Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography

We study the feasibility of data based machine learning applied to ultrasound tomography to estimate water-saturated porous material parameters. In this work, the data to train the neural networks is simulated by solving wave propagation in coupled poroviscoelastic-viscoelastic-acoustic media. As the forward model, we consider a high-order discontinuous Galerkin method while deep convolutional neural networks are used to solve the parameter estimation problem. In the numerical experiment, we estimate the material porosity and tortuosity while the remaining parameters which are of less interest are successfully marginalized in the neural networks-based inversion. Computational examples confirms the feasibility and accuracy of this approach

Cuticular Needle Erosion and Winter Drought in Polluted Environments - A Model Analysis

A method is developed for analyzing the consequences of pollutant-imposed cuticular erosion for the tolerance of winter drought in coniferous trees. The erosion rate of cuticular wax is modeled in terms of the contact angle of water droplets, as a function of sulphur dioxide, air temperature and relative humidity. Whole tree transpiration during drought is considered, assuming that the state of erosion affects the cuticular resistance of each needle age class. A formula is derived to compare transpiration with the water available in foliage and stem storage. The derivations are applied to a numerical example concerning the transpiration during a warm spell in the spring. Under certain assumptions, increased cuticular transpiration may well give rise to increased winter drought damage. However, many of the parameters and processes still need to be more thoroughly investigated. The most critical open question appears to be the quantitative relationship between cuticular resistance and the state of erosion of the cuticle

Ozone sensitivity of wild field layer plant species of northern Europe.

The increasing tropospheric ozone (O3) concentration constitutes a potential threat to nature. Plants are known to react to O3, but knowledge of the sensitivity and type of responses of different species and plant communities is widely lacking. This review focuses on the ecological effects of O3 on northern wild field layer plant species. Most of the 65 species examined thus far have proven to be quite tolerant of O3. Visible symptoms were observed in 54% of the 61 species studied, and growth reduction in 31% of the 55 species studied for growth. There were no signs to suggest that certain families or vegetation types are more sensitive or tolerant than others. There were, however, clear differences in sensitivity between the different species. It seems that forbs are usually more sensitive than grasses. It should be kept in mind, however, that we still lack knowledge on the responses of many common and abundant key species. The long-term effects are also far from clear. Hardly any field examinations have been carried out on the effects of O3 on plant communities

PRUNE: Dynamic and Decidable Dataflow for Signal Processing on Heterogeneous Platforms

The majority of contemporary mobile devices and personal computers are based on heterogeneous computing platforms that consist of a number of CPU cores and one or more Graphics Processing Units (GPUs). Despite the high volume of these devices, there are few existing programming frameworks that target full and simultaneous utilization of all CPU and GPU devices of the platform. This article presents a dataflow-flavored Model of Computation (MoC) that has been developed for deploying signal processing applications to heterogeneous platforms. The presented MoC is dynamic and allows describing applications with data dependent run-time behavior. On top of the MoC, formal design rules are presented that enable application descriptions to be simultaneously dynamic and decidable. Decidability guarantees compile-time application analyzability for deadlock freedom and bounded memory. The presented MoC and the design rules are realized in a novel Open Source programming environment "PRUNE" and demonstrated with representative application examples from the domains of image processing, computer vision and wireless communications. Experimental results show that the proposed approach outperforms the state-of-the-art in analyzability, flexibility and performance.Comment: This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publicatio

Geoeffectiveness and efficiency of CIR, Sheath and ICME in generation of magnetic storms

We investigate relative role of various types of solar wind streams in generation of magnetic storms. On the basis of the OMNI data of interplanetary measurements for the period of 1976-2000 we analyze 798 geomagnetic storms with Dst < -50 nT and their interplanetary sources: corotating interaction regions (CIR), interplanetary CME (ICME) including magnetic clouds (MC) and Ejecta and compression regions Sheath before both types of ICME. For various types of solar wind we study following relative characteristics: occurrence rate; mass, momentum, energy and magnetic fluxes; probability of generation of magnetic storm (geoeffectiveness) and efficiency of process of this generation. Obtained results show that despite magnetic clouds have lower occurrence rate and lower efficiency than CIR and Sheath they play an essential role in generation of magnetic storms due to higher geoeffectiveness of storm generation (i.e higher probability to contain large and long-term southward IMF Bz component).Comment: 23 pages, 4 figures, 3 tables, submitted to JGR special issue "Response of Geospace to High-Speed Streams