Density Approximation Research Articles

Structural, electronic, optical and mechanical properties of oxide-based perovskite ABO3 (A = Cu, Nd and B = Sn, Sc): A DFT study

The structural, electronic, optical and mechanical properties for oxide-based cubic perovskites ABO3 (A ​= ​Nd, Cu and B= Sc, Sn) were investigated employing density functional theory (DFT) within the CASTEP (Cambridge Serial Total Energy Package) code, based on ultra-soft pseudo-potential (USP) plane wave and Perdew Burke Ernzerhof (PBE) exchange-correlation functional of Generalized Gradient Approximation (GGA) and Local Density Approximation (LDA). The structural results showed that all compounds are stable. The computed elastic constants also meet the requirements of mechanical stability, hardness, ductile/brittle and bonding nature of materials. All the compounds have anisotropic nature. The electronic band structure calculations show that CuScO3 and CuSnO3 compounds have indirect band gap nature. NdScO3 compound has a direct band gap and NdSnO3 compounds show metallic behavior. All the compounds were identified as semiconductors, except NdSnO3 compounds. The band gap values were in the best agreement with the information that is already available. Partial density of states (PDOS) and total density of states (TDOS) were employed to measure the degree of localized electrons in different bands. The optical transition in the compounds was computed by fitting the dispersion relation of the imagined component. Optical properties showed that these compounds were excellent absorbers of incident radiation. Therefore, it may be assumed that these compounds could be in employment in optoelectronics to capture the ultraviolet range of solar radiations.

OBJECT DETECTION BASED ON SPECTRAL ANALYSIS USING SOBEL AND ROBERTS EDGE DETECTION ALGORITHM

Aim: This paper proposes novel object detection (OD) approach based on a thorough examination of the image's details and its approximate density chart. Results: Our proposed OD approach is divided into two phases. Knowledge about Spatial Distribution of Objects obtained from a density map that is used to compute initial object positions. With the aid of the original object positions estimated, a saliency map that provides entity boundaries is then used to calculate the bounding boxes with precision, which is inspired by human attention to detail. The scale variance of objects induced by uncertain perspective is a common problem in object density map estimation. A new method for estimating the prior focus for map for any image is proposed. Sobel and Roberts Edge Detection Algorithm are used in this study. The proposed approach is based on sparse defocus dictionary learning on a newly constructed dataset. The focus power is determined by the number of non-zero coefficients of the dictionary atoms. Conclusion: The algorithm's output can capture spatial features and pick the threshold type in a variety of ways. HIGHLIGHTS: Object detection based on spectral analysis using Sobel and Roberts edge detection algorithm proved to be effective when compared with existing methodologies.

Chemical properties of Bimetallic (Au+Pt) using Density Functional Theory

In this work, we present a systematic theoretical study based on the density function theory (DFT), Through which we aim to shed light on the potential effects of dopped gold Au clusters with a platinum Pt atom, and the search for the new structural, chemical properties that gold clusters will have thanks to this doping, Where the study is limited to the selection of clusters with the lowest energy among the other isomers for each cluster size. The resulting stable structures with lower energy reveal three dimensional structures starting at n = 6, Doping Aun clusters with platinum Pt atom leads to improvement in all properties calculated for these clusters. The chemical and electronic properties have been studied and discussed, for example Vertical electronic affinity, adiabatic electronic affinity, enthalpy and chemical hardness as a function of cluster size. All properties were calculated using generalized gradient density approximation (GGA) and locus density approximation (LDA) and compared them with each other. Where it turns out that the results obtained are close to previous theoretical and experimental studies somewhat similar to them. This type of study is presented for the first time using the density function theory.

Comparison of individualized behavioral predictions across anatomical, diffusion and functional connectivity MRI

A fundamental goal across the neurosciences is the characterization of relationships linking brain anatomy, functioning, and behavior. Although various MRI modalities have been developed to probe these relationships, direct comparisons of their ability to predict behavior have been lacking. Here, we compared the ability of anatomical T1, diffusion and functional MRI (fMRI) to predict behavior at an individual level. Cortical thickness, area and volume were extracted from anatomical T1 images. Diffusion Tensor Imaging (DTI) and approximate Neurite Orientation Dispersion and Density Imaging (NODDI) models were fitted to the diffusion images. The resulting metrics were projected to the Tract-Based Spatial Statistics (TBSS) skeleton. We also ran probabilistic tractography for the diffusion images, from which we extracted the stream count, average stream length, and the average of each DTI and NODDI metric across tracts connecting each pair of brain regions. Functional connectivity (FC) was extracted from both task and resting-state fMRI. Individualized prediction of a wide range of behavioral measures were performed using kernel ridge regression, linear ridge regression and elastic net regression. Consistency of the results were investigated with the Human Connectome Project (HCP) and Adolescent Brain Cognitive Development (ABCD) datasets. In both datasets, FC-based models gave the best prediction performance, regardless of regression model or behavioral measure. This was especially true for the cognitive component. Furthermore, all modalities were able to predict cognition better than other behavioral components. Combining all modalities improved prediction of cognition, but not other behavioral components. Finally, across all behaviors, combining resting and task FC yielded prediction performance similar to combining all modalities. Overall, our study suggests that in the case of healthy children and young adults, behaviorally-relevant information in T1 and diffusion features might reflect a subset of the variance captured by FC.

Random vibration analysis of nonlinear structure with pounding tuned mass damper

To mitigate the undesired vibrations of the structure, a cost-effective approach is to set up the nonlinear dynamic vibration absorber (NLDVA) on the structure. As an alternative NLDVA, the Pounding Tuned Mass Damper (PTMD) gathered extensively attention in recent years. However, the random vibration analysis of structure coupled with PTMD still poses a challenge. Besides, there remains an urgent need to construct a more comprehensive recovery coefficient (RC) for the two-stage damping mechanism of PTMD. To fill in this gap, this work involves the nonlinear random vibration of a type of two degree-of-freedom system composing of a main structure (MS) coupled to a PTMD device, in which the collision process of the system is portrayed by a segmented recovery coefficient (RC) model. Specifically, an equivalent system of structure-PTMD is firstly constructed by coordinate transformation. Then, the approximate probability density function (PDF) of equivalent system is performed by combining non-smooth conversion and stochastic averaging method (SAM). Further, the approximate PDF solution of the structure-PTMD can be determined by resorting to Jacobi transformation and verified numerically. Remarkably, the approximate PDF solutions of the system can also be applied to estimate the power spectral density of the system response. Being analytical, the analysis in this work yields results in the closed-form expressions that enable one to acquire new insight into the dynamic features of the structure-PTMD system. Moreover, the proposed scheme will promote the design and application of PTMD in practical projects from a theoretical point of view.

Rapid and low-cost synthesis of ZSM-5 zeolite nanosheet assemblies for conversion of methanol to gasoline

Nanoscale zeolites with short diffusion paths show significantly enhanced mass transportation and easier accessibility for active sites in catalysis compared to microsized zeolites. However, the high cost and complex process involved in existing synthetic methods limit their application, so the development of a rapid and low-cost synthesis technology is of great significance. Herein, ZSM-5 zeolite nanosheet assemblies (Z5-NS-t) are rapidly synthesized by a microwave irradiation (MW) assisted seed-induced method using low-cost polyhexamethylene biguanide hydrochloride (PHMB) as a crystal growth inhibitor of the b-axis. The crystallization kinetics of the resultant materials and the formation mechanism of ZSM-5 zeolite nanosheets, as well as the influence of physico-chemical properties on their catalytic performance for the methanol-to-gasoline (MTG) reaction, are systematically investigated. Compared with the ZSM-5 nanoparticle assemblies (Z5-NP-60), which are synthesized by using the same method except for the addition of PHMB, Z5-NS-180 nanosheets with an approximate density of strong Brønsted acid sites exhibit excellent catalytic performance in the MTG reaction, giving rise to a high gasoline selectivity of 73.2% at a methanol conversion of 99.9% and a large amount of external carbon deposits. This is attributed to the synergy of accessibility of acid sites located in the pore intersections and the shorter diffusion paths for coke precursors out of the zeolite channel. This study provides an effective strategy for the synthesis of ZSM-5 nanosheets as catalysts for the MTG reaction, and it is expected to be applied for the synthesis of other zeolite nanosheets for important catalytic processes.

First-principles investigation of structural, electronic, optical, and mechanical properties of Na-based fluoro-perovskites NaXF3: (X = Ni, Co, Be, Ba)

Several structural, electrical, optical and mechanical properties for the cubic sodium-based fluoro-perovskite NaXF3 (X = Ni, Co, Be, Ba) were investigated employing density functional theory (DFT) within generalized gradient approximation (GGA) and local density approximation (LDA). According to the computations like an electronic group formation, electrical charge density includes electronic states, NaNiF3 and NaBeF3 give the indirect energy bandgap while NaCoF3 shows metallic behavior, and however, NaBaF3 gives the direct bandgap. NaNiF3 and NaBaF3 are semiconductors, NaCoF3 is a conductor while NaBeF3 has insulating behavior. Optical constants like refractive index, absorption coefficient, reflectivity and loss function were determined by employing both real and imagined portions in dielectric work. An imaginary component from its dielectric function was used to determine various transitions between bands. These compounds NaXF3 have a mixture of ionic and covalent bonding characteristics. The greater bulk modulus from elastic characteristics and B/G ratio, suggest that such compounds were highly strong but ductile. In the future, such findings will present theoretical guidance for experimental studies and industrial applications of NaXF3 (X = Ni, Co, Be, Ba) compounds.

Exact Sum-Rule Approach to Polarizability and Asymptotic van der Waals Functionals─Derivation of Exact Single-Particle Benchmarks

Using a sum-rule approach, we develop an exact theoretical framework for polarizability and asymptotic van der Waals correlation energy functionals of small isolated objects. The functionals require only monomer ground-state properties as input. Functional evaluation proceeds via solution of a single position-space differential equation, without the usual summations over excited states or frequency integrations. Explicit functional forms are reported for reference physical systems, including atomic hydrogen and single electrons subject to harmonic confinement, and immersed in a spherical-well potential. A direct comparison to the popular Vydrov-van Voorhis density functional shows that the best performance is obtained when density decay occurs at atomic scales. The adopted sum-rule approach implies general validity of our theory, enabling exact benchmarking of van der Waals density functionals and direct inspection of the subtle long-range correlation effects that constitute a major challenge for approximate (semi)local density functionals.

Triboelectric Nanogenerator Based on PTFE Plastic Waste Bottle and Aluminum Foil

In this work, authors used waste plastic bottle and aluminIum foil further modified with graphene oxide as triboelectric material to construct a triboelectric nanogenerator (TENG). The proposed device is based on a single electrode system. The operating mechanism involves the generation of energy by tapping the surfaces with hand or finger. TENG material provided good response and charge retaining capacity. The device is eco-friendly; provide easiness, and simplicity of process. The substrate material is of inertness nature so can be used in wet conditions as well. The results were conducted by measuring the open-circuit voltage, short circuit current, total charge density, and power density at different frequencies from 1Hz to 3Hz. The TENG generated approximate open-circuit voltage, short-circuit current, charge density, and maximum power density values of 1400 V, 45 µA, 120 nC/m2, and 300 μW/cm2, respectively by finger pressing and releasing. The application was run to charge 2 nF and 10 nF capacitor by TENG and successful results were obtained. This study provides an effective method for developing a cost-effective TENG without the use of complex surface micro-/nano-texturing.

Trajectory PHD and CPHD Filters With Unknown Detection Profile

Compared to the probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters, the trajectory PHD (TPHD) and trajectory CPHD (TCPHD) filters are for sets of trajectories, and thus are able to produce trajectory estimates with better performance. In this paper, we develop the TPHD and TCPHD filters which can adaptively learn the history of the unknown target detection probability, and therefore they can perform more robustly in scenarios where targets are with unknown and time-varying detection probabilities. These filters are referred to as the unknown TPHD (U-TPHD) and unknown TCPHD (U-TCPHD) filters. By minimizing the Kullback-Leibler divergence (KLD), the U-TPHD and U-TCPHD filters can obtain, respectively, the best Poisson and independent identically distributed (IID) density approximations over a set of augmented trajectories. For computational efficiency, we also propose the U-TPHD and U-TCPHD filters that only consider the unknown detection profile at the current time. Specifically, the Beta-Gaussian mixture method is adopted for the implementations of proposed filters, which are referred to as the BG-U-TPHD and BG-U-TCPHD filters. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L$</tex-math></inline-formula> -scan approximations of these filters with much lower computational burden are also presented. Finally, various simulation results demonstrate that the BG-U-TPHD and BG-U-TCPHD filters can achieve robust tracking performance to adapt to unknown detection profile. Besides, it also shows that usually a small value of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L$</tex-math></inline-formula> in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L$</tex-math></inline-formula> -scan approximation has similar performance than with a large value at a fraction of the computational cost.

Novel Approximate Distribution of the Sum of Lognormal-Rician Turbulence Channels With Pointing Errors and Applications in MIMO FSO Links

In this paper, an approximate closed-form probability density function expression for the sum of lognormal-Rician turbulence channels with Rayleigh pointing errors is developed. The results of Kolmogorov-Smirnov goodness-of-fit statistical tests show that the proposed approximation is highly accurate across a wide range of channel conditions. Also, the analysis of approximation error is presented in detail, and it indicates that a more efficient approximation can be achieved for larger coherence parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$r$</tex-math></inline-formula> and smaller variance <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sigma _{z}^{2}$</tex-math></inline-formula> . To reveal the importance of proposed approximation, the closed-form expressions for the ergodic capacity, outage probability, and bit-error rate are derived in terms of Meijer’s G-function. The performance of multiple-input multiple-output (MIMO) free-space optical (FSO) systems with equal gain combining (EGC) diversity technique are analyzed in detail under different scenarios, including the number of transmit and receive apertures, turbulence channels, and presence of pointing errors. It is observed that MIMO technology can offer a significant improvement in FSO performance when compared with the single-input single-output (SISO) systems. The ergodic capacity and BER performance at high signal-to-noise ratio are also obtained to provide further insights. Numerical results demonstrate the accuracy of the proposed approach.

Molecular and Electronic Structure of Isolated Platinum Sites Enabled by the Expedient Measurement of 195Pt Chemical Shift Anisotropy.

Techniques that can characterize the molecular structures of dilute surface species are required to facilitate the rational synthesis and improvement of Pt-based heterogeneous catalysts. 195Pt solid-state NMR spectroscopy could be an ideal tool for this task because 195Pt isotropic chemical shifts and chemical shift anisotropy (CSA) are highly sensitive probes of the local chemical environment and electronic structure. However, the characterization of Pt surface-sites is complicated by the typical low Pt loadings that are between 0.2 and 5 wt% and broadening of 195Pt solid-state NMR spectra by CSA. Here, we introduce a set of solid-state NMR methods that exploit fast MAS and indirect detection using a sensitive spy nucleus (1H or 31P) to enable the rapid acquisition of 195Pt MAS NMR spectra. We demonstrate that high-resolution wideline 195Pt MAS NMR spectra can be acquired in minutes to a few hours for a series of molecular and single-site Pt species grafted on silica with Pt loading of only 3-5 wt%. Low-power, long-duration, sideband-selective excitation, and saturation pulses are incorporated into t1-noise eliminated dipolar heteronuclear multiple quantum coherence, perfect echo resonance echo saturation pulse double resonance, or J-resolved pulse sequences. The complete 195Pt MAS NMR spectrum is then reconstructed by recording a series of 1D NMR spectra where the offset of the 195Pt pulses is varied in increments of the MAS frequency. Analysis of the 195Pt MAS NMR spectra yields the 195Pt chemical shift tensor parameters. Zeroth order approximation density functional theory calculations accurately predict 195Pt CS tensor parameters. Simple and predictive orbital models relate the CS tensor parameters to the Pt electronic structure and coordination environment. The methodology developed here paves the way for the detailed structural and electronic analysis of dilute platinum surface-sites.

On approximation properties of matrix-valued multi-resolution analyses

We study approximation properties of multi-resolution analyses in the context of matrix-valued function spaces. Here, we generalize the notions of approximation order and density order given by the reference [de Boor C, DeVore RA, Ron A. Approximation from shift-invariant subspaces of . Trans Am Math Soc. 1994;341(2):787–806]. Indeed, we prove a characterization of the closed subspaces generated by the shifts of a single matrix-valued function that provide approximation order and/or density order . To give our conditions, we need the classical notion of approximate continuity. As a consequence, we prove necessary and sufficient conditions on a matrix-valued function to be a scaling function in a multi-resolution analysis.

Performance Analysis of FSO Systems Over a Lognormal-Rician Turbulence Channel With Generalized Pointing Errors

In this paper, an approximate closed-form probability density function expression for the Lognormal-Rician atmospheric turbulence with generalized pointing errors model is developed by using a series representation. The Kolmogorov-Smirnov (KS) goodness-of-fit statistical tool is employed to verify the accuracy of the proposed approximation. We demonstrate that a more efficient approximation can be achieved for the smaller jitter variances and nonzero boresight displacements. To reveal the importance of the proposed approximation, the approximate analytic expressions for the ergodic capacity and outage performance of single-input single-output free-space optical (FSO) systems are derived. It is observed that the pointing errors significantly degrade the performance of FSO links. By using the obtained asymptotic expressions, the impact of pointing errors on the ergodic capacity is considerably mitigated by selecting the optimum beam width at the transmitter side. We find that the optimum beam width is independent of atmospheric turbulence and the Pearson correlation coefficient in high signal-to-noise ratio conditions. All of the derived analytical results are confirmed by Monte Carlo simulation results.

High-throughput Method for Novel Medium Development for Culture of Anaerobic Gut Bacteria.

Gut microbiota play important roles in the health of their host and detailed investigation of these organisms requires in vitro culture. Culturing strictly anaerobic bacteria can be a challenge as the gut environment they inhabit is nutritionally complex. Use of complex media containing nutritionally rich but undefined gut fluid reduces the accuracy of physiological and metabolomic studies. Here we present a high-throughput protocol for comparing growth rates of fastidiously anaerobic bacteria on different media. These protocols can be used to develop a solid medium made up of commercially sourced ingredients, providing replicable growth conditions for previously uncultured anaerobic bacteria. As many fastidious bacteria grow poorly in a liquid broth, these protocols measure bacterial growth rate on solid media. These protocols speed up and simplify the growth rate measurement process by using a multiwell format and equations in place of physical McFarland standards to calculate approximate cell density. Bacterial strains belonging to the families Erysipelotrichaceae and Lachnospiraceae (phylum Firmicutes) isolated from the hindgut of Kyphosus sydneyanus were used to demonstrate the efficacy of these protocols. Bacterial growth rates were compared between a nutritionally rich medium with gut fluid versus a novel replicable medium with mannitol. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of solid YCFA growth medium Basic Protocol 2: Collection of fish gut samples and plating to single isolates Basic Protocol 3: Genetic identification of single isolates with colony PCR and 16S rRNA gene sequencing Basic Protocol 4: Measurement of bacterial growth rates on solid media.

Differentially Private Normalizing Flows for Synthetic Tabular Data Generation

Normalizing flows have shown to be a promising approach to deep generative modeling due to their ability to exactly evaluate density --- other alternatives either implicitly model the density or use approximate surrogate density. In this work, we present a differentially private normalizing flow model for heterogeneous tabular data. Normalizing flows are in general not amenable to differentially private training because they require complex neural networks with larger depth (compared to other generative models) and use specialized architectures for which per-example gradient computation is difficult (or unknown). To reduce the parameter complexity, the proposed model introduces a conditional spline flow which simulates transformations at different stages depending on additional input and is shared among sub-flows. For privacy, we introduce two fine-grained gradient clipping strategies that provide a better signal-to-noise ratio and derive fast gradient clipping methods for layers with custom parameterization. Our empirical evaluations show that the proposed model preserves statistical properties of original dataset better than other baselines.

Cooperative Localization Based on Augmented State Belief Propagation for Mobile Agent Networks

Belief propagation (BP) is widely used to solve the cooperative localization problem due to its excellent performance and natural distributed structure of implementation. For a mobile agent network, its factor graph inevitably encounters loops. In this case, the BP algorithm becomes iterative and can only provide an approximate marginal probability density function of the estimate with finite iterations. We propose an augmented-state BP algorithm for mobile agent networks to alleviate the effect of loops. By performing state augmentation, the messages in the factor graph will actually be allowed to be backward propagated, which reduces the number of loops in the factor graph, increases the available information of agents, and thus, benefits the localization. Experimental results demonstrate the better performance of the proposed algorithm over the original BP method.

Systematically Improvable Generalization of Self-Interaction Corrected Density Functional Theory.

Perdew-Zunger self-interaction correction (PZSIC) reintroduces an exact constraint to approximate density functional theory (DFT). However, PZSIC can paradoxically degrade performance, and standard DFT approximations (with or without PZSIC) are not systematically improvable. We use the adiabatic projection formalism (Janesko, B. G. J. Chem. Phys. 2022, 156, 014111, https://doi.org/10.1063/5.0076144) to derive PZSIC in terms of a reference system experiencing only electron self-interaction. Generalization to a "self-and-some-others" interaction introduces correlation into the reference system, systematically bridging from PZSIC to exact wave function theory without the double counting of correlation. Minimal active spaces accurately treat nearly one electron, near-equilibrium, and strongly correlated model systems at modest computational expense.

Introducing screening in one-body density matrix functionals: Impact on charged excitations of model systems via the extended Koopmans' theorem

In this work we get insight into the impact of reduced density matrix functionals on the quality of removal/addition energies obtained using the extended Koopmans' theorem (EKT). Within the reduced density matrix functional theory (RDMFT) the EKT approach reduces to a matrix diagonalization, whose ingredients are the one- and two-body reduced density matrices. A striking feature of the EKT within RDMFT is that it opens a band gap, although it is too large, in strongly correlated materials, which are a challenge for state-of-the-art methods such as $GW$. Using the one-dimensional Hubbard model and the homogeneous electron gas as test cases, we find that (i) with exact or very accurate density matrices the EKT systematically overestimates the band gap in the Hubbard model and the bandwidth in the homogeneous electron gas and (ii) with approximate density matrices, instead, the EKT can benefit from error cancellation. In particular we test a new approximation which combines random-phase approximation screening with the power functional approximation to the two-body reduced density matrix introduced by Sharma et al. [Phys. Rev. B 78, 201103 (2008)]. An important feature of this approximation is that it reduces the EKT band gap in the studied models; it is hence a promising approximation for correcting the EKT band-gap overestimation in strongly correlated materials.

Non-linear reconstruction of features in the primordial power spectrum from large-scale structure

ABSTRACT Potential features in the primordial power spectrum have been searched for in galaxy surveys in recent years since these features can assist in understanding the nature of inflation. The null detection to date suggests that any such features should be fairly weak, and next-generation galaxy surveys, with their unprecedented sizes and precisions, are in a position to place stronger constraints than before. However, even if such primordial features once existed in the early Universe, they would have been significantly damped in the non-linear regime at low redshift due to structure formation, which makes them difficult to be directly detected in real observations. A potential way to tackle this challenge for probing the features is to undo the cosmological evolution, i.e. using reconstruction to obtain an approximate linear density field. By employing a set of N-body simulations, here we show that a recently proposed non-linear reconstruction algorithm can effectively retrieve damped oscillatory features from halo catalogues and improve the accuracy of the measurement of feature parameters (assuming that such primordial features do exist). We do a Fisher analysis to forecast how non-linear reconstruction affects the constraining power, and find that it can lead to significantly more robust constraints on the feature amplitude for a DESI-like survey. Comparing non-linear reconstruction with other ways of improving constraints, such as increasing the survey volume and range of scales, this shows that it is possible to achieve what the latter do, but at a lower cost.