Thermal conditions affecting heat transfer in FDM/FFE: a contribution towards the numerical modelling of the process

The performance of parts produced by Free Form Extrusion (FFE), an increasingly popular additive manufacturing technique, depends mainly on their dimensional accuracy, surface quality and mechanical performance. These attributes are strongly influenced by the evolution of the filament temperature and deformation during deposition and solidification. Consequently, the availability of adequate process modelling software would offer a powerful tool to support efficient process set-up and optimisation. This work examines the contribution to the overall heat transfer of various thermal phenomena developing during the manufacturing sequence, including convection and radiation with the environment, conduction with support and between adjacent filaments, radiation between adjacent filaments and convection with entrapped air. The magnitude of the mechanical deformation is also studied. Once this exercise is completed, it is possible to select the material properties, process variables and thermal phenomena that should be taken in for effective numerical modelling of FFE.

Engineering of fatty acid production and secretion in Saccharomyces cerevisiae

Tese de Doutoramento em Ciências - Especialidade em Biologia

Creep behaviour of cracked steel fibre reinforced self-compacting concrete laminar structures

Tese de Doutoramento - Civil Engineering

Tunnel engineering – influence of the type and the quantity of measurements in the back analysis of geomechanical parameters

The monitoring data collected during tunnel excavation can be used in inverse analysis procedures in order to identify more realistic geomechanical parameters that can increase the knowledge about the interested formations. These more realistic parameters can be used in real time to adapt the project to the real structure in situ behaviour. However, monitoring plans are normally designed for safety assessment and not especially for the purpose of inverse analysis. In fact, there is a lack of knowledge about what types and quantity of measurements are needed to succeed in identifying the parameters of interest. Also, the optimisation algorithm chosen for the identification procedure may be important for this matter. In this work, this problem is addressed using a theoretical case with which a thorough parametric study was carried out using two optimisation algorithms based on different calculation paradigms, namely a conventional gradient-based algorithm and an evolution strategy algorithm. Calculations were carried for different sets of parameters to identify several combinations of types and amount of monitoring data. The results clearly show the high importance of the available monitoring data and the chosen algorithm for the success rate of the inverse analysis process.

Engineering modular viral scaffolds for targeted bacterial population editing

Bacteria are central to human health and disease, but existing tools to edit microbial consortia are limited. For example, broad-spectrum antibiotics are unable to precisely manipulate bacterial communities. Bacteriophages can provide highly specific targeting of bacteria, but assembling well-defined phage cocktails solely with natural phages can be a time-, labor- and cost-intensive process. Here, we present a synthetic biology strategy to modulate phage host ranges by engineering phage genomes in Saccharomyces cerevisiae. We used this technology to redirect Escherichia coli phage scaffolds to target pathogenic Yersinia and Klebsiella bacteria, and conversely, Klebsiella phage scaffolds to target E. coli by modular swapping of phage tail components. The synthetic phages achieved efficient killing of their new target bacteria and were used to selectively remove bacteria from multi-species bacterial communities with cocktails based on common viral scaffolds. We envision this approach accelerating phage biology studies and enabling new technologies for bacterial population editing.

A demonstration case on the derivation of process-level logical architectures for ambient assisted living ecosystems

When representing the requirements for an intended software solution during the development process, a logical architecture is a model that provides an organized vision of how functionalities behave regardless of the technologies to be implemented. If the logical architecture represents an ambient assisted living (AAL) ecosystem, such representation is a complex task due to the existence of interrelated multidomains, which, most of the time, results in incomplete and incoherent user requirements. In this chap- ter, we present the results obtained when applying process-level modeling techniques to the derivation of the logical architecture for a real industrial AAL project. We adopt a V-Model–based approach that expresses the AAL requirements in a process-level perspec- tive, instead of the traditional product-level view. Additionally, we ensure compliance of the derived logical architecture with the National Institute of Standards and Technology (NIST) reference architecture as nonfunctional requirements to support the implementa- tion of the AAL architecture in cloud contexts.

Numerical simulation of the reflow soldering process

Dissertação de mestrado integrado em Mechanical Engineering

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Micro/nano-structured superhydrophobic surfaces in the biomedical field: part I: basic concepts and biomimetic approaches.

Inspired by natural structures, great attention has been devoted to the study and development of surfaces with extreme wettable properties. The meticulous study of natural systems revealed that the micro/nano-topography of the surface is critical to obtaining unique wettability features, including superhydrophobicity. However, the surface chemistry also has an important role in such surface characteristics. As the interaction of biomaterials with the biological milieu occurs at the surface of the materials, it is expected that synthetic substrates with extreme and controllable wettability ranging from superhydrophilic to superhydrophobic regimes could bring about the possibility of new investigations of cellâ material interactions on nonconventional surfaces and the development of alternative devices with biomedical utility. This first part of the review will describe in detail how proteins and cells interact with micro/nano-structured surfaces exhibiting extreme wettabilities.

Highly robust chitosan hydrogels via a fast, simple and biocompatible dual crosslinking-based process

Load-bearing soft tissues such as cartilage, blood vessels and muscles are able to withstand a remarkable compressive stress of several MPa without fracturing. Interestingly, most of these structural tissues are mainly composed of water and in this regard, hydrogels, as highly hydrated 3D-crosslinked polymeric networks, constitute a promising class of materials to repair lesions on these tissues. Although several approaches can be employed to shape the mechanical properties of artificial hydrogels to mimic the ones found on biotissues, critical issues regarding, for instance, their biocompatibility and recoverability after loading are often neglected. Therefore, an innovative hydrogel device made only of chitosan (CHI) was developed for the repair of robust biological tissues. These systems were fabricated through a dual-crosslinking process, comprising a photo- and an ionic-crosslinking step. The obtained CHIbased hydrogels exhibited an outstanding compressive strength of ca. 20 MPa at 95% of strain, which is several orders of magnitude higher than those of the individual components and close to the ones found in native soft tissues. Additionally, both crosslinking processes occur rapidly and under physiological conditions, enabling cellsâ encapsulation as confirmed by high cell survival rates (ca. 80%). Furthermore, in contrast with conventional hydrogels, these networks quickly recover upon unloading and are able to keep their mechanical properties under physiological conditions as result of their non-swell nature.

Los entornos virtuales como herramienta sustituta del laboratorio "real" y como complemento de la enseñanza de Química a alumnos de Ingeniería. Virtual environments as substitute tools for the "conventional" laboratories and as a complement for Chemistry teaching to Engineering students.

El presente proyecto se plantea el siguiente problema de investigación:¿Cuál es la eficacia de los entornos virtuales de enseñanza para optimizar los aprendizajes de Química? Se sostiene la hipótesis de que los entornos virtuales de enseñanza, empleados como mediación instrumental, son eficaces para optimizar los aprendizajes de química, particularmente facilitando la vinculación y reversibilidad entre "mundo micro y macroscópico"; capacidad que usualmente sólo se atribuye al trabajo experimental de laboratorio. Los objetivos propuestos son: Determinar la eficacia de entornos virtuales de enseñanza, como mediaciones instrumentales, para optimizar los aprendizajes de química en estudiantes de ingeniería. Implementar un entrono virtual de enseñanza de química, diseñado como mediación instrumental y destinado a estudiantes de dos carreras de ingeniería del IUA. Evaluar el desarrollo y los resultados de la innovación introducida. Comparar los resultados de la innovación con los resultados de la enseñanza usual. Derivar conclusiones acerca de la eficacia de la innovación propuesta. Socializar el conocimiento producido en ámbitos científico-tecnológicos reconocidos. Se generará un aula virtual en plataforma Educativa y utilidzando el laboratorio de computación de la institución se buscará desarrollar laboratorios virtuales donde se propondrán actividades de simulación de trabajo experimental. Los resultados esperados son: - Un Aula Virtual que cumpla funciones análogas a las de un laboratorio experimental. - Información válida y confiable acerca de la eficacia de la misma como medio para optimizar los aprendizajes de química. - Publicaciones en ámbitos científico-tecnológicos reconocidos que sometan a juicio público la innovación y la investigación efectuadas. La importancia del proyecto radica principalmente en poner a prueba la eficacia de los entornos virtuales para optimizar los aprendizajes de química, analogando tareas usualmente limitadas al trabajo experimental de laboratorio. Su pertinencia apunta a un replanteo del curriculo de los cursos de Química para estudiantes de Ingeniería.

Application of multivariate statistical process control to fuel cell manufacturing

Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.

Translation of biomechanical concepts in bone tissue engineering: from animal study to revision knee arthroplasty.

Bone defects in revision knee arthroplasty are often located in load-bearing regions. The goal of this study was to determine whether a physiologic load could be used as an in situ osteogenic signal to the scaffolds filling the bone defects. In order to answer this question, we proposed a novel translation procedure having four steps: (1) determining the mechanical stimulus using finite element method, (2) designing an animal study to measure bone formation spatially and temporally using micro-CT imaging in the scaffold subjected to the estimated mechanical stimulus, (3) identifying bone formation parameters for the loaded and non-loaded cases appearing in a recently developed mathematical model for bone formation in the scaffold and (4) estimating the stiffness and the bone formation in the bone-scaffold construct. With this procedure, we estimated that after 3 years mechanical stimulation increases the bone volume fraction and the stiffness of scaffold by 1.5- and 2.7-fold, respectively, compared to a non-loaded situation.

Uncovering a role for micro-RNAs in sleep homeostasis and energy metabolism

Micro-RNAs (miRNAs) are key, post-transcriptional regulators of gene expression and have been implicated in almost every cellular process investigated thus far. However, their role in sleep, in particular the homeostatic aspect of sleep control, has received little attention. We here assessed the effects of sleep deprivation on the brain miRNA transcriptome in the mouse. Sleep deprivation affected miRNA expression in a brain-region specific manner. The forebrain expression of the miRNA miR-709 was affected the most and in situ analyses confirmed its robust increase throughout the brain, especially in the cerebral cortex and the hippocampus. The hippocampus was a major target of the sleep deprivation affecting 37 miRNAs compared to 52 in the whole forebrain. Moreover, independent from the sleep deprivation condition, miRNA expression was highly region-specific with 45% of all expressed miRNAs showing higher expression in hippocampus and 55% in cortex. Next we demonstrated that down-regulation of miRNAs in Com/c2o-expressing neurons of adult mice, through a conditional and inducible Dicer knockout mice model (cKO), results in an altered homeostatic response after sleep deprivation eight weeks following the tamoxifen-induced recombination. Dicer cKO mice showed a larger increase in the electro-encephalographic (EEG) marker of sleep pressure, EEG delta power, and a reduced Rapid Eye Movement sleep rebound, compared to controls, highlighting a functional role of miRNAs in sleep homeostasis. Beside a sleep phenotype, Dicer cKO mice developed an unexpected, severe obesity phenotype associated with hyperphagia and altered metabolism. Even more surprisingly, after reaching maximum body weight 5 weeks after tamoxifen injection, obese cKO mice spontaneously started losing weight as rapidly as it was gained. Brain transcriptome analyses in obese mice identified several obesity-related pathways (e.g. leptin, somatostatin, and nemo-like kinase signaling), as well as genes involved in feeding and appetite (e.g. Pmch, Neurotensin). A gene cluster with anti-correlated expression in the cerebral cortex of post-obese compared to obese mice was enriched for synaptic plasticity pathways. While other studies have identified a role for miRNAs in obesity, we here present a unique model that allows for the study of processes involved in reversing obesity. Moreover, our study identified the cortex as a brain area important for body weight homeostasis. Together, these observations strongly suggest a role for miRNAs in the maintenance of homeostatic processes in the mouse, and support the hypothesis of a tight relationship between sleep and metabolism at a molecular - Les micro-ARNS (miARNs) sont des régulateurs post-transcriptionnels de l'expression des gènes, impliqués dans la quasi-totalité des processus cellulaires. Cependant, leur rôle dans la régulation du sommeil, et en particulier dans le maintien de l'homéostasie du sommeil, n'a reçu que très peu d'attention jusqu'à présent. Dans cette étude, nous avons étudié les conséquences d'une privation de sommeil sur l'expression cérébrale des miARNs chez la souris, et observé des changements dans l'expression de nombreux miARNs. Dans le cerveau antérieur, miR-709 est le miARN le plus affecté par la perte de sommeil, en particulier dans le cortex cérébral et l'hippocampe. L'hippocampe est la région la plus touchée avec 37 miARNs changés comparés à 52 dans le cerveau entier. Par ailleurs, indépendamment de la privation de sommeil, certains miARNs sont spécifiquement enrichis dans certaines aires cérébrales, 45% des miARNs étant surexprimés dans l'hippocampe contre 55% dans le cortex. Dans une seconde étude, nous avons observé que la délétion de DICER, enzyme essentielle à la biosynthèse des miARNs, et la perte subséquente des miARNs dans les neurones exprimant la protéine CAMK2a altère la réponse homéostatique à une privation de sommeil, 8 semaines après l'induction de la recombinaison génétique par le tamoxifen. Les souris sans Dicer (cKO) ont une plus large augmentation de l'EEG delta power, le principal marqueur électro-encéphalographique du besoin de sommeil, comparée aux contrôles, ainsi qu'un rebond en sommeil paradoxal plus petit. De façon surprenante, les souris Dicer cKO développent une obésité rapide, sévère et transitoire, associée à de l'hyperphagie et une altération de leur métabolisme énergétique. Après avoir atteint un pic maximal d'obésité, les souris cKO entrent spontanément dans une période de perte de poids rapide. L'analyse du transcriptome cérébral des souris obèses nous a permis d'identifier des voies associées à l'obésité (leptine, somatostatine et nemo-like kinase), et à la prise alimentaire (Pmch, Neurotensin), tandis que celui des souris post-obèses a révélé un groupe de gènes liés à la plasticité synaptique. Au-delà des nombreux modèles d'obésité existant chez la souris, notre étude présente un modèle unique permettant d'étudier les mécanismes sous-jacent la perte de poids. De plus, nous avons mis en évidence un rôle important du cortex cérébral dans le maintien de la balance énergétique. En conclusion, toutes ces observations soutiennent l'idée que les miARNs sont des régulateurs cruciaux dans le maintien des processus homéostatiques et confortent l'hypothèse d'une étroite relation moléculaire entre le sommeil et le métabolisme.

Abstracting qualitative information for process supervision

Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant