Exploring complex chemical systems: insights from mass spectrometry, electrochemistry and continuous cell culture

The work presented herein covers a broad range of research topics and so, in the interest of clarity, has been presented in a portfolio format. Accordingly, each chapter consists of its own introductory material prior to presentation of the key results garnered, this is then proceeded by a short discussion on their significance. In the first chapter, a methodology to facilitate the resolution and qualitative assessment of very large inorganic polyoxometalates was designed and implemented employing ion-mobility mass spectrometry. Furthermore, the potential of this technique for ‘mapping’ the conformational space occupied by this class of materials was demonstrated. These claims are then substantiated by the development of a tuneable, polyoxometalate-based calibration protocol that provided the necessary platform for quantitative assessments of similarly large, but unknown, polyoxometalate species. In addition, whilst addressing a major limitation of travelling wave ion mobility, this result also highlighted the potential of this technique for solution-phase cluster discovery. The second chapter reports on the application of a biophotovoltaic electrochemical cell for characterising the electrogenic activity inherent to a number of mutant Synechocystis strains. The intention was to determine the key components in the photosynthetic electron transport chain responsible for extracellular electron transfer. This would help to address the significant lack of mechanistic understanding in this field. Finally, in the third chapter, the design and fabrication of a low-cost, highly modular, continuous cell culture system is presented. To demonstrate the advantages and suitability of this platform for experimental evolution investigations, an exploration into the photophysiological response to gradual iron limitation, in both the ancestral wild type and a randomly generated mutant library population, was undertaken. Furthermore, coupling random mutagenesis to continuous culture in this way is shown to constitute a novel source of genetic variation that is open to further investigation.

Sparse Signal Representation in Digital and Biological Systems

Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.

Growth and development of three key summer grasses in Australian cotton systems

Awnless barnyard grass, feathertop Rhodes grass, and windmill grass are important weeds in Australian cotton systems. In October 2014, an experiment was established to investigate the phenological plasticity of these species. Seed of these species were planted in a glasshouse every four weeks and each cohort grown for 6 months. A developmental response to day length was observed in barnyard grass but not in the other species. Days to maturity increased with each planting for feathertop Rhodes and windmill grass for the first six cohorts. Barnyard grass showed a similar pattern in growth for seeds planted from October to December with an increase in the onset of maturity from 51 to 58 days. However, the onset of maturity for cohorts planted between January and March decreased to between 50 and 52 days. All species had a decrease in the total number of panicles produced from the first four plantings. Feathertop Rhodes grass planted in October produced 41 panicles compared to those planted at the end of December producing 30 panicles, barnyard grass had a decrease from 99 to 47 panicles and windmill grass 37 to 15 panicles on average. By comparing the development of these key weed species over 12 months, detailed information on the phenological plasticity of these species will be obtained. This information will contribute to more informed management decisions by improving our understanding of appropriate weed control timings or herbicide rates depending on weed emergence and development.

Evaluating Risks of Dam-Reservoir Systems Using Efficient Importance Sampling

The occurrence frequency of failure events serve as critical indexes representing the safety status of dam-reservoir systems. Although overtopping is the most common failure mode with significant consequences, this type of event, in most cases, has a small probability. Estimation of such rare event risks for dam-reservoir systems with crude Monte Carlo (CMC) simulation techniques requires a prohibitively large number of trials, where significant computational resources are required to reach the satisfied estimation results. Otherwise, estimation of the disturbances would not be accurate enough. In order to reduce the computation expenses and improve the risk estimation efficiency, an importance sampling (IS) based simulation approach is proposed in this dissertation to address the overtopping risks of dam-reservoir systems. Deliverables of this study mainly include the following five aspects: 1) the reservoir inflow hydrograph model; 2) the dam-reservoir system operation model; 3) the CMC simulation framework; 4) the IS-based Monte Carlo (ISMC) simulation framework; and 5) the overtopping risk estimation comparison of both CMC and ISMC simulation. In a broader sense, this study meets the following three expectations: 1) to address the natural stochastic characteristics of the dam-reservoir system, such as the reservoir inflow rate; 2) to build up the fundamental CMC and ISMC simulation frameworks of the dam-reservoir system in order to estimate the overtopping risks; and 3) to compare the simulation results and the computational performance in order to demonstrate the ISMC simulation advantages. The estimation results of overtopping probability could be used to guide the future dam safety investigations and studies, and to supplement the conventional analyses in decision making on the dam-reservoir system improvements. At the same time, the proposed methodology of ISMC simulation is reasonably robust and proved to improve the overtopping risk estimation. The more accurate estimation, the smaller variance, and the reduced CPU time, expand the application of Monte Carlo (MC) technique on evaluating rare event risks for infrastructures.

Biological Inspiration for Artificial Immune Systems

Artificial immune systems (AISs) to date have generally been inspired by naive biological metaphors. This has limited the effectiveness of these systems. In this position paper two ways in which AISs could be made more biologically realistic are discussed. We propose that AISs should draw their inspiration from organisms which possess only innate immune systems, and that AISs should employ systemic models of the immune system to structure their overall design. An outline of plant and invertebrate immune systems is presented, and a number of contemporary systemic models are reviewed. The implications for interdisciplinary research that more biologically-realistic AISs could have is also discussed.

'Investigating Artificial Immune Systems For Job Shop Rescheduling In Changing Environments'

ABSTRACT Artificial immune system can be used to generate schedules in changing environments and it has been proven to be more robust than schedules developed using a genetic algorithm. Good schedules can be produced especially when the number of the antigens is increased. However, an increase in the range of the antigens had somehow affected the fitness of the immune system. In this research, we are trying to improve the result of the system by rescheduling the same problem using the same method while at the same time maintaining the robustness of the schedules.

The Danger Theory and Its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems.

The Danger Theory and its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems. Notes: Uwe Aickelin, Department of Computing, University of Bradford, Bradford, BD7 1DP

An ecosystem of products and systems for ambient intelligence – the AAL4ALL users perspective

Texto completo em atas de encontros científicos internacionais com arbitragem

Extraction and purification of immunoglobulin G with aqueous biphasic systems

The immune system is able to produce antibodies, which have the capacity to recognize and to bind to foreign molecules or pathogenic organisms. Currently, there are a diversity of diseases that can be treated with antibodies, like immunoglobulins G (IgG). Thereby, the development of cost-efficient processes for their extraction and purification is an area of main interest in biotechnology. Aqueous biphasic systems (ABS) have been investigated for this purpose, once they allow the reduction of costs and the number of steps involved in the process, when compared with conventional methods. Nevertheless, typical ABS have not showed to be selective, resulting in low purification factors and yields. In this context, the addition of ionic liquids (ILs) as adjuvants can be a viable and potential alternative to tailor the selectivity of these systems. In this work, ABS composed of polyethylene glycol (PEG) of different molecular weight, and a biodegradable salt (potassium citrate) using ILs as adjuvants (5 wt%), were studied for the extraction and purification of IgG from a rabbit source. Initially, it was tested the extraction time, the effect on the molecular weight of PEG in a buffer solution of K3C6H5O7/C6H8O7 at pH≈7, and the effect of pH (59) on the yield (YIgG) and extraction efficiency (EEIgG%) of IgG. The best results regarding EEIgG% were achieved with a centrifugation step at 1000 rpm, during 10 min, in order to promote the separation of phases followed by 120 min of equilibrium. This procedure was then applied to the remaining experiments. The results obtained in the study of PEGs with different molecular weights, revealed a high affinity of IgG for the PEG-rich phase, and particularly for PEGs of lower molecular weight (EEIgG% of 96 % with PEG 400). On the other hand, the variation of pH in the buffer solution did not show a significant effect on the EEIgG%. Finally, it was evaluated the influence of the addition of different ILs (5% wt) on the IgG extraction in ABS composed of PEG 400 at pH≈7. In these studies, it was possible to obtain EEIgG% of 100% with the ILs composed of the anions [TOS]-, [CH3CO2]-and Cl-, although the obtained YIgG% were lower than 40%. On the other hand, the ILs composed of the anions Br-, as well as of the cation [C10mim]+, although not leading to EEIgG% of 100%, provide an increase in the YIgG%. ABS composed of PEG, a biodegradable organic salt and ILs as adjuvants, revealed to be an alternative and promising method to purify IgG. However, additional studies are still required in order to reduce the loss of IgG.

Probabilistic verification of satellite systems for mission critical applications

In this thesis, we present a quantitative approach using probabilistic verification techniques for the analysis of reliability, availability, maintainability, and safety (RAMS) properties of satellite systems. The subject of our research is satellites used in mission critical industrial applications. A strong case for using probabilistic model checking to support RAMS analysis of satellite systems is made by our verification results. This study is intended to build a foundation to help reliability engineers with a basic background in model checking to apply probabilistic model checking to small satellite systems. We make two major contributions. One of these is the approach of RAMS analysis to satellite systems. In the past, RAMS analysis has been extensively applied to the field of electrical and electronics engineering. It allows system designers and reliability engineers to predict the likelihood of failures from the indication of historical or current operational data. There is a high potential for the application of RAMS analysis in the field of space science and engineering. However, there is a lack of standardisation and suitable procedures for the correct study of RAMS characteristics for satellite systems. This thesis considers the promising application of RAMS analysis to the case of satellite design, use, and maintenance, focusing on its system segments. Data collection and verification procedures are discussed, and a number of considerations are also presented on how to predict the probability of failure. Our second contribution is leveraging the power of probabilistic model checking to analyse satellite systems. We present techniques for analysing satellite systems that differ from the more common quantitative approaches based on traditional simulation and testing. These techniques have not been applied in this context before. We present the use of probabilistic techniques via a suite of detailed examples, together with their analysis. Our presentation is done in an incremental manner: in terms of complexity of application domains and system models, and a detailed PRISM model of each scenario. We also provide results from practical work together with a discussion about future improvements.

Improving the use of G-CSF during chemotherapy using physiological mathematical modelling : a quantitative systems pharmacology approach

La diminution des doses administrées ou même la cessation complète d'un traitement chimiothérapeutique est souvent la conséquence de la réduction du nombre de neutrophiles, qui sont les globules blancs les plus fréquents dans le sang. Cette réduction dans le nombre absolu des neutrophiles, aussi connue sous le nom de myélosuppression, est précipitée par les effets létaux non spécifiques des médicaments anti-cancéreux, qui, parallèlement à leur effet thérapeutique, produisent aussi des effets toxiques sur les cellules saines. Dans le but d'atténuer cet impact myélosuppresseur, on administre aux patients un facteur de stimulation des colonies de granulocytes recombinant humain (rhG-CSF), une forme exogène du G-CSF, l'hormone responsable de la stimulation de la production des neutrophiles et de leurs libération dans la circulation sanguine. Bien que les bienfaits d'un traitement prophylactique avec le G-CSF pendant la chimiothérapie soient bien établis, les protocoles d'administration demeurent mal définis et sont fréquemment déterminés ad libitum par les cliniciens. Avec l'optique d'améliorer le dosage thérapeutique et rationaliser l'utilisation du rhG-CSF pendant le traitement chimiothérapeutique, nous avons développé un modèle physiologique du processus de granulopoïèse, qui incorpore les connaissances actuelles de pointe relatives à la production des neutrophiles des cellules souches hématopoïétiques dans la moelle osseuse. À ce modèle physiologique, nous avons intégré des modèles pharmacocinétiques/pharmacodynamiques (PK/PD) de deux médicaments: le PM00104 (Zalypsis®), un médicament anti-cancéreux, et le rhG-CSF (filgrastim). En se servant des principes fondamentaux sous-jacents à la physiologie, nous avons estimé les paramètres de manière exhaustive sans devoir recourir à l'ajustement des données, ce qui nous a permis de prédire des données cliniques provenant de 172 patients soumis au protocol CHOP14 (6 cycles de chimiothérapie avec une période de 14 jours où l'administration du rhG-CSF se fait du jour 4 au jour 13 post-chimiothérapie). En utilisant ce modèle physio-PK/PD, nous avons démontré que le nombre d'administrations du rhG-CSF pourrait être réduit de dix (pratique actuelle) à quatre ou même trois administrations, à condition de retarder le début du traitement prophylactique par le rhG-CSF. Dans un souci d'applicabilité clinique de notre approche de modélisation, nous avons investigué l'impact de la variabilité PK présente dans une population de patients, sur les prédictions du modèle, en intégrant des modèles PK de population (Pop-PK) des deux médicaments. En considérant des cohortes de 500 patients in silico pour chacun des cinq scénarios de variabilité plausibles et en utilisant trois marqueurs cliniques, soient le temps au nadir des neutrophiles, la valeur du nadir, ainsi que l'aire sous la courbe concentration-effet, nous avons établi qu'il n'y avait aucune différence significative dans les prédictions du modèle entre le patient-type et la population. Ceci démontre la robustesse de l'approche que nous avons développée et qui s'apparente à une approche de pharmacologie quantitative des systèmes (QSP). Motivés par l'utilisation du rhG-CSF dans le traitement d'autres maladies, comme des pathologies périodiques telles que la neutropénie cyclique, nous avons ensuite soumis l'étude du modèle au contexte des maladies dynamiques. En mettant en évidence la non validité du paradigme de la rétroaction des cytokines pour l'administration exogène des mimétiques du G-CSF, nous avons développé un modèle physiologique PK/PD novateur comprenant les concentrations libres et liées du G-CSF. Ce nouveau modèle PK a aussi nécessité des changements dans le modèle PD puisqu’il nous a permis de retracer les concentrations du G-CSF lié aux neutrophiles. Nous avons démontré que l'hypothèse sous-jacente de l'équilibre entre la concentration libre et liée, selon la loi d'action de masse, n'est plus valide pour le G-CSF aux concentrations endogènes et mènerait en fait à la surestimation de la clairance rénale du médicament. En procédant ainsi, nous avons réussi à reproduire des données cliniques obtenues dans diverses conditions (l'administration exogène du G-CSF, l'administration du PM00104, CHOP14). Nous avons aussi fourni une explication logique des mécanismes responsables de la réponse physiologique aux deux médicaments. Finalement, afin de mettre en exergue l’approche intégrative en pharmacologie adoptée dans cette thèse, nous avons démontré sa valeur inestimable pour la mise en lumière et la reconstruction des systèmes vivants complexes, en faisant le parallèle avec d’autres disciplines scientifiques telles que la paléontologie et la forensique, où une approche semblable a largement fait ses preuves. Nous avons aussi discuté du potentiel de la pharmacologie quantitative des systèmes appliquées au développement du médicament et à la médecine translationnelle, en se servant du modèle physio-PK/PD que nous avons mis au point.

Use of Products and Systems for Scientific and Technical College Education and Development for Industrial

Have been less than thirty years since a group of graduate students and computer scientists working on a federal contract performed the first successful connection between two computers located at remote sites. This group known as the NWG Network Working Group, comprised of highly creative geniuses who as soon as they began meeting started talking about things like intellectual graphics, cooperating processes, automation questions, email, and many other interesting possibilities 1 . In 1968, the group's task was to design NWG's first computer network, in October 1969, the first data exchange occurred and by the end of that year a network of four computers was in operation. Since the invention of the telephone in 1876 no other technology has revolutionized the field of communications over the computer network. The number of people who have made great contributions to the creation and development of the Internet are many, the computer network a much more complex than the phone is the result of people of many nationalities and cultures. However, remember that some years later in 19732 two computer scientists Robert Kahn and Vinton Cerft created a more sophisticated communication program called Transmission Control Protocol - Internet Protocol TCP / IP which is still in force in the Internet today.

Organizational, systems and human issues in production planning, scheduling and control

With global markets and global competition, pressures are placed on manufacturing organizations to compress order fulfillment times, meet delivery commitments consistently and also maintain efficiency in operations to address cost issues. This chapter argues for a process perspective on planning, scheduling and control that integrates organizational planning structures, information systems as well as human decision makers. The chapter begins with a reconsideration of the gap between theory and practice, in particular for classical scheduling theory and hierarchical production planning and control. A number of the key studies of industrial practice are then described and their implications noted. A recent model of scheduling practice derived from a detailed study of real businesses is described. Socio-technical concepts are then introduced and their implications for the design and management of planning, scheduling and control systems are discussed. The implications of adopting a process perspective are noted along with insights from knowledge management. An overview is presented of a methodology for the (re-)design of planning, scheduling and control systems that integrates organizational, system and human perspectives. The most important messages from the chapter are then summarized.