nils-herrmann/clean_scirepeval huggingface dataset:
The Blink Frequency Relationship between Reading from a Computer Screen and Reading from a Printed Page

One of the components of what has become known as Computer Vision Syndrome (CVS) is a complaint of dry eyes which is not present in other near work situations. The etiology of the dryness is believed to be decreased blink rate and/or a wide palpebral aperture while viewing a computer monitor. This study examined the first theory only, although if the first theory is disproven the second one gains more credence.  There were 31 subjects enrolled in this study. All initially filled out a questionnaire of symptomatology and underwent a series of refractive and ocular examinations in order to exclude those subjects with clinical dry eye or other related ocular conditions. In the second phase each subject read a selection for 10 minutes once from a computer screen and once from a printed page. This experimental phase was conducted in a standard classroom with standard lighting, without internal air conditioning or heating. The order of reading and selected tests was performed randomly during morning hours on consecutive days. The text and angle of gaze was uniform for both sessions, with each condition (computer screen or paper) having its own specific working distance and angle of gaze. The performance was filmed with an internet camera and later the amount of blinking was scored manually.  The number of blinks per minute while reading from a computer screen was greater, on average (1.73 ±0.43) than reading from a printed page. However, this difference was only significant at the p=0.22 level. 18 subjects had a higher blink rate with computer work while 13 had a higher blink rate with a printed page. The subjects with the higher blink rate reading from a computer screen had a higher differential between the two scores.  No significant difference in blink rate was found between the blink rate when reading from computer screen as opposed to a printed page. Even the mildly significant result indicated the opposite. This would indicate that the theory that dry eye associated with computer work is not caused by excessive “staring” and lower blink rate. This gives indirect support to the theory that the height of the computer screen is a more important variable.
Dupilumab for the treatment of asthma.

Dupilumab is a fully human IgG4 monoclonal antibody directed against the α subunit of the interleukin (IL)-4 receptor (IL-4Rα). Since the activation of IL-4Rα is utilized by both IL-4 and IL-13 to mediate their pathophysiological effects, dupilumab behaves as a dual antagonist of these two sister cytokines, which blocks IL-4/IL-13-dependent signal transduction.  They also review: the mechanism of action of dupilumab, the phase I, II and III studies evaluating the pharmacokinetics as well as the safety, tolerability and clinical efficacy of dupilumab in asthma therapy.  Supported by a strategic mechanism of action, as well as by convincing preliminary clinical results, dupilumab currently appears to be a very promising biological drug for the treatment of severe uncontrolled asthma. It also may have benefits to comorbidities of asthma including atopic dermatitis, chronic sinusitis and nasal polyposis.
Data-Driven Techniques in Disaster Information Management

Improving disaster management and recovery techniques is one of national priorities given the huge toll caused by man-made and nature calamities. Data-driven disaster management aims at applying advanced data collection and analysis technologies to achieve more effective and responsive disaster management, and has undergone considerable progress in the last decade. However, to the best of our knowledge, there is currently no work that both summarizes recent progress and suggests future directions for this emerging research area. To remedy this situation, we provide a systematic treatment of the recent developments in data-driven disaster management. Specifically, we first present a general overview of the requirements and system architectures of disaster management systems and then summarize state-of-the-art data-driven techniques that have been applied on improving situation awareness as well as in addressing users’ information needs in disaster management. We also discuss and categorize general data-mining and machine-learning techniques in disaster management. Finally, we recommend several research directions for further investigations.
The geometry of spherical curves and the algebra of quaternions

Contents  Chapter I. The geometry of curves on S 2 3 § 1. The elementary geometry of smooth curves and wavefronts 3 § 2. Contact manifolds, their Legendrian submanifolds and their fronts 9 § 3. Dual curves and derivative curves of fronts 10 § 4. The caustic and the derivatives of fronts 12 Chapter II. Quaternions and the triality theorem 13 § 5. Quaternions and the standard contact structures on the sphere S 3 13 § 6. Quaternions and contact elements of the sphere 5? 15 § 7. The action of quaternions on the contact elements of the sphere 5| 18 § 8. The action of right shifts on left-invariant fields 20 § 9. The duality of j-fronts and fc-fronts of «-Legendrian curves 20 Chapter III. Quaternions and curvatures 22 § 10. The spherical radii of curvature of fronts 22 § 11. Quaternions and caustics 23 § 12. The geodesic curvature of the derivative curve 24 § 13. The derivative of a small curve and the derivative of curvature of the curve 28 Chapter IV. The characteristic chain and spherical indices of a hyper-surface 30 § 14. The characteristic 2-chain 31 § 15. The indices of hypersurfaces on a sphere 33 § 16. Indices as linking coefficients 35 § 17. The indices of hypersurfaces on a sphere as intersection indices 36 § 18. Proofs of the index theorems 38 § 19. The indices of fronts of Legendrian submanifolds on an even-dimensional sphere 40 Chapter V. Exact Lagrangian curves on a sphere and their Maslov indices 44 § 20. Exact Lagrangian curves and their Legendrian lifts 45 V. I. Arnol'd § 21. The integral of a horizontal form as the area of the characteristic chain 48 §22. A horizontal contact form as a Levi-Civita connection and a generalized Gauss-Bonnet formula 49 § 23. Proof of the formula for the Maslov index 52 § 24. The area-length duality 54 §25. The parities of fronts and caustics 56 Chapter VI. The Bennequin invariant and the spherical invariant J + 57 § 26. The spherical invariant J + 58 § 27. The topological meaning of the invariant SJ + 59 Chapter VII. Pseudo-functions 60 §28. The quasi-functions of Chekanov 61 § 29. From quasi-functions on the cylinder to pseudo-functions on the sphere, and conversely 62 § 30. Conjectures concerning pseudo-functions 63 §31. Space curves and Sturm's theorem 66 Bibliography 68
Data analytics for game development: NIER track

The software engineering community has had seminal papers on data analysis for software productivity, quality, reliability, performance etc. Analyses have involved software systems ranging from desktop software to telecommunication switching systems. Little work has been done on the emerging digital game industry. In this paper we explore how data can drive game design and production decisions in game development. We define a mixture of qualitative and quantitative data sources, broken down into three broad categories: internal testing, external testing, and subjective evaluations. We present preliminary results of a case study of how data collected from users of a released game can inform subsequent development.
App-guided exposure and response prevention for obsessive compulsive disorder: an open pilot trial.

Although effective treatments for obsessive-compulsive disorder (OCD) exist, there are significant barriers to receiving evidence-based care. Mobile health applications (Apps) offer a promising way of overcoming these barriers by increasing access to treatment. The current study investigated the feasibility, acceptability, and preliminary efficacy of LiveOCDFree, an App designed to help OCD patients conduct exposure and response prevention (ERP). Twenty-one participants with mild to moderate symptoms of OCD were enrolled in a 12-week open trial of App-guided self-help ERP. Self-report assessments of OCD, depression, anxiety, and quality of life were completed at baseline, mid-treatment, and post-treatment. App-guided ERP was a feasible and acceptable self-help intervention for individuals with OCD, with high rates of retention and satisfaction. Participants reported significant improvement in OCD and anxiety symptoms pre- to post-treatment. Findings suggest that LiveOCDFree is a feasible and acceptable self-help intervention for OCD. Preliminary efficacy results are encouraging and point to the potential utility of mobile Apps in expanding the reach of existing empirically supported treatments.
The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives

In this position paper, we discuss how different branches of research on clustering and pattern mining, while rather different at first glance, in fact have a lot in common and can learn a lot from each other’s solutions and approaches. We give brief introductions to the fundamental problems of different sub-fields of clustering, especially focusing on subspace clustering, ensemble clustering, alternative (as a variant of constraint) clustering, and multiview clustering (as a variant of alternative clustering). Second, we relate a representative of these areas, subspace clustering, to pattern mining. We show that, while these areas use different vocabularies and intuitions, they share common roots and they are exposed to essentially the same fundamental problems; in particular, we detail how certain problems currently faced by the one field, have been solved by the other field, and vice versa. The purpose of our survey is to take first steps towards bridging the linguistic gap between different (sub-) communities and to make researchers from different fields aware of the existence of similar problems (and, partly, of similar solutions or of solutions that could be transferred) in the literature on the other research topic.
A survey of network virtualization

Due to the existence of multiple stakeholders with conflicting goals and policies, alterations to the existing Internet architecture are now limited to simple incremental updates; deployment of any new, radically different technology is next to impossible. To fend off this ossification, network virtualization has been propounded as a diversifying attribute of the future inter-networking paradigm. By introducing a plurality of heterogeneous network architectures cohabiting on a shared physical substrate, network virtualization promotes innovations and diversified applications. In this paper, we survey the existing technologies and a wide array of past and state-of-the-art projects on network virtualization followed by a discussion of major challenges in this area.
The Advanced Compact MOSFET Model and its Application to Inversion Coefficient Based Circuit Design

Contemporary MOSFET mathematical models contain many parameters, most of which have little or no meaning to circuit designers. Designers therefore, continue to use obsolete models -such as the MOSFET square law -for circuit design calculations. However, low-voltage, lowpower systems development demands more advanced circuit design techniques. In this paper I present a brief literature review of MOSFET modeling, which has culminated in the development of the Advanced Compact MOSFET model. Next, I discuss the key ideas and equations of the ACM model, a physically based model with few parameters and equations. Additionally, I show that the ACM model can aid designers in small and large signal circuit analysis in three major respects. First, the ACM model is continuous throughout all regions of operation. Second, terms in ACM model equations appear explicitly in equations that specify circuit performance. Third, the ACM model can aid designers in neglecting MOSFET small signal components that have little influence on circuit performance. Lastly, I conclude with a brief discussion of transconductor linearity, and conclude by mentioning some promising areas of research. The Advanced Compact MOSFET Model and its Application to Inversion Coefficient Based Circuit Design Sean T. Nicolson
Declarative Programming and Knowledge Management

Applying parallelism to constraint solving seems a promising approach and it has been done with varying degrees of success. Early attempts to parallelize constraint propagation, which constitutes the core of traditional interleaved propagation and search constraint solving, were hindered by its essentially sequential nature. Recently, parallelization efforts have focussed mainly on the search part of constraint solving, as well as on local-search based solving. Lately, a particular source of parallelism has become pervasive, in the guise of GPUs, able to run thousands of parallel threads, and they have naturally drawn the attention of researchers in parallel constraint solving. In this paper, we address challenges faced when using multiple devices for constraint solving, especially GPUs, such as deciding on the appropriate level of parallelism to employ, load balancing and inter-device communication, and present our current solutions.
Deep Semantic Architecture with discriminative feature visualization for neuroimage analysis

Neuroimaging data analysis often involves a-priori selection of data features to study the underlying neural activity. Since this could lead to sub-optimal feature selection and thereby prevent the detection of subtle patterns in neural activity, datadriven methods have recently gained popularity for optimizing neuroimaging data analysis pipelines and thereby, improving our understanding of neural mechanisms. In this context, we developed a deep convolutional architecture that can identify discriminating patterns in neuroimaging data and applied it to electroencephalography (EEG) recordings collected from 25 subjects performing a hand motor task before and after a rest period or a bout of exercise. The deep network was trained to classify subjects into exercise and control groups based on differences in their EEG signals. Subsequently, we developed a novel method termed the cue-combination for Class Activation Map (ccCAM), which enabled us to identify discriminating spatio-temporal features within definite frequency bands (23–33 Hz) and assess the effects of exercise on the brain. Additionally, the proposed architecture allowed the visualization of the differences in the propagation of underlying neural activity across the cortex between the two groups, for the first time in our knowledge. Our results demonstrate the feasibility of using deep network architectures for neuroimaging analysis in different contexts such as, for the identification of robust brain biomarkers to better characterize and potentially treat neurological disorders.  Work in progress. ar X iv :1 80 5. 11 70 4v 2 [ qbi o. N C ] 2 9 Ju n 20 18
Grid-connected PV monitoring system (GCPV-MS)

This paper presents the concept and operating principles of a flexible real-time long-term monitoring system for photovoltaic (PV) plants. Compared to traditional solutions which require dedicated hardware and/or specific data logging systems, the monitoring system we propose allows the user to monitor the grid-connected PV system using commercial of the shelf hardware devices and software programs such as LabVIEW and Weather Link software. The proposed system is built around wired/wireless devices and internet of things (IoT) concept. It provides customizable fast, reliable and secure monitoring tool suitable for deployment in PV systems management. The grid-connected PV monitoring system (GCPV-MS) is developed and installed at the University of Huddersfield, United Kingdom. The results obtained from this project indicate how IoT concept can be utilized in remote PV monitoring systems.
Hepatitis B Reactivation With Hepatitis C Treatment: Bringing Some Clarity to the Black Box.

75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 Tthe treatment of chronic hepatitis C virus (HCV) infection has been nothing short of remarkable with the prospect of elimination never more within reach. Attention has shifted to the safety and efficacy of DAAs in special populations, such as hepatitis B virus (HBV)/HCV coinfected individuals. Although the true prevalence of coinfection is unknown, studies from the United States report that 1.4% to 5.8% of HCV-infected individuals are hepatitis B surface antigen (HBsAg) positive compared with 1.4% to 4.1% in China. Coinfection is associated with higher rates of cirrhosis, decompensation, and hepatocellular carcinoma compared with monoinfected individuals. Because HBsAgpositive individuals were excluded from clinical trials of DAAs, HBV reactivation after HCV clearance was only reported after DAAs entered clinical use. Reports of severe and even fatal cases led the US Food and Drug Administration (FDA) to issue a strong directive regarding the risk of HBV reactivation with DAA treatment. The FDA boxed warning was based on 29 cases of HBV reactivation, including 2 fatal events and one that led to liver transplantation. However, owing to the nature of postapproval reporting, critical data were often missing, including baseline HBV serology, making it difficult to truly assess the risk. To err on the safe side, the FDA recommended screening all individuals scheduled to receive DAAs for evidence of current or past HBV infection with follow-up HBV DNA testing for any positive serology. Differing recommendations from international guidelines left clinicians unsure of how to proceed. The study by Liu et al in this issue of Gastroenterology provides much-needed data regarding the risk of HBV reactivation in coinfected individuals treated with DAAs. This prospective study enrolled 111 patients with HBV/ HCV coinfection who received sofosbuvir/ledipasvir for 12 weeks. Notably, although 61% were infected with HCV genotype 1, 39% had genotype 2 infection, a group for whom sofosbuvir/ledipasvir is not currently recommended. All patients achieved sustained virologic response (SVR). More important, the authors carefully evaluated what happened to HBV during and after HCV therapy. Patients were divided into 2 groups: those with undetectable HBV DNA and those with an HBV DNA of >20 IU/mL at baseline. Increases in HBV DNA levels were common in both groups. DNA increased to quantifiable levels in 31 of 37 initially
EMMBTT: A Novel Event Evolution Model Based on TFxIEF and TDC in Tracking News Streams

With the popularity of the Internet, online news media are pouring numerous of news reports into the Internet every day. People get lost in the information explosion. Although the existing methods are able to extract news reports according to key words, and aggregate news reports into stories or events, they just list the related reports or events in order. Moreover, they are unable to provide the evolution relationships between events within a topic, thus people hardly capture the events development vein. In order to mine the underlying evolution relationships between events within the topic, we propose a novel event evolution Model in this paper. This model utilizes TFIEF and Temporal Distance Cost factor (TDC) to model the event evolution relationships. we construct event evolution relationships map to show the events development vein. The experimental evaluation on real dataset show that our technique precedes the baseline technique.
Multi-label Fashion Image Classification with Minimal Human Supervision

We tackle the problem of multi-label classification of fashion images, learning from noisy data with minimal human supervision. We present a new dataset of full body poses, each with a set of 66 binary labels corresponding to the information about the garments worn in the image obtained in an automatic manner. As the automatically-collected labels contain significant noise, we manually correct the labels for a small subset of the data, and use these correct labels for further training and evaluation. We build upon a recent approach that both cleans the noisy labels and learns to classify, and introduce simple changes that can significantly improve the performance.
Learning switched mode power supply design using MATLAB/SIMULINK

Switched Mode Power Supplies (SMPS) have become an indispensable part of modem electronic systems. In this paper, a generalized MATLAB/SIMULINK modeling techniques is presented. The proposed techniques have been successfully integrated into SMPS design course at Lunghua University, Taiwan. The main objective of the course is to teach final year undergraduate students and first year Master's students how to design an SMP in real life. Positive response from students indicates that the proposed technique is useful for SMPS design courses.
Cyberbullying and the law: A review of psychological and legal challenges

Cyberbullying, in its different forms, is common among children and adolescents and is facilitated by the increased use of technology. The consequences of cyberbullying could be severe, especially on mental health, potentially leading to suicide in extreme cases. Although parents, schools and online social networking sites are encouraged to provide a safe online environment, little is known about the legal avenues which could be utilised to prevent cyberbullying or act as a deterrent to such. This article attempts to explore current laws, and the challenges that exist to establishing cyberbullying legislation in the context of the UK. It is arguable that a number of statutes may be of assistance in relation to cyberbullying, namely Education and Inspections Act 2006, Protection from Harassment Act 1997, Communications Act 2003, Telecommunication Act 1988, Public Order Act 1986, Obscene Publications Act 1959, Computer Misuse Act 1990, Crime and Disorder Act 1998, Defamation Act 2013. However, given the lack of clear definition of bullying, the applicability of these laws to cyberbullying is open to debate. Establishing new legislation or a modification to existing laws is particularly challenging for a number of reasons, namely: an absence of consistent bullying/cyberbullying definition, a difficulty in determining intention to harm or evidence of such, a lack of surveillance, a lack of general awareness, issues surrounding jurisdiction, the role of technology, and the age of criminal responsibility. These challenges are elaborated and discussed in this article.
A 1.83 µJ/Classification, 8-Channel, Patient-Specific Epileptic Seizure Classification SoC Using a Non-Linear Support Vector Machine

A non-linear support vector machine (NLSVM) seizure classification SoC with 8-channel EEG data acquisition and storage for epileptic patients is presented. The proposed SoC is the first work in literature that integrates a feature extraction (FE) engine, patient specific hardware-efficient NLSVM classification engine, 96 KB SRAM for EEG data storage and low-noise, high dynamic range readout circuits. To achieve on-chip integration of the NLSVM classification engine with minimum area and energy consumption, the FE engine utilizes time division multiplexing (TDM)-BPF architecture. The implemented log-linear Gaussian basis function (LL-GBF) NLSVM classifier exploits the linearization to achieve energy consumption of 0.39 μ J/operation and reduces the area by 28.2% compared to conventional GBF implementation. The readout circuits incorporate a chopper-stabilized DC servo loop to minimize the noise level elevation and achieve noise RTI of 0.81 μ Vrms for 0.5-100 Hz bandwidth with an NEF of 4.0. The 5 × 5 mm (2) SoC is implemented in a 0.18 μm 1P6M CMOS process consuming 1.83 μ J/classification for 8-channel operation. SoC verification has been done with the Children's Hospital Boston-MIT EEG database, as well as with a specific rapid eye-blink pattern detection test, which results in an average detection rate, average false alarm rate and latency of 95.1%, 0.94% (0.27 false alarms/hour) and 2 s, respectively.