nils-herrmann/clean_scirepeval huggingface dataset:
Statistics of co-occurring keywords on Twitter

Online social media such as the micro-blogging site Twitter has become a rich source of real-time data on online human behaviors. Here we analyze the occurrence and co-occurrence frequency of keywords in user posts on Twitter. From the occurrence rate of major international brand names, we provide examples on predictions of brand-user behaviors. From the co-occurrence rates, we further analyze the user-perceived relationships between international brand names and construct the corresponding relationship networks. In general the user activity on Twitter is highly intermittent and we show that the occurrence rate of brand names forms a highly correlated time signal.
Implementation of Robust Image Artifact Removal in SWarp through Clipped Mean Stacking

We implement an algorithm for detecting and removing artifacts from astronomical images by means of outlier rejection during stacking. Our method is capable of addressing both small, highly significant artifacts such as cosmic rays and, by applying a filtering technique to generate single frame masks, larger area but lower surface brightness features such as secondary (ghost) images of bright stars. In contrast to the common method of building a median stack, the clipped, or outlier-filtered mean stacked point-spread function (PSF), is a linear combination of the single frame PSFs as long as the latter are moderately homogeneous, a property of great importance for weak lensing shape measurement or model fitting photometry. In addition, our method has superior noise properties, allowing a significant reduction in exposure time compared to median stacking. We make publicly available a modified version of SWarp that implements clipped mean stacking and software to generate single frame masks from the list of outlier pixels.
DETECTION OF ULTRAVIOLET HALOS AROUND HIGHLY INCLINED GALAXIES

We report the discovery of diffuse ultraviolet light around late-type galaxies out to 5–20 kpc from the midplane using Swift and GALEX images. The emission is consistent with the stellar outskirts in the early-type galaxies but not in the late-type galaxies, where the emission is quite blue and consistent with a reflection nebula powered by light escaping from the galaxy and scattering off dust in the halo. Our results agree with expectations from halo dust discovered in extinction by Ménard et al. to within a few kpc of the disk and imply a comparable amount of hot and cold gas in galaxy halos (a few× 108 M☉ within 20 kpc) if the dust resides primarily in Mg ii absorbers. The results also highlight the potential of UV photometry to study individual galaxy halos.
Massive Gravity

We review recent progress in massive gravity. We start by showing how different theories of massive gravity emerge from a higher-dimensional theory of general relativity, leading to the Dvali-Gabadadze-Porrati model (DGP), cascading gravity, and ghost-free massive gravity. We then explore their theoretical and phenomenological consistency, proving the absence of Boulware-Deser ghosts and reviewing the Vainshtein mechanism and the cosmological solutions in these models. Finally, we present alternative and related models of massive gravity such as new massive gravity, Lorentz-violating massive gravity and non-local massive gravity.
Is the Higgs Boson Associated with Coleman-Weinberg Dynamical Symmetry Breaking?

The Higgs mechanism may be a quantum phenomenon, i.e., a Coleman-Weinberg potential generated by the explicit breaking of scale symmetry in Feynman loops. We review the relationship of scale symmetry, trace anomalies, and emphasize the role of the renormalization group in determining Coleman- Weinberg potentials. We propose a simple phenomenological model with "maximal visibility" at the LHC containing a "dormant" Higgs doublet (no VEV, coupled to standard model gauge interactions $$SU(2)\times U(1)$$) with a mass of $$\sim 380$$ GeV. We discuss the LHC phenomenology and UV challenges of such a model. We also give a schematic model in which new heavy fermions, with masses $$\sim 230$$ GeV, can drive a Coleman-Weinberg potential at two-loops. The role of the "improved stress tensor" is emphasized, and we propose a non-gravitational term, analogous to the $$\theta$$-term in QCD, which generates it from a scalar action.
BLACK HOLE QUBIT CORRESPONDENCE FROM QUANTUM CIRCUITS

We consider the black hole qubit correspondence (BHQC) from quantum circuits, taking into account the use of gate operations with base in the formulation of wrapped brane qubits. We interpret these quantum circuits with base on the BHQC classification of entanglement classes and apply in specific examples as the generation of Bell, Greenberger–Horne–Zeilinger (GHZ) states, quantum circuit teleportation and consider the implementation of interchanges in supersymmetry (SUSY), black hole configurations, Freudenthal and rank system constructions. These results are discussed from the superstring viewpoint showing that the importance of the construction of the physical states formed by the entanglement of geometrical entities by cohomological operations automatically allows the preservation of different amounts of SUSY in the compactification process given an alternative to the case when fluxes are introduced in the game: the generalized Calabi–Yau of Hitchin.
Brownian dynamics without Green's functions.

We develop a Fluctuating Immersed Boundary (FIB) method for performing Brownian dynamics simulations of confined particle suspensions. Unlike traditional methods which employ analytical Green's functions for Stokes flow in the confined geometry, the FIB method uses a fluctuating finite-volume Stokes solver to generate the action of the response functions "on the fly." Importantly, we demonstrate that both the deterministic terms necessary to capture the hydrodynamic interactions among the suspended particles, as well as the stochastic terms necessary to generate the hydrodynamically correlated Brownian motion, can be generated by solving the steady Stokes equations numerically only once per time step. This is accomplished by including a stochastic contribution to the stress tensor in the fluid equations consistent with fluctuating hydrodynamics. We develop novel temporal integrators that account for the multiplicative nature of the noise in the equations of Brownian dynamics and the strong dependence of the mobility on the configuration for confined systems. Notably, we propose a random finite difference approach to approximating the stochastic drift proportional to the divergence of the configuration-dependent mobility matrix. Through comparisons with analytical and existing computational results, we numerically demonstrate the ability of the FIB method to accurately capture both the static (equilibrium) and dynamic properties of interacting particles in flow.
Epidemiological modeling of online social network dynamics

The last decade has seen the rise of immense online social networks (OSNs) such as MySpace and Facebook. In this paper we use epidemiological models to explain user adoption and abandonment of OSNs, where adoption is analogous to infection and abandonment is analogous to recovery. We modify the traditional SIR model of disease spread by incorporating infectious recovery dynamics such that contact between a recovered and infected member of the population is required for recovery. The proposed infectious recovery SIR model (irSIR model) is validated using publicly available Google search query data for "MySpace" as a case study of an OSN that has exhibited both adoption and abandonment phases. The irSIR model is then applied to search query data for "Facebook," which is just beginning to show the onset of an abandonment phase. Extrapolating the best fit model into the future predicts a rapid decline in Facebook activity in the next few years.
Modeling Emotion Influence from Images in Social Networks

Images become an important and prevalent way to express users' activities, opinions and emotions. In a social network, individual emotions may be influenced by others, in particular by close friends. We focus on understanding how users embed emotions into the images they uploaded to the social websites and how social influence plays a role in changing users' emotions. We first verify the existence of emotion influence in the image networks, and then propose a probabilistic factor graph based emotion influence model to answer the questions of "who influences whom". Employing a real network from Flickr as experimental data, we study the effectiveness of factors in the proposed model with in-depth data analysis. Our experiments also show that our model, by incorporating the emotion influence, can significantly improve the accuracy (+5%) for predicting emotions from images. Finally, a case study is used as the anecdotal evidence to further demonstrate the effectiveness of the proposed model.
Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective

An extensive analysis of the presence of different altmetric indicators provided by Altmetric.com across scientific fields is presented, particularly focusing on their relationship with citations. Our results confirm that the presence and density of social media altmetric counts are still very low and not very frequent among scientific publications, with 15%–24% of the publications presenting some altmetric activity and concentrated on the most recent publications, although their presence is increasing over time. Publications from the social sciences, humanities, and the medical and life sciences show the highest presence of altmetrics, indicating their potential value and interest for these fields. The analysis of the relationships between altmetrics and citations confirms previous claims of positive correlations but is relatively weak, thus supporting the idea that altmetrics do not reflect the same kind of impact as citations. Also, altmetric counts do not always present a better filtering of highly‐cited publications than journal citation scores. Altmetric scores (particularly mentions in blogs) are able to identify highly‐cited publications with higher levels of precision than journal citation scores (JCS), but they have a lower level of recall. The value of altmetrics as a complementary tool of citation analysis is highlighted, although more research is suggested to disentangle the potential meaning and value of altmetric indicators for research evaluation.
Superconducting nanowire single photon detector on diamond

Superconducting nanowire single photon detectors are fabricated directly on diamond substrates and their optical and electrical properties are characterized. Dark count performance and photon count rates are measured at varying temperatures for 1310 nm and 632 nm photons. A multi-step diamond surface polishing procedure is reported, involving iterative reactive ion etching and mechanical polishing to create a suitable diamond surface for the deposition and patterning of thin film superconducting layers. Using this approach, diamond substrates with less than 300 pm Root Mean Square surface roughness are obtained.
Wealth distribution and collective knowledge: a Boltzmann approach

We introduce and discuss a nonlinear kinetic equation of Boltzmann type that describes the influence of knowledge in the evolution of wealth in a system of agents that interact through the binary trades, an equation first introduced by Cordier et al. (2005  253–277 (doi:10.1007/S10955-005-5456-0)). The trades, which include both saving propensity and the risks of the market, are here modified in the risk and saving parameters, which now are assumed to depend on the personal degree of knowledge. The numerical simulations show that the presence of knowledge has the potential to produce a class of wealthy agents and to account for a larger proportion of wealth inequality.
Auxiliary field Monte-Carlo simulation of strong coupling lattice QCD for QCD phase diagram

Auxiliary field Monte Carlo simulation of strong-coupling lattice QCD for QCD phase diagram Terukazu Ichihara1,2,∗, Akira Ohnishi2,∗, and Takashi Z. Nakano3,∗ 1Department of Physics, Kyoto University, Kyoto 606-8502, Japan 2Yukawa Institute for Theoretical Physics, Kyoto University, Kyoto 606-8502, Japan 3Kozo Keikaku Engineering Inc., Tokyo 164-0012, Japan ∗E-mail: t-ichi@ruby.scphys.kyoto-u.ac.jp, ohnishi@yukawa.kyoto-u.ac.jp, takashi-nakano@kke.co.jp
Mathematical Foundations for the Economy of Giving

This paper shows how we can build a model for transactions when goods are given away in the expectation of a later settlement. In settings where people keep track of their social accounts we are able to redefine concepts like account balance, yield curve and the law of diminishing returns. The model provides us with a result that expresses how people have a structural preference for one recipient over the other regardless the actual account balance. Hence a building block in the social fabric of a community. Finally, a fundamental theorem is presented to show how suppliers and recipients use their account balance in order to reach an equilibrium in the exchange of goods much like the traditional balance between supply and demand.
First data from DM-Ice17

Astrophysical observations have provided convincing evidence for the existence of dark matter, yet direct observation of the dark matter particles has not been conclusively established. DAMA experiment claimed to have observed the annual modulation signal of dark matter using NaI detectors at the Gran Sasso Lab in Italy. The DM-Ice project aims to conclusively test this claim with a new detector array at the South Pole. It will be one of the first direct dark matter detection experiments in the southern hemisphere. DM-Ice17 is a prototype 17 kg NaI detector deployed in the South Pole ice. The speaker will report first data collected with the detector and discuss R&D progress and prospects of the full scale DM-Ice detector.
Establishing an analogue population for the most distant galaxies

Lyman break analogues (LBAs) are local galaxies selected to match a more distant (usually z ∼ 3) galaxy population in luminosity, UV-spectral slope and physical characteristics, and so provide an accessible laboratory for exploring their properties. However, as the Lyman break technique is extended to higher redshifts, it has become clear that the Lyman break galaxies (LBGs) at z ∼ 3 are more massive, luminous, redder, more extended and at higher metallicities than their z ∼ 5 counterparts. Thus extrapolations from the existing LBA samples (which match z = 3 properties) have limited value for characterizing z > 5 galaxies, or inferring properties unobservable at high redshift. We present a new pilot sample of 21 compact star-forming galaxies in the local (0.05 < z < 0.25) Universe, which are tuned to match the luminosities and star formation volume densities observed in z ≳ 5 LBGs. The analysis of optical emission line indices suggests that these sources have typical metallicities of a few tenths solar (again, consistent with the distant population). We also present radio continuum observations of a subset of this sample (13 sources) and determine that their radio fluxes are consistent with those inferred from the ultraviolet, precluding the presence of a heavily obscured active galactic nuclei or significant dusty star formation.
Gravitational instability of planetary gaps and its effect on orbital migration

Gap formation by giant planets in self-gravitating disks may lead to a gravitational edge instability (GEI). We demonstrate this GEI with global 3D and 2D self-gravitating disk-planet simulations using the ZEUS, PLUTO and FARGO hydrodynamic codes. High resolution 2D simulations show that an unstable outer gap edge can lead to outward migration. Our results have important implications for theories of giant planet formation in massive disks.
Localization and centrality in networks

Eigenvector centrality is a common measure of the importance of nodes in a network. Here we show that under common conditions the eigenvector centrality displays a localization transition that causes most of the weight of the centrality to concentrate on a small number of nodes in the network. In this regime the measure is no longer useful for distinguishing among the remaining nodes and its efficacy as a network metric is impaired. As a remedy, we propose an alternative centrality measure based on the nonbacktracking matrix, which gives results closely similar to the standard eigenvector centrality in dense networks where the latter is well behaved but avoids localization and gives useful results in regimes where the standard centrality fails.
Why free markets die: An evolutionary perspective

Company mergers and acquisitions are often perceived to act as catalysts for corporate growth in free markets systems: it is conventional wisdom that those activities lead to better and more efficient markets. However, the broad adoption of this perception into corporate strategy is prone to result in a less diverse and more unstable environment, dominated by either very large or very small niche entities. We show here that ancestry, i.e. the cumulative history of mergers, is the key characteristic that encapsulates the diverse range of drivers behind mergers and acquisitions, across a range of industries and geographies. A long-term growth analysis reveals that entities which have been party to fewer mergers tend to grow faster than more highly acquisitive businesses.
On the representation of de Bruijn graphs

The de Bruijn graph plays an important role in bioinformatics, especially in the context of de novo assembly. However, the representation of the de Bruijn graph in memory is a computational bottleneck for many assemblers. Recent papers proposed a navigational data structure approach in order to improve memory usage. We prove several theoretical space lower bounds to show the limitations of these types of approaches. We further design and implement a general data structure (dbgfm) and demonstrate its use on a human whole-genome dataset, achieving space usage of 1.5 GB and a 46% improvement over previous approaches. As part of dbgfm, we develop the notion of frequency-based minimizers and show how it can be used to enumerate all maximal simple paths of the de Bruijn graph using only 43 MB of memory. Finally, we demonstrate that our approach can be integrated into an existing assembler by modifying the ABySS software to use dbgfm.
Light WIMPs, Equivalent Neutrinos, BBN, and the CMB

Recent updates to the observational determinations of the primordial abundances of helium and deuterium are compared to the predictions of BBN to infer the universal ratio of baryons to photons (or, the present Universe baryon mass density parameter Omega_B h^2), as well as to constrain the effective number of neutrinos (N_eff) and the number of equivalent neutrinos (Delta N_nu). These BBN results are compared to those derived independently from the Planck CMB data. In the absence of a light WIMP (chi), N_eff = 3.05(1 + Delta N_nu/3). In this case, there is excellent agreement between BBN and the CMB, but the joint fit finds that Delta N_nu = 0.40 +/- 0.17, disfavoring standard big bang nucleosynthesis (SBBN: Delta N_nu = 0) at 2.4 sigma, as well as a sterile neutrino (Delta N_nu = 1) at 3.5 sigma. In the presence of a light WIMP, the relation between N_eff and Delta N_nu depends on the WIMP mass, leading to degeneracies among N_eff, Delta N_nu, and m_chi. The complementary and independent BBN and CMB data can break some of these degeneracies. Depending on the nature of the light WIMP (Majorana or Dirac fermion, real or complex scalar) the joint BBN + CMB analyses set a lower bound to m_chi in the range from 0.5 to 5 MeV, and they identify best fit values for m_chi in the range from 5 to 10 MeV. The joint BBN + CMB analyses find a best fit value for the number of equivalent neutrinos, Delta N_nu = 0.65, nearly independent of the nature of the WIMP. The best fit still disfavors the absence of dark radiation (Delta N_nu = 0 at 95% confidence), while allowing for the presence of a sterile neutrino (Delta N_nu = 1 at less than 1 sigma). For all cases considered here, the lithium problem persists. These results, presented at the 2013 Rencontres de l'Observatoire de Paris - ESO Workshop, are based on Nollett & Steigman 2013 ().
Peer Ratings in Massive Online Social Networks

Instant quality feedback in the form of online peer ratings is a prominent feature of modern massive online social networks (MOSNs). It allows network members to indicate their appreciation of a post, comment, photograph, etc. Some MOSNs support both positive and negative (signed) ratings. In this study, we rated 11 thousand MOSN member profiles and collected user responses to the ratings. MOSN users are very sensitive to peer ratings: 33% of the subjects visited the researcher's profile in response to rating, 21% also rated the researcher's profile picture, and 5% left a text comment. The grades left by the subjects are highly polarized: out of the six available grades, the most negative and the most positive are also the most popular. The grades fall into three almost equally sized categories: reciprocal, generous, and stingy. We proposed quantitative measures for generosity, reciprocity, and benevolence, and analyzed them with respect to the subjects' demographics.
Generalized Lüscher’s formula in multichannel baryon-baryon scattering

In this paper, L\"uscher's formula is generalized to the case of two spin-$\frac{1}{2}$ particles in two-channel scattering based on Ref. \cite{Li:2012bi}. This is first done in a non-relativistic quantum mechanics model and then generalized to quantum field theory. 
We show that L\"uscher's formula obtained from these two different methods are equivalent up to terms that are exponentially suppressed in the box size. This formalism can be readily applied to future lattice QCD calculations.
The Gabor-Einstein Wavelet: A Model for the Receptive Fields of V1 to MT Neurons

Our visual system is astonishingly efficient at detecting moving objects. This process is mediated by the neurons which connect the primary visual cortex (V1) to the middle temporal (MT) area. Interestingly, since Kuffler's pioneering experiments on retinal ganglion cells, mathematical models have been vital for advancing our understanding of the receptive fields of visual neurons. However, existing models were not designed to describe the most salient attributes of the highly specialized neurons in the V1 to MT motion processing stream; and they have not been able to do so. Here, we introduce the Gabor-Einstein wavelet, a new family of functions for representing the receptive fields of V1 to MT neurons. We show that the way space and time are mixed in the visual cortex is analogous to the way they are mixed in the special theory of relativity (STR). Hence we constrained the Gabor-Einstein model by requiring: (i) relativistic-invariance of the wave carrier, and (ii) the minimum possible number of parameters. From these two constraints, the sinc function emerged as a natural descriptor of the wave carrier. The particular distribution of lowpass to bandpass temporal frequency filtering properties of V1 to MT neurons (Foster et al 1985; DeAngelis et al 1993b; Hawken et al 1996) is clearly explained by the Gabor-Einstein basis. Furthermore, it does so in a manner innately representative of the motion-processing stream's neuronal hierarchy. Our analysis and computer simulations show that the distribution of temporal frequency filtering properties along the motion processing stream is a direct effect of the way the brain jointly encodes space and time. We uncovered this fundamental link by demonstrating that analogous mathematical structures underlie STR and joint cortical spacetime encoding. This link will provide new physiological insights into how the brain represents visual information.