nils-herrmann/clean_scirepeval huggingface dataset:
q-ary Compressive Sensing

We introduce q-ary compressive sensing, an extension of 1-bit compressive sensing. We propose a novel sensing mechanism and a corresponding recovery procedure. The recovery properties of the proposed approach are analyzed both theoretically and empirically. Results in 1-bit compressive sensing are recovered as a special case. Our theoretical results suggest a tradeoff between the quantization parameter q, and the number of measurements m in the control of the error of the resulting recovery algorithm, as well its robustness to noise.
Mixed neutron-star-plus-wormhole systems: Linear stability analysis

We consider configurations consisting of a neutron star with a wormhole at the core. The wormhole is held open by a ghost scalar field with a quartic coupling. The neutron matter is described by a perfect fluid with a polytropic equation of state. We obtain static regular solutions for these systems. A stability analysis, however, shows that they are unstable with respect to linear perturbations.
Recent progress in staggered chiral perturbation theory

We present a review on recent progress in staggered chiral perturbation theory (SChPT). In the last decade, the scope of the application of SChPT has been extended beyond the level of calibration into the region of prediction with high precision. SChPT becomes an essential tool to do the data analysis reliably for physical observables calculated using improved staggered fermions. Here, we focus on the following examples: pion spectrum, pion decay constants, $\varepsilon_K$, and $\pi-\pi$ scattering amplitudes. In each subject, we review the recent progress and future prospects.
Predicting the Temporal Dynamics of Information Diffusion in Social Networks

Online social networks play a major role in the spread of information at very large scale and it becomes essential to provide means to analyse this phenomenon. In this paper we address the issue of predicting the temporal dynamics of the information diffusion process. We develop a graph-based approach built on the assumption that the macroscopic dynamics of the spreading process are explained by the topology of the network and the interactions that occur through it, between pairs of users, on the basis of properties at the microscopic level. We introduce a generic model, called T-BaSIC, and describe how to estimate its parameters from users behaviours using machine learning techniques. Contrary to classical approaches where the parameters are fixed in advance, T-BaSIC's parameters are functions depending of time, which permit to better approximate and adapt to the diffusion phenomenon observed in online social networks. Our proposal has been validated on real Twitter datasets. Experiments show that our approach is able to capture the particular patterns of diffusion depending of the studied sub-networks of users and topics. The results corroborate the "two-step" theory (1955) that states that information flows from media to a few "opinion leaders" who then transfer it to the mass population via social networks and show that it applies in the online context. This work also highlights interesting recommendations for future investigations.
Stable Self-Interacting Pais-Uhlenbeck Oscillator

It is shown that the interacting Pais-Uhlenbeck oscillator necessarily leads to a description with a Hamiltonian that contains positive and negative energies associated with two oscillators. Descriptions with a positive definite Hamiltonians, considered by some authors, can hold only for a free Pais-Uhlenbeck oscillator. We demonstrate that the solutions of a self-interacting Pais-Uhlenbeck oscillator are stable on islands in the parameter space, as already observed in the literature. If we slightly modify the system, by considering a sine interaction term, and/or by taking unequal masses of the two oscillators, then the system is stable on the continents that extend from zero to infinity in the parameter space. Therefore, the Pais-Uhlenbeck oscillator is quite acceptable physical system.
Theory of Performance Participation Strategies

The purpose of this article is to introduce, analyze and compare two performance participation methods based on a portfolio consisting of two risky assets: Option-Based Performance Participation (OBPP) and Constant Proportion Performance Participation (CPPP). By generalizing the provided guarantee to a participation in the performance of a second risky underlying, the new strategies allow to cope with well-known problems associated with standard portfolio insurance methods, like e.g. the CPPI cash lock-in. This is especially an issue in times of market crisis. However, the minimum guaranteed portfolio value at the end of the investment horizon is not deterministic anymore, but subject to systematic risk instead. With respect to the comparison of the two strategies, various criteria are applied such as comparison of terminal payoffs and payoff distributions. General analytical expressions for all moments of both performance participation strategies as well as standard OBPI and CPPI are derived. Furthermore, dynamic hedging properties are examined, in particular classical delta hedging.
Precovery of near-Earth asteroids by a citizen-science project of the Spanish Virtual Observatory

This article describes a citizen-science project conducted by the Spanish Virtual Observatory (SVO) to improve the orbits of near-Earth asteroids (NEAs) using data from astronomical archives. The list of NEAs maintained at the Minor Planet Center (MPC) is checked daily to identify new objects or changes in the orbital parameters of already catalogued objects. Using NEODyS we compute the position and magnitude of these objects at the observing epochs of the 938 046 images comprising the Eigth Data Release of the Sloan Digitised Sky Survey (SDSS). If the object lies within the image boundaries and the magnitude is brighter than the limiting magnitude, then the associated image is visually inspected by the project's collaborators (the citizens) to confirm or discard the presence of the NEA. If confirmed, accurate coordinates and, sometimes, magnitudes are submitted to the MPC. Using this methodology, 3,226 registered users have made during the first fifteen months of the project more than 167,000 measurements which have improved the orbital elements of 551 NEAs (6% of the total number of this type of asteroids). Even more remarkable is the fact that these results have been obtained at zero cost to telescope time as NEAs were serendipitously observed while the survey was being carried out. This demonstrates the enormous scientific potential hidden in astronomical archives. 
The great reception of the project as well as the results obtained makes it a valuable and reliable tool for improving the orbital parameters of near-Earth asteroids.
A preliminary reconstruction of the orbit of the Chelyabinsk Meteoroid

In February 15 2013 a medium-sized meteoroid impacted the atmosphere in the region of Chelyabinsk, Russia. After its entrance to the atmosphere and after travel by several hun- dred of kilometers the body exploded in a powerful event responsible for physical damages and injured people spread over a region enclosing several large cities. We present in this letter the results of a preliminary reconstruction of the orbit of the Chelyabinsk meteoroid. Using evidence gathered by one camera at the Revolution Square in the city of Chelyabinsk and other videos recorded by witnesses in the close city of Korkino, we calculate the trajectory of the body in the atmosphere and use it to reconstruct the orbit in space of the meteoroid previous to the violent encounter with our planet. In order to account for the uncertainties implicit in the determination of the trajectory of the body in the atmosphere, we use Monte Carlo methods to calculate the most probable orbital parameters. We use this result to classify the meteoroid among the near Earth asteroid families finding that the parent body belonged to the Apollo asteroids. Although semimajor axis and inclination of the preliminary orbit computed by us are uncertain, the rest of orbital elements are well constrained in this preliminary reconstruction.
An Ontology Construction Approach for the Domain Of Poultry Science Using Protege

The information retrieval systems that are present nowadays are mainly based on full text matching of keywords or topic based classification. This matching of keywords often returns a large number of irrelevant information and this does not meet the users query requirement. In order to solve this problem and to enhance the search using semantic environment, a technique named ontology is implemented for the field of poultry in this paper. Ontology is an emerging technique in the current field of research in semantic environment. This paper constructs ontology using the tool named Protege version 4.0 and this also generates Resource Description Framework schema and XML scripts for using poultry ontology in web.
Discovery of Fourier-dependent time lags in cataclysmic variables

We report the first study of Fourier-frequency-dependent coherence and phase/time lags at optical wavelengths of cataclysmic variables (MV Lyr and LU Cam) displaying typical flickering variability in white light. Observations were performed on the William Herschel Telescope using ULTRACAM. Light curves for both systems have been obtained with the SDSS filters u′, g′ and r′ simultaneously with cadences in the range ≈0.5–2 s, and allow us to probe temporal frequencies between ≈10−3 and ≈1 Hz. We find high levels of coherence between the u′, g′ and r′ light curves up to at least ≈10−2 Hz. Furthermore, we detect red/negative lags where the redder bands lag the bluer ones at the lowest observed frequencies. For MV Lyr time lags up to ≈3 s are observed, whilst LU Cam displays larger time lags of ≈10 s. Mechanisms which seek to explain red/negative lags observed in X-ray binaries and active galactic nuclei involve reflection of photons generated close to the compact object on to the surface layers of the accretion disc, where the lag delay is simply the light travel time from the emitting source to the reflecting accretion disc area. Although this could be a viable explanation for the lags observed in MV Lyr, the lags observed in LU Cam are too large to be explained by reflection from the disc and/or the donor star. We suggest reprocessing on the thermal time-scale of boundary layer photons on to the accretion disc as a possible mechanism to explain the lags observed in accreting white dwarfs, or reverse (inside-out) shocks within the disc travelling through cooler disc regions as they move outwards.
Nonparametric Basis Pursuit via Sparse Kernel-Based Learning: A Unifying View with Advances in Blind Methods

Signal processing tasks as fundamental as sampling, reconstruction, minimum mean-square error interpolation, and prediction can be viewed under the prism of reproducing kernel Hilbert spaces (RKHSs). Endowing this vantage point with contemporary advances in sparsity-aware modeling and processing promotes the nonparametric basis pursuit advocated in this article as the overarching framework for the confluence of kernel-based learning (KBL) approaches leveraging sparse linear regression, nuclear-norm regularization, and dictionary learning. The novel sparse KBL toolbox goes beyond translating sparse parametric approaches to their nonparametric counterparts to incorporate new possibilities such as multikernel selection and matrix smoothing. The impact of sparse KBL to signal processing applications is illustrated through test cases from cognitive radio sensing, microarray data imputation, and network traffic prediction.
The Quantum Entropy Cone of Stabiliser States

We investigate the universal linear inequalities that hold for the von Neumann entropies in a multi-party system, prepared in a stabiliser state. We demonstrate here that entropy vectors for stabiliser states satisfy, in addition to the classic inequalities, a type of linear rank inequalities associated with the combinatorial structure of normal subgroups of certain matrix groups. In the 4-party case, there is only one such inequality, the so-called Ingleton inequality. For these systems we show that strong subadditivity, weak monotonicity and Ingleton inequality exactly characterize the entropy cone for stabiliser states.
SOAP3-dp: Fast, Accurate and Sensitive GPU-Based Short Read Aligner

To tackle the exponentially increasing throughput of Next-Generation Sequencing (NGS), most of the existing short-read aligners can be configured to favor speed in trade of accuracy and sensitivity. SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, CUSHAW2, GEM and GPU-based aligners BarraCUDA and CUSHAW, SOAP3-dp was found to be two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina reads with different lengths. Transcending its predecessor SOAP3, which does not allow gapped alignment, SOAP3-dp by default tolerates alignment similarity as low as 60%. Real data evaluation using human genome demonstrates SOAP3-dp's power to enable more authentic variants and longer Indels to be discovered. Fosmid sequencing shows a 9.1% FDR on newly discovered deletions. SOAP3-dp natively supports BAM file format and provides the same scoring scheme as BWA, which enables it to be integrated into existing analysis pipelines. SOAP3-dp has been deployed on Amazon-EC2, NIH-Biowulf and Tianhe-1A.
Simulating fermion production in 1+1 dimensional QED

We investigate fermion--anti-fermion production in 1+1 dimensional QED using real-time lattice techniques. In this non-perturbative approach the full quantum dynamics of fermions is included while the gauge field dynamics can be accurately represented by classical-statistical simulations for relevant field strengths. We compute the non-equilibrium time evolution of gauge invariant correlation functions implementing 'low-cost' Wilson fermions. Introducing a lattice generalization of the Dirac-Heisenberg-Wigner function, we recover the Schwinger formula in 1+1 dimensions in the limit of a static background field. We discuss the decay of the field due to the backreaction of the created fermion--anti-fermion pairs and apply the approach to strongly inhomogeneous gauge fields. The latter allows us to discuss the striking phenomenon of a linear rising potential building up between produced fermion bunches after the initial electric pulse ceased.
How to Make Dupire's Local Volatility Work with Jumps

There are several (mathematical) reasons why Dupire's formula fails in the non-diffusion setting. And yet, in practice, ad-hoc preconditioning of the option data works reasonably well. In this note we attempt to explain why. In particular, we propose a regularization procedure of the option data so that Dupire's local vol diffusion process recreates the correct option prices, even in manifest presence of jumps.
Distinct stellar populations in the inner bars of double-barred galaxies

Numerical simulations of double-barred galaxies predict the build-up of different structural components (e.g. bulges, inner discs) in the central regions of disc galaxies. In those simulations, inner bars have a prominent role in the internal secular evolution of their host galaxies. The development of bulges and inner discs is, however, poorly understood observationally due to the small number of studies focusing on the stellar populations of these systems. In order to provide constraints on the relevant processes inducing the creation of these components in the presence of inner bars, we have carried out a detailed kinematical and stellar population analysis in a sample of four double-barred galaxies, ranging from SB0 to SBb, observed with integral-field spectroscopy. We find that the inner bars present distinct stellar population properties, being younger and more metal-rich than the surrounding bulges and outer bars. While we detect signatures of gas inflow through the inner bars, we find no evidence of associated star-forming regions or newly formed structures around them. This result suggests that, regardless of their formation scenario, at present these inner bars are playing a moderate or even a minor role in the morphological evolution of this sample of double-barred galaxies.
Exploring QCD phase diagram at vanishing baryon density on the lattice

I report on the current status of QCD phase diagram at vanishing baryon density. I focus on the QCD phase diagram with three degenerate quark flavor using Highly Improved Staggered Quarks on NT = 6 lattices. No evidence of a first order phase transition in the pion mass window of 80 ≲ mπ ≲ 230 MeV is found. The pion mass at the critical point where the chiral first order phase transition ends is estimated to be mπc ≲ 45 MeV.
Measuring Visual Complexity of Cluster-Based Visualizations

Handling visual complexity is a challenging problem in visualization owing to the subjectiveness of its definition and the difficulty in devising generalizable quantitative metrics. In this paper we address this challenge by measuring the visual complexity of two common forms of cluster-based visualizations: scatter plots and parallel coordinatess. We conceptualize visual complexity as a form of visual uncertainty, which is a measure of the degree of difficulty for humans to interpret a visual representation correctly. We propose an algorithm for estimating visual complexity for the aforementioned visualizations using Allen’s interval algebra. We first establish a set of primitive 2-cluster cases in scatter plots and another set for parallel coordinatess based on symmetric isomorphism. We confirm that both are the minimal sets and verify the correctness of their members computationally. We score the uncertainty of each primitive case based on its topological properties, including the existence of overlapping regions, splitting regions and meeting points or edges. We compare a few optional scoring schemes against a set of subjective scores by humans, and identify the one that is the most consistent with the subjective scores. Finally, we extend the 2-cluster measure to k-cluster measure as a general purpose estimator of visual complexity for these two forms of cluster-based visualization.
Highly Correlated Electron State and High-Temperature Superconductivity in Iron Pnictides

It is shown that the qualitative model of the high-temperature superconductivity suggested earlier for cuprates and doped picene and based on the idea that the valence electron state depends on the character of the chemical bonds they form and on the Coulomb interaction between the electrons is not only confirmed by the experimental data on iron pnictides but is also improved. From the chemical point of view, the high-temperature superconductivity is associated with additional π bonding along chains of covalently bonded ions via a delocalized π orbital, just like in cuprates. From the physical point of view, as the data on iron pnictides show, the superconductivity is associated with a FeAs layer transition into the state similar to a macroscopic quantum system characterized by a highly correlated electron state, formation of two-dimensional crystals of electron pairs with quantized energy levels, and a strong Coulomb interaction between these crystals. Superconductivity in such a system is accomplished by a two-dimensional Wigner crystal consisting of onedimensional Wigner crystals formed by bosons, i.e., singlet electron pairs that are in the same quasi-one-dimensional state extending along the ion chain, which corresponds to a delocalized π orbital in chemistry. The model applicability to three different classes of materials (cuprates, picene, iron pnictides) indicates that it can prove useful for development of the theory of superconductivity taking into consideraion the highly correlated state of valence electrons and strong Coulomb interactions between the electrons.
Social resilience in online communities: the autopsy of friendster

We empirically analyze five online communities: Friendster, Livejournal, Facebook, Orkut, and Myspace, to study how social networks decline. We define social resilience as the ability of a community to withstand changes. We do not argue about the cause of such changes, but concentrate on their impact. Changes may cause users to leave, which may trigger further leaves of others who lost connection to their friends. This may lead to cascades of users leaving. A social network is said to be resilient if the size of such cascades can be limited. To quantify resilience, we use the k-core analysis, to identify subsets of the network in which all users have at least k friends. These connections generate benefits (b) for each user, which have to outweigh the costs (c) of being a member of the network. If this difference is not positive, users leave. After all cascades, the remaining network is the k-core of the original network determined by the cost-to-benefit (c/b) ratio. By analysing the cumulative distribution of k-cores we are able to calculate the number of users remaining in each community. This allows us to infer the impact of the c/b ratio on the resilience of these online communities. We find that the different online communities have different k-core distributions. Consequently, similar changes in the c/b ratio have a different impact on the amount of active users. Further, our resilience analysis shows that the topology of a social network alone cannot explain its success of failure. As a case study, we focus on the evolution of Friendster. We identify time periods when new users entering the network observed an insufficient c/b ratio. This measure can be seen as a precursor of the later collapse of the community. Our analysis can be applied to estimate the impact of changes in the user interface, which may temporarily increase the c/b ratio, thus posing a threat for the community to shrink, or even to collapse.
The role of information diffusion in the evolution of social networks

Every day millions of users are connected through online social networks, generating a rich trove of data that allows us to study the mechanisms behind human interactions. Triadic closure has been treated as the major mechanism for creating social links: if Alice follows Bob and Bob follows Charlie, Alice will follow Charlie. Here we present an analysis of longitudinal micro-blogging data, revealing a more nuanced view of the strategies employed by users when expanding their social circles. While the network structure affects the spread of information among users, the network is in turn shaped by this communication activity. This suggests a link creation mechanism whereby Alice is more likely to follow Charlie after seeing many messages by Charlie. We characterize users with a set of parameters associated with different link creation strategies, estimated by a Maximum-Likelihood approach. Triadic closure does have a strong effect on link formation, but shortcuts based on traffic are another key factor in interpreting network evolution. However, individual strategies for following other users are highly heterogeneous. Link creation behaviors can be summarized by classifying users in different categories with distinct structural and behavioral characteristics. Users who are popular, active, and influential tend to create traffic-based shortcuts, making the information diffusion process more efficient in the network.