Using HCMM Thermal Data to Improve Classification of MSS Data

Spectral overlap between urban and rural land use/land cover categories can lead to unacceptable map accuracy levels in the classification of LANDSAT multispectral scanner (MSS) data. The four MSS bands used alone are not always adequate to distinguish among various land uses and cover types having similar spectral responses. The use of thermal data from the Heat Capacity Mapping Mission (HCMM) satellite as a means of improving MSS land cover classification accuracies for urban versus rural categories was investigated. The approaches used to integrate the HCMM data are described

Adaptive Meshing for Deep-drawing Process

The paper incorporates the concept of adaptive meshing for finite-element analysis of the deep-drawing process. In adaptive meshing, the mesh is automatically refined both in the areas of insufficient accuracy and sharp stress gradients. The Zienkiewicz-Zhu error estimator based upon the difference between the finite-element solution and the corresponding smoothened solution is used to judge the accuracy both at the element and the global levels. The post-processing for determining more accurate solutions is done by fitting a higher order polynomial expansion to the finite-element solution in nodal patches. An illustrative problem is solved and the adaptive refinement at differention is presented

Finite Element Simulation of Sheet Metal Forming Processes

In the present study, the survey of research work on finite element analysis of metal forming processes has been carried out. A classification of formulations dealing with geometry and material nonlinearity in the context of finite element simulation of forming operations has been recapitulated. The procedures based upon shell and continuum approaches and methods of dealing withfrictional contact, are described. Topics of current interest on finite element analysis such as error estimation, projection of error, and adaptive mesh refinement have been reviewed

Importance-performance analysis of UK and US bank customer perceptions of service delivery technologies

Importance-performance analysis is utilised to compare the perceptions held by bank customers regarding selected service delivery technologies (SDTs) such as automated teller machines (ATMs), telephone banking and internet banking. Bank patrons in the United Kingdom and the United States are surveyed to examine which service delivery factors they consider to be most important toward assessing the performance of SDTs offered by banking institutions. Customer views are plotted onto importance-performance grids which offer banking strategists a straightforward, graphic illustration of service factors that patrons consider to be salient and well-addressed by current installations of bank SDTs in each respective nation. The grids also offer heuristic decision guides for translating customer perceptions into strategic allocations of organisational investments toward SDT

MicroRNA-383 located in frequently deleted chromosomal locus 8p22 regulates CD44 in prostate cancer.

A major genomic alteration in prostate cancer (PCa) is frequent loss of chromosome (chr) 8p with a common region of loss of heterozygosity (LOH) at chr8p22 locus. Genomic studies implicate this locus in the initiation of clinically significant PCa and with progression to metastatic disease. However, the genes within this region have not been fully characterized to date. Here we demonstrate for the first time that a microRNA component of this region-miR-383-is frequently downregulated in prostate cancer, has a critical role in determining tumor-initiating potential and is involved in prostate cancer metastasis via direct regulation of CD44, a ubiquitous marker of PCa tumor-initiating cells (TICs)/stem cells. Expression analyses of miR-383 in PCa clinical tissues established that low miR-383 expression is associated with poor prognosis. Functional data suggest that miR-383 regulates PCa tumor-initiating/stem-like cells via CD44 regulation. Ectopic expression of miR-383 inhibited tumor-initiating capacity of CD44+ PCa cells. Also, 'anti-metastatic' effects of ectopic miR-383 expression were observed in a PCa experimental metastasis model. In view of our results, we propose that frequent loss of miR-383 at chr8p22 region leads to tumor initiation and prostate cancer metastasis. Thus, we have identified a novel finding that associates a long observed genomic alteration to PCa stemness and metastasis. Our data suggest that restoration of miR-383 expression may be an effective therapeutic modality against PCa. Importantly, we identified miR-383 as a novel PCa tissue diagnostic biomarker with a potential that outperforms that of serum PSA

Kinetic models for dilute solutions of dumbbells in non-homogeneous flows revisited

We propose a two fluid theory to model a dilute polymer solution assuming that it consists of two phases, polymer and solvent, with two distinct macroscopic velocities. The solvent phase velocity is governed by the macroscopic Navier-Stokes equations with the addition of a force term describing the interaction between the two phases. The polymer phase is described on the mesoscopic level using a dumbbell model and its macroscopic velocity is obtained through averaging. We start by writing down the full phase-space distribution function for the dumbbells and then obtain the inertialess limits for the Fokker-Planck equation and for the averaged friction force acting between the phases from a rigorous asymptotic analysis. The resulting equations are relevant to the modelling of strongly non-homogeneous flows, while the standard kinetic model is recovered in the locally homogeneous case

Transport processes in the soil as factors of potassium availability

RESP-892

Sufficient Covariate, Propensity Variable and Doubly Robust Estimation

Statistical causal inference from observational studies often requires adjustment for a possibly multi-dimensional variable, where dimension reduction is crucial. The propensity score, first introduced by Rosenbaum and Rubin, is a popular approach to such reduction. We address causal inference within Dawid's decision-theoretic framework, where it is essential to pay attention to sufficient covariates and their properties. We examine the role of a propensity variable in a normal linear model. We investigate both population-based and sample-based linear regressions, with adjustments for a multivariate covariate and for a propensity variable. In addition, we study the augmented inverse probability weighted estimator, involving a combination of a response model and a propensity model. In a linear regression with homoscedasticity, a propensity variable is proved to provide the same estimated causal effect as multivariate adjustment. An estimated propensity variable may, but need not, yield better precision than the true propensity variable. The augmented inverse probability weighted estimator is doubly robust and can improve precision if the propensity model is correctly specified