840 resultados para Competencies assessment tool


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The highly dynamic nature of some sandy shores with continuous morphological changes require the development of efficient and accurate methodological strategies for coastal hazard assessment and morphodynamic characterisation. During the past decades, the general methodological approach for the establishment of coastal monitoring programmes was based on photogrammetry or classical geodetic techniques. With the advent of new geodetic techniques, space-based and airborne-based, new methodologies were introduced in coastal monitoring programmes. This paper describes the development of a monitoring prototype that is based on the use of global positioning system (GPS). The prototype has a GPS multiantenna mounted on a fast surveying platform, a land vehicle appropriate for driving in the sand (four-wheel quad). This system was conceived to perform a network of shore profiles in sandy shores stretches (subaerial beach) that extend for several kilometres from which high-precision digital elevation models can be generated. An analysis of the accuracy and precision of some differential GPS kinematic methodologies is presented. The development of an adequate survey methodology is the first step in morphodynamic shore characterisation or in coastal hazard assessment. The sample method and the computational interpolation procedures are important steps for producing reliable three-dimensional surface maps that are real as possible. The quality of several interpolation methods used to generate grids was tested in areas where there were data gaps. The results obtained allow us to conclude that with the developed survey methodology, it is possible to Survey sandy shores stretches, under spatial scales of kilometers, with a vertical accuracy of greater than 0.10 m in the final digital elevation models.

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Energy auditing can be an important contribution for identification and assessment of energy conservation measures (ECMs) in buildings. Numerous tools and software have been developed, with varying degree of precision and complexity and different areas of use.   This paper evaluates PHPP as a versatile, easy-to-use energy auditing tool and gives examples of how it has been compared to a dynamic simulation tool, within the EU-project iNSPiRe. PHPP is a monthly balance energy calculation tool based on EN13790. It is intended for assisting the design of Passive Houses and energy renovation projects and as guidance in the choice of appropriate ECMs.   PHPP was compared against the transient simulation software TRNSYS for a single family house and a multi-family house. It should be mentioned that dynamic building simulations might strongly depend on the model assumptions and simplifications compared to reality, such as ideal heating or real heat emission system. Setting common boundary conditions for both PHPP and TRNSYS, the ideal heating and cooling loads and demands were compared on monthly and annual basis for seven European locations and buildings with different floor area, S/V ratio, U-values and glazed area of the external walls.   The results show that PHPP can be used to assess the heating demand of single-zone buildings and the reduction of heating demand with ECMs with good precision. The estimation of cooling demand is also acceptable if an appropriate shading factor is applied in PHPP. In general, PHPP intentionally overestimates heating and cooling loads, to be on the safe side for system sizing. Overall, the agreement with TRNSYS is better in cases with higher quality of the envelope as in cold climates and for good energy standards. As an energy auditing tool intended for pre-design it is a good, versatile and easy-to-use alternative to more complex simulation tools.

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Recognising the deteriorating patient is an essential nursing skill, and structured frameworks should be in place to assist effective patient assessment. The aim of this article is to encourage nurses to consider how to promote the 6Cs of nursing within such assessment. The article provides an overview of the Patient Assessment and Clinical reasoning Tool designed to facilitate the development of clinical reasoning skills and effective communication with other healthcare professionals, therebyenhancing patientcentred care.

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The Short Term Assessment of Risk and Treatability is a structured judgement tool used to inform risk estimation for multiple adverse outcomes. In research, risk estimates outperform the tool's strength and vulnerability scales for violence prediction. Little is known about what its’component parts contribute to the assignment of risk estimates and how those estimates fare in prediction of non-violent adverse outcomes compared with the structured components. START assessment and outcomes data from a secure mental health service (N=84) was collected. Binomial and multinomial regression analyses determined the contribution of selected elements of the START structured domain and recent adverse risk events to risk estimates and outcomes prediction for violence, self-harm/suicidality, victimisation, and self-neglect. START vulnerabilities and lifetime history of violence, predicted the violence risk estimate; self-harm and victimisation estimates were predicted only by corresponding recent adverse events. Recent adverse events uniquely predicted all corresponding outcomes, with the exception of self-neglect which was predicted by the strength scale. Only for victimisation did the risk estimate outperform prediction based on the START components and recent adverse events. In the absence of recent corresponding risk behaviour, restrictions imposed on the basis of START-informed risk estimates could be unwarranted and may be unethical.

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This paper describes a methodological proposal for the design, creation and evaluation of Learning Objects (LOs). This study arises from the compilation and analysis of several LO design methodologies currently used in Ibero-America. This proposal, which has been named DICREVOA, defines five different phases: analysis, design (instructional and multimedia), implementation (LO and metadata), evaluation (from the perspective of both the producer and the consumer of the LO), and publishing. The methodology focuses not only on the teaching inexperienced, but also on those having a basic understanding of the technological and educational aspects related to LO design; therefore, the study emphasizes LO design activities centered around the Kolb cycle and the use of the ExeLearning tool in order to implement the LO core. Additionally, DICREVOA was used in a case study, which demonstrates how it provides a feasible mechanism for LO design and implementation within different contexts. Finally, DICREVOA, the case study to which it was applied, and the results obtained are presented

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The aim of this study was to assess the relative contribution of natural productivity and compound food to the growth of the juvenile blue shrimp Litopenaeus stylirostris reared in a biofloc system. Two experiments were carried out based on the same protocol with three treatments: clear water with experimental diet (CW), biofloc with experimental diet (BF) and biofloc unfed (BU). Shrimp survival was significantly higher in biofloc rearing than in CW rearing. The contribution of the biofloc to shrimp diet was estimated through measurement of carbon and nitrogen stable isotope ratios in shrimp and food sources. Different isotopic compositions between feeds were obtained by feeding natural productivity with a mixture rich in fish meal and the shrimps with a pellet containing a high level of soy protein concentrate. Using a two source one-isotope mixing model, we found that the natural productivity of the biofloc system contributed to shrimp growth at a level of 39.8% and 36.9%, for C and N, respectively. The natural food consumed by the shrimps reared in the biofloc system resulted in higher gene expression (mRNA transcript abundance) and activities of two digestive enzymes in their digestive gland: α-amylase and trypsin. The growth of shrimp biomass reared in biofloc was, on average, 4.4 times that of those grown in clear water. Our results confirmed the best survival and promoted growth of shrimps using biofloc technology and highlighted the key role of the biofloc in the nutrition of rearing shrimps. Statement of relevance In this study, we have applied an original protocol to determine the respective contribution of natural productivity and artificial feeds on the alimentation of the juvenile blue shrimp L. stylirostris reared in biofloc system by using C and N natural stable isotope analysis. Moreover, we have compared, in shrimp digestive gland, the α-amylase and trypsin enzyme activities at biochemical and molecular levels for two different shrimp rearing systems, biofloc and clear water. In our knowledge, the use of molecular tool to study the influence of biofloc consumption on digest process of shrimp was never carried out. We think that our research is new and important to increase knowledge on biofloc topic.

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Although the value of primary forests for biodiversity conservation is well known, the potential biodiversity and conservation value of regenerating forests remains controversial. Many factors likely contribute to this, including: 1. the variable ages of regenerating forests being studied (often dominated by relatively young regenerating forests); 2. the potential for confounding on-going human disturbance (such as logging and hunting); 3. the relatively low number of multi-taxa studies; 4. the lack of studies that directly compare different historic disturbances within the same location; 5. contrasting patterns from different survey methodologies and the paucity of knowledge on the impacts across different vertical levels of rainforest biodiversity (often due to a lack of suitable methodologies available to assess them). We also know relatively little as to how biodiversity is affected by major current impacts, such as unmarked rainforest roads, which contribute to this degradation of habitat and fragmentation. This thesis explores the potential biodiversity value of regenerating rainforests under the best of scenarios and seeks to understand more about the impact of current human disturbance to biodiversity; data comes from case studies from the Manu and Sumaco Biosphere Reserves in the Western Amazon. Specifically, I compare overall biodiversity and conservation value of a best case regenerating rainforest site with a selection of well-studied primary forest sites and with predicted species lists for the region; including a focus on species of key conservation concern. I then investigate the biodiversity of the same study site in reference to different types of historic anthropogenic disturbance. Following this I investigate the impacts to biodiversity from an unmarked rainforest road. In order to understand more about the differential effects of habitat disturbance on arboreal diversity I directly assess how patterns of butterfly biodiversity vary between three vertical strata. Although assessments within the canopy have been made for birds, invertebrates and bats, very few studies have successfully targeted arboreal mammals. I therefore investigate the potential of camera traps for inventorying arboreal mammal species in comparison with traditional methodologies. Finally, in order to investigate the possibility that different survey methodologies might identify different biodiversity patterns in habitat disturbance assessments, I investigate whether two different but commonly used survey methodologies used to assess amphibians, indicate the same or different responses of amphibian biodiversity to historic habitat change by people. The regenerating rainforest study site contained high levels of species richness; both in terms of alpha diversity found in nearby primary forest areas (87% ±3.5) and in terms of predicted primary forest diversity from the region (83% ±6.7). This included 89% (39 out of 44) of the species of high conservation concern predicted for the Manu region. Faunal species richness in once completely cleared regenerating forest was on average 13% (±9.8) lower than historically selectively logged forest. The presence of the small unmarked road significantly altered levels of faunal biodiversity for three taxa, up to and potentially beyond 350m into the forest interior. Most notably, the impact on biodiversity extended to at least 32% of the whole reserve area. The assessment of butterflies across strata showed that different vertical zones within the same rainforest responded differently in areas with different historic human disturbance. A comparison between forest regenerating after selective logging and forest regenerating after complete clearance, showed that there was a 17% greater reduction in canopy species richness in the historically cleared forest compared with the terrestrial community. Comparing arboreal camera traps with traditional ground-based techniques suggests that camera traps are an effective tool for inventorying secretive arboreal rainforest mammal communities and detect a higher number of cryptic species. Finally, the two survey methodologies used to assess amphibian communities identified contrasting biodiversity patterns in a human modified rainforest; one indicated biodiversity differences between forests with different human disturbance histories, whereas the other suggested no differences between forest disturbance types. Overall, in this thesis I find that the conservation and biodiversity value of regenerating and human disturbed tropical forest can potentially contribute to rainforest biodiversity conservation, particularly in the best of circumstances. I also highlight the importance of utilising appropriate study methodologies that to investigate these three-dimensional habitats, and contribute to the development of methodologies to do so. However, care should be taken when using different survey methodologies, which can provide contrasting biodiversity patterns in response to human disturbance.

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The Multicriteria decision analysis is a tool to support decision-making in the identification of areas with the utmost beekeeping potential. This paper design a GIS multicriteria approach to assess the beekeeping potential. The development of a conceptual model structure requires the participation of stakeholders and experts in that process. The spatial Multicriteria Decision Analysis (MCDA) allowed defining the potential beekeeping map. The resulting maps can be used by the beekeepers associations to easily select the more suitable areas for the apiaries location or relocation and avoid prohibited areas by legal requirements.

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Planners require solutions that address routine work needs and seems essential to improving efficiency and productivity. There are a great number of different factors related to beekeeper activity as well the quality and productivity of different bee products. The spatial analysis is a powerful tool for overlap and relates various levels of information on a map, and consequently a very useful for beekeeping activity planning. This work proposes and applies a methodology to potential beekeeping assessment in Montesinho Natural Park, a region in the northwest of Portugal. The beekeeping potential maps were developed with the following data sources: legal standards, vegetation, land use, topography, water resources, roads, electromagnetic fields, and some honey physico-chemical analysis. The design and implementation of spatial analysis model based on Geographic Information System (GIS) to beekeeping planning activities has already been described by Anjos et al (2014). Spatial analysis techniques allows to define the potential beekeeper map supporting the beekeeper management in this region. Anjos O, Silva G, Roque N, Fernandez P, 2014. GIS based analysis to support the beekeeping planning. Book of abstracts of the International Symposium on Bee Products 3rd edition – Annual meeting of the International Honey Commission (IHC), Faculty of medicine, University of Rijeka, p:61

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Critical infrastructures are based on complex systems that provide vital services to the nation. The complexities of the interconnected networks, each managed by individual organisations, if not properly secured, could offer vulnerabilities that threaten other organisations’ systems that depend on their services. This thesis argues that the awareness of interdependencies among critical sectors needs to be increased. Managing and securing critical infrastructure is not isolated responsibility of a government or an individual organisation. There is a need for a strong collaboration among critical service providers of public and private organisations in protecting critical information infrastructure. Cyber exercises have been incorporated in national cyber security strategies as part of critical information infrastructure protection. However, organising a cyber exercise involved multi sectors is challenging due to the diversity of participants’ background, working environments and incidents response policies. How well the lessons learned from the cyber exercise and how it can be transferred to the participating organisations is still a looming question. In order to understand the implications of cyber exercises on what participants have learnt and how it benefits participants’ organisation, a Cyber Exercise Post Assessment (CEPA) framework was proposed in this research. The CEPA framework consists of two parts. The first part aims to investigate the lessons learnt by participants from a cyber exercise using the four levels of the Kirkpatrick Training Model to identify their perceptions on reaction, learning, behaviour and results of the exercise. The second part investigates the Organisation Cyber Resilience (OCR) of participating sectors. The framework was used to study the impact of the cyber exercise called X Maya in Malaysia. Data collected through interviews with X Maya 5 participants were coded and categorised based on four levels according to the Kirkpatrick Training Model, while online surveys distributed to ten Critical National Information Infrastructure (CNII) sectors participated in the exercise. The survey used the C-Suite Executive Checklist developed by World Economic Forum in 2012. To ensure the suitability of the tool used to investigate the OCR, a reliability test conducted on the survey items showed high internal consistency results. Finally, individual OCR scores were used to develop the OCR Maturity Model to provide the organisation cyber resilience perspectives of the ten CNII sectors.

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Objective: The purpose of this study was to develop and test psychometric properties of a Mealtime Interaction Clinical Observation Tool (MICOT) that could be used to facilitate assessment and behavioural intervention in childhood feeding difficulties. Methods: Thematic analysis of four focus groups with feeding and behaviour experts identified the content and structure of the MICOT. Following refinement, inter-rater reliability was tested between three healthcare professionals. Results: Six themes were identified for the MICOT, which utilises a traffic-light system to identify areas of strength and areas for intervention. Despite poor inter-rater reliability, for which a number of reasons are postulated, some correlation between psychologists’ ratings was evident. Healthcare professionals liked the tool and reported that it could have good clinical utility. Conclusion: The study provides a promising first version of a clinical observation tool that facilitates assessment and behavioural intervention in childhood feeding difficulties.

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Background: Prevalence of psychosis is known to be higher in adults with intellectual disabilities (ID) than in the general adult population. However, there have been no attempts to develop a psychosis screening tool specifically for the adult ID population. The present study describes the development and preliminary evaluation of a new measure, the Glasgow Psychosis Screening tool for use in Adults with Intellectual Disabilities (GPS-ID). Method: An item pool was generated following: 1) focus groups with adults with ID and psychosis, and their carers and/or workers; 2) expert input from clinicians. A draft scale was compiled and refined following expert feedback. The new scale, along with the Psychotic Symptom Rating Scales was administered to 20 adults with ID (10 with and 10 without psychosis) and their relative or carers. Results: The GPS-ID total score, self-report subscale and informant rating-subscale differentiated psychosis and non-psychosis groups. The tool had good internal consistency (Cronbach’s α=0.91), and a cut-off score ≥4 yielded high sensitivity (90%) and specificity (100%). The method of tool development supports face and content validity. Criterion validity was not supported. Conclusions: Preliminary investigation of the tool’s psychometric properties is positive, although further investigation is required. The tool is accessible to adults with mild to moderate ID and can be completed in 15-30 minutes. The GPS-ID is not a diagnostic tool, therefore any adult exceeding the cut-off score of ≥4 should receive further assessment.

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Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

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Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.

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Uma das condições que mais influencia a competitividade entre instituições de ensino é a Qualidade. Sendo a sociedade cada vez mais exigente, é necessário medir e avaliá-la. A utilização de uma ferramenta de autoavaliação, desenvolvida ao nível da União Europeia, a Common Assessment Framework (CAF), que teve como modelo de origem o European Foundation for Quality Management (EFQM), veio permitir a medição da qualidade dos serviços prestados na administração pública. Este estudo apresenta os diversos aspectos referentes à temática da qualidade, o modelo CAF e os principais resultados obtidos num inquérito por questionário, junto dos alunos, colaboradores internos e gestores dos Serviços Académicos da Universidade de Évora, com o objectivo de avaliar o grau de satisfação com a qualidade do serviço prestado, o desempenho de todas as partes interessadas e, consequentemente, a sustentabilidade desse serviço. Desses resultados retiraram-se alguns pontos fortes, enunciaram-se diversos pontos fracos e evidenciaram-se sugestões de melhoria para o serviço em estudo. Neste sentido, este trabalho serviu de diagnóstico e apresenta uma ferramenta que permite aos Serviços académicos da Universidade de Évora conhecerem-se melhor e poderem mover-se no caminho da qualidade. ABSTRACT: One of the conditions that most influences the competitiveness among institutions of education is quality. As society increasingly demanding in terms of professional skills, it is necessary to measure and assess the quality of education, through continuous improvement to achieve excellence. Currently, the quality must be measured and seen as a competitive advantage. The use of a tool for self-evaluation of the quality, developed at EU level, the Common Assessment Framework (CAF) that has had its origin on European Foundation for Quality Management (EFQM), carne allow the measurement of quality of services provided to the clients, based on an internal guidance for quality in the organization and on the adoption of quality ratings as a routine in their work. This study presents the various aspects relating to the issue of quality and the Common Assessment Framework (CAF) and presents the main results obtained through a survey by questionnaire. These questionnaires were applied to the students, staff and internal managers from the Academic Services of the University of Évora with the aim of assessing the grade of satisfaction with the quality of the services provided, the performance of all interested parties and therefore the sustainability of this service in this institution of higher education. As results obtained on this research there are some strengths, several weaknesses and suggestions for improvement that can benefit the service under study. This work can be used as a diagnosis and gives a tool that allows Academic Services of the University of Évora know themselves better and to be able to move on the path of quality.