Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

GRASP with Hybrid Path Relinking for Bi-Objective Winner Determination in Combinatorial Transportation Auctions

The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper's task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm.

Use of multi-media for spreading the experiences

The global World Overview of Conservation Approaches and Technologies (WOCAT) initiative has developed standardised tools and methods to compile and evaluate knowledge available about SLM. This knowledge is now combined and enriched with audiovisual information in order to give a voice to land users, reach a broad range of stakeholders, and assist in scaling up SLM to reverse trends of degradation, desertification, and drought. Five video products, adapted to the needs of different target groups, are created and embedded in already existing platforms for knowledge sharing of SLM such as the WOCAT database and Google Earth application. A pilot project was carried out in Kenya and Tajikistan to verify ideas and tools while at the same time assessing the usefulness of the suggested products on the ground. Video has the potential to bridge the gap between different actor groups and enable communication and sharing on different levels and scales: locally, regionally, and globally. Furthermore, it is an innovative tool to link local and scientific knowledge, raise awareness, and support advocacy for SLM.

Ocean acidification induces multi-generational decline in copepod naupliar production with possible conflict for reproductive resource allocation

Climate change, including ocean acidification (OA), presents fundamental challenges to marine biodiversity and sustained ecosystem health. We determined reproductive response (measured as naupliar production), cuticle composition and stage specific growth of the copepod Tisbe battagliai over three generations at four pH conditions (pH 7.67, 7.82, 7.95, and 8.06). Naupliar production increased significantly at pH 7.95 compared with pH 8.06 followed by a decline at pH 7.82. Naupliar production at pH 7.67 was higher than pH 7.82. We attribute the increase at pH 7.95 to an initial stress response which was succeeded by a hormesis-like response at pH 7.67. A multi-generational modelling approach predicted a gradual decline in naupliar production over the next 100 years (equivalent to approximately 2430 generations). There was a significant growth reduction (mean length integrated across developmental stage) relative to controls. There was a significant increase in the proportion of carbon relative to oxygen within the cuticle as seawater pH decreased. Changes in growth, cuticle composition and naupliar production strongly suggest that copepods subjected to OA-induced stress preferentially reallocate resources towards maintaining reproductive output at the expense of somatic growth and cuticle composition. These responses may drive shifts in life history strategies that favour smaller brood sizes, females and perhaps later maturing females, with the potential to profoundly destabilise marine trophodynamics.

Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data

Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.

Multi-threaded Communicating Agents in Qu-Prolog

In this tutorial paper we summarise the key features of the multi-threaded Qu-Prolog language for implementing multi-threaded communicating agent applications. Internal threads of an agent communicate using the shared dynamic database used as a generalisation of Linda tuple store. Threads in different agents, perhaps on different hosts, communicate using either a thread-to-thread store and forward communication system, or by a publish and subscribe mechanism in which messages are routed to their destinations based on content test subscriptions. We illustrate the features using an auction house application. This is fully distributed with multiple auctioneers and bidders which participate in simultaneous auctions. The application makes essential use of the three forms of inter-thread communication of Qu-Prolog. The agent bidding behaviour is specified graphically as a finite state automaton and its implementation is essentially the execution of its state transition function. The paper assumes familiarity with Prolog and the basic concepts of multi-agent systems.

The appraisal and management of multi-storey dwelling blocks using large concrete panel systems

This exploratory study is concerned with the integrated appraisal of multi-storey dwelling blocks which incorporate large concrete panel systems (LPS). The first step was to look at U.K. multi-storey dwelling stock in general, and under the management of Birmingham City Council in particular. The information has been taken from the databases of three departments in the City of Birmingham, and rearranged in a new database using a suite of PC software called `PROXIMA' for clarity and analysis. One hundred of their stock were built large concrete panel system. Thirteen LPS blocks were chosen for the purpose of this study as case-studies depending mainly on the height and age factors of the block. A new integrated appraisal technique has been created for the LPS dwelling blocks, which takes into account the most physical and social factors affecting the condition and acceptability of these blocks. This appraisal technique is built up in a hierarchical form moving from the general approach to particular elements (a tree model). It comprises two main approaches; physical and social. In the physical approach, the building is viewed as a series of manageable elements and sub-elements to cover every single physical or environmental factor of the block, in which the condition of the block is analysed. A quality score system has been developed which depends mainly on the qualitative and quantitative conditions of each category in the appraisal tree model, and leads to physical ranking order of the study blocks. In the social appraisal approach, the residents' satisfaction and attitude toward their multi-storey dwelling block was analysed in relation to: a. biographical and housing related characteristics; and b. social, physical and environmental factors associated with this sort of dwelling, block and estate in general.The random sample consisted of 268 residents living in the 13 case study blocks. Data collected was analysed using frequency counts, percentages, means, standard deviations, Kendall's tue, r-correlation coefficients, t-test, analysis of variance (ANOVA) and multiple regression analysis. The analysis showed a marginally positive satisfaction and attitude towards living in the block. The five most significant factors associated with the residents' satisfaction and attitude in descending order were: the estate, in general; the service categories in the block, including heating system and lift services; vandalism; the neighbours; and the security system of the block. An important attribute of this method, is that it is relatively inexpensive to implement, especially when compared to alternatives adopted by some local authorities and the BRE. It is designed to save time, money and effort, to aid decision making, and to provide ranked priority to the multi-storey dwelling stock, in addition to many other advantages. A series of solution options to the problems of the block was sought for selection and testing before implementation. The traditional solutions have usually resulted in either demolition or costly physical maintenance and social improvement of the blocks. However, a new solution has now emerged, which is particularly suited to structurally sound units. The solution of `re-cycling' might incorporate the reuse of an entire block or part of it, by removing panels, slabs and so forth from the upper floors in order to reconstruct them as low-rise accommodations.

High-power spectral bistability in a multi-section quantum-dot laser under continuous-wave or mode-locked operation

Wavelength bistability between 1245nm and 1295nm is demonstrated in a multi-section quantum-dot laser, controlled via the reverse bias on the saturable absorber. Continuous-wave or mode-locked regimes are achieved (output power up to 25mW and 17mW). © OSA/CLEO 2011.

Improved adaptivity and robustness in decentralised multi-camera networks

In this paper we present increased adaptivity and robustness in distributed object tracking by multi-camera networks using a socio-economic mechanism for learning the vision graph. To build-up the vision graph autonomously within a distributed smart-camera network, we use an ant-colony inspired mechanism, which exchanges responsibility for tracking objects using Vickrey auctions. Employing the learnt vision graph allows the system to optimise its communication continuously. Since distributed smart camera networks are prone to uncertainties in individual cameras, such as failures or changes in extrinsic parameters, the vision graph should be sufficiently robust and adaptable during runtime to enable seamless tracking and optimised communication. To better reflect real smart-camera platforms and networks, we consider that communication and handover are not instantaneous, and that cameras may be added, removed or their properties changed during runtime. Using our dynamic socio-economic approach, the network is able to continue tracking objects well, despite all these uncertainties, and in some cases even with improved performance. This demonstrates the adaptivity and robustness of our approach.

A multi-method approach for the assessment of composite indices and rankings

There is growing popularity in the use of composite indices and rankings for cross-organizational benchmarking. However, little attention has been paid to alternative methods and procedures for the computation of these indices and how the use of such methods may impact the resulting indices and rankings. This dissertation developed an approach for assessing composite indices and rankings based on the integration of a number of methods for aggregation, data transformation and attribute weighting involved in their computation. The integrated model developed is based on the simulation of composite indices using methods and procedures proposed in the area of multi-criteria decision making (MCDM) and knowledge discovery in databases (KDD). The approach developed in this dissertation was automated through an IT artifact that was designed, developed and evaluated based on the framework and guidelines of the design science paradigm of information systems research. This artifact dynamically generates multiple versions of indices and rankings by considering different methodological scenarios according to user specified parameters. The computerized implementation was done in Visual Basic for Excel 2007. Using different performance measures, the artifact produces a number of excel outputs for the comparison and assessment of the indices and rankings. In order to evaluate the efficacy of the artifact and its underlying approach, a full empirical analysis was conducted using the World Bank's Doing Business database for the year 2010, which includes ten sub-indices (each corresponding to different areas of the business environment and regulation) for 183 countries. The output results, which were obtained using 115 methodological scenarios for the assessment of this index and its ten sub-indices, indicated that the variability of the component indicators considered in each case influenced the sensitivity of the rankings to the methodological choices. Overall, the results of our multi-method assessment were consistent with the World Bank rankings except in cases where the indices involved cost indicators measured in per capita income which yielded more sensitive results. Low income level countries exhibited more sensitivity in their rankings and less agreement between the benchmark rankings and our multi-method based rankings than higher income country groups.

Étude fonctionnelle d’un nouveau complexe multi-enzymatique régulant l’épigénome

L’ubiquitination, une modification post-traductionnelle importante pour le contrôle de nombreux processus cellulaires, est une réaction réversible. La réaction inverse, nommée déubiquitination est catalysée par les déubiquitinases (DUB). Nous nous sommes intéressés dans nos travaux à étudier l’ubiquitination de l’histone H2A (H2Aub), au niveau des résidus lysines 118 et 119 (K118/K119), une marque épigénétique impliquée dans la régulation de la prolifération cellulaire et la réparation de l’ADN. Le régulateur transcriptionnel BAP1, une déubiquitinase nucléaire, a été initialement identifié pour sa capacité à promouvoir la fonction suppressive de tumeurs de BRCA1. BAP1 forme un complexe multi-protéique avec plusieurs facteurs transcriptionnels et sa fonction principale est la déubiquitination de H2Aub. Plusieurs études ont démontré que BAP1 est un gène suppresseur de tumeurs majeur et qu’il est largement muté et inactivé dans une multitude de cancers. En effet, BAP1 émerge comme étant la DUB la plus mutée au niveau des cancers. Cependant, le ou les mécanismes d’action et de régulation du complexe BAP1 restent très peu connus. Dans cette étude nous nous sommes intéressés à la caractérisation moléculaire et fonctionnelle des partenaires protéiques de BAP1. De manière significative nous avons caractérisé un mécanisme unique de régulation entre deux composants majeurs du complexe BAP1 à savoir, HCF-1 et OGT. En effet, nous avons démontré que HCF-1 est requis pour maintenir le niveau protéique de OGT et que cette dernière est indispensable pour la maturation protéolytique de HCF-1 en promouvant son clivage par O-GlcNAcylation, une signalisation cellulaire nécessaire au bon fonctionnement de HCF-1. Également, nous avons découvert un nouveau mécanisme de régulation de BAP1 par l’ubiquitine ligase atypique UBE2O. En effet, UBE2O agit comme un régulateur négatif de BAP1 puisque l’ubiquitination de ce dernier induit sa séquestration dans le cytoplasme et l’inhibition de sa fonction suppressive de tumeurs. D’autre part nous nous sommes penchés sur la caractérisation de l’association de BAP1 avec deux facteurs de la famille des protéines Polycombes nommés ASXL1 et ASXL2 (ASXL1/2). Nous avons investigué le rôle de BAP1/ASXL1/2, particulièrement dans les mécanismes de déubiquitination et suppression de tumeurs. Nous avons démontré que BAP1 interagit directement iii via son domaine C-terminale avec le même domaine ASXM de ASXL1/2 formant ainsi deux complexes mutuellement exclusifs indispensables pour induire l’activité déubiquitinase de BAP1. De manière significative, ASXM s’associe avec BAP1 pour créer un nouveau domaine composite de liaison à l’ubiquitine. Ces interactions BAP1/ASXL1/2 régulent la progression harmonieuse du cycle cellulaire. De plus, la surexpression de BAP1 et de ASXL2 au niveau des fibroblastes induit la sénescence de manière dépendante de leurs interactions. D’autre part, nous avons identifié des mutations de cancers au niveau de BAP1 le rendant incapable de lier ASXL1/2, d’exercer sa fonction d’autodéubiquitination et de ce fait d’agir comme suppresseur de tumeurs. Ainsi nous avons révélé un lien étroit entre le gène suppresseur de tumeurs BAP1, son activité déubiquitinase et le contrôle de la prolifération cellulaire.

Language-based Techniques for Practical and Trustworthy Secure Multi-party Computations

Secure Multi-party Computation (MPC) enables a set of parties to collaboratively compute, using cryptographic protocols, a function over their private data in a way that the participants do not see each other's data, they only see the final output. Typical MPC examples include statistical computations over joint private data, private set intersection, and auctions. While these applications are examples of monolithic MPC, richer MPC applications move between "normal" (i.e., per-party local) and "secure" (i.e., joint, multi-party secure) modes repeatedly, resulting overall in mixed-mode computations. For example, we might use MPC to implement the role of the dealer in a game of mental poker -- the game will be divided into rounds of local decision-making (e.g. bidding) and joint interaction (e.g. dealing). Mixed-mode computations are also used to improve performance over monolithic secure computations. Starting with the Fairplay project, several MPC frameworks have been proposed in the last decade to help programmers write MPC applications in a high-level language, while the toolchain manages the low-level details. However, these frameworks are either not expressive enough to allow writing mixed-mode applications or lack formal specification, and reasoning capabilities, thereby diminishing the parties' trust in such tools, and the programs written using them. Furthermore, none of the frameworks provides a verified toolchain to run the MPC programs, leaving the potential of security holes that can compromise the privacy of parties' data. This dissertation presents language-based techniques to make MPC more practical and trustworthy. First, it presents the design and implementation of a new MPC Domain Specific Language, called Wysteria, for writing rich mixed-mode MPC applications. Wysteria provides several benefits over previous languages, including a conceptual single thread of control, generic support for more than two parties, high-level abstractions for secret shares, and a fully formalized type system and operational semantics. Using Wysteria, we have implemented several MPC applications, including, for the first time, a card dealing application. The dissertation next presents Wys*, an embedding of Wysteria in F*, a full-featured verification oriented programming language. Wys* improves on Wysteria along three lines: (a) It enables programmers to formally verify the correctness and security properties of their programs. As far as we know, Wys* is the first language to provide verification capabilities for MPC programs. (b) It provides a partially verified toolchain to run MPC programs, and finally (c) It enables the MPC programs to use, with no extra effort, standard language constructs from the host language F*, thereby making it more usable and scalable. Finally, the dissertation develops static analyses that help optimize monolithic MPC programs into mixed-mode MPC programs, while providing similar privacy guarantees as the monolithic versions.

Étude fonctionnelle d’un nouveau complexe multi-enzymatique régulant l’épigénome

L’ubiquitination, une modification post-traductionnelle importante pour le contrôle de nombreux processus cellulaires, est une réaction réversible. La réaction inverse, nommée déubiquitination est catalysée par les déubiquitinases (DUB). Nous nous sommes intéressés dans nos travaux à étudier l’ubiquitination de l’histone H2A (H2Aub), au niveau des résidus lysines 118 et 119 (K118/K119), une marque épigénétique impliquée dans la régulation de la prolifération cellulaire et la réparation de l’ADN. Le régulateur transcriptionnel BAP1, une déubiquitinase nucléaire, a été initialement identifié pour sa capacité à promouvoir la fonction suppressive de tumeurs de BRCA1. BAP1 forme un complexe multi-protéique avec plusieurs facteurs transcriptionnels et sa fonction principale est la déubiquitination de H2Aub. Plusieurs études ont démontré que BAP1 est un gène suppresseur de tumeurs majeur et qu’il est largement muté et inactivé dans une multitude de cancers. En effet, BAP1 émerge comme étant la DUB la plus mutée au niveau des cancers. Cependant, le ou les mécanismes d’action et de régulation du complexe BAP1 restent très peu connus. Dans cette étude nous nous sommes intéressés à la caractérisation moléculaire et fonctionnelle des partenaires protéiques de BAP1. De manière significative nous avons caractérisé un mécanisme unique de régulation entre deux composants majeurs du complexe BAP1 à savoir, HCF-1 et OGT. En effet, nous avons démontré que HCF-1 est requis pour maintenir le niveau protéique de OGT et que cette dernière est indispensable pour la maturation protéolytique de HCF-1 en promouvant son clivage par O-GlcNAcylation, une signalisation cellulaire nécessaire au bon fonctionnement de HCF-1. Également, nous avons découvert un nouveau mécanisme de régulation de BAP1 par l’ubiquitine ligase atypique UBE2O. En effet, UBE2O agit comme un régulateur négatif de BAP1 puisque l’ubiquitination de ce dernier induit sa séquestration dans le cytoplasme et l’inhibition de sa fonction suppressive de tumeurs. D’autre part nous nous sommes penchés sur la caractérisation de l’association de BAP1 avec deux facteurs de la famille des protéines Polycombes nommés ASXL1 et ASXL2 (ASXL1/2). Nous avons investigué le rôle de BAP1/ASXL1/2, particulièrement dans les mécanismes de déubiquitination et suppression de tumeurs. Nous avons démontré que BAP1 interagit directement iii via son domaine C-terminale avec le même domaine ASXM de ASXL1/2 formant ainsi deux complexes mutuellement exclusifs indispensables pour induire l’activité déubiquitinase de BAP1. De manière significative, ASXM s’associe avec BAP1 pour créer un nouveau domaine composite de liaison à l’ubiquitine. Ces interactions BAP1/ASXL1/2 régulent la progression harmonieuse du cycle cellulaire. De plus, la surexpression de BAP1 et de ASXL2 au niveau des fibroblastes induit la sénescence de manière dépendante de leurs interactions. D’autre part, nous avons identifié des mutations de cancers au niveau de BAP1 le rendant incapable de lier ASXL1/2, d’exercer sa fonction d’autodéubiquitination et de ce fait d’agir comme suppresseur de tumeurs. Ainsi nous avons révélé un lien étroit entre le gène suppresseur de tumeurs BAP1, son activité déubiquitinase et le contrôle de la prolifération cellulaire.

Culturable Bacterial Diversity From A Feed Water Of A Reverse Osmosis System, Evaluation Of Biofilm Formation And Biocontrol Using Phages.

Biofilm formation on reverse osmosis (RO) systems represents a drawback in the application of this technology by different industries, including oil refineries. In RO systems the feed water maybe a source of microbial contamination and thus contributes for the formation of biofilm and consequent biofouling. In this study the planktonic culturable bacterial community was characterized from a feed water of a RO system and their capacities were evaluated to form biofilm in vitro. Bacterial motility and biofilm control were also analysed using phages. As results, diverse Protobacteria, Actinobacteria and Bacteroidetes were identified. Alphaproteobacteria was the predominant group and Brevundimonas, Pseudomonas and Mycobacterium the most abundant genera. Among the 30 isolates, 11 showed at least one type of motility and 11 were classified as good biofilm formers. Additionally, the influence of non-specific bacteriophage in the bacterial biofilms formed in vitro was investigated by action of phages enzymes or phage infection. The vB_AspP-UFV1 (Podoviridae) interfered in biofilm formation of most tested bacteria and may represent a good alternative in biofilm control. These findings provide important information about the bacterial community from the feed water of a RO system that may be used for the development of strategies for biofilm prevention and control in such systems.

Doehlert Design-desirability Function Multi-criteria Optimal Separation Of 17 Phenolic Compounds From Extra-virgin Olive Oil By Capillary Zone Electrophoresis.

In Brazil, the consumption of extra-virgin olive oil (EVOO) is increasing annually, but there are no experimental studies concerning the phenolic compound contents of commercial EVOO. The aim of this work was to optimise the separation of 17 phenolic compounds already detected in EVOO. A Doehlert matrix experimental design was used, evaluating the effects of pH and electrolyte concentration. Resolution, runtime and migration time relative standard deviation values were evaluated. Derringer's desirability function was used to simultaneously optimise all 37 responses. The 17 peaks were separated in 19min using a fused-silica capillary (50μm internal diameter, 72cm of effective length) with an extended light path and 101.3mmolL(-1) of boric acid electrolyte (pH 9.15, 30kV). The method was validated and applied to 15 EVOO samples found in Brazilian supermarkets.