La télémédecine en radiothérapie : développement d’un modèle et analyse des coûts

But : La radiothérapie (RT) est disponible seulement dans les grandes villes au Québec. Les patients atteints de cancer vivant en zone rurale doivent voyager pour obtenir ces soins. Toute proportion gardée, moins de ces patients accèdent à la RT. L’accessibilité serait améliorée en instaurant de petits centres de RT qui dépendraient de la télémédecine (téléRT). Cette étude tente (1) de décrire un modèle (population visée et technologie) réaliste de téléRT; (2) d’en estimer les coûts, comparativement à la situation actuelle où les patients voyagent (itineRT). Méthode : (1) À l’aide de données probantes, le modèle de téléRT a été développé selon des critères de : faisabilité, sécurité, absence de transfert des patients et minimisation du personnel. (2) Les coûts ont été estimés du point de vue du payeur unique en utilisant une méthode publiée qui tient compte des coûts en capitaux, de la main d’oeuvre et des frais généraux. Résultats : (1) Le modèle de téléRT proposé se limiterait aux traitements palliatifs à 250 patients par année. (2) Les coûts sont de 5918$/patient (95% I.C. 4985 à 7095$) pour téléRT comparativement à 4541$/patient (95%I.C. 4351 à 4739$) pour itineRT. Les coûts annuels de téléRT sont de 1,48 M$ (d.s. 0,6 M$), avec une augmentation des coûts nets de seulement 0,54 M$ (d.s. 0,26 M$) comparativement à itineRT. Si on modifiait certaines conditions, le service de téléRT pourrait s’étendre au traitement curatif du cancer de prostate et du sein, à coûts similaires à itineRT. Conclusion : Ce modèle de téléRT pourrait améliorer l’accessibilité et l’équité aux soins, à des coûts modestes.

Simulative Risikoanalyse von Biomethanprojekten

Im Zuge der Novellierung der Gasnetzzugangsverordnung sowie des Erneuerbare-Energien-Gesetzes entwickelte sich die Einspeisung von Biomethan in das Erdgasnetz als alternative Investitionsmöglichkeit der Erneuerbare-Energien-Branche. Als problematisch erweist sich dabei die Identifikation und Strukturierung einzelner Risikofaktoren zu einem Risikobereich, sowie die anschließende Quantifizierung dieser Risikofaktoren innerhalb eines Risikoportfolios. Darüber hinaus besteht die Schwierigkeit, diese Risikofaktoren in einem cashflowbasierten und den Ansprüchen der Investoren gewachsenem Risikomodell abzubilden. Zusätzlich müssen dabei Wechselwirkungen zwischen einzelnen Risikofaktoren berücksichtigt werden. Aus diesem Grund verfolgt die Dissertation das Ziel, die Risikosituation eines Biomethanprojektes anhand aggregierter und isolierter Risikosimulationen zu analysieren. Im Rahmen einer Diskussion werden Strategien und Instrumente zur Risikosteuerung angesprochen sowie die Implementierungsfähigkeit des Risikomodells in das Risikomanagementsystem von Investoren. Die Risikomaße zur Beschreibung der Risikoauswirkung betrachten die Shortfälle einer Verteilung. Dabei beziehen sich diese auf die geplanten Ausschüttungen sowie interne Verzinsungsansprüche der Investoren und die von Kreditinstituten geforderte minimale Schuldendienstdeckungsrate. Im Hinblick auf die Risikotragfähigkeit werden liquiditätsorientierte Kennzahlen hinzugezogen. Investoren interessieren sich vor dem Hintergrund einer gezielten Risikosteuerung hauptsächlich für den gefahrvollsten Risikobereich und innerhalb dessen für den Risikofaktor, der die größten Risikoauswirkungen hervorruft. Zudem spielt der Zeitpunkt maximaler Risikoauswirkung eine große Rolle. Als Kernaussage dieser Arbeit wird festgestellt, dass in den meisten Fällen die Aussagefähigkeit aggregierter Risikosimulationen durch Überlagerungseffekte negativ beeinträchtigt wird. Erst durch isoliert durchgeführte Risikoanalysen können diese Effekte eliminiert werden. Besonders auffällig gestalten sich dabei die Ergebnisse der isoliert durchgeführten Risikoanalyse des Risikobereichs »Politik«. So verursacht dieser im Vergleich zu den übrigen Risikobereichen, wie »Infrastruktur«, »Rohstoffe«, »Absatzmarkt« und »Finanzmarkt«, die geringsten Wahrscheinlichkeiten avisierte Planwerte der Investoren zu unterschreiten. Kommt es jedoch zu einer solchen Planwert-Unterschreitung, nehmen die damit verbundenen Risikoauswirkungen eine überraschende Position im Risikoranking der Investoren ein. Hinsichtlich der Aussagefähigkeit des Risikomodells wird deutlich, dass spezifische Risikosichtweisen der Investoren ausschlaggebend dafür sind, welche Strategien und Instrumente zur Risikosenkung umgesetzt werden. Darüber hinaus wird festgestellt, dass die Grenzen des Risikomodells in der Validität der Expertenmeinungen und dem Auffinden einer Optimallösung zu suchen sind.

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

Model de competència i actuacions de l'alumnat

Una preocupació constant per als investigadors dels diferents camps relacionats amb l’educació obligatòria, així com també de les administracions educatives i d’altres organismes que hi incideixen, consisteix a seleccionar continguts i orientar els processos més útils per aconseguir que els nous ciutadans s’integrin en la societat avançada del segle XXI. Es vol que s’integrin amb unes eines culturals mínimes i que adquireixen la capacitat d’autoaprenentatge, considerada com a bàsica per entendre la complexitat i inserir-se en el món actual

Aligning sequences to structures

Most newly sequenced proteins are likely to adopt a similar structure to one which has already been experimentally determined. For this reason, the most successful approaches to protein structure prediction have been template-based methods. Such prediction methods attempt to identify and model the folds of unknown structures by aligning the target sequences to a set of representative template structures within a fold library. In this chapter, I discuss the development of template-based approaches to fold prediction, from the traditional techniques to the recent state-of-the-art methods. I also discuss the recent development of structural annotation databases, which contain models built by aligning the sequences from entire proteomes against known structures. Finally, I run through a practical step-by-step guide for aligning target sequences to known structures and contemplate the future direction of template-based structure prediction.

A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data

We describe a general likelihood-based 'mixture model' for inferring phylogenetic trees from gene-sequence or other character-state data. The model accommodates cases in which different sites in the alignment evolve in qualitatively distinct ways, but does not require prior knowledge of these patterns or partitioning of the data. We call this qualitative variability in the pattern of evolution across sites "pattern-heterogeneity" to distinguish it from both a homogenous process of evolution and from one characterized principally by differences in rates of evolution. We present studies to show that the model correctly retrieves the signals of pattern-heterogeneity from simulated gene-sequence data, and we apply the method to protein-coding genes and to a ribosomal 12S data set. The mixture model outperforms conventional partitioning in both these data sets. We implement the mixture model such that it can simultaneously detect rate- and pattern-heterogeneity. The model simplifies to a homogeneous model or a rate- variability model as special cases, and therefore always performs at least as well as these two approaches, and often considerably improves upon them. We make the model available within a Bayesian Markov-chain Monte Carlo framework for phylogenetic inference, as an easy-to-use computer program.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.

Optimal observers for ARMA models

A polynomial-based ARMA model, when posed in a state-space framework can be regarded in many different ways. In this paper two particular state-space forms of the ARMA model are considered, and although both are canonical in structure they differ in respect of the mode in which disturbances are fed into the state and output equations. For both forms a solution is found to the optimal discrete-time observer problem and algebraic connections between the two optimal observers are shown. The purpose of the paper is to highlight the fact that the optimal observer obtained from the first state-space form, commonly known as the innovations form, is not that employed in an optimal controller, in the minimum-output variance sense, whereas the optimal observer obtained from the second form is. Hence the second form is a much more appropriate state-space description to use for controller design, particularly when employed in self-tuning control schemes.

Model inter-comparison between statistical and dynamic model assessments of the long-term stability of blanket peat in Great Britain (1940-2099)

We compared output from 3 dynamic process-based models (DMs: ECOSSE, MILLENNIA and the Durham Carbon Model) and 9 bioclimatic envelope models (BCEMs; including BBOG ensemble and PEATSTASH) ranging from simple threshold to semi-process-based models. Model simulations were run at 4 British peatland sites using historical climate data and climate projections under a medium (A1B) emissions scenario from the 11-RCM (regional climate model) ensemble underpinning UKCP09. The models showed that blanket peatlands are vulnerable to projected climate change; however, predictions varied between models as well as between sites. All BCEMs predicted a shift from presence to absence of a climate associated with blanket peat, where the sites with the lowest total annual precipitation were closest to the presence/absence threshold. DMs showed a more variable response. ECOSSE predicted a decline in net C sink and shift to net C source by the end of this century. The Durham Carbon Model predicted a smaller decline in the net C sink strength, but no shift to net C source. MILLENNIA predicted a slight overall increase in the net C sink. In contrast to the BCEM projections, the DMs predicted that the sites with coolest temperatures and greatest total annual precipitation showed the largest change in carbon sinks. In this model inter-comparison, the greatest variation in model output in response to climate change projections was not between the BCEMs and DMs but between the DMs themselves, because of different approaches to modelling soil organic matter pools and decomposition amongst other processes. The difference in the sign of the response has major implications for future climate feedbacks, climate policy and peatland management. Enhanced data collection, in particular monitoring peatland response to current change, would significantly improve model development and projections of future change.

Mutual dependency grid for stakeholder mapping: a component-based approach to supply chain participant analysis

Stakeholder analysis plays a critical role in business analysis. However, the majority of the stakeholder identification and analysis methods focus on the activities and processes and ignore the artefacts being processed by human beings. By focusing on the outputs of the organisation, an artefact-centric view helps create a network of artefacts, and a component-based structure of the organisation and its supply chain participants. Since the relationship is based on the components, i.e. after the stakeholders are identified, the interdependency between stakeholders and the focal organisation can be measured. Each stakeholder is associated with two types of dependency, namely the stakeholder’s dependency on the focal organisation and the focal organisation’s dependency on the stakeholder. We identify three factors for each type of dependency and propose the equations that calculate the dependency indexes. Once both types of the dependency indexes are calculated, each stakeholder can be placed and categorised into one of the four groups, namely critical stakeholder, mutual benefits stakeholder, replaceable stakeholder, and easy care stakeholder. The mutual dependency grid and the dependency gap analysis, which further investigates the priority of each stakeholder by calculating the weighted dependency gap between the focal organisation and the stakeholder, subsequently help the focal organisation to better understand its stakeholders and manage its stakeholder relationships.

Public real estate and the term structure of interest rates: a cross-country study

Using a variation of the Nelson-Siegel term structure model we examine the sensitivity of real estate securities in six key global markets to unexpected changes in the level, slop and curvature of the yield curve. Our results confirm the time-sensitive nature of the exposure and sensitivity to interest rates and highlight the importance of considering the entire term structure of interest rates. One issue that is of particular of interest is that despite the 2007-9 financial crisis the importance of unanticipated interest rate risk weakens post 2003. Although the analysis does examine a range of markets the empirical analysis is unable to provide definitive evidence as to whether REIT and property-company markets display heightened or reduced exposure.

Thermo-solvatochromism of merocyanine polarity probes - What are the consequences of increasing probe lipophilicity through annelation?

The question raised in the title has been answered by comparing the solvatochromism of two series of polarity probes, the lipophilicities of which were increased either by increasing the length of an alkyl group (R) attached to a fixed pyridine-based structure or through annelation (i.e., by fusing benzene rings onto a central pyridine-based structure). The following novel solvatochromic probes were synthesized: 2,6-dibromo-4-[(E)-2-(1-methylquinolinium-4-yl)ethenyl]-phenolate (MeQMBr(2)) and 2,6-dibromo-4-[(E)-2-(1-methyl-acridinium-4- yl) ethenyl)]phenolate (MeAMBr(2) The solvatochromic behavior of these probes, along with that of 2,6dibromo-4-[(E)-2-(1-methylpyridinium-4-yl)ethenyl]phenol-ate(MePMBr(2)) was analyzed in terms of increasing probe lipophilicity, through annelation. Values of the empirical solvent polarity scale [E(T)(MePMBr(2))] in kcalmol(-1) correlated linearly with ET(30), the corresponding values for the extensively employed probe 2,6-diphenyl-4-(2,4,6-triphenylpyridinium-1-yl)phenolate (RB). On the other hand, the nonlinear correlations of ET(MeQMBr(2)) or ET(MeAMBr(2)) with E(T)(30) are described by second-order polynomials. Possible reasons for this behavior include: i) self-aggregation of the probe, ii) photoinduced cis/trans isomerization of the dye, and iii) probe structure- and solvent-dependent contributions of the quinonoid and zwitterionic limiting formulas to the ground and excited states of the probe. We show that mechanisms (i) and (ii) are not operative under the experimental conditions employed; experimental evidence (NMR) and theoretical calculations are presented to support the conjecture that the length of the central ethenylic bond in the dye increases in the order MeAMBr(2) > MeQMBr(2) > MePMBr(2), That is, the contribution of the zwitterionic limiting formula predominates for the latter probe, as is also the case for RB, this being the reason for the observed linear correlation between the ET(MePMBr2) and the ET(30) scales. The effect of increasing probe lipophilicity on solvatochromic behavior therefore depends on the strategy employed. Increasing the length of R affects solvatochromism much less than annelation, because the former structural change hardly perturbs the energy of the intramolecular charge-transfer transition responsible for solvatochromism. The thermo-solvatochromic behavior (effect of temperature on solvatochromism) of the three probes was studied in mixtures of water with propanol and/or with DMSO. The solvation model used explicitly considers the presence of three ""species"" in the system: bulk solution and probe solvation shell [namely, water (W), organic solvent (Solv)], and solvent-water hydrogen-bonded aggregate (Solv-W). For aqueous propanol, the probe is efficiently solvated by Solv-W; the strong interaction of DMSO with W drastically decreases the efficiency of Solv-W in solvating the probe, relative to its precursor solvents. Temperature increases resulted in desolvation of the probes, due to the concomitant reduction in the structured characters of the components of the binary mixtures.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Extracting Causal Graphs from an Open Provenance Data Model

The open provenance architecture (OPA) approach to the challenge was distinct in several regards. In particular, it is based on an open, well-defined data model and architecture, allowing different components of the challenge workflow to independently record documentation, and for the workflow to be executed in any environment. Another noticeable feature is that we distinguish between the data recorded about what has occurred, emphprocess documentation, and the emphprovenance of a data item, which is all that caused the data item to be as it is and is obtained as the result of a query over process documentation. This distinction allows us to tailor the system to separately best address the requirements of recording and querying documentation. Other notable features include the explicit recording of causal relationships between both events and data items, an interaction-based world model, intensional definition of data items in queries rather than relying on explicit naming mechanisms, and emphstyling of documentation to support non-functional application requirements such as reducing storage costs or ensuring privacy of data. In this paper we describe how each of these features aid us in answering the challenge provenance queries.

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.