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This paper deals with the design, simulation, and practical modeling of metamaterial-based multiband conformal bandpass filter (BPF) for various wireless communication applications with improved quality factors. The novel metamaterial in the form of a split ring resonator is loaded on the ground plane face of the proposed BPF. The overall dimension of the designed BPF is only 2 8 × 2 8 mm 2 . The proposed BPF is tuned initially for quality factor enhancement based on the thickness of the substrate, physical parameters of the f transmission line, ground plane, externally loaded elements, and the gap in the metamaterial loading. The suggested filter operates at triple band covering the frequency bands from 1.4 to 2.2, 3.6 to 3.9, and 4.8 to 5.9 GHz, which are suitable for sub-6 GHz 5G and other wireless applications. The insertion loss is observed as 1 dB, which is suitable for the proposed BPF. The conformal behavior of the filter is judged through bending deformation analysis at various bending positions like (15 ∘ , 30 ∘ , 45 ∘ , 60 ∘ , and 90 ∘ ). The proposed BPF retains triple pass band characteristics at various bending deformations, which makes it suitable to be used in curved structures or flexible circuitry. The theory of equivalent circuits and quality factor (Q) of the designed BPF is discussed in this paper. The results are analyzed experimentally through ANRITSU-MS2037C combinational analyzer. The proposed BPF is suitable for sub-6 GHz 5G, WLAN, and Wi-Max applications. [ABSTRACT FROM AUTHOR]

Tri-rhythmical nature has attracted extensive attention from scholars in describing the dynamical behaviors of self-sustained systems. In this paper, we consider a tri-rhythmic van der Pol system and give a bifurcation analysis of a stochastic tri-rhythmic self-sustained system under joint noise perturbation. Based on an approximate approach, we give the stationary probability density function of amplitudes, and we find that the noise and time-delay feedback, regulating the velocity time-delay feedback strength parameter, may not cause transitions among unimodal, bimodal and trimodal in the tri-rhythmic system. More stochastic bifurcations appear by regulating the time delay in this system. The system, surprisingly, undergoes five times of stochastic bifurcations when the time delay is monotonically increased. It is shown that the time delay is more sensitive to the tri-rhythmic system and a much stronger dependence on the system. From a biological point of view, the reaction rate of biological molecules can be enhanced or diminished by the change of the noise intensity or correlation time of Gaussian colored noise. More surprisingly, an increase in displacement feedback will delay the reaction rate; however, the effect of an increase in velocity feedback on the reaction rate depends on the time delay. A detailed research on the parameter space indicates that time delay and colored noise parameters can effectively control the multirhythmicity of the system. Finally, this paper verifies the effectiveness of the theoretical solution through the numerical results of Monte Carlo simulation of the original system. These results may help to further explore forking bifurcations in real-world applications. This research provides new insight into the understanding of nontrivial effects of joint noise on the tri-rhythmic system. [ABSTRACT FROM AUTHOR]

This paper conducts the analytical investigation on the buckling of cylindrical shells with axially variable elastic modulus subjected to axial compressive load for the first time. First, it proves that the axially distributed elastic modulus can be expressed as the combination of constant and variable component. Then, governing differential equations for buckling analysis are derived and exactly solved by the combined perturbation method and Fourier analysis. Accordingly, the closed analytical solutions for the cylinder with arbitrarily variable elastic modulus are obtained, which reveal the explicit relations among buckling load, shell sizes and elastic modulus functions. Based on the presented analytical formulas, four types of elastic modulus variations for shell material which are uniform, periodic, linear and combined are studied in detail, and the results are also well verified. The derived analytical solutions in this paper can serve as benchmarks for buckling analyses of thin-walled cylinders with elastic modulus variations resulted from design, material manufacturing process, material imperfections and so on. [ABSTRACT FROM AUTHOR]

As the number of long-span bridges continues to grow, wind-induced vibration issues have become increasingly intensified. Among them, flutter is a serious wind-induced vibration that can lead to bridge collapse. To address this problem, this paper proposes inerter-based dampers as a solution for flutter control and compares their performance to traditional tuned mass dampers (TMDs). Firstly, eight distinct inerter-based dampers were proposed, based on various combinations of mass-inerter-spring-damper (MISD) components. Secondly, the equations of motion of the bridge-MISD system were derived based on the two-mode coupled flutter theory and the mechanical impedance analysis method. Thirdly, the flutter control performance of the eight proposed MISDs is examined using a simply supported beam, with the six better-performing dampers further evaluated using the Jiangyin Bridge. The results show that inerter-based dampers can effectively improve the critical flutter wind speed of bridges, with performance sensitive to frequency. Additionally, incorporating an inerter decreases the static displacement of the mass block, while increasing the mass of MISD and the distance between the damper and the section center improves flutter control performance. The optimal spring stiffness ratios for the six MISDs are identified, largely dependent on the damper's inertance and mass. In conclusion, this paper offers a promising solution to addressing flutter in long-span bridges and provides insights into the design and optimization of inerter-based dampers. [ABSTRACT FROM AUTHOR]

The development of modern process CMOS integrated circuits has reduced the feature sizes and thus the reliability of the chip continuously. First, this paper proposed two kinds of single-node upset self-recovery feedback loops with low overhead. One is called P-RFL which is composed of P-type complementary element (CP) and Clocked CP (C2P), and the other is called N-RFL which is composed of N-type complementary element (CN) and Clocked CN (C2N). Second, in order to fully tolerate triple-node upsets (TNUs), this paper presents three TNU-hardened latches: C2P-C2N, DMR-C2P and DMR-C2N. Using the blocking ability of the C-element, the outputs of two RFLs are connected to the C-element array. Therefore, when any three nodes upset at the same time, the transient pulse propagates inside the latch step by step, and disappears after being blocked by the C-element, ensuring that the TNU-hardened latches can restore to the correct logic state. HSPICE simulations show that all the three proposed latches achieve lower power, delay and APDP, compared with other six TNU-hardened latches. DMR-C2N achieves the lowest power, delay and APDP. In addition, the PVT variations analysis show that three proposed TNU-hardened latches are less sensitive to the variations of process, voltage and temperature. [ABSTRACT FROM AUTHOR]

For the actual circuit with fractional order characteristics, the fractional order circuit model is more concise and precise than the classical circuit model. So studying the synthesis of fractional order immittance is of great significance. This paper investigates the passive synthesis method of the three-element-kind fractional order immittance function. It means designing a network with three kinds of passive fractional-order elements that exhibit a specific impedance function. This paper proposes a variable substitution method to solve this problem. The method consists of three steps: The first step of the process is to establish the correspondence between the fractional order and lossy reactance. This way, the fractional order immittance function is transformed into an integer order immittance function. Then the Brune procedure realizes the immittance function as a network with lossy reactance. Finally, a fractional order network is obtained by replacing the lossy reactance with the corresponding fractional reactance. A simulation example and an experiment are also given for verification. This method applies to all three-element-kind network impedance functions that meet the passive condition. [ABSTRACT FROM AUTHOR]

In this paper, the flow of an incompressible fluid is thermally studied. Investigations into the heat transfer process have been conducted in non-Newtonian fluid flows with chemical reactions and heat sources present. The application of this work is the fluid flow around the stretching sheet; fluid flow on a stretching sheet can be applied to polymer extrusion, drawing or plastic films, hot rolling, casting and other engineering problems. The novelty of this paper is that the governing equations have been solved by a new and efficient semi-analytical approach, the Akbari–Ganji method (AGM). In order to investigate the issue, the finite element method (FEM) has also been applied. Comparing the results of problem-solving with the applied methods with the results of the previous research shows a perfect agreement. The results show that the parameters of Hartmann number and interaction improve the velocity profiles. Additionally, for greater Hartmann number values, raising the parameter of interaction decreases the temperature value, but a smaller value has the reverse effect. As the Hartmann number increases, the fluid velocity decreases and it shows that with the increase of electromagnetic force, the velocity of fluid flow decreases. [ABSTRACT FROM AUTHOR]

The primary focus of this paper is the determination of novel soliton solutions for the (2 + 1) -dimensional Heisenberg ferromagnetic spin chain (HFSC) problem. The suggested model may be thought of as a special case of the nonlinear Schrödinger equation. Exact solutions to the proposed equation have been found using efficient analytical approaches such as the singular manifold method and the tan (η 2) -expansion method. These proposed methods are significant mathematical tools to obtain the exact traveling wave solutions of nonlinear complex partial differential equations (PDEs). After decomposing the governing problem into its real and imaginary components, we analyze both the real and imaginary components separately. Soliton solutions are obtained using computational tools like Maple. Trigonometric function solutions, rational solutions and hyperbolic function solutions are found for Heisenberg ferromagnetic model by the application of the proposed techniques. Furthermore, the physical properties of the solutions, such as hyperbolic functions, are important. The hyperbolic tangent is used in the computation of magnetic moment and velocity in special relativity. As a result, we hypothesize that the obtained results have physically comparable meanings to those stated by these collocations. By selecting suitable values of arbitrary parameters, it has been observed graphically that the amplitude of obtained solutions can be changed. Graphical representations of few of the reported solutions are presented in both two and three dimensions by choosing appropriate values of parameters. The suggested approaches are very efficient and reliable for finding exact solutions of wide range of nonlinear PDEs in a complex medium. The advantage of these techniques is evident since they are not limited in their ability to locate such wave patterns. Back substitution in the original equation using Maple 18 validated all solutions found, and the physical significance of these results has been underlined. The constraint conditions for the existence of constructed solutions are also provided in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we examine the time-dependent two-dimensional cable equation of fractional order in terms of the Caputo fractional derivative. This cable equation plays a vital role in diverse areas of electrophysiology and modeling neuronal dynamics. This paper conveys a precise semi-analytical method called the q-homotopy analysis transform method to solve the fractional cable equation. The proposed method is based on the conjunction of the q-homotopy analysis method and Laplace transform. We explained the uniqueness of the solution produced by the suggested method with the help of Banach’s fixed-point theory. The results obtained through the considered method are in the form of a series solution, and they converge rapidly. The obtained outcomes were in good agreement with the exact solution and are discussed through the 3D plots and graphs that express the physical representation of the considered equation. It shows that the proposed technique used here is reliable, well-organized and effective in analyzing the considered non-homogeneous fractional differential equations arising in various branches of science and engineering. [ABSTRACT FROM AUTHOR]

In this paper, the effects of the Ohmic and magnetic density currents are investigated in the linearized Euler–Heisenberg (EH) electrodynamics (ED). The linearization is introduced through an external magnetic field, in which the vector potential of the EH ED is expanded around a magnetic background field that we consider uniform and constant in this paper. From the EH linearized equations, we obtain the solutions for the refractive index associated with the electromagnetic wave superposition, when the current density is ruled by the Ohm law, and in the second case, when the current density is set by an isotropic magnetic conductivity. These solutions are functions of the magnetic background (B) of the wave propagation direction (k). It also depends on the conductivity and on the wave frequency. As a consequence, the dispersion and the absorption of plane waves change when B is parallel to k in relation to the case of B perpendicular to k in the medium. The characteristics of the refraction index are related to direction of B and of the wave polarization, where there is an open discussion for the birefringence in this medium. [ABSTRACT FROM AUTHOR]

In this work, we generalize the theory of perturbations in a (D + 1)-dimensional space–time with cosmological constant, studying scalar, vector and tensor perturbations, as well as its structure in Newtonian and Synchronous gauge. We also show the theory of perturbations in the context of brane cosmology, where branes are embedded in a set of D-spatial dimensions, a temporal dimension, and an additional spatial dimension. In both standard and brane cosmology, an unperturbed space–time is provided with a Friedmann–Lemaitre–Robertson–Walker metric and arbitrary sectional curvature, the matter content has the shape of a perfect fluid. In addition, we consider the arbitrary sectional curvature, obtaining the respective equations in the Newtonian and Synchronous gauge. We highlight that the results presented in this paper can be used to treat brane cosmology with two concentric branes or tackle the σ 8 tension with a braneworld approach. Finally, as an example of the utility of all the technology presented in this paper, we show an application to the energy flux and the repercussions in the framework of the braneworlds. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid technique for enhancing power quality (PQ) in distributed generation (DG) systems by deploying a unified power quality conditioner (UPQC). Here, the proposed hybrid method is the joint execution of white shark optimizer (WSO) and recalling-enhanced recurrent neural network (RERNN), called the WSO-RERNN technique. The primary objective of this novel approach is to effectively mitigate voltage sag and reduce voltage harmonics under varying load conditions. It is important to investigate the voltage sag, swell and harmonic distortion of the system to obtain an enhanced PQ of the energy supply. Therefore, this paper shows the brief impact of PQ in DG utilizing the proposed unified PQ conditioner controller. The WSO-RERNN control technique enhances the performance of the UPQC controller by providing the optimal control signal. By then, the efficiency of the proposed approach is done in MATLAB, and the performance is compared with those of existing optimization techniques, including Ant Lion Optimizer (ALO), Grey wolf optimization (GWO) and Salp swarm algorithm (SSA) methods. [ABSTRACT FROM AUTHOR]

This paper reports the splitting morphology of low-viscous fingers in the microchannels that are associated with flat T-shaped, curved T-shaped, and Y-shaped junctions. The numerical simulations are based on the finite volume approach and the volume of the fluid model. In this study, microchannels are filled with silicon oil. Perfluorodecalin is used to displace silicon oil from the microchannels. Due to viscosity differences, the low-viscous finger (LVF)-shaped instability evolves at the interface of fluids. A single LVF propagates in the parent channel, and at the junction, it splits into two identical LVFs. It is noted that the splitting morphology of LVF depends upon the shape of the junction and its wettability. Therefore, there are three different junctions, i.e. flat T-shaped, curved T-shaped, and Y-shaped, with three different wettability conditions (θ), i.e. hydrophilic (60∘), hydrophobic (120∘), and superhydrophobic (150∘) are used for numerical investigation. It is found that a LVF splits symmetrically at all three different junctions but tips of LVFs are found to be convex in superhydrophobic conditions. The LVFs-shaped are curved in the limbs of curved T-shaped microchannel and straight in the limbs of flat T-shaped and Y-shaped microchannels. The findings of this paper may be used in lung biomechanics, respiratory diseases, biochemical testing, and many more. [ABSTRACT FROM AUTHOR]

The regularized lattice Boltzmann method (RLBM) has the advantage of improving the accuracy of numerical simulations without increasing the computational overhead. The RLBM usually uses the standard Cartesian grid in numerical simulation. This paper introduces the multi-layer grid technique, the multi-layer grid has different resolutions, which is also more consistent with the physical laws of the flow field. Based on this, a multi-layer grid regularized lattice Boltzmann method (ML-RLBM) for solving complex flow problems is proposed. The proposed method performs local refinement of the grid on the standard Cartesian grid to achieve a multi-layer grid, which can reduce the computational overhead. In order to realize the local grid refinement easily, this paper adopts the center point format to store the multi-layer grid. The ML-RLBM designs a buffer scheme between different layers of grids, which realizes that only spatial interpolation is required at the interface of different layers of grids without temporal interpolation. The numerical results show that the ML-RLBM has excellent numerical accuracy and numerical stability, and it can effectively reduce the computational cost. [ABSTRACT FROM AUTHOR]

Because of their applications, the study of piecewise-linear differential systems has become increasingly important in recent years. This type of system already exists to model many different natural phenomena in physics, biology, economics, etc. As is well known, the study of the qualitative theory of piecewise differential systems focuses mainly on limit cycles. Most papers studying the problem of existence and the maximum number of limit cycles of piecewise differential systems have precisely considered planar systems. However, few papers have examined this problem in ℝ 3 . In this paper, our main goal is to examine a class of discontinuous piecewise differential systems in ℝ 3 , where we consider the unit sphere as the separation surface that divides the entire space into two regions, each one has a linear vector field analogous to planar center. In general, it is hard to determine an exact upper bound for the number of limit cycles that a class of differential systems can exhibit. We prove that this class of differential systems can have at most four limit cycles. We show that there are examples of such differential systems with exactly 1, 2, 3 and 4 limit cycles. [ABSTRACT FROM AUTHOR]

The bifurcation theory for homoclinic networks with singular and nonsingular equilibriums is a key to understand the global dynamics of nonlinear dynamical systems, which will help one determine the dynamical behaviors of physical and engineering nonlinear systems. In this paper, the appearing and switching bifurcations for homoclinic networks through equilibriums in planar polynomial dynamical systems are studied. The appearing and switching bifurcations are discussed for the homoclinic networks of nonsingular and singular sources, sinks, saddles with singular saddle-sources, saddle-sinks, and double-saddles in self-univariate polynomial systems. The first integral manifolds for nonsingular and singular equilibrium networks are determined. The illustrations of singular equilibriums to networks of nonsingular sources, sinks and saddles are given. The appearing and switching bifurcations are studied for homoclinic networks of singular and nonsingular saddles and centers with singular parabola-saddles and double-inflection saddles in crossing-univariate polynomial systems, and the first integral manifolds of such homoclinic networks are determined through polynomial functions. The illustrations of singular equilibriums to networks of nonsingular saddles and centers are given. This paper may help one understand higher-order bifurcation theory in nonlinear dynamical systems, which is completely different from the classic bifurcation theories. [ABSTRACT FROM AUTHOR]

The central purpose of this paper is to explore the nonlinear dynamics of the (2+1)-dimensional Kadomtsev–Petviashvili equation (KPE). The multiple soliton solutions (MSSs) are constructed via applying the Hirota method. Then the soliton molecules on the (x,y)-, (x,t)- and (y,t)-planes are extracted via imposing the velocity resonance conditions to the MSSs. Eventually, two effective techniques, the sub-equation approach (SEA) and the variational approach (VA), are employed to probe some other diverse wave solutions, which are the bright wave, dark wave, singular wave and the singular periodic wave solutions. The dynamics of the extracted solutions are unveiled graphically to exhibit the physical attributes. The attained solutions in this paper can enlarge the exact solutions of the (2+1)-dimensional KPE and enable us to understand the nonlinear dynamic behaviors better. [ABSTRACT FROM AUTHOR]

The concealment of rootkits makes them a significant security threat. Kernel-level rootkits can be extremely dangerous as they have high system privileges. A typical type of kernel-level rootkits is to hook system calls which are essential for overall system functionality. This paper presents drootkit, a tool to detect kernel-level rootkits that hook system calls. Additionally, drootkit can recover damaged systems. This tool utilizes eBPF technology, ensuring both flexibility and security. When installing new kernel modules, the virtual address range of the initial kernel code will not be affected. In light of this, drootkit conducts bounds checking on all system calls within the system. In the case of system calls being hooked, drootkit can detect and recover them while issuing warning messages. For testing purposes, this paper also implements a malicious kernel module that can hook system calls and run on the arm64 platform. We have conducted an experiment that confirms drootkit's capability to detect rootkits while also effectively restoring the system. Moreover, drootkit has very low system overhead and does not significantly affect system performance, making it a reliable choice for a backend program that can run for an extended period of time. [ABSTRACT FROM AUTHOR]

The limitations of scaling in CMOS technology pose challenges in meeting the requirements of future applications. To address these challenges, researchers are exploring various design techniques, including Approximate Computing (AC), which leverages the inherent error resilience of applications to achieve high performance and energy gains with desired quality. AC has gained popularity as a computer paradigm for error-resilient applications, and many researchers have studied AC across computing layers and developed tools for implementing these techniques. This paper provides a comprehensive survey of AC techniques at the abstraction levels of software and hardware and discusses the tools to implement AC in hardware and software, quality evaluation tools and comparison points. The paper also covers existing frameworks for AC, potential applications, future research directions, challenges and limitations. This information can guide researchers in identifying promising avenues for further advancements and innovations in this domain. Additionally, this paper compares state-of-the-art surveys of AC and highlights the unique features and contributions of this work that distinguish our work from previous surveys. [ABSTRACT FROM AUTHOR]

The leisure agriculture in suburban towns provides important space for citizens to carry out leisure activities. This paper takes Xinkou town in Tianjin city as an example to analyze the development efficiency of leisure agriculture in suburban towns. On the premise of establishing the indicators for evaluating the development efficiency of leisure agriculture in Xinkou town, this paper first uses the data envelopment analysis (DEA) to measure the input and output indicators of leisure agriculture in 18 natural villages in Xinkou town, and calculates the comprehensive technical efficiency, target values, redundancy and returns to scale of leisure agriculture, and then evaluates the development efficiency of leisure agriculture in Xinkou town. Furthermore, by using the high/low clustering tool under the ArcGIS spatial statistics module, this paper conducts a high/low clustering analysis of the development efficiency of leisure agriculture in 18 natural villages of Xinkou town, and figures out the reasons for the high/low clustering of natural villages in Xinkou town spatially. After the research and analysis, the following conclusions are drawn: From the input–output perspective, except for Zhengzhuangzi village, Diliubu village, Yuejiakai village, and Dangcheng village, the development efficiency of leisure agriculture in other villages is relatively low due to their poor resource foundations, or deficiencies in management experience and transportation location. The development of leisure agriculture in Xinkou town is unbalanced, showing a pattern of polarized clusters: Diliubu village and Shuigaozhuang village form the most obvious high-value cluster, while Xiaoshawo village, Bijia village and Xuanjiayuan village form the most obvious low-value cluster, where the southeast corner of Xinkou town registers the lowest development efficiency value of leisure agriculture because it is far away from the town center and the main transportation arteries, and falls short of high-quality pastoral scenery. For the future development of leisure agriculture in Xinkou town, it is supposed to optimize the land use policy, provide active support to the competitive industrial and commercial capital, non-governmental capital, rural collective economic organizations, farmers’ cooperatives, and family farms, strengthen the in-depth integration of industries, improve the support system for new-type leisure agriculture, and build leisure agriculture brands with local features. [ABSTRACT FROM AUTHOR]

This paper aims to provide a comprehensive review on Elliptic Curve Cryptography (ECC), a public key cryptographic system and its applications. The paper discusses important mathematical properties and operations of elliptic curves, like point addition and multiplication operations and its implementation in cryptographic methods such as encryption and decryption. This paper provides a detailed workout on important mathematical problems on elliptic curves and ECC which provides insight into working of essential cryptographic techniques in ECC. And the paper also provides a literature review of research works based on ECC in various fields such as Internet of Things (IoT), Cloud computing, Blockchain and Image Security. And the paper further provides insight into the recent applications of ECC in fields like IoT and Blockchain by comprehensively discussing the proposed mechanism for each of the recent applications and also briefly discussing the security of the proposed mechanism. [ABSTRACT FROM AUTHOR]

A decomposition of a graph is a collection of its edge — disjoint subgraphs whose union equals the edge set of the graph. A decomposition all of whose members are paths is called a path decomposition. In this paper, we introduce and initiate a study of a new variation of decomposition namely equitable path decomposition of a graph G which is defined to be a decomposition in which all the members are paths and the lengths of any two paths are differ by at most one in G. In this paper, we initiate a study on this parameter. [ABSTRACT FROM AUTHOR]

The goal of the paper is to establish quadrature formulas on combinatorial graphs. Three types of quadrature formulas are developed. Quadrature formulas of the first type are obtained through interpolation by variational splines. This set of formulas is exact on spaces of variational splines on graphs. Since bandlimited functions can be obtained as limits of variational splines we obtain quadrature formulas which are approximately exact on spaces of bandlimited functions. Accuracy of this type of quadrature formulas is given in terms of geometry of the set of nodes of splines and in terms of smoothness of functions which is measured by means of the combinatorial Laplace operator. Quadrature formulas of the second type are obtained through point-wise sampling for bandlimited functions and based on existence of certain frames in appropriate subspaces of bandlimited functions. The third type quadrature formulas are based on the average sampling over subgraphs. Our quadrature formulas which are based on sampling are exact on a relevant subspaces of bandlimited functions. The results of the paper have potential applications to problems that arise in data mining. [ABSTRACT FROM AUTHOR]

In order to reveal the general escape mechanism of non-hyperbolic chaotic invariant sets under both weak noise limit and finite noise intensity, the simplest example of Hénon map, which represents the stretching and folding of the phase space, is taken to study the escape mechanism under two kinds of global bifurcation: the fractal boundary crisis and the attractor contact crisis. In this paper, we revealed the general exit mechanism by analyzing the escape paths derived from the shooting method and Monte Carlo simulation. Finally, to further demonstrate universality, an example of high-dimensional differential dynamical system, namely the transient chaos Duffing oscillator, is examined, which underscores the main idea of this paper analyzing specific deterministic structures not only enhances the comprehensibility of the escape process, but also allows for predictions of general escape behavior under weak noise intensity. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of stability of linear time-varying stochastic perturbed systems. We present sufficient conditions ensuring the global practical uniform exponential stability of a different class of stochastic perturbed systems based on generalized integral inequalities of Gronwall type. Finally, we provide numerical examples to prove the usefulness of the main results of this paper. [ABSTRACT FROM AUTHOR]

Due to their small size, nanoparticles have brought a new era for researchers. They are utilized in different areas, including the food industry, pharmaceuticals, and medicals, for their outstanding properties. Many medicines are also used to treat patients with various diseases. Many researchers are continuing their research to find more applications of these materials. This paper reviews how nanoparticles synthesized from plants can help the immune response. Different nanoparticles have been initially studied with their source of origin, properties, and applications in the immune response. Then, how various nanoparticles work on the immune response has been briefly discussed. Different applications of nanoparticles on immune response with different perceptions have also been considered. The results of the applications of these particles have been debated as well. In the end, these particles' potential challenges and future opportunities for immune response have been reviewed. This review paper will work as a guide for nanoparticle researchers in immunity. [ABSTRACT FROM AUTHOR]

The enhanced power graph P E (S) of a semigroup S is a simple graph whose vertex set is S and two vertices x , y ∈ S are adjacent if and only if x , y ∈ ⟨ z ⟩ for some z ∈ S , where ⟨ z ⟩ is the subsemigroup generated by z. In this paper, we first describe the structure of P E (S) for an arbitrary semigroup S , and then discuss the connectedness of P E (S). Further, we characterize the semigroup S in the cases when P E (S) is separately a complete, bipartite, regular, tree and null graph. The planarity, together with the minimum degree and independence number, of P E (S) is also investigated. The chromatic number of a spanning subgraph, i.e., the cyclic graph, of P E (S) is proved to be countable. In the final part of this paper, we construct an example of a semigroup S such that the chromatic number of P E (S) need not be countable. [ABSTRACT FROM AUTHOR]

In this paper, a three-dimensional dynamic model of a dual-cable winding hoisting system is presented to simulate and analyze its coupled vibrations. The equations of motion of this system are derived based on a substructure method and Lagrange’s equations of the first kind, in which the longitudinal–torsional coupled mechanical characteristics of the hoisting cables are considered. Longitudinal and transverse natural frequencies of the system are obtained and studied, and its dynamic responses due to some assumed displacement excitations are calculated. Numerical results agree well with those from ADAMS simulation, and the results have shown that longitudinal and transverse resonances are inevitable, but the transverse resonance has little effect on the conveyance; Slow longitudinal excitations should be avoided, thus avoiding the first-order longitudinal resonance since the system longitudinal vibration is dominated by its first-order mode; the torque in the hoisting cable is mainly induced by its tension under longitudinal–torsional coupled mechanical characteristics of the cable, and a torque release device is suggested to protect the hoisting cable from torsion failure; Torsional and transverse vibrations of the conveyance are been well restricted by the guiding cables even when the guiding cable pre-tension is zero. The results of this paper can be used to improve the parameter design of the ultra-deep shaft hoisting systems. [ABSTRACT FROM AUTHOR]

The given text is a list of references and author information for a research paper on advanced persistent threats (APTs) and insider threats in cybersecurity. The paper explores strategies, models, and games to detect and defend against these threats. The authors' research interests include game theory, distributed optimization, cybersecurity, and control systems. [Extracted from the article]

The finding of new integrable coupling systems has become an important area of research in mathematical physics and their study will aid in the classification of multi-component integrable systems. A basic method for generating integrable coupling systems is algebraic expansion, for example, the Frobenius algebra, the Lie algebra, the superalgebra, and so on. In this paper, we introduce a Frobenius Boussinesq equation based on the Frobenius algebra, and then we present a Lax pair of it. It follows that we give a Bäcklund transformation of the Frobenius Boussinesq equation. Furthermore, the lattice equation of the Frobenius Boussinesq equation is presented by using three Bäcklund transformations, and then obtain the exact solutions. Additionally, we obtain the conservation laws of the Frobenius Boussinesq equation via the Bäcklund transformation. Strongly coupled and weakly coupled systems physically represent strong and weak interactions, respectively. In this paper, we introduce a weakly coupled Degasperis–Procesi (DP) equation, and construct a Lax pair of it. In addition, the Bäcklund transformation and superposition principle are applied to investigate the weakly coupled DP equation. We also obtain the conservation laws of the weakly coupled DP equation. Then, we introduce a strongly coupled DP equation, and use the same method to study the strongly coupled DP equation. The exact solutions of these two equations are obtained. Moreover, we introduce a Z n -DP equation. Considering the superposition principle, we obtain the solution of an associated Z n -DP equation by using Bäcklund transformations. These new multi-component integrable systems can enrich the existing integrable models and possibly describe new nonlinear phenomena. [ABSTRACT FROM AUTHOR]

In this paper, it has been proven that locally the inertial frames and gauge states of the electromagnetic field are equivalent. This proof is valid for Einstein–Maxwell theories in four-dimensional Lorentzian spacetimes. Theorems proved in a previous paper will be used. These theorems state that locally the group of electromagnetic gauge transformations is isomorphic to the local group of Lorentz transformations of a special set of tetrad vectors. The tetrad that locally and covariantly diagonalizes any non-null electromagnetic stress–energy tensor. There are in total two isomorphisms, one for each orthogonal plane of stress–energy eigenvectors. We discuss the opposite problem in this paper. What happens with local electromagnetic gauge when the test object under study is boosted by any mechanical means? We will prove that boosting matter is indistinguishable from introducing an appropriate local electromagnetic gauge transformation. [ABSTRACT FROM AUTHOR]

In this paper, we develop an epidemic model with a nonlinear function that describes the saturated digital contact tracing. The model is theoretically and numerically analyzed based on its dynamics. The model equilibria points and the basic reproduction number are obtained. However, the proposed model reveals both backward and forward bifurcation, and backward bifurcation occurs when the digital contact tracing saturation parameter is larger than a specific threshold. Real data are used to fit the model and estimate the parameter values. Sensitivity analysis reveals that interventions such as reducing the infection rate, enhancing quarantine efforts, and accelerating vaccination can effectively reduce the basic reproduction number, R 0 . Simulations show that improving tracing accuracy and encouraging greater participation in providing personal track information can effectively reduce the peak of undetected exposed individuals. Moreover, we analyze the expression for the specific threshold and determine that the increasing hospital resources and strengthening patient quarantine can reduce the potential occurrence of backward bifurcation. The analysis and simulations presented in this paper provide valuable suggestions for the prevention and control of the epidemic. [ABSTRACT FROM AUTHOR]

Multi-Objective Travelling Salesman Problem (MOTSP) is one of the most crucial problems in realistic scenarios, and it is difficult to solve by classical methods. However, it can be solved by evolutionary methods. This paper investigates the Constrained Multi-Objective Travelling Salesman Problem (CMOTSP) and the Constrained Multi-Objective Solid Travelling Salesman Problem (CMOSTSP) under an uncertain environment with zigzag uncertain variables. To solve CMOTSP and CMOSTSP models under uncertain environment, the expected value and optimistic value models are developed using two different ranking criteria of uncertainty theory. The models are transformed to their deterministic forms using the fundamentals of uncertainty. The Models are solved using two solution methodologies Aspiration level-based Multi-Objective Quasi Oppositional Jaya Algorithm (AL-based MOQO Jaya) and Fuzzy Programming Technique (FPT) with linear membership function. Further, the numerical illustration is solved using both methodologies to demonstrate its application. The sensitivity of the OVM model's objective functions regarding confidence levels is also investigated to look at the variation in the objective function. The paper concludes that the developed approach has solved CMOTSP and CMOSTSP efficiently with an effective output and provides alternative solutions for decision-making to DM. [ABSTRACT FROM AUTHOR]

In this paper, we study a novel model of the dynamics of alcohol consumption under induced complications. The mentioned model is considered under some advanced concept of fractional derivative called piecewise fractional-order derivative. Currently, most real-world problems are considered under fractional derivatives because of their stable and global behavior. To deal with and detect the crossover behavior in the dynamics of the proposed model, the piecewise derivative containing the Mittag-Leffler-type kernel combined with classical integer order derivatives in piecewise form is used. First, we will investigate the model for qualitative theory in detail. For qualitative theory, we will use fixed point theory. Additionally, we establish sufficient conditions for Ulam–Hyers (UH) stability. To simulate the model, we develop a numerical algorithm based on the Euler technique. The numerical method is applied to present graphically the approximate solutions of the model. In the final part of the paper, we give a detailed discussion of our numerical results. [ABSTRACT FROM AUTHOR]

This paper explores a predator–prey system featuring fear and disease within the predator population,utilizing the Rosenzweig–MacArthur model with Holling type-II functional response. The primary focus lies in investigating the impact of a fear factor, wherein the prey's growth rate is hindered due to predator-induced fear. Additionally, the model accounts for the spread of disease among predators,leading to a division between susceptible and infected predator subpopulations. The inclusion of an Allee effect in the susceptible predator further enriches the model. The study involves a thorough examination, encompassing local and global stability analysis as well as Hopf bifurcation analysis around the interior equilibrium point. Numerical simulations underscore a noteworthy observation: an escalation in interaction force propels the system into chaotic dynamics,marked by stable focus, limit cycles and period-doubling phenomena. A noteworthy finding pertains to the influence of the Allee parameter (θ) on chaotic dynamics. As the Allee parameter values increase, the system tends to stable focus through a sequence of chaotic states, period-doubling and limit cycles. Subsequently, the paper introduces the role of another pivotal parameter, the fear factor, into the chaotic dynamics. Intriguingly, chaos transforms into stable focus through diverse nonlinear phenomena, including period-doubling and limit cycles. This nuanced exploration of parameters sheds light on the intricate dynamics governing the predator–prey system, offering a comprehensive understanding of the interplay between fear, disease and ecological factors. So our observation throughout this paper that how chaos behaves here after one by one injection of our new features: fear factor and Allee parameter? [ABSTRACT FROM AUTHOR]

This paper provides an explanation of the type classification of von Neumann algebras, which has made many appearances in the recent work on entanglement in quantum field theory and quantum gravity. The goal is to bridge a gap in the literature between resources that are too technical for the non-expert reader, and resources that seek to explain the broad intuition of the theory without giving precise definitions. Reading this paper will provide you with: (i) an argument for why "factors" are the fundamental von Neumann algebras that one needs to study; (ii) an intuitive explanation of the type classification of factors in terms of renormalization schemes that turn unnormalizable positive operators into "effective density matrices"; (iii) a mathematical explanation of the different types of renormalization schemes in terms of the allowed traces on a factor; (iv) an intuitive characterization of type I and type II factors in terms of their "standard forms"; and (v) a list of some interesting connections between type classification and modular theory, including the argument for why type III1 factors are believed to be the relevant ones in quantum field theory. None of the material is new, but the pedagogy is different from other sources the author has read; it is most similar in spirit to the recent work on gravity and the crossed product by Chandrasekaran, Longo, Penington, and Witten. [ABSTRACT FROM AUTHOR]

In this paper, we consider the Boltzmann equation with external force in the whole space, where the collision kernel is assumed to be hard potential and cutoff. We prove that the solutions of such Boltzmann equations are L p (1 ≤ p < ∞) stable under the perturbation of external force. Our estimate is based on the gradient estimate of the solution. The key step of this paper is to estimate the solutions of the equations propagate in different forward bi-characteristic. [ABSTRACT FROM AUTHOR]

How to improve the high resolution and remove the noise of composite infrared thermal wave detection image have become important research topics in machine vision. Therefore, this paper proposes a composite image enhancement algorithm based on edge adaptive total variation of direction. Using the improved adaptive directional total variation model to construct the guidance image of the guidance filter can provide better structural information for the guidance filter and conduct the guidance filter. This process is iterated to eliminate noise and ladder effect. Experimental results show that this algorithm is superior to other advanced methods in objective evaluation index and subjective vision. The algorithm proposed in this paper can not only effectively eliminate noise and ladder effect, but also highlight image details and structure information, which proves the effectiveness of this algorithm. Discover the cutting-edge algorithm for high-resolution improvement and noise elimination in infrared thermal wave detection images. Our innovative composite image enhancement technique, based on edge adaptive total variation, outperforms traditional methods. The improved directional model provides better structural information, optimizing the guidance filter process. Experimental results reveal its superiority in objective evaluation and subjective vision. This algorithm effectively eliminates noise and ladder effect while highlighting image details, validating its remarkable effectiveness. [ABSTRACT FROM AUTHOR]

In view of the problems of high production cost, scarcity and lack of diversity of 3D face datasets, this paper designs an end-to-end self-supervised learning 3D face reconstruction algorithm with a single 2D face image as input, which only uses 2D face datasets to complete model training. First, the improved ResNet module is introduced to preprocess the input face image. The deep residual neural network has strong feature extraction and characterization ability for the image, which can provide rich high-level semantic feature maps for the subsequent subnetwork. Then, add transformer module completely based on self-attention mechanism to the parameter prediction subnetwork, which can make different parameters of the subnetwork focus on self-related feature map information and avoid interference from invalid feature map information, so as to further improve the parameter prediction accuracy of the subnetwork. Next, training, ablation and comparison experiments were conducted on CelebA, BFM and Photoface datasets, and the combined function of pixel loss function and perceptual loss function was selected as the loss function. The experimental results show that: compared with the historical optimal results of the same network structure, the scale-invariant depth error (SIDE) and mean angle deviation (MAD) are improved by 5.9% and 10.8%, respectively, which strongly proves the effectiveness of the algorithm. Finally, in order to verify the actual effect of the 3D face reconstruction algorithm, examples are selected in this paper for reconstruction. The 3D faces generated by the algorithm all have a good sense of reality, which intuitively and effectively proves the advancement of the algorithm. [ABSTRACT FROM AUTHOR]

Multiple objects tracking in a video sequence can be performed by detecting and distinguishing the objects that appear in the sequence. In the context of computer vision, the robust multi-object tracking problem is a difficult problem to solve. Visual tracking of multiple objects is a vital part of an autonomous driving vehicle's vision technology. Wide-area video surveillance is increasingly using advanced imaging devices with increased megapixel resolution and increased frame rates. As a result, there is a huge increase in demand for high-performance computation system of video surveillance systems for real-time processing of high-resolution videos. As a result, in this paper, we used a single stage framework to solve the MOT problem. We proposed a novel architecture in this paper that allows for the efficient use of one and multiple GPUs are used to process Full High Definition video in real time. For high-resolution video and images, the suggested approach is real-time multi-object detection based on Enhanced Yolov5-7S on Multi-GPU Vertex. We added one more layer at the top in backbone to increase the resolution of feature extracted image to detect small object and increase the accuracy of model. In terms of speed and accuracy, our proposed approach outperforms the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Thyroid Cancer (TC) is a common malignant tumor, head and neck in the incidence of malignant tumors in the seventh, ranked fourth in the incidence in women. There are several methods to diagnose and recognize TC, such as ultrasonic, computed tomography (CT) and other means. While, it is an important role for CT examination in the diagnosis of TC, because it has the characteristics of objectivity, repeatability, and multi-dimensional imaging, and can clearly understand the scope and spatial characteristics of the lesion. CT has unique advantages in showing lymph nodes and distant metastases, such as coarse-walled or thick-walled ring calcification. The early diagnosis of TC mainly relies on manual labor, which is very inefficient. With the continuous development of information science, the construction of TC diagnosis and recognition models based on artificial intelligence (AI) has gradually become a research hotspot. At present, research on AI-based thyroid screening models mainly focuses on four aspects: first, thyroid region segmentation and image denoising based on image-omics; second, the establishment of a high-precision TC risk prediction model based on multi-omics data; third, screening of biomarkers of TC for clinical diagnosis; fourth, establish the early screening model of TC based on AI. This paper reviews the research status of the AI-based thyroid screening model based on the above four aspects. In addition, this paper also summarizes the main challenges faced by the current AI -based TC recognition and detection model and it proposes a new research idea for the future TC early screening research based on enhanced CT. [ABSTRACT FROM AUTHOR]

This research introduces a novel method for emotion recognition using Electroencephalography (EEG) signals, leveraging advancements in emotion computing and EEG signal processing. The proposed method utilizes a semisupervised deep convolutional generative adversarial network (SSDNet) as the central model. The model fully integrates the feature extraction methods of the generative adversarial network (GAN), deep convolutional GAN (DCGAN), spectrally normalized GAN (SSGAN) and the encoder, maximizing the advantages of each method to construct a more accurate emotion classification model. In our study, we introduce a flow-form-consistent merging pattern, which successfully addresses mismatches between the data by fusing the EEG data with the features. Implementing this merging pattern not only enhances the uniformity of the input but also decreases the computational load on the network, resulting in a more efficient model. By conducting experiments on the DEAP and SEED datasets, we evaluate the SSDNet model proposed in this paper in detail. The experimental results show that the accuracy of the proposed algorithm is improved by 6.4% and 8.3% on the DEAP and SEED datasets, respectively, compared to the traditional GAN. This significant improvement in performance validates the effectiveness and feasibility of the SSDNet model. The research contributions of this paper are threefold. First, we propose and implement an SSDNet model that integrates multiple feature extraction methods, providing a more accurate and comprehensive solution for emotion recognition tasks. Second, by introducing a flow-form-consistent merging pattern, we successfully address the problem of interdata mismatches and improve the generalization performance of the model. Finally, we experimentally demonstrate that the method in this paper achieves a significant improvement in accuracy over the traditional GANs on the DEAP and SEED datasets, providing an innovative solution in the field of EEG-based emotion recognition. [ABSTRACT FROM AUTHOR]

Presently, a significant number of students enrolled in colleges and universities encounter mental health challenges, including academic stress and difficulties in interpersonal relationships. These factors contribute to a decline in mental well-being and necessitate prompt intervention and assistance. The automation of mental health identification in students greatly benefits from the implementation of intelligent emotion recognition systems. Through the analysis of students' emotional states, educational institutions can gain a deeper understanding of students' mental well-being, enabling them to promptly identify and address any issues and offer more complete care and support to students. This paper proposes a method for automated emotion recognition that is driven by data. The method is developed based on the provided background information. The proposed approach incorporates a feature fusion mechanism and an attention mechanism into the ResNet-34 model. This integration enhances the model's capability to analyze intricate details and subsequently improves its classification performance when applied to electroencephalography (EEG) signals. This paper introduces several key innovations. First, an optimization technique is applied to the input component of the model, enabling multifeature fusion. Second, an attention mechanism is incorporated after the residual network module, enabling the model to prioritize parts that contribute to classification and enhance feature extraction. Finally, the network parameters are optimized using both softmax loss and center loss functions. The findings from the analysis of the sentiment EEG public data SJTU Emotion EEG Dataset (SEED) indicate that the proposed sentiment recognition approach not only enhances the classification performance of the model on the sentiment EEG data but also improves the stability of the results. This paper presents a novel approach that enables automatic and efficient recognition of students' emotions on commonly used platforms. The findings of this study hold significant implications for mental health assessment and detection in real-life production settings, offering substantial reference value in this domain. [ABSTRACT FROM AUTHOR]

Epilepsy is a neurological disorder, and its sudden seizures pose a serious threat to the quality of life of patients. Not only does this condition cause patients to potentially lose control and consciousness during seizures, leading to possible injuries or dangerous situations, but it also has a significant impact on their mental health, triggering issues such as anxiety and depression. An intelligent epilepsy diagnosis process based on electroencephalogram (EEG) signals offers notable advantages. First, it provides noninvasive brainwave signals that accurately monitor and record the patterns and characteristics of epileptic seizures, offering objective diagnostic criteria for doctors. Second, with the use of artificial intelligence and machine learning technologies, large amounts of EEG data can be efficiently analyzed, improving the speed and accuracy of diagnosis and providing timely and effective treatment plans for patients. Additionally, intelligent diagnostic systems can achieve real-time monitoring, promptly alert people to potential epileptic seizures, and provide a safer living environment for patients. In this context, this paper proposes an epilepsy diagnosis method based on a transferred AlexNet model and EEG signals. The main contributions of this paper are as follows. (1) A transfer learning mechanism is incorporated into the AlexNet model through the direct transfer of its neural network structure and the modification of some existing neural network structures, followed by collaborative training with the addition of a domain adaptation layer in the network. This introduced transfer mechanism can address small sample size issues. (2) The traditional AlexNet model suffers from redundant feature extraction, leading to slow training. This paper adds batch normalization (BN) layers after each convolutional layer in the AlexNet model to normalize the features extracted from the convolutional layers. This emphasizes the representation of the important features of EEG signals and enables the lower layers of the network to learn the features needed for EEG signal processing. (3) The transferred AlexNet model proposed in this paper is applied to extract the features of epilepsy EEG signals, and the extracted features are input into a support vector machine (SVM) classifier to obtain epilepsy diagnosis results. Comparative experiments show that the diagnostic method used in this paper yields superior results and shorter training times than those of the competing approaches. [ABSTRACT FROM AUTHOR]

Acupuncture treatment (AT) of depressive insomnia by traditional Chinese medicine has the advantages of fewer side effects, quicker results, and lower prices compared to medication and psychological and cognitive therapy. Clinicians often select multiple acupoints, such as Bai Hui (GV20), San Yin Jiao (SP6), and Shen Men (HT7), for combined treatment in a single AT session to improve sleep quality. Since the ancient literature on AT often only records the general order of acupoints, there needs to be more discussion on the influence of the multiple acupoint sequence on the priority of efficacy for a specific disease. At the same time, determining the ranking of acupoints in-patient treatment in clinical practice is mainly dependent on the treatment experience of practitioners, and there is no transparent quantitative model or evaluation method for generating credible acupoint sequences from a small and limited scale of cases. Therefore, it is essential to explore the optimization of the order of multiple acupoints in treating depressive insomnia by Traditional Chinese Medicine acupuncture both for the symptom relief of depressive insomnia patients and for the efficient use of national health care resources. This paper proposes a reinforcement learning-based method for optimizing the acupoint sequence for depressive insomnia AT to address these issues. This paper provides a post-AT EEG signal prediction model with related interpretable models to construct a reinforcement learning framework to represent the state transfer of the AT environment and a quantitative EEG signal-based AT efficacy model to represent the reward function. Finally, 30 patients with depressive insomnia were recruited to collect EEG signals during AT for depressive insomnia, and the case data were used to quantify the efficacy of AT and to model the post-AT EEG signal prediction. The above two models were applied to optimize the acupoint sequence based on reinforcement learning. Satisfactory results were obtained, verifying the effectiveness and feasibility of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

It is around a century that sample autocorrelation function has been introduced and used as a standard tool in time series analysis. A vast literature can be found on the statistical properties of the sample autocorrelation function. However, it has been highlighted recently that the sum of the sample autocorrelation function over the lags 1 to T−1 is −0.5 for all time series of length T. This property produces a big concern for the cases in which all available sample autocorrelations are used in the inference.This paper provides two new alternative for estimating the autocorrelation function. These estimators come from the idea of singular spectrum analysis which is a non-parametric technique for time series analysis. The paper utilizes a simulation study to illustrate the performance of the new approach. The results suggest that further improvement to the sample autocorrelation is possible and the new methods provide an attractive alternative to the classical approach. [ABSTRACT FROM AUTHOR]

This paper analyzes the beam under isolated and uniform loads, extending this calculation towards the structural type of the continuous beam, by means of a single expression of the elastic curve. A general expression of the bending is proposed, deduced by integrating the different differential equations of the elastica, associated to each section between discontinuities produced by the loads. In this paper, support reactions are incorporated into the load system. Therefore, the continuous beam is understood as a bar made up of sections aligned between discontinuities. With this, the isostatic beam, the hyperstatic beam and the continuous beam can be treated by means of the same integrated expression of the displacement, also called the Macaulay method. Equivalent notations are provided to the expression of bending for the cases of traction–compression and torsion, obtained through the same reasoning and sequence of operations. The formulation of elastic type and the associated operations shown allow us to cover the analysis of the generic structural form, which we can define as the beam of any number of spans, or continuous beam of n spans. The load system is also generalized, being able to contemplate loads of a different nature and form of distribution, both static and mobile. The examples that have been developed always provide analytical results of solicitation and deformation. They intend to explain the systematic path followed from the approach of the structural problem to its mathematical modelling, and the resolution procedure developed to obtain useful values for the structural verification. In these examples, an increasing degree of complexity and generalization has been followed. The expressions obtained are validated by comparing them with those that are usual in the structural literature for the same or similar problems. [ABSTRACT FROM AUTHOR]

This paper proposes a directly self-starting second-order s-sub-step explicit method, within which the three novel members are developed and analyzed for demonstration. The novel explicit schemes can output second-order accelerations for general structures, which cannot be achieved for the directly self-starting single- and two-sub-step algorithms. Each explicit algorithm achieves controllable algorithmic dissipation and adjustable bifurcation points. As a result, the novel explicit algorithms impose two algorithmic parameters, ρb and Ωb, to control numerical dissipation and bifurcation point, respectively. The parameter ρb, denoting the spectral radius at the bifurcation point, controls numerical dissipation, whereas the parameter Ωb, denoting the bifurcation point, adjusts the amount of dissipation imposed in the low-frequency range. This paper provides users with two recommended selections of Ωb. Apart from these desirable features, each novel explicit algorithm attains the maximum stability bound, 2 × s where s denotes the number of sub-steps. The four- and five-sub-step algorithms perform optimization to reduce numerical low-frequency dissipation. As the number of sub-steps increases, the novel explicit algorithms can have better numerical characteristics without an increase in the computational effort. Numerical examples are simulated to validate the performance and superiority of the novel explicit algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a low dropout bandgap voltage reference circuit that combines high output voltage accuracy and low temperature-coefficient in a wide temperature range. The low temperature-coefficient is achieved by an advanced high-order curvature compensation technique, which is implemented by a novel exponential piecewise compensation term in a high-temperature range. A supply noise self-regulation technique is proposed to realize an excellent power supply rejection ratio (PSRR) without using any amplifiers in this paper. The proposed high-accuracy voltage reference is designed in a 2 μ m bipolar process. The circuit generates a reference voltage of 3.3 V and can operate under a minimum supply voltage of 3.8 V, while consuming 44.8 μ A. The output voltage accuracy is ± 0.15%. The PSRR at 10 Hz and 1 MHz is − 6 4 dB and − 7 8 dB, respectively. The line regulation is 2.45 ppm/V in a supply voltage range from 3.8 V to 20 V. The average temperature coefficient is 11.9 ppm/∘C in a temperature range from − 5 5 ∘ C to +125∘C. [ABSTRACT FROM AUTHOR]

With advances in unmanned aerial vehicle (UAV) technologies, they have been put to use in a wide variety of scenarios, including emergency surveillance and disaster management. However, their widespread usage is still limited due to their expensive nature. Only user-piloted UAVs are extensively used still today; but their low-budget design leads to lack of auto-guidance and cooperative functions in both line-of-sight and obstacle-sensitive operations. This paper presents a new approach of self-guidance in these budget UAVs for stable maneuverability even in the obstacle-sensitive surroundings. Further, the paper additionally incorporates cooperative functioning in such self-guided budget UAVs for completing collaborative tasks of emergency surveillance. Comparative testbed results show the cost-effective benefits of the proposed methods and the precise working abilities in no-obstacle as well as obstacle-sensitive sites. [ABSTRACT FROM AUTHOR]