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Predicting the mechanical response of materials subjected to transient heat processes is crucial in various engineering applications. This paper introduces a novel peridynamic (PD) coupled field model formulated within the framework of Non-Ordinary State-Based Peridynamics (NOSBPD). This model offers the capability to simulate the coupled thermo-mechanical behavior of materials by incorporating both thermal transport and mechanical deformation analyses. To verify the model's accuracy, a benchmark problem involving a steel plate undergoing transient thermal expansion is investigated. This model presents a valuable tool for various engineering applications involving coupled thermo-mechanical processes. [ABSTRACT FROM AUTHOR]

Abstract This article is concerned with a thermoelastic response in a non-local micro-stretch completely covered in the endless non-viscous fluid under temperature dependent, the medium is investigated employing the theory of Green-Naghdi (G-N III) and the model of three-phase-lag (3PHL).Basic equations are derived based on these models. The normal mode technique is employed to achieve an analysis solution to the problem. The study used a magnesium crystal element to compare non-local measurements of thermo-micro-stretch elasticity in water using the (G-N III) theory and the (3PHL) model. The non-local effect has been discovered to have a considerable impact on all physical quantities. Furthermore, comparisons are made between three different frequency values.

This article is concerned with a thermoelastic response in a non-local micro-stretch completely covered in the endless non-viscous fluid under temperature dependent, the medium is investigated employing the theory of Green-Naghdi (G-N III) and the model of three-phase-lag (3PHL).Basic equations are derived based on these models. The normal mode technique is employed to achieve an analysis solution to the problem. The study used a magnesium crystal element to compare non-local measurements of thermo-micro-stretch elasticity in water using the (G-N III) theory and the (3PHL) model. The non-local effect has been discovered to have a considerable impact on all physical quantities. Furthermore, comparisons are made between three different frequency values. [ABSTRACT FROM AUTHOR]

The present work is implicated with the investigation of wave propagation in a homogeneous, isotropic, non-local microelongated viscothermoelastic solid half space with variable thermal conductivity under the dual phase lag (DPL) model. It is found analytically that three coupled longitudinal waves and one independent transverse wave exist in the medium which travel with distinct speeds. Reflection coefficients and energy ratios of various reflected waves are obtained analytically and presented graphically for aluminum epoxy-like material. The variations of these reflection coefficients are analyzed for different values of non-local parameter, microelongational parameter, viscosity and variable thermal conductivity. The expressions of energy ratios acquired in explicit form are also represented graphically as functions of the angle of incidence in accordance with the defined rule of conservation of energy. [ABSTRACT FROM AUTHOR]

Image itself information is naturally robust to image reconstruction, yet most current super-resolution methods do not fully utilize global feature information. This study proposes a new image super-resolution model mixing multiple and multi-scale attentions, including two new modules: Multi-scale hybrid non-local attention upsampling module and residual dense attention block. Different from previous nonlocal methods, multi-scale hybrid non-local attention upsampling module mixes pixel-based and patch-based nonlocal attention and establishes patch-level upsampling mapping relationships at multiple scales, which enables a wider global search space. The residual dense attention block establishes attention associations in channel and spatial dimensions, which enhances the transfer and fusion of front-to-back attention information through dense connections. In this study, quantitative and qualitative evaluations are conducted on several benchmark datasets, and the experimental results show that the model outperforms similar super-resolution models in terms of performance and reconstruction quality. [ABSTRACT FROM AUTHOR]

Atherosclerotic plaques are fatty deposits that form in the walls of major arteries and are one of the major causes of heart attacks and strokes. Macrophages are the main immune cells in plaques and macrophage dynamics influence whether plaques grow or regress. Macrophage proliferation is a key process in atherosclerosis, particularly in the development of mid-stage plaques, but very few mathematical models include proliferation. In this paper we reframe the lipid-structured model of Ford et al. (J Theor Biol 479:48–63, 2019. ) to account for macrophage proliferation. Proliferation is modelled as a non-local decrease in the lipid structural variable. Steady state analysis indicates that proliferation assists in reducing eventual necrotic core lipid content and spreads the lipid load of the macrophage population amongst the cells. The contribution of plaque macrophages from proliferation relative to recruitment from the bloodstream is also examined. The model suggests that a more proliferative plaque differs from an equivalent (defined as having the same lipid content and cell numbers) recruitment-dominant plaque in the way lipid is distributed amongst the macrophages. The macrophage lipid distribution of an equivalent proliferation-dominant plaque is less skewed and exhibits a local maximum near the endogenous lipid content. [ABSTRACT FROM AUTHOR]

In this study, a novel theoretical approach to describe thermo-optical elastic materials is proposed. This formulation offers insights into the relationship between plasma waves and thermomechanical waves when the microtemperature properties of semiconductor materials such as silicon are taken into account. The proposed model involves incorporating the concept of microtemperature effect according to photothermal (PT) excitation processes in nonlocal photo-thermoelasticity. The investigation of the electron-hole interaction concerning the elasto-thermodiffusion (ETD) theory in the context of thermoelastic (TD) and electronic (ED) deformation is the main focus of the work. The advanced model is utilized to analyze how the mechanical loading of ramp-like structures impacts the unrestricted nonlocality semiconductor material on a free outer plane. The Laplace transform approach in one-dimensional (1D) provides an analytical solution for main non-dimensional thermo-photo-elastic fields (the hole charge carrier field, the displacement (acoustic) wave, thermal wave, and plasma wave (carrier density). The primary fields in the Laplace domain are obtained analytically, and boundary conditions are established using a mechanical ramp type. Using a numerical inverse Laplace transform, full time domain solutions for the fundamental fields are obtained numerically according to the Riemann-sum approximation approach. The graphical representations illustrate and discuss the outcomes of the main physical fields. [ABSTRACT FROM AUTHOR]

In this paper the governing equations of plane wave in non-local thermoelastic solid half space with initial stress and two temperature is derived. The governing equations of the plane harmonic wave are solved in the x-y plane obtain the three different waves namely thermal wave, P-wave and SV- wave with distinctspeeds. Appropriate potential for incident and reflected waves are formulated which satisfies the boundary condition on solid half space. The phase speed and reflection coefficient are computed for a relevant material parameter. The effect of phase speed and reflection coefficient are plotted on the frequency and the effect of reflection coefficient are also plotted at angle of incidence. [ABSTRACT FROM AUTHOR]

In current problem, fundamental solution in an isotropic non-local couple stress micropolar thermoelastic solid with voids is investigated. We observed that there are five waves, viz. a set of three coupled longitudinal waves and a set of two coupled transverse waves propagating with different phase velocities. The impact of non-local and void parameters on the penetration depth, specific loss, attenuation coefficient and phase velocity has been studied numerically and graphically with respect to angular frequency. The fundamental solutions of the system of differential equations in case of steady oscillations have been investigated. Particular cases are established and compared with the known results. [ABSTRACT FROM AUTHOR]

An axisymmetric problem in micropolar thermoelastic model based on the Moore-Gibson-Thompson heat equation (MGT) under non-local and hyperbolic two-temperature (HTT) is explored due to mechanical loading. After transforming the system of equations into dimensionless form and employing potential functions, a new set of governing equations are solved using Laplace and Hankel transforms. A specific set of restrictions are applied on the boundary in the form of ring load and disk load for examining the significance of the problem. The transformed form of components of displacement, stresses, tangential couple stress, conductive temperature, and thermodynamic temperature are obtained. A numerical inversion technique is applied to recover the physical quantities in the original domain. The graphic representation of numerical findings for stress components, tangential couple stress, and conductive temperature reveals the impact of non-local and HTT parameters. Certain cases of interest are drawn out. Physical views presented in the article may be useful for the composition of new materials, geophysics, earthquake engineering, and other scientific disciplines. [ABSTRACT FROM AUTHOR]

In this work, we are concerned with the terminal value problem for the time fractional equation (in the sense of Conformable fractional derivative) with a nonlocal term of the Kirchhoff type$ \partial_t^\alpha u = K\Big(\|\nabla u\|_{L^2(\mathcal{D})}\Big)\Delta u + f(x,t), \quad (x,t) \in (0,T)\times \mathcal{D} $subject to the final data which is blurred by random Gaussian white noise. The principal goal of this article is to recover the solution $ u $. This problem is severely ill-posed in the sense of Hadamard, because of the violation of the continuous dependence of the solution on the data (the solution's behavior does not change continuously with the final condition). By applying non-parametric estimates of the value data from observation data and the truncation method for the Fourier series, we obtain a regularized solution. Under some priori assumptions, we derive an error estimate between a mild solution and its regularized solution. [ABSTRACT FROM AUTHOR]

This study explores the behavior of laser-exposed photo-excited carriers, investigating the propagation of photoacoustic waves in the thermoelastic domain. It also delves into the theoretical generation of surface acoustic waves in semiconductors through photo-thermoelastic processes. The research considers the interaction between thermomechanical and acoustic waves in a nonlocal medium with temperature-dependent thermal conductivity. Unlike relying on electron–phonon or electron-hole thermalization processes, photoacoustic waves here result from thermoelastic stress induced by the laser-induced temperature increase. The investigation accounts for the optical, mechanical, and thermoelastic properties of nanoscale semiconductor materials. Predictions of photoacoustic signals are derived by solving a combined thermal diffusion issue and a thermoelastic problem, using Laplace and Fourier transforms in the mathematical model. Numerical solutions encompass various physical fields within the time domain using the inversion technique of Laplace and Fourier transforms, such as thermal, acoustic, mechanical, and carrier density diffusion. The study evaluates and compares the influences of thermal memory and thermal conductivity presenting visual representations.

Small-scale pedestrian detection is a challenge. The main issues are as follows: 1) Troubled by their small scale, it is difficult to extract features effectively; 2) During the detection process, it is easily disturbed by background noise such as inter-class occlusion and intra-class occlusion, leading to missed or false detection; 3) The current widely used IoU measurement method is very sensitive to the position deviation of small objects, which seriously reduces the detection performance. To address these problems, we improve YOLOv5 structure by integrating Non-Local and Convolution structures, building a new feature extraction module called ResNet-Conv&NonL, combined with the ResNet structure. This module was then integrated into the backbone of YOLOv5 for better image feature extraction. In addition, we developed a novel model to measure the similarity between bounding boxes, which are embedded in the loss function of the YOLOv5 structure to replace the normal IoU measurement. Experiments on a self-made dataset and a combined dataset from Caltech and CityPersons show the feasibility of the proposed network structure. Results demonstrate the feasibility of the improved network structure is superior to the original method because it increases average precision by 6.0% compared to the original one.

In this manuscript, a two-dimensional axi-symmetric problem within a thermoelastic medium featuring fractional order derivatives, focusing on the Moore-Gibson-Thompson heat equation (MGT) in response to mechanical loading is investigated. The study assesses the problem's applicability under the influence of hyperbolic two temperature (HTT) and the non-local parameter resulting from ring and disc loads. The governing equations are rendered dimensionless, simplified through the introduction of potential functions, and solved using Laplace and Hankel transforms. Analytical expressions for displacement, stresses, conductive temperature, and temperature distribution components are derived in the transformed domain. Numerical inversion techniques are employed to obtain solutions in the physical domain. The purpose of the manuscript is to analyze the effects of non-local parameters, HTT, and various thermoelasticity theories graphically on resulting stresses, conductive temperature, and temperature distributions. It is observed that the behavior of composite materials under mechanical loading is effected by non-local and HTT. It will provide information about the different constituents of a composite material respond to temperature changes and mechanical stresses, which is crucial for designing and optimizing composite structures. Additionally, specific cases of interest are deduced from the findings of this investigation. [ABSTRACT FROM AUTHOR]

The present paper deals with the propagation of waves in non-local couple stress microploar thermoelastic solid half space lying under an inviscid liquid layer. We found two sets of coupled longitudinal waves and coupled transverse waves which are dispersive in nature and associated with attenuation. In addition to coupled waves, there also exists one independent longitudinal microroational wave which is dispersive in nature. Two types of waves namely coupled longitudinal waves and coupled transverse waves incident at the common interface. The value of various reflection coefficients and their energy ratios are calculated in both cases against the angle of incidence for a specific model. It is found that all reflection coefficients and energy ratios are affected by presence of non-locality, couple stress and angle of incidence. Their impact on various coefficients and energy ratios are studied numerically and depicted graphically. Some special cases are also deduced from the present investigation. The seismic reflection techniques are of great utility in determining the seismic structure of the earth and oceanic crust. Not only this, current findings may also be helpful in forecasting geophysical parameters at greater depths through signal processing, non-destructive testing and seismic data analysis. [ABSTRACT FROM AUTHOR]

This research project involved a mixed-methods study investigating language-related challenges of first-year students at an English Medium Instruction (EMI) university in Hong Kong. The two-phased sequential study employed a questionnaire survey and semi-structured student interviews. The survey and interview findings indicate that first-year students face a number of language-related academic challenges during their first year at an EMI university in writing, reading, speaking, and listening, many of which appear to stem from lower levels of vocabulary knowledge in English, unfamiliarity with academic and technical terminology, and limited exposure to varieties of English. Additionally, the findings suggest that these challenges can vary significantly based on background and first language, relating specifically to three different demographic student groups: local Hong Kong Cantonese-speaking students, Putonghua-speaking mainland Chinese students, and non-Chinese speaking local and international students. [ABSTRACT FROM AUTHOR]

Speckle noise is an inherent problem of synthetic aperture radar (SAR) images, which not only seriously affects the acquisition of SAR image information, but also greatly reduces the efficiency of image segmentation and feature classification. Therefore, research on how to effectively suppress speckle noise while preserving SAR image content information as much as possible has received increasing attention. Based on the non-local idea of SAR image block-matching three-dimensional (SAR-BM3D) algorithm and the concept of sparse representation, a novel SAR image despeckling algorithm is proposed. The new algorithm uses K-means singular value decomposition (K-SVD) to learn the dictionary to distinguish valid information and speckle noise and constructs a block filter based on K-SVD for despeckling, so as to avoid strong point diffusion problem in SAR-BM3D and achieve better speckle noise suppression with stronger adaptability. The experimental results on real SAR images show that the proposed algorithm achieves better comprehensive effect of speckle noise suppression in terms of evaluation indicators and information preservation of SAR images compared with several existing algorithms. [ABSTRACT FROM AUTHOR]

Although deep learning-based approaches for video processing have been extensively investigated, the lack of generality in network construction makes it challenging for practical applications, particularly in video restoration. As a result, this paper presents a universal video restoration model that can simultaneously tackle video inpainting and super-resolution tasks. The network, called Video-Restoration-Net (VRN), consists of four components: (1) an encoder to extract features from each frame, (2) a non-local network that recombines features from adjacent frames or different locations of a given frame, (3) a decoder to restore the coarse video from the output of a non-local block, and (4) a refinement network to refine the coarse video on the frame level. The framework is trained in a three-step pipeline to improve training stability for both tasks. Specifically, we first suggest an automated technique to generate full video datasets for super-resolution reconstruction and another complete-incomplete video dataset for inpainting, respectively. A VRN is then trained to inpaint the incomplete videos. Meanwhile, the full video datasets are adopted to train another VRN frame-wisely and validate it against authoritative datasets. We show quantitative comparisons with several baseline models, achieving 40.5042 dB/0.99473 on PSNR/SSIM in the inpainting task, while during the SR task we obtained 28.41 dB/0.7953 and 27.25/0.8152 on BSD100 and Urban100, respectively. The qualitative comparisons demonstrate that our proposed model is able to complete masked regions and implement super-resolution reconstruction in videos of high quality. Furthermore, the above results show that our method has greater versatility both in video inpainting and super-resolution tasks compared to recent models. [ABSTRACT FROM AUTHOR]

The present study introduces a theoretical framework according to the Moore-Gibson-Thompson (MGT) Model in the context of generalized thermoelasticity theory. The excited semiconductor material is utilized to formulate the governing equations in one dimensional (1D) with a non-local parameter. According to the photo- thermoelasticity theory, the overlapping between the electronic (optical) deformation and elastic deformation is taken into account. During the photo-excitation processes, the non-local equation of motion and the heat equation is introduced according to the model of Moore-Gibson-Thompson (MGT). The novel model describes the interaction between plasma and thermomechanical waves in a non-dimensional form. Laplace transform for time variable is applied to convert the governing equations into system of ordinary differential equations. The vector-matrix differential equation with the eigenvalues approach method is employed to obtain the solutions of the physical quantities analytically. Laplace transform invers numerically is utilized when some boundary conditions are applied at the semiconductor free surface to obtain the complete general of the main physical quantities. The numerical computations for the input parameters of Silicon as semiconductor material are used to illustrate the obtained results graphically and discussed.

The aim of this paper is to prove the existence and qualitative property of random attractors for a stochastic non-local delayed reaction–diffusion equation (SNDRDE) on a semi-infinite interval with a Dirichlet boundary condition at the finite end. This equation models the spatial–temporal evolution of the mature individuals for a two-stage species whose juvenile and adults both diffuse that lives on a semi-infinite domain and subject to random perturbations. By transforming the SNDRDE into a random evolution equation with delay, by means of a stationary conjugate transformation, we first establish the global existence and uniqueness of solutions to the equation, after which we show the solutions generate a random dynamical system. Then, we deduce uniform a priori estimates of the solutions and show the existence of bounded random absorbing sets. Subsequently, we prove the pullback asymptotic compactness of the random dynamical system generated by the SNDRDE with respect to the compact open topology, and hence obtain the existence of random attractors. At last, it is proved that the random attractor is an exponentially attracting stationary solution under appropriate conditions. The theoretical results are illustrated by application to the stochastic non-local delayed Nicholson's blowfly equation. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) automatic target recognition (ATR) has been widely applied in multiple fields. However, the special imaging mechanism of SAR results in different visual features of the same target at different azimuth angles, so single-aspect SAR target recognition has the limitation of observing the target from a single perspective. Multi-aspect SAR target recognition technology can overcome this limitation by utilizing information from different azimuths and effectively improve target recognition performance. Considering the order dependency and data limitation of existing methods, this paper proposes a multi-aspect SAR recognition method based on Non-Local, which applies a self-attention calculation to feature maps to learn the correlation between multi-aspect SAR images. Meanwhile, in order to improve the generalization ability of the proposed method under limited data, a network based on contrastive learning was designed to pre-train the feature extraction part of the whole network. The experimental results using the MSTAR dataset show that the proposed method has excellent recognition accuracy and good robustness. [ABSTRACT FROM AUTHOR]

The numerical solution of peridynamics equations is usually done by using uniform spatial discretisation. Although implementation of uniform discretisation is straightforward, it can increase computational time significantly for certain problems. Instead, non-uniform discretisation can be utilised and different discretisation sizes can be used at different parts of the solution domain. Moreover, the peridynamic length scale parameter, horizon, can also vary throughout the solution domain. Such a scenario requires extra attention since conservation laws must be satisfied. To deal with these issues, dual-horizon peridynamics was introduced so that both non-uniform discretisation and variable horizon sizes can be utilised. In this study, dual-horizon peridynamics formulation is derived by using Euler–Lagrange equation for state-based peridynamics. Moreover, application of boundary conditions and determination of surface correction factors are also explained. Finally, the current formulation is verified by considering two benchmark problems including plate under tension and vibration of a plate. [ABSTRACT FROM AUTHOR]

Based upon the Green–Lindsay (GL) theory of thermoelasticity and the Eringen non-local elasticity theory, we describe the new constitutive relations and the field equations for generalized non-local thermoelastic model. The propagation of harmonically time-dependent thermoelastic plane waves of assigned frequency is studied in a homogeneous, isotropic, non-local infinite elastic solid by employing these equations. Reflection phenomenon of thermoelastic waves at a stress-free thermally insulated or isothermal flat boundary of a non-local thermoelastic solid half-space is also studied in case of incident coupled longitudinal wave. The amplitude ratios of the reflected waves to that of incident wave are determined analytically and numerically by considering an appropriate material. The numerical results are presented graphically to highlight the effects of various parameters of interest. [ABSTRACT FROM AUTHOR]

At present, the crack segmentation model based on deep neural network has problems such as many training parameters, rough edge segmentation of cracks, insufficient segmentation accuracy, and lack of deep feature semantic information. In order to solve the above problems, the DeepLabv3 + model with better segmentation performance was studied, the Non-local attention mechanism was embedded and the backbone network ResNet101 was improved to obtain the optimized model DeepLabv3 + (N-S), and finally based on the output of the optimized model, the crack skeleton extraction method was used to quantify the crack feature parameters. The data set used was the self-made concrete beam crack image data set, and the comparison experiments of the model before and after the optimization were carried out to analyze the effectiveness of the optimization of the model in various performances, and the measured data were used to verify the quantification method for evaluating various characteristic parameters of fractures. The experimental results show that the mean pixel accuracy(mPA) and mean intersection over union( mIoU) of the DeepLabv3 + (N-S) network on the dataset have reached 88. 86% and 82. 04%, which are 2. 21% and 2. 54% higher than the original model, respectively. The crack segmentation performance is better than the original model, and the average error of quantification of various characteristic parameters of crack samples is + 8. 7%, which is lower than the original model, and can meet the requirements of engineering detection accuracy. [ABSTRACT FROM AUTHOR]

• The refraction law considering the phase gradient and the periodicity of grating structure is derived by the grating diffraction theory. • The improvements of anomalous refractions for different frequencies and different refractive angles for vertical incidence by the cooperative optimal design. • The optimizations of different orders anomalous refractions for oblique incidence through the cooperative optimal design. • Benefit by the structural reconfigurability, the conversions between different high efficient anomalous refractions can be realized. Currently, the metasurface design of flexural wave is primarily based on the generalized Snell's law (GSL). However, due to GSL only considering phase gradient, high-order parasitic diffraction leads to poor performance of larger angle anomalous refraction. In this paper, to suppress parasitic diffraction, a collaborative optimal method is proposed for metasurface design. Firstly, the diffraction formula considering both phase gradient and periodicity of grating structures is derived based on the grating diffraction theory (GDT). Then, the reconfigurable metasurface constructed of 'screw-nut' substructures are designed in conjunction with the genetic algorithm (GA). For the vertical incident flexural wave, the anomalous refractions of medium angle 51° and large angle 77° for 6.4 kHz, as well as 90° for 6.066 kHz are considered. Finally, oblique incidence is considered, in which the improvements of collaborative optimization design methods to 1 and −1 orders anomalous refractions are analyzed separately. The results are compared with the local ones obtained by GSL. It indicates that the proposed non-local design method opens a new perspective for parasitic diffraction suppression and efficient flexural wave manipulation. [ABSTRACT FROM AUTHOR]

Due to rapid advances in deep learning, many polarimetric image denoising networks have been developed and achieved promising results. However, these methods are based on general network architectures that do not fully exploit problem-specific knowledge, leading to over-smoothing results and poor generalization. Inspired by the non-local, which is an effective prior for image restoration, we propose a cube matching convolutional neural network to incorporate non-local operations into denoising models for polarimetric images. Specifically, the cube matching technique allows the denoising network to simultaneously exploit the non-local correlation and polarization relationship between the corresponding voxels of similar cubes. Rather than applying self-similarity directly in an isolated manner, the proposed cube matching module can be flexibly integrated into existing deep networks by combining with 3D convolution, achieving an effect equivalent to non-local means. This design enhances the generalization ability against various types and levels of noise. Experimental results show that using cube matching operations significantly improves denoising performance.   • A cube matching convolutional neural network was proposed for denoising of polarimetric images. • The non-local information and polarization relationships were fully exploited by the proposed method. • The cube matching module was flexibly integrated into existing deep networks by combining with 3D convolution. • The denoising performance and the generalization ability against various types and levels of noise are enhanced. [ABSTRACT FROM AUTHOR]

We have studied the problem of homogenous, isotropic non-local couple stress micropolar thermoelastic solid in the absence of body forces, couple density and heat resources. The reflection and transmission of waves at the interface of two distinct media have been investigated. It is observed that amplitude ratios of various reflected and transmitted waves are functions of wave number of incident waves and are affected by the non-local parameter of thermoelastic solid.

The images and videos of the high-voltage copper contact are disturbed by various noises in the factory. In this paper, an improved Non-local Self-similarity Recurrent Neural Network(NSRNN) is proposed for image denoising. The sparse representation is used for initializing the images, and then NSRNN is trained and tested based on the image datasets with different noise levels and magnification. Due to the similarity and the time correlation between the sequential images, RNN is used to improve the parameter utilization and model robustness. By measuring the self-similarity of the neighborhood features, NSRNN model outperforms other state-of-the-art methods in term of image denoising performance. [ABSTRACT FROM AUTHOR]

In this note we show finite time blow-up for a class of non-local active scalar equations on compact Riemannian manifolds. The strategy we follow was introduced by Silvestre and Vicol [Trans. Amer. Math. Soc. 368 (2016), pp. 6159–6188] to deal with the one dimensional Córdoba-Córdoba-Fontelos equation and might be regarded as an instance of De Giorgi's method. [ABSTRACT FROM AUTHOR]

The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like, fingerprint or face. Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users' identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session. However, divergent issues remain unaddressed. This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called, Gaussian Weighted Cauchy Krigingbased Continuous Czekanowski's (GWCK-CC). First, a Gaussian Weighted Non-local Mean Filter Preprocessing model is applied for reducing the noise present in the raw input face images. Cauchy Kriging Regression function is employed to reduce the dimensionality. Finally, Continuous Czekanowski's Classification is utilized for proficient classification between the genuine user and attacker. By this way, the proposed GWCK-CC method achieves accurate authentication with minimum error rate and time. Experimental assessment of the proposed GWCK-CC method and existing methods are carried out with different factors by using UMDAA-02 Face Dataset. The results confirm that the proposed GWCK-CC method enhances authentication accuracy, by 9%, reduces the authentication time, and error rate by 44%, and 43% as compared to the existing methods. [ABSTRACT FROM AUTHOR]

We have discussed reflection and refraction phenomenon of wave propagation from a plane interface dividing the non-local couple stress micropolar thermoelastic medium into two half-spaces. we have examined the problem by making incidence of two sets of coupled longitudinal waves and two sets of coupled transverse waves. Here, we observed that there exist five waves, viz., two sets of coupled longitudinal waves, two sets of coupled transverse waves and a longitudinal microrotational wave in non-local couple stress thermoelastic micropolar solid. One of them is propagating independently while others are set of coupled waves. We have also observed that these waves are propagating with different speeds. By making incidence of different waves; the reflection and refraction coefficients of numerous waves against the angle of incidence and angular frequency has been evaluated and portrayed graphically. [ABSTRACT FROM AUTHOR]

The main goal of this research is to provide a novel model that describes an optically heated layer of an excited non-local microelongated semiconductor material. In a rotating field, the model is examined as the photo-excitation processes occur. The model presents the microelongation scalar function, which describes the microelement processes according to the micropolar-thermoelasticity theory. The model analyses the interaction situation between optical-thermomechanical waves under the impact of rotation parameters when the microelongation parameters are taken into consideration according to the photo-thermoelasticity theory. During the electronic and thermoelastic deformation, the fundamental governing equations were obtained in dimensionless form, and they were investigated using the harmonic wave methodology. Two-dimensional general solutions for the fundamental fields of an isotropic, homogeneous, and linear non-local microelongated semiconductor medium are derived (2D). The free surface of the medium is subjected to several conditions to produce complete solutions due to the laser pulse. The physical properties of silicon (Si) material are used to show numerical modeling of the main fields. Some comparisons are made and graphically shown under the impact of various relaxation time and rotational parameters. [ABSTRACT FROM AUTHOR]

Based on the generalized nonlocal thermoelastic theory and the memory-dependent differential (MMD) theory, the dynamic response of the inner surface of an infinite hollow cylinder under thermal shock is investigated. The heat transfer coefficient varies linearly with the temperature, the outer surface of the hollow cylinder is insulated, and there is traction-free on the inner and outer surfaces. The governing equation of the problem is established, and the Laplace transform is used to solve the governing equation, and the distribution law of physical quantity is expressed by the modified Bessel function. In the numerical calculation, the influence of non-local parameters is firstly studied. Second, the influence of different thermal conductivity on various physical quantities is studied. Finally, the effects of time delay factor and kernel function on physical quantities are studied. The results show that the non-local parameters have little effect on temperature, but have significant effect on displacement and stress. The change of thermal conductivity has obvious influence on temperature, displacement, and stress. The hysteresis factor affects the extremum of a physical quantity. [ABSTRACT FROM AUTHOR]

A sensitivity study is presented to evaluate the influence of different parameters on the simulation of an underground excavation in the Callovo-Oxfordian (COx) argillaceous formation performed in the Meuse/Haute-Marne underground research laboratory. An elasto-viscoplastic constitutive law representing the characteristic behaviour of indurated mudrocks and stiff clays has been employed. It incorporates anisotropy, strain-softening, creep deformations and dependence of permeability on damage. In addition, a non-local formulation, able to simulate localised deformations objectively, has been incorporated in the analyses. The following features affecting the excavation have been studied: initial stress, strength and stiffness anisotropy, strength parameters, hydraulic and hydromechanical parameters, and scale effects. A simulation reported in a companion paper provides the base case for benchmarking. The results are compared in terms of extent and configuration of the excavation fractured zone, vertical and horizontal tunnel convergences, and the development and evolution of pore pressures in the rock. From the comparisons, an enhanced understanding of the hydromechanical mechanisms associated with underground excavations in COx claystone, and other similar argillaceous materials, has been achieved. [ABSTRACT FROM AUTHOR]

The paper presents the numerical simulation of an underground excavation in the Callovo-Oxfordian argillaceous formation, performed in the Meuse/Haute-Marne underground research laboratory, within the context of deep geological nuclear waste disposal. The constitutive model adopted incorporates a number of characteristic features of the hydromechanical behaviour of the Callovo-Oxfordian claystone, and other indurated clays, including anisotropy and time-dependent deformations. Model parameters have been largely determined from available experimental results. Particular attention has been given to the incorporation of a non-local formulation in order to simulate localised deformations objectively. It is shown that the numerical analysis is able to provide a very satisfactory reproduction of the extent and configuration of the excavation-induced fractured zone, the development of rock displacements and the evolution of water pressures in the rock. The analysis is also able to provide a deeper insight into the mechanisms underlying the generation of water pressures inside the rock mass. [ABSTRACT FROM AUTHOR]

The present study introduces a theoretical framework according to the Moore-Gibson-Thompson (MGT) Model in the context of generalized thermoelasticity theory. The excited semiconductor material is utilized to formulate the governing equations in one dimensional (1D) with a non-local parameter. According to the photo- thermoelasticity theory, the overlapping between the electronic (optical) deformation and elastic deformation is taken into account. During the photo-excitation processes, the non-local equation of motion and the heat equation is introduced according to the model of Moore-Gibson-Thompson (MGT). The novel model describes the interaction between plasma and thermomechanical waves in a non-dimensional form. Laplace transform for time variable is applied to convert the governing equations into system of ordinary differential equations. The vector-matrix differential equation with the eigenvalues approach method is employed to obtain the solutions of the physical quantities analytically. Laplace transform invers numerically is utilized when some boundary conditions are applied at the semiconductor free surface to obtain the complete general of the main physical quantities. The numerical computations for the input parameters of Silicon as semiconductor material are used to illustrate the obtained results graphically and discussed. [ABSTRACT FROM AUTHOR]

Although the segmentation of retinal vessels in the fundus is of great significance for screening and diagnosing retinal vascular diseases, it remains difficult to detect the low contrast and the information around the lesions provided by retinal vessels in the fundus and to locate and segment micro-vessels in the fine-grained area. To overcome this problem, we propose herein an improved U-Net segmentation method NoL-UNet. This work introduces NoL-UNet. First of all, the ordinary convolution block of the U-Net network is changed to random dropout convolution blocks, which can better extract the relevant features of the image and effectively alleviate the network overfitting. Next, a NoL-Block attention mechanism added to the bottom of the encoding-decoding structure expands the receptive field and enhances the correlation of pixel information without increasing the number of parameters. The proposed method is verified by applying it to the fundus image datasets DRIVE, CHASE_DB1, and HRF. The AUC for DRIVE, CHASE_DB1 and HRF is 0.9861, 0.9891 and 0.9893, Se for DRIVE, CHASE_DB1 and HRF is 0.8489, 0.8809 and 0.8476, and the Acc for DRIVE, CHASE_DB1 and HRF is 0.9697, 0.9826 and 0.9732, respectively. The total number of parameters is 1.70M, and for DRIVE, it takes 0.050s to segment an image. Our method is statistically significantly different from the U-Net method, and the improved method shows superior performance with better accuracy and robustness of the model, which has good practical application in auxiliary diagnosis. 1. Developed computer-aided diagnosis of retinal vascular system for eye diseases. 2. Neural network based on improved attention mechanism to improve the accuracy and robustness of segmentation. 3. Segment retinal blood vessels from DRIVE, CHASE_DB1, and HRF images. • The improved convolution blocks can better extract feature and alleviate overfitting. • The attention expands the receptive field and enhances the correlation of pixel. • The model is lighter and has fewer parameters, which reduces the inference time. • The model has better accuracy, and is practical for computer-aided diagnosis. [ABSTRACT FROM AUTHOR]

Although deep learning-based approaches for video processing have been extensively investigated, the lack of generality in network construction makes it challenging for practical applications, particularly in video restoration. As a result, this paper presents a universal video restoration model that can simultaneously tackle video inpainting and super-resolution tasks. The network, called Video-Restoration-Net (VRN), consists of four components: (1) an encoder to extract features from each frame, (2) a non-local network that recombines features from adjacent frames or different locations of a given frame, (3) a decoder to restore the coarse video from the output of a non-local block, and (4) a refinement network to refine the coarse video on the frame level. The framework is trained in a three-step pipeline to improve training stability for both tasks. Specifically, we first suggest an automated technique to generate full video datasets for super-resolution reconstruction and another complete-incomplete video dataset for inpainting, respectively. A VRN is then trained to inpaint the incomplete videos. Meanwhile, the full video datasets are adopted to train another VRN frame-wisely and validate it against authoritative datasets. We show quantitative comparisons with several baseline models, achieving 40.5042 dB/0.99473 on PSNR/SSIM in the inpainting task, while during the SR task we obtained 28.41 dB/0.7953 and 27.25/0.8152 on BSD100 and Urban100, respectively. The qualitative comparisons demonstrate that our proposed model is able to complete masked regions and implement super-resolution reconstruction in videos of high quality. Furthermore, the above results show that our method has greater versatility both in video inpainting and super-resolution tasks compared to recent models.