Now showing items 110-129 of 624

• #### Dance Bands in Chester & North Wales, 1930 – 1970: Revealing a Hidden History

Dance bands in Chester and North Wales, 1930 - 1970 : Revealing a Hidden History “… the work of local amateur musicians is not just haphazard or formless, the result of individual whim or circumstance. On the contrary, a consistent - if sometimes changing - structure lies behind these surface activities. The public events … are part of an invisible but organised system through which individuals make their contribution to both the changes and the continuities of English music today.” (Finnegan, 2007) Chester (UK) in the period around World War II had a thriving live dance music scene, in which most of the music-making was done by local semi-professional musicians. Although they were busiest in the 1940s and 50s, many of the bands involved continued to operate alongside groups playing rock 'n' roll and pop, often in the same venues and sometimes at the same events, and the infrastructure which had supported the dance bands is an essential, if under-recorded, part of the history of rock 'n' roll and beat bands in the area (including the Beatles). This presentation looks at evidence from a recently-completed Ph.D. project to investigate how this local dance band scene worked, including the nature and evolution of its 'invisible but organised' underlying structure. The majority of the data was collected from private sources, with the aim of recording information which was not available in a single, academically-accessible archive. Fieldwork included over 30 recorded interviews with musicians, promoters and dancers. It also yielded more than 200 photographs and images which helped to illuminate the world of the bands, musicians and venues mentioned, and to produce a comprehensive snapshot of the local dance band scene, covering as wide a range as possible of social and musical backgrounds and experiences. Inspirations for this oral history project include The Hidden Musicians (Finnegan, 2007), Jazz Places (Becker, 2004), Rock Culture in Liverpool (Cohen, 1991), Other Voices (Brocken, 2010) and Victory Through Harmony (Baade, 2013). It is hoped that combining ideas from these and other sources with a detailed investigation of this specific local scene, as this work has done, will contribute further to a better understanding of amateur and semi-professional music-making in an urban landscape. Becker, Howard S. (2004). Jazz Places. In A. Bennett & R. A. Peterson (Eds.), Music Scenes: Local, Translocal and Virtual (pp. 17 - 27): Vanderbilt University Press. Brocken, Michael. (2010). Other voices : hidden histories of Liverpool's popular music scenes, 1930s - 1970s: Ashgate Publishing Ltd. Cohen, Sara. (1991). Rock Culture in Liverpool : Popular Music in the Making: Oxford University Press. Finnegan, Ruth H. . (2007). The Hidden Musicians: Music-Making in an English Town: Wesleyan University Press.
• #### Dance bands in Chester (1930 - 1970) : An evolving professional network

Headings are: the city of Chester; a hidden history; jazz places; economic places; social networks; methodology and findings.
• #### Data aggregation in wireless sensor networks with minimum delay and minimum use of energy: A comparative study

The prime objective of deploying large- scale wireless sensor networks is to collect information from to control systems associated with these networks. Wireless sensor networks are widely used in application domains such as security and inspection, environmental monitoring, warfare, and other situations especially where immediate responses are required such as disasters and medical emergency. Whenever there is a growth there are challenges and to cope with these challenges strategies and solutions must be developed. This paper discusses the recently addressed issues of data aggregation through presenting a comparative study of different research work done on minimizing delay in different structures of wireless sensor networks. Finally we introduce our proposed method to minimize both delay and power consumption using a tree based clustering scheme with partial data aggregation.
• #### Data-driven selection and parameter estimation for DNA methylation mathematical models

Epigenetics is coming to the fore as a key process which underpins health. In particular emerging experimental evidence has associated alterations to DNA methylation status with healthspan and aging. Mammalian DNA methylation status is maintained by an intricate array of biochemical and molecular processes. It can be argued changes to these fundamental cellular processes ultimately drive the formation of aberrant DNA methylation patterns, which are a hallmark of diseases, such as cancer, Alzheimer's disease and cardiovascular disease. In recent years mathematical models have been used as e ective tools to help advance our understanding of the dynamics which underpin DNA methylation. In this paper we present linear and nonlinear models which encapsulate the dynamics of the molecular mechanisms which de ne DNA methylation. Applying a recently developed Bayesian algorithm for parameter estimation and model selection, we are able to estimate distributions of parameters which include nominal parameter values. Using limited noisy observations, the method also identifed which methylation model the observations originated from, signaling that our method has practical applications in identifying what models best match the biological data for DNA methylation.
• #### DC-Link Voltage Coordinated-Proportional Control for Cascaded Converter with Zero Steady-State Error and Reduced System Type

Cascaded converter is formed by connecting two sub-converters together, sharing a common intermediate DC-link voltage. Regulation of this DC-link voltage is frequently realized with a Proportional-Integral (PI) controller, whose high gain at DC helps to force a zero steady-state tracking error. Such precise tracking is however at the expense of increasing the system type, caused by the extra pole at the origin introduced by the PI controller. The overall system may hence be tougher to control. To reduce the system type while preserving precise DC-link voltage tracking, this paper proposes a coordinated control scheme for the cascaded converter, which uses only a proportional DC-link voltage regulator. The resulting converter is thus dynamically faster, and when compared with the conventional PI-controlled converter, it is less affected by impedance interaction between its two sub-converters. The proposed scheme can be used with either unidirectional or bidirectional power flow, and has been verified by simulation and experimental results presented in the paper.
• #### De-smokeGCN: Generative Cooperative Networks for Joint Surgical Smoke Detection and Removal

Surgical smoke removal algorithms can improve the quality of intra-operative imaging and reduce hazards in image-guided surgery, a highly desirable post-process for many clinical applications. These algorithms also enable effective computer vision tasks for future robotic surgery. In this paper, we present a new unsupervised learning framework for high-quality pixel-wise smoke detection and removal. One of the well recognized grand challenges in using convolutional neural networks (CNNs) for medical image processing is to obtain intra-operative medical imaging datasets for network training and validation, but availability and quality of these datasets are scarce. Our novel training framework does not require ground-truth image pairs. Instead, it learns purely from computer-generated simulation images. This approach opens up new avenues and bridges a substantial gap between conventional non-learning based methods and which requiring prior knowledge gained from extensive training datasets. Inspired by the Generative Adversarial Network (GAN), we have developed a novel generative-collaborative learning scheme that decomposes the de-smoke process into two separate tasks: smoke detection and smoke removal. The detection network is used as prior knowledge, and also as a loss function to maximize its support for training of the smoke removal network. Quantitative and qualitative studies show that the proposed training framework outperforms the state-of-the-art de-smoking approaches including the latest GAN framework (such as PIX2PIX). Although trained on synthetic images, experimental results on clinical images have proved the effectiveness of the proposed network for detecting and removing surgical smoke on both simulated and real-world laparoscopic images.
• #### Dead-zone logic in autonomic systems

Dead-Zone logic is a mechanism to prevent autonomic managers from unnecessary, inefficient and ineffective control brevity when the system is sufficiently close to its target state. It provides a natural and powerful framework for achieving dependable self-management in autonomic systems by enabling autonomic managers to smartly carry out a change (or adapt) only when it is safe and efficient to do so-within a particular (defined) safety margin. This paper explores and evaluates the performance impact of dead-zone logic in trustworthy autonomic computing. Using two case example scenarios, we present empirical analyses that demonstrate the effectiveness of dead-zone logic in achieving stability, dependability and trustworthiness in adaptive systems. Dynamic temperature target tracking and autonomic datacentre resource request and allocation management scenarios are used. Results show that dead-zone logic can significantly enhance the trustability of autonomic systems.
• #### Delamination Detection via Reconstructed Frequency Response Function of Composite Structures

Online damage detection technologies could reduce the weight of structures by allowing the use of less conservative margins of safety. They are also associated with high economical benefits by implementing a condition-based maintenance system. This paper presented a damage detection and location technique based on the dynamic response of glass fibre composite laminate structures (frequency response function). Glass fibre composite laminate plates of 200×200×2.64 mm, which had a predefined delamination, were excited using stationary random vibration waves of 500 Hz band-limited noise input at ≈1.5 g. The response of the structure was captured via Micro-ElectroMechanical System (MEMS) accelerometer to detect damage. The frequency response function requires data from damaged structures only, assuming that healthy structures are homogeneous and smooth. The frequency response of the composite structure was then reconstructed and fitted using the least-squares rational function method. Delamination as small as 20 mm was detected using global changes in the natural frequencies of the structure, the delamination was also located with greater degree of accuracy due to local changes of frequency response of the structure. It was concluded that environmental vibration waves (stationary random vibration waves) can be utilised to monitor damage and health of composite structures effectively.
• #### Delay differential equations: Detection of small solutions

This thesis concerns the development of a method for the detection of small solutions to delay differential equations. The detection of small solutions is important because their presence has significant influence on the analytical prop¬erties of an equation. However, to date, analytical methods are of only limited practical use. Therefore this thesis focuses on the development of a reliable new method, based on finite order approximations of the underlying infinite dimen¬sional problem, which can detect small solutions. Decisions (concerning the existence, or otherwise, of small solutions) based on our visualisation technique require an understanding of the underlying methodol¬ogy behind our approach. Removing this need would be attractive. The method we have developed can be automated, and at the end of the thesis we present a prototype Matlab code for the automatic detection of small solutions to delay differential equations.
• #### Design and finite element simulation of metal-core piezoelectric fiber/epoxy matrix composites for virus detection

Undoubtedly, the coronavirus disease 2019 (COVID-19) has received the greatest concern with a global impact, and this situation will continue for a long period of time. Looking back in history, airborne transimission diseases have caused huge casualties several times. COVID-19 as a typical airborne disease caught our attention and reminded us of the importance of preventing such diseases. Therefore, this study focuses on finding a new way to guard against the spread of these diseases such as COVID-19. This paper studies the dynamic electromechanical response of metal-core piezoelectric fiber/epoxy matrix composites, designed as mass load sensors for virus detection, by numerical modelling. The dynamic electromechanical response is simulated by applying an alternating current (AC) electric field to make the composite vibrate. Furthermore, both concentrated and distributed loads are considered to assess the sensitivity of the biosensor during modelling of the combination of both biomarker and viruses. The design parameters of this sensor, such as the resonant frequency, the position and size of the biomarker, will be studied and optimized as the key values to determine the sensitivity of detection. The novelty of this work is to propose functional composites that can detect the viruses from changes of the output voltage instead of the resonant frequency change using piezoelectric sensor and piezoelectric actuator. The contribution of this detection method will significantly shorten the detection time as it avoids fast Fourier transform (FFT) or discrete Fourier transform (DFT). The outcome of this research offers a reliable numerical model to optimize the design of the proposed biosensor for virus detection, which will contribute to the production of high-performance piezoelectric biosensors in the future.
• #### Design and specification of building integrated DC electricity networks

Adoption of millions of small energy efficient, low power digital and DC appliances at home and at work is resulting in a significant and fast growing fraction of a building's electricity actually consumed in low voltage DC form. Building integrated energy systems featuring renewable photovoltaics are also increasingly attractive as part of an overall electricity and emissions reduction strategy. This paper details design and specification of a novel system level method of matching building integrated photovoltaic electricity generation with local low voltage DC appliances in office and other ICT intensive environments such as schools. The chosen scenario considers load components consisting of a diverse range of modern low power ICT and DC appliances, networked and powered by industry certified smart DC distribution technologies. Energy supply to the converged DC, IT and ICT network is described as featuring a roof-mounted or other on-site photovoltaic array in combination with conventional supply from the local grid infrastructure. The direct and strategic benefits of smart DC infrastructures are highlighted as the enabling technology for optimal demand reduction through fully integrated energy management of DC systems in buildings.
• #### Design, Synthesis and Evaluation of New Bioactive Oxadiazole Derivatives as Anticancer Agents Targeting Bcl-2

A series of 2-(1H-indol-3-yl)-5-substituted-1,3,4-oxadiazoles, 4a–m, were designed, synthesized and tested in vitro as potential pro-apoptotic Bcl-2 inhibitory anticancer agents based on our previously reported hit compounds. Synthesis of the target 1,3,4-oxadiazoles was readily accomplished through a cyclization reaction of indole carboxylic acid hydrazide 2 with substituted carboxylic acid derivatives 3a–m in the presence of phosphorus oxychloride. New compounds 4a–m showed a range of IC50 values concentrated in the low micromolar range selectively in Bcl-2 positive human cancer cell lines. The most potent candidate 4-trifluoromethyl substituted analogue 4j showed selective IC50 values of 0.52–0.88 μM against Bcl-2 expressing cell lines with no inhibitory effects in the Bcl-2 negative cell line. Moreover, 4j showed binding that was two-fold more potent than the positive control gossypol in the Bcl-2 ELISA binding affinity assay. Molecular modeling studies helped to further rationalize anti-apoptotic Bcl-2 binding and identified compound 4j as a candidate with drug-like properties for further investigation as a selective Bcl-2 inhibitory anticancer agent.
• #### Detailed error analysis for a fractional Adams method

This preprint discusses a method for a numerical solution of a nonlinear fractional differential equation, which can be seen as a generalisation of the Adams–Bashforth–Moulton scheme.
• #### Detailed error analysis for a fractional adams method with graded meshes

We consider a fractional Adams method for solving the nonlinear fractional differential equation $\, ^{C}_{0}D^{\alpha}_{t} y(t) = f(t, y(t)), \, \alpha >0$, equipped with the initial conditions $y^{(k)} (0) = y_{0}^{(k)}, k=0, 1, \dots, \lceil \alpha \rceil -1$. Here $\alpha$ may be an arbitrary positive number and $\lceil \alpha \rceil$ denotes the smallest integer no less than $\alpha$ and the differential operator is the Caputo derivative. Under the assumption $\, ^{C}_{0}D^{\alpha}_{t} y \in C^{2}[0, T]$, Diethelm et al. \cite[Theorem 3.2]{dieforfre} introduced a fractional Adams method with the uniform meshes $t_{n}= T (n/N), n=0, 1, 2, \dots, N$ and proved that this method has the optimal convergence order uniformly in $t_{n}$, that is $O(N^{-2})$ if $\alpha > 1$ and $O(N^{-1-\alpha})$ if $\alpha \leq 1$. They also showed that if $\, ^{C}_{0}D^{\alpha}_{t} y(t) \notin C^{2}[0, T]$, the optimal convergence order of this method cannot be obtained with the uniform meshes. However, it is well known that for $y \in C^{m} [0, T]$ for some $m \in \mathbb{N}$ and $0 < \alpha 1$, we show that the optimal convergence order of this method can be recovered uniformly in $t_{n}$ even if $\, ^{C}_{0}D^{\alpha}_{t} y$ behaves as $t^{\sigma}, 0< \sigma <1$. Numerical examples are given to show that the numerical results are consistent with the theoretical results.
• #### Determining control parameters for dendritic cell-cytotoxic T lymphocyte interaction

Dendritic cells (DC) are potent immunostimulatory cells facilitating antigen transport to lymphoid tissues and providing efficient stimulation of T cells. A series of experimental studies in mice demonstrated that cytotoxic T lymphocytes (CTL) can be efficiently induced by adoptive transfer of antigen-presenting DC. However, the success of DC-based immunotherapeutic treatment of human cancer, for example, is still limited because the details of the regulation and kinetics of the DC-CTL interaction are not yet completely understood. Using a combination of experimental mouse studies, mathematical modeling, and nonlinear parameter estimation, we analyzed the population dynamics of DC-induced CTL responses. The model integrates a predator-prey-type interaction of DC and CTL with the non-linear compartmental dynamics of T cells. We found that T cell receptor avidity, the half-life of DC, and the rate of CTL-mediated DC-elimination are the major control parameters for optimal DC-induced CTL responses. For induction of high avidity CTL, the number of adoptively transferred DC was of minor importance once a minimal threshold of approximately 200 cells per spleen had been reached. Taken together, our study indicates that the availability of high avidity T cells in the recipient in combination with the optimal application regimen is of prime importance for successful DC-based immunotherapy.
• #### A deterministic oscillatory model of microtubule growth and shrinkage for differential actions of short chain fatty acids

Short chain fatty acids (SCFA), principally acetate, propionate, butyrate and valerate, are produced in pharmacologically relevant concentrations by the gut microbiome. Investigations indicate that they exert beneficial effects on colon epithelia. There is increasing interest in whether different SCFAs have distinct functions which may be exploited for prevention or treatment of colonic diseases including colorectal cancer (CRC), inflammatory bowel disease and obesity. Based on experimental evidence, we hypothe-sised that odd-chain SCFAs may possess anti-mitotic capabilities in colon cancer cells by disrupting microtubule (MT) structural integrity via dysregulation of b-tubulin isotypes. MT dynamic instability is an essential characteristic of MT cellular activity. We report a minimal deterministic model that takes a novel approach to explore the hypothesised pathway by triggering spontaneous oscillations to represent MT dynamic behaviour. The dynamicity parameters in silico were compared to those reported in vitro.Simulations of untreated and butyrate (even-chain length) treated cells reflected MT behaviour in interphase or untreated control cells. The propionate and valerate (odd-chain length) simulations displayed increased catastrophe frequencies and longer periods of MT-fibre shrinkage. Their enhanced dynamicity wasdissimilar to that observed in mitotic cells, but parallel to that induced by MT-destabilisation treatments.Antimicrotubule drugs act through upward or downward modulation of MT dynamic instability. Our computational modelling suggests that metabolic engineering of the microbiome may facilitate managing CRC risk by predicting outcomes of SCFA treatments in combination with AMDs