nils-herrmann/clean_scirepeval huggingface dataset:
On the Use of Human Mobility Proxies for Modeling Epidemics

Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Correctly modeling and quantifying human mobility is critical for improving epidemic control, but may be hindered by data incompleteness or unavailability. Here we explore the opportunity of using proxies for individual mobility to describe commuting flows and predict the diffusion of an influenza-like-illness epidemic. We consider three European countries and the corresponding commuting networks at different resolution scales, obtained from (i) official census surveys, (ii) proxy mobility data extracted from mobile phone call records, and (iii) the radiation model calibrated with census data. Metapopulation models defined on these countries and integrating the different mobility layers are compared in terms of epidemic observables. We show that commuting networks from mobile phone data capture the empirical commuting patterns well, accounting for more than 87% of the total fluxes. The distributions of commuting fluxes per link from mobile phones and census sources are similar and highly correlated, however a systematic overestimation of commuting traffic in the mobile phone data is observed. This leads to epidemics that spread faster than on census commuting networks, once the mobile phone commuting network is considered in the epidemic model, however preserving to a high degree the order of infection of newly affected locations. Proxies' calibration affects the arrival times' agreement across different models, and the observed topological and traffic discrepancies among mobility sources alter the resulting epidemic invasion patterns. Results also suggest that proxies perform differently in approximating commuting patterns for disease spread at different resolution scales, with the radiation model showing higher accuracy than mobile phone data when the seed is central in the network, the opposite being observed for peripheral locations. Proxies should therefore be chosen in light of the desired accuracy for the epidemic situation under study.
Flavor Physics and Lattice QCD

Our ability to resolve new physics effects is, largely, limited by the precision with which we calculate. The calculation of observables in the Standard (or a new physics) Model requires knowledge of associated hadronic contributions. The precision of such calculations, and therefore our ability to leverage experiment, is typically limited by hadronic uncertainties. The only first-principles method for calculating the nonperturbative, hadronic contributions is lattice QCD. Modern lattice calculations have controlled errors, are systematically improvable, and in some cases, are pushing the sub-percent level of precision. I outline the role played by, highlight state of the art efforts in, and discuss possible future directions of lattice calculations in flavor physics.
Timeline generation: tracking individuals on twitter

In this paper, we preliminarily learn the problem of reconstructing users' life history based on the their Twitter stream and proposed an unsupervised framework that create a chronological list for personal important events (PIE) of individuals. By analyzing individ- ual tweet collections, we find that what are suitable for inclusion in the personal timeline should be tweets talking about personal (as opposed to public) and time-specific (as opposed to time-general) topics. To further extract these types of topics, we introduce a non-parametric multi-level Dirichlet Process model to recognize four types of tweets: personal time-specific (PersonTS), personal time-general (PersonTG), public time-specific (PublicTS) and pub- lic time-general (PublicTG) topics, which, in turn, are used for fur- ther personal event extraction and timeline generation. To the best of our knowledge, this is the first work focused on the generation of timeline for individuals from Twitter data. For evaluation, we have built gold standard timelines that contain PIE related events from 20 ordinary twitter users and 20 celebrities. Experimental results demonstrate that it is feasible to automatically extract chronologi- cal timelines for Twitter users from their tweet collection
Knock-on damage in bilayer graphene: Indications for a catalytic pathway

We study by high-resolution transmission electron microscopy the structural response of bilayer graphene to electron irradiation with energies below the knock-on damage threshold of graphene. We observe that one type of divacancy, which we refer to as the butterfly defect, is formed for radiation energies and doses for which no vacancies are formed in clean monolayer graphene. By using first principles calculations based on density-functional theory, we analyze two possible causes related with the presence of a second layer that could explain the observed phenomenon: an increase of the defect stability or a catalytic effect during its creation. For the former, the obtained formation energies of the defect in monolayer and bilayer systems show that the change in stability is negligible. For the latter, ab initio molecular dynamics simulations indicate that the threshold energy for direct expulsion does not decrease in bilayer graphene as compared with monolayer graphene, and we demonstrate the possibility of creating divacancies through catalyzed intermediate states below this threshold energy. The estimated cross section agrees with what is observed experimentally. Therefore, we show the possibility of a catalytic pathway for creating vacancies under electron radiation below the expulsion threshold energy.
Freeze-in through portals

The popular freeze-out paradigm for Dark Matter (DM) production, relies on DM-baryon couplings of the order of the weak interactions. However, different search strategies for DM have failed to provide a conclusive evidence of such (non-gravitational) interactions, while greatly reducing the parameter space of many representative models. This motivates the study of alternative mechanisms for DM genesis. In the freeze-in framework, the DM is slowly populated from the thermal bath while never reaching equilibrium. In this work, we analyse in detail the possibility of producing a frozen-in DM via a mediator particle which acts as a portal. We give analytical estimates of different freeze-in regimes and support them with full numerical analyses, taking into account the proper distribution functions of bath particles. Finally, we constrain the parameter space of generic models by requiring agreement with DM relic abundance observations.
Sharpening the second law of thermodynamics with the quantum Bayes theorem.

We prove a generalization of the classic Groenewold-Lindblad entropy inequality, combining decoherence and the quantum Bayes theorem into a simple unified picture where decoherence increases entropy while observation decreases it. This provides a rigorous quantum-mechanical version of the second law of thermodynamics, governing how the entropy of a system (the entropy of its density matrix, partial-traced over the environment and conditioned on what is known) evolves under general decoherence and observation. The powerful tool of spectral majorization enables both simple alternative proofs of the classic Lindblad and Holevo inequalities without using strong subadditivity, and also novel inequalities for decoherence and observation that hold not only for von Neumann entropy, but also for arbitrary concave entropies.
Evolution of star clusters in a cosmological tidal field

We present a method to couple N-body star cluster simulations to a cosmological tidal field, using the Astrophysical Multipurpose Software Environment. We apply this method to star clusters embedded in the CosmoGrid dark matter-only LambdaCDM simulation. Our star clusters are born at z = 10 (corresponding to an age of the Universe of about 500 Myr) by selecting a dark matter particle and initializing a star cluster with 32,000 stars on its location. We then follow the dynamical evolution of the star cluster within the cosmological environment. 
We compare the evolution of star clusters in two Milky-Way size haloes with a different accretion history. The mass loss of the star clusters is continuous irrespective of the tidal history of the host halo, but major merger events tend to increase the rate of mass loss. From the selected two dark matter haloes, the halo that experienced the larger number of mergers tends to drive a smaller mass loss rate from the embedded star clusters, even though the final masses of both haloes are similar. We identify two families of star clusters: native clusters, which become part of the main halo before its final major merger event, and the immigrant clusters, which are accreted upon or after this event; native clusters tend to evaporate more quickly than immigrant clusters. Accounting for the evolution of the dark matter halo causes immigrant star clusters to retain more mass than when the z=0 tidal field is taken as a static potential. The reason for this is the weaker tidal field experienced by immigrant star clusters before merging with the larger dark matter halo.
Modeling Capital Gains Taxes for Trading Strategies of Infinite Variation

In this article, we show that the payment flow of a linear tax on trading gains from a security with a semimartingale price process can be constructed for all càglàd and adapted trading strategies. It is characterized as the unique continuous extension of the tax payments for elementary strategies w.r.t. the convergence “uniformly in probability.” In this framework, we prove that under quite mild assumptions dividend payoffs have almost surely a negative effect on investor’s after-tax wealth if the riskless interest rate is always positive. In addition, we give an example for tax-efficient strategies for which the tax payment flow can be computed explicitly.
Flavor Oscillation Modes In Dense Neutrino Media

We study two-flavor neutrino oscillations in homogeneous neutrino gases in which neutrinos and anti-neutrinos are in nearly pure weak interaction states initially. We find that the monopole and dipole oscillation modes can trigger flavor instabilities in the opposite neutrino mass hierarchies in a nearly isotropic neutrino gas. For a class of simple neutrino systems we are able to identify the normal modes of neutrino oscillations in the linear regime. Our results provide new insights into the recently discovered multi-azimuthal angle (MAA) instability of neutrino oscillations in supernovae.
A Model of the Mechanisms Underlying Exploratory Behaviour

A model of the mechanisms underlying exploratory behaviour, based on empirical research and refined using a computer simulation, is presented. The behaviour of killifish from two lakes, one with killifish predators and one without, was compared in the laboratory. Plotting average activity in a novel environment versus time resulted in an inverted-U-shaped curve for both groups; however, the curve for killifish from the lake without predators was (1) steeper, (2) reached a peak value earlier, (S) reached a higher peak value, and (4) subsumed less area than the curve for killifish from the lake with predators. We hypothesize that the shape of the exploration curve reflects a competition between motivational subsystems that excite and inhibit exploratory behaviour in a way that is tuned to match the affordance probabilities of the animal's environment. A computer implementation of this model produced curves which differed along the same four dimensions as differentiate the two killifish curves. All four differences were reproduced in the model by tuning a single parameter: the time-dependent component of the decay-rate of the exploration-inhibiting subsystem.
Regression Trees for Longitudinal Data

While studying response trajectory, often the population of interest may be diverse enough to exist distinct subgroups within it and the longitudinal change in response may not be uniform in these subgroups. That is, the timeslope and/or influence of covariates in longitudinal profile may vary among these different subgroups. For example, Raudenbush [21] used depression as an example to argue that it is incorrect to assume that all the people in a given population would be experiencing either increasing or decreasing levels of depression. In such cases, traditional linear mixed effects model (assuming common parametric form for covariates and time) is not directly applicable for the entire population as a group-averaged trajectory can mask important subgroup differences. Our aim is to identify and characterize longitudinally homogeneous subgroups based on the combination of baseline covariates in the most parsimonious way. This goal can be achieved via constructing regression tree for longitudinal data using baseline covariates as partitioning variables. We have proposed LongCART algorithm to construct regression tree for the longitudinal data. In each node, the proposed LongCART algorithm determines the need for further splitting (i.e. whether parameter(s) of longitudinal profile is influenced by any baseline attributes) via parameter instability tests and thus the decision of further splitting is type-I error controlled. We have obtained the asymptotic results for the proposed instability test and examined finite sample behavior of the whole algorithm through simulation studies. Finally, we have applied the LongCART algorithm to study the longitudinal changes in choline level among HIV patients.
Probabilistic Aspects of Finance

In the past decades, advanced probabilistic methods have had significant impact on the field of finance, both in academia and in the financial industry. Conversely, financial questions have stimulated new research directions in probability. In this survey paper, we review some of these developments and point to some areas that might deserve further investigation. We start by reviewing the basics of arbitrage pricing theory, with special emphasis on incomplete markets and on the different roles played by the "real-world" probability measure and its equivalent martingale measures. We then focus on the issue of model ambiguity, also called Knightian uncertainty. We present two case studies in which it is possible to deal with Knightian uncertainty in mathematical terms. The first case study concerns the hedging of derivatives, such as variance swaps, in a strictly pathwise sense. The second one deals with capital requirements and preferences specified by convex and coherent risk measures. In the final two sections we discuss mathematical issues arising from the dramatic increase of algorithmic trading in modern financial markets.
Known Unknowns of Dark Matter Annihilation over Cosmic Time

Dark matter self-annihilation holds promise as one of the most robust mechanisms for the identification of the particle responsible for the Universe's missing mass. In this work, I examine the evolution of the dark matter annihilation power produced by smooth and collapsed structures over cosmic time, taking into account uncertainties in the structure of dark matter halos. As we search for observational signatures of annihilation, an understanding of this time evolution will help us to best direct our observational efforts, either with local measurements or investigation of the effects of annihilation on the intergalactic medium at high redshift. As I show in this work, there are several key sources of uncertainty in our ability to estimate the dark matter annihilation from collapsed structures, including: the density profile of dark matter halos; the small-scale cut-off in the dark matter halo mass function; the redshift-dependent mass-concentration relation for small halos; and the particle-velocity dependence of the dark matter annihilation process. Varying assumptions about these quantities can result in annihilation power predictions that differ by several orders of magnitude. These uncertainties must be resolved, through a combination of observation and modeling, before robust estimations of the cosmological annihilation signal can be made.
Does information have mass? [Point of View]

This article addresses the fundamental question of minimum mass related to a bit of information from the angles of quantum physics and special relativity. The results indicate that there are different answers depending on the physical situation, and sometimes the mass can even be negative. It tends to be skeptical about the earlier mass estimations, mentioned above, because the results indicate that the electron's mass does not play a role in any one of them. Finally, in a seemingly related but actually different and independent context of measured inaccuracies of the gravitation constant, it refers to experiments on the weight transient of memory devices after information writing and erasure.
THE COSMIC EVOLUTION OF FERMI BL LACERTAE OBJECTS

Fermi has provided the largest sample of γ-ray-selected blazars to date. In this work we use a uniformly selected set of 211 BL Lacertae (BL Lac) objects detected by Fermi during its first year of operation. We obtained redshift constraints for 206 out of the 211 BL Lac objects in our sample, making it the largest and most complete sample of BL Lac objects available in the literature. We use this sample to determine the luminosity function of BL Lac objects and its evolution with cosmic time. We find that for most BL Lac classes the evolution is positive, with a space density peaking at modest redshift (z ≈ 1.2). Low-luminosity, high-synchrotron–peaked (HSP) BL Lac objects are an exception, showing strong negative evolution, with number density increasing for z ≲ 0.5. Since this rise corresponds to a drop-off in the density of flat-spectrum radio quasars (FSRQs), a possible interpretation is that these HSPs represent an accretion-starved end state of an earlier merger-driven gas-rich phase. We additionally find that the known BL Lac correlation between luminosity and photon spectral index persists after correction for the substantial observational selection effects with implications for the so-called “blazar sequence.” Finally, by estimating the beaming corrections to the luminosity function, we find that BL Lac objects have an average Lorentz factor of , and that most are seen within 10° of the jet axis.
Energy spectrum of gravitational waves in a loop quantum cosmological model

We explore the consequences of loop quantum cosmology (inverse-volume corrections) in the spectrum of the gravitational waves using the method of the Bogoliubov coefficients. These corrections are taken into account at the background level of the theory as well as at the first order in the perturbations theory framework. We show that these corrections lead to an intense graviton production during the loop super-inflationary phase prior to the standard slow-roll era, which leave their imprints through new features on the energy spectrum of the gravitational waves as would be measured today, including a new maximum on the low frequency end of the spectrum.
Ion-photon entanglement and Bell inequality violation with ^138Ba^+

We report on the demonstration of ion–photon entanglement and Bell inequality violation in a system of trapped Ba138+ ions. Entanglement between the Zeeman sublevels of the ground state of a single Ba138+ ion and the polarization state of a single 493 nm photon emitted by the ion with a fidelity of 0.84±0.01 was achieved, along with a Bell signal of 2.3, exceeding the classical limit of 2 by more than eight standard deviations. This system is a promising candidate for a loophole-free Bell inequality violation test using long-range ion–ion entanglement as the wavelengths of the transitions of Ba138+ are in the visible region and thus suitable for long-range transmission over fiber optic cable.
The elliptic model for communication fluxes

In this paper, a model (called the elliptic model) is proposed to estimate the number of social ties between two locations using population data in a similar manner to how transportation research deals with trips. To overcome the asymmetry of transportation models, the new model considers that the number of relationships between two locations is inversely proportional to the population in the ellipse whose foci are in these two locations. The elliptic model is evaluated by considering the anonymous communications patterns of 25 million users from three different countries, where a location has been assigned to each user based on their most used phone tower or billing zip code. With this information, spatial social networks are built at three levels of resolution: tower, city and region for each of the three countries. The elliptic model achieves a similar performance when predicting communication fluxes as transportation models do when predicting trips. This shows that human relationships are influenced at least as much by geography as is human mobility.
Massive spin-2 theories

We give an introduction to massive spin-2 theories and the problem of their non-linear completion. We review the Boulware-Deser ghost problem and two ways to circumvent classic no-go theorems. In turn, massive spin-2 theories are not uniquely defined. In the case of truncated theories, we show that the Boulware-Deser ghost may only be avoided if the derivative structure of the theory is not tuned to be Einsteinian.
The Effective Field Theory of Large Scale Structures at two loops

Large scale structure surveys promise to be the next leading probe of cosmological information. It is therefore crucial to reliably predict their observables. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a manifestly convergent perturbation theory for the weakly non-linear regime of dark matter, where correlation functions are computed in an expansion of the wavenumber k of a mode over the wavenumber associated with the non-linear scale kNL. Since most of the information is contained at high wavenumbers, it is necessary to compute higher order corrections to correlation functions. After the one-loop correction to the matter power spectrum, we estimate that the next leading one is the two-loop contribution, which we compute here. At this order in k/kNL, there is only one counterterm in the EFTofLSS that must be included, though this term contributes both at tree-level and in several one-loop diagrams. We also discuss correlation functions involving the velocity and momentum fields. We find that the EFTofLSS prediction at two loops matches to percent accuracy the non-linear matter power spectrum at redshift zero up to k∼ 0.6 h Mpc−1, requiring just one unknown coefficient that needs to be fit to observations. Given that Standard Perturbation Theory stops converging at redshift zero at k∼ 0.1 h Mpc−1, our results demonstrate the possibility of accessing a factor of order 200 more dark matter quasi-linear modes than naively expected. If the remaining observational challenges to accessing these modes can be addressed with similar success, our results show that there is tremendous potential for large scale structure surveys to explore the primordial universe.
Evidence that Cross-Domain Re-interpretations of Creative Ideas are Recognizable

The goal of this study was to investigate the translate-ability of creative works into other domains. We tested whether people were able to recognize which works of art were inspired by which pieces of music. Three expert painters created four paintings, each of which was the artist’s interpretation of one of four different pieces of instrumental music. Participants were able to identify which paintings were inspired by which pieces of music at statistically significant above-chance levels. The findings support the hypothesis that creative ideas can exist in an at least somewhat domain-independent state of potentiality and become more well-defined as they are actualized in accordance with the constraints of a particular domain.