939 resultados para Concept development


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The U.S. National Science Foundation metadata registry under development for the National Science Digital Library (NSDL) is a repertory intended to manage both metadata schemes and schemas. The focus of this draft discussion paper is on the scheme side of the development work. In particular, the concern of the discussion paper is with issues around the creation of historical snapshots of concept changes and their encoding in SKOS. Through framing the problem as we see it, we hope to find an optimal solution to our need for a SKOS encoding of these snapshots. Since what we are seeking to model is concept change, it is necessary at the outset to make it clear that we are not talking about changes to a concept of such a nature that would require the declaration a new concept with its own URI.In the project, we avoid the use of the terms “version” and “versioning” with regard to changes in concepts and reserve their use to the significant changes of schemes as a whole. Significant changes triggering a new scheme version might include changes in scheme documentation that express a significant shift in the purpose, use or architecture of the scheme. We use the term “snapshot” to denote the state of a scheme at identifiable points in time. Thus, snapshots are identifiable views of a scheme that record the incremental changes that have occurred to concepts, relationships among concepts, and scheme documentation since the last snapshot. Aspects of concept change occur that we need to capture and make available both through the registry and through potentially in transmission of a scheme to other registries. We call these capturings “concept instances.”

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A prototype for a Responsive Fisheries Management System (RFMS) was developed in the context of the European FP7 project EcoFishMan and tested on the Portuguese crustacean trawl fishery. Building on Results Based Management principles, RFMS involves the definition of specific and measurable objectives for a fishery by the relevant authorities but allows resource users the freedom to find ways to achieve the objectives and to provide adequate documentation. Taking into account the main goals of the new Common Fisheries Policy, such as sustainable utilization of the resources, end of discards and unwanted catches, a management plan for the Portuguese crustacean trawl fishery was developed in cooperation with the fishing industry, following the process and design laid out in the RFMS concept. The plan considers biological, social and economic goals and assigns a responsibility for increased data collection to the resource users. The performance of the plan with regard to selected indicators was evaluated through simulations. In this paper the process towards a RFMS is described and the lessons learnt from the interaction with stakeholders in the development of an alternative management plan are discussed. (C) 2014 Elsevier Ltd. All rights reserved.

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This research aimed to develop a questionnaire measure of workers’ perceptions of decent work. The initial pool of 72 items covered the substantive elements used by the International Labour Organization to characterize decent work. It was administered to workers from Portugal (N = 636) and Brazil (N = 1039) and submitted to exploratory and confirmatory factor analysis. The final 31-item version yields seven factor scores in addition to the global decent work score. With good reliability, convergent and discriminant validity indices, the DWQ could open new avenues for empirical studies of the decent work concept.

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Organizational Cooperation (OC) is a current concept that responds to the growing interdependence among individuals and teams. Likewise, Knowledge Management (KM) accompanies specialization in all sectors of human activity. Most KM processes are cooperation-intensive, and the way both constructs relate to each other is relevant in understanding organizations and promoting performance. The present paper focuses on that relationship. The Organizational Cooperation Questionnaire (ORCOQ) and the Short form of the Knowledge Management Questionnaire (KMQ-SF) were applied to 639 members of research and development (R&D) organizations (Universities and Research Institutes). Descriptive, correlational, linear multiple regression and multivariate multiple regression analyses were performed. Results showed significant positive relationships between the ORCOQ and all the KMQ-SF dimensions. The prediction of KMQ-SF showed a large effect size (R2 = 62%). These findings will impact on how KM and OC are seen, and will be a step forward in the development of this field.

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At worldwide level, the classical viticulture produces wines is almost all places in different climate types, where it is possible to obtain only one harvest per year. In these conditions, bud burst in vines occurs as a result of temperature raising at the end of the winter?beginning of spring. With the development of the vegetative cycle, grapes arrive to maturity/harvest period at the end of the summer?beginning of the fall season. After the fall of the leaves, vines undergo a dormant period with a vegetative repose (condition found also in some intertropical producer regions). A lot of grapes are produced for a long-time in the intertropical zone, but only a little part is used to winemaking. Considered a challenge in the past, to produce quality wines in the tropics became reality. The present industry of fine wines began about 30 years ago. Today, there are many commercial wineries in several countries in Occident and Orient in the tropical zone of the globe, like in Brazil, India, Thailand and Venezuela, producing some million liters of fine wines per year - called ?tropical wines?. This article analysis these climates, in relation to the particular viticulture adapted and developed, where it is possible to have more than one cycle per year, with one or more harvests per year. Based on the particularities of this viticulture, a characterization is proposed for the viticulture of ?tropical wines?. Some examples showing different tropical climates are presented.

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The purpose of the air traffic management system is to ensure the safe and efficient flow of air traffic. Therefore, while augmenting efficiency, throughput and capacity in airport operations, attention has rightly been placed on doing it in a safe manner. In the control tower, many advances in operational safety have come in the form of visualization tools for tower controllers. However, there is a paradox in developing such systems to increase controllers' situational awareness: by creating additional computer displays, the controller's vision is pulled away from the outside view and the time spent looking down at the monitors is increased. This reduces their situational awareness by forcing them to mentally and physically switch between the head-down equipment and the outside view. This research is based on the idea that augmented reality may be able to address this issue. The augmented reality concept has become increasingly popular over the past decade and is being proficiently used in many fields, such as entertainment, cultural heritage, aviation, military & defense. This know-how could be transferred to air traffic control with a relatively low effort and substantial benefits for controllers’ situation awareness. Research on this topic is consistent with SESAR objectives of increasing air traffic controllers’ situation awareness and enable up to 10 % of additional flights at congested airports while still increasing safety and efficiency. During the Ph.D., a research framework for prototyping augmented reality tools was set up. This framework consists of methodological tools for designing the augmented reality overlays, as well as of hardware and software equipment to test them. Several overlays have been designed and implemented in a simulated tower environment, which is a virtual reconstruction of Bologna airport control tower. The positive impact of such tools was preliminary assessed by means of the proposed methodology.

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Network monitoring is of paramount importance for effective network management: it allows to constantly observe the network’s behavior to ensure it is working as intended and can trigger both automated and manual remediation procedures in case of failures and anomalies. The concept of SDN decouples the control logic from legacy network infrastructure to perform centralized control on multiple switches in the network, and in this context, the responsibility of switches is only to forward packets according to the flow control instructions provided by controller. However, as current SDN switches only expose simple per-port and per-flow counters, the controller has to do almost all the processing to determine the network state, which causes significant communication overhead and excessive latency for monitoring purposes. The absence of programmability in the data plane of SDN prompted the advent of programmable switches, which allow developers to customize the data-plane pipeline and implement novel programs operating directly in the switches. This means that we can offload certain monitoring tasks to programmable data planes, to perform fine-grained monitoring even at very high packet processing speeds. Given the central importance of network monitoring exploiting programmable data planes, the goal of this thesis is to enable a wide range of monitoring tasks in programmable switches, with a specific focus on the ones equipped with programmable ASICs. Indeed, most network monitoring solutions available in literature do not take computational and memory constraints of programmable switches into due account, preventing, de facto, their successful implementation in commodity switches. This claims that network monitoring tasks can be executed in programmable switches. Our evaluations show that the contributions in this thesis could be used by network administrators as well as network security engineers, to better understand the network status depending on different monitoring metrics, and thus prevent network infrastructure and service outages.

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CDKL5 (cyclin-dependent kinase-like 5) deficiency disorder (CDD) is a severe X-linked neurodevelopmental disease caused by mutations in the CDKL5 gene, characterized by early-onset epileptic seizures, intellectual disability, motor and visual impairment and respiratory dysregulation. Although pharmacological treatments are used to control seizures, there is currently no cure to ameliorate symptoms for CDD. Albeit delivery of a wild-type copy of the mutated gene to cells represents the most curative approach for a monogenic disease, proof-of-concept studies highlight significant efficacy caveats for brain gene therapy. The major one regards the low efficiency of gene delivery to the CNS by viral vectors. We used a secretable Igk-TATk-CDKL5 protein to enhance the efficiency of a gene therapy for CDD. In view of the properties of the Igk-chain leader sequence, the TATk-CDKL5 protein produced by infected cells is secreted via constitutive secretory pathways. Importantly, due to the transduction property of the TATk peptide, the secreted CDKL5 protein is internalized by cells. We compared the effects of a CDKL5 gene therapy with an IgK-TATk-CDKL5 gene therapy in a Cdkl5 KO mouse model to validate whether the Igk-TATk-CDKL5 approach significantly improve the therapeutic efficacy. We found that, although AAVPHP.B_Igk-TATk-CDKL5 and AAVPHP.B_CDKL5 vectors had similar brain infection efficiency, the AAVPHP.B_Igk-TATk-CDKL5 vector led to a higher CDKL5 protein replacement and Cdkl5 KO mice treated with the AAVPHP.B_Igk-TATk-CDKL5 vector showed a behavioral and neuroanatomical improvement in comparison with Cdkl5 KO mice treated with the AAVPHP.B_CDKL5 vector.

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Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.

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With an increasing demand for rural resources and land, new challenges are approaching affecting and restructuring the European countryside. While creating opportunities for rural living, it has also opened a discussion on rural gentrification risks. The concept of rural gentrification encircles the influx of new residents leading to an economic upgrade of an area making it unaffordable for local inhabitants to stay in. Rural gentrification occurs in areas perceived as attractive. Paradoxically, in-migrants re-shape their surrounding landscape. Rural gentrification may not only cause displacement of people but also landscape values. Thus, this research aims to understand the twofold role of landscape in rural gentrification theory: as a possible driver to attract residents and as a product shaped by its residents. To understand the potential gentrifiers’ decision process, this research has provided a collection of drivers behind in-migration. Moreover, essential indicators of rural gentrification have been collected from previous studies. Yet, the available indicators do not contain measures to understand related landscape changes. To fill this gap, after analysing established landscape assessment methodologies, evaluating the relevance for assessing gentrification, a new Landscape Assessment approach is proposed. This method introduces a novel approach to capture landscape change caused by gentrification through a historical depth. The measures to study gentrification was applied on Gotland, Sweden. The study showed a population stagnating while the number of properties increased, and housing prices raised. These factors are not indicating positive growth but risks of gentrification. Then, the research applied the proposed Landscape Assessment method for areas exposed to gentrification. Results suggest that landscape change takes place on a local scale and could over time endanger key characteristics. The methodology contributes to a discussion on grasping nuances within the rural context. It has also proven useful for indicating accumulative changes, which is necessary in managing landscape values.

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This thesis describes the development of the Sample Fetch Rover (SFR), studied for Mars Sample Return (MSR), an international campaign carried out in cooperation between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The focus of this document is the design of the electro-mechanical systems of the rover. After placing this work into the general context of robotic planetary exploration and summarising the state of the art for what concerns Mars rovers, the architecture of the Mars Sample Return Campaign is presented. A complete overview of the current SFR architecture is provided, touching upon all the main subsystems of the spacecraft. For each area, it is discussed what are the design drivers, the chosen solutions and whether they use heritage technology (in particular from the ExoMars Rover) or new developments. This research focuses on two topics of particular interest, due to their relevance for the mission and the novelty of their design: locomotion and sample acquisition, which are discussed in depth. The early SFR locomotion concepts are summarised, covering the initial trade-offs and discarded designs for higher traverse performance. Once a consolidated architecture was reached, the locomotion subsystem was developed further, defining the details of the suspension, actuators, deployment mechanisms and wheels. This technology is presented here in detail, including some key analysis and test results that support the design and demonstrate how it responds to the mission requirements. Another major electro-mechanical system developed as part of this work is the one dedicated to sample tube acquisition. The concept of operations of this machinery was defined to be robust against the unknown conditions that characterise the mission. The design process led to a highly automated robotic system which is described here in its main components: vision system, robotic arm and tube storage.

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The Deep Underground Neutrino Experiment (DUNE) is a long-baseline accelerator experiment designed to make a significant contribution to the study of neutrino oscillations with unprecedented sensitivity. The main goal of DUNE is the determination of the neutrino mass ordering and the leptonic CP violation phase, key parameters of the three-neutrino flavor mixing that have yet to be determined. An important component of the DUNE Near Detector complex is the System for on-Axis Neutrino Detection (SAND) apparatus, which will include GRAIN (GRanular Argon for Interactions of Neutrinos), a novel liquid Argon detector aimed at imaging neutrino interactions using only scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is investigated. This dissertation aims to demonstrate the feasibility of reconstructing particle tracks and the topology of CCQE (Charged Current Quasi Elastic) neutrino events in GRAIN with such a technique. To this end, the development and implementation of a reconstruction algorithm based on Maximum Likelihood Expectation Maximization was carried out to directly obtain a three-dimensional distribution proportional to the energy deposited by charged particles crossing the LAr volume. This study includes the evaluation of the design of several camera configurations and the simulation of a multi-camera optical system in GRAIN.

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In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

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Although there is broad agreement on the need to transition to a fairer agro-food system, consumer potential in shaping a fair food system has often been overlooked. There is no unique definition of the concept of fairness from the consumer’s perspective. In addition, there are no scales in the academic literature that address fairness in its broad sense, as the existing scales focus on specific and limited aspects that provide a partial picture of the concept. Lack of a true and trustworthy measurement of the notion has been a significant barrier to the knowledge of fairness in agro-food systems from the individual-differences perspective. The individual-differences perspective helps explain why some individuals are more likely than others to put emphasis on the extent to which agro-food chains are fair. Individual consumer perception of an ethical problem is followed by the perception of various alternatives that might lead to a solution. Therefore, the current research intends to make two significant contributions by resolving these constraints. First, advance the literature by providing a new viewpoint to understand fairness in the agro-food chain. Indeed, the research provides a comprehensive conceptualisation of fairness that embraces different aspects of fairness and describes the concept in all its facets and nuances. Second, the research provides a valid, reliable, and invariant measurement of the individual disposition toward fairness in agro-food chains by rooting the items in the theoretical underpinnings of the fairness literature. Overall, this research provides a comprehensive suite of approaches and tools to enhance the resilience, integrity and sustainability of agro-food chains.

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In this elaborate, a textile-based Organic Electrochemical Transistor (OECT) was first developed for the determination of uric acid in wound exudate based on the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), which was then coupled to an electrochemically gated textile transistor consisting of a composite of iridium oxide particles and PEDOT:PSS for pH monitoring in wound exudate. In that way a sensor for multiparameter monitoring of wound health status was assembled, including the ability to differentiate between a wet-dry status of the smart bandage by implementing impedance measurements exploiting the OECT architecture. Afterwards, for both wound management as well as generic health status tracking applications, a glass-based calcium sensor was developed employing polymeric ion-selective membranes on a novel architecture inspired by the Wrighton OECT configuration, which was later converted to a Proof-of-Concept textile prototype for wearable applications. Lastly, in collaboration with the King Abdullah University of Science and Technology (KAUST, Thuwal, Saudi Arabia) under the supervision of Prof. Sahika Inal, different types of ion-selective thiophene-based monomers were used to develop ion-selective conductive polymers to detect sodium ion by different methods, involving standard potentiometry and OECT-based approaches. The textile OECTs for uric acid detection performances were optimized by investigating the geometry effect on the instrumental response and the properties of the different textile materials involved in their production, with a special focus on the final application that implies the operativity in flow conditions to simulate the wound environment. The same testing route was followed for the multiparameter sensor and the calcium sensor prototype, with a particular care towards the ion-selective membrane composition and electrode conditioning protocol optimization. The sodium-selective polymer electrosynthesis was optimized in non-aqueous environments and was characterized by means of potentiostatic and potentiodynamic techniques coupled with Quartz Crystal Microbalance and spectrophotometric measurements.