The ovarian cycle histochemistry and its relationship with hepatopancreas weight in the blue crab Callinectes danae (Crustacea: Portunidae)

Zara, F.J., Gaeta, H.H., Costa, T.M., Toyama, M.H. and Caetano, F.H. 2011. The ovarian cycle histochemistry and its relationship with hepatopancreas weight in the blue crab Callinectes danae (Crustacea: Portunidae). -Acta Zoologica (Stockholm) 00:1-13. Several studies use macroscopic patterns of the ovarian development in crustaceans. Here, we examined the relationship between ovary histochemistry, changes in gonadosomatic and hepatosomatic indices against the macroscopic pattern of the ovarian development in Callinectes danae. Animals were collected in the south coast of São Paulo State, Brazil. Ovaries were macroscopically classified as juvenile, rudimentary, developing, intermediary, mature, and rudimentary ovigerous. Samples were fixed in 4% paraformaldehyde, processed for historesin, and stained with HE, protein, and neutral and acid polysaccharides detection. The juvenile oocytes are not enclosed by follicular cells and have fewer yolk nuclei being less intense in PAS reactivity than rudimentary oocytes. Developing oocytes show yolk granules and thick follicular cells. Yolk granules were positive for proteins and neutral polysaccharides. The intermediary stage is marked by a qualitative increase in yolk granules and the onset of chorion formation. In mature oocytes, cytoplasm is completely filled by yolk granules and the chorion is completely formed. Ovigerous ovaries have several atretic follicles and large quantities of hemocytes in the process of tissue reorganization. In C. danae, the changes in cell, goandosomatic and hepatosomatic indices coinciding with macroscopic observations and any combination of different macroscopic stages in a single pattern should be avoided. © 2011 The Royal Swedish Academy of Sciences.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Célula de comutação de três estados aplicada ao pré-regulador boost de estágio único e elevado fator de potência

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Load Characterization and Revenue Metering Under Non-Sinusoidal and Asymmetrical Operation

This paper proposes an approach to load characterization and revenue metering, which accounts for the influence of supply deterioration and line impedance. It makes use of the Conservative Power Theory and aims at characterizing the load from the measurements done at the point of common coupling. Despite the inherent limitations of a single-point measurement, the proposed methodology enables evaluation of power terms, which clarify the effects of reactivity, asymmetry and distortion, and attempts to depurate the power consumption accounted to the load from those terms deriving from supply nonidealities.

Tool Condition Monitoring of Single-Point Dresser Using Acoustic Emission and Neural Networks Models

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

Clinical and psychological repercussions of videolaparoscopic tubal ligation: observational, single cohort, retrospective study

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

SPECT (Single photon emission tomography): Gama câmara, reconstrução tomográfica e características funcional

The SPECT (Single Photon Emission Computed Tomography) systems are part of a medical image acquisition technology which has been outstanding, because the resultant images are functional images complementary to those that give anatomic information, such as X-Ray CT, presenting a high diagnostic value. These equipments acquire, in a non-invasive way, images from the interior of the human body through tomographic mapping of radioactive material administered to the patient. The SPECT systems are based on the Gamma Camera detection system, and one of them being set on a rotational gantry is enough to obtain the necessary data for a tomographic image. The images obtained from the SPECT system consist in a group of flat images that describe the radioactive distribution on the patient. The trans-axial cuts are obtained from the tomographic reconstruction techniques. There are analytic and iterative methods to obtain the tomographic reconstruction. The analytic methods are based on the Fourier Cut Theorem (FCT), while the iterative methods search for numeric solutions to solve the equations from the projections. Within the analytic methods, the filtered backprojection (FBP) method maybe is the simplest of all the tomographic reconstruction techniques. This paper's goal is to present the operation of the SPECT system, the Gamma Camera detection system, some tomographic reconstruction techniques and the requisites for the implementation of this system in a Nuclear Medicine service

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Synchronous reconstruction of bilateral osteoradionecrosis of the mandible using a single fibular osteocutaneous flap in patients with nasopharyngeal carcinoma

The reconstruction of bilateral osteoradionecrosis (ORN) of mandibular defects using a single free bone flap is rarely performed because extensively radiated neck tissue with severe fibrosis is usually unsuitable for vascularized reconstruction. Thirty-one patients with nasopharyngeal carcinoma (NPC) underwent bilateral reconstruction of advanced ORN in the mandible using a single fibular osteocutaneous flap. Clinical factors associated with the operation were assessed, including classification of mandible defects, types of recipient vessels, perioperative complications, and postoperative outcomes. All of the fibular osteocutaneous flaps survived completely, with the exception of 1 inner skin paddle that presented partial necrosis in a reconstruction of through-and-through defects. All patients experienced an improvement in cosmetic results 6 months after the reconstruction, whereas 23 patients experienced improved mouth opening compared to the preoperative condition. Advanced bilateral ORN in patients with NPC could be synchronously reconstructed with a single fibular osteocutaneous flap. © 2015 Wiley Periodicals, Inc. Head Neck, 2015.

A novel single-phase ZCS-PWM high power factor boost rectifier

This paper presents a novel single-phase high power factor PWM boost rectifier, featuring soft commutation of the active switches at zero-current (ZCS). It incorporates the most desirable properties of the conventional PWM and the soft-switching resonant techniques. The input current shaping is achieved with average current mode control, and continuous inductor current mode. This new PWM converter provides ZCS turn-on and turn-off of the active switches, and it is suitable for high power applications employing IGBTs. Principle of operation, theoretical analysis, a design example, and experimental results from a laboratory prototype rated at 1600 W with 400 Vdc output voltage are presented. The measured efficiency and power factor were 96.2% and 0.99 respectively, with an input current THD equal to 3.94%, for an input voltage THD equal to 3.8%, at rated load.

Net power optimization of an irreversible Otto cycle using ECOP and ecological function

This paper presents an analysis of an irreversible Otto cycle aiming to optimize the net power through ECOP and ecological function. The studied cycle operates between two thermal reservoirs of infinite thermal capacity, with internal irreversibilities derived from non-isentropic behavior of compression and expansion processes, irreversibilities from thermal resistance in heat exchangers and heat leakage from the high temperature reservoir to the low temperature reservoir. Analytical expressions are applied for the power outputs optimized by the ECOP, by the ecological function and by the maximum power criteria, in conjunction with a graphic analysis, in which some cycle operation parameters are analyzed for an increased comprehension of the effects of the irreversibilities in the optimized power.