8 resultados para Evaluation of different sources of proteins

em Cambridge University Engineering Department Publications Database


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A multi-disciplinary team based at Heriot-Watt University and other Universities has been set up to tackle the design and manufacturing of lab-on-a-chip for industries as one of the demonstrators of the EPSRC Grand Challenge project "3D-Mintegration". The team focuses on the analysis of foetal genetic material extracted from maternal blood as a smart alternative to invasive prenatal testing such as amniocentesis. The first module of the microsystem envisaged achieves a separation of blood cells from plasma. This system permits the testing of different manufacturing techniques.

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Using spcctroscopic ellipsometry (SE), we have measured the optical properties and optical gaps of a series of amorphous carbon (a-C) films ∼ 100-300 Å thick, prepared using a filtered beam of C+ ions from a cathodic arc. Such films exhibit a wide range of sp3-bonded carbon contents from 20 to 76 at.%, as measured by electron energy loss spectroscopy (EELS). The Taue optical gaps of the a-C films increase monotonically from 0.65 eV for 20 at.% sp3 C to 2.25 eV for 76 at.% sp3 C. Spectra in the ellipsometric angles (1.5-5 eV) have been analyzed using different effective medium theories (EMTs) applying a simplified optical model for the dielectric function of a-C, assuming a composite material with sp2 C and sp3 C components. The most widely used EMT, namely that of Bruggeman (with three-dimensionally isotropic screening), yields atomic fractions of sp3 C that correlate monotonically with those obtained from EELS. The results of the SE analysis, however, range from 10 to 25 at.% higher than those from EELS. In fact, we have found that the volume percent sp3 C from SE using the Bruggeman EMT shows good numerical agreement with the atomic percent sp3 C from EELS. The SE-EELS discrepancy has been reduced by using an optical model in which the dielectric function of the a-C is determined as a volume-fraction-weighted average of the dielectric functions of the sp2 C and sp3 C components. © 1998 Elsevier Science S.A.

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We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

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An experimental evaluation of small two-phase induction motor drives operating with different inverter topologies is described. Results show that a PWM-based four-switch inverter, having only low-side switches is attractive for high-speed low-cost applications where speeds greater than those that can be obtained using single phase induction motors are required.

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We systematically study the growth of carbon nanotube forests by chemical vapor deposition using evaporated monometallic or bimetallic Ni, Co, or Fe films supported on alumina. Our results show two regimes of catalytic activity. When the total thickness of catalyst is larger than nominally 1nm, bimetallic catalysts tend to outperform the equivalent layers of a single metal, yielding taller forests of multi-walled carbon nanotubes (CNTs). In contrast, for layers thinner than ~1nm, bimetallic catalysts are notably less active than individually. However, the amount of small diameter and single-walled CNTs is significantly increased. This possible transition at ~1nm might be related to different catalyst composition after annealing, depending whether or not the films overlap during evaporation and alloy during catalyst formation. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Humans appear to be sensitive to relative small changes in their surroundings. These changes are often initially perceived as irrelevant, but they can cause significant changes in behavior. However, how exactly people's behavior changes is often hard to quantify. A reliable and valid tool is needed in order to address such a question, ideally measuring an important point of interaction, such as the hand. Wearable-body-sensor systems can be used to obtain valuable, behavioral information. These systems are particularly useful for assessing functional interactions that occur between the endpoints of the upper limbs and our surroundings. A new method is explored that consists of computing hand position using a wearable sensor system and validating it against a gold standard reference measurement (optical tracking device). Initial outcomes related well to the gold standard measurements (r = 0.81) showing an acceptable average root mean square error of 0.09 meters. Subsequently, the use of this approach was further investigated by measuring differences in motor behavior, in response to a changing environment. Three subjects were asked to perform a water pouring task with three slightly different containers. Wavelet analysis was introduced to assess how motor consistency was affected by these small environmental changes. Results showed that the behavioral motor adjustments to a variable environment could be assessed by applying wavelet coherence techniques. Applying these procedures in everyday life, combined with correct research methodologies, can assist in quantifying how environmental changes can cause alterations in our motor behavior.

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We present the development of a drug-loaded triple-layer platform consisting of thin film biodegradable polymers, in a properly designed form for the desired gradual degradation. Poly(dl-lactide-co-glycolide) (PLGA (65:35), PLGA (75:25)) and polycaprolactone (PCL) were grown by spin coating technique, to synthesize the platforms with the order PCL/PLGA (75:25)/PLGA (65:35) that determine their degradation rates. The outer PLGA (65:35) layer was loaded with dipyridamole, an antiplatelet drug. Spectroscopic ellipsometry (SE) in the Vis-far UV range was used to determine the nanostructure, as well as the content of the incorporated drug in the as-grown platforms. In situ and real-time SE measurements were carried out using a liquid cell for the dynamic evaluation of the fibrinogen and albumin protein adsorption processes. Atomic force microscopy studies justified the SE results concerning the nanopores formation in the polymeric platforms, and the dominant adsorption mechanisms of the proteins, which were defined by the drug incorporation in the platforms. © 2013 Elsevier B.V. All rights reserved.

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© 2014 AIP Publishing LLC. Superparamagnetic nanoparticles are employed in a broad range of applications that demand detailed magnetic characterization for superior performance, e.g., in drug delivery or cancer treatment. Magnetic hysteresis measurements provide information on saturation magnetization and coercive force for bulk material but can be equivocal for particles having a broad size distribution. Here, first-order reversal curves (FORCs) are used to evaluate the effective magnetic particle size and interaction between equally sized magnetic iron oxide (Fe2O3) nanoparticles with three different morphologies: (i) pure Fe2O3, (ii) Janus-like, and (iii) core/shell Fe2O3/SiO2synthesized using flame technology. By characterizing the distribution in coercive force and interaction field from the FORC diagrams, we find that the presence of SiO2in the core/shell structures significantly reduces the average coercive force in comparison to the Janus-like Fe2O3/SiO2and pure Fe2O3particles. This is attributed to the reduction in the dipolar interaction between particles, which in turn reduces the effective magnetic particle size. Hence, FORC analysis allows for a finer distinction between equally sized Fe2O3particles with similar magnetic hysteresis curves that can significantly influence the final nanoparticle performance.