469 resultados para PIM-SSM


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Barneko ikerkuntza-txostena

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A point interpolation method with locally smoothed strain field (PIM-LS2) is developed for mechanics problems using a triangular background mesh. In the PIM-LS2, the strain within each sub-cell of a nodal domain is assumed to be the average strain over the adjacent sub-cells of the neighboring element sharing the same field node. We prove theoretically that the energy norm of the smoothed strain field in PIM-LS2 is equivalent to that of the compatible strain field, and then prove that the solution of the PIM- LS2 converges to the exact solution of the original strong form. Furthermore, the softening effects of PIM-LS2 to system and the effects of the number of sub-cells that participated in the smoothing operation on the convergence of PIM-LS2 are investigated. Intensive numerical studies verify the convergence, softening effects and bound properties of the PIM-LS2, and show that the very ‘‘tight’’ lower and upper bound solutions can be obtained using PIM-LS2.

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This paper aims to develop a meshless approach based on the Point Interpolation Method (PIM) for numerical simulation of a space fractional diffusion equation. Two fully-discrete schemes for the one-dimensional space fractional diffusion equation are obtained by using the PIM and the strong-forms of the space diffusion equation. Numerical examples with different nodal distributions are studied to validate and investigate the accuracy and efficiency of the newly developed meshless approach.

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In recent times, zebrafish has garnered lot of popularity as model organism to study human cancers. Despite high evolutionary divergence from humans, zebrafish develops almost all types of human tumors when induced. However, mechanistic details of tumor formation have remained largely unknown. Present study is aimed at analysis of repertoire of kinases in zebrafish proteome to provide insights into various cellular components. Annotation using highly sensitive remote homology detection methods revealed ``substantial expansion'' of Ser/Thr/Tyr kinase family in zebrafish compared to humans, constituting over 3% of proteome. Subsequent classification of kinases into subfamilies revealed presence of large number of CAMK group of kinases, with massive representation of PIM kinases, important for cell cycle regulation and growth. Extensive sequence comparison between human and zebrafish PIM kinases revealed high conservation of functionally important residues with a few organism specific variations. There are about 300 PIM kinases in zebrafish kinome, while human genome codes for only about 500 kinases altogether. PIM kinases have been implicated in various human cancers and are currently being targeted to explore their therapeutic potentials. Hence, in depth analysis of PIM kinases in zebrafish has opened up new avenues of research to verify the model organism status of zebrafish.

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A new algorithm based on the multiparameter neural network is proposed to retrieve wind speed (WS), sea surface temperature (SST), sea surface air temperature, and relative humidity ( RH) simultaneously over the global oceans from Special Sensor Microwave Imager (SSM/I) observations. The retrieved geophysical parameters are used to estimate the surface latent heat flux and sensible heat flux using a bulk method over the global oceans. The neural network is trained and validated with the matchups of SSM/I overpasses and National Data Buoy Center buoys under both clear and cloudy weather conditions. In addition, the data acquired by the 85.5-GHz channels of SSM/I are used as the input variables of the neural network to improve its performance. The root-mean-square (rms) errors between the estimated WS, SST, sea surface air temperature, and RH from SSM/I observations and the buoy measurements are 1.48 m s(-1), 1.54 degrees C, 1.47 degrees C, and 7.85, respectively. The rms errors between the estimated latent and sensible heat fluxes from SSM/I observations and the Xisha Island ( in the South China Sea) measurements are 3.21 and 30.54 W m(-2), whereas those between the SSM/ I estimates and the buoy data are 4.9 and 37.85 W m(-2), respectively. Both of these errors ( those for WS, SST, and sea surface air temperature, in particular) are smaller than those by previous retrieval algorithms of SSM/ I observations over the global oceans. Unlike previous methods, the present algorithm is capable of producing near-real-time estimates of surface latent and sensible heat fluxes for the global oceans from SSM/I data.

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The differential diagnosis of soft tissue tumours poses a considerable challenge for pathologists, especially adipocytic tumours, as these may show considerable overlap in clinical presentation and morphological features with many other mesenchymal neoplasms. Hence, a specific and reliable marker that identifies adipocytic differentiation is much sought. We investigated the immunohistochemical expression of PIM-1 kinase in 35 samples of soft tissue tumours using tissue microarray technology and 49 full sections of adipocytic (n = 26) and non-adipocytic tumours (n = 23). Benign and malignant adipocytic tumours showed strong expression of PIM-1 while the non-adipocytic tumours were either negative or showed only weak staining for the protein. In myxoid liposarcomas, PIM-1 showed a distinct, unique vacuolar staining pattern, clearly outlining fine cytoplasmic lipid vacuoles. By contrast, non-adipocytic myxoid tumours (myxoma, chordoma and myxoid chondrosarcoma) did not show this vacuolar pattern of PIM-1 staining, although vacuolated cells were present on H&E. This differential expression was confirmed at a gene expression level in selected cases. Our results indicate that the expression of PIM-1 in adipose tissue may be a useful marker of adipocytic differentiation, in particular if the staining is both of high intensity and present in a unique, vacuolar pattern.

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Resumen tomado del autor. Incluye imágenes y material anexo

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PIM systems help organise people’s lives by providing address book, schedule and task management facilities. Current PIM’s manage this information by collecting and storing it as textual data. With the advent of the wearable computer, using text only is no longer an efficient and convenient mechanism for managing personal information. A wearable computer should use data from various sensors (video, audio, location, environmental, user state) to organise personal information. In this paper we examine how audio can be used to enhance the facilities provided by text-only PIM’s and present an example implementation of an audio based wearable PIM (wPIM) that has the capability of storing and retrieving PIM information as audio recordings. The results of the user evaluation we conducted, which was carried out outside of the laboratory, suggests that users strongly accept audio as a way to manage their personal information and to augment their memory, supporting our hypothesis that audio enhances wearable personal information management.