Feedback, necesidades psicológicas básicas y vitalidad subjetiva en futbolistas estudiantes de las preparatorias la UANL

Dado que el deporte representa un contexto de gran valor para el desarrollo de la madurez individual y social de los adolescentes, lo cual probablemente influirá en su desarrollo, maduración y en su comportamiento, así como en su forma de entender las relaciones sociales. De aquí la influencia que un entrenador pueda tener sobre sus jóvenes jugadores, ya que tiene un papel de gran relevancia, pues puede repercutir de forma significativa en los patrones de comportamiento, en las cogniciones y en los afectos que los mismos vayan a desarrollar (Graham, 2008). Una tarea fundamental del entrenador es proporcionar retroalimentación o feedback a los atletas durante el aprendizaje de las habilidades motoras. El entrenador debe de ser capaz de generar las condiciones del medio en donde se perciba la legitimidad de su retroalimentación al proporcionar el feedback a los atletas, y generar las condiciones en donde se satisfagan las necesidades psicológicas básicas, lo cual propiciará un sentimiento de vitalidad y energía, de acuerdo con la Teoría de la autodeterminación (Deci y Rian, 1985, 2000, 2002 y 2008). En el marco de la Teoría de la autodeterminación (Deci y Rian, 1985, 2000, 2002 y 2008) y la Teoría de de las necesidades psicológicas básicas (Deci y Ryan 1985, 2000), esta tesis doctoral tuvo como objetivo estudiar el modelo representado por los factores sociales (cantidad de feedback correctivo, percepción legítima), los factores personales (necesidades psicológicas básicas: autonomía, competencia y socialización) y el bienestar (vitalidad subjetiva) propuesto en esta misma secuencia, en concordancia con el modelo de Vallerand (1997). Para los fines del presente trabajo se consideró una muestra de 377 estudiantes del nivel medio superior que forman parte de los equipos representativos de fútbol soccer de las preparatorias de la UANL, durante el período comprendido Agosto-Diciembre 2012. El muestreo fue de tipo no probabilístico y por conveniencia. La muestra estuvo compuesta por futbolistas de edades comprendidas entre los 15 y 20 años (M = 16.46, DT = 1.077). El error muestral fue del 4%. En el estudio se utilizaron distintas escalas para medir las variables involucradas en el estudio, como son: la Subescala de la Cantidad del Feedback Correctivo y la Subescala de la Percepción Legítima, a partir de la Escala del Feedback Correctivo; la Escala de Necesidad de Autonomía (NAS), la Escala de Percepción de Competencia del Cuestionario de Motivación Intrínseca (IMI), y la Escala de Necesidad de Relación (NRS); y la Escala de Vitalidad Subjetiva. Entre los resultados más destacados se encontró que existen relaciones positivas y altamente significativas entre todas las variables del estudio; la cantidad de feedback correctivo ofrecido por el entrenador actuó como un predictor positivo de la percepción legítima y, éste a su vez, operó como un predictor positivo de la satisfacción de las necesidades psicológicas básicas; la cantidad de feedback correctivo ofrecido por el entrenador actuó como un predictor positivo de la percepción legítima y, este a su vez, como un predictor positivo de la vitalidad subjetiva; la cantidad de feedback correctivo ofrecido por el entrenador actuó como predictor positivo de la satisfacción de las necesidades psicológicas básicas y, éste a su vez, fue un predictor positivo de la vitalidad subjetiva; la percepción legítima percibida por el jugador actuó como un predictor positivo de la satisfacción de las necesidades psicológicas básicas y, éste a su vez, como predictor positivo de la vitalidad subjetiva. Además, el modelo general nos condujo a que la cantidad de feedback correctivo ofrecido por el entrenador el cual actuó como predictor positivo de la percepción legítima y, este a su vez, predijo la satisfacción de las necesidades psicológicas básicas, la cual a su vez, 15 predijo la vitalidad subjetiva de los jugadores. Los resultados mostraron la puesta a prueba de los diferentes modelos generados a través de la combinación de las distintas variables, las cuales están en línea con la secuencia teórica. Se confirmaron adecuados índices de ajuste en cada uno de los modelos hipotetizado. El análisis de la mediación de las necesidades psicológicas básicas se realizó siguiendo a Holmbeck (1997). Los resultados mostraron que la satisfacción de las necesidades psicológicas básicas es un mediador total entre la cantidad de feedback correctivo y la vitalidad subjetiva. Por otro lado, se encontró que las necesidades psicológicas básicas no fueron un mediador entre la percepción legítima y la vitalidad subjetiva. En conclusión, se tiene que el entrenador es quien genera las condiciones del contexto ya sean de promoción de la autonomía o de control, además, de él depende generar las condiciones que promuevan la percepción de legitimidad en los atletas, mismas que probablemente concebirán en los deportistas la satisfacción de las necesidades psicológicas básicas, que permitan percibir una sensación de bienestar o malestar en los atletas.

H-infinity control design for time-delay linear systems: a rational transfer function based approach

The aim of this paper is to present new results on H-infinity control synthesis for time-delay linear systems. We extend the use of a finite order LTI system, called comparison system to H-infinity analysis and design. Differently from what can be viewed as a common feature of other control design methods available in the literature to date, the one presented here treats time-delay systems control design with classical numeric routines based on Riccati equations arisen from H-infinity theory. The proposed algorithm is simple, efficient and easy to implement. Some examples illustrating state and output feedback design are solved and discussed in order to put in evidence the most relevant characteristic of the theoretical results. Moreover, a practical application involving a 3-DOF networked control system is presented.

Optimal sequence of landfills in solid waste management

Given that landfills are depletable and replaceable resources, the right approach, when dealing with landfill management, is that of designing an optimal sequence of landfills rather than designing every single landfill separately. In this paper we use Optimal Control models, with mixed elements of both continuous and discrete time problems, to determine an optimal sequence of landfills, as regarding their capacity and lifetime. The resulting optimization problems involve splitting a time horizon of planning into several subintervals, the length of which has to be decided. In each of the subintervals some costs, the amount of which depends on the value of the decision variables, have to be borne. The obtained results may be applied to other economic problems such as private and public investments, consumption decisions on durable goods, etc.

Branch and Bound algorithms in greenhouse climate control

The horticultural sector has become an increasingly important sector of food production, for which greenhouse climate control plays a vital role in improving its sustainability. One of the methods to control the greenhouse climate is Model Predictive Control, which can be optimized through a branch and bound algorithm. The application of the algorithm in literature is examined and analyzed through small examples, and later extended to greenhouse climate simulation. A comparison is made of various alternative objective functions available in literature. Subsequently, a modidified version of the B&B algorithm is presented, which reduces the number of node evaluations required for optimization. Finally, three alternative algorithms are developed and compared to consider the optimization problem from a discrete to a continuous control space.

INTEGRATED THRESHOLD-ACTIVATED FEEDBACK MICROSYSTEM FOR REAL-TIME CHARACTERIZATION, SENSING AND TREATMENT OF BACTERIAL BIOFILMS

Biofilms are the primary cause of clinical bacterial infections and are impervious to typical amounts of antibiotics, necessitating very high doses for treatment. Therefore, it is highly desirable to develop new alternate methods of treatment that can complement or replace existing approaches using significantly lower doses of antibiotics. Current standards for studying biofilms are based on end-point studies that are invasive and destroy the biofilm during characterization. This dissertation presents the development of a novel real-time sensing and treatment technology to aid in the non-invasive characterization, monitoring and treatment of bacterial biofilms. The technology is demonstrated through the use of a high-throughput bifurcation based microfluidic reactor that enables simulation of flow conditions similar to indwelling medical devices. The integrated microsystem developed in this work incorporates the advantages of previous in vitro platforms while attempting to overcome some of their limitations. Biofilm formation is extremely sensitive to various growth parameters that cause large variability in biofilms between repeated experiments. In this work we investigate the use of microfluidic bifurcations for the reduction in biofilm growth variance. The microfluidic flow cell designed here spatially sections a single biofilm into multiple channels using microfluidic flow bifurcation. Biofilms grown in the bifurcated device were evaluated and verified for reduced biofilm growth variance using standard techniques like confocal microscopy. This uniformity in biofilm growth allows for reliable comparison and evaluation of new treatments with integrated controls on a single device. Biofilm partitioning was demonstrated using the bifurcation device by exposing three of the four channels to various treatments. We studied a novel bacterial biofilm treatment independent of traditional antibiotics using only small molecule inhibitors of bacterial quorum sensing (analogs) in combination with low electric fields. Studies using the bifurcation-based microfluidic flow cell integrated with real-time transduction methods and macro-scale end-point testing of the combination treatment showed a significant decrease in biomass compared to the untreated controls and well-known treatments such as antibiotics. To understand the possible mechanism of action of electric field-based treatments, fundamental treatment efficacy studies focusing on the effect of the energy of the applied electrical signal were performed. It was shown that the total energy and not the type of the applied electrical signal affects the effectiveness of the treatment. The linear dependence of the treatment efficacy on the applied electrical energy was also demonstrated. The integrated bifurcation-based microfluidic platform is the first microsystem that enables biofilm growth with reduced variance, as well as continuous real-time threshold-activated feedback monitoring and treatment using low electric fields. The sensors detect biofilm growth by monitoring the change in impedance across the interdigitated electrodes. Using the measured impedance change and user inputs provided through a convenient and simple graphical interface, a custom-built MATLAB control module intelligently switches the system into and out of treatment mode. Using this self-governing microsystem, in situ biofilm treatment based on the principles of the bioelectric effect was demonstrated by exposing two of the channels of the integrated bifurcation device to low doses of antibiotics.

Wave impedance selection for passivity-based bilateral teleoperation

When a task must be executed in a remote or dangerous environment, teleoperation systems may be employed to extend the influence of the human operator. In the case of manipulation tasks, haptic feedback of the forces experienced by the remote (slave) system is often highly useful in improving an operator's ability to perform effectively. In many of these cases (especially teleoperation over the internet and ground-to-space teleoperation), substantial communication latency exists in the control loop and has the strong tendency to cause instability of the system. The first viable solution to this problem in the literature was based on a scattering/wave transformation from transmission line theory. This wave transformation requires the designer to select a wave impedance parameter appropriate to the teleoperation system. It is widely recognized that a small value of wave impedance is well suited to free motion and a large value is preferable for contact tasks. Beyond this basic observation, however, very little guidance exists in the literature regarding the selection of an appropriate value. Moreover, prior research on impedance selection generally fails to account for the fact that in any realistic contact task there will simultaneously exist contact considerations (perpendicular to the surface of contact) and quasi-free-motion considerations (parallel to the surface of contact). The primary contribution of the present work is to introduce an approximate linearized optimum for the choice of wave impedance and to apply this quasi-optimal choice to the Cartesian reality of such a contact task, in which it cannot be expected that a given joint will be either perfectly normal to or perfectly parallel to the motion constraint. The proposed scheme selects a wave impedance matrix that is appropriate to the conditions encountered by the manipulator. This choice may be implemented as a static wave impedance value or as a time-varying choice updated according to the instantaneous conditions encountered. A Lyapunov-like analysis is presented demonstrating that time variation in wave impedance will not violate the passivity of the system. Experimental trials, both in simulation and on a haptic feedback device, are presented validating the technique. Consideration is also given to the case of an uncertain environment, in which an a priori impedance choice may not be possible.

Optimal impulsive collision avoidance in low earth orbit

This paper presents a high-accuracy fully analytical formulation to compute the miss distance and collision probability of two approaching objects following an impulsive collision avoidance maneuver. The formulation hinges on a linear relation between the applied impulse and the objects? relative motion in the b-plane, which allows one to formulate the maneuver optimization problem as an eigenvalue problem coupled to a simple nonlinear algebraic equation. The optimization criterion consists of minimizing the maneuver cost in terms of delta-V magnitude to either maximize collision miss distance or to minimize Gaussian collision probability. The algorithm, whose accuracy is verified in representative mission scenarios, can be employed for collision avoidance maneuver planning with reduced computational cost when compared with fully numerical algorithms.

Control of the spatial homogeneity of pore surface chemistry in particulate activated carbon

We show here that a physical activation process that is diffusion-controlled yields an activated carbon whose chemistry – both elemental and functional – varies radially through the particles. For the ∼100 μm particles considered here, diffusion-controlled activation in CO2 at 800 °C saw a halving in the oxygen concentration from the particle periphery to its center. It was also observed that this activation process leads to an increase in keto and quinone groups from the particle periphery towards the center and the inverse for other carbonyls as well as ether and hydroxyl groups, suggesting the two are formed under CO2-poor and -rich environments, respectively. In contrast to these observations, use of physical activation processes where diffusion-control is absent are shown to yield carbons whose chemistry is radially invariant. This suggests that a non-diffusion limited activation processes should be used if the performance of a carbon is dependent on having a specific optimal pore surface chemical composition.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Development and Verification of Control and Protection Strategies in Hybrid AC/DC Power Systems for Smart Grid Applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Design Optimization of Modern Machine-drive Systems for Maximum Fault Tolerant and Optimal Operation

Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.

Modelling and control of a floating oscillating water column

A novel numerical model of a Bent Backwards Duct Buoy (BBDB) Oscillating Water Column (OWC) Wave Energy Converter was created based on existing isolated numerical models of the different energy conversion systems utilised by an OWC. The novel aspect of this numerical model is that it incorporates the interdependencies of the different power conversion systems rather than modelling each system individually. This was achieved by accounting for the dynamic aerodynamic damping caused by the changing turbine rotational velocity by recalculating the turbine damping for each simulation sample and applying it via a feedback loop. The accuracy of the model was validated using experimental data collected during the Components for Ocean Renewable Energy Systems (CORES) EU FP-7 project that was tested in Galway Bay, Ireland. During the verification process, it was discovered that the model could also be applied as a valuable tool when troubleshooting device performance. A new turbine was developed and added to a full scale model after being investigated using Computational Fluid Dynamics. The energy storage capacity of the impulse turbine was investigated by modelling the turbine with both high and low inertia and applying three turbine control theories to the turbine using the full scale model. A single Maximum Power Point Tracking algorithm was applied to the low-inertia turbine, while both a fixed and dynamic control algorithm was applied to the high-inertia turbine. These results suggest that the highinertia turbine could be used as a flywheel energy storage device that could help minimize output power variation despite the low operating speed of the impulse turbine. This research identified the importance of applying dynamic turbine damping to a BBDB OWC numerical model, revealed additional value of the model as a device troubleshooting tool, and found that an impulse turbine could be applied as an energy storage system.

An internet-based control engineering laboratory

This paper presents LABNET, an internet-based remote laboratory for control engineering education developed at UEM-University. At present, the remote laboratory integrates three basic physical systems (level control, temperature control and ship stabilizing system). In this paper, the LABNET architecture is presented and discussed in detail. Issues concerned with concurrent user access, local or remote feedback, automatic report generating and reusing of experiment’s templates have been addressed. Furthermore, the experiences gained developing, testing and using the system will be also presented and their consequences for future design.

The impact and control of malignant catarrhal fever in Tanzania

Malignant Catarrhal Fever (MCF), an often-lethal infectious disease, presents as a variable complex of lesions in susceptible ungulate species. The disease is caused by a -herpesvirus following transmission from an inapparent carrier host. Two major epidemiological forms exist: wildebeest-associated MCF (WA-MCF), in which the virus is transmitted to susceptible species by wildebeest calves less than approximately four months of age, and sheepassociated MCF (SA-MCF) in which the virus is spread by sheep (primarily adolescents). Due to the lack of an in-vitro propagation system for the causative agent of the more economically significant SA-MCF, and with the expectation that cross-protective immunity may be provided, vaccine development has focused on the more easily propagated alcelaphine herpesvirus-1 (AlHV-1) that causes WA-MCF. In 2008 a direct viral challenge trial showed that a novel vaccine, employing an attenuated AlHV-1 (atAlHV-1) `C5000 virus strain, protected British Friesian-Holstein (FH) cattle against an intranasal challenge with virulent AlHV-1 `C5000 virus. For cattle keeping people living near wildebeest calving areas in sub-Saharan Africa an effective vaccine would have value as it would release them from the costly annual disease avoidance strategy of having to move their herds away from the oncoming wildebeest. On the other hand, an effective vaccine will release herd owners from the need to avoid MCF, allowing them to graze their cattle alongside wildebeest on the highly nutritious pastures of the calving areas. As such conservationists have raised concerns that the development of a vaccine might lead to detrimental grazing competition. The principle objective of this study was to test the novel vaccine on Tanzanian shorthorn zebu cross cattle (SZC).We did this firstly using a natural challenge field trial (Chapter Two) which demonstrated that immunisation with the atAlHV-1 vaccine was well tolerated and induced an oro-nasopharyngeal AlHV-1-specific and -neutralising antibody response. This resulted in an immunity in SZC cattle that was partially protective and reduced naturally transmitted infection by 56%. We also demonstrated that non-fatal infections occurred with a much higher frequency than previously thought. Because the calculated efficacy of the vaccine was less than that seen in British FH cattle we wanted to determine whether host factors, particular to SZC cattle, had impacted the outcomes of the field trial. To do this we repeated the 2008 direct viral challenge trial using SZC cattle (Chapter Four). During this trial we also investigated whether the recombinant bacterial flagellin monomer (FliC), when used as an adjuvant, might improve the vaccine’s efficacy. The findings from this trial indicated that direct challenge with pathogenic AlHV-1 is effective at inducing MCF in SZC cattle and that FliC is not an appropriate adjuvant for this vaccine. Furthermore, with less control group cattle dying of MCF than expected we speculate that SZC cattle may have a degree of resistance to MCF that affords them protection from infection and developing fatal disease. In Chapter Three we investigated aspects of the epidemiology of MCF, specifically whether wildebeest placenta, long implicated by Maasai cattle owners as a source of MCF, might play a role in viral transmission. Additionally, through comparative sequence analysis, at two specific genes (A9.5 and ORF50) of wild-type and atAlHV-1, we investigated whether the `C5000 strain, the source of which was taken from Africa more than 40 years ago, was appropriate for vaccine development. The detection of AlHV-1 virus in approximately 50% of placentae indicated that infection can occur in-utero and that this tissue might play a role in disease transmission. And, despite describing three new alleles of the A9.5 gene (supporting previous evidence that this gene is polymorphic and encodes a secretory protein with interleukin-4 as the major homologue), the observation that the most frequently detected haplotypes, in both wild-type and attenuated AlHV-1, were identical suggests that AlHV-1 has a slow molecular clock and that the attenuated strain was appropriate for vaccine development. In Chapter Five we present the first quantitative assessment of the annual MCF avoidance costs that Maasai pastoralists incur. In particular we estimated that as a result of MCF avoidance 64% of the total daily milk yield during the MCF season was not available to be used by the 81% of the family unit remaining at the permanent boma. This represents an upper-bound loss of approximately 8% of a household0s annual income. Despite these considerable losses we concluded that, given an incidence of fatal MCF in cattle living in wildebeest calving areas of 5% to 10%, if herd owners were to stop trying to avoid MCF by allowing their cattle to graze alongside wildebeest, any gains made through increased availability of milk, improved body condition and reduced energy demands would be offset by an increase in MCF-incidence. With the development of an effective vaccine, however, this alternative strategy might become optimal. The overall conclusion we draw therefore is that, despite the substantial costs incurred each year avoiding MCF, the partial protection afforded by the novel vaccine strategy is not sufficient to warrant a wholesale change in disease avoidance strategy. Nonetheless, even the partial protection provided by this vaccine could be of value to protect animals that cannot be moved, for example where some of the herd remain at the boma to provide milk or where land-use changes make traditional disease avoidance difficult. Furthermore, the vaccine may offer a feasible solution to some of the current land-use challenges and conflicts, providing a degree of protection to valuable livestock where avoidance strategies are not possible, but with less risk of precipitating the potentially damaging environmental consequences, such as overgrazing of highly nutritious seasonal pastures, that might result if herd owners decide they no longer need to avoid wildebeest.

Development of Optimal Energy Management Strategies for a Hybrid Boat

The present work proposes different approaches to extend the mathematical methods of supervisory energy management used in terrestrial environments to the maritime sector, that diverges in constraints, variables and disturbances. The aim is to find the optimal real-time solution that includes the minimization of a defined track time, while maintaining the classical energetic approach. Starting from analyzing and modelling the powertrain and boat dynamics, the energy economy problem formulation is done, following the mathematical principles behind the optimal control theory. Then, an adaptation aimed in finding a winning strategy for the Monaco Energy Boat Challenge endurance trial is performed via ECMS and A-ECMS control strategies, which lead to a more accurate knowledge of energy sources and boat’s behaviour. The simulations show that the algorithm accomplishes fuel economy and time optimization targets, but the latter adds huge tuning and calculation complexity. In order to assess a practical implementation on real hardware, the knowledge of the previous approaches has been translated into a rule-based algorithm, that let it be run on an embedded CPU. Finally, the algorithm has been tuned and tested in a real-world race scenario, showing promising results.