985 resultados para Fusion Method


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The DNA binding fusion protein, LacI-His6-GFP, together with the conjugate PEG-IDA-Cu(II) (10 kDa) was evaluated as a dual affinity system for the pUC19 plasmid extraction from an alkaline bacterial cell lysate in poly(ethylene glycol) (PEG)/dextran (DEX) aqueous two-phase systems (ATPS). In a PEG 600-DEX 40 ATPS containing 0.273 nmol of LacI fusion protein and 0.14% (w/w) of the functionalised PEG-IDA-Cu(II), more than 72% of the plasmid DNA partitioned to the PEG phase, without RNA or genomic DNA contamination as evaluated by agarose gel electrophoresis. In a second extraction stage, the elution of pDNA from the LacI binding complex proved difficult using either dextran or phosphate buffer as second phase, though more than 75% of the overall protein was removed in both systems. A maximum recovery of approximately 27% of the pCU19 plasmid was achieved using the PEG-dextran system as a second extraction system, with 80-90% of pDNA partitioning to the bottom phase. This represents about 7.4 microg of pDNA extracted per 1 mL of pUC19 desalted lysate.

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Purpose: (1) To devise a model-based method for estimating the probabilities of binocular fusion, interocular suppression and diplopia from psychophysical judgements, (2) To map out the way fusion, suppression and diplopia vary with binocular disparity and blur of single edges shown to each eye, (3) To compare the binocular interactions found for edges of the same vs opposite contrast polarity. Methods: Test images were single, horizontal, Gaussian-blurred edges, with blur B = 1-32 min arc, and vertical disparity 0-8.B, shown for 200 ms. In the main experiment, observers reported whether they saw one central edge, one offset edge, or two edges. We argue that the relation between these three response categories and the three perceptual states (fusion, suppression, diplopia) is indirect and likely to be distorted by positional noise and criterion effects, and so we developed a descriptive, probabilistic model to estimate both the perceptual states and the noise/criterion parameters from the data. Results: (1) Using simulated data, we validated the model-based method by showing that it recovered fairly accurately the disparity ranges for fusion and suppression, (2) The disparity range for fusion (Panum's limit) increased greatly with blur, in line with previous studies. The disparity range for suppression was similar to the fusion limit at large blurs, but two or three times the fusion limit at small blurs. This meant that diplopia was much more prevalent at larger blurs, (3) Diplopia was much more frequent when the two edges had opposite contrast polarity. A formal comparison of models indicated that fusion occurs for same, but not opposite, polarities. Probability of suppression was greater for unequal contrasts, and it was always the lower-contrast edge that was suppressed. Conclusions: Our model-based data analysis offers a useful tool for probing binocular fusion and suppression psychophysically. The disparity range for fusion increased with edge blur but fell short of complete scale-invariance. The disparity range for suppression also increased with blur but was not close to scale-invariance. Single vision occurs through fusion, but also beyond the fusion range, through suppression. Thus suppression can serve as a mechanism for extending single vision to larger disparities, but mainly for sharper edges where the fusion range is small (5-10 min arc). For large blurs the fusion range is so much larger that no such extension may be needed. © 2014 The College of Optometrists.

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Objective In this study, we have used a chemometrics-based method to correlate key liposomal adjuvant attributes with in-vivo immune responses based on multivariate analysis. Methods The liposomal adjuvant composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and trehalose 6,6-dibehenate (TDB) was modified with 1,2-distearoyl-sn-glycero-3-phosphocholine at a range of mol% ratios, and the main liposomal characteristics (liposome size and zeta potential) was measured along with their immunological performance as an adjuvant for the novel, postexposure fusion tuberculosis vaccine, Ag85B-ESAT-6-Rv2660c (H56 vaccine). Partial least square regression analysis was applied to correlate and cluster liposomal adjuvants particle characteristics with in-vivo derived immunological performances (IgG, IgG1, IgG2b, spleen proliferation, IL-2, IL-5, IL-6, IL-10, IFN-γ). Key findings While a range of factors varied in the formulations, decreasing the 1,2-distearoyl-sn-glycero-3-phosphocholine content (and subsequent zeta potential) together built the strongest variables in the model. Enhanced DDA and TDB content (and subsequent zeta potential) stimulated a response skewed towards a cell mediated immunity, with the model identifying correlations with IFN-γ, IL-2 and IL-6. Conclusion This study demonstrates the application of chemometrics-based correlations and clustering, which can inform liposomal adjuvant design.

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Purpose: Traditionally, it has been thought that no binocular combination occurs in amblyopia. However, there is a growing body of evidence that there are intact binocular mechanisms in amblyopia rendered inactive under normal viewing conditions due to imbalanced monocular inputs. Georgeson and Wallis (2014) recently introduced a novel method to investigate fusion, suppression and diplopia in normal population. We have modified this method to assess binocular interactions in amblyopia. Methods: Ten amblyopic and ten control subjects viewed briefly-presented (200 ms) pairs of dichoptically separated horizontal Gaussian blurred edges. Subjects reported one central edge, one offset edge, or a double edge as the vertical disparity was manipulated. The experiment was conducted at a range of spatial scales (blur widths of 4, 8, 16, and 32 arc min) and contrasts. Our model, based Georgeson and Wallis (2014), converted subjects’ responses into probabilities of fusion, suppression, and diplopia. Results: When the normal participants were presented equal contrast to each eye the probability of fusion gradually decreased with increasing disparity, as the probability of diplopia gradually increased. In only a small proportion of the trials, normal participants experienced suppression. The pattern was consistent across all edge blurs. Interestingly, the majority of amblyopes had a comparable pattern of fusion, i.e. decreasing probability with increasing disparity. However, with increasing disparity the amblyopes tended to suppress the amblyopic eye, experiencing diplopia only in a small proportion of trials particularly at large blurs. Increasing the interocular contrast offset favouring the amblyopic eye normalized the pattern of data in a way similar to normal participants. There were some interesting exceptions: strong suppressors for which our contrast range was inadequate and one case in which diplopia dominated. Conclusions: This task is suitable for assessing binocular interactions in amblyopic participants and providing a way to quantify the relationship between fusion, suppression and diplopia. In agreement with previous studies, our data indicate the presence of binocular mechanisms in amblyopia. A contrast offset favouring the amblyopic eye normalizes the measured binocular interactions in the amblyopic visual system.

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This is a comprehensive study of protein-mediated membrane fusion through single-molecule fluorescence resonance energy transfer (smFRET). Membrane fusion is one of the important cellular processes by which two initially distinct lipid bilayers merge their hydrophobic cores, resulting in one interconnected structure. For example, exocytosis, fertilization of an egg by a sperm and communication between neurons are a few among many processes that rely on some form of fusion. Proteins called soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) play a central role in fusion processes which is also regulated by many accessory proteins, such as synaptotagmin, complexin and Munc18. By a new lipid mixing method at the single-vesicle level, we are able to accurately detect different stages of SNARE-mediated membrane fusion including docking, hemi and full fusion via FRET value of single donor/acceptor vesicle pair. Through this single-vesicle lipid mixing assay, we discovered the vesicle aggregation induced by C2AB/Ca2+, the dual function of complexin, and the fusion promotion role of Munc18/SNARE-core binding mode. While this new method provides the information regarding the extent of the ensemble lipid mixing, the fusion pore opening between two vesicular cavities and the interaction between proteins cannot be detected. In order to overcome these limitations, we then developed a single-vesicle content mixing method to reveal the key factor of pore expansion by detecting the FRET change of dual-labeled DNA probes encapsulated in vesicles. Through our single-vesicle content mixing assay, we found the fusion pore expansion role of yeast SNAREs as well as neuronal SNAREs plus synaptotagmin 1.

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Current space exploration has transpired through the use of chemical rockets, and they have served us well, but they have their limitations. Exploration of the outer solar system, Jupiter and beyond will most likely require a new generation of propulsion system. One potential technology class to provide spacecraft propulsion and power systems involve thermonuclear fusion plasma systems. In this class it is well accepted that d-He3 fusion is the most promising of the fuel candidates for spacecraft applications as the 14.7 MeV protons carry up to 80% of the total fusion power while ‘s have energies less than 4 MeV. The other minor fusion products from secondary d-d reactions consisting of 3He, n, p, and 3H also have energies less than 4 MeV. Furthermore there are two main fusion subsets namely, Magnetic Confinement Fusion devices and Inertial Electrostatic Confinement (or IEC) Fusion devices. Magnetic Confinement Fusion devices are characterized by complex geometries and prohibitive structural mass compromising spacecraft use at this stage of exploration. While generating energy from a lightweight and reliable fusion source is important, another critical issue is harnessing this energy into usable power and/or propulsion. IEC fusion is a method of fusion plasma confinement that uses a series of biased electrodes that accelerate a uniform spherical beam of ions into a hollow cathode typically comprised of a gridded structure with high transparency. The inertia of the imploding ion beam compresses the ions at the center of the cathode increasing the density to the point where fusion occurs. Since the velocity distributions of fusion particles in an IEC are essentially isotropic and carry no net momentum, a means of redirecting the velocity of the particles is necessary to efficiently extract energy and provide power or create thrust. There are classes of advanced fuel fusion reactions where direct-energy conversion based on electrostatically-biased collector plates is impossible due to potential limits, material structure limitations, and IEC geometry. Thermal conversion systems are also inefficient for this application. A method of converting the isotropic IEC into a collimated flow of fusion products solves these issues and allows direct energy conversion. An efficient traveling wave direct energy converter has been proposed and studied by Momota , Shu and further studied by evaluated with numerical simulations by Ishikawa and others. One of the conventional methods of collimating charged particles is to surround the particle source with an applied magnetic channel. Charged particles are trapped and move along the lines of flux. By introducing expanding lines of force gradually along the magnetic channel, the velocity component perpendicular to the lines of force is transferred to the parallel one. However, efficient operation of the IEC requires a null magnetic field at the core of the device. In order to achieve this, Momota and Miley have proposed a pair of magnetic coils anti-parallel to the magnetic channel creating a null hexapole magnetic field region necessary for the IEC fusion core. Numerically, collimation of 300 eV electrons without a stabilization coil was demonstrated to approach 95% at a profile corresponding to Vsolenoid = 20.0V, Ifloating = 2.78A, Isolenoid = 4.05A while collimation of electrons with stabilization coil present was demonstrated to reach 69% at a profile corresponding to Vsolenoid = 7.0V, Istab = 1.1A, Ifloating = 1.1A, Isolenoid = 1.45A. Experimentally, collimation of electrons with stabilization coil present was demonstrated experimentally to be 35% at 100 eV and reach a peak of 39.6% at 50eV with a profile corresponding to Vsolenoid = 7.0V, Istab = 1.1A, Ifloating = 1.1A, Isolenoid = 1.45A and collimation of 300 eV electrons without a stabilization coil was demonstrated to approach 49% at a profile corresponding to Vsolenoid = 20.0V, Ifloating = 2.78A, Isolenoid = 4.05A 6.4% of the 300eV electrons’ initial velocity is directed to the collector plates. The remaining electrons are trapped by the collimator’s magnetic field. These particles oscillate around the null field region several hundred times and eventually escape to the collector plates. At a solenoid voltage profile of 7 Volts, 100 eV electrons are collimated with wall and perpendicular component losses of 31%. Increasing the electron energy beyond 100 eV increases the wall losses by 25% at 300 eV. Ultimately it was determined that a field strength deriving from 9.5 MAT/m would be required to collimate 14.7 MeV fusion protons from d-3He fueled IEC fusion core. The concept of the proton collimator has been proven to be effective to transform an isotropic source into a collimated flow of particles ripe for direct energy conversion.

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Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporated into automatic analysis. Incorporation of expert knowledge is frequently a matter of combining multiple data sources from disparate hypothetical spaces. In cases where such spaces belong to different data types, this task becomes even more challenging. In this paper we present a novel immune-inspired method that enables the fusion of such disparate types of data for a specific set of problems. We show that our method provides a better visual understanding of one hypothetical space with the help of data from another hypothetical space. We believe that our model has implications for the field of exploratory data analysis and knowledge discovery.

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Purpose: To evaluate and compare the performance of Ripplet Type-1 transform and directional discrete cosine transform (DDCT) and their combinations for improved representation of MRI images while preserving its fine features such as edges along the smooth curves and textures. Methods: In a novel image representation method based on fusion of Ripplet type-1 and conventional/directional DCT transforms, source images were enhanced in terms of visual quality using Ripplet and DDCT and their various combinations. The enhancement achieved was quantified on the basis of peak signal to noise ratio (PSNR), mean square error (MSE), structural content (SC), average difference (AD), maximum difference (MD), normalized cross correlation (NCC), and normalized absolute error (NAE). To determine the attributes of both transforms, these transforms were combined to represent the entire image as well. All the possible combinations were tested to present a complete study of combinations of the transforms and the contrasts were evaluated amongst all the combinations. Results: While using the direct combining method (DDCT) first and then the Ripplet method, a PSNR value of 32.3512 was obtained which is comparatively higher than the PSNR values of the other combinations. This novel designed technique gives PSNR value approximately equal to the PSNR’s of parent techniques. Along with this, it was able to preserve edge information, texture information and various other directional image features. The fusion of DDCT followed by the Ripplet reproduced the best images. Conclusion: The transformation of images using Ripplet followed by DDCT ensures a more efficient method for the representation of images with preservation of its fine details like edges and textures.

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This paper proposes a novel hierarchical data fusion technique for the non-destructive testing (NDT) and condition assessment of timber utility poles. The new method analyzes stress wave data from multisensor and multiexcitation guided wave testing using a hierarchical data fusion model consisting of feature extraction, data compression, pattern recognition, and decision fusion algorithms. The researchers validate the proposed technique using guided wave tests of a sample of in situ timber poles. The actual health states of these poles are known from autopsies conducted after the testing, forming a ground-truth for supervised classification. In the proposed method, a data fusion level extracts the main features from the sampled stress wave signals using power spectrum density (PSD) estimation, wavelet packet transform (WPT), and empirical mode decomposition (EMD). These features are then compiled to a feature vector via real-number encoding and sent to the next level for further processing. Principal component analysis (PCA) is also adopted for feature compression and to minimize information redundancy and noise interference. In the feature fusion level, two classifiers based on support vector machine (SVM) are applied to sensor separated data of the two excitation types and the pole condition is identified. In the decision making fusion level, the Dempster–Shafer (D-S) evidence theory is employed to integrate the results from the individual sensors obtaining a final decision. The results of the in situ timber pole testing show that the proposed hierarchical data fusion model was able to distinguish between healthy and faulty poles, demonstrating the effectiveness of the new method.

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Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.

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