nils-herrmann/clean_scirepeval huggingface dataset:
Kernelized Bayesian Matrix Factorization

We extend kernelized matrix factorization with a full-Bayesian treatment and with an ability to work with multiple side information sources expressed as different kernels. Kernels have been introduced to integrate side information about the rows and columns, which is necessary for making out-of-matrix predictions. We discuss specifically binary output matrices but extensions to realvalued matrices are straightforward. We extend the state of the art in two key aspects: (i) A full-conjugate probabilistic formulation of the kernelized matrix factorization enables an efficient variational approximation, whereas full-Bayesian treatments are not computationally feasible in the earlier approaches. (ii) Multiple side information sources are included, treated as different kernels in multiple kernel learning which additionally reveals which side sources are informative. We then show that the framework can also be used for supervised and semi-supervised multilabel classification and multi-output regression, by considering samples and outputs as the domains where matrix factorization operates. Our method outperforms alternatives in predicting drug-protein interactions on two data sets. On multilabel classification, our algorithm obtains the lowest Hamming losses on 10 out of 14 data sets compared to five state-of-the-art multilabel classification algorithms. We finally show that the proposed approach outperforms alternatives in multi-output regression experiments on a yeast cell cycle data set.
Funded Bilateral Valuation Adjustment

We show how the cost of funding the collateral in a particular set up can be equal to the Bilateral Valuation Adjustment with the "funded" probability of default, leading to the definition of a Funded Bilateral Valuation Adjustment (FBVA). That set up can also be viewed by an investor as an effective way to restructure the counterparty risk arising from an uncollateralized transaction with a counterparty, mitigating or even avoiding entirely the additional capital charge introduced by the new Basel III framework.
CGB: A UNIX shell program to create custom instances of the UCSC Genome Browser

The UCSC Genome Browser is a popular tool for the exploration and analysis of reference genomes. Mirrors of the UCSC Genome Browser and its contents exist at multiple geographic locations, and this mirror procedure has been modified to support genome sequences not maintained by UCSC and generated by individual researchers. While straightforward, this procedure is lengthy and tedious and would benefit from automation, especially when processing many genome sequences. We present a Unix shell program that facilitates the creation of custom instances of the UCSC Genome Browser for genome sequences not being maintained by UCSC. It automates many steps of the browser creation process, provides password protection for each browser instance, and automates the creation of basic annotation tracks. As an example we generate a custom UCSC Genome Browser for a bacterial genome obtained from a massively parallel sequencing platform.
High-Frequency Trading Synchronizes Prices in Financial Markets

High-speed computerized trading, often called "high-frequency trading" (HFT), has increased dramatically in financial markets over the last decade. In the US and Europe, it now accounts for nearly one-half of all trades. Although evidence suggests that HFT contributes to the efficiency of markets, there are concerns it also adds to market instability, especially during times of stress. Currently, it is unclear how or why HFT produces these outcomes. In this paper, I use data from NASDAQ to show that HFT synchronizes prices in financial markets, making the values of related securities change contemporaneously. With a model, I demonstrate how price synchronization leads to increased efficiency: prices are more accurate and transaction costs are reduced. During times of stress, however, localized errors quickly propagate through the financial system if safeguards are not in place. In addition, there is potential for HFT to enforce incorrect relationships between securities, making prices more (or less) correlated than economic fundamentals warrant. This research highlights an important role that HFT plays in markets and helps answer several puzzling questions that previously seemed difficult to explain: why HFT is so prevalent, why HFT concentrates in certain securities and largely ignores others, and finally, how HFT can lower transaction costs yet still make profits.
A quantum mechanical model for the rate of return

In their activity, the traders approximate the rate of return by integer multiples of a minimal one. Therefore, it can be regarded as a quantized variable. On the other hand, there is the impossibility of observing the rate of return and its instantaneous forward time derivative, even if we consider it as a continuous variable. We present a quantum model for the rate of return based on the mathematical formalism used in the case of quantum systems with finite-dimensional Hilbert space. The rate of return is described by a discrete wave function and its time evolution by a Schodinger type equation.
Performance of the RPC-based ALICE muon trigger system at the LHC

The forward muon spectrometer of ALICE (A Large Ion Collider Experiment) is equipped with a trigger system made of four planes of Resistive Plate Chambers (RPC), arranged in two stations with two planes each, for a total area of about 140 m2 . The system provides single and di-muon triggers with suitable transverse momentum selection, optimised for the physics of quarkonia and open heavy flavour. In the first two years of data-taking at the Large Hadron Collider (2010 and 2011) the 72 RPCs were operated in highly saturated avalanche mode in both pp and Pb-Pb collisions. The integrated charge was about 1.3 mC/cm2 on average and 3.5 mC/cm2 for the most exposed detectors. This paper describes two main results. The first result is the determination of the RPC performance, with particular focus on the stability of the main detector parameters such as efficiency, dark current, and dark rate. The second result is the measurement of the muon trigger performance in Pb-Pb collisions at sqrt(s_NN) = 2.76 TeV, in terms of the reliability and stability of the trigger decision logic.
On The Origin of IceCube's PeV Neutrinos

The IceCube collaboration has recently reported the observation of two events with energies in excess of 1 PeV. While an atmospheric origin of these events cannot be ruled out at this time, this pair of showers may potentially represent the first observation of high-energy astrophysical neutrinos. In this paper, we argue that if these events are neutrino-induced, then the neutrinos are very likely to have been produced via photo-meson interactions taking place in the same class of astrophysical objects that are responsible for the acceleration of the ~ 1017 eV cosmic ray spectrum. Among the proposed sources of such cosmic rays, gamma-ray bursts stand out as particularly capable of generating PeV neutrinos at the level implied by IceCube's two events. In contrast, the radiation fields in typical active galactic nuclei models are likely dominated by lower energy (UV) photons, and thus feature higher energy thresholds for pion production, leading to neutrino spectra which peak at EeV rather than PeV energies (models with significant densities of x-ray emission, however, could evade this problem). Cosmogenic neutrinos generated from the propagation of ultra-high energy cosmic rays similarly peak at energies that are much higher than those of the events reported by IceCube.
Pathways to social evolution: reciprocity, relatedness, and synergy

Many organisms live in populations structured by space and by class, exhibit plastic responses to their social partners, and are subject to non-additive ecological and fitness effects. Social evolution theory has long recognized that all of these factors can lead to different selection pressures but has only recently attempted to synthesize how these factors interact. Using models for both discrete and continuous phenotypes, we show that analyzing these factors in a consistent framework reveals that they interact with one another in ways previously overlooked. Specifically, behavioral responses (reciprocity), genetic relatedness, and synergy interact in non-trivial ways that cannot be easily captured by simple summary indices of assortment. We demonstrate the importance of these interactions by showing how they have been neglected in previous synthetic models of social behavior both within and between species. These interactions also affect the level of behavioral responses that can evolve in the long run; proximate biological mechanisms are evolutionarily stable when they generate enough responsiveness relative to the level of responsiveness that exactly balances the ecological costs and benefits. Given the richness of social behavior across taxa, these interactions should be a boon for empirical research as they are likely crucial for describing the complex relationship linking ecology, demography, and social behavior.
Can We Explain Unexpected Fluctuation of Long-Term Real Interest Rate?

In this paper, we create a model of unexpected fluctuation of the long-term real interest rate. This model is based on our new version of IS-LM model. The new IS-LM model eliminates two main deficiencies of the original model: assumptions of constant price level and of strictly exogenous money supply. The unexpected fluctuations of the long-term real interest rate can be explained by existence of special type of cycle called relaxation oscillation on money (or financial assets) market. Relaxation oscillations include some short parts looking like "jumps". These "jumps" can be interpreted like unexpected. In other words, we try to explain these "unexpected" fluctuations of long-term real interest rate and show that these fluctuations can be only seemingly unexpected. Last but not least, we show some impacts of the government intervention by fiscal or monetary policy on economics using this models. Then we suggest possible interaction between fiscal and monetary policy.
Time-dependent 3D magnetohydrodynamic pulsar magnetospheres: oblique rotators

The current state of the art in pulsar magnetosphere modeling assumes the force-free limit of magnetospheric plasma. This limit retains only partial information about plasma velocity and neglects plasma inertia and temperature. We carried out time-dependent 3D relativistic magnetohydrodynamic (MHD) simulations of oblique pulsar magnetospheres that improve upon force-free by retaining the full plasma velocity information and capturing plasma heating in strong current layers. We find rather low levels of magnetospheric dissipation, with less than 10% of pulsar spindown energy dissipated within a few light cylinder radii, and the MHD spindown that is consistent with that in force-free. While oblique magnetospheres are qualitatively similar to the rotating split-monopole force-free solution at large radii, we find substantial quantitative differences with the split-monopole, e.g., the luminosity of the pulsar wind is more equatorially concentrated than the split-monopole at high obliquities, and the flow velocity is modified by the emergence of reconnection flow directed into the current sheet.
Nonlinear Wightman fields

A nonlinear Wightman field is taken to be a nonlinear map from a linear space of test functions to a linear space of Hilbert space operators, with inessential modifications to other axioms only to the extent dictated by the introduction of nonlinearity. Two approaches to nonlinear quantum fields are constructed and discussed, the first of which, starting from Lagrangian QFT, offers a fresh perspective on renormalization, while the second, starting from linear Wightman fields, provides an extensive range of well-defined nonlinear theories.
Hurst exponents for short time series.

A concept called balanced estimator of diffusion entropy is proposed to detect quantitatively scalings in short time series. The effectiveness is verified by detecting successfully scaling properties for a large number of artificial fractional Brownian motions. Calculations show that this method can give reliable scalings for short time series with length ~10(2). It is also used to detect scalings in the Shanghai Stock Index, five stock catalogs, and a total of 134 stocks collected from the Shanghai Stock Exchange Market. The scaling exponent for each catalog is significantly larger compared with that for the stocks included in the catalog. Selecting a window with size 650, the evolution of scaling for the Shanghai Stock Index is obtained by the window's sliding along the series. Global patterns in the evolutionary process are captured from the smoothed evolutionary curve. By comparing the patterns with the important event list in the history of the considered stock market, the evolution of scaling is matched with the stock index series. We can find that the important events fit very well with global transitions of the scaling behaviors.
Can we predict long-run economic growth?

For those concerned with the long-term value of their accounts, it can be a challenge to plan in the present for inflation-adjusted economic growth over coming decades. Here, I argue that there exists an economic constant that carries through time, and that this can help us to anticipate the more distant future: global economic wealth has a fixed link to civilization's overall rate of energy consumption from all sources; the ratio of these two quantities has not changed over the past 40 years that statistics are available. Power production and wealth rise equally quickly because civilization, like any other system in the universe, must consume and dissipate its energy reserves in order to sustain its current size. One perspective might be that financial wealth must ultimately collapse as we deplete our energy reserves. However, we can also expect that highly aggregated quantities like global wealth have inertia, and that growth rates must persist. Exceptionally rapid innovation in the two decades following 1950 allowed for unprecedented acceleration of inflation-adjusted rates of return. But today, real innovation rates are more stagnant. This means that, over the coming decade or so, global GDP and wealth should rise fairly steadily at an inflation-adjusted rate of about 2.2% per year.
A model for (non-lognormal) density distributions in isothermal turbulence

We propose a new, physically motivated fitting function for density PDFs in turbulent gas. Although it is known that when gas is isothermal, the PDF is approximately lognormal in the core, high-resolution simulations show large deviations from exact log-normality. The proposed function provides an extraordinarily accurate description of the density PDFs in simulations with Mach numbers ~0.1-15 and dispersion in log(rho) from ~0.01-4 dex. Compared to a lognormal or lognormal-skew-kurtosis model, the fits are improved by orders of magnitude in the wings of the distribution (with fewer free parameters). This is true in simulations using distinct numerical methods, including or excluding magnetic fields. Deviations from lognormality are represented by a parameter T that increases with the compressive Mach number. The proposed distribution can be derived from intermittent cascade models of the longitudinal (compressive) velocity differences, which should be directly related to density fluctuations, and we provide a simple interpretation of the density PDF as the product of a continuous-time relaxation process. As such the parameter T is consistent with the same parameter needed to explain the (intermittent) velocity structure functions; its behavior is consistent with turbulence becoming more intermittent as it becomes more dominated by strong shocks. It provides a new and unique probe of the role of intermittency in the density (not just velocity) structure of turbulence. We show that this naturally explains some apparent contradictory results in the literature based on use of different moments of the density PDF, as well as differences based on whether volume-weighted or mass-weighted quantities are measured. We show how these are fundamentally related to the fact that mass conservation requires violations of log-normal statistics.
Dark energy as an elastic strain fluid

The origin of the accelerated expansion of the universe is still unclear and new physics is needed on cosmological scales. We propose and test a novel interpretation of dark energy as originated by an elastic strain due to a cosmic defect in an ot herwise Euclidean space-time. The strain modifies the expansion history of the universe. Th is new effective contribution tracks radiation at early times and mimics a cosmological constant at late times. The theory is tested against observations, from nucleosynthesis to the c osmic microwave background and formation and evolution of large scale structure to supernovae. Data are very well reproduced
Pulsars are cool. Seriously.

Ever since the first pulsar was discovered by Bell and Hewish over 40 years ago, we've known that not only are pulsars fascinating and truly exotic objects, but that we can use them as powerful tools for basic physics and astrophysics as well. Taylor and Hulse hammered these views home with their discovery and timing of the spectacular “binary pulsar” in the 1970s and 1980s. In the last two decades a host of surprises and a promise of phenomenal scientific riches in the future has come from the millisecond pulsars. As our instrumentation has become more sensitive and better suited to measuring the pulses from these objects, they've given us new tests of general relativity, fantastic probes of the interstellar medium, constraints on the physics of ultra-dense matter, new windows into binary and stellar evolution, and the promise of a direct detection of gravitational waves. These things really are cool, and there is much more we will do with them in the future.
Host Species and Environmental Effects on Bacterial Communities Associated with Drosophila in the Laboratory and in the Natural Environment

The fruit fly Drosophila is a classic model organism to study adaptation as well as the relationship between genetic variation and phenotypes. Although associated bacterial communities might be important for many aspects of Drosophila biology, knowledge about their diversity, composition, and factors shaping them is limited. We used 454-based sequencing of a variable region of the bacterial 16S ribosomal RNA gene to characterize the bacterial communities associated with wild and laboratory Drosophila isolates. In order to specifically investigate effects of food source and host species on bacterial communities, we analyzed samples from wild Drosophila melanogaster and D. simulans collected from a variety of natural substrates, as well as from adults and larvae of nine laboratory-reared Drosophila species. We find no evidence for host species effects in lab-reared flies; instead, lab of origin and stochastic effects, which could influence studies of Drosophila phenotypes, are pronounced. In contrast, the natural Drosophila–associated microbiota appears to be predominantly shaped by food substrate with an additional but smaller effect of host species identity. We identify a core member of this natural microbiota that belongs to the genus Gluconobacter and is common to all wild-caught flies in this study, but absent from the laboratory. This makes it a strong candidate for being part of what could be a natural D. melanogaster and D. simulans core microbiome. Furthermore, we were able to identify candidate pathogens in natural fly isolates.
Improved estimator for non-Gaussianity in cosmic microwave background observations

An improved estimator for the amplitude fnl of local-type non-Gaussianity from the cosmic microwave background (CMB) bispectrum is discussed. The standard estimator is constructed to be optimal in the zero-signal (i.e., Gaussian) limit. When applied to CMB maps which have a detectable level of non-Gaussianity the standard estimator is no longer optimal, possibly limiting the sensitivity of future observations to a non-Gaussian signal. Previous studies have proposed an improved estimator by using a realization-dependent normalization. Under the approximations of a flat sky and a vanishingly thin last-scattering surface, these studies showed that the variance of this improved estimator can be significantly smaller than the variance of the standard estimator when applied to non-Gaussian CMB maps. Here this technique is generalized to the full sky and to include the full radiation transfer function, yielding expressions for the improved estimator that can be directly applied to CMB maps. The ability of this estimator to reduce the variance as compared to the standard estimator in the face of a significant non-Gaussian signal is re-assessed using the full CMB transfer function. As a result of the late time integrated Sachs-Wolfe effect, the performance of the improved estimator is degraded. If CMB maps are first cleaned of the late-time ISW effect using a tracer of foreground structure, such as a galaxy survey or a measurement of CMB weak lensing, the new estimator does remove a majority of the excess variance, allowing a higher significance detection of fnl.
Synthesis of Homogeneous Manganese-Doped Titanium Oxide Nanotubes from Titanate Precursors

We report a novel synthesis route of homogeneously manganese-doped TiO2 nanotubes in a broad concentration range. The scroll-type trititanate (H2Ti3O7) nanotubes prepared by hydrothermal synthesis were used as precursors. Mn2+ ions were introduced by an ion exchange method resulting MnxH2–xTi3O7. In a subsequent heat treatment, they were transformed into MnyTi1–yO2, where y = x/(3 + x). The state and the local environment of the Mn2+ ions in the precursor and final products were studied by the electron spin resonance (ESR) technique. It was found that the Mn2+ ions occupy two positions: the first having an almost perfect cubic symmetry while the other is in a strongly distorted octahedral site. The ratio of the two Mn2+ sites is independent of the doping level and amounts to 15:85 in MnxH2–xTi3O7 and to 5:95 in MnyTi1–yO2. SQUID magnetometry does not show long-range magnetic order in the homogeneously Mn2+-doped nanotubes.
Network analysis of correlation strength between the most developed countries

A new algorithm of the analysis of correlation among economy time series is proposed. The algorithm is based on the power law classification scheme (PLCS) followed by the analysis of the network on the percolation threshold (NPT). The algorithm was applied to the analysis of correlations among GDP per capita time series of 19 most developed countries in the periods (1982, 2011), (1992, 2011) and (2002, 2011). The representative countries with respect to strength of correlation, convergence of time series and stability of correlation are distinguished. The results are compared with ultrametric distance matrix analysed by NPT.