Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relation between CSR and Financial Performance under Crisis: The Mediating Effect of Foreign Investment

Prior scholars put a lot of effort into exploring the relationship between CSR and financial performance by utilizing financial statistics. However, it is a lack of empirical study about the whole financial environment and discussing its impact on foreign investment. This study analyzes data before and after the 2008 crisis to determine whether: (1) companies that implemented CSR successfully attracted more foreign investment and maintained superior performance during the financial crisis and (2) the CSR and financial performance of companies were influenced by the mediating effect of foreign investment. The results illustrated: (1) the foreign ownership ratio was positively correlated to the quality of the CSR system, (2) CSR exhibited higher financial performance during the crisis; and (3) mediating effect of foreign investment existed between CSR and financial performance, especially during the crisis.
Transfer Learning for Automatic Detection of COVID-19 Disease in Medical Chest X-ray Images

The world has experienced the spread of a dangerous virus, Coronavirus (COVID-19), that has caused the death of millions of people worldwide at an extremely rapid rate, many studies have confirmed that the virus can be detected effectively using medical images. However, it takes a long time to analyze each image by radiologists who suffer from high pressures, especially due to the high similarity of symptoms between this virus and other respiratory diseases, which can lead to the confusion of cases and, consequently, the inability to identify them quickly, which could be a problem in a pandemic situation. In this paper, a methodology is proposed for the rapid and automatic diagnosis of this virus from chest radiographic images through the use of Artificial Intelligence (AI) techniques. There are two stages of the proposed model. The first step is data augmentation and preprocessing;the second step is the detection of COVID-19 with a transfer learning technique using a pre-trained deep convolutional network (CNN) architecture to extract features, Then, the obtained feature vectors are classified into three classes: COVID-19, Normal, and pneumonia, from two open medical repositories. In the experimentation phase of our model, we evaluate a set of common metrics to measure the performance of the architecture. Experimental conclusions show an accuracy of 96.52% for all classes, then a comparison with existing models in literature demonstrates that our proposed model achieves better classification accuracy © 2022. IAENG International Journal of Computer Science.All Rights Reserved.
Adaptive Successive Interference Cancellation using Deep Learning for High Altitude Platform Station in Various K-Rician Channel

— This research proposed the Adaptive-Successive Interference Cancellation (ASIC) method, which enlisted the performance and power efﬁciency from Successive Interference Cancellation (SIC) conventional. We employed deep learning as new technology for wireless communications. We have simulated for High Altitude Platform System (HAPS) communication using the Power Domain-Non-Orthogonal Multiple Access (PD-NOMA) method for three Ground Stations (GS). We consider three different areas with the various K-Rician channel model on low, medium, and high elevation for analysis. To compare ASIC and SIC performance, we used the Signal-To-Noise Ratio (SNR) and Bit Error Rate (BER) as performance parameters. From the results of extensive research, we prove that ASIC performance is more efﬁcient at the SNR value around 48.21%, 30.27%, and 42.85% in low, medium, and high elevation, respectively.
Assessment Nutritional Status of Elderly People at Old Folk Home in Klang Valley: A Cross-Sectional Study

Background & Aims : Undernutrition has a detrimental effect on health, especially in elderly individuals. Early detection of malnutrition and malnutrition risk allows for timely prevention and initiation of the necessary nutritional support. The study aimed to determine the prevalence of malnutrition among elderly residents at the old folk home in Selangor, Malaysia. Materials and methods : A total of 46 Klang valley nursing facility residents were enrolled for this cross-sectional study. The Mini Nutritional Assessment-Short Form (MNA-SF), 24-hour food recall, Food frequency questionnaire, Habitual physical activity, 24-hours physical activity recall, and anthropometric measurements were used to assess malnutrition by a trained healthcare professional. Results : Of the 46 participants, 41% had adequate nutrition, 11% had malnutrition, and 48% had malnutrition risk. According to BMI, 6.7% of the population was underweight, 35.6% were overweight, 11.1% were obese, and 46.7% were normal weight. The energy consumption was 2453.9 (±421.6) kcal for female residents and 2248.2 (±536.5) kcal for male residents, which was higher than the Recommended Nutrient consumption (RNI). Contrary to the cereals and grains category, it was determined that enough fruits and vegetables were consumed, as advised by the Food Pyramid. Consumption of milk and dairy products was higher than suggested by the Food Pyramid. Among older adults who are sedentary and inactive, results showed a higher incidence of malnutrition than those who were at risk for it. The amount of daily energy consumed surpassed the RNI, and the elderly did not consume enough of the food groups as advised by the Food Pyramid.
Chapter 1 DC MicroGrids

This chapter introduces concepts of DC MicroGrids exposing their elements, features, modeling, control, and applications. Renewable energy sources, energy storage systems, and loads are the basics components of a DC MicroGrid. These components can be better integrated thanks to their DC feature, resulting in simpler power converter topologies, as well as the control strategy required for this application. A DC MicroGrid is developed as a realistic average model where the dynamics of the system are expressed in diﬀerential equations, including the nonlinearities of the model. A nonlinear distributed control strategy is developed for the DC MicroGrid, assuring the stability of the DC bus to guarantee the proper operation of each component of the MicroGrid. The energy storage systems are separated according to their time-scale operation, where a faster one (supercapacitor) controls voltage variations on the DC bus, and a slower one (battery) provides the power ﬂow balance. The comparison with classical linear controllers is carried out to highlight the better performance of the nonlinear approach.
The Return and Volatility Dynamics of VIX-ETFs: An Empirical Study of Structural Breaks

This study examines the existence of multiple structural breaks in the Volatility Index (VIX) – Exchange-traded Fund (ETF) returns. This paper also confirms structural changes in testing VIX-ETFs series means through the Bai and Perron procedure. The work demonstrates the significance of structural changes in the VIX-ETF volatility clustering valuation practice. The results found that the stock market possessed structure breaks and indicated that the stock market was a weak efficient market. These breakpoints will then be incorporated into the GARCH-based models to measure the effect of a given change in the length of volatility, including BP-ARFIMA and BP-ARFIMA-FIGARCH models.
Polarization-independent electromagnetically induced transparency-like metasurface

Abstract. A classical electromagnetically induced transparency-like (EIT-like) metasurface is numerically simulated. This metasurface is composed of two identical and orthogonal double-end semitoroidals (DESTs) metal resonators. Under the excitation of the normal incidence waves, each of the two DESTs structure exhibits electromagnetic dipole responses at different frequencies, which leads to the polarization-independent EIT-like effect. The features of the EIT-like effect are qualitatively analyzed based on the surface current and magnetic field distribution. In addition, the large index is extracted to verify the slow-light property within the transmission window. The EIT-like metasurface structure with the above-mentioned characteristics may have potential applications in some areas, such as sensing, slow light, and filtering devices.
Characterizations of ρ-algebra and Generation Permutation Topological ρ-algebra using Permutation in Symmetric Group

The aim of this work is to introduce new branch of the pure algebra it's called algebra. Further, some new concepts like subalgebra, ideal, ideal and permutation topological algebra are introduced and studied. It is pointed out that algebra need not be algebra or algebra by a counterexample. Moreover, several examples are given to illustrate the concepts introduced in this paper.
Comparative dosimetric characterization for different types of detectors in high-energy electron beams

The purpose of this study is to perform a comparison and on analysis of measured dose factor values by using various commercially available high-energy electron beam detectors to measure dose profiles and energy property data. By analyzing the high-energy electron beam data from each detector, we determined the optimal detector for measuring electron beams in clinical applications. The dose linearity, dose-rate dependence, percentage depth dose, and dose profile of each detector were measured to evaluate the dosimetry characteristics of high-energy electron beams. The dose profile and the energy characteristics of high-energy electron beams were found to be different when measured by different detectors. Through comparison with other detectors based on the analyzed data, the microdiamond detector was found to have outstanding dose linearity, a low dose-rate dependency, and a small effective volume. Thus, this detector has outstanding spatial resolution and is the optimal detector for measuring electron beams. Radiation therapy results can be improved and related medical accidents can be prevented by using the procedure developed in this research in clinical practice for all beam detectors when measuring the electron beam dose.
Combined Use of Immune Checkpoint Inhibitors and Phytochemicals as a Novel Therapeutic Strategy against Cancer

Immune checkpoint inhibitor (ICI) therapy has dramatically changed cancer treatment, opening novel opportunities to cure malignant diseases. To date, most prevalently targeted immune checkpoints are programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), with many others being under extensive investigations. However, according to available data, only a fraction of patients may respond to ICI therapy. Additionally, this therapy may cause severe adverse immune-related side effects, such as diarrhea, headache, muscle weakness, rash, hepatitis and leucopenia, although most of them are not fatal, they can affect the patient's treatment outcome and quality of life. On the other hand, growing evidence has shown that phytochemicals with anticancer effects may combine ICI therapy to augment the safety and effectiveness of the treatment against cancer while reducing the adverse side effects. In this review, we summarize the state of art in the various experiments and clinical application of ICIs plus phytochemicals, with a focus on their combined use as a novel therapeutic strategy to cure cancer.
Phlomis species protects the cells from oxidative stress by upregulating catalase enzyme expression

Recently, interest in the pharmacological effects of plants has increased and studies on bioactive compounds have intensified. In this study, we aimed at evaluating the antioxidant and neuroprotective potential of Lamiaceae plants including Stachys lavandulifolia, Salvia verticillata, Phlomis herba venti sp. pungens and Phlomis sieheana in both cell-free systems and the cell culture model. Methanol extracts of the aerial parts of these plants, cultivated in Elazig, Turkey were carried out. Antioxidant activity assays (ABTS and DPPH) and total phenolic and flavonoid contents of the extracts were measured. Next, the effects of methanol extracts on cell viability and catalase protein levels were investigated in hydrogen peroxide induced oxidative stress model. DPPH radical scavenging activities were determined with the IC 50 value of 31.36±0.25, 30.44±0.19, 30.16±0.08 and 56.54±0.93 for Stachys lavandulifolia, Salvia verticillata, Phlomis herba venti sp. pungens and Phlomis sieheana , respectively. ABTS radical scavenging activities were determined as 6.38±1.48,16.93±0.68,5.97±4.04 and 2.28±0.51. The highest cellular protection and catalase expression were determined in Phlomis -treated cells against H 2 O 2 (p<0.05). On the other hand, no statistically significant change in cell viability was observed when the extracts were compared with each other. Our findings support the neuroprotective and antioxidant potential of these four Lamiaceae plants, particularly Phlomis species.
Spatial heterogeneity of interaction strength has contrasting 1 effects on synchrony and stability in trophic metacommunities 2

5 Spatial heterogeneity is a fundamental feature of ecosystems, and ecologists have identified it 6 as a factor promoting the stability of population dynamics. In particular, differences in interaction 7 strengths and resource supply between patches generates an asymmetry of biomass turnover with 8 a fast and a slow patch. The coupling of these two energy channels by mobile predators has been 9 identified to increase stability at different scales by promoting the asynchrony of population dynamics 10 between each patch. Here, we demonstrate that asymmetry has a contrasting effect on the stability 11 of metacommunities receiving localised perturbations. We built a model of an asymmetric metacom-12 munity with two patches linked by the dispersal of predators and in which prey receive stochastic 13 perturbations only in one patch. Perturbing prey in the fast patch synchronises the dynamics of prey 14 biomass between the two patches and destabilises predator dynamics by increasing their temporal 15 variability. Conversely, perturbing prey in the slow patch decreases the synchrony of their dynamics 16 and stabilises predator dynamics. This discrepancy between the responses is due to the asymmetric 17 transmission of perturbations caused by the different distributions of biomass between the fast and 18 the slow patch. Consequently, the fast patch drives the dynamics of the metacommunity and imposes 19 synchrony while the slow patch does not. Therefore, local perturbations can have opposite conse-20 quences at the regional scale depending on the characteristics of the perturbed patch. Our results 21 have strong implications for conservation ecology and suggest reinforcing protection policies in fast 22 patches to dampen the effects of perturbations and promote the stability of population dynamics at 23 the regional scale. 24
A Petri-Net-Based Approach to Modeling Communication Algorithms for HPC Molecular Dynamics Simulations

With the development of increasing node numbers in High Performance Computing (HPC), i.e. strong-scaling, we get the problem that many HPC applications become communication-bound. Thus, there is a need for optimizing communication. Apart from improving the communication protocols, one can work on problem-specific communication patterns. A commonly used, efficient communication pattern for the simulation of homogeneously distributed particle systems is the Shift communication. Aiming to use the Shift for our own molecular dynamics simulation library, FMSolvr, we modeled it with timed Petri nets in order to get an estimation of the communication time. For the time analysis we use Max-Plus Algebra. We put our model’s timing predictions up against an implementation of the Shift and found that our model is correct. However, our approach is over-modeling the problem.
Diffraction of short pulsed Laguerre–Gaussian beams

Based on the numerical solution of the parabolic wave equation for the complex spectral amplitude of the wave field the propagation of a short pulsed Laguerre–Gaussian beam with femtosecond duration was studied. It has been shown that the diffraction broadening of the Laguerre–Gaussian beam decreases with the pulse duration in comparison with continuous-wave radiation.
Control of photoassociation of atomic Bose-Einstein condensates by laser field configuration

Dans ce travail, nous montrons qu'il est possible d'effectuer un passage adiabatique efficace dans un systeme quantique non-lineaire quadratique a deux etats decrivant la formation de molecules faiblement liees dans les condensats atomiques de Bose-Einstein par la photo-association par champs laser.Un transfert adiabatique efficace est egalement possible si on prend en compte les non-linearites de troisieme ordre decrivant les collisions elastiques atome-atome, atome-molecule et moleculaire-molecule.Le transfert est obtenu en choisissant un desaccord approprie calcule en resolvant le probleme inverse.Nous montrons egalement que l'on peut effectuerun suivi Raman stimule exact dans un systeme non-lineaire quantique a trois etats.Dans le passage d'atomes libres a l'etat moleculaire stable, les pertes irreversibles de l'etat moleculaire intermediaire faiblement lie peuvent etre evitees par un schema a trois etats en deux couleurs dans le cas avec resonances a un ou deux photons.Ceci est obtenu par une technique de suivi exacte.Nous avons egalement etudie des modeles lineaires a deux etats bi-confluents de Heun, dependant du temps, avec des solutions en termes de combinaisons lineaires d'un nombre fini de fonctions Hermite d'ordre non entier.Nous avons presente un modele dont la solution implique seulement deux fonctions Hermite. Il s'agit d'une configuration de champ avec croisement par resonance donnee par une frequence Rabi exponentiellement divergente et un desaccord qui commence a partir de la resonance exacte et diverge exponentiellement a l'infini. Le modele prend en compte les pertes irreversibles du second etat.
Metric-locating-dominating partitions in graphs

A partition $\Pi=\{S_1,\ldots,S_k\}$ of the vertex set of a connected graph $G$ is a \emph{metric-locating partition} of $G$ if for every pair of vertices $u,v$ belonging to the same part $S_i$, $d(u,S_j)\neq d(v,S_j)$, for some other part $S_j$. The partition dimension $\beta_p(G)$ is the minimum cardinality of a metric-locating partition of $G$. A metric-locating partition $\Pi$ is called metric-locating-dominanting if for every vertex $v$ of $G$, $d(v,S_j)=1$, for some part $S_j$ of $\Pi$. The partition metric-location-domination number $\eta_p(G)$ is the minimum cardinality of a metric-locating-dominating partition of $G$. In this paper we show, among other results, that $\beta_p(G) \le \eta_p(G) \le \beta_p(G)+1$. We also characterize all connected graphs of order $n\ge7$ satisfying any of the following conditions: $\eta_p(G)\ge n-1$, $\eta_p(G)= n-2$ and $\beta_p(G) = n-2$. Finally, we present some tight Nordhaus-Gaddum bounds for both the partition dimension $\beta(G)$ and the partition metric-location-domination number $\eta(G)$.
Kernel Density Smoothing Using Probability Density Functions and Orthogonal Polynomials

This article is the first of a series devoted to providing a way to correctly explore stock market data through kernel smoothing methods. Here, we are mainly interested in kernel density smoothing, our approach revolves around introducing and testing the goodness of fit of some non-classical kernels based on probability density functions and orthogonal polynomials, the latter ones are of interest to us when they are of order two and above. For each kernel, we use a modified version of the “rules of thumb” principle in order to compute a smoothing parameter that would offer optimal smoothing for a reasonable computational cost. Compared to the Gaussian kernel, some of the tested kernels have provided a better Chi-square statistic, especially the kernels of order 2 based on Hermite and Laguerre polynomials. These results are illustrated using data from the Moroccan stock market.
On Spectral-Homotopy Perturbation Method Solution of Nonlinear Differential Equations in Bounded Domains

In this study, a combination of the hybrid Chebyshev spectral technique and the homotopy perturbation method is used to construct an iteration algorithm for solving nonlinear boundary value problems. Test problems are solved in order to demonstrate the efficiency, accuracy and reliability of the new technique and comparisons are made between the obtained results and exact solutions. The results demonstrate that the new spectral homotopy perturbation method is more efficient and converges faster than the standard homotopy analysis method. The methodology presented in the work is useful for solving the BVPs consisting of more than one differential equation in bounded domains.
Estimation of Motion Fields from Noisy Image Sequences: Using Generalized Cross-Correlation Methods

The present study proposes an approach for robust motion estimation between two successive image frames from a degraded sequence. The method is based on Generalized Cross-Correlation (GCC) Methods, where the phase of the Fourier components is used for motion parameter estimation. This method uses "Whitening" FIR filters to sharpen the cross correlation maximum, thereby improving the accuracy of identification of the peak. The estimators of interest are the the Phase Transform (PHAT) and the WIENER estimator. For robust motion estimation between two successive image frames degraded it is found that the WIENER estimator is particularly suited to this purpose. The accuracy of the estimators is also discussed. Good results have been obtained for sub-pixel translation of images of different nature and across different spectral bands.
Implantable optogenetic device with CMOS IC technology for simultaneous optical measurement and stimulation

In this study, we have developed an implantable optogenetic device that can measure and stimulate neurons by an optical method based on CMOS IC technology. The device consist of a blue LED array for optically patterned stimulation, a CMOS image sensor for acquiring brain surface image, and eight green LEDs surrounding the CMOS image sensor for illumination. The blue LED array is placed on the CMOS image sensor. We implanted the device in the brain of a genetically modified mouse and successfully demonstrated the stimulation of neurons optically and simultaneously acquire intrinsic optical images of the brain surface using the image sensor. The integrated device can be used for simultaneously measuring and controlling neuronal activities in a living animal, which is important for the artificial control of brain functions.
Prediction of contact stresses for tyre-road noise modelling

Tyre/road noise is greatly influenced by the dynamic forces generated in the contact patch. The current research for predicting the contact stresses is based on analytical formulations in two or three dimensions. The paper deals with the validation of an analytical multipoint contact pattern currently developed for introduction in a full model for tyre/road noise. The tyre tread is modelled by an elastic half-space and the road surface by several rigid asperities with random shapes. The contact law for each indenter depends on the interpenetrated volume, the area and the perimeter of its base. The model is three-dimensional and considers the interaction between the contact points. The contact between a rubber block and a periodic surface composed of spherical indenters was studied. The contact areas and stresses were measured using pressure sensitive Fuji Prescale films. The accuracy of the measurement method was estimated using the hertzian contact between a spherical indenter and the rubber block. The experimental results were compared with the multipoint model. Next work will focus on the validation of the model for real road surfaces, by evaluating the contact stresses first in statics and then in rolling conditions.