Explosive chemistry: Simulating the chemistry of energetic materials at extreme conditions

In this article, we review recent atomistic computational techniques to study the electronic structure aspects and chemistry of energetic materials at high-pressure and/or high temperature. While several mechanisms have been proposed for the initial events of energetic materials at high-pressure, we explore the validity of a proposed shear-induced local metallization via molecular bond bending in the insensitive explosive TATB. We study the effect of high-stress (both uniform and uniaxial) on the electronic energy band-gap and the first chemical event of a prototypical energetic material, that of nitromethane. We also determine chemical reactions rate laws and decomposition mechanisms from a quantum-based molecular dynamics simulation of HMX, a widely used explosive material, at conditions of high density and temperature similar to that encounter under detonation. Finally, we review a new multi-scale computational tool recently developed to model the shock-induced chemistry of energetic materials at the atomistic level, and report its applicability to shocked solid nitromethane. This revised version was published online in June 2006 with corrections to the Cover Date.     

Phytochemical and biological investigation of <Emphasis Type="Italic">Stevia rebaudiana</Emphasis> Bertoni; 1-labdane-type diterpene

Five labdane diterpenoids, austroinulin, iso-austroinulin, sterebin E, sterebin E acetate, and sterebin A acetate, along with hydrocarbons, aliphatic alcohols, β-amyrin, β-sitosterol and stigmasterol were isolated from the chloroform soluble fraction of the methanol extract of Stevia rebaudiana leaves. Chlorogenic and caffeic acids were isolated from the EtOAc fraction. All the isolated compounds were identified using spectral tools. The chloroform and methanol extracts proved significant anti-inflammatory effect and caused marked inhibition of carrageenan-induced paw oedema in rats.     

A new application of Hydroxyapatite extracted from dromedary bone: Adsorptive removal of Congo red from aqueous solution

The aim of this paper is to evaluate the efficiency of the natural hydroxyapatite powder for anionic dye (Congo red) elimination from water and optimization of adsorption process parameters that are contact time (0-360 min), solution pH (4-9), initial dye concentration (400-2400 mg/l), and adsorbent dosage (0.4-20 g/l). Natural hydroxyapatite with high surface area was prepared from animal agriculture waste dromedary bone. X-ray diffraction, transmission electron microscopy, transform infrared spectroscopy, and elemental analysis characterizations of the powder prepared show a hexagonal structure, the irregular form of hydroxyapatite and presence of other elements as trace element. The results of adsorption tests demonstrated the high efficiency of natural hydroxyapatite for removal of Congo red from water solution whose maximum experimental capacity adsorption of Congo red by natural hydroxyapatite is 900 mg/g at pH 4.5, equilibrium time 240 min and adsorbent dosage 2 g/l. According to the correlation coefficient value, the pseudo-second order kinetic model identified the sorption mechanism of pollutant used on natural hydroxyapatite. The Freundlich isotherm is the best representative theoretical model of the dye molecules’ adsorption on the natural hydroxyapatite support.     

An industrial portrait background removal solution based on knowledge infusion

Background removal of an identity (ID) picture consists in separating the foreground (face, body, hair and clothes) from the background of the image. It is a necessary groundwork for all modern identity documents that also has many benefits for improving ID security. State of the art image processing techniques encountered several segmentation issues and offer only partial solutions. It is due to the presence of erratic components like hairs, poor contrast, luminosity variation, shadow, color overlap between clothes and background. In this paper, a knowledge infused approach is proposed that hybridizes smart image processing tasks and prior knowledge. The research is based on a divide and conquer strategy aiming at simulating the sequential attention of human when performing a manual segmentation. Knowledge is infused by considering the spatial relation between anatomic elements of the ID image (face feature, forehead, body and hair) as well as their “signal properties”. The process consists in first determining a convex hull around the person’s body including all the foreground while keeping very close to the contour between the background and the foreground. Then, a body map generated from biometric analysis associated to an automatic grab cut process is applied to reach a finer segmentation. Finally, a heuristic-based post-processing step consisting in correcting potential hair and fine boundary issues leads to the final segmentation. Experimental results show that the newly proposed architecture achieves better performances than tested current state-of-the-art methodologies including active contours, generalist popular deep learning techniques, and also two other ones considered as the smartest for portrait segmentation. This new technology has been adopted by an international company as its industrial ID foreground solution.

     

Hysteresis‐Free 1D Network Mixed Halide‐Perovskite Semitransparent Solar Cells

The morphology of hybrid organic–inorganic perovskite films is known to strongly affect the performance of perovskite‐based solar cells. CH₃NH₃PbI_3‐xCl_x (MAPbI_3‐xCl_x) films have been previously fabricated with 100% surface coverage in glove boxes. In ambient air, fabrication generally relies on solvent engineering to obtain compact films. In contrast, this work explores the potential of altering the perovskites microstructure for solar cell engineering. This work starts with CH₃NH₃PbI_3‐xCl_x, films with grain morphology carefully controlled by varying the deposition speed during the spin‐coating process to fabricate efficient and partially transparent solar cells. Devices produced with a CH₃NH₃PbI_3‐xCl_x film and a compact thick top gold electrode reach a maximum efficiency of 10.2% but display a large photocurrent hysteresis. As it is demonstrated, the introduction of different concentrations of bromide in the precursor solution addresses the hysteresis issues and turns the film morphology into a partially transparent interconnected network of 1D microstructures. This approach leads to semitransparent solar cells with negligible hysteresis and efficiencies up to 7.2%, while allowing average transmission of 17% across the visible spectrum. This work demonstrates that the optimization of the perovskites composition can mitigate the hysteresis effects commonly attributed to the charge trapping within the perovskite film.     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

A predictive bottom-up parser

Despite all advances in parsing, parser size, conflict resolution and error recovery are still of important consideration. In this research, we propose a predictive bottom-up parser. The parser is implemented in two versions. Both versions constitute an algorithm that simulates the run of a shift–reduce automaton, defined and constructed in a way that integrates its parsing actions with reduction prediction, conflict resolution and error recovery. However, the first implementation version performs explicit shift–reduce parsing actions based on implicit prediction of the reduction sequences. The second one performs parsing actions based on explicit prediction of the reduction sequences with implied shift–reduce actions. The proposed parser has been experimented against the ones based on similar approaches. 10–20% reduction of the parser size has been achieved, with a parsing behaviour proportional to a factor reflecting the grammar ambiguity.     

Analysis of the Earthʼs magnetic field variations on the basis of a wavelet-based approach

In the present paper we will discuss a new wavelet-based approach aimed at processing and analyzing different features of complex geomagnetic signals. This approach makes it possible to automatically extract different kinds of disturbances in the Earth?s magnetic field variations, which characterize solar activity and help to predict magnetic storms. In order to analyze geomagnetic signals wavelet packets are used in order to isolate local variations for quiet and perturbed periods and determine their intensity. Furthermore, a new automatic method of calculating the index of geomagnetic activity K is suggested on the basis of forming a quiet-day diurnal variation (Sq-curve). This method allows us to do calculations in the way that is closest to that developed by J. Bartels, who introduced the K-index in 1938. The results are compared with those obtained by INTERMAGNET and the original method of J. Bartels and the advantages of the suggested method are clearly demonstrated. For geomagnetic data collected in high-latitude regions of our planet it has become possible to reduce the error of estimating the K-index by 20% and unlike the technique used by INTERMAGNET here all the calculations can be done automatically. We will use geomagnetic signals that were kindly provided to us by the Institute of Cosmophysical Research and Radio Wave Propagation (Paratunka, Kamchatka region, Far East of Russia) for the period from January, 2002 till December, 2010.     

Comparison of an effect-model-law-based method versus traditional clinical practice guidelines for optimal treatment decision-making: application to statin treatment in the French population

Healthcare authorities make difficult decisions about how to spend limited budgets for interventions that guarantee the best cost-efficacy ratio. We propose a novel approach for treatment decision-making, OMES—in French: Objectif thérapeutique Modèle Effet Seuil (in English: Therapeutic Objective–Threshold–Effect Model; TOTEM). This approach takes into consideration results from clinical trials, adjusted for the patients'' characteristics in treatment decision-making. We compared OMES with the French clinical practice guidelines (CPGs) for the management of dyslipidemia with statin in a computer-generated realistic virtual population, representing the adult French population, in terms of the number of all-cause deaths avoided (number of avoided events: NAEs) under treatment and the individual absolute benefit. The total budget was fixed at the annual amount reimbursed by the French social security for statins. With the CPGs, the NAEs was 292 for an annual cost of 122.54 M€ compared with 443 with OMES. For a fixed NAEs, OMES reduced costs by 50% (60.53 M€ yr⁻¹). The results demonstrate that OMES is at least as good as, and even better than, the standard CPGs when applied to the same population. Hence the OMES approach is a practical, useful alternative which will help to overcome the limitations of treatment decision-making based uniquely on CPGs.