Chaotic synchronization in general network topology for scene segmentation

Chaotic synchronization has been discovered to be an important property of neural activities, which in turn has encouraged many researchers to develop chaotic neural networks for scene and data analysis. In this paper, we study the synchronization role of coupled chaotic oscillators in networks of general topology. Specifically, a rigorous proof is presented to show that a large number of oscillators with arbitrary geometrical connections can be synchronized by providing a sufficiently strong coupling strength. Moreover, the results presented in this paper not only are valid to a wide class of chaotic oscillators, but also cover the parameter mismatch case. Finally, we show how the obtained result can be applied to construct an oscillatory network for scene segmentation.

SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

A complex network approach to text summarization

Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this paper, we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features. (c) 2008 Elsevier Inc. All rights reserved.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Effectiveness of different final irrigation protocols in removing debris in flattened root canals

This study evaluated in vitro the capacity of debris removal from the apical third of flattened root canals, using different final irrigation protocols. Thirty human mandibular central incisors with a mesiodistal flattened root were prepared using rotary instrumentation by Endo-Flare 25.12 and Hero 642 30.06, 35.02, 40.02 files, irrigated with 2 mL of 1% NaOCl after each file. The specimens were randomly distributed into 5 groups according to the final irrigation of root canals: Group I: 10 mL of distilled water (control), Group II: 10 mL of 1% NaOCl for 8 min, Group III: 2 mL of 1% NaOCl for 2 min (repeated 4 times), Group IV: 10 mL of 2.5% NaOCl for 8 min, and Group V: 10 mL of 2.5% NaOCl for 2 min (repeated 4 times). The apical thirds of the specimens were subjected to histological processing and 6-μm cross-sections were obtained and stained with hematoxylin-eosin. The specimens were examined under optical microscopy at ×40 magnification and the images were subjected to morphometric analysis using the Scion image-analysis software. The total area of root canal and the area with debris were measured in square millimeters. Analysis of variance showed no statistically significant difference (p>0.05) among the groups GI (2.39 ± 3.59), GII (2.91 ± 2.21), GIII (0.73 ± 1.36), GIV (0.95 ± 0.84) and GV (0.51 ± 0.22). In conclusion, the final irrigation protocols evaluated in this study using the Luer syringe presented similar performance in the removal of debris from the apical third of flattened root canals.

Temperature of denture base resin under different protocols of microwave irradiation

This in vitro study evaluated the temperature of dentures after different microwave irradiation protocols. Two complete dentures (one maxillary and one mandibular denture) were irradiated separately 4 times for each of the following 5 protocols: dentures immersed in water (G1- 6 min, G2- 3 min); dentures kept dry (G3- 6 min); dentures placed in the steam sterilizer (G4- 6 min, G5- 3 min). The final temperature of the dentures was gauged in a thin and in a thick area of each denture with an infrared thermometer. All groups presented an increase in the resin base temperature. The thin areas of the dentures underwent greater heating than the thick areas. There was no significant difference (p>0.05) between the final mean temperatures of dentures immersed in water for 6 (G1) and 3 min (G2). However, the final mean temperatures recorded in G1 and G2 exceeded 71°C and were significantly higher (<0.001) than the final mean temperatures recorded in the other groups. It may be concluded that denture base resins subjected to microwave irradiation immersed in water may be exposed to deleterious temperatures.

Protocols for obtainment and isolation of two mesenchymal stem cell sources in sheep

PURPOSE: To evaluate different protocols to isolate stem cells from ovine umbilical cord blood and adipose tissue. METHODS: There were used 5 samples of umbilical blood and 5 samples of perirenal adipose tissue from 10 female sheep. All the samples were obtained through surgery, to harvest aseptic samples. There were used 3 protocols for obtainment and culture of umbilical cord blood stem cells and 4 protocols for ovine adipose tissue stem cells. RESULTS: It was possible to observe only one successful protocol for the obtainment of umbilical cord blood stem cells. When analyzing the techniques used to obtain adipose tissue stem cells, only one of the methods was effective as well. Through colony forming unit assay, there were obtained 58 colonies of cells after seven days in culture. Flow citometry tests revealed the cells were positive to CD44 and exhibited negative reaction to CD38, CD45, CD41/61. These cells showed a growth curve with very well defined phases LOG, LAG and PLATEAU. This phases are typically seem in mesenchymal stem cells growth curves. CONCLUSIONS: The isolation and culture of mesenchymal stem cells from ovine umbilical cord blood are complex and request more detailed assays. Stem cells from fat tissue sheep showed mesenchymal characteristics, according to their cell growth curve, ability to origin colonies of fibroblastoid cells and positive reactivity with the antibody CD44 by flow citometry.

Evaluation of DNA extraction protocols for Brucella abortus pcr detection in aborted fetuses or calves born from cows experimentally infected with strain 2308

The objective of the present study was to improve the detection of B. abortus by PCR in organs of aborted fetuses from infected cows, an important mechanism to find infected herds on the eradication phase of the program. So, different DNA extraction protocols were compared, focusing the PCR detection of B. abortus in clinical samples collected from aborted fetuses or calves born from cows challenged with the 2308 B. abortus strain. Therefore, two gold standard groups were built based on classical bacteriology, formed from: 32 lungs (17 positives), 26 spleens (11 positives), 23 livers (8 positives) and 22 bronchial lymph nodes (7 positives). All samples were submitted to three DNA extraction protocols, followed by the same amplification process with the primers B4 and B5. From the accumulated results for organ, the proportion of positives for the lungs was higher than the livers (p=0.04) or bronchial lymph nodes (p=0.004) and equal to the spleens (p=0.18). From the accumulated results for DNA extraction protocol, the proportion of positives for the Boom protocol was bigger than the PK (p<0.0001) and GT (p=0.0004). There was no difference between the PK and GT protocols (p=0.5). Some positive samples from the classical bacteriology were negative to the PCR and viceversa. Therefore, the best strategy for B. abortus detection in the organs of aborted fetuses or calves born from infected cows is the use, in parallel, of isolation by classical bacteriology and the PCR, with the DNA extraction performed by the Boom protocol.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Mobility and social network effects on extremist opinions

Understanding the emergence of extreme opinions and in what kind of environment they might become less extreme is a central theme in our modern globalized society. A model combining continuous opinions and observed discrete actions (CODA) capable of addressing the important issue of measuring how extreme opinions might be has been recently proposed. In this paper I show extreme opinions to arise in a ubiquitous manner in the CODA model for a multitude of social network structures. Depending on network details reducing extremism seems to be possible. However, a large number of agents with extreme opinions is always observed. A significant decrease in the number of extremists can be observed by allowing agents to change their positions in the network.

Architecture for machining process and production monitoring based in open computer numerical control

This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.

Anticipation of pain enhances the nociceptive transmission and functional connectivity within pain network in rats

Background: Expectation is a very potent pain modulator in both humans and animals. There is evidence that pain transmission neurons are modulated by expectation preceding painful stimuli. Nonetheless, few studies have examined the influence of pain expectation on the pain-related neuronal activity and the functional connectivity within the central nociceptive network. Results: This study used a tone-laser conditioning paradigm to establish the pain expectation in rats, and simultaneously recorded the anterior cingulate cortex (ACC), the medial dorsal thalamus (MD), and the primary somatosensory cortex (SI) to investigate the effect of pain expectation on laser-induced neuronal responses. Cross-correlation and partial directed coherence analysis were used to determine the functional interactions within and between the recorded areas during nociceptive transmission. The results showed that under anticipation condition, the neuronal activity to the auditory cue was significantly increased in the ACC area, whereas those to actual noxious stimuli were enhanced in all the recorded areas. Furthermore, neuronal correlations within and between these areas were significantly increased under conditions of expectation compared to those under non-expectation conditions, indicating an enhanced synchronization of neural activity within the pain network. In addition, information flow from the medial (ACC and MD) to the lateral (SI cortex) pain pathway increased, suggesting that the emotion-related neural circuits may modulate the neuronal activity in the somatosensory pathway during nociceptive transmission. Conclusion: These results demonstrate that the nociceptive processing in both medial and lateral pain systems is modulated by the expectation of pain.