Monitoring spinach shelf-life with hyperspectral image through

Different procedures for monitoring the evolution of leafy vegetables, under plastic covers during cold storage, have been studied. Fifteen spinach leaves were put inside Petri dishes covered with three different plastic films and stored at 4 °C for 21 days. Hyperspectral images were taken during this storage. A radiometric correction is proposed in order to avoid the variation in transmittance of the plastic films during time in the hyperspectral images. Afterwards, three spectral pre-processing procedures (no pre-process, Savitsky–Golay and Standard Normal Variate, combined with Principal Component Analysis) were applied to obtain different models. The corresponding artificial images of scores were studied by means of Analysis of Variance to compare their ability to sense the aging of the leaves. All models were able to monitor the aging through storage. Radiometric correction seemed to work properly and could allow the supervision of shelf-life in leafy vegetables through commercial transparent films.

Páncreas artificial basado en un controlador Smith paramétrico

La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Actualmente existen dos tipos de terapias aplicada en tejido subcutáneo: mediante inyección múltiple realizada con plumas, y la otra es mediante infusión continua de insulina por bomba (CSII). El mayor problema de esta terapia son los retardos por la absorción, tanto de los carbohidratos como de la insulina, y los retardos introducidos por el sensor subcutáneo de glucosa que mide la glucosa del líquido intersticial, lo deseable es controlar la glucosa en sangre. Para intentar independizar al paciente de su enfermedad se está trabajando en el desarrollo del páncreas endocrino artificial (PEA) que dotaría al paciente de una bomba de insulina, un sensor de glucosa y un controlador, el cual se encargaría de la toma de decisiones de las infusiones de insulina. Este proyecto persigue el diseño de un regulador en modo de funcionamiento en CL, con el objetivo de conseguir una regulación óptima del nivel de glucosa en sangre. El diseño de dicho regulador va a ser acometido utilizando la teoría del control por modelo interno (IMC). Esta teoría se basa en la idea de que es necesario realimentar la respuesta de un modelo aproximado del proceso que se quiere controlar. La salida del modelo, comparada con la del proceso real nos da la incertidumbre del modelo de la planta, frente a la planta real. Dado que según la teoría del modelo interno, estas diferencias se dan en las altas frecuencias, la teoría IMC propone un filtro paso bajo como regulador en serie con la inversa del modelo de la planta para conseguir el comportamiento deseado. Además se pretende implementar un Predictor Smith para minimizar los efectos del retardo de la medida del sensor. En el proyecto para conseguir la viabilidad del PEA se ha adaptado el controlador IMC clásico utilizando las ganancias estáticas de un modelo de glucosa, a partir de la ruta subcutánea de infusión y la vía subcutánea de medida. El modo de funcionamiento del controlador en SCL mejora el rango de normoglucemia, necesitando la intervención del paciente indicando anticipadamente el momento de las ingestas al controlador. El uso de un control SCL con el Predictor de Smith mejora los resultados pues se añade al controlador una variable sobre las ingestas con la participación del paciente. ABSTRACT. Diabetes mellitus is a group of metabolic diseases in which a person has high blood sugar, due to the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. There are currently two types of therapies applied in subcutaneous tissue: the first one consists in using the intensive therapy with an insulin pen, and the other one is by continuous subcutaneous insulin infusion (CSII). The biggest problems of this therapy are the delays caused by the absorption of carbohydrates and insulin, and the delays introduced by the subcutaneous glucose sensor that measures glucose from interstitial fluid, it is suitable to control glucose blood. To try to improve these patients quality of life, work is being done on the development of an artificial endocrine pancreas (PEA) consisting of a subcutaneous insulin pump, a subcutaneous glucose sensor and an algorithm of glucose control, which would calculate the bolus that the pump would infuse to patient. This project aims to design a controller for closed-loop therapy, with the objective of obtain an optimal regulation of blood glucose level. The design of this controller will be formed using the theory of internal model control (IMC). This theory is based on the uncertainties given by a model to feedback the system control. Output model, in comparison with the actual process gives the uncertainty of the plant model, compared to the real plant. Since the theory of the internal model, these differences occur at high frequencies, the theory proposes IMC as a low pass filter regulator in series with the inverse model of the plant to get the required behavior. In addition, it will implement a Smith Predictor to minimize the effects of the delay measurement sensor. The project for the viability of PEA has adapted the classic IMC controller using the gains static of glucose model from the subcutaneous infusion and subcutaneous measuring. In simulation the SemiClosed-Loop controller get on the normoglycemia range, requiring patient intervention announce the bolus priming connected to intakes. Using an SCL control with the Smith Predictor improves the outcome because a variable about intakes is added to the controller through patient intervention.

Automatic physical activity pattern recognition and meal intake modelling in type 1 diabetes for their inclusion in artificial pancreas systems

La diabetes comprende un conjunto de enfermedades metabólicas que se caracterizan por concentraciones de glucosa en sangre anormalmente altas. En el caso de la diabetes tipo 1 (T1D, por sus siglas en inglés), esta situación es debida a una ausencia total de secreción endógena de insulina, lo que impide a la mayoría de tejidos usar la glucosa. En tales circunstancias, se hace necesario el suministro exógeno de insulina para preservar la vida del paciente; no obstante, siempre con la precaución de evitar caídas agudas de la glucemia por debajo de los niveles recomendados de seguridad. Además de la administración de insulina, las ingestas y la actividad física son factores fundamentales que influyen en la homeostasis de la glucosa. En consecuencia, una gestión apropiada de la T1D debería incorporar estos dos fenómenos fisiológicos, en base a una identificación y un modelado apropiado de los mismos y de sus sorrespondientes efectos en el balance glucosa-insulina. En particular, los sistemas de páncreas artificial –ideados para llevar a cabo un control automático de los niveles de glucemia del paciente– podrían beneficiarse de la integración de esta clase de información. La primera parte de esta tesis doctoral cubre la caracterización del efecto agudo de la actividad física en los perfiles de glucosa. Con este objetivo se ha llevado a cabo una revisión sistemática de la literatura y meta-análisis que determinen las respuestas ante varias modalidades de ejercicio para pacientes con T1D, abordando esta caracterización mediante unas magnitudes que cuantifican las tasas de cambio en la glucemia a lo largo del tiempo. Por otro lado, una identificación fiable de los periodos con actividad física es un requisito imprescindible para poder proveer de esa información a los sistemas de páncreas artificial en condiciones libres y ambulatorias. Por esta razón, la segunda parte de esta tesis está enfocada a la propuesta y evaluación de un sistema automático diseñado para reconocer periodos de actividad física, clasificando su nivel de intensidad (ligera, moderada o vigorosa); así como, en el caso de periodos vigorosos, identificando también la modalidad de ejercicio (aeróbica, mixta o de fuerza). En este sentido, ambos aspectos tienen una influencia específica en el mecanismo metabólico que suministra la energía para llevar a cabo el ejercicio y, por tanto, en las respuestas glucémicas en T1D. En este trabajo se aplican varias combinaciones de técnicas de aprendizaje máquina y reconocimiento de patrones sobre la fusión multimodal de señales de acelerometría y ritmo cardíaco, las cuales describen tanto aspectos mecánicos del movimiento como la respuesta fisiológica del sistema cardiovascular ante el ejercicio. Después del reconocimiento de patrones se incorpora también un módulo de filtrado temporal para sacar partido a la considerable coherencia temporal presente en los datos, una redundancia que se origina en el hecho de que en la práctica, las tendencias en cuanto a actividad física suelen mantenerse estables a lo largo de cierto tiempo, sin fluctuaciones rápidas y repetitivas. El tercer bloque de esta tesis doctoral aborda el tema de las ingestas en el ámbito de la T1D. En concreto, se propone una serie de modelos compartimentales y se evalúan éstos en función de su capacidad para describir matemáticamente el efecto remoto de las concetraciones plasmáticas de insulina exógena sobre las tasas de eleiminación de la glucosa atribuible a la ingesta; un aspecto hasta ahora no incorporado en los principales modelos de paciente para T1D existentes en la literatura. Los datos aquí utilizados se obtuvieron gracias a un experimento realizado por el Institute of Metabolic Science (Universidad de Cambridge, Reino Unido) con 16 pacientes jóvenes. En el experimento, de tipo ‘clamp’ con objetivo variable, se replicaron los perfiles individuales de glucosa, según lo observado durante una visita preliminar tras la ingesta de una cena con o bien alta carga glucémica, o bien baja. Los seis modelos mecanísticos evaluados constaban de: a) submodelos de doble compartimento para las masas de trazadores de glucosa, b) un submodelo de único compartimento para reflejar el efecto remoto de la insulina, c) dos tipos de activación de este mismo efecto remoto (bien lineal, bien con un punto de corte), y d) diversas condiciones iniciales. ABSTRACT Diabetes encompasses a series of metabolic diseases characterized by abnormally high blood glucose concentrations. In the case of type 1 diabetes (T1D), this situation is caused by a total absence of endogenous insulin secretion, which impedes the use of glucose by most tissues. In these circumstances, exogenous insulin supplies are necessary to maintain patient’s life; although caution is always needed to avoid acute decays in glycaemia below safe levels. In addition to insulin administrations, meal intakes and physical activity are fundamental factors influencing glucose homoeostasis. Consequently, a successful management of T1D should incorporate these two physiological phenomena, based on an appropriate identification and modelling of these events and their corresponding effect on the glucose-insulin balance. In particular, artificial pancreas systems –designed to perform an automated control of patient’s glycaemia levels– may benefit from the integration of this type of information. The first part of this PhD thesis covers the characterization of the acute effect of physical activity on glucose profiles. With this aim, a systematic review of literature and metaanalyses are conduced to determine responses to various exercise modalities in patients with T1D, assessed via rates-of-change magnitudes to quantify temporal variations in glycaemia. On the other hand, a reliable identification of physical activity periods is an essential prerequisite to feed artificial pancreas systems with information concerning exercise in ambulatory, free-living conditions. For this reason, the second part of this thesis focuses on the proposal and evaluation of an automatic system devised to recognize physical activity, classifying its intensity level (light, moderate or vigorous) and for vigorous periods, identifying also its exercise modality (aerobic, mixed or resistance); since both aspects have a distinctive influence on the predominant metabolic pathway involved in fuelling exercise, and therefore, in the glycaemic responses in T1D. Various combinations of machine learning and pattern recognition techniques are applied on the fusion of multi-modal signal sources, namely: accelerometry and heart rate measurements, which describe both mechanical aspects of movement and the physiological response of the cardiovascular system to exercise. An additional temporal filtering module is incorporated after recognition in order to exploit the considerable temporal coherence (i.e. redundancy) present in data, which stems from the fact that in practice, physical activity trends are often maintained stable along time, instead of fluctuating rapid and repeatedly. The third block of this PhD thesis addresses meal intakes in the context of T1D. In particular, a number of compartmental models are proposed and compared in terms of their ability to describe mathematically the remote effect of exogenous plasma insulin concentrations on the disposal rates of meal-attributable glucose, an aspect which had not yet been incorporated to the prevailing T1D patient models in literature. Data were acquired in an experiment conduced at the Institute of Metabolic Science (University of Cambridge, UK) on 16 young patients. A variable-target glucose clamp replicated their individual glucose profiles, observed during a preliminary visit after ingesting either a high glycaemic-load or a low glycaemic-load evening meal. The six mechanistic models under evaluation here comprised: a) two-compartmental submodels for glucose tracer masses, b) a single-compartmental submodel for insulin’s remote effect, c) two types of activations for this remote effect (either linear or with a ‘cut-off’ point), and d) diverse forms of initial conditions.

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae): adequação de uma dieta artificial e avaliação do seu controle biológico com Trichogramma pretiosum Riley em tomateiro

Tuta absoluta (Meyrick, 1917) é uma das pragas-chave da cultura do tomate e outras solanáceas na América do Sul e atualmente também na Eurásia e África. Devido aos grandes prejuízos que causa à cultura, são principalmente usados inseticidas para o seu controle. Entretanto, na busca de estratégias mais sustentáveis, cada dia adquire maior importância o uso do controle biológico, como uma das estratégias do manejo integrado de pragas. Para o desenvolvimento destas estratégias é fundamental desenvolver um método de criação de T. absoluta em laboratório, em dieta artificial, sem necessitar do hospedeiro natural, muitas vezes difícil de ser obtido e mantido em laboratório, e, de grande importância para produzir parasitoides específicos para esta praga. Dentre os parasitoides mais usados para ovos de lepidópteros está Trichogramma pretiosum Riley 1879 que é usado no controle biológico aplicado desta praga. Tendo como foco principal T. absoluta, neste trabalho foram pesquisados 1) a seleção de uma dieta artificial para este lepidóptero baseando-se em características físicas e químicas, avaliando o seu desempenho por várias gerações em laboratório, e 2) avaliação de aspectos biológicos e reprodutivos de T. pretiosum parasitando ovos de T. absoluta e aspectos físicos da planta (tricomas) para compreender o controle biológico desta praga no tomateiro. Foi encontrado que uma dieta à base de germe-de-trigo, caseína e celulose é apropriada para a criação deste lepidóptero, já que o inseto mostrou adaptação à mesma no transcorrer das gerações com base em características biológicas e de tabela de vida; adicionalmente, os ovos provenientes de T. absoluta alimentada com dieta artificial são comparáveis aos da dieta natural, no parasitismo de T. pretiosum. Com relação ao controle biológico foi demonstrado que este parasitoide desenvolvido em ovos de T. absoluta, diminui seu tamanho e desempenho com o transcorrer das gerações, apresentando menor capacidade de voo do que os insetos produzidos em A. kuenhiella, sendo necessária a liberação de altas densidades de parasitoides por ovo da praga. Foi observado que, embora o parasitismo de T. pretiosum de ovos de T. absoluta seja melhor em variedades com poucos tricomas, uma alta densidade destas estruturas não impede o controle da praga alvo dependendo da disposição destas estruturas. O controle biológico de T. absoluta com T. pretiosum tem uma ação momentânea, sendo necessárias liberações frequentes devido ao fato de os parasitoides desenvolvidos na praga serem menos competitivos com aqueles provenientes do hospedeiro alternativo que apresenta ovos maiores do que T. absoluta.

The mechanistic conception of life; biological essays,

Reprinted from various sources.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

Application of the Artificial Intelligence Algorithms with a Cognitive Graphic as a Tool for a System Analysis of Electrophysiological Processes

Summarizing the accumulated experience for a long time in the polyparametric cognitive modeling of different physiological processes (electrocardiogram, electroencephalogram, electroreovasogram and others) and the development on this basis some diagnostics methods give ground for formulating a new methodology of the system analysis in biology. The gist of the methodology consists of parametrization of fractals of electrophysiological processes, matrix description of functional state of an object with a unified set of parameters, construction of the polyparametric cognitive geometric model with artificial intelligence algorithms. The geometry model enables to display the parameter relationships are adequate to requirements of the system approach. The objective character of the elements of the models and high degree of formalization which facilitate the use of the mathematical methods are advantages of these models. At the same time the geometric images are easily interpreted in physiological and clinical terms. The polyparametric modeling is an object oriented tool possessed advances functional facilities and some principal features.

Performance Comparison of MATLAB and Neuro Solution Software on Estimation of Fuel Economy by Using Artificial Neural Network

In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair:a retrospective observational study

Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

Castles in the air: the life, times and influence of the Reverend Moses Harvey (1820-1901).

The period from 1874 to 1901 was a time of significant transition in the economic and political life of Newfoundland. Twenty years into responsible government and with Confederation on the backburner, the colony’s politicians turned their attention to economic diversification, landward development and carving out the island’s place in the British Empire. The period saw both economic prosperity and retrenchment; the construction of a trans-insular railway; the adoption of policies to foster agriculture, forestry, manufacturing and mining; and diplomatic efforts to resolve France’s outstanding claims on the northwest coast of the island. At the same time, the government made an attempt to intervene directly in its primary industry, the fisheries. It created a Fisheries Commission in 1889 that recommended conservation measures and artificial propagation as ways to restore the health of some of the island’s fish stocks. They also proposed new methods of curing, packaging and marketing Newfoundland’s cod, as well as a complete overhaul of the truck system. A major player in both the public and private debates surrounding all of these subjects was the Reverend Moses Harvey. Along with being minister of the Free Church of Scotland in St. John’s, Harvey was one of Newfoundland’s most active promoters in the late nineteenth century. He served as the media mouthpiece for both Prime Minister William Whiteway and Prime Minister Robert Thorburn; editing the Evening Mercury – the official organ of the Liberal Party and then the Reform Party – from 1882 to 1883 and 1885 until 1890. As well, Harvey wrote regular columns on Newfoundland issues for newspapers in London, New York, Boston, Montreal, Toronto, and Halifax. He also produced numerous books, articles, encyclopedia entries, and travel guides outlining the island’s attractions and its vast economic potential. In short, Harvey made a significant contribution in shaping the way residents and the outside world viewed Newfoundland during this period. This thesis examines late nineteenth-century Newfoundland through the writing of Moses Harvey. The biographical approach offers a fuller, more nuanced account of some of the major historical themes of the period including the politics of progress, opening up the interior, railway construction and attitudes toward the fisheries. It also provides an insider’s prospective on what led to some of the major political decisions, policy positions or compromises taken by the Whiteway and Thorburn governments. Finally, a more detailed review of Harvey’s work exposes the practical and political differences that he had with people like D.W. Prowse and Bishop Michael Howley. While these so-called “boomers” in Newfoundland’s historiography agreed on broad themes, they parted ways over what should be done with the fisheries and how best to channel the colony’s growing sense of nationalism.

Activity-based life cycle costing model for cost estimation and monitoring – Case: manned and autonomous dry bulk carrier

Recent developments in automation, robotics and artificial intelligence have given a push to a wider usage of these technologies in recent years, and nowadays, driverless transport systems are already state-of-the-art on certain legs of transportation. This has given a push for the maritime industry to join the advancement. The case organisation, AAWA initiative, is a joint industry-academia research consortium with the objective of developing readiness for the first commercial autonomous solutions, exploiting state-of-the-art autonomous and remote technology. The initiative develops both autonomous and remote operation technology for navigation, machinery, and all on-board operating systems. The aim of this study is to develop a model with which to estimate and forecast the operational costs, and thus enable comparisons between manned and autonomous cargo vessels. The building process of the model is also described and discussed. Furthermore, the model’s aim is to track and identify the critical success factors of the chosen ship design, and to enable monitoring and tracking of the incurred operational costs as the life cycle of the vessel progresses. The study adopts the constructive research approach, as the aim is to develop a construct to meet the needs of a case organisation. Data has been collected through discussions and meeting with consortium members and researchers, as well as through written and internal communications material. The model itself is built using activity-based life cycle costing, which enables both realistic cost estimation and forecasting, as well as the identification of critical success factors due to the process-orientation adopted from activity-based costing and the statistical nature of Monte Carlo simulation techniques. As the model was able to meet the multiple aims set for it, and the case organisation was satisfied with it, it could be argued that activity-based life cycle costing is the method with which to conduct cost estimation and forecasting in the case of autonomous cargo vessels. The model was able to perform the cost analysis and forecasting, as well as to trace the critical success factors. Later on, it also enabled, albeit hypothetically, monitoring and tracking of the incurred costs. By collecting costs this way, it was argued that the activity-based LCC model is able facilitate learning from and continuous improvement of the autonomous vessel. As with the building process of the model, an individual approach was chosen, while still using the implementation and model building steps presented in existing literature. This was due to two factors: the nature of the model and – perhaps even more importantly – the nature of the case organisation. Furthermore, the loosely organised network structure means that knowing the case organisation and its aims is of great importance when conducting a constructive research.

Exploiting Collective Effects to Direct Light Absorption in Natural and Artificial Light-harvesters

Photosynthesis –the conversion of sunlight to chemical energy –is fundamental for supporting life on our planet. Despite its importance, the physical principles that underpin the primary steps of photosynthesis, from photon absorption to electronic charge separation, remain to be understood in full. Electronic coherence within tightly-packed light-harvesting (LH) units or within individual reaction centers (RCs) has been recognized as an important ingredient for a complete understanding of the excitation energy transfer (EET) dynamics. However, the electronic coherence across units –RC and LH or LH and LH –has been consistently neglected as it does not play a significant role during these relatively slow transfer processes. Here, we turn our attention to the absorption process, which, as we will show, has a much shorter built-in timescale. We demonstrate that the- often overlooked- spatially extended but short-lived excitonic delocalization plays a relevant role in general photosynthetic systems. Most strikingly, we find that absorption intensity is, quite generally, redistributed from LH units to the RC, increasing the number of excitations which can effect charge separation without further transfer steps. A biomemetic nano-system is proposed which is predicted to funnel excitation to the RC-analogue, and hence is the first step towards exploiting these new design principles for efficient artificial light-harvesting.

Ambiente para avaliação de controladores fuzzy aplicados ao método de elevação artificial por bombeio centrífugo submerso

From their early days, Electrical Submergible Pumping (ESP) units have excelled in lifting much greater liquid rates than most of the other types of artificial lift and developed by good performance in wells with high BSW, in onshore and offshore environments. For all artificial lift system, the lifetime and frequency of interventions are of paramount importance, given the high costs of rigs and equipment, plus the losses coming from a halt in production. In search of a better life of the system comes the need to work with the same efficiency and security within the limits of their equipment, this implies the need for periodic adjustments, monitoring and control. How is increasing the prospect of minimizing direct human actions, these adjustments should be made increasingly via automation. The automated system not only provides a longer life, but also greater control over the production of the well. The controller is the brain of most automation systems, it is inserted the logic and strategies in the work process in order to get you to work efficiently. So great is the importance of controlling for any automation system is expected that, with better understanding of ESP system and the development of research, many controllers will be proposed for this method of artificial lift. Once a controller is proposed, it must be tested and validated before they take it as efficient and functional. The use of a producing well or a test well could favor the completion of testing, but with the serious risk that flaws in the design of the controller were to cause damage to oil well equipment, many of them expensive. Given this reality, the main objective of the present work is to present an environment for evaluation of fuzzy controllers for wells equipped with ESP system, using a computer simulator representing a virtual oil well, a software design fuzzy controllers and a PLC. The use of the proposed environment will enable a reduction in time required for testing and adjustments to the controller and evaluated a rapid diagnosis of their efficiency and effectiveness. The control algorithms are implemented in both high-level language, through the controller design software, such as specific language for programming PLCs, Ladder Diagram language.