nils-herrmann/clean_scirepeval huggingface dataset:
Internet use and online safety in adults with Williams syndrome.

Individuals with intellectual and developmental disabilities (IDD) increasingly have access to the Internet. Whilst Internet access increases opportunities for social connection for individuals with IDD, it also may increase risk of victimisation. Adults with Williams syndrome (WS), who display an extreme pro-social drive to engage with both familiar and unfamiliar people, might be especially vulnerable to online victimisation. This study first explores how often and why individuals with WS use the Internet and social networking sites. Next, the online vulnerability of individuals with WS is assessed through responses to hypothetical scenarios of potentially dangerous online interactions.



Twenty-eight young adults with WS (mean age = 27.7 years) and their parents completed questionnaires about their Internet and social networking use and parental oversight. Participants with WS then responded to hypothetical scenarios assessing their likelihood to take social and non-social risks online.



Most participants with WS frequently use the Internet and the majority visit social networking sites every day or almost every day, with little parental supervision or oversight. Individuals with WS interact with both known and unknown individuals through social networking sites. Participants are more likely to agree to engage in socially risky behaviours compared to risky behaviours that are not social in nature when online. For example, participants were more likely to agree to meet an 'online friend' in person than they were to give their bank account information for winning a 'contest'.



Individuals with WS, who are a socially vulnerable group in the real world, display behaviours that could also lead to victimisation online as well. As the Internet continues to become more accessible, more research is needed to increase online safety of individuals with WS and other IDDs. Implications for intervention and future research are discussed.
The CAP theorem versus databases with relaxed ACID properties

The CAP theorem combines the three desirable properties C (data consistency), A (data availability), and P (partition-tolerance: tolerance of inconsistencies between data stored in a distributed database where partitions are allowed). The CAP theorem asserts that any distributed system that uses data from different locations can have at most two of the three desirable CAP properties [5]. The NoSQL movement has applied the CAP theorem as an argument against traditional ACID (atomicity, consistency, isolation, and durability) databases, which prioritize consistency and partition-tolerance at the cost of a potentially low availability. Recently, Brewer [4] has modified the CAP theorem, pointing out that all the CAP properties are more or less continuous, and possible to optimize, weighing them against each other., in practice it is possible for an application area to have both relative high availability and sufficient data consistency, despite the presence of network partitions.
 The overall objective of this paper is to improve the CAP optimization methods by using optimization techniques outside of those preferred in CAP optimization literature. The main contribution is to use relaxed ACID properties in the CAP optimization process. This may be viewed as a bridge between the CAP theorem and the traditional ACID theory. Traditional ACID properties are weakened, but not completely dropped, in order to optimize CAP properties. From a user point of view, systems should thus function as if both the traditional ACID properties and all the CAP properties were implemented.
 This optimizing is especially important in mobile integrated databases, where disconnections are normal and frequent. It is also important in distributed databases like EHR (electronic Health Records) where many different hospital locations are involved, since the risk for disconnections increases with the number of participating locations. We use distributed integrated EHR databases as an example where our optimizing method may contribute.
Predicting Domain-Specific Risk Taking With the HEXACO Personality Structure

Although risk taking traditionally has been viewed as a unitary, stable individual difference variable, emerging evidence in behavioral decision-making research suggests that risk taking is a domain-specific construct. Utilizing a psychological risk-return framework that regresses risk taking on the perceived benefits and perceived riskiness of an activity (Weber & Milliman, 1997), this study examined the relations between risk attitude and broad personality dimensions using the new HEXACO personality framework (Lee &Ashton, 2004) across four risk domains. This personality framework, which has been replicated in lexical studies in over 12 natural languages, assess personality over six broad personality dimensions, as opposed to the traditional Five-Factor Model, or ‘‘Big Five.’’ Through path analysis, we regressed risk taking in four separate domains on risk perceptions, perceived benefits, and the six HEXACO dimensions. Across all risk domains, we found that the emotionality dimension was associated with heightened risk perceptions and high conscientiousness was associated with less perceived benefits. We also report several unique patterns of domain-specific relations between the HEXACO dimensions and risk attitude. Specifically, openness was associated with risk taking and perceived benefits for social and recreational risks, whereas lower honesty/humility was associated with greater health/safety and ethical risk taking. These findings extend our understanding of how individuals approach risk across a variety of contexts, and further highlight the utility of honesty/humility, a dimension not recovered in Big Five models, in individual differences research.  Risk taking has traditionally been viewed as an enduring, stable, and domain-invariant construct in both behavioral decision making and personality research (e.g., Eysenck & Eysenck, 1977; Kahneman & Tversky, 1979; Paunonen & Jackson, 1996; Tellegen, 1985). However, recent advances suggest that risk taking is content, or domain, specific (Blais &Weber, 2006; Hanoch, Johnson, &Wilke, 2006; Soane & Chmiel, 2005; Weber, Blais, & Betz, 2002). In light of this knowledge, psychologists would benefit from a deeper ler, Decision Research, Eugene, OR 97401, USA. E-mail: jweller@decisionresearch.org
Design of a CMOS bandgap Reference Circuit with a Wide temperature Range, High Precision and Low temperature coefficient

This paper presents an approach to the design of a high-precision CMOS voltage reference. The proposed circuit is designed for TSMC 0.35 m standard CMOS process. We design the ̄rstorder temperature compensation bandgap voltage reference circuit. The proposed post-simulated circuit delivers an output voltage of 0.596V and achieves the reported temperature coe±cient (TC) of 3.96 ppm/ C within the temperature range from 60 C to 130 C when the supply voltage is 1.8V. When simulated in a smaller temperature range from 40 C to 80 C, the circuit achieves the lowest reported TC of 2.09 ppm/ C. The reference current is 16.586 A. This circuit provides good performances in a wide range of temperature with very small TC.
SDPA: Enhancing Stateful Forwarding for Software-Defined Networking

As the prevailing technique of Software-Defined Networking (SDN), OpenFlow introduces significant programmability, granularity and flexibility for many network applications to effectively manage and process network flows. However, OpenFlow only provides a simple "match-action" paradigm and lacks the function of stateful forwarding for SDN data plane, which limits it to support advanced network applications. Heavily relying on SDN controllers for all state maintenance incurs both scalability and performance issues. In this paper, we propose a novel Stateful Data Plane Architecture (SDPA) for SDN data plane. A co-processing unit, Forwarding Processor (FP), is designed for SDN switches to manage state information through new instructions and state tables. We design and implement an extended OpenFlow protocol to implement the communication between the controller and FP. To demonstrate the practicality and feasibility of our approach, we implement both software and hardware prototypes of SDPA switches, and develop a sample network function chain with stateful firewall, DNS reflection attack defense and NAT applications in one SDPA-based switch. Experimental results show that the SDPA architecture can effectively improve the forwarding efficiency with manageable processing overhead for those applications that need stateful forwarding in SDN-based networks.
The public health risks of media violence: a meta-analytic review.

To conduct a meta-analytic review of studies that examine the impact of violent media on aggressive behavior and to determine whether this effect could be explained through methodological problems inherent in this research field.



A detailed literature search identified peer-reviewed articles addressing media violence effects. Effect sizes were calculated for all studies. Effect sizes were adjusted for observed publication bias.



Publication bias was a problem for studies of aggressive behavior, and methodological problems such as the use of poor aggression measures inflated effect size. Once corrected for publication bias, studies of media violence effects provided little support for the hypothesis that media violence is associated with higher aggression. The corrected overall effect size for all studies was r = .08.



Results from the current analysis do not support the conclusion that media violence leads to aggressive behavior. It cannot be concluded at this time that media violence presents a significant public health risk.
Passivity-Based Controller Design of Grid-Connected VSCs for Prevention of Electrical Resonance Instability

The time delay in the current control loop of a grid-connected voltage-source converter (VSC) may cause destabilization of electrical resonances in the grid or in the VSC's input filter. Instability is prevented if the input admittance of the VSC can be made passive. This paper presents an analytical controller design method for obtaining passivity. The method is equally applicable to single- and three-phase systems, i.e., in the latter case, for both stationary- and synchronous-frame control. Simulations and experiments verify the theoretical results.
Fast unfolding of communities in large networks

We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection method in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2 million customers and by analyzing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad-hoc modular networks.
Discriminative shape from shading in uncalibrated illumination

Estimating surface normals from just a single image is challenging. To simplify the problem, previous work focused on special cases, including directional lighting, known reflectance maps, etc., making shape from shading impractical outside the lab. To cope with more realistic settings, shading cues need to be combined and generalized to natural illumination. This significantly increases the complexity of the approach, as well as the number of parameters that require tuning. Enabled by a new large-scale dataset for training and analysis, we address this with a discriminative learning approach to shape from shading, which uses regression forests for efficient pixel-independent prediction and fast learning. Von Mises-Fisher distributions in the leaves of each tree enable the estimation of surface normals. To account for their expected spatial regularity, we introduce spatial features, including texton and silhouette features. The proposed silhouette features are computed from the occluding contours of the surface and provide scale-invariant context. Aside from computational efficiency, they enable good generalization to unseen data and importantly allow for a robust estimation of the reflectance map, extending our approach to the uncalibrated setting. Experiments show that our discriminative approach outperforms state-of-the-art methods on synthetic and real-world datasets.
A taxonomy for user-healthcare robot interaction

This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it is important that the spurring relationship between robot and patient is well understood.
Automatic colorization of grayscale images using multiple images on the web

Colorization is the process of adding color to monochrome images and video. It is used to increase the visual appeal of images such as old black and white photos, classic movies, and scientific visualizations. Since colorizing grayscale images involves assigning three-dimensional (RGB) pixel values to an image whose elements are characterized by one feature (luminance) only, the colorization problem does not have a unique solution. Hence, human interaction is typically required in the colorization process. Although existing colorization methods attempt to minimize the amount of user intervention, they require users to manually sellect a similar image to the target image or input a set of color seeds for different regions of the target image. In this paper, we present an entirely automatic colorization method using multiple images collected from the Web. The method generates various and natural colorized images from an input monochrome image by using the information of the scene structure.
THD of Closed-Loop Analog PWM Class-D Amplifiers

This paper presents an analytical modeling of the mechanisms of total harmonic distortion (THD) of second-order based single-feedback and double-feedback class-D amplifiers (CDAs). We show that the overall THD in these closed-loop CDAs comprises the THD of their open-loop counterparts reduced by the Loop Gain+1 and the THD due to the combined phase and duty cycle error that is due to feedback, hence unique to closed-loop CDAs. We show that the latter THD can be large and is the dominant THD at high input frequencies ( > 3 kHz), and that the mechanisms therein are the phase and duty cycle errors. By means of double Fourier series analysis, analytical expressions for the harmonic components and thereafter a THD expression for closed-loop CDAs are derived. The derived expressions depict the parameters that affect THD, and are insightful to designers to optimize/vary pertinent parameters to reduce THD. The derived THD expression is verified against HSPICE and on the basis of measurements on a prototype CDA IC and other CDAs realized discretely.
A Coplanar Vivaldi-Style Launcher for Goubau Single-Wire Transmission Lines

In this letter, we present a coplanar Vivaldi-style launcher for single-wire transmission lines (SWTLs), sometimes called Goubau lines. The launcher converts a transverse electromagnetic mode (TEM) mode from a coaxial feed port to the transverse magnetic (TM<inline-formula><tex-math notation="LaTeX">$_{01}$</tex-math></inline-formula>) surface-wave mode supported by the SWTL. The original Goubau design for SWTL launchers uses large horns to enforce the mode conversion. In contrast, the proposed coplanar Vivaldi-type launcher comprises a planar structure with dimensions of 100 mm <inline-formula><tex-math notation="LaTeX">$\times$</tex-math></inline-formula> 150 mm, which is more convenient to install on existing infrastructure, such as power lines, communication wires, structural steel cables, or pipes. The proposed launcher can be used to provide a broadband communication channel for ultrahigh frequency and microwave radio-frequency signals from 0.81 <inline-formula><tex-math notation="LaTeX">$\text{to}$ </tex-math></inline-formula> 2.29 GHz. It has a measured 10 dB return loss bandwidth of 1.39 GHz. The measured line loss with an 8 mm diameter SWTL conductor is approximately 0.19 dB/m at 1.5 GHz, which is comparable to high-quality coaxial cables. We have also shown that multiple launcher pairs can be used back-to-back on the same SWTL conductor to provide isolated communication links. With a launcher separation distance of 250 mm, the measured back-to-back isolation exceeds 30 dB.
Honesty on the Streets : A Natural Field Experiment on Newspaper Purchasing

A publisher uses an honor system for selling a newspaper in the street. The customers are supposed to pay, but they can also pay less than the price or not pay at all. We conduct an experiment to study honesty in this market. The results show that appealing to honesty increases payments, whereas reminding the customers of the legal norm has no effect. Furthermore, appealing to honesty does not affect the behavior of the dishonest. These findings suggest that some people have internalized an honesty norm, whereas others have not, and that the willingness to pay to obey the norm differs among individuals. In a follow-up survey study we find that honesty is associated with family characteristics, self-esteem, social connectedness, trust in the legal system, and compliance with tax regulations.
Combining Residual Networks with LSTMs for Lipreading

We propose an end-to-end deep learning architecture for wordlevel visual speech recognition. The system is a combination of spatiotemporal convolutional, residual and bidirectional Long Short-Term Memory networks. We train and evaluate it on the Lipreading In-The-Wild benchmark, a challenging database of 500-size target-words consisting of 1.28sec video excerpts from BBC TV broadcasts. The proposed network attains word accuracy equal to 83.0%, yielding 6.8% absolute improvement over the current state-of-the-art, without using information about word boundaries during training or testing.
Sketching informal presentations

Informal presentations are a lightweight means for fast and convenient communication of ideas. People communicate their ideas to others on paper and whiteboards, which afford fluid sketching of graphs, words and other expressive symbols. Unlike existing authoring tools that are designed for formal presentations, we created SketchPoint to help presenters design informal presentations via freeform sketching. In SketchPoint, presenters can quickly author presentations by sketching slide content, overall hierarchical structures and hyperlinks. To facilitate the transition from idea capture to communication, a note-taking workspace was built for accumulating ideas and sketching presentation outlines. Informal feedback showed that SketchPoint is a promising tool for idea communication.
Design of orthogonal pulse shapes for communications via semidefinite programming

In digital communications, orthogonal pulse shapes are often used to represent message symbols for transmission through a channel. In this paper, the design of such pulse shapes is formulated as a convex semidefinite programming problem, from which a globally optimal pulse shape can be efficiently found. The formulation is used to design filters that achieve a) the minimal bandwidth for a given filter length; b) the minimal filter length for a given bandwidth; c) the maximal robustness to timing error for a given bandwidth and filter length. Bandwidth is measured either in spectral energy concentration terms or with respect to a spectral mask. The effectiveness of the method is demonstrated by the design of waveforms with substantially improved performance over the “chip” waveforms specified in recent standards for digital mobile telecommunications.
Celebrity face recognition using deep learning

Received May 29, 2018 Revised Jul 30, 2018  2018 Face recognition is one of the well studied problems by researchers in computer visions. Among the challenges of this task are the occurrence of different facial expressions like happy or sad, and different views of the images such as front and side views. This paper experiments a publicly available dataset that consists of 200,000 images of celebrity faces. Deep Learning technique is gaining its popularity in computer vision and this paper applies this technique for face recognition problem. One of the techniques under deep learning is Convolutional Neural Network (CNN). There is also pre-trained CNN models that are AlexNet and GoogLeNet, which produce excellent accuracy results. The experimental results indicate that AlexNet is better than basic CNN and GoogLeNet for face recognition.
Intelligent control of the regenerative braking in an induction motor drive

This work deal with the problem related to the energy recovered in an induction motor drive. During deceleration, a regenerative braking control strategy allows the recovery of the mechanical energy stored in an inertial mass. This process involves the conversion of the kinetic energy into electric energy. The parts that compose the system are a squirrel cage induction motor variable frequency drive and controller and the mechanical system (flywheel) representing the inertia of the automobile. In order to test the performance of the intelligent control, it is compared with a conventional control scheme. The conventional control scheme is used to generate the samples of the input and output signals, which allows the identification of the dynamics of the system (plant). Also, it is used as a reference for the performance of the intelligent control.
Single Cesium Lead Halide Perovskite Nanocrystals at Low Temperature: Fast Single-Photon Emission, Reduced Blinking, and Exciton Fine Structure.

Metal-halide semiconductors with perovskite crystal structure are attractive due to their facile solution processability, and have recently been harnessed very successfully for high-efficiency photovoltaics and bright light sources. Here, we show that at low temperature single colloidal cesium lead halide (CsPbX3, where X = Cl/Br) nanocrystals exhibit stable, narrow-band emission with suppressed blinking and small spectral diffusion. Photon antibunching demonstrates unambiguously nonclassical single-photon emission with radiative decay on the order of 250 ps, representing a significant acceleration compared to other common quantum emitters. High-resolution spectroscopy provides insight into the complex nature of the emission process such as the fine structure and charged exciton dynamics.
Real-Time Hand Gesture Recognition Using Finger Segmentation

Hand gesture recognition is very significant for human-computer interaction. In this work, we present a novel real-time method for hand gesture recognition. In our framework, the hand region is extracted from the background with the background subtraction method. Then, the palm and fingers are segmented so as to detect and recognize the fingers. Finally, a rule classifier is applied to predict the labels of hand gestures. The experiments on the data set of 1300 images show that our method performs well and is highly efficient. Moreover, our method shows better performance than a state-of-art method on another data set of hand gestures.