Frictional dynamics of viscoelastic solids driven on a rough surface

We study the effect of viscoelastic dynamics on the frictional properties of a (mean field) spring-block system pulled on a rough surface by an external drive. When the drive moves at constant velocity V, two dynamical regimes are observed: at fast driving, above a critical threshold Vc, the system slides at the drive velocity and displays a friction force with velocity weakening. Below Vc the steady sliding becomes unstable and a stick-slip regime sets in. In the slide-hold-slide driving protocol, a peak of the friction force appears after the hold time and its amplitude increases with the hold duration. These observations are consistent with the frictional force encoded phenomenologically in the rate-and-state equations. Our model gives a microscopical basis for such macroscopic description.Comment: 10 figures, 7 pages, +4 pages of appendi

Definition study for photovoltaic residential prototype system

A site evaluation was performed to assess the relative merits of different regions of the country in terms of the suitability for experimental photovoltaic powered residences. Eight sites were selected based on evaluation criteria which included population, photovoltaic systems performance and the cost of electrical energy. A parametric sensitivity analysis was performed for four selected site locations. Analytical models were developed for four different power system implementation approaches. Using the model which represents a direct (or float) charge system implementation the performance sensitivity to the following parameter variations is reported: (1) solar roof slope angle; (2) ratio of the number of series cells in the solar array to the number of series cells in the lead-acid battery; and (3) battery size. For a Cleveland site location, a system with no on site energy storage and with a maximum power tracking inverter which feeds back excess power to the utility was shown to have 19 percent greater net system output than the second place system. The experiment test plan is described. The load control and data acquisition system and the data display panel for the residence are discussed

SE(3)-equivariant Graph Neural Networks for Learning Glassy Liquids Representations

Within the glassy liquids community, the use of Machine Learning (ML) to model particles' static structure in order to predict their future dynamics is currently a hot topic. The actual state of the art consists in Graph Neural Networks (GNNs) (Bapst 2020) which, beside having a great expressive power, are heavy models with numerous parameters and lack interpretability. Inspired by recent advances (Thomas 2018), we build a GNN that learns a robust representation of the glass' static structure by constraining it to preserve the roto-translation (SE(3)) equivariance. We show that this constraint not only significantly improves the predictive power but also allows to reduce the number of parameters while improving the interpretability. Furthermore, we relate our learned equivariant features to well-known invariant expert features, which are easily expressible with a single layer of our network.Comment: 8 pages, 7 figures plus appendi

Quantitative assessment of angiogenesis in murine antigen-induced arthritis by intravital fluorescence microscopy

Inhibition of angiogenesis might be a therapeutic approach to prevent joint destruction caused by the overgrowing synovial tissue during chronic joint inflammation. The aim of this study was to investigate angiogenesis in the knee joint of mice with antigen-induced arthritis (AIA) by means of intravital microscopy. In 14 mice (C57BL6/129Sv) intravital microscopic assessment was performed on day 8 after AIA induction in two groups (controls, AIA). Synovial tissue was investigated by intravital fluorescence microscopy using FITC-dextran (150 kD). Quantitative assessment of vessel density was performed according to the following categories: functional capillary density (FCD, vessels 10 mum) and FVD of vessels with angiogenic criteria (convoluted vessels, abrupt changes of diameter, vessels which are generated by sprouting and progressively pruned and remodelled). Microvessel count was performed using immunohistochemistry. There was no significant difference in FCD between the control group (337 +/- 9 cm/cm(2); mean +/-SEM) and the AIA group (359 +/- 13 cm/cm(2)). The density of vessels larger than 10 gm diameter was significantly increased in animals with AIA (135 +/- 10 vs. 61 +/- 5 cm/cm(2) in control). The density of blood vessels with angiogenic criteria was enhanced in arthritic animals (79 +/- 17 vs. 12 +/- 2 cm/cm(2) in control). There was a significant increase in the microvessel count in arthritic animals (297 +/- 25 vs. 133 +/- 16 mm(-2) in control). These findings demonstrate that angiogenesis in murine AIA can be assessed quantitatively using intravital microscopy. Further studies will address antiangiogenic strategies in AIA

The influence of the brittle-ductile transition zone on aftershock and foreshock occurrence

Aftershock occurrence is characterized by scaling behaviors with quite universal exponents. At the same time, deviations from universality have been proposed as a tool to discriminate aftershocks from foreshocks. Here we show that the change in rheological behavior of the crust, from velocity weakening to velocity strengthening, represents a viable mechanism to explain statistical features of both aftershocks and foreshocks. More precisely, we present a model of the seismic fault described as a velocity weakening elastic layer coupled to a velocity strengthening visco-elastic layer. We show that the statistical properties of aftershocks in instrumental catalogs are recovered at a quantitative level, quite independently of the value of model parameters. We also find that large earthquakes are often anticipated by a preparatory phase characterized by the occurrence of foreshocks. Their magnitude distribution is significantly flatter than the aftershock one, in agreement with recent results for forecasting tools based on foreshocks

Extension of an automatic building extraction technique to airborne laser scanner data containing damaged buildings

Airborne laser scanning systems generate 3-dimensional point clouds of high density and irregular spacing. These data consist of multiple returns coming from terrain, buildings, and vegetation. The major difficulty is the extraction of object categories, usually buildings. In the field of disaster management, the detection of building damages plays an important role. Therefore, the question arises, if damaged buildings can also be detected by a method developed for the automatic extraction of buildings. Another purpose of this study is to extend and test an automatic building detection method developed initially for first echo laser scanner data on data captured in first and last echo. In order to answer these two questions, two institutes share their data and knowledge: the Institute of Photogrammetry and Remote Sensing (IPF, Universität Karlsruhe (TH), Germany) and the MAP-PAGE team (INSA de Strasbourg, France). The used 3D LIDAR data was captured over an area containing undamaged and damaged buildings. The results achieved for every single processing step by applying the original and the extended algorithm to the data are presented, analysed and compared. It is pointed out which buildings can be extracted by which algorithm and why some buildings remain undetecte