Autonomous Finite Capacity Scheduling using Biological Control Principles

The vast majority of the research efforts in finite capacity scheduling over the past several years has focused on the generation of precise and almost exact measures for the working schedule presupposing complete information and a deterministic environment. During execution, however, production may be the subject of considerable variability, which may lead to frequent schedule interruptions. Production scheduling mechanisms are developed based on centralised control architecture in which all of the knowledge base and databases are modelled at the same location. This control architecture has difficulty in handling complex manufacturing systems that require knowledge and data at different locations. Adopting biological control principles refers to the process where a schedule is developed prior to the start of the processing after considering all the parameters involved at a resource involved and updated accordingly as the process executes. This research reviews the best practices in gene transcription and translation control methods and adopts these principles in the development of an autonomous finite capacity scheduling control logic aimed at reducing excessive use of manual input in planning tasks. With autonomous decision-making functionality, finite capacity scheduling will as much as practicably possible be able to respond autonomously to schedule disruptions by deployment of proactive scheduling procedures that may be used to revise or re-optimize the schedule when unexpected events occur. The novelty of this work is the ability of production resources to autonomously take decisions and the same way decisions are taken by autonomous entities in the process of gene transcription and translation. The idea has been implemented by the integration of simulation and modelling techniques with Taguchi analysis to investigate the contributions of finite capacity scheduling factors, and determination of the ‘what if’ scenarios encountered due to the existence of variability in production processes. The control logic adopts the induction rules as used in gene expression control mechanisms, studied in biological systems. Scheduling factors are identified to that effect and are investigated to find their effects on selected performance measurements for each resource in used. How they are used to deal with variability in the process is one major objective for this research as it is because of the variability that autonomous decision making becomes of interest. Although different scheduling techniques have been applied and are successful in production planning and control, the results obtained from the inclusion of the autonomous finite capacity scheduling control logic has proved that significant improvement can still be achieved

Computational methods toward early detection of neuronal deterioration

In today's world, because of developments in medical sciences, people are living longer, particularly in the advanced countries. This increasing of the lifespan has caused the prevalence of age-related diseases like Alzheimer’s and dementia. Researches show that ion channel disruptions, especially the formation of permeable pores to cations by Aβ plaques, play an important role in the occurrence of these types of diseases. Therefore, early detection of such diseases, particularly using non-invasive tools can aid both patients and those scientists searching for a cure. To achieve the goal toward early detection, the computational analysis of ion channels, ion imbalances in the presence of Aβ pores in neurons and fault detection is done. Any disruption in the membrane of the neuron, like the formation of permeable pores to cations by Aβ plaques, causes ionic imbalance and, as a result, faults occur in the signalling of the neuron.The first part of this research concentrates on ion channels, ion imbalances and their impacts on the signalling behaviour of the neuron. This includes investigating the role of Aβ channels in the development of neurodegenerative diseases. Results revealed that these types of diseases can lead to ionic imbalances in the neuron. Ion imbalances can change the behaviour of neuronal signalling. Therefore, by identifying the pattern of these changes, the disease can be detected in the very early stages. Then the role of coupling and synchronisation effects in such diseases were studied. After that, a novel method to define minimum requirements for synchronicity between two coupled neurons is proposed. Further, a new computational model of Aβ channels is proposed and developed which mimics the behaviour of a neuron in the course of Alzheimer's disease. Finally, both fault computation and disease detection are carried out using a residual generation method, where the residuals from two observers are compared to assess their performance

Digital control networks for virtual creatures

Robot control systems evolved with genetic algorithms traditionally take the form of floating-point neural network models. This thesis proposes that digital control systems, such as quantised neural networks and logical networks, may also be used for the task of robot control. The inspiration for this is the observation that the dynamics of discrete networks may contain cyclic attractors which generate rhythmic behaviour, and that rhythmic behaviour underlies the central pattern generators which drive lowlevel motor activity in the biological world. To investigate this a series of experiments were carried out in a simulated physically realistic 3D world. The performance of evolved controllers was evaluated on two well known control tasks—pole balancing, and locomotion of evolved morphologies. The performance of evolved digital controllers was compared to evolved floating-point neural networks. The results show that the digital implementations are competitive with floating-point designs on both of the benchmark problems. In addition, the first reported evolution from scratch of a biped walker is presented, demonstrating that when all parameters are left open to evolutionary optimisation complex behaviour can result from simple components

Colorectal Cancer Through Simulation and Experiment

Colorectal cancer has continued to generate a huge amount of research interest over several decades, forming a canonical example of tumourigenesis since its use in Fearon and Vogelstein’s linear model of genetic mutation. Over time, the field has witnessed a transition from solely experimental work to the inclusion of mathematical biology and computer-based modelling. The fusion of these disciplines has the potential to provide valuable insights into oncologic processes, but also presents the challenge of uniting many diverse perspectives. Furthermore, the cancer cell phenotype defined by the ‘Hallmarks of Cancer’ has been extended in recent times and provides an excellent basis for future research. We present a timely summary of the literature relating to colorectal cancer, addressing the traditional experimental findings, summarising the key mathematical and computational approaches, and emphasising the role of the Hallmarks in current and future developments. We conclude with a discussion of interdisciplinary work, outlining areas of experimental interest which would benefit from the insight that mathematical and computational modelling can provide

Selected Topics on Computed Tomography

This book is a research publication that covers developments within the Diagnostics field of study. The book is a collection of reviewed scholarly contributions written by different authors and edited by an expert with specific expertise. Each scholarly contribution represents a chapter which is complete in itself but related to the major topics and objectives. The target audience comprises scholars and specialists in the field

Non-visual effects of light on human circadian physiology and neurobehavioral performance

Light is of crucial importance for human circadian rhythms. In fact, light exposure allows for resetting individual biological rhythms to the 24-h day. Besides its synchronizing effects, light also acts on different behavioural and physiological variables. The overarching aim of this thesis was to investigate the effect of different light properties, such as intensity, wavelength, duration, timing and dynamics, on neurobehavioral performance and circadian physiology, and possible inter-individual differences. In the first part, we investigated the effect of three morning light settings (dim light, DL < 8 lux; monochromatic blue light, mBL at 100 lux; and dawn simulation light, DsL increasing from 0 to 250 lux) in 17 young participants (20-35 years old), after two nights of 6-h sleep restriction, on alertness, well-being, melatonin and cortisol profiles and cognitive performance. We found that exposure to artificial morning DsL improved subjective perception of well-being and mood, as well as cognitive performance across the day compared to DL and mBL. Only morning mBL induced a phase advance of the circadian profile of melatonin, thus impacting on the circadian system. In the second part, we compared the effect of three light settings (dim light, DL <8 lux; polychromatic white light, WL at 250 lux; and blue- enriched polychromatic white light, BL at 250 lux) on subjective sleepiness and physiological variables during a 40-h sleep deprivation protocol. Inter-individual differences were investigated with respect to (1) age, by enrolling a cohort of 26 young (20-35 years old) and 12 older participants (55-75 years old); and (2) genetic predisposition (polymorphism in clock gene Period3), by enrolling 8 young PER34/4 and 8 young PER35/5 participants. Accordingly, the age-related effects were such that exposure to BL and WL improved subjective sleepiness in both age groups, while melatonin suppression was only detectable in the young, with a more pronounced effect under BL, and not in the older. Only the blue-enriched light modified cortisol levels, with a decrease in the young and an increase in the older. Both lights had a contrary effect depending on the age of the participant in regard to skin temperature and motor activity. With respect to the genetic predisposition, exposure to BL and WL suppressed melatonin in both groups, with a stronger effect under BL in the PER35/5. However, we showed a significant alerting response, a better well-being, and a decrease in cortisol levels only in the short allele carriers (PER34/4). In contrast, cognitive performance was decreased only in PER35/5 under WL. In conclusion, depending on the purpose to use non-visual effects of light, either DsL or mDL can be used to improve subjective mood and cognitive performance or to shift internal rhythms, respectively. In a broader perspective, the use of moderately bright light in night work and shift work settings, where constant light levels are very common, may differ across shift workers given their age and their genetic predisposition

Experimental evolution of environment dependent gene regulation.

The effects of environment on evolution can be explored by experimentally controlling the environment experienced by a population. Data can be collected continuously on evolutionary change and related to the experimental environment. Further, the controlled conditions allow theoretical predictions to be tested. This thesis reports on the development of two experimental evolution systems that can be used to investigate the effects of environmental change on the evolution of gene regulation. In both systems the fission yeast Schizosaccharomyces pombe grows under defined selection pressures in two alternating environments. Conditions in both environments are under tight control, with one selecting positively for expression of a target gene, and the other selecting negatively against expression. Alternating growth between the two environments creates a selection pressure for environment dependent regulation of the gene. This is an example of phenotypic plasticity – an environment dependent phenotypic change. Thus, the two systems can be used to investigate phenotypic plasticity and gene regulation, including testing of related theories. The first system targets the expression of the ura4 gene. This gene is necessary for the production of uracil, so an environment lacking uracil selects strongly for expression. The alternate environment contains the compound 5-fluoroorotic acid (FOA) which is metabolised by URA4 into a toxin, thus strongly selecting against expression. The second system targets the expression of an introduced green fluorescent protein (GFP) gene using fluorescence activated cell sorting (FACS). The sorting can alternately select for high and low expressing cells from a population. Environmental conditions between the sorts can be altered to provide a cue for the selection the population will face next, thus allowing evolution of environment dependent expression. Experimental work in developing and testing these systems is presented