Dans le cadre de la qualité environnementale des matériaux, il est essentiel d'apporter la preuve que les matériaux à base de ciments adjuvantés ne relarguent pas ou peu de matières organiques lors de leur contact avec l'eau constituant une solution lixiviante. Les additifs organiques, tels que les agents de mouture et les superplastifiants, constituent deux classes d'adjuvants organiques utilisés de manière systématique dans la fabrication ou la formulation des matériaux cimentaires, notamment quand ils sont en contact avec l'eau potable (conduites et châteaux d'eau). Pour évaluer le piégeage de ces composés organiques par une pâte de ciment CEM I, cinq montages de lixiviation dynamique CTG-LEACHCRETE ont été mis en place et adaptés pour l'étude de pâtes de ciment formulées avec des adjuvants organiques. La seconde partie de ce travail a pour objectif de mettre au point des techniques analytiques sensibles pour la détection de traces des constituants du superplastifiant et de l'agent de mouture directement dans les produits de la lixiviation de pâtes de ciment (les lixiviats) grâce aux techniques de spectrométrie de masse MALDI-TOF et Py-THM-MS. Enfin, l'application du protocole global de "lixiviation dynamique couplée à la spectrométrie de masse" nous permet d'apprécier la présence des composés organiques suite à des essais de lixiviation de pâtes de ciment formulées avec de l'agent de mouture et du superplastifiant. Cette démarche nous a permis d'obtenir de nombreux résultats donnant des informations sur les mécanismes de piégeage des différents additifs organiques par une pâte de ciment / Evidence that materials used by the industry are not damageable for the environment has become a major issue. In cement industry, organic admixtures such as grinding aids or superplasticizers ar widely used. In particular, they constitute cementitious materials in concrete contacting water like in water pipes and water tower. It is therefore essential to test whether these organic coumpounds are enventually dissolved into water by leaching. In this aim, five different dynamic leaching tests were developed and applied to a CEM I cement paste formulated with organic admixtures. In paralell, highly sensitive analytical methods based on MALDI-TOF and Py-THM-MS mass spectrometry techniques were designed in order to detect traces of leached superplasticizers or grinding aids. The dynamic leaching tests coupled to mass spectrometry allowed us to detect the presence of organic compounds in the leachate, and to better understand the mechanisms involved in the trapping of additives into a cement paste

Complex systems offer broad, unique research challenges due to their inability to be understood through a classic reductionist perspective, as they exhibit emergent phenomena that arise through the interactions of their components. In this thesis, we briefly review some characteristics of complex systems and the interplay of mathematical and computational methods to study them. We then discuss these approaches, how they are implemented, and how they support one another in three settings. First, we present a study that connects weather data to seasonal population-abundance of mosquitoes, using a microscopic model. Secondly, we consider the collective motions that arise in ensembles of disks interacting through non-elastic collisions and investigate how such behaviors affect macroscopic transport properties. Finally, we consider a 'self-sorting' one-dimensional collection of point-particles. In all of these cases, agent-based models and simulations are used to guide analysis, and in the final example, we explain how the simulations led to new theorems. Articles and molecular dynamics computer codes are provided as appendices.

E-learning is increasingly adopted to support face-to-face classroom-based learning or implemented as a complete standalone learning system. Its inherent adaptable nature and ability to provide learning anywhere, everywhere and anytime makes it a versatile tool for access to basic, professional and higher education. This research proposes and develops an adaptable e-learning approach, focusing on the learner's requirement specification and negotiation of course with multiple providers to improve online learning. This addresses issues of inflexible learning model, narrow coverage of subject domains in existing systems and ineffective use of educational resources, using design research methodology (DRM). The proposed Intelligent Learning approach provides learning support by applying collaborative and deliberative capabilities of software agents to e-learning systems. Designated learning support agents negotiate with providers on behalf of the learner for courses, matching specified requirements. This is achieved through agent negotiation strategies, devising dynamic learning plans (DPLAN) and online learning contract (or EContract) between the system and a range of providers, to harness the changing needs of the learner, hence, providing an Adaptive Agent Learner Plan (ADALP) approach. It develops and applies a 'Basic Requirements Learning' model, addressing specific learning objectives, supported by a two way evaluation process that enforces learning flexibility, empowering learners and accommodating a wide spectrum of learning needs. Unlike traditional Intelligent Tutoring System (ITS), learning objectives are not fixed and are constituted dynamically from learner specifications. The ADALP approach provides multiple provider support options, generating learner feedback for goal oriented, but flexible learning. This deviates from the traditional 'top-down' approach, where instructors and designers create fixed models of different categories of learners and their needs. The prototype of multi-agent system (MAS) demonstrates contributions of the approach, applying Multi-issue-Negotiation and Contracting Courses with Multiple Providers; devising dynamic personalised learning plans and learning commitment (or e-contracts) between learners and providers. It implements designated agents which generate tasks and sub-tasks corresponding to the learners' goals and objectives; 'biding' for learning and tutoring resources from multiple providers to deliver on the derived tasks. Personalised learning plan aligned with online learning contract is generated for each learner based on the specified requirements and learning goals, as a result. It is argued that the ADALP approach empowers learners and improves on similar approaches, in comparison to existing adaptive learning systems.

L'objectif de ce travail était de développer des méthodes pour permettre une évaluation in vivo plus robuste du réseau vasculaire dans la tumeur par imagerie de contraste ultrasonore. Trois aspects de l'analyse de donnée ont été abordé: 1) la régression des modèles paramétriques de flux sur les données de puissance linéaire, 2) la compensation du mouvement 3) l’évaluation d’une méthode de clustering pour identifier les hétérogénéités dans les tumeurs. Un modèle multiplicatif est proposé pour décrire le signal DCE-US. Une méthode de régression en est dérivée. La caractérisation du signal permet la mise au point d’une méthode de simulation de séquences 2D+T. La méthode de régression permet une diminution de la variabilité des paramètres de flux fonctionnels extraits, sur données simulées expérimentales. La méthode de simulation est appliquée pour évaluer une méthode combinant estimation du mouvement et estimations des paramètres micro-vasculaires dans un unique problème mathématique d'optimisation. Cette nouvelle méthode présente en plus l'avantage d'être indépendante de l'opérateur. Il est montré que dans une large majorité des cas l'estimation du mouvement est meilleure avec la nouvelle méthode qu'avec une méthode de références. Une méthode de clustering est adaptée et évaluée sur données DCE-US simulées et in-vivo. Elle permet de détecter des hétérogénéités dans la structure vasculaire des tumeurs. Les méthodes développées permettent d'améliorer l’évaluation du réseau microvasculaire par DCE-US grâce à une description rigoureuse du signal, à la mise au point d'outil diminuant l'intervention de l'opérateur et la prise en compte de l'hétérogénéité du réseau vasculaire. / This work aimed to develop methods to robustly evaluate in vivo functional flow within the tumor vascular network with Dynamic contrast-enhanced ultrasound (DCE-US). Three aspects of data analysis were addressed: 1) insuring best fit between parametric flow models and the experimentally acquired echo-power curves, 2) compensating sequences for motion and 3) evaluating a method to discriminate between tissues with different functional flow. A multiplicative model is proposed to describe the DCE-US signal. Based on this model, a new parametric regression method of the signal is derived. Characterization of the statistical properties of the noise and signal is also used to develop a new method simulating contrast-enhanced ultrasound 2D+t sequences. A significant decrease in the variability of the functional flow parameters extracted according to the new multiplicative-noise fitting method is demonstrated using both simulated and experimentally-acquired sequences. The new sequence simulations are applied to test a method combining motion estimation and flow-parameter estimation within a single mathematical framework. Because this new method does not require the selection of a reference image, it reduces operator intervention. Tests of the method on both simulations and clinical data and demonstrate in a majority of sequences a more accurate motion estimation than the commonly used image registration method. Finally, a non-parametric method for perfusion curve clustering is evaluated on 2D+t sequences. The aim of this method is to regroup similar filling patterns without a priori knowledge about the patterns. The method is tested on simulated and on pre-clinical data.

<div>The 1999 Columbine High School shooting was a bold reminder which emphasized the importance of active shooter preparedness for the first responder communities and the general public. Since Columbine, the preparedness for active shooter incidents (ASIs) both in the public and private sectors proactively took place. Currently, the RUN.HIDE.FIGHT.{\textregistered} (RHF) response for unarmed individuals is implemented as part of the emergency response throughout the United States. Despite the RHF's nationwide implementation, there is a lack of literature that supports the effectiveness of RHF to lower casualty rates during ASIs. </div><div></div><div>This thesis examined casualty differences of RHF and the shooters' discharge interval by creating the incidents that have occurred in the library during the 1999 Columbine High School shooting with AnyLogic's agent-based modeling capabilities. Recreating ASI in a virtual environment naturally removes the participants’ physiological and psychological implications. Additionally, the flexibility of agent-based modeling allows validating the model based on the historical events than to run various what-if scenarios. The outcome of this thesis examines the effectiveness of RHF by comparing the output data from the actual event to models with RHF implementation.</div>

Role of N-methylated lysines (K) and arginines (R) was underappreciated for a long time before the turn of the century. With the help of new emerging technologies, their crucial role in chromatin regulation was established and now their mention when discussing gene regulation is almost a given. Despite this, much about how they contribute to the cellular chemistry is still to be discovered. There is a major gap in current knowledge base due to an incomplete list of possible lysine and arginine methylation sites. This is because of their low copy number inside the cell which makes it difficult to detect them. New methylation sites are being added every day. This thesis aims to provide a solution to this problem by establishing methods that can help detect N-methylated lysines and argnines that are present in really low quantity inside the cell. The work is influenced by a previously established fact that p-sulfonatocalix[4]arene binds methylated lysine over unmethylated ones. We have first attempted to improve this native affinity by decorating the calix[4]arene skeleton with different substituents. To this effect, we have developed methods for regioselective functionalization of calix[4]arene scaffold and then studied their effect on its binding profile against a set of test peptides derived from proteins found in vivo. We then demonstrate a proof-of-concept enrichment method using selected molecules from our inventory. We use these calix[4]arene based molecules as a stationary phase modifier in a chromatography setup and then show that it can separate peptides based on presence of N-methylated lysines and arginines. We propose that introduction of such a method would improve the visibility of low level N-methylated peptides by removing the bulk of back ground unmethylated analytes and thus improving their signal strength. Finally, we establish the utility of this method by showing that more N-methylated lysines are detected from a real-world proteomics sample prepared using our enrichment method. This work opens new avenues for use of supramolecular chemistry in proteomics studies. We believe that this thesis is a confident demonstration that host-guest chemistry can help expand the existing knowledge about bimolecular processes found in vivo and must be explored further. / Graduate / 2021-12-23

"Chain walking” catalytic polymerization CWCP is a powerful tool for the one-pot synthesis of a unique class of hyperbranched polyethylene HBPE-based macromolecules with a controllable molecular weight, topology, and composition. This dissertation focuses on new synthetic routes to prepare HBPE-based macromolecular architectures by combining the CWCP technique with ring opening polymerization ROP, atom–transfer radical polymerization ATRP, and “click” chemistry. Taking advantage of end-functionalized HBPE, and a new ethynyl-soketal star-shape agent, we were able to synthesize different types of the HBPE-based architectures including hyperbranched-on-hyperbranched core-shell nanostructure, and miktoarm-star-HBPE-based block copolymers. The first part of the dissertation provides a general introduction to the synthesis of polyethylene types with controllable structures. Well-defined polyethylene with different macromolecule architectures were synthesized either for academic or industrial purposes. In the second part, the HBPE with different topologies was synthesized by CWCP, using a α-diimine Pd (II) catalyst. The effect of the temperature and pressure on the catalyst activity and polymer properties, including branch content, molecular weight, distribution, and thermal properties were studied. Two series of samples were synthesized: a) serial samples (A) under pressures of 1, 5, and 27 atm at 5˚C, and b) serial samples (B) at temperatures of 5, 15, and 35 ˚C under 5 atm. Proton nuclear magnetic resonance spectroscopy, 1H NMR, and gel permeation chromatography, GPC, analysis were used to calculate the branching content, molecular weight, and distribution, whereas differential scanning calorimetry, DSC, was used to record the melting and glass transition temperatures as well as the degree of the crystallinity. Well-defined HBPE-based core diblock copolymers with predictable amphiphilic properties are studied in the third part of the project. Hyperbranched polyethylene-b-poly(N-isopropylacrylamide), HBPE-b-PNIPAM, and hyperbranched polyethylene-b-poly(solketal acrylate), HBPE-b-PSA, were successfully synthesized by combining CWCP and ATRP. The synthetic methodology includes the following steps; a) synthesis of multifunction hyperbranched polyethylene initiators HBPE-MI by direct copolymerization of ethylene with 2-(2-bromoisobutyryloxy)ethyl acrylate BIEA in the presence of a α-diimine Pd(II) catalyst, and b) HBPE-MI with α-bromoester groups used as initiation sites for ATRP. Proton nuclear magnetic resonance spectroscopy, 1H NMR, gel permeation chromatography,GPC, and Fourier transform infrared, FT-IR, spectroscopy, were used for determining the molecular and composition structures. Also, differential scanning calorimetry, DSC, and thermogravimetric analysis, TGA, were used to record the melting temperature and to study the thermal stability, respectively. In the fourth part, a well-defined 3-miktoarm star copolymer 3μ-HBPE(PCL)2 (HBPE: hyperbranched polyethylene, PCL: poly(ε-caprolactone) was synthesized by combining CWCP, ring opening polymerization, ROP, and “click” chemistry. The synthetic methodology includes the following steps: a) synthesis of azido-functionalized hyperbranched polyethylene HBPE-N3 by CWCP of ethylene with the α-diimine Pd(II) catalyst, followed by quenching with an excess of 4-vinylbenzyl chloride and transformation of –Cl to the azido group with sodium azide, b) synthesis of in-chain ethynyl-functionalized poly(ε-caprolactone), (PCL)2-C≡CH by ROP of ε-CL with ethynylfunctionalized solketal [3-(prop-2-yn-1-yloxy) propane-1,2-diol] as a bifunctional initiator, in the presence of P2-t-Bu phosphazene super base, and c) “clicking” HBPE-N3 and (PCL)2-C≡CH using the copper(I)-catalyzed alkyne–azide cycloaddition CuAAC. Proton nuclear magnetic resonance spectroscopy, 1H NMR, gel permeation chromatography, GPC, and Fourier transform infrared, FT-IR, spectroscopy, were used to determine the molecular and composition structures. Also, the differential scanning calorimetry, DSC, was used to record the melting point temperature. The fifth part illustrates the self-assembly behavior of the HBPE-based block copolymers of poly(N-isopropylacrylamide), NIPAM, and poly(ε-caprolactone), PCL, at room temperature in water and a petroleum ether-selective solvent for NIPAM and PCL respectively. The synthesized copolymers HBPE-b-NIPAM and 3μ-HBPE(PCL)2 revealed either core-shell nanostructure in vesicles or worms and worm-likes branches, as confirmed by combining the analysis of dynamic light scattering, DLS, transmission electron microscopy, TEM, and atomic force spectroscopy, AFM. All the findings presented in this dissertation emphasize the utility of "living" CWCP to synthesize end-functionalized HBPE, and new star-linkage HBPE-based complex architectures. The summary and future works concerning predictable properties and applications are discussed in the sixth part.

京都大学 / 新制・課程博士 / 博士(エネルギー科学) / 甲第23294号 / エネ博第419号 / 新制||エネ||79(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 手塚 哲央, 教授 宇根﨑 博信, 准教授 MCLELLAN Benjamin / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

This thesis explores the uses of a multi-agent system(MAS) for procedural content generation(PCG) in the Generative Design in Minecraft (GDMC) competition. The generatorconstructed is capable of surveying the terrain and determining where to start building a roadnetwork. Extendor and connector agents build the road network used for the settlement. Aplotting agent surveys the area around the created roads for plots appropriate for buildinghouses. A house building agent then generates basic buildings on these plots. Finally afurniture agent places furniture in these buildings. The result of the thesis shows that thegenerator is capable of generating an interesting road network that is appropriate to its terrain.The buildings have potential but are lacking in form of adaptability to the current biome andbuildings are overall too similar to be interesting, causing it to get low scores in the userstudy and competition. The generator was entered to the GDMC-competition in 2021 where itplaced 17th of 20th place.

In Multi-Agent Systems consisting of intelligent agents that interact with one another, where the agents are software entities which represent individuals or organizations, it is important for the agents to be equipped with trust evaluation models which allow the agents to evaluate the trustworthiness of other agents when dishonest agents may exist in an environment. Evaluating trust allows agents to find and select reliable interaction partners in an environment. Thus, the cost incurred by an agent for establishing trust in an environment can be compensated if this improved trustworthiness leads to an increased number of profitable transactions. Therefore, it is equally important to design effective trust establishment models which allow an agent to generate trust among other agents in an environment. This thesis focuses on providing improvements to the designs of existing and future trust establishment models. Robust trust establishment models, such as the Integrated Trust Establishment (ITE) model, may use dynamically updated variables to adjust the predicted importance of a task’s criteria for specific trustors. This thesis proposes a cluster-based approach to update these dynamic variables more accurately to achieve improved trust establishment performance. Rather than sharing these dynamic variables globally, a model can learn to adjust a trustee’s behaviours more accurately to trustor needs by storing the variables locally for each trustor and by updating groups of these variables together by using data from a corresponding group of similar trustors. This work also presents a generalized trust establishment model architecture to help models be easier to design and be more modular. This architecture introduces a new transaction-level preprocessing module to help improve a model’s performance and defines a trustor-level postprocessing module to encapsulate the designs of existing models. The preprocessing module allows a model to fine-tune the resources that an agent will provide during a transaction before it occurs. A trust establishment model, named the Generalized Trust Establishment Model (GTEM), is designed to showcase the benefits of using the preprocessing module. Simulated comparisons between a cluster-based version of ITE and ITE indicate that the cluster-based approach helps trustees better meet the expectations of trustors while minimizing the cost of doing so. Comparing GTEM to itself without the preprocessing module and to two existing models in simulated tests exhibits that the preprocessing module improves a trustee’s trustworthiness and better meets trustor desires at a faster rate than without using preprocessing.