DETECTION OF SPORES AND HYPHAE OF ARTWORKS’ BIODETERIOGENIC FILAMENTOUS FUNGI BY RNA-FISH

Filamentous fungi are a threat to the conservation of Cultural Heritage. Thus, detection and identification of viable filamentous fungi are crucial for applying adequate Safeguard measures. RNA-FISH protocols have been previously applied with this aim in Cultural Heritage samples. However, only hyphae detection was reported in the literature, even if spores and conidia are not only a potential risk to Cultural Heritage but can also be harmful for the health of visitors, curators and restorers. Thus, the aim of this work was to evaluate various permeabilizing strategies for their application in the detection of spores/conidia and hyphae of artworks’ biodeteriogenic filamentous fungi by RNA-FISH. Besides of this, the influence of cell aging on the success of the technique and on the development of fungal autofluorescence (that could hamper the RNA-FISH signal detection) were also investigated. Five common biodeteriogenic filamentous fungi species isolated from biodegradated artworks were used as biological model: Aspergillus niger, Cladosporium sp, Fusarium sp, Penicillium sp. and Exophialia sp. Fungal autofluorescence was only detected in cells harvested from Fusarium sp, and Exophialia sp. old cultures, being aging-dependent. However, it was weak enough to allow autofluorescence/RNA-FISH signals distinction. Thus, autofluorescence was not a limitation for the application of RNA-FISH for detection of the taxa investigated. All the permeabilization strategies tested allowed to detect fungal cells from young cultures by RNA-FISH. However, only the combination of paraformaldehyde with Triton X-100 allowed the detection of conidia/spores and hyphae of old filamentous fungi. All the permeabilization strategies failed in the Aspergillus niger conidia/spores staining, which are known to be particularly difficult to permeabilize. But, even in spite of this, the application of this permeabilization method increased the analytical potential of RNA FISH in Cultural Heritage biodeterioration. Whereas much work is required to validate this RNA-FISH approach for its application in real samples from Cultural Heritage it could represent an important advance for the detection, not only of hyphae but also of spores and conidia of various filamentous fungi taxa by RNA-FISH.

Agronomic efficiency of Bradyrhizobium in peanut under different environments in Brazilian Northeast.

Several legumes have natural ability to associate with nitrogen - fixing bacteria known as rhizobia. The efficiency of this association depends on the plant and bacterial genotype and the edaphoclimatic conditions. Peanut is a tropical legume able to associate with a wide range of rhizobia and the selection of efficient bacteria is important to increase the nitrogen fixation in this crop. In order to investigate the agronomic efficiency of two Bradyrhizobiumstrains, two peanut genotypes were used in field trails carried out in three environments located at Brazilian Northeast. The genotypes (BR1 and L7 Bege) were submitted to rhizobial inoculation (SEMIA 6144 or ESA 123, both Bradyrhizobium strains, and chemical nitrogen fertilization in randomized block design experiments. The following traits were analyzed: flowering (F), main axis height (MAH), number of nodules/plant (NN), number of pods/plant (NP) and weight of pods (WP). Differential responses were found in all to treatments to NN, NP and WP, in the three environments studied. Overall, ESA 123 showed good agronomic performance inducing higher pod production. The results supportthe evaluation of the Bradyrhizobium in further experiments aiming at its recommendation to commercial inoculants in Brazilian Northeast region.

Machine Learning Unsupervised Methods in the Design of an On-board Health Monitoring System for Satellite Applications

The dissertation starts by providing a description of the phenomena related to the increasing importance recently acquired by satellite applications. The spread of such technology comes with implications, such as an increase in maintenance cost, from which derives the interest in developing advanced techniques that favor an augmented autonomy of spacecrafts in health monitoring. Machine learning techniques are widely employed to lay a foundation for effective systems specialized in fault detection by examining telemetry data. Telemetry consists of a considerable amount of information; therefore, the adopted algorithms must be able to handle multivariate data while facing the limitations imposed by on-board hardware features. In the framework of outlier detection, the dissertation addresses the topic of unsupervised machine learning methods. In the unsupervised scenario, lack of prior knowledge of the data behavior is assumed. In the specific, two models are brought to attention, namely Local Outlier Factor and One-Class Support Vector Machines. Their performances are compared in terms of both the achieved prediction accuracy and the equivalent computational cost. Both models are trained and tested upon the same sets of time series data in a variety of settings, finalized at gaining insights on the effect of the increase in dimensionality. The obtained results allow to claim that both models, combined with a proper tuning of their characteristic parameters, successfully comply with the role of outlier detectors in multivariate time series data. Nevertheless, under this specific context, Local Outlier Factor results to be outperforming One-Class SVM, in that it proves to be more stable over a wider range of input parameter values. This property is especially valuable in unsupervised learning since it suggests that the model is keen to adapting to unforeseen patterns.

Machine learning tools for protein annotation: the cases of transmembrane β-barrel and myristoylated proteins

Biology is now a “Big Data Science” thanks to technological advancements allowing the characterization of the whole macromolecular content of a cell or a collection of cells. This opens interesting perspectives, but only a small portion of this data may be experimentally characterized. From this derives the demand of accurate and efficient computational tools for automatic annotation of biological molecules. This is even more true when dealing with membrane proteins, on which my research project is focused leading to the development of two machine learning-based methods: BetAware-Deep and SVMyr. BetAware-Deep is a tool for the detection and topology prediction of transmembrane beta-barrel proteins found in Gram-negative bacteria. These proteins are involved in many biological processes and primary candidates as drug targets. BetAware-Deep exploits the combination of a deep learning framework (bidirectional long short-term memory) and a probabilistic graphical model (grammatical-restrained hidden conditional random field). Moreover, it introduced a modified formulation of the hydrophobic moment, designed to include the evolutionary information. BetAware-Deep outperformed all the available methods in topology prediction and reported high scores in the detection task. Glycine myristoylation in Eukaryotes is the binding of a myristic acid on an N-terminal glycine. SVMyr is a fast method based on support vector machines designed to predict this modification in dataset of proteomic scale. It uses as input octapeptides and exploits computational scores derived from experimental examples and mean physicochemical features. SVMyr outperformed all the available methods for co-translational myristoylation prediction. In addition, it allows (as a unique feature) the prediction of post-translational myristoylation. Both the tools here described are designed having in mind best practices for the development of machine learning-based tools outlined by the bioinformatics community. Moreover, they are made available via user-friendly web servers. All this make them valuable tools for filling the gap between sequential and annotated data.

Effective field theories and their phenomenological applications

Effective field theories (EFTs) are ubiquitous in theoretical physics and in particular in field theory descriptions of quantum systems probed at energies much lower than one or few characterizing scales. More recently, EFTs have gained a prominent role in the study of fundamental interactions and in particular in the parametriasation of new physics beyond the Standard Model, which would occur at scales Λ, much larger than the electroweak scale. In this thesis, EFTs are employed to study three different physics cases. First, we consider light-by-light scattering as a possible probe of new physics. At low energies it can be described by dimension-8 operators, leading to the well-known Euler-Heisenberg Lagrangian. We consider the explicit dependence of matching coefficients on type of particle running in the loop, confirming the sensitiveness to the spin, mass, and interactions of possibly new particles. Second, we consider EFTs to describe Dark Matter (DM) interactions with SM particles. We consider a phenomenologically motivated case, i.e., a new fermion state that couples to the Hypercharge through a form factor and has no interactions with photons and the Z boson. Results from direct, indirect and collider searches for DM are used to constrain the parameter space of the model. Third, we consider EFTs that describe axion-like particles (ALPs), whose phenomenology is inspired by the Peccei-Quinn solution to strong CP problem. ALPs generically couple to ordinary matter through dimension-5 operators. In our case study, we investigate the rather unique phenomenological implications of ALPs with enhanced couplings to the top quark.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Screening Of Miners And Millers At Decreasing Levels Of Asbestos Exposure: Comparison Of Chest Radiography And Thin-section Computed Tomography.

Chest radiography (CXR) is inferior to Thin-section computed tomography in the detection of asbestos related interstitial and pleural abnormalities. It remains unclear, however, whether these limitations are large enough to impair CXR´s ability in detecting the expected reduction in the frequency of these asbestos-related abnormalities (ARA) as exposure decreases. Clinical evaluation, CXR, Thin-section CT and spirometry were obtained in 1418 miners and millers who were exposed to progressively lower airborne concentrations of asbestos. They were separated into four groups according to the type, period and measurements of exposure and/or procedures for controlling exposure: Group I (1940-1966/tremolite and chrysotile, without measurements of exposure and procedures for controlling exposure); Group II (1967-1976/chrysotile only, without measurements of exposure and procedures for controlling exposure); Group III (1977-1980/chrysotile only, initiated measurements of exposure and procedures for controlling exposure) and Group IV (after 1981/chrysotile only, implemented measurements of exposure and a comprehensive procedures for controlling exposure). In all groups, CXR suggested more frequently interstitial abnormalities and less frequently pleural plaques than observed on Thin-section CT (p<0.050). The odds for asbestosis in groups of decreasing exposure diminished to greater extent at Thin-section CT than on CXR. Lung function was reduced in subjects who had pleural plaques evident only on Thin-section CT (p<0.050). In a longitudinal evaluation of 301 subjects without interstitial and pleural abnormalities on CXR and Thin-section CT in a previous evaluation, only Thin-section CT indicated that these ARA reduced as exposure decreased. CXR compared to Thin-section CT was associated with false-positives for interstitial abnormalities and false-negatives for pleural plaques, regardless of the intensity of asbestos exposure. Also, CXR led to a substantial misinformation of the effects of the progressively lower asbestos concentrations in the occurrence of asbestos-related diseases in miners and millers.

Ecomateriais: desenvolvimento e aplicação de materiais porosos funcionais para proteção ambiental

Fundamental aspects of the conception and applications of ecomaterials, in particular porous materials in the perspective of green chemistry are discussed in this paper. General recommendations for description and classification of porous materials are reviewed briefly. By way of illustration, some case studies of materials design and applications in pollution detection and remediation are described. It is shown here how different materials developed by our groups, such as porous glasses, ecomaterials from biomass and anionic clays were programmed to perform specific functions. A discussion of the present and future of ecomaterials in green chemistry is presented along with important key goals.

Estrutura de um curso de taxonomia de campo: o modelo aplicado em Ubatuba, São Paulo

The field activities are essential for the education of a good taxonomist. The most common problems found in field activities are: a) large number of students, b) heterogeneous educational background and unlevelled knowledge of the participants, c) repetitions and tendency of collecting the more evidents life-forms. The causes and consequences of such problems are discussed herein. The proposed solution is a methodology, based on many years of experience in field courses for undergraduate and graduate courses. Topics about the ideal number of participants, area of coverage, period of activity, division of work and the necessary material and equipment are discussed. According to the number of species collected at the same place, this methodology may result in a list of local species with precise information about the life-forms, habitat, common names, frequency, uses, phenology and further information in this kind of work. The results of the aplication of this metodology in a field course held in the region of Ubatuba-SP are presented.

História do lazer na natureza no Rio de Janeiro entre 1779 e 1838 : um estudo de caso

Universidade Estadual de Campinas . Faculdade de Educação Física

O brincar no contexto escolar : significados das brincadeiras realizadas em aulas de educação física e no recreio

Universidade Estadual de Campinas . Faculdade de Educação Física

Uma analise das alterações nas variáveis fisiológicas e aptidão física (teste da FIFA) e suas prováveis interferências no desempenho do arbitro durante a partida

Universidade Estadual de Campinas. Faculdade de Educação Física

Lazer e participação em um grupo de praticantes de escalada

Universidade Estadual de Campinas . Faculdade de Educação Física

O corpo que dança : os jovens e suas tribos urbanas

Universidade Estadual de Campinas . Faculdade de Educação Física

Lazer e grupos sociais ; : concepções e metodo

Universidade Estadual de Campinas . Faculdade de Educação Física