nils-herrmann/clean_scirepeval huggingface dataset:
Comparative assembly hubs: Web-accessible browsers for comparative genomics

Researchers now have access to large volumes of genome sequences for comparative analysis, some generated by the plethora of public sequencing projects and, increasingly, from individual efforts. It is not possible, or necessarily desirable, that the public genome browsers attempt to curate all these data. Instead, a wealth of powerful tools is emerging to empower users to create their own visualizations and browsers.



We introduce a pipeline to easily generate collections of Web-accessible UCSC Genome Browsers interrelated by an alignment. It is intended to democratize our comparative genomic browser resources, serving the broad and growing community of evolutionary genomicists and facilitating easy public sharing via the Internet. Using the alignment, all annotations and the alignment itself can be efficiently viewed with reference to any genome in the collection, symmetrically. A new, intelligently scaled alignment display makes it simple to view all changes between the genomes at all levels of resolution, from substitutions to complex structural rearrangements, including duplications. To demonstrate this work, we create a comparative assembly hub containing 57 Escherichia coli and 9 Shigella genomes and show examples that highlight their unique biology.



The source code is available as open source at: https://github.com/glennhickey/progressiveCactus The E.coli and Shigella genome hub is now a public hub listed on the UCSC browser public hubs Web page.
Detecting cosmic rays with the LOFAR radio telescope

The low frequency array (LOFAR), is the first radio telescope designed with the capability to measure radio emission from cosmic-ray induced air showers in parallel with interferometric observations. In the first ~2 years of observing, 405 cosmic-ray events in the energy range of 1016−1018 eV have been detected in the band from 30−80 MHz. Each of these air showers is registered with up to ~1000 independent antennas resulting in measurements of the radio emission with unprecedented detail. This article describes the dataset, as well as the analysis pipeline, and serves as a reference for future papers based on these data. All steps necessary to achieve a full reconstruction of the electric field at every antenna position are explained, including removal of radio frequency interference, correcting for the antenna response and identification of the pulsed signal.
Resolving the fine-scale structure in turbulent Rayleigh–Bénard convection

We present high-resolution direct numerical simulation studies of turbulent Rayleigh–Bénard convection in a closed cylindrical cell with an aspect ratio of one. The focus of our analysis is on the finest scales of convective turbulence, in particular the statistics of the kinetic energy and thermal dissipation rates in the bulk and the whole cell. The fluctuations of the energy dissipation field can directly be translated into a fluctuating local dissipation scale which is found to develop ever finer fluctuations with increasing Rayleigh number. The range of these scales as well as the probability of high-amplitude dissipation events decreases with increasing Prandtl number. In addition, we examine the joint statistics of the two dissipation fields and the consequences of high-amplitude events. We have also investigated the convergence properties of our spectral element method and have found that both dissipation fields are very sensitive to insufficient resolution. We demonstrate that global transport properties, such as the Nusselt number, and the energy balances are partly insensitive to insufficient resolution and yield correct results even when the dissipation fields are under-resolved. Our present numerical framework is also compared with high-resolution simulations which use a finite difference method. For most of the compared quantities the agreement is found to be satisfactory.
Large x physics: recent results and future plans

The valence region is exceedingly important in hadron physics since this region not only defines a hadron but also is an excellent discriminator of nucleon structure models. Present uncertainties in light quark distribution functions at high x could also impact high energy physics. Here we will describe a new generation of experiments at Jefferson Lab that is aimed at the high x region of the nucleon. It is noted that the proposed Electron Ion Collider could explore the high x regime.
Gravitational Pressure and the Accelerating Universe

In the context of the Teleparallel Equivalent of General Relativity (TEGR) one can obtain an alternative insight into General Relativity, as has been shown in addressing properties as energy, momentum and angular momentum of the gravitational field. In this paper, we apply the definition, that arises from the field equation of the the TEGR, for the stress-energy-momentum tensor of the gravitational field, whose spatial components naturally lead to the definition of gravitational pressure, to compute the total space-time pressure, due to the gravitational and matter fields, over a spherical, space-like two-surface of a Friedman-Robertson-Walker (FRW) universe, for any curvature index. In particular, for a spatially flat FRW universe in the actual era (i.e., for "cold matter"), it resulted that the pressure (now due only to the gravitational field) is outwardly directed over any spherical, spatial two-surface. This surface can be, in particular, the apparent horizon of a spatially flat FRW universe (in this case, the apparent horizon coincides with the Hubble horizon). Assuming the validity of the first law of thermodynamics for matter and gravity, and taking into account the contribution of the gravitational field to both the energy and the pressure terms in the first law of the (gravitational) thermodynamics, as well as considering the thermal character of the apparent horizon of the spatially flat FRW universe, we have thus obtained a value of the gravitational pressure that is very close to the observed value. We interpret this result as a possibility that the accelerated expansion of the actual universe might be due to the effect of the pressure of the very gravitational field, instead of an totally unkown (dark) energy.
On the Reality of Unruh Temperature

In contrast to recent criticism we undertake to show that the notion of Unruh temperature describes a real thermal property of the vacuum if viewed from an accelerated reference frame. We embed our investigation in a more general analysis of general relativistic temperature (Tolman-Ehrenfest effect) with the entropy-maximum principle being our guiding principle. We show that the Unruh effect neatly fits into this more general framework. Our criterion of reality is, first, the possibility to transfer a quantum of acceleration radiation to the inertial laboratory where it can be studied in principle under ordinary thrmodynamical conditions. Second, we emphasize as another criterion the importance of the coincidence of the accelerated and inertial observer description as far as the final objective result is concerned.
Scalable Recommendation with Poisson Factorization

We develop a Bayesian Poisson matrix factorization model for forming recommendations from sparse user behavior data. These data are large user/item matrices where each user has provided feedback on only a small subset of items, either explicitly (e.g., through star ratings) or implicitly (e.g., through views or purchases). In contrast to traditional matrix factorization approaches, Poisson factorization implicitly models each user's limited attention to consume items. Moreover, because of the mathematical form of the Poisson likelihood, the model needs only to explicitly consider the observed entries in the matrix, leading to both scalable computation and good predictive performance. We develop a variational inference algorithm for approximate posterior inference that scales up to massive data sets. This is an efficient algorithm that iterates over the observed entries and adjusts an approximate posterior over the user/item representations. We apply our method to large real-world user data containing users rating movies, users listening to songs, and users reading scientific papers. In all these settings, Bayesian Poisson factorization outperforms state-of-the-art matrix factorization methods.
Game theory in models of pedestrian room evacuation.

We analyze the pedestrian evacuation of a rectangular room with a single door considering a lattice gas scheme with the addition of behavioral aspects of the pedestrians. The movement of the individuals is based on random and rational choices and is affected by conflicts between two or more agents that want to advance to the same position. Such conflicts are solved according to certain rules closely related to the concept of strategies in game theory, cooperation and defection. We consider game rules analogous to those from the Prisoner's Dilemma and Stag Hunt games, with payoffs associated to the probabilities of the individuals to advance to the selected site. We find that, even when defecting is the rational choice for any agent, under certain conditions, cooperators can take advantage from mutual cooperation and leave the room more rapidly than defectors.
Acceleration of particles in spacetimes of black string

The particle acceleration mechanism in $S^2 \times\mathbb{R}^1$ topology, namely in the spacetime of the five-dimensional compact black string has been studied. The expression of center-of-mass energy of the colliding neutral particles near static black string has been found. The collision of charged particle moving at the innermost stable circular orbit with neutral particle coming from infinity have been considered when black string is immersed in external uniform magnetic field. It has been shown that the unlimited center-of-mass energy can be approached in case of the extremal rotation of the black string which is similar to the analogous effect in the Kerr spacetime. We have also obtained that the scattering energy of particles in the center-of-mass system can take arbitrary large values not only for extremal black string but also for nonextremal one. It has been derived that the presence of the extra dimension can, in principle, increase the upper limit of efficiency of energy extraction from the extremely rotating black string up to $203\%$ versus to $143\%$ which can be extracted from the extreme Kerr black hole.
Dimensionality reduction and spectral properties of multiplex networks

Network representations are useful for describing the structure of a large variety of complex systems. Although most studies of real-world networks suppose that nodes are connected by only a single type of edge, most natural and engineered systems include multiple subsystems and layers of connectivity. This new paradigm has attracted a great deal of attention and one fundamental challenge is to characterize multilayer networks both structurally and dynamically. One way to address this question is to study the spectral properties of such networks. Here we apply the framework of graph quotients, which occurs naturally in this context, and the associated eigenvalue interlacing results to the adjacency and Laplacian matrices of undirected multilayer networks. Specifically, we describe relationships between the eigenvalue spectra of multilayer networks and their two most natural quotients, the network of layers and the aggregate network, and show the dynamical implications of working with either of the two simplified representations. Our work thus contributes in particular to the study of dynamical processes whose critical properties are determined by the spectral properties of the underlying network.
Tolman IV solution in the Randall-Sundrum Braneworld

AbstractIn the context of the Randall-Sundrum braneworld, the minimal geometric deformation ap-proach(MGD) is usedto generateanexact analyticinteriorsolutionto four-dimensionaleﬀectiveEinstein’s ﬁeld equations for a spherically symmetric compact distribution. This solution rep-resents the braneworld version of the well known Tolman IV solution in General Relativity. Byusing this analytic solution, an exhaustive analysis of the braneworld eﬀects on realistic stellarinteriors is developed, ﬁnding strong evidences in favor of the hypothesis that compactness isreduced due to bulk eﬀects on stellar conﬁgurations. 1  In recent years there has been great interest in ﬁnding alternative theories to General Relativity(GR) [1, 2], mainly due to the inability of the latter to explain satisfactorily some fundamental issuesassociated with the gravitational interaction, such as the dark matter problem, the dark energyproblem, as well as the impossibility to reconcile GR with the Standard Model of particle physics.Extra-dimensional theories, which are mostly inspired by String/M-theory, are among the theoriesthat lead to gravity beyond GR. One of these extra-dimensional theories is the Braneworld (BW)proposed by Randall and Sundrum (RS)  which has been largely studied and which explains oneof the fundamental problems of Physics, i.e. the hierarchy problem (see also the ADD model [4]and ). Because of this, its study and impact on GR is fully justiﬁed and is of great importance[6].Even though we have a covariant approach that is useful to study many fundamental aspectsof the theory of RS BW [7], we are still far from fully understanding its impact on gravity, mainlydue to the lack of the complete ﬁve-dimensional solution (bulk plus brane), which could helpsto explain certain key issues that remain unresolved, such as the existence of black holes in RSBW [8]-[11] and the bulk eﬀects on stellar conﬁgurations . Since the complete ﬁve-dimensional
A 30 mK, 13.5 T scanning tunneling microscope with two independent tips.

We describe the design, construction, and performance of an ultra-low temperature, high-field scanning tunneling microscope (STM) with two independent tips. The STM is mounted on a dilution refrigerator and operates at a base temperature of 30 mK with magnetic fields of up to 13.5 T. We focus on the design of the two-tip STM head, as well as the sample transfer mechanism, which allows in situ transfer from an ultra high vacuum preparation chamber while the STM is at 1.5 K. Other design details such as the vibration isolation and rf-filtered wiring are also described. Their effectiveness is demonstrated via spectral current noise characteristics and the root mean square roughness of atomic resolution images. The high-field capability is shown by the magnetic field dependence of the superconducting gap of CuxBi2Se3. Finally, we present images and spectroscopy taken with superconducting Nb tips with the refrigerator at 35 mK that indicate that the effective temperature of our tips/sample is approximately 184 mK, corresponding to an energy resolution of 16 μeV.
General relativistic density perturbations

We investigate a general relativistic mechanism in which spikes generate matter overdensities in the early universe. When the cosmological fluid is tilted, the tilt provides another mechanism in generating matter inhomogeneities. We numerically investigate the effect of a sign change in the tilt, when there is a spike but the tilt does not change sign, and when the spike and the sign change in the tilt coincide. We find that the tilt plays the primary role in generating matter inhomogeneities, and it does so by creating both local overdensities and underdensities. We discuss of the physical implications of the work.
D3PO - Denoising, Deconvolving, and Decomposing Photon Observations

The analysis of astronomical images is a non-trivial task. The DPO algorithm addresses the inference problem of denoising, deconvolving, and decomposing photon observations. The primary goal is the simultaneous reconstruction of the diffuse and point-like photon flux from a given photon count image. In order to discriminate between these morphologically different signal components, a probabilistic algorithm is derived in the language of information field theory based on a hierarchical Bayesian parameter model. The signal inference exploits prior information on the spatial correlation structure of the diffuse component and the brightness distribution of the spatially uncorrelated point-like sources. A maximum a posteriori solution and a solution minimizing the Gibbs free energy of the inference problem using variational Bayesian methods are discussed. Since the derivation of the solution does not dependent on the underlying position space, the implementation of the DPO algorithm uses the NIFTy package to ensure operationality on various spatial grids and at any resolution. The fidelity of the algorithm is validated by the analysis of simulated data, including a realistic high energy photon count image showing a 32× 32 arcmin observation with a spatial resolution of 0.1 arcmin. In all tests the DPO algorithm successfully denoised, deconvolved, and decomposed the data into a diffuse and a point-like signal estimate for the respective photon flux components.
Community detection for correlation matrices

A challenging problem in the study of complex systems is that of resolving, without prior information, the emergent, mesoscopic organization determined by groups of units whose dynamical activity is more strongly correlated internally than with the rest of the system. The existing techniques to filter correlations are not explicitly oriented towards identifying such modules and can suffer from an unavoidable information loss. A promising alternative is that of employing community detection techniques developed in network theory. Unfortunately, this approach has focused predominantly on replacing network data with correlation matrices, a procedure that tends to be intrinsically biased due to its inconsistency with the null hypotheses underlying the existing algorithms. Here we introduce, via a consistent redefinition of null models based on random matrix theory, the appropriate correlation-based counterparts of the most popular community detection techniques. Our methods can filter out both unit-specific noise and system-wide dependencies, and the resulting communities are internally correlated and mutually anti-correlated. We also implement multiresolution and multifrequency approaches revealing hierarchically nested sub-communities with `hard' cores and `soft' peripheries. We apply our techniques to several financial time series and identify mesoscopic groups of stocks which are irreducible to a standard, sectorial taxonomy, detect `soft stocks' that alternate between communities, and discuss implications for portfolio optimization and risk management.
Nonparametric Multi-group Membership Model for Dynamic Networks

Relational data—like graphs, networks, and matrices—is often dynamic, where the relational structure evolves over time. A fundamental problem in the analysis of time-varying network data is to extract a summary of the common structure and the dynamics of the underlying relations between the entities. Here we build on the intuition that changes in the network structure are driven by dynamics at the level of groups of nodes. We propose a nonparametric multi-group membership model for dynamic networks. Our model contains three main components: We model the birth and death of individual groups with respect to the dynamics of the network structure via a distance dependent Indian Buffet Process. We capture the evolution of individual node group memberships via a Factorial Hidden Markov model. And, we explain the dynamics of the network structure by explicitly modeling the connectivity structure of groups. We demonstrate our model's capability of identifying the dynamics of latent groups in a number of different types of network data. Experimental results show that our model provides improved predictive performance over existing dynamic network models on future network forecasting and missing link prediction.
Querying Knowledge Graphs by Example Entity Tuples

We witness an unprecedented proliferation of knowledge graphs that record millions of entities and their relationships. While knowledge graphs are structure-flexible and content-rich, they are difficult to use. The challenge lies in the gap between their overwhelming complexity and the limited database knowledge of non-professional users. If writing structured queries over “simple” tables is difficult, complex graphs are only harder to query. As an initial step toward improving the usability of knowledge graphs, we propose to query such data by example entity tuples, without requiring users to form complex graph queries. Our system, Graph Query By Example (GQBE), automatically discovers a weighted hidden maximum query graph based on input query tuples, to capture a user's query intent. It then efficiently finds and ranks the top approximate matching answer graphs and answer tuples. We conducted experiments and user studies on the large Freebase and DBpedia datasets and observed appealing accuracy and efficiency. Our system provides a complementary approach to the existing keyword-based methods, facilitating user-friendly graph querying. To the best of our knowledge, there was no such proposal in the past in the context of graphs.
Kurtoses and high order cumulants: Insights from resummed perturbation theory

Cumulants of conserved charges provide important information about the physics of the quark-gluon plasma around the phase transition region, as they are by construction sensitive to changes in the degrees of freedom of the system. In this brief proceedings contribution, I report on recent results for two such quantities from two different improved perturbative frameworks, as well as discuss their relevance for heavy ion experiments.
Idea of a new Personality-Type based Recommendation Engine

(MBTI) types depict the psychological preferences by which a person perceives the world and make decisions. There are 4 principal functions through which the people see the world: sensation, intuition, feeling, and thinking. These functions along with the Introverted\Extroverted nature of the person, there are 16 personalities types, the humans are divided into. Here an idea is presented where a user can get recommendations for books, web media content, music and movies on the basis of the users' MBTI type. Only things like books and other media content has been chosen because the preferences in such things are mostly subjective. Apart from the recommended content that is generally generated on the basis of the previous purchases, searches can be enhanced by using the MBTI. A minimalist survey was designed for collecting the data. This has a more than 100 features that show the preference of a personality type. Those include preferences in book genres, music genres, movie genres and even video games genres. After analyzing the data that is collected from the survey, some inferences were drawn from it which can be used to design a new recommendation engine for recommending the content that coincides with the personality of the user.