Updating of the hierarchical rock mass rating (HRMR) system and a new subsystem developed for weathered granite formations

The RMR system is still very much applied in rock mechanics engineering context. It is based on the evaluation of six weights to obtain a final rating. To obtain the final rating a considerable amount of information is needed concerning the rock mass which can be difficult to obtain in some projects or project stages at least with accuracy. In 2007 an alternative classification scheme based on the RMR, the Hierarchical Rock Mass Rating (HRMR) was presented. The main feature of this system was the adaptation to the level of knowledge existent about the rock mass to obtain the classification of the rock mass since it followed a decision tree approach. However, the HRMR was only valid for hard rock granites with low fracturing degrees. In this work, the database was enlarged with approximately 40% more cases considering other types of granite rock masses including weathered granites and based on this increased database the system was updated. Granite formations existent in the north of Portugal including Porto city are predominantly granites. Some years ago a light rail infrastructure was built in the city of Porto and surrounding municipalities whi h involved considerable challenges due to the high heterogeneity levels of the granite formations and the difficulties involved in their geomechanical characterization. In this work it is intended to provide also a contribution to improve the characterization of these formations with special emphasis to the weathered horizons. A specific subsystem applicable to the weathered formations was developed. The results of the validation of these systems are presented and show acceptable performances in identifying the correct class using less information than with the RMR system.

Outcrossing rate of Couratari multiflora (J.Smith) Eyma (Lecythidaceae), a low-density tropical tree species from a central Amazonian rainforest

A multilocus mixed-mating model was used to evaluate the mating system of a population of Couratari multiflora, an emergent tree species found in low densities (1 individual/10 ha) in lowland forests of central Amazonia. We surveyed and observed phenologically 41 trees in an area of 400 ha. From these, only four mother trees were analyzed here because few of them set fruits, which also suffered high predation. No difference was observed between the population multilocus outcrossing rate (t mp = 0.953 ± 0.040) and the average single locus rate (t sp = 0.968 ± 0.132). The four mother trees were highly outcrossed (t m ~ 1). Two out of five loci showed departures from the Hardy-Weinberg Equilibrium (HWE) expectations, and the same results occurred with the mixed-mating model. Besides the low number of trees analyzed, the proportion of loci in HWE suggests random mating in the population. However, the pollen pool was heterogeneous among families, probably due to both the small sample number and the flowering of trees at different times of the flowering season. Reproductive phenology of the population and the results presented here suggest, at least for part of the population, a long-distance pollen movement, around 1,000 m.

Density, size and distribution of stomata in 35 rainforest tree species in Central Amazonia

Stomata are turgor-operated valves that control water loss and CO2 uptake during photosynthesis, and thereby water relation and plant biomass accumulation is closely related to stomatal functioning. The aims of this work were to document how stomata are distributed on the leaf surface and to determine if there is any significant variation in stomatal characteristics among Amazonian tree species, and finally to study the relationship between stomatal density (S D) and tree height. Thirty five trees (>17 m tall) of different species were selected. Stomatal type, density (S D), size (S S) and stomatal distribution on the leaf surface were determined using nail polish imprints taken from both leaf surfaces. Irrespective of tree species, stomata were located only on the abaxial surface (hypostomaty), with large variation in both S D and S S among species. S D ranged from 110 mm-2 in Neea altissima to 846 mm-2 in Qualea acuminata. However, in most species S D ranges between 271 and 543 mm-2, with a negative relationship between S D and S S. We also found a positive relationship between S D and tree height (r² = 0.14, p < 0.01), but no correlation was found between S D and leaf thickness. The most common stomatal type was anomocytic (37%), followed by paracytic (26%) and anisocytic (11%). We conclude that in Amazonian tree species, stomatal distribution on the leaf surface is a response most likely dependent on the genetic background of every species, rather than a reaction to environmental changes, and that somehow S D is influenced by environmental factors dependent on tree height.

Tree communities of white-sand and terra-firme forests of the upper Rio Negro

The high tree diversity and vast extent of Amazonian forests challenge our understanding of how tree species abundance and composition varies across this region. Information about these parameters, usually obtained from tree inventories plots, is essential for revealing patterns of tree diversity. Numerous tree inventories plots have been established in Amazonia, yet, tree species composition and diversity of white-sand and terra-firme forests of the upper Rio Negro still remain poorly understood. Here, we present data from eight new one-hectare tree inventories plots established in the upper Rio Negro; four of which were located in white-sand forests and four in terra-firme forests. Overall, we registered 4703 trees > 10 cm of diameter at breast height. These trees belong to 49 families, 215 genera, and 603 species. We found that tree communities of terra-firme and white-sand forests in the upper Rio Negro significantly differ from each other in their species composition. Tree communities of white-sand forests show a higher floristic similarity and lower diversity than those of terra-firme forests. We argue that mechanisms driving differences between tree communities of white-sand and terra-firme forests are related to habitat size, which ultimately influences large-scale and long-term evolutionary processes.

Biological and morphometric aspects and rearing of Syssphinx molina (Cramer) (Lepidoptera: Saturniidae), a defoliator of parica tree

The objective of this research was to describe the biological and morphometric aspects of the parica tree defoliator, Syssphinx molina (Cramer), and make recommendations about the insect rearing. The life cycle was 62.9 days with mean periods for the egg, larval, pre-pupal and pupal stages of 5.6, 31.1, 2.2 and 16.6 days respectively. The pupal viability was 60.5% for females and 48.6% for males. The sexual ratio was 0.5 with mean production of 182.3 ± 2.2 eggs per female and egg viability of 24.3%. The mean longevity was 7.9 ± 2 and 8.1 ± 3 days for females and males respectively. Other parameters were also observed and compared with description of other Saturniidae species.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Updated List and identification key of 219 tree species of white sand forests of the Allpahuayo Mishana National Reserve, Loreto, Peru

White sand forests, although low in nutrients, are characterized not only by several endemic species of plants but also by several monodominant species. In general, plants in this forest have noticeably thin stems. The aim of this work was to elaborate a parallel dichotomous key for the identification of Angiosperm tree species occurring on white sand forests at the Allpahuayo Mishana National Reserve, Loreto, Peru. We compiled a list of species from several publications in order to have the most comprehensive list of species that occur on white sand forest. We found 219 species of Angiosperm, the more abundant species were Pachira brevipes (26.27%), Caraipa utilis (17.90%), Dicymbe uaiparuensis (13.27%), Dendropanax umbellatus (3.28%), Sloanea spathulata (2.52%), Ternstroemia klugiana (2.30%), Haploclathra cordata (2.28%), Parkia igneiflora (1.20%), Emmotum floribundum (1.06%), Ravenia biramosa (1.04%) among others. Most species of white sand forests can be distinguished using characteristics of stems, branches and leaves. This key is very useful for the development of floristic inventories and related projects on white sand forests from Allpahuayo Mishana National Reserve.

Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Fine time scaling of purifying selection on human nonsynonymous mtDNA mutations based on the worldwide population tree and mother-child pairs

A high-resolution mtDNA phylogenetic tree allowed us to look backward in time to investigate purifying selection. Purifying selection was very strong in the last 2,500 years, continuously eliminating pathogenic mutations back until the end of the Younger Dryas (∼11,000 years ago), when a large population expansion likely relaxed selection pressure. This was preceded by a phase of stable selection until another relaxation occurred in the out-of-Africa migration. Demography and selection are closely related: expansions led to relaxation of selection and higher pathogenicity mutations significantly decreased the growth of descendants. The only detectible positive selection was the recurrence of highly pathogenic nonsynonymous mutations (m.3394T>C-m.3397A>G-m.3398T>C) at interior branches of the tree, preventing the formation of a dinucleotide STR (TATATA) in the MT-ND1 gene. At the most recent time scale in 124 mother-children transmissions, purifying selection was detectable through the loss of mtDNA variants with high predicted pathogenicity. A few haplogroup-defining sites were also heteroplasmic, agreeing with a significant propensity in 349 positions in the phylogenetic tree to revert back to the ancestral variant. This nonrandom mutation property explains the observation of heteroplasmic mutations at some haplogroup-defining sites in sequencing datasets, which may not indicate poor quality as has been claimed.

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

New approach on the bioconversion of vineyard pruning waste into surface-active compounds by Lactobacillus paracasei

Strategic funding of UID/BIO/04469/2013 unit and project ref RECI/BBB-EBI/0179/2012 (project number FCOMP-01-0124-FEDER-027462) and Xanel Vecino post-doctoral grant (ref SFRH/BPD/101476/2014) funded by Fundação para a Ciência e a Tecnologia, Portugal