nils-herrmann/clean_scirepeval huggingface dataset:
The Genomic Impacts of Drift and Selection for Hybrid Performance in Maize

Although maize is naturally an outcrossing organism, modern breeding utilizes highly inbred lines in controlled crosses to produce hybrids. The U.S. Department of Agriculture’s reciprocal recurrent selection experiment between the Iowa Stiff Stalk Synthetic (BSSS) and the Iowa Corn Borer Synthetic No. 1 (BSCB1) populations represents one of the longest running experiments to understand the response to selection for hybrid performance. To investigate the genomic impact of this selection program, we genotyped the progenitor lines and >600 individuals across multiple cycles of selection using a genome-wide panel of ∼40,000 SNPs. We confirmed previous results showing a steady temporal decrease in genetic diversity within populations and a corresponding increase in differentiation between populations. Thanks to detailed historical information on experimental design, we were able to perform extensive simulations using founder haplotypes to replicate the experiment in the absence of selection. These simulations demonstrate that while most of the observed reduction in genetic diversity can be attributed to genetic drift, heterozygosity in each population has fallen more than expected. We then took advantage of our high-density genotype data to identify extensive regions of haplotype fixation and trace haplotype ancestry to single founder inbred lines. The vast majority of regions showing such evidence of selection differ between the two populations, providing evidence for the dominance model of heterosis. We discuss how this pattern is likely to occur during selection for hybrid performance and how it poses challenges for dissecting the impacts of modern breeding and selection on the maize genome.
The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.
Multiversality

Valid ideas that physical reality is vastly larger than human perception of it, and that the perceived part may not be representative of the whole, exist on many levels and have a long history. After a brief general inventory of those ideas and their implications, I consider the cosmological ‘multiverse’ much discussed in recent scientific literature. I review its theoretical and (broadly) empirical motivations, and its disruptive implications for the traditional program of fundamental physics. I discuss the inflationary axion cosmology, which provides an example where firmly rooted, plausible ideas from microphysics lead to a well-characterized ‘mini-multiverse’ scenario, with testable phenomenological consequences.
Compton Effect in the Medium with Non-unity Refractive Index

The foundations of the modern quantum theory of electro-magnetic radiation and its interaction with medium is constituted by the Einstein's theory of photo-efiect and the theory of Compton efiect. However, in the theory proposed by Compton and subsequent reflnements, the medium features in explicit form are not generally accounted at all. This theory is based on the relationship between the photon momentum and its energy that may take place only in vacuum, but not in a medium with non-unity refractive index n. Here we use Abraham's representation for the momentum of a photon in medium for the creation of a new consistent Compton efiect theory accounting for media features. A new condition under which anomalous Compton efiect is possible, is deflned. In our case, due to the photon scattering on a moving electron, the photon's energy can increase when the electron velocity is above a threshold value, in analogy with the Vavilov-Cherenkov radiation efiect. In our theory we also provide a new description of the parameters for scattered electrons, which is important for the experimental determination of the dependence of the Compton efiect in medium on refractive index n.
THE DENSEST GALAXY

We report the discovery of a remarkable ultra-compact dwarf galaxy around the massive Virgo elliptical galaxy NGC 4649 (M60), which we call M60-UCD1. With a dynamical mass of 2.0 × 108 M☉ but a half-light radius of only ∼24 pc, M60-UCD1 is more massive than any ultra-compact dwarfs of comparable size, and is arguably the densest galaxy known in the local universe. It has a two-component structure well fit by a sum of Sérsic functions, with an elliptical, compact (rh = 14 pc; n ∼ 3.3) inner component and a round, exponential, extended (rh = 49 pc) outer component. Chandra data reveal a variable central X-ray source with LX ∼ 1038 erg s−1 that could be an active galactic nucleus associated with a massive black hole or a low-mass X-ray binary. Analysis of optical spectroscopy shows the object to be old (≳ 10 Gyr) and of solar metallicity, with elevated [Mg/Fe] and strongly enhanced [N/Fe] that indicates light-element self-enrichment; such self-enrichment may be generically present in dense stellar systems. The velocity dispersion (σ ∼ 70 km s−1) and resulting dynamical mass-to-light ratio (M/LV = 4.9 ± 0.7) are consistent with—but slightly higher than—expectations for an old, metal-rich stellar population with a Kroupa initial mass function. The presence of a massive black hole or a mild increase in low-mass stars or stellar remnants is therefore also consistent with this M/LV. The stellar density of the galaxy is so high that no dynamical signature of dark matter is expected. However, the properties of M60-UCD1 suggest an origin in the tidal stripping of a nucleated galaxy with MB ∼ −18 to −19.
Susceptibility at the superfluid-insulator transition for one-dimensional disordered bosons

A pair of recent Monte Carlo studies have reported evidence for and against a crossover from weak to strong-disorder criticality in the one-dimensional dirty boson problem. The Monte Carlo analyses rely on measurement of two observables: the effective Luttinger parameter K_(eff) and the superfluid susceptibility χ. The former quantity was previously calculated analytically, using the strong-disorder renormalization group (SDRG), by Altman, Kafri, Polkovnikov, and Refael. Here, we use an extension of the SDRG framework to find a non-universal anomalous dimension η_(sd) characterizing the divergence of the susceptibility with system size: χ ~ L^(2-η_(sd)). We show that η_(sd) obeys the hyperscaling relation η_(sd) = 1/2K_(eff). We also identify an important obstacle to measuring this exponent on finite-size systems and comment on the implications for numerics and experiments.
Tensor network trial states for chiral topological phases in two dimensions

Trial wavefunctions that can be represented by summing over locally-coupled degrees of freedom are called tensor network states; they have seemed difficult to construct for two-dimensional topological phases that possess protected gapless edge excitations. We show it can be done for chiral states of free fermions, using a Gaussian Grassmann integral, yielding p_x \pm i p_y and Chern insulator states. We show that any strictly short-range quadratic parent Hamiltonian for these states is gapless. Further examples are analogs of fractional (including non-Abelian) quantum Hall phases.
Supercritical instability in graphene with two charged impurities

We study the supercritical instability in gapped graphene with two charged impurities separated by distance R using the two-dimensional Dirac equation for electron quasiparticles. Attention is paid to a situation when charges of impurities are subcritical, whereas their total charge exceeds a critical one. The critical distance R_{cr} in the system of two charged centers is defined as that at which the electron bound state with the lowest energy reaches the boundary of the lower continuum. A variational calculation of the critical distance R_{cr} separating the supercritical (R R_{cr}) regimes is carried out. It is shown that the critical distance R_{cr} increases as the quasiparticle gap decreases. The energy and width of a quasistationary state as functions of the distance between two impurities are derived in the quasiclassical approximation.
A Population Genetic Signal of Polygenic Adaptation

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results.
The Majorana Demonstrator: A Search for Neutrinoless Double-beta Decay of Germanium-76

The observation of neutrino less double-beta decay would show that neutrinos are Majorana particles and provide information on neutrino mass. Attaining sensitivities for neutrino masses in the inverted hierarchy region requires large, tonne scale detectors with extremely low backgrounds, at the level of 10−3 counts keV−1 t−1 y−1 or lower in the region of the signal. The MAJORANA collaboration is constructing the DEMONSTRATOR, an array consisting of 40 kg of p-type point contact germanium detectors, at least half of which will be enriched to 86% in 76Ge. The primary aim is to show the feasibility for a future tonne scale measurement. With a sub-keV energy threshold, the array should also be able to search for light WIMP dark matter. This paper presents a brief update on the status of constructing the DEMONSTRATOR including an electroforming facility that is now operating underground at the Sanford Underground Research Facility.
Ancient west Eurasian ancestry in southern and eastern Africa

The hunter–gatherer and pastoralist populations of southern Africa are among the culturally, linguistically, and genetically most diverse human populations. However, little is known about their history. We show that all of these populations have some ancestry most closely related to Europeans and Middle Easterners and use this to reconstruct the history of population movements between Eurasia, eastern Africa, and southern Africa. The history of southern Africa involved interactions between indigenous hunter–gatherers and a range of populations that moved into the region. Here we use genome-wide genetic data to show that there are at least two admixture events in the history of Khoisan populations (southern African hunter–gatherers and pastoralists who speak non-Bantu languages with click consonants). One involved populations related to Niger–Congo-speaking African populations, and the other introduced ancestry most closely related to west Eurasian (European or Middle Eastern) populations. We date this latter admixture event to ∼900–1,800 y ago and show that it had the largest demographic impact in Khoisan populations that speak Khoe–Kwadi languages. A similar signal of west Eurasian ancestry is present throughout eastern Africa. In particular, we also find evidence for two admixture events in the history of Kenyan, Tanzanian, and Ethiopian populations, the earlier of which involved populations related to west Eurasians and which we date to ∼2,700–3,300 y ago. We reconstruct the allele frequencies of the putative west Eurasian population in eastern Africa and show that this population is a good proxy for the west Eurasian ancestry in southern Africa. The most parsimonious explanation for these findings is that west Eurasian ancestry entered southern Africa indirectly through eastern Africa.
Systematic and Nonsystematic Mortality Risk in Pension Portfolios

We study the effects of nonsystematic and systematic mortality risks on the required initial capital in a pension plan, in the presence of financial risks. We discover that for a pension plan with few members the impact of pooling on the required capital per person is strong, but nonsystematic risk diminishes rapidly as the number of members increases. Systematic mortality risk, on the other hand, is a significant source of risk in a pension portfolio.
Exploring genome characteristics and sequence quality without a reference

The de novo assembly of large, complex genomes is a significant challenge with currently available DNA sequencing technology. While many de novo assembly software packages are available, comparatively little attention has been paid to assisting the user with the assembly.  This article addresses the practical aspects of de novo assembly by introducing new ways to perform quality assessment on a collection of sequence reads. The software implementation calculates per-base error rates, paired-end fragment-size distributions and coverage metrics in the absence of a reference genome. Additionally, the software will estimate characteristics of the sequenced genome, such as repeat content and heterozygosity that are key determinants of assembly difficulty.  The software described is freely available online (https://github.com/jts/sga) and open source under the GNU Public License.  Supplementary data are available at Bioinformatics online.
Manipulating scattering of ultracold atoms with light-induced dissipation

Recently it has been shown that pairs of atoms can form metastable bonds due to non-conservative forces induced by dissipation [Lemeshko\&Weimer,  2230 (2013)]. Here we study the dynamics of interaction-induced coherent population trapping -- the process responsible for the formation of dissipatively bound molecules. We derive the effective dissipative potentials induced between ultracold atoms by laser light, and study the time evolution of the scattering states. We demonstrate that binding occurs on short timescales of $\sim10~\mu$s, even if the initial kinetic energy of the atoms significantly exceeds the depth of the dissipative potential. Dissipatively-bound molecules with preordained bond lengths and vibrational wavefunctions can be created and detected in current experiments with ultracold atoms.
DeBaCl: A Python Package for Interactive DEnsity-BAsed CLustering

The level set tree approach of Hartigan (1975) provides a probabilistically based and highly interpretable encoding of the clustering behavior of a dataset. By representing the hierarchy of data modes as a dendrogram of the level sets of a density estimator, this approach offers many advantages for exploratory analysis and clustering, especially for complex and high-dimensional data. Several R packages exist for level set tree estimation, but their practical usefulness is limited by computational inefficiency, absence of interactive graphical capabilities and, from a theoretical perspective, reliance on asymptotic approximations. To make it easier for practitioners to capture the advantages of level set trees, we have written the Python package DeBaCl for DEnsity-BAsed CLustering. In this article we illustrate how DeBaCl's level set tree estimates can be used for difficult clustering tasks and interactive graphical data analysis. The package is intended to promote the practical use of level set trees through improvements in computational efficiency and a high degree of user customization. In addition, the flexible algorithms implemented in DeBaCl enjoy finite sample accuracy, as demonstrated in recent literature on density clustering. Finally, we show the level set tree framework can be easily extended to deal with functional data.
Rosetta stone for parametrized tests of gravity

Several model-independent parameterizations of deviations from General Relativity have been developed to test Einstein's theory. Although these different parameterizations were developed for different gravitational observables, they ultimately all test the same underlying physics. In this paper, we develop connections between the parameterized post-Newtonian, parameterized post-Keplerian, and the parameterized post-Einsteinian frameworks, developed to carry out tests of General Relativity with Solar System, binary pulsar, and gravitational wave observations respectively. These connections allow us to use knowledge gained from one framework to inform and guide tests using the others. Relating these parameterizations and combining the results from each approach strengthens our tests of General Relativity.
Einstein gravity of a diffusing fluid

We discuss the Einstein gravity for a fluid consisting of particles interacting with an environment of some other particles. The environment is described by a time-dependent cosmological term which compensates the lack of the conservation law of the energy–momentum of the dissipative fluid. The dissipation is approximated by a relativistic diffusion in the phase space. We are interested in a homogeneous isotropic flat expanding Universe described by a scale factor a. At an early stage the particles are massless. We obtain explicit solutions of the diffusion equation for a fluid of massless particles at finite temperature. The solution is of the form of a modified Jüttner distribution with a time-dependent temperature. Later, Universe evolution is described as a diffusion at zero temperature with no equilibration. We find solutions of the diffusion equation at zero temperature which can be treated as a continuation to a later time of the finite temperature solutions describing an early stage of the Universe. The energy–momentum of the diffusing particles is defined by their phase space distribution. A conservation of the total energy–momentum determines the cosmological term up to a constant. The resulting energy–momentum inserted into the Einstein equations gives a modified Friedmann equation. Solutions of the Friedmann equation depend on the initial value of the cosmological term. The large value of the cosmological constant implies an exponential expansion. If the initial conditions allow a power-like solution for a large time then it must be of the form a ≃ τ (no deceleration, τ is the cosmic time). The final stage of the Universe evolution is described by a non-relativistic diffusion of a cold dust.
Posterior Contraction Rates of the Phylogenetic Indian Buffet Processes.

By expressing prior distributions as general stochastic processes, nonparametric Bayesian methods provide a flexible way to incorporate prior knowledge and constrain the latent structure in statistical inference. The Indian buffet process (IBP) is such an example that can be used to define a prior distribution on infinite binary features, where the exchangeability among subjects is assumed. The phylogenetic Indian buffet process (pIBP), a derivative of IBP, enables the modeling of non-exchangeability among subjects through a stochastic process on a rooted tree, which is similar to that used in phylogenetics, to describe relationships among the subjects. In this paper, we study the theoretical properties of IBP and pIBP under a binary factor model. We establish the posterior contraction rates for both IBP and pIBP and substantiate the theoretical results through simulation studies. This is the first work addressing the frequentist property of the posterior behaviors of IBP and pIBP. We also demonstrated its practical usefulness by applying pIBP prior to a real data example arising in the field of cancer genomics where the exchangeability among subjects is violated.
Critical transitions in social network activity

A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the internal dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments and climate conditions. Data and models suggest that detectable warning signs may precede some of these drastic events. This view is also corroborated by abstract mathematical theory for generic bifurcations in stochastic multi-scale systems. Whether the stochastic scaling laws used as warning signs are also present in social networks that anticipate a-priori {\it unknown} events in society is an exciting open problem, to which at present only highly speculative answers can be given. Here, we instead provide a first step towards tackling this formidable question by focusing on a-priori {\it known} events and analyzing a social network data set with a focus on classical variance and autocorrelation warning signs. Our results thus pertain to one absolutely fundamental question: Can the stochastic warning signs known from other areas also be detected in large-scale social network data? We answer this question affirmatively as we find that several a-priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relation between abstract mathematical theory and various classes of critical transitions in social networks.