993 resultados para 796.015
Resumo:
Background: An arteriovenous loop (AVL) enclosed in a polycarbonate chamber in vivo, produces a fibrin exudate which acts as a provisional matrix for the development of a tissue engineered microcirculatory network. Objectives: By administering enoxaparin sodium - an inhibitor of fibrin polymerization, the significance of fibrin scaffold formation on AVL construct size (including the AVL, fibrin scaffold, and new tissue growth into the fibrin), growth, and vascularization were assessed and compared to controls. Methods: In Sprague Dawley rats, an AVL was created on femoral vessels and inserted into a polycarbonate chamber in the groin in 3 control groups (Series I) and 3 experimental groups (Series II). Two hours before surgery and 6 hours post-surgery, saline (Series I) or enoxaparin sodium (0.6 mg/kg, Series II) was administered intra-peritoneally. Thereafter, the rats were injected daily with saline (Series I) or enoxaparin sodium (1.5 mg/kg, Series II) until construct retrieval at 3, 10, or 21 days. The retrieved constructs underwent weight and volume measurements, and morphologic/morphometric analysis of new tissue components. Results: Enoxaparin sodium treatment resulted in the development of smaller AVL constructs at 3, 10, and 21 days. Construct weight and volume were significantly reduced at 10 days (control weight 0.337 ± 0.016 g [Mean ± SEM] vs treated 0.228 ± 0.048, [P < .001]: control volume 0.317 ± 0.015 mL vs treated 0.184 ± 0.039 mL [P < .01]) and 21 days (control weight 0.306 ± 0.053 g vs treated 0.198 ± 0.043 g [P < .01]: control volume 0.285 ± 0.047 mL vs treated 0.148 ± 0.041 mL, [P < .01]). Angiogenesis was delayed in the enoxaparin sodium-treated constructs with the absolute vascular volume significantly decreased at 10 days (control vascular volume 0.029 ± 0.03 mL vs treated 0.012 ± 0.002 mL [P < .05]). Conclusion: In this in vivo tissue engineering model, endogenous, extra-vascularly deposited fibrin volume determines construct size and vascular growth in the first 3 weeks and is, therefore, critical to full construct development.
Vertical graphene gas- and bio-sensors via catalyst-free, reactive plasma reforming of natural honey
Resumo:
A rapid reforming of natural honey exposed to reactive low-temperature Ar + H2 plasmas produced high-quality, ultra-thin vertical graphenes, without any metal catalyst or external heating. This transformation is only possible in the plasma and fails in similar thermal processes. The process is energy-efficient, environmentally benign, and is much cheaper than common synthesis methods based on purified hydrocarbon precursors. The graphenes retain the essential minerals of natural honey, feature reactive open edges and reliable gas- and bio-sensing performance.
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We present results of computational simulations of tungsten-inert-gas and metal-inert-gas welding. The arc plasma and the electrodes (including the molten weld pool when necessary) are included self-consistently in the computational domain. It is shown, using three examples, that it would be impossible to accurately estimate the boundary conditions on the weld-pool surface without including the arc plasma in the computational domain. First, we show that the shielding gas composition strongly affects the properties of the arc that influence the weld pool: heat flux density, current density, shear stress and arc pressure at the weld-pool surface. Demixing is found to be important in some cases. Second, the vaporization of the weld-pool metal and the diffusion of the metal vapour into the arc plasma are found to decrease the heat flux density and current density to the weld pool. Finally, we show that the shape of the wire electrode in metal-inert-gas welding has a strong influence on flow velocities in the arc and the pressure and shear stress at the weld-pool surface. In each case, we present evidence that the geometry and depth of the weld pool depend strongly on the properties of the arc.
Resumo:
The primary aim of this paper was to investigate heterogeneity in language abilities of children with a confirmed diagnosis of an ASD (N = 20) and children with typical development (TD; N = 15). Group comparisons revealed no differences between ASD and TD participants on standard clinical assessments of language ability, reading ability or nonverbal intelligence. However, a hierarchical cluster analysis based on spoken nonword repetition and sentence repetition identified two clusters within the combined group of ASD and TD participants. The first cluster (N = 6) presented with significantly poorer performances than the second cluster (N = 29) on both of the clustering variables in addition to single word and nonword reading. The significant differences between the two clusters occur within a context of Cluster 1 having language impairment and a tendency towards more severe autistic symptomatology. Differences between the oral language abilities of the first and second clusters are considered in light of diagnosis, attention and verbal short term memory skills and reading impairment.
Resumo:
Carbon microcoils (CMCs) have been coated with a Ni nanoparticle film using an electroless plating process. The morphology, the elemental composition and the phases in the coating layer, complex permittivity and permeability of the CMCs and Ni-coated CMCs were, respectively, investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and microwave vector network analysis at room temperature. A homogeneous dispersion of Ni nanoparticles on the outer surface of the CMCs was obtained, with a mean particle size of ∼34.4 nm and the phosphorus content of about 8.5 wt%. When comparing the coated and uncoated CMC samples, the real (ε′) and imaginary (ε″) part of the complex permittivity as well as dielectric dissipation factor (tgδε = ε″/ε′) of the Ni-coated CMCs were much smaller, while the real (μ′) and imaginary (μ″) part of the complex permeability and the magnetic dissipation factor (t g σμ = μ″ / μ′) were larger. The enhanced microwave absorption of Ni-coated CMCs resulted from stronger dielectric and magnetic losses. In contrast, the microwave absorption of uncoated CMCs was mainly attributed to the dielectric rather than magnetic losses.
Resumo:
It is well established that the time to name target objects can be influenced by the presence of categorically related versus unrelated distractor items. A variety of paradigms have been developed to determine the level at which this semantic interference effect occurs in the speech production system. In this study, we investigated one of these tasks, the postcue naming paradigm, for the first time with fMRI. Previous behavioural studies using this paradigm have produced conflicting interpretations of the processing level at which the semantic interference effect takes place, ranging from pre- to post-lexical. Here we used fMRI with a sparse, event-related design to adjudicate between these competing explanations. We replicated the behavioural postcue naming effect for categorically related target/distractor pairs, and observed a corresponding increase in neuronal activation in the right lingual and fusiform gyri-regions previously associated with visual object processing and colour-form integration. We interpret these findings as being consistent with an account that places the semantic interference effect in the postcue paradigm at a processing level involving integration of object attributes in short-term memory.
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A new source of low-frequency (0.46 MHz) inductively coupled plasmas sustained by the internal planar "unidirectional" RF current driven through a specially designed internal antenna configuration has been developed. The experimental results of the investigation of the optical and global argon plasma parameters by the optical and Langmuir probes are presented. It is shown that the spatial profiles of the electron density, the effective electron temperature and plasma potential feature a great deal of the radial and axial uniformity compared with conventional sources of inductively coupled plasmas with external at coil configurations. The measurements also reveal a weak azimuthal dependence of the global plasma parameters at low values of the input RF power, which was earlier predicted theoretically. The azimuthal dependence of the global plasma parameters vanishes at high input RF powers. Moreover, under certain conditions, the plasma becomes unstable due to spontaneous transitions between low-density (electrostatic, E) and high-density (electromagnetic, H) operating modes. Excellent uniformity of high-density plasmas makes the plasma reactor promising for various plasma processing applications and surface engineering.
Resumo:
The results of numerical simulation of the equilibrium parameters of a low pressure nanopowder-generating discharge in silane for the plasma enhanced chemical vapor deposition (PECVD) of nanostructured silicon-based films are presented. It is shown that a low electron temperature and a low density of negative SiH3 - ions are favorable for the PECVD process. This opens a possibility to predict the main parameters of the reactive plasma and plasma-nucleated nanoparticles, and hence, to control the quality of silicon nanofilms.
Resumo:
This paper recognises that customer loyalty is important for many competitive organisations, and that retail firms make investments to build and maintain loyal relationships with their existing and potential customers (e.g. loyalty programs). However, there has been little focus on the mechanisms by which these relationship investments operate to achieve customer loyalty. This paper examines one mechanism, namely customer gratitude, which works to make a firm’s relationship marketing investment a success or a failure. Using data from 1600 undergraduate students, this study empirically confirms the mediating role of customer gratitude between the customers’ perceptions a firm’s relationship marketing investments and customers’ perceptions of the value of the relationship with the firm. Further, a significant moderating effect of perceived benevolence on the relationship between customers’ perceptions a firm’s relationship marketing investments and customer gratitude was identified. For theorists, this customer gratitude model offers a better psychological explanation of how relationship marketing investments operate to improve the value that customers place on their relationships with retailers. Our research suggests that managers should invest resources to stimulate customer gratitude in order to build strong customer–seller relationships.
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The axial coefficients of thermal expansion (CTE) of various carbon nanotubes (CNTs), i.e., single-wall carbon nanotubes (SWCNTs), and some multi-wall carbon nanotubes (MWCNTs), were predicted using molecular dynamics (MDs) simulations. The effects of two parameters, i.e., temperature and the CNT diameter, on CTE were investigated extensively. For all SWCNTs and MWCNTs, the obtained results clearly revealed that within a wide low temperature range, their axial CTEs are negative. As the diameter of CNTs decreases, this temperature range for negative axial CTEs becomes narrow, and positive axial CTEs appear in high temperature range. It was found that the axial CTEs vary nonlinearly with the temperature, however, they decrease linearly as the CNT diameter increases. Moreover, within a wide temperature range, a set of empirical formulations was proposed for evaluating the axial CTEs of armchair and zigzag SWCNTs using the above two parameters. Finally, it was found that the absolute value of the negative axial CTE of any MWCNT is much smaller than those of its constituent SWCNTs, and the average value of the CTEs of its constituent SWCNTs. The present fundamental study is very important for understanding the thermal behaviors of CNTs in such as nanocomposite temperature sensors, or nanoelectronics devices using CNTs.
Resumo:
Among the clay minerals, montmorillonite is the most extensively studied material using as adsorbents, but palygorskite and its organically modified products have been least explored for their potential use in contaminated water remediation. In this study, an Australian palygorskite was modified with cationic surfactants octadecyl trimethylammonium bromide and dioctadecyl dimethylammonium bromide at different doses. A full structural characterization of prepared organo-palygorskite by X-ray diffraction, infrared spectroscopy, surface analysis and thermogravimetric analysis was performed. The morphological changes of palygorskite before and after modification were recorded using scanning electron microscopy, which showed the surfactant molecules can attach on the surface of rod-like crystals and thus can weaken the interactions between palygorskite single crystals. Real surfactants loadings on organo-palygorskites were also calculated based on thermogravimetric analysis. 1 CEC, 2 CEC octadecyl trimethylammonium bromide modified palygorskites, 1 CEC and 2 CEC dioctadecyl dimethylammonium bromide modified palygorskites absorbed as much as 12 mg/g, 42 mg/g, 9 mg/g and 25 mg/g of 2,4- dichlorophenoxyacetic acid respectively. This study has shown a potential on organo-palygorskites for organic herbicide adsorption especially anionic ones from waste water. In addition, equilibration time effects and the Langmuir and Freundlich models fitting were also investigated in details.
Resumo:
Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.
Resumo:
Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.