Laser-induced breakdown spectroscopy analysis of energetic materials

A number of energetic materials and explosives have been studied by laser-induced breakdown spectroscopy (LIBS). They include black powder, neat explosives such as TNT, PETN, HMX, and RDX (in various forms), propellants such as M43 and JA2, and military explosives such as C4 and LX-14. Each of these materials gives a unique spectrum, and generally the spectra are reproducible shot to shot. We observed that the laser-produced microplasma did not initiate any of the energetic materials studied. Extensive studies of black powder and its ingredients by use of a reference spectral library have demonstrated excellent accuracy for unknown identification. Finally, we observed that these nitrogen- and oxygen-rich materials yield LIBS spectra in air that have correspondingly different O:N peak ratios compared with air. This difference can help in the detection and identification of such energetic materials.     

A homology model of penicillin acylase from Alcaligenes faecalis and in silico evaluation of its selectivity

A three-dimensional model of the relatively unknown penicillin acylase from Alcaligenes faecalis (PA-AF) was built up by means of homology modeling based on three different crystal structures of penicillin acylase from various sources. An in silico selectivity study was performed to compare this homology model to the structure of the Escherichia coli enzyme (PA-EC) in order to find any selectivity differences between the two enzymes. The program GRID was applied in combination with the principal component analysis technique to identify the regions of the active sites where the PAs potentially engage different interactions with ligands. These differences were further analyzed and confirmed by molecular docking simulations. The PA-AF homology model provided the structural basis for the explanation of the different enantioselectivities of the enzymes previously demonstrated experimentally and reported in the literature. Different substrate selectivities were also predicted for PA-AF compared to PA-EC. Since no crystallographic data are available for PA-AF to date, the three-dimensional homology model represents a useful and efficient tool for fully exploiting this attractive and efficient biocatalyst, particularly in enantioselective acylations of amines.     

CSL model checking algorithms for QBDs

We present an in-depth treatment of model checking algorithms for a class of infinite-state continuous-time Markov chains known as quasi-birth death processes. The model class is described in detail, as well as the logic CSL to express properties of interest. Using a new property-independency concept, we provide model checking algorithms for all the CSL operators. Special emphasis is given to the time-bounded until operator for which we present a new and efficient computational procedure named uniformization with representatives. By the use of an application-driven dynamic stopping criterion, the algorithm stops whenever the property to be checked can be certified (or falsified). A comprehensive case study of a connection management system shows the versatility of our new algorithms.     

An application-centric evaluation of OpenCL on multi-core CPUs

Although designed as a cross-platform parallel programming model, OpenCL remains mainly used for GPU programming. Nevertheless, a large amount of applications are parallelized, implemented, and eventually optimized in OpenCL. Thus, in this paper, we focus on the potential that these parallel applications have to exploit the performance of multi-core CPUs. Specifically, we analyze the method to systematically reuse and adapt the OpenCL code from GPUs to CPUs. We claim that this work is a necessary step for enabling inter-platform performance portability in OpenCL.     

Reference spectra to classify Amazon water types

Reference spectra extracted from spectral libraries can distinguish different water types in images when associated with limnological information. In this study, we compiled available databases into a single spectral library, using field water reflectance spectra and limnological data collected by different researchers and campaigns in the Amazonian region. By using an iterative clustering procedure based on the combination of reflectance and optically active components (OACs), reference spectra representative of the major Amazonian water types were defined from this library. Differences between the resultant limnological classes were also evaluated by paired t-tests at significance level 0.05. Finally, reference spectra were tested for Spectral Angle Mapper (SAM) classification of waters in Hyperion/Earth Observing-One (EO-1) and Medium Resolution Imaging Spectrometer (MERIS)/Environment Satellite (Envisat) images acquired simultaneously as the field campaigns. Results showed highly variable concentrations of OACs due to the complexity of the Amazonian aquatic environments. Ten classes were defined to represent this complexity, broadly grouped into four limnological characteristics: clear waters with low concentrations of OACs (class 1); black waters rich in dissolved organic carbon (DOC) (class 2); waters with large concentrations of inorganic suspended solids (ISSs) (classes 3–7); and waters dominated by chlorophyll-a (chl-a) (classes 8–10). Using the ten reference spectra, SAM classification of the field water curves produced an overall accuracy of 86% with the highest values observed for classes 3, 4, 6 and 7 and the lowest accuracy for classes 1 and 2. The results of paired t-tests confirmed the class differences based on the concentrations of OACs. SAM classification of the Hyperion and MERIS images using ground truth information resulted in overall classification accuracies of 48% and 67%, respectively, with the highest errors associated with specific portions of the scenes that were not adequately represented in the spectral library.     

Commercial activated carbon for the catalytic production of hydrogen via the sulfur-Iodine thermochemical water splitting cycle

Eight commercial activated carbon catalysts were examined for their catalytic activity to decompose hydroiodic acid (HI) to produce hydrogen; a key reaction in the sulfur-iodine (S-I) thermochemical water splitting cycle. Activity was examined under a temperature ramp from 473 to 773 K. No statistically significant correlation was found between the measured catalyst sample properties and catalytic activity. Four of the eight samples were examined for one week of continuous operation at 723 K. All samples appeared to be stable over the period of examination.     

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.     

Development and evaluation of a virtual campus on Second Life: The case of SecondDMI

Video games and new communication metaphors are quickly changing today’s young people habits. Considering the actual e-learning scenarios, embedded in a fully technological enabled environment it is crucial to take advantage of this kind of capabilities to let learning process gain best results.     

Control of vitamin C losses in vegetables prepared at a food service

This study aimed to elaborate a set of measures to control vitamin C losses in vegetables prepared at a food service (FS). Vegetables were randomly selected for vitamin C analysis by high performance liquid chromatography (HPLC) after delivery of raw material and during distribution for consumption of the food prepared. Some principles underlying the Hazards Analysis and Critical Control Points (HACCP) were applied to identify the Nutritional Control Points (NCP) for vitamin C losses. A Nutritional Control Measure (NCM) was adopted for each NCP as well as the monitoring criteria. The vegetables were again collected for vitamin C analysis after adoption of the NCMs. The results indicated reduction of vitamin C losses with NCM adoption.     

Disgust selectively modulates reciprocal fairness in economic interactions.

We report two studies aimed at investigating the effects of distinct negative emotions on pairwise economic interactions. In the ultimatum game, a proposer offers a division of a sum of money to a responder who decides whether to accept the split, or reject and leave both players with nothing. In Experiment 1, we investigated whether induced disgust, as compared to sadness and neutral emotion, specifically influences responders' decisions to reject unfair proposals. In Experiment 2, we assessed whether the effects of disgust were selectively related to social contexts by contrasting interactions with a human partner with those involving a computer. Results showed that relative to being in a sad or neutral mood, induced feelings of disgust significantly increased rejection rates of unfair offers. Moreover, we found that when the partner was not responsible for the fairness violation, such as in the computer-offer condition, the disgust induction failed to affect participants' choices. We conclude by focusing on the hypothesis that disgust and social norm violations may share common computational components, both at a psychological and a neural level. (PsycINFO Database Record (c) 2010 APA, all rights reserved)