Bridging Bernstein and Lagrange polynomials

Linear combinations of iterates of Bernstein polynomials exponentially converging to Lagrange interpolating polynomial are given. The results are applied in CAGD to get a faster weighted progressive iterative approximation technique to fit data with finer and finer precision

Bridging Bernstein and Lagrange polynomials

Linear combinations of iterates of Bernstein polynomials exponentially converging to Lagrange interpolating polynomial are given. The results are applied in CAGD to get a faster weighted progressive iterative approximation technique to fit data with finer and finer precision

Noise Removal from Remote Sensed Images by NonLocal Means with OpenCL Algorithm

We introduce a multi-platform portable implementation of the NonLocal Means methodology aimed at noise removal from remotely sensed images. It is particularly suited for hyperspectral sensors for which real-time applications are not possible with only CPU based algorithms. In the last decades computational devices have usually been a compound of cross-vendor sets of specifications (heterogeneous system architecture) that bring together integrated central processing (CPUs) and graphics processor (GPUs) units. However, the lack of standardization resulted in most implementations being too specific to a given architecture, eliminating (or making extremely difficult) code re-usability across different platforms. In order to address this issue, we implement a multi option NonLocal Means algorithm developed using the Open Computing Language (OpenCL) applied to Hyperion hyperspectral images. Experimental results demonstrate the dramatic speed-up reached by the algorithm on GPU with respect to conventional serial algorithms on CPU and portability across different platforms. This makes accurate real time denoising of hyperspectral images feasible

Noisy Independent Factor Analysis Model for Density Estimation and Classification

We consider the problem of multivariate density estimation when the unknown density is assumed to follow a particular form of dimensionality reduction, a noisy independent factor analysis (IFA) model. In this model the data are generated by a number of latent independent components having unknown distributions and are observed in Gaussian noise. We do not assume that either the number of components or the matrix mixing the components are known. We show that the densities of this form can be estimated with a fast rate. Using the mirror averaging aggregation algorithm, we construct a density estimator which achieves a nearly parametric rate log^(1/4)n/sqrt(n), independent of the dimensionality of the data, as the sample size $n$ tends to infinity. This estimator is adaptive to the number of components, their distributions and the mixing matrix. We then apply this density estimator to construct nonparametric plug-in classifiers and show that they achieve the best obtainable rate of the excess Bayes risk, to within a logarithmic factor independent of the dimension of the data. Applications of this classifier to simulated data sets and to real data from a remote sensing experiment show promising results

Reelin expression in liver and pancreas and its correlation with liver fibrosis

Reelin is an extracellular glycoprotein secreted by a variety of cell types in both embryonic and adult tissue and plays a critical role during brain development (1,2). Reelin is up-regulated in experimental liver cirrhosis of rats in hepatic stellate cell(HSC)s, the cell type mainly implicated in liver fibrogenesis, supporting that reelin is involved in the pathogenesis of liver fibrosis (3). Pancreatic stellate cell(PSC)s share similar morphology and function to HSCs, in pancreatic fibrosis setting (4). Currently, the role of reelin in human liver and pancreas is still unclear. We investigated reelin expression in different stages of chronic liver disease in 81 liver biopsies of HCV affected patients and in pancreatic tissue near to tumoral lesions. The expression of Reelin, HSC markers (CRBP1, alpha-SMA) and Dab1, a Reelin adaptor protein, was investigated by immunohistochemistry and immunofluorescence. Reelin protein was expressed by HSCs and a strong correlation was found between Reelin expression and liver fibrosis stage (

Th17-Gene Expression Profile in Patients with Chronic Venous Disease and Venous Ulcers: Genetic Modulations and Preliminary Clinical Evidence

Chronic venous disease is a condition globally widespread, resulting in a disabling pathological disorder. The CD4 + Th17+ (Cluster Differentiation 4) lymphocytes represent a regulative factor for innate immunity related to the development of complex diseases. Recently, these mechanisms have been associated with vascular disease. The aim of this work is to validate whether the Th17 response correlates with the development of CVI (Chronic venous insufficiency)and CVLUs (chronic venous limbs ulcers) and whether Th17 markers can be used, both as intrinsic risk factors and diagnostic markers, for disease development. PBL derived from peripheral blood samples of patients and controls were subjected to gene expression analysis for IL23R, IL17, SGK1, TGFβ, RORγ, FOXO1, and RANBP1 by qRT-PCR and immunoblot. A post hoc correlation, the diagnostic performance of the target genes, and multivariable analyses were properly conducted. The main expression markers of the CD4 + Th17+ switch were strongly activated in chronic venous insufficiency and in advanced ulceration. The correlation analysis demonstrated the inter-dependence on Th17’s signature modulation. ROC (Receiver Operating Characteristic) analysis defined, for the examined genes, a clinical value as the potential diagnostic markers. Multi-logistic regression studies showed that Th17 markers behave as empirical risk factors for CVD (chronic venous disease) development. Taken together, the present data provide a new hypothesis for the TH17-dependent pathogenesis of CVD, favoring the possibility for the development of new diagnostic, preventive, and therapeutic approaches

"Until death do us part". A multidisciplinary study on human- Animal co- burials from the Late Iron Age necropolis of Seminario Vescovile in Verona (Northern Italy, 3rd-1st c. BCE).

Animal remains are a common find in prehistoric and protohistoric funerary contexts. While taphonomic and osteological data provide insights about the proximate (depositional) factors responsible for these findings, the ultimate cultural causes leading to this observed mortuary behavior are obscured by the opacity of the archaeological record and the lack of written sources. Here, we apply an interdisciplinary suite of analytical approaches (zooarchaeological, anthropological, archaeological, paleogenetic, and isotopic) to explore the funerary deposition of animal remains and the nature of joint human-animal burials at Seminario Vescovile (Verona, Northern Italy 3rd-1st c. BCE). This context, culturally attributed to the Cenomane culture, features 161 inhumations, of which only 16 included animal remains in the form of full skeletons, isolated skeletal parts, or food offerings. Of these, four are of particular interest as they contain either horses (Equus caballus) or dogs (Canis lupus familiaris)-animals that did not play a dietary role. Analyses show no demographic, dietary, funerary similarities, or genetic relatedness between individuals buried with animals. Isotopic data from two analyzed dogs suggest differing management strategies for these animals, possibly linked to economic and/or ritual factors. Overall, our results point to the unsuitability of simple, straightforward explanations for the observed funerary variability. At the same time, they connect the evidence from Seminario Vescovile with documented Transalpine cultural traditions possibly influenced by local and Roman customs

Reelin expression by hepatic stellate cells and ductular reaction in HCV related liver fibrosis

Reelin is a secreted extracellular glycoprotein that is thought to guide migrat- ing neurons during brain development and maturation cooperating with Disabled-1 (Dab1), an adaptor protein obligate effector of reelin signalling pathway (1). Reelin is also expressed in human liver by hepatic stellate cell(HSC)s that following liver injury become activated, migrating and fibrogenic cells (2). The cross-talk between HSCs and other cells such as those of ductular reaction (DR) is believed to rule liver fibrogenesis leading to cirrhosis (3). In order to better understand the role of ree- lin in human liver tissue with ongoing fibrosis, we aim to analyse the hepatic reelin expression and its relationship with the main histological determinants of the dis- ease activity and severity. Eighty-one liver biopsies of patients with chronic hepatitis C were studied. The expression of Reelin, Dab1, and HSC markers was investigated by immunohistochemistry and immunofluorescence. The Knodell histology activity index and DR score were evaluated. Activated HSC were frequently reelin positive and a statistical correlation was found between the number of reelin positive HSCs and Knodell’s stage (r= 0,3; p<0,05). Dab1 was expressed by cells of DR and the number of reelin positive HSCs correlated with DR score in mild/moderate fibrosis (r=0,4; p<0,05). Since reelin expression by HSCs correlates with increasing fibrosis and DR, whose cells in turn express Dab1, it might act as mediator in DR activation by HSCs. Further studies are needed to test reelin as useful biomarker for liver fibrosis assess- ment