Intraspecific variability of Holostylis reniformis: concentration of lignans, as determined by maceration and supercritical fluid extraction (SFE-CO2), as a function of plant provenance and plant parts

Maceration and supercritical fluid extraction were used to prepare extracts from parts of plants (Holostylis reniformis) collected in two different regions of Brazil. ¹H NMR, HPLC-DAD-ESI/MS, HPLC-DAD, GC-MS, and chemometric techniques were used to analyse lignans in the extracts and showed that yields of SFE-CO2 were less than or equal to those of hexane maceration extracts. These analyses, in conjunction with the concentrations of aliphatic hydrocarbons, fatty acids and their methyl and ethyl derivatives in the extracts, also allowed the chemical composition of parts and provenance of the plant to be differentiated.

Simultaneous determination of four phenolic compounds in extracts of aerial parts of Ipomoea pes-caprae (L.) R. Br. (Convolvulaceae) by HPLC-UV

Among other applications, Ipomoea pes-caprae is popularly used to treat jellyfish stings, supporting the development of a product for dermatological use. Hydroethanolic spray-dried extract was chosen for the further development of phytomedicines, and a stability-indicative HPLC-UV method was developed and validated for the determination of isoquercitrin and isochlorogenic acids A, B and C. The method was developed using a C18 column (250 x 4.6 mm, 5 µm) with an acetonitrile:water mobile phase at pH 3.0 in a gradient run. The four constituents and other unidentified components of the extract were appropriately resolved without interference of degradation products after stress tests (acid, alkali, neutral, oxidant, photolysis). The method showed linearity in the isoquercitrin concentration range from 5.0-50.0 µg mL-1, with adequate precision (RSD% < 2.5% for the intra- and inter-day studies), accuracy (recovery of 100.0 ± 2.0%), and robustness. Both the herbal drug and spray-dried extract of I. pes-caprae were subjected to stability studies in accelerated and long-term conditions over four months. The samples maintained their characteristics and marker contents (< 10% of variation).

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.

Financier’s credit risk: A Performance-Based Classification Model

The purpose of this study is to view credit risk from the financier’s point of view in a theoretical framework. Results and aspects of the previous studies regarding measuring credit risk with accounting based scoring models are also examined. The theoretical framework and previous studies are then used to support the empirical analysis which aims to develop a credit risk measure for a bank’s internal use or a risk management tool for a company to indicate its credit risk to the financier. The study covers a sample of Finnish companies from 12 different industries and four different company categories and employs their accounting information from 2004 to 2008. The empirical analysis consists of six stage methodology process which uses measures of profitability, liquidity, capital structure and cash flow to determine financier’s credit risk, define five significant risk classes and produce risk classification model. The study is confidential until 15.10.2012.

Classification, comorbidity, heredity, and risk factors of female sexual dysfunctions

Female sexual dysfunctions, including desire, arousal, orgasm and pain problems, have been shown to be highly prevalent among women around the world. The etiology of these dysfunctions is unclear but associations with health, age, psychological problems, and relationship factors have been identified. Genetic effects explain individual variation in orgasm function to some extent but until now quantitative behavior genetic analyses have not been applied to other sexual functions. In addition, behavior genetics can be applied to exploring the cause of any observed comorbidity between the dysfunctions. Discovering more about the etiology of the dysfunctions may further improve the classification systems which are currently under intense debate. The aims of the present thesis were to evaluate the psychometric properties of a Finnish-language version of a commonly used questionnaire for measuring female sexual function, the Female Sexual Function Index (FSFI), in order to investigate prevalence, comorbidity, and classification, and to explore the balance of genetic and environmental factors in the etiology as well as the associations of a number of biopsychosocial factors with female sexual functions. Female sexual functions were studied through survey methods in a population based sample of Finnish twins and their female siblings. There were two waves of data collection. The first data collection targeted 5,000 female twins aged 33–43 years and the second 7,680 female twins aged 18–33 and their over 18–year-old female siblings (n = 3,983). There was no overlap between the data collections. The combined overall response rate for both data collections was 53% (n = 8,868), with a better response rate in the second (57%) compared to the first (45%). In order to measure female sexual function, the FSFI was used. It includes 19 items which measure female sexual function during the previous four weeks in six subdomains; desire, subjective arousal, lubrication, orgasm, sexual satisfaction, and pain. In line with earlier research in clinical populations, a six factor solution of the Finnish-language version of the FSFI received supported. The internal consistencies of the scales were good to excellent. Some questions about how to avoid overestimating the prevalence of extreme dysfunctions due to women being allocated the score of zero if they had had no sexual activity during the preceding four weeks were raised. The prevalence of female sexual dysfunctions per se ranged from 11% for lubrication dysfunction to 55% for desire dysfunction. The prevalence rates for sexual dysfunction with concomitant sexual distress, in other words, sexual disorders were notably lower ranging from 7% for lubrication disorder to 23% for desire disorder. The comorbidity between the dysfunctions was substantial most notably between arousal and lubrication dysfunction even if these two dysfunctions showed distinct patterns of associations with the other dysfunctions. Genetic influences on individual variation in the six subdomains of FSFI were modest but significant ranging from 3–11% for additive genetic effects and 5–18% for nonadditive genetic effects. The rest of the variation in sexual functions was explained by nonshared environmental influences. A correlated factor model, including additive and nonadditive genetic effects and nonshared environmental effects had the best fit. All in all, every correlation between the genetic factors was significant except between lubrication and pain. All correlations between the nonshared environment factors were significant showing that there is a substantial overlap in genetic and nonshared environmental influences between the dysfunctions. In general, psychological problems, poor satisfaction with the relationship, sexual distress, and poor partner compatibility were associated with more sexual dysfunctions. Age was confounded with relationship length but had over and above relationship length a negative effect on desire and sexual satisfaction and a positive effect on orgasm and pain functions. Alcohol consumption in general was associated with better desire, arousal, lubrication, and orgasm function. Women pregnant with their first child had fewer pain problems than nulliparous nonpregnant women. Multiparous pregnant women had more orgasm problems compared to multiparous nonpregnant women. Having children was associated with less orgasm and pain problems. The conclusions were that desire, subjective arousal, lubrication, orgasm, sexual satisfaction, and pain are separate entities that have distinct associations with a number of different biopsychosocial factors. However, there is also considerable comorbidity between the dysfunctions which are explained by overlap in additive genetic, nonadditive genetic and nonshared environmental influences. Sexual dysfunctions are highly prevalent and are not always associated with sexual distress and this relationship might be moderated by a good relationship and compatibility with partner. Regarding classification, the results supports separate diagnoses for subjective arousal and genital arousal as well as the inclusion of pain under sexual dysfunctions.

Erään teollisuuslaitoksen suur- ja keskijännitesähkönjakelun ennakkohuoltoperiaatteet

Tämän diplomityön tavoitteena oli luoda suuren teollisuuslaitoksen suur- ja keskijännitesähkönjakelujärjestelmälle ennakkohuoltosuunnitelmaesitys, joka selkeyttää järjestelmän ennakkohuoltotoimintaa. Ennakkohuoltosuunnitelmaesityksen perusteella voidaan tulevaisuudessa luoda ennakkohuolto-ohjelma kunnossapitojärjestelmään. Ennakkohuoltosuunnitelmaesityksen kehittäminen aloitettiin selvittämällä suur- ja keskijännitesähkönjakelujärjestelmien ennakkohuoltotoimintaan vaikuttavaa lainsäädäntöä, määräyksiä, ohjeita sekä standardeja. Myös sähkönjakelujärjestelmän komponenttien luotettavuudesta ja pitoajasta saatavilla olevaa informaatiota etsittiin eri lähteistä. Tutkittavana olevaan suur- ja keskijännitesähkönjakelujärjestelmään perehtymisen yhteydessä selvitettiin myös järjestelmän komponenttien varaosatilanne, sekä järjestelmässä käytettävissä olevat varayhteydet. Tutkittavalle suur- ja keskijännitesähkönjakelujärjestelmälle suoritettiin kriittisyysluokittelu, sekä selvitettiin järjestelmän ennakkohuoltotoiminnan nykytilanne. Lisäksi tutkittiin järjestelmän vikahistoriakirjauksia kymmenen vuoden ajalta. Työn viimeisessä osassa laadittiin ennakkohuoltosuunnitelmaesitys tutkittavalle suur- ja keskijännitesähkönjakelujärjestelmälle. Ennakkohuoltosuunnitelmaesitykseen ovat osaltaan vaikuttaneet suoritettu kriittisyysluokittelu sekä vikahistoriasta selvinneet asiat. Lisäksi työssä tutustuttiin sähkönjakelun ennakkohuoltotöiden optimointiin. Työssä esiteltiin optimointilaskennan laskentayhtälöt, sekä suoritettiin esimerkkioptimointilaskenta kuvitteellisen sähkönjakelujärjestelmän muuntajien ennakkohuollolle.

Solving the puzzle of mobile learning adoption

The dissertation seeks to explore how to improve users‘ adoption of mobile learning in current education systems. Considering the difference between basic and tertiary education in China, the research consists of two separate but interrelated parts, which focus on the use of mobile learning in basic and tertiary education contexts, respectively. In the dissertation, two adoption frameworks are developed based on previous studies. The frameworks are then evaluated using different technologies. Concerning mobile learning use in basic education settings, case study methodology is utilized. A leading provider of mobile learning services and products in China, Noah Ltd., is investigated. Multiple sources of evidence are collected to test the framework. Regarding mobile learning adoption in tertiary education contexts, survey research methodology is utilized. Based on 209 useful responses, the framework is evaluated using structural equation modelling technology. Four proposed determinants of intention to use are evaluated, which are perceived ease of use, perceived near-term usefulness, perceived ong-term usefulness and personal innovativeness. The dissertation provides a number of new insights for both researchers and practitioners. In particular, the dissertation specifies a practical solution to deal with the disruptive effects of mobile learning in basic education, which keeps the use of mobile learning away from the schools across such as European countries. A list of new and innovative mobile learning technologies is systematically introduced as well. Further, the research identifies several key factors driving mobile learning adoption in tertiary education settings. In theory, the dissertation suggests that since the technology acceptance model is initiated in work-oriented innovations by testing employees, it is not necessarily the best model for studying educational innovations. The results also suggest that perceived longterm usefulness for educational systems should be as important as perceived usefulness for utilitarian systems, and perceived enjoyment for hedonic systems. A classification based on the nature of systems purpose (utilitarian, hedonic or educational) would contribute to a better understanding of the essence of IT innovation adoption.

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.

CLASSIFICATION OF FOREST ROADS AND DETERMINATION OF ROUTE USING GEOGRAPHIC INFORMATION SYSTEM

ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.

Huolto– ja kunnossapitoliiketoiminnan tuotteistaminen

Tässä diplomityössä pyritään selvittämään, mitä kaikkea huolto– ja unnossapitosopimuksiin perustuvan liiketoiminnan tuotteistamiselta vaaditaan. Kyseisiä palveluita halutaan markkinoida uusien kerrosleiju–teknologiaan (BFB) perustuvien voimakattilatoimitusten yhteydessä. Diplomityön kirjallisessa osiossa asiaa tutkitaan ensin palveluliiketoimintaan ja tuotteistamiseen liittyvien seikkojen näkökulmasta sekä esitellään kunnossapidon teoriaa ja eri strategiakonsepteja sekä tunnuslukuja. Tutkimuksen empiirisessä osassa luodaan toimintamalli huolto– ja kunnossapitosopimuksia varten. Toimintamallissa pyritään löytämään laitekohtaisesti optimaalinen kunnossapitostrategia soveltaen RCM–menetelmään eli luotettavuuskeskistä kunnossapitotapaa. Käytettäviä kunnossapitostrategioita ovat parantava, ennakoiva, kuntoon perustuva ja korjaava kunnossapito. Optimoinnin päämäärä on saavuttaa mahdollisimman korkea tuotantovarmuus kustannustehokkaasti. Lisäksi työssä arvioidaan eri kunnossapitoresurssien tarve ensimmäisen kymmenen käyttövuoden ajalle. Toinen tutkimustavoite on saattaa elinkaarenseurantatyökalun kehittämisprojekti alkuun. Elinkaarenseurantatyökalulla halutaan seurata eri laitteiden elinkaaren vaihetta sekä löytää paras mahdollinen ajotapojen ja elinkaaren suhde. Työssä saavutettiin kunnossapito–ohjelma ja arvio eri resurssien tarpeesta voimakattilan laitteille. Resurssitarvearvio sisältää arvion työvoiman tarpeesta henkilötyötunteina sekä vaihdettavien vara– ja kulutusosien määrän.

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Montreal classification of patient operated for Crohn's disease and identification of surgical recurrence predictors

OBJECTIVE: to evaluate Crohn's disease recurrence and its possible predictors in patients undergoing surgical treatment. METHODS: We conducted a retrospective study with Crohn's disease (CD) patients undergoing surgical treatment between January 1992 and January 2012, and regularly monitored at the Bowel Clinic of the Hospital das Clínicas of the UFMG. RESULTS: we evaluated 125 patients, 50.4% female, with a mean age of 46.12 years, the majority (63.2%) diagnosed between 17 and 40 years of age. The ileum was involved in 58.4%, whereas stenotic behavior was observed in 44.8%, and penetrating, in 45.6%. We observed perianal disease in 26.4% of cases. The follow-up average was 152.40 months. Surgical relapse occurred in 29.6%, with a median time of 68 months from the first operation. CONCLUSION: The ileocolic location, penetrating behavior and perianal involvement (L3B3p) were associated with increased risk of surgical recurrence.