nils-herrmann/clean_scirepeval huggingface dataset:
Recovery of natural antioxidants from spent coffee grounds.

Spent coffee grounds (SCG) were extracted with an environmentally friendly procedure and analyzed to evaluate the recovery of relevant natural antioxidants for use as nutritional supplements, foods, or cosmetic additives. SCG were characterized in terms of their total phenolic content by the Folin-Ciocalteu procedure and antioxidant activity by the DPPH scavenging assay. Flavonoid content was also determined by a colorimetric assay. The total phenolic content was strongly correlated with the DPPH scavenging activity, suggesting that phenolic compounds are mainly responsible for the antioxidant activity of SCG. An UHPLC-PDA-TOF-MS system was used to separate, identify, and quantify phenolic and nonphenolic compounds in the SCG extracts. Important amounts of chlorogenic acids (CGA) and related compounds as well as caffeine (CAF) evidenced the high potential of SCG, a waste material that is widely available in the world, as a source of natural phenolic antioxidants.
Intelligent Interfaces for Information Retrieval A Review

An intelligent interface for an information retrieval system has the aims of controlling an underlying information retrieval system di rectly interacting with the user and allowing him to retrieve relevant information without the support of a human intermediary Developing intelligent interfaces for information retrieval is a di cult activity and no well established models of the functions that such systems should possess are available Despite of this di culty many intelligent in terfaces for information retrieval have been implemented in the past years This paper surveys these systems with two aims to stand as a useful entry point for the existing literature and to sketch an ana lysis of the functionalities that an intelligent interface for information retrieval has to possess
1 8 Ethernet Passive Optical Network ( EPON )

In recent years the telecommunications backbone has experienced substantial growth; however, little has changed in the access network. The tremendous growth of Internet traffic has accentuated the aggravating lag of access network capacity. The “last mile” still remains the bottleneck between high-capacity Local Area Networks (LANs) and the backbone network. The most widely deployed “broadband” solutions today are Digital Subscriber Line (DSL) and cable modem (CM) networks. Although they are an improvement compared to 56 Kbps dial-up lines, they are unable to provide enough bandwidth for emerging services such as Video-On-Demand (VoD), interactive gaming or two-way video conferencing. A new technology is required; one that is inexpensive, simple, scalable, and capable of delivering bundled voice, data and video services to an end-user over a single network. Ethernet Passive Optical Networks (EPONs), which represent the convergence of low-cost Ethernet equipment and low-cost fiber infrastructure, appear to be the best candidate for the next-generation access network.
Road detection using support vector machine based on online learning and evaluation

Road detection is an important problem with application to driver assistance systems and autonomous, self-guided vehicles. The focus of this paper is on the problem of feature extraction and classification for front-view road detection. Specifically, we propose using Support Vector Machines (SVM) for road detection and effective approach for self-supervised online learning. The proposed road detection algorithm is capable of automatically updating the training data for online training which reduces the possibility of misclassifying road and non-road classes and improves the adaptability of the road detection algorithm. The algorithm presented here can also be seen as a novel framework for self-supervised online learning in the application of classification-based road detection algorithm on intelligent vehicle.
Incremental Natural Language Processing: Challenges, Strategies, and Evaluation

Incrementality is ubiquitous in human-human interaction and beneficial for human-computer interaction. It has been a topic of research in different parts of the NLP community, mostly with focus on the specific topic at hand even though incremental systems have to deal with similar challenges regardless of domain. In this survey, I consolidate and categorize the approaches, identifying similarities and differences in the computation and data, and show trade-offs that have to be considered. A focus lies on evaluating incremental systems because the standard metrics often fail to capture the incremental properties of a system and coming up with a suitable evaluation scheme is non-trivial. Title and Abstract in German Inkrementelle Sprachverarbeitung: Herausforderungen, Strategien und Evaluation Inkrementalität ist allgegenwärtig in Mensch-Mensch-Interaktiton und hilfreich für MenschComputer-Interaktion. In verschiedenen Teilen der NLP-Community wird an Inkrementalität geforscht, zumeist fokussiert auf eine konkrete Aufgabe, obwohl sich inkrementellen Systemen domänenübergreifend ähnliche Herausforderungen stellen. In diesem Überblick trage ich Ansätze zusammen, kategorisiere sie und stelle Ähnlichkeiten und Unterschiede in Berechnung und Daten sowie nötige Abwägungen vor. Ein Fokus liegt auf der Evaluierung inkrementeller Systeme, da Standardmetriken of nicht in der Lage sind, die inkrementellen Eigenschaften eines Systems einzufangen und passende Evaluationsschemata zu entwickeln nicht einfach ist.
Designing a Fuzzy Rule Based Expert System for Cyber Security

The topic of cyber security has been subject to more attention and interest outside the community of computer security experts. Cyber security is not a single problem, but rather it is a group of highly different problems involving different sets of threats. Fuzzy Rule based system for cyber security is a system that consists of a rule depository and a mechanism for accessing and running the rules. The depository is usually constructed with a collection of related rule sets. The aim of this study is to develop a fuzzy rule based technical indicator for cyber security with the use of an expert system which is named FRBCES (Fuzzy Rule Based Cyber Expert System). Rule based systems employ fuzzy rule to automate complex processes. Common cyber threats assumed for cyber experts are used as linguistic variables in this paper. KeywordsCyber security, cyber terrorism, fuzzy logic, fuzzy rules, Fuzzy Rule Based Cyber Expert System (FRBCES).
A loss combination based deep model for person re-identification

The Convolutional Neural Network (CNN) has significantly improved the state-of-the-art in person re-identification (re-ID). In the existing available identification CNN model, the softmax loss function is employed as the supervision signal to train the CNN model. However, the softmax loss only encourages the separability of the learned deep features between different identities. The distinguishing intra-class variations have not been considered during the training process of CNN model. In order to minimize the intra-class variations and then improve the discriminative ability of CNN model, this paper combines a new supervision signal with original softmax loss for person re-ID. Specifically, during the training process, a center of deep features is learned for each pedestrian identity and the deep features are subtracted from the corresponding identity centers, simultaneously. So that, the deep features of the same identity to the center will be pulled efficiently. With the combination of loss functions, the inter-class dispersion and intra-class aggregation can be constrained as much as possible. In this way, a more discriminative CNN model, which has two key learning objectives, can be learned to extract deep features for person re-ID task. We evaluate our method in two identification CNN models (i.e., CaffeNet and ResNet-50). It is encouraging to see that our method has a stable improvement compared with the baseline and yields a competitive performance to the state-of-the-art person re-ID methods on three important person re-ID benchmarks (i.e., Market-1501, CUHK03 and MARS).
Infantile and congenital hemangiomas.

Infantile hemangiomas (IHs) are the most common benign vascular tumors of infancy. Since they predominantly involute without significant residua, the majority do not require treatment. Indications for intervention include ulceration, prevention of disfigurement, and impairment of function or vital structures. Some IHs have associated structural anomalies. When and which IH to treat requires knowledge of the natural history and clinical findings of increased risk. Congenital hemangiomas (CHs) are fully formed at birth. They also differ from IHs in their histological and immunohistochemical findings and thus represent a distinct clinical entity. Their clinical characteristics and management are also discussed.
Once a Treg, always a Treg?

Regulatory T cells (Tregs) prevail as a specialized cell lineage that has a central role in the dominant control of immunological tolerance and maintenance of immune homeostasis. Thymus-derived Tregs (tTregs) and their peripherally induced counterparts (pTregs) are imprinted with unique Forkhead box protein 3 (Foxp3)-dependent and independent transcriptional and epigenetic characteristics that bestows on them the ability to suppress disparate immunological and non-immunological challenges. Thus, unidirectional commitment and the predominant stability of this regulatory lineage is essential for their unwavering and robust suppressor function and has clinical implications for the use of Tregs as cellular therapy for various immune pathologies. However, recent studies have revealed considerable heterogeneity or plasticity in the Treg lineage, acquisition of alternative effector or hybrid fates, and promotion rather than suppression of inflammation in extreme contexts. In addition, the absolute stability of Tregs under all circumstances has been questioned. Since these observations challenge the safety and efficacy of human Treg therapy, the issue of Treg stability versus plasticity continues to be enthusiastically debated. In this review, we assess our current understanding of the defining features of Foxp3(+) Tregs, the intrinsic and extrinsic cues that guide development and commitment to the Treg lineage, and the phenotypic and functional heterogeneity that shapes the plasticity and stability of this critical regulatory population in inflammatory contexts.
Deep multilayer network for automatic targeting system of gun turret

Military vehicles are important part to maintain territories of a country. Military vehicle is often equipped with a gun turret mounted on top of the vehicle. Traditionally, gun turret is operated manually by an operator sitting on the vehicle. With the advance of current robotic technology an automatic operation of gun turret is highly possible. Notable works on automatic gun turret tend to use features that are manually designed as an input to a classifier for target tracking. These features can cause less optimal parameters and require highly complex kinematic and dynamic analysis specific to a particular turret. In this paper, toward the goal of realizing an automatic targeting system of gun turret, a gun turret simulation system is developed by leveraging fully connected network of deep learning using only visual information from a camera. It includes designing convolutional layers to accurately detect and tracking a target with input from a camera. All network parameters are automatically and jointly learned without any human intervention, all network parameters are driven purely by data. This method also requires less kinematic and dynamic model. Experiments show encouraging results that the automatic targeting system of gun turret using only a camera can benefit research in the related fields.
An Analysis of Introductory Programming Courses at UK Universities

In the context of exploring the art, science and engineering of programming, the question of which programming languages should be taught first has been fiercely debated since computer science teaching started in universities. Failure to grasp programming readily almost certainly implies failure to progress in computer science. What first programming languages are being taught? There have been regular national-scale surveys in Australia and New Zealand, with the only US survey reporting on a small subset of universities. This the first such national survey of universities in the UK.  We report the results of the first survey of introductory programming courses (N = 80) taught at UK universities as part of their first year computer science (or related) degree programmes, conducted in the first half of 2016. We report on student numbers, programming paradigm, programming languages and environment/tools used, as well as the underpinning rationale for these choices.  The results in this first UK survey indicate a dominance of Java at a time when universities are still generally teaching students who are new to programming (and computer science), despite the fact that Python is perceived, by the same respondents, to be both easier to teach as well as to learn.  We compare the results of this survey with a related survey conducted since 2010 (as well as earlier surveys from 2001 and 2003) in Australia and New Zealand.  This survey provides a starting point for valuable pedagogic baseline data for the analysis of the art, science and engineering of programming, in the context of substantial computer science curriculum reform in UK schools, as well as increasing scrutiny of teaching excellence and graduate employability for UK universities.
An Improved Intrusion Detection Algorithm Based on GA and SVM

In the era of big data, with the increasing number of audit data features, human-centered smart intrusion detection system performance is decreasing in training time and classification accuracy, and many support vector machine (SVM)-based intrusion detection algorithms have been widely used to identify an intrusion quickly and accurately. This paper proposes the FWP-SVM-genetic algorithm (GA) (feature selection, weight, and parameter optimization of support vector machine based on the genetic algorithm) based on the characteristics of the GA and the SVM algorithm. The algorithm first optimizes the crossover probability and mutation probability of GA according to the population evolution algebra and fitness value; then, it subsequently uses a feature selection method based on the genetic algorithm with an innovation in the fitness function that decreases the SVM error rate and increases the true positive rate. Finally, according to the optimal feature subset, the feature weights and parameters of SVM are simultaneously optimized. The simulation results show that the algorithm accelerates the algorithm convergence, increases the true positive rate, decreases the error rate, and shortens the classification time. Compared with other SVM-based intrusion detection algorithms, the detection rate is higher and the false positive and false negative rates are lower.
Matching Convolutional Neural Networks without Priors about Data

We propose an extension of Convolutional Neural Networks (CNNs) to graph-structured data, including strided convolutions and data augmentation defined from inferred graph translations. Our method matches the accuracy of state-of-the-art CNNs when applied on images, without any prior about their 2D regular structure. On fMRI data, we obtain a significant gain in accuracy compared with existing graph-based alternatives.
HaptoMime: mid-air haptic interaction with a floating virtual screen

We present HaptoMime, a mid-air interaction system that allows users to touch a floating virtual screen with hands-free tactile feedback. Floating images formed by tailored light beams are inherently lacking in tactile feedback. Here we propose a method to superpose hands-free tactile feedback on such a floating image using ultrasound. By tracking a fingertip with an electronically steerable ultrasonic beam, the fingertip encounters a mechanical force consistent with the floating image. We demonstrate and characterize the proposed transmission scheme and discuss promising applications with an emphasis that it helps us 'pantomime' in mid-air.
Representations of Buddhism in Ondaatje's Anil's Ghost

Marlene Goldman suggests in her paper "Representations of Buddhism in Ondaatje's Anil's Ghost" that at first glance Ondaatje appears to promote the idea of a Sri Lankan Buddhist faith as transcending history. Ondaatje introduces the subject of Buddhism early on in the novel, emphasizing initially the devastation wrought by imperial and colonial forces. Goldman, however, argues that subsequent references to Buddhism undermine the initial portrayal of a religion besieged by external imperialist forces. For example, at one point, the character Palipana refers to the assassination of his brother, Narada, a Buddhist monk. Narada was possibly the victim of a "political killing" and rumours suggest he was killed by a novice and thus his death recalls the historical connection between the JVP (termed "the antigovernment insurgents" in the novel) and young Buddhist monks. Goldman argues that rather than offering a sanitized account that ignores Buddhism's enmeshment in politics, Ondaatje's novel addresses the complex relationship between religion, politics, and violence in Sri Lanka. Marlene Goldman, "Representations of Buddhism in Ondaatje's Anil's Ghost" page 2 of 9 CLCWeb: Comparative Literature and Culture 6.3 (2004): <http://docs.lib.purdue.edu/clcweb/vol6/iss3/4>
Convergence and Consistency Analysis for a 3-D Invariant-EKF SLAM

In this letter, we investigate the convergence and consistency properties of an invariant-extended Kalman filter (RI-EKF) based simultaneous localization and mapping (SLAM) algorithm. Basic convergence properties of this algorithm are proven. These proofs do not require the restrictive assumption that the Jacobians of the motion and observation models need to be evaluated at the ground truth. It is also shown that the output of RI-EKF is invariant under any <italic>stochastic rigid body transformation</italic> in contrast to <inline-formula><tex-math notation="LaTeX"> $\mathbb {SO}(3)$</tex-math></inline-formula> based EKF SLAM algorithm (<inline-formula><tex-math notation="LaTeX"> $\mathbb {SO}(3)$</tex-math></inline-formula>-EKF) that is only invariant under <italic>deterministic rigid body transformation</italic>. Implications of these invariance properties on the consistency of the estimator are also discussed. Monte Carlo simulation results demonstrate that RI-EKF outperforms <inline-formula> <tex-math notation="LaTeX">$\mathbb {SO}(3)$</tex-math></inline-formula>-EKF, Robocentric-EKF and the “First Estimates Jacobian” EKF, for three-dimensional point feature-based SLAM.
Cytogenetic studies of Hynobiidae (Urodela). XIV. Analysis of the chromosome of a Chinese salamander, Batrachuperus pinchonii (David)

The chromosome number of a Chinese salamander, Batrachuperus pinchonii, was re-examined. Adults and embryonic specimens had a diploid number of 66, with 33 bivalents during meiosis, in contrast to previous reported results. Furthermore, when C-banding analysis was performed with embryos, chromosomes with banding patterns homoeologous to those of Salamandrella keyserlingii and Hynobius species were found. It appears, therefore, that Batrachuperus, Salamandrella and Hynobius might be derived from a common ancestral species in eastern Asia.
Miniaturization of FBAR duplexer using PCB embedded high Q spiral inductors

In this paper, extremely miniaturized film bulk acoustic resonator (FBAR) duplexer was newly designed and fabricated for advanced mobile/wireless applications by using PCB embedded vertically stacked high Q spiral inductors. Proposed FBAR duplexer was comprised of FBAR Tx/Rx filters and PCB embedded shunt high Q inductors. The fabricated FBAR duplexer has insertion loss of −3.0 dBMax in pass-band and absolute attenuation of −41 dBmin at transmitter to antenna ports, while it has insertion loss of −3.4 dBMax in pass-band and absolute attenuation of −51 dBmin at antenna to receiver ports. The simulation and measurement of the fabricated FBAR duplexer were well-matched, respectively. The fabricated duplexer has a size of 3.0 mm × 2.5 mm which is the smallest in the reported ones so far. Since it has excellent performance characteristics and small size/volume, it can be directly applied for US-PCS handsets.
Optimization of high density interconnections (HDI) printed circuit boards robustness

This document provides a first "how-to" guide for modelling thermo-mechanical behaviour of an HDI board submitted to reflow process using finite element modelling (FEM). The parametric model constructed here includes microvias, buried vias and plated through holes (PTH). The HDI board is composed of a central core and two micro via layers on each external side. Firstly, equivalent material properties of the complete stack-up were determined according to three pre-preg materials (mat. A as ref., mat. B and mat. C) and core thickness (0.9, 1.1 and 1.3 mm as ref.) below and above their glass transition temperature, Tg. Several simulations were then done on the reference board in order to evaluate the impact of the temperature shock (above Tg) on the ageing of the HDI board. Finally, we focused on the behaviour of the buried via, which is a highly critic part of the HDI board. The objective was to optimize, for the different assembly processes (leaded and lead free), the choice of the FR4 material types as well as the design rules (core thickness and buried via diameter for example). Discussions on results in link with experimental data and calculation approximations are done in this study in order to better understand the failure roots and to determine way of simulation methodology improvements.
Real-time price discovery in global stock , bond and foreign exchange markets ☆

Using a unique high-frequency futures dataset, we characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. We find that news produces conditional mean jumps; hence high-frequency stock, bond and exchange rate dynamics are linked to fundamentals. Equity markets, moreover, react differently to news depending on the stage of the business cycle, which explains the low correlation between stock and bond returns when averaged over the cycle. Hence our results qualify earlier work suggesting that bond markets react most strongly to macroeconomic news; in particular, when conditioning on the state of the economy, the equity and foreign Journal of International Economics 73 (2007) 251–277 www.elsevier.com/locate/econbase ☆ This work was supported by the National Science Foundation, the Guggenheim Foundation, the BSI Gamma Foundation, and CREATES. For useful comments we thank the Editor and referees, seminar participants at the Bank for International Settlements, the BSI Gamma Foundation, the Symposium of the European Central Bank/Center for Financial Studies Research Network, the NBER International Finance and Macroeconomics program, and the American Economic Association Annual Meetings, as well as Rui Albuquerque, Annika Alexius, Boragan Aruoba, Anirvan Banerji, Ben Bernanke, Robert Connolly, Jeffrey Frankel, Lingfeng Li, Richard Lyons, Marco Pagano, Paolo Pasquariello, and Neng Wang.  Corresponding author. Department of Economics, University of Pennsylvania, 3718 Locust Walk Philadelphia, PA 19104-6297, United States. Tel.: +1 215 898 1507; fax: +1 215 573 4217. E-mail addresses: t-andersen@kellogg.nwu.edu (T.G. Andersen), boller@econ.duke.edu (T. Bollerslev), fdiebold@sas.upenn.edu (F.X. Diebold), vega@simon.rochester.edu (C. Vega). 0022-1996/$ see front matter  exchange markets appear equally responsive. Finally, we also document important contemporaneous links across all markets and countries, even after controlling for the effects of macroeconomic news.