Towards an ecological index for tropical soil quality based on soil macrofauna

The objective of this work was to construct a simple index based on the presence/absence of different groups of soil macrofauna to determine the ecological quality of soils. The index was tested with data from 20 sites in South and Central Tabasco, Mexico, and a positive relation between the model and the field observations was detected. The index showed that diverse agroforestry systems had the highest soil quality index (1.00), and monocrops without trees, such as pineapple, showed the lowest soil quality index (0.08). Further research is required to improve this model for natural systems that have very low earthworm biomass (<10 g m-2) and a high number of earthworm species (5-7), as it is in the tropical rain forest, whose soil quality index was medium (0.5). The application of this index will require an illustrated guide for its users. Further studies are required in order to test the use of this index by farmers.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Real-time tree-foliage surface estimation using a ground laser scanner

The optimization of most pesticide and fertilizer applications is based on overall grove conditions. In this work we measurements. Recently, Wei [9, 10] used a terrestrial propose a measurement system based on a ground laser scanner to LIDAR to measure tree height, width and volume developing estimate the volume of the trees and then extrapolate their foliage a set of experiments to evaluate the repeatability and surface in real-time. Tests with pear trees demonstrated that the accuracy of the measurements, obtaining a coefficient of relation between the volume and the foliage can be interpreted as variation of 5.4% and a relative error of 4.4% in the linear with a coefficient of correlation (R) of 0.81 and the foliar estimation of the volume but without real-time capabilities. surface can be estimated with an average error less than 5 %.

Mobile E-commerce business model – A value web based approach to business models in mobile gaming industry

Tämän tutkimuksen tavoitteena oli tutkia langattomien internet palveluiden arvoverkkoa ja liiketoimintamalleja. Tutkimus oli luonteeltaan kvalitatiivinen ja siinä käytettiin strategiana konstruktiivista case-tutkimusta. Esimerkkipalveluna oli Treasure Hunters matkapuhelinpeli. Tutkimus muodostui teoreettisesta ja empiirisestä osasta. Teoriaosassa liitettiin innovaatio, liiketoimintamallit ja arvoverkko käsitteellisesti toisiinsa, sekä luotiin perusta liiketoimintamallien kehittämiselle. Empiirisessä osassa keskityttiin ensin liiketoimintamallien luomiseen kehitettyjen innovaatioiden pohjalta. Lopuksi pyrittiin määrittämään arvoverkko palvelun toteuttamiseksi. Tutkimusmenetelminä käytettiin innovaatiosessiota, haastatteluja ja lomakekyselyä. Tulosten pohjalta muodostettiin useita liiketoimintakonsepteja sekä kuvaus arvoverkon perusmallista langattomille peleille. Loppupäätelmänä todettiin että langattomat palvelut vaativat toteutuakseen useista toimijoista koostuvan arvoverkon.

Developing customer-based e-solutions

Logistiikkapalveluiden markkinat ovat viime vuosina muuttuneet. Kilpailtu toimiala ja asiakasvaatimusten muuttuminen ovat pakottaneet yritykset pyrkimään entistä tehokkaampaan jakeluketjuun. Työn tarkoituksena oli tutkia sähköisten asiakasliittymien toimivuutta asiakkaan näkökulmasta Euro Express tuotannossa ja prosessissa. Tarkoituksena oli selvittää eri sidosryhmien vaatimukset prosessille huomioiden sähköisen liiketoiminnan tuomat edut ja ominaispiirteet. Tavoitteena oli kuvata olemassa oleva prosessi ja tutkia prosessin rajapinnat –asiakas, tuotanto ja ulkoiset sidosryhmät. Tutkielmassa sähköisten ratkaisujen ominaispiirteet on käyty läpi ja tulevaisuuden kehitysnäkökulmista keskusteltu. Kehittyneiden tietoteknisten ratkaisujen avulla jatkuva prosessien uudistaminen (Business Process Reengineering) on mahdollista. Yleisesti epäolennaisuudet asiakasrajapinnassa, informaation kulussa ja yhteyksissä eri järjestelmien välillä aiheuttavat ongelmia sähköisten ratkaisujen toteuttamisessa. Tulevaisuudessa logistiikka yritykset ottavat entistä enemmän käyttöönsä uudenaikaisia teknologisia ratkaisuja tilaukseen, tuotantoon ja asiakaspalveluun. Näiden uudenlaisten ratkaisujen kehittämisestä on hyötyä sekä käyttäjälle että tarjoajalle, mutta ne ovat myös pakollisia palveluntarjoajalle kehittyäkseen markkinoilla. Tulevaisuudessa kilpailun tiivistyessä ja asiakkaiden vaatimusten kasvaessa on kiinnitettävä entistä suurempaa huomiota koko prosessiketjun toimivuuteen. Uudet teknologiset ratkaisut ja niiden käyttäminen tehokkaasti tuovat yrityksille kilpailuetuja, joita ei muuten olisi saavutettavissa.

Aluminium fouling and its impact on activated carbon based dioxin and furan removal in a wet scrubber at a co-incineration plant

Dioxins and furans, PCDD/Fs, are highly toxic substances formed in post combustion zones in furnaces. PCDD/F emissions are regulated by a waste incineration directive which relates also to co-incineration plants. Several observations of dioxin and furan enhancements in wet scrub- bers have been reported previously. This is thought to be due to the so-called "memory effect" which occurs when dioxins and furans absorb into plastic material in scrubbers and desorb when ambient circumstances alter significantly. At the co-incineration plant involved, dioxins and furans are controlled with a wet scrubber, the tower packing of which is made of plastic in which activated carbon particles are dispersed. This should avoid the memory effect and act as a dioxin and furan sink since dioxins and furans are absorbed irreversibly into the packing ma- terial. In this case, the tower packing in the scrubber is covered with a white layer that has been found to be mainly aluminium. The aim of this thesis was to determine the aluminium balance and the dioxin and furan behaviour in the scrubber and, thus, the impacts that the foul- ing has on dioxin and furan removal. The source of aluminium, reasons for fouling and further actions to minimize its impacts on dioxin and furan removal were also to be discovered. Measurements in various media around the scrubber and in fuels were made and a profile analysis of PCDD/F and mass balance calculations were carried out. PCDD/F content de- creased in the scrubber. The reduced PCDD/F was not discharged into scrubbing water. The removal mechanism seems to work in spite of the fouling, at least with low PCDD/F loads. Most of the PCDD/F in excess water originates from the Kymijoki River which is used as feeding water in the scrubber. Fouling turned out to consist mainly of aluminium hydroxides. Sludge combusted in the furnace was found to be a significant source of aluminium. Ways to minimize the fouling would be adjustment of pH to a proper lever, installation of a mechanical filter to catch the loose material from the scrubbing water and affecting the aluminium content of the sludge.

A Population-Based Model to Consider the Effect of Seasonal Variation on Serum 25(OH)D and Vitamin D Status.

Background. We elaborated a model that predicts the centiles of the 25(OH)D distribution taking into account seasonal variation. Methods. Data from two Swiss population-based studies were used to generate (CoLaus) and validate (Bus Santé) the model. Serum 25(OH)D was measured by ultra high pressure LC-MS/MS and immunoassay. Linear regression models on square-root transformed 25(OH)D values were used to predict centiles of the 25(OH)D distribution. Distribution functions of the observations from the replication set predicted with the model were inspected to assess replication. Results. Overall, 4,912 and 2,537 Caucasians were included in original and replication sets, respectively. Mean (SD) 25(OH)D, age, BMI, and % of men were 47.5 (22.1) nmol/L, 49.8 (8.5) years, 25.6 (4.1) kg/m(2), and 49.3% in the original study. The best model included gender, BMI, and sin-cos functions of measurement day. Sex- and BMI-specific 25(OH)D centile curves as a function of measurement date were generated. The model estimates any centile of the 25(OH)D distribution for given values of sex, BMI, and date and the quantile corresponding to a 25(OH)D measurement. Conclusions. We generated and validated centile curves of 25(OH)D in the general adult Caucasian population. These curves can help rank vitamin D centile independently of when 25(OH)D is measured.

Effects of unit - based pricing on the waste collection demand : a meta - regression analysis

We perform a meta - analysis of 21 studies that estimate the elasticity of the price of waste collection demand upon waste quantities, a prior literature review having revealed that the price elasticity differs markedly. Based on a meta - regression with a total of 65 observations, we find no indication that municipal data give higher estimates for price elasticities than those associated with household data. Furthermore, there is no evidence that treating prices as exogenous underestimates the price elasticity. We find that much of the variation can be explained by sample size, the use of a weight - based as opposed to a volume - based pricing system, and the pricing of compostable waste. We also show that price elasticities determined in the USA and point estimations of elasticities are more elastic, but these effects are not robust to the changing of model specifications. Finally, our tests show that there is no evidence of publication bias while there is some evidence of the existence of genuine empirical effect.

Genetics-Based Population Pharmacokinetics and Pharmacodynamics of Risperidone in a Psychiatric Cohort.

BACKGROUND: High interindividual variability in plasma concentrations of risperidone and its active metabolite, 9-hydroxyrisperidone, may lead to suboptimal drug concentration. OBJECTIVE: Using a population pharmacokinetic approach, we aimed to characterize the genetic and non-genetic sources of variability affecting risperidone and 9-hydroxyrisperidone pharmacokinetics, and relate them to common side effects. METHODS: Overall, 150 psychiatric patients (178 observations) treated with risperidone were genotyped for common polymorphisms in NR1/2, POR, PPARα, ABCB1, CYP2D6 and CYP3A genes. Plasma risperidone and 9-hydroxyrisperidone were measured, and clinical data and common clinical chemistry parameters were collected. Drug and metabolite concentrations were analyzed using non-linear mixed effect modeling (NONMEM(®)). Correlations between trough concentrations of the active moiety (risperidone plus 9-hydroxyrisperidone) and common side effects were assessed using logistic regression and linear mixed modeling. RESULTS: The cytochrome P450 (CYP) 2D6 phenotype explained 52 % of interindividual variability in risperidone pharmacokinetics. The area under the concentration-time curve (AUC) of the active moiety was found to be 28 % higher in CYP2D6 poor metabolizers compared with intermediate, extensive and ultrarapid metabolizers. No other genetic markers were found to significantly affect risperidone concentrations. 9-hydroxyrisperidone elimination was decreased by 26 % with doubling of age. A correlation between trough predicted concentration of the active moiety and neurologic symptoms was found (p = 0.03), suggesting that a concentration >40 ng/mL should be targeted only in cases of insufficient, or absence of, response. CONCLUSIONS: Genetic polymorphisms of CYP2D6 play an important role in risperidone, 9-hydroxyrisperidone and active moiety plasma concentration variability, which were associated with common side effects. These results highlight the importance of a personalized dosage adjustment during risperidone treatment.

CYP17A1 Enzyme activity is linked to ambulatory blood pressure in a family-based population study.

BACKGROUND: Genome-wide association studies have linked CYP17A1 coding for the steroid hormone synthesizing enzyme 17α-hydroxylase (CYP17A1) to blood pressure (BP). We hypothesized that the genetic signal may translate into a correlation of ambulatory BP (ABP) with apparent CYP17A1 activity in a family-based population study and estimated the heritability of CYP17A1 activity. METHODS: In the Swiss Kidney Project on Genes in Hypertension, day and night urinary excretions of steroid hormone metabolites were measured in 518 participants (220 men, 298 women), randomly selected from the general population. CYP17A1 activity was assessed by 2 ratios of urinary steroid metabolites: one estimating the combined 17α-hydroxylase/17,20-lyase activity (ratio 1) and the other predominantly 17α-hydroxylase activity (ratio 2). A mixed linear model was used to investigate the association of ABP with log-transformed CYP17A1 activities exploring effect modification by urinary sodium excretion. RESULTS: Daytime ABP was positively associated with ratio 1 under conditions of high, but not low urinary sodium excretion (P interaction <0.05). Ratio 2 was not associated with ABP. Heritability estimates (SE) for day and night CYP17A1 activities were 0.39 (0.10) and 0.40 (0.09) for ratio 1, and 0.71 (0.09) and 0.55 (0.09) for ratio 2 (P values <0.001). CYP17A1 activities, assessed with ratio 1, were lower in older participants. CONCLUSIONS: Low apparent CYP17A1 activity (assessed with ratio 1) is associated with elevated daytime ABP when salt intake is high. CYP17A1 activity is heritable and diminished in the elderly. These observations highlight the modifying effect of salt intake on the association of CYP17A1 with BP.

Bio-based composites from stone groundwood applied to new product development

This paper deals with the product design, engineering, and material selection intended for the manufacturing of an eco-friendly chair. The final product is expected to combine design attributes with technical and legal feasibility with the implementation of new bio-based materials. Considering the industrial design, a range of objectives and trends were determined after setting the market requirements, and the final concept was proposed and modeled. The product geometry, production technology, and legal specifications were the input data for product engineering. The material selection was based on the technical requirements. Polypropylene (PP) composite materials based on coupled-fiberglass, sized-fiberglass, and coupled-stone ground wood reinforcements were prepared and characterized. Final formulations based on these PP composites are proposed and justified

Multifrequency VLBI Observations of Selected Active Galactic Nuclei

In this dissertation, active galactic nuclei (AGN) are discussed, as they are seen with the high-resolution radio-astronomical technique called Very Long Baseline Interferometry (VLBI). This observational technique provides very high angular resolution (_ 10−300 = 1 milliarcsecond). VLBI observations, performed at different radio frequencies (multi-frequency VLBI), allow to penetrate deep into the core of an AGN to reveal an otherwise obscured inner part of the jet and the vicinity of the AGN’s central engine. Multi-frequency VLBI data are used to scrutinize the structure and evolution of the jet, as well as the distribution of the polarized emission. These data can help to derive the properties of the plasma and the magnetic field, and to provide constraints to the jet composition and the parameters of emission mechanisms. Also VLBI data can be used for testing the possible physical processes in the jet by comparing observational results with results of numerical simulations. The work presented in this thesis contributes to different aspects of AGN physics studies, as well as to the methodology of VLBI data reduction. In particular, Paper I reports evidence of optical and radio emission of AGN coming from the same region in the inner jet. This result was obtained via simultaneous observations of linear polarization in the optical and in radio using VLBI technique of a sample of AGN. Papers II and III describe, in detail, the jet kinematics of the blazar 0716+714, based on multi-frequency data, and reveal a peculiar kinematic pattern: plasma in the inner jet appears to move substantially faster that that in the large-scale jet. This peculiarity is explained by the jet bending, in Paper III. Also, Paper III presents a test of the new imaging technique for VLBI data, the Generalized Maximum Entropy Method (GMEM), with the observed (not simulated) data and compares its results with the conventional imaging. Papers IV and V report the results of observations of the circularly polarized (CP) emission in AGN at small spatial scales. In particular, Paper IV presents values of the core CP for 41 AGN at 15, 22 and 43 GHz, obtained with the help of the standard Gain transfer (GT) method, which was previously developed by D. Homan and J.Wardle for the calibration of multi-source VLBI observations. This method was developed for long multi-source observations, when many AGN are observed in a single VLBI run. In contrast, in Paper V, an attempt is made to apply the GT method to single-source VLBI observations. In such observations, the object list would include only a few sources: a target source and two or three calibrators, and it lasts much shorter than the multi-source experiment. For the CP calibration of a single-source observation, it is necessary to have a source with zero or known CP as one of the calibrators. If the archival observations included such a source to the list of calibrators, the GT could also be used for the archival data, increasing a list of known AGN with the CP at small spatial scale. Paper V contains also calculation of contributions of different sourced of errors to the uncertainty of the final result, and presents the first results for the blazar 0716+714.

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.

Observations on the Pharmacokinetics and Pharmacodynamics of Dexmedetomidine. Clinical Studies on Healthy Volunteers and Intensive Care Patients

Patients treated in intensive care units require sedation and analgesia. However, sedative drugs also have potential adverse effects, and there is no single ideal sedativeanalgesic drug for these patients. Dexmedetomidine is an apha2-adrenoceptor agonist licenced for sedation of intensive care patients and patients undergoing surgery and other invasive procedures. Several routes of parenteral administration (intravenous, intramuscular, subcutaneous and intranasal) have been utilized. In the present series of studies, the pharmacokinetics and pharmacodynamics of intranasally administered dexmedetomidine as well as the gastrointestinal effects of intravenous dexmedetomidine were determined in healthy volunteers. Pharmacokinetics of dexmedetomidine during long lasting, high-dose infusions were characterized in intensive care patients. The bioavailability of intranasal dexmedetomidine was relatively good (65%), but interindividual variation was large. Dexmedetomidine significantly inhibited gastric emptying and gastrointestinal transit. In intensive care patients, the elimination half-life of dexmedetomidine was somewhat longer than reported for infusions of shorter duration and in less ill patients or healthy volunteers. Dexmedetomidine appeared to have linear pharmacokinetics up to the studied dose rate of 2.5 μg/kg/h. Dexmedetomidine clearance was decreasing with age and its volume of distribution was increased in hypoalbuminaemic patients, resulting in a longer elimination half-life and context-sensitive half-time. Intranasally administered dexmedetomidine was efficacious and well tolerated, making it appropriate for clinical situations requiring light sedation. The clinical significance of the gastrointestinal inhibitory effects of dexmedetomidine should be further evaluated in intensive care patients. The possibility of potentially altered potency and effect duration should be taken into account when administering dexmedetomidine to elderly or hypoalbuminaemic patients.

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.