Genetic transformation of Eucalyptus camaldulensis by agrobalistic method

Eucalyptus stands in the setting of worldwide forestry due to its adaptability, rapid growth, production of high-quality and low cost of wood pulp fibers. The eucalyptus convetional breeding is impaired mainlly by the long life cycle making the genetic transformation systems an important tool for this purpose. However, this system requires in vitro eficient protocols for plant induction, regeneration and seletion, that allow to obtain transgenic plants from the transformed cell groups. The aim of this work was to evaluate the callus formation and to optimize the leaves and callus genetic transformation protocol by using the Agrobacterium tumefaciens system. Concerning callus formation, two different culture media were evaluated: MS medium supplemented with auxin, cytokinin (M1) and the MS medium with reduced nitrogen concentration and supplemented with auxin, cytokinin coconut water (M2). To establish the leave genetic transformation, those were exposed to agrobiolistics technique (gene gun), to tissue injury, and A. tumesfasciens EHA 105 contening the vetor pCambia 3301 (35S::GUS::NOS), for gene transference and to establish the callus transformation thoses were exposed only to A. tumefasciens. For both experiments, the influence of different infection periods was evaluated. The M2 medium provided the best values for callus sizea and fresh and dry weight. The leaves genetic transformation using the agrobiolistics technique was effective, the gus gene transient expression could be observed. No significant differences were obtained in the infection periods (4, 6 and 8 minutes). The callus genetic transformation with A. tumefaciens also promotend the gus gene transient expression on the callus co-cultiveted for 15 e 30 minutes. The transformed callus was transfered to a regeneration and selection medium and transformed plants were obtained.

Control system for forced-air cooling of horticultural products

This work is a study of the implementation of a classical controller using a tuning method referred to as IMC (Internal Model Control) and aimed at the reduction of electrical energy consumption by the appropriate relation between energy consumption and the cooling time with forced air. The supervisory system installed was able to manipulate the variable of frequency of the signal power of the exhaust fan engine (forced air module), to accelerate or decelerate the loss of heat from the product to be cooled by airflow variation that passes through the mass of the produce. The results demonstrated a reduction in energy consumption from 64% and an increase of only 8% in the cooling time to the system using PI/IMC (Proportional - Integral with IMC) tuning method compared with the system in its operating nominal condition. This PI/IMC control may be implemented directly in a frequency converter, without the need to purchase a computer or PLC (programmable logic controller) to run the dedicated application, increasing its economical viability.

Development of an environmentally friendly method of starch oxidation by hydrogen peroxide and a complex water-soluble Iron catalyst

Oxidized starch is a key component in the paper industry, where it is used as both surfacing sizer and filler. Large quantities are annually used for this purpose; however, the methods for the oxidation are not environmentally friendly. In our research, we have studied the possibility to replace the harmful oxidation agents, such as hypochlorite or iodates and transition metal catalysts, with a more environmentally friendly oxidant, hydrogen peroxide (H2O2), and a special metal complex catalyst (FePcS), of which only a small amount is needed. The work comprised batch and semi-batch studies by H2O2, ultrasound studies of starch particles, determination of low-molecular by-products and determination of the decomposition kinetics of H2O2 in the presence of starch and the catalyst. This resulted in a waste-free oxidation method, which only produces water and oxygen as side products. The starch oxidation was studied in both semi-batch and batch modes in respective to the oxidant (H2O2) addition. The semi-batch mode proved to yield a sufficient degree of substitution (COOH groups) for industrial purposes. Treatment of starch granules by ultrasound was found to improve the reactivity of starch. The kinetic results were found out to have a rather complex pattern – several oxidation phases were observed, apparently due to the fact that the oxidation reaction in the beginning only took place on the surface, whereas after a prolonged reaction time, partial degradation of the solid starch granules allowed further reaction in the interior parts. Batch-mode experiments enabled a more detailed study of the mechanisms of starch in the presence of H2O2 and the catalyst, but yielded less oxidized starch due to rapid decomposition of H2O2 due to its high concentrations. The effect of the solid-liquid (S/L) ratio in the reaction system was studied in batch experiments. These studies revealed that the presence of the catalyst and the starch enhance the H2O2 decomposition.

The analysis of bifurcations in the spatially distributed Langford system

In this thesis the bifurcational behavior of the solutions of Langford system is analysed. The equilibriums of the Langford system are found, and the stability of equilibriums is discussed. The conditions of loss of stability are found. The periodic solution of the system is approximated. We consider three types of boundary condition for Langford spatially distributed system: Neumann conditions, Dirichlet conditions and Neumann conditions with additional requirement of zero average. We apply the Lyapunov-Schmidt method to Langford spatially distributed system for asymptotic approximation of the periodic mode. We analyse the influence of the diffusion on the behavior of self-oscillations. As well in the present work we perform numerical experiments and compare it with the analytical results.

Evaluation of bursal lymphoid depletion: comparison between the conventional histology method and digital lymphocyte depletion evaluation system

Abstract: Fifty-five bursa of Fabricius (BF) were evaluated by optical microscopy for three different avian histopathologists (H1, H3 and H4) to determine the degree of lymphoid depletion. One histologist evaluated the same slides at two different times (H1 and H2) with four-months interval between the observations. The same BFs were evaluated using the system of Digital Lymphocyte Depletion Evaluation (ADDL), being performed by three differents operators of the system, not histopathologists. The results showed was a significant difference between the histopathologists and between the scores established by the same expert (H1 and H2). However, there were not significant differences between the scores with the ADDL system, obtained using ADDL. The results make clear the fragility of the subjective lymphocyte depletion score classification by the traditional histologic method, while the ADDL system proves to be more appropriated for the assessment of the lymphoid loss in the BF.

Algorithm to determine the intersection curves between bezier surfaces by the solution of multivariable polynomial system and the differential marching method

The determination of the intersection curve between Bézier Surfaces may be seen as the composition of two separated problems: determining initial points and tracing the intersection curve from these points. The Bézier Surface is represented by a parametric function (polynomial with two variables) that maps a point in the tridimensional space from the bidimensional parametric space. In this article, it is proposed an algorithm to determine the initial points of the intersection curve of Bézier Surfaces, based on the solution of polynomial systems with the Projected Polyhedral Method, followed by a method for tracing the intersection curves (Marching Method with differential equations). In order to allow the use of the Projected Polyhedral Method, the equations of the system must be represented in terms of the Bernstein basis, and towards this goal it is proposed a robust and reliable algorithm to exactly transform a multivariable polynomial in terms of power basis to a polynomial written in terms of Bernstein basis .

Substitution-Newton-Raphson method applied to the modeling of a vapour compression refrigeration system using different representations of the thermodynamic properties of R-134a

This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

A gasometric method to determine erythrocyte catalase activity

We describe a new gasometric method to determine erythrocyte catalase activity by the measurement of the volume of oxygen produced as a result of hydrogen peroxide decomposition in a system where enzyme and substrate are separated in a special reaction test tube connected to a manometer and the reagents are mixed with a motor-driven stirrer. The position of the reagents in the test tube permits the continuous measurement of oxygen evolution from the time of mixing, without the need to stop the reaction by the addition of acid after each incubation time. The enzyme activity is reported as KHb, i.e., mg hydrogen peroxide decomposed per second per gram of hemoglobin (s-1 g Hb-1). The value obtained for catalase activity in 28 samples of hemolyzed human blood was 94.4 ± 6.17 mg H2O2 s-1 g Hb-1. The results obtained were precise and consistent, indicating that this rapid, simple and inexpensive method could be useful for research and routine work.

Numerical simulation of two-chamber plasma sources using finite element method

Numerical simulation of plasma sources is very important. Such models allows to vary different plasma parameters with high degree of accuracy. Moreover, they allow to conduct measurements not disturbing system balance.Recently, the scientific and practical interest increased in so-called two-chamber plasma sources. In one of them (small or discharge chamber) an external power source is embedded. In that chamber plasma forms. In another (large or diffusion chamber) plasma exists due to the transport of particles and energy through the boundary between chambers.In this particular work two-chamber plasma sources with argon and oxygen as active mediums were onstructed. This models give interesting results in electric field profiles and, as a consequence, in density profiles of charged particles.

A fast and efficient method for the study of caffeine levels in energy drinks using micellar electrokinetic chromatography (MEKC)

Energy drinks are becoming popular in Brazil and in the world due to their stimulant properties. Caffeine is present in energy drinks with the aim of stimulating the central nervous system and intensifying brain activity. On the other hand, the ingestion of high doses of caffeine can cause undesirable symptoms such as anxiety and tachycardia. Therefore, it is necessary to monitor the caffeine content added to energy drinks to guarantee that the levels in the final product are in accordance with the labeling and within the legislation limits. The goal of this work was to validate a fast, efficient, and low-cost method for the determination of caffeine in energy drinks by micellar electrokinetic chromatography (MEKC). A total of seven brands were analyzed, each in three lots. The electrolyte was prepared with 50 mmol.L-1 of sodium dodecyl sulfate (SDS) and 10 mmol.L-1 of sodium carbonate (pH 11.0). The mean concentration of caffeine ranged from 122.8 to 318.6 mg.L-1. None of the brands had caffeine levels above the maximum limit. Considering the interval of confidence (95%), 72% of the samples had less caffeine than the amount informed on the product label.

A new practical and easy method of learning after the system

UANL

A Type-Preserving Compiler from System F to Typed Assembly Language

L'utilisation des méthodes formelles est de plus en plus courante dans le développement logiciel, et les systèmes de types sont la méthode formelle qui a le plus de succès. L'avancement des méthodes formelles présente de nouveaux défis, ainsi que de nouvelles opportunités. L'un des défis est d'assurer qu'un compilateur préserve la sémantique des programmes, de sorte que les propriétés que l'on garantit à propos de son code source s'appliquent également au code exécutable. Cette thèse présente un compilateur qui traduit un langage fonctionnel d'ordre supérieur avec polymorphisme vers un langage assembleur typé, dont la propriété principale est que la préservation des types est vérifiée de manière automatisée, à l'aide d'annotations de types sur le code du compilateur. Notre compilateur implante les transformations de code essentielles pour un langage fonctionnel d'ordre supérieur, nommément une conversion CPS, une conversion des fermetures et une génération de code. Nous présentons les détails des représentation fortement typées des langages intermédiaires, et les contraintes qu'elles imposent sur l'implantation des transformations de code. Notre objectif est de garantir la préservation des types avec un minimum d'annotations, et sans compromettre les qualités générales de modularité et de lisibilité du code du compilateur. Cet objectif est atteint en grande partie dans le traitement des fonctionnalités de base du langage (les «types simples»), contrairement au traitement du polymorphisme qui demande encore un travail substantiel pour satisfaire la vérification de type.

A Beacon based Localization System for Autonomous Mobile Robots and its Applications in Traffic and Transport Control

ACCURATE sensing of vehicle position and attitude is still a very challenging problem in many mobile robot applications. The mobile robot vehicle applications must have some means of estimating where they are and in which direction they are heading. Many existing indoor positioning systems are limited in workspace and robustness because they require clear lines-of-sight or do not provide absolute, driftfree measurements.The research work presented in this dissertation provides a new approach to position and attitude sensing system designed specifically to meet the challenges of operation in a realistic, cluttered indoor environment, such as that of an office building, hospital, industrial or warehouse. This is accomplished by an innovative assembly of infrared LED source that restricts the spreading of the light intensity distribution confined to a sheet of light and is encoded with localization and traffic information. This Digital Infrared Sheet of Light Beacon (DISLiB) developed for mobile robot is a high resolution absolute localization system which is simple, fast, accurate and robust, without much of computational burden or significant processing. Most of the available beacon's performance in corridors and narrow passages are not satisfactory, whereas the performance of DISLiB is very encouraging in such situations. This research overcomes most of the inherent limitations of existing systems.The work further examines the odometric localization errors caused by over count readings of an optical encoder based odometric system in a mobile robot due to wheel-slippage and terrain irregularities. A simple and efficient method is investigated and realized using an FPGA for reducing the errors. The detection and correction is based on redundant encoder measurements. The method suggested relies on the fact that the wheel slippage or terrain irregularities cause more count readings from the encoder than what corresponds to the actual distance travelled by the vehicle.The application of encoded Digital Infrared Sheet of Light Beacon (DISLiB) system can be extended to intelligent control of the public transportation system. The system is capable of receiving traffic status input through a GSM (Global System Mobile) modem. The vehicles have infrared receivers and processors capable of decoding the information, and generating the audio and video messages to assist the driver. The thesis further examines the usefulness of the technique to assist the movement of differently-able (blind) persons in indoor or outdoor premises of his residence.The work addressed in this thesis suggests a new way forward in the development of autonomous robotics and guidance systems. However, this work can be easily extended to many other challenging domains, as well.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.