860 resultados para Multidimensional deprivation
Resumo:
We address the problem of mining targeted association rules over multidimensional market-basket data. Here, each transaction has, in addition to the set of purchased items, ancillary dimension attributes associated with it. Based on these dimensions, transactions can be visualized as distributed over cells of an n-dimensional cube. In this framework, a targeted association rule is of the form {X -> Y} R, where R is a convex region in the cube and X. Y is a traditional association rule within region R. We first describe the TOARM algorithm, based on classical techniques, for identifying targeted association rules. Then, we discuss the concepts of bottom-up aggregation and cubing, leading to the CellUnion technique. This approach is further extended, using notions of cube-count interleaving and credit-based pruning, to derive the IceCube algorithm. Our experiments demonstrate that IceCube consistently provides the best execution time performance, especially for large and complex data cubes.
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Many fishes are exposed to air in their natural habitat or during their commercial handling. In natural habitat or during commercial handling, the cat fish Heteropneustes fossilis is exposed to air for > 24 h. Data on its oxidative metabolism in the above condition are not available. Oxidative stress (OS) indices (lipid and protein oxidation), toxic reactive oxygen species (ROS: H2O2) generation, antioxidative status (levels of superoxide dismutase, catalase, glutathione peroxidase and reductase, ascorbic acid and nonprotein sulfhydryl) and activities of electron transport chain (ETC) enzymes (complex I-IV) were investigated in brain tissue of H. fossilis under air exposure condition (0, 3, 6, 12 and 18 h at 25 degrees C). Decreased activities of antioxidant (except catalase) and ETC enzymes (except complex II) with increased H2O2 and OS levels were observed in the tissue under water deprivation condition. Positive correlation was observed for complex II activity and non-protein thiol groups with time period of air exposure. The critical time period to induce OS and to reduce most of the studied antioxidant level in brain was found to be 3-6 h air exposure. The data can be useful to minimize the stress generated during commercial handling of the live fishes those exposed to air in general and H. fossilis in particular. (C) 2013 Elsevier Inc. All rights reserved.
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Responses of redox regulatory system to long-term survival (> 18 h) of the catfish Heteropneustes fossilis in air are not yet understood. Lipid and protein oxidation level, oxidant (H2O2) generation, antioxidative status (levels of superoxide dismutase, catalase, glutathione peroxidase and reductase, ascorbic acid and non-protein sulfhydryl) and activities of respiratory complexes (I, II, III and IV) in mitochondria were investigated in muscle of H. fossilis under air exposure condition (0, 3, 6, 12 and 18 h at 25 A degrees C). The increased levels of both H2O2 and tissue oxidation were observed due to the decreased activities of antioxidant enzymes in muscle under water deprivation condition. However, ascorbic acid and non-protein thiol groups were the highest at 18 h air exposure time. A linear increase in complex II activity with air exposure time and an increase up to 12 h followed by a decrease in activity of complex I at 18 h were observed. Negative correlation was observed for complex III and V activity with exposure time. Critical time to modulate the above parameters was found to be 3 h air exposure. Dehydration induced oxidative stress due to modulation of electron transport chain and redox metabolizing enzymes in muscle of H. fossilis was clearly observed. Possible contribution of redox regulatory system in muscle tissue of the fish for long-term survival in air is elucidated. Results of the present study may be useful to understand the redox metabolism in muscle of fishes those are exposed to air in general and air breathing fishes in particular.
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The paper proposes a non-destructive method for simultaneous measurement of in-plane and out-of-plane displacements and strains undergone by a deformed specimen from a single moire fringe pattern obtained on the specimen in a dual beam digital holographic interferometry setup. The moire fringe pattern encodes multiple interference phases which carry the information on multidimensional deformation. The interference field is segmented in each column and is modeled as multicomponent quadratic/cubic frequency-modulated signal in each segment. Subsequently, the product form of modified cubic phase function is used for accurate estimation of phase parameters. The estimated phase parameters are further utilized for direct estimation of the unwrapped interference phases and phase derivatives. The simulation and experimental results are provided to validate the effectiveness of the proposed method.
Resumo:
Finite volume methods traditionally employ dimension by dimension extension of the one-dimensional reconstruction and averaging procedures to achieve spatial discretization of the governing partial differential equations on a structured Cartesian mesh in multiple dimensions. This simple approach based on tensor product stencils introduces an undesirable grid orientation dependence in the computed solution. The resulting anisotropic errors lead to a disparity in the calculations that is most prominent between directions parallel and diagonal to the grid lines. In this work we develop isotropic finite volume discretization schemes which minimize such grid orientation effects in multidimensional calculations by eliminating the directional bias in the lowest order term in the truncation error. Explicit isotropic expressions that relate the cell face averaged line and surface integrals of a function and its derivatives to the given cell area and volume averages are derived in two and three dimensions, respectively. It is found that a family of isotropic approximations with a free parameter can be derived by combining isotropic schemes based on next-nearest and next-next-nearest neighbors in three dimensions. Use of these isotropic expressions alone in a standard finite volume framework, however, is found to be insufficient in enforcing rotational invariance when the flux vector is nonlinear and/or spatially non-uniform. The rotationally invariant terms which lead to a loss of isotropy in such cases are explicitly identified and recast in a differential form. Various forms of flux correction terms which allow for a full recovery of rotational invariance in the lowest order truncation error terms, while preserving the formal order of accuracy and discrete conservation of the original finite volume method, are developed. Numerical tests in two and three dimensions attest the superior directional attributes of the proposed isotropic finite volume method. Prominent anisotropic errors, such as spurious asymmetric distortions on a circular reaction-diffusion wave that feature in the conventional finite volume implementation are effectively suppressed through isotropic finite volume discretization. Furthermore, for a given spatial resolution, a striking improvement in the prediction of kinetic energy decay rate corresponding to a general two-dimensional incompressible flow field is observed with the use of an isotropic finite volume method instead of the conventional discretization. (C) 2014 Elsevier Inc. All rights reserved.
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Single fluid schemes that rely on an interface function for phase identification in multicomponent compressible flows are widely used to study hydrodynamic flow phenomena in several diverse applications. Simulations based on standard numerical implementation of these schemes suffer from an artificial increase in the width of the interface function owing to the numerical dissipation introduced by an upwind discretization of the governing equations. In addition, monotonicity requirements which ensure that the sharp interface function remains bounded at all times necessitate use of low-order accurate discretization strategies. This results in a significant reduction in accuracy along with a loss of intricate flow features. In this paper we develop a nonlinear transformation based interface capturing method which achieves superior accuracy without compromising the simplicity, computational efficiency and robustness of the original flow solver. A nonlinear map from the signed distance function to the sigmoid type interface function is used to effectively couple a standard single fluid shock and interface capturing scheme with a high-order accurate constrained level set reinitialization method in a way that allows for oscillation-free transport of the sharp material interface. Imposition of a maximum principle, which ensures that the multidimensional preconditioned interface capturing method does not produce new maxima or minima even in the extreme events of interface merger or breakup, allows for an explicit determination of the interface thickness in terms of the grid spacing. A narrow band method is formulated in order to localize computations pertinent to the preconditioned interface capturing method. Numerical tests in one dimension reveal a significant improvement in accuracy and convergence; in stark contrast to the conventional scheme, the proposed method retains its accuracy and convergence characteristics in a shifted reference frame. Results from the test cases in two dimensions show that the nonlinear transformation based interface capturing method outperforms both the conventional method and an interface capturing method without nonlinear transformation in resolving intricate flow features such as sheet jetting in the shock-induced cavity collapse. The ability of the proposed method in accounting for the gravitational and surface tension forces besides compressibility is demonstrated through a model fully three-dimensional problem concerning droplet splash and formation of a crownlike feature. (C) 2014 Elsevier Inc. All rights reserved.
Resumo:
Myopathies are among the major causes of mortality in the world. There is no complete cure for this heterogeneous group of diseases, but a sensitive, specific, and fast diagnostic tool may improve therapy effectiveness. In this study, Raman spectroscopy is applied to discriminate between muscle mutants in Drosophila on the basis of associated changes at the molecular level. Raman spectra were collected from indirect flight muscles of mutants, upheld1 (up1), heldup(2) (hdp(2)), myosin heavy chain7 (Mhc7), actin88F(KM88) (Act88F(KM88)), upheld101 (up101), and Canton-S (CS) control group, for both 2 and 12 days old flies. Difference spectra (mutant minus control) of all the mutants showed an increase in nucleic acid and beta-sheet and/or random coil protein content along with a decrease in a-helix protein. Interestingly, the 12th day samples of up1 and Act88F(KM88) showed significantly higher levels of glycogen and carotenoids than CS. A principal components based linear discriminant analysis classification model was developed based on multidimensional Raman spectra, which classified the mutants according to their pathophysiology and yielded an overall accuracy of 97% and 93% for 2 and 12 days old flies, respectively. The up1 and Act88F(KM88) (nemaline-myopathy) mutants form a group that is clearly separated in a linear discriminant plane from up101 and hdp2 (cardiomyopathy) mutants. Notably, Raman spectra from a human sample with nemaline-myopathy formed a cluster with the corresponding Drosophila mutant (up1). In conclusion, this is the first demonstration in which myopathies, despite their heterogeneity, were screened on the basis of biochemical differences using Raman spectroscopy.
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Using the positivity of relative entropy arising from the Ryu-Takayanagi formula for spherical entangling surfaces, we obtain constraints at the nonlinear level for the gravitational dual. We calculate the Green's function necessary to compute the first order correction to the entangling surface and use this to find the relative entropy for non-constant stress tensors in a derivative expansion. We show that the Einstein value satisfies the positivity condition, while the multidimensional parameter space away from it gets constrained.
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India needs to significantly increase its electricity consumption levels, in a sustainable manner, if it has to ensure rapid economic development, a goal that remains the most potent tool for delivering adaptation capacity to its poor who will suffer the worst consequences of climate change. Resource/supply constraints faced by conventional energy sources, techno-economic constraints faced by renewable energy sources, and the bounds imposed by climate change on fossil fuel use are likely to undermine India's quest for having a robust electricity system that can effectively contribute to achieving accelerated, sustainable and inclusive economic growth. One possible way out could be transitioning into a sustainable electricity system, which is a trade-off solution having taken into account the economic, social and environmental concerns. As a first step toward understanding this transition, we contribute an indicator based hierarchical multidimensional framework as an analytical tool for sustainability assessment of electricity systems, and validate it for India's national electricity system. We evaluate Indian electricity system using this framework by comparing it with a hypothetical benchmark sustainable electrical system, which was created using best indicator values realized across national electricity systems in the world. This framework, we believe, can be used to examine the social, economic and environmental implications of the current Indian electricity system as well as setting targets for future development. The analysis with the indicator framework provides a deeper understanding of the system, identify and quantify the prevailing sustainability gaps and generate specific targets for interventions. We use this framework to compute national electricity system sustainability index (NESSI) for India. (C) 2014 Elsevier Ltd. All rights reserved.
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We report the synthesis of stable rGO/TiO2/Au nanowire hybrids showing excellent electrocatalytic activity for ethanol oxidation. Phase-pure anatase TiO2 nanoparticles (similar to 3 nm) were grown on GO sheets followed by the growth of ultrathin Au nanowires leading to the formation of a multidimensional ternary structure (0-D TiO2 and 1-D Au on 2-D graphene oxide). The oleylamine used for the synthesis of the Au nanowires not only leads to stable Au nanowires anchored on the GO sheets but also leads to the functionalization and room temperature reduction of GO. Using control experiments, we delineate the role of the three components in the hybrid and show that there is a significant synergy. We show that the catalytic activity for ethanol oxidation primarily stems from the Au nanowires. While TiO2 triggers the formation of oxygenated species on the Au nanowire surface at a lower potential and also imparts photoactivity, rGO provides a conducting support to minimize the charge transfer resistance in addition to stabilizing the Au nanowires. Compared with nanoparticle hybrids, the nanowire hybrids display a much better electrocatalytic performance. In addition to high efficiency, the nanowire hybrids also show a remarkable tolerance towards H2O2. While our study has a direct bearing on fuel cell technology, the insights gained are sufficiently general such that they provide guiding principles for the development of multifunctional ternary hybrids.
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Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.
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Glioblastoma (GBM) is the most common malignant adult primary brain tumor. We profiled 724 cancer-associated proteins in sera of healthy individuals (n = 27) and GBM (n = 28) using antibody microarray. While 69 proteins exhibited differential abundance in GBM sera, a three-marker panel (LYAM1, BHE40 and CRP) could discriminate GBM sera from that of healthy donors with an accuracy of 89.7% and p < 0.0001. The high abundance of C-reactive protein (CRP) in GBM sera was confirmed in 264 independent samples. High levels of CRP protein was seen in GBM but without a change in transcript levels suggesting a non-tumoral origin. Glioma-secreted Interleukin 6 (IL6) was found to induce hepatocytes to secrete CRP, involving JAK-STAT pathway. The culture supernatant from CRP-treated microglial cells induced endothelial cell survival under nutrient-deprivation condition involving CRP-Fc gamma RIII signaling cascade. Transcript profiling of CRP-treated microglial cells identified Interleukin 1 beta (IL1 beta) present in the microglial secretome as the key mediator of CRP-induced endothelial cell survival. IL1 beta neutralization by antibody-binding or siRNA-mediated silencing in microglial cells reduced the ability of the supernatant from CRP-treated microglial cells to induce endothelial cell survival. Thus our study identifies a serum based three-marker panel for GBM diagnosis and provides leads for developing targeted therapies. Biological significance A complex antibody microarray based serum marker profiling identified a three-marker panel - LYAM1, BHE40 and CRP as an accurate discriminator of glioblastoma sera from that of healthy individuals. CRP protein is seen in high levels without a concomitant increase of CRP transcripts in glioblastoma. Glioma-secreted IL6 induced hepatocytes to produce CRP in a JAK-STAT signaling dependent manner. CRP induced microglial cells to release IL1 beta which in turn promoted endothelial cell survival. This study, besides defining a serum panel for glioblastoma discrimination, identified IL1 beta as a potential candidate for developing targeted therapy. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
The alarmone (p)ppGpp regulates transcription, translation, replication, virulence, lipid synthesis, antibiotic sensitivity, biofilm formation, and other functions in bacteria. Signaling nucleotide cyclic di-GMP (c-di-GMP) regulates biofilm formation, motility, virulence, the cell cycle, and other functions. In Mycobacterium smegmatis, both (p) ppGpp and c-di-GMP are synthesized and degraded by bifunctional proteins Rel(Msm) and DcpA, encoded by rel(Msm) and dcpA genes, respectively. We have previously shown that the Delta rel(Msm) and Delta dcpA knockout strains are antibiotic resistant and defective in biofilm formation, show altered cell surface properties, and have reduced levels of glycopeptidolipids and polar lipids in their cell wall (K. R. Gupta, S. Kasetty, and D. Chatterji, Appl Environ Microbiol 81:2571-2578, 2015, http://dx.doi.org/10.1128/AEM.03999-14). In this work, we have explored the phenotypes that are affected by both (p) ppGpp and c-di-GMP in mycobacteria. We have shown that both (p) ppGpp and c-di-GMP are needed to maintain the proper growth rate under stress conditions such as carbon deprivation and cold shock. Scanning electron microscopy showed that low levels of these second messengers result in elongated cells, while high levels reduce the cell length and embed the cells in a biofilm-like matrix. Fluorescence microscopy revealed that the elongated Delta rel(Msm) and Delta dcpA cells are multinucleate, while transmission electron microscopy showed that the elongated cells are multiseptate. Gene expression analysis also showed that genes belonging to functional categories such as virulence, detoxification, lipid metabolism, and cell-wall-related processes were differentially expressed. Our results suggests that both (p) ppGpp and c-di-GMP affect some common phenotypes in M. smegmatis, thus raising a possibility of cross talk between these two second messengers in mycobacteria. IMPORTANCE Our work has expanded the horizon of (p) ppGpp and c-di-GMP signaling in Gram-positive bacteria. We have come across a novel observation that M. smegmatis needs (p) ppGpp and c-di-GMP for cold tolerance. We had previously shown that the Delta rel(Msm) and Delta dcpA strains are defective in biofilm formation. In this work, the overproduction of (p) ppGpp and c-di-GMP encased M. smegmatis in a biofilm-like matrix, which shows that both (p) ppGpp and c-di-GMP are needed for biofilm formation. The regulation of cell length and cell division by (p) ppGpp was known in mycobacteria, but our work shows that c-di-GMP also affects the cell size and cell division in mycobacteria. This is perhaps the first report of c-di-GMP regulating cell division in mycobacteria.
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We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.
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The propensity of protein molecules to self-assemble into highly ordered, fibrillar aggregates lies at the heart of understanding many disorders ranging from Alzheimer's disease to systemic lysozyme amyloidosis. In this paper we use highly accurate kinetic measurements of amyloid fibril growth in combination with spectroscopic tools to quantify the effect of modifications in solution conditions and in the amino acid sequence of human lysozyme on its propensity to form amyloid fibrils under acidic conditions. We elucidate and quantify the correlation between the rate of amyloid growth and the population of nonnative states, and we show that changes in amyloidogenicity are almost entirely due to alterations in the stability of the native state, while other regions of the global free-energy surface remain largely unmodified. These results provide insight into the complex dynamics of a macromolecule on a multidimensional energy landscape and point the way for a better understanding of amyloid diseases.