nils-herrmann/clean_scirepeval huggingface dataset:
CHARACTERIZING THE COOL KOIs. VII. REFINED PHYSICAL PROPERTIES OF THE TRANSITING BROWN DWARF LHS 6343 C

We present an updated analysis of LHS 6343, a triple system in the Kepler field which consists of a brown dwarf transiting one member of a widely separated M+M binary system. By analyzing the full Kepler data set and 34 Keck/HIgh Resolution Echelle Spectrometer radial velocity observations, we measure both the observed transit depth and Doppler semiamplitude to 0.5% precision. With Robo-AO and Palomar/PHARO adaptive optics imaging as well as TripleSpec spectroscopy, we measure a model-dependent mass for LHS 6343 C of 62.1 ± 1.2 MJup and a radius of 0.783  ±  0.011 RJup. We detect the secondary eclipse in the Kepler data at 3.5σ, measuring ecos ω = 0.0228  ±  0.0008. We also derive a method to measure the mass and radius of a star and transiting companion directly, without any direct reliance on stellar models. The mass and radius of both objects depend only on the orbital period, stellar density, reduced semimajor axis, Doppler semiamplitude, eccentricity, and inclination, as well as the knowledge that the primary star falls on the main sequence. With this method, we calculate a mass and radius for LHS 6343 C to a precision of 3% and 2%, respectively.
Nested Canalizing Functions and Their Networks

The concept of a nested canalizing Boolean function has been studied over the last decade in the context of understanding the regulatory logic of molecular interaction networks, such as gene regulatory networks. Such networks are predominantly governed by nested canalizing functions. Derrida values are frequently used to analyze the robustness of a Boolean network to perturbations. This paper introduces closed formulas for the calculation of Derrida values of networks governed by Boolean nested canalizing functions, which previously required extensive simulations. Recently, the concept of nested canalizing functions has been generalized to include multistate functions, and a recursive formula has been derived for their number, as a function of the number of variables. This paper contains a detailed analysis of the class of nested canalizing functions over an arbitrary finite field. In addition, the concept of nested canalization is further generalized and closed formulas for the number of such generalized functions, as well as for the number of equivalence classes under permutation of variables, are derived. The latter is motivated by the fact that two nested canalizing functions that differ only by a permutation of the variables share many important properties.
A unified view of generative models for networks: models, methods, opportunities, and challenges

Research on probabilistic models of networks now spans a wide variety of fields, including physics, sociology, biology, statistics, and machine learning. These efforts have produced a diverse ecology of models and methods. Despite this diversity, many of these models share a common underlying structure: pairwise interactions (edges) are generated with probability conditional on latent vertex attributes. Differences between models generally stem from different philosophical choices about how to learn from data or different empirically-motivated goals. The highly interdisciplinary nature of work on these generative models, however, has inhibited the development of a unified view of their similarities and differences. For instance, novel theoretical models and optimization techniques developed in machine learning are largely unknown within the social and biological sciences, which have instead emphasized model interpretability. Here, we describe a unified view of generative models for networks that draws together many of these disparate threads and highlights the fundamental similarities and differences that span these fields. We then describe a number of opportunities and challenges for future work that are revealed by this view.
Antenna Mechanism of Length Control of Actin Cables

Actin cables are linear cytoskeletal structures that serve as tracks for myosin-based intracellular transport of vesicles and organelles in both yeast and mammalian cells. In a yeast cell undergoing budding, cables are in constant dynamic turnover yet some cables grow from the bud neck toward the back of the mother cell until their length roughly equals the diameter of the mother cell. This raises the question: how is the length of these cables controlled? Here we describe a novel molecular mechanism for cable length control inspired by recent experimental observations in cells. This “antenna mechanism” involves three key proteins: formins, which polymerize actin, Smy1 proteins, which bind formins and inhibit actin polymerization, and myosin motors, which deliver Smy1 to formins, leading to a length-dependent actin polymerization rate. We compute the probability distribution of cable lengths as a function of several experimentally tuneable parameters such as the formin-binding affinity of Smy1 and the concentration of myosin motors delivering Smy1. These results provide testable predictions of the antenna mechanism of actin-cable length control.
Breaking of Vainshtein screening in scalar-tensor theories beyond Horndeski

The Horndeski theory of gravity is known as the most general scalar-tensor theory with second-order field equations. Recently, it was demonstrated by Gleyzes et al. that the Horndeski theory can further be generalized in such a way that although field equations are of third order, the number of propagating degrees of freedom remains the same. We study small-scale gravity in the generalized Horndeski theory, focusing in particular on an impact of the new derivative interaction beyond Horndeski on the Vainshtein screening mechanism. In the absence of the quintic galileon term and its generalization, we show that the new interaction does not change the qualitative behavior of gravity outside and near the source: the two metric potentials coincide, $\Phi = \Psi \;(\sim r^{-1})$, while the gravitational coupling is given by the cosmological one and hence is time-dependent in general. We find, however, that the gravitational field inside the source shows a novel behavior due to the interaction beyond Horndeski: the gravitational attraction is not determined solely from the enclosed mass and two potentials do not coincide, indicating breaking of the screening mechanism.
Using Description Logics for RDF Constraint Checking and Closed-World Recognition

RDF and Description Logics work in an open-world setting where absence of information is not information about absence. Nevertheless, Description Logic axioms can be interpreted in a closed-world setting and in this setting they can be used for both constraint checking and closed-world recognition against information sources. When the information sources are expressed in well-behaved RDF or RDFS (i.e., RDF graphs interpreted in the RDF or RDFS semantics) this constraint checking and closed-world recognition is simple to describe. Further this constraint checking can be implemented as SPARQL querying and thus effectively performed.
Percolation in networks of networks with random matching of nodes in different layers

We consider robustness and percolation properties of the networks of networks, in which random nodes in different individual networks (layers) can be interdependent. We explore the emergence of the giant mutually connected component, generalizing the percolation cluster in a single network to interdependent networks, and observe the strong effect of loops of interdependencies. In particular, we find that the giant mutual component does not emerge in a loop formed by any number of layers. In contrast, we observe multiple hybrid transitions in networks of networks formed by infinite number of randomly connected layers, corresponding to the percolation of layers with different number of interdependencies. In particular we find that layers with many interdependencies are more fragile than layers with less interdependencies. These hybrid transitions, combining a discontinuity and a singularity, are responsible for joining a finite fraction of nodes in different layers to the giant mutually connected component. In the case of partial interdependence, when only a fraction of interlinks between layers provide interdependence, some of these transitions can become continuous.
New model of massive spin two field

We propose a new ghost-free model describing massive spin two field. This model consists of a kinetic term and interaction terms without derivative. We report on the properties of this model, especially we consider what could happen when this model couples with gravity. Although the model does not generate any ghost on the Minkowski space-time, it is not so clear whether or not this property is preserved even on curved space-time. In fact, Buchbinder et al. have found that the ghost appears even in the Fierz-Pauli theory on curved space-time if we do not include non-minimal coupling terms. We report on the model with interactions on curved space-time and show that we can construct a model without ghost by including non-minimal coupling terms.
On the Coherent Risk Measure Representations in the Discrete Probability Spaces

We give a complete characterization of both comonotone and not comonotone coherent risk measures in the discrete finite probability space, where each outcome is equally likely. To the best of our knowledge, this is the first work that characterizes \textit{and} distinguishes comonotone and not comonotone coherent risk measures via a simplified AVaR representation in this probability space, which is crucial in applications and simulations.
Mining cross-cultural relations from Wikipedia: A study of 31 European food cultures

For many people, Wikipedia represents one of the primary sources of knowledge about foreign cultures. Yet, different Wikipedia language editions offer different descriptions of cultural practices. Unveiling diverging representations of cultures provides an important insight, since they may foster the formation of cross-cultural stereotypes, misunderstandings and potentially even conflict. In this work, we explore to what extent the descriptions of cultural practices in various European language editions of Wikipedia differ on the example of culinary practices and propose an approach to mine cultural relations between different language communities trough their description of and interest in their own and other communities' food culture. We assess the validity of the extracted relations using 1) various external reference data sources (i.e., the European Social Survey, migration statistics), 2) crowdsourcing methods and 3) simulations.
Implicitly Constrained Semi-supervised Linear Discriminant Analysis

Semi-supervised learning is an important and active topic of research in pattern recognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Using any one of these methods is not guaranteed to outperform the supervised classifier which does not take the additional unlabeled data into account. In this work we compare traditional Expectation Maximization type approaches for semi-supervised linear discriminant analysis with approaches based on intrinsic constraints and propose a new principled approach for semi-supervised linear discriminant analysis, using so-called implicit constraints. We explore the relationships between these methods and consider the question if and in what sense we can expect improvement in performance over the supervised procedure. The constraint based approaches are more robust to misspecification of the model, and may outperform alternatives that make more assumptions on the data in terms of the log-likelihood of unseen objects.
TaxMan: an online facility for the coding of continuous characters for cladistic analysis

A consensus is emerging that continuous (or metric) measures can be useful in phylogenetic systematics. Many of the methods for coding such characters, how- ever, employ elements that are arbitrary and therefore should be excluded from use in cladistic analysis. The continued use of such potentially inappropriate methods can be attributed to either their simplicity or the availability of computer programs specifically designed to produce data matrices using these methods. Conversely, one of the most suitable methods, homogeneous subset coding (HSC), is underused, probably due to the lack of a suitable software implementation for this somewhat complex procedure. 
This paper describes TaxMan, a Web-based facility for the coding of continuous data using HSC. Data are entered using a form accessible via any internet browser and are automatically converted to a matrix suitable for input into tree-searching software. This implementation of the HSC technique provides an uncomplicated procedure for the incorporation of metric data in phylogenetic systematics. The algorithmic implementation of the HSC procedure, and interpolation of the Studentised range and maximum modulus distributions required by it, is described in detail in appendices.
MAIN-SEQUENCE STARS MASQUERADING AS YOUNG STELLAR OBJECTS IN THE CENTRAL MOLECULAR ZONE

In contrast to most other galaxies, star formation rates in the Milky Way can be estimated directly from young stellar objects (YSOs). In the central molecular zone the star formation rate calculated from the number of YSOs with 24 μm emission is up to an order of magnitude higher than the value estimated from methods based on diffuse emission (such as free–free emission). Whether this effect is real or whether it indicates problems with either or both star formation rate measures is not currently known. In this paper, we investigate whether estimates based on YSOs could be heavily contaminated by more evolved objects such as main-sequence stars. We present radiative transfer models of YSOs and of main-sequence stars in a constant ambient medium which show that the main-sequence objects can indeed mimic YSOs at 24 μm. However, we show that in some cases the main-sequence models can be marginally resolved at 24 μm, whereas the YSO models are always unresolved. Based on the fraction of resolved MIPS 24 μm sources in the sample of YSOs previously used to compute the star formation rate, we estimate the fraction of misclassified “YSOs” to be at least 63%, which suggests that the star formation rate previously determined from YSOs is likely to be at least a factor of three too high.
Unifying framework for relaxations of the causal assumptions in Bell's theorem.

Bell's theorem shows that quantum mechanical correlations can violate the constraints that the causal structure of certain experiments impose on any classical explanation. It is thus natural to ask to which degree the causal assumptions-e.g., locality or measurement independence-have to be relaxed in order to allow for a classical description of such experiments. Here we develop a conceptual and computational framework for treating this problem. We employ the language of Bayesian networks to systematically construct alternative causal structures and bound the degree of relaxation using quantitative measures that originate from the mathematical theory of causality. The main technical insight is that the resulting problems can often be expressed as computationally tractable linear programs. We demonstrate the versatility of the framework by applying it to a variety of scenarios, ranging from relaxations of the measurement independence, locality, and bilocality assumptions, to a novel causal interpretation of Clauser-Horne-Shimony-Holt inequality violations.
Feedback Solution to Optimal Switching Problems With Switching Cost

The problem of optimal switching between nonlinear autonomous subsystems is investigated in this paper where the objective is not only bringing the states to close to the desired point, but also adjusting the switching pattern, in the sense of penalizing switching occurrences and assigning different preferences to utilization of different modes. The mode sequence is unspecified and a switching cost term is used in the cost function for penalizing each switching. It is shown that once a switching cost is incorporated, the optimal cost-to-go function depends on the subsystem which was active at the previous time step. Afterward, an approximate dynamic programming-based method is developed, which provides an approximation of the optimal solution to the problem in a feedback form and for different initial conditions. Finally, the performance of the method is analyzed through numerical examples.
Waveguide engineering of graphene's nonlinearity

Graphene has recently been shown to possess giant nonlinearity; however, the utility of this nonlinearity is limited due to high losses and small interaction volume. We show that by performing waveguide engineering to graphene's nonlinearity, we are able to dramatically increase the nonlinear parameter and decrease the switching optical power to sub-watt levels. Our design makes use of the hybrid plasmonic waveguide and careful manipulation of graphene's refractive index by tuning its Fermi level. The ability to tailor the nonlinear parameter in graphene based waveguides via the Fermi level provides a paradigm of nonlinear optics devices to be realized.
New physics searches in $B \rightarrow D^{(*)}\tau \nu$ decays

I review the current status of measurements involving semi-tauonic $B$ meson decay at the $B$-factories. I briefly discuss the experimental methods and highlight the importance of background contributions especially from poorly understood $D^{**}$ in this study. Perhaps this can also shed some light on the discrepancy in the BaBar measurement of ratio of semi-tauonic and semi-leptonic ($e$/$\mu$) modes of $B$ decay from the Standard Model (SM) at 3.2$\sigma$. I will also discuss one of the New Physics (NP) models that could be experimentally sensitive in being distinguished from the Standard Model (SM).
Torsional instanton effects in quantum gravity

We show that, in the first order gravity theory coupled to axions, the instanton number of the Giddings-Strominger wormhole can be interpreted as the Nieh-Yan topological index. The axion charge of the baby universes is quantized in terms of the Nieh-Yan integers. Tunneling between universes of different Nieh-Yan charges implies a nonperturbative vacuum state. The associated topological vacuum angle can be identified with the Barbero-Immirzi parameter.
Observation of two new Ξ(b)(-) baryon resonances.

Two structures are observed close to the kinematic threshold in the Ξ(b)(0)π(-) mass spectrum in a sample of proton-proton collision data, corresponding to an integrated luminosity of 3.0  fb(-1), recorded by the LHCb experiment. In the quark model, two baryonic resonances with quark content bds are expected in this mass region: the spin-parity J(P)=(1/2)(+) and J(P)=(3/2)(+) states, denoted Ξ(b)('-) and Ξ(b)(*-). Interpreting the structures as these resonances, we measure the mass differences and the width of the heavier state to be m(Ξ(b)('-))-m(Ξ(b)(0))-m(π(-))=3.653±0.018±0.006  MeV/c(2), m(Ξ(b)(*-))-m(Ξ(b)(0))-m(π(-))=23.96±0.12±0.06  MeV/c(2), Γ(Ξ(b)(*-))=1.65±0.31±0.10  MeV, where the first and second uncertainties are statistical and systematic, respectively. The width of the lighter state is consistent with zero, and we place an upper limit of Γ(Ξ(b)('-))<0.08  MeV at 95% confidence level. Relative production rates of these states are also reported.
DYNAMIC DEFAULTABLE TERM STRUCTURE MODELING BEYOND THE INTENSITY PARADIGM

The two main approaches in credit risk are the structural approach pioneered by Merton and the reduced‐form framework proposed by Jarrow and Turnbull and by Artzner and Delbaen. The goal of this paper is to provide a unified view on both approaches. This is achieved by studying reduced‐form approaches under weak assumptions. In particular, we do not assume the global existence of a default intensity and allow default at fixed or predictable times, such as coupon payment dates, with positive probability. In this generalized framework, we study dynamic term structures prone to default risk following the forward‐rate approach proposed by Heath, Jarrow, and Morton. It turns out that previously considered models lead to arbitrage possibilities when default can happen at a predictable time. A suitable generalization of the forward‐rate approach contains an additional stochastic integral with atoms at predictable times and necessary and sufficient conditions for an appropriate no‐arbitrage condition are given. For efficient implementations, we develop a new class of affine models that do not satisfy the standard assumption of stochastic continuity. The chosen approach is intimately related to the theory of enlargement of filtrations, for which we provide an example by means of filtering theory where the Azéma supermartingale contains upward and downward jumps, both at predictable and totally inaccessible stopping times.
Respondent-driven sampling and an unusual epidemic

Respondent-driven sampling (RDS) is frequently used when sampling from hidden populations. In RDS, sampled individuals pass on participation coupons to at most c of their acquaintances in the community (c = 3 being a common choice). If these individuals choose to participate, they in turn pass coupons on to their acquaintances, and so on. The process of recruiting is shown to behave like a new Reed–Frost-type network epidemic, in which 'becoming infected' corresponds to study participation. We calculate R0, the probability of a major 'outbreak', and the relative size of a major outbreak for c < ∞ in the limit of infinite population size and compare to the standard Reed–Frost epidemic. Our results indicate that c should often be chosen larger than in current practice.
The Hyperboloidal Foliation Method

The Hyperboloidal Foliation Method presented in this monograph is based on a (3+1)-foliation of Minkowski spacetime by hyperboloidal hypersurfaces. It allows us to establish global-in-time existence results for systems of nonlinear wave equations posed on a curved spacetime and to derive uniform energy bounds and optimal rates of decay in time. We are also able to encompass the wave equation and the Klein-Gordon equation in a unified framework and to establish a well-posedness theory for nonlinear wave-Klein-Gordon systems and a large class of nonlinear interactions. The hyperboloidal foliation of Minkowski spacetime we rely upon in this book has the advantage of being geometric in nature and, especially, invariant under Lorentz transformations. As stated, our theory applies to many systems arising in mathematical physics and involving a massive scalar field, such as the Dirac-Klein-Gordon system. As it provides uniform energy bounds and optimal rates of decay in time, our method appears to be very robust and should extend to even more general systems.
Music Data Analysis: A State-of-the-art Survey

Music accounts for a significant chunk of interest among various online activities. This is reflected by wide array of alternatives offered in music related web/mobile apps, information portals, featuring millions of artists, songs and events attracting user activity at similar scale. Availability of large scale structured and unstructured data has attracted similar level of attention by data science community. This paper attempts to offer current state-of-the-art in music related analysis. Various approaches involving machine learning, information theory, social network analysis, semantic web and linked open data are represented in the form of taxonomy along with data sources and use cases addressed by the research community.