Compressão Seletiva de Imagens Coloridas com Detecção Automática de Regiões de Interesse

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

Técnica para segmentação automática de imagens microscópicas de componentes sanguíneos e classificação diferencial de leucócitos baseada em lógica fuzzy

Automatic detection of blood components is an important topic in the field of hematology. The segmentation is an important stage because it allows components to be grouped into common areas and processed separately and leukocyte differential classification enables them to be analyzed separately. With the auto-segmentation and differential classification, this work is contributing to the analysis process of blood components by providing tools that reduce the manual labor and increasing its accuracy and efficiency. Using techniques of digital image processing associated with a generic and automatic fuzzy approach, this work proposes two Fuzzy Inference Systems, defined as I and II, for autosegmentation of blood components and leukocyte differential classification, respectively, in microscopic images smears. Using the Fuzzy Inference System I, the proposed technique performs the segmentation of the image in four regions: the leukocyte’s nucleus and cytoplasm, erythrocyte and plasma area and using the Fuzzy Inference System II and the segmented leukocyte (nucleus and cytoplasm) classify them differentially in five types: basophils, eosinophils, lymphocytes, monocytes and neutrophils. Were used for testing 530 images containing microscopic samples of blood smears with different methods. The images were processed and its accuracy indices and Gold Standards were calculated and compared with the manual results and other results found at literature for the same problems. Regarding segmentation, a technique developed showed percentages of accuracy of 97.31% for leukocytes, 95.39% to erythrocytes and 95.06% for blood plasma. As for the differential classification, the percentage varied between 92.98% and 98.39% for the different leukocyte types. In addition to promoting auto-segmentation and differential classification, the proposed technique also contributes to the definition of new descriptors and the construction of an image database using various processes hematological staining

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Análise cintilográfica da deposição pulmonar de radioaerossol após associação da nebulização através dos dispositivos mesh e jato com a ventilação não invasiva em indivíduos normais e com pneumopatias obstrutivas crônicas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Avaliação por ressonância magnética funcional e estimulação magnética transcraniana da intervenção única da terapia espelho em pacientes após acidente vascular cerebral isquêmico

Mirror therapy (MT) is being used as a rehabilitation tool in various diseases, including stroke. Although some studies have shown its effectiveness, little is known about neural mechanisms that underlie the rehabilitation process. Therefore, this study aimed at assessing cortical neuromodulation after a single MT intervention in ischemic stroke survivors, by means of by functional Magnetic Resonance Imaging (fMRI) and Transcranial Magnetic Stimulation (TMS). Fifteen patients participated in a single thirty minutes MT session. fMRI data was analyzed bilaterally in the following Regions of Interest (ROI): Supplementary Motor Area (SMA), Premotor cortex (PMC), Primary Motor cortex (M1), Primary Sensory cortex (S1) and Cerebellum. In each ROI, changes in the percentage of occupation and beta values were computed. Group fMRI data showed a significant decreased in the percentage of occupation in PMC and cerebellum, contralateral to the affected hand (p <0.05). Significant increase in beta values was observed in the following contralateral motor areas: SMA, Cerebellum, PMC and M1 (p<0,005). Moreover, a significant decrease was observed in the following ipsilateral motor areas: PMC and M1 (p <0,001). In S1 a bilateral significant decrease (p<0.0005) was observed.TMS consisted of the analysis of Motor Evoked Potential (MEP) of M1 hotspot. A significant increase in the amplitude of the MEP was observed after therapy in the group (p<0,0001) and individually in 4 patients (p <0.05). Altogether, our results imply that single MT intervention is already capable of promoting changes in neurobiological markers toward patterns observed in healthy subjects. Furthermore, the contralateral hemisphere motor areas changes are opposite to the ones in the ipsilateral side, suggesting an increase system homeostasis.

Participação do circuito dopaminérgico nas alterações do comportamento de medo inato de camundongos infectados pelo Toxoplasma gondii

The protozoan parasite Toxoplasma gondii transforms the innate aversion of rats for cat urine into a fatal attraction, that increases the likelihood of the parasite completing its life cycle in the cat s intestine. The neural circuits implicated in innate fear, anxiety, and learned fear all overlap considerably, raising the possibility, that T. gondii may disrupt all of these nonspecifically. In this study, we evaluated immunoreactivity for tyrosine hydroxylase (TH) in areas associated with innate fear of infected male swiss mice. The latent Toxoplasma infection converted the aversion of mice to feline odors into attraction. This loss of fear is remarkably specific, as demonstrated by Vyas et al (2007), because infection did not diminish learned fear, anxiety-like behavior, olfaction, or nonaversive learning. However, the neurochemical mechanism related to alterations in innate fear due to T. gondii infection remains poorly studied. 20 mice were inoculated with bradyzoites (25 cysts) from a Toxoplasma gondii (Me-49 strain). The brains were removed after 60 days, sectioned and processed for TH immunohistochemistry. The correlation between the amount of cysts per area and the densitometric analysis of neurotransmitter reactivity was low in the areas implicated in innate fear of infected animals, when comparated with noninfected controls

Estudo da digestão de sedimento de curtume visando a extração do cromo por microemulsão

Leather tanneries generate effluents with high content of heavy metals, especially chromium, which is used in the mineral tanning process. Microemulsions have been studied in the extraction of heavy metals from aqueous solutions. Considering the problems related with the sediment resulting from the tanning process, due to its high content in chromium, in this work this sediment was characterized and microemulsion systems were applied for chromium removal. The extraction process consists in the removal of heavy metal ions present in an aqueous feeding solution (acid digestion solution) by a microemulsion system. First three different solid sludge digestion methods were evaluated, being chosen the method with higher digestion capacity. For this digestion method, seeking its optimization, was evaluated the influence of granule size, temperature and digestion time. Experimental results showed that the method proposed by USEPA (Method A) was the most efficient one, being obtained 95.77% of sample digestion. Regarding to the evaluated parameters, the best results were achieved at 95°C, 14 Mesh granule size, and 60 minutes digestion time. For chromium removal, three microemulsion extraction methods were evaluated: Method 1, in a Winsor II region, using as aqueous phase the acid digestion solution; Method 2, in a Winsor IV region, being obtained by the addition of the acid digestion solution to a microemulsion phase, whose aqueous phase is distilled water, until the formation of Winsor II system; and Method 3, in a Winsor III region, consisting in the formation of a Winsor III region using as aqueous phase the acid digestion solution, diluted in NaOH 0.01N. Seeking to optimize the extraction process only Method 1 (Systems I, II, and VIII) and Method 2 (System IX) were evaluated, being chosen points inside the interest regions (studied domains) to study the influence of contact time and pH in the extraction percentiles. The studied systems present the following compositions: System I: Surfactant Saponified coconut oil, Cosurfactant 1-Butanol, Oil phase Kerosene, Aqueous phase 2% NaCl solution; System II: Aqueous phase Acid digestion solution with pH adjusted using KOH (pH 3.5); System VIII: Aqueous phase - Acid digestion solution (pH 0.06); and System IX Aqueous phase Distilled water (pH 10.24), the other phases of Systems II, VIII and IX are similar to System I. Method 2 showed to be the more efficient one regarding chromium extraction percentile (up to 96.59% - pH 3.5). Considering that with Method 2 the microemulsion region only appears in the Winsor II region, it was studied Method 3 (System X) for the evaluation and characterization of a triphasic system, seeking to compare with a biphases system. System X is composed by: Surfactant Saponified coconut oil, Cosurfactant 1-Butanol, Oil phase Kerosene, Aqueous phase Acid digestion solution diluted with water and with its pH adjusted using 0.01N NaOH solution. The biphasic and triphasic microemulsion systems were analyzed regarding its viscosity, extraction efficiency and drop effective diameter. The experimental results showed that for viscosity studies the obtained values were low for all studied systems, the diameter of the drop is smaller in the Winsor II region, with 15.5 nm, reaching 46.0 nm in Winsor III region, being this difference attributed to variations in system compositions and micelle geometry. In chromium extraction, these points showed similar results, being achieved 99.76% for Winsor II system and 99.62% for Winsor III system. Winsor III system showed to be more efficient due to the obtaining of a icroemulsion with smaller volume, with the possibility to recover the oil phase in excess, and the use of a smaller proportion of surfactant and cosurfactant (C/S)

When wolves cry: long distance calling by wild maned wolves

The maned wolf (Chrysocyon brachyurus Illiger 1815) is the biggest canid in South America and it is considered a “near threatened” species by IUCN. Because of its nocturnal, territorial and solitary habits, there are still many understudied aspects of their behavior in natural environments, including acoustic communication. In its vocal repertoire, the wolf presents a longdistance call named “roar-bark” which, according to literature, functions for spacing maintenance between individuals and/or communication between members of the reproductive pair inside the territory. In this context, this study aimed: 1) to compare four methods for detecting maned wolf’s roar-barks in recordings made in a natural environment, in order to elect the most efficient one for our project; 2) to understand the night emission pattern of these vocalizations, verifying possible weather and moon phases influences in roarbark’s emission rates; and 3) to test Passive Acoustic Monitoring as a tool to identify the presence of maned wolves in a natural environment. The study area was the Serra da Canastra National Park (Minas Gerais, Brazil), where autonomous recorders were used for sound acquisition, recording all night (from 06pm to 06am) during five days in December/2013 and every day from April to July/2014. Roar-barks’ detection methods were tested and compared regarding time needed to analyze files, number of false positives and number of correctly identified calls. The mixed method (XBAT + manual) was the most efficient one, finding 100% of vocalizations in almost half of the time the manual method did, being chosen for our data analysis. By studying roarbarks’ temporal variation we verified that the wolves vocalize more in the early hours of the evening, suggesting an important social function for those calls at the beginning of its period of most intense activity. Average wind speed negatively influenced vocalization rate, which may indicate lower sound reception of recorders or a change in behavioral patterns of wolves in high speed wind conditions. A better understanding of seasonal variation of maned wolves’ vocal activity is required, but our study already shows that it is possible to detect behavioral patterns of wild animals only by sound, validating PAM as a tool in this species’ conservation.

Ocorrência de compostos de interesse emergente no aquífero Dunas-Barreiras e nos esgotos de Natal/RN

The detection of emerging interest microcontaminants in environmental samples of surface water, groundwater, drinking water, wastewater and effluents from water and sewage treatment plants (WTP and STP), in many countries, suggests these pollutants are widespread in the environment, mainly in urban areas. This is a reason for great concern, since many of these compounds are potentially harmful for humans other living beings, and they are not efficiently removed in the majority of WTP and STP, which is exacerbated by precariousness of water supply and sanitation services. In Natal, like other Brazilian cities, the sewage system serves only part of the urban area (about 30%), so that the rest of the wastewater is infiltrated in the sandy soil of the region in cesspool-dry well systems. This has resulted in contamination of groundwater in the area (sand-dune barrier aquifer, which supplies more than 50% of the city population), which has been observed by the increase in nitrate concentration in supply wells. The vulnerability of the sanddune barrier aquifer, combined with reports of the presence of emerging interest microcontaminants in Brazil and worldwide, led to this research, which investigated the occurrence of fifteen microcontaminants in Natal groundwater and sewage. Samples were collected at five wells used for water supply, the raw sewage and the effluents from biological reactors from STP (UASB and activated sludge reactors). Two samples of each sample were taken, with one week apart between the samples. To determine the contaminants, extraction of aquifer water, and raw and treated sewage samples were performed, through the technique of using SPE Strata X cartridge (Phenomenex®) to the aquifer water, and Strata SAX and Strata X (Phenomenex® ) for samples of raw and treated sewage. Subsequently the extracts were analyzed using GC-MS technique. Much of the analyzed microcontaminants were detected in groundwater and sewage. The concentrations in groundwater are generally lower than those found in the sewers. Some of the compounds (estrone, estradiol, bisphenol A, caffeine, diclofenac, naproxen, paracetamol and ibuprofen) are partially removed at STP.

Metagenômica comparativa de solo de regiões de mata atlântica e caatinga do estado do Rio Grande do Norte - Brasil

The microorganisms play very important roles in maintaining ecosystems, which explains the enormous interest in understanding the relationship between these organisms as well as between them and the environment. It is estimated that the total number of prokaryotic cells on Earth is between 4 and 6 x 1030, constituting an enormous biological and genetic pool to be explored. Although currently only 1% of all this wealth can be cultivated by standard laboratory techniques, metagenomic tools allow access to the genomic potential of environmental samples in a independent culture manner, and in combination with third generation sequencing technologies, the samples coverage become even greater. Soils, in particular, are the major reservoirs of this diversity, and many important environments around us, as the Brazilian biomes Caatinga and Atlantic Forest, are poorly studied. Thus, the genetic material from environmental soil samples of Caatinga and Atlantic Forest biomes were extracted by direct techniques, pyrosequenced, and the sequences generated were analyzed by bioinformatics programs (MEGAN MG-RAST and WEBCarma). Taxonomic comparative profiles of the samples showed that the phyla Proteobacteria, Actinobacteria, Acidobacteria and Planctomycetes were the most representative. In addition, fungi of the phylum Ascomycota were identified predominantly in the soil sample from the Atlantic Forest. Metabolic profiles showed that despite the existence of environmental differences, sequences from both samples were similarly placed in the various functional subsystems, indicating no specific habitat functions. This work, a pioneer in taxonomic and metabolic comparative analysis of soil samples from Brazilian biomes, contributes to the knowledge of these complex environmental systems, so far little explored

Estudo do genoma do vírus causador da mionecrose infecciosa em camarões e desenvolvimento de métodos para detecção de diferentes variantes

Shrimp farming is one of the activities that contribute most to the growth of global aquaculture. However, this business has undergone significant economic losses due to the onset of viral diseases such as Infectious Myonecrosis (IMN). The IMN is already widespread throughout Northeastern Brazil and affects other countries such as Indonesia, Thailand and China. The main symptom of disease is myonecrosis, which consists of necrosis of striated muscles of the abdomen and cephalothorax of shrimp. The IMN is caused by infectious myonecrosis virus (IMNV), a non-enveloped virus which has protrusions along its capsid. The viral genome consists of a single molecule of double-stranded RNA and has two Open Reading Frames (ORFs). The ORF1 encodes the major capsid protein (MCP) and a potential RNA binding protein (RBP). ORF2 encodes a probable RNA-dependent RNA polymerase (RdRp) and classifies IMNV in Totiviridae family. Thus, the objective of this research was study the IMNV complete genome and encoded proteins in order to develop a system differentiate virus isolates based on polymorphisms presence. The phylogenetic relationship among some totivirus was investigated and showed a new group to IMNV within Totiviridae family. Two new genomes were sequenced, analyzed and compared to two other genomes already deposited in GenBank. The new genomes were more similar to each other than those already described. Conserved and variable regions of the genome were identified through similarity graphs and alignments using the four IMNV sequences. This analyze allowed mapping of polymorphic sites and revealed that the most variable region of the genome is in the first half of ORF1, which coincides with the regions that possibly encode the viral protrusion, while the most stable regions of the genome were found in conserved domains of proteins that interact with RNA. Moreover, secondary structures were predicted for all proteins using various softwares and protein structural models were calculated using threading and ab initio modeling approaches. From these analyses was possible to observe that the IMNV proteins have motifs and shapes similar to proteins of other totiviruses and new possible protein functions have been proposed. The genome and proteins study was essential for development of a PCR-based detection system able to discriminate the four IMNV isolates based on the presence of polymorphic sites

Estudo e implementação de algoritmos inteligentes para detecção e classificação de falhas na medição de gás natural

This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented

Frequência da infecção por Toxoplasma gondii em galinhas caipira e frangos de corte em regiões dos Estados do Rio Grande do Norte e Paraíba

Toxoplasmosis is a zoonosis caused by Toxoplasma gondii, a protozoan that has a cosmopolitan geographic distribution and low host specificity. Usually a benign and selflimiting, infection can manifest itself in a severe systemic becoming overwhelming in fetuses and patients with immunosuppression. Domestic fowl are considered one of the most important hosts in the epidemiology of toxoplasmosis, since they are potential sources of infection for humans, in addition to playing the role of important indicators of environmental contamination by oocysts of T. gondii. We studied the prevalence of infection by the protozoan in chickens of different breeding systems mesoregions from the states of Rio Grande do Norte and Paraiba: broilers from commercial farms (200/PB) and free-range chickens of small farms (322/RN and PB). Were standardized IFAT and ELISA techniques for detecting specific antibodies in blood samples of birds, and commercial kit was used to determine the prevalence by IHAT. There was no seropositive reaction by T. gondii in the samples of broilers tested, indicating that the particularities of intensive management limit the chances of infection for these animals. Among the hens, the frequency of IgG anti-T. gondii diagnosed by the techniques of IHAT, IFAT and ELISA, respectively, were 3.73% (12/322), 37.88% (122/322) and 40.37% (130/322), for both young and adult animals. Amongst the seropositive samples by IFAT, 33 (27.05%) were positive at a dilution of 1:16, in 1:32, 31 (25.41%), in 1:64, 24 (19.67%), 15 (12.29%) in 1:128, and 19 presented titer greater than or equal to 1:256 (15.57%). The evaluation of the presence of anti-T. gondii should be careful, and reagents IHAT provided erratic results in this measure for the specie studied. This suggests the need for own standardization of the kit before the use in epidemiological studies in animal species. On the other hand, substantial agreement observed between IFAT and ELISA techniques (Kappa = 0.62) enables these methods as effective methodologies for the diagnosis of toxoplasmosis in chickens. The high prevalence of specific antibodies among poultry in the region studied attempts to the potential risk of transmission of toxoplasmosis to humans

Detecção e classificação de modos de operação do bombeio mecânico via cartas dinamométricas

The precision and the fast identification of abnormalities of bottom hole are essential to prevent damage and increase production in the oil industry. This work presents a study about a new automatic approach to the detection and the classification of operation mode in the Sucker-rod Pumping through dynamometric cards of bottom hole. The main idea is the recognition of the well production status through the image processing of the bottom s hole dynamometric card (Boundary Descriptors) and statistics and similarity mathematics tools, like Fourier Descriptor, Principal Components Analysis (PCA) and Euclidean Distance. In order to validate the proposal, the Sucker-Rod Pumping system real data are used