867 resultados para 230118 Optimisation
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Introduction: There is increasing evidence that electronic prescribing (ePrescribing) or computerised provider/physician order entry (CPOE) systems can improve the quality and safety of healthcare services. However, it has also become clear that their implementation is not straightforward and may create unintended or undesired consequences once in use. In this context, qualitative approaches have been particularly useful and their interpretative synthesis could make an important and timely contribution to the field. This review will aim to identify, appraise and synthesise qualitative studies on ePrescribing/CPOE in hospital settings, with or without clinical decision support. Methods and analysis: Data sources will include the following bibliographic databases: MEDLINE, MEDLINE In Process, EMBASE, PsycINFO, Social Policy and Practice via Ovid, CINAHL via EBSCO, The Cochrane Library (CDSR, DARE and CENTRAL databases), Nursing and Allied Health Sources, Applied Social Sciences Index and Abstracts via ProQuest and SCOPUS. In addition, other sources will be searched for ongoing studies (ClinicalTrials.gov) and grey literature: Healthcare Management Information Consortium, Conference Proceedings Citation Index (Web of Science) and Sociological abstracts. Studies will be independently screened for eligibility by 2 reviewers. Qualitative studies, either standalone or in the context of mixed-methods designs, reporting the perspectives of any actors involved in the implementation, management and use of ePrescribing/CPOE systems in hospital-based care settings will be included. Data extraction will be conducted by 2 reviewers using a piloted form. Quality appraisal will be based on criteria from the Critical Appraisal Skills Programme checklist and Standards for Reporting Qualitative Research. Studies will not be excluded based on quality assessment. A postsynthesis sensitivity analysis will be undertaken. Data analysis will follow the thematic synthesis method. Ethics and dissemination: The study does not require ethical approval as primary data will not be collected. The results of the study will be published in a peer-reviewed journal and presented at relevant conferences.
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Phospholipid oxidation by adventitious damage generates a wide variety of products with potentially novel biological activities that can modulate inflammatory processes associated with various diseases. To understand the biological importance of oxidised phospholipids (OxPL) and their potential role as disease biomarkers requires precise information about the abundance of these compounds in cells and tissues. There are many chemiluminescence and spectrophotometric assays available for detecting oxidised phospholipids, but they all have some limitations. Mass spectrometry coupled with liquid chromatography is a powerful and sensitive approach that can provide detailed information about the oxidative lipidome, but challenges still remain. The aim of this work is to develop improved methods for detection of OxPLs by optimisation of chromatographic separation through testing several reverse phase columns and solvent systems, and using targeted mass spectrometry approaches. Initial experiments were carried out using oxidation products generated in vitro to optimise the chromatography separation parameters and mass spectrometry parameters. We have evaluated the chromatographic separation of oxidised phosphatidylcholines (OxPCs) and oxidised phosphatidylethanolamines (OXPEs) using C8, C18 and C30 reverse phase, polystyrene – divinylbenzene based monolithic and mixed – mode hydrophilic interaction (HILIC) columns, interfaced with mass spectrometry. Our results suggest that the monolithic column was best able to separate short chain OxPCs and OxPEs from long chain oxidised and native PCs and PEs. However, variation in charge of polar head groups and extreme diversity of oxidised species make analysis of several classes of OxPLs within one analytical run impractical. We evaluated and optimised the chromatographic separation of OxPLs by serially coupling two columns: HILIC and monolith column that provided us the larger coverage of OxPL species in a single analytical run.
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From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.
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Water-alternating-gas (WAG) is an enhanced oil recovery method combining the improved macroscopic sweep of water flooding with the improved microscopic displacement of gas injection. The optimal design of the WAG parameters is usually based on numerical reservoir simulation via trial and error, limited by the reservoir engineer’s availability. Employing optimisation techniques can guide the simulation runs and reduce the number of function evaluations. In this study, robust evolutionary algorithms are utilized to optimise hydrocarbon WAG performance in the E-segment of the Norne field. The first objective function is selected to be the net present value (NPV) and two global semi-random search strategies, a genetic algorithm (GA) and particle swarm optimisation (PSO) are tested on different case studies with different numbers of controlling variables which are sampled from the set of water and gas injection rates, bottom-hole pressures of the oil production wells, cycle ratio, cycle time, the composition of the injected hydrocarbon gas (miscible/immiscible WAG) and the total WAG period. In progressive experiments, the number of decision-making variables is increased, increasing the problem complexity while potentially improving the efficacy of the WAG process. The second objective function is selected to be the incremental recovery factor (IRF) within a fixed total WAG simulation time and it is optimised using the same optimisation algorithms. The results from the two optimisation techniques are analyzed and their performance, convergence speed and the quality of the optimal solutions found by the algorithms in multiple trials are compared for each experiment. The distinctions between the optimal WAG parameters resulting from NPV and oil recovery optimisation are also examined. This is the first known work optimising over this complete set of WAG variables. The first use of PSO to optimise a WAG project at the field scale is also illustrated. Compared to the reference cases, the best overall values of the objective functions found by GA and PSO were 13.8% and 14.2% higher, respectively, if NPV is optimised over all the above variables, and 14.2% and 16.2% higher, respectively, if IRF is optimised.
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Peer reviewed
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Peer reviewed
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We show experimentally a 57nm gain bandwidth for an ultra-long Raman fiber laser based amplification technique using only a single pump wavelength. The enhanced gain bandwidth and gain flatness is investigated for single and multi-cavity designs. ©2010 IEEE.
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This thesis involved the development of two Biosensors and their associated assays for the detection of diseases, namely IBR and BVD for veterinary use and C1q protein as a biomarker to pancreatic cancer for medical application, using Surface Plasmon Resonance (SPR) and nanoplasmonics. SPR techniques have been used by a number of groups, both in research [1-3] and commercially [4, 5] , as a diagnostic tool for the detection of various biomolecules, especially antibodies [6-8]. The biosensor market is an ever expanding field, with new technology and new companies rapidly emerging on the market, for both human [8] and veterinary applications [9, 10]. In Chapter 2, we discuss the development of a simultaneous IBR and BVD virus assay for the detection of antibodies in bovine serum on an SPR-2 platform. Pancreatic cancer is the most lethal cancer by organ site, partially due to the lack of a reliable molecular signature for diagnostic testing. C1q protein has been recently proposed as a biomarker within a panel for the detection of pancreatic cancer. The third chapter discusses the fabrication, assays and characterisation of nanoplasmonic arrays. We will talk about developing C1q scFv antibody assays, clone screening of the antibodies and subsequently moving the assays onto the nanoplasmonic array platform for static assays, as well as a custom hybrid benchtop system as a diagnostic method for the detection of pancreatic cancer. Finally, in chapter 4, we move on to Guided Mode Resonance (GMR) sensors, as a low-cost option for potential use in Point-of Care diagnostics. C1q and BVD assays used in the prior formats are transferred to this platform, to ascertain its usability as a cost effective, reliable sensor for diagnostic testing. We discuss the fabrication, characterisation and assay development, as well as their use in the benchtop hybrid system.
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CD73 est un ecto-enzyme qui a été associé à la suppression de l'immunité anti-tumorale. Ses valeurs pronostiques et thérapeutiques ont été mises de l'avant dans plusieurs types de cancer. La première hypothèse du projet est que l'expression de CD73 dans la tumeur prédit le pronostic des patients atteints du cancer de la prostate. L'expression de CD73 a été étudiée par immunofluorescence dans des échantillons de tumeur. Puis, des analyses univariées et multivariées ont été conduites pour déterminer si l'expression de CD73 permet de prédire la récidive biochimique des patients. Nous avons déterminé que CD73 prédit indépendamment le pronostic des patients atteints du cancer de la prostate. De plus, nous avons déterminé que son expression dans le tissu normal adjacent ou dans la tumeur prédit différemment la survenue de la récidive biochimique. La deuxième hypothèse est que l'inhibition de CD73 permet d'améliorer l'efficacité d'un vaccin thérapeutique contre le cancer de la prostate. L'effet d'un vaccin de type GVAX a été étudié dans des souris CD73KO ou en combinaison avec un anticorps ciblant CD73. Nous avons observé que l'efficacité du vaccin était augmentée dans les souris où CD73 était absent. Cependant, la combinaison avec l'anti-CD73 n'a pas permis d'améliorer l'efficacité.
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Schistosomiasis is a chronically debilitating helminth infection with a significant socio-economic and public health impact. Accurate diagnostics play a pivotal role in achieving current schistosomiasis control and elimination goals. However, many of the current diagnostic procedures, which rely on detection of schistosome eggs, have major limitations including lack of accuracy and the inability to detect pre-patent infections. DNA-based detection methods provide a viable alternative to the current tests commonly used for schistosomiasis diagnosis. Here we describe the optimisation of a novel droplet digital PCR (ddPCR) duplex assay for the diagnosis of Schistosoma japonicum infection which provides improved detection sensitivity and specificity. The assay involves the amplification of two specific and abundant target gene sequences in S. japonicum; a retrotransposon (SjR2) and a portion of a mitochondrial gene (nad1). The assay detected target sequences in different sources of schistosome DNA isolated from adult worms, schistosomules and eggs, and exhibits a high level of specificity, thereby representing an ideal tool for the detection of low levels of parasite DNA in different clinical samples including parasite cell free DNA in the host circulation and other bodily fluids. Moreover, being quantitative, the assay can be used to determine parasite infection intensity and, could provide an important tool for the detection of low intensity infections in low prevalence schistosomiasis-endemic areas.
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In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.
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Ce projet de recherche s’inscrit dans le domaine de la dosimétrie à scintillation en radiothérapie, plus précisément en curiethérapie à haut débit de dose (HDR). Lors de ce type de traitement, la dose est délivrée localement, ce qui implique de hauts gradients de dose autour de la source. Le but de ce travail est d’obtenir un détecteur mesurant la dose en 2 points distincts et optimisé pour la mesure de dose en curiethérapie HDR. Pour ce faire, le projet de recherche est séparé en deux études : la caractérisation spectrale du détecteur à 2-points et la caractérisation du système de photodétecteur menant à la mesure de la dose. D’abord, la chaine optique d’un détecteur à scintillation à 2-points est caractérisée à l’aide d’un spectromètre afin de déterminer les composantes scintillantes optimales. Cette étude permet de construire quelques détecteurs à partir des composantes choisies pour ensuite les tester avec le système de photodétecteur multi-point. Le système de photodétecteur est aussi caractérisé de façon à évaluer les limites de sensibilité pour le détecteur 2-points choisi précédemment. L’objectif final est de pouvoir mesurer le débit de dose avec précision et justesse aux deux points de mesure du détecteur multi-point lors d’un traitement de curiethérapie HDR.