nils-herrmann/clean_scirepeval huggingface dataset:
Complex systems approach for sports injuries: moving from risk factor identification to injury pattern recognition-narrative review and new concept.

Injury prediction is one of the most challenging issues in sports and a key component for injury prevention. Sports injuries aetiology investigations have assumed a reductionist view in which a phenomenon has been simplified into units and analysed as the sum of its basic parts and causality has been seen in a linear and unidirectional way. This reductionist approach relies on correlation and regression analyses and, despite the vast effort to predict sports injuries, it has been limited in its ability to successfully identify predictive factors. The majority of human health conditions are complex. In this sense, the multifactorial complex nature of sports injuries arises not from the linear interaction between isolated and predictive factors, but from the complex interaction among a web of determinants. Thus, the aim of this conceptual paper was to propose a complex system model for sports injuries and to demonstrate how the implementation of complex system thinking may allow us to better address the complex nature of the sports injuries aetiology. According to this model, we should identify features that are hallmarks of complex systems, such as the pattern of relationships (interactions) among determinants, the regularities (profiles) that simultaneously characterise and constrain the phenomenon and the emerging pattern that arises from the complex web of determinants. In sports practice, this emerging pattern may be related to injury occurrence or adaptation. This novel view of preventive intervention relies on the identification of regularities or risk profile, moving from risk factors to risk pattern recognition.
An alternative treatment for anxiety: a systematic review of human trial results reported for the Ayurvedic herb ashwagandha (Withania somnifera).

To assess existing reported human trials of Withania somnifera (WS; common name, ashwagandha) for the treatment of anxiety.



Systematic review of the literature, with searches conducted in PubMed, SCOPUS, CINAHL, and Google Scholar by a medical librarian. Additionally, the reference lists of studies identified in these databases were searched by a research assistant, and queries were conducted in the AYUSH Research Portal. Search terms included "ashwagandha," "Withania somnifera," and terms related to anxiety and stress. Inclusion criteria were human randomized controlled trials with a treatment arm that included WS as a remedy for anxiety or stress. The study team members applied inclusion criteria while screening the records by abstract review.



Treatment with any regimen of WS.



Number and results of studies identified in the review.



Sixty-two abstracts were screened; five human trials met inclusion criteria. Three studies compared several dosage levels of WS extract with placebos using versions of the Hamilton Anxiety Scale, with two demonstrating significant benefit of WS versus placebo, and the third demonstrating beneficial effects that approached but did not achieve significance (p=0.05). A fourth study compared naturopathic care with WS versus psychotherapy by using Beck Anxiety Inventory (BAI) scores as an outcome; BAI scores decreased by 56.5% in the WS group and decreased 30.5% for psychotherapy (p<0.0001). A fifth study measured changes in Perceived Stress Scale (PSS) scores in WS group versus placebo; there was a 44.0% reduction in PSS scores in the WS group and a 5.5% reduction in the placebo group (p<0.0001). All studies exhibited unclear or high risk of bias, and heterogenous design and reporting prevented the possibility of meta-analysis.



All five studies concluded that WS intervention resulted in greater score improvements (significantly in most cases) than placebo in outcomes on anxiety or stress scales. Current evidence should be received with caution because of an assortment of study methods and cases of potential bias.
oPass: A User Authentication Protocol Resistant to Password Stealing and Password Reuse Attacks

Text password is the most popular form of user authentication on websites due to its convenience and simplicity. However, users' passwords are prone to be stolen and compromised under different threats and vulnerabilities. Firstly, users often select weak passwords and reuse the same passwords across different websites. Routinely reusing passwords causes a domino effect; when an adversary compromises one password, she will exploit it to gain access to more websites. Second, typing passwords into untrusted computers suffers password thief threat. An adversary can launch several password stealing attacks to snatch passwords, such as phishing, keyloggers and malware. In this paper, we design a user authentication protocol named oPass which leverages a user's cellphone and short message service to thwart password stealing and password reuse attacks. oPass only requires each participating website possesses a unique phone number, and involves a telecommunication service provider in registration and recovery phases. Through oPass, users only need to remember a long-term password for login on all websites. After evaluating the oPass prototype, we believe oPass is efficient and affordable compared with the conventional web authentication mechanisms.
Candy and Tipping 1 Running head : USING CANDY TO INCREASE TIPS Sweetening the Till : The Use of Candy to Increase Restaurant Tipping

A common practice among servers in restaurants is to give their dining parties an unexpected gift in the form of candy when delivering the check. Two studies were conducted to evaluate the impact of this gesture on the tip percentages received by servers. Study 1 found that customers who received a small piece of chocolate along with the check tipped more than did customers who received no candy. Study 2 found that tips varied with the amount of the candy given to the customers as well as with the manner in which it was offered. It is argued that reciprocity is a stronger explanation for these findings than either impression management or the good mood effect.
On the role of positive and negative affectivity in job performance: a meta-analytic investigation.

Although interest regarding the role of dispositional affect in job behaviors has surged in recent years, the true magnitude of affectivity's influence remains unknown. To address this issue, the authors conducted a qualitative and quantitative review of the relationships between positive and negative affectivity (PA and NA, respectively) and various performance dimensions. A series of meta-analyses based on 57 primary studies indicated that PA and NA predicted task performance in the hypothesized directions and that the relationships were strongest for subjectively rated versus objectively rated performance. In addition, PA was related to organizational citizenship behaviors but not withdrawal behaviors, and NA was related to organizational citizenship behaviors, withdrawal behaviors, counterproductive work behaviors, and occupational injury. Mediational analyses revealed that affect operated through different mechanisms in influencing the various performance dimensions. Regression analyses documented that PA and NA uniquely predicted task performance but that extraversion and neuroticism did not, when the four were considered simultaneously. Discussion focuses on the theoretical and practical implications of these findings.
Dual Polarized Array Antenna for S / X Band Active Phased Array Radar Application

A dual-band dual-polarized microstrip antenna array for an advanced multi-function radio function concept (AMRFC) radar application operating at S and X-bands is proposed. Two stacked planar arrays with three different thin substrates (RT/Duroid 5880 substrates with εr=2.2 and three different thicknesses of 0.253 mm, 0.508 mm and 0.762 mm) are integrated to provide simultaneous operation at S band (3~3.3 GHz) and X band (9~11 GHz). To allow similar scan ranges for both bands, the S-band elements are selected as perforated patches to enable the placement of the X-band elements within them. Square patches are used as the radiating elements for the X-band. Good agreement exists between the simulated and the measured results. The measured impedance bandwidth (VSWR≤2) of the prototype array reaches 9.5 % and 25 % for the Sand X-bands, respectively. The measured isolation between the two orthogonal polarizations for both bands is better than 15 dB. The measured cross-polarization level is ≤—21 dB for the S-band and ≤—20 dB for the X-band.
An Evaluation of OCR Accuracy

The data used in the test consisted of 500 pages selected at random from a collection of approximately 2,500 documents containing 100,000 pages. The documents in this collection were chosen by the U.S. Department of Energy (DOE) to represent the kinds of documents from which the DOE plans to build large, full-text retrieval databases using OCR for document conversion. The documents are mostly scientific and technical papers [Nartker 92].
ROSRemote, using ROS on cloud to access robots remotely

Cloud computing is an area that, nowadays, has been attracting a lot of researches and is expanding not only for processing data, but also for robotics. Cloud robotics is becoming a well-known subject, but it only works in a way to find a faster manner of processing data, which is almost like the idea of cloud computing. In this paper we have created a way to use cloud not only for this kind of operation but, also, to create a framework that helps users to work with ROS in a remote master, giving the possibility to create several applications that may run remotely. Using SpaceBrew, we do not have to worry about finding the robots addresses, which makes this application easier to implement because programmers only have to code as if the application is local.
Gyroscope-based video stabilisation with auto-calibration

We propose a technique for joint calibration of a wide-angle rolling shutter camera (e.g. a GoPro) and an externally mounted gyroscope. The calibrated parameters are time scaling and offset, relative pose between gyroscope and camera, and gyroscope bias. The parameters are found using non-linear least squares minimisation using the symmetric transfer error as cost function. The primary contribution is methods for robust initialisation of the relative pose and time offset, which are essential for convergence. We also introduce a robust error norm to handle outliers. This results in a technique that works with general video content and does not require any specific setup or calibration patterns. We apply our method to stabilisation of videos recorded by a rolling shutter camera, with a rigidly attached gyroscope. After recording, the gyroscope and camera are jointly calibrated using the recorded video itself. The recorded video can then be stabilised using the calibrated parameters. We evaluate the technique on video sequences with varying difficulty and motion frequency content. The experiments demonstrate that our method can be used to produce high quality stabilised videos even under difficult conditions, and that the proposed initialisation is shown to end up within the basin of attraction. We also show that a residual based on the symmetric transfer error is more accurate than residuals based on the recently proposed epipolar plane normal coplanarity constraint, and that the use of robust errors is a critical component to obtain an accurate calibration.
Review of modified and hybrid flower pollination algorithms for solving optimization problems

Flower pollination algorithm (FPA) is a nature-inspired meta-heuristics to handle a large scale optimization process. This paper reviews the previous studies on the application of FPA, modified FPA and hybrid FPA for solving optimization problems. The effectiveness of FPA for solving the optimization problems are highlighted and discussed. The improvement aspects include local and global search strategies and the quality of the solutions. The measured enhancements in FPA are based on various research domains. The results of review indicate the capability of the enhanced and hybrid FPA for solving optimization problems in variety of applications and outperformed the results of other established optimization techniques.
Ontology based Chatbot ( For E-commerce Website ) Anusha Vegesna Information Technology

A working model of Ontology based chatbot is proposed that handles queries from users for an E-commerce website. It is mainly concerned with providing user the total control over the search result on the website. This chatbot helps the user by mapping relationships of the various entities required by the user, thus providing detailed and accurate information there by overcoming the drawbacks of traditional chatbots. The Ontology template is developed using Protégé which stores the knowledge acquired from the website APIs while the dialog manager is handled using Wit.ai. The integration of the dialog manager and the ontology template is managed through Python. The related response to the query will be formatted and returned to the user on the dialog manager. General Terms Artificial intelligence and Machine learning
Contextual Parameter Generation for Universal Neural Machine Translation

We propose a simple modification to existing neural machine translation (NMT) models that enables using a single universal model to translate between multiple languages while allowing for language specific parameterization, and that can also be used for domain adaptation. Our approach requires no changes to the model architecture of a standard NMT system, but instead introduces a new component, the contextual parameter generator (CPG), that generates the parameters of the system (e.g., weights in a neural network). This parameter generator accepts source and target language embeddings as input, and generates the parameters for the encoder and the decoder, respectively. The rest of the model remains unchanged and is shared across all languages. We show how this simple modification enables the system to use monolingual data for training and also perform zero-shot translation. We further show it is able to surpass state-of-theart performance for both the IWSLT-15 and IWSLT-17 datasets and that the learned language embeddings are able to uncover interesting relationships between languages.
Building facade detection, segmentation, and parameter estimation for mobile robot stereo vision

Building facade detection is an important problem in comput er vision, with applications in mobile robotics and semanti c scene understanding. In particular, mobile platform localizati on and guidance in urban environments can be enabled with acc urate models of the various building facades in a scene. Toward that end, w e present a system for detection, segmentation, and paramet er estimation of building facades in stereo imagery. The propo sed method incorporates multilevel appearance and dispari ty features in a binary discriminative model, and generates a set of cand id te planes by sampling and clustering points from the imag e with Random Sample Consensus (RANSAC), using local normal estim ates derived from Principal Component Analysis (PCA) to inf rm the planar models. These two models are incorporated into a t w -layer Markov Random Field (MRF): an appearanceand disp ar tybased discriminative classifier at the mid-level, and a geom etric model to segment the building pixels into facades at th e highlevel. By using object-specific stereo features, our discri minative classifier is able to achieve substantially higher accuracy than standard boosting or modeling with only appearance-based f eatures. Furthermore, the results of our MRF classification indicate a strong improvement in accuracy for the binary building dete ction problem and the labeled planar surface models provide a good approximation to the ground truth planes.
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Cytokines are small, short-lived proteins secreted by many different cell types. As signaling molecules, cytokines provide communication between cells and play a crucial role in modulating innate and adaptive immune response. The family of cytokines includes interferons, interleukins, chemokines, mesenchymal growth factors, tumor necrosis factor family and adipokines. Interferons (IFNs) are a multigene family of inducible cytokines with antiviral, antiproliferative, and immunomodulatory function. Recombinant DNA technology can be useful in the production of human IFNs. This process includes fermentation, purification, and formation of the final product. Interleukins are classified in families based on sequence homology, receptor-binding properties, biological function, and cellular sources. TNF and IL-1 are considered to be key mediators of inflammatory response, while IL-6 plays a key role in the transition from acute to chronic inflammation. The inhibition of TNF includes administration of anti-TNF antibody and TNF receptor (TNFR). The reduction of IL-1 level can be achieved by the administration of anti-IL-1 antibody or IL-1 receptor antagonist (IL-1Ra), and the reduction of IL-6 level in the treatment of chronic inflammatory diseases can be achieved by the administration of anti-IL-6 antibody and anti-IL-6 receptor antibody. Recombinant cytokines and cytokine antagonists (antibodies and receptors) can be used in treating many different diseases.
A front-illuminated stacked global-shutter CMOS image sensor with multiple chip-on-chip integration

A front-illuminated global-shutter CMOS image sensor has been developed with super 35-mm optical format. We have developed a chip-on-chip integration process to realize a front-illuminated image sensor stacked with 2 diced logic chips through 38K micro bump interconnections. The global-shutter pixel achieves a parasitic light sensitivity of −99.6dB. The stacked device allows highly parallel column ADCs and high-speed output interfaces to attain a frame rate of 480 fps with 8.3M-pixel resolution.
Non-intrusive tongue machine interface

There has been recent interest in designing systems that use the tongue as an input interface. Prior work however either require surgical procedures or in-mouth sensor placements. In this paper, we introduce TongueSee, a non-intrusive tongue machine interface that can recognize a rich set of tongue gestures using electromyography (EMG) signals from the surface of the skin. We demonstrate the feasibility and robustness of TongueSee with experimental studies to classify six tongue gestures across eight participants. TongueSee achieves a classification accuracy of 94.17% and a false positive probability of 0.000358 per second using three-protrusion preamble design.
Functional and clinical neuroanatomy of morality.

Morality is among the most sophisticated features of human judgement, behaviour and, ultimately, mind. An individual who behaves immorally may violate ethical rules and civil rights, and may threaten others' individual liberty, sometimes becoming violent and aggressive. In recent years, neuroscience has shown a growing interest in human morality, and has advanced our understanding of the cognitive and emotional processes involved in moral decisions, their anatomical substrates and the neurology of abnormal moral behaviour. In this article, we review research findings that have provided a key insight into the functional and clinical neuroanatomy of the brain areas involved in normal and abnormal moral behaviour. The 'moral brain' consists of a large functional network including both cortical and subcortical anatomical structures. Because morality is a complex process, some of these brain structures share their neural circuits with those controlling other behavioural processes, such as emotions and theory of mind. Among the anatomical structures implicated in morality are the frontal, temporal and cingulate cortices. The prefrontal cortex regulates activity in subcortical emotional centres, planning and supervising moral decisions, and when its functionality is altered may lead to impulsive aggression. The temporal lobe is involved in theory of mind and its dysfunction is often implicated in violent psychopathy. The cingulate cortex mediates the conflict between the emotional and the rational components of moral reasoning. Other important structures contributing to moral behaviour include the subcortical nuclei such as the amygdala, hippocampus and basal ganglia. Brain areas participating in moral processing can be influenced also by genetic, endocrine and environmental factors. Hormones can modulate moral behaviour through their effects on the brain. Finally, genetic polymorphisms can predispose to aggressivity and violence, arguing for a genetic-based predisposition to morality. Because abnormal moral behaviour can arise from both functional and structural brain abnormalities that should be diagnosed and treated, the neurology of moral behaviour has potential implications for clinical practice and raises ethical concerns. Last, since research has developed several neuromodulation techniques to improve brain dysfunction (deep brain stimulation, transcranial magnetic stimulation and transcranial direct current stimulation), knowing more about the 'moral brain' might help to develop novel therapeutic strategies for neurologically based abnormal moral behaviour.
Lexical Processing Drives Motor Simulation

While growing evidence suggests that sentence understanding engages perceptual and motor systems for the purpose of mentally imagining or simulating the content of utterances (Barsalou 1999) it is not known whether processing words alone does the same. We investigated whether making a decision about the form of a word would lead to activation of motor mechanisms, using a modified version of the Actionsentence Compatibility Effect (Glenberg and Kaschak 2002). Fluent signers of American Sign Language (ASL) were shown pairs of ASL signs which were either identical or not. Critical signs involved hand motion forward or backward, relative to the body. Subjects indicated whether the two signs were the same or different with a manual response requiring their hand to move either forward or backward thus in a direction either compatible or incompatible with the direction of motion denoted by the sign. Results demonstrated a compatibility effect literal and metaphorical motion signs facilitated response motion in the same direction, suggesting that mere phonological processing of a lexical item with motion meaning engages the motor system. The same experiment, performed with non-signers yielded no such effect, demonstrating that the effect was not simply the result of perceptual processing of the form of the sign. These results support an embodied view of linguistic processing where the content of language about motor actions is simulated using parts of the cognitive system responsible for actually performing the described actions.
Towards proactive event-driven computing

Event driven architecture is a paradigm shift from traditional computing architectures which employ synchronous, request-response interactions. In this paper we introduce a conceptual architecture for what can be considered the next phase of that evolution: proactive event-driven computing. Proactivity refers to the ability to mitigate or eliminate undesired future events, or to identify and take advantage of future opportunities, by applying prediction and automated decision making technologies. We investigate an extension of the event processing conceptual model and architecture to support proactive event-driven applications, and propose the main building blocks of a novel architecture. We first describe several extensions to the existing event processing functionality that is required to support proactivity; next, we extend the event processing agent model to include two more type of agents: predictive agents that may derive future uncertain events based on prediction models, and proactive agents that compute the best proactive action that should be taken. Those building blocks are demonstrated through a comprehensive scenario that deals with proactive decision making, ensuring timely delivery of critical material for a production plant.