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This paper presents a simulation of the structural and optoelectronic properties of Scandium Arsenide (ScAs) and Aluminum Arsenide (AlAs) compounds. Theoretical modeling was performed using ab initio first-principles calculations, specifically the density functional theory (DFT), and the Mindlab numerical software. The software used two methods: the full-potential muffin-tin orbital method (FP-LMTO) and the full-potential plane-wave method (FP-LAPW). These two methods are employed to solve the Schrödinger equation. The exchange correlation effects have been computed using two different approximations: the generalized gradient approximation (GGA) and the local density approximation (LDA). Our findings indicate that the zinc blende structure (B3) is the stable phase, while the Wurtzite phase (B4) is metastable for the AlAs compound. On the other hand, the ScAs compound crystallizes in the NaCl phase (B1). The AlAs compounds undergo three phase transitions: $\mathrm{\text{B3}}\to \mathrm{\text{B4}}$, $\mathrm{\text{B3}}\to \mathrm{\text{B2}}$ and $\mathrm{\text{B3}}\to \mathrm{\text{B1}}$. In contrast, ScAs does not undergo any transition. The obtained results for equilibrium energies, lattice parameters and gap energies are in closer agreement with the experimental and theoretical data. The AlAs compound exhibits a semiconducting character, while ScAs exhibits a semi-metallic character. Additionally, the refractive index of these two compounds is similar to that of silicon, which is crucial for their application in photovoltaic cells.

In this paper, we present the implementation of the Density Functional Theory (DFT) method using the Geant4-DNA framework in the Single Instruction Single Data (SISD) mode. Furthermore, this implementation is improved in terms of execution time within the GeantV project with vectorization techniques such as Single Instruction Multiple Data (SIMD). Within this framework, a set of SIMD strategies in molecular calculation algorithms such as one-electron operators, two-electron operator, quadrature grids, and functionals, was implemented using the VecCore library. The applications developed in this work implement two DFT functionals, the Local Density Approximation (LDA) and the General Gradient Approximation (GGA), to approximate the molecular ground-state energies of small molecules and amino acids. To assess the performance of the implementations, a standard test simulation was performed in multiple CPU platforms. The SIMD vectorization strategy significantly accelerates DFT calculations, leading to time ratios ranging from 1.6 to 5.4 in either individual steps or entire implementations when compared with the scalar process within Geant4.

Accurately quantifying the goodness of music based on the seemingly subjective taste of the public is a multi-million industry. Recording companies can make sound decisions on which songs or artists to prioritize if accurate forecasting is achieved. We extract 56 single-valued musical features (e.g. pitch and tempo) from 380 Original Pilipino Music (OPM) songs (190 are hit songs) released from 2004 to 2006. Based on an effect size criterion which measures a variable's discriminating power, the 20 highest ranked features are fed to a classifier tasked to predict hit songs. We show that regardless of musical genre, a trained feed-forward neural network (NN) can predict potential hit songs with an average accuracy of Φ_NN = 81%. The accuracy is about +20% higher than those of standard classifiers such as linear discriminant analysis (LDA, Φ_LDA = 61%) and classification and regression trees (CART, Φ_CART = 57%). Both LDA and CART are above the proportional chance criterion (PCC, Φ_PCC = 50%) but are slightly below the suggested acceptable classifier requirement of 1.25*Φ_PCC = 63%. Utilizing a similar procedure, we demonstrate that different genres (ballad, alternative rock or rock) of OPM songs can be automatically classified with near perfect accuracy using LDA or NN but only around 77% using CART.

Word adjacency networks constructed from written works reflect differences in the structure of prose and poetry. We present a method to disambiguate prose and poetry by analyzing network parameters of word adjacency networks, such as the clustering coefficient, average path length and average degree. We determine the relevant parameters for disambiguation using linear discriminant analysis (LDA) and the effect size criterion. The accuracy of the method is 74.9 ± 2.9% for the training set and 73.7 ± 6.4% for the test set which are greater than the acceptable classifier requirement of 67.3%. This approach is also useful in locating text boundaries within a single article which falls within a window size where the significant change in clustering coefficient is observed. Results indicate that an optimal window size of 75 words can detect the text boundaries.

The phonon spectra, band structure and density of states of cubic perovskite SnTiO₃ were investigated using first-principles density functional theory (DFT) computation. The potential energy curves of cations displacement and the formation energy of Sn substitution to B-site were calculated to estimate the structure stability. The results indicate that perovskite SnTiO₃ is a promising ferroelectric end member for lead-free piezoelectric materials and applications.

We present results from ab-initio, self-consistent local density approximation (LDA) calculations of electronic and related properties of zinc blende indium phosphide (InP) and gallium phosphide (GaP). We employed a LDA potential and implemented the linear combination of atomic orbitals (LCAO) formalism. This implementation followed the Bagayoko, Zhao and Williams (BZW) method, as enhanced by Ekuma and Franklin (BZW–EF). This method searches for the optimal basis set that yields the minima of the occupied energies. This search entails increases of the size of the basis set and the related modifications of angular symmetry and of radial orbitals. Our calculated, direct band gap of 1.398 eV (1.40 eV), at the Γ point, is in excellent agreement with experimental values, for InP, and our preliminary result for the indirect gap of GaP is 2.135 eV, from the Γ to X high symmetry points. We have also calculated electron and hole effective masses for both InP and GaP. These calculated properties also agree with experimental findings. We conclude that the BZW–EF method could be employed in calculations of electronic properties of high-T_c superconducting materials to explain their complex properties.

We studied the crystal structure of perovskite BiAlO₃ using ab initio density functional theory (DFT) calculations. Using the atomic positions given by the previous literature, we were able to create a lattice structure using visualization software Material Studio. Such sophisticated structure is found in rhombohedral perovskite system with space group with R3c (#161) and lattice parameter of $a=b=c=5.338\mathrm{\text{Å}}$, bond angle of $\alpha =\beta =\gamma =60^{\circ }$, while treating the exchange–correlation potential with the local density approximations (LDA) method. The calculations were performed to investigate the electronic, optical, elastic and phonon properties.

The electronic structure and density of states (DOS) of BaMnO₃ compound are studied in the framework of density functional theory (DFT) using the generalized gradient approximation (GGA) and local density approximation (LDA). A number of different exchange-correlation functionals including hybrid (PBE, PZ and BLYP) exchange techniques have been used. The results show that in ambient conditions, the compound has metallic structure. It has been found from DOS calculations that the overlapping of bands near the Fermi energy are mainly due to the 3d state of Mn atoms.

This chapter deals with the calibration of a new simplified experimental method to evaluate absolute roughness of vegetated channels. The method is based on boundary layer measurements in a short channel rather than on uniform flow measurements, as usual. The proposed method can be applied to any kind of rough bed, but it is particularly useful in vegetated beds where long channels are difficult to prepare. In this paper a calibration coefficient is experimentally obtained. In order to perform suitable comparisons with literature data relationships between ε absolute roughness and Manning's n coefficient are deepened. The results are successfully compared with literature experimental data with a very good fit. Finally, a particular dependence of ε values on the vegetation density are explained through further experiences. In conclusion it is possible to state that the proposed method, once calibrated, can provide reliable prediction of absolute roughness in vegetated channels.

Classification techniques are routinely utilized on satellite images. Pansharpening techniques can be used to provide super resolved multispectral images that can improve the performance of classification methods. So far, these pansharpening methods have been explored only as a preprocessing step. In this work we address the problem of adaptively modifying the pansharpening method in order to improve the precision and recall figures of merit of the classification of a given class without significantly deteriorating the performance of the classifier over the other classes. The validity of the proposed technique is demonstrated using a real Quickbird image.