Ultrafast molecular dynamics of model biological systems

Femtosecond time resolved photoelectron imaging spectroscopy equipment was designed, constructed, and used to reveal the non-adiabatic dynamics of model biological systems. Indole and phenol derivatives were studied as models for eumelanin, a pigment found in humans designed to protect the body from ultraviolet radiation. The photo-dynamics of these molecules was studied after excitation with ultraviolet radiation, with particular emphasis on the effect that the hydroxyl groups have on the p * dissociative state. It was found that adding a hydroxyl group onto indole to create 5-hydroxyindole had little significant effect on the photodynamics at the excitation wavelengths studied. Adding a second hydroxyl group to phenol had a strongly marked effect only when the hydroxyl groups were in close proximity to each other, in which case it dramatically increased the relaxation rate. An ultrafast optical system, imaging photoelectron spectrometer, and software to control the hardware, and collect and analyse photoelectron data were successfully implemented and used to collect and analyse data. This system will be of use for many more years and will be the basis of much future research.Engineering and Physical Sciences Research Council (EPSRC

Advanced optical microscopy toolkits for non-invasive imaging in oncology

Thesis: Ph. D. in Medical Engineering and Medical Physics, Harvard-MIT Program in Health Sciences and Technology, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 245-271).Despite significant advances in the fields of biophotonics and oncology alike, several challenges persist in the study, assessment, and treatment of cancer, ranging from the accurate identification and examination of potential risk factors, early diagnosis of dysplastic lesions, and monitoring of the complex heterogeneity of cellular populations within tumors. To study such dynamics at the microscale, non-invasive optical toolkits offer the potential to identify, characterize, and visualize key molecules and their interactions in their native biological context, ranging from in vitro cell cultures to in vivo studies in both animal models and humans. In the present thesis, examples of such applications of optical tools will be presented, including: (1) the assessment of cellular oxidative stress in ex vivo human skin cultures by imaging endogenous and exogenous fluorescent compounds using two-photon excitation fluorescence (TPEF) and fluorescence lifetime imaging microscopy (FLIM); (2) visualizing water and lipid distribution as well as cellular morphology using coherent Raman scattering (CRS) imaging techniques in the stratum corneum, the most superficial layer of the epidermis; (3) using photoconvertible labels to optically tag cell sub-populations of interest in situ for long-term monitoring of heterogeneous cell cultures from in vitro monolayers to in vivo xenograft models; (4) visualizing melanin species in the context of melanoma with coherent anti-Stokes Raman scattering (CARS) and sum-frequency absorption (SFA) microscopies. Altogether, development of such advanced microscopy toolkits will serve to improve both understanding of cancer pathology, as well as to validate clinical diagnostic and therapeutic strategies.by Sam Osseiran.Ph. D. in Medical Engineering and Medical Physic

New Directions for Contact Integrators

Contact integrators are a family of geometric numerical schemes which guarantee the conservation of the contact structure. In this work we review the construction of both the variational and Hamiltonian versions of these methods. We illustrate some of the advantages of geometric integration in the dissipative setting by focusing on models inspired by recent studies in celestial mechanics and cosmology.Comment: To appear as Chapter 24 in GSI 2021, Springer LNCS 1282

Digital Signal Processing (Second Edition)

This book provides an account of the mathematical background, computational methods and software engineering associated with digital signal processing. The aim has been to provide the reader with the mathematical methods required for signal analysis which are then used to develop models and algorithms for processing digital signals and finally to encourage the reader to design software solutions for Digital Signal Processing (DSP). In this way, the reader is invited to develop a small DSP library that can then be expanded further with a focus on his/her research interests and applications. There are of course many excellent books and software systems available on this subject area. However, in many of these publications, the relationship between the mathematical methods associated with signal analysis and the software available for processing data is not always clear. Either the publications concentrate on mathematical aspects that are not focused on practical programming solutions or elaborate on the software development of solutions in terms of working ‘black-boxes’ without covering the mathematical background and analysis associated with the design of these software solutions. Thus, this book has been written with the aim of giving the reader a technical overview of the mathematics and software associated with the ‘art’ of developing numerical algorithms and designing software solutions for DSP, all of which is built on firm mathematical foundations. For this reason, the work is, by necessity, rather lengthy and covers a wide range of subjects compounded in four principal parts. Part I provides the mathematical background for the analysis of signals, Part II considers the computational techniques (principally those associated with linear algebra and the linear eigenvalue problem) required for array processing and associated analysis (error analysis for example). Part III introduces the reader to the essential elements of software engineering using the C programming language, tailored to those features that are used for developing C functions or modules for building a DSP library. The material associated with parts I, II and III is then used to build up a DSP system by defining a number of ‘problems’ and then addressing the solutions in terms of presenting an appropriate mathematical model, undertaking the necessary analysis, developing an appropriate algorithm and then coding the solution in C. This material forms the basis for part IV of this work. In most chapters, a series of tutorial problems is given for the reader to attempt with answers provided in Appendix A. These problems include theoretical, computational and programming exercises. Part II of this work is relatively long and arguably contains too much material on the computational methods for linear algebra. However, this material and the complementary material on vector and matrix norms forms the computational basis for many methods of digital signal processing. Moreover, this important and widely researched subject area forms the foundations, not only of digital signal processing and control engineering for example, but also of numerical analysis in general. The material presented in this book is based on the lecture notes and supplementary material developed by the author for an advanced Masters course ‘Digital Signal Processing’ which was first established at Cranfield University, Bedford in 1990 and modified when the author moved to De Montfort University, Leicester in 1994. The programmes are still operating at these universities and the material has been used by some 700++ graduates since its establishment and development in the early 1990s. The material was enhanced and developed further when the author moved to the Department of Electronic and Electrical Engineering at Loughborough University in 2003 and now forms part of the Department’s post-graduate programmes in Communication Systems Engineering. The original Masters programme included a taught component covering a period of six months based on two semesters, each Semester being composed of four modules. The material in this work covers the first Semester and its four parts reflect the four modules delivered. The material delivered in the second Semester is published as a companion volume to this work entitled Digital Image Processing, Horwood Publishing, 2005 which covers the mathematical modelling of imaging systems and the techniques that have been developed to process and analyse the data such systems provide. Since the publication of the first edition of this work in 2003, a number of minor changes and some additions have been made. The material on programming and software engineering in Chapters 11 and 12 has been extended. This includes some additions and further solved and supplementary questions which are included throughout the text. Nevertheless, it is worth pointing out, that while every effort has been made by the author and publisher to provide a work that is error free, it is inevitable that typing errors and various ‘bugs’ will occur. If so, and in particular, if the reader starts to suffer from a lack of comprehension over certain aspects of the material (due to errors or otherwise) then he/she should not assume that there is something wrong with themselves, but with the author