Semi-empirical methods for determining the efflux velocity from a ship's propeller

The present study proposed the semi-empirical methods for determining the efflux velocity from a ship's propeller. Ryan [1] defined the efflux velocity as the maximum velocity taken from a time-averaged velocity distribution along the initial propeller plane. The Laser Doppler Anemometry (LDA) and Computational Fluid Dynamics (CFD) were used to acquire the efflux velocity from the two propellers with different geometrical characteristics. The LDA and CFD results were compared in order to investigate the equation derived from the axial momentum theory. The study confirmed the validation of the axial momentum theory and its linear relationship between the efflux velocity and the multiplication of the rotational speed, propeller diameter and the square root of thrust coefficient. The linear relationship of these two terms is connected by an efflux coefficient and the value of this efflux coefficient reduced when the blade number increased.

A computational model of cellular response to modulated radiation fields

Purpose:
To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies.

Materials and Methods:
A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields.

Results:
The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses.

Conclusions:
The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.

The Characteristics of Wave Impacts on an Oscillating Wave Surge Converter

Wave impacts on an oscillating wave surge converter are examined using experimental and numerical methods. The mechanics of the impact event are identified experimentally with the use of images recorded with a high-speed camera. It is shown that it is the device that impacts the wave rather than a breaking wave impacting the device. Numerical simulations using two different approaches are used to further understand the issue. Good agreement is shown between numerical simulations and experimental measurements at 25th scale.

Development and validation of Fluid Structure Interaction Methods for an Oscillating Wave Surge Converter

The term fatigue loads on the Oyster Oscillating Wave Surge Converter (OWSC) is used to describe hydrostatic loads due to water surface elevation with quasi-static changes of state. Therefore a procedure to implement hydrostatic pressure distributions into finite element analysis of the structure is desired. Currently available experimental methods enable one to measure time variant water surface elevation at discrete locations either on or around the body of the scale model during tank tests. This paper discusses the development of a finite element analysis procedure to implement time variant, spatially distributed hydrostatic pressure derived from discretely measured water surface elevation. The developed method can process differently resolved (temporal and spatial) input data and approximate the elevation over the flap faces with user defined properties. The structural loads, namely the forces and moments on the body can then be investigated by post processing the numerical results. This method offers the possibility to process surface elevation or hydrostatic pressure data from computational fluid dynamics simulations and can thus be seen as a first step to a fluid-structure interaction model.

Two-dimensional images of dissolved sulfide and metals in anoxic sediments by a novel diffusive gradients in thin film probe and optical scanning techniques

A novel diffusive gradients in thin film probe developed comprises diffusive gel layer of silver iodide (AgI) and a back-up Microchelex resin gel layer. 2D high-resolution images of sulfide and trace metals were determined respectively on the AgI gel by densitometric analysis and on the Microchelex resin layer with laser-ablation-inductively-coupled plasma mass spectrometry (LA-ICP-MS).We investigated the validity of the analytical procedures used for the determination of sulfide and trace metals. We found low relative standard deviations on replicate measurements, linear trace-metal calibration curves between the LA-ICP-MS signal and the true trace-metal concentration in the resin gel, and a good agreement of the sulfide results obtained with the AgI resin gel and with other analytical methods. The method was applied on anoxic sediment pore waters in an estuarine and marine system. Simultaneous remobilization of sulfide and trace metals was observed in the marine sediment.

The Characteristics of Wave Impacts on an Oscillating Wave Surge Converter

Wave impacts on an Oscillating Wave Surge Converter are examined using experimental and numerical methods. The mechanics of the impact event are identified experimentally with the use of images recorded with a high speed camera. It is shown that it is the device which impacts the wave rather than a breaking wave impacting the device. Numerical simulations using two different approaches are used to further understand the issue. Good agreement is shown between numerical simulations and experimental measurements at 25th scale.

Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

Two-Stage Orthogonal Least Squares Methods for Neural Network Construction

A number of neural networks can be formulated as the linear-in-the-parameters models. Training such networks can be transformed to a model selection problem where a compact model is selected from all the candidates using subset selection algorithms. Forward selection methods are popular fast subset selection approaches. However, they may only produce suboptimal models and can be trapped into a local minimum. More recently, a two-stage fast recursive algorithm (TSFRA) combining forward selection and backward model refinement has been proposed to improve the compactness and generalization performance of the model. This paper proposes unified two-stage orthogonal least squares methods instead of the fast recursive-based methods. In contrast to the TSFRA, this paper derives a new simplified relationship between the forward and the backward stages to avoid repetitive computations using the inherent orthogonal properties of the least squares methods. Furthermore, a new term exchanging scheme for backward model refinement is introduced to reduce computational demand. Finally, given the error reduction ratio criterion, effective and efficient forward and backward subset selection procedures are proposed. Extensive examples are presented to demonstrate the improved model compactness constructed by the proposed technique in comparison with some popular methods.

Reflection of Qualitative Methods: “memoring” fieldwork experience in organisational research with photographs

The paper is a reflection on the use of photographs in multiple case study research. It explores the crossovers between interpreting visual artefacts, the qualitative approach to case study research in organisations, and the move from cases to theory guided by the grounded theory tenets. The paper proposes an additional use of photographs as a visual method to those in the literature, as a device for data analysis. Photograph-based analysis techniques are explored, using e sequence of individual images and photo collages on case data, moving from interpretation of single to multiple case themes. This makes the case of using photograph analysis as an interpretation device for case research to illuminate theory development.

Prediction of the solar radiation using RBF neural networks and ground-to-sky images

In this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.

Automatic processing of bidimensional images of ''omic'' expression blobs

In this work, a comprehensive review on automatic analysis of Proteomics and Genomics images is presented. Special emphasis is given to a particularly complex image produced by a technique called Two-Dimensional Gel Electrophoresis (2-DE), with thousands of spots (or blobs). Automatic methods for the detection, segmentation and matching of blob like features are discussed and proposed. In particular, a very robust procedure was achieved for processing 2-DE images, consisting mainly of two steps: a) A very trustworthy new approach for the automatic detection and segmentation of spots, based on the Watershed Transform, without any foreknowledge of spot shape or size, and without user intervention; b) A new method for spot matching, based on image registration, that performs well for either global or local distortions. The results of the proposed methods are compared to state-of-the-art academic and commercial products.

3D Reconstruction of Medical Images from Slices Automatically Landmarked with Growing Neural Models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

Snapshot gradient-recalled echo-planar images of rat brains at long echo time at 9.4 T.

With improved B 0 homogeneity along with satisfactory gradient performance at high magnetic fields, snapshot gradient-recalled echo-planar imaging (GRE-EPI) would perform at long echo times (TEs) on the order of T2*, which intrinsically allows obtaining strongly T2*-weighted images with embedded substantial anatomical details in ultrashort time. The aim of this study was to investigate the feasibility and quality of long TE snapshot GRE-EPI images of rat brain at 9.4 T. When compensating for B 0 inhomogeneities, especially second-order shim terms, a 200 x 200 microm2 in-plane resolution image was reproducibly obtained at long TE (>25 ms). The resulting coronal images at 30 ms had diminished geometric distortions and, thus, embedded substantial anatomical details. Concurrently with the very consistent stability, such GRE-EPI images should permit to resolve functional data not only with high specificity but also with substantial anatomical details, therefore allowing coregistration of the acquired functional data on the same image data set.

An analysis of students' travel motivations and images of China as a tourist destination

Despite China's rapid growth in inbound tourism, the nature of its Canadian tourist market has been insufficiently studied. In response to this need, the objectives of this study are to identify China's destination image in Canadian students' minds, their possible internal motivations for visiting China as well as examining demographic influences on people's destination image formation. The study reviews image formation process and travel motivation categorisation, discusses their relationship, and implements Baloglu and McCleary's (1999) perceptual and affective image formation model and "push and pull factors" theory as its framework. A self-administered survey was applied to 424 undergraduate students in a Canadian university in early 2004. Exploratory factor analyses were conducted to identify perceived images and travel motivation. Summated means were calculated to illustrate the affective attitudes. A series of f-test and ANOVA tests were employed to examine the influence of demographics. An open-ended question format was adopted to analyse other images, motivations and visitation barriers that students may have. Findings demonstrate that cultural and natural attractions are the predominant image which the Canadian students have of China'; some stereotypes and negative images still influence the students' perception; travel service quality is largely unknown; increasing knowledge and seeking excitement and fun are the significant motivators in the likelihood of the Canadian students choosing to visit China; and personal interests may be a factor that significantly influences an individual's destination image and travel motivation. Raising awareness and increasing familiarity through promotion are suggested as methods to create a positive destination image of China.

Application of Reptation Quantum Monte Carlo and Related Methods to LiH

This work investigates mathematical details and computational aspects of Metropolis-Hastings reptation quantum Monte Carlo and its variants, in addition to the Bounce method and its variants. The issues that concern us include the sensitivity of these algorithms' target densities to the position of the trial electron density along the reptile, time-reversal symmetry of the propagators, and the length of the reptile. We calculate the ground-state energy and one-electron properties of LiH at its equilibrium geometry for all these algorithms. The importance sampling is performed with a single-determinant large Slater-type orbitals (STO) basis set. The computer codes were written to exploit the efficiencies engineered into modern, high-performance computing software. Using the Bounce method in the calculation of non-energy-related properties, those represented by operators that do not commute with the Hamiltonian, is a novel work. We found that the unmodified Bounce gives good ground state energy and very good one-electron properties. We attribute this to its favourable time-reversal symmetry in its target density's Green's functions. Breaking this symmetry gives poorer results. Use of a short reptile in the Bounce method does not alter the quality of the results. This suggests that in future applications one can use a shorter reptile to cut down the computational time dramatically.