Avaliação da taxa de concepção de novilhas e vacas (Bos taurus x Bos indicus) com o uso de sêmen sexado na inseminação artificial ou embriões produzidos in vivo e in vitro

Pós-graduação em Medicina Veterinária - FCAV

Efeito do período pós-parto sobre a taxa de prenhez de vacas de corte submetidas à IATF (Inseminação Artificial em Tempo Fixo)

This work aimed to evaluate the influence of postpartum period (precocious - of 28 to 44 days and late - of 45 to 90 days) on the bovine pregnancy rate using fixed-time AI. For that, 678 cows were divided in two groups: precocious group (G-P, n=151) and late group (G-T, n=527). The animals received CIDR® + 2 mL of estradiol benzoate (BE) in the day zero (D0). After eight days (D8) the dispositive was removed and both groups received 2.5mL PGF2α, concurrent with PGF2α injection, they received either 1.5mL of eCG or temporary calf removal (RTB). In the next day (D9), the cows received 1 mL de BE and 24 hours later, the fixed-time AI was performed with Nelore bovine semen. The calves were returned to their mothers. The pregnancy rate was not different between the groups (p>0.05), G-P=40% and G-T=48%. The results indicate that females with less than 45 days of postpartum are able to hormone protocol of fixed-time IA.

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

Expanding the horizontal capabilities of CRT monitors using artificial inter-pixel steps for neuroscience experiments

This article describes the development of a visual stimulus generator to be used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of a fixed image that is displaced horizontally according to the stimulus data. The system is capable of displaying 640 x 480 pixels with 256 intensity levels at 200 frames per second (FPS) on conventional raster monitors. To double the possible horizontal positioning possibilities from 640 to 1280, a novel technique is presented introducing artificial inter-pixel steps. The implementation consists in using two video frame buffers containing each a distinct view of the desired image pattern. This implementation generates a visual effect capable of doubling the horizontal positioning capabilities of the visual stimulus generator allowing more precise and movements more contiguous. (C) 2011 Elsevier Inc. All rights reserved.

Controlled reproduction in Anguilla anguilla (L.): advanced studies on broodstock management, spawning techniques and system design for artificial seed production.

The thesis aims to expose the advances achieved in the practices of captive breeding of the European eel (Anguilla anguilla). Aspects investigated concern both approaches livestock (breeding selection, response to hormonal stimulation, reproductive performance, incubation of eggs) and physiological aspects (endocrine plasma profiles of players), as well as engineering aspects. Studies conducted on various populations of wild eel have shown that the main determining factor in the selection of wild females destined to captive breeding must be the Silver Index which may determine the stage of pubertal development. The hormonal induction protocol adopted, with increasing doses of carp pituitary extract, it has proven useful to ovarian development, with a synchronization effect that is positively reflected on egg production. The studies on the effects of photoperiod show how the condition of total darkness can positively influence practices of reproductions in captivity. The effects of photoperiod were also investigated at the physiological level, observing the plasma levels of steroids ( E2, T) and thyroid hormones (T3 and T4) and the expression in the liver of vitellogenin (vtg1 and vtg2) and estradiol membrane receptor (ESR1). From the comparison between spontaneous deposition and insemination techniques through the stripping is inferred as the first ports to a better qualitative and quantitative yield in the production of eggs capable of being fertilized, also the presence of a percentage of oocytes completely transparent can be used to obtain eggs at a good rate of fertility. Finally, the design and implementation of a system for recirculating aquaculture suited to meet the needs of species-specific eel showed how to improve the reproductive results, it would be preferable to adopt low-flow and low density incubation.

Adaptive Pointing Theory (APT) Artificial Neural Network

The choice value and the testing process against the vigilance parameter, characteristic of ART Neural Network, are merged. Only, a single unique test is required to determine if a committed category node can represent the current input or not. Advantages of APT over ART are: 1-Avoid testing every committed category node before deciding to train a committed category node or a new node must be committed, 2-The vigilance parameter is fixed during training, and 3-The choice value parameter is eliminated.

Directions for impregnating water with fixed air in order to communicate to it the peculiar spirit and virtues of Pyrmont water,

"Priestley and carbonated waters, by John J. Riley": p. [1]-17 (1st group)

Fixed-satellite and broadcasting-satellite service considerations for 1979 GWARC planning /

Issued Oct. 1978.

Artificial neural network application in short-term prediction in an oscillating water column

Oscillating Water Column (OWC) is one type of promising wave energy devices due to its obvious advantage over many other wave energy converters: no moving component in sea water. Two types of OWCs (bottom-fixed and floating) have been widely investigated, and the bottom-fixed OWCs have been very successful in several practical applications. Recently, the proposal of massive wave energy production and the availability of wave energy have pushed OWC applications from near-shore to deeper water regions where floating OWCs are a better choice. For an OWC under sea waves, the air flow driving air turbine to generate electricity is a random process. In such a working condition, single design/operation point is nonexistent. To improve energy extraction, and to optimise the performance of the device, a system capable of controlling the air turbine rotation speed is desirable. To achieve that, this paper presents a short-term prediction of the random, process by an artificial neural network (ANN), which can provide near-future information for the control system. In this research, ANN is explored and tuned for a better prediction of the airflow (as well as the device motions for a wide application). It is found that, by carefully constructing ANN platform and optimizing the relevant parameters, ANN is capable of predicting the random process a few steps ahead of the real, time with a good accuracy. More importantly, the tuned ANN works for a large range of different types of random, process.

The comparative effects of habitat complexity on faunal assemblages of northern temperate artificial and natural reefs

Several north temperate marine species were recorded on subtidal hard-substratum reef sites selected to produce a gradient of structural complexity. The study employed an established scuba-based census method, the belt transect. The three types of reef examined, with a measured gradient of increasing structural complexity, were natural rocky reef, artificial reef constructed of solid concrete blocks, and artificial reef made of concrete blocks with voids. Surveys were undertaken monthly over a calendar year using randomly placed fixed rope transects. For a number of conspicuous species of fish and invertebrates, significant differences were found between the levels of habitat complexity and abundance. Overall abundance for many of the species examined was 2-3 times higher on the complex artificial habitats than on simple artificial or natural reef habitats. The enhanced habitat availability produced by the increased structural complexity delivered through specifically designed artificial reefs may have the potential to augment faunal abundance while promoting species diversity. 

'Artificial Immune Systems: A new Decision Making Paradigm for Operational Research'

Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

Assessment of naproxen adsorption on bone char in aqueous solutions using batch and fixed-bed processes

An integrated analysis of naproxen adsorption on bone char in batch and packed-bed column conditions has been performed. Kinetic, thermodynamic and breakthrough parameters have been calculated using adsorption models and artificial neural networks. Results show that naproxen removal using bone char in batch conditions is a feasible and effective process, which could involve electrostatic and non-electrostatic interactions depending mainly on pH conditions. However, the application of packed-bed column for naproxen adsorption on bone char is not effective for the treatment of diluted solutions due to the low degree of adsorbent utilization (below 4%) at tested operating conditions. The proposed mechanism for naproxen removal using bone char could include a complexation process via phosphate and naproxen, hydrogen bonding and the possibility of hydrophobic interactions via π–π electron. This study highlights the relevance of performing an integrated analysis of adsorbent effectiveness in batch and dynamic conditions to establish the best process configuration for the removal of emerging water pollutants such as pharmaceuticals.

Artificial fertilization of oocytes and sperm activation in pacu: effects of the spermatozoa:oocyte ratio, water volume, and in natura semen preservation

Objetivou-se foi avaliar a fertilização artificial e a duração da motilidade espermática em pacus com diferentes doses inseminantes, volumes de água e preservação do sêmen in natura. Foram realizados quatro experimentos para avaliação do efeito de doses inseminantes (7x10³, 7x10(4), 7x10(5), 7x10(6) e 7x10(7) espermatozoides ovócito-1) sobre a fertilização artificial dos ovócitos; do efeito do volume de água (0,5; 15,0; 30,0; 45,0 e 60,0 mL de água mL-1 de ovócitos) com doses inseminantes de 105.481 e 210.963 espermatozoides ovócito-1; do efeito de diluição do sêmen (0,005; 0,05; 0,5 e 5,0 µL de sêmen mL-1 de água) sobre a duração da motilidade espermática; e do efeito do armazenamento a 15 ºC por 9 h sobre a duração da motilidade espermática e o índice de sobrevivência espermática. Os maiores resultados obtidos foram: doses inseminantes entre 7x10³ e 7x10(7) espermatozoides ovócito-1; 15 a 60 mL de água mL-1 de ovócitos; diluição de 0.005 µL sêmen mL-1 de água e 98,65% de sobrevivência espermática até o tempo de preservação de 2h45min36s. A preservação a 15ºC por 9 horas não influencia a duração da motilidade espermática. As maiores taxas de fertilização podem ser observadas no emprego de 0,27 a 270 µL de sêmen mL-1 de ovócitos, com 15 a 60 mL de água para ativação.