A posteriori error estimates of finite element method for the time-dependent Darcy problem in an axisymmetric domain

We consider the time dependent Darcy problem in a three-dimensional axisymmetric domain and, by writing the Fourier expansion of its solution with respect to the angular variable, we observe that each Fourier coefficient satisfies a system of equations on the meridian domain. We propose a discretization of these equations in the case of general solution. This discretization relies on a backward Euler’s scheme for the time variable and finite elements for the space variables. We prove a posteriori error estimates that allow for an efficient adaptivity strategy both for the time steps and the meshes. Computations for an example with a known solution are presented which support the a posteriori error estimate.     

Surface modification of halogenated polymers. 4. Functionalisation of poly(tetrafluoroethylene) surfaces by diazonium salts

Reduced PTFE can be grafted by nitro and bromo-phenyl diazonium tetrafluoroborate salts in a manner similar to that used for carbon, except that no application of a reductive potential during grafting was required. Grafting was evidenced by cyclic voltammetry, X-ray fluorescence or ToF-SIMS. Nitro- and bromo-phenyl moieties were covalently linked to the PTFE material and could be eliminated only by abrasion.     

Influence of alkali metal (Li and Cs) addition to Mo2N catalyst for CO hydrogenation to hydrocarbons and oxygenates

The aim of this work is to understand the catalytic behaviour of Li and Cs promoted Mo₂N for CO hydrogenation to hydrocarbons and oxygenates at the reaction conditions 275–325 °C, 7 MPa, and 30 000 h^?1 GHSV. Molybdenum nitrides were synthesized via temperature programmed treatment of ammonium heptamolybdate (AHM) and alkali metal (AM) precursors under continuous gaseous ammonia flow. Unpromoted Mo₂N and AM‐Mo₂N catalysts were characterized using BET‐pore size, X‐ray diffraction, TPD‐mass of CO, HR‐TEM, and XPS techniques. Nominal loadings of 1, 5, and 10 wt% of Li and Cs were selected for these studies. At a 10 % CO conversion level, the total oxygenate selectivity of 28, 11, and 6.5 % was observed on 5Cs‐Mo₂N, 5Li‐Mo₂N, and unpromoted Mo₂N, respectively. The decreased oxygenate selectivity for unpromoted Mo₂N was mainly associated with CO dissociative hydrogenation on Mo^δ+ sites. On the other hand, improved molecular CO insertion into ?C_xH_y intermediate accelerates the total oxygenate formation on the Cs‐Mo‐N catalyst. However, during nitridation, crystal structure changes were observed in Li‐Mo‐N and the obtained oxygenates selectivity was attributed to the Li₂MoO₄ phases. At lower AM loadings, the active sites corresponding to oxygenates formation were inadequate, and at higher AM loadings, surface metallic molybdenum decreased the total oxygenate selectivity.

     

First-principles study of structural, elastic, electronic, and thermal properties of LaAlO3 perovskite

In this paper, we study the structural, elastic and electronic properties of perovskite LaAlO₃ using two different methods: the full-potential linearized augmented plane wave (FP-LAPW) method and the pseudopotential plane wave (PP-PW) scheme in the frame of generalized gradient approximation (GGA). We have evaluated the ground-state quantities such as lattice parameter, bulk modulus and its pressure derivative as well as the elastic constants. Also, we have presented the results of the band structure, densities of states and charge densities. These results were in favourable agreement with previous theoretical works and the existing experimental data. To complete the fundamental characteristics of this compound we have analyzed the thermodynamic properties using the quasi-harmonic Debye model.     

Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture

A growing number of studies have focused on evaluating spectral indices in terms of their sensitivity to vegetation biophysical parameters, as well as to external factors affecting canopy reflectance. In this context, leaf and canopy radiative transfer models are valuable for modeling and understanding the behavior of such indices. In the present work, PROSPECT and SAILH models have been used to simulate a wide range of crop canopy reflectances in an attempt to study the sensitivity of a set of vegetation indices to green leaf area index (LAI), and to modify some of them in order to enhance their responsivity to LAI variations. The aim of the paper was to present a method for minimizing the effect of leaf chlorophyll content on the prediction of green LAI, and to develop new algorithms that adequately predict the LAI of crop canopies. Analyses based on both simulated and real hyperspectral data were carried out to compare performances of existing vegetation indices (Normalized Difference Vegetation Index [NDVI], Renormalized Difference Vegetation Index [RDVI], Modified Simple Ratio [MSR], Soil-Adjusted Vegetation Index [SAVI], Soil and Atmospherically Resistant Vegetation Index [SARVI], MSAVI, Triangular Vegetation Index [TVI], and Modified Chlorophyll Absorption Ratio Index [MCARI]) and to design new ones (MTVI1, MCARI1, MTVI2, and MCARI2) that are both less sensitive to chlorophyll content variations and linearly related to green LAI. Thorough analyses showed that the above existing vegetation indices were either sensitive to chlorophyll concentration changes or affected by saturation at high LAI levels. Conversely, two of the spectral indices developed as a part of this study, a modified triangular vegetation index (MTVI2) and a modified chlorophyll absorption ratio index (MCARI2), proved to be the best predictors of green LAI. Related predictive algorithms were tested on CASI (Compact Airborne Spectrographic Imager) hyperspectral images and, then, validated using ground truth measurements. The latter were collected simultaneously with image acquisition for different crop types (soybean, corn, and wheat), at different growth stages, and under various fertilization treatments. Prediction power analysis of proposed algorithms based on MCARI2 and MTVI2 resulted in agreements between modeled and ground measurement of non-destructive LAI, with coefficients of determination (r²) being 0.98 for soybean, 0.89 for corn, and 0.74 for wheat. The corresponding RMSE for LAI were estimated at 0.28, 0.46, and 0.85, respectively.     

Parameters identification of photovoltaic solar cells and module using the genetic algorithm with convex combination crossover

To design a high-performance photovoltaic (PV) system, the parameters extraction of solar cell models is exceedingly crucial. A new variant of the genetic algorithm (GA) called Genetic Algorithm with Convex Combination Crossover (GACCC) is proposed to identify the unknown electrical parameters of different solar cell models, i.e. single diode, double diode, and PV module. GACCC is achieved by integrating a new crossover operation to maintain a good balance between the intensification of the best solutions and the diversification of the search space. To test the proposed GACCC, we have compared it to the basic GA and with other literature techniques. The results indicate a high performance of developed approach GACCC and a high accuracy of estimated parameters. In addition, the efficiency of the results is confirmed by the good agreement between the experimental I-V data and the simulated results in all cases.     

Density Functional Theory Study on the Thermo-elastic and Magneto-electronic Properties of Double Perovskite Oxides Sr2MNbO6 (M = V,Cr)

Journal of Superconductivity and Novel Magnetism - Double perovskite oxides have attracted much attention in material science and spintronic applications due to their exceptional physical...     

Experimental and numerical validation of hygrothermal transfer in brick wall

In this paper, a mathematical model dealing with a coupled heat, air, and moisture transfer in a building envelope was developed. Based on the three-following driving potential: vapor pressure, dry air pressure, and temperature, an application on a hygrothermal behavior of a real wall was carried out for different climatic conditions. For this purpose, a characterization of the heat and moisture properties of the materials constituting the wall made with red brick and cement mortar was carried out in the laboratory. This was used to evaluate experimentally the input parameters of the model as a function of relative humidity. To validate the numerical model, an experimental platform was improved. The wall was set up in a double-climatic chamber with different boundary conditions, and then the temperature and humidity evolutions were recorded using several sensors within the wall thickness. The results have highlighted a good agreement between numerical simulation results and experimental ones.     

Global outliers detection in wireless sensor networks: A novel approach integrating time-series analysis,entropy, and random forest-based classification.

Wireless sensor networks (WSNs) have recently attracted greater attention worldwide due to their practicality in monitoring, communicating, and reporting specific physical phenomena. The data collected by WSNs is often inaccurate as a result of unavoidable environmental factors, which may include noise, signal weakness, or intrusion attacks depending on the specific situation. Sending high-noise data has negative effects not just on data accuracy and network reliability, but also regarding the decision-making processes in the base station. Anomaly detection, or outlier detection, is the process of detecting noisy data amidst the contexts thus described. The literature contains relatively few noise detection techniques in the context of WSNs, particularly for outlier-detection algorithms applying time series analysis, which considers the effective neighbors to ensure a global-collaborative detection. Hence, the research presented in this article is intended to design and implement a global outlier-detection approach, which allows us to find and select appropriate neighbors to ensure an adaptive collaborative detection based on time-series analysis and entropy techniques. The proposed approach applies a random forest algorithm for identifying the best results. To measure the effectiveness and efficiency of the proposed approach, a comprehensive and real scenario provided by the Intel Berkeley Research Laboratory has been simulated. Noisy data have been injected into the collected data randomly. The results obtained from the experiment then conducted experimentation demonstrate that our approach can detect anomalies with up to 99% accuracy.     

Site-Specific Phosphorylation of Huntingtin Exon 1 Recombinant Proteins Enabled by the Discovery of Novel Kinases

Post-translational modifications (PTMs) within the first 17 amino acids (Nt17) of exon 1 of the Huntingtin protein (Httex1) play important roles in modulating its cellular properties and functions in health and disease. In particular, phosphorylation of threonine and serine residues (T3, S13, and/or S16) has been shown to inhibit Htt aggregation in vitro and inclusion formation in cellular and animal models of Huntington's disease (HD). In this paper, we describe a new and simple methodology for producing milligram quantities of highly pure wild-type or mutant Httex1 proteins that are site-specifically phosphorylated at T3 or at both S13 and S16. This advance was enabled by 1) the discovery and validation of novel kinases that efficiently phosphorylate Httex1 at S13 and S16 (TBK1), at T3 (GCK) or T3 and S13 (TNIK and HGK), and 2) the development of an efficient methodology for producing recombinant native Httex1 proteins by using a SUMO-fusion expression and purification strategy.^[26] As a proof of concept, we demonstrate how this method can be applied to produce Httex1 proteins that are both site-specifically phosphorylated and fluorescently or isotopically labeled. Together, these advances should increase access to these valuable tools and expand the range of methods and experimental approaches that can be used to elucidate the mechanisms by which phosphorylation influences Httex1 or HTT structure, aggregation, interactome, and function(s) in health and disease.