Fixed-time artificial insemination with estradiol and progesterone for Bos indicus cows II: Strategies and factors affecting fertility

In Experiments 1, 2, and 3, we evaluated the effects of temporary weaning (TW), equine chorionic gonadotropin (eCG), and follicle-stimulating hormone (FSH) treatments on results of it fixed-time artificial insemination (TAI) protocol in postpartum Bos indicus cows. In Experiment 1, treatment with 400 IU eCG or with TW for 48 h consistently improved pregnancy rates (PRs) at TAI, but, in Experiment 2, FSH treatment was less effective than eCG or TW. In Experiment 3, the inclusion of eCG treatment in cows subjected to TW did not improve PRs. We concluded that TW or 400 IU eCG should be included in the TAI protocol in postpartum Bos indicus cows to enhance fertility. In Experiment 4, we used records front heifers and cows treated with the proposed protocol during the 2006-2007 (n = 27,195) and 2007-2008 (n = 36,838) breeding seasons from multiple locations in Brazil to evaluate factors potentially affecting PRs. Overall PR at TAI was 49.6% (31,786 of 64,033). Pregnancy rate differed (P < 0.01) among farm within location (results ranging between 26.8% and 68.0%; P < 0.01), cow group within farm, by breed (Bos indicus, 48.3% [26,123 of 54,145]; Bos taurus, 61.7% [3652 of 5922]; and crossbred Bos indicus x Bos taurus, 50.7% [2011 of 3966]), category (nulliparous, 39.6% [2095 of 52901] suckled primiparous, 45.2% [3924 of 8677]; suckled multiparous, 51.8% [24,245 of 46,767]; and nonsuckled multiparous, 46.1% [1522 of 3299]), body condition score at TAI (<= 2.5 43.0% [3409 of 7923]; 3.0, 49.6% [18,958 of 38,229]; and >3.5, 52.7% [9419 of 17,881]). Days postpartum at beginning, of protocol did not affect PR (30 to 60 d, 47.6% [4228 of 8881]; 61 to 90 d, 51.7% 116,325 to 31,5721; and 91 to 150 d, 50.8% [7616 to 14,991]; P > 0.1). Pregnancy rate was also consistently affected (P < 0.01) by sire (results ranging from 7.2% to 77.3%) and artificial insemination technician (results ranging from 15.1% to 81.8%). (C) 2009 Elsevier B.V. All rights reserved.

Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala

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

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

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

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Impedance-based structural health monitoring with artificial neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically >30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, multiple sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

Surface electromyography of facial muscles during natural and artificial feeding of infants

Objective: To measure and compare the activity of the masseter, temporalis and buccinator muscles in different infant feeding methods. Method: Cross-sectional study of 60 full-term infants with no intercurrent diseases, aged between two and three months, classified into the following groups: 1) exclusive breastfeeding; 2) breastfeeding plus bottle-feeding; and 3) exclusive breastfeeding plus cup feeding. Surface electromyography was performed during infant feeding. The Krushal-Wallis test was used, complemented by multiple paired comparisons of the groups. A 5% significance level was chosen for the tests. Results: Statistically higher results were verified in the breastfeeding group in relation to the bottle-feeding one, both in the range of movement and the mean contraction of the masseter. With regard to the temporalis muscle, statistically higher results were found in the breastfeeding group comparatively to the bottle-feeding one. As to the buccinator muscle, statistically higher results were observed in the breastfeeding group in relation to the bottle-feeding one, although in this case, the difference concerned only the range of contraction. Conclusion: The similarities between the muscle activity in the breastfeeding and in the cup-feeding groups suggests that cup-feeding can be used as an alternative infant feeding method, being better than bottle-feeding, due to the hyperactivity of the buccinator muscle, which could result in changes to the structural growth and development of the stomatognathic system functions. Copyright © 2006 by Sociedade Brasileira de Pediatria.

Avaliação eletromiográfica dos músculos masseter, temporal e bucinador de lactentes em situação de aleitamento natural e artificial

Pós-graduação em Pediatria - FMB

Efeito do flushing sobre o desempenho reprodutivo de ovelhas Morada Nova e Santa Inês submetidas à inseminação artificial em tempo fixo

The aim of this study was to analyze the effect of flushing on the reproductive performance of Morada Nova (MN) and Santa Inês (SI) ewes submitted to fixed time artificial insemination (TAI). Twenty seven SI and 24 MN supplemented with concentrate (1% of live weight, on average), for 75 days during the breeding season. After 30 days of supplementation, ewes were synchronized with the aid of a hormonal protocol (HP) based on progesterone, eCG and cloprostenol. The estrus observation was conducted at 12, 24, 36 and 48 h after the end of HP with the aid of two ruffians. TAI was done 55 h after the end of HP. From 20 to 45 days after the beginning of the HP ewes were exposed to rams (natural breeding). The pregnancy diagnosis was evaluated 70 days after TAI. We analyzed the weight, body condition score, estrus rate, pregnancy rate and prolificacy testing the effects of race, week of supplementation and body condition score class. The weight and body conditions of ewes varied according to the week of supplementation, with higher values in the first two weeks following TAI. The estrus rate was 88.2% and 43.2% of the ewes showed estrus up to 24 hours of the end of the HP. The pregnancy rate per TAI was 31.3% and the pregnancy rate after natural breeding was 50.0%. It was observed that body condition score classes interfered in pregnancy rates. There was a higher percentage of multiple births by pregnancy by TAI than by natural breeding. It was concluded that the flushing resulted in weight gain and better body conditions ensuring the standardization of the herd for breeding season, which therefore improved reproductive performance. The HP used advanced the onset of estrus and increased prolificacy, but was inefficient in the synchronization of woolless sheep.

Control of Buffalo Follicular Dynamics for Artificial Insemination, Superovulation and In Vitro Embryo Production

Currently, timed ovulation induction and timed artificial insemination (TAI) can be performed in buffalo using GnRH or estradiol plus progesterone/progestin (P4)-releasing devices and prostaglandin F-2 alpha (PGF(2 alpha)). The control of the emergence of follicular waves and of ovulation at predetermined times, without the need for estrus detection, has facilitated the management and improved the efficiency of AI programs in buffalo during the breeding and nonbreeding season. Multiple ovulations, embryo transfer, ovum collection and in vitro embryo production have been shown to be feasible in buffalo, although low efficiency and limited commercial application of these techniques have been documented as well. These results could be associated with low ovarian follicular pools, high levels of follicular atresia and failures of the oocyte to enter the oviduct after superstimulation of follicular growth. This review discusses a number of key points related to the manipulation of ovarian follicular growth to improve pregnancy rates following TAI and embryo transfer of in vivo- and in vitro-derived embryos in buffalo.

Effect of thermal and mechanical cycles on the hardness and roughness of artificial teeth

In this study the effects of thermal and mechanical cycles on the hardness and roughness of artificial teeth were evaluated. Materials and Methods:Specimens were prepared and stored in distilled water at 37ºC for 48 hours (n=10).The hardness and roughness readings were made in the following time intervals, according to each group:G1: after specimen storage in distilled water at 37°C for 48 hours; G2: after 600.000 constant mechanical cycles; G3: after 1.200.000 constant mechanical cycles; G4: after 2.500 thermalcycling baths, alternated between hot water (55°C) and cold water (5°C) and G5: after 5.000 thermalcycling baths, alternated between hot water (55°C) and cold water (5°C). After cycling and storage procedures, the specimens of each group were submittedto surface roughness and hardness readouts. Statistical evaluation was performed by three-way analysis of variance, complemented by the Tukey multiple comparisons of means test. The level of significance adopted was 5%. There was no significant difference between G1, G4 and G5 as regards mean roughness of different brands of artificial teeth. Groups G2 and G3 showed higher mean roughness values, and generally equivalent values in all time intervals, except for Trilux (G3> G2). Significant differences in hardness values were observed in different brands of artificial teeth, and differences in values after thermal and mechanical cycling. In conclusion, our findings suggest that thermal cyclingdid not change the roughness of the artificial teeth tested, but after the mechanical cycling the roughness values increased. Thermal and mechanical cycling influenced the hardness of the artificial teeth tested.

Avaliação in vitro do efeito das tinturas de Camellia sinensis e de Aloe arborescens na remineralização de lesão de cárie artificial em esmalte dentário humano

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Bond strength of artificial teeth attached to a microwave-polymerized denture base resin after immersion in disinfectant solutions

To evaluate the bond strength between two types of acrylic resin teeth and a microwave denture base resin after immersion in disinfectant solutions for 180 days. Eighty specimens made of acrylic resin teeth (Biotone and Biotone IPN) attached to a microwave polymerized denture base resin (Nature-Cryl MC) were divided into eight groups (n = 10) according to the treatment (distilled water-control, 2% chlorhexidine digluconate, 1% sodium hypochlorite and sodium perborate solution-Corega Tabs). The shear strength tests (MPa) were carried out using a universal testing machine with a 0.5 mm/min speed. Data analysis was performed using ANOVA and multiple comparison Student-Newman-Keuls post hoc test (α = 0.05). Biotone IPN showed similar results among the groups (distilled water, 8.25 ± 1.81 MPa; chlorhexidine, 7.81 ± 3.34 MPa; hypochlorite, 7.75 ± 3.72 MPa; and Corega Tabs, 7.58 ± 2.27 MPa, whereas Biotone showed significantly lower shear bond strength values for the groups immersed in Corega Tabs (5.25 ± 3.27 MPa) and chlorhexidine (6.08 ± 2.35 MPa). Soaking the dentures in 1% sodium hypochlorite could be recommended as a disinfectant solution for dentures fabricated with conventional acrylic resin denture teeth and microwave denture base resin. For dentures fabricated with IPN teeth and microwave denture base resin, all the soaking solutions evaluated in this study could be suggested to denture wearers.

Machine vision and planning applied on assembby line of multiple products

This article describes the use of Artificial Intelligence (IA) techniques applied in cells of a manufacturing system. Machine Vision was used to identify pieces and their positions of two different products to be assembled in the same productive line. This information is given as input for an IA planner embedded in the manufacturing system. Therefore, initial and final states are sent automatically to the planner capable to generate assembly plans for a robotic cell, in real time.

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.