X-ray and radio observations of RX J1826.2-1450/LS 5039

RX J1826.2-1450/LS 5039 has been recently proposed to be a radio emitting high mass X-ray binary. In this paper, we present an analysis of its X-ray timing and spectroscopic properties using different instruments on board the RXTE satellite. The timing analysis indicates the absence of pulsed or periodic emission on time scales of 0.02-2000 s and 2-200 d, respectively. The source spectrum is well represented by a power-law model, plus a Gaussian component describing a strong iron line at 6.6 keV. Significant emission is seen up to 30 keV, and no exponential cut-off at high energy is required. We also study the radio properties of the system according to the GBI-NASA Monitoring Program. RX J1826.2-1450/LS 5039 continues to display moderate radio variability with a clearly non-thermal spectral index. No strong radio outbursts have been detected after several months.

Visual impairment and multimorbidity in a representative sample of the Spanish population

BACKGROUND: In the context of population aging, visual impairment has emerged as a growing concern in public health. However, there is a need for further research into the relationship between visual impairment and chronic medical conditions in the elderly. The aim of our study was to examine the relationship between visual impairment and three main types of co-morbidity: chronic physical conditions (both at an independent and additive level), mental health and cognitive functioning. METHODS: Data were collected from the COURAGE in Europe project, a cross-sectional study. A total of 4,583 participants from Spain were included. Diagnosis of chronic medical conditions included self-reported medical diagnosis and symptomatic algorithms. Depression and anxiety were assessed using CIDI algorithms. Visual assessment included objective distance/near visual acuity and subjective visual performance. Descriptive analyses included the whole sample (n = 4,583). Statistical analyses included participants aged over 50 years (n = 3,625; mean age = 66.45 years) since they have a significant prevalence of chronic conditions and visual impairment. Crude and adjusted binary logistic regressions were performed to identify independent associations between visual impairment and chronic medical conditions, physical multimorbidity and mental conditions. Covariates included age, gender, marital status, education level, employment status and urbanicity. RESULTS: The number of chronic physical conditions was found to be associated with poorer results in both distance and near visual acuity [OR 1.75 (CI 1.38-2.23); OR 1.69 (CI 1.27-2.24)]. At an independent level, arthritis, stroke and diabetes were associated with poorer distance visual acuity results after adjusting for covariates [OR 1.79 (CI 1.46-2.21); OR 1.59 (CI 1.05-2.42); OR 1.27 (1.01-1.60)]. Only stroke was associated with near visual impairment [OR 3.01 (CI 1.86-4.87)]. With regard to mental health, poor subjective visual acuity was associated with depression [OR 1.61 (CI 1.14-2.27); OR 1.48 (CI 1.03-2.13)]. Both objective and subjective poor distance and near visual acuity were associated with worse cognitive functioning. CONCLUSIONS: Arthritis, stroke and the co-occurrence of various chronic physical diseases are associated with higher prevalence of visual impairment. Visual impairment is associated with higher prevalence of depression and poorer cognitive function results. There is a need to implement patient-centered care involving special visual assessment in these cases.

Synthesis, characterization and thermal behaviour of solid-state compounds of benzoates with some bivalent transition metal ions

Solid-state MBz compounds, where M stands for bivalent Mn, Fe, Co, Ni, Cu and Zn and Bz is benzoate, have been synthesized. Simultaneous thermogravimetry and differential thermal analysis (TG-DTA), differential scanning calorimetry (DSC), infrared spectroscopy and complexometry were used to characterize and to study the thermal behaviour of these compounds. The procedure used in the preparation of the compounds via reaction of basic carbonates with benzoic acid is not efficient in eliminating excess acid. However the TG-DTA curves permitted to verify that the binary compounds can be obtained by thermosynthesis, because the benzoic acid can be eliminated before the thermal decomposition of these compounds. The results led to information about the composition, dehydration, thermal stability, thermal decomposition and structure of the isolated compounds. On heating, these compounds decompose in two (Mn, Co, Ni, Zn) or three (Fe, Cu) steps with formation of the respective oxide (Mn3O4, Fe2O3, Co3O4, NiO, CuO and ZnO) as final residue. The theoretical and experimental spectroscopic studies suggest a covalent bidentate bond between ligand and metallic center.

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Preparation and properties of perichromic dye: an undergraduate laboratory

An undergraduate experiment that illustrates the phenomenon of perichromism-the sensitivity of a dye to its microenvironment, as assessed by color changes of its solutions-is described. An easily prepared perichromic imine is synthesized and characterized, and its solvatochromism, thermochromism, halochromism, and preferential solvation in binary solvent mixtures are demonstrated by visual inspection of its solutions. The results are rationalized by invoking solute - solvent interactions in the various media.

UV determination of epinephrine, uric acid, and acetaminophen in pharmaceutical formulations and some human body fluids using multivariate calibration

In this work, a spectrophotometric methodology was applied in order to determine epinephrine (EP), uric acid (UA), and acetaminophen (AC) in pharmaceutical formulations and spiked human serum, plasma, and urine by using a multivariate approach. Multivariate calibration methods such as partial least squares (PLS) methods and its derivates were used to obtain a model for simultaneous determination of EP, UA and AC with good figures of merit and mixture design was in the range of 1.8 - 35.3, 1.7 - 16.8, and 1.5 - 12.1 µg mL-1. The 2nd derivate PLS showed recoveries of 95.3 - 103.3, 93.3 - 104.0, and 94.0 - 105.5 µg mL-1 for EP, UA, and AC, respectively.

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.

Synthesis and thermal studies of solid state 2-chloro-benzylidenepyruvic acid and its compounds with sodium, aluminium (III), gallium (III) and indium (III) cations

The synthesis of sodium 2-chlorobenzylidenepyruvate and its corresponding acid as well as binary, binary together with it's acid or hydroxo-2-chorobenzylidenepyruvate of aluminium (III), gallium (III) and indium (III), were isolated. Chemical analysis, thermogravimetry, derivative thermogravimetry (TG/DTG), simultaneous thermogravimetry-differential thermal analysis (TG-DTA) and X-ray powder diffractometry have been employed to characterize and to study the thermal behaviour of these compounds. The results provided information concerning the stoichiometry, crystallinity, thermal stability and thermal decomposition.

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.

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.

Word Equations and Related Topics. Independence, Decidability and Characterizations

The three main topics of this work are independent systems and chains of word equations, parametric solutions of word equations on three unknowns, and unique decipherability in the monoid of regular languages. The most important result about independent systems is a new method giving an upper bound for their sizes in the case of three unknowns. The bound depends on the length of the shortest equation. This result has generalizations for decreasing chains and for more than three unknowns. The method also leads to shorter proofs and generalizations of some old results. Hmelevksii’s theorem states that every word equation on three unknowns has a parametric solution. We give a significantly simplified proof for this theorem. As a new result we estimate the lengths of parametric solutions and get a bound for the length of the minimal nontrivial solution and for the complexity of deciding whether such a solution exists. The unique decipherability problem asks whether given elements of some monoid form a code, that is, whether they satisfy a nontrivial equation. We give characterizations for when a collection of unary regular languages is a code. We also prove that it is undecidable whether a collection of binary regular languages is a code.

Immunogenicity of an inactivated bovine herpesvirus type 5 strain defective in thymidine kinase and glycoprotein E

The immunogenicity of an inactivated, experimental vaccine based on a bovine herpesvirus type 5 strain defective in thymidine kinase and glycoprotein E (BoHV-5 gE/TKΔ) was evaluated in cattle and the results were compared with a vaccine containing the parental BoHV-5 strain (SV507/99). To formulate the vaccines, each virus (wildtype SV507/99 and BoHV-5 gE/TK∆) was multiplied in cell culture and inactivated with binary ethyleneimine (BEI). Each vaccine dose contained approximately of 10(7.5) TCID50 of inactivated virus mixed with an oil-based adjuvant (46:54). Forty calves, 6 to 9-months-old, were allocated into two groups of 20 animals each and vaccinated twice (days 0 and 22pv) by the subcutaneous route with either vaccine. Serum samples collected at day 0 and at different intervals after vaccination were tested for virus neutralizing (VN) antibodies against the parental virus and against heterologous BoHV-5 and BoHV-1 isolates. The VN assays demonstrated seroconversion to the respective homologous viruses in all vaccinated animals after the second vaccine dose (mean titers of 17.5 for the wildtype vaccine; 24.1 for the recombinant virus). All animals remained reagents up to day 116 pv, yet showing a gradual reduction in VN titers. Animals from both vaccine groups reacted in similar VN titers to different BoHV-1 and BoHV-5 isolates, yet the magnitude of serological response of both groups was higher against BoHV-5 field isolates. Calves vaccinated with the recombinant virus did not develop antibodies to gE as verified by negative results in a gE-specific ELISA, what would allow serological differentiation from naturally infected animals. Taken together, these results indicate that inactivated antigens of BoHV-5 gE/TK recombinant virus induced an adequate serological response against BoHV-5 and BoHV-1 and thus can be used as an alternative, differential vaccine candidate.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Combinatorics on Words. New Aspects on Avoidability, Defect Effect, Equations and Palindromes

In this thesis we examine four well-known and traditional concepts of combinatorics on words. However the contexts in which these topics are treated are not the traditional ones. More precisely, the question of avoidability is asked, for example, in terms of k-abelian squares. Two words are said to be k-abelian equivalent if they have the same number of occurrences of each factor up to length k. Consequently, k-abelian equivalence can be seen as a sharpening of abelian equivalence. This fairly new concept is discussed broader than the other topics of this thesis. The second main subject concerns the defect property. The defect theorem is a well-known result for words. We will analyze the property, for example, among the sets of 2-dimensional words, i.e., polyominoes composed of labelled unit squares. From the defect effect we move to equations. We will use a special way to define a product operation for words and then solve a few basic equations over constructed partial semigroup. We will also consider the satisfiability question and the compactness property with respect to this kind of equations. The final topic of the thesis deals with palindromes. Some finite words, including all binary words, are uniquely determined up to word isomorphism by the position and length of some of its palindromic factors. The famous Thue-Morse word has the property that for each positive integer n, there exists a factor which cannot be generated by fewer than n palindromes. We prove that in general, every non ultimately periodic word contains a factor which cannot be generated by fewer than 3 palindromes, and we obtain a classification of those binary words each of whose factors are generated by at most 3 palindromes. Surprisingly these words are related to another much studied set of words, Sturmian words.

Climate, soil and tree flora relationships in forests in the state of São Paulo, southeastern Brasil

ABSTRACT - (Climate, soil and tree flora relationships in forests in the state of São Paulo, southteastern Brasil). With the aim of verifying possible influences of abiotic features on the spatial distribution of forest tree species and families, thirteen surveys in the state of São Paulo were selected, representing different conditions (localization at the extreme coordenates and altitudes, succesional stages, surveying methods). By applying Jaccard's Index to the binary matrices of 806 synonymized specific binomina and 79 families (Cronquist's system) phenograms were constructed using the method of the unweighted pair grouping by mathematical average (UPGMA). The species formed two floristic blocks: hygrophyllous (yearly rainfall greater than 2000 mm without dry season) and mesophyllous (yearly rainfall about 1400 mm with variable dry season). The latter was divided in two other groups: the high-altitudinal (median altitudes higher than 750 m, frost average frequency greater than 3 days/year) and low-altitudinal. Both mesophyllous floristic blocks were subdivided according to soil conditions (texture, eutrophism, acid or allic dystrophism, iron content). At the family level the relations were weak, but also showed the soil nutritional status as a possible constraint to the spatial partition of families.