908 resultados para radial glia


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This paper presents two methods of star camera calibration to determine camera calibrating parameters (like principal point, focal length etc) along with lens distortions (radial and decentering). First method works autonomously utilizing star coordinates in three consecutive image frames thus independent of star identification or biased attitude information. The parameters obtained in autonomous self-calibration technique helps to identify the imaged stars with the cataloged stars. Least Square based second method utilizes inertial star coordinates to determine satellite attitude and star camera parameters with lens radial distortion, both independent of each other. Camera parameters determined by the second method are more accurate than the first method of camera self calibration. Moreover, unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters, the second method has the advantage of computing spacecraft attitude independent of camera calibrating parameters except lens distortions (radial). Finally Kalman filter based sequential estimation scheme is employed to filter out the noise of the LS based estimation.

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Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

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Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

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Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for health care applications.

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Heat exchanger design plays a significant role in the performance of solid state hydrogen storage device. In the present study, a cylindrical hydrogen storage device with an embedded annular heat exchanger tube with radial circular copper fins, is considered. A 3-D mathematical model of the storage device is developed to investigate the sorption performance of metal hydride (MH). A prototype of the device is fabricated for 1 kg of MH alloy, LaNi5, and tested at constant supply pressure of hydrogen, validating the simulation results. Absorption characteristics of storage device have been examined by varying different operating parameters such as hydrogen supply pressure and cooling fluid temperature and velocity. Absorption process is completed in 18 min when these parameters are 15 bar, 298 K and 1 m/s respectively. A study of geometric parameters of copper fins (such as perforation, number and thickness of fin) has been carried out to investigate their effects on absorption process. Copyright (C) 2015, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

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We report molecular dynamics (MD) simulations to explore the influence of a counterion on the structure and dynamics of cationic and anionic solvation shells for various ions in methanol at 298 K. We show that the variation in ionic size of either the cation or the anion in an ion pair influences the solvation structure of the other ion as well as the diffusivity in an electrolyte solution of methanol. The extent of ionic association between the cation and its counteranion of different ionic sizes has been investigated by analyzing the radial distribution functions (RDFs) and the orientation of methanol molecules in the first solvation shell (FSS) of ions. It is shown that the methanol in the FSS of the anion as well the cation exhibit quite different radial and orientational structures as compared to methanol which lie in the FSS of either the anion or the cation but not both. We find that the coordination number (CN) of F-, Cr-, and I- ions decreases with increasing size of the anion which is contrary to the trend reported for the anions in H2O. The mean residence time (MRT) of methanol molecules in the FSS of ions has been calculated using the stable states picture (SSP) approach. It is seen that the ion-counterion interaction has a considerable influence on the MRT of methanol molecules in the FSS of ions. We also discuss the stability order of the ion-counterion using the potentials of mean force (PMFs) for ion pairs with ions of different sizes. The PMF plots reveal that the Li+-F- pair (small-small) is highly stable and the Li+-I- pair is least stable (small-large) in electrolyte solutions.

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Pressure-swirl nozzles (simplex nozzles) are used in various field applications such as aero-engines, power generation, spray painting and agricultural irrigation. For this particular nozzle, research in the past decade has dealt with the development of numerical models for predicting droplet distribution profiles. Although these results have been valuable, the experimental results have been contradictory, therefore fundamental understanding of the influence of properties in nozzle is important. This paper experimentally investigates the effect of surfactants on breakup and coalescence. Since most of the fuels and biofuels have low surface tension compared to water, a comparative analysis between a surfactant solution and a liquid fuel is imperative. For this experimental study, a simplex nozzle characterized as flow number 0.4 will be utilized. The injection pressures will range from 0.3 - 4Mpa while altering the surface tension from 72 to 28mN/m. By applying Phase Doppler Particle Anemometry (PDPA) which is a non-intrusive laser diagnostic technique, the differences in spray characteristics due to spray surface tension can be highlighted. The average droplet diameter decreases for a low surface tension fluid in the axial direction in comparison to pure water. The average velocity of droplets is surprisingly lower in the same spray zone. Measurements made in the radial direction show no significant changes, but at the locations close to the nozzle, water droplets have larger diameter and velocity. The results indicate the breakup and coalescence regimes have been altered when surface tension is lowered. A decrease in surface tension alters the breakup length while increasing the spray angle. Moreover, higher injection pressure shortens the breakup length and decrease in overall diameter of the droplets. By performing this experimental study the fundamentals of spray dynamics, such as spray formation, liquid breakup length, and droplet breakup regimes can be observed as a function of surface tension and how a surrogate fuel compares with a real fuel for experimental purposes. This knowledge potentially will lead to designing a better atomizer or new biofuels.

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Blood travels throughout the body and thus its flow is modulated by changes in body condition. As a consequence, the wrist pulse signal contains important information about the status of the human body. In this work we have employed signal processing techniques to extract important information from these signals. Radial artery pulse pressure signals are acquired at wrist position noninvasively for several subjects for two cases of interest, viz. before and after exercise, and before and after lunch. Further analysis is performed by fitting a bi-modal Gaussian model to the data and extracting spatial features from the fit. The spatial features show statistically significant (p < 0.001) changes between the groups for both the cases, which indicates that they are effective in distinguishing the changes taking place due to exercise or food intake. Recursive cluster elimination based support vector machine classifier is used to classify between the groups. A high classification accuracy of 99.71% is achieved for the exercise case and 99.94% is achieved for the lunch case. This paper demonstrates the utility of certain spatial features in studying wrist pulse signals obtained under various experimental conditions. The ability of the spatial features in distinguishing changing body conditions can be potentially used for various healthcare applications. (C) 2015 Elsevier Ltd. All rights reserved.

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Free vibration problem of a rotating Euler-Bernoulli beam is solved with a truly meshless local Petrov-Galerkin method. Radial basis function and summation of two radial basis functions are used for interpolation. Radial basis function satisfies the Kronecker delta property and makes it simpler to apply the essential boundary conditions. Interpolation with summation of two radial basis functions increases the node carrying capacity within the sub-domain of the trial function and higher natural frequencies can be computed by selecting the complete domain as a sub-domain of the trial function. The mass and stiffness matrices are derived and numerical results for frequencies are obtained for a fixed-free beam and hinged-free beam simulating hingeless and articulated helicopter blades. Stiffness and mass distribution suitable for wind turbine blades are also considered. Results show an accurate match with existing literature.

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A new class of dendrimers, the poly(propyl ether imine) (PETIM) dendrimer, has been shown to be a novel hyperbranched polymer having potential applications as a drug delivery vehicle. Structure and dynamics of the amine terminated PETIM dendrimer and their changes with respect to the dendrimer generation are poorly understood. Since most drugs are hydrophobic in nature, the extent of hydrophobicity of the dendrimer core is related to its drug encapsulation and retention efficacy. In this study, we carry out fully atomistic molecular dynamics (MD) simulations to characterize the structure of PETIM (G2-G6) dendrimers in salt solution as a function of dendrimer generation at different protonation levels. Structural properties such as radius of gyration (R-g), radial density distribution, aspect ratio, and asphericity are calculated. In order to assess the hydrophilicity of the dendrimer, we compute the number of bound water molecules in the interior of dendrirner as well as the number of dendrimer-water hydrogen bonds. We conclude that PETIM dendrimers have relatively greater hydrophobicity and flexibility when compared with their extensively investigated PAMAM counterparts. Hence PETIM dendrimers are expected to have stronger interactions with lipid membranes as well as improved drug encapsulation and retention properties when compared with PAMAM dendrimers. We compute the root-mean-square fluctuation of dendrimers as well as their entropy to quantify the flexibility of the dendrimer. Finally we note that structural and solvation properties computed using force field parameters derived based on the CHARMM general purpose force field were in good quantitative agreement with those obtained using the generalized Amber force field (GAFF).

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Colloidal systems offer an effective medium to micro-engineer complex structures without involving sophisticated fabrication procedures. This article presents a deployment strategy of multiple droplets of different colloidal composition and utilizes the inherent capillary flow driven self assembly of nanoparticles to construct stacks of multiple materials on a given glass substrate. Here we used aqueous nano-crystalline titania and nano-amorphous silica solutions as the two materials. Initially, a pure nanotitania (nanosilica) droplet is deployed and allowed to dry partially. Subsequently, a second droplet of pure nanosilica (nanotitania) is deployed co-axially on the partially dried precipitate. The proposed deployment strategy allowed significant morphological differences when the deployment order of nanosilica and nanotitania were interchanged. Compositional analysis performed using EDX (Energy Dispersive X-ray spectroscopy) showed preferential deposition of nanosilica and nanotitania along the radial as well as the axial plane of the final deposit pattern. The underlying mechanism for such a phenomenon could be attributed to the contact line dynamics of a sessile double droplet. We also observe heteroaggregation of the nanosilica-nanotitania interaction along a narrow interface which resulted in nanotitania particles clustering into isolated islands embedded into a matrix of nanosilica particles. Overall, this work elucidates the evaporation driven dynamics of a mixed colloidal system which displays both macroscopic as well as microscopic phenomena. Such a system could be used to generate ordered arrays of functional materials with engineered micro to nano-scale properties.

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We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind map of metallicity up to a radius of 4 degrees-5 degrees, derived using photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. We identify the RGB in the V, (V - I) colour-magnitude diagrams of small subregions of varying sizes in both data sets. We use the slope of the RGB as an indicator of the average metallicity of a subregion, and calibrate the RGB slope to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The average metallicity of the LMC is found to be Fe/H] = -0.37 dex (sigmaFe/H] = 0.12) from MCPS data, and Fe/H] = -0.39 dex (sigmaFe/H] = 0.10) from OGLE III data. The bar is found to be the most metal-rich region of the LMC. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc (-0.049 +/- 0.002 dex kpc(-1) to -0.066 +/- 0.006 dex kpc(-1)). Subregions in which the mean metallicity differs from the surrounding areas do not appear to correlate with previously known features; spectroscopic studies are required in order to assess their physical significance.

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Purpose - The purpose of this paper is to investigate the possibility to construct tissue-engineered bone repair scaffolds with pore size distributions using rapid prototyping techniques. Design/methodology/approach - The fabrication of porous scaffolds with complex porous architectures represents a major challenge in tissue engineering and the design aspects to mimic complex pore shape as well as spatial distribution of pore sizes of natural hard tissue remain unexplored. In this context, this work aims to evaluate the three-dimensional printing process to study its potential for scaffold fabrication as well as some innovative design of homogeneously porous or gradient porous scaffolds is described and such design has wider implication in the field of bone tissue engineering. Findings - The present work discusses biomedically relevant various design strategies with spatial/radial gradient in pore sizes as well as with different pore sizes and with different pore geometries. Originality/value - One of the important implications of the proposed novel design scheme would be the development of porous bioactive/biodegradable composites with gradient pore size, porosity, composition and with spatially distributed biochemical stimuli so that stem cells loaded into scaffolds would develop into complex tissues such as those at the bone-cartilage interface.

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The ability to quantify leakage flow and windage heating for labyrinth seals with honeycomb lands is critical in understanding gas turbine engine system performance and predicting its component life. Variety of labyrinth seal configurations (number of teeth, stepped or straight, honeycomb cell size) are in use in gas turbines, and for each configuration, there are many geometric factors that can impact a seal's leakage and windage characteristics. This paper describes the development of a numerical methodology aimed at studying the effect of honeycomb lands on leakage and windage heating. Specifically, a three-dimensional computational fluid dynamics (CFD) model is developed utilizing commercial finite volume-based software incorporating the renormalization group (RNG) k-epsilon turbulence model with modified Schmidt number. The modified turbulence model is benchmarked and fine-tuned based on several experiments. Using this model, a broad parametric study is conducted by varying honeycomb cell size, pressure ratio (PR), and radial clearance for a four-tooth straight-through labyrinth seal. The results show good agreement with available experimental data. They further indicate that larger honeycomb cells predict higher seal leakage and windage heating at tighter clearances compared to smaller honeycomb cells and smooth lands. However, at open seal clearances larger honeycomb cells have lower leakage compared to smaller honeycomb cells.

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Controlled breakup of droplets using heat or acoustics is pivotal in applications such as pharmaceutics, nanoparticle production, and combustion. In the current work we have identified distinct thermal acoustics-induced deformation regimes (ligaments and bubbles) and breakup dynamics in externally heated acoustically levitated bicomponent (benzene-dodecane) droplets with a wide variation in volatility of the two components (benzene is significantly more volatile than dodecane). We showcase the physical mechanism and universal behavior of droplet surface caving in leading to the inception and growth of ligaments. The caving of the top surface is governed by a balance between the acoustic pressure field and the restrictive surface tension of the droplet. The universal collapse of caving profiles for different benzene concentration (<70% by volume) is shown by using an appropriate time scale obtained from force balance. Continuous caving leads to the formation of a liquid membrane-type structure which undergoes radial extension due to inertia gained during the precursor phase. The membrane subsequently closes at the rim and the kinetic energy leads to ligament formation and growth. Subsequent ligament breakup is primarily Rayleigh-Plateau type. The breakup mode shifts to diffusional entrapment-induced boiling with an increase in concentration of the volatile component (benzene >70% by volume). The findings are portable to any similar bicomponent systems with differential volatility.