg/ml) weekly. Before and after treatment, the groups were compared according to the following parameters: photographic evolution, Melasma Area and Severity Index (MASI) evolution, self-assessment and colorimetry.  Seventeen patients completed the study. In group A, photographic evaluation showed improvement in 12,5%, worsening in 50%, and 37.5% had no change. In group B, there was improvement in 66.7% and 22.2% had no change. For the MASI, there was signifi cant improvement (p = 0.0026), with no difference between treatments (p = 0.6512). In group A self-assessment, 37.5% of the patients rated as good and 50% as imperceptible. In group B, 66.7% rated as good and 33.3% as imperceptible. Colorimetric evaluation showed signifi cant improvement on both treatments (p = 0.0008).  Although the subjective clinical evaluation has demonstrated the superiority of injected treatment, in objective evaluation, both treatments were signifi cantly effective, presenting TA as a promising new therapeutic option for melasma.
Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex.

Mouse visual cortex is subdivided into multiple distinct, hierarchically organized areas that are interconnected through feedforward (FF) and feedback (FB) pathways. The principal synaptic targets of FF and FB axons that reciprocally interconnect primary visual cortex (V1) with the higher lateromedial extrastriate area (LM) are pyramidal cells (Pyr) and parvalbumin (PV)-expressing GABAergic interneurons. Recordings in slices of mouse visual cortex have shown that layer 2/3 Pyr cells receive excitatory monosynaptic FF and FB inputs, which are opposed by disynaptic inhibition. Most notably, inhibition is stronger in the FF than FB pathway, suggesting pathway-specific organization of feedforward inhibition (FFI). To explore the hypothesis that this difference is due to diverse pathway-specific strengths of the inputs to PV neurons we have performed subcellular Channelrhodopsin-2-assisted circuit mapping in slices of mouse visual cortex. Whole-cell patch-clamp recordings were obtained from retrobead-labeled FF(V1→LM)- and FB(LM→V1)-projecting Pyr cells, as well as from tdTomato-expressing PV neurons. The results show that the FF(V1→LM) pathway provides on average 3.7-fold stronger depolarizing input to layer 2/3 inhibitory PV neurons than to neighboring excitatory Pyr cells. In the FB(LM→V1) pathway, depolarizing inputs to layer 2/3 PV neurons and Pyr cells were balanced. Balanced inputs were also found in the FF(V1→LM) pathway to layer 5 PV neurons and Pyr cells, whereas FB(LM→V1) inputs to layer 5 were biased toward Pyr cells. The findings indicate that FFI in FF(V1→LM) and FB(LM→V1) circuits are organized in a pathway- and lamina-specific fashion.
A Grouping Based Cooperative Driving Strategy for CAVs Merging Problems

In general, there are two kinds of cooperative driving strategies, planning based strategy and ad hoc negotiation based strategy, for connected and automated vehicles (CAVs) merging problems. The planning based strategy aims to find the global optimal passing order, but it is time-consuming when the number of considered vehicles is large. In contrast, the ad hoc negotiation based strategy runs fast, but it always finds a local optimal solution. In this paper, we propose a grouping based cooperative driving strategy to make a good tradeoff between time consumption and coordination performance. The key idea is to fix the passing orders for some vehicles whose intervehicle headways are small enough (e.g., smaller than the preselected grouping threshold). From the viewpoint of optimization, this method reduces the size of the solution space. A brief analysis shows that the sub-optimal passing order found by the grouping based strategy has a high probability to be close to the global optimal passing order, if the grouping threshold is appropriately chosen. A series of simulation experiments are carried out to validate that the proposed strategy can yield a satisfied coordination performance with less time consumption and is promising to be used in practice.
Facebook and YouTube addiction: The usage pattern of Malaysian students

This paper explores the usage of Facebook and YouTube among Malaysian students and the possibility of internet addiction in order to determine the effect of using social media in their social and academic lives. Data was collected from 667 Facebook users and 1056 YouTube users. Examining Young's [1]Internet addiction scale among the students revealed that 18% of Facebook users and 22% of YouTube users are addicted, and they spend more than two hours on Facebook and YouTube per day. They use Facebook for information, maintain relationships, academic learning, product inquiry, and meeting people, while YouTube is used for entertainment, information, academic learning, and product inquiry. These results create awareness for instructors and academic institution using YouTube videos and Facebook as complementary tools for teaching. They should be aware of the potential for compulsive and addicted users to be distracted from prescribed videos to unrelated materials.
Learning Decision Trees Using the Area Under the ROC Curve

ROC analysis is increasingly being recognised as an important tool for evaluation and comparison of classifiers when the operating characteristics (i.e. class distribution and cost parameters) are not known at training time. Usually, each classifier is characterised by its estimated true and false positive rates and is represented by a single point in the ROC diagram. In this paper, we show how a single decision tree can represent a set of classifiers by choosing different labellings of its leaves, or equivalently, an ordering on the leaves. In this setting, rather than estimating the accuracy of a single tree, it makes more sense to use the area under the ROC curve (AUC) as a quality metric. We also propose a novel splitting criterion which chooses the split with the highest local AUC. To the best of our knowledge, this is the first probabilistic splitting criterion that is not based on weighted average impurity. We present experiments suggesting that the AUC splitting criterion leads to trees with equal or better AUC value, without sacrificing accuracy if a single labelling is chosen.
Design of an anthropomorphic dual-arm robot with biologically inspired 8-DOF arms

From the perspective of kinematics, dual-arm manipulation in robots differs from single-arm manipulation in that it requires high dexterity in a specific region of the manipulator’s workspace. This feature has motivated research on the specialized design of manipulators for dualarm robots. These recently introduced robots often utilize a shoulder structure with a tilted angle of some magnitude. The tilted shoulder yields better kinematic performance for dual-arm manipulation, such as a wider common workspace for each arm. However, this method tends to reduce total workspace volume, which results in lower kinematic performance for single-arm tasks in the outer region of the workspace. To overcome this trade-off, the authors of this study propose a design for a dual-arm robot with a biologically inspired four degree-of-freedom shoulder mechanism. This study analyzes the kinematic performance of the proposed design and compares it with that of a conventional dual-arm robot from the perspective of workspace and single-/dual-arm manipulability. The comparative analysis Electronic supplementary material The online version of this article (doi:10.1007/s11370-017-0215-z) contains supplementary material, which is available to authorized users. B Ji-Hun Bae joseph@kitech.re.kr Dong-Hyuk Lee donghyuk@kitech.re.kr Hyeonjun Park pionyy@kitech.re.kr Jae-Han Park hans1024@kitech.re.kr Moon-Hong Baeg mhbaeg@kitech.re.kr 1 Robot Control and Cognition Lab., Robot R&D Group, Korea Institute of Industrial Technology (KITECH), Ansan, Korea revealed that the proposed structure can significantly enhance singleand dual-arm kinematic performance in comparison with conventional dual-arm structures. This superior kinematic performance was verified through experiments, which showed that the proposed method required shorter settling time and trajectory-following performance than the conventional dual-arm robot.
CELLULAR AND NETWORK ARCHITECTURE FOR 5 G WIRELESS COMMUNICATION NETWORKS IN MOBILE TECHNOLOGY

5G Technology stands for Fifth Generation Mobile technology. From generation 1G to 2.5G and from 3G to 5G this world of telecommunication has seen a number of improvements along with improved performance with every passing day. Fifth generation network provide affordable broadband wireless connectivity (very high speed). The paper throws light on network architecture of fifth generation technology. Currently 5G term is not officially used. In fifth generation researches are being made on development of World Wide Wireless Web (WWWW), Dynamic Adhoc Wireless Networks (DAWN) and Real Wireless World. Fifth generation focus on (Voice over IP) VOIP-enabled devices that user will experience a high level of call volume and data transmission. Wire-less system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore has started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. The proposed network is enforced by nanotechnology, cloud computing and based on all IP Platform. The main features in 5G mobile network is that user can simultaneously connect to the multiple wireless technologies and can switch between them. This forthcoming mobile technology will support IPv6 and flat IP.
AQUA: an aquatic walking robot

This paper describes an underwater walking robotic system being developed under the name AQUA, the goals of the AQUA project, the overall hardware and software design, the basic hardware and sensor packages that have been developed, and some initial experiments. The robot is based on the RHex hexapod robot and uses a suite of sensing technologies, primarily based on computer vision and INS, to allow it to navigate and map clear shallow-water environments. The sensor-based navigation and mapping algorithms are based on the use of both artificial floating visual and acoustic landmarks as well as on naturally occurring underwater landmarks and trinocular stereo.
Clavision: visual automatic piano music transcription

One significant problem in the science of Musical Information Retrieval is Automatic Music Transcription, which is an automated conversion process from played music to a symbolic notation such as sheet music. Since the accuracy of previous audio-based transcription systems is not satisfactory, an innovative visual-based automatic music transcription system named claVision is proposed to perform piano music transcription. Instead of processing the music audio, the system performs the transcription only from the video performance captured by a camera mounted over the piano keyboard. claVision can be used as a transcription tool, but it also has other applications such as music education. The software has a very high accuracy (over 95%) and a very low latency (less than 6.6 ms) in real-time music transcription, even under different illumination conditions. This technology can also be used for other musical keyboard instruments. claVision is the winner of the 2014 Microsoft Imagine Cup Competition in the category of innovation in both Canadian national finals and world semifinals. As one of the top 11 teams in the world, claVision advanced to World Finals in Seattle to be demonstrated at the University of Washington, Microsoft headquarters, and the Museum of History & Industry.
Permuted successive cancellation decoder for polar codes

We study a new variant of Arikan's successive cancellation decoder (SCD) for polar codes. We first propose a new decoding algorithm on a new decoder graph, where the various stages of the graph are permuted. We then observe that, even though the usage of the permuted graph doesn't affect the encoder, it can significantly affect the decoding performance of a given polar code. The new permuted successive cancellation decoder (PSCD) typically exhibits a performance degradation, since the polar code is optimized for the standard SCD. We then present a new polar code construction rule matched to the PSCD and show their performance in simulations. For all rates we observe that the polar code matched to a given PSCD performs the same as the original polar code with the standard SCD. We also see that a PSCD with a reversal permutation can lead to a natural decoding order, avoiding the standard bit-reversal decoding order in SCD without any loss in performance.
Virality and Susceptibility in Information Diffusions

Viral diffusion allows a piece of information to widely and quickly spread within the network of users through word-ofmouth. In this paper, we study the problem of modeling both item and user factors that contribute to viral diffusion in Twitter network. We identify three behaviorial factors, namely user virality, user susceptibility and item virality, that contribute to viral diffusion. Instead of modeling these factors independently as done in previous research, we propose a model that measures all the factors simultaneously considering their mutual dependencies. The model has been evaluated on both synthetic and real datasets. The experiments show that our model outperforms the existing ones for synthetic data with ground truth labels. Our model also performs well for predicting the hashtags that have higher retweet likelihood. We finally present case examples that illustrate how the models differ from one another.
Indoor tracking of multiple persons with a 77 GHz MIMO FMCW radar

In this paper, we tackle the task of multi-target tracking of humans in an indoor setting using a low power 77 GHz MIMO CMOS radar. A drawback of such a highresolution and low-power device is the higher sensitivity to noise, which makes the analysis of signals more challenging. Therefore, a pipeline is proposed to address both pre-processing of the radar signal and multi-target tracking. In the pre-processing phase, we focus on handling the low Signal-to-Noise Ratio (SNR) and eliminating so-called ghost targets. The tracking method we propose is based on Markov Chain Monte Carlo Data Association (MCMCDA), thus taking a combinatorial approach towards the task of tracking. The pipeline is tested on a number of real-world scenarios and shows promising results, overcoming the significant amount of noise associated with embedded radar devices.
Continuous Renal Replacement Therapy as a Supportive Treatment for Acute Pediatric Necrotizing Fasciitis

Acute necrotizing fasciitis (NF) in children is a dangerous illness characterized by progressive necrosis of the skin and subcutaneous tissue. The present study summarizes our recent experience with the treatment of pediatric patients with severe NF. Between 2000 and 2009, eight children suffering from NF were admitted to our department. Four of the children received an active treatment strategy including continuous renal replacement therapy (CRRT), radical debridement, and broad-spectrum antibiotics. Another four children presented at a late stage of illness, and did not complete treatment. Clinical data for these two patient groups were retrospectively analyzed. The four patients that completed CRRT, radical debridement, and a course of broad-spectrum antibiotics were cured without any significant residual morbidity. The other four infants died shortly after admission. Early diagnosis, timely debridement, and aggressive use of broad-spectrum antibiotics are key factors for achieving a satisfactory outcome for cases of acute NF. Early intervention with CRRT to prevent septic shock may also improve patient outcome.
Visual Human+Machine Learning

In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combines the vast search and processing power of the computer with the superior reasoning and pattern recognition capabilities of the human user. An evolutionary search algorithm has been adapted to assist in the fuzzy logic formalization of hypotheses that aim at explaining features inside multivariate, volumetric data. Up to now, users solely rely on their knowledge and expertise when looking for explanatory theories. However, it often remains unclear whether the selected attribute ranges represent the real explanation for the feature of interest. Other selections hidden in the large number of data variables could potentially lead to similar features. Moreover, as simulation complexity grows, users are confronted with huge multidimensional data sets making it almost impossible to find meaningful hypotheses at all. We propose an interactive cycle of knowledge-based analysis and automatic hypothesis generation. Starting from initial hypotheses, created with linking and brushing, the user steers a heuristic search algorithm to look for alternative or related hypotheses. The results are analyzed in information visualization views that are linked to the volume rendering. Individual properties as well as global aggregates are visually presented to provide insight into the most relevant aspects of the generated hypotheses. This novel approach becomes computationally feasible due to a GPU implementation of the time-critical parts in the algorithm. A thorough evaluation of search times and noise sensitivity as well as a case study on data from the automotive domain substantiate the usefulness of the suggested approach.
Effectiveness of Computer-Based Education in Elementary Schools

Abst rac t -A meta-analysis of 32 comparative studies showed that computer-based education has generally had positive effects on the achievement of elementary school pupils. These effects have been different, however, for programs of @line computer-managed instruction (CMI) and for interactive computer-assisted instruction (CAI). The average effect in 28 studies of CAI programs was an increase in pupil achievement scores of O. 47 standard deviations, or from the 50th to the 68th percentile. The average effect in four studies of CMI programs, however, was an increase in scores of only O. 07 standard deviations. Study features were not significantly related to study outcomes.
Deep scattering: rendering atmospheric clouds with radiance-predicting neural networks

We present a technique for efficiently synthesizing images of atmospheric clouds using a combination of Monte Carlo integration and neural networks. The intricacies of Lorenz-Mie scattering and the high albedo of cloud-forming aerosols make rendering of clouds---e.g. the characteristic silverlining and the "whiteness" of the inner body---challenging for methods based solely on Monte Carlo integration or diffusion theory. We approach the problem differently. Instead of simulating all light transport during rendering, we pre-learn the spatial and directional distribution of radiant flux from tens of cloud exemplars. To render a new scene, we sample visible points of the cloud and, for each, extract a hierarchical 3D descriptor of the cloud geometry with respect to the shading location and the light source. The descriptor is input to a deep neural network that predicts the radiance function for each shading configuration. We make the key observation that progressively feeding the hierarchical descriptor into the network enhances the network's ability to learn faster and predict with higher accuracy while using fewer coefficients. We also employ a block design with residual connections to further improve performance. A GPU implementation of our method synthesizes images of clouds that are nearly indistinguishable from the reference solution within seconds to minutes. Our method thus represents a viable solution for applications such as cloud design and, thanks to its temporal stability, for high-quality production of animated content.