Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

Differential Regulation of c-FLIP Isoforms Through Post-translational Modifications

Cells are constantly responding to signals from the surrounding tissues and the environment. To dispose of infected and potentially dangerous cells, to ensure the optimal execution of developmental processes and to maintain tissue homeostasis, a multicellular organism needs to tightly control both the number and the quality of its cells. Apoptosis is a form of active cellular self-destruction that enables an organism to regulate its cell number by deleting damaged or potentially dangerous cells. Apoptosis can be induced by death ligands, which bind to death receptors on the cell surface. Ligation of the receptors leads to the formation of an intracellular death inducing signaling complex (DISC). One of the DISC components is caspase-8, a protease that triggers the caspase cascade and is thereby a key initiator of programmed cell death. The activation of caspase-8 is controlled by the cellular FLICE-inhibitory proteins (c-FLIPs). Consequently, sensitivity towards receptor-mediated apoptosis is determined by the amount of c-FLIP, and the c-FLIP levels are actively regulated for example during erythroid differentiation of K562 erythroleukemia cells and by hyperthermia in Jurkat leukemia cells. The aim of my thesis was to investigate how c-FLIP is regulated during these processes. We found that c-FLIP isoforms are short-lived proteins, although c-FLIPS had an even shorter half-life than c-FLIPL. In both experimental models, increased death receptor sensitivity correlated with induced ubiquitylation and consequent proteasomal degradation of c-FLIP. Furthermore, we elucidated how phosphorylation regulates the biological functions and the turnover of c-FLIP, thereby contributing to death receptor sensitivity. We mapped the first phosphorylation sites on c-FLIP and dissected how their phosphorylation affects c-FLIP. Moreover, we demonstrated that phosphorylation of serine 193, a phosphorylated residue common to all c-FLIPs, is primarily mediated by the classical PKC. Furthermore, we discovered a novel connection between the phosphorylation and ubiquitylation of c-FLIP: phosphorylation of S193 protects c-FLIP from ubiquitylation. Surprisingly, although all c-FLIP isoforms are phosphorylated on this conserved residue, the biological outcome is different for the long and short isoforms, since S193 specifically prolongs the half-lives of the short c-FLIP isoforms, but not c-FLIPL. To summarize, we show that c-FLIP proteins are modified by ubiquitylation and phosphorylation, and that the biological outcomes of these modifications are isoform-specifically determined.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Assessment of Coals from Russia and Countries of Former Soviet Union for Utility Fluidized Bed Boilers

With the occurrence of fossil fuels such as oil, gas and coal we found new sources of energy that have played a critical role in the progress of our modern society. Coal is very ample compared to the other two fossil fuels. Global coal reserves at the end of 2005 were estimated at 847,5 billion tones. Along with the major energy sources, coal is the most fast growing fuel on a global basis, it provides 26% of primary energy needs and remains essential to the economies of many developed and developing countries. Coal-fired power generation accounts for 41% of the world‘s total electricity production and in some countries, such as South Africa, Poland, China, Australia, Kazakhstan and India is on very high level. Still, coal utilization represents challenges related to high emissions of air pollutants such as sulphur and nitrogen dioxides, particulate matter, mercury and carbon dioxide. In relation to these a number of technologies have been developed and are in marketable use, with further potential developments towards ―Near Zero Emission‖ coal plants. In present work, coals mined in Russia and countries of Former Soviet Union were reviewed. Distribution of coal reserves on the territory of Russia and the potential for power generation from coal-fired plants across Russia was shown. Physical and chemical properties of coals produced were listed and examined, as main factor influencing on design of the combustion facility and incineration process performance. The ash-related problems in coal-fired boilers were described. The analysis of coal ash of Russia and countries of Former Soviet Union were prepared. Feasible combustion technologies also were reviewed.

Boundary identification in the domain of a parabolic partial differential equation

Bakgrunden och inspirationen till föreliggande studie är tidigare forskning i tillämpningar på randidentifiering i metallindustrin. Effektiv randidentifiering möjliggör mindre säkerhetsmarginaler och längre serviceintervall för apparaturen i industriella högtemperaturprocesser, utan ökad risk för materielhaverier. I idealfallet vore en metod för randidentifiering baserad på uppföljning av någon indirekt variabel som kan mätas rutinmässigt eller till en ringa kostnad. En dylik variabel för smältugnar är temperaturen i olika positioner i väggen. Denna kan utnyttjas som insignal till en randidentifieringsmetod för att övervaka ugnens väggtjocklek. Vi ger en bakgrund och motivering till valet av den geometriskt endimensionella dynamiska modellen för randidentifiering, som diskuteras i arbetets senare del, framom en flerdimensionell geometrisk beskrivning. I de aktuella industriella tillämpningarna är dynamiken samt fördelarna med en enkel modellstruktur viktigare än exakt geometrisk beskrivning. Lösningsmetoder för den s.k. sidledes värmeledningsekvationen har många saker gemensamt med randidentifiering. Därför studerar vi egenskaper hos lösningarna till denna ekvation, inverkan av mätfel och något som brukar kallas förorening av mätbrus, regularisering och allmännare följder av icke-välställdheten hos sidledes värmeledningsekvationen. Vi studerar en uppsättning av tre olika metoder för randidentifiering, av vilka de två första är utvecklade från en strikt matematisk och den tredje från en mera tillämpad utgångspunkt. Metoderna har olika egenskaper med specifika fördelar och nackdelar. De rent matematiskt baserade metoderna karakteriseras av god noggrannhet och låg numerisk kostnad, dock till priset av låg flexibilitet i formuleringen av den modellbeskrivande partiella differentialekvationen. Den tredje, mera tillämpade, metoden kännetecknas av en sämre noggrannhet förorsakad av en högre grad av icke-välställdhet hos den mera flexibla modellen. För denna gjordes även en ansats till feluppskattning, som senare kunde observeras överensstämma med praktiska beräkningar med metoden. Studien kan anses vara en god startpunkt och matematisk bas för utveckling av industriella tillämpningar av randidentifiering, speciellt mot hantering av olinjära och diskontinuerliga materialegenskaper och plötsliga förändringar orsakade av “nedfallande” väggmaterial. Med de behandlade metoderna förefaller det möjligt att uppnå en robust, snabb och tillräckligt noggrann metod av begränsad komplexitet för randidentifiering.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Stochastic variability of output levels in a pulp mill

Quite often, in the construction of a pulp mill involves establishing the size of tanks which will accommodate the material from the various processes in which case estimating the right tank size a priori would be vital. Hence, simulation of the whole production process would be worthwhile. Therefore, there is need to develop mathematical models that would mimic the behavior of the output from the various production units of the pulp mill to work as simulators. Markov chain models, Autoregressive moving average (ARMA) model, Mean reversion models with ensemble interaction together with Markov regime switching models are proposed for that purpose.

Molecular diagnostics of rare inherited SYNDROMES with a view on diagnostic test development

CHARGE syndrome, Sotos syndrome and 3p deletion syndrome are examples of rare inherited syndromes that have been recognized for decades but for which the molecular diagnostics only have been made possible by recent advances in genomic research. Despite these advances, development of diagnostic tests for rare syndromes has been hindered by diagnostic laboratories having limited funds for test development, and their prioritization of tests for which a (relatively) high demand can be expected. In this study, the molecular diagnostic tests for CHARGE syndrome and Sotos syndrome were developed, resulting in their successful translation into routine diagnostic testing in the laboratory of Medical Genetics (UTUlab). In the CHARGE syndrome group, mutation was identified in 40.5% of the patients and in the Sotos syndrome group, in 34%, reflecting the use of the tests in routine diagnostics in differential diagnostics. In CHARGE syndrome, the low prevalence of structural aberrations was also confirmed. In 3p deletion syndrome, it was shown that small terminal deletions are not causative for the syndrome, and that testing with arraybased analysis provides a reliable estimate of the deletion size but benign copy number variants complicate result interpretation. During the development of the tests, it was discovered that finding an optimal molecular diagnostic strategy for a given syndrome is always a compromise between the sensitivity, specificity and feasibility of applying a new method. In addition, the clinical utility of the test should be considered prior to test development: sometimes a test performing well in a laboratory has limited utility for the patient, whereas a test performing poorly in the laboratory may have a great impact on the patient and their family. At present, the development of next generation sequencing methods is changing the concept of molecular diagnostics of rare diseases from single tests towards whole-genome analysis.

Early detection of severe sepsis in the emergency room in adults - Clinical utility of prognostic markers

Vaikean sepsiksen varhainen tunnistaminen päivystyspoliklinikalla – merkkiaineiden käyttökelpoisuus aikuispotilaiden arvioinnissa Päivystyspotilaan vakavan yleisinfektion eli sepsiksen varhainen tunnistaminen ja taudin vaikeusasteen arviointi on päivystävälle lääkärille tärkeä haaste. Arvioimme prospektiivisessa kohorttitutkimuksessa eri merkkiaineiden hyödyllisyyttä sepsiksen varhaisessa tunnistamisessa ja vaikeusasteen arvioinnissa. Työssä I ja III oli 539 päivystyspotilasta, joilta kliinikko päätti ottaa veriviljelyn sepsistä epäillen. Tutkimuksessa II oli 525 potilasta ja tutkimuksessa IV 537 potilasta. Tutkimuksessa I plasman C-reaktiivisen proteiinin (CRP) pitoisuuksia verrattiin plasman prokalsitoniinin (PCT) ja interleukiinin (IL-6) pitoisuuksiin. Tutkimuksessa II verrattiin plasman baktersidisen/ permeabiliteettia lisäävän proteiinin (BPI), ryhmän IIA fosfolipaasi A2:n (PLA2GIIA) ja CRP:n pitoisuuksia sekä valkosolujen määriä toisiinsa. Tutkimuksessa III arvioitiin liukoisen urokinaasi-tyyppisen plasminogeenin aktivaattorireseptorin (suPAR) ja tutkimuksessa IV pentraksiini 3:n (PTX3) määrityksen käyttökelpoisuutta. Tutkimuksessa I todettiin päivystystilanteessa mitattujen korkeiden PCT - ja IL-6 - pitoisuuksien ennustavan vaikean sepsiksen kehittymistä paremmin kuin korkean CRP:n. Tutkimuksessa II plasman PLA2GIIA vaikutti hiukan paremmalta vaikean sepsiksen ennustajalta kuin CRP tai veren valkosolutaso, mutta BPI ei ollut hyödyllinen. Tutkimuksessa III korkea plasman suPAR- pitoisuus osoittautui itsenäiseksi kuolleisuuden riskitekijäksi ja se liittyi myös vaikean sepsiksen kehittymiseen. Tutkimuksessa IV korkea PTX3 - pitoisuus toimi samaan tapaan kuin suPAR. Kokonaisuutena PCT osoittautui parhaaksi merkkiaineeksi ennustamaan elinhäiriön kehittymistä ja suPAR kuolleisuutta. PTX3 ei tarjonnut merkittävää lisäetua PCT:iin ja suPAR:iin verrattuna. CRP osoitti suhteellisen hyvin bakteeri-infektion esiintymistä, mutta ennusteellista arvoa sillä ei ollut. suPAR on kiinnostava kuolleisuuden ja elinhäiriön kehittymisen merkkiaine.