Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Mobile robot experimental modeling and control strategies using sensor fusion

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational, and research tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

Modeling and control of electromechanical systems

The material presented in the these notes covers the sessions Modelling of electromechanical systems, Passive control theory I and Passive control theory II of the II EURON/GEOPLEX Summer School on Modelling and Control of Complex Dynamical Systems.We start with a general description of what an electromechanical system is from a network modelling point of view. Next, a general formulation in terms of PHDS is introduced, and some of the previous electromechanical systems are rewritten in this formalism. Power converters, which are variable structure systems (VSS), can also be given a PHDS form.We conclude the modelling part of these lectures with a rather complex example, showing the interconnection of subsystems from several domains, namely an arrangement to temporally store the surplus energy in a section of a metropolitan transportation system based on dc motor vehicles, using either arrays of supercapacitors or an electric poweredflywheel. The second part of the lectures addresses control of PHD systems. We first present the idea of control as power connection of a plant and a controller. Next we discuss how to circumvent this obstacle and present the basic ideas of Interconnection and Damping Assignment (IDA) passivity-based control of PHD systems.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.

Modeling and Simulation ofReal-Time System as a Tool to Improve Capacity Management - Case Fenix

Tämän tutkimustyön kohteena on TietoEnator Oy:n kehittämän Fenix-tietojärjestelmän kapasiteettitarpeen ennustaminen. Työn tavoitteena on tutustua Fenix-järjestelmän eri osa-alueisiin, löytää tapa eritellä ja mallintaa eri osa-alueiden vaikutus järjestelmän kuormitukseen ja selvittää alustavasti mitkä parametrit vaikuttavat kyseisten osa-alueiden luomaan kuormitukseen. Osa tätä työtä on tutkia eri vaihtoehtoja simuloinnille ja selvittää eri vaihtoehtojen soveltuvuus monimutkaisten järjestelmien mallintamiseen. Kerätyn tiedon pohjaltaluodaan järjestelmäntietovaraston kuormitusta kuvaava simulaatiomalli. Hyödyntämällä mallista saatua tietoa ja tuotantojärjestelmästä mitattua tietoa mallia kehitetään vastaamaan yhä lähemmin todellisen järjestelmän toimintaa. Mallista tarkastellaan esimerkiksi simuloitua järjestelmäkuormaa ja jonojen käyttäytymistä. Tuotantojärjestelmästä mitataan eri kuormalähteiden käytösmuutoksia esimerkiksi käyttäjämäärän ja kellonajan suhteessa. Tämän työn tulosten on tarkoitus toimia pohjana myöhemmin tehtävälle jatkotutkimukselle, jossa osa-alueiden parametrisointia tarkennetaan lisää, mallin kykyä kuvata todellista järjestelmää tehostetaanja mallin laajuutta kasvatetaan.

Utilization of Knowledge Management in Business Process Modeling and Process Improvements

Tutkimuksen tavoitteena on tutkia telekommunikaatioalalla toimivan kohdeyrityksen ohjelmistojen toimitusprosessia° Tutkimus keskittyy mallintamaan toimitusprosessin, määrittelemään roolit ja vastuualueet, havaitsemaan ongelmakohdat ja ehdottamaan prosessille kehityskohteita. Näitä tavoitteita tarkastellaan teoreettisten prosessimallinnustekniikoiden ja tietojohtamisen SECI-prosessikehyksen läpi. Tärkein tiedonkeruun lähde oli haastatteluihin perustuva tutkimus, johon osallistuvat kaikki kohdeprosessiin kuuluvat yksiköt. Mallinnettu toimitusprosessi antoi kohdeyritykselle paremman käsityksen tarkasteltavasta prosessista ja siinä toimivien yksiköiden rooleistaja vastuualueista. Parannusehdotuksia olivat tiedonjaon kanavoinnin määritteleminen, luottamuksen ja sosiaalisten verkostojen parantaminen, ja tietojohtamisen laajamittainen implementointi.

Modeling and Synthesis of Tracking Control for the Belt Drive System

Usingof belt for high precision applications has become appropriate because of the rapid development in motor and drive technology as well as the implementation of timing belts in servo systems. Belt drive systems provide highspeed and acceleration, accurate and repeatable motion with high efficiency, long stroke lengths and low cost. Modeling of a linear belt-drive system and designing its position control are examined in this work. Friction phenomena and position dependent elasticity of the belt are analyzed. Computer simulated results show that the developed model is adequate. The PID control for accurate tracking control and accurate position control is designed and applied to the real test setup. Both the simulation and the experimental results demonstrate that the designed controller meets the specified performance specifications.

Modeling and measuring organizational renewal capability

Globalization and new information technologies mean that organizations have to face world-wide competition in rapidly transforming, unpredictable environments, and thus the ability to constantly generate novel and improved products, services and processes has become quintessential for organizational success. Performance in turbulent environments is, above all, influenced by the organization's capability for renewal. Renewal capability consists of the ability of the organization to replicate, adapt, develop and change its assets, capabilities and strategies. An organization with a high renewal capability can sustain its current success factors while at the same time building new strengths for the future. This capability does not only mean that the organization is able to respond to today's challenges and to keep up with the changes in its environment, but also that it can actas a forerunner by creating innovations, both at the tactical and strategic levels of operation and thereby change the rules of the market. However, even though it is widely agreed that the dynamic capability for continuous learning, development and renewal is a major source of competitive advantage, there is no widely shared view on how organizational renewal capability should be defined, and the field is characterized by a plethora of concepts and definitions. Furthermore,there is a lack of methods for systematically assessing organizational renewal capability. The dissertation aims to bridge these gaps in the existing research by constructing an integrative theoretical framework for organizational renewal capability and by presenting a method for modeling and measuring this capability. The viability of the measurement tool is demonstrated in several contexts, andthe framework is also applied to assess renewal in inter-organizational networks. In this dissertation, organizational renewal capability is examined by drawing on three complimentary theoretical perspectives: knowledge management, strategic management and intellectual capital. The knowledge management perspective considers knowledge as inherently social and activity-based, and focuses on the organizational processes associated with its application and development. Within this framework, organizational renewal capability is understood as the capacity for flexible knowledge integration and creation. The strategic management perspective, on the other hand, approaches knowledge in organizations from the standpoint of its implications for the creation of competitive advantage. In this approach, organizational renewal is framed as the dynamic capability of firms. The intellectual capital perspective is focused on exploring how intangible assets can be measured, reported and communicated. From this vantage point, renewal capability is comprehended as the dynamic dimension of intellectual capital, which consists of the capability to maintain, modify and create knowledge assets. Each of the perspectives significantly contributes to the understanding of organizationalrenewal capability, and the integrative approach presented in this dissertationcontributes to the individual perspectives as well as to the understanding of organizational renewal capability as a whole.

Angiogenic activity of breast cancer patients' monocytes reverted by combined use of systems modeling and experimental approaches.

Angiogenesis plays a key role in tumor growth and cancer progression. TIE-2-expressing monocytes (TEM) have been reported to critically account for tumor vascularization and growth in mouse tumor experimental models, but the molecular basis of their pro-angiogenic activity are largely unknown. Moreover, differences in the pro-angiogenic activity between blood circulating and tumor infiltrated TEM in human patients has not been established to date, hindering the identification of specific targets for therapeutic intervention. In this work, we investigated these differences and the phenotypic reversal of breast tumor pro-angiogenic TEM to a weak pro-angiogenic phenotype by combining Boolean modelling and experimental approaches. Firstly, we show that in breast cancer patients the pro-angiogenic activity of TEM increased drastically from blood to tumor, suggesting that the tumor microenvironment shapes the highly pro-angiogenic phenotype of TEM. Secondly, we predicted in silico all minimal perturbations transitioning the highly pro-angiogenic phenotype of tumor TEM to the weak pro-angiogenic phenotype of blood TEM and vice versa. In silico predicted perturbations were validated experimentally using patient TEM. In addition, gene expression profiling of TEM transitioned to a weak pro-angiogenic phenotype confirmed that TEM are plastic cells and can be reverted to immunological potent monocytes. Finally, the relapse-free survival analysis showed a statistically significant difference between patients with tumors with high and low expression values for genes encoding transitioning proteins detected in silico and validated on patient TEM. In conclusion, the inferred TEM regulatory network accurately captured experimental TEM behavior and highlighted crosstalk between specific angiogenic and inflammatory signaling pathways of outstanding importance to control their pro-angiogenic activity. Results showed the successful in vitro reversion of such an activity by perturbation of in silico predicted target genes in tumor derived TEM, and indicated that targeting tumor TEM plasticity may constitute a novel valid therapeutic strategy in breast cancer.

Modeling and manufacturability assessment of bistable quantum-dot cells

We have investigated the behavior of bistable cells made up of four quantum dots and occupied by two electrons, in the presence of realistic confinement potentials produced by depletion gates on top of a GaAs/AlGaAs heterostructure. Such a cell represents the basic building block for logic architectures based on the concept of quantum cellular automata (QCA) and of ground state computation, which have been proposed as an alternative to traditional transistor-based logic circuits. We have focused on the robustness of the operation of such cells with respect to asymmetries derived from fabrication tolerances. We have developed a two-dimensional model for the calculation of the electron density in a driven cell in response to the polarization state of a driver cell. Our method is based on the one-shot configuration-interaction technique, adapted from molecular chemistry. From the results of our simulations, we conclude that an implementation of QCA logic based on simple ¿hole arrays¿ is not feasible, because of the extreme sensitivity to fabrication tolerances. As an alternative, we propose cells defined by multiple gates, where geometrical asymmetries can be compensated for by adjusting the bias voltages. Even though not immediately applicable to the implementation of logic gates and not suitable for large scale integration, the proposed cell layout should allow an experimental demonstration of a chain of QCA cells.

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal