cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26984751
title: Analysis of stability and bifurcation and design of optimal control for phytoplankton–zooplankton–fish model with additional food and fish harvesting

description: This paper investigates the dynamics of a four-dimensional plankton-fish system that contains three communities of plankton: non-toxic phytoplankton, toxic-producing phytoplankton, and zooplankton. The zooplankton consumes both non-toxic and toxic-producing phytoplankton. First, the positivity and boundedness of the solutions in the plankton-fish model are evaluated. Then, we derive the conditions for the existence of ecologically possible equilibria and their local and global asymptotic nature. Furthermore, we evaluate the criteria for the existence of Hopf-bifurcation and transcritical bifurcation. By applying Pontryagin’s maximum principle, we investigate the optimal control of fish harvesting, where fishing effort is taken as a control parameter. By using phase-space diagrams, time responses, bifurcation diagrams, and numerical analyses validate the theoretical results. The numerical results including maximum Lyapunov exponent verify chaotic dynamics of the system. We notice that a suitable choice of harvesting, phytoplankton growth rate, and additional food parameters can control the chaotic behavior of the presented model. The proposed novel mathematical model gives deeper insights to theoretical ecologists on how toxic-producing phytoplankton affects zooplankton and fish populations in aquatic systems. Furthermore, the proposed model is more appropriate for fish harvesting to maximize profit as well as species conversion in the presence of toxic phytoplankton.
DOI: 10.6084/m9.figshare.26984751.v1
title: Analysis of stability and bifurcation and design of optimal control for phytoplankton–zooplankton–fish model with additional food and fish harvesting

description: This paper investigates the dynamics of a four-dimensional plankton-fish system that contains three communities of plankton: non-toxic phytoplankton, toxic-producing phytoplankton, and zooplankton. The zooplankton consumes both non-toxic and toxic-producing phytoplankton. First, the positivity and boundedness of the solutions in the plankton-fish model are evaluated. Then, we derive the conditions for the existence of ecologically possible equilibria and their local and global asymptotic nature. Furthermore, we evaluate the criteria for the existence of Hopf-bifurcation and transcritical bifurcation. By applying Pontryagin’s maximum principle, we investigate the optimal control of fish harvesting, where fishing effort is taken as a control parameter. By using phase-space diagrams, time responses, bifurcation diagrams, and numerical analyses validate the theoretical results. The numerical results including maximum Lyapunov exponent verify chaotic dynamics of the system. We notice that a suitable choice of harvesting, phytoplankton growth rate, and additional food parameters can control the chaotic behavior of the presented model. The proposed novel mathematical model gives deeper insights to theoretical ecologists on how toxic-producing phytoplankton affects zooplankton and fish populations in aquatic systems. Furthermore, the proposed model is more appropriate for fish harvesting to maximize profit as well as species conversion in the presence of toxic phytoplankton.
DOI: 10.6084/m9.figshare.27015635
title: Load frequency control performance enhancement of an electric vehicle integrated time-delay multi-microgrid system

description: Frequency control in a microgrid (<i>μ</i>G) is problematic due to low inertia of distributed generators (DGs) and uncertainty of the renewable energy source-dependent DGs. Consequently, deploying distributed storage units (DSUs) in a <i>μ</i>G is crucial for quickly arresting frequency deviations. The electric vehicle (EV) technology, as DSU, is being preferred over conventional energy storage due to its lower cost and slower degradation rate, facilitating demand side response in a <i>μ</i>G. The adoption of the EV technology necessitates an open communication infrastructure in the <i>μ</i>G, with a pre-existing communication time delay (CTD). This article explores the impact of EV integration on load frequency control (LFC) performance of a multi-microgrid (M<i>μ</i>G) system and determines an optimal CTD value simultaneously. A cyclical parthenogenesis algorithm-optimized 2DOF-FOPID controller is implemented to obtain dynamic responses of the M<i>μ</i>G system. Simulation results reveal significant improvements in dynamic responses when integrating EVs in the M<i>μ</i>G, with a 97.33% increase in objective function value. The recommended controller also outperforms standard controllers in terms of how quickly frequency and tie-line power variations settle down to zero. Thus, the proposed controller meets the LFC requirements. Robustness of the proposed LFC scheme is tested against parametric variations in the M<i>μ</i>G system.
DOI: 10.6084/m9.figshare.27015635.v1
title: Load frequency control performance enhancement of an electric vehicle integrated time-delay multi-microgrid system

description: Frequency control in a microgrid (<i>μ</i>G) is problematic due to low inertia of distributed generators (DGs) and uncertainty of the renewable energy source-dependent DGs. Consequently, deploying distributed storage units (DSUs) in a <i>μ</i>G is crucial for quickly arresting frequency deviations. The electric vehicle (EV) technology, as DSU, is being preferred over conventional energy storage due to its lower cost and slower degradation rate, facilitating demand side response in a <i>μ</i>G. The adoption of the EV technology necessitates an open communication infrastructure in the <i>μ</i>G, with a pre-existing communication time delay (CTD). This article explores the impact of EV integration on load frequency control (LFC) performance of a multi-microgrid (M<i>μ</i>G) system and determines an optimal CTD value simultaneously. A cyclical parthenogenesis algorithm-optimized 2DOF-FOPID controller is implemented to obtain dynamic responses of the M<i>μ</i>G system. Simulation results reveal significant improvements in dynamic responses when integrating EVs in the M<i>μ</i>G, with a 97.33% increase in objective function value. The recommended controller also outperforms standard controllers in terms of how quickly frequency and tie-line power variations settle down to zero. Thus, the proposed controller meets the LFC requirements. Robustness of the proposed LFC scheme is tested against parametric variations in the M<i>μ</i>G system.
DOI: 10.6084/m9.figshare.24883912
title: Darcy-Forchheimer flow of MHD free convective CNTs Casson nanoliquid via a cosinusoidally fluctuating heated plate

description: This study explores the influence of carbon nanotubes (CNTs), spanwise cosinusoidally fluctuating thermal and mass diffusion on unsteady MHD free convective flow of Casson nanoliquid via an infinite hot vertical porous plate in a Darcy-Forchheimer porous medium. The overlapping grid multi-domain trivariate spectral collocation method is used to solve the non-dimensional equations. The impact of varying physical estimators on profiles alongside skin friction factor, rate of heat, and mass transport is contemplated. It was disclosed that the velocity and skin friction factors can be maximized via strong buoyancy forces and porous permeability but minimized through strong magnetic field and the Darcy–Forchheimer relation. The temperature and rate of heat transport can be increased by higher levels of heat generation, viscous dissipation, diffusion-thermo, and radiation absorption. Conversely, these factors can be minimized with higher thermal radiation. The introduction of activation energy and nonlinear chemically reactive species is responsible for the increase in species concentration and the rate of mass transport. The velocity and temperature are enhanced with increasing CNTs volume fraction, which leads to an increment in skin friction factor and thermal transport rate. Therefore, the suspension of CNTs in conventional fluids to control the coolant level in industrial apparatuses is absolutely practical.
DOI: 10.6084/m9.figshare.24883912.v1
title: Darcy-Forchheimer flow of MHD free convective CNTs Casson nanoliquid via a cosinusoidally fluctuating heated plate

description: This study explores the influence of carbon nanotubes (CNTs), spanwise cosinusoidally fluctuating thermal and mass diffusion on unsteady MHD free convective flow of Casson nanoliquid via an infinite hot vertical porous plate in a Darcy-Forchheimer porous medium. The overlapping grid multi-domain trivariate spectral collocation method is used to solve the non-dimensional equations. The impact of varying physical estimators on profiles alongside skin friction factor, rate of heat, and mass transport is contemplated. It was disclosed that the velocity and skin friction factors can be maximized via strong buoyancy forces and porous permeability but minimized through strong magnetic field and the Darcy–Forchheimer relation. The temperature and rate of heat transport can be increased by higher levels of heat generation, viscous dissipation, diffusion-thermo, and radiation absorption. Conversely, these factors can be minimized with higher thermal radiation. The introduction of activation energy and nonlinear chemically reactive species is responsible for the increase in species concentration and the rate of mass transport. The velocity and temperature are enhanced with increasing CNTs volume fraction, which leads to an increment in skin friction factor and thermal transport rate. Therefore, the suspension of CNTs in conventional fluids to control the coolant level in industrial apparatuses is absolutely practical.
DOI: 10.6084/m9.figshare.25242627
title: A new hybrid approach based on fuzzy logic and optimization for load frequency control

description: This paper presents a fuzzy logic and optimization-based controller design for load frequency control of a single area system with a non-reheated turbine. The controller’s unknown parameters are determined using Big Bang-Big Crunch (BB-BC) optimization algorithm by minimizing the integral square error. In addition, extensive simulation experiments on an existing single-area power system were conducted to test the efficacy of the proposed design technique. The findings show that the proposed controller outperforms the recently developed controllers regarding transient response and error parameters. The suggested controller’s capability is also demonstrated by improved external disturbance rejections despite plant parameter variations. The reduced model of a single area load frequency control system is also obtained in this paper. It found that the dynamic response of the obtained reduced system is close to the original single area LFC system.
DOI: 10.6084/m9.figshare.25242627.v1
title: A new hybrid approach based on fuzzy logic and optimization for load frequency control

description: This paper presents a fuzzy logic and optimization-based controller design for load frequency control of a single area system with a non-reheated turbine. The controller’s unknown parameters are determined using Big Bang-Big Crunch (BB-BC) optimization algorithm by minimizing the integral square error. In addition, extensive simulation experiments on an existing single-area power system were conducted to test the efficacy of the proposed design technique. The findings show that the proposed controller outperforms the recently developed controllers regarding transient response and error parameters. The suggested controller’s capability is also demonstrated by improved external disturbance rejections despite plant parameter variations. The reduced model of a single area load frequency control system is also obtained in this paper. It found that the dynamic response of the obtained reduced system is close to the original single area LFC system.
DOI: 10.6084/m9.figshare.24720009
title: Impact of social media on academics: a fractional order mathematical model

description: Due to the COVID pandemic and lockdown, usage of social platforms increased for academic and non-academic purposes. As a result, students are at significant risk of developing social media addiction, so techniques to control social media addiction throughout society are required. There are several positive and negative ways in which social media affects the academic performance of a student. Most of the mathematical models exclude the past of an individual, which is critical for controlling social media consumption. Hence, this study offers a fractional-order mathematical model to analyze the impact of social media on academics. There are two equilibrium points for the proposed model: social web-free and endemic equilibrium. Based on an evaluation of the threshold value, the social web-free equilibrium point is globally asymptotically stable whenever the threshold value is less than one. Endemic equilibrium points exist when the threshold value is greater than 1. Additionally, numerical simulations have been performed to examine changes in population dynamics and validate analytical outcomes. In summary, the findings of this research reveal that social media addiction decreases as the order of the derivative decreases, demonstrating the high efficiency of a fractional-order model over an integer-order model.
DOI: 10.6084/m9.figshare.24720009.v1
title: Impact of social media on academics: a fractional order mathematical model

description: Due to the COVID pandemic and lockdown, usage of social platforms increased for academic and non-academic purposes. As a result, students are at significant risk of developing social media addiction, so techniques to control social media addiction throughout society are required. There are several positive and negative ways in which social media affects the academic performance of a student. Most of the mathematical models exclude the past of an individual, which is critical for controlling social media consumption. Hence, this study offers a fractional-order mathematical model to analyze the impact of social media on academics. There are two equilibrium points for the proposed model: social web-free and endemic equilibrium. Based on an evaluation of the threshold value, the social web-free equilibrium point is globally asymptotically stable whenever the threshold value is less than one. Endemic equilibrium points exist when the threshold value is greater than 1. Additionally, numerical simulations have been performed to examine changes in population dynamics and validate analytical outcomes. In summary, the findings of this research reveal that social media addiction decreases as the order of the derivative decreases, demonstrating the high efficiency of a fractional-order model over an integer-order model.
DOI: 10.6084/m9.figshare.26235319
title: Mathematical analysis of a novel fractional order vaccination model for Tuberculosis incorporating susceptible class with underlying ailment

description: Tuberculosis (TB) is a communicable, airborne infection caused by the bacillus Mycobacterium tuberculosis. Pulmonary tuberculosis (PTB) is the most common presentation, although infection can spread anywhere to cause extra-pulmonary tuberculosis (EPTB). In this paper, a novel fractional order mathematical model is designed for the transmission dynamics of tuberculosis. Uninfected vulnerable individuals are categorized into the following: susceptible with underline ailment and susceptible without underline ailment. The research seeks to qualitatively and quantitatively analyze the proposed model and suggests comprehensive intervention measures for the control of tuberculosis among individuals with underline ailment. Some of the major highlights from the numerical investigation points out that TB vaccination is key to reducing the spread of TB among individuals with underline ailment. Furthermore, efforts to step down the spread of TB through awareness campaigns could significantly reduce the burden of the disease among individuals with co-morbidity.
DOI: 10.6084/m9.figshare.26235319.v1
title: Mathematical analysis of a novel fractional order vaccination model for Tuberculosis incorporating susceptible class with underlying ailment

description: Tuberculosis (TB) is a communicable, airborne infection caused by the bacillus Mycobacterium tuberculosis. Pulmonary tuberculosis (PTB) is the most common presentation, although infection can spread anywhere to cause extra-pulmonary tuberculosis (EPTB). In this paper, a novel fractional order mathematical model is designed for the transmission dynamics of tuberculosis. Uninfected vulnerable individuals are categorized into the following: susceptible with underline ailment and susceptible without underline ailment. The research seeks to qualitatively and quantitatively analyze the proposed model and suggests comprehensive intervention measures for the control of tuberculosis among individuals with underline ailment. Some of the major highlights from the numerical investigation points out that TB vaccination is key to reducing the spread of TB among individuals with underline ailment. Furthermore, efforts to step down the spread of TB through awareness campaigns could significantly reduce the burden of the disease among individuals with co-morbidity.
DOI: 10.6084/m9.figshare.26862522
title: (α+2)-Dimensional fractional evolution equation: group classification, symmetries, reduction and conservation laws

description: A preliminary group classification based on symmetry operators is applied to study invariance properties of the time-fractional (α+2)-dimensional fractional evolution equation. The concepts of Riemann–Liouville and Caputo fractional derivatives are used in this study. The similarity variables obtained from symmetries and one-dimensional optimal systems of constructed Lie algebras are used in order to find the group-invariant solutions of the equation. Finally conservation laws of the equation are derived via a modified version of Noether’s theorem.
DOI: 10.6084/m9.figshare.26862522.v1
title: (α+2)-Dimensional fractional evolution equation: group classification, symmetries, reduction and conservation laws

description: A preliminary group classification based on symmetry operators is applied to study invariance properties of the time-fractional (α+2)-dimensional fractional evolution equation. The concepts of Riemann–Liouville and Caputo fractional derivatives are used in this study. The similarity variables obtained from symmetries and one-dimensional optimal systems of constructed Lie algebras are used in order to find the group-invariant solutions of the equation. Finally conservation laws of the equation are derived via a modified version of Noether’s theorem.
DOI: 10.6084/m9.figshare.24634817
title: The convergence of a generalized convex neural network

description: The convergence of neural networks is a central area of research that is essential in understanding the universal approximation capability and the structural complexity of these systems. In this study, we investigate a generalized convex incremental iteration method. This iteration method is presented in a more general form than previous studies and is capable of scraping a broader range of weight parameters. Additionally, we systematically demonstrate the convergence rate of the convex iteration. Our findings are also easily extensible to deep convolutional neural networks, which helps to explain their effectiveness in various real-world applications. Furthermore, we provide a discrete statistical perspective to address issues of input data non-compactness and unknowability of the objective function in practical settings. To support our conclusions, we propose two algorithms, namely back propagation and random search, the latter of which can prevent the network from getting stuck in a local minimum during training. Finally, we present results from several regression problems, which indicate that our algorithms exhibit superior performance and are consistent with our theoretical predictions. These results provide a more comprehensive understanding of the convergence of neural networks and its significance in the universal approximation capability of these systems.
DOI: 10.6084/m9.figshare.24634817.v1
title: The convergence of a generalized convex neural network

description: The convergence of neural networks is a central area of research that is essential in understanding the universal approximation capability and the structural complexity of these systems. In this study, we investigate a generalized convex incremental iteration method. This iteration method is presented in a more general form than previous studies and is capable of scraping a broader range of weight parameters. Additionally, we systematically demonstrate the convergence rate of the convex iteration. Our findings are also easily extensible to deep convolutional neural networks, which helps to explain their effectiveness in various real-world applications. Furthermore, we provide a discrete statistical perspective to address issues of input data non-compactness and unknowability of the objective function in practical settings. To support our conclusions, we propose two algorithms, namely back propagation and random search, the latter of which can prevent the network from getting stuck in a local minimum during training. Finally, we present results from several regression problems, which indicate that our algorithms exhibit superior performance and are consistent with our theoretical predictions. These results provide a more comprehensive understanding of the convergence of neural networks and its significance in the universal approximation capability of these systems.
DOI: 10.5281/zenodo.18374153
title: Data from: GWAS of CK in Elite Winter Sports Athletes
DOI: 10.5281/zenodo.18374154
title: Data from: GWAS of CK in Elite Winter Sports Athletes
DOI: 10.5281/zenodo.10572949
title: FTIR MIR soil spectra database of Relict Charcoal Hearths in Connecticut, USA
DOI: 10.5281/zenodo.18233313
title: FTIR MIR soil spectra database of Relict Charcoal Hearths in Connecticut, USA
DOI: 10.6084/m9.figshare.30397450
title: Antibody Screening and Binding Prediction Analysis Targeting Stx2

description: <b>Background: </b>Shiga toxin (Stx), produced by enterohemorrhagic Escherichia coli (EHEC), is a highly potent exotoxin responsible for severe complications such as hemolytic uremic syndrome (HUS). Among its isoforms, Stx2 exhibits stronger cytotoxicity and poses greater clinical risk, yet no effective therapy currently exists. Methods: In this study, two human monoclonal antibodies, YG12-1 and YG12-2, were identified from a phage display library and systematically characterized using an integrated modeling–validation workflow. <b>Results: </b>Structural modeling with ImmuneBuilder and Rosetta revealed that YG12- 2 possessed a longer CDRH3 topology, more short-range hydrogen bonds, and stronger electrostatic complementarity, corresponding to lower binding energy and higher apparent affinity in ELISA and SPR. Although YG12-2 had a better affinity, YG12-1 shows better protective activity in a murine model of acute peritoneal infection. This paradox highlights a non-linear relationship between structural affinity and biological efficacy, emphasizing the importance of functional epitope accessibility and pharmacokinetic behavior in determining neutralization outcomes. <b>Conlusion: </b>Overall, these results indicated that targeting Stx2 with YG12-1 and YG12-2 could serve as a promising protective strategy against E. coli O157:H7 infection