Agent-based modelling for cement hydration

The Agent-Based Modelling and simulation (ABM) is a rather new approach for studying complex systems withinteracting autonomous agents that has lately undergone great growth in various fields such as biology, physics, social science, economics and business. Efforts to model and simulate the highly complex cement hydration process have been made over the past 40 years, with the aim of predicting the performance of concrete and designing innovative and enhanced cementitious materials. The ABM presented here - based on previous work - focuses on the early stages of cement hydration by modelling the physical-chemical processes at the particle level. The model considers the cement hydration process as a time and 3D space system, involving multiple diffusing and reacting species of spherical particles. Chemical reactions are simulated by adaptively selecting discrete stochastic simulation for the appropriate reaction, whenever that is necessary. Interactions between particles are also considered. The model has been inspired by reported cellular automata?s approach which provides detailed predictions of cement microstructure at the expense of significant computational difficulty. The ABM approach herein seeks to bring about an optimal balance between accuracy and computational efficiency.

Prion crystalization model and its application to recognition pattern

This paper introduces APA (?Artificial Prion Assembly?): a pattern recognition system based on artificial prion crystalization. Specifically, the system exhibits the capability to classify patterns according to the resulting prion self- assembly simulated with cellular automata. Our approach is inspired in the biological process of proteins aggregation, known as prions, which are assembled as amyloid fibers related with neurodegenerative disorders.

Simulación de la propagación del malware: modelos continuos vs. modelos discretos

La gran mayoría de modelos matemáticos propuestos hasta la fecha para simular la propagación del malware están basados en el uso de ecuaciones diferenciales. Dichos modelos son analizados de manera crítica en este trabajo, determinando las principales deficiencias que presentan y planteando distintas alternativas para su subsanación. En este sentido, se estudia el uso de los autómatas celulares como nuevo paradigma en el que basar los modelos epidemiológicos, proponiendo una alternativa explícita basada en ellos a un reciente modelo continuo.

Interference between propagating changes and its effect on system failure

Computer-based, socio-technical systems projects are frequently failures. In particular, computer-based information systems often fail to live up to their promise. Part of the problem lies in the uncertainty of the effect of combining the subsystems that comprise the complete system; i.e. the system's emergent behaviour cannot be predicted from a knowledge of the subsystems. This paper suggests uncertainty management is a fundamental unifying concept in analysis and design of complex systems and goes on to indicate that this is due to the co-evolutionary nature of the requirements and implementation of socio-technical systems. The paper shows a model of the propagation of a system change that indicates that the introduction of two or more changes over time can cause chaotic emergent behaviour.

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.

Epigenetics and alternative splicing

Dissertação de Mestrado, Oncobiologia: Mecanismos Moleculares do Cancro, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2015

Development of novel human cellular models for neurotoxicity studies

Dissertation to obtain master degree in Genética Molecular e Biomedicina

Viral and cellular modulation of virus-induced apoptosis in experimental infection models

The aim of this study was to investigate herpes simplex virus type 1 (HSV-1)- and measles virus (MV)-induced cell death. HSV-1 with deletion in genes encoding infected cell protein (ICP)4 and protein kinase Us3 (d120) induced apoptosis and cathepsin activation in epithelial (HEp-2) and monocytic (U937) cells. Inhibition of cathepsin activity decreased the amount of d120-induced apoptosis indicating that d120-induced apoptosis could be cathepsin-mediated. Also, HSV-1 infection increased caspase activation suggesting that d120-induced apoptosis is probably caspase-mediated. Cystatin treatment decreased the activity of cathepsins and the replication of HSV-1 indicating that cathepsins contribute to HSV-1 infection. Interestingly, d120 induced also necroptosis in monocytic cells. This is the first report on necroptosis in HSV-1- infected cells. MV induced apoptosis in uninfected bystander T lymphocytes, probably via interaction of MV-infected monocytes with uninfected lymphocytes. The expression of death receptor Fas was clearly increased on the surface of lymphocytes. The number of apoptotic cells and the activation of cathepsins and caspases were increased in MVinfected U937 cells suggesting that MV-induced apoptosis could be cathepsin- and caspase-mediated. Cystatin treatment inhibited cathepsin activities but not MV-induced apoptosis. Besides HSV-1-induced apoptosis, innate immune responses were studied in HSV-1-infection. HSV-1 viruses with either ICP4 and Us3, or Us3 deletion only, increased the expression of Toll-like receptor (TLR)3 and stimulated its downstream pathways leading to increased expression of type I interferon gene and to functional interferons. These findings suggest that besides controlling apoptosis, HSV-1 ICP4 and Us3 genes are involved in the control of TLR3 response in infected cell.

Transcriptional dysregulation of coding and non-coding genes in cellular models of Huntington's disease

HD (Huntington's disease) is a late onset heritable neurodegenerative disorder that is characterized by neuronal dysfunction and death, particularly in the cerebral cortex and medium spiny neurons of the striatum. This is followed by progressive chorea, dementia and emotional dysfunction, eventually resulting in death. HD is caused by an expanded CAG repeat in the first exon of the HD gene that results in an abnormally elongated polyQ (polyglutamine) tract in its protein product, Htt (Huntingtin). Wild-type Htt is largely cytoplasmic; however, in HD, proteolytic N-terminal fragments of Htt form insoluble deposits in both the cytoplasm and nucleus, provoking the idea that mutHtt (mutant Htt) causes transcriptional dysfunction. While a number of specific transcription factors and co-factors have been proposed as mediators of mutHtt toxicity, the causal relationship between these Htt/transcription factor interactions and HD pathology remains unknown. Previous work has highlighted REST [RE1 (repressor element 1)-silencing transcription factor] as one such transcription factor. REST is a master regulator of neuronal genes, repressing their expression. Many of its direct target genes are known or suspected to have a role in HD pathogenesis, including BDNF (brain-derived neurotrophic factor). Recent evidence has also shown that REST regulates transcription of regulatory miRNAs (microRNAs), many of which are known to regulate neuronal gene expression and are dysregulated in HD. Thus repression of miRNAs constitutes a second, indirect mechanism by which REST can alter the neuronal transcriptome in HD. We will describe the evidence that disruption to the REST regulon brought about by a loss of interaction between REST and mutHtt may be a key contributory factor in the widespread dysregulation of gene expression in HD.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Regulation and localization of tyrosine216 phosphorylation of glycogen synthase kinase-3β in cellular and animal models of neuronal degeneration

Inactivation of glycogen synthase kinase-3β (GSK3β) by S9 phosphorylation is implicated in mechanisms of neuronal survival. Phosphorylation of a distinct site, Y216, on GSK3β is necessary for its activity; however, whether this site can be regulated in cells is unknown. Therefore we examined the regulation of Y216 phosphorylation on GSK3β in models of neurodegeneration. Nerve growth factor withdrawal from differentiated PC12 cells and staurosporine treatment of SH-SY5Y cells led to increased phosphorylation at Y216, GSK3β activity, and cell death. Lithium and insulin, agents that lead to inhibition of GSK3β and adenoviral-mediated transduction of dominant negative GSK3β constructs, prevented cell death by the proapoptotic stimuli. Inhibitors induced S9 phosphorylation and inactivation of GSK3β but did not affect Y216 phosphorylation, suggesting that S9 phosphorylation is sufficient to override GSK3β activation by Y216 phosphorylation. Under the conditions examined, increased Y216 phosphorylation on GSK3β was not an autophosphorylation response. In resting cells, Y216 phosphorylation was restricted to GSK3β present at focal adhesion sites. However, after staurosporine, a dramatic alteration in the immunolocalization pattern was observed, and Y216-phosphorylated GSK3β selectively increased within the nucleus. In rats, Y216 phosphorylation was increased in degenerating cortical neurons induced by ischemia. Taken together, these results suggest that Y216 phosphorylation of GSK3β represents an important mechanism by which cellular insults can lead to neuronal death.

Human single-chain Fv intrabodies counteract in situ huntingtin aggregation in cellular models of Huntington's disease

This investigation was pursued to test the use of intracellular antibodies (intrabodies) as a means of blocking the pathogenesis of Huntington's disease (HD). HD is characterized by abnormally elongated polyglutamine near the N terminus of the huntingtin protein, which induces pathological protein–protein interactions and aggregate formation by huntingtin or its exon 1-containing fragments. Selection from a large human phage display library yielded a single-chain Fv (sFv) antibody specific for the 17 N-terminal residues of huntingtin, adjacent to the polyglutamine in HD exon 1. This anti-huntingtin sFv intrabody was tested in a cellular model of the disease in which huntingtin exon 1 had been fused to green fluorescent protein (GFP). Expression of expanded repeat HD-polyQ-GFP in transfected cells shows perinuclear aggregation similar to human HD pathology, which worsens with increasing polyglutamine length; the number of aggregates in these transfected cells provided a quantifiable model of HD for this study. Coexpression of anti-huntingtin sFv intrabodies with the abnormal huntingtin-GFP fusion protein dramatically reduced the number of aggregates, compared with controls lacking the intrabody. Anti-huntingtin sFv fused with a nuclear localization signal retargeted huntingtin analogues to cell nuclei, providing further evidence of the anti-huntingtin sFv specificity and of its capacity to redirect the subcellular localization of exon 1. This study suggests that intrabody-mediated modulation of abnormal neuronal proteins may contribute to the treatment of neurodegenerative diseases such as HD, Alzheimer's, Parkinson's, prion disease, and the spinocerebellar ataxias.

Toward bacterial protein sub-cellular location prediction:single-class discrimminant models for all gram- and gram+ compartments

Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation - which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.