A New Methodology for Efficient Classification of Multispectral Satellite Images Using Neural Network Techniques

A methodology based on self-organizing feature maps and indexing techniques for time and memory efficient neural network training and classification of large volumes of remotely sensed data is presented. Results on land-cover classification of multispectral satellite images using two popular neural models show orders of magnitude of speedup with respect to both training and classification times. The generality of the proposed methodology is demonstrated with a dramatic improvement of the classification time of the k-nearest neighbors statistical classifier.     

API-Evolution Support with Diff-CatchUp

Applications built on reusable component frameworks are subject to two independent, and potentially conflicting, evolution processes. The application evolves in response to the specific requirements and desired qualities of the application's stakeholders. On the other hand, the evolution of the component framework is driven by the need to improve the framework functionality and quality while maintaining its generality. Thus, changes to the component framework frequently change its API on which its client applications rely and, as a result, these applications break. To date, there has been some work aimed at supporting the migration of client applications to newer versions of their underlying frameworks, but it usually requires that the framework developers do additional work for that purpose or that the application developers use the same tools as the framework developers. In this paper, we discuss our approach to tackle the API-evolution problem in the context of reuse-based software development, which automatically recognizes the API changes of the reused framework and proposes plausible replacements to the "obsolete" API based on working examples of the framework code base. This approach has been implemented in the Diff-CatchUp tool. We report on two case studies that we have conducted to evaluate the effectiveness of our approach with its Diff-CatchUp prototype.     

Regulatory Noncoding and Predicted Pathogenic Coding Variants of CCR5 Predispose to Severe COVID-19

Genome-wide association studies (GWAS) found locus 3p21.31 associated with severe COVID-19. CCR5 resides at the same locus and, given its known biological role in other infection diseases, we investigated if common noncoding and rare coding variants, affecting CCR5, can predispose to severe COVID-19. We combined single nucleotide polymorphisms (SNPs) that met the suggestive significance level (P ≤ 1 × 10⁻⁵) at the 3p21.31 locus in public GWAS datasets (6406 COVID-19 hospitalized patients and 902,088 controls) with gene expression data from 208 lung tissues, Hi-C, and Chip-seq data. Through whole exome sequencing (WES), we explored rare coding variants in 147 severe COVID-19 patients. We identified three SNPs (rs9845542, rs12639314, and rs35951367) associated with severe COVID-19 whose risk alleles correlated with low CCR5 expression in lung tissues. The rs35951367 resided in a CTFC binding site that interacts with CCR5 gene in lung tissues and was confirmed to be associated with severe COVID-19 in two independent datasets. We also identified a rare coding variant (rs34418657) associated with the risk of developing severe COVID-19. Our results suggest a biological role of CCR5 in the progression of COVID-19 as common and rare genetic variants can increase the risk of developing severe COVID-19 by affecting the functions of CCR5.     

Role of microporosity and surface chemistry in adsorption of 4,6-dimethyldibenzothiophene on polymer-derived activated carbons

Two carbon samples derived from poly(4-styrenesulfonic acid-co-maleic acid) based polymer by carbonization between 700 and 800 °C were oxidized to two different levels of surface acidity. The surfaces of resulting adsorbents were characterized by potentiometric titration, adsorption of nitrogen, FTIR, SEM/EDAX and thermal analysis. The materials were used as adsorbents of 4,6-dimethyldibenzothiophene (4,6-DMDBT) from hexadecane with initial concentration of sulfur between 10-150 ppmw. Although it was found that pores with diameter less than 10 Å govern the amount of 4,6-DMDBT adsorbed, that amount is enhanced when acidic groups are present in the larger pores owing to the contributions of specific interactions. Surface chemistry plays an important role in reactive adsorption and deposition of the products of surface reactions in the pore system.     

Evaluation of the antiradical and reducing properties of selected Greek white wines: correlation with polyphenolic composition

The total hydroxycinnamate (THC) and total flavanol (TF) contents were determined in 26 selected Greek white wines of ‘Appellation of Origin of High Quality’ using well‐established spectrophotometric methodology. Furthermore, two parameters related to the antioxidant capacity of wines, the antiradical activity (A_AR) and the reducing power (P_R), were also determined using the stable DPPH· radical and a ferric reducing power assay respectively. THC content varied from 64.4 to 197.1 mg l^?1 chlorogenic acid equivalents (CGAE), whereas TF content exhibited larger variation, ranging from 3.3 to 205.3 mg l^?1 catechin equivalents (CTE). A_AR and P_R were found to range from 0.47 to 0.60 mM Trolox equivalents (TRE) and from 0.32 to 2.05 mM quercetin equivalents (QE) respectively. Regression analysis at 95% significance level indicated that reducing effects are likely to be exerted by the flavanol fraction (SF < 0.05), as opposed to antiradical efficiency which is primarily affected by the sum of THC and TF contents (SF < 0.05), suggesting that synergistic phenomena account for the overall antioxidant status of white wines. © 2002 Society of Chemical Industry