Processo de reparo em feridas de extração dentária em camundongos tratados com o complexo Symphytum officinale e Calendula officinallis

Medicamentos homeopáticos como o Symphytum officinalle e a Calendula officinallis são dotados de propriedades anti-sépticas, antiinflamatória, cicatrizantes e também agem como promotores da consolidação de fraturas ósseas. Neste trabalho, uniram-se esses dois medicamentos similares em um complexo para verificar o seu efeito no reparo em feridas de extração dentária em camundongos. O complexo Symphytum officinalle e Calendula officinallis nas potências de 6CH e 3CH, respectivamente, foi ministrado por via oral ao grupo tratado durante 5 dias antes e após a extração do incisivo superior direito. No grupo controle, administraram-se 5ml de álcool etílico a 70% diluídos em 30 ml de soro fisiológico. Após a proservação, os animais foram sacrificados, a maxila direita separada da esquerda, fixada e processada para inclusão em parafina. Após a microtomia, os cortes obtidos foram corados pela H/E. A análise histológica mostrou que, tanto no grupo controle como no tratado, o alvéolo dentário estava preenchido por tecido de granulação e tecido ósseo neoformado, com graus variáveis de maturação, rico em osteócitos. No entanto, nos animais tratados, o processo de reparo em feridas após extração dentária do incisivo superior direito mostrou um avanço progressivo de neoformação óssea mais acentuado quando comparado ao grupo controle, em tempos equivalentes. Estes resultados enfatizam as propriedades biológicas do complexo Symphytum officinalle e Calendula officinallis e sua possível utilização como recurso terapêutico na Odontologia.

Análise de risco da ocorrência de Sigatoka-negra baseada em modelos polinomiais: um estudo de caso

A Sigatoka-negra (Mycosphaerella fijiensis) ameaça os bananais comerciais em todas as áreas produtoras do mundo e provoca danos quantitativos e qualitativos na produção, acarretando sérios prejuízos financeiros. Faz-se necessário o estudo da vulnerabilidade das plantas em diversos estádios de desenvolvimento e das condições climáticas favoráveis à ocorrência da doença. Objetivou-se com este trabalho desenvolver um modelo probabilístico baseado em funções polinomiais que represente o risco de ocorrência da Sigatokanegra em função da vulnerabilidade decorrente de fatores intrínsecos à planta e ao ambiente. Realizou-se um estudo de caso, em bananal comercial localizado em Jacupiranga, Vale do Ribeira, SP, considerando o monitoramento semanal do estado da evolução da doença, séries temporais de dados meteorológicos e dados de sensoriamento remoto. Foram gerados mapas georreferenciados do risco da Sigatoka-negra em diferentes épocas do ano. Um modelo para estimar a evolução da doença a partir de imagens de satélite foi obtido com coeficiente de determinação R² igual a 0,9. A metodologia foi desenvolvida para a detecção de épocas e locais que reúnem condições favoráveis à ocorrência da Sigatoka-negra e pode ser aplicada, com os devidos ajustes, em diferentes localidades, para avaliar o risco da ocorrência da doença em polos produtores de banana.

A study of the hydrolysis pathway in oxalic acid catalyzed reacting TMOS-water mixtures under ultrasound stimulation

The hydrolysis of TMOS in oxalic acid catalyzed reacting TMOS-water mixtures, under ultrasound stimulation, was studied by fitting a simplified dissolution and reaction modeling for samples, the hydrolysis rate of which had been measured in a previous work. The reaction pathway represented in a ternary diagram shows a heterogeneous step for the reaction which gradually progresses until complete homogenization of the system. Besides the water dissolved due to the homogenizing effect of the alcohol, ultrasound maintains a virtual and additional dissolution of water located at the interface between the TMOS and water during the heterogeneous step of the reaction. The mean radius of the heterogeneity represented by water dispersed in TMOS was evaluated as around 150 Angstrom. The oxalic acid concentration accordingly increases the hydrolysis rate constant but its fundamental role on the solubility of water in TMOS could not unequivocally be established.

A recursive approach to space resection using straight lines

An approach using straight lines as features to solve the photogrammetric space resection problem is presented. An explicit mathematical model relating straight lines, in both object and image space, is used. Based on this model, Kalman Filtering is applied to solve the space resection problem. The recursive property of the filter is used in an iterative process which uses the sequentially estimated camera location parameters to feedback to the feature extraction process in the image. This feedback process leads to a gradual reduction of the image space for feature searching, and consequently eliminates the bottleneck due to the high computational cost of the image segmentation phase. It also enables feature extraction and the determination of feature correspondence in image and object space in an automatic way, i.e., without operator interference. Results obtained from simulated and real data show that highly accurate space resection parameters are obtained as well as a progressive processing time reduction. The obtained accuracy, the automatic correspondence process, and the short related processing time show that the proposed approach can be used in many real-time machine vision systems, making possible the implementation of applications not feasible until now.

Rainfall representativeness at TRMM & GPM PR resolution

Precipitation radar on board the TRMM satellite was a milestone in the rainfall observation capability in the large scale. Stemming from TRMM the new mission GPM (Global Precipitation Measurement) is to overcome some TRMM shortcomings like the high level of the PR MDZ. However, for major problems like the PR horizontal resolution, significant improvements are not foreseeable. This papers investigates the impact of TRMM PR resolution on the structure of tropical rainfall. The issue is approached by both gradient analysis and texture verification. Results indicate that the impact maybe significant, affecting important applications like in NWP. © 2005 IEEE.

Solid particles in the tropical lowest stratosphere

We report in situ and remote observations proving occasional occurrence of solid particles in the tropical lowest stratosphere, 200km from deep convective events. The particles were found during field campaigns in Southeast Brazil (49.03 W 22.36 S). They occur in the altitude range from 17.5 to 20.8 km, at temperatures up to at least 10 K above the expected frost point temperature. While stability of ice particles at these altitudes is unexpected from a theoretical point of view, it is argued that these observations are indications of tropospheric air masses penetrating into the stratosphere during convective overshoots. It is argued that the intrusion of tropospheric air must have carried a large amount of water with it, which effectively hydrated the lowest stratosphere, and consequently suppressed sublimation. This conclusion is further supported by a separate water vapor mixing ratio profile obtained at the same observation site.

Investigations on the full polarimetric PALSAR data to discriminate macrophytes species in the Amazon floodplain wetland

The purpose of this work is to evaluate the capacity of full polarimetric L band data to discriminate macrophyte species in Amazon wetland. Fieldwork was carried out almost simultaneously to the acquisition of the full polarimetric PALSAR data. Coherent and incoherent attributes were extracted from the image, and macrophyte morphological variables were measured on the ground. The image attributes and the macrophyte variables were compared in order to evaluate their application for discriminating macrophytes species. The findings suggest that polarimetric information could be adopted to discriminate plant species based on morphology, and that estimation of plant biomass and productivity could be improved by using the polarimetric information. © 2010 IEEE.

Prevention of soil-transmitted helminth infection

Soil-transmitted helminths (STHs) form one of the most important groups of infectious agents and are the cause of serious global health problems. The most important STHs are roundworms (Ascaris lumbricoides), whipworms (Trichuris trichiura) and hookworms (Necator americanus or Ancylostoma duodenale); on a global level, more than a billion people have been infected by at least one species of this group of pathogens. This review explores the general concepts of transmission dynamics and the environment and intensity of infection and morbidity of STHs. The global strategy for the control of soil-transmitted helminthiasis is based on (i) regular anthelminthic treatment, (ii) health education, (iii) sanitation and personal hygiene and (iv) other means of prevention with vaccines and remote sensoring. The reasons for the development of a control strategy based on population intervention rather than on individual treatment are discussed, as well as the costs of the prevention of STHs, although these cannot always be calculated because interventions in health education are difficult to measure. An efficient sanitation infrastructure can reduce the morbidity of STHs and eliminates the underlying cause of most poverty-related diseases and thus supports the economic development of a country.

Land use image classification through optimum-path forest clustering

Land use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Model of a game for improving integrated decisions in production management

This paper presents the results obtained with a business game whose model represents the decision making process related to two moments at an industrial company. The first refers to the project of the industrial plant, and the second to its management. The game model was conceived so the player's first decision would establish capacity and other parameters such as quantities of each product to produce, marketing expenses, research and development, quality, advertising, salaries, if purchases will be made in installments or in cash, if there will be credit sales and how many installments will be allowed and the number of workers in the assembly area. An experiment was conducted with employees of a Brazilian company. Data obtained indicate that the players have lack of contents, especially in finances. Although these results cannot be generalized, they confirm prior results with undergraduate and graduate students and they indicate the need for reinforcement in this undergraduate area. © 2012 Springer-Verlag.

Submerged macrophytes height estimation by echosounder data sample

Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Greenhouse gas mitigation potential from green harvested sugarcane scenarios in São Paulo State, Brazil

Brazil is a major sugarcane producer and São Paulo State cultivates 5.5 million hectares, close to 50% of Brazil's sugarcane area. The rapid increase in production has brought into question the sustainability of biofuels, especially considering the greenhouse gas (GHG) emissions associated to the agricultural sector. Despite the significant progress towards the green harvest practices, 1.67 million hectares were still burned in São Paulo State during the 2011 harvest season. Here an emissions inventory for the life cycle of sugarcane agricultural production is estimated using IPCC methodologies, according to the agriculture survey data and remote sensing database. Our hypothesis is that 1.67 million hectares shall be converted from burned to green harvest scenarios up to years 2021 (rate 1), 2014 (rate 2) or 2029 (rate 3). Those conversions would represent a significant GHG mitigation, ranging from 50.5 to 70.9 megatons of carbon dioxide equivalent (Mt CO2eq) up to 2050, depending on the conversion rate and the green harvest systems adopted: conventional (scenario S1) or conservationist management (scenario S2). We show that a green harvest scenario where crop rotation and reduced soil tillage are practiced has a higher mitigation potential (70.9 Mt CO2eq), which is already practiced in some of the sugarcane areas. Here we support the decision to not just stop burning prior to harvest, but also to consider other better practices in sugarcane areas to have a more sustainable sugarcane based ethanol production in the most dense cultivated sugarcane region in Brazil. © 2013 Elsevier Ltd. All rights reserved.