Aspects of the washout of salmonid eggs. 1. Observations on the physical characteristics of real and artificial eggs, their rate of fall in a water column and their pattern of settlement in an experimental channel

When salmonid redds are disrupted by spates, the displaced eggs will drift downstream. The mean distance of travel, the types of locations in which the eggs resettle and the depth of reburial of displaced eggs are not known. Investigation of these topics under field conditions presents considerable practical problems, though the use of artificial eggs might help to overcome some of them. Attempts to assess the similarities and/or differences in performance between real and artificial eggs are essential before artificial eggs can validly be used to simulate real eggs. The present report first compares the two types of egg in terms of their measurable physical characteristics (e.g. dimensions and density). The rate at which eggs fall in still water will relate to the rate at which they are likely to resettle in flowing water in the field. As the rate of fall will be influenced by a number of additional factors (e.g. shape and surface texture) which are not easily measured directly, the rates of fall of the two types of egg have been compared directly under controlled conditions. Finally, comparisons of the pattern of settlement of the two types of egg in flowing water in an experimental channel have been made. Although the work was primarily aimed at testing the value of artificial eggs as a simulation of real eggs, several side issues more directly concerned with the properties of real eggs and the likely distance of drift in natural streams have also been explored. This is the first of three reports made on this topic by the author in 1984.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Marine biology of the Sierra Leone River Estuary. 1. The physical environment

The Sierra Leone River Estuary is a relatively young drowned river valley, it is shallow except for a deep channel which passes close to the Freetown shoreline. The upper reaches merge into a network of creeks and channels fringed by large areas of mangrove swamps. It is a tidal estuary of the semi-mixed type with the saline oceanic water entering it on a diurnal cycle. The climate of Sierra Leone is marked by a very distinct change between a very wet rainy season and a dry season. The tidal range of the Estuary (spring 3.03m; neap 2.28m) does not impede normal use of the harbour. The tidal variations can be felt as far as 42 miles inland along the water courses of the Sierra Leone River and its tributaries. The volume of fresh water entering the Estuary is large during the rainy season and greatly reduced during the dry season. Consequently there is a marked fall in salinity during the rainy season and higher salinities due to the marine influence prevailing during the dry season. The nature of the shores and bottom, the hydrography and chemistry of the estuarine system have been outlined in relation to the prevailing climatic conditions.

Simulation of growth process of thin film on non-planar substrate

In (2 + 1) dimension, growth process of thin film on non-planar substrate in Kuramoto-Sivashinsky model is studied with numerical simulation approach. 15 x 15 semi-ellipsoids arranged orderly on the surface of substrate are used to represent initial rough surface. The results show that at the initial stage of growth process, the surface morphology of thin film appears to be grid-structure, and the interface width constantly decreases with the growth time, then reaches minimum. However, the grid-structure becomes ambiguous, and granules of different sizes distribute evenly on the surface of thin film with the increase of growth time. Thereafter, the average size of granules and the interface width gradually increase, and the surface morphology of thin film presents fractal properties. The numerical results of height-height correlation functions of thin film verify the surface morphology of thin film to be fractal for a longer growth time. By fitting of the height-height correlation functions of thin film with different growth times, the growth process is described quantitatively. (c) 2004 Elsevier B.V. All rights reserved.

Influência do comportamento semi-rígido de placas de base e de ligações viga-coluna na resposta dinâmica de pórticos de aço.

Tradicionalmente, na análise e dimensionamento de estruturas de aço, assume-se que as ligações viga-coluna são rígidas ou flexíveis (rotuladas). Por outro lado, é de conhecimento geral que a grande maioria das ligações viga-coluna apresenta um comportamento intermediário, ou seja, semi-rígido. Inúmeros trabalhos de pesquisa têm sido desenvolvidos nos últimos vinte e cinco anos, de forma a estudar o comportamento desse tipo de ligação. Um dos principais objetivos desta investigação é o de propor uma metodologia de análise que represente de forma apropriada a influência do comportamento semi-rígido de placas de base e de ligações viga-coluna, sobre a resposta dinâmica (linear e não-linear) de estruturas de aço. Outra contribuição desta dissertação diz respeito à investigação do comportamento dinâmico (linear e não-linear) de pórticos de aço, a partir da consideração de ligações viga-coluna simétricas e não-simétricas e especialmente das placas de base. A análise estrutural é desenvolvida com base no emprego do programa de elementos finitos ANSYS [27]. Nos modelos em elementos finitos foram considerados os efeitos de não-linearidade geométrica (efeitos de segunda ordem), o comportamento não-linear das placas de base e das ligações viga-coluna e, bem como, o efeito de histerese que ocorre quando a estrutura é submetida a cargas cíclicas. Os resultados alcançados indicaram que o fenômeno físico da ressonância não ocorre no que se refere à resposta dinâmica dos modelos semi-rígidos não-lineares. A ressonância não ocorre na resposta dos modelos devido ao fato de que, na análise dinâmica não-linear, o efeito de histerese presente nas ligações (placas de base e viga-coluna), essencialmente com comportamento não-linear, provoca um amortecimento na resposta dinâmica da estrutura.

Digital Quantum Simulation of Spin Models with Circuit Quantum Electrodynamics

Systems of interacting quantum spins show a rich spectrum of quantum phases and display interesting many-body dynamics. Computing characteristics of even small systems on conventional computers poses significant challenges. A quantum simulator has the potential to outperform standard computers in calculating the evolution of complex quantum systems. Here, we perform a digital quantum simulation of the paradigmatic Heisenberg and Ising interacting spin models using a two transmon-qubit circuit quantum electrodynamics setup. We make use of the exchange interaction naturally present in the simulator to construct a digital decomposition of the model-specific evolution and extract its full dynamics. This approach is universal and efficient, employing only resources that are polynomial in the number of spins, and indicates a path towards the controlled simulation of general spin dynamics in superconducting qubit platforms.

Elementos finitos em fluidos dominados pelo fenômeno de advecção: um método semi-Lagrangeano.

Os escoamentos altamente convectivos representam um desafio na simulação pelo método de elementos finitos. Com a solução de elementos finitos de Galerkin para escoamentos incompressíveis, a matriz associada ao termo convectivo é não simétrica, e portanto, a propiedade de aproximação ótima é perdida. Na prática as soluções apresentam oscilações espúrias. Muitos métodos foram desenvolvidos com o fim de resolver esse problema. Neste trabalho apresentamos um método semi- Lagrangeano, o qual é implicitamente um método do tipo upwind, que portanto resolve o problema anterior, e comparamos o desempenho do método na solução das equações de convecção-difusão e Navier-Stokes incompressível com o Streamline Upwind Petrov Galerkin (SUPG), um método estabilizador de reconhecido desempenho. No SUPG, as funções de forma e de teste são tomadas em espaços diferentes, criando um efeito tal que as oscilações espúrias são drasticamente atenuadas. O método semi-Lagrangeano é um método de fator de integração, no qual o fator é um operador de convecção que se desloca para um sistema de coordenadas móveis no fluido, mas restabelece o sistema de coordenadas Lagrangeanas depois de cada passo de tempo. Isto prevê estabilidade e a possibilidade de utilizar passos de tempo maiores.Existem muitos trabalhos na literatura analisando métodos estabilizadores, mas não assim com o método semi-Lagrangeano, o que representa a contribuição principal deste trabalho: reconhecer as virtudes e as fraquezas do método semi-Lagrangeano em escoamentos dominados pelo fenômeno de convecção.

Semi-intensive shrimp farming system of Kerala, India: a production function analysis

An analysis of the factor-product relationship in the semi-intensive shrimp farming system of Kerala, farm basis and hectare basis, we are attempted and the results reported in this paper. The Cobb-Douglas model, in which the physical relationship between input and output is estimated, and the marginal analysis then employed to evaluate the producer behaviour, was used for the analysis. The study was based on empirical data collected during November 1994 to May 1996, covering three seasons, from 21 farms spread over Alappuzha, Ernakulam and Kasaragod districts of the state. The sample covered a total area of 61.06 ha. Of the 11 explanatory variables considered in the model, the size of the farm, casual labour and chemical fertilizers were found statistically significant. It was also observed that the factors such as age of pond, experience of the farmer, feed, miscellaneous costs, number of seed stocked and skilled labour contributed positively to the output. The estimated industry production function exhibited unitary economies of scale. The estimated mean output was 3937 kg/ha. The test of multi-co-linearity showed that there is no problem of dominant variable. On the basis of the marginal product and the given input-output prices, the optimum amounts of seed, feed and casual labour were estimated. They were about 97139 seed, 959 kg of feed and 585 man-days of casual labour per farm. This indicated the need for reducing the stocking density and amount of feed from the present levels, in order to maximise profit. Based on the finding of the study, suggestions for improving the industry production function are proposed.

On computing the physical sources of jet noise

We derive a closed system of equations that relates the acoustically radiating flow variables to the sources of sound for homentropic flows. We use radiating density, momentum density and modified pressure as the dependent variables which leads to simple source terms for the momentum equations. The source terms involve the non-radiating parts of the density and momentum density fields. These non-radiating components are obtained by removing the radiating wavenumbers in the Fourier domain. We demonstrate the usefulness of this new technique on an axi-symmetric jet solution of the Navier-Stokes equations, obtained by direct numerical simulation (DNS). The dominant source term is proportional to the square of the non-radiating part of the axial momentum density. We compare the sound sources to that obtained by an acoustic analogy and find that they have more realistic physical properties. Their frequency content and amplitudes are consistent with. We validate the sources by computing the radiating sound field and comparing it to the DNS solution. © 2010 by S. Sinayoko, A. Agarwal.