We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

This study extends the CGAN-based MODIS cloud vertical-profile (64×64-scene, about 70km width×15km height) retrieval technique developed by Leinonen et al. (2019) [1] to construct seamless 3D cloud fields for the MODIS granules [2]. Firstly, the accuracy and spatial continuity of the Leinonen et al. [1] retrievals are statistically evaluated. Then, according to the characteristics of the retrieval error, a spatially overlapping-scene ensemble generation method and a bi-directional Ensemble Binning Probability Fusion (CGAN-BEBPF) technique are developed, which improves the CGAN retrieval accuracy and support to construct seamless 3D clouds. The CGAN-BEBPF technique involves three steps: cloud masking, intensity scaling, and optimal value selection. It ensures adequate coverage of the low reflectivity areas while preserving the high reflectivity cloud cores. The technique is applied to retrieve the 3D cloud fields of Typhoon Chaba and a multi-cell convective system. The cloud structures of the CGAN-BEBPF results are highly consistent with the ground-based radar observations. It can retrieve weak clouds at the top levels of convective storms and hurricanes that were missed by ground-based radars and fill the gaps of the ground-based radar lower-level PPI scan. Overall, CGAN-BEBPF can be automated to retrieve the rich informative 3D structures of typhoons and severe convective systems over the oceans along the MODIS swath, which certainly presents great value for improving maritime and near-shore typhoons and convection prediction and other cloud-sensitive applications.

Rubella infection is typically mild or asymptomatic except when infection occurs during pregnancy. Infection in early pregnancy can cause miscarriage, stillbirth, or congenital rubella syndrome. Only individuals that are still susceptible to rubella infection during child-bearing age are vulnerable to this burden. Rubella containing vaccine (RCV) is safe and effective, providing life-long immunity. However, average age-at-infection increases with increasing vaccination coverage, which could potentially lead to increased disease burden as well, if the absolute risk of infection during child-bearing age increases. Dynamics of rubella transmission were explored using EMOD, a software tool for building stochastic, agent-based infection models. Simulations of pre-vaccine, endemic transmission of rubella virus introduced RCV at varying levels of coverage to determine the expected future trajectories of disease burden. Introducing RCV reduces both rubella virus transmission and disease burden for a period of around 15 years. Increased disease burden is only possible more than a decade post-introduction, and only for contexts with low current burden and high transmission intensity. Low or declining rubella virus transmission intensity is concurrently associated with both greater disease burden and greater vaccine effectiveness. The risk of increasing burden through vaccination only exists for locations with persistently high infectivity, high connectivity, and high fertility. A trade-off between the risk of a small, future burden increase and a large, immediate burden decrease strongly favors RCV introduction.

The problem of simulating wakes in a stratified oceanic environment with active background turbulence is considered. Anisotropic RANS turbulence models are tested against laboratory and eddy-resolving models of the problem. An important aspect of our work is to acknowledge that the environment is not quiescent; therefore, additional sources are included in the models to provide a non-zero background turbulence. The RANS models are found to reproduce some key features from the eddy-resolving and laboratory descriptions of the problem. Tests using the freestream sources show the intuitive result that background turbulence causes more rapid wake growth and decay.

The effective macroscopic model describing interactions of a viscous compressible heat-conducting fluid and a two-level fine bristly thermoelastic structure is derived from microstructure by means of the Allaire–Briane multi-scale convergence method. This new model naturally generalizes the isothermal formulation earlier constructed by the authors in 2020, see in Siberian Electronic Mathematical Reports, vol. 17 (https://doi.org/10.33048/semi.2020.17.100). In applications, the established model can be used, for example, in description, with account of heat transfer phenomemon, of airflow near surface of plant’s leaf, in simulation of epithelium surfaces of blood vessels, and in design of biotechnological devices operating in liquids.

This paper draws upon the theory of turbulence in physics to explore the similarities and differences between volatility in financial markets and turbulent phenomena at a statistical physics level. By analogizing the dynamics of financial markets with fluid turbulence, we have developed an innovative analytical framework aimed at deepening the understanding of the complexity inherent in financial markets. Our research methodology includes a comparative analysis of simulated time series data for the Standard & Poor's 500 Index and fully developed turbulent velocity time series. We focus on the similarities in key statistical physical properties, including probability distributions, correlation structures, and power spectral densities. Furthermore, we have established a model of capital flow in financial markets and proposed corresponding solutions. Through computational simulations and data analysis, we find that while financial market volatility shares some statistical characteristics with turbulent phenomena, significant differences exist in the shapes of probability distributions and the temporal scales of correlations. This suggests that although financial markets exhibit patterns akin to turbulence, the behavior of this complex, multi-variable driven system does not completely correspond to natural turbulence, highlighting the limitations of directly applying turbulence theory to financial market analysis. Our study offers a new perspective for the theories of financial markets and the field of econophysics, providing fresh insights into the complexity of financial markets and contributing to the prevention and management of financial risk.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

The fractional advection-dispersion equation FADE plays an important role, especially in explaining the process of solute-transport in natural porous media with different degrees of heterogeneity. However, studies of the flow and transport of contaminants in the underground environment are based on the knowledge of many functional parameters of the subsoil. The delay factor caused by nonlinear absorption is one of these parameters inheriting significant ambiguities in its estimation in heterogeneous media. In the study, a fractional advection-dispersion FADE model was developed by the implicit Euler method, based on a Grunwald and Caputo-Liousville approximation to explicitly evaluate and simulate the transport mechanism of contaminants in media with unsaturated porous materials subjected to a nonlinear sorption model. Better solute mass retention was observed for fractional advection-dispersion FADE model. Moreover, the absorption parameter of the retardation coefficient has a better impact on the motion of the solute in a saturated porous medium. In other words, it has a significant effect on the dispersion of pollutants in aquifers. This study highlights the need to characterize the aquifer to predict solute transport in porous media.

This study aims to investigate the psychological cognitive mechanisms of rural residents amidst the renewal of suburban historical and cultural villages by examining the interplay between nostalgia, collective memory, subjective well-being and place identity in rural tourism destinations. Using Naobao Village as a case study—a suburban historical and cultural village in Hohhot, Inner Mongolia, this research employs a comprehensive approach integrating experimental methods and questionnaire surveys. The findings demonstrate that analyzing the interaction among the four emotions can elucidate the psychological cognitive mechanism of residents. Moreover, it uncovers that tourism effects significantly influence residents' perception of their living environment with positive effects on collective memory, subjective well-being and place identity. In the theoretical model for generating psychological cognition among residents in suburban historical and cultural villages, subjective well-being and collective memory play crucial mediating roles. This study provides a theoretical foundation and practical guidance for spatial reconstruction and cultural evolution of tourist landscapes in suburban rural tourist destinations.

This review is focused on the current status of quantitative MR (qMR) of skeletal muscle. The first section covers the techniques of qMR in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/ pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1 weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, diffusion tensor imaging to emerging qMR features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMR of muscle; the intent is to demonstrate the utility qMR in different disease states of the muscle rather than a complete comprehensive survey.

This paper is devoted to the study of multi-dimensional integral transform with Fox H-function in the kernel in weighted spaces integrable functions in the domain R+n with positive coordinates. Mapping properties such as the boundedness, the range, the representations of the considered transformation are established.

In this paper we suggest a first ever construction of fractional integral and differential operators based on signed measures including a vector-valued case. The study focuses on constructing the fractional power of the Riemann-Stieltjes integral with a signed measure, using semigroup theory. The main result is a theorem that provides the exact form of a semigroup for the Riemann-Stieltjes integral with a measure having a countable number of extrema. The article provides examples of semigroups based on integral operators with signed measures and discusses the fractional powers of differential operators with partial derivatives.

This study revisits the Reynolds-averaged Navier--Stokes equations (RANS) and finds that the existing literature is erroneous regarding the primary unknowns and the number of independent unknowns in the RANS. The literature claims that the Reynolds stress tensor has six independent unknowns, but in fact the six unknowns can be reduced to three that are functions of the three velocity fluctuation components, because the Reynolds stress tensor is simply an integration of a second-order dyadic tensor of flow velocity fluctuations rather than a general symmetric tensor. This difficult situation is resolved by returning to the time of Reynolds in 1895 and revisiting Reynolds' averaging formulation of turbulence. The study of turbulence modeling could focus on the velocity fluctuations instead of on the Reynolds stress. An advantage of modeling the velocity fluctuations is, from both physical and experimental perspectives, that the velocity fluctuation components are observable whereas the Reynolds stress tensor is not.

Conditions under which compositions of component systems form a well-defined system-of-systems here are formulated at a fundamental level. Statement of what defines a well-defined composition and sufficient conditions guaranteeing such a result offers insight into exemplars that can be found in special cases such as differential equation and discrete event systems. For any given global state of a composition, two requirements can be stated informally as: 1) the system can leave this state, i.e., there is at least one trajectory defined that starts from the state, and 2) the trajectory evolves over time without getting stuck at a point in time. Considered for every global state, these conditions determine whether the resultant is a well-defined system and if so, whether it is non-deterministic or deterministic. We formulate these questions within the framework of iterative specifications for mathematical system models that are shown to be behaviorally equivalent to the Discrete Event System Specification (DEVS) formalism. This formalization supports definitions and proofs of the afore-mentioned conditions. Implications are drawn at the fundamental level of existence where the emergence of a system from an assemblage of components can be characterized. We focus on systems with feedback coupling where existence and uniqueness of solutions is problematic.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

Market turbulence with fiscal investment influences has altered IT infrastructure performance as business pursue extravagant new technology adoption. Yet, few studies have examined how shareware solution goes beyond Medium Size Enterprise that pushes efficiency and sustainability. This PLS-SEM integrated with dual primary compilation approach lessens shallow perceptions coupled with outlooks that streamline each phenomenal activity that is worthy of the necessity for competitive innovation. This unified model was applied to sampling respondents and analyzed using an ordinal regression relationship that generates a robust association that triggers the hypothesis acceptance. The adopting of BOINC shareware mesh network towards unified processing designs that were employed to build the yield by promising financial possibility using coordinated interworks hence improved group accomplishment and establishing greater esteem. This paper showcases a flexible inner IT infrastructure alongside the economic uncertainty with the framework advancement for Exostructure as a Service. Associated theoretical and practical implications were discussed.

The role of energy and entropy in decomposition of turbulent velocity flow-fields is to be shown in the paper. The decomposition methods based on energy concept are taken into account, namely the Proper Orthogonal Decomposition (POD) and its extension Bi-Orthogonal Decomposition (BOD). Entropy motivated view on the decomposed modes could offer new possibilities in the modes physical interpretation and in Reduced Order Modelling (ROM) strategy efficiency evaluation.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

Cancers are complex, adaptive ecosystems. They remain the leading cause of disease-related death among children in North America. As we approach computational oncology and Deep Learning Healthcare, our mathematical models of cancer dynamics must be revised. Recent findings support the perspective that cancer-microenvironment interactions consist of turbulent flows. As such, cancer pattern formation, protein-folding and metastatic invasion are discussed herein as processes driven by chemical turbulence within the framework of complex systems theory. Current state-of-the-art quantitative approaches used in reconstructing cancer stem cell networks are reviewed. To conclude, cancer stem cells are presented as strange attractors of the Waddington landscape.

This paper brings to fruition recently found \cite{migdal2023exact} exact reduction of decaying turbulence in the Navier-Stokes equation in $3 + 1$ dimensions to a Number Theory problem of finding the statistical limit of the Euler ensemble. We reformulate the Euler ensemble as a Markov chain and show the equivalence of this formulation to the \textbf{quantum} statistical theory of $N$ fermions on a ring, with an external field related to the random fractions of $\pi$. We find the solution of this system in the turbulent limit $N\to \infty, \nu \to 0$ in terms of a complex trajectory (instanton) providing a saddle point to the path integral over the density of these fermions. This results in an analytic formula for the observable correlation function of vorticity in wavevector space. This is a full solution of decaying turbulence from the first principle without approximations or fitted parameters. The energy spectrum decays as $k^{-\frac{7}{2}}$. We compute resulting integrals in \Mathematica{} and present effective index $n(t) = -t\partial_t \log E $ for the energy decay as a function of time Fig.\ref{fig::NPlot}. The asymptotic value of the effective index in energy decay $n(\infty) = \frac{5}{4}$, but the universal function $n(t)$ is neither constant nor linear.

We have found an infinite dimensional manifold of exact solutions of the Navier-Stokes loop equation for the Wilson loop in decaying Turbulence in arbitrary dimension $d >2$. This solution family is equivalent to a fractal curve in complex space $\mathbb C^d$ with random steps parametrized by $N$ Ising variables $\sigma_i=\pm 1$, in addition to a rational number $\frac{p}{q}$ and an integer winding number $r$, related by $\sum \sigma_i = q r$. This equivalence provides a \textbf{dual} theory describing a strong turbulent phase of the Navier-Stokes flow in $\mathbb R_d$ space as a random geometry in a different space, like ADS/CFT correspondence in gauge theory. From a mathematical point of view, this theory implements a stochastic solution of the unforced Navier-Stokes equations. For a theoretical physicist, this is a \textbf{quantum} statistical system with integer-valued parameters, satisfying some number theory constraints. Its long-range interaction leads to critical phenomena when its size $N \rightarrow \infty$ or its chemical potential $\mu \rightarrow 0$. The system with fixed $N$ has different asymptotics at odd and even $N\rightarrow \infty$, but the limit $\mu \rightarrow 0$ is well defined. The energy dissipation rate is analytically calculated as a function of $\mu$ using methods of number theory. It grows as $\nu/\mu^2$ in the continuum limit $\mu \rightarrow 0$, leading to anomalous dissipation at $\mu \propto \sqrt{\nu} \to 0$. The same method is used to compute all the local vorticity distribution, which has no continuum limit but is renormalizable in the sense that infinities can be absorbed into the redefinition of the parameters. The small perturbation of the fixed manifold satisfies the linear equation we solved in a general form. This perturbation decays as $t^{-\lambda}$, where the anomalous dimensions $\lambda$ satisfy the spectral equation \eqref{spectralEq}. The spectrum becomes a continuum in the statistical limit $N \to \infty$, presumably leading to multifractal phenomena.

The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.

The main contribution of this paper is to develop a graphical tool to evaluate the suitability of a candidate parametric model to fit a data set. The practical motivation is to check the adequacy of the so called SAINT model proposed in Jarner and Kryger (2011). This model has been implemented in practice by an important European pension fund concerned with setting annuity reserves for all current or former employees of Denmark. So, one particular relevant question is whether this mortality model is actually fitting old-age. Our graphical test can be described as follows. First we transform the data by means of the parametric model which is being evaluated. Should the model be correct, the transformed data will be in accordance with an Exponential distribution with rate 1. Then we construct a family of local linear hazard estimates based on the data on the transformed scale. Finally we use the statistical tool SiZer to assess the goodness-of-fit of the Exponential distribution to the data on the transformed scale. If the model is correct the SiZer map should not reveal any significant feature in the family of kernel estimates. Our method allow us to establish a diagnostic regarding the validity of the SAINT model when describing mortality patterns in four different countries.

We develop a quantitative microscopic theory of decaying Turbulence by studying the dimensional reduction of the Navier-Stokes loop equation for the velocity circulation. We have found an infinite dimensional manifold of solutions of the Navier-Stokes loop equation\cite{M93, M23PR} for the Wilson loop in decaying Turbulence in arbitrary dimension $d >2$. This family of solutions corresponds to a fractal curve in complex space $\mathbb C^d$, described by an algebraic equation between consecutive positions plus a nonlinear periodicity condition. We derive the constrained SDE for the evolution of the fractal curve at a fixed moment of physical time as a function of an auxiliary stochastic time. We expect this stochastic process to cover our fixed manifold of the solutions of the decaying Turbulence. The energy density of the fluid decays as $\mathcal E_0/t$, where $\mathcal E_0$ is an initial dissipation rate. Presumably, we have found a new phase of extreme Turbulence yet to be observed in real or numerical experiments.

While laminar flow heat transfer and mixing in microfluidic geometries has been investigated experimentally, as has the effect of geometry-induced turbulence in microfluidic flow (it is well documented that turbulence increases convective heat transfer in macrofluidic flow), little literature exists investigating the effect of electrokinetically-induced turbulence on heat transfer at the micro scale. Using recently observed experimental data, this work employed computational fluid dynamics coupled with electromagnetic simulations to determine if electrokinetically-forced, low-Reynolds number turbulence could be observed in a rectangular microchannel with using Newtonian fluids. Analysis of the results was done via comparison to the experimental criteria defined for turbulent flow. This work shows that, even with a simplified simulation setup, computational fluid dynamics (CFD) software can produce results comparable to experimental observations of low-Reynolds turbulence in microchannels using Newtonian fluids. In addition to comparing simulated velocities and turbulent energies to experimental data this work also presents initial data on the effects of electrokinetic forcing on microfluidic flow based on entropy generation rates.

Atmospheric turbulence characteristics are essential in determining the quality of astronomical images and implementing adaptive optics systems. In this study, the vertical distributions of optical turbulence at the Peak Terskol observatory (43.27472 ° N 42.50083 ° E, 3127 m a.s.l.) using the Era-5 re-analysis and scintillation measurements are investigated. For the closest reanalysis grid node to the observatory, vertical profiles of the structural constant of the air refractive index turbulent fluctuations Cn2 were obtained. The calculated Cn2(z) vertical profiles are compared with the vertical distribution of turbulence intensity obtained from tomographic measurements with Shack-Hartmann sensor. The atmospheric coherence length at the location of Terskol Peak was estimated. Using combination of atmospheric models and scheme paramaterization of turbulence, Cn2(z) profiles at Mt. Kurapdag were obtained. The values of atmospheric coherence length at the Peak Terskol are compared with estimated values of this length at the ten astronomical sites including Ali, Lenghu and Daocheng.

As motor capacity and rated voltage increase, the demand for motor insulation also increases. Additionally, the electric field distribution at the end of a large-scale hydro generator is extremely non-uniform, and corona discharge readily occurs. This destroys the main insulation, which significantly affects the service life of electrical machinery. Thus, the regulation of the electric field concentration at the end of a large-scale hydro generator needs to be addressed. There are many problems in resistance–capacitance chain model research. Particularly, these models cannot accurately reflect the insulation, corona structure, and electric field distribution in electrical machinery. Additionally, the corner electric field and loss distributions cannot be obtained, leading to a higher calculation error. The electric field distribution at the motor end and the loss distribution were analyzed using the finite-element method. First, by applying the basic principles of electric circuits and electromagnetic field theory, we calculated the electric field distribution at the stator bar end. Second, a 3D model of the stator bar was built using Creo Parametric, yielding a model that is more closely related to the prototype wirebar model. Then, the potential, electric field, and loss distributions around the stator bar were simulated by using COMSOL simulation software. The effects of the circular arc corner, nonlinearity coefficient, anti-corona coating length, and resistivity of the stator bar on the electric field distribution at the motor end were explored.

This paper employs the Finite Element Method (FEM) to simulate and analyze the effects of corrosion defect parameters on the stress and failure pressure of pipelines. It investigates how the boundary conditions of the pipeline model influence stress and examines the sensitivity of failure pressure to corrosion defect parameters. A nonlinear regression equation has been developed from a dataset obtained through simulation experiments to predict the failure pressure of corroded pipelines. To validate the effects of corrosion defect parameters on failure pressure, a hydrostatic test platform for an API 5L X65 pipeline with corrosion defects was established to measure stress levels and failure pressures across varying corrosion defects. The study reveals that failure pressure is negatively correlated with corrosion length and depth, while positively correlated with corrosion width. Among these parameters, corrosion depth exerts a more significant influence on the pipeline's failure pressure than corrosion length and width. Within the range of corrosion defect parameters examined, the maximum deviation of the prediction equation's results from the simulation results is 8.71%, with an average deviation of 5.81%. The standard deviation of the fitted residuals is 0.01837. Additionally, the maximum deviation between the predicted results and experimental measurements is 8.39%, with an average deviation of 7.77%. The strong agreement between the predicted results from the equation and the actual measured data underscores the effectiveness of the nonlinear regression equation.

We consider the developed turbulence of capillary waves on shallow water. Analytic theory shows that an isotropic cascade spectrum is unstable with the respect to small angular perturbations, in particular, to spontaneous breakdown of the reflection symmetry and generation of nonzero momentum. By computer modeling we show that indeed a random pumping, generating on average zero momentum, produces turbulence with a nonzero total momentum. A strongly anisotropic large-scale pumping produces turbulence whose degree of anisotropy decreases along a cascade. It tends to saturation in the inertial interval and then further decreases in the dissipation interval. Surprisingly, neither the direction of the total momentum nor the direction of the compensated spectrum anisotropy is locked by our square box preferred directions (side or diagonal) but fluctuate.

Crisis environments, which are becoming systemic, pose significant challenges to smart government strategies. The paper aims to contribute to academic debate by proposing an analytical framework for examining the institutional capacities of smart government systems in addressing local crises. The paper focuses on the recent approach of robust governance and highlights a set of variables that promote effective smart government: contingency planning capacity, analytical capacity, organizational management capacity, and collaborative capacity. The study presents an analytical model for evaluating the robustness and effectiveness of local smart government systems in crises. One of the significant findings of this study has been the identification of critical indicators that inform institutional capacities of smart government systems. By analyzing these indicators, the proposed analytical framework provides a comprehensive approach to assess the preparedness of smart government systems in dealing with crises. Moreover, it can be used to benchmark the performance of local smart government systems in similar contexts and identify best practices for improving crisis management.

The structure of turbulent flow over non-flat surfaces is a topic of major interest in practical applications in both engineering and geophysical settings. A lot of work has been done in the fully rough regime at high Reynolds numbers where the effect on the outer layer turbulence structure and the resulting friction drag is well documented. It turns out that surface topology plays a significant role on the flow drag especially in the transitional roughness regime and therefore, hard to characterize. Survey of literature shows that roughness function depends on the interaction of roughness height, flow Reynolds number and topology shape. In addition, if the surface topology contains large enough scales then it can impact the outer layer dynamics and in turn modulate the total frictional force. Therefore, it is important to understand the mechanisms underlying drag increase from systematically varied surface undulations in order to better interpret quantifications based on mean statistics such as roughness function. In this study, we explore the mechanisms that modulate the turbulence structure over a two-dimensional (2D) sinusoidal wavy surface with a fixed amplitude, but varying slope. To accomplish this, we model the turbulent flow between two infinitely wide 2D wavy plates at a friction Reynolds number, $Re_{\tau}=180$. We pursue two different but related flavors of analysis. The first one adopts a roughness characterization flavor of such wavy surfaces. The second one focuses on understanding the non-equilibrium near surface turbulence structure and their impact on roughness characterization. Analysis of the different statistical quantifications show strong dependence on wave slope for the roughness function indicating drag increase due to enhanced turbulent stresses resulting from increased production of vertical velocity variance from the surface undulations.

The quest for youthful, healthy skin and full, vibrant hair has long been a driving force in the dermocosmetics field. However, traditional approaches often struggle to address the underlying causes of aging, damage, and hair loss. Regenerative cosmetics, powered by skin tissue engineering, offer a transformative alternative. This review explores the emerging field of using engineered skin tissues for cosmetic purposes, focusing specifically on their potential for anti-aging, repair, and hair restoration applications. We discuss how these technologies aim to rejuvenate aging skin by promoting collagen production, reducing wrinkles, and improving overall skin function. Additionally, the use of engineered skin for wound healing and scar reduction is examined, highlighting their potential to improve the appearance and functionality of damaged skin. Finally, we advance the exciting prospects of utilizing skin tissue engineering techniques to regenerate hair follicles, potentially offering solutions for hair loss and promoting denser hair growth.

Systematic reviews represent a powerful instrument to summarize the existing evidence in medical literature. However, articles for a systematic review are hard to identify, and mostly require a structured search of the literature through a number of databases, using keyword-based search strategies, followed by the painstaking manual selection of pieces of evidence that are pertinent to the query. A.I. algorithms may offer solutions to reduce the workload on investigators. We applied BERTopic, a newer and much-recognized transformer-based topic-modeling algorithm, to two datasets of 6137 and 5309 articles of newly published systematic reviews in the area of peri-implantitis and bone regeneration in implant dentistry. In the two datasets, BERTopic identified 14 and 22 clusters, respectively, and it automatically created labels describing the nature of the topics for each individual cluster based on semantic interpretation of their titles. Most themes regarded the query theme, but in both conditions, BERTopic also uncovered articles related to off-themes, which composed around 30% of the dataset—with sensitivity up to 0.79 and specificities of at least 0.99. Our results suggest that adding a topic-modeling step to the screening process could potentially save working hours for researchers involved in systematic reviews of the literature.

It’s very well known that the world's attention is currently focused on the energy transition. The energy security, in addition to the drive to reduce greenhouse gas emissions in order to limit global warming, and the generalization of the access to energy, have contributed to adoption of the Moroccan Energy Strategy with a strong focus on Renewable Energies (RE). Morocco is notoriously poor in conventional fossil primary energy resources with an energy dependence on the order of 90%. The energy crisis and that resulted from Covid-19 pandemic and the geopolitical conflicts, combined compounded with steady increase in demand have heavily affected the security and the stability of the country's energy situation. The transition to RE, by strongly engaging in the implementation of several solar, wind and hydro energy projects benefiting from the country's excellent solar and wind energy potential, has made the country the leader in RE in Africa. By 2030, the share of RE in the installed capacity is expected to reach 52%. In this work, an overview of the current situation of RE (particularly solar energy) in Morocco is provided, including, the potentials, obstacles and challenges, and future perspectives. Thanks to its high solar potential location, it’s predictable that Morocco effort will be focused on this field: the Erasmus Plus Innomed Project is a virtuous example of international cooperation, aiming at create a Solar Energy Network, in synergy with EU Partners.

This study systematically addresses the challenge of accurately modeling memristors, focusing on four distinct types doped with tungsten, tin, chromium, and carbon, fabricated by Known Inc. A comprehensive characterization was performed by subjecting the devices to sinusoidal excitations with varying frequencies and amplitudes, followed by data averaging and high-frequency filtering. The resulting measurements were fitted using three prominent memristor models: VTEAM, MMS, and Yakopcic, with additional bespoke modifications assessed. These models, typically formulated as coupled algebraic-differential equations integrating electrical quantities (voltage and current) with internal state variables governing device dynamics, were optimized using two robust approaches: (1) interior-point optimization with gradient-based search, and (2) Nelder-Mead gradient-free optimization, both with box constraints applied. A thorough comparison and discussion of the optimized model parameters ensued, accompanied by an examination of sensitivity to diverse frequency and amplitude ranges. The findings inform conclusions and provide a foundation for future refinements, underscoring the importance of multi-model evaluation and advanced optimization strategies in precise memristor modeling. The presented methodology offers a valuable framework for elucidating optimal modeling paradigms tailored to specific memristor architectures and operating regimes, ultimately enhancing their integration in emerging neuromorphic and computational applications.

This is the second paper in a cycle investigating the exact solution of loop equations in decaying turbulence. We perform numerical simulations of the Euler ensemble, suggested in the previous work, as a solution to the loop equations. We designed novel algorithms for simulation, which take a small amount of computer RAM so that only the CPU time grows linearly with the size of the system and its statistics. This algorithm allows us to simulate systems with billions of discontinuity points on our fractal curve, dual to the decaying turbulence. For the vorticity correlation function, we obtain \textbf{quantum fractal laws} with regime changes between universal discrete values of indexes. The traditional description of turbulence with fractal or multifractal scaling laws does not apply here. The measured conditional probabilities of fluctuating variables are smooth functions of the logarithm of scale, with statistical errors being negligible at our large number of random samples $T = 167,772,160$ with $N = 200,000,000$ points on a fractal curve. The quantum jumps arise from the analytical distribution of scaling variable $X = \frac{\cot^2(\pi p/q)}{q^2}$ where $\frac{p}{q}$ is a random fraction. This distribution is related to the totient summatory function and is a discontinuous function of $X$. In particular, the energy spectrum is a devil's staircase with tilted uneven steps with slopes between $-1$ and $-2.03$. The logarithmic derivative of energy decay $n(t)$ as a function of time is jumping down the stairs of universal levels between $1.50$ and $1.53$. The quantitative verification of this quantization would require more precise experimental data.

This article examines the wavelet transforms and the machine learning methods in accelerating large eddy simulations of turbulent flows. An overarching challenge of large eddy simulations is to accurately represent the cascade of kinetic energy across the cut-off length scale. Taylor hypothesis suggests that the energy cascade occurs through the process of vortex stretching. However, Richardson hypothesis assumes the self-amplification of the strain field and a hierarchical break down of large eddies lead the energy cascade. The large eddy simulations typically employs the self-amplification of the strain in formulating subgrid models. However, several studies also proposed subgrid models based on vortex stretching. The wavelet-based coherent vortex simulation of turbulence directly accounts for vortex stretching in overall forward scatter of energy, while allowing local backscatter. The wavelet-based large eddy simulation adapts the grid to capture the creation of small-scale eddies, while adopting subgrid models based on the self-amplification of strain. The advancement of artificial intelligence in turbulence modelling is currently evolving around accelerating the numerical simulations of turbulent flow. However, there is a clear connection between the application of wavelet transfroms and neural networks for directly solving the Navier-Stokes equation, indicating some potential benefits of wavelet methods over the neural networks.

Among the various types of gas sensors, the chemoresistive gas sensors based on metal oxides are considered the most attractive ones due to their simple operation, low costs and miniaturization. Thin films of V2O5 undoped and doped with TiO2 were studied as nitrogen dioxide, methane and hydrogen sensors. The experimental kinetics of the electrical conductivity changes due to introduction and removal of gas on metal oxide gas sensors were successfully explained in terms of the Langmuir adsorption theory.

The manuscript deals with a new two-parameter unit stochastic distribution, obtained by transforming the Gumbel distribution, using generalized logistic mapping, into a unit interval. The distribution thus obtained is called the Gumbel–Logistic Unit (abbr. GLU) distribution, and its key stochastic properties have been investigated in detail. Among others, it is shown that the GLU distribution, unlike the Gumbel one which is always positively asymmetric, can take both asymmetric forms. Also, the procedure for estimating parameters based on quantiles, along with the asymptotic properties of the obtained estimators and the study of their numerical simulation, is presented. Finally, the application of the GLU distribution in modeling some real–world data related to telecommunications is considered.

Turbulent dissipation is a central issue in the star and galaxy formation process. Its fundamental property of space-time intermittency, well characterised in incompressible laboratory experiments, remains elusive in cosmic turbulence. Progress requires the combination of state-of-the-art modelling, numerical simulations and observations. The power of such a combination is illustrated here where the statistical method intended to locate extrema of velocity shears in a turbulent field is applied to numerical simulations of compressible magneto-hydrodynamical (MHD) turbulence dedicated to dissipation scales and to a nearby turbulent diffuse molecular cloud. We demonstrate that short-spacing increments of observables can detect strongly dissipative structures. In our simulations, we compute structure functions of various synthetic observables and show that they verify Extended Self-Similarity. This allows to compute their intermittency exponents and we show how they could help constraining some properties of the underlying three-dimensional turbulence. In observations of a turbulent cloud close to the Sun in our Galaxy, a remarkable coherent structure of velocity shear extremum is disclosed . At the location of the largest velocity shear, this coherent structure is found to foster 10 × more carbon monoxide molecules than standard diffuse molecular gas, an enrichment supported by models of non-equilibrium warm chemistry triggered by turbulent dissipation. The power of the combination between modelling and observations is also illustrated by observations of the CH+ cation that provide unique quantitative informations on the kinetic energy trail in the massive, multi-phase and turbulent circum-galactic medium of a galaxy group at redshift z = 2.8.

The nonlocality (superdiffusion) of turbulence is expressed in the empiric Richardson t3 scaling law for the mean square of the mutual separation of a pair of particles in a fluid or gaseous medium. The development of the theory of nonlocality of various processes in physics and other sciences based on the concept of Lévy flights resulted in the idea of Shlesinger and colleagues about the possibility of describing the nonlocality of turbulence using a linear integro-differential equation with a slowly falling kernel. The close approach developed by us made it possible to establish the closeness of the superdiffusion parameter of plasma density fluctuations moving across a strong magnetic field in a tokamak to the Richardson law. In this paper, we show the possibility of a universal description of the characteristics of nonlocality of transfer in a stochastic medium (including turbulence of gases and fluids) using the Biberman-Holstein approach to the transfer of excitation of a medium by photons, generalized to take into account the finiteness of the velocity of excitation carriers. This approach enables us to propose a scaling that generalizes Richardson's t3 scaling law to the combined regime of Lévy flights and Lévy walks.

Tropical cyclones have long been known to be powered by turbulent enthalpy fluxes from the ocean surface and retarded by turbulent momentum fluxes into the surface. Here were review evidence that the development and structure of these storms are also partially controlled by turbulence in the outflow near the storm top. Finally, we present new research that shows that tropical cyclone-like, low-aspect-ratio vortices are most likely in systems in which the bottom heat flux is controlled by mechanical turbulence and the top boundary is insulating.

The capabilities of a quadcopter in the hover mode for low-altitude sensing of atmospheric turbulence with high spatial resolution in urban areas characterized by complex orography are investigated. The studies were carried out in different seasons (winter, spring, summer, and fall), and the quadcopter hovered in the immediate vicinity of ultrasonic weather stations. The DJI Phantom 4 Pro quadcopter and AMK-03 ultrasonic weather stations installed in different places of the studied territory were used in the experiment. The smoothing procedure was used to main regularities in the behavior of the longitudinal and lateral spectra of turbulence in the inertial and energy production ranges. The longitudinal and lateral turbulence scales were estimated by the least-square fit method with the von Karman model as a regression curve. It is shown that the turbulence spectra obtained with DJI Phantom 4 Pro and AMK-03 generally coincide with minor differences observed in the high-frequency region of the spectrum. In the inertial range, the behavior of the turbulence spectra shows that they obey the Kolmogorov-Obukhov “5/3” law. In the energy production range, the longitudinal and lateral turbulence scales and their ratio measured by DJI Phantom 4 Pro and AMK-03 agree to a good accuracy. Discrepancies in the data obtained with the quadcopter and the ultrasonic weather stations at the territory with complex orography are explained by the partial correlation of the wind velocity series at different measurement points and the influence of the inhomogeneous surface.

The problems of modeling the human bladder and its stress-strain state under external static influence were considered. A method for identification of the anisotropic biomechanical characteristics of bladder tissue was proposed. A FEM model was created, which accepts into regard that the bladder is surrounded by fiber and affected by surrounding organs, and partially protected by pelvic bones. The model considered the presence of constant hydrostatic pressure on the walls of the bladder when it is full. It has been shown that isotropic mechanical characteristics of biological tissue can be used for studying the deformed state of a filled bladder if the filled bladder 300 ml is considered as initial non-deformed stage. This was shown by modeling and verification the effect of the external static force on the bladder. Numerical experiments were conducted based on the constructed model. To validate the results obtained, a series of natural experiments on the effect of external pressure on the bladder under ultrasound control was conducted. In the future, it is planned to use the constructed model to study rupture deformations of the bladder under the influence of static and dynamic loads.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

A constant effort is made in the physical metallurgy of transformation induced plasticity (TRIP) steels. These are multiphase steels, whose mechanical behavior depends on the different phases present, the intrinsic strength of each phase, the work hardening of each constituent and the austenite to martensite transformation, among others. Hard and soft phases can be distinguished in these steels and both stress and strain are distributed between them. The objective of this work was to simulate the stress-strain behavior for two TRIP steels. Bouquerel’s model was modified to account for the initial martensite, a moderate hard austenite and adjustable strain hardening parameters. The austenite fraction that transforms into martensite was computed through an Olson and Cohen model. The Mecking-Kocks model was used to evaluate the increment in the dislocation density and the Rodriguez-Gutierrez model, to compute the hardening of martensite. Ferrite is considered a soft phase, martensite and bainite, hard phases and austenite, a phase with a moderate hardness. The routine was implemented in MATLAB, and results were compared with those obtained experimentally in a tension test of two TRIP steels of the same composition but different heat treatments, obtaining in both cases a good agreement for the stress-strain-curves.

We develop an action principle for producing a single fluid, two-constituent system with dissipation in general relativity. The two constituents in the model are particles and entropy. The particle flux creation rate is taken to be zero, while the entropy creation rate is non-zero. Building on previous work, it is demonstrated that a new term (the proper time derivative of the matter space ``metric'') is required in the Lagrangian in order to produce terms typically associated with bulk and shear viscosity. Equations of motion, entropy creation rate, and energy-momentum-stress tensor are derived. Using an Onsager approach of identifying thermodynamic ``forces'' and ``fluxes'' a model is produced which delivers the same entropy creation rate as the standard, relativistic Navier-Stokes equations. This result is then contrasted with a model generated in the spirit of the action principle, which takes as its starting point a specific Lagrangian and then produces the equations of motion, entropy creation rate, and energy-momentum-stress tensor. Unlike the equations derived from Onsager reasoning, where the analogs of the bulk and shear viscosity coefficients are prescribed ``externally'', we find that the form of the coefficients in the second example are a direct result of the specified Lagrangian. Furthermore, the coefficients are shown to satisfy evolution equations along the fluid worldline; also a product of the specific Lagrangian.

This work presents a novel approach for the study of the movement of droplets on inclined surfaces under the influence of gravity and chemical heterogeneities. The developed numerical methodology uses data-driven modeling to extend the applicability limits of an analytically derived reduced-order model for the contact line velocity. More specifically, while the reduced-order model is able to capture the effects of the chemical heterogeneities to a satisfactory degree, it does not account for gravity. To alleviate this shortcoming, datasets generated from direct numerical simulations are used to train a data-driven model for the contact line velocity, which is based on the Fourier neural operator and corrects the reduced-order model predictions to match the reference solutions. This hybrid surrogate model, which comprises of both analytical and data-driven components, is then integrated in time to simulate the droplet movement, offering a speedup of five orders of magnitude compared to direct numerical simulations. The performance of this hybrid model is quantified and assessed in different wetting scenarios, by considering various inclination angles and values for the Bond number, demonstrating the accuracy of the predictions as long as the adopted parameters lie within the ranges considered in the training dataset.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

An aneurysm is a vascular malformation, it can be classified according to its location (cerebral, aortic); and according its shape (saccular, fusiform, and mycotic). The study of blood flow interaction with the aneurysms has gained attention from physicists an engineers in recent years. Shear stresses, oscillatory shear index (OSI), gradient oscillatory number (GON), and residence time had been used as potential variables to describe the hemodynamics as well as the origin and evolution of aneurysm. However, the causes of aneurysms and the hemodynamics conditions that promote the growth of these structures are still under debate. The present work presents numerical simulation on three aneurysms: 2 aortic and 1 cerebral. The results shows that the blood rheology is not relevant for aortic aneurysms, however, for cerebral aneurysm could play a relevant role in the hemodynamics. The turbulence models evaluated show equivalent results in both cases. Lastly, a simulation considering the fluid-structure interaction (FSI) shows that this phenomenon is the dominant factor for aneurysms simulation.

The development of computational acoustics allows simulation of sound generation and propagation in complex environment. In particular, meshfree methods are widely used to solve acoustics problems through arbitrarily distributed field points and approximation smoothness flexibility. As a Lagrangian meshfree method, smoothed particle hydrodynamics (SPH) method reduce the difficulty in solving problems with deformable boundaries, complex topologies, or multiphase medium. The traditional SPH method has been applied in acoustic simulation. This study presents the corrective smoothed particle method (CSPM), which is a combination of SPH kernel estimate and Taylor series expansion. The CSPM is introduced as a Lagrangian approach to improve accuracy in solving acoustic wave equations in the time domain. Moreover, a boundary treatment technique based on the hybrid meshfree and finite difference time domain (FDTD) method is proposed to represent different acoustic boundaries with particles. To model sound propagation in pipes with different boundaries, soft, rigid, and absorbing boundary conditions are built with this technique. Numerical results show that the CSPM algorithm is consistent and demonstrates convergence with exact solutions. Main computational parameters are discussed, and different boundary conditions are validated to be effective for benchmark problems in computational acoustics.

Memory and emotion are highly vulnerable to psychiatric disorders like post-traumatic stress disorder (PTSD), which has been linked to serotonin (5-HT) metabolism disruptions. In fact, over 90% of the 5-HT precursor tryptophan (Trp) is metabolized via the Trp-kynurenine (KYN) meta-bolic pathway, producing a variety of bioactive molecules. The aadat (kat2) gene encodes mito-chondrial kynurenine aminotransferase (KAT) isotype 2, responsible for kynurenic acid (KYNA) production. Little is known about its role in behavior. In CRISPR/Cas9-induced aadat knockout (kat2−/−) mice, we examined the effects on emotion, memory, motor function, Trp and its metabolite levels, enzyme activities in the plasma and the urine of 8-week-old males compared to wild-type mice. Transgenic mice showed more depressive-like behaviors in the forced swim test, but not in the tail suspension, anxiety, or memory tests. They also had fewer center field and corner entries, shorter walking distances, and fewer jumping counts in the open field test. Plasma metabolite levels are generally consistent with those of urine: KYN, antioxidant KYNs, 5-hydroxyindolacetic acid, and indole-3-acetic acid levels are lower; enzyme activities in KATs, kynureninase, and monoamine oxidase/aldehyde dehydrogenase are lower, but kynurenine 3-monooxygenase is higher; and ox-idative stress and excitotoxicity indices are higher. Transgenic mice show depression-like behavior in a learned helplessness model, emotional indifference, and motor deficits, coupled with a decrease in KYNA, a shift of Trp metabolism toward the KYN-3-HK pathway, and a partial decrease in the gut microbial Trp-indole pathway metabolite. This is the first evidence that deleting the aadat gene causes depression-like behaviors that are unique to despair experience, which appears to be linked to excitatory neurotoxic and oxidative stresses. This may lead to the development of a double-hit preclinical model in experience-based depression, better understanding of these complex condi-tions, and more effective therapeutic strategies by elucidating the relationship between Trp me-tabolism and PTSD pathogenesis.

A comprehensive modeling framework for the thermoforming of polymer matrix woven laminate composite was developed. Two numerical indicators, the slip path length and traction magnitude, have been identified to be positively correlated to matrix smearing and wrinkling defects. The material model has been calibrated with picture-frame experimental results, and the prediction accuracy for intra-ply shear and thickness distribution were examined with measurements on the physically formed parts. Finally, a parametric study was conducted to determine the relationship between various process parameters and the quality of the formed part. For the trapezoidal part, orienting the laminate at 45-degrees to the mold axis reduces the likelihood of matrix smear and wrinkling defects. Although this laminate orientation yielded a greater spatial variation of part thickness, the thickness deviation is lower than that for the 0-degree orientation case. Higher forming rates were found to result in more defects due to increased slip path lengths and traction magnitudes. Optimal forming speeds should balance rapid shaping within the operating temperature window while avoiding tear. It was discovered that shallower molds benefit from faster ramp rates, while deeper molds require slower rates to manage extensive shearing, stretching, and bending. Faster forming rates lead to smaller thickness increases at high intra-ply shear regions, indicating a shift from intra-ply shear to out-of-plane bending due to the visco-plastic effect of the molten laminate, and can negatively impact part quality. Lastly, it was shown that a well-conceived strategy using darts could improve the part quality by reducing the magnitude of the defect indicators.

In this paper, spatial pulse position modulation (SPPM) is used as a case study to investigate the performance of the optical spatial modulation (SM) technique in outdoor atmospheric turbulence (AT). A closed-form expression for the upper bound on the asymptotic symbol error rate (SER) of SPPM in AT is derived and validated by closely-matching simulation results. The error performance is evaluated in weak to strong AT conditions. As the AT strength increases from the weak to strong, the channel fading coefficients become more dispersed and differentiable. Thus, a better error performance is observed under moderate-to-strong AT compared to weak AT. The performance in weak AT can be improved by applying unequal power allocation to make FSO links more distinguishable at the receiver. Receive diversity is considered to mitigate irradiance fluctuation and improve the robustness of the system to turbulence-induced channel fading. The diversity order is computed as half of the number of detectors. Performance comparisons, in terms of energy and spectral efficiencies, are drawn between the SPPM scheme and conventional MIMO schemes such as repetition coding and spatial multiplexing.

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

This study investigates the diversity and evolution of research topics within the dental sciences from 1994 to 2023 using topic modeling and Shannon's entropy as a measure of research diversity. We analyzed a dataset of 412036 scientific articles across six dental disciplines: Orthodontics, Pros-thodontics, Periodontics, Implant Dentistry, Oral Surgery, and Restorative Dentistry. This research relies on BERTopic to identify distinct topics within each field. The study revealed significant shifts in research focus over time, with some disciplines exhibiting robust growth in article numbers such as Periodontics and Prosthodontics. The application of Shannon's entropy revealed an increasing diversification of research efforts in disciplines such as Restorative Dentistry, while others, like Prosthodontics, in spite of their size and their high number of research topics, maintain a more specialized research focus. Taken together, our findings describe the dynamic nature of dental re-search and highlight the balance shifts in research focus across several key areas of Dentistry.

Chemical vapor deposition (CVD) is a vital process for depositing thin films of various materials with precise control over thickness, composition, and properties. Understanding the heat and mass transfer mechanisms during CVD is essential for optimizing process parameters and ensuring high-quality film deposition. This review provides an overview of recent advancements in the heat and mass transfer modeling for chemical vapor deposition processes. It explores innovative modeling techniques, recent research findings, emerging applications, and challenges in the field. Additionally, it discusses future directions and potential areas for further advancement in CVD modeling.

Electrical contacts are important circuit components with diverse industrial applications, and their failure can lead to multiple unwanted effects. Hence, the behavior of electrical contacts is a widely studied topic in scientific literature based on various approaches, tools, and techniques. The present study proposes a numerical modeling and simulation approach based on the Holm contact theory to study the dependence between the electric potential and the temperature within an electrical contact. Structured in 5 sections, the research was conducted using COMSOL Multiphysics software and its solid-state mechanics, electric current, and heat transfer modules in order to highlight contact behavior from mechanical, electrical and thermal points of view: the von Mises stress, contact force, the electric field amplitude, the variation of the electrical potential along the current path, the temperature gradient, and dependence of temperature along the contact elements edges were obtained by simulation and graphically represented. The results are in line with the expectations and with past research that was studied in the literature review.

Advanced Finite Element (FE) modeling and simulations were performed on vehicular crashes into a Three-bar Metal Bridge Rail (TMBR). The FE models of a sedan, a pickup truck, and a TMBR section were adopted in the crash simulations subject to Manual for Assessing Safety Hardware (MASH) Test Level 2 (TL-2) and Test Level 3 (TL-3) requirements. The test vehicle models were first validated using full-scale physical crash tests conducted on a two-bar metal bridge using a sedan and a pickup truck with similar overall physical properties and sizes to their respective vehicles used in the simulations. The validated vehicular models were then used to evaluate the crash performance of the TMBR using MASH Evaluation Criteria for structural adequacy, occupant risk, and post-impact trajectory. The TMBR met all MASH TL-2 requirements but failed to meet the MASH TL-3 Criteria H and N requirements when impacted by the sedan. The TMBR was also evaluated under in-service conditions (behind a 1.52-m wide sidewalk) and impacted by the sedan under MASH TL-3 conditions. The simulation results showed that the TMBR behind a sidewalk met all safety requirements except for the occupant impact velocity in the longitudinal direction, which exceeded the MASH limit by 3.93%.

The devastating effects of COVID-19 permeates virtually all aspects of life across geographic boundaries. As the lockdown is eased, and reinstated, across many parts of the world, attention is now shifting towards how to navigate the ‘now normal’ rather than the ‘next normal,’ of doing business with a view to achieving sustainable development. This study highlights some of the challenges and opportunities for micro, small, and medium enterprises (MSMEs) in times of crisis such as COVID-19. Conceptual by orientation, the study provides a broad overview of trends in crises times, drawing upon a range of qualitative accounts. The overarching message is the current direction of travel for MSMEs in sustaining their bottom-line, not after the crisis, but at this particular moment in time. The study highlights some implications for ‘pivoting,’ in order to cushion the impact of the pandemic on efforts to capacitate MSMEs in leveraging value co-creation with the consumers. The implications of the here and now are discussed.

Our recent analysis of empirical limit order flow data in financial markets reveals a power-law distribution in limit order cancellation times. These times are modeled using a discrete probability mass function derived from the Tsallis q-exponential distribution, closely aligned with the second form of the Pareto distribution. We elucidate this distinctive power-law statistical property through the lens of agent heterogeneity in trading activity and asset possession. Our study introduces a novel modeling approach that combines fractional Lévy stable motion for limit order inflow with this power-law distribution for cancellation times, significantly enhancing the prediction of order imbalances. This model not only addresses gaps in current financial market modeling but also extends to broader contexts such as opinion dynamics in social systems, capturing the finite lifespan of opinions. Characterized by stationary increments and a departure from self-similarity, our model provides a unique framework for exploring long-range dependencies in time series. This work paves the way for more precise financial market analyses and offers new insights into the dynamic nature of opinion formation in social systems.

The paper presents two procedures for creating 3D discrete models of apple using the finite element method (FEM). The study focused on a new Polish apple variety, Chopin at development, ripening, and senescence maturity stages. The analysis of the results allowed for the determination that, depending on the desired outcomes, the parenchymal tissue can be considered as a material with either elastic or elastoplastic properties. Model validation was performed using displacement-force relationships and changes in contact area as a function of loading force obtained from compression tests. Elastoplastic models reflect empirical studies much better. The fit of the elastic models, based on force vs. displacement curves, ranged from 79% to 83%, while the fit of the elastoplastic models to empirical data ranged from 91% to 96%. Elastic models, on the other hand, are well-suited to the modified force vs. displacement curves, which reflect the elastic behavior of apples under compression test. Contour plots of pressures for elastoplastic models align much better with the test results than those for elastic models. 4. Similarly, in the case of contact area values, the elastoplastic models outperformed the elastic models, achieving a fit between 92% and 96%, while the elastic models reached only 82% to 83% compliance.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.

Tidal stream energy is a low carbon energy source. Tidal stream turbines operate in a turbulent environment, and the effect of the structure between the turbine and seabed on this environment is not fully understood. An experimental study using 1:72 scale models based on a commercial turbine design was carried out to study the support structure influence on turbulence intensity around turbine blades. The study was conducted using the wave-current tank at LABIMA, University of Florence. A realistic flow environment (ambient turbulent intensity = 11%) was established. Turbulence intensity was measured upstream and downstream of a turbine mounted on two different support structures (one resembling a commercial design, the other the same with an additional vertical element), in order to quantify any variation in turbulence and performance between the support structures. Turbine drive power was used to calculate power generation. Acoustic Doppler Velocimetry was used to record and calculate upstream and downstream turbulence intensity. In otherwise identical conditions, performance variation of only 4% was observed between two support structures. Turbulent intensity at 1, 3 and 5 blade diameters, both upstream and downstream, showed variation up to 21% between the two cases. The additional turbulent structures generated by the additional element of the second support structure appears to cause this effect, and the upstream propagation of turbulent intensity is believed to be permitted by surface waves. This result is significant for the prediction of turbine array performance.

This article discusses the application of thermal quality control methods for plant tissues. The purpose of the work is to determine the optimal parameters of thermal impact on a spherical-shaped plant control object, ensuring the detection of surface and subsurface defects. The authors of the work proposed mathematical models of the temperature field for a spherical body with defects and a flat sample when exposed to the thermal influence of a pulsed source. As a result of the use of mathematical models, the thermophysical characteristics of plant tissues of varying degrees of disease damage were obtained, which made it possible to simulate the temperature field of the control object and obtain an image of classified tissues. The developed recommendations made it possible to select the optimal parameters of the thermal effect on the test object.

Existing research indicates that mineralization of Carlin-type gold deposit is related to geological structures, but current studies mostly focus on the qualitative association, and lack quantitative analysis of the relationship between mineralization and structural features, which limits the potential for predictive mineral exploration. In this study, the Nibao Carlin-type gold deposit was selected as the research area to conduct three-dimensional geological modeling, spatial analysis, and three-dimensional prospectivity modeling. Spatial analysis revealed that the majority of gold ore bodies are situated near the main fault, with gold mineralization primarily occurring within a spatial range of approximately -80 meters to 20 meters from the main fault plane. This spatial distribution predominantly aligns in a SW-NE direction. Spatial characteristic extraction of fault slope indicators suggests that the slope angles are conducive to the migration and accumulation of ore-forming hydrothermal fluids, with ore body metal content rapidly increasing within an angle range of approximately 20° to 60°. The shape analysis of the mainfault indicates that the principal spaces of mineralization enrichment are within -10m to 20m of the fault plane undulations, where gold resources are concentrated in a relatively flat area. However, the degree of mineralization is more pronounced in the protruding sections than in the depressed areas. The areas with significant dip changes in faults display higher variations in orebody attitudes, with mineralization noticeably weaker in areas where the fault steepness changes markedly. Ore-bearing units exhibit significantly higher grades within the -17° to 3° interval of fault steepness transition. This interval also sees a rapid accumulation of gold resources. The Nibao gold mine's mineralization is derived from deep, ore-bearing hydrothermal fluids ascending along major fractures, precipitating, and accumulating in favorable ore-hosting spaces (faults, anticline cores) and lithological combinations (sedimentary tuffs, tuffs). Three deep potential gold targets were identified, highlighting the deep western edge of the F1 fault and the deep southeast-trending lower plate as prospective areas for future exploration. This study underscores the effectiveness of 3D prospective modeling as an indispensable tool for elucidating the spatial distribution of fault-controlled Carlin-type gold deposits and their tectonic determinants.

Three-dimensional (3D) geological modeling technology offers intricate geological information services and technical support for the research of urban geological conditions and their evolutionary mechanisms. It further facilitates the analysis of environmental geological problems, encompassing their distinguishing features and genetic mechanisms. The precision of such three-dimensional models is predominantly influenced by the caliber of modeling data, the chosen modeling methodologies, and the intricacy of the modeled geological objects. This research, exemplified by the three-dimensional geological structure modeling of the Wuhan metropolitan development area, aims to explore a comprehensive three-dimensional modeling framework for urban geology, particularly in scenarios with large-scale and complex geological conditions. This study holds significant technical value in enhancing the application of 3D geological modeling, as well as practical importance for urban geological investigations and research.

Developmental hazard evaluation is an important part of assessing chemical risks during pregnancy. Toxicological outcomes from prenatal testing in pregnant animals result from complex chemical-biological interactions, and while New Approach Methods (NAMs) based on in vitro bioactivity profiles of human cells offer promising alternatives to animal testing, most of these assays lack cellular positional information, physical constraints, and regional organization of the intact embryo. Here, we engineered a fully computable model of the embryonic disc in the compucell3d.org modeling environment to simulate epithelial-mesenchymal transition of epiblast cells and self-organization of mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Cell fate in the model is determined by an autonomous homeobox (HOX) clock driven by morphogenetic signals (e.g., FGF, WNT, ATRA, CDX). Executing the model renders a quantitative cell-level computation of mesodermal subpopulations and consequences of perturbation based on known embryogeny. For example, synthetic perturbation of the control network rendered altered phenotypes (cybermorphs) mirroring experimental mouse embryology, with 50% reductions in FGF4, FGF8 and BMP4 signaling resulting in 86%, 98% and 59% reductions, respectively in the posterior mesodermal population, while ATRA exposure also resulted in a 78% decrease in this population. This model enables integration of in vitro chemical bioactivity data for specific molecular targets with known embryology to test mechanistic veracity and quantitative prediction of altered development.

The optimal structural design is imperative to minimize material consumption and reduce the environmental impact of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as Genetic Algorithm (GA). However, the integration of AI-based optimization together with visual programming (VP) in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps including: (i) generation of parametric trusses in Dynamo VP; (ii) performing the finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. The feasibility of the proposed workflow was tested on benchmark problems and compared with open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction.

Abstract: The SARS-CoV-2 pandemic has reemphasized the urgent need for broad-spectrum antiviral therapies. We developed a computational workflow using scRNA-Seq data to assess cellular metabolism during viral infection. With this workflow we predicted the capacity of cells to sustain SARS-CoV-2 virion production in patients and found a tissue-wide induction of metabolic pathways that support viral replication. Expanding our analysis to influenza A and dengue viruses, we identified metabolic targets and inhibitors for potential broad-45 spectrum antiviral treatment. These targets were highly enriched for known interaction partners of all analyzed viruses. Indeed, phenformin, an NADH:ubiquinone oxidoreductase inhibitor, suppressed SARS-CoV-2 and dengue virus replication. Atpenin A5, blocking succinate dehydrogenase, inhibited SARS-CoV-2, dengue virus, respiratory syncytial virus, and influenza A with high selectivity indices. In vivo, phenformin showed antiviral activity against SARS-CoV-2 in a Syrian hamster model. Our work establishes host metabolism as druggable for broad-spectrum antiviral strategies, providing invaluable tools for pandemic preparedness.

In order to solve the problem of large eddy current loss and high temperature rise caused by large amount of permanent magnet, a new type of combined magnetic pole permanent magnet motor is proposed in this paper. The sinusoidal distribution subdomain model of non-uniform air gap rotor is established by using Laplace equation, and the analytical expression of eddy current loss of rotor in uniform air-gap and non-uniform air-gap is derived. The effect of rotor eccentricity on eddy current loss is obtained. According to the characteristics of distributed winding of non-uniform air gap combined pole permanent magnet motor, equivalent treatment is performed to obtain the equivalent thermal conductivity, so as to establish equivalent thermal network model of motor, calculate the temperature value of each component of the motor, and verify the correctness of the thermal network model through the method of magnetothermal bidirectional coupling. Finally, an experimental platform is set up to carry out temperature rise experiments on the two prototypes respectively. Experimental results show that the non-uniform air-gap rotor structure can effectively reduce the rotor eddy current loss and motor temperature rise, and also verify the accuracy of the analytical model calculation results.

In this review we explore the recent progress in catalytic materials for ammonia synthesis that are based on metal nitrides and other catalytic surfaces. It comprises a detailed overlook of various techniques used in ammonia synthesis research and the state-of-the-art modeling techniques employed to investigate new reaction mechanisms and more efficient processes for sustainable ammonia synthesis production. The review is discussed in the context of reaction mechanisms developed and recent progress that has been made with respect to thermal, electrochemical and photocatalytic ammonia synthesis.

System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV) , serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

In this paper, for the Reynolds-averaged Navier-Stokes equations, a self-closed turbulence model without any adjustable parameter is formulated and a simple model is proposed. The validation rule for self-closed turbulence model is rigorously derived from the Reynolds-averaged Navier-Stokes equation. The rule is not effected by turbulence modelling on the Reynolds stresses. As an application, two dimensional turbulent boundary layers, and plate turbulent boundary layers have been formulated.

A rigid protruding surface, agitator and vortex generator often dissipate more energy than to produce a satisfied turbulence production. In contrast, a passively-oscillating flexible protruding surface has the ability in generating greater turbulence level. In the current study, a circular finite cylinder (cantilever) was used as the geometry of the rigid and protruding surface. They were varied through the aspect ratio (AR) and materials. Also, a local Reynolds number within the subcritical flow range (102<ReD<105) was considered. The results from the rigid protruding surface (finite cylinder) is served as a validation to the published results and benchmark to the improve-ment of the turbulence generated by the flexible protruding surface. It was mentioned in the pre-vious work that the increment of turbulence production by the flexible cylinder is speculated to be oscillation, this work investigates the validity of the speculation through manipulating the struc-tural stiffness of the flexible cylinder by employing different materials. The results have further demonstrated that the flexible cylinder is capable of generating a greater turbulence through the examination of turbulence intensity, turbulence production term and Reynolds stress. All the flex-ible cylinders that oscillate show increment in turbulence production but at a different percentage. The cylinders studied in this work ranged from the least structural stiffness (EVA), moderate (al-uminium) to the highest structural stiffness (carbon steel). Through studying the normalized am-plitude responses graph of the flexible cylinder, it is identified that the oscillating motion does in-deed contribute to increment. A further investigation into the results, it is found that the factor which governs the increment is the structural velocity instead of just oscillating motion alone.

Capabilities of hovering unmanned aerial vehicles (UAVs) in low-altitude sensing of atmospheric turbulence with high spatial resolution are studied experimentally. The experiment was carried out at the Basic Experimental Observatory of the V.E. Zuev Institute of Atmospheric Optics SB RAS. UAV findings are compared with objective data on the state of the atmosphere that were measured by acoustic anemometers installed at weather towers at altitudes of 4, 10, and 27 m. Profiles of atmospheric turbulence were recorded with three UAVs hovering at the same heights at a distance of 5 m from the anemometers. The behavior of the longitudinal and lateral wind velocity components is studied in the frequency band 0-10 Hz before and after one-minute smoothing, which reveals long turbulent wind gusts. The discrepancy between the UAV and anemometer data is analyzed. It is found that after smoothing, the discrepancy does not exceed 0.5 m/s in 95% cases. This value meets the requirements of the World Meteorological Organization for some applications in wind velocity measurements. The spectral and correlation analysis of the UAV and anemometer measurements is carried out. The profiles of the longitudinal and lateral scales of turbulence are examined based on the UAV data and are found to be in agreement with the anemometer data to a good accuracy.

Based on the theory of turbulence, equations are derived for estimations of turbulent fluctuations of the longitudinal and transverse components of the wind velocity during ideal hovering of a quadcopter in a turbulent atmosphere. We present the results of experiments which were carried out on the territory of the Geophysical Observatory of Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch, Russian Academy of Sciences, located in Tomsk Akademgorodok on the territory with complex orography, in a parkland zone with buildings of research institutes and motorways. Time series of turbulent fluctuations of the longitudinal and transverse components of wind velocity fluctuations were received with the use of an automated weather station, and time series of estimates of these components, from data of a DJI Phantom 4 Pro quadcopter during hovering. According to the automated weather station data, anisotropy was observed in one experiment during measurements in the atmosphere, but this phenomenon was not observed in the other experiment: the fluctuation spectra of all components of wind speed fluctuations coincide. The spectra of fluctuations of the longitudinal and transverse wind velocity components based on the automated weather station data and UAV telemetry are presented. The fluctuation spectra of these components for the automated weather station data and quadcopter generally coincide. The behavior of the spectra coincides with the spectrum which corresponds to Kolmogorov–Obukhov “–5/3” law within the inertial range. The turbulent spectra of the wind velocity fluctuations obtained with the use of the automatic weather station and with the unmanned aerial vehicle differ in the high-frequency spectral region.

The ever-growing concerns about global warming and the rapid depletion of fossil fuels have triggered a rising interest in research for cleaner, more efficient and cost-effective energy generation. Organic Rankine cycle systems have immense potential to become a strong alternative to conventional methods of energy generation. However, such systems’ efficiency is limited by the performance of the incorporated gas expanders or prime movers. Conventional gas expanders often utilize ports or cam-operated valves. Ported expanders offer limited efficiency and controllability, and produce high emissions causing a large amount of heated and compressed gas to be wasted. Cam-operated valves, in contrast, increase expansion performance compared to ported expanders, however, they have no variability and adaptability to changes in system parameters such as gas pressure, temperature, dryness fraction, and load variation to name a few. On a positive note, this issue can be addressed by adopting a variable timing and fast-operating, control valve with an accurate and adaptive control mechanism at the expander inlet. A properly designed and controlled valve can greatly improve the system performance of gas expanders and pave the way for an efficient low-cost alternative energy generation. This manuscript provides a comparative review of recent progress on the design, modeling, optimization, and control aspects of valves for gas expanders. A clear pathway on the scope of further development is also drawn based on the present state of the art.

The liver diseases are posing serious threat to human health associated with abusive use of allopathy medicines, especially in developing economies like Pakistan. The strengthening of detoxification system using natural products might be a suitable option to minimize the liver problems. In this current research, Zingiber officinale and Azadirachta indica were evaluated for their hepatoprotective role. For the purpose, 20 Sprague Dawley rats were equally divided into four groups i.e., negative control, paracetamol positive control, 2.5% ginger and 2% neem powder, respectively. During 42 days study, the levels of bilirubin and liver enzymes significantly elevated due to liver damage. Although, the values dropped (20-25%) in treatment group. Serum glucose and serum lipid profile increased in positive control group, but reduced (5-10%) in both ginger and neem groups. The serum protein profile declined in liver damage group, however, improved (~5%) in treatment groups. The hematological parameters slightly declined in liver damage group, but increased in ginger and neem groups. Moreover, the white blood cells differential count and renal parameters showed abnormal values in liver damage group, but improved after treatment. This study is promising and highlighted the hepato-protective role of neem and ginger that may open several avenues of research.

High-frequency circuit performance is significantly impacted by impedance variations, particularly within the low-resistance regime. Traditional Ohm’s Law based modeling approaches often fail to accurately predict circuit behavior in these conditions, leading to design inaccuracies and potential system failures. The Standard Ohm’s Law based model’s prediction of infinite current as resistance approaches zero is physically unrealistic and hinders its application in practical scenarios. Despite the recognition of these limitations, existing models have not comprehensively addressed the complex impedance behavior observed in high-frequency circuits. To overcome these challenges, this paper introduces a modified version of the Ohm’s Law incorporating an exponential correction term. The Modified Ohm’s Law’s accuracy was evaluated through simulated experiments across a wide frequency range (1kHz to 1GHz) using various electronic components. The findings demonstrate the superior performance of the modified model in predicting currents under low-resistance and high-current conditions compared to the Standard Ohm’s Law model. By providing finite and accurate current values, the proposed model effectively mitigates the unrealistic infinite current predictions of the standard approach. The enhanced predictive capabilities of the Modified Ohm’s Law hold significant implications for high-frequency circuit design and analysis. Its application can lead to improved performance and reliability in power electronics, telecommunications, and other high-frequency systems. By incorporating non-linear impedance behavior, the model offers a more accurate representation of real-world circuit conditions. Future research should focus on refining the exponential term’s parameters to optimize the model's accuracy across a broader range of applications. Additionally, real-time implementation and hardware validation are essential to assess the model's practical utility in complex circuit environments.

Real-time simulation of toxic gas dispersion is critical for emergency management in high-sulphur gas fields. The CALPUFF (California Puff model) gas dispersion model, a Lagrangian Gaussian Puff model, is often used in mountainous environments due to its ability to handle complex terrain and weather conditions. Verifying the accuracy of toxic gas dispersion simulations under mountainous conditions is vital for emergency response and rescue. In this article, CALPUFF and Computational Fluid Dynamics (CFD) gas dispersion modeling are compared, studying emissions from a hypothetical pipeline breakout accident in a mountainous area, focusing on range of Semi-Lethal Concentration (LC$_{50}$), Immediate Danger to Life and Health Concentration(IDLH). Thirteen groups of simulation conditions are set up for the experiment, including static wind and winds from the east(E), south(S), west(W), and north(N) at speeds of 1, 2, and 3$m/s$. Comparative experiments between CALPUFF and CFD models show consistent results, confirming the feasibility of CALPUFF for near-field moutainous applications. The overall dispersion range deviation between two methods under calm or light wind of N, E and W is about 300$m$. However,the simulation results of the CALPUFF model and the CFD model show significant differences in S wind. In CALPUFF simulation that the toxic gases are channeled by the valleys, while in the CFD model the toxic gases climb over the mountain top and continue to spread and extend towards the northern valley. The evaluation of CALPUFF’s suitability for applications in near-field mountainous environments indicates its potential use for high-sulfur gas fields and gas dispersion simulations in emergency scenarios.

The International Renewable Energy Agency (IRENA) was established in 2009 and in 2024, its membership increased to 168 members plus the European Union countries. The purpose of IRENA is to promote the adoption of renewable energy across all industries in the world. Despite the utilization of renewable energy in sectors like power generation and construction, its application in other industries remains limited. Therefore, a literature review study was conducted to investigate the cost and other spatial constraints associated with renewable energy resources, including modeling and optimization techniques that could offer viable solutions to the future challenges faced by the renewable energy production systems. This paper has summarized the result of this study with a focus on the significance of modeling and optimization techniques in energy conservation to highlight the untapped potential for leveraging renewable energy resources in industrial applications. This paper also examined a few case studies from various regions of the world, demonstrating the promising opportunities for research in the modeling and optimization of renewable energy management systems.

Modern building automation systems implement plenty of advanced control and monitoring functions considering various parameters like users’ activity, lighting, temperature changes etc. Moreover, new solutions based on Internet of Things and cloud services are also being developed for smart buildings to ensure comfort of use, user safety, energy efficiency improvements and integration with smart grids and smart city platforms. Such a wide spectrum of technologies and functions requires a new approach in building automation systems design to provide effective way of their implementation and flexibility during operation. At the same time, in the building design and operation industries, tools based on building information modeling and digital twins are being developed. In this paper, the authors discuss development directions and application areas of these solutions, identifying new trends and possibilities of their use in smart homes and buildings. In particular, the focus is on procedures for selecting automation functions, effective integration, and interoperability of building management systems with Internet of Things considering organization of prediction mechanisms and dynamic functional changes in buildings and smart networks. Chosen solutions and functions should consider the requirements from EN ISO 52120 standard and the guidelines defined for the Smart Readiness Indicator.

Induction motors are the most numerous and significant dynamic loads in power systems. In transient voltage stability analysis, dynamic equivalent models are commonly used to simplify the representation of a group of induction motors. This paper presents an method for the grouping and aggregation of induction motors at a common bus. Firstly, grouping rules were provided for clustering induction motors into several subgroups based on the mechanical principles of rotor force and motion, and Aggregation Rules were provided for aggregating a motor subgroup into a single-unit model based on the relationship between voltage drop and power transmission in distribution networks. Secondly, guided by the grouping rules, high-speed remaining electromagnetic torque and low-speed remaining electromagnetic torque were defined as new clustering indicators, and an adaptive K-means clustering method using silhouette coefficient verification was provided to obtain the optimal motor subgroups. Thirdly, guided by the Aggregation Rules, a dynamic equivalent method was further provided to obtain the equivalent single-unit model from a motor subgroup. Lastly, a transient voltage stability simulation in a typical distribution network was presented to illustrate that the proposed clustering and equivalent methods are more reasonable, accurate, and effective than traditional methods, as the obtained model has better dynamic characteristics and can more accurately reproduce the process of voltage collapse.

This research paper aims to evaluate and model the performance of rice husk gasifier cook stoves for household energy use, a byproduct of rice milling. The study aims to address environmental issues and promote the use of rice husk as a renewable energy source and pest repellent in stoves. The study compared insulated and non-insulated gasifier stoves using rice husk gasification. The study compared the start-up time of insulated and non-insulated gasifier stoves, where the insulated stove showed a lower start-up time, but there was no significant difference at a 5% probability level. The temperature change also was not significant, as heat transfer and temperature change started when the husk was ignited. The burner stoves had different size and volume. The maximum operated or flame temperature was 1,190.30oC at room or minimum temperature of 27.33 oC, whereas the average temperature was 758.916oC for the non-insulated type of gasifier stove. The insulated gasifier stove also observed maximum and average temperatures of 518.30 oC and 289.014oC respectively at the same room temperature. The operating time of stoves directly influences the fuel consumption rate, specific gasification rate, and combustion zone rate of stoves. The fuel consumption rate has a significant effect on the type of gasifier stove, with the maximum rates being 3.820 and 2.099 kg/hr. The time to consume rice husks to gasify them depends on the density of the rice husk, reactor volume, and fuel consumption rate. The average specific gasification rate for insulated and non-insulated stoves is 106.45 and 120.63 kg/m2h, respectively. The fuel or rice husk holding capacity of each type of stove is significant at a 5% level, with the amount of rice husk and biochar produced being 1.18kg and 0.27kg for insulated stoves, and 2.511kg and 0.688kg for non-insulated stoves, respectively. The performance of gasifier stoves varies based on the bio char conversion rate, with non-insulated stoves producing a higher bio char mass per rice husk. Multiple regression analysis was used to model the relationship between time elapse with temperature and heat energy. The Squirrel-2020 data logger was used to measure the temperature produced by burning rice husks in the reactor of the stove as well as related generated and losses of heat. A relationship between the heat energy produced and the operating time of gasifier stoves was conducted to estimate the model. The cubic polynomial model was found to be the best predictive model fit for all variables of this study.

In 2018, Iran witnessed approximately 21,000 fatalities resulting from road accidents, ranking it as the fifth leading cause of death across all age groups. These incidents carry substantial economic and social burden for the nation, claiming more than 5% of its GDP. Human behavior emerges as a significant contributing factor to high-risk driving offenses. It has been proposed that by influencing general deterrence, a rigorous defense can be established against such violations. Various theories posit that by reinforcing or diminishing influential factors, general deterrence perception can be molded, presenting a potential avenue for an effective deterrent against traffic infractions. This study examines deterrence perceptions prevailing among the public in Iran regarding the enforcement of traffic laws. Employing Structural Equation Modeling (SEM), we delve into the intricate relationships between variables, allowing for a comprehensive exploration of the factors influencing general deterrence. The study draws on the data derived from a survey comprising 548 questionnaires for modeling purposes. An innovative concept, private sector enforcement, is introduced and incorporated into the questioning and modeling process. The findings reveal that socioeconomic status (p-value&lt;0.01), police enforcement (p-value&lt;0.05), private sector enforcement (p-value&lt;0.05), specific deterrence (p-value&lt;0.01), and the use of technology (p-value&lt;0.01) have direct and indirect impacts on the general deterrence perception of drivers.

The construction time of concrete structures in hydraulic tunnels is long, the construction environment is complex, and there are many influencing factors. The requirements for construction quality are high, not only to meet the strength requirements, but also to meet the design requirements of erosion resistance, crack resistance, and seepage resistance according to its specific operating environment. Therefore, evaluating the construction quality of concrete structures in hydraulic tunnels is of great significance. Considering the randomness and fuzziness of factors affecting the construction quality of concrete structures in hydraulic tunnels, this paper proposes a comprehensive evaluation model based on Combined Weighting (CWM) and Uncertainty Measurement Theory (UM). The IAHP method and CRITIC method are used to determine the subjective and objective weights of evaluation indicators, combined weighting is based on the principle of minimum entropy, and the UM method is used to evaluate the construction quality level. Finally, taking a hydraulic tunnel as an example, its construction quality grade is calculated to be III according to the evaluation model proposed in this paper, which matches with the engineering reality, and a comparative study is made with the mixture element topology theory at the same time. It is verified that the evaluation model can scientifically and reasonably evaluate the construction quality level of concrete structures in hydraulic tunnels.

Gravity forward modeling as a basic tool has been wildly used to topography correction and 3D density inversion. The source region is usually discretized into tesseroid (i.e., spherical prism) to consider the influence of the curvature of planets in global or large-scale problems. Traditional gravity forward modeling methods in spherical coordinates, including the Taylor expansion and Gaussian-Legendre quadrature, are all based on spatial domain, which are mostly low computational efficiency. This study proposes a high-efficient forward modeling method of gravitational fields in spherical harmonic domain, in which the gravity anomalies and gradient tensors can be expressed as spherical harmonic synthesis form of spherical harmonic coefficients of 3D density distribution. A homogeneous spherical shell model has been used to test its effectiveness compared with traditional spatial domain methods. It demonstrates that the computational efficiency of the proposed spherical harmonic domain method has improved by four orders of magnitude and with a similar level of computational accuracy compared with the optimized 3D GLQ method. Finally, the proposed forward method is applied to topography correction of the Moon. The results show that the gravity response of the topography by our method is close to that of the optimized 3D GLQ method, and is also consistent with previous results.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

Optical communications are described and analyzed by shaped beams; we challenge the ‎effects of parameters that impact the profile of a Flat Top Gaussian (FTG) beam. When ‎the laser beam propagates throughout the atmosphere, it can be influenced by different ‎optical phenomena including scattering, absorption, and turbulence due to changes in the ‎scintillation index and the forms of intensity that are displayed in the source and receiver ‎planes. In this project, the FTG laser beam that propagates through a weak turbulent ‎region is numerically investigated using open-source software. This simulation will be ‎performed according to a mathematical model based on the split-step beam propagation ‎method. Intensity distributions at the source plane and the received average intensity in ‎atmospheric turbulence are calculated, and additional contour is in the transducer plane. ‎The scintillation index, structure constant, source size, and other parameters, are applied ‎in the Rytov method to quantify the weak turbulent model. Moreover, these parameters ‎are analyzed in near-field propagation. Also, the effects of the beam’s scintillation and ‎beam wander are determined. All results simulated are discussed and compared with the ‎TEM00 Gaussian beam. Finally, these results are compared to measurements in the ‎experimental part of the work.

We present a mixing length based algebraic turbulence model calibrated to pipe flow; the main purpose of the model is to capture the increasing turbulence production-to-dissipation ratio observed in connection with the high Reynolds number transition region. The model includes the mixing length description by Gersten and Herwig which takes the observed variation of the von Kármán number with Reynolds number into account. Pipe wall roughness effects are included in the model. Results are presented for area-averaged (integral) quantities which can be used both as a self-contained model and as initial inlet boundary conditions for computational fluid dynamics simulations.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

The year 2022 was characterized by several major events that impacted the business world in Indonesia and even globally after the COVID-19 pandemic devastated all business sectors in Indonesia and the world. The current business environment is experiencing accelerating turbulence characterized by increasing intensity of business competition, rapid changes in the market, and industrial connections climate. The industrial connection climate of an institution can be measured by the pattern of relationships that occur between workers and management. Industrial connections are fundamental to the sustainability of an organization and are understood as an important factor in influencing institutional performance. This research aims to look at the impact of the existence of industrial connections instruments, turbulence in the business environment on the industrial connections climate. Besides, how the industrial connections climate relates to firm performance. The research design is an inferential quantitative, using sampling and snowball sampling methods with total sample are 406. The data collected were analyzed using Structural Equation Model using LISREL version 8.70. This research used a survey to build an SEM model that tested the effect of organizational turbulence and industrial connections instruments on organizational climate directly, and tested mediation on organizational performance. All related indicators have outer loading more than 0.5 and T-value more than 1.96. Therefore, the conclusion is that all measurements are valid. Composite Reliability (CR) and VE for all indicators are >0.7 and >0.5 respectively. This research shows that industrial assosiation climate has a positive effect on business turbulence and industrial connections instruments. However, industrial connections instruments show a greater impact on the assosiation climate. This is because industrial connections instruments are the media used in the implementation of industrial connections in organizations. This research also confirms that industrial assosiation climate is positively related to organizational performance. The result of the indirect influence (IE) of 0.20 with t value is 8.47 means that the climate of Industrial connections is able to mediate the influence of Industrial connections Facilities on Organizational Performance.

To gain insight into the differences between onshore and offshore atmospheric turbulence, 2 pressure fluctuations were measured for offshore wind under different environmental conditions. 3 A durable piezo-electric sensor was used to sample turbulent pressure data at 50 kHz. Offshore 4 measurements were performed at 100 m height on Germany’s FINO3 offshore platform in the 5 German Bight together with additional meteorological data provided by Deutscher Wetterdienst 6 (DWD). The statistical evaluation revealed that the stability state in the atmospheric boundary has a 7 large impact on turbulent fluctuations. Therefore, we used higher statistical properties (described 8 by so-called shape factors) to the stability state. Data was classified to be either within the unstable, 9 neutral or stable stratification. We found that in case of stable stratification, the shape factor is 10 mostly close to zero, indicating that a thermally stable environment produces closer-to Gaussian 11 distributions. Non-Gaussian distributions were found in unstable and neutral boundary layer states 12 and an occurrence probability was estimated. Possible impact on laminar-turbulent transition on the 13 blade is discussed with application of so-called laminar aerofoils on wind turbine blades. Use of a 14 cut-off frequency to separate load and aerodynamic turbulence is proposed.

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and re-analysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, to capture the nuanced dynamics of Cyprus's atmospheric conditions. With a temporal resolution of 15 minutes and a spatial of 0.05°x0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models' accuracy but also highlights their proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), of -2 to -4% per decade have been found in Autumn, especially marked on the island’s Northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of -2 to -3% per decade that were found in Spring do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the Daylight Integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

Computational fluid dynamics (CFD) modeling has emerged as a valuable tool for investigating complex processes like microencapsulation. This paper aims to validate the ability of CFD simulations to predict particle size distribution in a polymer microencapsulation process. The CFD modeling approach employed an Eulerian multiphase framework, incorporating a discrete population balance model to track the evolution of the droplet population. A realizable k-ε turbulence model and a multiple reference frame strategy were utilized to capture the system’s flow dynamics. The results reveal that while the CFD simulations align well with experimental data at higher agitation speeds (>10000 rpm), discrepancies arise at lower speeds (<7500 rpm), indicating a challenge in accurately capturing turbulent viscous regimes. Despite these challenges, the CFD model demonstrates robust predictive capabilities for droplet formation and distribution in microencapsulation processes, validated by error margins within acceptable limits. The validated model can be used as a reliable tool to guide experimental efforts and optimize process parameters, contributing to an enhanced understanding and control of microencapsulation processes.

The alcoholic fermentation process with agitation/static, followed by the acetic fermentation submerged in banana was evaluated. Kinetics parameters of alcoholic fermentation for the maximum ethanol/glycerol metabolites in agitated process was 29 and 27 h, and in static 47 and 45 h, respectively. For acetic fermentation, the kinetics parameters were medium time of 39.9 h, acetic acid yield of 53.1% and acetic acid productivity of 0.216 g/Lh. Wines from agitated/static process presented 5.73 and 6.81% (v/v) of alcohol content, respectively. Wine obtained by the static process presented higher concentrations of volatile compounds. The vinegar showed 49.2 g/L of acetic acid and the esters concentrations were higher than in wine. The wine and vinegar minerals were consistent with amount observed in the pulp, with an increase in sulphur concentration after alcoholic fermentation and decrease after acetic fermentation. Products showed chemical and composition of sensory and nutritional interest.

The automotive market is very competitive and presents a demand for the consistent improvement of the used technologies and reduction of the product cost and dimensions with each product model iteration. Hence, it is important to have access to well-defined reference designs of high quality products, in order to evaluate the new ideas and technologies. This paper provides the readers with a numerical model of such a high quality product, i.e., the IPMSM type traction motor from the 4th generation of the Toyota Prius hybrid transaxle. In the introductory section, the brief history of the Prius model is given together with the references to the reverse engineering reports. Afterwards, the machine dimensions, material properties and winding configuration are described. Then, the model is validated with the torque measurements at constant speed. In the next chapters the simulation results are presented and the numerical source data are supplied to the reader. Finally, the design philosophy of the Toyota drive is briefly discussed in comparison with the BMWi3 drive and the results are concluded in the last section.

This study challenges the prevailing belief in the necessity of complex models for accurate forecasting by demonstrating the effectiveness of parsimonious econometric models, namely ARCH(1) and GARCH(1,1), over deep learning robust approaches, such as LSTM and 1D-CNN neural networks, in modeling historical volatility within pre-emerging stock markets, specifically the Moroccan and Bahraini stock markets. The findings suggest reevaluating the balance between model complexity and predictive accuracy. Future research directions include investigating the potential existence of threshold effects in market capitalization for optimal model performance. This research contributes to a deeper understanding of volatility dynamics and enhances forecasting models’ effectiveness in diverse market conditions.