Emotional intelligence development in student radiation therapists: A longitudinal pilot study

Emotional intelligence (EI) is defined as “the ability to recognise, understand and manage emotions in ourselves and others”. Initially identified as a concept applied to leadership and management, EI is now recognised as an important skill in a number of areas, including healthcare [2]. Empathy (the ability to see the world through someone else’s eyes) is known to play an important role in the therapeutic relationship with patients [3]. As EI has been shown to improve empathy [4], it is clear that developing the EI of student health professionals should benefit patients in the long term. It is not surprising, then, that a number of studies have investigated the role of EI in medical, dental and nursing students, however there is little reported evidence relating to EI development in pre-registration radiation therapy (RT) students.

Uncanny nature: Hybrid stop motion using Blender

This talk gives an overview of the project "Uncanny Nature", which incoporates a style of animation called Hybrid Stop Motion, that combines physical object armatures with virtual copies. The development of the production pipeline (using a mix of Blender, Dragonframe, Photoscan and Arduino) is discussed, as well as the way that Blender was used throughout the production to visualise, model, animate and composite the elements together.

A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

Study of thermal fluctuations during thermal denaturation of DNA

In this paper we address the fundamental issue of temperature fluctuation during the thermal denaturation (or the unzipping of the two strands on heating) of double stranded (ds) DNA. From our experiments we observe the presence of extremely high thermal fluctuations during DNA denaturation. This thermal fluctuation is several orders higher than the thermal fluctuation at temperatures away from the denaturation temperature range. This fluctuation is absent in single stranded (ss) DNA. The magnitude of fluctuation is much higher in heteropolymeric DNA and is almost absent in short homopolymeric DNA fragments. The temperature range over which the denaturation occurs (i.e., over which the thermal fluctuation is large) depends on the length of the DNA and is largest for the longest DNA.

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.

A new FIR filter for image restoration

Image filtering techniques have potential applications in biomedical image processing such as image restoration and image enhancement. The potential of traditional filters largely depends on the apriori knowledge about the type of noise corrupting the image. This makes the standard filters to be application specific. For example, the well-known median filter and its variants can remove the salt-and-pepper (or impulse) noise at low noise levels. Each of these methods has its own advantages and disadvantages. In this paper, we have introduced a new finite impulse response (FIR) filter for image restoration where, the filter undergoes a learning procedure. The filter coefficients are adaptively updated based on correlated Hebbian learning. This algorithm exploits the inter pixel correlation in the form of Hebbian learning and hence performs optimal smoothening of the noisy images. The application of the proposed filter on images corrupted with Gaussian noise, results in restorations which are better in quality compared to those restored by average and Wiener filters. The restored image is found to be visually appealing and artifact-free

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.

Diffusion Studies in A(3)B Compounds with A15 Structure

There is a constant effort to understand the defect structure and diffusion behavior in intermetallic compounds with the A15 structure. Diffusion of elements in intermetallic compounds depends mainly on antisites and vacancies on different sublattices. In this article, we shall discuss the diffusion of elements in A(3)B compounds with the A15 structure.

Interdiffusion Studies in the Co- Mo System

Study of interdiffusion in the Co-Mo system is important to understand the performance of turbine blades in jet engine applications. Mo is added to superalloys to increase the solid solution strengthening and the creep resistance. In this study, the interdiffusion coefficient in the Co(Mo) solid solution and impurity diffusion coefficient of Mo in Co are determined. Further, the activation energy and pre-exponential factors are calculated, which provide an idea about the atomic mechanism of diffusion.

Study on the Growth of Nb3Sn Superconductor in Cu(Sn)/Nb Diffusion Couple

Nb3Sn growth following the bronze technique, (i.e. by interdiffusion between Cu(Sn) alloy (bronze) and Nb) is one of the important methodologies to produce this superconductor. In this study, we have addressed the confusion over the growth rate of the Nb3Sn phase. Furthermore, a possible explanation for the corrugated layer in the multifilamentary structure is discussed. Kirkendall marker experiments were conducted to study the relative mobilities of the species, which also explained the reason for finding pores in the product phase layer. Based on the parabolic growth constant at different temperatures, the activation energy for the growth is determined. We have further explained the dramatic increase in the growth rate of the prod

Three Dimensional Line-Clipping by Systematic Enumeration

Three dimensional clipping is a critical component of the 3D graphics pipeline. A new 3D clipping algorithm is presented in this paper. An efficient 2D clipping routine reported earlier has been used as a submodule. This algorithm uses a new classification scheme for lines of all possible orientations with respect to a rectangular parallelopiped view volume. The performance of this algorithm has been evaluated using exact arithmetic operation counts. It is shown that our algorithm requires less arithmetic operations than the Cyrus-Beck 3D clipping algorithm in all cases. It is also shown that for lines that intersect the clipping volume, our algorithm performs better than the Liang-Barsky 3D clipping algorithm.

An ultra-stable Cu nanowire under thermo-mechanical loading: A molecular dynamic study

We report on the formation of a stable Body-Centered Heptahedral (BCH) crystalline nanobridge structure of diameter ~ 1nm under high strain rate tensile loading to a <100> Cu nanowire. Extensive Molecular Dynamics (MD) simulations are performed. Six different cross-sectional dimensions of Cu nanowires are analyzed, i.e. 0.3615 x 0.3615 nm2, 0.723 x 0.723 nm2, 1.0845 x 1.0845 nm2, 1.446 x 1.446 nm2, 1.8075 x 1.8075 nm2, and 2.169 x 2.169 nm2. The strain rates used in the present simulations are 1 x 109 s-1, 1 x 108 s-1, and 1 x 107 s-1. We have shown that the length of the nanobridge can be characterized by larger plastic strain. A large plastic deformation is an indication that the structure is highly stable. The BCH nanobridge structure also shows enhanced mechanical properties such as higher fracture toughness and higher failure strain. The effect of temperature, strain rate and size of the nanowire on the formation of BCH structure is also explained in details. We also show that the initial orientation of the nanowires play an important role on the formation of BCH crystalline structure. Results indicate that proper tailoring of temperature and strain rate during processing or in the device can lead to very long BCH nanobridge structure of Cu with enhanced mechanical properties, which may find potential application for nano-scale electronic circuits.