Novel technology for preparation of optically active chemicals

Asymmetric synthesis using modified heterogeneous catalysts has gained lots of interest in the production of optically pure chemicals, such as pharmaceuticals, nutraceuticals, fragrances and agrochemicals. Heterogeneous modified catalysts capable of inducing high enantioselectivities are preferred in industrial scale due to their superior separation and handling properties. The topic has been intensively investigated both in industry and academia. The enantioselective hydrogenation of ethyl benzoylformate (EBF) to (R)-ethyl mandelate over (-)-cinchonidine (CD)-modified Pt/Al2O3 catalyst in a laboratory-scale semi-batch reactor was studied as a function of modifier concentration, reaction temperature, stirring rate and catalyst particle size. The main product was always (R)-ethyl mandelate while small amounts of (S)-ethyl mandelate were obtained as by product. The kinetic results showed higher enantioselectivity and lower initial rates approaching asymptotically to a constant value as the amount of modifier was increased. Additionally, catalyst deactivation due to presence of impurities in the feed was prominent in some cases; therefore activated carbon was used as a cleaning agent of the raw material to remove impurities prior to catalyst addition. Detailed characterizations methods (SEM, EDX, TPR, BET, chemisorption, particle size distribution) of the catalysts were carried out. Solvent effects were also studied in the semi-batch reactor. Solvents with dielectric constant (e) between 2 and 25 were applied. The enantiomeric excess (ee) increased with an increase of the dielectric coefficient up to a maximum followed by a nonlinear decrease. A kinetic model was proposed for the enantioselectivity dependence on the dielectric constant based on the Kirkwood treatment. The non-linear dependence of ee on (e) successfully described the variation of ee in different solvents. Systematic kinetic experiments were carried out in the semi-batch reactor. Toluene was used as a solvent. Based on these results, a kinetic model based on the assumption of different number of sites was developed. Density functional theory calculations were applied to study the energetics of the EBF adsorption on pure Pt(1 1 1). The hydrogenation rate constants were determined along with the adsorption parameters by non-linear regression analysis. A comparison between the model and the experimental data revealed a very good correspondence. Transient experiments in a fixed-bed reactor were also carried out in this work. The results demonstrated that continuous enantioselective hydrogenation of EBF in hexane/2-propanol 90/10 (v/v) is possible and that continuous feeding of (-)-cinchonidine is needed to maintain a high steady-state enantioselectivity. The catalyst showed a good stability and high enantioselectivity was achieved in the fixed-bed reactor. Chromatographic separation of (R)- and (S)-ethyl mandelate originating from the continuous reactor was investigated. A commercial column filled with a chiral resin was chosen as a perspective preparative-scale adsorbent. Since the adsorption equilibrium isotherms were linear within the entire investigated range of concentrations, they were determined by pulse experiments for the isomers present in a post-reaction mixture. Breakthrough curves were measured and described successfully by the dispersive plug flow model with a linear driving force approximation. The focus of this research project was the development of a new integrated production concept of optically active chemicals by combining heterogeneous catalysis and chromatographic separation technology. The proposed work is fundamental research in advanced process technology aiming to improve efficiency and enable clean and environmentally benign production of enantiomeric pure chemicals.

Development of agnostic mobile applications with cross-platform cloud computing platforms

Smart phones became part and parcel of our life, where mobility provides a freedom of not being bounded by time and space. In addition, number of smartphones produced each year is skyrocketing. However, this also created discrepancies or fragmentation among devices and OSes, which in turn made an exceeding hard for developers to deliver hundreds of similar featured applications with various versions for the market consumption. This thesis is an attempt to investigate whether cloud based mobile development platforms can mitigate and eventually eliminate fragmentation challenges. During this research, we have selected and analyzed the most popular cloud based development platforms and tested integrated cloud features. This research showed that cloud based mobile development platforms may able to reduce mobile fragmentation and enable to utilize single codebase to deliver a mobile application for different platforms.

Decision making and decision support in service systems

This thesis is a literature study that develops a conceptual model of decision making and decision support in service systems. The study is related to the Ä-Logi, Intelligent Service Logic for Welfare Sector Services research project, and the objective of the study is to develop the necessary theoretical framework to enable further research based on the research project results and material. The study first examines the concepts of service and service systems, focusing on understanding the characteristics of service systems and their implications for decision making and decision support to provide the basis for the development of the conceptual model. Based on the identified service system characteristics, an integrated model of service systems is proposed that views service systems through a number of interrelated perspectives that each offer different, but complementary, implications on the nature of decision making and the requirements for decision support in service systems. Based on the model, it is proposed that different types of decision making contexts can be identified in service systems that may be dominated by different types of decision making processes and where different types of decision support may be required, depending on the characteristics of the decision making context and its decision making processes. The proposed conceptual model of decision making and decision support in service systems examines the characteristics of decision making contexts and processes in service systems, and their typical requirements for decision support. First, a characterization of different types of decision making contexts in service systems is proposed based on the Cynefin framework and the identified service system characteristics. Second, the nature of decision making processes in service systems is proposed to be dual, with both rational and naturalistic decision making processes existing in service systems, and having an important and complementary role in decision making in service systems. Finally, a characterization of typical requirements for decision support in service systems is proposed that examines the decision support requirements associated with different types of decision making processes in characteristically different types of decision making contexts. It is proposed that decision support for the decision making processes that are based on rational decision making can be based on organizational decision support models, while decision support for the decision making processes that are based on naturalistic decision making should be based on supporting the decision makers’ situation awareness and facilitating the development of their tacit knowledge of the system and its tasks. Based on the proposed conceptual model a further research process is proposed. The study additionally provides a number of new perspectives on the characteristics of service systems, and the nature of decision making and requirements for decision support in service systems that can potentially provide a basis for further discussion and research, and support the practice alike.

Mathematical modeling and optimal control of malaria

Malaria continues to infect millions and kill hundreds of thousands of people worldwide each year, despite over a century of research and attempts to control and eliminate this infectious disease. Challenges such as the development and spread of drug resistant malaria parasites, insecticide resistance to mosquitoes, climate change, the presence of individuals with subpatent malaria infections which normally are asymptomatic and behavioral plasticity in the mosquito hinder the prospects of malaria control and elimination. In this thesis, mathematical models of malaria transmission and control that address the role of drug resistance, immunity, iron supplementation and anemia, immigration and visitation, and the presence of asymptomatic carriers in malaria transmission are developed. A within-host mathematical model of severe Plasmodium falciparum malaria is also developed. First, a deterministic mathematical model for transmission of antimalarial drug resistance parasites with superinfection is developed and analyzed. The possibility of increase in the risk of superinfection due to iron supplementation and fortification in malaria endemic areas is discussed. The model results calls upon stakeholders to weigh the pros and cons of iron supplementation to individuals living in malaria endemic regions. Second, a deterministic model of transmission of drug resistant malaria parasites, including the inflow of infective immigrants, is presented and analyzed. The optimal control theory is applied to this model to study the impact of various malaria and vector control strategies, such as screening of immigrants, treatment of drug-sensitive infections, treatment of drug-resistant infections, and the use of insecticide-treated bed nets and indoor spraying of mosquitoes. The results of the model emphasize the importance of using a combination of all four controls tools for effective malaria intervention. Next, a two-age-class mathematical model for malaria transmission with asymptomatic carriers is developed and analyzed. In development of this model, four possible control measures are analyzed: the use of long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic, and screening and treatment of asymptomatic individuals. The numerical results show that a disease-free equilibrium can be attained if all four control measures are used. A common pitfall for most epidemiological models is the absence of real data; model-based conclusions have to be drawn based on uncertain parameter values. In this thesis, an approach to study the robustness of optimal control solutions under such parameter uncertainty is presented. Numerical analysis of the optimal control problem in the presence of parameter uncertainty demonstrate the robustness of the optimal control approach that: when a comprehensive control strategy is used the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the design of cost-effective strategies for disease control with multiple interventions, even under considerable uncertainty of model parameters. Finally, a separate work modeling the within-host Plasmodium falciparum infection in humans is presented. The developed model allows re-infection of already-infected red blood cells. The model hypothesizes that in severe malaria due to parasite quest for survival and rapid multiplication, the Plasmodium falciparum can be absorbed in the already-infected red blood cells which accelerates the rupture rate and consequently cause anemia. Analysis of the model and parameter identifiability using Markov chain Monte Carlo methods is presented.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Active Magnetic Bearing System Identification Methods and Rotor Model Updating

Active magnetic bearing is a type of bearing which uses magnetic field to levitate the rotor. These bearings require continuous control of the currents in electromagnets and data from position of the rotor and the measured current from electromagnets. Because of this different identification methods can be implemented with no additional hardware. In this thesis the focus was to implement and test identification methods for active magnetic bearing system and to update the rotor model. Magnetic center calibration is a method used to locate the magnetic center of the rotor. Rotor model identification is an identification method used to identify the rotor model. Rotor model update is a method used to update the rotor model based on identification data. These methods were implemented and tested with a real machine where rotor was levitated with active magnetic bearings and the functionality of the methods was ensured. Methods were developed with further extension in mind and also with the possibility to apply them for different machines with ease.

Toimintokohtainen kustannuslaskenta muovialan teollisuusyrityksessä

Jatkuva teknologioiden kehittyminen ja globaalin talousjärjestelmän lainalaisuudet pakottavat yrityksiä kiinnittämään enenevässä määrin huomiota kilpailukykyyn ja kannattavuuteen. Kustannuslaskennan tarkkuus on yksi tärkeimmistä taloushallinnon elementeistä kilpailukyvyn ylläpitämisessä. Virheisiin ei ole varaa, sillä väärin perustein tehdyt kustannuslaskennat ajavat yrityksen nopeasti taloudellisiin vaikeuksiin. Tässä tutkimuksessa oli tavoitteena etsiä teollisen muovialan yrityksen tarpeisiin parhaiten sopiva kustannuslaskentajärjestelmä. Tutkimuksen teoriaosassa tutustuttiin eri kustannuslaskentamenetelmiin, ja tarkemmin toimintolaskennan yksinkertaisempaan muotoon, aikaperusteiseen toimintolaskentaan, sen toimivuuden ja käytettävyyden kannalta. Tutkimus toteutettiin konstruktiivisena case -tutkimuksena, jossa pyrittiin kuvaamaan ja havainnollistamaan uusi laskentamalli eli konstruktio. Tutkimuksen empiirisessä osuudessa suoritettiin esimerkkilaskelmia case yrityksen valmistamalle tuoteryhmälle ja vertailtiin laskelman tuloksia nykyiseen laskentamalliin. Saatujen tietojen pohjalta yritys pystyy muokkaamaan hinnoittelua vastaamaan kannattavuustavoitteita ja parantamaan kilpailukykyään, sillä malli tuottaa tarkempaa tietoa kustannuksista ja asiakaskohtaisista kannattavuuksista.

Palveluruokamarkkinoiden innovatiivisen toimintamallin suunnittelu

Diplomityön tavoitteena on ollut kehittää elintarvikeyrityksen palveluruokamarkkinoille uusi innovatiivinen toimintamalli haastattelujen, havainnoinnin ja kirjallisuuden perusteella. Tutkimusongelman päätutkimuskysymys on: Miten yrityksen palveluruoka- eli valmisruokatuotteille suunnitellaan innovatiivinen toimintamalli tuoteperheen ja jakelun suhteen? Tavoitteena on kartoittaa yrityksen palveluruoan nykytilanne ja luoda toimintamalli, joka toisi yritykselle selkeää lisäarvoa ja kilpailuetua. Teoreettisessa osuudessa selvitetään elintarviketeollisuuden, valmisruoan ja elintarvikelogistiikan tilannetta suomalaisesta ja globaalista näkökulmasta. Työssä on tarkasteltu elintarvikepuolen nykytilannetta ja tulevaisuuden suuntauksia tuotteiden, ruokailutottumusten ja logistiikan osalta. Innovaatioiden osalta työ painottuu palveluruokapuolen konseptin ja uuden logistisen yhteistyöhön pohjautuvan mallin kehittämiseen. Työn käytännön osiossa on tehty case-tutkimus ”yrityksen palveluruoan nykytilanne tuotteiden ja logistiikan osalta”. Toimialan markkinatilannetta on kartoitettu, jotta hahmotetaan, missä on potentiaalisimmat markkinat palveluruoalle. Työn tavoitteena on ollut kehittää Hoviruoka Oy:lle palveluruoan segmentointiin ja logistiikkaan liittyvä innovatiivinen toimintamalli. Toimintamallin avulla yritys saa kilpailuetua ja taloudellista hyötyä kilpailijoihin nähden, ja on edelläkävijä kyseisen toimintamallin ansiosta. Työn tuloksissa on käsitelty keskeiset tulokset ja mahdolliset jatkotoimenpiteet. Työssä kehitettiin yritykselle uusi toimintamalli palveluruoka puolelle. Työlle asetetut tavoitteet saavutettiin kaikkien kolmen - tekijän, yliopiston ja yrityksen - kannalta.

Online MBPeT dashboard : enabling performance testing as a service in the cloud

In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.