Continuous Descent Arrival (CDA) is a procedure where aircraft descend, at or near idle thrust, from their cruise altitude to their Final Approach Fix without leveling off. By eliminating inefficient leveling off at low altitude, CDA provides benefits such as fuel savings, flight time savings, and the significant noise reduction near airports, but the usage of CDAs has been limited in low traffic condition due to difficulty in the separation management. For the successful CDA without degradation of the runway throughput, air traffic controllers should know the performance bound of the CDA trajectory and control the time of arrival for each aircraft, which is interpreted as Required Time of Arrival (RTA) from the aircraft standpoint. This thesis proposes a novel trajectory optimization methodology to meet RTA constraint. The CDA trajectory optimization problem in the flight management system is modeled as a path constrained optimal control problem of switched dynamical system. A sequential method that performs mode sequence estimation and parameter optimization, sequentially, is proposed to solve this problem. By analyzing the relaxed optimal solution with simplified dynamics, a computationally efficient algorithm to find the optimal switching structure is proposed and applied for the mode sequence estimation. This thesis also proposes a performance-bound analysis methodology using optimal control techniques to help controllers make a feasible schedule for CDA operations at a meter fix. The feasible time range analysis for a wide variety of aircraft is performed by using the proposed methodology. Based on the analysis result, a single flight time strategy is proposed for the application of CDA in high traffic conditions. The simulation with real traffic data has been shown that the single flight time strategy, combined with the proposed fixed RTA trajectory optimization, guarantees the conflict free CDA operation.

According to the International Energy Agency 2016 statistics, Ethiopia is among the lowest countries in annual electricity consumption, 70 KWh/capita. Rural areas hold more than 80% of the country’s population and less than 30% of them have been electrified. Most of the population (the rural areas) still predominantly depend on traditional biomass energy sources for cooking and heating, and household lights are provided mainly by kerosene and biomass including this study area, Tadacha Rarasa, which consist of 4100 households with 6 members, totally 24,600 people[1, 2]. The feasibility study of hybrid system consisting of small Hydro, PV, Wind and Battery is carried out using HOMER as a tool for optimization and sensitivity analysis. TURBNPRO software also assists for the optimization of the small hydropower which is suggested to utilize the 2.2 m3/s ecological flow of the Genale 3 multipurpose hydropower plant’s reservoir. The wind speed and solar radiation data of the site is collected from NASA. Then, the wind speed, solar radiation, electric load and hydro data is input to HOMER in their respective appropriate format for simulation and analysis of the proposed hybrid system.  Electric loads of the community is estimated bearing in mind the irrigation, fishery and other opportunities which will arise after the multipurpose project completion in addition to basic household demands. The daily average estimated residential consumption by each family is 9.118 kWh and the daily average total energy consumption per person is 1.872 kWh.   After optimization and sensitivity analysis using HOMER, several different feasible configurations of Hydro, PV, Wind and Battery hybrid system has been displayed with a range of 0.049 to 0.067 $/kWh cost of energy. The optimum configuration becomes Hydro/PV/Battery hybrid system with 0.049 $/kWh levelized COE which is closer to the national energy tariff, 0.032 USD/kWh. The optimum Hydro/PV/Battery hybrid system generates annually 18,647,372 kWh with 0.18% capacity shortage and 0.15% unmet load. The hydropower supports the base load and the PV supplies for the peak load demand in the daytime which shares 19% of the total electric production.

Nos sociétés sont de plus en plus préoccupées par l’impact très nocif des ressources énergétiques polluantes, essentiellement, le pétrole, le charbon et le gaz. Ainsi, l’intérêt dans l’utilisation des énergies renouvelables et propres est en constant augmentation et la conception de nouveaux systèmes énergétiques est devenue un challenge scientifique et technologique. Pour concevoir de nouvelles solutions énergétiques compétitives et efficaces, les fabricants de composants (panneaux solaires, pile à combustible, convertisseurs, etc.) et les secteurs industriels concernés sont confrontés à des problématiques d’optimisation, de contrôle et de durabilité. Par ailleurs, les sources d’énergie renouvelable sont dépendantes de plusieurs facteurs incontrôlables (lieu géographique, météorologie, etc.). Pour parer à ces facteurs, et donc au caractère aléatoire de disponibilité énergétique, l’hybridation des sources et la gestion énergétique peut s’avérer être une approche pertinente pour la conception de solutions énergétiques efficaces. Cette thèse est une contribution au problème de l’hybridation et de la gestion d’énergie. Plus précisément, nous considérons un système hybride composé de panneaux solaires photovoltaïques et d’une pile à combustible. Ce système est supposé être doté de convertisseurs et d’un système de stockage (batterie et super-condensateurs). / Our societies are increasingly concerned about the very harmful impact of clean energy resources, mainly oil, coal and gas. Thus, interest in the use of renewable and clean energy is constantly increasing and the development of new energy systems has become a scientific and technological challenge. To develop new competitive and efficient energy solutions, manufacturers of components (solar panels, fuel cells, inverters, etc.) and industrial sectors are facing problems of optimization, control and durability. In addition, renewable energy sources depend on several uncontrollable factors (geographical location, weather, etc.). To address these factors, and thus the randomness of energy availability, sources hybridization and energy management can prove to be an appropriate approach for the design of efficient energy solutions. This thesis is a contribution to the problem of hybridization and energy management. More precisely, we consider a hybrid system composed of photovoltaic solar panels and a fuel cell. This system is supposed to be equipped with converters and storage system (battery and supercapacitors). The goal is to develop control strategies to extract the maximum power available from the considered sources and to optimize the overall energy system to meet the load requirements. To do this, our approach is based on the tracking of the maximum power point and the use of compensators.

Melanome stellen die gefährlichste Form von Hautkrebs mit der höchsten Mortalitätsrate dar. Der Transformation normaler Melanozyten zu malignen Melanomen liegen komplexe molekulare und biochemische Veränderungen zu Grunde. Im Xiphophorus-Melanom-Modell ist die onkogene Rezeptortyrosinkinase "Xiphophorus melanoma receptor kinase" (Xmrk) der alleinige Auslöser der Melanominitiation und -progression. Die Aufklärung der Xmrk-vermittelten Signaltransduktion kann zum besseren Verständnis von Ereignissen, die auch bei der humanen Melanomentwicklung eine Rolle spielen, beitragen. In der vorliegenden Arbeit wurde mit Hilfe der Microarray-Technologie die Regulation der Genexpression durch Xmrk analysiert. Zu den nach Rezeptoraktivierung am stärksten herabregulierten Genen gehörten "son of sevenless homolog 1" (Sos1) und "ubiquitin-conjugating enzyme E2I" (Ube2i); stark hochreguliert waren "early growth response 1" (Egr1), "cysteine-rich protein 61" (Cyr61), "dual-specificity phosphatase 4" (Dusp4), "fos-like antigen 1" (Fosl1), "epithelial membrane protein" (Emp1), Osteopontin (Opn), "insulin-like growth factor binding protein 3" (Igfbp3) und "tumor-associated antigen L6" (Taal6). Die für die Regulation dieser Gene verantwortlichen Signalwege wurden durch die Anwendung von niedermolekularen Inhibitoren und siRNA identifiziert, wobei für die SRC-Kinase FYN eine zentrale Bedeutung bei der Xmrk-abhängigen Regulation der Genexpression festgestellt wurde. Darüber hinaus wurde die Expression der Gene in humanen Melanomzelllinien im Vergleich zu normalen humanen Melanozyten untersucht. Als besonders vielversprechende Kandidaten stellten sich dabei DUSP4 und TAAL6 heraus, deren Rolle in der humanen Melanominduktion und -progression Gegenstand zukünftiger Studien sein wird. In einem anderen Ansatz zur Aufklärung des Signalnetzwerkes sollten Zielproteine von Xmrk durch Protein-Protein-Interaktionsstudien mit Hilfe des Split-Ubiquitin-Systems ermittelt werden. Aufgrund ungünstiger Expressions- oder Faltungseigenschaften von Xmrk in diesem System war es aber nicht möglich, den Rezeptor als Köderprotein einzusetzen. Das für die Xmrk-vermittelte Melanomentstehung zentrale Protein FYN konnte jedoch als Köder etabliert und seine Wechselwirkung mit der Tyrosinkinase FAK analysiert werden. Es wurde gezeigt, dass der phosphorylierte Tyrosinrest an Position 397 von FAK für die Interaktion einer N-terminal trunkierten FAK-Variante mit FYN notwendig ist und dass diese Phosphorylierung in Hefe gewährleistet zu sein scheint. Die Suche nach neuen Interaktionspartnern von FYN mittels der Split-Ubiquitin-Technologie könnte Einblicke in weitere FYN-abhängige Ereignisse bieten, die zur Aufklärung seiner zentralen Rolle bei der Tumorentstehung dienen könnte. / Melanoma is the most aggressive type of skin cancer with the highest mortality rate. The transformation of melanocytes to malignant melanoma is based on complex molecular and biochemical alterations. In the Xiphophorus melanoma model, the oncogenic receptor tyrosine kinase Xiphophorus melanoma receptor kinase (Xmrk) is the sole trigger of melanoma initiation and progression. Elucidating Xmrk-dependent signaling pathways may contribute to a better understanding of processes that play a role in human melanomagenesis, too. Here, the regulation of gene expression by Xmrk was analyzed using a microarray approach. The genes with the strongest down-regulation in response to receptor activation included son of sevenless homolog 1 (Sos1) and ubiquitin-conjugating enzyme E2I (Ube2i), whereas early growth response 1 (Egr1), cysteine-rich protein 61 (Cyr61), dual-specificity phosphatase 4 (Dusp4), fos-like antigen 1 (Fosl1), epithelial membrane protein (Emp1), Osteopontin (Opn), insulin-like growth factor binding protein 3 (Igfbp3), and tumor-associated antigen L6 (Taal6) were strongly up-regulated. The pathways regulating expression of these genes were identified by applying small molecule inhibitors and siRNA. Interestingly, the SRC-family kinase FYN was found to be a key-player in Xmrk-dependent gene regulation. Furthermore, expression of the genes in human melanoma cell lines compared to normal human melanocytes was investigated. The most promising candidates, which might be important for melanoma induction and progression, were DUSP4 and TAAL6. Their potential suitability as diagnostic and prognostic melanoma markers will be addressed in future studies. In addition to gene expression analysis, protein-protein interactions were to be assayed by the split-ubiquitin-system in order to identify novel Xmrk targets. Unfortunately, inappropriate expression or folding of the receptor in this system precluded it from working as bait. However, the FYN protein, which has a central role in Xmrk-mediated signaling, was established as bait and its association with FAK was analyzed in more detail. A phosphorylated tyrosine residue at position 397 of FAK was demonstrated to be necessary for the interaction of an N-terminally truncated FAK variant with FYN, and this phosphorylation event seems to be feasible in yeast. In future, a split-ubiquitin based screen for novel interaction partners of FYN might provide insights into FYN-dependent processes and help to understand its central role in tumor development.

Septinas são proteínas que pertencem a super família das GTPases e que foram inicialmente identificadas em Saccharomyces cerevisae, mas logo em seguida, também em eucariotos superiores, exceto em plantas. Estas proteínas estão envolvidas em uma variedade de processos celulares tais como segregação de cromossomos, polaridade celular, dinâmica da membrana, tráfego de vesículas, exocitose, apoptose, entre outros. Mutações ou alterações no padrão de expressão de septinas são associadas com vários cânceres e doenças neurológicas. Objetivando contribuir com informações funcionais sobre tais proteínas, as septinas humanas 1, 5 e 7 foram usadas como iscas em ensaios de duplo híbrido em leveduras visando à identificação de seus parceiros protéicos. Após a varredura de bibliotecas de cDNA de leucócitos e cérebro fetal humano, os parceiros protéicos predominantemente encontrados foram outras septinas de grupos diferentes aos das iscas. As interações septina-septina envolveram o domínio de ligação a GTP. Ainda, outros parceiros, diferentes de septinas, foram também identificados nas bibliotecas e estes se mostraram funcionalmente relacionados à endocitose, à regulação da atividade de GTPases, ao tráfego intracelular, aos ciclos de sumoilação, à manutenção da placa metafásica e à maturação do centrossomo. Algumas destas funções são inéditas e foram pela primeira vez relacionadas às septinas. Este trabalho também esteve voltado à caracterização biofísica das septinas 3 e 5 (SEPT3 e SEPT5). Muitos protocolos diferentes foram desenvolvidos na tentativa de obter amostras homogêneas de SEPT5, mas não foram bem sucedidos. Por outro lado, SEPT3 recombinante, destituída do domínio amino-terminal (SEPT3GC) foi eficientemente produzida em E. coli. O estado monomérico de SEPT3GC em solução foi confirmado por cromatografia de exclusão molecular e espalhamento de raios-X a baixos ângulos (SAXS). SEPT3GC mostrou-se ativa e capaz de hidrolizar GTP in vitro. A afinidade de SEPT3GC por GTPγS e GDP foi avaliada por calorimetria de titulação isotérmica (ITC), sendo que o KD de SEPT3GC para GTPγS foi de 5,43 μM e a ligação para este nucleotídeo foi dependente de Mg2+. A ligação para GDP não foi detectável. Agregados de SEPT3GC induzidos por temperatura foram capazes de ligar a sonda fluorescente tioflavina-T, sugerindo uma natureza amilóide para tais estruturas. / Septins are proteins that belong to the superfamily of GTPases, which were initially identified in Saccharomyces cerevisiae, and then in higher eukaryotes, except plants. These proteins are involved in a variety of cellular processes such as chromosome segregation, cell polarity, membrane dynamics, vesicle trafficking, exocytosis, apoptosis, among others. Mutations or changes in the expression of septins have been associated with various cancers and neurological diseases. Aiming to provide functional information about these proteins, the human septins 1, 5 and 7 were used as baits in yeast two-hybrid assay in order to identify their protein partners. After screening cDNA libraries from human leukocytes and fetal brain, the protein partners predominantly found were septins from others groups. The septin-septin interactions involved the GTP binding domain. Others non-septins interactors have also been identified in the libraries and were functionally related to endocytosis, the regulation of the GTPase activity, intracellular trafficking, sumoylation, maintenance of metaphase plate and centrosome maturation. Some of these functions are new and were related to the septins for the first time. This work also focused on the biophysical characterization of the septins 3 and 5 (SEPT3 and SEPT5). Many different protocols were developed aiming to obtain homogeneous samples of SEPT5, but were not successful. On the other hand, recombinant SEPT3, without the amino-terminal domain (SEPT3GC), was produced in a homogeneous form in E. coli. SEPT3GC is monomeric in solution as confirmed by size exclusion chromatography and small-angle X-ray scattering (SAXS). Also, SEPT3GC has shown to be active and able to hydrolyze GTP in vitro. The SEPT3GC affinity by GTPγS and GDP were evaluated by isothermal titration calorimetry (ITC). The KD for GTPγS was about 5,43 μM and it was observed to be Mg2+ dependent. The binding to GDP was not detectable. SEPT3GC aggregates induced by temperature were able to bind the thioflavin-T fluorescent probe, suggesting an amyloid nature for such structures.

Les systèmes de contrôle en réseau sont un champ actif de recherche, où les différentes composantes du réseau sont spatialement distribué et tentent d'atteindre un objectif global. Ils apparaissent naturellement lors l'interaction d'un système piloté par ordinateur avec le monde physique.Avec les systèmes de contrôle en réseau une classe connexe des systèmes est décrit par les systèmes Cyber-physique, où les capacités de calcul embarqué peuvent interagir avec le monde physique.Dans ce travail, nous allons considérer la tâche classique d'observation et d'estimation et étudier les cas où les contraintes induite par le réseau nécessite une adaptation des mécanismes classique d'observation et d'estimation.Dans les système de contrôle en raison de limitation des capteurs (pour des raisons pratiques telles que la réduction des coûts) certains états ou paramètre du système ne sont pas connus. Dans ce contexte, la notion classique d'observabilitéexprime la capacité de déduire de la mesure les valeurs d'intérêt.Premièrement nous considérons le problème de la réduction de l'échantillonnage par l'utilisation de échantillonnage événementiel et ce pour plusieurs classes de systèmes. Ensuite, une procédure d'estimation et de contrôle sera proposé pour résoudre le problème du consensus dans un système multi-agent.Considérant enfin une dynamique de véhicule plus complexe, nous nous concentrons sur l'estimation du coefficient de frottement de la route pour résoudre un problème de suivi. / Network control systems is an active field of study where interacting component spatially distributed try to achieve a global goal. They naturally emerge from the interaction of computer driven mechanism and the physical world.Along with network control system a related class of systems is described by the so called: Cyber-physical systems, where integrated physical computational capabilities can interact.In this work we will consider the classical task of observation and estimation and investigate cases where network induced constraint calls for adapted observation and estimation scheme.In control system due to limitation in sensors ( for practical reason such as cost reduction) all the value of interest (whether the some unmeasured state or unknown parameter)are unknown. The classical notion of observabilityaccount for the ability to deduce from measurement those value of interest.First sampling reduction by use of event trigger will be studied for several class of systems. Then an estimation and control scheme will be establish to solve the problem of consensus in a multi agents system.Finally considering a more complex vehicle dynamic we focus on the estimation of tire road friction coefficient to solve a tracking problem.

The general problem of multi-agent persistent monitoring finds applications in a variety of domains ranging from meter to kilometer-scale systems, such as surveillance or environmental monitoring, down to nano-scale systems such as tracking biological macromolecules for studying basic biology and disease. The problem can be cast as moving the agents between targets, acquiring information from or in some fashion controlling the states of the targets. Under this formulation, at least two questions need to be addressed. The first is the design of motion trajectories for the agents as they move among the spatially distributed targets and jointly optimize a given cost function that describes some desired application. The second is the design of the controller that an agent will use at a target to steer the target's state as desired. The first question can be viewed in at least two ways: first, as an optimal control problem with the domain of the targets described as a continuous space, and second as a discrete scheduling task. In this work we focus on the second approach, which formulates the target dynamics as a hybrid automaton, and the geometry of the targets as a graph. We show how to find solutions by translating the scheduling problem into a search for the optimal route. With a route specifying the visiting sequence in place, we derive the optimal time the agent spends at each target analytically. The second question, namely that of steering the target's state, can be formulated from the perspective of the target, rather than the agent. The mobile nature of the agents leads to intermittencontrol, such that the controller is assumed to be disconnected when no agent is at the target. The design of the visiting schedule of agents to one target can affect the reachability (controllability) of this target's control system and the design of any specific controller. Existing test techniques for reachability are combined with the idea of lifting to provide conditions on systems such that reachability is maintained in the presence of periodic disconnections from the controller. While considering an intermittently connected control with constraints on the control authority and in the presence of a disturbance, the concept of 'degree of controllability' is introduced. The degree is measured by a region of states that can be brought back to the origin in a given finite time. The size of this region is estimated to evaluate the performance of a given sequence.

Cell-semiconductor hybrid systems are a potential centerpiece in the scenery of biotechnological applications. The selection and study of promising crystalline semiconductor materials for bio-sensing applications is at the basis of the development of such hybrid systems. In this work we introduce crystalline SiC as an extremely appealing material for bio-applications. For the first time we report biocompatibility studies of different SiC polytypes whose results document the biocompatibility of this material and its capability of directly interfacing cells without the need of surface functionalization. Since the successful implementation of biosensors requires a good understanding and versatile control of the semiconductor surface properties, the chemistry, crystallography and electronic status of different SiC surfaces are extensively studied while their surface morphologies are thoroughly controlled via hydrogen etching. Also, investigations of the effect of cell surface charge on the electronic status of SiC surfaces are attempted adopting a contactless surface potential monitoring technique. The results obtained from these contactless measurements lead to the development of theoretical models well-suited for the description of cell-semiconductor hybrid systems electronic interactions.

In the survival and reliability data analysis, parametric and nonparametric methods are used to estimate the hazard/risk rate and survival functions. A parametric approach is based on the assumption that the underlying survival distribution belongs to some specific family of closed form distributions (normal, Weibull, exponential, etc.). On the other hand, a nonparametric approach is centered around the best-fitting member of a class of survival distribution functions. Moreover, the Kaplan-Meier and Nelson-Aalen type nonparametric approach do not assume either distribution class or closed-form distributions. Historically, well-known time-to-event processes are death of living specie in populations and failure of component in engineering systems. Recently, the human mobility, electronic communications, technological changes, advancements in engineering, medical, and social sciences have further diversified the role and scope of time-to-event processes in cultural, epidemiological, financial, military, and social sciences. To incorporate extensions, generalizations and minimize scope of existing methods, we initiate an innovative alternative modeling approach for time-to-event dynamic processes. The innovative approach is composed of the following basic components: (1) development of continuous-time state of dynamic process, (2) introduction of discrete-time dynamic intervention process, (3) formulation of continuous and discrete-time interconnected dynamic system, (4) utilizing Euler-type discretized schemes, developing theoretical dynamic algorithms, and (5) introduction of conceptual and computational state and parameter estimation procedures. The presented approach is motivated by state and parameter estimation of time-to-event processes in biological, chemical, engineering, epidemiological, medical, military, multiple-markets and social dynamic processes under the influence of discrete-time intervention processes. We initiate (1) a time-to-event process to be a probabilistic dynamic process with unitary state. Action, normal, operational, radical, survival, susceptible, etc. and its complementary states, reaction, abnormal, nonoperational, non-radical, failure, infective and so on (quantitative and qualitative variables), are considered to be illustrations of a unitary state of time-to-event dynamic processes. A unitary state is measured by a probability distribution function. Employing Newtonian dynamic modeling approach and observing the definition of hazard rate as a specific rate, survival or failure probabilistic state dynamic model is developed. This dynamic model is further extended to incorporate internal or external discrete-time dynamic intervention processes acting on unitary state time-to-event processes (2). This further demanded a formulation and development of an interconnected continuous-discrete-time hybrid, and totally discrete-time dynamic models for time-to-event processes (3). Employing the developed hybrid model, Euler-type discretized schemes, a very general fundamental conceptual analytic algorithm is outlined (4). Using the developed theoretical computational procedure in (4), a general conceptual computational data organizational and simulation schemes are presented (5) for state and parameter estimation problems in unitary state time-to-event dynamic processes. The well-known theoretical existing results in the literature are exhibited as special cases in a systematic and unified manner (6). In fact, the Kaplan-Meier and Nelson-Aalen type nonparametric estimation approaches are systematically analyzed by the developed totally discrete-time hybrid dynamic modeling process. The developed approach is applied to two data sets. Moreover, this approach does not require a knowledge of either a closed-form solution distribution or a class of distributions functions. A hazard rate need not be constant. The procedure is dynamic. In the existing literature, the failure and survival distribution functions are treated to be evolving/progressing mutually exclusively with respect to corresponding to two mutually exclusive time varying events. We refer to these two functions (failure and survival) as cumulative distributions of two mutually disjoint state output processes with respect to two mutually exclusive time-varying complementary unitary states of a time-to-event processes in any discipline of interest (7). This kind of time-to-event process can be thought of as a Bernoulli-type of deterministic/stochastic process. Corresponding to these two complementary output processes of the Bernoulli-type of stochastic process, we associate two unitary dynamic states corresponding to a binary choice options/actions (8), namely, ({action, reaction}, {normal, abnormal}, {survival, failure}, {susceptible, infective}, {operational, nonoperational}, {radical, non-radical}, and so on.) Under this consideration, we extend unitary state time-to-event dynamic model to binary state time-to-event dynamic model. Using basic tools in mathematical sciences, we initiate a Newtonian-type dynamic approach for binary state time-to-event processes in the sciences, technologies, and engineering (9). Introducing an innovative concept of “survival state dynamic principle”, an innovative interconnected nonlinear non-stationary large-scale hybrid dynamic model for number of units/species and its unitary survival state corresponding to binary state time-to-event process is formulated (10). The developed model in (10) includes dynamic model (3) as a special case. The developed approach is directly applicable to binary state time-to-event dynamic processes in biological, chemical, engineering, financial, medical, physical, military, and social sciences in a coherent manner. A by-product of this is a transformed interconnected nonlinear hybrid dynamic model with a theoretical discrete-time conceptual computational dynamic process (11). Employing the transformed discrete-time conceptual computational dynamic process, we introduce notions of data coordination, state data decomposition and aggregation, theoretical conceptual iterative processes, conceptual and computational parameter estimation and simulation schemes, conceptual and computational state simulation schemes in a systematic way (12). The usefulness of the developed interconnected algorithm is validated by using three real world data sets (13). We note that the presented algorithm does not need a closed-form representation of distribution/likelihood function. In fact, it is free from any required assumptions of the “Classical Maximum Likelihood Function Approach” in the “Survival and Reliability Analysis.” The rapid electronic communication and human mobility processes have facilitated to transform information, knowledge, and ideas almost instantly around the globe. This indeed generates heterogeneity, and it causes to form nonlinear and non-stationary dynamic processes. Moreover, the heterogeneity, non-linearity, non-stationarity, further generates two types of uncertainties, namely, deterministic, and stochastic. In view of this, it is obvious that nothing is deterministic. In short, the 21st century problems are highly nonlinear, non-stationary and under the influence of internal and external random perturbations. Using tools in stochastic analysis, interconnected deterministic models in (3) and (10) are extended to interconnected stochastic hybrid dynamic model for binary state time-to-event processes (14). The developed model is described by a large-scale nonlinear and non-stationary stochastic differential equations. Moreover, a stochastic version of a survival function is also introduced (15). Analytical, computational, statistical, and simulation algorithms/procedures are also extended and analyzed in a systematic and unified way (16). The presented interconnected stochastic model is motivated to initiate conceptual computational parameter and state estimation schemes for time-to-event statistical data (17). Again, stochastic version of computational algorithms are validated in the context of three real world data sets. The obtained parameter and state estimates show that the algorithm is independent of the choice of nonlinear transformation (18). Utilizing the developed alternative innovative procedure and the recently modified deterministic version of Local Lagged Adapted Generalized Method of Moments (LLGMM) is also extended to stochastic version in a natural way (19). This approach provides a degree of measure of confidence, prediction, and planning assessments (20). In addition, it initiates a conceptual computational parameter and state estimation and simulation schemes that is suitable for the usage of mean square sub-optimal procedure (21). The usefulness and the significance of the approach is illustrated by applying to three data sets (22). The approach provides insight for investigating various type of invariant sets, namely, sustainable/unsustainable, survival/failure, reliable/unreliable (23), and qualitative properties such as sustainability versus unsustainability, reliability versus unreliability, etc. (24) Once again, the presented algorithm is independent of any form of survival distribution functions or data sets. Moreover, it does not require a closed form survival function distribution. We also note that the introduction of intervention processes provides a measure of influence and confidence for the usage of new tools/procedures/approaches in continuous-time binary state time-to-event dynamic process (25). Moreover, the presented dynamic modeling is more feasible for its usage of investigating a more complex time-to-event dynamic process (26). The developed procedure is dynamic and indeed non-parametric (27). The dynamic approach adapts with current changes and updates statistic process (28). The dynamic nature is natural rather than the existing static and single-shot techniques (29).

Equine infectious anemia virus (EIAV) is an important animal model to study the contribution of macrophages in viral persistence during lentiviral infections. EIAV is unique amongst the lentiviruses in that it causes a rapid, rather than the very slow disease progression, characteristic of other lentiviral infections. The accessory gene, S2, unique to EIAV, is an important determinant in viral pathogenesis. A functional S2 gene is required to achieve high-titer viremia and the development of disease in infected horses. Despite its essential role, the mechanisms by which S2 influences EIAV pathogenesis remain elusive. The goal of this research was to gain insight into the role of S2 in pathogenesis. To accomplish this goal we: (i) Examined the effects of EIAV and its S2 protein in the regulation of the cytokine and chemokine responses in macrophages, (ii) Assessed the influence of EIAV infection and the effect of S2 on global gene expression in macrophages and (iii) Identified host cellular proteins that interact with S2 as a starting point for the identification of host factors implicated in S2 function. The results from this study provide evidence for a role of S2 in enhancing a proinflammatory cytokine and chemokine response in infected macrophages. Specifically, S2 enhances the expression of IL-1 alpha, IL-1 beta IL-8, MCP-2, MIP-1 beta, IP-10 and a newly discovered cytokine, IL-34. Involvement of S2 in cytokine and chemokine dysregulation may contribute to disease development by optimizing the host cell environment to promote viral dissemination and replication. Microarray analyses revealed an interesting set of differentially expressed genes upon EIAV infection. Genes affected by EIAV were involved in the immune response, transcription, translation, cell cycle and cell survival. Finally, we used the yeast two-hybrid system to identify S2 host cellular interacting proteins. We identified osteosarcoma amplified 9 (OS-9) and proteasome 26S ATPase subunit 3 (PSMC3) proteins as interacting partners of S2. Additional evidence is needed to demonstrate the physiological relevance of these interactions in vivo. In summary, the results from this study contribute towards our understanding of the role S2 in disease expression and allow the formulation of new hypotheses as to the potential mechanisms of action of S2 during EIAV infection.