Choosing the target loci : heat shock factors HSF1 and HSF2 as regulators of cell stress and development

Heat shock factors (HSFs) are an evolutionarily well conserved family of transcription factors that coordinate stress-induced gene expression and direct versatile physiological processes in eukaryote organisms. The essentiality of HSFs for cellular homeostasis has been well demonstrated, mainly through HSF1-induced transcription of heat shock protein (HSP) genes. HSFs are important regulators of many fundamental processes such as gametogenesis, metabolic control and aging, and are involved in pathological conditions including cancer progression and neurodegenerative diseases. In each of the HSF-mediated processes, however, the detailed mechanisms of HSF family members and their complete set of target genes have remained unknown. Recently, rapid advances in chromatin studies have enabled genome-wide characterization of protein binding sites in a high resolution and in an unbiased manner. In this PhD thesis, these novel methods that base on chromatin immunoprecipitation (ChIP) are utilized and the genome-wide target loci for HSF1 and HSF2 are identified in cellular stress responses and in developmental processes. The thesis and its original publications characterize the individual and shared target genes of HSF1 and HSF2, describe HSF1 as a potent transactivator, and discover HSF2 as an epigenetic regulator that coordinates gene expression throughout the cell cycle progression. In male gametogenesis, novel physiological functions for HSF1 and HSF2 are revealed and HSFs are demonstrated to control the expression of X- and Y-chromosomal multicopy genes in a silenced chromatin environment. In stressed human cells, HSF1 and HSF2 are shown to coordinate the expression of a wide variety of genes including genes for chaperone machinery, ubiquitin, regulators of cell cycle progression and signaling. These results highlight the importance of cell type and cell cycle phase in transcriptional responses, reveal the myriad of processes that are adjusted in a stressed cell and describe novel mechanisms that maintain transcriptional memory in mitotic cell division.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Development of an HTR-10 model in the Serpent reactor physics code

The use of exact coordinates of pebbles and fuel particles of pebble bed reactor modelling becoming possible in Monte Carlo reactor physics calculations is an important development step. This allows exact modelling of pebble bed reactors with realistic pebble beds without the placing of pebbles in regular lattices. In this study the multiplication coefficient of the HTR-10 pebble bed reactor is calculated with the Serpent reactor physics code and, using this multiplication coefficient, the amount of pebbles required for the critical load of the reactor. The multiplication coefficient is calculated using pebble beds produced with the discrete element method and three different material libraries in order to compare the results. The received results are lower than those from measured at the experimental reactor and somewhat lower than those gained with other codes in earlier studies.

Palvelutuotteiden strateginen johtaminen suunnitteluliiketoiminnassa

Tutkimuksen tarkoituksena oli löytää suunnitteluliiketoiminnan palvelutuotteiden strategisen johdon käyttöön soveltuva menetelmä, tai työkalu, jonka avulla palvelutuotteiden kilpailukykyä ja kehitystarpeita voidaan helposti arvioida. Diplomityö pitää sisällään kolme tutkimuskysymystä. Ensimmäisellä tutkimuskysymyksellä pyritään keräämään tietoa suunnitteluorganisaation taustalla vaikuttavista menestystekijöistä. Toisen tutkimuskysymyksen avulla pyrittiin löytämään työkalu, tai menetelmä, palvelutuotteiden strategisen johdon käyttöön, tai sellaisen muodostamisen pohjaksi. Kolmas tutkimuskysymys liittyi suunnittelupalveluiden strategisen johtamisen työkalun muodostamiseen. Tutkimuksen tuloksena tuotettiin suunnitteluorganisaation palvelutuotteiden johtamisen viitekehys. Viitekehyksessä palvelutuotteet lajitellaan havainnolliselle luokittelutaululle, jossa pystykoordinaattina käytetään palvelutuotteen markkinoiden houkuttelevuutta ja vaakakoordinaattina palvelutuotteen vahvuutta organisaatiossa. Tutkimuksessa on esitetty suunnitteluliiketoiminnan strategisen johtamisen onnistumisessa vaikuttavat taustatekijät, markkinoiden houkuttelevuuden keskeisimmät mittarit, sekä suunnittelupalveluiden vahvuutta kuvaavat tekijät.

Real-time simulation of multibody systems with applications for working mobile vehicles

This dissertation describes an approach for developing a real-time simulation for working mobile vehicles based on multibody modeling. The use of multibody modeling allows comprehensive description of the constrained motion of the mechanical systems involved and permits real-time solving of the equations of motion. By carefully selecting the multibody formulation method to be used, it is possible to increase the accuracy of the multibody model while at the same time solving equations of motion in real-time. In this study, a multibody procedure based on semi-recursive and augmented Lagrangian methods for real-time dynamic simulation application is studied in detail. In the semirecursive approach, a velocity transformation matrix is introduced to describe the dependent coordinates into relative (joint) coordinates, which reduces the size of the generalized coordinates. The augmented Lagrangian method is based on usage of global coordinates and, in that method, constraints are accounted using an iterative process. A multibody system can be modelled as either rigid or flexible bodies. When using flexible bodies, the system can be described using a floating frame of reference formulation. In this method, the deformation mode needed can be obtained from the finite element model. As the finite element model typically involves large number of degrees of freedom, reduced number of deformation modes can be obtained by employing model order reduction method such as Guyan reduction, Craig-Bampton method and Krylov subspace as shown in this study The constrained motion of the working mobile vehicles is actuated by the force from the hydraulic actuator. In this study, the hydraulic system is modeled using lumped fluid theory, in which the hydraulic circuit is divided into volumes. In this approach, the pressure wave propagation in the hoses and pipes is neglected. The contact modeling is divided into two stages: contact detection and contact response. Contact detection determines when and where the contact occurs, and contact response provides the force acting at the collision point. The friction between tire and ground is modelled using the LuGre friction model, which describes the frictional force between two surfaces. Typically, the equations of motion are solved in the full matrices format, where the sparsity of the matrices is not considered. Increasing the number of bodies and constraint equations leads to the system matrices becoming large and sparse in structure. To increase the computational efficiency, a technique for solution of sparse matrices is proposed in this dissertation and its implementation demonstrated. To assess the computing efficiency, augmented Lagrangian and semi-recursive methods are implemented employing a sparse matrix technique. From the numerical example, the results show that the proposed approach is applicable and produced appropriate results within the real-time period.