936 resultados para Chemical etching method combining static etching and dynamic etching


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Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

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A compilation of chemical analyses of Pacific Ocean nodules using an x-ray fluorescence technique. The equipment used was a General Electric XRD-5 with a tungsten tube. Lithium fluoride was used as the diffraction element in assaying for all elements above calcium in the atomic table and EDDT was used in conjunction with a helium path for all elements with an atomic number less than calcium. Flow counters were used in conjunction with a pulse height analyzer to eliminate x-ray lines of different but integral orders in gathering count data. The stability of the equipment was found to be excellent by the author. The equipment was calibrated by the use of standard ores made from pure oxide forms of the elements in the nodules and carefully mixed in proportion to the amounts of these elements generally found in the manganese nodules. Chemically analyzed standards of the nodules themselves were also used. As a final check, a known amount of the element in question was added to selected samples of the nodules and careful counts were taken on these samples before and after the addition of the extra amount of the element. The method involved the determination and subsequent use of absorption and activation factors for the lines of the various elements. All the absorption and activation factors were carefully determined using the standard ores. The chemically analyzed samples of the nodules by these methods yielded an accuracy to at least three significant figures.

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Nucleic acids (DNA and RNA) play essential roles in the central dogma of biology for the storage and transfer of genetic information. The unique chemical and conformational structures of nucleic acids – the double helix composed of complementary Watson-Crick base pairs, provide the structural basis to carry out their biological functions. DNA double helix can dynamically accommodate Watson-Crick and Hoogsteen base-pairing, in which the purine base is flipped by ~180° degrees to adopt syn rather than anti conformation as in Watson-Crick base pairs. There is growing evidence that Hoogsteen base pairs play important roles in DNA replication, recognition, damage or mispair accommodation and repair. Here, we constructed a database for existing Hoogsteen base pairs in DNA duplexes by a structure-based survey from the Protein Data Bank, and structural analyses based on the resulted Hoogsteen structures revealed that Hoogsteen base pairs occur in a wide variety of biological contexts and can induce DNA kinking towards the major groove. As there were documented difficulties in modeling Hoogsteen or Watson-Crick by crystallography, we collaborated with the Richardsons’ lab and identified potential Hoogsteen base pairs that were mis-modeled as Watson-Crick base pairs which suggested that Hoogsteen can be more prevalent than it was thought to be. We developed solution NMR method combined with the site-specific isotope labeling to characterize the formation of, or conformational exchange with Hoogsteen base pairs in large DNA-protein complexes under solution conditions, in the absence of the crystal packing force. We showed that there are enhanced chemical exchange, potentially between Watson-Crick and Hoogsteen, at a sharp kink site in the complex formed by DNA and the Integration Host Factor protein. In stark contrast to B-form DNA, we found that Hoogsteen base pairs are strongly disfavored in A-form RNA duplex. Chemical modifications N1-methyl adenosine and N1-methyl guanosine that block Watson-Crick base-pairing, can be absorbed as Hoogsteen base pairs in DNA, but rather potently destabilized A-form RNA and caused helix melting. The intrinsic instability of Hoogsteen base pairs in A-form RNA endows the N1-methylation as a functioning post-transcriptional modification that was known to facilitate RNA folding, translation and potentially play roles in the epitranscriptome. On the other hand, the dynamic property of DNA that can accommodate Hoogsteen base pairs could be critical to maintaining the genome stability.

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Ankle sprains are the most common injuries in sports, usually causing damage to the lateral ligaments. Recurrence has as usual result permanent instability, and thus loss of proprioception. This fact, together with residual symptoms, is what is known as chronic ankle instability, CAI, or FAI, if it is functional. This problem tries to be solved by improving musculoskeletal stability and proprioception by the application of bandages and performing exercises. The aim of this study has been to review articles (meta-analisis, systematic reviews and revisions) published in 2009-2015 in PubMed, Medline, ENFISPO and BUCea, using keywords such as “sprain instability”, “sprain proprioception”, “chronic ankle instability”. Evidence affirms that there does exist decreased proprioception in patients who suffer from CAI. Rehabilitation exercise regimen is indicated as a treatment because it generates a subjective improvement reported by the patient, and the application of bandages works like a sprain prevention method limiting the range of motion, reducing joint instability and increasing confidence during exercise. As podiatrists we should recommend proprioception exercises to all athletes in a preventive way, and those with CAI or FAI, as a rehabilitation programme, together with the application of bandages. However, further studies should be generated focusing on ways of improving proprioception, and on the exercise patterns that provide the maximum benefit.

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The dynamics, shape, deformation, and orientation of red blood cells in microcirculation affect the rheology, flow resistance and transport properties of whole blood. This leads to important correlations of cellular and continuum scales. Furthermore, the dynamics of RBCs subject to different flow conditions and vessel geometries is relevant for both fundamental research and biomedical applications (e.g drug delivery). In this thesis, the behaviour of RBCs is investigated for different flow conditions via computer simulations. We use a combination of two mesoscopic particle-based simulation techniques, dissipative particle dynamics and smoothed dissipative particle dynamics. We focus on the microcapillary scale of several μm. At this scale, blood cannot be considered at the continuum but has to be studied at the cellular level. The connection between cellular motion and overall blood rheology will be investigated. Red blood cells are modelled as viscoelastic objects interacting hydrodynamically with a viscous fluid environment. The properties of the membrane, such as resistance against bending or shearing, are set to correspond to experimental values. Furthermore, thermal fluctuations are considered via random forces. Analyses corresponding to light scattering measurements are performed in order to compare to experiments and suggest for which situations this method is suitable. Static light scattering by red blood cells characterises their shape and allows comparison to objects such as spheres or cylinders, whose scattering signals have analytical solutions, in contrast to those of red blood cells. Dynamic light scattering by red blood cells is studied concerning its suitability to detect and analyse motion, deformation and membrane fluctuations. Dynamic light scattering analysis is performed for both diffusing and flowing cells. We find that scattering signals depend on various cell properties, thus allowing to distinguish different cells. The scattering of diffusing cells allows to draw conclusions on their bending rigidity via the effective diffusion coefficient. The scattering of flowing cells allows to draw conclusions on the shear rate via the scattering amplitude correlation. In flow, a RBC shows different shapes and dynamic states, depending on conditions such as confinement, physiological/pathological state and cell age. Here, two essential flow conditions are studied: simple shear flow and tube flow. Simple shear flow as a basic flow condition is part of any more complex flow. The velocity profile is linear and shear stress is homogeneous. In simple shear flow, we find a sequence of different cell shapes by increasing the shear rate. With increasing shear rate, we find rolling cells with cup shapes, trilobe shapes and quadrulobe shapes. This agrees with recent experiments. Furthermore, the impact of the initial orientation on the dynamics is studied. To study crowding and collective effects, systems with higher haematocrit are set up. Tube flow is an idealised model for the flow through cylindric microvessels. Without cell, a parabolic flow profile prevails. A single red blood cell is placed into the tube and subject to a Poiseuille profile. In tube flow, we find different cell shapes and dynamics depending on confinement, shear rate and cell properties. For strong confinements and high shear rates, we find parachute-like shapes. Although not perfectly symmetric, they are adjusted to the flow profile and maintain a stationary shape and orientation. For weak confinements and low shear rates, we find tumbling slippers that rotate and moderately change their shape. For weak confinements and high shear rates, we find tank-treading slippers that oscillate in a limited range of inclination angles and strongly change their shape. For the lowest shear rates, we find cells performing a snaking motion. Due to cell properties and resultant deformations, all shapes differ from hitherto descriptions, such as steady tank-treading or symmetric parachutes. We introduce phase diagrams to identify flow regimes for the different shapes and dynamics. Changing cell properties, the regime borders in the phase diagrams change. In both flow types, both the viscosity contrast and the choice of stress-free shape are important. For in vitro experiments, the solvent viscosity has often been higher than the cytosol viscosity, leading to a different pattern of dynamics, such as steady tank-treading. The stress-free state of a RBC, which is the state at zero shear stress, is still controversial, and computer simulations enable direct comparisons of possible candidates in equivalent flow conditions.

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This chapter describes a parallel optimization technique that incorporates a distributed load-balancing algorithm and provides an extremely fast solution to the problem of load-balancing adaptive unstructured meshes. Moreover, a parallel graph contraction technique can be employed to enhance the partition quality and the resulting strategy outperforms or matches results from existing state-of-the-art static mesh partitioning algorithms. The strategy can also be applied to static partitioning problems. Dynamic procedures have been found to be much faster than static techniques, to provide partitions of similar or higher quality and, in comparison, involve the migration of a fraction of the data. The method employs a new iterative optimization technique that balances the workload and attempts to minimize the interprocessor communications overhead. Experiments on a series of adaptively refined meshes indicate that the algorithm provides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more quickly. The dynamic evolution of load has three major influences on possible partitioning techniques; cost, reuse, and parallelism. The unstructured mesh may be modified every few time-steps and so the load-balancing must have a low cost relative to that of the solution algorithm in between remeshing.

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Vector-borne disease emergence in recent decades has been associated with different environmental drivers including changes in habitat, hosts and climate. Lyme borreliosis is among the most important vector-borne diseases in the Northern hemisphere and is an emerging disease in Scotland. Transmitted by Ixodid tick vectors between large numbers of wild vertebrate host species, Lyme borreliosis is caused by bacteria from the Borrelia burgdorferi sensu lato species group. Ecological studies can inform how environmental factors such as host abundance and community composition, habitat and landscape heterogeneity contribute to spatial and temporal variation in risk from B. burgdorferi s.l. In this thesis a range of approaches were used to investigate the effects of vertebrate host communities and individual host species as drivers of B. burgdorferi s.l. dynamics and its tick vector Ixodes ricinus. Host species differ in reservoir competence for B. burgdorferi s.l. and as hosts for ticks. Deer are incompetent transmission hosts for B. burgdorferi s.l. but are significant hosts of all life-stages of I. ricinus. Rodents and birds are important transmission hosts of B. burgdorferi s.l. and common hosts of immature life-stages of I. ricinus. In this thesis, surveys of woodland sites revealed variable effects of deer density on B. burgdorferi prevalence, from no effect (Chapter 2) to a possible ‘dilution’ effect resulting in lower prevalence at higher deer densities (Chapter 3). An invasive species in Scotland, the grey squirrel (Sciurus carolinensis), was found to host diverse genotypes of B. burgdorferi s.l. and may act as a spill-over host for strains maintained by native host species (Chapter 4). Habitat fragmentation may alter the dynamics of B. burgdorferi s.l. via effects on the host community and host movements. In this thesis, there was lack of persistence of the rodent associated genospecies of B. burgdorferi s.l. within a naturally fragmented landscape (Chapter 3). Rodent host biology, particularly population cycles and dispersal ability are likely to affect pathogen persistence and recolonization in fragmented habitats. Heterogeneity in disease dynamics can occur spatially and temporally due to differences in the host community, habitat and climatic factors. Higher numbers of I. ricinus nymphs, and a higher probability of detecting a nymph infected with B. burgdorferi s.l., were found in areas with warmer climates estimated by growing degree days (Chapter 2). The ground vegetation type associated with the highest number of I. ricinus nymphs varied between studies in this thesis (Chapter 2 & 3) and does not appear to be a reliable predictor across large areas. B. burgdorferi s.l. prevalence and genospecies composition was highly variable for the same sites sampled in subsequent years (Chapter 2). This suggests that dynamic variables such as reservoir host densities and deer should be measured as well as more static habitat and climatic factors to understand the drivers of B. burgdorferi s.l. infection in ticks. Heterogeneity in parasite loads amongst hosts is a common finding which has implications for disease ecology and management. Using a 17-year data set for tick infestations in a wild bird community in Scotland, different effects of age and sex on tick burdens were found among four species of passerine bird (Chapter 5). There were also different rates of decline in tick burdens among bird species in response to a long term decrease in questing tick pressure over the study. Species specific patterns may be driven by differences in behaviour and immunity and highlight the importance of comparative approaches. Combining whole genome sequencing (WGS) and population genetics approaches offers a novel approach to identify ecological drivers of pathogen populations. An initial analysis of WGS from B. burgdorferi s.s. isolates sampled 16 years apart suggests that there is a signal of measurable evolution (Chapter 6). This suggests demographic analyses may be applied to understand ecological and evolutionary processes of these bacteria. This work shows how host communities, habitat and climatic factors can affect the local transmission dynamics of B. burgdorferi s.l. and the potential risk of infection to humans. Spatial and temporal heterogeneity in pathogen dynamics poses challenges for the prediction of risk. New tools such as WGS of the pathogen (Chapter 6) and blood meal analysis techniques will add power to future studies on the ecology and evolution of B. burgdorferi s.l.

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We estimate a dynamic model of mortgage default for a cohort of Colombian debtors between 1997 and 2004. We use the estimated model to study the effects on default of a class of policies that affected the evolution of mortgage balances in Colombia during the 1990's. We propose a framework for estimating dynamic behavioral models accounting for the presence of unobserved state variables that are correlated across individuals and across time periods. We extend the standard literature on the structural estimation of dynamic models by incorporating an unobserved common correlated shock that affects all individuals' static payoffs and the dynamic continuation payoffs associated with different decisions. Given a standard parametric specification the dynamic problem, we show that the aggregate shocks are identified from the variation in the observed aggregate behavior. The shocks and their transition are separately identified, provided there is enough cross-sectionavl ariation of the observeds tates.

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Tese de Doutoramento, Ciências do Mar da Terra e do Ambiente, Ramo: Ciências e Tecnologias do Ambiente, Especialidade em Biotecnologia, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

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Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

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With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

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In the presented thesis work, the meshfree method with distance fields was coupled with the lattice Boltzmann method to obtain solutions of fluid-structure interaction problems. The thesis work involved development and implementation of numerical algorithms, data structure, and software. Numerical and computational properties of the coupling algorithm combining the meshfree method with distance fields and the lattice Boltzmann method were investigated. Convergence and accuracy of the methodology was validated by analytical solutions. The research was focused on fluid-structure interaction solutions in complex, mesh-resistant domains as both the lattice Boltzmann method and the meshfree method with distance fields are particularly adept in these situations. Furthermore, the fluid solution provided by the lattice Boltzmann method is massively scalable, allowing extensive use of cutting edge parallel computing resources to accelerate this phase of the solution process. The meshfree method with distance fields allows for exact satisfaction of boundary conditions making it possible to exactly capture the effects of the fluid field on the solid structure.

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In this research the integration of nanostructures and micro-scale devices was investigated using silica nanowires to develop a simple yet robust nanomanufacturing technique for improving the detection parameters of chemical and biological sensors. This has been achieved with the use of a dielectric barrier layer, to restrict nanowire growth to site-specific locations which has removed the need for post growth processing, by making it possible to place nanostructures on pre-pattern substrates. Nanowires were synthesized using the Vapor-Liquid-Solid growth method. Process parameters (temperature and time) and manufacturing aspects (structural integrity and biocompatibility) were investigated. Silica nanowires were observed experimentally to determine how their physical and chemical properties could be tuned for integration into existing sensing structures. Growth kinetic experiments performed using gold and palladium catalysts at 1050 ˚C for 60 minutes in an open-tube furnace yielded dense and consistent silica nanowire growth. This consistent growth led to the development of growth model fitting, through use of the Maximum Likelihood Estimation (MLE) and Bayesian hierarchical modeling. Transmission electron microscopy studies revealed the nanowires to be amorphous and X-ray diffraction confirmed the composition to be SiO2 . Silica nanowires were monitored in epithelial breast cancer media using Impedance spectroscopy, to test biocompatibility, due to potential in vivo use as a diagnostic aid. It was found that palladium catalyzed silica nanowires were toxic to breast cancer cells, however, nanowires were inert at 1µg/mL concentrations. Additionally a method for direct nanowire integration was developed that allowed for silica nanowires to be grown directly into interdigitated sensing structures. This technique eliminates the need for physical nanowire transfer thus preserving nanowire structure and performance integrity and further reduces fabrication cost. Successful nanowire integration was physically verified using Scanning electron microscopy and confirmed electrically using Electrochemical Impedance Spectroscopy of immobilized Prostate Specific Antigens (PSA). The experiments performed above serve as a guideline to addressing the metallurgic challenges in nanoscale integration of materials with varying composition and to understanding the effects of nanomaterials on biological structures that come in contact with the human body.

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Power system policies are broadly on track to escalate the use of renewable energy resources in electric power generation. Integration of dispersed generation to the utility network not only intensifies the benefits of renewable generation but also introduces further advantages such as power quality enhancement and freedom of power generation for the consumers. However, issues arise from the integration of distributed generators to the existing utility grid are as significant as its benefits. The issues are aggravated as the number of grid-connected distributed generators increases. Therefore, power quality demands become stricter to ensure a safe and proper advancement towards the emerging smart grid. In this regard, system protection is the area that is highly affected as the grid-connected distributed generation share in electricity generation increases. Islanding detection, amongst all protection issues, is the most important concern for a power system with high penetration of distributed sources. Islanding occurs when a portion of the distribution network which includes one or more distributed generation units and local loads is disconnected from the remaining portion of the grid. Upon formation of a power island, it remains energized due to the presence of one or more distributed sources. This thesis introduces a new islanding detection technique based on an enhanced multi-layer scheme that shows superior performance over the existing techniques. It provides improved solutions for safety and protection of power systems and distributed sources that are capable of operating in grid-connected mode. The proposed active method offers negligible non-detection zone. It is applicable to micro-grids with a number of distributed generation sources without sacrificing the dynamic response of the system. In addition, the information obtained from the proposed scheme allows for smooth transition to stand-alone operation if required. The proposed technique paves the path towards a comprehensive protection solution for future power networks. The proposed method is converter-resident and all power conversion systems that are operating based on power electronics converters can benefit from this method. The theoretical analysis is presented, and extensive simulation results confirm the validity of the analytical work.

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Despite the development of improved performance test protocols by renowned researchers, there are still road networks which experience premature cracking and failure. One area of major concern in asphalt science and technology, especially in cold regions in Canada is thermal (low temperature) cracking. Usually right after winter periods, severe cracks are seen on poorly designed road networks. Quality assurance tests based on improved asphalt performance protocols have been implemented by government agencies to ensure that roads being constructed are at the required standard but asphalt binders that pass these quality assurance tests still crack prematurely. While it would be easy to question the competence of the quality assurance test protocols, it should be noted that performance tests which are being used and were repeated in this study, namely the extended bending beam rheometer (EBBR) test, double edge-notched tension test (DENT), dynamic shear rheometer (DSR) test and X-ray fluorescence (XRF) analysis have all been verified and proven to successfully predict asphalt pavement behaviour in the field. Hence this study looked to probe and test the quality and authenticity of the asphalt binders being used for road paving. This study covered thermal cracking and physical hardening phenomenon by comparing results from testing asphalt binder samples obtained from the storage ‘tank’ prior to paving (tank samples) and recovered samples for the same contracts with aim of explaining why asphalt binders that have passed quality assurance tests are still prone to fail prematurely. The study also attempted to find out if the short testing time and automated procedure of torsion bar experiments can replace the established but tedious procedure of the EBBR. In the end, it was discovered that significant differences in performance and composition exist between tank and recovered samples for the same contracts. Torsion bar experimental data also indicated some promise in predicting physical hardening.