Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of the Relationship between Foreign Language Anxiety and Motivation of English Language learners at intermediate level in Pakistan

Foreign Language Anxiety (FLA) is the unpleasant emotional response to learning a second language, whereas motivation is the fundamental urge to initiate foreign language study and the subsequent impetus to maintain the learning of language. Motivation and anxiety (though studied separately as well by researchers) have yielded groundbreaking results in this study. The researcher works to find the relationship between anxiety and motivation. The investigation employs a quantitative methodology and questionnaires. In order to accomplish this aim, Foreign Language Classroom Anxiety Scale (FLCAS) and the Language Learning Orientations Scale (LLOS) were administered to 318 participants of intermediate-level from Kohat's public colleges. For analysis, the data were subjected to Exploratory Factor Analysis (EFA), Correlation Analysis (CA), and Regression Analysis (RA) utilizing the Statistical Package for the Social Sciences (SPSS). As per the findings of the study, various forms of FL motivation are substantially associated with subscales of FL anxiety. In other words, students with various English learning motivations experience varying levels and types of anxiety. We discover a strong yet negative association between motivation and anxiety in this study. In addition, the study demonstrates that intrinsic motivation and amotivation have a greater relationship with anxiety and producing apprehension in language learners; therefore, motivating language learners by fostering their intrinsic motivation is likely to reduce their anxiety regarding English language learning. Teachers should utilize approaches that enhance pupils' intrinsic motivation. Anxiety was negatively associated with language accomplishment; consequently, in order to boost students' English language achievement, language tutors and students must take steps for decreasing FL anxiety. Teachers can reduce the anxiety of language learners by instructing them in learning processes, establishing goals that are neither too simple nor too tough, and employing anxiety-reduction approaches.
Option Pricing under Heston Stochastic Volatility Model using Discontinuous Galerkin Finite Elements

We consider interior penalty discontinuous Galerkin finite element (dGFEM) method for variable coefficient diffusion-convection-reaction equation to discretize the Heston PDE for the numerical pricing of European options. The mixed derivatives in the cross diffusion term are handled in a natural way compared to the finite difference methods. The advantages of dGFEM space discretization and Crank-Nicolson method with Rannacher smoothing as time integrator for Heston model with non-smooth initial and boundary conditions are illustrated in several numerical examples for European call, butterfly spread and digital options. The convection dominated Heston PDE for vanishing volatility is efficiently solved utilizing the adaptive dGFEM algorithm. Numerical experiments illustrate that dGFEM is highly accurate and very efficient for pricing financial options.
A modified differential quadrature procedure for numerical solution of moving load problem

The differential quadrature method is a powerful numerical method for the solution of partial differential equations that arise in various fields of engineering, mathematics, and physics. It is easy to use and also straightforward to implement. However, similar to the conventional point discretization methods like the collocation and finite difference methods, the differential quadrature method has some difficulty in solving differential equations involving singular functions like the Dirac-delta function. This is due to complexities introduced by the singular functions to the discretization process of the problem region. To overcome this difficulty, this paper presents a combined differential quadrature–integral quadrature procedure in which such singular functions are simply handled. The mixed scheme can be easily applied to the problems in which the location of the singular point coincides with one of the differential quadrature grid points. However, for problems in which such condition is not fulfilled (i.e. for the case of arbitrary arranged grid points), especially for moving load class of problems, the coupled approach may fail to produce accurate solutions. To solve this drawback, we also introduce two simple approximations and show that they can yield accurate results. The reliability and applicability of the proposed method are demonstrated herein through the solution of some illustrative problems, including the moving load problems of Euler–Bernoulli and Timoshenko beams. The results generated by the proposed method are compared with analytical and numerical results available in the literature and excellent agreement is achieved.
Research on Cache Algorithm for Internet of Vehicles Based on Edge Computing

A huge number of computational resource-intensive applications and other content delivery services have evolved with the arrival of the 5G era and the adoption of Internet-connected devices, and the data in the Internet of Vehicles has exhibited accelerated growth. To improve the service performance of telematics, caching content at the network edge is an effective solution to reduce content delivery latency. In this paper, we propose an edge caching scheme based on content popularity with cooperation between base stations, roadside units(RSUs) and vehicles, and use an improved sparrow search algorithm(PSSA)for optimization. Simulations show that the proposed caching scheme has advantages in terms of hit rate improvement and delay reduction.
Vortex particle-in-cell method for three-dimensional viscous unbounded flow computations

A new vortex particle-in-cell (PIC) method is developed for the computation of three-dimensional unsteady, incompressible viscous flow in an unbounded domain. The method combines the advantages of the Lagrangian particle methods for convection and the use of an Eulerian grid to compute the diffusion and vortex stretching. The velocity boundary conditions used in the method are of Dirichlet-type, and can be calculated using the vorticity field on the grid by the Biot-Savart equation. The present results for the propagation speed of the single vortex ring are in good agreement with the Saffman's model
Tunable UV Absorption and Mobility of Yttrium-Doped ZnO using First-Principles Calculations

The electronic structures and optical properties of Y-doped ZnO are calculated using first-principles calculations. It is found that the replacement of Zn by the rare-earth element Y presents a shallow donor, and the Fermi level moves into the conduction band (CB). The high dispersion and s-type character of CB is expected to result in an increase in conductivity. Moreover, the absorption spectrum of the Y-doped ZnO system exhibits a slight blue shift with an increase of Y concentration, and a higher transparency in visible light is expected. Therefore, the Y-doping in ZnO would enhance the mobility and hence increase the electrical conductivity without sacrificing the optical transparency, which is essential for the improvement of ZnO's behavior and its performance in extension applications.
Potential Roles of m6A and FTO in Synaptic Connectivity and Major Depressive Disorder

RNA modifications known as epitranscriptomics have emerged as a novel layer of transcriptomic regulation. Like the well-studied epigenetic modifications characterized in DNA and on histone-tails, they have been shown to regulate activity-dependent gene expression and play a vital role in shaping synaptic connections in response to external stimuli. Among the hundreds of known RNA modifications, N6-methyladenosine (m6A) is the most abundant mRNA modification in eukaryotes. Through recognition of its binding proteins, m6A can regulate various aspects of mRNA metabolism and is essential for maintaining higher brain functions. Indeed, m6A is highly enriched in synapses and is involved in neuronal plasticity, learning and memory, and adult neurogenesis. m6A can also respond to environmental stimuli, suggesting an important role in linking molecular and behavioral stress. This review summarizes key findings from fields related to major depressive disorder (MDD) including stress and learning and memory, which suggest that activity-dependent m6A changes may, directly and indirectly, contribute to synaptic connectivity changes underlying MDD. Furthermore, we will highlight the roles of m6A and FTO, a m6A eraser, in the context of depressive-like behaviors. Although we have only begun to explore m6A in the context of MDD and psychiatry, elucidating a link between m6A and MDD presents a novel molecular mechanism underlying MDD pathogenesis.
Deep Adversary based Stealthy False Data Injection Attacks against AC state estimation

Conventional power systems are increasingly getting converted into smart cyber-physical systems with the incorporation of communication and information technologies. These changes are being made to ensure efficient control and reliability of operations under large-scale penetration of renewable energy-based generation and flexible loads like Electric Vehicles. However, these transformations are also responsible for making the power system increasingly susceptible to cyber threats like False Data Injection Attacks. In this paper, we propose a novel stealthy false data injection attack model by leveraging the concepts of adversarial attacks using just historical data collected from the power system. The power system state estimator is first approximated with a neural network which is then used to generate adversarial samples that are used for stealthy attack injection. Simulation results on the IEEE 118 bus test system show that the attack vectors generated using this model can introduce significant deviations in the estimated state values without triggering the conventional bad data detection safeguards.
Effects of Spatial System Design on Spatial Interaction Models. 1: The Spatial System Definition Problem

Rather little has been published about systematic empirical research on the problem of spatial aggregation and its effects on spatial interaction models. Of the work which has been published, all of it has dealt almost exclusively with single-parameter spatial interaction models. In this article five different aggregation procedures are examined. The experiments were based on the use of a multivariate multiparametric spatial interaction model. A first set of hypotheses tests was performed with respect to the sensitivity of model parameters to spatial aggregation methods. A second set was performed with respect to the sensitivity of model goodness-of-fit to the five spatial aggregation methods. Although questions remain, the results clearly show that the multiparametric model responds well to different aggregation algorithms. Some parameters showed substantial response, as they should, to different zonal aggregations, whereas others are shown to be much less responsive. Further, the results clearly indicate that systematic aggregation procedures generally produce better results than do random procedures. A future paper will continue with a discussion of zone definition criteria, and recommendations will be made with regard to aggregation algorithms.
Cubic Polishing Spline-Based Algorithms for Industrial Image Processing

Industrial image processing is a major technology in the fourth industrial revolution. In recent years, the spline method has gained more and more attention in image processing. To explore an efficient industrial image processing algorithm, this article proposes novel cubic polishing spline algorithms. The cubic polishing spline is a high precision spline algorithm that brings more degrees of freedom by adding nodes to better balance the local and global aspects. First, the direct and indirect cubic polishing spline transforms are used for the image interpolation filter. Then, we construct the least squares cubic polishing spline and pyramid approximation method with application to the image reconstruction and image scaling (image upscaling or downscaling). Next, the frequency domain cubic polishing spline lowpass filter and highpass filter are proposed, and the proposed schemes are applied to image smoothing and image sharpening, respectively. Finally, the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) and root mean square error (RMSE) evaluation metrics are used to illustrate the reconstruction effects, and experiments show that the algorithms proposed in this article can achieve better reconstruction results with better fidelity and competitiveness compared with other schemes.
An EEG-Based Brain-Computer Interface Using Spectral Correlation Function

Brain-Computer Interface (BCI) is a promising technique because of its wide variety of applications, from treating cognition in humans to person authentication. Brain signals can be transmitted straight to a prosthetic device from the BCI system, without the need for nerve or muscle activity. For accurately identifying the transmitted signals at the prosthetic device, considering the nature of the Electroencephalography (EEG) signal, and extracting the most informative features are effective keys. In this paper, we studied the cyclostationarity of the Slow Cortical Potential (SCP) EEG signals for BCI applications, following our previous studies. Cyclostationary analysis reveals the hidden periodicity in the signal and provides a second-order statistical description in the frequency domain. We used the FFT Accumulation Method (FAM), an effective computational algorithm, to extract the features of the Spectral Correlation Function (SCF). The features are classified using SVM RBF, SVM polynomial, and K-Nearest Neighbor classifiers, and they are considered with different pre-processing. Our research indicates that the SCP EEG signal has cyclostationary properties and this idea is applied to the BCIs as well. The classification accuracy on the BCI Competition 2003 dataset Ia’s increased considerably, by spotting the intrinsic correlation between just two EEG signals.
Broadband calculation of scattering parameters in the time domain

By exciting a broadband pulse in the time domain and performing a fast Fourier transform on the sampled time domain data it is possible to obtain the scattering parameters for a broad frequency range with one single time domain calculation. This known technique, valid for non-dispersive waveguides, is extended to homogeneously loaded dispersive waveguides. In most cases this extended technique outperforms the frequency domain approach by orders of magnitude in terms of calculation time. We will give a short introduction to this method and present some examples. >
Neutron scattering and molecular dynamics simulations: synergetic tools to unravel structure and dynamics in polymers

We present a methodology based on the tandem neutron scattering/fully atomistic molecular dynamics simulations that allows structural and dynamical features of polymer melts at different length scales to be unraveled, mainly in the intermolecular and monomeric range. Its particular success rests on that (i) both techniques cover approximately the same length and time scales and (ii) the classical van Hove formalism allows easy calculation of the magnitudes measured by neutron scattering from the simulated atomic trajectories. So, direct comparison with experimental results provides a demanding test for validating the simulated cell. Once validated, the information of the simulations can be exploited, calculating magnitudes that are not experimentally observable or extending the parameters range beyond the experimental capabilities.
Drag Reduction by Polymer Additives in Turbulent Channel Flow Simulated by Discrete-Element Models.

To investigate the mechanism of drag reduction by dilute addition of polymer in turbulent flows, a direct numerical simulation (DNS) of turbulent channel flow including discrete-element models has been carried out. The influence of polymers is approximated by beads-spring-dashpot model. The number of grid point for fluid turbulence is 64×64×64 and the number of discrete-elements is 250000. The DNS result achieved 15% drag reduction. The viscosity represented by a dashpot, rather than the elongated elasticity by a spring, contributed to the drag reduction. Experimental evidence such as enhancement of streamwise fluctuation, reduction of Reynolds shear stress, increase of streak spacing in the near-wall turbulence was consistently reproduced in our simulation.
Ac conductance and capacitance of carbon black polymer composites during thermal cycling and isothermal annealing

The ac electrical properties of acetylene black composites mixed into ethylene butylacrylate copolymer (EBA) and into poly (methyl methacrylate) (PMMA) have been measured in thermal cycling and isothermal annealing experiments. The results show that changes in electrical properties are due to rearrangement of gaps between the carbon black aggregates. This has been concluded using an exponent z that relates the critical frequency ωc denoting the crossover of the conductivity from the dc-plateau to its frequency-dependent part to the dc conductivity, σdc, according to ωc ∝σdcz. Below the melting range of EBA and the glass transition of PMMA z is about one corresponding to strong variation of the conductivity and weak dependence of the permittivity on the gaps. Above the melting range of EBA z is about 1.5, indicating strong dependence of both the conductivity and the permittivity on the gaps, as predicted by percolation theory. This was not found in the PMMA composites above the glass transition. We conclude that the polymer matrix affects the nature of the gaps between carbon black aggregates, either allowing their size to vary continuously (z about 1) or letting them open and close (z about 1.5).
Anterior tongue and jaw movement in sVd words

The relations between jaw and tongue movements were examined using words of the form sVd for eight different speakers from the X‐Ray Microbeam Speech Production Database. Measurements were examined at the maximum speeds during the release and during the closure of the tongue blade and tongue body. For nonhigh vowels the tongue blade traveled in the same direction as the jaw during release, and, to a lesser extent, the same was true during closure. Further, the magnitude of the projection of the tongue blade velocity onto the direction of the jaw movement was often large compared with the speed of the jaw. There was less consistency in the relation between tongue body and jaw movement. These results indicate that the jaw and tongue movements are not rigidly coupled. Rather the jaw, which can provide a hard boundary for the tongue, is getting out of the tongue’s way during release and following the tongue on closure for subsequent bracing. [Work supported by Grant NIDCD‐01247 to CReSS LLC. ]
Outcomes of a QST Protocol in Healthy Subjects and Chronic Pain Patients: A Controlled Clinical Trial

Chronic pain is an important cause of disability with a high burden to society. Quantitative sensory testing (QST) is a noninvasive multimodal method used to discriminate the function of nerve fibers. The aim of this study is to propose a new, reproducible, and less time-consuming thermal QST protocol to help characterize and monitor pain. Additionally, this study also compared QST outcomes between healthy and chronic pain subjects. Forty healthy young/adult medical students and fifty adult/elderly chronic pain patients were evaluated in individual sessions including pain history, followed by QST assessments divided into three proposed tests: pain threshold, suprathreshold, and tonic pain. In the chronic pain group, a significantly higher pain threshold (hypoesthesia) and a higher pain sensibility (hyperalgesia) were demonstrated at threshold temperature when compared to healthy participants. The sensitivity to the suprathreshold and tonic stimulus did not prove to be significantly different between both groups. The main results demonstrated that the heat threshold QST tests can be helpful in evaluating hypoesthesia and that the sensitivity threshold temperature test can demonstrate hyperalgesia in individuals with chronic pain. In conclusion, this study demonstrates the importance of using tools such as QST as a complement to detect changes in several pain dimensions.
Plasma Density Fluctuations in a Magnetic Field

Sinusoidal electron charge density fluctuations with propagation vector k are considered for a fully ionized gas in complete thermodynamic equilibrium in a constant magnetic field. Let $\ensuremath{\alpha}$ and $\ensuremath{\epsilon}$ be the ratio of the Debye length and of an electron gyroradius, respectively, to the wavelength ${k}^{\ensuremath{-}1}$. A general formula is derived for the frequency spectrum of these fluctuations for arbitrary values of $\ensuremath{\alpha}$, $\ensuremath{\epsilon}$, and of the angle ($\ensuremath{\varphi}\ensuremath{-}\frac{1}{2}\ensuremath{\pi}$) between k and the magnetic field. The dispersion relation implied by this expression has been obtained previously by Gross and by Bernstein, but the method of derivation is different. A very small electron-ion mass ratio $\frac{m}{M}$ is assumed.
Dynamic Load Balance Strategy Based on Hash Slots in Distributed Storage Environment

Distributed storage technology solves the problem of data explosion in the Internet era, but at the same time introduces the problem of load balance. If the load of distributed storage service is not balanced enough, it will cause some hosts to go down to reduce service availability, as well as reducing resource utilization. Aiming at the shortcomings of the current load balance strategy, this paper proposes a dynamic load balance strategy based on hash slots, which not only satisfies the uniform distribution of data, but also makes dynamic load balance for the dynamic changes in distributed storage. The experimental results showed that, compared with the commonly used consistent hashing algorithm with virtual nodes, the strategy proposed in this paper has a better load balance effect.
Hydrodynamic design of a horizontal axis current turbine with passive flow control using vortex generator and inserted tube

ABSTRACT Energy from river currents is one of the available renewable energy sources to produce electricity. An improvement in the efficiency of the horizontal axis current turbine is required for the successful utilization of this energy. This paper compares the power production of a horizontal axis current turbine and a turbine with two passive flow control attachments, the vortex generator, and the inserted tube. Firstly, the NACA S1210 hydrofoil shape has been selected. Then the variation of chord length and twist angle along the blade span has been determined. Finally, a 5-meter-diameter, three-bladed, horizontal-axis current turbine has been designed using the blade element momentum theory.The rotor has a maximum power coefficient and a maximum power of 0.47 and 42.71 kW, respectively, at the current speed of 2.1 m/s and a tip speed ratio of 6 when the hydrofoil with tubes has been chosen to design the horizontal axis current turbine. It has been proven that including vortex generators and tubes on the turbine can help increase power production by 9.8% and 14.7%, respectively.
Algebraic characterization of minimum weight codewords of cyclic codes

We consider primitive cyclic codes of length n over GF(q), where n=q/sup m/-1, and for any such code with defining set I(C), we define a system of algebraic equations, S/sub I(C/)(w), constructed with the Newton identities for the weight w. We prove that algebraic solutions of this system are in correspondence with all codewords of C of weight lower than w. To deal effectively with the system S/sub I(C/)(w), we compute a Groebner basis of this system, which gives pertinent information on minimum weight codewords. A few examples are given. <<ETX>>