ANION-BINDING AND SENSING PROPERTIES OF NOVEL RECEPTORS BASED ON N-(INDOL-3-YLGLYOXYLYL)BENZYLAMINE

Indole-based receptors such as biindole, carbazole, and indolocarbazole are regarded as some of the most favorable anion receptors in molecular recognition. This is because indole groups possess N–H groups as hydrogen-bonding donors. The introduction of amide groups in the indole framework can induce strong binding properties and good water solubility. In this study, we designed and synthesized a series of N-(indol-3-ylglyoxylyl)benzylamine derivatives as novel and simple anion receptors. The receptors derived by aryl and aliphatic amines can selectively recognize F– based on a color change from colorless-to-yellow in DMSO. The receptors derived by hydrazine hydrate can recognize F–, AcO–, and H2PO4– by similar color changes in DMSO and can even enable the selective recognition of F– in a DMSO–H2O binary solution by the naked eye. Spectrographic data indicate that complexes are formed between receptors and anions through multiple hydrogen-bonding interactions in dual solutions.

Identification of Races of Selected Isolates of Uromyces appendiculatus from Minas Gerais (Brazil) Based on the new international classification system

Twelve single-pustule isolates of Uromyces appendiculatus, the etiological agent of common bean rust, were collected in the state of Minas Gerais, Brazil, and classified according to the new international differential series and the binary nomenclature system proposed during the 3rd Bean Rust Workshop. These isolates have been used to select rust-resistant genotypes in a bean breeding program conducted by our group. The twelve isolates were classified into seven different physiological races: 21-3, 29-3, 53-3, 53-19, 61-3, 63-3 and 63-19. Races 61-3 and 63-3 were the most frequent in the area. They were represented by five and two isolates, respectively. The other races were represented by just one isolate. This is the first time the new international classification procedure has been used for U. appendiculatus physiological races in Brazil. The general adoption of this system will facilitate information exchange, allowing the cooperative use of the results obtained by different research groups throughout the world. The differential cultivars Mexico 309, Mexico 235 and PI 181996 showed resistance to all of the isolates that were characterized. It is suggested that these cultivars should be preferentially used as sources for resistance to rust in breeding programs targeting development lines adapted to the state of Minas Gerais.

Tutkimus- ja kehitysvaiheen toteuttaminen teknologisessa innovaatioprosessissa

Through the ages technological changes have created new challenges and possibilities to develop products, services, processes or organizations. Management of the technology concerns all of those activities from technical invention to commercial application. Management of the technologic innovation process is the more challenging the more technology is involved in a process. Researches of the technological innovations are seldom concern the implementation of early phases and especially in product manufacturing company. Still there are research and development activities. Therefore the purpose of this research is to develop the pattern for implementation of research and development phases in technological innovation process. This study focuses the main elements of the technological innovation management and main obstacles and drivers. This study also focuses decision making and the other influencing elements of the decision making. The research design of this explorative research applies a qualitative research strategy where a case study method is utilized to collect and analyze the data. The study consisted of a single case to utilize of technological ideas and possibilities. The selected case company was the product manufacturing company which didn’t have own technological research and development organization. The case was a process which was analyzed from two different perspectives. The main unit of analysis was the whole process. The data collecting method of this study included semi-structured and open interviews, participant-observations and experimental tests. Analyzing the case data relies on the theoretical propositions of the framework based on the previous research. Based on this research the key elements of the research and development phases in technological innovation process were technical expertise and preliminary investigation. The obstacles and drivers in the R&D phases by the case were management of the whole process and resources and knowing objectives of process and learning during the process. In addition to the result of the research was the feature of decision making to optimize used time. The findings of this study gave further insight implementation of the technological innovation in the product manufacturing company. The research was based a single case which means the results cannot be generalized to different companies or industry fields. Therefore the results generalizing require further research with multiple researchers.

Tutkimus- ja kehitysvaiheen toteuttaminen teknologisessa innovaatioprosessissa

Teknologiset muutokset ovat kautta aikojen luoneet uusia haasteita ja mahdollisuuksia tuotteiden, palveluiden, prosessien tai organisaatioiden kehittämiseen. Teknologian johtaminen tarkoittaa kaikki niitä toimia, joiden avulla teknologisesta keksinnöstä saadaan kaupallinen sovellus. Teknologisen innovaatioprosessin johtaminen on, sitä haasteellisempaa, mitä enemmän siinä on mukana teknologiaa. Harvoin teknologisten innovaatioiden tutkimukset ovat kohdistuneet prosessin varhaisen vaiheen toteutukseen ja erityisesti tuotannolliseen toimintaan keskittyvissä yrityksissä, vaikka kaikissa tuotteita valmistavissa teollisuuksissa tapahtuu tutkimus- ja kehitystyötä. Siksi tämän tutkimuksen tavoitteena on kehittää toimintamalli teknologisen innovaatioprosessin tutkimus- ja kehitysvaiheen toteuttamiselle. Tutkimus keskittyy teknologisen innovaatioprosessin tärkeimpiin elementteihin johtamisen ja prosessin kannalta sekä sen estäviin ja edistäviin tekijöihin. Tutkimuksessa tarkastellaan myös päätöksentekoa ja siihen vaikuttavia tekijöitä. Tutkimus oli kartoittava ja sillä oli laadullinen tutkimusstrategia. Tarkempi tutkimusmenetelmä kerätä ja analysoida tutkimustietoa oli tapaustutkimus. Tämä tutkimus perustui yhteen tapaukseen teknologisten ideoiden ja mahdollisuuksien hyödyntämisestä. Valittu tapausyritys oli tuotteita valmistava yritys, jolla ei ollut varsinaista tutkimus- ja kehitysorganisaatiota teknologian kehittämistä varten. Itse tapaus oli prosessi, jota analysoitiin kahdesta eri näkökulmasta, mutta primääri analysointiyksikkö oli koko prosessi. Aineiston hankintamenetelmät olivat puolistrukturoidut ja avoimet haastattelut, osallistuva havainnointi ja kokeelliset tutkimukset. Aineiston analysointi perustui aikaisemmin tutkimuksen yhteydessä rakennettuun teoreettiseen viitekehykseen. Teknologisen innovaatioprosessin tutkimus- ja kehitysvaiheen tärkeimmät elementit tutkimuksen mukaan olivat oman teknologian asiantuntemus ja esitutkimusvaihe. Tekijät, jotka tutkimuksen mukaan estivät ja edistivät T&K -vaiheen onnistumista, olivat koko prosessin ja resurssien johtaminen sekä tietoisuus prosessin tavoitteista ja prosessin aikainen oppiminen. Tutkimuksessa löydettiin myös päätöksentekoon liittyvä ominaisuus optimoida siihen käytettävää aikaa. Tutkimuksen tulokset lisäsivät näkemystä teknologisten innovaatioiden toteuttamisesta tuotteita valmistavassa yrityksessä. Tutkimus perustui yhteen tapaukseen, minkä vuoksi tulokset eivät ole yleistettävissä muihin yrityksiin tai toimialoihin. Tulosten yleistämistä varten tutkimuksia tulisi suorittaa lisää ja käyttää useita tutkijoita.

Terveyskaupan erikoisliikkeen menestystarina: strategia ja houkuttelevuus yritysostajan perspektiivistä

Tutkielman tavoitteena on tiivistetysti edesauttaa Lappeenrannan Lifeterveyskaupan yritysmyyntiprosessia kuvailemalla kohdeyrityksen strategiaa, menestystekijöitä ja houkuttelevuutta yritysostajan näkökulma huomioiden siten, että niiden hahmottaminen ja omaksuminen helpottuu yritysostajalle. Tutkielman sisältöä voidaan hyödyntää yritysmyyntiprosessissa sellaisenaan tai tarpeen mukaan muunneltuna. Tutkielma on kvalitatiivinen tapaustutkimus, joka sisältää piirteitä käsite- ja toiminta-analyyttisestä sekä osin nomoteettisesta tutkimusotteesta. Aineisto kerättiin puolistrukturoiduilla teemahaastatteluilla. Kohdeyrityksen strategia on asiakaslähtöinen. Perusstrategia kohdeyrityksessä on riippuvainen kilpailijakontekstista, mutta useimmissa tapauksissa kilpailuetu perustuu differointiin. Suurena terveyskaupan erikoisliikkeenä voidaan hyödyntää myös suuruuden ekonomiaa. Yrityksen toiminta on alalle fokusoitua. Life-terveyskauppaketjuun kuuluminen ja erinomainen liiketilan sijainti ovat olleet tärkeitä tekijöitä menestyksessä. Runsas mainonta, suuri neuvotteluvoima toimittajiin nähden, tuoteportfolion hallinta, osaava henkilöstö ja hyvät sopimusehdot ovat edesauttaneet menestystä. Venäjä-potentiaali Lappeenrannassa on suuri. Markkina-asema on talousaseman ohella erinomainen ja hyödyksi sekä yritykselle että yritysostajalle.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Active teaching-learning methodologies: medical students' views of problem-based learning

The prevailing undergraduate medical training process still favors disconnection and professional distancing from social needs. The Brazilian Ministries of Education and Health, through the National Curriculum Guidelines, the Incentives Program for Changes in the Medical Curriculum (PROMED), and the National Program for Reorientation of Professional Training in Health (PRO-SAÚDE), promoted the stimulus for an effective connection between medical institutions and the Unified National Health System (SUS). In accordance to the new paradigm for medical training, the Centro Universitário Serra dos Órgãos (UNIFESO) established a teaching plan in 2005 using active methodologies, specifically problem-based learning (PBL). Research was conducted through semi-structured interviews with third-year undergraduate students at the UNIFESO Medical School. The results were categorized as proposed by Bardin's thematic analysis, with the purpose of verifying the students' impressions of the new curriculum. Active methodologies proved to be well-accepted by students, who defined them as exciting and inclusive of theory and practice in medical education.

Future prospects of short distance rail based passenger transport in Northern Europe

The worlds’ population is increasing and cities have become more crowded with people and vehicles. Communities in the fringe of metropolitans’ increase the traffic done with private cars, but also increase the need for public transportation. People have typically needs traveling to work located in city centers during the morning time, and return to suburbs in the afternoon or evening. Rail based passenger transport is environmentally friendly transport mode with high capacity to transport large volume of people. Railways have been regulated markets with national incumbent having monopoly position. Opening the market for competition is believed to have a positive effect by increasing the efficiency of the industry. National passenger railway market is opened for competition only in few countries, where as international traffic in EU countries was deregulated in 2010. The objective of this study is to examine the passenger railway market of three North European countries, Sweden, Denmark and Estonia. The interest was also to get an understanding of the current situation and how the deregulation has proceeded. Theory of deregulation is unfolded with literature analyses and empirical part of the study is constructed from two parts. Customer satisfaction survey was chosen as a method to collect real life experiences from the passengers and measure their knowledge of the market situation and possible changes appeared. Interviews of experts from the industry and labor unions give more insights and able better understanding for example of social consequences caused from opening the market for competition. Expert interviews were conducted by using semi-structured theme interview. Based on the results of this study, deregulation has proceeded quite differently in the three countries researched. Sweden is the most advanced country, where the passenger railway market is open for new entrants. Denmark and Estonia are lagging behind. Opening the market is considered positive among passengers and most of the experts interviewed. Common for the interviews were the labour unions negative perspective concerning deregulation. Despite the fact deregulation is considered positive among the respondents of the customer satisfaction survey, they could not name railway undertakings operating in their country. Generally respondents were satisfied with the commuter trains. Ticket price, punctuality of trains and itinerary affect the most to customer satisfaction.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Effects of thermal environment and supplementation levels on the physiological parameters of moxotó goats in confined and semi-confined rising systems

The objective of this work was to determine the effect of environmental variables and supplementation levels on physiological parameters of Moxotó goats in confined and semi-confined rising systems, in the Brazilian semi-arid region. The semi-confined individuals were kept on a grass based diet during the day and arrested in the end of the afternoon. The confined animals were kept in a management center, receiving two diets composed by forage cactus and maniçoba hay into two different levels (0.5 and 1.5% of the body weight). Inside the management center and in the external environment the environmental comfort parameters were set high during the afternoon period characterizing a situation of thermal discomfort for the animals. During the morning the semi-confined animals presented an average respiratory frequency (69.5 mov min-1) and rectal temperature (39.5 ºC) higher than the confined ones (62.6 mov min-1 and 39.0 ºC, respectively). The confined and semi-confined animals were able to maintain their rectal temperature within normal limits, with increase in the cardiac beatings rate and respiratory frequency. The greater percentage of the used supplementations (1.5%) seemed to increase rectal temperature in the two studied rising systems.

Rapid detection of bovine coronavirus by a semi-nested RT-PCR

Bovine coronavirus (BCoV) is a member of the group 2 of the Coronavirus (Nidovirales: Coronaviridae) and the causative agent of enteritis in both calves and adult bovine, as well as respiratory disease in calves. The present study aimed to develop a semi-nested RT-PCR for the detection of BCoV based on representative up-to-date sequences of the nucleocapsid gene, a conserved region of coronavirus genome. Three primers were designed, the first round with a 463bp and the second (semi-nested) with a 306bp predicted fragment. The analytical sensitivity was determined by 10-fold serial dilutions of the BCoV Kakegawa strain (HA titre: 256) in DEPC treated ultra-pure water, in fetal bovine serum (FBS) and in a BCoV-free fecal suspension, when positive results were found up to the 10-2, 10-3 and 10-7 dilutions, respectively, which suggests that the total amount of RNA in the sample influence the precipitation of pellets by the method of extraction used. When fecal samples was used, a large quantity of total RNA serves as carrier of BCoV RNA, demonstrating a high analytical sensitivity and lack of possible substances inhibiting the PCR. The final semi-nested RT-PCR protocol was applied to 25 fecal samples from adult cows, previously tested by a nested RT-PCR RdRp used as a reference test, resulting in 20 and 17 positives for the first and second tests, respectively, and a substantial agreement was found by kappa statistics (0.694). The high sensitivity and specificity of the new proposed method and the fact that primers were designed based on current BCoV sequences give basis to a more accurate diagnosis of BCoV-caused diseases, as well as to further insights on protocols for the detection of other Coronavirus representatives of both Animal and Public Health importance.

Scaling up stepwise feature introduction to construction of large software systems

Developing software is a difficult and error-prone activity. Furthermore, the complexity of modern computer applications is significant. Hence,an organised approach to software construction is crucial. Stepwise Feature Introduction – created by R.-J. Back – is a development paradigm, in which software is constructed by adding functionality in small increments. The resulting code has an organised, layered structure and can be easily reused. Moreover, the interaction with the users of the software and the correctness concerns are essential elements of the development process, contributing to high quality and functionality of the final product. The paradigm of Stepwise Feature Introduction has been successfully applied in an academic environment, to a number of small-scale developments. The thesis examines the paradigm and its suitability to construction of large and complex software systems by focusing on the development of two software systems of significant complexity. Throughout the thesis we propose a number of improvements and modifications that should be applied to the paradigm when developing or reengineering large and complex software systems. The discussion in the thesis covers various aspects of software development that relate to Stepwise Feature Introduction. More specifically, we evaluate the paradigm based on the common practices of object-oriented programming and design and agile development methodologies. We also outline the strategy to testing systems built with the paradigm of Stepwise Feature Introduction.

Pulse response based control for positive definite systems

Pulse Response Based Control (PRBC) is a recently developed minimum time control method for flexible structures. The flexible behavior of the structure is represented through a set of discrete time sequences, which are the responses of the structure due to rectangular force pulses. The rectangular force pulses are given by the actuators that control the structure. The set of pulse responses, desired outputs, and force bounds form a numerical optimization problem. The solution of the optimization problem is a minimum time piecewise constant control sequence for driving the system to a desired final state. The method was developed for driving positive semi-definite systems. In case the system is positive definite, some final states of the system may not be reachable. Necessary conditions for reachability of the final states are derived for systems with a finite number of degrees of freedom. Numerical results are presented that confirm the derived analytical conditions. Numerical simulations of maneuvers of distributed parameter systems have shown a relationship between the error in the estimated minimum control time and sampling interval

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Model based analysis of the post-combustion calcium looping process for carbon dioxide capture

This thesis presents a one-dimensional, semi-empirical dynamic model for the simulation and analysis of a calcium looping process for post-combustion CO2 capture. Reduction of greenhouse emissions from fossil fuel power production requires rapid actions including the development of efficient carbon capture and sequestration technologies. The development of new carbon capture technologies can be expedited by using modelling tools. Techno-economical evaluation of new capture processes can be done quickly and cost-effectively with computational models before building expensive pilot plants. Post-combustion calcium looping is a developing carbon capture process which utilizes fluidized bed technology with lime as a sorbent. The main objective of this work was to analyse the technological feasibility of the calcium looping process at different scales with a computational model. A one-dimensional dynamic model was applied to the calcium looping process, simulating the behaviour of the interconnected circulating fluidized bed reactors. The model incorporates fundamental mass and energy balance solvers to semi-empirical models describing solid behaviour in a circulating fluidized bed and chemical reactions occurring in the calcium loop. In addition, fluidized bed combustion, heat transfer and core-wall layer effects were modelled. The calcium looping model framework was successfully applied to a 30 kWth laboratory scale and a pilot scale unit 1.7 MWth and used to design a conceptual 250 MWth industrial scale unit. Valuable information was gathered from the behaviour of a small scale laboratory device. In addition, the interconnected behaviour of pilot plant reactors and the effect of solid fluidization on the thermal and carbon dioxide balances of the system were analysed. The scale-up study provided practical information on the thermal design of an industrial sized unit, selection of particle size and operability in different load scenarios.