nils-herrmann/clean_scirepeval huggingface dataset:
Employing Event Inference to Improve Semi-Supervised Chinese Event Extraction

Although semi-supervised model can extract the event mentions matching frequent event patterns, it suffers much from those event mentions, which match infrequent patterns or have no matching pattern. To solve this issue, this paper introduces various kinds of linguistic knowledge-driven event inference mechanisms to semi-supervised Chinese event extraction. These event inference mechanisms can capture linguistic knowledge from four aspects, i.e. semantics of argument role, compositional semantics of trigger, consistency on coreference events and relevant events, to further recover missing event mentions from unlabeled texts. Evaluation on the ACE 2005 Chinese corpus shows that our event inference mechanisms significantly outperform the refined state-of-the-art semi-supervised Chinese event extraction system in F1-score by 8.5%.
Benchmarking ETL Workflows

Extraction–Transform–Load (ETL) processes comprise complex data workflows, which are responsible for the maintenance of a Data Warehouse. A plethora of ETL tools is currently available constituting a multi-million dollar market. Each ETL tool uses its own technique for the design and implementation of an ETL workflow, making the task of assessing ETL tools extremely difficult. In this paper, we identify common characteristics of ETL workflows in an effort of proposing a unified evaluation method for ETL. We also identify the main points of interest in designing, implementing, and maintaining ETL workflows. Finally, we propose a principled organization of test suites based on the TPC-H schema for the problem of experimenting with ETL workflows.
Reduction of Torque Ripple in Inset Permanent Magnet Synchronous Motor by Magnets Shifting

This paper proposes a method of reducing total torque ripple by magnets shifting. The key of this method is to consider the reluctance torque ripple, because the reluctance torque ripple is the main source of torque ripple in inset permanent magnet synchronous motor. This method is realized by appropriately choosing Repeating Unit, which indicates a group of poles producing torques with consistency in waveforms and phases. Meanwhile, the uniform analytical expressions of torques with magnets shifting are established, including cogging torque, reluctance torque, and total torque. Moreover, the total torque ripple can be reduced greatly, and the average total torque loss is acceptable when one pole-pair is chosen as one Repeating Unit and the shifting angles of Repeating Unit are 3.75 and 1.875 mechanical degrees. These theoretical analyses are verified by the finite-element method.
Physiotherapy approaches in the treatment of ataxic multiple sclerosis: a pilot study.

This study was planned to investigate the efficacy of neuromuscular rehabilitation and Johnstone Pressure Splints in the patients who had ataxic multiple sclerosis.



Twenty-six outpatients with multiple sclerosis were the subjects of the study. The control group (n = 13) was given neuromuscular rehabilitation, whereas the study group (n = 13) was treated with Johnstone Pressure Splints in addition.



In pre- and posttreatment data, significant differences were found in sensation, anterior balance, gait parameters, and Expanded Disability Status Scale (p < 0.05). An important difference was observed in walking-on-two-lines data within the groups (p < 0.05). There also was a statistically significant difference in pendular movements and dysdiadakokinesia (p < 0.05). When the posttreatment values were compared, there was no significant difference between sensation, anterior balance, gait parameters, equilibrium and nonequilibrium coordination tests, Expanded Disability Status Scale, cortical onset latency, and central conduction time of somatosensory evoked potentials and motor evoked potentials (p > 0.05). Comparison of values revealed an important difference in cortical onset-P37 peak amplitude of somatosensory evoked potentials (right limbs) in favor of the study group (p < 0.05).



According to our study, it was determined that physiotherapy approaches were effective to decrease the ataxia. We conclude that the combination of suitable physiotherapy techniques is effective multiple sclerosis rehabilitation.
Motion Estimation Based on EMG and EEG Signals to Control Wearable Robots

An EMG signal shows almost one-to-one relationship with the corresponding muscle. Therefore, each joint motion can be estimated relatively easily based on the EMG signals to control wearable robots. However, necessary EMG signals are not always able to be measured with every user. On the other hand, an EEG signal is one of the strongest candidates for the additional input signals to control wearable robots. Since the EEG signals are available with almost all people, an EEG based method can be applicable to many users. However, it is more difficult to estimate the user's motion intention based on the EEG signals compared with the EMG signals. In this paper, a user's motion estimation method is proposed to control the wearable robots based on the user's motion intention. In the proposed method, the motion intention of the user is estimated based on the user's EMG and EEG signals. The EMG signals are used as main input signals because the EMG signals have higher correlation with the motion. Furthermore, the EEG signals are used to estimate the part of the motion which is not able to be estimated based on EMG signals because of the muscle unavailability.
Do Functional Movement Screen (FMS) composite scores predict subsequent injury? A systematic review with meta-analysis.

This paper aims to systematically review studies investigating the strength of association between FMS composite scores and subsequent risk of injury, taking into account both methodological quality and clinical and methodological diversity.



Systematic review with meta-analysis.



A systematic search of electronic databases was conducted for the period between their inception and 3 March 2016 using PubMed, Medline, Google Scholar, Scopus, Academic Search Complete, AMED (Allied and Complementary Medicine Database), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Health Source and SPORTDiscus.


 (1) English language, (2) observational prospective cohort design, (3) original and peer-reviewed data, (4) composite FMS score, used to define exposure and non-exposure groups and (5) musculoskeletal injury, reported as the outcome.



(1) data reported in conference abstracts or non-peer-reviewed literature, including theses, and (2) studies employing cross-sectional or retrospective study designs.



24 studies were appraised using the Quality of Cohort Studies assessment tool. In male military personnel, there was 'strong' evidence that the strength of association between FMS composite score (cut-point ≤14/21) and subsequent injury was 'small' (pooled risk ratio=1.47, 95% CI 1.22 to 1.77, p<0.0001, I2=57%). There was 'moderate' evidence to recommend against the use of FMS composite score as an injury prediction test in football (soccer). For other populations (including American football, college athletes, basketball, ice hockey, running, police and firefighters), the evidence was 'limited' or 'conflicting'.



The strength of association between FMS composite scores and subsequent injury does not support its use as an injury prediction tool.
A vision-based intelligent path following control of a four-wheel differentially driven skid steer mobile robot

In this paper a Fuzzy Logic Controller (FLC) for path following of a four-wheel differentially skid steer mobile robot is presented. Fuzzy velocity and fuzzy torque control of the mobile robot is compared with classical controllers. To assess controllers robot kinematics and dynamics are simulated with parameters of P2-AT mobile robot. Results demonstrate the better performance of fuzzy logic controllers in following a predefined path.
Embracing Continuous Auditing : A Case for Public Sector in Kenya

The objective of this study was to assess the current state of continuous auditing in the state departments in Kenya and to adapt a framework to implement continuous auditing by the Public Sector Audit Organization.  Adoption of existing model and survey using questionnaires. Place and Duration of Study: Kenya, 2013.  Existing continuous auditing models were studied and the Integrated Continuous Auditing, Monitoring and Assurance Conceptual Model was adopted for use. The model was tested using data collected using questionnaires. Data was collected from 76 auditors in the Public Sector Audit Organization. A database system of a government Ministry was used to demonstrate how data can be obtained directly from a client system.  The study found the need for training in the skills required for continuous auditing and the acquisition of IT resources and infrastructure were necessary in realizing continuous auditing.  The paper shows that Public Sector Audit Organization in Kenya, like institutions in other countries such as USA [8] and Australia [11], are preparing to advance from traditional audit to continuous auditing. The Integrated Continuous Auditing, Monitoring and Assurance Conceptual Model would offer a good starting point. Original Research Article British Journal of Economics, Management & Trade,  2014 1645
Clinical whole-exome sequencing for the diagnosis of rare disorders with congenital anomalies and/or intellectual disability: substantial interest of prospective annual reanalysis

PurposeCongenital anomalies and intellectual disability (CA/ID) are a major diagnostic challenge in medical genetics—50% of patients still have no molecular diagnosis after a long and stressful diagnostic “odyssey.” Solo clinical whole-exome sequencing (WES) was applied in our genetics center to improve diagnosis in patients with CA/ID.MethodsThis retrospective study examined 416 consecutive tests performed over 3 years to demonstrate the effectiveness of periodically reanalyzing WES data. The raw data from each nonpositive test was reanalyzed at 12 months with the most recent pipeline and in the light of new data in the literature. The results of the reanalysis for patients enrolled in the third year are not yet available.ResultsOf the 416 patients included, data for 156 without a diagnosis were reanalyzed. We obtained 24 (15.4%) additional diagnoses: 12 through the usual diagnostic process (7 new publications, 4 initially misclassified, and 1 copy-number variant), and 12 through translational research by international data sharing. The final yield of positive results was 27.9% through a strict diagnostic approach, and 2.9% through an additional research strategy.ConclusionThis article highlights the effectiveness of periodically combining diagnostic reinterpretation of clinical WES data with translational research involving data sharing for candidate genes.
Saliva-Based Biosensors: Noninvasive Monitoring Tool for Clinical Diagnostics

Saliva is increasingly recognised as an attractive diagnostic fluid. The presence of various disease signalling salivary biomarkers that accurately reflect normal and disease states in humans and the sampling benefits compared to blood sampling are some of the reasons for this recognition. This explains the burgeoning research field in assay developments and technological advancements for the detection of various salivary biomarkers to improve clinical diagnosis, management, and treatment. This paper reviews the significance of salivary biomarkers for clinical diagnosis and therapeutic applications, with focus on the technologies and biosensing platforms that have been reported for screening these biomarkers.
Factors associated with latent fingerprint exclusion determinations.

Exclusion is the determination by a latent print examiner that two friction ridge impressions did not originate from the same source. The concept and terminology of exclusion vary among agencies. Much of the literature on latent print examination focuses on individualization, and much less attention has been paid to exclusion. This experimental study assesses the associations between a variety of factors and exclusion determinations. Although erroneous exclusions are more likely to occur on some images and for some examiners, they were widely distributed among images and examiners. Measurable factors found to be associated with exclusion rates include the quality of the latent, value determinations, analysis minutia count, comparison difficulty, and the presence of cores or deltas. An understanding of these associations will help explain the circumstances under which errors are more likely to occur and when determinations are less likely to be reproduced by other examiners; the results should also lead to improved effectiveness and efficiency of training and casework quality assurance. This research is intended to assist examiners in improving the examination process and provide information to the broader community regarding the accuracy, reliability, and implications of exclusion decisions.
EQ-5D: a measure of health status from the EuroQol Group.

Established in 1987, the EuroQol Group initially comprised a network of international, multilingual and multidisciplinary researchers from seven centres in Finland, the Netherlands, Norway, Sweden and the UK. Nowadays, the Group comprises researchers from Canada, Denmark, Germany, Greece, Japan, New Zealand, Slovenia, Spain, the USA and Zimbabwe. The process of shared development and local experimentation resulted in EQ-5D, a generic measure of health status that provides a simple descriptive profile and a single index value that can be used in the clinical and economic evaluation of health care and in population health surveys. Currently, EQ-5D is being widely used in different countries by clinical researchers in a variety of clinical areas. EQ-5D is also being used by eight out of the first 10 of the top 50 pharmaceutical companies listed in the annual report of Pharma Business (November/December 1999). Furthermore, EQ-5D is one of the handful of measures recommended for use in cost-effectiveness analyses by the Washington Panel on Cost Effectiveness in Health and Medicine. EQ-5D has now been translated into most major languages with the EuroQol Group closely monitoring the process.
Higher-order clustering in networks

A fundamental property of complex networks is the tendency for edges to cluster. The extent of the clustering is typically quantified by the clustering coefficient, which is the probability that a length-2 path is closed, i.e., induces a triangle in the network. However, higher-order cliques beyond triangles are crucial to understanding complex networks, and the clustering behavior with respect to such higher-order network structures is not well understood. Here we introduce higher-order clustering coefficients that measure the closure probability of higher-order network cliques and provide a more comprehensive view of how the edges of complex networks cluster. Our higher-order clustering coefficients are a natural generalization of the traditional clustering coefficient. We derive several properties about higher-order clustering coefficients and analyze them under common random graph models. Finally, we use higher-order clustering coefficients to gain new insights into the structure of real-world networks from several domains.
Hajj crowd management and navigation system: People tracking and location based services via integrated mobile and RFID systems

Yearly there's an influx of over three million Muslims to Makkah., Saudi Arabia to perform Hajj. As this large group of pilgrims move between the different religious sites safety and security becomes an issue of main concern. This research looks into the integration of different mobile technologies to serve the purpose of crowd management., people tracking and location based services. It explores the solution to track the movement of pilgrims via RFID technology. A location aware mobile solution will also be integrated into this. This will be made available to pilgrims with smartphones to enhance the accuracy and tracking time of the pilgrims and provide them with location based services for Hajj.
Computational Analyses of Multilevel Discourse Comprehension

The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework.
Haptics Issues in Virtual Environments

Haptics is a recent enhancement to virtual environments allowing users to “touch” and feel the simulated objects they interact with. Current commercial products allow tactile feedback through desktop interfaces (such as the FEELIt mouse or the PHANToM arm) and dextrous tactile and force feedback at the fingertips through haptic gloves (such as the CyberTouch and the CyberGrasp). Haptics VR programming requires good physical modeling of user interactions, primarily through collision detection, and of object response, such as surface deformation, hard-contact simulation, slippage, etc. It is at present difficult to simulate complex virtual environments that have a realistic behavior. This task is added by the recent introduction of haptic toolkits (such
New Improved Recursive Least-Squares Adaptive-Filtering Algorithms

Two new improved recursive least-squares adaptive-filtering algorithms, one with a variable forgetting factor and the other with a variable convergence factor are proposed. Optimal forgetting and convergence factors are obtained by minimizing the mean square of the noise-free a posteriori error signal. The determination of the optimal forgetting and convergence factors requires information about the noise-free a priori error which is obtained by solving a known L1-L2 minimization problem. Simulation results in system-identification and channel-equalization applications are presented which demonstrate that improved steady-state misalignment, tracking capability, and readaptation can be achieved relative to those in some state-of-the-art competing algorithms.
Generalizing Value Estimation over Timescale

General value functions (GVFs) are an approach to representing models of an agent’s world as a collection of predictive questions. A GVF is defined by: a policy, a prediction target, and a timescale. Traditionally predictions for a given timescale must be specified by the engineer and each timescale learned independently. Here we present γ-nets, a method for generalizing value function estimation over timescale, allowing a given GVF to be trained and queried for any fixed timescale. The key to our approach is to use timescale as one of the network inputs. The prediction target for any fixed timescale is then available at every timestep and we are free to train on any number of timescales. We present preliminary results on a simple test signal. 1. Value Functions and Timescale Reinforcement learning (RL) studies algorithms in which an agent learns to maximize the amount of reward it receives over its lifetime. A key method in RL is the estimation of value — the expected cumulative sum of discounted future rewards (called the return). In loose terms this tells an agent how good it is to be in a particular state. The agent can then learn a policy — a way of behaving — which maximizes the amount of reward received. Sutton et al. (2011) broadened the use of value estimation by introducing general value functions (GVFs), in which value estimates are made of other sensorimotor signals, not just reward. GVFs can be thought of as representing an agent’s model of itself and its environment as a collection of questions about future sensorimotor returns; a predictive representation of state. A GVF is defined by three elements: 1) the policy, 2) the cumulant (the sensorimotor signal to be Department of Computing Science, University of Alberta, Edmonton, Canada Cogitai, Inc., United States. Correspondence to: Craig Sherstan <sherstan@ualberta.ca>, Patrick M. Pilarski <pilarski@ualberta.ca>. Accepted at the FAIM workshop “Prediction and Generative Modeling in Reinforcement Learning”, Stockholm, Sweden, 2018.
Dissecting the Role of Anti-ganglioside Antibodies in Guillain-Barré Syndrome: an Animal Model Approach

Guillain-Barré syndrome (GBS) is an autoimmune polyneuropathy disease affecting the peripheral nervous system (PNS). Most of the GBS patients experienced neurological symptoms such as paresthesia, weakness, pain, and areflexia. There are also combinations of non-neurological symptoms which include upper respiratory tract infection and diarrhea. One of the major causes of GBS is due largely to the autoantibodies against gangliosides located on the peripheral nerves. Gangliosides are sialic acid-bearing glycosphingolipids consisting of a ceramide lipid anchor with one or more sialic acids attached to a neutral sugar backbone. Molecular mimicry between the outer components of oligosaccharide of gangliosides on nerve membrane and lipo-oligosaccharide of microbes is thought to trigger the autoimmunity. Intra-peritoneal implantation of monoclonal ganglioside antibodies secreting hybridoma into animals induced peripheral neuropathy. Recent studies demonstrated that injection of synthesized anti-ganglioside antibodies raised by hybridoma cells into mice initiates immune response against peripheral nerves, and eventually failure in peripheral nerve regeneration. Accumulating evidences indicate that the conjugation of anti-ganglioside monoclonal antibodies to activating FcγRIII present on the circulating macrophages inhibits axonal regeneration. The activation of RhoA signaling pathways is also involved in neurite outgrowth inhibition. However, the link between these two molecular events remains unresolved and requires further investigation. Development of anti-ganglioside antagonists can serve as targeted therapy for the treatment of GBS and will open a new approach of drug development with maximum efficacy and specificity.