Phenotypic characterization of Candida spp. isolates from chronic periodontitis patients

Aim: Several typing methods for Candida spp. have been suggested in the literature in order to distinguish isolates for studies about the virulence or infection routes of these microorganisms and, in particular, for epidemiological purposes. The aim of this study was to establish a comparison between the phenotypic profile of oral Candida isolates from periodontitis patients and control individuals. Methods: The morphotyping and biotyping of 35 C. albicans isolates obtained from chronic periodontitis patients and 48 isolates from control individuals were performed. For morphotyping, the isolates were plated on malt extract agar and incubated for 10 days. Sixteen different morphotypes were observed for C. albicans, the most frequently observed being 0000 and 0001. Results: Biotype 0000 (complete absence of fringe) was most prevalent among the isolates obtained from periodontitis patients compared to those from control individuals, with statistical significance. Biotyping revealed 5 different biotypes with higher prevalence of the biotype 357 among the isolates from control and periodontitis groups. Conclusions: The results obtained by biotyping of the isolates did not permit to differentiate a characteristic model related to periodontal disease, whilst the morphotype 0000 was most frequently isolated from periodontitis patients.

Optimal clone identifier based on dynamic rules and process algebra

The rule creation to clone selection in different projects is a hard task to perform by using traditional implementations to control all the processes of the system. The use of an algebraic language is an alternative approach to manage all of system flow in a flexible way. In order to increase the power of versatility and consistency in defining the rules for optimal clone selection, this paper presents the software OCI 2 in which uses process algebra in the flow behavior of the system. OCI 2, controlled by an algebraic approach was applied in the rules elaboration for clone selection containing unique genes in the partial genome of the bacterium Bradyrhizobium elkanii Semia 587 and in the whole genome of the bacterium Xanthomonas axonopodis pv. citri. Copyright© (2009) by the International Society for Research in Science and Technology.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Preliminary results concerning the VSS X- chart with unknow in-control parameters

The VSS X- chart is known to perform better than the traditional X- control chart in detecting small to moderate mean shifts in the process. Many researchers have used this chart in order to detect a process mean shift under the assumption of known parameters. However, in practice, the process parameters are rarely known and are usually estimated from an in-control Phase I data set. In this paper, we evaluate the (run length) performances of the VSS X- control chart when the process parameters are estimated and we compare them in the case where the process parameters are assumed known. We draw the conclusion that these performances are quite different when the shift and the number of samples used during the phase I are small. ©2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Statistical model applied to NetFlow for network intrusion detection

The computers and network services became presence guaranteed in several places. These characteristics resulted in the growth of illicit events and therefore the computers and networks security has become an essential point in any computing environment. Many methodologies were created to identify these events; however, with increasing of users and services on the Internet, many difficulties are found in trying to monitor a large network environment. This paper proposes a methodology for events detection in large-scale networks. The proposal approaches the anomaly detection using the NetFlow protocol, statistical methods and monitoring the environment in a best time for the application. © 2010 Springer-Verlag Berlin Heidelberg.

The use of molecular spectra simulation for diagnostics of reactive flows

The C 2 * radical is used as a system probe tool to the reactive flow diagnostic, and it was chosen due to its large occurrence in plasma and combustion in aeronautics and aerospace applications. The rotational temperatures of C 2 * species were determined by the comparison between experimental and theoretical data. The simulation code was developed by the authors, using C++ language and the object oriented paradigm, and it includes a set of new tools that increase the efficacy of the C 2 * probe to determine the rotational temperature of the system. A brute force approach for the determination of spectral parameters was adopted in this version of the computer code. The statistical parameter c 2 was used as an objective criterion to determine the better match of experimental and synthesized spectra. The results showed that the program works even with low-quality experimental data, typically collected from in situ airborne compact apparatus. The technique was applied to flames of a Bunsen burner, and the rotational temperature of ca. 2100 K was calculated.

Analysis of inventory management in small business auto parts

The objective of this study was to analyze the production process and supply control in order to identify possible gaps and develop a method for managing supplies. The relevance of this research is on the benefits that can obtain by identifying the problems of supply control. The research method used was the case study, which was grounded on tripod semi-structured interviews, on-site observation, and document analysis. This methodology was very suitable because it can be analyzed and cross checked. The possibility of implementation of the proposal obtained from the theoretical framework, that together with the complementary actions suggested here, offers the opportunity to make the process more productive and profitable. This work allowed one to observe the weaknesses in managing the supply chain and at what points to work should be improved. It allowed to use some scientific models in the company object of study in order to improve supply management. © 2011 IEEE.

Knowledge-based risk management: Survey on Brazilian software development enterprises

A risks management, carried on in an effective way, leads the software development to success and may influence on the organization. The knowledge takes part of such a process as a way to help taking decisions. This research aimed to analyze the use of Knowledge Management techniques to the Risk Management in software projects development and the possible influence on the enterprise revenue. It had, as its main studying subject, Brazilian incubated and graduated software developing enterprises. The chosen research method was the Survey type. Multivariate statistical methods were used for the treatment and analysis of the obtained results, this way identifying the most significant factors, that is, enterprise's achievement constraining factors and those outcome achievement ones. Among the latter we highlight the knowledge methodology, the time of existence of the enterprise, the amount of employees and the knowledge externalization. The results encourage contributing actions to the increasing of financial revenue. © 2013 Springer-Verlag.

Effect of low-fluoride dentifrices supplemented with calcium glycerophosphate on enamel demineralization in situ

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quality of performance of the operation of sugarcane mechanized planting in day and night shifts

The sugarcane mechanized planting is becoming increasingly widespread in Brazil due to a higher operability and better working conditions offered to workers compared to other types of planting. Studies related to this topic are insufficient or scarce in Brazil. In this context, the aim of this study was to evaluate the operation quality of sugarcane mechanized planting in two operation shifts, by means of statistical process control. The mechanized planting was held on March 2012 and statistical design was completely randomized with two treatments, totaling 40 replications for the day shift and 40 replications for the night shift. The variables evaluated were: speed, engine rotation, engine oil pressure, water temperature of the engine, effective field capacity and the time consumption hourly and effective fuel. The use of statistical control charts showed that random intrinsic do not cause this process. The tractor alignment error showed outliers in the day and night shifts operations, indicating a possible delay in receiving the signal. The water temperature of the engine and the effective fuel consumption showed lower variability in nighttime operation with average values of 81°C and 22.66 L ha-1, respectively. The hourly fuel consumption had greater variability and consequently lower quality during the night of the operation, with an average consumption of 25.46 L h-1 while the day shift showed 26.86 L h-1.

Desempenho de trator agrícola em duas profundidades de escarificação e dois teores de água no solo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variabilidade espacial e diagnóstico da qualidade do processo em semeadura de amendoim

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Pomada a base de óleo de semente de maracujá no tratamento de lesões cutâneas em coelhos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Utilização do controle estatístico de processo na unidade de produção e desenvolvimento de derivados de soja - UNISOJA - F.C.F. - UNESP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)