Dissertations / Theses on the topic 'Uncertainty treatment'

This dissertation addresses the issue of robustness in proton therapy treatment planning for cancer treatment. Proton therapy is considered to be advantageous in treating most childhood cancers and certain adult cancers, including those of the skull base, spine and head and neck. Protons, unlike X-rays, have a finite range highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. These characteristics, together with advancements in computation and technology have led to the ability to plan and deliver treatments with greater conformality, sparing normal tissue and organs at risk. Radiotherapy treatment plans aim to meet set dosimetric constraints, and meet them at every fraction. Plan robustness is a measure of deviation between the delivered dose distribution and the planned dose distribution. Due to the same characteristics that make protons advantageous, conventional means of using margins to create a Planning Target Volume (PTV) to ensure plan robustness are inadequate. Additional to this, without a PTV, a new method of analysing plan quality is required in proton therapy. My original contribution to the knowledge in this area is the demonstration of how site- and centre- specific robustness constraints can be established. Robustness constraints can be used both for proton plan analysis and to identify patients that require plans of greater individualisation. I have also used the daily volumetric imaging from patients previously treated with conventional radiotherapy to quantify range uncertainty from inter- and intra-fraction motion. These new methods of both quantifying and analysing the change in proton range in the patient can aid in the choice of beam directions, provide input into a multi- criteria optimisation algorithm or can be used as criteria to determine when adaptive planning may be required. This greater understanding in range uncertainty better informs the planner on how best to balance the trade-off between plan conformality and robustness in proton therapy. This research is directly relevant to furthering the knowledge base in light of HM Government pledging £250 million to build two proton centres in England, to treat NHS patients from 2018. Use of methods described in this dissertation will aid in the establishment of clear and pre-defined protocols for treating patients in the future.

Bibliography: leaves 142-149.
The nature of human decision making dictates that a decision must often be considered under conditions of uncertainty. Decisions may be influenced by uncertain future events, doubts regarding the precision of inputs, doubts as to what the decision maker considers important, and many other forms of uncertainty. The multicriteria decision models that are designed to facilitate and aid decision making must therefore consider these uncertainties if they are to be effective. In this thesis, we consider the treatment of uncertainty in multicriteria decision making (MCDM), with a specific view to investigating the types of uncertainty that are most relevant to MCDM, [and] how the uncertainties identified as relevant may be treated by various different MCDM methodologies.

The purpose of this thesis was to acquaint the reader on the nature of the uncertainty present in construction price forecasting and to introduce an environment that has the ability to integrate these uncertainties with greater consistency than that possessed by available price models. The objective of this thesis was to establish that uncertainty can be explicitly treated in price forecasting models. This would have two benefits to concerned parties. Firstly, the effectiveness of price forecasts could be improved as provision could be made for any uncertain variable. This will be of great benefit to the client, as a more accurate assessment of the building process could be established at an earlier stage of the design process. Secondly, the price forecast will be more useful to quantity surveyors, architects and clients, as it would 'quantify' the extent of the uncertainty which could be provided for in a more meaningful manner. In order to establish that existing price models do not deal with the uncertainty present at the time of forecasting, the price models used by practitioners were evaluated against the different types of uncertainty found at the different stages of the price forecasting process. Once this had been established, eight techniques that have the ability to treat various forms of uncertainty, were presented. After analysing the techniques abilities to cope with the uncertainties associated with price forecasting, it was established that certain of these techniques do have the ability, and are suitable, to be incorporated into the price forecasting process. From the results of a questionnaire survey conducted on quantity surveying offices in South Africa, it was found that the price models used by practitioners do not take uncertainty into account, and have in fact, the potential for uncertainty inducement. Some of the uncertainty found to be present in the preparation of a construction price forecast include the lack or incompleteness of design information, the uncertainty in the communication of design information, the variability in the data used by quantity surveyors and, the uncertainty in the choice of price model during the different stages of the design process. As a possible solution to the problem of uncertainty, an expert system environment, utilising a three-dimensional classification of uncertainty, has been proposed. It has been proved that this environment has the ability to cater for the uncertainty associated with the price forecasting process, as well as having the attribute of providing the user with the reasoning behind the logic that the expert system has followed, a characteristic not possible with the traditional forms of price models. From the findings of this thesis, it can be concluded that the methods of price modelling used by quantity surveying practitioners, are unable to take uncertainty into account effectively. It can also be concluded that an expert system environment has the ability to handle the different forms of uncertainty found at the various stages of construction design. The proposed model is conceptual in nature and has not been tested in practice. It is therefore recommended that further research be carried out in this field, with the aim of producing a construction price forecasting expert system which utilises the proposed three-dimensional classification of uncertainty.

2010/2011
Nello studio dei sistemi di trasporto l’acquisizione e l’utilizzo di informazioni corrette e aggiornate sullo stato dei sistemi rappresentano da sempre elementi di centrale importanza per la produzione di analisi adeguate ed affidabili. Sfortunatamente in molti ambiti applicativi le informazioni disponibili per le analisi sono invece spesso carenti o di bassa qualità, e il loro utilizzo si traduce in risultati affetti da elevata incertezza e talvolta di dubbia validità. I processi di evoluzione tecnologica che interessano campi quali l’informatica, l’elettronica e le telecomunicazioni stanno rendendo progressivamente più semplice e conveniente l’acquisizione di rilevanti quantità di dati di interesse per le analisi trasportistiche, sia tradizionalmente raccolti per studi trasportistici (ad esempio dati di traffico rilevati su tronchi stradali) sia non direttamente connessi ad un uso trasportistico (ad esempio segnali Bluetooth e GPS provenienti da dispositivi di telefonia mobile). Tuttavia in molti casi l’ampia disponibilità di dati, soprattutto nel secondo caso, non si traduce in immediata spendibilità applicativa. I dati sono infatti spesso disomogenei dal punto di vista informativo, caratterizzati da una qualità non necessariamente elevata e spesso richiedono onerosi processi di verifica e validazione. In questi particolari contesti l’applicazione di tecniche di Data Mining può dimostrarsi una soluzione indubbiamente vantaggiosa. Esse infatti, per loro intrinseca natura, rendono possibile la gestione efficace di grandi quantità di dati e la produzione di risultati sempre più robusti all’aumentare delle dimensioni della base di dati disponibile. Sulla base di queste considerazioni questo lavoro di tesi si è concentrato in primo luogo su un’attenta revisione delle più consolidate tecniche di Data Mining, individuando gli ambiti applicativi, nel campo dei trasporti, in cui esse possono rappresentare dei validi strumenti di analisi. Con il termine Data Mining si fa riferimento al processo di estrazione dell’informazione presente in un certo insieme di dati, finalizzato ad individuare relazioni “nascoste” nei dati stessi o comunque a sintetizzare in modalità nuove la visione su di essi. Esso rappresenta una parte di un più ampio processo di estrazione della conoscenza, che inizia con un’accurata selezione e trasformazione dei dati disponibili (come detto i dati sottoposti a “mining” sono spesso raccolti con altri obiettivi) e si conclude con un’attenta interpretazione e valutazione dei risultati. Uno schema di classificazione generalmente accettato suddivide le tecniche di Data Mining in sei categorie in rapporto alla funzione considerata: stima (reti neurali, modelli di regressione, alberi decisionali), previsione (reti neurali, alberi decisionali), classificazione (k-nearest neighbour, alberi decisionali, reti neurali), raggruppamento (tecniche di clustering, Self-Organising-Maps), associazione (regole di associazione) e descrizione (regole di associazione, clustering, alberi decisionali). Nel presentare un quadro d’insieme dell’ampia letteratura esistente in materia, uno specifico rilievo è stato dato alle più consolidate tecniche di classificazione, raggruppamento e associazione, in quanto maggiormente impiegate nei diversi contesti applicativi. Successivamente è stato tracciato uno stato dell’arte per ciò che attiene le applicazioni in ambito trasportistico. In tal senso la revisione dei lavori prodotti ha evidenziato la notevole flessibilità d’uso di queste tecniche e la loro crescente diffusione applicativa. Molti sono infatti i filoni di ricerca che hanno beneficiato di queste tecniche innovative; tra questi nel lavoro di tesi si sono evidenziati alcuni tra i più interessanti: la previsione a breve termine dei flussi di traffico da dati storici o in real-time (traffic forecasting), l’identificazione e la quantificazione dei fattori che influenzano i fenomeni di incidentalità, l’analisi di sistemi di gestione delle pavimentazioni stradali e di sistemi di monitoraggio del traffico. La seconda parte della tesi si è invece focalizzata su un’applicazione delle tecniche di Data Mining allo studio del funzionamento di un sistema viario, attraverso una revisione critica della Procedura FHWA (Federal Highway Administration) per il monitoraggio del traffico stradale. La scelta di questo filone di ricerca è data dal fatto che la raccolta di informazioni sui volumi di traffico è un aspetto rilevante nell’attività di pianificazione dei trasporti (ambito stradale), quale componente significativa del processo conoscitivo. D’altra parte i costi legati alla gestione dei sistemi di monitoraggio, sia per attrezzature che per personale, richiedono una crescente attenzione alla loro progettazione, al fine di ottenere la massima qualità dei risultati. Negli Stati Uniti la FHWA definisce periodicamente alcune linee guida per migliorare questi aspetti attraverso la Traffic Monitoring Guide (2001) e ha raggiunto progressivamente un ruolo di riferimento per altre agenzie dello stesso tipo in altre parti del mondo, Italia compresa. Tale procedura è basata sull’uso congiunto di rilievi di diversa durata (rilievi in continuo con strumenti fissi e rilievi di breve durata con apparecchiature portatili) ed è finalizzata principalmente alla stima del Traffico Giornaliero Medio Annuo (Annual Average Daily Traffic, AADT). L’analisi della letteratura esistente ha individuato la lacuna principale della procedura FHWA nella determinazione dei gruppi tipologici di strade sulla base dei profili temporali di traffico e nell’assegnazione delle sezioni monitorate con rilievi di breve durata a questi gruppi. L’approccio elaborato si è pertanto posto l’obiettivo di migliorare la procedura relativamente a questi due aspetti rilevanti. Per trattare l’esistenza di situazioni di incerta attribuzione di una sezione stradale ad un certo gruppo tipologico, specie quando non è semplice fornire una chiara definizione in termini trasportistici (ad esempio strada “pendolare” o “turistica”), sono state adottate tecniche di Fuzzy Clustering, garantendo un’opportuna trattazione formale del problema. Per quanto concerne il secondo aspetto, le sezioni non monitorate in continuo vengono inserite nel gruppo tipologico più simile rispetto ai profili temporali di traffico osservati. Per effettuare l’assegnazione di queste sezioni ai gruppi tipologici, l’approccio proposto ha utilizzato una Rete Neurale Artificiale, opportunamente progettata per mantenere l’incertezza presente nella fase di creazione dei gruppi fino alla fine del processo. L’output della rete è infatti rappresentato dall’insieme delle probabilità di appartenenza del rilievo di breve durata ai diversi gruppi tipologici ed è interpretato utilizzando la teoria di Dempster-Shafer. Le misure di incertezza associate all’output (indici di non-specificità e discordanza) permettono di descrivere sinteticamente la qualità dell’informazione disponibile. L’approccio proposto è stato implementato considerando i dati di monitoraggio provenienti dal programma SITRA (Sistema Informativo TRAsporti) della Provincia di Venezia. Rispetto all’ambito applicativo di interesse è stata verificata la validità dell’approccio, confrontando i risultati ottenuti nella stima dell’AADT con precedenti approcci proposti in letteratura. L’analisi comparativa dei risultati ha permesso di rilevare una migliore accuratezza delle stime e soprattutto la possibilità, assente nei precedenti approcci, di evidenziare eventuali carenze informative (dovute all’esiguo numero di dati) e la necessità di procedere con ulteriori rilievi di traffico. I risultati positivi ottenuti in questa fase sperimentale hanno permesso di avviare il progetto per la realizzazione di uno strumento software di immediata spendibilità applicativa
In the study of transportation systems, the collection and the use of correct information of the state of the system represent a central point for the development of reliable and proper analyses. Unfortunately in many application fields information is generally obtained using limited, scarce and low-quality data and their use produces results affected by high uncertainty and in some cases low validity. Technological evolution processes which interest different fields, including Information Technology, electronics and telecommunications make easier and less expensive the collection of large amount of data which can be used in transportation analyses. These data include traditional information gathered in transportation studies (e.g. traffic volumes in a given road section) and new kind of data, not directly connected to transportation needs (i.e. Bluetooth and GPS data from mobile phones). However in many cases, in particular for the latter case, this large amount of data cannot be directly applied to transportation problems. Generally there are low-quality, non-homogeneous data, which need time consuming verification and validation process to be used. Data Mining techniques can represent an effective solution to treat data in these particular contexts since they are designed to manage large amount of data producing results whose quality increases as the amount of data increases. Based on these facts, this thesis first presents a review of the most well-established Data Mining techniques, identifying application contexts in transportation field for which they can represent useful analysis tools. Data mining can be defined as the process of exploration and analysis which aims to discover meaningful patterns and ‘’hidden’’ rules in the set of data under analysis. Data Mining could be considered a step of a more general Knowledge Discovery in Databases Process, which begins with selection, pre-processing and transformation of data (“mined” data are generally collected for reasons different from the analysis) and is completed with the interpretation and evaluation of results. A classification scheme generally accepted identifies six categories of DM techniques, which are related to the objective one would achieve from the analysis: estimation (neural networks, regression models, decision trees), prediction (neural networks, decision trees), classification (k-nearest neighbor, decision trees, neural networks), clustering (clustering techniques, Self-Organizing-Maps), affinity grouping or association (association rules) and profiling (association rules). In the review of the wide literature concerning Data Mining methods, particular attention has been devoted to the well-established technique of clustering, classification and association, since they are the most applied in different application contexts. The literature review process has been further extended to Data Mining applications in the transportation field. This review highlights the great flexibility of use of these techniques and the increasing number of applications. Many research topics have taken advantages of these innovative tools and some of them are presented due to their interest: short-term traffic flow forecasting from historical and real-time data, identification and quantification of factor risks in accident analysis, analysis of pavement management systems and traffic monitoring systems. The second part of the thesis has focused on the application of Data Mining techniques to road system analysis, through a critical review of U.S. Federal Highway Administration (FHWA) traffic monitoring approach. The choice of this topic is due to the fact that traffic monitoring activities represent a relevant aspect of highway planning activities, as a part of the knowledge process. However data collection activities produce relevant management costs, both for equipment and personnel, therefore monitoring programs need to be designed with attention to obtain the maximum quality of results. In the U.S.A., the Federal Highway Administration (FHWA) provides guidance for improving these aspects by way of its Traffic Monitoring Guide (TMG) (FHWA, 2001), which has a reference role for other similar agencies in the world. The FHWA procedure is based on two types of counts (short duration counts taken with portable traffic counters and continuous counts taken with fixed counters) and has the main objective of determine the Annual Average Daily Traffic (AADT). Critical review of literature on this topic has pointed out that the most critical aspects of this procedure are the definition of road groups based on traffic flow patterns and the assignment of a section to a road group using short counts. The proposed approach has been designed to solve both issues. The first issue is related to situations for which road section could belong to more than one road group, and the groups cannot be easily defined in transportation terms, (e.g. “commuter road”, “recreational road”). The proposed approach introduces Fuzzy Clustering techniques, which adopt an analytical framework consistent with this kind of uncertainty. Concerning the second issue, road sections monitored with short counts are assigned to the road group with more similar traffic patterns. In the proposed approach an Artificial Neural Network is implemented to assign short counts to roads groups. The Neural network is specifically designed to maintain the uncertainty related to the definition of road groups until the end of the estimation process. In fact the output of the Neural Network are the probabilities that the a specific short counts belongs to the road groups. These probabilities are interpreted using the Dempster-Shafer theory; measures of uncertainty related to the output (indices of non-specificity and discord) provide an assessment of the quality of information in a synthetic manner. The proposed approach have been implement on a case study, using traffic data from SITRA (Sistema Informativo TRAsporti) monitoring program of the Province of Venice. In this specific context the approach has been validated and the results obtained (AADT estimates) from the proposed method have been compared with those obtained by two approaches proposed in previous studies. The comparative analysis highlights that the proposed approach increases the accuracy of estimates and gives indication of the quality of assignment (depending on sample size) and suggests the need for additional data collection. The positive results obtained in the experimental phase of the research have led to the design of a software tool to be used in next future in real world applications.
XXIV Ciclo
1983

Copies of the author's published articles derived from this thesis work are included in appendix. Bibliography: p. 223-237. This thesis involves three major streams of research including investigation of the actual dose delivered to target and normal tissue, the effect of dose uncertainty on radiobiological indices, and techniques to display the dose uncertainty in a treatment planning system. All of the analyses are performed with the dose distribution from a four-field box treatment using 6 MV photons.

Uncertainty is recognized as a significant perceptual variable in the experience of illness. The purpose of this study was to gain an understanding of how parents of ill infants cope with the uncertainty inherent in illness-related events and situations. A conceptual framework of coping with uncertainty was proposed and tested. The four constructs in the model and their measures were perceived uncertainty (Mishel's Parents' Perceptions of Uncertainty Scale), cognitive appraisal (Lazarus and Folkman's Appraisal Questionnaire), coping efforts (Lazarus and Folkman's Ways of Coping Checklist) and cognitive schema (Mishel's Parents' Perceptions of Uncertainty Scale and grounded theory methodology). Methodological triangulation was used. A quantitative, longitudinal, descriptive correlational design examined the model. A qualitative study using grounded theory methodology explored the forming and using of a cognitive schema. A convenience sample of 37 parents of critically ill neonates participated in the quantitative study with 15 of those also participating in the qualitative study. Self report questionnaires measured model variables. Interviews comprised the grounded theory approach. Descriptive and correlational statistics characterized model variables and their relationships. Constant comparative analysis identified processes central to forming and using a cognitive schema. From the descriptive results, parents perceived high levels of uncertainty when measured at approximately 2.5 days following the ill infant's birth. Appraisal of uncertainty as harmful to well-bring was correlated with perceived ambiguity (r =.63) and complexity (r =.36). The coping efforts of self-blame (r =.53) and wishful thinking (r =.44) were related to the harm appraisal. Significant decreases in perceived ambiguity and lack of information were demonstrated when uncertainty was measured again at approximately eight days following birth. From the grounded theory methodology, three processes central to cognitive schema were identified (forming, framing, using) were discovered and conceptualized. When uncertainty was perceived, parents actively sought information in forming a schema. With sufficient information, information was categorized to frame an explanation of illness experiences. With framing, schema was created and used by the parents. Methodological triangulation accounted for consistencies and inconsistencies across quantitative and qualitative results. The model of coping with uncertainty was supported through triangulation.

[EN] Patients suffering from Type 1 Diabetes are not able to secrete insulin, thus, they have to get it administered externally. Current research is focused on developing an artificial pancreas, a control system that automatically administers insulin according to patient's needs. The work presented here aims to improve the efficiency and safety of control algorithms for artificial pancreas. Glucose-insulin models try to mimic the administration of external insulin, the absorption of carbohydrates, and the influence of both of them in blood glucose concentration. However, these processes are infinitely complex and they are characterized by their high variability. The mathematical models used are often a simplified version which does not include all the process variability and, therefore, they do not always match reality. This deficiency on the models can be addressed by considering uncertainty on their parameters and initial conditions. In this way, the exact values are unknown but they can be bounded by intervals that comprehend all the variability of the considered process. When the value of the parameters and initial conditions is known, there is usually just one possible behaviour. However, if they are bounded by intervals, a set of possible solutions exists. In this case, it is interesting to compute a solution envelope that guarantees the inclusion of all the possible behaviours. A common technique to compute this envelope is the monotonicity analysis of the system. Nevertheless, some overestimation is produced if the system is not fully monotone. In this thesis, several methods and approaches have been developed to reduce, or even eliminate, the overestimation in the computation of solution envelopes, while satisfying the inclusion guarantee. Another problem found during the use of an artificial pancreas is that only the subcutaneous glucose concentration can be measured in real time, with some noise in the measurements. The rest of the system states are unknown, but they could be estimated from this set of noisy measurements by state observers, like Kalman filters. A detailed example is shown at the end of this thesis, where an Extended Kalman Filter is used to estimate in real time insulin concentration based on the food ingested and in periodical measurements of subcutaneous glucose.
[ES] Los pacientes que sufren de diabetes tipo 1 no son capaces de secretar insulina, por lo que tienen que administrársela externamente. La investigación actual se centra en el desarrollo de un páncreas artificial, un sistema de control que administre automáticamente la insulina en función de las necesidades del paciente. El trabajo que aquí se presenta tiene como objetivo mejorar la eficiencia y la seguridad de los algoritmos de control para el páncreas artificial. Los modelos de glucosa-insulina tratan de emular la administración externa de la insulina, la absorción de carbohidratos y la influencia de ambos en la concentración de glucosa en sangre. El problema es que estos procesos son infinitamente complejos y se caracterizan por su alta variabilidad. Los modelos matemáticos utilizados suelen ser una versión simplificada que no incluye toda la variabilidad del proceso y, por lo tanto, no coinciden con la realidad. Esta deficiencia de los modelos puede subsanarse considerando inciertos sus parámetros y las condiciones iniciales, de manera que se desconoce su valor exacto pero sí podemos englobarlos en ciertos intervalos que comprendan toda la variabilidad del proceso considerado. Cuando los valores de los parámetros y de las condiciones iniciales son conocidos, existe, por lo general, un único comportamiento posible. Sin embargo, si están delimitados por intervalos se obtiene un conjunto de posibles soluciones. En este caso, interesa obtener una envoltura de las soluciones que garantice la inclusión de todos los comportamientos posibles. Una técnica habitual que facilita el cómputo de esta envoltura es el análisis de la monotonicidad del sistema. Sin embargo, si el sistema no es totalmente monótono la envoltura obtenida estará sobrestimada. En esta tesis se han desarrollado varios métodos para reducir, o incluso eliminar, la sobrestimación en el cálculo de envolturas, al tiempo que se satisface la garantía de inclusión. Otro inconveniente con el que nos encontramos durante el uso de un páncreas artificial es que solo es posible medir en tiempo real, con cierto ruido en la medida, la glucosa subcutánea. El resto de los estados del sistema son desconocidos, pero podrían ser estimados a partir de este conjunto limitado de mediciones con ruido utilizando observadores de estado, como el Filtro de Kalman. Un ejemplo detallado se muestra al final de la tesis, donde se estima en tiempo real la concentración de insulina en plasma en función de la comida ingerida y de mediciones periódicas de la glucosa subcutánea con ayuda de un Filtro de Kalman Extendido.
[CAT] Els pacients que pateixen de diabetis tipus 1 no són capaços de secretar insulina, motiu pel qual han d'administrar-se-la externament. La investigació actual es centra en el desenvolupament d'un pàncrees artificial, un sistema de control que administre automàticament la insulina en funció de les necessitats del pacient. El treball que ací es presenta té com a objectiu millorar l'eficiència i la seguretat dels algorismes de control per al pàncrees artificial. Els models de glucosa-insulina tracten d'emular l'administració externa de la insulina, l'absorció de carbohidrats i la influència d'ambdós factors en la concentració de glucosa en sang. El problema és que estos processos són infinitament complexos i es caracteritzen per la seua alta variabilitat. Els models matemàtics emprats solen ser una versió simplificada que no inclou tota la variabilitat del procés i, per tant, no coincideixen amb la realitat. Esta deficiència dels models pot esmenar-se considerant incerts els seus paràmetres i les condicions inicials, de manera que es desconeix el seu valor exacte però sí podem englobar-los en certs intervals que comprenguen tota la variabilitat del procés considerat. Quan els valors dels paràmetres i de les condicions inicials són coneguts, existeix, en general, un únic comportament possible. No obstant, si estan delimitats per intervals s'obté un conjunt de possibles solucions. En este cas, interessa obtindre un embolcall de les solucions que assegure la inclusió de tots els comportaments possibles. Una tècnica habitual que facilita el còmput d'este embolcall és l'anàlisi de la monotonicitat del sistema. No obstant, si el sistema no és totalment monòton l'embolcall obtingut estarà sobreestimat. En esta tesi s'han desenvolupat diversos mètodes per a reduir, o fins i tot eliminar, la sobreestimació en el càlcul dels embolcalls, al temps que se satisfà la garantia d'inclusió. Altre inconvenient amb què ens trobem durant l'ús d'un pàncrees artificial és que només és possible mesurar en temps real, amb cert soroll en la mesura, la glucosa subcutània. La resta dels estats del sistema són desconeguts, però podrien ser estimats a partir d'este conjunt limitat de mesures amb soroll utilitzant observadors d'estat, com el Filtre de Kalman. Un exemple detallat es mostra al final de la tesi, on s'estima en temps real la concentració d'insulina en plasma en funció del menjar ingerit i de les mesures periòdiques de la glucosa subcutània amb ajuda d'un Filtre de Kalman Estés.
Pereda Sebastián, DD. (2015). Methods for the treatment of uncertainty in dynamical systems: Application to diabetes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/54121
TESIS

In order to perform the environmental analysis and find the best management in the wastewater treatment processes using life cycle assessment (LCA) method, uncertainty in LCA has to be evaluated. A qualitative and quantitative procedure was constructed to deal with uncertainty for the wastewater treatment LCA studies during the inventory and analysis stages. The qualitative steps in the procedure include setting rules for the inclusion of inputs and outputs in the life cycle inventory (LCI), setting rules for the proper collection of data, identifying and conducting data collection analysis for the significant contributors in the model, evaluating data quality indicators, selecting the proper life cycle impact assessment (LCIA) method, evaluating the uncertainty in the model through different cultural perspectives, and comparing with other LCIA methods. The quantitative steps in the procedure include assigning the best guess value and the proper distribution for each input or output in the model, calculating the uncertainty for those inputs or outputs based on data characteristics and the data quality indicators, and finally using probabilistic analysis (Monte Carlo simulation) to estimate uncertainty in the outcomes. Environmental burdens from the solids handling unit at Bissell Point Wastewater Treatment Plant (BPWWTP) in Saint Louis, Missouri was analyzed. Plant specific data plus literature data were used to build an input-output model. Environmental performance of an existing treatment scenario (dewatering-multiple hearth incineration-ash to landfill) was analyzed. To improve the environmental performance, two alternative scenarios (fluid bed incineration and anaerobic digestion) were proposed, constructed, and evaluated. System boundaries were set to include the construction, operation and dismantling phases. The impact assessment method chosen was Eco-indicator 99 and the impact categories were: carcinogenicity, respiratory organics and inorganics, climate change, radiation, ozone depletion, ecotoxicity, acidification-eutrophication, and minerals and fossil fuels depletion. Analysis of the existing scenario shows that most of the impacts came from the operation phase on the categories related to fossil fuels depletion, respiratory inorganics, and carcinogens due to energy consumed and emissions from incineration. The proposed alternatives showed better performance than the existing treatment. Fluid bed incineration had better performance than anaerobic digestion. Uncertainty analysis showed there is 57.6% possibility to have less impact on the environment when using fluid bed incineration than the anaerobic digestion. Based on single scores ranking in the Eco-indicator 99 method, the environmental impact order is: multiple hearth incineration > anaerobic digestion > fluid bed incineration. This order was the same for the three model perspectives in the Eco-indicator 99 method and when using other LCIA methods (Eco-point 97 and CML 2000). The study showed that the incorporation of qualitative/quantitative uncertainty analysis into LCA gave more information than the deterministic LCA and can strengthen the LCA study. The procedure tested in this study showed that Monte Carlo simulation can be used in quantifying uncertainty in the wastewater treatment studies. The procedure can be used to analyze the performance of other treatment options. Although the analysis in different perspectives and different LCIA methods did not impact the order of the scenarios, it showed a possibility of variation in the final outcomes of some categories. The study showed the importance of providing decision makers with the best and worst possible outcomes in any LCA study and informing them about the perspectives and assumptions used in the assessment. Monte Carlo simulation is able to perform uncertainty analysis in the comparative LCA only between two products or scenarios based on the (A-B) approach due to the overlapping between the probability distributions of the outcomes. It is recommended to modify it to include more than two scenarios.

Increasing population, diminishing supplies and variable climatic conditions can cause difficulties in meeting water demands. When this long range water supply plan is developed to cope with future water demand changes, accuracy and reliability are the two most important factors. To develop an accurate model, the water supply system has become more complicated and comprehensive structures. Future uncertainty also has been considered to improve system reliability as well as economic feasibility.In this study, a general large-scale water supply system that is comprised of modular components was developed in a dynamic simulation environment. Several possible scenarios were simulated in a realistic hypothetical system. In addition to water balances and quality analyses, construction and operation of system components costs were estimated for each scenario. One set of results demonstrates that construction of small-cluster decentralized wastewater treatment systems could be more economical than a centralized plant when communities are spatially scattered or located in steep areas.The Shuffled Frog Leaping Algorithm (SFLA), then, is used to minimize the total system cost of the general water supply system. Decisions are comprised of sizing decisions - pipe diameter, pump design capacity and head, canal capacity, and water/wastewater treatment capabilities - and flow allocations over the water supply network. An explicit representation of energy consumption cost for the operation is incorporated into the system in the optimization process of overall system cost. Although the study water supply systems included highly nonlinear terms in the objective function and constraints, a stochastic search algorithm was applied successfully to find optimal solutions that satisfied all the constraints for the study networks.Finally, a robust optimization approach was introduced into the design process of a water supply system as a framework to consider uncertainties of the correlated future data. The approach allows for the control of the degree of conservatism which is a crucial factor for the system reliabilities and economical feasibilities. The system stability is guaranteed under the most uncertain condition and it was found that the water supply system with uncertainty can be a useful tool to assist decision makers to develop future water supply schemes.

Dans les moteurs d'avions modernes, le bruit de fan est une des principales sources de bruit du fait d'une augmentation constante du taux de dilution des moteurs visant à réduire leur consommation. Le bruit de fan étant caractérisé par des composantes tonales et multimodales, des traitements acoustiques appelés liners sont utilisés pour leur efficacité à réduire des composantes de bruit, par des effets de dissipation acoustique réglables en modifiant la géométrie du liner. Des modèles de prédictions numériques sont alors utilisés pour leur réglage. Le design du liner étant gelé dans des phases préliminaires du développement d'un avion, il existe une variabilité non négligeable sur son environnement de fonctionnement. Cette variabilité impacte directement le design du liner en induisant une large disparité des données utilisées pour son design. De plus, à mesure que la maturité de l'avion augmente, chaque mise-à-jour de ces données impose une réoptimisation du liner. Cette étape de réoptimisation induit alors d'importants coûts de calcul qui pourraient être évités en prenant en compte cette variabilité durant les phases préliminaires de design. Il s'agit de la principale problématique de ce travail. À mesure que cette variabilité externe impacte l'environnement d'opérabilité du liner, le modèle numérique de performance du liner devient alors incertain. Afin de quantifier et prendre en compte cette nature incertaine, une conception robuste du liner est alors entreprise, par quantifiant l'incertitude globale qui réside dans le modèle numérique de performance acoustique du liner. Le modèle aéroacoustique numérique utilisé est un code industriel, ACTRAN/TM, et nécessite d'être intensivement étudié afin d'en déduire les principaux composants les plus sensibles vis-à-vis de l'incertitude globale. Un modèle stochastique des incertitudes est alors introduit et greffé sur le modèle aéroacoustique. Il permet de simuler l'incertitude globale mentionnée précédemment, en prenant en compte l'incertitude qui réside dans le modèle numérique (erreurs de modèles et erreurs des paramètres du modèle), en utilisant les approches probabilistes paramétriques et non-paramétriques. Ensuite, la propagation des incertitudes dans le système est analysée en utilisant un solveur stochastique tel que la méthode de Monte Carlo. La réponse acoustique du système est alors aléatoire et la quantification des incertitudes consiste en une estimation de données statistiques telles que les intervalles de confiances associés à un certain niveau de confiance sur les quantités d'intérêts. À partir de cette information statistique, la robustesse d'un design spécifique de liner vis-à-vis d'une variabilité simulée sur son modèle de performance peut être définie, en plus de l'information classique de performance acoustique. Cette information permet alors de connaître la propension d'un design à maintenir sa performance nominale lorsque son environnement change dans un intervalle de variation préalablement défini par le niveau d'incertitudes imposé au modèle stochastique. Alors, le meilleur design peut être choisi en faisant un compromis entre performance et robustesse
In modern turbofan engines, fan noise is one of the main noise sources due to the constant increasing of engines bypass ratio for fuel burn reduction purposes. As fan noise is characterized by broadband and tonal components, acoustic liners are introduced for their effectiveness in mitigating both components through dissipation effects that are tunable by modifying the liner geometry. Simulations issued from prediction numerical tools are thus extensively used for their tuning, since experiments cannot be considered for obvious costs reasons. As the design of liner systems is frozen in early stages of an aircraft development, it exists a non-negligible variability on its operating environment. This variability directly impacts the design of liners by inducing large discrepencies on the quantities used for its numerical design. Moreover, each time these quantities are updated due to the increased maturity of the aircraft program, lined surfaces are to be reoptimized. The updating phase thus represents important costs in terms of computational time, which could be avoided by accounting for such a variability in preliminary phases of the liner design. This is the main problematic of the present work. As this external variability directly impacts the liner environment, the computational modeling of the liner acoustic performance is uncertain. In order to quantify and account for such an uncertain nature, a robust design of the liner is carried out, by quantifying the overall uncertainty that lies within the liner design computational process. The state-of-the-art computational aeroacoustic model of nacelle liners performance is an industrial numerical code, Actran/TM, which therefore has to be extensively studied so as to exhibit the principle components that are subject to the overall uncertainty. A stochastic modeling of uncertainties is then introduced and grafted on the computational model. It allows for simulating the previously mentioned external variability, by accounting for the uncertainty that lies within the model (modeling errors and model parameters errors), through parametric and nonparametric probabilistic approaches of uncertainties. Then, the propagation of uncertainties in the system is analyzed using the computational model and the Monte Carlo stochastic solver. The acoustic response is then random and the quantification of uncertainties consists in estimating statistics, such as confidence regions associated with a certain confidence level of quantities of interest. From these statistical information, the robustness of a given liner design towards a simulated variability on its performance model can be defined, in addition to the state-of-the-art liner acoustic performance. This information then allows for knowing the propensity of a given liner design to maintain its nominal performance when its environment is changing in a predefined range of variation accounted for by the level of uncertainty imposed on the stochastic model. Then, making a compromise between performance and robustness, the best liner design can be chosen

Thesis (M.S.M.E.)--University of Massachusetts Amherst, 2009.
Open access. "This protocol is the basis of an ongoing pilot study in conjunction with Cooley Dickinson Hospital, Northampton, MA."--P. vii. Includes bibliographical references (p. 118-121).

Little is known about people's responses to the impact of a transient ischaemic attack or minor stroke on their health status and future risk of stroke. In this thesis my aims are: to explore how the experience of TIA or minor stroke affects people's perception of their health and their uptake of health maintenance measures; to examine people's assessment, interpretation and perceptions of evidence in relation to their stroke risk; to explore the ways in which people reach decisions about treatment options in the light of their personal experience and in the context of evidence-based healthcare; and to explore the effect of anticipated regret in these processes. I conducted 28 audiotaped one-to one interviews with a purposive sample of 20 participants, each of whom had previously experienced a TIA or minor stroke. Ten of them had carotid endarterectomy in addition to best medical treatment (BMT). The data collection and analysis used a reflexive approach, based on my clinical nursing practice in this field, and was informed by the constant comparative method of grounded theory. My findings show that the experience of TIA diminishes people's quality of life and leads to a process of acknowledgement versus denial of its potential threat to health. People access evidence from formal and informal sources in the process of reaching decisions about their treatment. Their decisions tend to be deterministic in nature, even when they are aware of the scientific evidence. I present a theoretical framework, in which the central theme is the person's use of strategies to reduce uncertainty relating to their risk of stroke. I propose that people's primary aim in seeking health care, accessing information, and making treatment choices after TIA or minor stroke, is to reduce their perception of uncertainty about the threat of a future stroke, rather than to reduce stroke risk itself. I discuss the implications of these findings in relation to directions for future research, health care policy and nursing practice.

This thesis investigates roadmapping in the context of its application to strategic early-stage innovation planning. It is concerned with providing an understanding of how uncertainty and risk are manifested in roadmapping in this application, and with developing and testing a roadmapping process that supports appropriate treatment of uncertainty and risk. Roadmapping is an approach to early-stage innovation planning, which is strategic in nature. It is seeing increasing application in practice and receiving growing attention in management literature. There has, however, been a noticeable lack of attention to uncertainty and risk in roadmapping theory and practice (and generally in strategic planning and at innovation’s early-stages). This is despite the awareness that uncertainty and risk are fundamental to strategy and innovation (i.e. application domains of roadmapping), and that roadmapping is meant to deliver, as part of its benefits, the identification, resolution and communication of uncertainties and risks. There is very limited theoretical or practical direction on what this entails. It is this gap that the research reported in thesis addresses. The research is divided into two phases. The first phase explains the manifestations and mechanisms of uncertainty and risk in roadmapping. It also introduces ‘risk-aware roadmapping’, a concept of roadmapping that includes a conscious and explicit effort to address uncertainty and risk, and points out what the process would entail in terms of necessary steps and procedures. The research here is designed using mixed methods (a combination of experience surveys, archival analysis, and case studies). The second phase provides a practical risk-aware roadmapping process. This practical process is developed based on the results of the first phase, and is designed according to procedural action research. This thesis contributes to the fields of roadmapping, early-stage innovation and organisational sensemaking. It is found that factors related to the content, process and nature of roadmapping interact to influence the perception and treatment of uncertainty and risk. Characteristics of organisational sensemaking as theorised by Weick (1995) are explored in the light of the findings and challenged. Aspects of early-stage innovation including the generation and selection of innovation ideas are explored in the context of uncertainty and risk and important paradoxes and constraints at innovation’s early-stages.

Thesis (Ph.D.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.
We used Monte Carlo and Probability Bounds Analysis, to examine uncertainty in removal of oocysts of Cryptosporidium and viruses in membranes used to treat drinking water. In chapter 2, we examined variability and uncertainty in the determination of parameters used in pressure-based direct integrity tests of hollow fiber micro- and ultra-filtration membranes. We found that variability and model uncertainty related to the contact angle may result in defect size resolution that is greater than 3 micrometers. This implies that the test is not always compliant with Environmental Protection Agency requirements established to detect defects large enough to allow the passage of oocysts of Cryptosporidium. Chapter 3 analyzes the decline in pathogen removal from commercial hollow fiber membranes given that fibers will break and that breakage may not be detected and therefore may accumulate. The analysis used reported fiber breakage rates and simple models to determine the flow rate of unfiltered water through broken fibers given hydraulic configurations and operating conditions. We determined that the initial decline in [oo]cyst removal from one broken fiber per membrane is large. Thereafter the decline is gradual. We found the effect of hydraulic differences between manufacturers were small, as was the effect of differences in initial removal in a new membrane. The decline in virus removal on the lower boundary is gradual. We conclude that a qualitative examination of the potential rate of decline in pathogen removal given the resolution of both direct and indirect integrity monitoring should inform policy on awarding pathogen removal. In Chapter 4, we applied Quantitative Microbial Risk Analysis (QMRA) to examine the probability of infection by Cryptosporidium given that fibers may break on a daily basis. This later examination uses an uncertainty analysis of the levels of oocysts in source water bin classifications. The probability of fiber breakage increases the probability of infection, by up to a factor of 10 in the most contaminated waters, whereas the increased risk in less contaminated waters is negligible. This is the first application of Probability Bounds Analysis in a QMRA to determine the health risk of undetected fiber breakage. These results may inform policy on the frequency and resolution of integrity monitoring.

Thesis: Nav. E., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 87-88).
In design, modeling and simulation are commonly used to answer questions of interest as it is both inefficient and expensive to physically build and evaluate numerous possibilities. Any modeling effort aims to build the simplest model while capturing the real-world trends appropriately. When modeling highly complex systems or pushing technological bounds, variables in the model will possess elements of uncertainty. In a trade space approach, different design combinations may exhibit different uncertainty profiles. Omitting uncertainties in the modeling effort can bias design combinations in the overall trade space in terms of capability and cost as well as misrepresent the value of tradeoffs between designs. Therefore, if the uncertainties are not represented, the decision-maker is accepting an unknown level of risk when selecting a design. This thesis proposes that uncertainty in early stage design is not well represented, despite its playing a major role in a system's ultimate success. This research explicitly accounts for uncertainty in model inputs via probability distributions instead of simply applying "best estimate" deterministic values. These distributions are sampled via Monte Carlo simulation to generate uncertainty profiles for different design combinations, thereby increasing the validity of the model outputs. This approach for capturing the implications of uncertainty in early stage design allows for a more accurate representation of design risk. Ultimately, the deterministic design points in the trade space are quantitatively and qualitatively evaluated against the design points incorporating uncertainty. Understanding that model outputs can only ever be as good as model inputs, the exploration of the effect of uncertainty on the design trade space is important. An example of Trade Space Exploration for the conceptual design of a manned, mini-submersible is used to demonstrate an approach for quantifying and visualizing uncertainty to inform decision-making. This case study suggests that visualizing risk at the system level in a typical performance versus cost context is valuable.
by Nicholas Andrew Dadds.
Nav. E.
S.M.

This research proposes an original framework to account for the governance of large scale infrastructure projects. The framework offers a cultural perspective by breaking away from Transaction Cost Economics to put an emphasis on context, culture, action and sensemaking. It considers the current context for large scale infrastructure projects that is the emergence of Public-Private Partnership, market coordination and complex contracts that lead to multi- organizational arrangement with multiple stakeholders. It demonstrates that governance is dynamic due to the diversity of cultures and subcultures. Governance arrangements are changing over the project life cycle to respond to project imperatives. It shows that governance must remain flexible and open to change by telling the story of the first metro line of Istanbul: Taksim 4.Levent, the Jubilee Line Extension (JLE) in London and Meteor in Paris. The originality of the research relies on the use of the Grid-Group Model introduced by the British anthropologist Mary Douglas (Douglas, 1999). It is the first time that the model is applied in the project management context. Used in combination with Action Net (Czarniawska, 2004; 2008), the Grid-Group model depicts a process, the making of Urban Rail Infrastructure Projects. It gives a perspective on complexity and the treatment of risk and uncertainty. This perspective gives relevance to the early work of Scandinavian scholars on the temporary organization (Lundin and Söderholm, 1995, Packendorff 1995) and literature that tends to see change as the norm rather than the exception (Tsoukas and Chia, 2002). The most surprising finding of the research is to enable to name the project process in Grid- Group terms, particularly Hierarchies as an ideal structural and cultural form of governance that emerge ex-post through the project process.

In this thesis we develop new mathematical models, using dynamical systems, to represent localized gene delivery of bone morphogenetic protein 2 into bone marrow-derived mesenchymal stem cells and rat calvarial defects. We examine two approaches, using pDNA or cmRNA treatments, respectively, towards the production of calcium deposition and bone regeneration in in vitro and in vivo experiments. We first review the relevant scientific literature and survey existing mathematical representations for similar treatment approaches. We then motivate and develop our new models and determine model parameters from literature, heuristic approaches, and estimation using sparse data. We next conduct a qualitative analysis using dynamical systems theory. Due to the nature of the parameter estimation, it was important that we obtain local and global sensitivity analyses of model outputs to changes in model inputs. Finally we compared results from different treatment protocols. Our model suggests that cmRNA treatments may perform better than pDNA treatments towards bone fracture healing. This work is intended to be a foundation for predictive models of non-viral local gene delivery systems.

This thesis is about cultural aspects of advanced medical technology for treating end-stage heart failure. New medical technologies like mechanical help-hearts save lives, but they also bring new uncertainties, risks, and challenges. Based on nine months of ethnographic field work in a Swedish academic hospital, this study examines the ways of managing uncertainties of end-stage heart failure and of high-tech treatment, and also how these practices tie into the shared understandings of life-threatening chronic illness, the body, and medical technology’s role. This study draws on anthropological discussions of healing rituals as an analytical tool to make sense of social and cultural dimensions of mechanical help-heart implantation treatment. Viewed as a ritual, this treatment creates and maintains hope as a virtue through which possibilities of new medical technology are justified as culturally approved ways of handling the uncertainties of severe heart failure and mechanical help-heart treatment. Ultimately, even when treatment is regarded as successful, the patients may be saved but are never really ‘cured’ and remain, thus, permanently tied to the world of medicine. This new mode of existence is characterized by paradoxical permanent transit between uncertainty and hope.
Avhandlingen fokuserar på de kulturella aspekterna av den medicinska teknologin som används vid behandling av svår hjärtsvikt. Samtidigt som ny medicinsk teknologi som mekaniska hjälphjärtan räddar liv för den även med sig ovisshet och nya utmaningar som ofta är svåra att förutse. Baserat på nio månaders etnografiskt fältarbete vid ett universitetssjukhus i Sverige undersöks hur denna ovisshet och dessa utmaningar hanteras av medicinskt personal och patienter. I avhandlingen behandlas också sambanden mellan medicinska praktiker och de lokalt delade uppfattningarna om livshotande kroniska sjukdomar, den mänskliga kroppen och teknologins roll. Utifrån diskussioner inom antropologin om ’helande ritualer’ analyseras i avhandlingen de sociala och kulturella aspekterna av behandling med mekaniskt hjälphjärta. Studien visar att genom de rituella aspekterna av denna behandling, genereras och upprätthålls hoppet som en dygd. Den nya medicinska teknologins möjligheter rättfärdigas på så sätt som ett kulturellt accepterat sätt att hantera ovissheten vid svår hjärtsvikt och behandling med mekaniskt hjälphjärta. Även vid lyckade behandlingar, då patienternas liv räddas, blir de trots allt inte riktigt ’botade’ utan förblir bundna till den medicinska världen. Detta nya levnadssätt karakteriseras av en paradoxal och livslång balansgång mellan ovisshet och hopp.

With sustainable development as the new overarching goal, urban wastewater system (UWS) managers are now being asked to take all social, economic, technical and environmental facets related to their decisions into account. In this complex decision-making environment, uncertainty can be formidable. Uncertainty is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behaviour. This inherent uncertainty leads to the conclusion that better decisions will be made if the decision-making process is adaptive and iterative. UWS decision-support frameworks exist in the literature, but none of them effectively addresses all these needs. Hence, there is a need for an adaptive framework that supports UWS management by addressing aspects of sustainability and uncertainty of various types. The development of such a framework is the main outcome of this work, and is supported by two demonstrative applications presented in this thesis.
En el marc de desenvolupament sostenible, els gestors dels sistemes de sanejament han d’incloure factors socials, econòmics, tècnics i ambientals durant la presa de decisions. Donada l’elevada complexitat en la presa de decisions, la incertesa relacionada amb aquests factors pot esdevenir rellevant i per tant s’ha d’incorporar de forma adequada. La incertesa està present no només en la forma d’interpretar el sistema sinó també en el seu comportament natural i canviant. Necessitem processos de decisió que siguin adaptatiu i iteratiu per tal d’assegurar que el sistemes de sanejament mantenen la seva eficàcia durant la seva vida útil. Tot i que existeixen en la bibliografia alguns marcs d’ajuda a la presa de decisions cap d’ells inclou de forma efectiva tots aquests aspectes. Per tant, necessitem disposar d’un marc que ajudi en la gestió dels sistemes de sanejament sota el paradigma de gestió adaptativa al mateix temps que consideri aspectes de sostenibilitat i incertesa de diferent origen. Aquest és l’objectiu principal d’aquest treball, conjuntament amb dos aplicacions de demostració.

Generalised Anxiety Disorder (GAD) is a highly prevalent, chronic and costly mental disorder in children, that is characterised by excessive and uncontrollable worry about numerous topics, that occurs more days than not for a period of at least six months (APA, 2013). Our knowledge and understanding of worry and GAD in children remains a neglected area of empirical enquiry. Given the dearth of research conducted with children in this area, much of what is currently known about childhood GAD is derived from empirical studies conducted with adults. Within the adult literature, research has demonstrated that cognitive factors such as intolerance of uncertainty (IU), positive and negative beliefs about worry (PBW and NBW), negative problem orientation (NPO) and cognitive avoidance (CA) are particularly important in the development and maintenance of pathological worry and GAD, and these variables therefore constitute the basis of treatment for adult GAD. Treatment programs for child GAD, unlike those for adults, are almost uniformly transdiagnostic in nature and do not specifically target the cognitive variables demonstrated to be involved in the aetiology and maintenance of the disorder. This thesis investigated the cognitive variables of IU, NBW, PBW, NPO, and CA with respect to worry and GAD in children through a series of four studies, which have all been submitted for publication. The first study examined the cognitive variables of IU, NBW, PBW, NPO, and CA in a community sample of 114 children, aged 8 to 12 years. It was found that all child cognitive variables were significantly and positively related to child worry, and that parent worry, IU and CA were significantly and positively related to child worry. It was also found that the relationship between parent IU, NPO and CA and child worry was mediated by child IU, NPO and CA respectively.
Thesis (PhD Doctorate)
Doctor of Philosophy in Clinical Psychology (PhD ClinPsych)
School of Applied Psychology
Griffith Health
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La implementació de la Directiva Europea 91/271/CEE referent a tractament d'aigües residuals urbanes va promoure la construcció de noves instal·lacions al mateix temps que la introducció de noves tecnologies per tractar nutrients en àrees designades com a sensibles. Tant el disseny d'aquestes noves infraestructures com el redisseny de les ja existents es va portar a terme a partir d'aproximacions basades fonamentalment en objectius econòmics degut a la necessitat d'acabar les obres en un període de temps relativament curt. Aquests estudis estaven basats en coneixement heurístic o correlacions numèriques provinents de models determinístics simplificats. Així doncs, moltes de les estacions depuradores d'aigües residuals (EDARs) resultants van estar caracteritzades per una manca de robustesa i flexibilitat, poca controlabilitat, amb freqüents problemes microbiològics de separació de sòlids en el decantador secundari, elevats costos d'operació i eliminació parcial de nutrients allunyant-les de l'òptim de funcionament. Molts d'aquestes problemes van sorgir degut a un disseny inadequat, de manera que la comunitat científica es va adonar de la importància de les etapes inicials de disseny conceptual. Precisament per aquesta raó, els mètodes tradicionals de disseny han d'evolucionar cap a sistemes d'avaluació mes complexos, que tinguin en compte múltiples objectius, assegurant així un millor funcionament de la planta. Tot i la importància del disseny conceptual tenint en compte múltiples objectius, encara hi ha un buit important en la literatura científica tractant aquest camp d'investigació. L'objectiu que persegueix aquesta tesi és el de desenvolupar un mètode de disseny conceptual d'EDARs considerant múltiples objectius, de manera que serveixi d'eina de suport a la presa de decisions al seleccionar la millor alternativa entre diferents opcions de disseny. Aquest treball de recerca contribueix amb un mètode de disseny modular i evolutiu que combina diferent tècniques com: el procés de decisió jeràrquic, anàlisi multicriteri, optimació preliminar multiobjectiu basada en anàlisi de sensibilitat, tècniques d'extracció de coneixement i mineria de dades, anàlisi multivariant i anàlisi d'incertesa a partir de simulacions de Monte Carlo. Això s'ha aconseguit subdividint el mètode de disseny desenvolupat en aquesta tesis en quatre blocs principals: (1) generació jeràrquica i anàlisi multicriteri d'alternatives, (2) anàlisi de decisions crítiques, (3) anàlisi multivariant i (4) anàlisi d'incertesa. El primer dels blocs combina un procés de decisió jeràrquic amb anàlisi multicriteri. El procés de decisió jeràrquic subdivideix el disseny conceptual en una sèrie de qüestions mes fàcilment analitzables i avaluables mentre que l'anàlisi multicriteri permet la consideració de diferent objectius al mateix temps. D'aquesta manera es redueix el nombre d'alternatives a avaluar i fa que el futur disseny i operació de la planta estigui influenciat per aspectes ambientals, econòmics, tècnics i legals. Finalment aquest bloc inclou una anàlisi de sensibilitat dels pesos que proporciona informació de com varien les diferents alternatives al mateix temps que canvia la importància relativa del objectius de disseny.
El segon bloc engloba tècniques d'anàlisi de sensibilitat, optimització preliminar multiobjectiu i extracció de coneixement per donar suport al disseny conceptual d'EDAR, seleccionant la millor alternativa un cop s'han identificat decisions crítiques. Les decisions crítiques són aquelles en les que s'ha de seleccionar entre alternatives que compleixen de forma similar els objectius de disseny però amb diferents implicacions pel que respecte a la futura estructura i operació de la planta. Aquest tipus d'anàlisi proporciona una visió més àmplia de l'espai de disseny i permet identificar direccions desitjables (o indesitjables) cap on el procés de disseny pot derivar. El tercer bloc de la tesi proporciona l'anàlisi multivariant de les matrius multicriteri obtingudes durant l'avaluació de les alternatives de disseny. Específicament, les tècniques utilitzades en aquest treball de recerca engloben: 1) anàlisi de conglomerats, 2) anàlisi de components principals/anàlisi factorial i 3) anàlisi discriminant. Com a resultat és possible un millor accés a les dades per realitzar la selecció de les alternatives, proporcionant més informació per a una avaluació mes efectiva, i finalment incrementant el coneixement del procés d'avaluació de les alternatives de disseny generades. En el quart i últim bloc desenvolupat en aquesta tesi, les diferents alternatives de disseny són avaluades amb incertesa. L'objectiu d'aquest bloc és el d'estudiar el canvi en la presa de decisions quan una alternativa és avaluada incloent o no incertesa en els paràmetres dels models que descriuen el seu comportament. La incertesa en el paràmetres del model s'introdueix a partir de funcions de probabilitat. Desprès es porten a terme simulacions Monte Carlo, on d'aquestes distribucions se n'extrauen números aleatoris que es subsisteixen pels paràmetres del model i permeten estudiar com la incertesa es propaga a través del model. Així és possible analitzar la variació en l'acompliment global dels objectius de disseny per a cada una de les alternatives, quines són les contribucions en aquesta variació que hi tenen els aspectes ambientals, legals, econòmics i tècnics, i finalment el canvi en la selecció d'alternatives quan hi ha una variació de la importància relativa dels objectius de disseny. En comparació amb les aproximacions tradicionals de disseny, el mètode desenvolupat en aquesta tesi adreça problemes de disseny/redisseny tenint en compte múltiples objectius i múltiples criteris. Al mateix temps, el procés de presa de decisions mostra de forma objectiva, transparent i sistemàtica el perquè una alternativa és seleccionada en front de les altres, proporcionant l'opció que més bé acompleix els objectius marcats, mostrant els punts forts i febles, les principals correlacions entre objectius i alternatives, i finalment tenint en compte la possible incertesa inherent en els paràmetres del model que es fan servir durant les anàlisis. Les possibilitats del mètode desenvolupat es demostren en aquesta tesi a partir de diferents casos d'estudi: selecció del tipus d'eliminació biològica de nitrogen (cas d'estudi # 1), optimització d'una estratègia de control (cas d'estudi # 2), redisseny d'una planta per aconseguir eliminació simultània de carboni, nitrogen i fòsfor (cas d'estudi # 3) i finalment anàlisi d'estratègies control a nivell de planta (casos d'estudi # 4 i # 5).
The implementation of EU Directive 91/271/EEC concerning urban wastewater treatment promoted the construction of new facilities and the introduction of nutrient removal technologies in areas designated as sensitive. The need to build at a rapid pace imposed economically sound approaches for the design of the new infrastructures and the retrofit of the existing ones. These studies relied exclusively on the use of heuristic knowledge and numerical correlations generated from simplified activated sludge models. Hence, some of the resulting wastewater treatment plants (WWTPs) were characterized by a lack of robustness and flexibility, bad controller performance, frequent microbiology-related solids separation problems in the secondary settler, high operating and maintenance costs and/or partial nutrient removal, which made their performance far from optimal. Most of these problems arose because of inadequate design, making the scientific community aware of the crucial importance of the conceptual design stage. Thus, these traditional design approaches should turn into more complex assessment methods in order to conduct integrated assessments taking into account a multiplicity of objectives an hence ensuring a correct plant performance. Despite the importance of this fact only a few methods in the literature addressed the systematic evaluation of conceptual WWTP design alternatives using multiple objectives. Yet, the decisions made during this stage are of paramount importance in determining the future plant structure and operation. The main objective pursued in this thesis targets the development of a systematic conceptual design method for WWTP using multiple objectives, which supports decision making when selecting the most desirable option amongst several generated alternatives. This research work contributes with a modular and evolutionary approach combining techniques from different disciplines such as: a hierarchical decision approach, multicriteria decision analysis, preliminary multiobjective optimization using sensitivity functions, knowledge extraction and data mining techniques, multivariate statistical techniques and uncertainty analysis using Monte Carlo simulations. This is accomplished by dividing the design method into 4 different blocks: (1) hierarchical generation and multicriteria evaluation of the design alternatives, (2) analysis of critical decisions, (3) multivariate analysis and, finally, (4) uncertainty analysis. The first block of the proposed method, supports the conceptual design of WWTP combining a hierarchical decision approach with multicriteria analysis. The hierarchical decision approach breaks down the conceptual design into a number of issues that are easier to analyze and to evaluate while the multicriteria analysis allows the inclusion of different objectives at the same time. Hence, the number of alternatives to evaluate is reduced while the future WWTP design and operation is greatly influenced by environmental, technical, economical and legal aspects. Also, the inclusion of a sensitivity analysis facilitates the study of the variation of the generated alternatives with respect to the relative importance of the objectives. The second block, analysis of critical decisions, is tackled with sensitivity analysis, preliminary multiobjective optimization and knowledge extraction to assist the designer during the selection of the best alternative amongst the most promising alternatives i.e. options with a similar overall degree of satisfaction of the design objectives but with completely different implications for the future plant design and operation. The analysis provides a wider picture of the possible design space and allows the identification of desirable (or undesirable) WWTP design directions in advance.
The third block of the proposed method, involves the application of multivariate statistical techniques to mine the complex multicriteria matrixes obtained during the evaluation of WWTP alternatives. Specifically, the techniques used in this research work are i) cluster analysis, ii) principal component/factor analysis, and iii) discriminant analysis. As a result, there is a significant improvement in the accessibility of the information needed for effective evaluation of WWTP alternatives, yielding more knowledge than the current evaluation methods to finally enhance the comprehension of the whole evaluation process. In the fourth and last block, uncertainty analysis of the different alternatives is further applied. The objective of this tool is to support the decision making when uncertainty on the model parameters used to carry out the analysis of the WWTP alternatives is either included or not. The uncertainty in the model parameters is introduced, i.e input uncertainty, characterising it by probability distributions. Next, Monte Carlo simulations are run to see how those input uncertainties are propagated through the model and affect the different outcomes. Thus, it is possible to study the variation of the overall degree of satisfaction of the design objectives, the contributions of the different objectives in the overall variance to finally analyze the influence of the relative importance of the design objectives during the selection of the alternatives. Thus, in comparison with the traditional approaches the conceptual design method developed in this thesis addresses design/redesign problems with respect to multiple objectives and multiple performance measures. Also, it includes a more reliable decision procedure that shows in a systematic, objective and transparent fashion the rationale way a certain alternative is selected and not the others. The decision procedure provides to the designer/decision maker with the alternative that best fulfils the defined objectives, showing its main advantages and weaknesses, the different correlations between the alternatives and evaluation criteria and dealing with the uncertainty prevailing in some of the model parameters used during the analysis. A number of case studies, selection of biological nitrogen removal process (case study #1), optimization of the setpoints in two control loops (case study #2), redesign to achieve simultaneous organic carbon, nitrogen and phosphorus removal (case study #3) and evaluation of control strategies at plant wide level (case studies #4 and #5), are used to demonstrate the capabilities of the conceptual design method.

Investigating how lending programs of the International Monetary Fund (IMF) affect poverty and inequality, we explicitly address model uncertainty. We control for endogenous selection into IMF programs using data on 86 low- and middle income countries for the 1982-2009 period and analyze program effects on various poverty and inequality measures. The results rely on averaging over 90 specifications of treatment effect models and indicate adverse short-run effects of IMF agreements on poverty and inequality for the whole sample, while for a 2000-2009 subsample the results are reversed. There is evidence that significant short-run effects might disappear in the long-run. (author's abstract)

La dernière décennie a vu l'émergence de la prévision probabiliste de débits en tant qu'approche plus adaptée pour l'anticipation des risques et la mise en vigilance pour lasécurité des personnes et des biens. Cependant, au delà du gain en sécurité, la valeur ajoutée de l'information probabiliste se traduit également en gains économiques ou en une gestion optimale de la ressource en eau disponible pour les activités économiques qui en dépendent. Dans la chaîne de prévision de débits, l'incertitude des modèles météorologiques de prévision de pluies joue un rôle important. Pour pouvoir aller au-delà des limites de prévisibilité classiques, les services météorologiques font appel aux systèmes de prévision d'ensemble,générés sur la base de variations imposées dans les conditions initiales des modèlesnumériques et de variations stochastiques de leur paramétrisation. Des scénarioséquiprobables de l'évolution de l'atmosphère pour des horizons de prévision pouvant aller jusqu'à 10-15 jours sont ainsi proposés. L'intégration des prévisions météorologiques d'ensemble dans la chaîne de prévision hydrologique se présente comme une approche séduisante pour produire des prévisions probabilistes de débits et quantifier l'incertitude prédictive totale en hydrologie
The last decade has seen the emergence of streamflow probabilistic forecasting as the most suitable approach to anticipate risks and provide warnings for public safety and property protection. However, beyond the gains in security, the added‐value of probabilistic information also translates into economic benefits or an optimal management of water resources for economic activities that depend on it.In streamflow forecasting, the uncertainty associated with rainfall predictions from numerical weather prediction models plays an important role. To go beyond the limits of classical predictability, meteorological services developed ensemble prediction systems, which are generated on the basis of perturbations of the initial conditions of the models and stochastic variations in their parameterization. Equally probable scenarios of the evolution of the atmosphere are proposed for forecasting horizons up to 10‐15 days.The integration of weather ensemble predictions in the hydrological forecasting chain is an interesting approach to produce probabilistic streamflow forecasts and quantify the total predictive uncertainty in hydrology. Last and final summary in the thesis

Investigating how lending programs of the International Monetary Fund (IMF) affect poverty and inequality, we explicitly address model uncertainty. We control for endogenous selection into IMF programs using data on 86 low- and middle income countries for the 1982-2009 period and analyze program effects on various poverty and inequality measures. The results rely on averaging over 90 specifications of treatment effect models and indicate adverse short-run effects of IMF agreements on poverty and inequality for the whole sample, while for a 2000-2009 subsample the results are reversed. There is evidence that significant short-run effects might disappear in the long-run. (author's abstract)
Series: Department of Economics Working Paper Series

It is generally accepted that innovation is a source of competitiveness for companies and nations. The impact of innovation activities on business performance ranges from the effect on sales and market share to the improvement of productivity and operational efficiency. At a national level, the main effects of innovative activities are characterized by the raise of the sectorial competition, this increases the yield of the productive industry, along to the systematical permeation of know-how to the linked business networks. The first definition of the concept of innovation was established by Schumpeter (1934), indicating that innovation is what we call in a non-scientific way, economic progress. The UK Department of Trade and Industry (DTI, 1998) mentions that innovation is the successful exploitation of new ideas. The Oslo Manual (OECD, 2006) indicates that an innovation is the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations. It is noteworthy that the concept of innovation involves elements such as economic progress, business success, successful exploitation, etc. But, how does this happens exactly? Identifying the implications of innovative activities in business performance is highly relevant, as it opens a path for assisting a key issue in innovation research: systematically determine which resources, from those intended to manage continuous change within companies are justified, moreover, categorize which of them have had a major impact on the organization’s goals and objectives. The formula to address the previous question is somehow logical and has been widely studied by several authors. It consists on collecting information of the determinants of success or failure of companies in specialized studies on innovation management, then generating a list with the most relevant and frequent characteristics and elements, finally applying a scoring system to the selected best practices (Tidd and Bessant, 2013). However, that method faces complex challenges in the innovation environment: the heterogeneous terminology, dissimilar views and definitions of the concept, among other elements obstruct a standard measurement framework. Thus a correct evaluation, quantification and comparison of the innovative competencies of the organizations is highly challenging, since there is no single or main tendency to evaluate the measure of innovation. It is conventionally accepted that innovation is a concept demarcated by uncertainty. Thus, one of the most recurring problems is to treat innovation information with traditional methodologies, "the uncertainty that the innovation process entails is manifested by the fact that only one third of the new products introduced in the market end up being successful, a proportion that seems not to have been overcome in the last decades" (Velasco et al., 2008). Despite innovation is, by its nature, governed by random processes, in the business reality innovation must be the result of a deliberate process, guided by human intuition, intelligence and foresight (Cotec, 1999). It is therefore necessary to understand and manage the innovation process, so that there is little room for chance (Tidd; Bessant and Pavitt, 2005). Motivated on shedding light to the scientific gap found in the literature, we present our proposal, which is mainly focused in the application of methodologies and techniques for the treatment of information under uncertainty towards innovation management measurement and its interlaced complex decision-making process.
Es generalmente aceptado que la innovación es una fuente de competitividad para las empresas y para las naciones. El impacto de las actividades de innovación sobre los resultados de las empresas va desde el efecto sobre las ventas y la cuota del mercado hasta la mejora de la productividad y la eficiencia operacional. Los principales beneficios a nivel de nación se distinguen por el incremento de la competencia sectorial, lo cual eleva el rendimiento total de los factores productivos, así como el derrame del nuevo saber-hacer, que permea de forma sistémica las redes empresariales. Es notorio que alrededor del concepto de innovación se encuentran elementos tales como progreso económico, éxito empresarial, solución de problemas, etc. Por lo tanto, identificar las implicaciones que las actividades innovadoras suponen al rendimiento de las empresas es relevante, ya que abre camino para asistir un aspecto clave entorno a la innovación: determinar de forma sistemática qué recursos, de aquellos destinados a gestionar el cambio continuo dentro de las empresas es justificable, y más aún, cuáles de ellos han impactado mayormente a los objetivos y metas de la organización. La fórmula para conocer éste aspecto clave resulta de cierta forma lógica y previamente estudiado por varios autores. Consiste en recopilar información del éxito o fracaso empresarial documentado en estudios especializados en factores determinantes de innovación, a continuación, generar una lista con las características y elementos más relevantes y frecuentes, finalmente aplicar un sistema de puntuación con las mejores prácticas encontradas, sin embargo, tal método se enfrenta a retos complejos como lo es la heterogénea terminología, disimiles puntos de vista alrededor de la innovación y desemejantes definiciones del concepto. Así pues, una correcta evaluación, cuantificación y comparación de las competencias innovadoras de las organizaciones es complejo ya que no existe una tendencia única o principal para evaluar la medida la innovación. Motivados por acortar la brecha científica encontrada en la literatura, presentamos nuestra propuesta, que se centra en la aplicación de técnicas para el tratamiento de la información en la incertidumbre destinadas a apoyar la toma de decisiones hacia la gestión de la innovación y el cambio continuo en la empresa.

L'étalonnage de l’image tomodensitométrique X en pouvoirs d’arrêt relatif est source d'incertitudes pour la planification du traitement en protontherapie. L’imagerie proton permettrait d’obtenir directement les pouvoirs d’arrêt ou les épaisseurs équivalent-eau tout en maîtrisant les incertitudes sur la planification du traitement. Ce travail vise à caractériser et optimiser les performances du système de tomographie proton proposé dans le cadre d’une nouvelle approche faisceau à faisceau, composé d’un trajectographe et d’un range meter. La position et la largeur du faisceau obtenues avec le trajectographe ainsi que la modélisation matricielle de la réponse du range meter par simulation Monte Carlo combinée à la déconvolution de la courbe de Bragg résiduelle ont permis de reconstruire l’épaisseur équivalent-eau traversée pour chaque faisceau. L’évaluation de la qualité des images a permis de montrer que la méthode de déconvolution permettait d’obtenir des images dépourvues d’artefacts et d’estimer le parcours du proton avec une précision de l’ordre de 0,7%. Le travail présenté dans cette thèse démontre la faisabilité d’un tel système d’imagerie
Calibration of computed tomography image in relative stopping power is a source of uncertainties for the proton therapy treatment planning. Proton imaging could directly obtain stopping powers or equivalent water thicknesses and control uncertainties in the treatment planning. In the context of a new pencil beam approach, this work aims to characterize and optimize the performances of a proton tomography system consisting of a tracker and a range meter. Beam position and width obtained with the tracker and the range meter response matrix modelling by Monte Carlo simulation combined with the unfolding method of the residual Bragg curve enable to reconstruct the water equivalent thickness for each beam. The evaluation of the reconstructed images quality shows that images are artefact free and the proton range is estimated with 0.7% of accurancy by using the unfolding method. This thesis demonstrates the feasibility of such an imaging system

Alors que le contentieux des produits de santé n'a jamais été aussi fourni, l'application du régime spécial de responsabilité du fait des produits défectueux issu de la directive européenne du 25 juillet 1985, entraîne l'émergence d'un certain nombre d'incertitudes qui affectent directement le sort des demandes en réparation. Les incertitudes matérielles ont, pour la plupart reçu un traitement efficace par l'action conjuguée de la jurisprudence et du législateur. Si les outils juridiques traditionnels, tels que les présomptions ou la causalité alternative, ont permis de résoudre une partie non négligeable de ces incertitudes, les juges se sont également attachés à développer des outils nouveaux comme la balance bénéfice/risque ou encore la répartition de l'obligation à la dette selon les parts de marché. Cependant, si le développement de ces outils juridiques, plus adaptés aux spécificités des produits de santé, a permis d'apporter une solution efficace aux incertitudes matérielles, le traitement de l'incertitude scientifique, fondé sur les présomptions du fait de l'homme, n'apporte, toujours pas, de solutions satisfaisantes. L'étude du traitement des incertitudes dans le contentieux des produits de santé défectueux permet d'apprécier les acquis mais également les limites atteintes par l'utilisation de certains outils mis à la disposition des juges et qui se révèlent parfois inadaptés. L'intervention du législateur et la prise en compte des spécificités des produits de santé, permettraient de développer un système d'indemnisation adapté qui interviendrait de façon subsidiaire en cas d'échec de la voie contentieuse
At a time when healthcare-product litigation is attaining record heights, the implementation into French law of the special liability regime for defective products, which derives from the European Council Directive of 25 July 1985, has led to the emergence of several grey areas of uncertainty which have a direct impact on the outcome of claims for compensation. Areas of material uncertainty have, for the most part, been effectively dealt with through the combined application of case law and the intervention of the legislator. While classic legal tools such as presumption and alternative causality provide a means to resolve a non-negligible part of these uncertainties, judges have also endeavoured to develop new tools, such as risk/utility test and market-share liability. Still, although the development of these legal tools - better suited as they are to the specific features of healthcare products - provide an effective solution to resolving areas of material uncertainty, the treatment of scientific uncertainty, which is based on presumptions of fact, does not always provide satisfactory solutions. The study of the legal treatment of uncertainty in healthcare-product litigation provides a means to assess the benefits but also the limitations of certain tools that are now available to judges but which at times prove inadequate. Intervention on the part of the legislator, while at the same time taking into account the specific features of healthcare products, could lead to the development of a suitable compensation system that could afford relief when litigation fails

O estudo de características de isospin na excitação do estado 2 POT.+IND.1 foi implementado nos núcleos ANTPOT.70, 72, 74 Ge com a realização de medidas de espalhamento inelástico na região de interferência nuclear coulombiana (INC) com ANTPOT.6 Li de 28 MeV. A análise da INC, utilizando projéteis leves de interação isoescalar, na excitação de estados coletivos é uma ferramenta poderosa para evidenciar mudanças de estrutura em cadeias de núcleos, e fornecer resultados robustos para testes de modelos. A principal vantagem do método é a extração simultânea dos parâmetros de deformação de carga e massa das transições, minimizando as incertezas na razão entre as probabilidades reduzidas de transição elétrica e de massa, B(El) e B(ISl), indicadores importantes da coletividade dos estados nucleares. A análise foi realizada na aproximação de Born com ondas distorcidas e potencial óptico deformado (DWBA-DOMP), usando um conjunto de parâmetros de potencial óptico global. Os ajustes das previsões à distribuições angulares, empregando o método interativo de Gauss, exibiram excelente qualidade. Os parâmetros correlacionados extraídos na minimização do chi-quadrado, delta IND.n(comprimento de deformação nuclear) e C=delta IND.c/delta IND.n (razão entre os comprimentos de deformação de carga e nuclear), e suas incertezas, foram submetidos a testes estatísticos que os validaram. Dentre as grandezas determinadas a partir desses parâmetros, os valores de B(IS2), inéditos nos isótopos de Ge, mostraram uma mudança de estrutura não evidenciada pelos valores de B(E2). A probabilidade reduzida de transição isoescalar cresceu com o incremento do número de nêutrons, com um aumento abrupto no ANTPOT.74 Ge. Já a probabilidade reduzida de transição elétrica aumentou de maneira mais suave. Essa diferença de comportamento foi um reflexo da variação do parâmetro extraído C, que no ANTPOT.74 Ge indicou uma ) contribuição maior dos nêutrons frente aos prótons na excitação do primeiro estado quadrupolar. Os isótopos ANTPOT.70, 72 Ge, por outro lado, revelaram contribuições equivalentes e homogêneas para essas transições. Com a determinação precisa das contribuições de massa e de carga para a excitação do primeiro estado quadrupolar, novos subsídios estão disponíveis para futuros cálculos.
The analysis of the isospin character of the 2 POT.+ IND.1 excitation in the ANTPOT.70,72,74 Ge nuclei, with 28 MeV ANTPOT.6 Li, was applied to the inelastic scattering in the coulomb nuclear interference (CNI) region. The CNI measurements in the exitation of collective states with light isoscalar projectiles are powerful tools to evidence structure changes in nuclei chains, allowing tests of nuclear models. In this method the simultaneous extraction of the charge and mass deformation parameters, minimizes the uncertainties in the ratio of charge B(El) to mass B(ISl) trasition reduced probabilities, wich are important indicators of the nuclear collectivity. The present analysis was developed in the framework of the distorted wave Born approximation within a deformed optical potential approach (DWBA-DOMP), using a set of global optical model parameters. Excellent quality fits of the predictions to the experimental angular distributions, employing the Gauss iterative method, were obtained. The correlated parameters delta IND.N (nuclear deformation length) and C = delta IND.C/delta IND.N (ratio of charge to nuclear deformation lenghts), and their uncertainties extracted in the least squares method, were validated by statistical tests. The B(IS2) values for germanium isotopes, not previously reported, were determined in the analysis and revealed a structure change not evidenced by the B(E2) values. The isoscalar transition reduced probability raises when the neutron number increases, showing in the ANTPOT.74 Ge an abrupt enhancement. Nevertheless, the eletric transition reduced probability grows smoothly. This behavior was detected following the experimental extracted C parameters, indicating in the heavier isotope a predominance of neutrons in the first quadrupolar excitation. The ANTPOT.70,72 Ge isotopes, on the other hand, displayed equivalent and homogeneous contributions of protoons and neutrons. New information on mass and charge contributions for the 0 POT.+ IND.1 -> 2 POT.+ IND.1 transition, in the germanium isotopes, is now available for future theoretical interpretation.

Pharmaceuticals are ubiquitous water contaminants that have shown detrimental effects on aquatic organisms at low concentrations. National authorities are starting to plan and implement measures (Wastewater treatment plants (WWTP) upgrades and source control) to reduce pharmaceutical concentrations in rivers. Decision-makers use models to predict the fate and transport of pharmaceuticals and to evaluate measures for the reduction of pharmaceuticals. However, there is still large uncertainty in the predictions which compromises decision-making. The cost of implementing WWTP upgrades at catchment level can be daunting, hence the development of tools that optimize the costs are indeed required. Moreover, there is little scientific information on the effectiveness of source control measures for the reduction of pharmaceutical concentrations at catchment scale. The aim of this thesis is to provide decision-makers with modelling tools for the evaluation of measures to reduce pharmaceutical concentrations in rivers. The modelling tools include uncertainty in the whole decision-making process
Els fàrmacs són substàncies contaminants de l'aigua que han mostrat efectes perjudicials en organismes aquàtics a concentracions baixes. Alguns països estan començant a planificar i implementar mesures (millores en les EDARs i control de les fonts de la contaminació) per reduir les concentracions de fàrmacs en rius. Els responsables en la presa de decisions utilitzen models per a estimar concentracions de fàrmacs i per a avaluar mesures orientades a reduir aquestes concentracions. Malgrat això, encara existeix molta incertesa en les predictions, la qual cosa compromet la presa de decisions. A més, es requereix desenvolupar eines per optimitzar els costos que se'n deriven. Existeix poca informació científica sobre l'efectivitat de les mesures de control de les fonts per a la reducció de concentracions de fàrmacs en rius. L'objectiu d'aquesta tesi és proporcionar eines de modelització als responsables en la presa de decisions per avaluar mesures incloent incerteses en tot el procés de presa de decisions

Drinking water treatment plants (DWTPs) face significant challenges due to anthropocentric pressure and climate change. To address them, DWTP managers need to adjust treatment units. In the present work, a decision support system (EDSS) has been developed to respond to the main operational challenges of two real case studies: Llobregat and Ter DWTPs. Specifically, data-driven and knowledge-based models have been developed to address the control of the pre-oxidation process, the formation of disinfection by-products (DBPs) and to monitor the microbiological safety of the water produced. The various tools resulting from this thesis have been integrated into a decision support system and have been validated at full-scale DWTPs
Les estacions de tractament d’aigua potable (ETAPs) han de fer front a reptes significatius deguts a la pressió antropocèntrica i al canvi climàtic. Per a abordar-los, els gestors de les ETAPs han d’ajustar les unitats de tractament. En el present trebal, s’ha desenvolupat un sistema d’ajut a la decisió (EDSS) per respondre als reptes operacionals principals de dos casos d’estudi reals: les ETAPs del Llobregat i del Ter. Concretament, s’han desenvolupats models basats en el coneixement expert i les dades de procés per fer front al control del procés de pre-oxidació, la formació de subproductes de la desinfecció (DBPs) i per supervisar la seguretat microbiològica de l’aigua produïda. Les diferents eines resultants d’aquesta tesi s’han integrat en un sistema d’ajut a la decisió i han estat validades a escala industrial

Les cancers de l'ovaire et du sein sont définis par les principales voies impliquées dans la tumorigénèse. Dans les cancers héréditaires du sein/ovaire (HBOC), les tumeurs présentant des variants pathogènes (PV) de BRCA1/2 présentent une altération de la réparation de l'ADN par recombinaison homologue (RH). Des années après la découverte des gènes BRCA1/2, les PV ont été uniquement recherchés sur l'ADN constitutionnel. Aujourd’hui, cette information est également recherchée au niveau tumoral car en plus de leur utilité pour améliorer le conseil génétique, elle est aussi impliquée dans le choix thérapeutique. Cependant, les données recueillies indiquent que les PV inactivant la protéine ne seraient pas l’unique mécanisme d’inactivation de la voie de réparation de l’ADN par RH. Dans ce contexte, l'objectif principal de cette thèse est d'identifier des mécanismes alternatifs d'inactivation de la voie HR pour améliorer à la fois: le conseil génétique et la prise en charge thérapeutique. À cette fin, nous avons tenté de contribuer à la classification de variants non-codants et faux-sens (autre que provoquant un stop prématuré) de BRCA1/2 et également recherché de nouveaux biomarqueurs de réponse thérapeutique dans d’autres gènes de la voie de HR.Nous avons décrit des variants constitutionnels dans des régions potentiellement importantes de régulation des gènes BRCA1 et BRCA2, et démontré qu'une partie d'entre eux étaient fonctionnellement actifs à mettre en lien avec la pathogénicité. Nous avons également exploré les caractéristiques moléculaires des tumeurs du sein et de l'ovaire des porteurs des variants BRCA1 et observé une prédominance de la perte de l'allèle sauvage pour les tumeurs des porteurs de variants pathogènes. Etant donné ces résultats, nous proposons d’intégrer les informations de LOH dans le modèle multifactoriel de classification des variants BRCA1. Enfin, nous avons mis en évidence des mécanismes alternatifs d'inactivation de la voie RH, dans une cohorte de patientes avec un cancer de l'ovaire présentant une excellente réponse aux platines, y compris des mutations constitutionnelles et somatiques des gènes BRCA1/2, l'hyperméthylation du promoteur BRCA1 ainsi que des mutations dans d'autres gènes de la voie RH
Ovarian and breast cancers are currently defined by the main pathways involved in the tumorigenesis. In hereditary breast/ovarian cancers (HBOC), tumors with BRCA1/2 pathogenic variants (PV) present an impairment of DNA repair by homologous recombination (HR). For many years, BRCA1/2 PV were only searched on germline DNA. Currently, this information is also searched at tumor level to personalize treatment. Even so, the reason of the inactivation of this pathway remains uncertain for most cases, even in the presence of HR deficient signature.Gathered evidence indicates that protein inactivating PV may not be the only mechanism of HR dysfunction. In this context, the main objective of this thesis is to identify alternative mechanisms of HR inactivation to improve both: genetic counseling and therapeutic response. For this purpose, we have attempted to contribute to non-coding and missense (other than premature stop codon) BRCA1/2 variant classification and searched for new biomarkers of therapeutic response to DNA damage agents in other HR genes.We identified germline variants in key transcriptional regulatory elements of BRCA1 and BRCA2, and demonstrated that part of them were functionally active and had additional arguments suggesting pathogenicity. We also explored molecular features of breast and ovarian tumors from BRCA1 variant carriers and observed a predominance of loss of the wild-type allele. Conforming to this evidence, we propose to incorporate LOH information, into the multifactorial model for BRCA1 variant classification. Finally, besides the enrichment of BRCA1/2 germline and somatic PV, we described alternative mechanisms of HR inactivation in a OC population presenting optimal response to platinum-based chemotherapy, including BRCA1 promoter hypermethylation and also mutations in other genes of HR pathway

In this work, computationally efficient approximate methods are developed for analyzing uncertain dynamical systems. Uncertainties in both the excitation and the modeling are considered and examples are presented illustrating the accuracy of the proposed approximations.

For nonlinear systems under uncertain excitation, methods are developed to approximate the stationary probability density function and statistical quantities of interest. The methods are based on approximating solutions to the Fokker-Planck equation for the system and differ from traditional methods in which approximate solutions to stochastic differential equations are found. The new methods require little computational effort and examples are presented for which the accuracy of the proposed approximations compare favorably to results obtained by existing methods. The most significant improvements are made in approximating quantities related to the extreme values of the response, such as expected outcrossing rates, which are crucial for evaluating the reliability of the system.

Laplace's method of asymptotic approximation is applied to approximate the probability integrals which arise when analyzing systems with modeling uncertainty. The asymptotic approximation reduces the problem of evaluating a multidimensional integral to solving a minimization problem and the results become asymptotically exact as the uncertainty in the modeling goes to zero. The method is found to provide good approximations for the moments and outcrossing rates for systems with uncertain parameters under stochastic excitation, even when there is a large amount of uncertainty in the parameters. The method is also applied to classical reliability integrals, providing approximations in both the transformed (independently, normally distributed) variables and the original variables. In the transformed variables, the asymptotic approximation yields a very simple formula for approximating the value of SORM integrals. In many cases, it may be computationally expensive to transform the variables, and an approximation is also developed in the original variables. Examples are presented illustrating the accuracy of the approximations and results are compared with existing approximations.