894 resultados para work-related assessment
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The photocatalytic activity of self-cleaning glass is assessed using a resazurin (Rz) photocatalyst activity indicator ink, i.e. Rz paii, via both the rate of change in the colour of the ink (blue to pink), R(Abs), and the rate of change in the fluorescence intensity, R(Fl), (λ(excitation) = 593 nm; λ(emission) = 639 nm) of the ink. In both cases the kinetics are zero order. Additional work with a range of glass samples of different photocatalytic activity reveal R(Abs) is directly related to R(Fl), thereby showing that the latter, like the former, can be used to provide a measure of the photocatalytic activity of the sample under test. The measured value of R(Fl) is found to be the same for 5 pieces of, otherwise identical, selfcleaning glass with: black, red, blue, yellow and no coloured tape stuck to their backs, which demonstrates that R(Fl) measurements can be used to measure photocatalytic activity under conditions of high colour and opacity under which R(Abs) cannot be measured. The relevance of this novel, fluorescence-based paii to the assessment of the activity of highly coloured, opaque photocatalytic samples, such as paints and tiles, is discussed briefly.
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Barnsley College’s level 3 and 4 diplomas in digital learning design are delivered in one year, enabling apprentices to be employed alongside their studies in the college’s innovative learning design company, Elephant Learning Designs. The limited time this allows for delivery and assessment has prompted course leaders to rethink their approach to course structure, assessment and feedback design, and the role of technology in evidence collection.
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Many maritime countries in Europe have implemented marine environmental monitoring programmes which include the measurement of chemical contaminants and related biological effects. How best to integrate data obtained in these two types of monitoring into meaningful assessments has been the subject of recent efforts by the International Council for Exploration of the Sea (ICES) Expert Groups. Work within these groups has concentrated on defining a core set of chemical and biological endpoints that can be used across maritime areas, defining confounding factors, supporting parameters and protocols for measurement. The framework comprised markers for concentrations of, exposure to and effects from, contaminants. Most importantly, assessment criteria for biological effect measurements have been set and the framework suggests how these measurements can be used in an integrated manner alongside contaminant measurements in biota, sediments and potentially water. Output from this process resulted in OSPAR Commission (www.ospar.org) guidelines that were adopted in 2012 on a trial basis for a period of 3 years. The developed assessment framework can furthermore provide a suitable approach for the assessment of Good Environmental Status (GES) for Descriptor 8 of the European Union (EU) Marine Strategy Framework Directive (MSFD).
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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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Dissertação de Mestrado, Ciências Biomédicas, 28 de Junho de 2016, Universidade dos Açores.
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International audience
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Sustainable development has only recently started examining the existing infrastructure, and a key aspect of this is hazard mitigation. To examine buildings under a sustainable perspective requires an understanding of a building's life-cycle environmental costs, including the consideration of associated environmental impacts induced by earthquake damage. Damage repair costs lead to additional material and energy consumption, leading to harmful environmental impacts. Merging results obtained from a seismic evaluation and life-cycle analysis for buildings will give a novel outlook on sustainable design decisions. To evaluate the environmental impacts caused by buildings, long-term impacts accrued throughout a building's lifetime and impacts associated with damage repair need to be quantified. A method and literature review for completing this examination has been developed and is discussed. Using software Athena and HAZUS-MH, this study evaluated the performance of steel and concrete buildings considering their life-cycle assessments and earthquake resistance. It was determined that code design-level greatly effects a building repair and damage estimations. This study presented two case study buildings and found specific results that were obtained using several premade assumptions. Future research recommendations were provided to make this methodology more useful in real-world applications. Examining cost and environmental impacts that a building has through, a cradle-to-grave analysis and seismic damage assessment will help reduce material consumption and construction activities from taking place before and after an earthquake event happens.
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The daily experience with type 2 diabetes mellitus (T2DM) has significant adverse effects on health-related quality of life (HRQoL). HRQoL assessment is essential for measuring the impact of the disease on the patient and selecting individualized strategies. Generic measures for assessing HRQoL are very useful because, unlike specific measurement instruments, they allow for the comparison with other instruments. The EQ-5D-3L is a generic measure and it describes HRQoL in five dimensions; mobility, self-care, usual activities, pain/discomfort and anxiety/depression, with three levels each. In Portugal, studies using the EQ-5D-3L as a generic measure to assess HRQoL in diabetic patients are scarce. Objective: To assess HRQoL in individuals with T2DM using the Portuguese version of the EQ-5D-3L. Methodology: An accidental sample of patients with T2DM (n=437) was selected at Family Health Units and healthcare centers in Coimbra, Portugal, between January 2013 and January 2014. The EQ-5D-3L was applied in interviews. The EQ-5D-3L score was calculated based on the answers to the five dimensions and the value system for the Portuguese population. Results: In this sample, 100% of the participants answered the EQ-5D-3L. The HRQoL score was 0.6772 in the EQ-5D-3L and 64.85 in the EQ-VAS. The most frequent answers to the five dimensions were no problems or some problems. The mean score of the EQ-5D-3L was significantly associated with age, male gender, high level of education, having an occupation, practicing physical activity, being single and having been diagnosed with T2DM for less time. The Cronbach alpha's value was 0.674, confirming an acceptable internal consistency. Conclusion: HRQoL levels in individuals with T2DM are lower than the national average and vary depending on sociodemographic and clinical characteristics. The EQ-5D-3L is a reliable instrument that can be used to assess the quality of life of diabetic patients and contribute to assess the patients' overall health status, adding data from the subjective dimension of self-care management.
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Plants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process.
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It is well known that human resources play a valuable role in a sustainable organizational development. Indeed, this work will focus on the development of a decision support system to assess workers’ satisfaction based on factors related to human resources management practices. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data or knowledge in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process.
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The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).
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The ever-growing interest in scientific techniques, able to characterise the materials and rediscover the steps behind the execution of a painting, makes them widely accepted in its investigation. This research discusses issues emerging from attribution and authentication studies and proposes best practise for the characterisation of materials and techniques, favouring the contextualisation of the results in an integrated approach; the work aims to systematically classify paintings in categories that aid the examination of objects. A first grouping of paintings is based on the information initially available on them, identifying four categories. A focus of this study is the examination of case studies, spanning from the 16th to the 20th century, to evaluate and validate different protocols associated to each category, to show problems arising from paintings and explain advantages and limits of the approach. The research methodology incorporates a combined set of scientific techniques (non-invasive, such as technical imaging and XRF, micro-invasive, such as optical microscopy, SEM-EDS, FTIR, Raman microscopy and in one case radiocarbon dating) to answer the questions and, if necessary for the classification, exhaustively characterise the materials of the paintings, as the creation and contribution of shared technical databases related to various artists and their evolution over time is an objective tool that benefits this kind of study. The reliability of a close collaboration among different professionals is an essential aspect of this research to comprehensively study a painting, as the integration of stylistic, documentary and provenance studies corroborates the scientific findings and helps in the successful contextualisation of the results and the reconstruction of the history of the object.
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At the beginning, this Ph.D. project led to an overview of the most common and emerging types of fraud and possible countermeasures in the olive oil sector. Furthermore, possible weaknesses in the current conformity check system for olive oil were highlighted. Among those, despite the organoleptic assessment is a fundamental tool for establishing the virgin olive oils (VOOs) quality grade, the scientific community has evidenced some drawbacks in it. In particular, the application of instrumental screening methods to support the panel test could reduce the work of sensory panels and the cost of this analysis (e.g. for industries, distributors, public and private control laboratories), permitting the increase in the number and the efficiency of the controls. On this basis, a research line called “Quantitative Panel Test” is one of the main expected outcomes of the OLEUM project that is also partially discussed in this doctoral dissertation. In this framework, analytical activities were carried out, within this PhD project, aimed to develop and validate analytical protocols for the study of the profiles in volatile compounds (VOCs) of the VOOs headspace. Specifically, two chromatographic approaches, one targeted and one semi-targeted, to determine VOCs were investigated in this doctoral thesis. The obtained results, will allow the possible establishment of concentration limits and ranges of selected volatile markers, as related to fruitiness and defects, with the aim to support the panel test in the commercial categorization of VOOs. In parallel, a rapid instrumental screening method based on the analysis of VOCs has been investigated to assist the panel test through a fast pre-classification of VOOs samples based on a known level of probability, thus increasing the efficiency of quality control.
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The internet and digital technologies revolutionized the economy. Regulating the digital market has become a priority for the European Union. While promoting innovation and development, EU institutions must assure that the digital market maintains a competitive structure. Among the numerous elements characterizing the digital sector, users’ data are particularly important. Digital services are centered around personal data, the accumulation of which contributed to the centralization of market power in the hands of a few large providers. As a result, data-driven mergers and data-related abuses gained a central role for the purposes of EU antitrust enforcement. In light of these considerations, this work aims at assessing whether EU competition law is well-suited to address data-driven mergers and data-related abuses of dominance. These conducts are of crucial importance to the maintenance of competition in the digital sector, insofar as the accumulation of users’ data constitutes a fundamental competitive advantage. To begin with, part 1 addresses the specific features of the digital market and their impact on the definition of the relevant market and the assessment of dominance by antitrust authorities. Secondly, part 2 analyzes the EU’s case law on data-driven mergers to verify if merger control is well-suited to address these concentrations. Thirdly, part 3 discusses abuses of dominance in the phase of data collection and the legal frameworks applicable to these conducts. Fourthly, part 4 focuses on access to “essential” datasets and the indirect effects of anticompetitive conducts on rivals’ ability to access users’ information. Finally, Part 5 discusses differential pricing practices implemented online and based on personal data. As it will be assessed, the combination of an efficient competition law enforcement and the auspicial adoption of a specific regulation seems to be the best solution to face the challenges raised by “data-related dominance”.