Accretion through the inner edges of protoplanetary disks by a giant solid state pump

At the inner edge of a protoplanetary disk solids are illuminated by stellar light. This illumination heats the solids and creates temperature gradients along their surfaces. Interactions with ambient gas molecules lead to a radial net gas flow. Every illuminated solid particle within the edge is an individual small gas pump transporting gas inward. In total the inner edge can provide local mass flow rates as high as $\dot{M} = 10^{-5} M_{\odot}$ yr$^{-1}$

Universality of (2+1)-dimensional restricted solid-on-solid models

Extensive dynamical simulations of Restricted Solid on Solid models in $D=2+1$ dimensions have been done using parallel multisurface algorithms implemented on graphics cards. Numerical evidence is presented that these models exhibit KPZ surface growth scaling, irrespective of the step heights $N$. We show that by increasing $N$ the corrections to scaling increase, thus smaller step-sized models describe better the asymptotic, long-wave-scaling behavior

Bit-Vectorized GPU Implementation of a Stochastic Cellular Automaton Model for Surface Growth

Stochastic surface growth models aid in studying properties of universality classes like the Kardar--Paris--Zhang class. High precision results obtained from large scale computational studies can be transferred to many physical systems. Many properties, such as roughening and some two-time functions can be studied using stochastic cellular automaton (SCA) variants of stochastic models. Here we present a highly efficient SCA implementation of a surface growth model capable of simulating billions of lattice sites on a single GPU. We also provide insight into cases requiring arbitrary random probabilities which are not accessible through bit-vectorization.Comment: INES 2016, Budapest http://www.ines-conf.org/ines-conf/2016index.htm

Experimental Investigation of a High-lift Low-drag Aerofoil. Report no. 6802

One of a series of low-drag aerofoils (1) Designated GU 25-5(11) 8 was selected for low speed wind tunnel testing at Reynolds numbers around half a million. Coefficients of lift, drag and pitching moment were obtained for a range of incidence. The maximum section lift coefficient obtained was 1.93 and the minimum profile drag coefficient was 0.0112. Results compared favourably with those deduced theoretically. The addition of a boundary layer trip to the upper surface caused the profile drag to decrease at some incidences. At the design lift coefficient of 1.4, the ratio of lift to profile drag was 108 at a Reynolds number of 0.63 million. The addition of an extended, sealed, flat-plate flap (with a chord one tenth that of the aerofoil) at the trailing edge of the aerofoil gave favourable results. A maximum ratio of lift to profile drag of 116 was obtained at a lift coefficient of 1.8 with a flap deflection of 17.8 degrees, while the maximum lift coefficient achieved was 2.30

Experimental Investigation of a High-lift Low-drag Aerofoil. Report no. 6802

One of a series of low-drag aerofoils (1) Designated GU 25-5(11) 8 was selected for low speed wind tunnel testing at Reynolds numbers around half a million. Coefficients of lift, drag and pitching moment were obtained for a range of incidence. The maximum section lift coefficient obtained was 1.93 and the minimum profile drag coefficient was 0.0112. Results compared favourably with those deduced theoretically. The addition of a boundary layer trip to the upper surface caused the profile drag to decrease at some incidences. At the design lift coefficient of 1.4, the ratio of lift to profile drag was 108 at a Reynolds number of 0.63 million. The addition of an extended, sealed, flat-plate flap (with a chord one tenth that of the aerofoil) at the trailing edge of the aerofoil gave favourable results. A maximum ratio of lift to profile drag of 116 was obtained at a lift coefficient of 1.8 with a flap deflection of 17.8 degrees, while the maximum lift coefficient achieved was 2.30

Knowledge is Power? A market orientation approach to the global value chain analysis of aquaculture: Two cases linking Southeast Asia and the EU

This thesis adds the market orientation approach to a global value chain analysis of four farmed seafood value chains from two Asian countries to the EU. The overall aim of the research is to critically evaluate whether, and to what extent, access to market information is the key to unlocking the potential of developing countries to create greater value: whether knowledge is power. The objectives of the thesis are therefore to explore the process of generating market information in seafood value chains from Asia to the EU; understand under what conditions market information is, is not or is only partially disseminated; and, evaluate the role of market information in responses by chain agents that create value. In order to achieve these objectives, fieldwork was conducted along the length of shrimp (Penaeus monodon) and prawn (Macrobrachium rosenbergii) from Bangladesh, and shrimp (Penaeus vannamei) and tilapia (Oreochromis niloticus) from Thailand to the EU. The EU is the world’s largest single market for imported fish and fishery products. France, Germany and the UK were selected for fieldwork as they are primary importers of the species from the selected countries. The research found that although increased knowledge is necessary, it is not a sufficient condition for increased value creation. Instead, the research advances existing understanding of seafood value chains by revealing that successful integration of developing country producers into global markets is partly dependent on governance and industry development in the exporting country. Weaknesses in these structures and relationships undermine supplier power by reducing access to market information, lessening incentives for sharing information, and restricting response capabilities. A number of methods for overcoming these constraints were found in the chains examined, focusing on direct links between market and value chain agents. Importantly, the research found that integration is also dependent on the willingness of those with a market presence in importing countries to share knowledge and power. Critically, the research has led to the conclusion that the possession of market information is one way for value chain agents, particularly those downstream, to guard knowledge and power for themselves. A better understanding of seafood markets and an improved analysis of aquaculture value chains from Asian countries to the EU revealed through the research will facilitate public and private responses that focus on the competitive advantage of the whole chain as a means to more sustainable development. This may well promote new chain configurations that place a premium on stronger and more collaborative linkages, increasing coordination between weak and strong suppliers and contribute to private sector development assistance. Only when knowledge is shared and suppliers gain power, will the market orientation of seafood value chains be improved, if not optimised

Robust sound event detection in bioacoustic sensor networks

Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record sounds of wildlife over long periods of time in scalable and minimally invasive ways. Deriving per-species abundance estimates from these sensors requires detection, classification, and quantification of animal vocalizations as individual acoustic events. Yet, variability in ambient noise, both over time and across sensors, hinders the reliability of current automated systems for sound event detection (SED), such as convolutional neural networks (CNN) in the time-frequency domain. In this article, we develop, benchmark, and combine several machine listening techniques to improve the generalizability of SED models across heterogeneous acoustic environments. As a case study, we consider the problem of detecting avian flight calls from a ten-hour recording of nocturnal bird migration, recorded by a network of six ARUs in the presence of heterogeneous background noise. Starting from a CNN yielding state-of-the-art accuracy on this task, we introduce two noise adaptation techniques, respectively integrating short-term (60 milliseconds) and long-term (30 minutes) context. First, we apply per-channel energy normalization (PCEN) in the time-frequency domain, which applies short-term automatic gain control to every subband in the mel-frequency spectrogram. Secondly, we replace the last dense layer in the network by a context-adaptive neural network (CA-NN) layer. Combining them yields state-of-the-art results that are unmatched by artificial data augmentation alone. We release a pre-trained version of our best performing system under the name of BirdVoxDetect, a ready-to-use detector of avian flight calls in field recordings.Comment: 32 pages, in English. Submitted to PLOS ONE journal in February 2019; revised August 2019; published October 201