nils-herrmann/clean_scirepeval huggingface dataset:
Social media, social capital, and seniors: The impact of Facebook on bonding and bridging social capital of individuals over 65

Online social networks may be important avenues for building and maintaining social capital as adult’s age. However, few studies have explicitly examined the role online communities play in the lives of seniors. In this exploratory study, U.S. seniors were interviewed to assess the impact of Facebook on social capital. Interpretive thematic analysis reveals Facebook facilitates connections to loved ones and may indirectly facilitate bonding social capital. Awareness generated via Facebook often lead to the sharing and receipt of emotional support via other channels. As such, Facebook acted as a catalyst for increasing social capital. The implication of “awareness” as a new dimension of social capital theory is discussed. Additionally, Facebook was found to have potential negative impacts on seniors’ current relationships due to open access to personal information. Finally, common concerns related to privacy, comfort with technology, and inappropriate content were revealed.
FastQA: A Simple and Efficient Neural Architecture for Question Answering

Recent development of large-scale question answering (QA) datasets triggered a substantial amount of research into end-toend neural architectures for QA. Increasingly complex systems have been conceived without comparison to a simpler neural baseline system that would justify their complexity. In this work, we propose a simple heuristic that guided the development of FastQA, an efficient endto-end neural model for question answering that is very competitive with existing models. We further demonstrate, that an extended version (FastQAExt) achieves state-of-the-art results on recent benchmark datasets, namely SQuAD, NewsQA and MsMARCO, outperforming most existing models. However, we show that increasing the complexity of FastQA to FastQAExt does not yield any systematic improvements. We argue that the same holds true for most existing systems that are similar to FastQAExt. A manual analysis reveals that our proposed heuristic explains most predictions of our model, which indicates that modeling a simple heuristic is enough to achieve strong performance on extractive QA datasets. The overall strong performance of FastQA puts results of existing, more complex models into perspective.
Software Reliability Modeling

1  This chapter proposes an overview of some aspects of Software Reliability (SR) engineering. Most systems are now driven by software. So that, it is well-recognized that assessing reliability of software applications is a major issue in reliability engineering, particularly in terms of cost. But predicting software reliability is not easy. Perhaps the major difficulty is that we are concerned primarily with design faults which is a very different situation from that tackled by the conventional hardware theory. A fault (or bug) refers to the manifestation in the code of a mistake made by the programmer or designer with respect to the specification of the software. Activation of a fault by an input value leads to an incorrect output. Detection of such an event corresponds to an occurrence of a software failure. Input values may be considered as arriving to the software randomly. So although software failure may be not generated stochastically, it may be detected in such a manner. Therefore, this justifies the use of stochastic models of the underlying random process that governs the software failures. We briefly recall in Section 2, basic concepts of stochastic modeling for reliability. Two approaches are used in SR modeling. The prevalent is the so-called black-box one, in which only the interactions of the software with the environment are considered. Following  and , we use in Section 3 the self-exciting point processes as basic tool to model the failure process. That enables an overview of most of published SR models. A second approach, called the white-box one, incorporates in models, information on the structure of the software. This is presented in Section 4. Section 5 proposes basic techniques for calibrating black-box models. The last section tries to give an account for the current practices in SR modeling and to point out some challenging issues for future research. Note that this chapter does not aspire to cover the whole topic of SR engineering. In particular , we do not discuss: fault prevention, fault removal, fault tolerance which are three methods to achieve reliable software. We focus here on methods to forecast failure times. For a more complete view, we refer to , the handbooks  and . We have used the two recent books  and [6] to prepare this chapter. We also recommend to read the short paper , that describes, in particular, the available software reliability toolkits (with additional …
Evidence-based review of interventions for autism used in or of relevance to occupational therapy.

Occupational therapy practitioners are among the professionals who provide services to children and adults with autism spectrum disorder (ASD), embracing both leadership and supportive roles in service delivery. The study's primary aims were as follows: (1) to identify, evaluate, and synthesize the research literature on interventions for ASD of relevance to occupational therapy and (2) to interpret and apply the research literature to occupational therapy. A total of 49 articles met the authors' criteria and were included in the review. Six categories of research topics were identified, the first 3 of which are most closely related to occupational therapy: (1) sensory integration and sensory-based interventions; (2) relationship-based, interactive interventions; (3) developmental skill-based programs; (4) social cognitive skill training; (5) parent-directed or parent-mediated approaches; and (6) intensive behavioral intervention. Under each category, themes supported by research evidence and applicable to occupational therapy were defined. The findings have implications for intervention methods, communication regarding efficacious practices to professionals and consumers, and future occupational therapy research.
Doubly Fed Induction Generator Wind Turbine Systems Subject to Recurring Symmetrical Grid Faults

New grid codes demand the wind turbine systems to ride through recurring grid faults. In this paper, the performance of the doubly Ffed induction generator (DFIG) wind turbine system under recurring symmetrical grid faults is analyzed. The mathematical model of the DFIG under recurring symmetrical grid faults is established. The analysis is based on the DFIG wind turbine system with the typical low-voltage ride-through strategy-with rotor-side crowbar. The stator natural flux produced by the voltage recovery after the first grid fault may be superposed on the stator natural flux produced by the second grid fault, so that the transient rotor and stator current and torque fluctuations under the second grid fault may be influenced by the characteristic of the first grid fault, including the voltage dips level and the grid fault angle, as well as the duration between two faults. The mathematical model of the DFIG under recurring grid faults is verified by simulations on a 1.5-MW DFIG wind turbine system model and experiments on a 30-kW reduced scale DFIG test system.
Design of ultra-low-cost UHF RFID tags for supply chain applications

The availability of inexpensive CMOS technologies that perform well at microwave frequencies has created new opportunities for automated material handling within supply chain management (SCM) that in hindsight, be viewed as revolutionary. This article outlines the system architecture and circuit design considerations that influence the development of radio frequency identification (RFID) tags through a case study involving a high-performance implementation that achieves a throughput of nearly 800 tags/s at a range greater than 10 m. The impact of a novel circuit design approach ideally suited to the power and die area challenges is also discussed. Insights gleaned from first-generation efforts are reviewed as an object lesson in how to make RFID technology for SCM, at a cost measured in pennies per tag, reach its full potential through a generation 2 standard.
Analyzing Android Encrypted Network Traffic to Identify User Actions

Mobile devices can be maliciously exploited to violate the privacy of people. In most attack scenarios, the adversary takes the local or remote control of the mobile device, by leveraging a vulnerability of the system, hence sending back the collected information to some remote web service. In this paper, we consider a different adversary, who does not interact actively with the mobile device, but he is able to eavesdrop the network traffic of the device from the network side (e.g., controlling a Wi-Fi access point). The fact that the network traffic is often encrypted makes the attack even more challenging. In this paper, we investigate to what extent such an external attacker can identify the specific actions that a user is performing on her mobile apps. We design a system that achieves this goal using advanced machine learning techniques. We built a complete implementation of this system, and we also run a thorough set of experiments, which show that our attack can achieve accuracy and precision higher than 95%, for most of the considered actions. We compared our solution with the three state-of-the-art algorithms, and confirming that our system outperforms all these direct competitors.
A vision of smarter cities How cities can lead the way into a prosperous and sustainable future

Tamara Kulesa: Hello. This is Tamara Kulesa, Worldwide Marketing Manager for IBM Global Business Services for the Global Government Industry. I am here today with Susanne Dirks, Manager of the IBM Institute for Business Values Global Center for Economic Development in Ireland. Susanne is responsible for the research and writing of the newly published report, "A Vision of Smarter Cities: How Cities Can Lead the Way into a Prosperous and Sustainable Future." Susanne, thank you for joining me today.
Evolutionary Dynamics of Multi-Agent Learning: A Survey

The interaction of multiple autonomous agents gives rise to highly dynamic and nondeterministic environments, contributing to the complexity in applications such as automated financial markets, smart grids, or robotics. Due to the sheer number of situations that may arise, it is not possible to foresee and program the optimal behaviour for all agents beforehand. Consequently, it becomes essential for the success of the system that the agents can learn their optimal behaviour and adapt to new situations or circumstances. The past two decades have seen the emergence of reinforcement learning, both in single and multiagent settings, as a strong, robust and adaptive learning paradigm. Progress has been substantial, and a wide range of algorithms are now available. An important challenge in the domain of multi-agent learning is to gain qualitative insights into the resulting system dynamics. In the past decade, tools and methods from evolutionary game theory have been successfully employed to study multi-agent learning dynamics formally in strategic interactions. This article surveys the dynamical models that have been derived for various multi-agent reinforcement learning algorithms, making it possible to study and compare them qualitatively. Furthermore, new learning algorithms that have been introduced using these evolutionary game theoretic tools are reviewed. The evolutionary models can be used to study complex strategic interactions. Examples of such analysis are given for the domains of automated trading in stock markets and collision avoidance in multi-robot systems. The paper provides a roadmap on the progress that has been achieved in analysing the evolutionary dynamics of multi-agent learning by highlighting the main results and accomplishments.
An Online Transformerless Uninterruptible Power Supply (UPS) System With a Smaller Battery Bank for Low-Power Applications

Uninterruptible power supplies (UPS) are widely used to provide reliable and high-quality power to critical loads in all grid conditions. This paper proposes a nonisolated online UPS system. The proposed system consists of bridgeless PFC boost rectifier, battery charger/discharger, and an inverter. A new battery charger/discharger has been implemented which ensures the bidirectional flow of power between dc link and battery bank, reducing the battery bank voltage to only 24V, and regulates the dc-link voltage during the battery power mode. Operating batteries in parallel improves the battery performance and resolve the problems related to conventional battery banks that arrange batteries in series. A new control method, integrating slide mode and proportional-resonant control, for the inverter has been proposed which regulates the output voltage for both linear and nonlinear loads. The controller exhibits excellent performance during transients and step changes in load. The operating principle and experimental results of 1-kVA prototype have been presented for validation of the proposed system.
The Adverse Effects of Code Duplication in Machine Learning Models of Code

The field of big code relies on mining large corpora of code to perform some learning task. A significant threat to this approach has been recently identified by Lopes et al.  who found a large amount of near-duplicate code on GitHub. However, the impact of code duplication has not been noticed by researchers devising machine learning models for source code. In this article, we study the effect of code duplication to machine learning models showing that reported metrics are sometimes inflated by up to 100% when testing on duplicated code corpora compared to the performance on de-duplicated corpora which more accurately represent how machine learning models of code are used by software engineers. We present an “errata” for widely used datasets, list best practices for collecting code corpora and evaluating machine learning models on them, and release tools to help the community avoid this problem in
"These are not my hands!": Effect of Gender on the Perception of Avatar Hands in Virtual Reality

Rendering the user's body in virtual reality increases immersion and presence the illusion of "being there". Recent technology enables determining the pose and position of the hands to render them accordingly while interacting within the virtual environment. Virtual reality applications often use realistic male or female hands, mimic robotic hands, or cartoon hands. However, it is unclear how users perceive different hand styles. We conducted a study with 14 male and 14 female participants in virtual reality to investigate the effect of gender on the perception of six different hands. Quantitative and qualitative results show that women perceive lower levels of presence while using male avatar hands and male perceive lower levels of presence using non-human avatar hands. While women dislike male hands, men accept and feel presence with avatar hands of both genders. Our results highlight the importance of considering the users' diversity when designing virtual reality experiences.
Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet.

How do Shai et al. (July 17 issue)1 explain why the subjects in their study regained weight between month 6 and month 24, despite a reported reduction of 300 to 600 calories per day? Contributing possibilities may include the notion that a food-frequency questionnaire cannot precisely determine energy or macronutrient intake but, rather, ascertains general dietary patterns. Certain populations may underreport intake2,3 and have a decreased metabolic rate. The authors did not measure body composition, which is critical for documenting weight-loss components. In addition, the titles of the diets that are described in the article are misleading. Labeling the “low-carbohydrate” diet as such is questionable, since 40 to 42% of calories were from carbohydrates from month 6 to month 24, and data regarding ketosis support this view. Participants in the low-fat and Mediterranean-diet groups consumed between 30% and 33% of calories from fat and did not increase fiber consumption, highlighting the importance of diet quality. Furthermore, the authors should have provided baseline values and P values for within-group changes from baseline (see Table 2 of the article). Contrary to the authors’ assertion, it is not surprising that the effects on many biomarkers were minimal, since the dietary changes were minimal. The absence of biologically significant weight loss (2 to 4% after 2 years) highlights the fact that energy restriction and weight loss in themselves may minimally affect metabolic outcomes and that lifestyle changes must incorporate physical activity to optimize the reduction in the risk of chronic disease.4,5 Christian K. Roberts, Ph.D. R. James Barnard, Ph.D. Daniel M. Croymans, B.S.
Blockchain based smart contract for bidding system

Because of the popularity of the Internet, the integration services have gradually changed people daily life, such as e-commerce activities on transactions, transportation and so on. The E-auction, one of the popular e-commerce activities, allows bidders to directly bid the products over the Internet. As for sealed bid, the extra transaction cost is required for the intermediaries because the third-party is the important role between the buyers and the sellers help to trade both during the auction. In addition, it never guarantees whether the third-party is trust. To resolve the problems, the blockchain technology with low transaction cost is used to develop the smart contract of public bid and sealed bid. The smart contract, proposed in 1990 and implements via Ethereum platform, can ensure the bill secure, private, non-reputability and inalterability owing to all the transactions are recorded in the same but decentralized ledgers. The smart contract is composed of the address of Auctioneer, the start auction time, deadline, the address of current winner, the current highest price. In the experiments, the accounts are created through Ethereum wallet. In miner stage, the MinerGate is used in miner stage for obtaining money to pay the transaction fee. At recorder stage, the nodes of blockchain are synchronized to generate smart contract.
Towards Bidirectional Hierarchical Representations for Attention-Based Neural Machine Translation

This paper proposes a hierarchical attentional neural translation model which focuses on enhancing source-side hierarchical representations by covering both local and global semantic information using a bidirectional tree-based encoder. To maximize the predictive likelihood of target words, a weighted variant of an attention mechanism is used to balance the attentive information between lexical and phrase vectors. Using a tree-based rare word encoding, the proposed model is extended to sub-word level to alleviate the out-of-vocabulary (OOV) problem. Empirical results reveal that the proposed model significantly outperforms sequence-to-sequence attention-based and tree-based neural translation models in English-Chinese translation tasks.
Fabrication of linear Fresnel lens using UV embossing and a micromachined roller mold

Roll-to-roll embossing is able to produce functional optical films with high throughput and lower cost, compared to other conventional manufacturing technologies such like injection molding. In roll-to-roll ultraviolet (UV) embossing, the functional microstructures on an optical film are directly replicated from a high-precision roller mold; the roller mold requires strict control of profile accuracy and optical surface quality which have to be achieved using ultra-precision machining technology. In this study, optical films with linear Fresnel lens array have been developed by using ultra-precision diamond tuning for mold fabrication and roll-to-roll UV embossing for transferring the features from mold to the flexible plastic substrates. The roller mould for making Fresnel lens array was designed in such a way that one Fresnel lens was composed of 166 tiny prisms and all prisms have an equal-feature-height of 0.1 mm, resulting in a focal length of 82.5 mm. With the optimized roll-to-roll UV embossing process, the Fresnel lens film produced in large area demonstrated strong light concentration effect on a solar simulation system, with light intensity increased by more than 6 times.
An empirical study of the effect of outliers on the misclassification error rate

An outlier is an observation that deviates so much from other observations that it seems to have been generated by a different mechanism. Outlier detection has many applications, such as data cleaning, fraud detection and network intrusion. The existence of outliers can indicate individuals or groups that exhibit a behavior that is very different from most of the individuals of the data set. Frequently, outliers are removed to improve accuracy of estimators, but sometimes, the presence of an outlier has a certain meaning, which explanation can be lost if the outlier is deleted. In this paper we study the effect of the presence of outliers on the performance of three well-known classifiers based on the results observed on four real world datasets. We use detection of outliers based on robust statistical estimators of the center and the covariance matrix for the Mahalanobis distance, detection of outliers based on clustering using the partitioning around medoids (PAM) algorithm, and two data mining techniques to detect outliers: Bay’s algorithm for distance-based outliers, and the LOF, a density-based local outlier algorithm.
Therac 25: A New Medical Accelerator Concept

An electron linear accelerator system with several novel features has been developed for radiation therapy. The beam from a 25 cell S-band standing wave structure, operated in the ¿/2 mode with on-axis couplers, is reflected in an achromatic isochronous magnet and reinjected into the accelerator. The second pass doubles the energy while conserving rf power and minimizing the overall length of the unit. The beam is then transported through an annular electron gun and bent into the collimator by an innovative two-element doubly achromatic doubly focusing 270° magnet which allows a significant reduction in unit height. The energy is reduced by adjusting the position of the reflecting magnet with respect to the accelerator. The system generates 5 Gy m2min-1 beams of 25 MV photons and 5 to 25 MeV electrons. Extensive use of tungsten shielding minimizes neutron leakage. The photon mode surface dose is reduced by a carefully optimized electron filter. An improved scanning system gives exceptionally low electron -mode photon contamination.
Let your preference be your guide? Preferences and choices are more tightly linked for North Americans than for Indians.

Using experimental paradigms from economics and social psychology, the authors examined the cross-cultural applicability of 3 widely held assumptions about preference and choice: People (a) recruit or construct preferences to make choices; (b) choose according to their preferences; and (c) are motivated to express their preferences in their choices. In 6 studies, they compared how middle-class North American and Indian participants choose among consumer products. Participants in both contexts construct nonrandom preferences at similar speeds. Those in Indian contexts, however, are slower to make choices, less likely to choose according to their personal preferences, and less motivated to express their preferences in their choices. The authors infer that the strong link between preferences and choices observed among North Americans is not a universal feature of human nature. Instead, this link reflects the disjoint model of agency, which prescribes that people should choose freely on the basis of their preferences. In contrast, Indian contexts reflect and promote a conjoint model of agency, according to which agency is responsive to the desires and expectations of important others and may require restraining one's preferences.