24 research outputs found

    Characterization of maximally random jammed sphere packings: Voronoi correlation functions

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    We characterize the structure of maximally random jammed (MRJ) sphere packings by computing the Minkowski functionals (volume, surface area, and integrated mean curvature) of their associated Voronoi cells. The probability distribution functions of these functionals of Voronoi cells in MRJ sphere packings are qualitatively similar to those of an equilibrium hard-sphere liquid and partly even to the uncorrelated Poisson point process, implying that such local statistics are relatively structurally insensitive. This is not surprising because the Minkowski functionals of a single Voronoi cell incorporate only local information and are insensitive to global structural information. To improve upon this, we introduce descriptors that incorporate nonlocal information via the correlation functions of the Minkowski functionals of two cells at a given distance as well as certain cell-cell probability density functions. We evaluate these higher-order functions for our MRJ packings as well as equilibrium hard spheres and the Poisson point process. We find strong anticorrelations in the Voronoi volumes for the hyperuniform MRJ packings, consistent with previous findings for other pair correlations [A. Donev et al., Phys. Rev. Lett. 95, 090604 (2005)], indicating that large-scale volume fluctuations are suppressed by accompanying large Voronoi cells with small cells, and vice versa. In contrast to the aforementioned local Voronoi statistics, the correlation functions of the Voronoi cells qualitatively distinguish the structure of MRJ sphere packings (prototypical glasses) from that of the correlated equilibrium hard-sphere liquids. Moreover, while we did not find any perfect icosahedra (the locally densest possible structure in which a central sphere contacts 12 neighbors) in the MRJ packings, a preliminary Voronoi topology analysis indicates the presence of strongly distorted icosahedra.Comment: 13 pages, 10 figure

    Characterization of Anisotropic Gaussian Random Fields by Minkowski Tensors

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    Gaussian random fields are among the most important models of amorphous spatial structures and appear across length scales in a variety of physical, biological, and geological applications, from composite materials to geospatial data. Anisotropy in such systems can sensitively and comprehensively be characterized by the so-called Minkowski tensors from integral geometry. Here, we analytically calculate the expected Minkowski tensors of arbitrary rank for the level sets of Gaussian random fields. The explicit expressions for interfacial Minkowski tensors are confirmed in detailed simulations. We demonstrate how the Minkowski tensors detect and characterize the anisotropy of the level sets, and we clarify which shape information is contained in the Minkowski tensors of different rank. Using an irreducible representation of the Minkowski tensors in the Euclidean plane, we show that higher-rank tensors indeed contain additional anisotropy information compared to a rank two tensor. Surprisingly, we can nevertheless predict this information from the second-rank tensor if we assume that the random field is Gaussian. This relation between tensors of different rank is independent of the details of the model. It is, therefore, useful for a null hypothesis test that detects non-Gaussianities in anisotropic random fields

    Association of Clonal Hematopoiesis of Indeterminate Potential with Inflammatory Gene Expression in Patients with COPD

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    Chronic obstructive pulmonary disease (COPD) is a disease with an inflammatory pheno type with increasing prevalence in the elderly. Expanded population of mutant blood cells carrying somatic mutations is termed clonal hematopoiesis of indeterminate potential (CHIP). The associ ation between CHIP and COPD and its relevant effects on DNA methylation in aging are mainly unknown. Analyzing the deep-targeted amplicon sequencing from 125 COPD patients, we found enhanced incidence of CHIP mutations (~20%) with a predominance of DNMT3A CHIP-mediated hypomethylation of Phospholipase D Family Member 5 (PLD5), which in turn is positively correlated with increased levels of glycerol phosphocholine, pro-inflammatory cytokines, and deteriorating lung function

    Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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    The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

    Morphometrie von zufälligen räumlichen Strukturen in der Physik

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    From the large-scale structure of the universe to exotic states in nuclear matter: random or disordered spatial structures appear on nearly all length scales in very different physical, chemical, or biological systems. In systems with complex structure, there is often a close interconnection of physics and geometry, and physical insight is often best achieved by a rigorous characterization of the structure. This thesis demonstrates how a family of integral geometric shape descriptors, the so-called Minkowski functionals and tensors, provide an intuitive and versatile morphometric analysis. It sensitively and comprehensively describes the geometry in diverse systems on radically different length scales. The morphometric analysis is refined and applied to mathematical models and simulations of physical systems as well as experimental data sets. For example, the structures appearing in models from stochastic geometry are examined with a particular emphasis on anisotropy. In one of these models, the Minkowski functionals help to better understand and predict a geometrical phase transition. Moreover, a structural characterization across length scales of a physical model, which consists of hard particles, reveals how systems with similar local configurations can nevertheless exhibit a distinctly different global structure. On extremely small length scales, the Minkowski functionals help to characterize complex shapes of exotic states of nuclear matter. Among a variety of these spontaneously forming so-called pasta shapes, a gyroid network is identified, which was, e.g., already found in the wing scales of a butterfly. In a morphometric data analysis, the Minkowski functionals quantify the shape of noise in sky maps from gamma-ray astronomy. Thus, additional geometric information can be extracted from the data without prior assumptions about potential sources. The latter can then be detected by a significant deviation of the structure of the observed sky map from the shape of the background noise. By an enhanced characterization of this background structure, formerly undetected sources can eventually be detected in the same data. The Minkowski functionals and tensors allow for a better understanding of quite different mathematical models and physical systems as well as a sensitive analysis of experimental observations. Thereby, this morphometric analysis relates seemingly unrelated fields of research.Von der Großraumstruktur des Universums bis hin zu exotischen Zuständen in nuklearer Materie: auf beinahe allen Längenskalen und in sehr unterschiedlichen physikalischen, chemischen oder biologischen Systemen treten zufällige oder ungeordnete räumliche Strukturen auf. Bei komplexen Strukturen gibt es oft enge Beziehungen zwischen physikalischen und geometrischen Eigenschaften. Dabei können Einsichten in das physikalische Verhalten oft am Besten durch eine rigorose Strukturbeschreibung gewonnen werden. Diese Arbeit zeigt wie eine Familie integralgeometrischer Formmaße, die sogenannten Minkowski Funktionale und Tensoren, eine intuitive und vielseitige morphometrische Analyse ermöglichen. Diese beschreibt sensitiv und umfassend die Geometrie in unterschiedlichen Systemen auf verschiedensten Längenskalen. Die morphometrische Analyse wird erweitert und auf mathematische Modelle und physikalische Systeme angewandt ebenso wie auf experimentelle Datensätze. Zum Beispiel werden Strukturen untersucht, welche in Modellen aus der stochastischen Geometrie auftreten, mit einem besonderen Schwerpunkt auf Anisotropie. In einem dieser Modelle helfen die Minkowski Funktionale einen geometrischen Phasenübergang besser zu verstehen und vorherzusagen. Darüber hinaus zeigt eine Strukturbeschreibung über verschiedene Größenordnungen hinweg für ein physikalisches Modell, welches aus harten Teilchen besteht, wie Systeme mit ähnlichen lokalen Anordnungen trotzdem eine deutlich verschiedene globale Struktur aufweisen können. Auf extrem kleinen Längenskalen helfen die Minkowski Funktionale komplexe Formen exotischer Zustände nuklearer Materie zu charakterisieren. Unter einer Vielzahl dieser sich spontan bildenden sogenannten Pasta Formen wird ein Gyroidnetzwerk identifiziert. Dieses wurde zum Beispiel schon in den Schuppen von Schmetterlingsflügeln gefunden. In einer morphometrischen Datenanalyse quantifizieren die Minkowski Funktionale die Form des Rauschens in Himmelskarten der Gammastrahlenastronomie. Dadurch kann den Daten zusätzliche geometrische Information entnommen werden ohne jegliche a priori Annahmen über mögliche Quellen. Letztere können dann detektiert werden durch eine signifikante Abweichung der Struktur der beobachteten Himmelskarten von der des Hintergrundrauschens. Durch eine verbesserte Beschreibung dieser Hintergrundstruktur können ehemals undetektierte Quellen nun in denselben Datensätzen gefunden werden. Die Minkowski Funktionale und Tensoren ermöglichen ein besseres Verständnis von sehr verschiedenen mathematischen Modellen und physikalischen Systemen sowie eine sensitivere Analyse experimenteller Beobachtungen. Dadurch verbindet die morphometrische Analyse scheinbar unzusammenhängende Forschungsgebiete

    Variations of water mass properties in the Weddell Sea

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    Data from cruises between 1989 and 2005 with RV POLARSTERN reveal significant temperature and salinity variations of the Warm Deep Water and the Weddell Sea Bottom Water. In the bottom water of the Weddell Sea proper a temperature increase by 0.12°C was observed over 16 years from 1989 to 2005. At the prime meridian warming occurred in the Warm Deep Water from 1984 to 1996 followed by cooling since then. The warming trend in the bottom water is detected here as well and started in 1992.The warming of Warm Deep Water is associated to a salinity increase which is consistent with an intensified inflow from the Antarctic Circumpolar Current. However, in spite of cooling since 1996 the salinity remains constant. This suggests that the variations are generated by a period of intensified injection of Circumpolar Deep Water. The additional heat is lost to the atmosphere whereas the salt remains in the water column. Since the contrast of Warm Deep Water and Winter Water properties determines the stability of the upper water column, the observed variations have the potential to affect the formation of a large polynya in the area. However, intensive seasonal variations in the near surface layers render the detection of trends difficult and variable freshwater input might wipe out the input from the deeper layers. The Weddell Sea Bottom Water increases in temperature and salinity as well, suggesting that the variation of the source water is transmitted to the newly formed water masses.The Weddell Sea is known to feed freshly formed deep and bottom waters into the Antarctic circumpolar water belt from where it spreads as part of the global thermohaline circulation into the basins of all three world oceans. By this process the Southern Oceans plays a significant role in global climate. Variations in the Weddell Sea can therefore be essential for global thermohaline circulation
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