An appraisal and developments of laser holography for interferometric engineering measurement

Holography is a two-stage method of imagery in which both amplitude and phase information characterizing a wavefront are recorded, and subsequently reconstructed. Only with the advent of laser light sources in the early 1960s did the method become practical, motivating research into applications. One of these, holographic interferometry, was based on the fact that a reconstructed wavefront from a hologram could be used as a reference for interferometric comparison. This enabled interferometry to be extended to objects having scattering surfaces of any shape, and the potential of the method in engineering measurement was considered to be high. A literature survey carried out at the start of this project (1967 to 1968), and reported in Chapter 2, revealed that many potential applications in the fields of stress analysis, vibration analysis, fault detection in materials and structures, and dimensional inspection, had been proposed but were not quickly materializing. This was seen to be partly due to practical difficulties necessitating laboratory procedures, and partly due to difficulties in analysing interferograms to obtain specific measurements. Accordingly, the aims of this project were: (i) to develop apparatus and methods that would simplify and improve the practice of holographic interferometry and the interpretation of results; (ii) to investigate fringe interpretation, and to assess the accuracy and general feasibility, in relation to practical measurements of surface deformation. [Continues.

In Defence of Magical Ersatzism

David Lewis' objection to a generic theory of modality which he calls ‘magical ersatzism’ is that its linchpin, a relation he calls ‘selection’, must be either an internal or an external relation, and that this is unintelligible either way. But the problem he points out with classifying selection as internal is really just an instance of the general problem of how we manage to grasp underdetermined predicates, is not peculiar to magical ersatzism, and is amenable to some familiar solutions. He provides no compelling grounds for thinking that classifying selection as external is unintelligible, and his argument has a false presupposition. I conclude that magical ersatzism is still a viable option in the metaphysics of modalit

Neuropsychiatric Outcomes in UK Military Veterans with Mild Traumatic Brain Injury and Vestibular Dysfunction

Objective: To estimate the frequency of vestibular dysfunction following blunt, blast, and blunt & blast mild traumatic brain injury (mTBI) and thereon assess the long-term impact of vestibular dysfunction on neurobehavioral function and disability independently of co-morbid psychiatric symptoms. Setting: Combat Stress residential and Veterans’ Outreach drop-in centres for psychological support. Participants: 162 help-seeking UK military veterans. Main measures: Self-reported frequency and severity of mTBI (using the Ohio State Identification Method), Vertigo Symptom Scale, PTSD checklist for DSM5, Kessler Psychological Distress Scale, Neurobehavioral Symptom Inventory, HIT6, Memory Complaints Inventory, WHO Disability Assessment Scale 2.0. Results: 72% of the sample reported one or more mTBI over their lifetime. Chi-square analyses indicated that vestibular disturbance, which affected 69% of participants, was equally prevalent following blunt (59%) or blast (47%) injury and most prevalent following blunt and blast combined (83%). Mediation analysis indicated that when PTSD, depression and anxiety were taken into account, vestibular dysfunction in participants with mTBI was directly and independently associated with increased postconcussive symptoms and functional disability. Conclusion: Vestibular dysfunction is common after combined blunt and blast mTBI and singularly predictive of poor long-term mental health. From a treatment perspective, vestibular rehabilitation may provide relief from postconcussive symptoms other than dizziness and imbalance

Nonparametric Bayesian inference for perturbed and orthologous gene regulatory networks

Motivation: The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs). Most methods for reverse engineering GRNs from multiple datasets assume that each of the time series were generated from networks with identical topology. In this study, we outline a hierarchical, non-parametric Bayesian approach for reverse engineering GRNs using multiple time series that can be applied in a number of novel situations including: (i) where different, but overlapping sets of transcription factors are expected to bind in the different experimental conditions; that is, where switching events could potentially arise under the different treatments and (ii) for inference in evolutionary related species in which orthologous GRNs exist. More generally, the method can be used to identify context-specific regulation by leveraging time series gene expression data alongside methods that can identify putative lists of transcription factors or transcription factor targets. Results: The hierarchical inference outperforms related (but non-hierarchical) approaches when the networks used to generate the data were identical, and performs comparably even when the networks used to generate data were independent. The method was subsequently used alongside yeast one hybrid and microarray time series data to infer potential transcriptional switches in Arabidopsis thaliana response to stress. The results confirm previous biological studies and allow for additional insights into gene regulation under various abiotic stresses. Availability: The methods outlined in this article have been implemented in Matlab and are available on request

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation

Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence

Improving and accelerating the differentiation and functional maturation of human stem cell-derived neurons: role of extracellular calcium and GABA

Neurons differentiated from pluripotent stem cells using established neural culture conditions often exhibit functional deficits. Recently, we have developed enhanced media which both synchronize the neurogenesis of pluripotent stem cell-derived neural progenitors and accelerate their functional maturation; together these media are termed SynaptoJuice. This pair of media are pro-synaptogenic and generate authentic, mature synaptic networks of connected forebrain neurons from a variety of induced pluripotent and embryonic stem cell lines. Such enhanced rate and extent of synchronized maturation of pluripotent stem cell-derived neural progenitor cells generates neurons which are characterized by a relatively hyperpolarized resting membrane potential, higher spontaneous and induced action potential activity, enhanced synaptic activity, more complete development of a mature inhibitory GABAA receptor phenotype and faster production of electrical network activity when compared to standard differentiation media. This entire process – from pre-patterned neural progenitor to active neuron – takes 3 weeks or less, making it an ideal platform for drug discovery and disease modelling in the fields of human neurodegenerative and neuropsychiatric disorders, such as Huntington's disease, Parkinson's disease, Alzheimer's disease and Schizophrenia

Bringing numerous methods for expression and promoter analysis to a public cloud computing service

Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project