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Populations may adapt to similar environments via parallel or non-parallel genetic changes, but the frequency of these alternative mechanisms and underlying contributing factors are still poorly understood outside model systems. We used QTL mapping to investigate the genetic basis of highly divergent craniofacial traits between the scale-eater (Cyprinodon desquamator) and molluscivore (C. brontotheroides) pupfish adapting to two different hypersaline lake environments on San Salvador Island, Bahamas. We lab-reared F2 scale-eater x molluscivore intercrosses from two different lake populations, estimated linkage maps, scanned for significant QTL for 29 skeletal and craniofacial traits, female mate preference, and sex. We compared the location of QTL between lakes to quantify parallel and non-parallel genetic changes. We detected significant QTL for six craniofacial traits in at least one lake. However, nearly all shared QTL loci were associated with a different craniofacial trait within each lake. Therefore, our estimate of parallel evolution of craniofacial genetic architecture could range from one out of six identical trait QTL (low parallelism) to five out of six integrated trait QTL (high parallelism). We suggest that pleiotropy and trait integration can affect estimates of parallel evolution, particularly within rapid radiations. We also observed increased adaptive introgression in shared QTL regions, suggesting that gene flow contributed to parallel evolution. Overall, our results suggest that the same genomic regions may contribute to parallel adaptation across integrated suites of craniofacial traits, rather than specific traits, and highlight the need for a more expansive definition of parallel evolution.

Many autism spectrum disorder (ASD)-associated genes act as transcriptional regulators (TRs). Chromatin immunoprecipitation sequencing (ChIP-seq) was used to identify the regulatory targets of ARID1B, BCL11A, FOXP1, TBR1, and TCF7L2, ASD-associated TRs in the developing human and mouse cortex. These TRs shared substantial overlap in the binding sites, especially within open chromatin. The overlap within a promoter region, 1-2,000 bp upstream of the transcription start site, was highly predictive of brain-expressed genes. This signature was observed in 96 out of 102 ASD-associated genes. In vitro CRISPRi against ARID1B and TBR1 delineated downstream convergent biology in mouse cortical cultures. After 8 days, NeuN+ and CALB+ cells were decreased, GFAP+ cells were increased, and transcriptomic signatures correlated with the postmortem brain samples from individuals with ASD. We suggest that functional convergence across five ASD-associated TRs leads to shared neurodevelopmental outcomes of haploinsufficient disruption.

Plant root-nodule symbiosis (RNS) with mutualistic nitrogen-fixing bacteria is restricted to a single clade of angiosperms, the Nitrogen-Fixing Nodulation Clade (NFNC), and is best understood in the legume family. Nodulating species share many commonalities, explained either by divergence from a common ancestor over 100 million years ago or by convergence following independent origins over that same time period. Regardless, comparative analyses of diverse nodulation syndromes can provide insights into constraints on nodulation-what must be acquired or cannot be lost for a functional symbiosis-and the latitude for variation in the symbiosis. However, much remains to be learned about nodulation, especially outside of legumes. Here, we employed a large-scale phylogenomic analysis across 88 species, complemented by 151 RNA-seq libraries, to elucidate the evolution of RNS. Our phylogenomic analyses further emphasize the uniqueness of the transcription factor NIN as a master regulator of nodulation and identify key mutations that affect its function across the NFNC. Comparative transcriptomic assessment revealed nodule-specific upregulated genes across diverse nodulating plants, while also identifying nodule-specific and nitrogen-response genes. Approximately 70% of symbiosis-related genes are highly conserved in the four representative species, whereas defense-related and host-range restriction genes tend to be lineage specific. Our study also identified over 900 000 conserved non-coding elements (CNEs), over 300 000 of which are unique to sampled NFNC species. NFNC-specific CNEs are enriched with the active H3K9ac mark and are correlated with accessible chromatin regions, thus representing a pool of candidate regulatory elements for genes involved in RNS. Collectively, our results provide novel insights into the evolution of nodulation and lay a foundation for engineering of RNS traits in agriculturally important crops.

In this paper, we study the convergence of adaptive mixed interior penalty discontinuous Galerkin method for H (c u r l) -elliptic problems. We first get the mixed model of H (c u r l) -elliptic problem by introducing a new intermediate variable. Then we discuss the continuous variational problem and discrete variational problem, which based on interior penalty discontinuous Galerkin approximation. Next, we construct the corresponding posteriori error indicator, and prove the contraction of the summation of the energy error and the scaled error indicator. At last, we confirm and illustrate the theoretical result through some numerical experiments. [ABSTRACT FROM AUTHOR]

In this article, a new numerical algorithm for solving a 1-dimensional (1D) and 2-dimensional (2D) time-fractional diffusion equation is proposed. The Sinc-Galerkin scheme is considered for spatial discretization, and a higher-order finite difference formula is considered for temporal discretization. The convergence behavior of the methods is analyzed, and the error bounds are provided. The main objective of this paper is to propose the error bounds for 2D problems by using the Sinc-Galerkin method. The proposed method in terms of convergence is studied by using the characteristics of the Sinc function in detail with optimal rates of exponential convergence for 2D problems. Some numerical experiments validate the theoretical results and present the efficiency of the proposed schemes. [ABSTRACT FROM AUTHOR]

The gross encephalic morphology of representatives from 17 genera within the Geophagini tribe is comprehensively characterized, compared, and analyzed into a previously proposed phylogenetic hypothesis. Our morphological investigation highlights the prominence of the visual center within the cichlid encephalon. Notably, constrained phylogenetic analysis reveals probable convergent adaptations in two genera, Cichla and Saxatilia, characterized by diminutive gustatory lobes. In contrast, Retroculus, known for its sediment-shifting habits among Geophagini species, exhibits well-developed gustatory lobes. Previous research has established that species engaging in sediment sifting exhibit modifications in their pharyngeal apparatus and frequently adopt benthivorous feeding strategies, features that appear to be orchestrated by the gustative center in the encephalon. Furthermore, our findings underscore a putative relationship between encephalon morphology and factors such as feeding behavior, environmental conditions (including turbidity and depth), and their association with the studied cichlid species. The neuroanatomical characters proposed in this study hold promise as valuable phylogenetic markers for future analyses and contribute to our understanding of the complex interplay between neuroanatomy, behavior, and ecology within this diverse group of cichlids. [ABSTRACT FROM AUTHOR]

This study sought to ascertain the existence of convergence in environmental taxation among EU countries. By employing the sequential panel selection method and the panel KSS unit root test, it is demonstrated that the environmental taxation sequences in Luxembourg, Germany, Spain, France, and Cyprus diverge, while those of the remaining 22 countries converge. Similarly, the energy tax sequences of Croatia, Spain, Germany, and France are unstable, indicating divergence, while the remaining 23 countries exhibit significant convergence. Finally, transport taxes show a convergent trend across all EU countries. The convergence of environmental taxation can be explained by the catch-up and spatial spillover effects, and the non-convergence of a few EU countries is attributed to their minimal implementation of environmental goals. This study provides recommendations for improving environmental policies. [ABSTRACT FROM AUTHOR]

In this article, a numerical method is proposed and investigated for an initial boundary value problem governed by a fractional differential generalization of the nonlinear transient filtration law which describes fluid motion in a porous medium. This type of equation is widely used to describe complex filtration processes such as fluid movement in horizontal wells in fractured geological formations. To construct the numerical method, a high-order approximation formula for the fractional derivative in the sense of Caputo is applied, and a combination of the finite difference method with the finite element method is used. The article proves the uniqueness and continuous dependence of the solution on the input data in differential form, as well as the stability and convergence of the proposed numerical scheme. The linearization of nonlinear terms is carried out by the Newton method, which allows for achieving high accuracy in solving complex problems. The research results are confirmed by a series of numerical tests that demonstrate the applicability of the developed method in real engineering problems. The practical significance of the presented approach lies in its ability to accurately and effectively model filtration processes in shale formations, which allows engineers and geologists to make more informed decisions when designing and operating oil fields. [ABSTRACT FROM AUTHOR]

Industrial enterprises are characterized by significant energy consumption and high emissions. Therefore, the implementation of green innovation by these enterprises is beneficial for promoting sustainable economic development and safeguarding the ecological environment. In this study, a relational two-stage DEA model containing shared inputs and undesired outputs is constructed to evaluate and decompose the green innovation efficiency (GIE) of Chinese industrial enterprises across 30 provinces from 2012 to 2021. Since the objective function of this model is nonlinear, a heuristic search method is employed for its resolution. On the basis of efficiency evaluation, the Gini coefficient, kernel density estimation, and convergence analysis are further employed to investigate the regional disparities and convergence properties in the two-stage efficiency of green innovation. Our findings are as follows: (1) The average GIE of Chinese industrial enterprises demonstrates a fluctuating upward trajectory, with significant regional disparities observed between provinces. (2) Regional disparities in R&D efficiency (RDE) and achievement conversion efficiency (ACE) have diminished in all regions. Super-variable density and interregional differences serve as the primary sources of regional disparities in RDE and ACE, respectively. (3) The presence of absolute and conditional convergence in RDE and ACE is observed across all regions. To improve the GIE of Chinese industrial enterprises, it is imperative to emphasize the heterogeneous impact of economic levels, industrial structure, and the degree of openness across various regions and stages of green innovation. [ABSTRACT FROM AUTHOR]

This paper studies the convergence of environmental sustainability and its main determinants in selected American countries. In addition, it studies the impact of economic activity, income inequality, trade openness, and innovative activity on the sustainability of these countries. Convergence tests such as unit root and club convergence are applied. Furthermore, cointegration and causality tests are used, and long-term parameters are estimated using methods robust for cross-sectional dependence. The results show evidence of stochastic convergence with the univariate unit root tests in the five indicators (energy consumption, carbon dioxide emissions, ecological footprint, energy intensity, and load capacity factor) used, while with the panel data unit root tests only in four (carbon dioxide emissions, ecological footprint, energy intensity, and load capacity factor). There is no evidence of convergence towards a single club considering the complete sample, but there is evidence of convergence towards several clubs. The variables are integrated of order one and are cointegrated. Moreover, using robust estimators in the presence of cross-sectional dependence in long-term economic activity, income inequality, trade openness, and innovative activity deteriorate sustainability, while renewable energy improves it in these countries. [ABSTRACT FROM AUTHOR]

Transmedia narratives represent a novel form of communication and information in the era of media convergence. Media companies, producers, and the audience are immersed in a model that allows a story to expand across various platforms, promoting its continuous development and fostering active audience participation. The purpose of this study is to conduct a review of the most recent literature on transmedia narratives and their relationship with media, considering articles published between 2012 and 2022 in journals indexed in the Scopus database. Through bibliometric analysis, various aspects are explored, including the number of articles, most cited documents, authors’ H-index, journal impact, article languages, sponsors, and other relevant elements. In this way, it is confirmed that, although there have been significant periods in scientific production, there is still a knowledge gap to be addressed. However, a shift in the most researched themes and how this narrative manifests in digital media is also observed, indicating an evolution beyond mere fiction. [ABSTRACT FROM AUTHOR]

This paper proposes a new meta-heuristic optimization algorithm called Cleaner Fish Optimization algorithm (CFO) inspired by cleaner fish. The CFO simulates the movement behavior of cleaner fish when performing "cleaning services" and the behavior of female may change its sex to become a male, and defines two modes of position update. In addition, a two-generation cycle operation strategy is proposed to realize the optimization process. To verify the effectiveness of the CFO algorithm, 23 well-known CEC benchmark functions, CEC-2017 benchmark functions and 4 engineering design problems are adopted. Simulation results show that the proposed algorithm has a faster convergence rate and better optimal solution when it compared with several other meta-heuristic algorithms. [ABSTRACT FROM AUTHOR]

In the context of forward uncertainty quantification, we investigate the convergence of the Galerkin projections for random fractional differential equations. The governing system is formed by a finite set of independent input random parameters (a germ) and by a fractional derivative in the Caputo sense. Input uncertainty arises from biased measurements, and a fractional derivative, defined by a convolution, takes past history into account. While numerical experiments on the gPC-based Galerkin method are already available in the literature for random ordinary, partial and fractional differential equations, a theoretical analysis of mean-square convergence is still lacking for the fractional case. The aim of this contribution is to fill this gap, by establishing new inequalities and results and by raising new open problems. [ABSTRACT FROM AUTHOR]

In this investigation, a new algorithm based on the compact difference method is proposed. The purpose of this investigation is to solve the 2D time-fractional integro-differential equation. The Riemann–Liouville derivative was utilized to define the time-fractional derivative. Meanwhile, the weighted and shifted Grünwald difference operator and product trapezoidal formula were utilized to construct a high-order numerical scheme. Also, we analyzed the stability and convergence. The convergence order was O (τ 2 + h x 4 + h y 4) , where τ is the time step size, h x and h y are the spatial step sizes. Furthermore, several examples were provided to verify the correctness of our theoretical reasoning. [ABSTRACT FROM AUTHOR]

This paper introduces the fractional Fourier series on the fractional torus and proceeds to investigate several fundamental aspects. Our study includes topics such as fractional convolution, fractional approximation, fractional Fourier inversion, and the Poisson summation formula. We also explore the relationship between the decay of its fractional Fourier coefficients and the smoothness of a function. Additionally, we establish the convergence of the fractional Féjer means and Bochner–Riesz means. Finally, we demonstrate the practical applications of the fractional Fourier series, particularly in the context of solving fractional partial differential equations with periodic boundary conditions, and showcase the utility of approximation methods on the fractional torus for recovering non-stationary signals. [ABSTRACT FROM AUTHOR]

This paper investigates a high-order numerical method based on a spatial compact exponential scheme for solving the time-fractional Black–Scholes model. Firstly, the original time-fractional Black–Scholes model is converted into an equivalent time-fractional advection–diffusion reaction model by means of a variable transformation technique. Secondly, a novel high-order numerical method is constructed with (2 − α) accuracy in time and fourth-order accuracy in space based on a spatial compact exponential scheme, where α is the fractional derivative. The uniqueness of solvability of the derived numerical method is rigorously discussed. Thirdly, the unconditional stability and convergence of the derived numerical method are rigorously analyzed using the Fourier analysis technique. Finally, numerical examples are presented to test the effectiveness of the derived numerical method. The proposed numerical method is also applied to solve the time-fractional Black–Scholes model, whose exact analytical solution is unknown; numerical results are illustrated graphically. [ABSTRACT FROM AUTHOR]

Since the early 1970s, the study of Black–Scholes (BS) partial differential equations (PDEs) under the Efficient Market Hypothesis (EMH) has been a subject of active research in financial engineering. It has now become obvious, even to casual observers, that the classical BS models derived under the EMH framework fail to account for a number of realistic price evolutions in real-time market data. An alternative approach to the EMH framework is the Fractal Market Hypothesis (FMH), which proposes better and clearer explanations of market behaviours during unfavourable market conditions. The FMH involves non-local derivatives and integral operators, as well as fractional stochastic processes, which provide better tools for explaining the dynamics of evolving market anomalies, something that classical BS models may fail to explain. In this work, using the FMH, we derive a time-fractional Black–Scholes partial differential equation (tfBS-PDE) and then transform it into a heat equation, which allows for ease of implementing a high-order numerical scheme for solving it. Furthermore, the stability and convergence properties of the numerical scheme are discussed, and overall techniques are applied to pricing European put option problems. [ABSTRACT FROM AUTHOR]

We present a new family of optimal eighth-order numerical methods for finding the multiple zeros of nonlinear functions. The methodology used for constructing the iterative scheme is based on the approach called the 'weight factor approach'. This approach ingeniously combines weight functions to enhance convergence properties and stability. An extensive convergence analysis is conducted to prove that the proposed scheme achieves optimal eighth-order convergence, providing a significant improvement in efficiency over lower-order methods. Furthermore, the applicability of these novel methods to some real-world problems is demonstrated, showcasing their superior performance in terms of speed and accuracy. This is illustrated through a series of three examples involving basins of attraction with reflection symmetry, confirming the dominance of the new methods over existing counterparts. The examples highlight not only the robustness and precision of the proposed methods but also their practical utility in solving the complex nonlinear equations encountered in various scientific and engineering domains. Consequently, these eighth-order methods hold great promise for advancing computational techniques in fields that require the resolution of multiple roots with high precision. [ABSTRACT FROM AUTHOR]

Copyright of International Economics / Economia Internazionale is the property of Camera di Commercio di Genova and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The primary objective of this study is to scrutinize the industrialization patterns across 36 member states of the Organization of Islamic Cooperation (OIC) spanning from 1990 to 2021, adopting a club convergence approach. This study employed the Competitive Industrial Performance (CIP) index developed by the United Nations Industrial Development Organization. The CIP index serves as a yardstick for assessing countries’ effectiveness in manufacturing and exporting industrial goods, facilitating comparisons of industrial competitiveness across nations. The empirical findings derived from the convergence methodology established by Phillips & Sul (2007, 2009) unveiled the absence of convergence in CIP among OIC countries yet delineate the existence of four distinct convergence clusters. Notably, the CIP scores of countries exerted a significant influence on the formation of these clusters, with member states within the same cluster exhibiting comparable CIP performances. This outcome underscored the persistent dual structure characterizing the OIC panel, wherein nations with lower CIP standings failed to converge toward those with higher performance levels. [ABSTRACT FROM AUTHOR]

The use of absolute value equations (AVEs) is widespread across a wide range of fields, including scientific computing, management science, and engineering. Our aim in this study is to introduce two new methods for solving AVEs and to explore their convergence characteristics. Furthermore, numerical experiments will be carried out to demonstrate their feasibility, robustness, and effcacy. [ABSTRACT FROM AUTHOR]

In this paper, a partial Bregman alternating direction method of multipliers (ADMM) with a general relaxation factor α ∈ (0 , 1 + 5 2) is proposed for structured nonconvex and nonsmooth optimization, where the objective function is the sum of a nonsmooth convex function and a smooth nonconvex function without coupled variables. We add a Bregman distance to alleviate the difficulty of solving the nonsmooth subproblem. For the smooth subproblem, we directly perform a gradient descent step of the augmented Lagrangian function, which makes the computational cost of each iteration of our method very cheap. To our knowledge, the nonconvex ADMM with a relaxation factor α ≠ 1 in the literature has never been studied for the problem under consideration. Under some mild conditions, the boundedness of the generated sequence, the global convergence and the iteration complexity are established. The numerical results verify the efficiency and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes two simple and elegant proximal-type algorithms to solve equilibrium problems with pseudo-monotone bifunctions in the setting of Hilbert spaces. The proposed algorithms use one proximal point evaluation of the bifunction at each iteration. Consequently, prove that the sequences of iterates generated by the first algorithm converge weakly to a solution of the equilibrium problem (assuming existence) and obtain a linear convergence rate under standard assumptions. We also design a viscosity version of the first algorithm and obtain its corresponding strong convergence result. Some popular existing algorithms in the literature are recovered. We finally give some numerical tests and compare our algorithms with some related ones to show the performance and efficiency of our proposed algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem that minimizing the sum of a nonsmooth function with a smooth one in the nonconvex setting, which arising in many contemporary applications such as machine learning, statistics, and signal/image processing. To solve this problem, we propose a new nonmonotone accelerated proximal gradient method with variable stepsize strategy. Note that incorporating inertial term into proximal gradient method is a simple and efficient acceleration technique, while the descent property of the proximal gradient algorithm will lost. In our algorithm, the iterates generated by inertial proximal gradient scheme are accepted when the objective function values decrease or increase appropriately; otherwise, the iteration point is generated by proximal gradient scheme, which makes the function values on a subset of iterates are decreasing. We also introduce a variable stepsize strategy, which does not need a line search or does not need to know the Lipschitz constant and makes the algorithm easy to implement. We show that the sequence of iterates generated by the algorithm converges to a critical point of the objective function. Further, under the assumption that the objective function satisfies the Kurdyka–Łojasiewicz inequality, we prove the convergence rates of the objective function values and the iterates. Moreover, numerical results on both convex and nonconvex problems are reported to demonstrate the effectiveness and superiority of the proposed method and stepsize strategy. [ABSTRACT FROM AUTHOR]

We study the efficiency of the vector greedy algorithms for simultaneous sparse approximation in a Banach space. We employ a unified way of analyzing the approximation properties of the Vector Weak Chebyshev Greedy Algorithm, the Vector Weak Greedy Algorithm with Free Relaxation and the Vector Rescaled Weak Relaxed Greedy Algorithm. We obtain the necessary and sufficient conditions for the convergence and the optimal convergence rate on the basic sparse class for these algorithms. It shows that these vector greedy algorithms are simple but highly efficient in dealing with multi-target element. [ABSTRACT FROM AUTHOR]

This paper deals with speeding up the convergence of a class of two-step iterative methods for solving linear systems of equations. To implement the acceleration technique, the residual norm associated with computed approximations for each sub-iterate is minimized over a certain two-dimensional subspace. Convergence properties of the proposed method are studied in detail. The approach is further developed to solve (regularized) normal equations arising from the discretization of ill-posed problems. The results of numerical experiments are reported to illustrate the performance of exact and inexact variants of the method on several test problems from different application areas. [ABSTRACT FROM AUTHOR]

The DPG method with optimal test functions for solving linear quadratic optimal control problems with control constraints is studied. We prove existence of a unique optimal solution of the nonlinear discrete problem and characterize it through first-order optimality conditions. Furthermore, we systematically develop a priori as well as a posteriori error estimates. Our proposed method can be applied to a wide range of constrained optimal control problems subject to, e.g., scalar second-order PDEs and the Stokes equations. Numerical experiments that illustrate our theoretical findings are presented. [ABSTRACT FROM AUTHOR]

In this paper, an improved zeroing neural network (ZNN) model is proposed to obtain the positive definite solutions of the continuous coupled Lyapunov matrix equations (CLMEs) associated with continuous‐time Markovian jump (CMJ) systems. To achieve this, a general ZNN model is established by constructing a matrix‐valued error function. Then, to accelerate the convergence rate of the proposed ZNN model, the latest estimation is introduced to obtain an improved ZNN model. Some convergence conditions have been derived for the presented improved ZNN model through Lyapunov theory. Comparisons among the improved ZNN model and the existing results are conducted to illustrate the advantages of the proposed improved ZNN model in numerical examples. [ABSTRACT FROM AUTHOR]

China, the European Union, and the United States are the three largest digital economies in the world. This article compares the antitrust regulation of the digital economy in the three regions after the 2000s. It argues that over time, the antitrust regulation of the digital economy in the three regions tends to converge along three dimensions: growing separation of the antitrust regulation of the digital economy from that of the other economic sectors, convergence of regulatory objectives, and convergence of regulatory methods. In combination with the geopoliticization of the platform economy, this article argues that four factors have contributed to shape such convergence: (1) historical factors, (2) globalization of the digital economy, (3) increasing policy imitation and policy competition among the major digital powers of the world, (4) support from the civil society. [ABSTRACT FROM AUTHOR]

The notion of triangular inequality plays an important role in determining the structure of distance spaces. In particular, the structure of fuzzy metric spaces depends on the triangular inequality and the concerned t-norm. In most of the fixed point theorems in fuzzy metric spaces both the triangular inequality and the concerned t-norm have a major impact on the proof of fixed point theorems. Inspired by the concept of graphical metric space, it was recently introduced in N. Saleem et al., On Graphical Fuzzy Metric Spaces with Application to Fractional Differential Equations, Fractal and Fract., 6:5 (2022), 238:1-12, the notion of graphical fuzzy metric space and proved some fixed point results. The triangular inequality in such spaces is replaced by a weaker one which is directly associated with the graphical structure affine with the space. In this paper some observations on the recent results of Saleem et al. are made and so the results are revisited. Some related topological properties with some new fixed point results in graphical fuzzy metric spaces are also proved. The results of this paper generalize and extend Banach contraction principle and some other known results in this new setting. Several examples are given which support the claims and illustrate the significance of the new concepts and results. [ABSTRACT FROM AUTHOR]

We present an altered version of the inertial Krasnosel’skii-Mann algorithm and demonstrate convergence outcomes for mappings that are asymptotically nonexpansive within real, uniformly convex Banach spaces. To achieve our results, we skillfully construct the inequality in equation (6) and apply it accordingly. Our findings support and broadly generalize a number of significant findings from the literature. We demonstrate, as an application, the generation of maximal monotone operators’ zeros via fixed point methods in Hilbert spaces. Additionally, we solve convex minimization issues using our fixed-point techniques. [ABSTRACT FROM AUTHOR]

In the paper a new, fractional order, discrete model of a two-dimensional temperature field is addressed. The proposed model uses Grünwald-Letnikov definition of the fractional operator. Such a model has not been proposed yet. Elementary properties of the model: practical stability, accuracy and convergence are analysed. Analytical conditions of stability and convergence are proposed and they allow us to estimate the orders of the model. Theoretical considerations are validated using experimental data obtained with the use of a thermal imaging camera. Results of analysis supported by experiments point that the proposed model assures good accuracy and convergence for low order and relatively short memory length. [ABSTRACT FROM AUTHOR]

The purpose of this study is to introduce a computational method for solving the two-dimensional optimal control problem of the large membrane vibration equation of fractional order. Our proposed approach utilizes Chebyshev cardinal functions in two dimensions to obtain a finite dimensional optimal control problem. This problem is then solved using the Lagrange multipliers method by substituting the expansions of the state and control variables in terms of two-dimensional Chebyshev cardinal functions into the objective function, dynamical system, and initial conditions. The utilization of Chebyshev nodes offers a distinct advantage by effectively mitigating the Runge phenomenon, characterized by the undesirable oscillation and divergence of high-degree polynomial interpolants in close proximity to the interval's endpoints. We extensively discuss the convergence of our method and evaluate its accuracy using three test problems. Our results demonstrate that this technique provides highly accurate numerical solutions for these types of problems. [ABSTRACT FROM AUTHOR]

This paper presents a novel, robust, efficient, and simple optimization algorithm called the Object-Oriented Programming Optimization Algorithm (OOPOA) for tackling constrained and unconstrained optimization problems. The algorithm is inspired by the inheritance concept of Object-Oriented programming languages, where the features of a class are classified into three types according to inheritance probability: public, private, and protected. The object-oriented programming inheritance concept is implemented in the algorithm to update the population for the next generations. The proposed algorithm ensures exploitation by selecting the solution with the highest fitness to be inherited in each iteration. It ensures exploration by applying a mutation process that helps explore wide regions in the search space. The performance of this technique is demonstrated by solving 34 different optimization tasks, including 20 standard benchmark problems, ten IEEE Congress of Evolutionary Computation benchmark test functions, and four constrained real-world engineering design problems. [Display omitted] [ABSTRACT FROM AUTHOR]

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Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Russia, firms with consolidated financial statements must produce financial statements in both RAS (Russian accounting standards) and IFRS (international financial reporting standards). Unconsolidated SMEs are only required to use RAS. Using hand-collected data from 2010–2013 (pre- and post-IFRS adoption periods), we find income measures under RAS are converging to income measures under IFRS. The quality of earnings exhibits no change under IFRS, while RAS earnings are being managed upward for firms that have adopted IFRS and downward for firms that have not adopted IFRS. The relative variation in market and book values differs more widely under IFRS when compared to RAS, implying more volatility and risk under IFRS. We attribute our findings to a monitoring effect derived from IFRS. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient procedure to estimate the fractional Black–Scholes model in time-dependent on the market prices of European options using the composition of the orthogonal Gegenbauer polynomials (GB polynomials) and the approximation of the fractional derivative dependent on the Caputo derivative. First, the payoff function's singularity leads to a slow convergence in time. So, We construct an accurate and fast numerical method based on the improved method to restore the convergence rate. The derivative operational matrices for orthogonal GB polynomials are obtained by the fractional Caputo-type derivative. The implementation of this algorithm has high accuracy. The advantage of the numerical method is the orthogonality of GB polynomials and operational matrices, which reduces computation time and increases speed. Finally, three numerical examples are provided to illustrate the validity, and the numerical experiments are presented to illustrate the accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the distributed approximate subgradient-type method for minimizing a sum of differentiable and non-differentiable convex functions subject to nondifferentiable convex functional constraints in a Euclidean space. We establish the convergence of the sequence generated by our method to an optimal solution of the problem under consideration. Moreover, we derive a convergence rate of order O(N1−a) for the objective function values, where a ∈ (0.5, 1). Finally, we provide a numerical example illustrating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

For µ ≥ −1/2, and under appropriate conditions on the sequence {Mp}∞p=0 of weights, the elements, the (weakly, weakly*, strongly) bounded subsets, and the (weakly, weakly*, strongly) convergent sequences in the dual of a space Kµ of type Hankel-K{Mp} can be represented by distributional derivatives of functions and measures in terms of iterated adjoints of the differential operator x−1Dx and the Bessel operator Sµ = x−µ−1/2 Dx x 2µ+1Dxx−µ−1/2. In this paper, such representations are compiled, and new ones involving adjoints of suitable iterations of the Zemanian differential operator Nµ = xµ+1/2Dxx−µ−1/2 are proved. Prior to this, new descriptions of the topology of the space Kµ are given in terms of the latter iterations. [ABSTRACT FROM AUTHOR]

Picard's three step iteration algorithm was one of the iteration algorithms that was recently shown to be faster than some other iterative algorithms in the existing literature. The purpose of this paper was to study using this iteration algorithm for the solution of nonlinear Volterra integral equations. It was investigated that the sequences obtained from this iteration algorithm converged to the solution of nonlinear Volterra integral equations. Moreover, data dependence was obtained for nonlinear Volterra integral equations. An example was given that confirmed the applicability of the newly proven theorems. [ABSTRACT FROM AUTHOR]

In this article, a collocation technique based on quintic trigonometric B-spline (QTB-spline) functions was presented for homogeneous as well as the nonhomogeneous extended Fisher-Kolmogorov (F-K) equation. This technique was used for space integration, while the time-derivative was discretized by the usual finite difference method (FDM). To handle the nonlinear term, the process of Rubin-Graves (R-G) type linearization was employed. Three examples of the homogeneous extended F-K equation and one example of the nonhomogeneous extended F-K equation were considered for the analysis. Stability analysis and numerical convergence were also discussed. It was found that the discretized system of the extended F-K equation was unconditionally stable, and the projected technique was second order accurate in space. The consequences were portrayed graphically to verify the accuracy of the outcomes and performance of the projected technique, and a relative investigation was accomplished graphically. The figured results were found to be extremely similar to the existing results. [ABSTRACT FROM AUTHOR]

In this paper, we explore the numerical analysis of the microscale heat equation. We present the characteristics of numerical solutions obtained through both semi- and fully-discrete linear finite element methods. We establish a priori estimates and error bounds for both semi-discrete and fully-discrete finite element approximations. Additionally, the existence and uniqueness of the semi-discrete and fully-discrete finite element approximations have been confirmed. The study explores error bounds in various spaces, comparing the semi-discrete to the exact solutions, the semidiscrete against the fully-discrete solutions, and the fully-discrete solutions with the exact ones. A practical algorithm is introduced to address the system emerging from the fully-discrete finite element approximation at every time step. Additionally, the paper presents numerical error calculations to further demonstrate and validate the results. [ABSTRACT FROM AUTHOR]

Abstract: Convergence science is an intrepid form of interdisciplinarity defined by the US National Research Council as ‘the coming together of insights and approaches from originally distinct fields’ to strategically address grand challenges. Despite its increasing relevance to science policy and institutional design, there is still no practical framework for measuring convergence. We address this gap by developing a measure of disciplinary distance based upon disciplinary boundaries delineated by hierarchical ontologies. We apply this approach using two widely used ontologies—the Classification of Instructional Programs and the Medical Subject Headings—each comprised of thousands of entities that facilitate classifying two distinct research dimensions, respectively. The social dimension codifies the disciplinary pedigree of individual scholars, connoting core expertise associated with traditional modes of mono-disciplinary graduate education. The conceptual dimension codifies the knowledge, methods, and equipment fundamental to a given target problem, which together may exceed the researchers’ core expertise. Considered in tandem, this decomposition facilitates measuring social-conceptual alignment and optimizing team assembly around domain-spanning problems—a key aspect that eludes other approaches. We demonstrate the utility of this framework in a case study of the human brain science (HBS) ecosystem, a relevant convergence nexus that highlights several practical considerations for designing, evaluating, institutionalizing, and accelerating convergence. Econometric analysis of 655,386 publications derived from 9,121 distinct HBS scholars reveals a 11.4% article-level citation premium attributable to research featuring full topical convergence, and an additional 2.7% citation premium if the social (disciplinary) configuration of scholars is maximally aligned with the conceptual (topical) configuration of the research.

Abstract In this article, a new numerical algorithm for solving a 1-dimensional (1D) and 2-dimensional (2D) time-fractional diffusion equation is proposed. The Sinc-Galerkin scheme is considered for spatial discretization, and a higher-order finite difference formula is considered for temporal discretization. The convergence behavior of the methods is analyzed, and the error bounds are provided. The main objective of this paper is to propose the error bounds for 2D problems by using the Sinc-Galerkin method. The proposed method in terms of convergence is studied by using the characteristics of the Sinc function in detail with optimal rates of exponential convergence for 2D problems. Some numerical experiments validate the theoretical results and present the efficiency of the proposed schemes.

In this paper, we explore the numerical analysis of the microscale heat equation. We present the characteristics of numerical solutions obtained through both semi- and fully-discrete linear finite element methods. We establish a priori estimates and error bounds for both semi-discrete and fully-discrete finite element approximations. Additionally, the existence and uniqueness of the semi-discrete and fully-discrete finite element ap-proximations have been confirmed. The study explores error bounds in various spaces, comparing the semi-discrete to the exact solutions, the semi-discrete against the fully-discrete solutions, and the fully-discrete solutions with the exact ones. A practical algorithm is introduced to address the sys-tem emerging from the fully-discrete finite element approximation at every time step. Additionally, the paper presents numerical error calculations to further demonstrate and validate the results.

AIM: To assess the clinical efficacy of visual therapy in children with abnormal visual functions and asthenopia.METHODS: Retrospective case study. The data of 57 patients(114 eyes), aged 8.25±1.94 years, who underwent visual training at the optometry center of Xi'an Children's Hospital between January 2022 and April 2023, were collected. Patient assessments before and after training included refractive errors, a visual fatigue scale questionnaire, and visual function tests. These tests included the Worth 4 Dot for binocular vision, the Von Graefe method for measuring latent strabismus at distance and near, the gradient method for assessing the accommodative convergence/accommodation(AC/A)ratio, the push-up test for convergence near point, the negative lens method for amplitude of accommodation, the cross-cylinder test for accommodative response, and the flipper test for accommodative flexibility. Training programs were tailored based on the initial assessments of visual function and asthenopia. Comparisons were made between pre-training, 1 and 3 mo post-training evaluations.RESULTS: At baseline and 1 mo post-training, the visual fatigue scores were 26.00±6.77 and 19.57±8.90, respectively(P0.05). Furthermore, no significant differences were noted in the binocular amplitude of accommodation, NRA, PRA, and near phoria between 1 and 3 mo after training(all P>0.05). The visual function parameters of 30 patients with low myopia(SE: -1.99±1.22 D), 3 patients with low hyperopia(SE: +1.01±0.13 D)and 24 patients with emmetropia(SE: +0.25±0.11 D)were not statistically significant before training and at 1 mo after training(all P>0.05). Certain visual functions significantly improved at 1 mo after training, and most had returned normal by 3 mo.CONCLUSION: Vision therapy significantly enhances binocular visual function and alleviates symptoms of asthenopia in children with visual dysfunction. It is an effective, straightforward, and easily applicable method for relieving children's visual fatigue.

In this study, a skewness estimation method (SEM) and kurtosis estimation method (KEM) are introduced to determine the number of inactive cycles in Monte Carlo eigenvalue calculations. The SEM and KEM can determine the number of inactive cycles on the basis that fully converged fission source distributions may follow normal distributions without asymmetry or outliers. Two convergence criteria values and a minimum cycle length for the SEM and KEM were determined from skewness and kurtosis analyses of the AGN-201K benchmark and 1D slab problems. The SEM and KEM were then applied to two OECD/NEA slow convergence benchmark problems to evaluate the performance and reliability of the developed methods. Results confirmed that the SEM and KEM provide appropriate and effective convergence cycles when compared to other methods and fission source density fraction trends. Also, the determined criterion value of 0.5 for both ε1 and ε2 was concluded to be reasonable. The SEM and KEM can be utilized as a new approach for determining the number of inactive cycles and judging whether Monte Carlo tally values are fully converged. In the near future, the methods will be applied to various practical problems to further examine their performance and reliability, and optimization will be performed for the convergence criteria and other parameters as well as for improvement of the methodology for practical usage.

In the basis of a special area of genre PRology as a branch of the science of public relations the authors put the criterion of the diversity of PR-information in multi-channel public communication via new media. As a subject of genre PRology, the authors consider convergence of information formats of a PR text in a multi-channel PR. In the genre revision of PR communication in social media, the genre transformations of PR texts are influenced by the following factors: 1) technological, 2) intentional, 3) structural. Technologically, PR texts functioning in the space of social networks are characterized by 1) a polycode structure, which implies the equivalence of verbal and non-verbal levels of meaning; 2) the transgressive nature of the publication, which determines the animation of the message and its transgression (movement) in the digital space. PR texts are multi-intentional in nature. Structurally, PR texts in social networks undergo three types of convergence: 1) structural or presentational, 2) discursive, and 3) genre. Structural, or presentational, convergence of PR texts in social media is associated with the allocation in the post structure of the presentation (the actual text and iconic materials) and the reaction (readers’ comments). Discourse convergence of PR-text is associated with 1) diffusion of institutional and intentional types of discourse, 2) inter-institutional discursive interaction (PR and advertising). Genre convergence of PR-texts is a genre symbiosis of three types – convergence of primary and secondary speech genres, convergence of primary simple genres of PR-text, and intermedial convergence.