Effect of bleaching on sound enamel and with early artificial caries lesions using confocal laser microscopy

The aim of this study was to evaluate effect of bleaching agents on sound enamel (SE) and enamel with early artificial caries lesions (CL) using confocal laser scanning microscopy (CLSM). Eighty blocks (4 × 5 × 5 mm) of bovine enamel were used and half of them were submitted to a pH cycling model to induce CL. Eight experimental groups were obtained from the treatments and mineralization level of the enamel (SE or CL) (n=10). SE groups: G1 - unbleached (control); G2 - 4% hydrogen peroxide (4 HP); G3 - 4 HP containing 0.05% Ca (Ca); G4 - 7.5% hydrogen peroxide (7.5 HP) containing amorphous calcium phosphate (ACP). CL groups: G5 - unbleached; G6 - 4 HP; G7 - 4 HP containing Ca; G8 - 7.5 HP ACP. G2, G3, G6, G7 were treated with the bleaching agents for 8 h/day during 14 days, while G4 and G8 were exposed to the bleaching agents for 30 min twice a day during 14 days. The enamel blocks were stained with 0.1 mM rhodamine B solution and the demineralization was quantified using fluorescence intensity detected by CLSM. Data were analyzed using ANOVA and Fisher's tests (α=0.05). For the SE groups, the bleaching treatments increased significantly the demineralization area when compared with the unbleached group. In the CL groups, no statistically significant difference was observed (p>0.05). The addition of ACP or Ca in the composition of the whitening products did not overcome the effects caused by bleaching treatments on SE and neither was able to promote remineralization of CL.

Artificial satellites dynamics: Resonant effects

In this work, the resonance problem in the artificial satellites motion is studied. The development of the geopotential includes the zonal harmonics J20 and J40 and the tesseral harmonics J22 and J42. Through successive Mathieu transformations, the order of dynamical system is reduced and the final system is solved by numerical integration. In the simplified dynamical model, two critical angles are studied, 2201 and 4211. Numerical results show the time behavior of the semi-major axis and 2 angle.

Use of cooled bull semen as a strategy to increase the pregnancy rate in fixed-time artificial insemination programs-case report

Semen cryopreservation is still considered suboptimal due to lower fertility when compared to fresh semen. The reasons for the loss of fertility are various and related to irreversible damage caused to the cells during the freeze-thaw process. An alternative to conventional cryopreservation represents the use of chilled bull semen, preventing the damage associated with freezing, thereby guaranteeing greater sperm viability. The aim of this study was to describe the use of cooled bull semen as a strategy to increase the pregnancy for Fixed-Time Artificial Insemination (FTAI) of Nellore (Bos indicus) cows. One ejaculate of a select Nellore bull obtained by electroejaculation was used; the semen sample was fractioned into two aliquots: one diluted in Botu-Bov® extender containing 6.4% glycerol for cryopreservation (BB-F, frozen group) and one diluted in the same extender, free from cryoprotectants and used for cooling (BB-C, cooled semen group). The samples in the BB-C group were chilled to 5°C using an isothermic box and maintained for 24 h prior to use. A total of 349 lactating Nellore cows (70-90 days after birth) were synchronized by the insertion of a progesterone releasing device (1.0 g) and estradiol benzoate (2.0 mg i.m.) on a random day of the estrous cycle (Day 0); FTAI was performed 44-48 h after the removal of the device. The pregnancy rates were 45.71 and 61.49% (P<0.05), respectively, for the cryopreserved or chilled bovine semen groups. In conclusion, the use of bull semen cooled for 24 h represents an alternative to conventionally cryopreserved semen, as determined by the increase the pregnancy per artificial insemination in bovine herds. © 2012 Science Publication.

Influence of different disinfecting solutions on the color change of artificial irises used in ocular prostheses

Making an artificial iris with an aesthetically acceptable color is an important aspect of ocular rehabilitation. This work evaluated the influence of different disinfecting solutions on changes to the color of artificial irises used in ocular prostheses. Fifty samples simulating ocular prostheses were produced with cobalt blue artificial irises and divided (n = 10) according to the disinfectant used: neutral soap, Opti-free, Efferdent, 1% hypochlorite, and 4% chlorhexidine. The samples were disinfected for 120 days and subjected to a color readings by spectrophotometry, using the CIE L*a*b* system, before the disinfection period (B), after 60 days of disinfectant exposure (T 1), and after 120 days of disinfectant exposure (T 2). Color differences (ΔE) were calculated for the intervals between T 1 and B (T 1B), and between T 2 and B (T 2B). The data were evaluated by analysis of variance and the Tukey Honestly Significantly Different (α = 0.05). All disinfectant groups exhibited color changes. The mean color change observed for all groups overall during T 2B (ΔE = 3.51) was significantly greater than that observed during T 1B (ΔE = 2.10). All groups exhibited greater color change for the b* values when compared to the a* and L* values. There were no significant differences between the disinfectant groups. It can be concluded that the time period of disinfection and storage significantly affected the stability of artificial iris color, independent of the disinfectant used. © 2012 Wiley Periodicals, Inc.

Cluster analysis and artificial neural network on the superovulatory response prediction in mice

Complex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.

Fault location in underground systems using artificial neural networks and PSCAD/EMTDC

The need for high reliability and environmental concerns are making the underground networks the most appropriate choice of energy distribution. However, like any other system, underground distribution systems are not free of failures. In this context, this work presents an approach to study underground systems using computational tools by integrating the software PSCAD/EMTDC with artificial neural networks to assist fault location in power distribution systems. Targeted benefits include greater accuracy and reduced repair time. The results presented here shows the feasibility of the proposed approach. © 2012 IEEE.

Identification of steel bars immersed in reinforced concrete based on experimental results of eddy current testing and artificial neural network analysis

This paper presents an experimental research on the use of eddy current testing (ECT) and artificial neural networks (ANNs) in order to identify the gauge and position of steel bars immersed in concrete structures. The paper presents details of the ECT probe and concrete specimens constructed for the tests, and a study about the influence of the concrete on the values of measured voltages. After this, new measurements were done with a greater number of specimens, simulating a field condition and the results were used to generate training and validation vectors for multilayer perceptron ANNs. The results show a high percentage of correct identification with respect to both, the gauge of the bar and of the thickness of the concrete cover. © 2013 Copyright Taylor and Francis Group, LLC.

Bone morphology of the hind limbs in two caviomorph rodents

In order to evaluate the hind limbs of caviomorph rodents a descriptive analysis of the Cuniculus paca (Linnaeus, 1766) and Hydrochoerus hydrochaeris (Linnaeus, 1766) was performed using anatomical specimens, radiography, computed tomography (CT) and full-coloured prototype models to generate bone anatomy data. The appendicular skeleton of the two largest rodents of Neotropical America was compared with the previously reported anatomical features of Rattus norvegicus (Berkenhout, 1769) and domestic Cavia porcellus (Linnaeus, 1758). The structures were analyzed macroscopically and particular findings of each species reported. Features including the presence of articular fibular projection and lunulae were observed in the stifle joint of all rodents. Imaging aided in anatomical description and, specifically in the identification of bone structures in Cuniculus paca and Hydrochoerus hydrochaeris. The imaging findings were correlated with the anatomical structures observed. The data may be used in future studies comparing these animals to other rodents and mammalian species. © 2012 Blackwell Verlag GmbH.

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98 fb-1 of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (EÌ̧T>40 GeV) and total hadronic transverse energy (HT>120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified models. © 2013 CERN.

Onboard and real-time artificial satellite orbit determination using GPS

An algorithm for real-time and onboard orbit determination applying the Extended Kalman Filter (EKF) method is developed. Aiming at a very simple and still fairly accurate orbit determination, an analysis is performed to ascertain an adequacy of modeling complexity versus accuracy. The minimum set of to-be-estimated states to reach the level of accuracy of tens of meters is found to have at least the position, velocity, and user clock offset components. The dynamical model is assessed through several tests, covering force model, numerical integration scheme and step size, and simplified variational equations. The measurement model includes only relevant effects to the order of meters. The EKF method is chosen to be the simplest real-time estimation algorithm with adequate tuning of its parameters. In the developed procedure, the obtained position and velocity errors along a day vary from 15 to 20 m and from 0.014 to 0.018 m/s, respectively, with standard deviation from 6 to 10 m and from 0.006 to 0.008 m/s, respectively, with the SA either on or off. The results, as well as analysis of the final adopted models used, are presented in this work. © 2013 Ana Paula Marins Chiaradia et al.

Timing of prostaglandin F2α treatment in an estrogen-based protocol for timed artificial insemination or timed embryo transfer in lactating dairy cows

Objectives were to investigate progesterone concentrations and fertility comparing 2 different intervals from PGF2α treatment and induced ovulation in an estrogen-based ovulation synchronization protocol for timed artificial insemination (TAI) or timed embryo transfer (TET) in lactating dairy cows. A total of 1,058 lactating Holstein cows [primiparous (n=371) and multiparous (n=687)], yielding 34.1±0.33 kg of milk/d at various days in milk were randomly assigned to receive treatment with PGF2α on either d 7 or 8 of the following protocol: d 0: 2mg of estradiol benzoate + controlled internal drug release device; d 8: controlled internal drug release device removal + 1.0mg of estradiol cypionate; d 10: TAI or d 17: TET. Only cows with a corpus luteum at d 17 received an embryo and all cows received GnRH at TET. Pregnancy diagnoses were performed by detection (transrectal ultrasonography) of an embryo on d 28 or a fetus on d 60. Fertility [pregnancy per artificial insemination (P/AI) or pregnancy per embryo transfer (P/ET)] was affected by breeding technique (AI vs. ET) and time of PGF2α treatment (d 7 vs. 8) at the 28-d pregnancy diagnosis for TAI [32.9% (238) vs. 20.6% (168)] and TET cows [47% (243) vs. 40.7% (244)] and at the 60-d pregnancy diagnosis for TAI [30% (238) vs. 19.2% (168)] and TET cows [37.9% (243) vs. 33.5% (244)]. The progesterone (P4) concentration at d 10 altered fertility in TAI cows, with higher P/AI in cows with P4 concentration <0.1 ng/mL compared with cows with P4 concentration ≥0.1 ng/mL, and in ET cows, with higher P/ET in cows with P4 concentration <0.22 ng/mL compared with cows with P4 concentration ≥0.22 ng/mL. Prostaglandin F2α treatment at d 7 increased the percentage of cows with P4 <0.1 ng/mL on d 10 [39.4 (85) vs. 23.2 (54)]. Reducing the period between PGF2α and TAI from 72 to 48h in dairy cows resulted in a clear reduction in fertility in cows bred by TAI and a subtle negative effect in cows that received TET. The earlier PGF2α treatment benefits are most likely mediated through gamete transport, fertilization, or early embryo development and a more subtle effect of earlier PGF2α treatment that may be mediated through changes in the uterine or hormonal environment that manifests itself after ET on d 7. © 2013 American Dairy Science Association.

Effects of artificial substrate and night-time aeration on the water quality in Macrobrachium amazonicum (Heller 1862) pond culture

The effects of artificial substrate and night-time aeration on the culture of Macrobrachium amazonicum were evaluated in 12 ponds stocked with 45 prawns m-2. A completely randomized design in 2 × 2 factorial scheme with three replicates was used. The combination of factors resulted in four treatments: with substrate and aeration (SA), with substrate and without aeration (SWA), without substrate and with aeration (WSA) and without substrate and aeration (WSWA). The presence of substrate in SA and SWA treatments reduced suspended particles (seston) by ~17.3% and P-orthophosphate by ~50%. The use of aerator (WSA and SA treatments) significantly (P < 0.05) increased the concentration of dissolved oxygen, suspended particles and nutrients in the pond water. These results indicate that the effect of substrate on turbidity and total suspended solids (TSS) values is opposite to the effect of the aerator. The aerators in semi-intensive grow-out M. amazonicum farming lower water quality because they increased the amount of detritus and nutrients in the pond water. On the other hand, the use of artificial substrate reduces turbidity values, chlorophyll a, TSS and P-orthophosphate concentrations. Therefore, the combination of substrate addition and night-time aeration is not interesting because they have opposite effects. © 2013 John Wiley & Sons Ltd.

Artificial neural network model of discharge lamps in the power quality context

This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.