In a many-body fermionic system, the suppression of continuous transitions to absolute zero can result in a low temperature quantum fluid which deviates strongly from typical metallic behaviour; unconventional superconductivity can be induced by the strange metal region surrounding the zero-temperature phase transition. In this thesis we focus on three systems which demonstrate a highly tunable phase transition, with the aim of pushing them toward the border of a zero-temperature phase transition, and potentially superconductivity. CeAgSb2 is a uniaxial 4f ferromagnet, where physical pressure or a transverse field may be used to tune the magnetic transition towards T = 0 K. Our investigations, however, did not reveal the presence of superconductivity. It is likely that the field tuned transition does not correspond to a true critical point, whilst the high pressure region may be occupied by an antiferromagnetic phase, with the true critical point at higher pressures. However, other interesting features emerge in the electrical resistivity and AC-susceptibility, along with novel thermodynamic signatures linking the magnetisation to the specific heat. The doping series Lu(1-x)YxFe2Ge2 shows an antiferromagnetic transition which is suppressed to absolute zero at a critical concentration x_c=0.2. YFe2Ge2 displays anomalous low temperature behaviour consistent with the proximity to quantum critical fluctuations, along with a superconducting transition which appears in the electrical resistivity beneath a critical temperature of T_c ~ 1.7 K. Using low temperature DC magnetisation measurements, we show that this is a bulk effect, and that the superconductivity in YFe2Ge2 is of type-II. The thermodynamic and BCS properties of the superconducting phase are analysed in line with the parameters we extract experimentally. The superconducting 3-4-13 stannides (Ca,Sr)3Ir4Sn13 show a high temperature structural transition which may be suppressed by the application of hydrostatic pressure or effective chemical pressure. A superconducting dome is found, which appears to peak near where the structural transition extrapolates to zero temperature. Anomalous exponents are seen in the electrical resistivity over a wide temperature range. We investigate the influence of pressure on the superconducting critical temperature in Ca3Ir4Sn13 and the related compound Co3Ca4Sn13, along with an analysis of the upper critical field and flux-line phenomena in Ca3Ir4Sn13 and Sr3Ir4Sn13.

Cette recherche porte sur la conscience du risque chez différentes populations de motocyclistes. Il s’agit plus spécifiquement d’appréhender cette notion de « Conscience du Risque » selon deux points de vue complémentaires : celui de la Psychologie Sociale, qui traite des attitudes face aux risques et à la prise de risque, et celui de la Psychologie Cognitive, qui traite des compétences et des capacités du sujet à apprécier le risque « en situation ». La méthodologie mise en place propose un continuum entre ces deux dimensions.Un premier protocole (ARTIQ) porte sur les attitudes et vise à identifier des profils de motocyclistes sous l’angle particulier du risque et de la prise de risque. Le second protocole (CRITIC) repose sur les compétences cognitives des participants dans leurs évaluations du risque de 25 situations de conduite. Ce dispositif expérimental a été utilisé auprès de cinq populations de motocyclistes différentes (Bikers, Utilitaristes, Sportifs, Novices et Débutants), en fonction de leur expérience de conduite et de leurs pratiques respectives de la moto. Les résultats montrent certaines spécificités propres à chaque population, tant que pour ce qui est de leurs attitudes face aux risques que pour leur compétence dans l’évaluation du risque en situation. Ils permettent ainsi de valider l’efficacité et l’intérêt de notre protocole dans une perspective de classification des motocyclistes, selon leurs profils vis-à-vis du risque et de la prise de risque au guidon. / This is a research on risk awareness in different populations of motorcyclists.More specifically, this notion of “Risk Awareness” is to be observed under two complementary perspectives: social psychology dealing with attitudes toward risk and risk taking, and Cognitive Psychology dealing with the subject’s skills and abilities to evaluate risk “in situation”. The methodology that has been developed offers a continuum between these two dimensions.The first protocol (ARTIQ) deals with the attitudes and aims at identifying profiles of motorcyclists under the specific angle of risk and risk taking.The second protocol (CRITIC) is based on the participants’ cognitive skills to evaluate risk in 25 driving situations. This experimental protocol has been used among five different populations of motorcyclists (Bikers, Commuters, Sport Motorcyclists, Novices, Inexperienced Motorcyclists) according to their own driving experience and respective riding practices.The results reveal some characteristics peculiar to each population regarding their attitude toward risks as well as their skill to evaluate risk in situation. These characteristics confirm the effectiveness and the interest of our protocol to classify motorcyclists according to their profiles toward risk and risk taking while riding.

Vários problemas do mundo real podem ser analisados como problemas de otimização. Na bioinformática, em especial, como exemplos podem ser citados o alinhamento múltiplo de sequências, a filogenia, a predição de estruturas de proteínas e RNA, entre outros. As Meta-heurísticas Populacionais (MhP) são técnicas baseadas em interações de conjuntos de soluções candidatas, como elementos de uma população, utilizadas na otimização de funções. Seu uso é especialmente interessante na otimização de problemas onde há conhecimento parcial ou nenhum do espaço de busca. O objetivo deste trabalho é investigar o uso de auto-organização da população de um sistema imunológico artificial (AIS) a fim de aplicá-lo no problema de docking, que pode ser visto como um problema de otimização multimodal complexo. O AIS é um tipo de MhP inspirado na microevolução do sistema imunológico adaptativo de organismos complexos. Neste, as soluções candidatas representam células do sistema imunológico que busca se adaptar para a eliminação de um patógeno. O desenvolvimento do algoritmo foi baseado no opt-aiNet, que utiliza dos princípios das teorias de seleção clonal e maturação de afinidade para realizar a otimização de funções. Adicionalmente, o opt-aiNet, inspirado na teoria de redes imunológicas, realiza uma etapa de supressão, que busca eliminar soluções semelhantes, aumentando assim a diversidade populacional. Esta etapa é computacionalmente custosa, dado que é feito o cálculo da distância entre todos os possíveis pares de células (soluções) afim de eliminar aquelas próximas de acordo com um dado critério. A proposta deste trabalho é o desenvolvimento de um algoritmo de supressão auto-organizável, inspirado no fenômeno da criticalidade auto-organizada, buscando diminuir a influência da seleção de parâmetros e a complexidade da etapa de supressão. O algoritmo proposto foi testado em um conjunto de funções contínuas conhecidas e comumente utilizadas pela comunidade de computação evolutiva. Os resultados obtidos foram comparados com aqueles de uma implementação do opt-aiNet. Em adição, foi proposta a utilização de operadores de mutação com distribuição q-gaussiana nos AISs desenvolvidos. O algoritmo foi também aplicado no problema de docking rígido baseado em complementaridade de superfícies e minimização de colisões, especificamente no docking de proteínas. Os resultados foram comparados com aqueles de um algoritmo genético, resultando em um melhor desempenho obtido pelo algoritmo proposto. / Many real world problems can be described as optimization problems. In bioinformatics in special, there is multiple sequence alignment, filogeny and RNA and Protein structure prediction, among others. Population based metaheuristics are techniques based in the interaction of a set of candidate solutions as elements of a population. Its use is specially interesting in optimization problems where there is little or no knowledge of the search space. The objective of this work is to study the use of self-organization of population in an artificial imune system for use in the docking problem, considered a complex multimodal optimization problem. The artificial imunme system is a type of population based methaheuristics inspired in the microevolution of the adaptive immune system of complex organisms. Candidate solutions represent cells of the immune system adapting its antibodies to eliminate a pathogen. The development of the algorithm was based in the opt-aiNet, based in the principles of clonal selection and affinity maturation for function optimization. Additionally, the opt-aiNet, inspired in theories of immune network, makes a suppression stage to eliminate similiar solutions and control diversity. This stage is computationally expensive as it calculates the distance between every possible pair of cells (solutions) eliminating those closer than a threshold. This work proposes a self-organized suppression algorithm inspired in the self-organized criticality, looking to minimize the influence of parameter selection and complexity of the suppression stage in opt-aiNet. The proposed algorithm was tested in a set of well-known functions in the evolutionary computation community. The results were compared to those of an implementation of the opt-aiNet. In addition, we proposed a mutation operator with q-Gaussian distribution for the artificial immune systems. The algorithm was then applied in the rigid protein docking problem based in surface complementarity and colision avoidance. The results were compared with a genetic algorithm and achieved a better performance.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21554号 / 理博第4461号 / 新制||理||1640(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 石田 憲二, 教授 前野 悦輝, 教授 松田 祐司 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第22238号 / 理博第4552号 / 新制||理||1654(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 松田 祐司, 教授 石田 憲二, 教授 寺嶋 孝仁 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

Nowadays, security risk assessment has become an integral part of network security as everyday life has become interconnected with and dependent on computer networks. There are various types of data in the network, often with different criticality in terms of availability or confidentiality or integrity of information. Critical data is riskier when it is exploited. Data criticality has an impact on network security risks. The challenge of diminishing security risks in a specific network is how to conduct network security risk analysis based on data criticality. An interesting aspect of the challenge is how to integrate the security metric and the threat modeling, and how to consider and combine the various elements that affect network security during security risk analysis. To the best of our knowledge, there exist no security risk analysis techniques based on threat modeling that consider the criticality of data. By extending the security risk analysis with data criticality, we consider its impact on the network in security risk assessment. To acquire the corresponding security risk value, a method for integrating data criticality into graphical attack models via using relevant metrics is needed. In this thesis, an approach for calculating the security risk value considering data criticality is proposed. Our solution integrates the impact of data criticality in the network by extending the attack graph with data criticality. There are vulnerabilities in the network that have potential threats to the network. First, the combination of these vulnerabilities and data criticality is identified and precisely described. Thereafter the interaction between the vulnerabilities through the attack graph is taken into account and the final security metric is calculated and analyzed. The new security metric can be used by network security analysts to rank security levels of objects in the network. By doing this, they can find objects that need to be given additional attention in their daily network protection work. The security metric could also be used to help them prioritize vulnerabilities that need to be fixed when the network is under attack. In general, network security analysts can find effective ways to resolve exploits in the network based on the value of the security metric.

The influence of the strain rate and heat treatment on the occurrence of plastic instabilities in extruded AlSi1MgMn (6082) and cold rolled AlMg4.5Mn0.4 (5182) alloys was studied. The samples were uniaxially loaded at various strain rates and at room temperature (RT). The results are discussed using concurrent acoustic emission (AE) monitoring during mechanical testing and the AE parameters are correlated to the microstructure and to the stress-time curves. All samples exhibited the Portevin-Le Châtelier (PLC) effect of different types, dependently on the heat treatment and the applied strain rate. The occurrence of the PLC effect is manifested by burst AE signals with high amplitudes. Statistical analysis of the AE signals has shown the power-law probability distribution.

Multi- and many-core processors are becoming increasingly popular in embedded systems. Many of these processors now feature hardware virtualization capabilities, such as the ARM Cortex A15, and x86 processors with Intel VT-x or AMD-V support. Hardware virtualization offers opportunities to partition physical resources, including processor cores, memory and I/O devices amongst guest virtual machines. Mixed criticality systems and services can then co-exist on the same platform in separate virtual machines. However, traditional virtual machine systems are too expensive because of the costs of trapping into hypervisors to multiplex and manage machine physical resources on behalf of separate guests. For example, hypervisors are needed to schedule separate VMs on physical processor cores. Additionally, traditional hypervisors have memory footprints that are often too large for many embedded computing systems. This dissertation presents the design of the Quest-V separation kernel, which partitions services of different criticality levels across separate virtual machines, or sandboxes. Each sandbox encapsulates a subset of machine physical resources that it manages without requiring intervention of a hypervisor. In Quest-V, a hypervisor is not needed for normal operation, except to bootstrap the system and establish communication channels between sandboxes. This approach not only reduces the memory footprint of the most privileged protection domain, it removes it from the control path during normal system operation, thereby heightening security.

Cooperative behavior arises from the interactions of single units that globally produce a complex dynamics in which the system acts as a whole. As an archetype I refer to a flock of birds. As a result of cooperation the whole flock gets special abilities that the single individuals would not have if they were alone. This research work led to the discovery that the function of a flock, and more in general, that of cooperative systems, surprisingly rests on the occurrence of organizational collapses. In this study, I used cooperative systems based on self-propelled particle models (the flock models) which have been proved to be virtually equivalent to sociological network models mimicking the decision making processes (the decision making model). The critical region is an intermediate condition between a highly disordered state and a strong ordered one. At criticality the waiting times distribution density between two consecutive collapses shows an inverse power law form with an anomalous statistical behavior. The scientific evidences are based on measures of information theory, correlation in time and space, and fluctuation statistical analysis. In order to prove the benefit for a system to live at criticality, I made a flock system interact with another similar system, and then observe the information transmission for different disturbance values. I proved that at criticality the transfer of information gets the maximal efficiency. As last step, the flock model has been shown that, despite its simplicity, is sufficiently a realistic model as proved via the use of 3D simulations and computer animations.

For a graph G = (V, E), a set S ⊆ V is a total dominating set if every vertex in V is adjacent to some vertex in S. The smallest cardinality of any total dominating set is the total domination number γt(G). For an arbitrary edge e εE(Ḡ), γt(G) - 2 ≤ γt(G + e) ≤ γt(G); if the latter inequality is strict for each e ε E(Ḡ) ≠ φ, then G is said to be γt-critical. The criticality index of an edge e ε E(Ḡ) is γt(e) = γt(G) - γt(G + e). Let E(Ḡ) = [e1...,em} and S = ∑j=1m̄ci(ej). The criticality index of G is ci(G) = S/m̄. For any rational number k, 0 ≤ k ≤ 2, we construct a graph G with ci(G) = k. For 1 ≤ k ≤ 2, we construct graphs with this property that are γt-critical as well as graphs that are not γt-critical.