875 resultados para Development and applications


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This article goes into the development of NURBS models of quadratic curves and surfaces. Curves and surfaces which could be represented by one general equation (one for the curves and one for the surfaces) are addressed. The research examines the curves: ellipse, parabola and hyperbola, the surfaces: ellipsoid, paraboloid, hyperboloid, double hyperboloid, hyperbolic paraboloid and cone, and the cylinders: elliptic, parabolic and hyperbolic. Many real objects which have to be modeled in 3D applications possess specific features. Because of this these geometric objects have been chosen. Using the NURBS models presented here, specialized software modules (plug-ins) have been developed for a 3D graphic system. An analysis of their implementation and the primitives they create has been performed.

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We present some recent trends in the field of digital cultural heritage management and applications including digital cultural data curation, interoperability, open linked data publishing, crowd sourcing, visualization, platforms for digital cultural heritage, and applications. We present some examples from research and development projects of MUSIC/TUC in those areas.

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Clusters are aggregations of atoms or molecules, generally intermediate in size between individual atoms and aggregates that are large enough to be called bulk matter. Clusters can also be called nanoparticles, because their size is on the order of nanometers or tens of nanometers. A new field has begun to take shape called nanostructured materials which takes advantage of these atom clusters. The ultra-small size of building blocks leads to dramatically different properties and it is anticipated that such atomically engineered materials will be able to be tailored to perform as no previous material could.^ The idea of ionized cluster beam (ICB) thin film deposition technique was first proposed by Takagi in 1972. It was based upon using a supersonic jet source to produce, ionize and accelerate beams of atomic clusters onto substrates in a vacuum environment. Conditions for formation of cluster beams suitable for thin film deposition have only recently been established following twenty years of effort. Zinc clusters over 1,000 atoms in average size have been synthesized both in our lab and that of Gspann. More recently, other methods of synthesizing clusters and nanoparticles, using different types of cluster sources, have come under development.^ In this work, we studied different aspects of nanoparticle beams. The work includes refinement of a model of the cluster formation mechanism, development of a new real-time, in situ cluster size measurement method, and study of the use of ICB in the fabrication of semiconductor devices.^ The formation process of the vaporized-metal cluster beam was simulated and investigated using classical nucleation theory and one dimensional gas flow equations. Zinc cluster sizes predicted at the nozzle exit are in good quantitative agreement with experimental results in our laboratory.^ A novel in situ real-time mass, energy and velocity measurement apparatus has been designed, built and tested. This small size time-of-flight mass spectrometer is suitable to be used in our cluster deposition systems and does not suffer from problems related to other methods of cluster size measurement like: requirement for specialized ionizing lasers, inductive electrical or electromagnetic coupling, dependency on the assumption of homogeneous nucleation, limits on the size measurement and non real-time capability. Measured ion energies using the electrostatic energy analyzer are in good accordance with values obtained from computer simulation. The velocity (v) is measured by pulsing the cluster beam and measuring the time of delay between the pulse and analyzer output current. The mass of a particle is calculated from m = (2E/v$\sp2).$ The error in the measured value of background gas mass is on the order of 28% of the mass of one N$\sb2$ molecule which is negligible for the measurement of large size clusters. This resolution in cluster size measurement is very acceptable for our purposes.^ Selective area deposition onto conducting patterns overlying insulating substrates was demonstrated using intense, fully-ionized cluster beams. Parameters influencing the selectivity are ion energy, repelling voltage, the ratio of the conductor to insulator dimension, and substrate thickness. ^

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Thermodynamic stability measurements on proteins and protein-ligand complexes can offer insights not only into the fundamental properties of protein folding reactions and protein functions, but also into the development of protein-directed therapeutic agents to combat disease. Conventional calorimetric or spectroscopic approaches for measuring protein stability typically require large amounts of purified protein. This requirement has precluded their use in proteomic applications. Stability of Proteins from Rates of Oxidation (SPROX) is a recently developed mass spectrometry-based approach for proteome-wide thermodynamic stability analysis. Since the proteomic coverage of SPROX is fundamentally limited by the detection of methionine-containing peptides, the use of tryptophan-containing peptides was investigated in this dissertation. A new SPROX-like protocol was developed that measured protein folding free energies using the denaturant dependence of the rate at which globally protected tryptophan and methionine residues are modified with dimethyl (2-hydroxyl-5-nitrobenzyl) sulfonium bromide and hydrogen peroxide, respectively. This so-called Hybrid protocol was applied to proteins in yeast and MCF-7 cell lysates and achieved a ~50% increase in proteomic coverage compared to probing only methionine-containing peptides. Subsequently, the Hybrid protocol was successfully utilized to identify and quantify both known and novel protein-ligand interactions in cell lysates. The ligands under study included the well-known Hsp90 inhibitor geldanamycin and the less well-understood omeprazole sulfide that inhibits liver-stage malaria. In addition to protein-small molecule interactions, protein-protein interactions involving Puf6 were investigated using the SPROX technique in comparative thermodynamic analyses performed on wild-type and Puf6-deletion yeast strains. A total of 39 proteins were detected as Puf6 targets and 36 of these targets were previously unknown to interact with Puf6. Finally, to facilitate the SPROX/Hybrid data analysis process and minimize human errors, a Bayesian algorithm was developed for transition midpoint assignment. In summary, the work in this dissertation expanded the scope of SPROX and evaluated the use of SPROX/Hybrid protocols for characterizing protein-ligand interactions in complex biological mixtures.

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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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The main drivers for the development and evolution of Cyber Physical Systems (CPS) are the reduction of development costs and time along with the enhancement of the designed products. The aim of this survey paper is to provide an overview of different types of system and the associated transition process from mechatronics to CPS and cloud-based (IoT) systems. It will further consider the requirement that methodologies for CPS-design should be part of a multi-disciplinary development process within which designers should focus not only on the separate physical and computational components, but also on their integration and interaction. Challenges related to CPS-design are therefore considered in the paper from the perspectives of the physical processes, computation and integration respectively. Illustrative case studies are selected from different system levels starting with the description of the overlaying concept of Cyber Physical Production Systems (CPPSs). The analysis and evaluation of the specific properties of a sub-system using a condition monitoring system, important for the maintenance purposes, is then given for a wind turbine.

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Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.

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Using Macaulay's correspondence we study the family of Artinian Gorenstein local algebras with fixed symmetric Hilbert function decomposition. As an application we give a new lower bound for the dimension of cactus varieties of the third Veronese embedding. We discuss the case of cubic surfaces, where interesting phenomena occur.

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This paper focuses on computational models development and its applications on demand response, within smart grid scope. A prosumer model is presented and the corresponding economic dispatch problem solution is analyzed. The prosumer solar radiation production and energy consumption are forecasted by artificial neural networks. The existing demand response models are studied and a computational tool based on fuzzy clustering algorithm is developed and the results discussed. Consumer energy management applications within the InovGrid pilot project are presented. Computation systems are developed for the acquisition, monitoring, control and supervision of consumption data provided by smart meters, allowing the incorporation of consumer actions on their electrical energy management. An energy management system with integration of smart meters for energy consumers in a smart grid is developed.

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The scope of this dissertation is to study the transport phenomena of small molecules in polymers and membranes for gas separation applications, with particular attention to energy efficiency and environmental sustainability. This work seeks to contribute to the development of new competitive selective materials through the characterization of novel organic polymers such as CANALs and ROMPs, as well as through the combination of selective materials obtaining mixed matrix membranes (MMMs), to make membrane technologies competitive with the traditional ones. Kinetic and thermodynamic aspects of the transport properties were investigated in ideal and non-ideal scenarios, such as mixed-gas experiments. The information we gathered contributed to the development of the fundamental understanding related to phenomenon like CO2-induced plasticization and physical aging. Among the most significant results, ZIF-8/PPO MMMs provided materials whose permeability and selectivity were higher than those of the pure materials for He/CO2 separation. The CANALs featured norbornyl benzocyclobutene backbone and thereby introduced a third typology of ladder polymers in the gas separation field, expanding the structural diversity of microporous materials. CANALs have a completely hydrocarbon-based and non-polar rigid backbone, which makes them an ideal model system to investigate structure-property correlations. ROMPs were synthesized by means of the ring opening metathesis living polymerization, which allowed the formation of bottlebrush polymers. CF3-ROMP reveled to be ultrapermeable to CO2, with unprecedented plasticization resistance properties. Mixed-gas experiments in glassy polymer showed that solubility-selectivity controls the separation efficiency of materials in multicomponent conditions. Finally, it was determined that plasticization pressure in not an intrinsic property of a material and does not represent a state of the system, but rather comes from the contribution of solubility coefficient and diffusivity coefficient in the framework of the solution-diffusion model.

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This PhD project has been mainly focused on the synthesis of novel organic compounds containing heterocyclic and/or carbocyclic scaffold and on the study of stearic acid derivatives and their applications in biological field. The synthesis of novel derivatives of 9-hydroxystearic acid (9-HSA) evidenced how the presence of substituents on C9, able to make hydrogen bonds is of crucial importance for the biological activity. Also the position of the hydroxy group along the chain of hydroxystearic acids was investigated: regioisomers with the hydroxy group bound to odd carbons resulted more active than those bearing the hydroxy group on even carbons. Further, the insertion of (R)-9-HSA in magnetic nanoparticles gave a novel material which characterization remarked its suitability for drug delivery. Structural hybrids between amino aza-heterocycles and azelaic acid have been synthesized and some of them showed a selective activity towards osteosarcoma cell line U2OS. Several Apcin analogues bearing indole, benzothiazole, benzofurazan moieties connected to tryptaminyl-, amino pyridinyl-, pyrimidinyl- and pyrazinyl ring through a 1,1,1-trichloroethyl group were synthesized. Biological tests showed the importance of both the tryptaminyl and the pyrimidinyl moieties, confirming the effectiveness against acute leukemia models. The SNAr between 2-aminothiazole derivatives and 7-chlorodinitrobenzofuroxan revealed different behaviour depending from amino substituent of the thiazole. The reaction with 2-N-piperidinyl-, 2-N-morpholinyl-, or 2-N-pyrrolidinyl thiazole gave two isomeric species derived from the attack on C-5 of thiazole ring. Thiazoles substituted with primary- or not-cyclic secondary amines reacted with the exocyclic amino nitrogen atom giving a series of compounds whose biological activity have highlighted as they might be promising candidates for further development of antitumor agents. A series of 9-fluorenylidene derivatives, of interest in medical and optoelectronic field as organic scintillators, was synthesized through Wittig or Suzuky reaction and will be analyzed to test their potential scintillatory properties.

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The research project aims to improve the Design for Additive Manufacturing of metal components. Firstly, the scenario of Additive Manufacturing is depicted, describing its role in Industry 4.0 and in particular focusing on Metal Additive Manufacturing technologies and the Automotive sector applications. Secondly, the state of the art in Design for Additive Manufacturing is described, contextualizing the methodologies, and classifying guidelines, rules, and approaches. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened together with the Computer-Aided Technologies to support the approaches implementation. Therefore, a general Design for Additive Manufacturing workflow based on product and process optimization has been systematically defined. From the analysis of the state of the art, the use of a holistic approach has been considered fundamental and thus the use of integrated product-process design platforms has been evaluated as a key element for its development. Indeed, a computer-based methodology exploiting integrated tools and numerical simulations to drive the product and process optimization has been proposed. A validation of CAD platform-based approaches has been performed, as well as potentials offered by integrated tools have been evaluated. Concerning product optimization, systematic approaches to integrate topology optimization in the design have been proposed and validated through product optimization of an automotive case study. Concerning process optimization, the use of process simulation techniques to prevent manufacturing flaws related to the high thermal gradients of metal processes is developed, providing case studies to validate results compared to experimental data, and application to process optimization of an automotive case study. Finally, an example of the product and process design through the proposed simulation-driven integrated approach is provided to prove the method's suitability for effective redesigns of Additive Manufacturing based high-performance metal products. The results are then outlined, and further developments are discussed.

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Over the last decade, graphene and related materials (GRM) have drawn significant interest and resources for their development into the next generation of composite materials. This is because these nanoparticles have the ability to operate as reinforcing additives capable of imparting considerable mechanical property increases while also embedding multi-functional advantages on the host matrix. Because graphene and 2D materials are still in their early stages, the relative maturity of different types of composite systems varies. As a result, certain nanocomposite systems are currently commercially accessible, while others are not yet sufficiently developed to enter the market. A substantial emphasis has been placed on developing thermoplastic and thermosetting materials that combine a variety of mechanical and functional qualities. These include higher strength and stiffness, increased thermal and electrical conductivity, improved barrier properties, fire retardancy, and others, with the ultimate goal of providing multifunctionality to already employed composites. The work presented in this thesis investigates the use and benefits that GRM could bring to composites for a variety of applications, with the goal of realizing multifunctional components with improved properties that leads to lightweight and, as a result, energy and cost savings and pollution reduction in the environment. In particular, we worked on the following topics: • Benchmarking of commercial GRM-based master batches; • GRM-coatings for water uptake reduction; • GRM as thermo-electrical anti-icing /de-icing system; • GRM for Out of Oven curing of composites.

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In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

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The segment of the world population showing permanent or temporary lactose intolerance is quite significant. Because milk is a widely consumed food with an high nutritional value, technological alternatives have been sought to overcome this dilemma. Microfiltration combined with pasteurization can not only extend the shelf life of milk but can also maintain the sensory, functional, and nutritional properties of the product. This studied developed a pasteurized, microfiltered, lactose hydrolyzed (delactosed) skim milk (PMLHSM). Hydrolysis was performed using β-galactosidase at a concentration of 0.4mL/L and incubation for approximately 21h at 10±1°C. During these procedures, the degree of hydrolysis obtained (>90%) was accompanied by evaluation of freezing point depression, and the remaining quantity of lactose was confirmed by HPLC. Milk was processed using a microfiltration pilot unit equipped with uniform transmembrane pressure (UTP) ceramic membranes with a mean pore size of 1.4 μm and UTP of 60 kPa. The product was submitted to physicochemical, microbiological, and sensory evaluations, and its shelf life was estimated. Microfiltration reduced the aerobic mesophilic count by more than 4 log cycles. We were able to produce high-quality PMLHSM with a shelf life of 21 to 27d when stored at 5±1°C in terms of sensory analysis and proteolysis index and a shelf life of 50d in regard to total aerobic mesophile count and titratable acidity.