155 resultados para Experimental Analysis


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The ability to activate pro-matrix metalloproteinase (pro-MMP)-2 via membrane type-MMP is a hallmark of human breast cancer cell lines that show increased invasiveness, suggesting that MMP-2 contributes to human breast cancer progression. To investigate this, we have stably transfected pro-MMP-2 into the human breast cancer cell line MDA-MB-231, which lacks MMP-2 expression but does express its cell surface activator, membrane type 1-MMP. Multiple clones were derived and shown to produce pro-MMP-2 and to activate it in response to concanavalin A. In vitro analysis showed that the pro-MMP-2-transfected clones exhibited an increased invasive potential in Boyden chamber and Matrigel outgrowth assays, compared with the parental cells or those transfected with vector only. When inoculated into the mammary fat pad of nude mice, each of the MMP-2-tranfected clones grew faster than each of the vector controls tested. After intracardiac inoculation into nude mice, pro-MMP-2-transfected clones showed a significant increase in the incidence of metastasis to brain, liver, bone, and kidney compared with the vector control clones but not lung. Increased tumor burden was seen in the primary site and in lung metastases, and a trend toward increased burden was seen in bone, however, no change was seen in brain, liver, or kidney. This data supports a role for MMP-2 in breast cancer progression, both in the growth of primary tumors and in their spread to distant organs. MMP-2 may be a useful target for breast cancer therapy when refinement of MMP inhibitors provides for MMP-specific agents.

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Electrospray ionisation tandem mass spectrometry has allowed the unambiguous identification and quantification of individual lens phospholipids in human and six animal models. Using this approach ca. 100 unique phospholipids have been characterised. Parallel analysis of the same lens extracts by a novel direct-insertion electron-ionization technique found the cholesterol content of human lenses to be significantly higher (ca. 6 times) than lenses from the other animals. The most abundant phospholipids in all the lenses examined were choline-containing phospholipids. In rat, mouse, sheep, cow, pig and chicken, these were present largely as phosphatidylcholines, in contrast 66% of the total phospholipid in Homo sapiens was sphingomyelin, with the most abundant being dihydrosphingomyelins, in particular SM(d18:0/16:0) and SM(d18:0/24:1). The abundant glycerophospholipids within human lenses were found to be predominantly phosphatidylethanolamines and phosphatidylserines with surprisingly high concentrations of ether-linked alkyl chains identified in both classes. This study is the first to identify the phospholipid class (head-group) and assign the constituent fatty acid(s) for each lipid molecule and to quantify individual lens phospholipids using internal standards. These data clearly indicate marked differences in the membrane lipid composition of the human lens compared to commonly used animal models and thus predict a significant variation in the membrane properties of human lens fibre cells compared to those of other animals. © 2008 Elsevier B.V. All rights reserved.

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In the TREC Web Diversity track, novelty-biased cumulative gain (α-NDCG) is one of the official measures to assess retrieval performance of IR systems. The measure is characterised by a parameter, α, the effect of which has not been thoroughly investigated. We find that common settings of α, i.e. α=0.5, may prevent the measure from behaving as desired when evaluating result diversification. This is because it excessively penalises systems that cover many intents while it rewards those that redundantly cover only few intents. This issue is crucial since it highly influences systems at top ranks. We revisit our previously proposed threshold, suggesting α be set on a query-basis. The intuitiveness of the measure is then studied by examining actual rankings from TREC 09-10 Web track submissions. By varying α according to our query-based threshold, the discriminative power of α-NDCG is not harmed and in fact, our approach improves α-NDCG's robustness. Experimental results show that the threshold for α can turn the measure to be more intuitive than using its common settings.

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In this paper, we present fully Bayesian experimental designs for nonlinear mixed effects models, in which we develop simulation-based optimal design methods to search over both continuous and discrete design spaces. Although Bayesian inference has commonly been performed on nonlinear mixed effects models, there is a lack of research into performing Bayesian optimal design for nonlinear mixed effects models that require searches to be performed over several design variables. This is likely due to the fact that it is much more computationally intensive to perform optimal experimental design for nonlinear mixed effects models than it is to perform inference in the Bayesian framework. In this paper, the design problem is to determine the optimal number of subjects and samples per subject, as well as the (near) optimal urine sampling times for a population pharmacokinetic study in horses, so that the population pharmacokinetic parameters can be precisely estimated, subject to cost constraints. The optimal sampling strategies, in terms of the number of subjects and the number of samples per subject, were found to be substantially different between the examples considered in this work, which highlights the fact that the designs are rather problem-dependent and require optimisation using the methods presented in this paper.

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This paper introduces a novel cage induction generator and presents a mathematical model, through which its behavior can be accurately predicted. The proposed generator system employs a three-phase cage induction machine and generates single-phase and constant-frequency electricity at varying rotor speeds without an intermediate inverter stage. The technique uses any one of the three stator phases of the machine as the excitation winding and the remaining two phases, which are connected in series, as the power winding. The two-series-connected-and-one-isolated (TSCAOI) phase winding configuration magnetically decouples the two sets of windings, enabling independent control. Electricity is generated through the power winding at both sub- and super-synchronous speeds with appropriate excitation to the isolated single winding at any frequency of generation. A dynamic mathematical model, which accurately predicts the behavior of the proposed generator, is also presented and implemented in MATLAB/Simulink. Experimental results of a 2-kW prototype generator under various operating conditions are presented, together with theoretical results, to demonstrate the viability of the TSCAOI power generation. The proposed generator is simple and capable of both storage and retrieval of energy through its excitation winding and is expected to be suitable for applications, such as small wind turbines and microhydro systems.

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A combined experimental and numerical program was conducted to study the in-plane shear behaviour of hollow concrete masonry panels containing reinforced grout cores. This paper is focused on the numerical program. A two dimensional macromodelling strategy was used to simulate the behaviour of the confined masonry (CM) shear panels. Both the unreinforced masonry and the confining element were modelled using macromasonry properties and the steel reinforcement was modelled as an embedded truss element located within the grout using perfectly bonded constraint. The FE model reproduced key behaviours observed in the experiments, including the shear strength, the deformation and the crack patterns of the unconfined and confined masonry panels. The predictions of the validated model were used to evaluate the existing in-plane shear expressions available in the national masonry standards and research publications.

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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

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Continuous monitoring of diesel engine performance is critical for early detection of fault developments in an engine before they materialize into a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few nonintrusive condition monitoring techniques that can be utilized for such a task. Furthermore, the technique is more suitable for mass industry deployments than other non-intrusive methods such as vibration and acoustic emission techniques due to the low instrumentation cost, smaller data size and robust signal clarity since IAS is not affected by the engine operation noise and noise from the surrounding environment. A combination of IAS and order analysis was employed in this experimental study and the major order component of the IAS spectrum was used for engine loading estimation and fault diagnosis of a four-stroke four-cylinder diesel engine. It was shown that IAS analysis can provide useful information about engine speed variation caused by changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectra directly associated with the engine firing frequency (at twice the mean shaft rotating speed) can be utilized to estimate engine loading condition regardless of whether the engine is operating at healthy condition or with faults. The amplitude of this order component follows a distinctive exponential curve as the loading condition changes. A mathematical relationship was then established in the paper to estimate the engine power output based on the amplitude of this order component of the IAS spectrum. It was further illustrated that IAS technique can be employed for the detection of a simulated exhaust valve fault in this study.

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Albumin binds low–molecular-weight molecules, including proteins and peptides, which then acquire its longer half-life, thereby protecting the bound species from kidney clearance. We developed an experimental method to isolate albumin in its native state and to then identify [mass spectrometry (MS) sequencing] the corresponding bound low–molecular-weight molecules. We used this method to analyze pooled sera from a human disease study set (high-risk persons without cancer, n= 40; stage I ovarian cancer, n = 30; stage III ovarian cancer, n = 40) to demonstrate the feasibility of this approach as a discovery method. Methods Albumin was isolated by solid-phase affinity capture under native binding and washing conditions. Captured albumin-associated proteins and peptides were separated by gel electrophoresis and subjected to iterative MS sequencing by microcapillary reversed-phase tandem MS. Selected albumin-bound protein fragments were confirmed in human sera by Western blotting and immunocompetition. Results In total, 1208 individual protein sequences were predicted from all 3 pools. The predicted sequences were largely fragments derived from proteins with diverse biological functions. More than one third of these fragments were identified by multiple peptide sequences, and more than one half of the identified species were in vivo cleavage products of parent proteins. An estimated 700 serum peptides or proteins were predicted that had not been reported in previous serum databases. Several proteolytic fragments of larger molecules that may be cancer-related were confirmed immunologically in blood by Western blotting and peptide immunocompetition. BRCA2, a 390-kDa low-abundance nuclear protein linked to cancer susceptibility, was represented in sera as a series of specific fragments bound to albumin. Conclusion Carrier-protein harvesting provides a rich source of candidate peptides and proteins with potential diverse tissue and cellular origins that may reflect important disease-related information.

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This paper presents a comprehensive numerical procedure to treat the blast response of laminated glass (LG) panels and studies the influence of important material parameters. Post-crack behaviour of the LG panel and the contribution of the interlayer towards blast resistance are treated. Modelling techniques are validated by comparing with existing experimental results. Findings indicate that the tensile strength of glass considerably influences the blast response of LG panels while the interlayer material properties have a major impact on the response under higher blast loads. Initially, glass panes absorb most of the blast energy, but after the glass breaks, interlayer deforms further and absorbs most of the blast energy. LG panels should be designed to fail by tearing of the interlayer rather than failure at the supports to achieve a desired level of protection. From this aspect, material properties of glass, interlayer and sealant joints play important roles, but unfortunately they are not accounted for in the current design standards. The new information generated in this paper will enhance the capabilities of engineers to better design LG panels under blast loads and use better materials to improve the blast response of LG panels.

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Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.

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Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

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Stormwater bioretention basins are subjected to spontaneous intermittent wetting and drying, unlike water treatment filter systems that are subjected to continuous feed. Drinking water filters when constructed new or after back-wash, are subjected to a phase of stabilization. Experiments show that bioretention basins are similarly impacted by intermittent wetting and drying. The common parameter monitored in the stabilisation of filters is the concentration of total solids in the outflow. Filter media in bioretention basins however, consists of a mix of particulate organic matter and fine sand. Organic carbon and solids are therefore needed to be monitored. Four Perspex bioretention filter columns of 94 mm (ID) were packed with a filter layer (800 mm), transition layer and a gravel layer and operated with synthetic stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. Synthetic stormwater was prepared by adding NH4NO3 (ammonium nitrate) and C2H5NO2 (glycine) and a mixture of kaolinite and montmorillonite clay, to tapwater. The columns were fed with synthetic stormwater with different Antecedent Dry Days (ADD) (0 – 25 day) and constant inflow concentration (2 ppm: nitrate-nitrogen, 1.5 ppm: ammonium-nitrogen, 2.5 ppm: organic-nitrogen 100 ppm: total suspended solids and 7 ppm: organic carbon) at a feed rate of 100mL.min (85.7cm/h). Samples were collected from the outflow at different time intervals between 2 – 150 min from the start of outflow and were tested for Total Suspended Solids (TSS) and Total Organic Carbon (TOC). Both TSS and TOC concentrations in the outflow were observed to be much higher than the concentration of both the parameters in the inflow during the stabilisation period indicating a phase of wash-off (first flush) which lasted for approximately 30 min for both parameters at the beginning of each storm event. The wash-off of TSS and TOC were found to be highly variable depending on the age of the filter and the number of antecedent dry days. The duration of stabilisation phase in the experiments is significant compared with many of the stormwater events. A computational analysis on total mass of each pollutant further affirmed the significance of the first flush of an event on removal of these pollutants. Therefore, the kinetics of the first flush in the stabilisation phase needs to be considered in the performance analysis of the systems.

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Portable, water filled road safety barriers are used to provide protection and reduce the potential hazard due to errant vehicles in areas where the road conditions change frequently (e.g. near road work sites). As part of an effort to reduce excessive working widths typical of these systems, a study was conducted to assess the effectiveness of introducing polymeric foam filled panels into the design. Surrogate impact tests of a design typical of such as barrier system were conducted utilising a pneumatically powered horizontal impact testing machine up to impact energies of 7.40 kJ. Results of these tests are utilised to examine the barrier behaviour, in addition to being used to validate a couple FE/SPH model of the barrier system. Once validated, the FE/SPH model it utilised as the basis for a parametric study into the efficacy and effects of the inclusion of polymeric foam filled panels on the performance of portable water filled road safety barriers. It was found that extruded polystyrene foam functioned well, with a greater thickness of the foam panel significantly reducing the impacting body velocity as the barrier began to translate.