nils-herrmann/clean_scirepeval huggingface dataset:
Early Prediction of Student Success : Mining Students Enrolment Data

This paper explores the socio-demographic variables (age, gender, ethnicity, education, work status, and disability) and study environment (course programme and course block), that may influence persistence or dropout of students at the Open Polytechnic of New Zealand. We examine to what extent these factors, i.e. enrolment data help us in pre-identifying successful and unsuccessful students. The data stored in the Open Polytechnic student management system from 2006 to 2009, covering over 450 students who enrolled to 71150 Information Systems course was used to perform a quantitative analysis of study outcome. Based on a data mining techniques (such as feature selection and classification trees), the most important factors for student success and a profile of the typical successful and unsuccessful students are identified. The empirical results show the following: (i) the most important factors separating successful from unsuccessful students are: ethnicity, course programme and course block; (ii) among classification tree growing methods Classification and Regression Tree (CART) was the most successful in growing the tree with an overall percentage of correct classification of 60.5%; and (iii) both the risk estimated by the cross-validation and the gain diagram suggests that all trees, based only on enrolment data are not quite good in separating successful from unsuccessful students. The implications of these results for academic and administrative staff are discussed.
Dietary carbohydrate: relationship to cardiovascular disease and disorders of carbohydrate metabolism

The nature of carbohydrate is of considerable importance when recommending diets intended to reduce the risk of type II diabetes and cardiovascular disease and in the treatment of patients who already have established diseases. Intact fruits, vegetables, legumes and wholegrains are the most appropriate sources of carbohydrate. Most are rich in nonstarch polysaccharides (NSPs) (dietary fibre) and other potentially cardioprotective components. Many of these foods, especially those that are high in dietary fibre, will reduce total and low-density lipoprotein cholesterol and help to improve glycaemic control in those with diabetes. There is no good long-term evidence of benefit when NSPs or other components of wholegrains, fruits, vegetables and legumes are added to functional and manufactured foods. Frequent consumption of low glycaemic index foods has been reported to confer similar benefits, but it is not clear whether such benefits are independent of the dietary fibre content of these foods or the fact that low glycaemic index foods tend to have intact plant cell walls. Furthermore, it is uncertain whether functional and manufactured foods with a low glycaemic index confer the same long-term benefits as low glycaemic index plant-based foods. A wide range of carbohydrate intake is acceptable, provided the nature of carbohydrate is appropriate. Failure to emphasize the need for carbohydrate to be derived principally from wholegrain cereals, fruits, vegetables and legumes may result in increased lipoprotein-mediated risk of cardiovascular disease, especially in overweight and obese individuals who are insulin resistant.
Observing the Effects of Mindfulness-Based Meditation on Anxiety and Depression in Chronic Pain Patients.

People whose chronic pain limits their independence are especially likely to become anxious and depressed. Mindfulness training has shown promise for stress-related disorders.



Chronic pain patients who complained of anxiety and depression and who scored higher than moderate in Hamilton Depression Rating Scale (HDRS) and Hospital Anxiety and Depression Scale (HADS) as well as moderate in Quality of Life Scale (QOLS) were observed for eight weeks, three days a week for an hour of Mindfulness Meditation training with an hour daily home Mindfulness Meditation practice. Pain was evaluated on study entry and completion, and patients were given the Patients' Global Impression of Change (PGIC) to score at the end of the training program.



Forty-seven patients (47) completed the Mindfulness Meditation Training program. Over the year-long observation, patients demonstrated noticeable improvement in depression, anxiety, pain, and global impression of change.



Chronic pain patients who suffer with anxiety and depression may benefit from incorporating Mindfulness Meditation into their treatment plans.
Circuitry and Dynamics of Human Transcription Factor Regulatory Networks

The combinatorial cross-regulation of hundreds of sequence-specific transcription factors (TFs) defines a regulatory network that underlies cellular identity and function. Here we use genome-wide maps of in vivo DNaseI footprints to assemble an extensive core human regulatory network comprising connections among 475 sequence-specific TFs and to analyze the dynamics of these connections across 41 diverse cell and tissue types. We find that human TF networks are highly cell selective and are driven by cohorts of factors that include regulators with previously unrecognized roles in control of cellular identity. Moreover, we identify many widely expressed factors that impact transcriptional regulatory networks in a cell-selective manner. Strikingly, in spite of their inherent diversity, all cell-type regulatory networks independently converge on a common architecture that closely resembles the topology of living neuronal networks. Together, our results provide an extensive description of the circuitry, dynamics, and organizing principles of the human TF regulatory network.
Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review

Analysis and forecasting of sequential data, key problems in various domains of engineering and science, have attracted the attention of many researchers from different communities. When predicting the future probability of events using time series, recurrent neural networks (RNNs) are an effective tool that have the learning ability of feedforward neural networks and expand their expression ability using dynamic equations. Moreover, RNNs are able to model several computational structures. Researchers have developed various RNNs with different architectures and topologies. To summarize the work of RNNs in forecasting and provide guidelines for modeling and novel applications in future studies, this review focuses on applications of RNNs for time series forecasting in environmental factor forecasting. We present the structure, processing flow, and advantages of RNNs and analyze the applications of various RNNs in time series forecasting. In addition, we discuss limitations and challenges of applications based on RNNs and future research directions. Finally, we summarize applications of RNNs in forecasting.
Multinomial Adversarial Networks for Multi-Domain Text Classification

MAN for MDTC. The figure demonstrates the training on a mini-batch of data from one domain. One training iteration consists of one such mini-batch training from each domain. The parameters of Fs, Fd, C are updated together, and the training flows are illustrated by the green arrows. The parameters of D are updated separately, shown in red arrows. Solid lines indicate forward passes while dotted lines are backward passes. JD Fs is the domain loss for Fs, which is anticorrelated with JD (e.g. JD Fs = JD).
Sudden death in individuals in hobble restraints during paramedic transport.

For patient and personnel safety, agitated and violent individuals are sometime physically restrained during out-of-hospital ambulance transport. We report two cases of unexpected death in restrained, agitated individuals while they were being trans-ported by advanced life support ambulance. Both patients had been placed in hobble restraints by law enforcement. At autopsy, toxicologic analysis revealed nonlethal levels of amphetamines in one patient and nonlethal levels of ethanol, cocaine, and amphetamines in the other. In both cases the cause of death was determined to be positional asphyxiation during restraint for excited delirium. Physicians and emergency service personnel should be aware of the potential complications of using physical restraints for control of agitated patients.
Cheilitis Glandularis of Both Lips: Successful Treatment with a Combination of an Intralesional Steroid Injection and Tacrolimus Ointment

Cheilitis glandularis (CG) is an inflammatory condition of unknown cause that predominantly affects the minor salivary glands of the lips. Although a diagnosis of CG is not difficult, its treatment is a challenge. This article highlights the clinical presentation of the disease together with a case of successful management of this disease using a combination of a steroid injection followed by a topical immunosuppressor.
Juvenile generalized pustular psoriasis with IL36RN mutation treated with short-term infliximab.

A 8-year-old Chinese boy with generalized pustular psoriasis (GPP) refractory to cyclosporine and methylprednisolone was treated successfully with two infusions of infliximab 3.3 mg/kg. He remained in remission for 21 months. Direct sequencing of IL36RN gene showed a homozygous mutation, c.115 + 6T>C. Juvenile GPP is a rare severe form of psoriasis occasionally associated with life-threatening complications. Like acitretin, cyclosporine and methotrexate, infliximab has been reported to be effective for juvenile GPP in case reports. However, there is a lack of data in the optimal treatment course of infliximab for juvenile GPP. Prolonged administration of these medications may cause toxic or fatal complications. We suggest that short-term infliximab regimen should be recommended as a choice for acute juvenile GPP refractory to traditional systemic therapies. WBC count and CRP are sensitive parameters to reflect the disease activity and evaluate the effectiveness of treatment. Monitoring CD4 T lymphocyte count, preventing and correcting CD4 lymphocytopenia are important in the treatment course of juvenile GPP.
Botulinum toxin A in the mid and lower face and neck.

Botulinum toxins have been smoothing hyperkinetic lines in the upper face for over 15 years. More recently, their use has widened to include applications in the mid and lower face and neck to smooth, shape, and sculpt, blurring the line between science and art. Their use in the lower face, however, requires a thorough and detailed knowledge of not only facial and cervical anatomy, but also the complex interactions of muscles and the aesthetic and implications of a misplaced injection. Although proper patient selection and injection techniques do not guarantee optimal results, poor selection and techniques almost certainly guarantee disappointing results. In addition to its use as primary procedure, botulinum toxin is also an effective adjunct to other cosmetic procedures, enhancing and prolonging the benefits of surgery, soft tissue augmentation, and laser resurfacing.
Nonlinear Network-Induced Time Delay Systems With Stochastic Learning

This paper presents a new control approach for nonlinear network-induced time delay systems by combining online reset control, neural networks, and dynamic Bayesian networks. We use feedback linearization to construct a nominal control for the system then use reset control and a neural network to compensate for errors due to the time delay. Finally, we obtain a stochastic model of the Networked Control System (NCS) using a Dynamic Bayesian Network (DBN) and use it to design a predictive control. We apply our control methodology to a nonlinear inverted pendulum and evaluate its performance through numerical simulations. We also test our approach with real-time experiments on a dc motor-load NCS with wireless communication implemented using a Ubiquitous Sensor Network (USN). Both the simulation and experimental results demonstrate the efficacy of our control methodology.
Integrating Blockchain, Smart Contract-Tokens, and IoT to Design a Food Traceability Solution

Information asymmetry exists amongst stakeholders in the current food supply chain. Lack of standardization in data format, lack of regulations, and siloed, legacy information systems exasperate the problem. Global agriculture trade is increasing creating a greater need for traceability in the global supply chain. This paper introduces Harvest Network, a theoretical end-to-end, vis a vie “farm-to-fork”, food traceability application integrating the Ethereum blockchain and IoT devices exchanging GS1 message standards. The goal is to create a distributed ledger accessible for all stakeholders in the supply chain. Our design effort creates a basic framework (artefact) for building a prototype or simulation using existing technologies and protocols . The next step is for industry practitioners and researchers to apply AGILE methods for creating working prototypes and advanced projects that bring about greater transparency.
Comparison of single-phase T-type multilevel converters for grid-connected PV systems

Single-phase photovoltaic (PV) energy conversion systems are the main solution for small-scale rooftop PV applications. Some multilevel topologies have been commercialized for PV systems and an they are attractive alternative to implement small-scale rooftop PV applications. Efficiency, reliability, power quality and power losses are important concepts to consider in PV converters. For this reason this paper presents a comparison of four multilevel converter based in the T-type topology proposed by Conergy. The presented control scheme is based in single-phase voltage oriented control and simulation results are presented to provide a preliminary validation of each topology. Finally a summary table with the different features of the converters is provided.
Management of neonatal jaundice

Jaundice is the most common clinical sign in neonatal medicine, but only rarely is it associated with bilirubin neurotoxicity or the harbinger of significant underlying disease. Cases of kernicterus, which should be a never event, are still occurring. Delays in the diagnosis of pathological causes of prolonged jaundice, such as biliary atresia are still resulting in life long morbidity. These are salutary reminders that healthcare professionals should never take neonatal jaundice for granted. Phototherapy remains the mainstay of treatment of significant unconjugated hyperbilirubinaemia, and its optimal use will usually prevent the need for exchange blood transfusion. In cases of antibody-mediated haemolysis high-dose immunoglobulin is indicated if the serum bilirubin is continuing to rise despite multiple phototherapy. For babies with prolonged jaundice investigation should be directed towards making a timely diagnosis and avoiding secondary complications.
Foundation of rf CMOS and SiGe BiCMOS technologies

This paper provides a detailed description of the IBM SiGe BiCMOS and rf CMOS technologies. The technologies provide high-performance SiGe heterojunction bipolar transistors (HBTs) combined with advanced CMOS technology and a variety of passive devices critical for realizing an integrated mixed-signal system-on-a-chip (SoC). The paper reviews the process development and integration methodology, presents the device characteristics, and shows how the development and device selection were geared toward usage in mixed-signal IC development.
A K-fold Method for Baseline Estimation in Policy Gradient Algorithms

The high variance issue in unbiased policy-gradient methods such as VPG and REINFORCE is typically mitigated by adding a baseline. However, the baseline fitting itself suffers from the underfitting or the overfitting problem. In this paper, we develop a K-fold method for baseline estimation in policy gradient algorithms. The parameter K is the baseline estimation hyperparameter that can adjust the bias-variance trade-off in the baseline estimates. We demonstrate the usefulness of our approach via two state-of-the-art policy gradient algorithms on three MuJoCo locomotive control tasks.
Exponential Discriminative Metric Embedding in Deep Learning

With the remarkable success achieved by the Convolutional Neural Networks (CNNs) in object recognition recently, deep learning is being widely used in the computer vision community. Deep Metric Learning (DML), integrating deep learning with conventional metric learning, has set new records in many fields, especially in classification task. In this paper, we propose a replicable DML method, called Include and Exclude (IE) loss, to force the distance between a sample and its designated class center away from the mean distance of this sample to other class centers with a large margin in the exponential feature projection space. With the supervision of IE loss, we can train CNNs to enhance the intra-class compactness and inter-class separability, leading to great improvements on several public datasets ranging from object recognition to face verification. We conduct a comparative study of our algorithm with several typical DML methods on three kinds of networks with different capacity. Extensive experiments on three object recognition datasets and two face recognition datasets demonstrate that IE loss is always superior to other mainstream DML methods and approach the state-of-the-art results.
Totipotency: what it is and what it is not.

There is surprising confusion surrounding the concept of biological totipotency, both within the scientific community and in society at large. Increasingly, ethical objections to scientific research have both practical and political implications. Ethical controversy surrounding an area of research can have a chilling effect on investors and industry, which in turn slows the development of novel medical therapies. In this context, clarifying precisely what is meant by "totipotency" and how it is experimentally determined will both avoid unnecessary controversy and potentially reduce inappropriate barriers to research. Here, the concept of totipotency is discussed, and the confusions surrounding this term in the scientific and nonscientific literature are considered. A new term, "plenipotent," is proposed to resolve this confusion. The requirement for specific, oocyte-derived cytoplasm as a component of totipotency is outlined. Finally, the implications of twinning for our understanding of totipotency are discussed.
A Production Oriented Approach for Vandalism Detection in Wikidata - The Buffaloberry Vandalism Detector at WSDM Cup 2017

Wikidata is a free and open knowledge base from the Wikimedia Foundation, that not only acts as a central storage of structured data for other projects of the organization, but also for a growing array of information systems, including search engines. Like Wikipedia, Wikidata’s content can be created and edited by anyone; which is the main source of its strength, but also allows for malicious users to vandalize it, risking the spreading of misinformation through all the systems that rely on it as a source of structured facts. Our task at the WSDM Cup 2017 was to come up with a fast and reliable prediction system that narrows down suspicious edits for human revision . Elaborating on previous works by Heindorf et al. we were able to outperform all other contestants, while incorporating new interesting features, unifying the programming language used to only Python and refactoring the feature extractor into a simpler and more compact code base.
eview ethamphetamine use : A comprehensive review of molecular , preclinical and linical findings illiam

Methamphetamine (MA) is a highly addictive psychostimulant drug that principally affects the monoamine neurotransmitter systems of the brain and results in feelings of alertness, increased energy and euphoria. The drug is particularly popular with young adults, due to its wide availability, relatively low cost, and long duration of psychoactive effects. Extended use of MA is associated with many health problems that are not limited to the central nervous system, and contribute to increased morbidity and mortality in drug users. Numerous studies, using complementary techniques, have provided evidence that chronic MA use is associated with substantial neurotoxicity and cognitive impairment.
Defect-Oriented Testing and Defective-Part-Level Prediction

0740-7475/01/$10.00  Applying this test pattern set to every manufactured part reduces the fraction of defective parts erroneously sold to customers as defect-free parts. This fraction is referred to as the defect level (DL). However, many IC manufacturers quote defective part level, which is obtained by multiplying the defect level by one million to give the number of defective parts per million. Ideally, we could accurately estimate the defective part level by analyzing the circuit structure, the applied test-pattern set, and the manufacturing yield. If the expected defective part level exceeded some specified value, then either the test pattern set or (in extreme cases) the design could be modified to achieve adequate quality. Although the IC industry widely accepts stuck-at fault detection as a key test-quality figure of merit, it is nevertheless necessary to detect other defect types seen in real manufacturing environments.1,2 For example, designers and test engineers often use stuck-at fault coverage in the Williams-Brown model3 to estimate the defect level of a part:
Polyphase P4 code usage for target detection of pulse radar using Matlab and GNU radio

This paper presents the investigation of polyphase P4 code usage in pulse radar for target detection as part of range resolution. As one of essential parameters in pulse radar, the range resolution is acquired to determine the relative range between two or more close targets in order to be detected as different targets. The generation of phase-coded pulse signal and its processing are performed in Matlabreg; and GNU Radio by utilizing audio waves. From the result, it shows that the phase-coding with polyphase P4 code could provide good compression to the pulse signal. In addition, by making the code longer it generates side lobe level less than −40dB for the code with length of 2000.
Online steering: coordination and control of body center of mass, head and body reorientation

Steering is an integral component of adaptive locomotor behavior. Along with reorientation of gaze and body in the direction of intended travel, body center of mass must be controlled in the mediolateral plane. In this study we examine how these subtasks are sequenced when steering is planned early or initiated under time constraints. Whole body kinematics were monitored as individuals were required to change their direction of travel by varying amounts when visually cued either at the beginning of the walk or one stride before. The analyses focused on the transition stride from one travel direction to another. Timing of changes (with respect to first right foot contact) in trunk roll angle, head and trunk yaw angle, and right foot displacement in the mediolateral plane were analyzed. The magnitude of these measures along with right and left foot placement at the beginning and right foot placement at the end of the transition stride were also analyzed. The results show the CNS uses two mechanisms, foot placement and trunk roll motion (piking action about the hip joint in the frontal plane), to move the center of mass towards the new direction of travel in the transition stride, preferring to use the first option when planning can be done early. Control of body center of mass precedes all other changes and is followed by initiation of head reorientation. Only then is the rest of the body reorientation initiated.