431 research outputs found
Backbone of conductivity in two-dimensional metal-insulator composites
In percolation theory, the backbone is defined by chopping off dangling ends from the percolating cluster. For structures with high degree of spatial correlation, as they are typical for porous thin films, trimming of the full structure to reveal the part determining the electrical conductivity is more subtle than the classic definition of the backbone. To expand the applicability of the concept, we present a purely geometric definition for the backbone of a two-dimensional percolating cluster. It is based on a sequence of image analysis operations defining the backbone in terms of an image filter. The change of both area fraction and effective conductivity induced by applying the backbone filter to various binary images and a two-parameter family of sets is assessed by numerical means. It is found that the backbone filter simplifies the geometry of complex microstructures significantly and at the same time preserves their electrical DC behavior. We conclude that the backbone will be useful as a first ingredient for a geometric estimator of the effective conductivity of metal-insulator composites
Benchmarking the Utility of w-Event Differential Privacy Mechanisms: When Baselines Become Mighty Competitors
The w-event framework is the current standard for ensuring differential privacy on continuously monitored data streams. Following the proposition of w-event differential privacy, various mechanisms to implement the framework are proposed. Their comparability in empirical studies is vital for both practitioners to choose a suitable mechanism, and researchers to identify current limitations and propose novel mechanisms. By conducting a literature survey, we observe that the results of existing studies are hardly comparable and partially intrinsically inconsistent.
To this end, we formalize an empirical study of w-event mechanisms by re-occurring elements found in our survey. We introduce requirements on these elements that ensure the comparability of experimental results. Moreover, we propose a benchmark that meets all requirements and establishes a new way to evaluate existing and newly proposed mechanisms. Conducting a large-scale empirical study, we gain valuable new insights into the strengths and weaknesses of existing mechanisms. An unexpected - yet explainable - result is a baseline supremacy, i.e., using one of the two baseline mechanisms is expected to deliver good or even the best utility. Finally, we provide guidelines for practitioners to select suitable mechanisms and improvement options for researchers
The Influence of the Degree of Heterogeneity on the Elastic Properties of Random Sphere Packings
The macroscopic mechanical properties of colloidal particle gels strongly
depend on the local arrangement of the powder particles. Experiments have shown
that more heterogeneous microstructures exhibit up to one order of magnitude
higher elastic properties than their more homogeneous counterparts at equal
volume fraction. In this paper, packings of spherical particles are used as
model structures to computationally investigate the elastic properties of
coagulated particle gels as a function of their degree of heterogeneity. The
discrete element model comprises a linear elastic contact law, particle bonding
and damping. The simulation parameters were calibrated using a homogeneous and
a heterogeneous microstructure originating from earlier Brownian dynamics
simulations. A systematic study of the elastic properties as a function of the
degree of heterogeneity was performed using two sets of microstructures
obtained from Brownian dynamics simulation and from the void expansion method.
Both sets cover a broad and to a large extent overlapping range of degrees of
heterogeneity. The simulations have shown that the elastic properties as a
function of the degree of heterogeneity are independent of the structure
generation algorithm and that the relation between the shear modulus and the
degree of heterogeneity can be well described by a power law. This suggests the
presence of a critical degree of heterogeneity and, therefore, a phase
transition between a phase with finite and one with zero elastic properties.Comment: 8 pages, 6 figures; Granular Matter (published online: 11. February
2012
Generation of Porous Particle Structures using the Void Expansion Method
The newly developed "void expansion method" allows for an efficient
generation of porous packings of spherical particles over a wide range of
volume fractions using the discrete element method. Particles are randomly
placed under addition of much smaller "void-particles". Then, the void-particle
radius is increased repeatedly, thereby rearranging the structural particles
until formation of a dense particle packing.
The structural particles' mean coordination number was used to characterize
the evolving microstructures. At some void radius, a transition from an
initially low to a higher mean coordination number is found, which was used to
characterize the influence of the various simulation parameters. For structural
and void-particle stiffnesses of the same order of magnitude, the transition is
found at constant total volume fraction slightly below the random close packing
limit. For decreasing void-particle stiffness the transition is shifted towards
a smaller void-particle radius and becomes smoother.Comment: 9 pages, 8 figure
Correction: Interactions of prototype foamy virus capsids with host cell polo-like kinases are important for efficient viral DNA integration.
[This corrects the article DOI: 10.1371/journal.ppat.1005860.]
Detection of Semi-Major Axis Drifts in 54 Near-Earth Asteroids: New Measurements of the Yarkovsky Effect
We have identified and quantified semi-major axis drifts in Near-Earth
Asteroids (NEAs) by performing orbital fits to optical and radar astrometry of
all numbered NEAs. We focus on a subset of 54 NEAs that exhibit some of the
most reliable and strongest drift rates. Our selection criteria include a
Yarkovsky sensitivity metric that quantifies the detectability of semi-major
axis drift in any given data set, a signal-to-noise metric, and orbital
coverage requirements. In 42 cases, the observed drifts (~10^-3 AU/Myr) agree
well with numerical estimates of Yarkovsky drifts. This agreement suggests that
the Yarkovsky effect is the dominant non-gravitational process affecting these
orbits, and allows us to derive constraints on asteroid physical properties. In
12 cases, the drifts exceed nominal Yarkovsky predictions, which could be due
to inaccuracies in our knowledge of physical properties, faulty astrometry, or
modeling errors. If these high rates cannot be ruled out by further
observations or improvements in modeling, they would be indicative of the
presence of an additional non-gravitational force, such as that resulting from
a loss of mass of order a kilogram per second. We define the Yarkovsky
efficiency f_Y as the ratio of the change in orbital energy to incident solar
radiation energy, and we find that typical Yarkovsky efficiencies are ~10^-5.Comment: Accepted for publication by The Astronomical Journal. 42 pages, 8
figure
Workshop report: “Towards a Cure: HIV Reservoirs and Strategies to Control Them”
On 16 and 17 July 2010, immediately prior to the XVIII International AIDS Conference in Vienna, Austria, the International AIDS Society held a workshop on the important topic of moving beyond antiretroviral therapy and addressing HIV persistence. “Towards a Cure: HIV Reservoirs and Strategies to Control Them” was chaired by Nobel laureate Françoise Barré-Sinoussi and co-sponsored by the French National Agency for Research on AIDS and Viral Hepatitis, Bundesministerium für Wissenschaft und Forschung, the National Institutes of Health, Sidaction and the Treatment Action Group. This article gives an overview of the findings presented at the workshop; complete abstracts are included in this supplement to the Journal of the International AIDS Society
Roadmap on multiscale materials modeling
Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware
Modal behavior of a reduced scale pump-turbine impeller. Part 1: Experiments
An experimental investigation has been carried out to quantify the effects of surrounding fluid on the modal behavior of a reduced scale pump-turbine impeller. The modal properties of the fluid-structure system have been obtained by Experimental Modal Analysis (EMA) with the impeller suspended in air and inside a water reservoir. The impeller has been excited with an instrumented hammer and the response has been measured by means of miniature accelerometers. The Frequency Response Functions (FRF’s) have been obtained from a large number of impacting positions in order to ensure the identification of the main mode shapes. As a result, the main modes of vibration have been well characterized both in air and in water in terms of natural frequency, damping ratio and mode shape. The first mode is the 2 Nodal Diameter (ND), the second one is the 0ND and the following ones are the 3ND coupled with the 1ND. The visual observation of the animated mode shapes and the level of the Modal Assurance Criterion (MAC) have permitted to correlate the homologous modes of vibration of the fluid-structure system in air and in water. From this comparison the added mass effect on the natural frequencies and the fluid effect on the damping ratios have been quantified for the most significant modes. With the surrounding water, the natural frequencies decrease in average by 10%. On the other hand, the damping ratios increase in average by 0.5%. In any case, the damping ratio appears to decrease with the frequency value of the mode
Stepwise-edited, human melanoma models reveal mutations' effect on tumor and microenvironment.
Establishing causal relationships between genetic alterations of human cancers and specific phenotypes of malignancy remains a challenge. We sequentially introduced mutations into healthy human melanocytes in up to five genes spanning six commonly disrupted melanoma pathways, forming nine genetically distinct cellular models of melanoma. We connected mutant melanocyte genotypes to malignant cell expression programs in vitro and in vivo, replicative immortality, malignancy, rapid tumor growth, pigmentation, metastasis, and histopathology. Mutations in malignant cells also affected tumor microenvironment composition and cell states. Our melanoma models shared genotype-associated expression programs with patient melanomas, and a deep learning model showed that these models partially recapitulated genotype-associated histopathological features as well. Thus, a progressive series of genome-edited human cancer models can causally connect genotypes carrying multiple mutations to phenotype
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