nils-herrmann/clean_scirepeval huggingface dataset:
Community Structure in Time-Dependent, Multiscale, and Multiplex Networks

Network Notation Networks are often characterized by clusters of constituents that interact more closely with each other and have more connections to one another than they do with the rest of the components of the network. However, systematically identifying and studying such community structure in complicated networks is not easy, especially when the network interactions change over time or contain multiple types of connections, as seen in many biological regulatory networks or social networks. Mucha et al. (p. 876) developed a mathematical method to allow detection of communities that may be critical functional units of such networks. Application to real-world tasks—like making sense of the voting record in the U.S. Senate—demonstrated the promise of the method. A general mathematical method used to identify closely interacting groups can explain the behavior of complicated networks. Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows studies of community structure in a general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.
Opinion Dynamics With Decaying Confidence: Application to Community Detection in Graphs

We study a class of discrete-time multi-agent systems modeling opinion dynamics with decaying confidence. We consider a network of agents where each agent has an opinion. At each time step, the agents exchange their opinion with their neighbors and update it by taking into account only the opinions that differ from their own less than some confidence bound. This confidence bound is decaying: an agent gives repetitively confidence only to its neighbors that approach sufficiently fast its opinion. Essentially, the agents try to reach an agreement with the constraint that it has to be approached no slower than a prescribed convergence rate. Under that constraint, global consensus may not be achieved and only local agreements may be reached. The agents reaching a local agreement form communities inside the network. In this paper, we analyze this opinion dynamics model: we show that communities correspond to asymptotically connected components of the network and give an algebraic characterization of communities in terms of eigenvalues of the matrix defining the collective dynamics. Finally, we apply our opinion dynamics model to address the problem of community detection in graphs. We propose a new formulation of the community detection problem based on eigenvalues of normalized Laplacian matrix of graphs and show that this problem can be solved using our opinion dynamics model. We consider three examples of networks, and compare the communities we detect with those obtained by existing algorithms based on modularity optimization. We show that our opinion dynamics model not only provides an appealing approach to community detection but that it is also effective.
Higgs in space

We consider the possibility that the Higgs can be produced in dark matter annihilations, appearing as a line in the spectrum of gamma rays at an energy determined by the masses of the WIMP and the Higgs itself. We argue that this phenomenon occurs generally in models in which the the dark sector has large couplings to the most massive states of the SM and provide a simple example inspired by the Randall-Sundrum vision of dark matter, whose 4d dual corresponds to electroweak symmetry-breaking by strong dynamics which respect global symmetries that guarantee a stable WIMP. The dark matter is a Dirac fermion that couples to a Z' acting as a portal to the Standard Model through its strong coupling to top quarks. Annihilation into light standard model degrees of freedom is suppressed and generates a feeble continuum spectrum of gamma rays. Loops of top quarks mediate annihilation into γZ, γh, and γZ', providing a forest of lines in the spectrum. Such models can be probed by the Fermi/GLAST satellite and ground-based Air Cherenkov telescopes.
Spectral ranking

We sketch the history of spectral ranking—a general umbrella name for techniques that apply the theory of linear maps (in particular, eigenvalues and eigenvectors) to matrices that do not represent geometric transformations, but rather some kind of relationship between entities. Albeit recently made famous by the ample press coverage of Google's PageRank algorithm, spectral ranking was devised more than 60 years ago, almost exactly in the same terms, and has been studied in psychology, social sciences, bibliometrics, economy, and choice theory. We describe the contribution given by previous scholars in precise and modern mathematical terms: Along the way, we show how to express in a general way damped rankings, such as Katz's index, as dominant eigenvectors of perturbed matrices, and then use results on the Drazin inverse to go back to the dominant eigenvectors by a limit process. The result suggests a regularized definition of spectral ranking that yields for a general matrix a unique vector depending on a boundary condition.
Electroweak stars: How nature may capitalize on the standard model's ultimate fuel

We study the possible existence of an electroweak star — a compact stellar-mass object whose central core temperature is higher than the electroweak symmetry restoration temperature. We found a solution to the Tolman-Oppenheimer-Volkoff equations describing such an object. The parameters of such a star are not substantially different from a neutron star — its mass is around 1.3 Solar masses while its radius is around 8km. What is different is the existence of a small electroweak core. The source of energy in the core that can at least temporarily balance gravity are standard-model non-perturbative baryon number (B) and lepton number (L) violating processes that allow the chemical potential of B+L to relax to zero. The energy released at the core is enormous, but gravitational redshift and the enhanced neutrino interaction cross section at these energies make the energy release rate moderate at the surface of the star. The lifetime of this new quasi-equilibrium can be more than ten million years. This is long enough to represent a new stage in the evolution of a star if stellar evolution can take it there.
Results from the CDMS II experiment

I report recent results and the status of the Cryogenic Dark Matter Search (CDMS II) experiment at the Soudan Underground Laboratory in Minnesota, USA. A blind analysis of data taken by 30 detectors between October 2006 and July 2007 found zero events consistent with WIMPs elastically scattering in our Ge detectors. This resulted in an upper limit on the spin-independent, WIMP-nucleon cross section of 6.6 × 10−44 cm2 (4.6 × 10−44 cm2 when combined with our previous results) at the 90% C.L. for a WIMP of mass 60 GeV/c2. In March 2009 data taking with CDMS II stopped in order to install the first of 5 SuperTowers of detectors for the SuperCDMS Soudan project. Analysis of data taken between August 2007 and March 2009 is ongoing.
New ways of scientific publishing and accessing human knowledge inspired by transdisciplinary approaches

Inspired by interdisciplinary work touching biology and microtribology, the authors propose a new, dynamic way of publishing research results, the establishment of a tree of knowledge and the localisation of scientific articles on this tree. The current two-dimensional standard of scientific publications is outdated. Over-information in almost any field is a problem. Therefore, it is suggested that, to succeed and be read, modern publications should be dynamic and use all types of multimedia. Such ways of presenting and managing research results would be accessible by people with different kinds of backgrounds and levels of education, and allow for full use of the ever-increasing number of scientific and technical publications. This approach would dramatically change and revolutionise the way we are doing science, and contribute to overcoming the three gaps between the world of ideas, inventors, innovators and investors as introduced by Gebeshuber, Gruber and Drack in 2009 for accelerated scientific and technological breakthroughs to improve the human condition. Inspiration for the development of above methods was the fact that generally tribologists and biologists do not see many overlaps of their professions. However, both deal with materials, structures and processes. Tribology is omnipresent in biology and many biological systems have impressive tribological properties. Tribologists can therefore get valuable input and inspiration from living systems. The aim of biomimetics is knowledge transfer from biology to technology and successful biomimetics in tribology needs collaboration between biologists and tribologists. Literature search shows that the number of papers regarding biotribology is steadily increasing. However, at the moment, most scientific papers of the other respective field are hard to access and hard to understand, in terms of concepts and specific wording, hindering successful collaboration and resulting in long times that are needed to speak and understand the other's language. For example, there is a plenitude of biology papers that deal with friction, adhesion, wear and lubrication that were written solely for a biology readership and that have high potential to serve as inspiration for tribology if they were available in a language or in an environment accessible for tribologists. The three needs that can be identified regarding successful biomimetics for microtribologists (i.e. joint language, joint way of publishing results, and joint seminars, workshops and conferences) are developed further into a general concept concerning the future of scientific publications and ordering as well as accessing the knowledge of our time.
Effect of Sun and Planet-Bound Dark Matter on Planet and Satellite Dynamics in the Solar System

We apply our recent results on orbital dynamics around a mass-varying central body to the phenomenon of accretion of Dark Matter-assumed not self-annihilating-on the Sun and the major bodies of the solar system due to its motion throughout the Milky Way halo. We inspect its consequences on the orbits of the planets and their satellites over timescales of the order of the age of the solar system. It turns out that a solar Dark Matter accretion rate of ≈ 10−12 yr−1, inferred from the upper limit ΔM/M = 0.02−0.05 on the Sun's Dark Matter content, assumed somehow accumulated during last 4.5 Gyr, would have displaced the planets faraway by about 10−2−101 au 4.5 Gyr ago. Another consequence is that the semimajor axis of the Earth's orbit, approximately equal to the Astronomical Unit, would undergo a secular increase of 0.02-0.05 m yr−1, in agreement with the latest observational determinations of the Astronomical Unit secular increase of 0.07±0.02 m yr−1 and 0.05 m yr−1. By assuming that the Sun will continue to accrete Dark Matter in the next billions year at the same rate as putatively done in the past, the orbits of its planets will shrink by about 10−1−101 au ( ≈ 0.2−0.5 au for the Earth), with consequences for their fate, especially of the inner planets. On the other hand, lunar and planetary ephemerides set upper bounds on the secular variation of the Sun's gravitational parameter GM which are one one order of magnitude smaller than ≈ 10−12 yr−1. Dark Matter accretion on planets has, instead, less relevant consequences for their satellites. Indeed, 4.5 Gyr ago their orbits would have been just 10−2−101 km wider than now. Dark Matter accretion is not able to explain the observed accelerations of the orbits of some of the Galilean satellites of Jupiter, the secular decrease of the semimajor axis of the Earth's artificial satellite LAGEOS and the secular increase of the Moon's orbit eccentricity.
Bayesian Thought in Early Modern Detective Stories: Monsieur Lecoq, C. Auguste Dupin and Sherlock Holmes

This paper reviews the maxims used by three early modern fictional detectives: Monsieur Lecoq, C. Auguste Dupin and Sherlock Holmes. It find similarities between these maxims and Bayesian thought. Poe's Dupin uses ideas very similar to Bayesian game theory. Sherlock Holmes' statements also show thought patterns justifiable in Bayesian terms.
Markets are Efficient if and Only if P = NP

I prove that if markets are efficient, meaning current prices fully reflect all information available in past prices, then P=NP, meaning every computational problem whose solution can be verified in polynomial time can also be solved in polynomial time. I also prove the converse by showing how we can “program” the market to solve NP -complete problems. Since P probably does not equal NP, markets are probably not efficient. Specifically, markets become increasingly inefficient as the time series lengthens or becomes more frequent. An illustration by way of partitioning the excess returns to momentum strategies based on data availability confirms this prediction.
Entropic origin of disassortativity in complex networks.

Why are most empirical networks, with the prominent exception of social ones, generically degree-degree anticorrelated? To answer this long-standing question, we define the ensemble of correlated networks and obtain the associated Shannon entropy. Maximum entropy can correspond to either assortative (correlated) or disassortative (anticorrelated) configurations, but in the case of highly heterogeneous, scale-free networks a certain disassortativity is predicted--offering a parsimonious explanation for the question above. Our approach provides a neutral model from which, in the absence of further knowledge regarding network evolution, one can obtain the expected value of correlations. When empirical observations deviate from the neutral predictions--as happens for social networks--one can then infer that there are specific correlating mechanisms at work.
Exploring the Limits of GPUs With Parallel Graph Algorithms

In this paper, we explore the limits of graphics processors (GPUs) for general purpose parallel computing by studying problems that require highly irregular data access patterns: parallel graph algorithms for list ranking and connected components. Such graph problems represent a worst case scenario for coalescing parallel memory accesses on GPUs which is critical for good GPU performance. Our experimental study indicates that PRAM algorithms are a good starting point for developing efficient parallel GPU methods but require non-trivial modifications to ensure good GPU performance. We present a set of guidelines that help algorithm designers adapt PRAM graph algorithms for parallel GPU computation. We point out that the study of parallel graph algorithms for GPUs is of wider interest for discrete and combinatorial problems in general because many of these problems require similar irregular data access patterns.
Effects of mass media action on the Axelrod model with social influence.

The use of dyadic interaction between agents, in combination with homophily (the principle that "likes attract") in the Axelrod model for the study of cultural dissemination, has two important problems: the prediction of monoculture in large societies and an extremely narrow window of noise levels in which diversity with local convergence is obtained. Recently, the inclusion of social influence has proven to overcome them [A. Flache and M. W. Macy, ]. Here, we extend the Axelrod model with social influence interaction for the study of mass media effects through the inclusion of a superagent which acts over the whole system and has non-null overlap with each agent of the society. The dependence with different parameters as the initial social diversity, size effects, mass media strength, and noise is outlined. Our results might be relevant in several socioeconomic contexts and for the study of the emergence of collective behavior in complex social systems.
An Approach to Ad hoc Cloud Computing

We consider how underused computing resources within an enterprise may be harnessed to improve utilization and create an elastic computing infrastructure. Most current cloud provision involves a data center model, in which clusters of machines are dedicated to running cloud infrastructure software. We propose an additional model, the ad hoc cloud, in which infrastructure software is distributed over resources harvested from machines already in existence within an enterprise. In contrast to the data center cloud model, resource levels are not established a priori, nor are resources dedicated exclusively to the cloud while in use. A participating machine is not dedicated to the cloud, but has some other primary purpose such as running interactive processes for a particular user. We outline the major implementation challenges and one approach to tackling them.
Opinion dynamics with confidence threshold: an alternative to the Axelrod model

The voter model and the Axelrod model are two of the main stochastic processes that describe the spread of opinions on networks. The former includes social influence, the tendency of individuals to become more similar when they interact, while the latter also accounts for homophily, the tendency to interact more frequently with individuals which are more similar. The Axelrod model has been extensively studied during the past ten years based on numerical simulations. In contrast, we give rigorous analytical results for a generalization of the voter model that is closely related to the Axelrod model as it combines social influence and confidence threshold, which is modeled somewhat similarly to homophily. Each vertex of the network, represented by a finite connected graph, is characterized by an opinion and may interact with its adjacent vertices. Like the voter model, an interaction results in an agreement between both interacting vertices -- social influence -- but unlike the voter model, an interaction takes place if and only if the vertices' opinions are within a certain distance -- confidence threshold. In a deterministic static approach, we first give lower and upper bounds for the maximum number of opinions that can be supported by the network as a function of the confidence threshold and various characteristics of the graph. The number of opinions coexisting at equilibrium is then investigated in a probabilistic dynamic approach for the stochastic process starting from a random configuration ...
Galaxy Zoo:bars in disc galaxies

We present first results from Galaxy Zoo 2, the second phase of the highly successful Galaxy Zoo project (http://www.galaxyzoo.org). Using a volume-limited sample of 13 665 disc galaxies (0.01 < z < 0.06 and Mr < −19.38), we study the fraction of galaxies with bars as a function of global galaxy properties like colour, luminosity and bulge prominence. Overall, 29.4 ± 0.5 per cent of galaxies in our sample have a bar, in excellent agreement with previous visually classified samples of galaxies (although this overall fraction is lower than that measured by automated bar-finding methods). We see a clear increase in the bar fraction with redder (g−r) colours, decreased luminosity and in galaxies with more prominent bulges, to the extent that over half of the red, bulge-dominated disc galaxies in our sample possess a bar. We see evidence for a colour bimodality for our sample of disc galaxies, with a ‘red sequence’ that is both bulge and bar dominated, and a ‘blue cloud’ which has little, or no, evidence for a (classical) bulge or bar. These results are consistent with similar trends for barred galaxies seen recently both locally and at higher redshift, and with early studies using the RC3. We discuss these results in the context of internal (secular) galaxy evolution scenarios and the possible links to the formation of bars and bulges in disc galaxies.
Information-Sharing and Privacy in Social Networks

We present a new model for reasoning about the way information is shared among friends in a social network, and the resulting ways in which it spreads. Our model formalizes the intuition that revealing personal information in social settings involves a trade-off between the benefits of sharing information with friends, and the risks that additional gossiping will propagate it to people with whom one is not on friendly terms. We study the behavior of rational agents in such a situation, and we characterize the existence and computability of stable information-sharing networks, in which agents do not have an incentive to change the partners with whom they share information. We analyze the implications of these stable networks for social welfare, and the resulting fragmentation of the social network.
Comments on “The Depth-Dependent Current and Wave Interaction Equations: A Revision”

AbstractEquations for the wave-averaged three-dimensional momentum equations have been published in this journal. It appears that these equations are not consistent with the known depth-integrated momentum balance, especially over a sloping bottom. These equations should thus be considered with caution, because they can produce erroneous flows, particularly outside of the surf zone. It is suggested that the inconsistency in the equations may arise from the different averaging operators applied to the different terms of the momentum equation. It is concluded that other forms of the momentum equations, expressed in terms of the quasi-Eulerian velocity, are better suited for three-dimensional modeling of wave–current interactions.
The genome is software and evolution is a software developer

The genome is software because it a set of verbal instructions for a programmable computer, the ribosome. The theory of evolution now reads: evolution is the software developer responsible for the existence of the genome. We claim that this setting, whose official name is genetic programming, is necessary and sufficient to discuss all important questions about evolution. A great effort has been made to pass from wording to science, i.e., from naive theories to robust models to predictions to testing for falsification.
Centrality scaling in large networks.

Betweenness centrality lies at the core of both transport and structural vulnerability properties of complex networks; however, it is computationally costly, and its measurement for networks with millions of nodes is nearly impossible. By introducing a multiscale decomposition of shortest paths, we show that the contributions to betweenness coming from geodesics not longer than L obey a characteristic scaling versus L, which can be used to predict the distribution of the full centralities. The method is also illustrated on a real-world social network of 5.5 × 10(6) nodes and 2.7 × 10(7) links.
The relation between Eigenfactor, audience factor, and influence weight

We present a theoretical and empirical analysis of a number of bibliometric indicators of journal performance. We focus on three indicators in particular: the Eigenfactor indicator, the audience factor, and the influence weight indicator. Our main finding is that the last two indicators can be regarded as a kind of special case of the first indicator. We also find that the three indicators can be nicely characterized in terms of two properties. We refer to these properties as the property of insensitivity to field differences and the property of insensitivity to insignificant journals. The empirical results that we present illustrate our theoretical findings. We also show empirically that the differences between various indicators of journal performance are quite substantial.