Acrosomal ultrastructure of stallion spermatozoa cryopreserved with ethylene glycol using two packaging systems

The present experiments aimed to examine the substitution of glycerol (G) by ethylene glycol (E) as a cryoprotective agent for stallion spermatozoa. Two different ethylene glycol concentrations (5% and 10%) and also the association of glycerol (2%) and ethylene glycol (3%) (E/G) were studied (Experiment 1). In Experiment 2, two packing systems (0.5 x 4.0 ml) were evaluated using both cryoprotectors. In both experiments, the sperm membrane integrity after freezing was evaluated using transmission electron microscopy. The mean post-thaw motility was 34.25, 36.5, 29.25 and 34.75% for G5%, E5%, E10% and E/G, respectively. It was observed that the percentage of motile spermatozoa was significantly smaller (P<0.05) when semen was processed with E10%. A decrease in the acrosome integrity was observed in frozen thawed spermatozoa from all treated groups. It was observed that 28.0, 22.5, 25.5 and 22.5 % of the sperm cells had a normal acrosome following freezing with G5%, E5%, E10% and E/G, respectively. Undulation of the outer acrosomal membrane, acrosomal swelling and loss of acrosomal content density and homogeneity were the most evident ultrastructural alterations observed. In Experiment 2, the post-thaw motility was higher (P<0.05) for sperm frozen in 0.5 ml straws than in 4.0 mi straws, regardless of the cryoprotector used. The ultrastructural evaluation showed 26.7 and 16.0% of intact acrosomes for sperm frozen in 0.5 ml and 4.0 ml straws, respectively. We concluded that ethylene glycol has similar cryoprotective properties to glycerol and that utilisation of 0.5 ml straws improved the ability of horse sperm cells to withstand damage after the cryopreservation process.

Design of a reconfigurable pseudorandom number generator for use in intelligent systems

This paper deals with the design of a network-on-chip reconfigurable pseudorandom number generation unit that can map and execute meta-heuristic algorithms in hardware. The unit can be configured to implement one of the following five linear generator algorithms: a multiplicative congruential, a mixed congruential, a standard multiple recursive, a mixed multiple recursive, and a multiply-with-carry. The generation unit can be used both as a pseudorandom and a message passing-based server, which is able to produce pseudorandom numbers on demand, sending them to the network-on-chip blocks that originate the service request. The generator architecture has been mapped to a field programmable gate array, and showed that millions of numbers in 32-, 64-, 96-, or 128-bit formats can be produced in tens of milliseconds. (C) 2011 Elsevier B.V. All rights reserved.

An Intelligent Controller Design for Magnetorheological Damper Based on a Quarter-car Model

This paper presents the control strategies of nonlinear vehicle suspension using a magnetorheological (MR) damper. We used two different approaches for modeling and control of the mechanical and electrical parts of the suspension systems with the MR damper. First, we have formulated and resolved the control problem in order to design the linear feedback dumping force controller for a nonlinear suspension system. Then the values of the control dumping force functions were transformed into electrical control signals by the application of a fuzzy logic control method. The numerical simulations were provided in order to show the effectiveness of this method for the semi-active control of the quarter-car suspension.

Reducing the gap between mobile and intelligent software agents

This paper presents an approach to integrate an artificial intelligence (AI) technique, concretely rule-based processing, into mobile agents. In particular, it focuses on the aspects of designing and implementing an appropriate inference engine of small size to reduce migration costs. The main goal is combine two lines of agent research, First, the engineering oriented approach on mobile agent architectures, and, second, the AI related approach on inference engines driven by rules expressed in a restricted subset of first-order predicate logic (FOPL). In addition to size reduction, the main functions of this type of engine were isolated, generalized and implemented as dynamic components, making possible not only their migration with the agent, but also their dynamic migration and loading on demand. A set of classes for representing and exchanging knowledge between rule-based systems was also proposed.

An intelligent system for pavement management

This paper describes a method for the evaluation of pavement condition through artificial neural networks using the MLP backpropagation technique. Two of the most used procedures for detecting the pavement conditions were applied: the overall severity index and the irregularity index. Tests with the model demonstrated that the simulation with the neural network gives better results than the procedures recommended by the highway officials. This network may also be applied for the construction of a graphic computer environment.

Technique for application of hi-bright LED in automobile industry through intelligent systems

The advantages offered by the electronic component LED (Light Emitting Diode) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data.

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

Development of intelligent systems for well drilling and petroleum production

Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

H-2 and H-infinity - norm control of intelligent structures using LMI techniques

Linear Matrix Inequalities (LMIs) is a powerful too] that has been used in many areas ranging from control engineering to system identification and structural design. There are many factors that make LMI appealing. One is the fact that a lot of design specifications and constrains can be formulated as LMIs [1]. Once formulated in terms of LMIs a problem can be solved efficiently by convex optimization algorithms. The basic idea of the LMI method is to formulate a given problem as an optimization problem with linear objective function and linear matrix inequalities constrains. An intelligent structure involves distributed sensors and actuators and a control law to apply localized actions, in order to minimize or reduce the response at selected conditions. The objective of this work is to implement techniques of control based on LMIs applied to smart structures.

Packaging to Preserve 'Aurora-1' Peaches from Two Maturity Stages

The main objective of this research was to evaluate chemical and physical changes in 'Aurora-1' peach harvested at two maturity stages, packed in different types of packaging and kept under refrigeration. Fruit were harvested at the mature green and ripe stages, packed in four different types of packaging (control, PD-900 (TM), PVC and PET) and stored at 6 degrees C. The following variables were evaluated every eight days: coloration, accumulated fresh mass loss, firmness, appearance, acidity, total soluble solids contents, soluble sugars, and percentage of pectin solubilization. We observed that the postharvest life was influenced by packaging and the mature green fruits showed lower disease occurrence. Fresh mass loss was lower in packed fruits. The peel of mature green fruits developed a characteristic ripe peach color at the end of storage, but PD-900 (TM) provided a delay in color change. Packaging also influenced the firmness, allowing for more firmness retention than for the control fruits at both harvest stages. The organic acid content decreased in the packaged fruits and increased in the control fruits. In the packaged fruit, the amount of sugar increased until the eighth day and then decreased until the end of the storage period. The 'Aurora-1' peaches did not show compromised quality by packaging use and exhibited an increase in harvest life to 24 days (compared to 16 days for the control).

Urban Traffic Control and Monitoring - An Approach for the Brazilian Intelligent Cities Project

This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

Towards an intelligent graphical interface for linear programming modelling

The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

SISTAX - An intelligent tool for recovering information on natural products chemistry

This work describes the development of a new program, named SISTAX, for the expert system SISTEMAT. This program allows anyone interested in chemotaxonomy to carry out an intelligent search for organic compounds in databases through chemical structures. When coupled with can efficient encoding system, the program recognizes skeletal types and can find any substructural constraints demanded by the user. An example of an application of the program to the diterpene class found in plants is described.