nils-herrmann/clean_scirepeval huggingface dataset:
Hadron mass scaling near the s-wave threshold

The influence of a two-hadron threshold is studied for the hadron mass scaling with respect to some quantum chromodynamics parameters. A quantum mechanical model is introduced to describe the system with a one-body bare state coupled with a single elastic two-body scattering. The general behavior of the energy of the bound and resonance state near the two-body threshold for a local potential is derived from the expansion of the Jost function around the threshold. It is shown that the same scaling holds for the nonlocal potential induced by the coupling to a bare state. In p or higher partial waves, the scaling law of the stable bound state continues across the threshold describing the real part of the resonance energy. In contrast, the leading contribution of the scaling is forbidden by the nonperturbative dynamics near the s-wave threshold. As a consequence, the bound state energy is not continuously connected to the real part of the resonance energy. This universal behavior originates in the vanishing of the field renormalization constant of the zero-energy resonance in the s wave. A proof is given for the vanishing of the field renormalization constant, together with a detailed discussion.
Local and regional spread of chikungunya fever in the Americas.

Chikungunya fever (CHIKV), a viral disease transmitted by mosquitoes, is currently affecting several areas in the Caribbean. The vector is found in the Americas from southern Florida to Brazil, and the Caribbean is a highly connected region in terms of population movements. There is therefore a significant risk for the epidemic to quickly expand to a wide area in the Americas. Here, we describe the spread of CHIKV in the first three areas to report cases and between areas in the region. Local transmission of CHIKV in the Caribbean is very effective, the mean number of cases generated by a human case ranging from two to four. There is a strong spatial signature in the regional epidemic, with the risk of transmission between areas estimated to be inversely proportional to the distance rather than driven by air transportation. So far, this simple distance-based model has successfully predicted observed patterns of spread. The spatial structure allows ranking areas according to their risk of invasion. This characterisation may help national and international agencies to optimise resource allocation for monitoring and control and encourage areas with elevated risks to act.
Brand effect versus competitiveness in hypernetworks

A few of evolving models in hypernetworks have been proposed based on uniform growth. In order to better depict the growth mechanism and competitive aspect of real hypernetworks, we propose a model in term of the non-uniform growth. Besides hyperdegrees, the other two important factors are introduced to underlie preferential attachment. One dimension is the brand effect and the other is the competitiveness. Our model can accurately describe the evolution of real hypernetworks. The paper analyzes the model and calculates the stationary average hyperdegree distribution of the hypernetwork by using Poisson process theory and a continuous technique. We also address the limit in which this model has a condensation. The theoretical analyses agree with numerical simulations. Our model is universal, in that the standard preferential attachment, the fitness model in complex networks and scale-free model in hypernetworks can all be seen as degenerate cases of the model.
Identifying Cover Songs Using Information-Theoretic Measures of Similarity

This paper investigates methods for quantifying similarity between audio signals, specifically for the task of cover song detection. We consider an information-theoretic approach, where we compute pairwise measures of predictability between time series. We compare discrete-valued approaches operating on quantized audio features, to continuous-valued approaches. In the discrete case, we propose a method for computing the normalized compression distance, where we account for correlation between time series. In the continuous case, we propose to compute information-based measures of similarity as statistics of the prediction error between time series. We evaluate our methods on two cover song identification tasks using a data set comprised of 300 Jazz standards and using the Million Song Dataset. For both datasets, we observe that continuous-valued approaches outperform discrete-valued approaches. We consider approaches to estimating the normalized compression distance (NCD) based on string compression and prediction, where we observe that our proposed normalized compression distance with alignment (NCDA) improves average performance over NCD, for sequential compression algorithms. Finally, we demonstrate that continuous-valued distances may be combined to improve performance with respect to baseline approaches. Using a large-scale filter-and-refine approach, we demonstrate state-of-the-art performance for cover song identification using the Million Song Dataset.
Discovery of Important Crossroads in Road Network using Massive Taxi Trajectories

Massive Taxi Trajectories Ming Xu, Jianping Wu, Yiman Du, Haohan Wang, Geqi Qi, Kezhen Hu, Yunpeng Xiao School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China Department of Civil Engineering, Tsinghua University, Beijing, China School of Computer Science, Carnegie Mellon University, Pittsburgh PA USA School of Software, Chongqing University of Posts and Telecommunications, Chongqing, China {xum, xiaoyp}@bupt.edu.cn, {2855175, 153789104}@qq.com
Coding Together at Scale: GitHub as a Collaborative Social Network

GitHub is the most popular repository for open source code. It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities. 
In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration.
Compressed sensing for longitudinal MRI: An adaptive-weighted approach.

Repeated brain MRI scans are performed in many clinical scenarios, such as follow up of patients with tumors and therapy response assessment. In this paper, the authors show an approach to utilize former scans of the patient for the acceleration of repeated MRI scans.



The proposed approach utilizes the possible similarity of the repeated scans in longitudinal MRI studies. Since similarity is not guaranteed, sampling and reconstruction are adjusted during acquisition to match the actual similarity between the scans. The baseline MR scan is utilized both in the sampling stage, via adaptive sampling, and in the reconstruction stage, with weighted reconstruction. In adaptive sampling, k-space sampling locations are optimized during acquisition. Weighted reconstruction uses the locations of the nonzero coefficients in the sparse domains as a prior in the recovery process. The approach was tested on 2D and 3D MRI scans of patients with brain tumors.



The longitudinal adaptive compressed sensing MRI (LACS-MRI) scheme provides reconstruction quality which outperforms other CS-based approaches for rapid MRI. Examples are shown on patients with brain tumors and demonstrate improved spatial resolution. Compared with data sampled at the Nyquist rate, LACS-MRI exhibits signal-to-error ratio (SER) of 24.8 dB with undersampling factor of 16.6 in 3D MRI.



The authors presented an adaptive method for image reconstruction utilizing similarity of scans in longitudinal MRI studies, where possible. The proposed approach can significantly reduce scanning time in many applications that consist of disease follow-up and monitoring of longitudinal changes in brain MRI.
THE MOST DISTANT STARS IN THE MILKY WAY

We report on the discovery of the most distant Milky Way (MW) stars known to date: ULAS J001535.72+015549.6 and ULAS J074417.48+253233.0. These stars were selected as M giant candidates based on their infrared and optical colors and lack of proper motions. We spectroscopically confirmed them as outer halo giants using the MMT/Red Channel spectrograph. Both stars have large estimated distances, with ULAS J001535.72+015549.6 at 274 ± 74 kpc and ULAS J074417.48+253233.0 at 238 ± 64 kpc, making them the first MW stars discovered beyond 200 kpc. 253233.0 are both moving away from the Galactic center at 52 ± 10 km s−1 and 24 ± 10 km s−1, respectively. Using their distances and kinematics, we considered possible origins such as: tidal stripping from a dwarf galaxy, ejection from the MW's disk, or membership in an undetected dwarf galaxy. These M giants, along with two inner halo giants that were also confirmed during this campaign, are the first to map largely unexplored regions of our Galaxy's outer halo.
B-modes and the nature of inflation

Observations of the cosmic microwave background do not yet determine whether inflation was driven by a slowly-rolling scalar field or involved another physical mechanism. In this paper we discuss the prospects of using the power spectra of scalar and tensor modes to probe the nature of inflation. We focus on the leading modification to the slow-roll dynamics, which entails a sound speed cs for the scalar fluctuations. We derive analytically a lower bound on cs in terms of a given tensor-to-scalar ratio r, taking into account the difference in the freeze-out times between the scalar and tensor modes. We find that any detection of primordial B-modes with r > 0.01 implies a lower bound on cs that is stronger than the bound derived from the absence of non-Gaussianity in the Planck data. For r ≳ 0.1, the bound would be tantalizingly close to a critical value for the sound speed, (cs)⋆ = 0.47 (corresponding to (fNLequil)⋆ = -0.93), which we show serves as a threshold for non-trivial dynamics beyond slow-roll. We also discuss how an order-one level of equilateral non-Gaussianity is a natural observational target for other extensions of the canonical paradigm.
Learning Probabilistic Programs

We develop a technique for generalising from data in which models are samplers represented as program text. We establish encouraging empirical results that suggest that Markov chain Monte Carlo probabilistic programming inference techniques coupled with higher-order probabilistic programming languages are now sufficiently powerful to enable successful inference of this kind in nontrivial domains. We also introduce a new notion of probabilistic program compilation and show how the same machinery might be used in the future to compile probabilistic programs for efficient reusable predictive inference.
A New Optimal Stepsize for Approximate Dynamic Programming

Approximate dynamic programming (ADP) has proven itself in a wide range of applications spanning large-scale transportation problems, health care, revenue management, and energy systems. The design of effective ADP algorithms has many dimensions, but one crucial factor is the stepsize rule used to update a value function approximation. Many operations research applications are computationally intensive, and it is important to obtain good results quickly. Furthermore, the most popular stepsize formulas use tunable parameters and can produce very poor results if tuned improperly. We derive a new stepsize rule that optimizes the prediction error in order to improve the short-term performance of an ADP algorithm. With only one, relatively insensitive tunable parameter, the new rule adapts to the level of noise in the problem and produces faster convergence in numerical experiments.
Opinion formation in an open system and the spiral of silence

A new model is formulated of the sociological effect of the spiral of silence, introduced by Elisabeth Noelle-Neumann in 1974. The probability that a new opinion is openly expressed decreases with the difference between this new opinion and the perceived opinion of the majority. We also assume that the system is open, i.e. some people enter and some leave during the process of the opinion formation. An influence of a leader is simulated by a comparison of two runs of the simulation, where the leader has different opinion in each run. The difference of the mean expressed opinions in these two runs persists long after the leader's leave.
Particular Solutions in Bimetric Theory and Their Implications

Ghost-free bimetric theory can describe gravity in the presence of an extra spin-2 field. We study certain aspects of dynamics in this theory: (1) It is shown that if either of the metrics is an Einstein solution then the other is always forced to be Einstein, too. For a class of bimetric models this constraint is stronger and as soon as one metric is Einstein, the other metric is forced to be proportional to it. As a consequence, the models in this class avoid a branch of pathological solutions that exhibit determinant singularities or nonlinear ghosts. These constraints persists in a generalized form when sources are included, but are destroyed in the massive gravity limit of the theory. (2) For another class of bimetric models, we show the existence of solutions that do not admit a massive gravity limit. A bimetric model that could exhibit a nonlinear version of "partially massless" symmetry belongs to both these classes. It is argued that if such a model exits, its symmetry will not survive in the massive gravity limit.
Cauchy surfaces and diffeomorphism types of globally hyperbolic spacetimes

Chernov–Nemirovski observed that the existence of a globally hyperbolic Lorentzian metric on a ( 3 + 1 ) ?> -spacetime pins down a smooth structure on the underlying four-manifold. In this paper, we point out that the diffeomorphism type of a globally hyperbolic ( n + 1 ) ?> -spacetime is determined by the h-cobordism class of its Cauchy surface, hence extending Chernov–Nemirovskiʼs observation to arbitrary dimensions.
Visualizing criminal networks reconstructed from mobile phone records

In the fight against the racketeering and terrorism, knowledge about the structure and the organization of criminal networks is of fundamental importance for both the investigations and the development of efficient strategies to prevent and restrain crimes. Intelligence agencies exploit information obtained from the analysis of large amounts of heterogeneous data deriving from various informative sources including the records of phone traffic, the social networks, surveillance data, interview data, experiential police data, and police intelligence files, to acquire knowledge about criminal networks and initiate accurate and destabilizing actions. In this context, visual representation techniques coordinate the exploration of the structure of the network together with the metrics of social network analysis. Nevertheless, the utility of visualization tools may become limited when the dimension and the complexity of the system under analysis grow beyond certain terms. In this paper we show how we employ some interactive visualization techniques to represent criminal and terrorist networks reconstructed from phone traffic data, namely foci, fisheye and geo-mapping network layouts. These methods allow the exploration of the network through animated transitions among visualization models and local enlargement techniques in order to improve the comprehension of interesting areas. By combining the features of the various visualization models it is possible to gain substantial enhancements with respect to classic visualization models, often unreadable in those cases of great complexity of the network.
Quantum Dynamics, Minkowski-Hilbert space, and A Quantum Stochastic Duhamel Principle

In this paper we shall re-visit the well-known Schr\"odinger and Lindblad dynamics of quantum mechanics. However, these equations may be realized as the consequence of a more general, underlying dynamical process. In both cases we shall see that the evolution of a quantum state $P_\psi=\varrho(0)$ has the not so well-known pseudo-quadratic form $\partial_t\varrho(t)=\mathbf{V}^\star\varrho(t)\mathbf{V}$ where $\mathbf{V}$ is a vector operator in a complex Minkowski space and the pseudo-adjoint $\mathbf{V}^\star$ is induced by the Minkowski metric $\boldsymbol{\eta}$. The interesting thing about this formalism is that its derivation has very deep roots in a new understanding of the differential calculus of time. This Minkowski-Hilbert representation of quantum dynamics is called the \emph{Belavkin Formalism}; a beautiful, but not well understood theory of mathematical physics that understands that both deterministic and stochastic dynamics may be `unraveled' in a second-quantized Minkowski space. Working in such a space provided the author with the means to construct a QS (quantum stochastic) Duhamel principle and known applications to a Schr\"odinger dynamics perturbed by a continual measurement process are considered. What is not known, but presented here, is the role of the Lorentz transform in quantum measurement, and the appearance of Riemannian geometry in quantum measurement is also discussed.
Understanding the group dynamics and success of teams

Complex problems often require coordinated group effort and can consume significant resources, yet our understanding of how teams form and succeed has been limited by a lack of large-scale, quantitative data. We analyse activity traces and success levels for approximately 150 000 self-organized, online team projects. While larger teams tend to be more successful, workload is highly focused across the team, with only a few members performing most work. We find that highly successful teams are significantly more focused than average teams of the same size, that their members have worked on more diverse sets of projects, and the members of highly successful teams are more likely to be core members or ‘leads’ of other teams. The relations between team success and size, focus and especially team experience cannot be explained by confounding factors such as team age, external contributions from non-team members, nor by group mechanisms such as social loafing. Taken together, these features point to organizational principles that may maximize the success of collaborative endeavours.
Complex entangling surfaces for AdS and Lifshitz black holes?

We discuss the possible relevance of complex codimension-two extremal surfaces to the Ryu–Takayanagi holographic entanglement proposal and its covariant Hubeny–Rangamani–Takayanagi generalization. Such surfaces live in a complexified bulk spacetime defined by analytic continuation. We identify surfaces of this type for BTZ, Schwarzschild–AdS, and Schwarzschild–Lifshitz planar black holes. Since the dual CFT interpretation for the imaginary part of their areas is unclear, we focus on a straw man proposal relating CFT entropy to the real part of the area alone. For Schwarzschild–AdS and Schwarzschild–Lifshitz, we identify families where the real part of the area agrees with qualitative physical expectations for the time-dependence of the appropriate CFT entropy and, in addition, where it is smaller than the area of corresponding real extremal surfaces. It is thus plausible that the CFT entropy is controlled by these complex extremal surfaces.
Deconfined criticality in bilayer graphene

We propose that bilayer graphene can provide an experimental realization of deconfined criticality. Current experiments indicate the presence of N\'{e}el order in the presence of a moderate magnetic field. The N\'{e}el order can be destabilized by application of a transverse electric field. The resulting electric field induced state is likely to have valence bond solid order, and the transition can acquire the emergent fractionalized and gauge excitations of deconfined criticality.
WIDE COOL AND ULTRACOOL COMPANIONS TO NEARBY STARS FROM Pan-STARRS 1

We present the discovery of 57 wide (>5″) separation, low-mass (stellar and substellar) companions to stars in the solar neighborhood identified from Pan-STARRS 1 (PS1) data and the spectral classification of 31 previously known companions. Our companions represent a selective subsample of promising candidates and span a range in spectral type of K7–L9 with the addition of one DA white dwarf. These were identified primarily from a dedicated common proper motion search around nearby stars, along with a few as serendipitous discoveries from our Pan-STARRS 1 brown dwarf search. Our discoveries include 23 new L dwarf companions and one known L dwarf not previously identified as a companion. The primary stars around which we searched for companions come from a list of bright stars with well-measured parallaxes and large proper motions from the Hipparcos catalog (8583 stars, mostly A–K dwarfs) and fainter stars from other proper motion catalogs (79170 stars, mostly M dwarfs). We examine the likelihood that our companions are chance alignments between unrelated stars and conclude that this is unlikely for the majority of the objects that we have followed-up spectroscopically. We also examine the entire population of ultracool (>M7) dwarf companions and conclude that while some are loosely bound, most are unlikely to be disrupted over the course of ∼10 Gyr. Our search increases the number of ultracool M dwarf companions wider than 300 AU by 88% and increases the number of L dwarf companions in the same separation range by 82%. Finally, we resolve our new L dwarf companion to HIP 6407 into a tight (0.″13, 7.4 AU) L1+T3 binary, making the system a hierarchical triple. Our search for these key benchmarks against which brown dwarf and exoplanet atmosphere models are tested has yielded the largest number of discoveries to date.
Explosive metallic breakdown

We investigate the metallic breakdown of a substrate on which highly conducting particles are adsorbed and desorbed with a probability that depends on the local electric field. We find that, by tuning the relative strength $q$ of this dependence, the breakdown can change from continuous to explosive. Precisely, in the limit in which the adsorption probability is the same for any finite voltage drop, we can map our model exactly onto the $q$-state Potts model and thus the transition to a jump occurs at $q=4$. In another limit, where the adsorption probability becomes independent of the local field strength, the traditional bond percolation model is recovered. Our model is thus an example of a possible experimental realization exhibiting a truly discontinuous percolation transition.