nils-herrmann/clean_scirepeval huggingface dataset:
The Information Service Evaluation (ISE) Model

Information services are an inherent part of our everyday life. Especially since ubiquitous cities are being developed all over the world their number is increasing even faster. They aim at facilitating the production of information and the access to the needed information and are supposed to make life easier. Until today many different evaluation models (among others, TAM, TAM 2, TAM 3, UTAUT and MATH) have been developed to measure the quality and acceptance of these services. Still, they only consider subareas of the whole concept that represents an information service. As a holistic and comprehensive approach, the ISE Model studies five dimensions that influence adoption, use, impact and diffusion of the information service: information service quality, information user, information acceptance, information environment and time. All these aspects have a great impact on the final grading and of the success (or failure) of the service. Our model combines approaches, which study subjective impressions of users (e.g., the perceived service quality), and user-independent, more objective approaches (e.g., the degree of gamification of a system). Furthermore, we adopt results of network economics, especially the Success breeds success-principle.
Are singularities the limits of cosmology

We refer to the classic definition of a singularity in Einstein's general relativity (based on geodesic incompletness) as well as to some other criteria to evaluate the nature of singularities in cosmology. We review what different (non-Big-Bang) types of singularities are possible even in the simplest cosmological framework of Friedmann cosmology. We also show that various cosmological singularities may be removed or changed due to the variability of physical constants.
D4D-Senegal: The Second Mobile Phone Data for Development Challenge

The D4D-Senegal challenge is an open innovation data challenge on anonymous call patterns of Orange's mobile phone users in Senegal. The goal of the challenge is to help address society development questions in novel ways by contributing to the socio-economic development and well-being of the Senegalese population. Participants to the challenge are given access to three mobile phone datasets. This paper describes the three datasets. The datasets are based on Call Detail Records (CDR) of phone calls and text exchanges between more than 9 million of Orange's customers in Senegal between January 1, 2013 to December 31, 2013. The datasets are: (1) antenna-to-antenna traffic for 1666 antennas on an hourly basis, (2) fine-grained mobility data on a rolling 2-week basis for a year with bandicoot behavioral indicators at individual level for about 300,000 randomly sampled users, (3) one year of coarse-grained mobility data at arrondissement level with bandicoot behavioral indicators at individual level for about 150,000 randomly sampled users
Nightfall: Can Kalgash Exist

We investigate the imaginary world of Kalgash, a planetary system based on the novel "Nightfall" (Asimov & Silverberg, 1991). The system consists of a planet, a moon and an astonishing six suns. The six stars cause the wider universe to be invisible to the inhabitants of the planet. The author explores the consequences of an eclipse and the resulting darkness which the Kalgash people experience for the first time. Our task is to verify if this system is feasible, from the duration of the eclipse, the "invisibility" of the universe to the complex orbital dynamics.
Friends or Foes: Distributed and Randomized Algorithms to Determine Dishonest Recommenders in Online Social Networks

Viral marketing is becoming important due to the popularity of online social networks (OSNs). Companies may provide incentives (e.g., via free samples of a product) to a small group of users in an OSN, and these users provide recommendations to their friends, which eventually increases the overall sales of a given product. Nevertheless, this also opens a door for malicious behaviors: dishonest users may intentionally give misleading recommendations to their friends so as to distort the normal sales distribution. In this paper, we propose a detection framework to identify dishonest users in the OSNs. In particular, we present a set of fully distributed and randomized algorithms, and also quantify the performance of the algorithms by deriving probability of false positive, probability of false negative, and the distribution of number of detection rounds. Extensive simulations are also carried out to illustrate the impact of misleading recommendations and the effectiveness of our detection algorithms. The methodology we present here will enhance the security level of viral marketing in the OSNs.
An exact and explicit formula for pricing Asian options with regime switching

This paper studies the pricing of European-style Asian options when the price dynamics of the underlying risky asset are assumed to follow a Markov- modulated geometric Brownian motion; that is, the appreciation rate and the volatility of the underlying risky asset depend on unobservable states of the economy described by a continuous-time hidden Markov process. We derive the exact, explicit and closed-form solutions for European-style Asian options in a two-state regime switching model.
PageRank beyond the Web

Google's PageRank method was developed to evaluate the importance of web-pages via their link structure. The mathematics of PageRank, however, are entirely general and apply to any graph or network in any domain. Thus, PageRank is now regularly used in bibliometrics, social and information network analysis, and for link prediction and recommendation. It's even used for systems analysis of road networks, as well as biology, chemistry, neuroscience, and physics. We'll see the mathematics and ideas that unite these diverse applications.
Probing layer localization in twisted graphene bilayers via cyclotron resonance

Electron wavefunctions in twisted bilayer graphene may have a strong single layer character or be intrinsically delocalized between layers, with their nature often determined by how energetically close they are to the Dirac point. In this paper, we demonstrate that in magnetic fields, optical absorption (cyclotron resonance) spectra contain signatures which may be used to distinguish the nature of these wavefunctions at low energies, as well as to locate low energy critical points in the zero-field energy spectrum. Optical absorption for two different configurations -- electric field parallel and perpendicular to the bilayer -- are calculated, which are shown to have different selection rules with respect to which states are connected by the perturbation. Interlayer bias further distinguishes transitions involving states of a single layer nature from those with support in both layers. For doped systems, a sharp increase in intra-Landau level absorption occurs with increasing field as the level passes through the zero-field saddle point energy, where the states change character from single layer to bilayer.
Tight convex relaxations for sparse matrix factorization

Based on a new atomic norm, we propose a new convex formulation for sparse matrix factorization problems in which the number of non-zero elements of the factors is assumed fixed and known. The formulation counts sparse PCA with multiple factors, subspace clustering and low-rank sparse bilinear regression as potential applications. We compute slow rates and an upper bound on the statistical dimension  of the suggested norm for rank 1 matrices, showing that its statistical dimension is an order of magnitude smaller than the usual l1-norm, trace norm and their combinations. Even though our convex formulation is in theory hard and does not lead to provably polynomial time algorithmic schemes, we propose an active set algorithm leveraging the structure of the convex problem to solve it and show promising numerical results.
Highly stable polarization independent Mach-Zehnder interferometer.

We experimentally demonstrate optical Mach-Zehnder interferometer utilizing displaced Sagnac configuration to enhance its phase stability. The interferometer with footprint of 27×40 cm offers individually accessible paths and shows phase deviation less than 0.4° during a 250 s long measurement. The phase drift, evaluated by means of Allan deviation, stays below 3° or 7 nm for 1.5 h without any active stabilization. The polarization insensitive design is verified by measuring interference visibility as a function of input polarization. For both interferometer's output ports and all tested polarization states the visibility stays above 93%. The discrepancy in visibility for horizontal and vertical polarization about 3.5% is caused mainly by undesired polarization dependence of splitting ratio of the beam splitter used. The presented interferometer device is suitable for quantum-information and other sensitive applications where active stabilization is complicated and common-mode interferometer is not an option as both the interferometer arms have to be accessible individually.
Context Aware Dynamic Traffic Signal Optimization

Conventional urban traffic control systems have been based on historical traffic data. Later advancements made use of detectors, which enabled the gathering of real time traffic data, in order to reorganize and calibrate traffic signalization programs. Further evolvement provided the ability to forecast traffic conditions, in order to develop traffic signalization programs and strategies precomputed and applied at the most appropriate time frame for the optimal control of the current traffic conditions. We, propose the next generation of traffic control systems based on principles of Artificial Intelligence and Context Awareness. Most of the existing algorithms use average waiting time or length of the queue to assess an algorithms performance. However, a low average waiting time may come at the cost of delaying other vehicles indefinitely. In our algorithm, besides the vehicle queue, we use fairness also as an important performance metric to assess an algorithms performance.
Small oscillations via conservation of energy

The work describes an analogy-based small oscillations analysis of a standard static equilibrium lab problem. In addition to force analysis, a potential energy function for the system is developed, and by drawing out mathematical similarities to the simple harmonic oscillator, we are able to describe (and experimentally verify) the period of small oscillations about the static equilibrium state. The problem was developed and implemented in a standard University Physics course at Winona State University.
Minimal model of stochastic athermal systems: origin of non-Gaussian noise.

For a wide class of stochastic athermal systems, we derive Langevin-like equations driven by non-Gaussian noise, starting from master equations and developing a new asymptotic expansion. We found an explicit condition whereby the non-Gaussian properties of the athermal noise become dominant for tracer particles associated with both thermal and athermal environments. Furthermore, we derive an inverse formula to infer microscopic properties of the athermal bath from the statistics of the tracer particle. We apply our formulation to a granular motor under viscous friction and analytically obtain the angular velocity distribution function. Our theory demonstrates that the non-Gaussian Langevin equation is the minimal model of athermal systems.
An investigation of the false discovery rate and the misinterpretation of p-values

If you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations of t-tests. These mimic what is done in real life, which makes the results more persuasive. The simulation method is used also to evaluate the extent to which effect sizes are over-estimated, especially in underpowered experiments. A script is supplied to allow the reader to do simulations themselves, with numbers appropriate for their own work. It is concluded that if you wish to keep your false discovery rate below 5%, you need to use a three-sigma rule, or to insist on p≤0.001. And never use the word ‘significant’.
Interplay of network dynamics and ties heterogeneity on spreading dynamics

The structure of a network dramatically affects the spreading phenomena unfolding upon it. The contact distribution of the nodes has long been recognized as the key ingredient in influencing the outbreak events. However, limited knowledge is currently available on the role of the weight of the edges on the persistence of a pathogen. At the same time, recent works showed a strong influence of temporal network dynamics on disease spreading. In this work we provide an analytical understanding, corroborated by numerical simulations, about the conditions for infected stable state in weighted networks. In particular, we reveal the role of heterogeneity of edge weights and of the dynamic assignment of weights on the ties in the network in driving the spread of the epidemic. In this context we show that when weights are dynamically assigned to ties in the network, a heterogeneous distribution is able to hamper the diffusion of the disease, contrary to what happens when weights are fixed in time.
Reading the source code of social ties

Though online social network research has exploded during the past years, not much thought has been given to the exploration of the nature of social links. Online interactions have been interpreted as indicative of one social process or another (e.g., status exchange or trust), often with little systematic justification regarding the relation between observed data and theoretical concept. Our research aims to breach this gap in computational social science by proposing an unsupervised, parameter-free method to discover, with high accuracy, the fundamental domains of interaction occurring in social networks. By applying this method on two online datasets different by scope and type of interaction (aNobii and Flickr) we observe the spontaneous emergence of three domains of interaction representing the exchange of status, knowledge and social support. By finding significant relations between the domains of interaction and classic social network analysis issues (e.g., tie strength, dyadic interaction over time) we show how the network of interactions induced by the extracted domains can be used as a starting point for more nuanced analysis of online social data that may one day incorporate the normative grammar of social interaction. Our methods finds applications in online social media services ranging from recommendation to visual link summarization.
Contribution of evanescent waves to the effective medium of disordered waveguides

We consider a wave propagating through a thin disordered slab inside a wire or waveguide of finite width. In the dense weak-scattering limit, the statistics for the complex reflection and transmission coefficients (the coherent field) is found to depend dramatically on the contribution of evanescent modes or closed channels, leading to an effective refractive index whose real part is quite sensitive to the closed-channels inclusion. In contrast, evanescent modes play no role in the statistical average of transmittances and reflectances. The theoretical predictions, based on the perturbative Born series expansion, are in excellent agreement with numerical simulations in disordered wires.
Scalable tight-binding model for graphene.

Artificial graphene consisting of honeycomb lattices other than the atomic layer of carbon has been shown to exhibit electronic properties similar to real graphene. Here, we reverse the argument to show that transport properties of real graphene can be captured by simulations using "theoretical artificial graphene." To prove this, we first derive a simple condition, along with its restrictions, to achieve band structure invariance for a scalable graphene lattice. We then present transport measurements for an ultraclean suspended single-layer graphene pn junction device, where ballistic transport features from complex Fabry-Pérot interference (at zero magnetic field) to the quantum Hall effect (at unusually low field) are observed and are well reproduced by transport simulations based on properly scaled single-particle tight-binding models. Our findings indicate that transport simulations for graphene can be efficiently performed with a strongly reduced number of atomic sites, allowing for reliable predictions for electric properties of complex graphene devices. We demonstrate the capability of the model by applying it to predict so-far unexplored gate-defined conductance quantization in single-layer graphene.
An Aharonov-Bohm interferometer for determining Bloch band topology

Nailing down graphene's topology An electron traveling along a closed path in the momentum space of the graphene crystal lattice may not end up exactly the way it started. If its path happens to include one of the special points in momentum space, it will acquire a phase shift. Physicists can detect the signatures of this process by studying the transport properties of graphene. Duca et al. used interferometry to directly measure this so-called Berry flux in a hexagonal optical lattice, where intersecting laser beams simulate the environment that electrons experience in graphene (see the Perspective by Lamacraft). The high-precision technique may be useful in characterizing other topological structures. Science, this issue p. 288; see also p. 232 Interferometric techniques are used to measure the Berry flux in the momentum space of a hexagonal optical lattice.  The geometric structure of a single-particle energy band in a solid is fundamental for a wide range of many-body phenomena and is uniquely characterized by the distribution of Berry curvature over the Brillouin zone. We realize an atomic interferometer to measure Berry flux in momentum space, in analogy to an Aharonov-Bohm interferometer that measures magnetic flux in real space. We demonstrate the interferometer for a graphene-type hexagonal optical lattice loaded with bosonic atoms. By detecting the singular π Berry flux localized at each Dirac point, we establish the high momentum resolution of this interferometric technique. Our work forms the basis for a general framework to fully characterize topological band structures.
New Modified Mimetic Gravity

A modified Mimetic gravity (MMG) is proposed as a generalization of general relativity. The model contain a physical metric which is function of an auxiliary (unphysical) metric and a Lyra's metric. We construct different kinds of conformally invariant models in different levels of the expansion parameter $\lambda$. This model phenomenologically has been extended to higher order forms. Cosmology of a certain class of such models has been investigated in details. A cosmological solution has been proposed in inhomogeneous form of scalar field. For homogenous case, energy conditions are widely investigated. We have shown that the system evaluated at intervals shorter than a certain time $T_c$ meets all the energy conditions.
A framework for reversible circuit complexity

Reversible single-target gates are a generalization of Toffoli gates which are a helpful formal representation for the description of synthesis algorithms but are too general for an actual implementation based on some technology. There is an exponential lower bound on the number of Toffoli gates required to implement any reversible function, however, there is also a linear upper bound on the number of single-target gates which can be proven using a constructive proof based on a former presented synthesis algorithm. Since single-target gates can be mapped to a cascade of Toffoli gates, this synthesis algorithm provides an interesting framework for reversible circuit complexity. The paper motivates this framework and illustrates first possible applications based on it.
TRANSPARENT HELIUM IN STRIPPED ENVELOPE SUPERNOVAE

Using simple arguments based on photometric light curves and velocity evolution, we propose that some stripped envelope supernovae (SNe) show signs that a significant fraction of their helium is effectively transparent. The main pieces of evidence are the relatively low velocities with little velocity evolution, as are expected deep inside an exploding star, along with temperatures that are too low to ionize helium. This means that the helium should not contribute to the shaping of the main SN light curve, and thus the total helium mass may be difficult to measure from simple light curve modeling. Conversely, such modeling may be more useful for constraining the mass of the carbon/oxygen core of the SN progenitor. Other stripped envelope SNe show higher velocities and larger velocity gradients, which require an additional opacity source (perhaps the mixing of heavier elements or radioactive nickel) to prevent the helium from being transparent. We discuss ways in which similar analysis can provide insights into the differences and similarities between SNe Ib and Ic, which will lead to a better understanding of their respective formation mechanisms.
Creation of wormholes by quantum tunnelling in modified gravity theories

We study the process of quantum tunnelling in scalar-tensor theories in which the scalar field is non-minimally coupled to gravity. In these theories gravitational instantons can deviate substantially from sphericity and can in fact develop a neck - a feature prohibited in theories with minimal coupling. Such instantons with necks lead to the materialisation of bubble geometries containing a wormhole region. We clarify the relationship of neck geometries to violations of the null energy condition, and also derive a bound on the size of the neck relative to that of the instanton.
Event-shape fluctuations and flow correlations in ultra-relativistic heavy-ion collisions

I review recent measurements of a large set of flow observables associated with event-shape fluctuations and collective expansion in heavy ion collisions. First, these flow observables are classified and experiment methods are introduced. The experimental results for each type of observables are then presented and compared to theoretical calculations. A coherent picture of initial condition and collective flow based on linear and nonlinear hydrodynamic responses is derived, which qualitatively describe most experimental results. I discuss new types of fluctuation measurements that can further our understanding of the event-shape fluctuations and collective expansion dynamics.
Detecting Flow Anomalies in Distributed Systems

Deep within the networks of distributed systems, one often finds anomalies that affect their efficiency and performance. These anomalies are difficult to detect because the distributed systems may not have sufficient sensors to monitor the flow of traffic within the interconnected nodes of the networks. Without early detection and making corrections, these anomalies may aggravate over time and could possibly cause disastrous outcomes in the system in the unforeseeable future. Using only coarse-grained information from the two end points of network flows, we propose a network transmission model and a localization algorithm, to detect the location of anomalies and rank them using a proposed metric within distributed systems. We evaluate our approach on passengers' records of an urbanized city's public transportation system and correlate our findings with passengers' postings on social media micro blogs. Our experiments show that the metric derived using our localization algorithm gives a better ranking of anomalies as compared to standard deviation measures from statistical models. Our case studies also demonstrate that transportation events reported in social media micro blogs matches the locations of our detect anomalies, suggesting that our algorithm performs well in locating the anomalies within distributed systems.