Analysis Of Global Dynamics Research Articles

Intersecting inequalities: towards a critical discursive approach

ABSTRACT This introduction to the Special Issue delves into the intersection of critical discursive approaches and intersectionality in the study of language, gender, and societal inequalities. It traces the evolution of gender and language studies, with a focus on how discursive methodologies have facilitated the examination of the material consequences of discourse, particularly in relation to power, gender, and social structures. The aim of this Special Issue is to foster academic synergy by merging discursive and intersectional frameworks to analyze how socio-cultural categories—such as gender, race, and class, among others—intersect to produce inequalities. Furthermore, the issue incorporates a decolonial perspective, critically engaging with the Eurocentric foundations of existing methodologies and advocating for a more inclusive analysis of global power dynamics. The articles within this issue adopt interdisciplinary approaches, including Critical Discourse Studies and Sociocultural Linguistics, to explore diverse experiences and social structures. By integrating these frameworks, the issue offers a multifaceted understanding of how intersecting identities shape discourse and social power relations, underscoring the importance of critical praxis and self-reflexivity in academic research.

A second-order kinetic model for global analysis of vibrational polariton dynamics.

The interaction between cavity photons and molecular vibrations leads to the formation of vibrational polaritons, which have demonstrated the ability to influence chemical reactivity and change material characteristics. Although ultrafast spectroscopy has been extensively applied to study vibrational polaritons, the nonlinear relationship between signal and quantum state population complicates the analysis of their kinetics. Here, we employ a second-order kinetic model and transform matrix method (TMM) to develop an effective model to capture the nonlinear relationship between the two-dimensional IR (or pump-probe) signal and excited state populations. We test this method on two types of kinetics: a sequential relaxation from the second to the first excited states of dark modes, and a Raman state relaxing into the first excited state. By globally fitting the simulated data, we demonstrate accurate extraction of relaxation rates and the ability to identify intermediate species by comparing the species spectra with theoretical ground truth, validating our method. This study demonstrates the efficacy of a second-order TMM approximation in capturing essential spectral features with up to 10% excited state population, simplifying global analysis and enabling straightforward extraction of kinetic parameters, thus empowering our methodology in understanding excited-state dynamics in polariton systems.

Modeling and global stability analysis of COVID-19 dynamics with optimal control and cost-effectiveness analysis

In addressing the global challenges posed by COVID-19, this study introduces a mathematical model aimed at investigating the transmission dynamics of COVID-19 and forwarding strategies for controlling it. By employing Lyapunov functions, we perform a thorough stability analysis of both disease-free and endemic equilibria. We calibrated the model using daily COVID-19 data from early 2022 in Ethiopia, after vaccination initiation. A global sensitivity analysis confirmed the robustness of the model. In addition, we extended the model to address optimal control by incorporating vaccination, public health education, and treatment. Our findings highlight the effectiveness of individual control measures and reveal that vaccination, public health educational campaign and treatment is the most cost-effective method for mitigating COVID-19 spread.

Complex Network Model of Global Financial Time Series Based on Different Distance Functions

By constructing a complex network model grounded in time series analysis, this study delves into the intricate relationships between the stock markets of 18 countries worldwide. Utilizing 31 distinct time series distance functions to formulate the network, we employ Hamming distance to quantify the resemblance between networks derived from different distance functions. By modulating the network density through distance percentiles (p=0.1, 0.3, 0.5), we demonstrate the similarity of various distance functions across multiple density levels. Our findings reveal that certain distance functions exhibit high degrees of similarity across varying network densities, suggesting their potential for mutual substitution in network construction. Furthermore, the centroid network identified via hierarchical cluster analysis highlights the similarities between the stock markets of different nations, mirroring the intricate interconnections within the global financial landscape. The insights gained from this study offer crucial perspectives for comprehending the intricate network structure of global financial time series data, paving the way for further analysis and prediction of global financial market dynamics.

A modified perturbation method for global dynamic analysis of generalized mixed Rayleigh–Liénard oscillator with cubic and quintic nonlinearities

Deriving analytical relationship between the system parameters and amplitude of the limit cycle is a meaningful and challenging task. Currently, numerous existing analytical approximate methods struggle to achieve this goal when expressions of restoring force or nonlinear damping is complicated. To overcome this shortcoming, this study proposes a modified generalized harmonic function perturbation method. Using the proposed method, a generalized mixed RayleighLiénard oscillator with cubic and quintic nonlinearities was investigated. The analytical relationships between the system parameters and amplitude of the limit cycle, as well as the expression of its characteristic quantity, were derived. By employing these analytical relationships, the existence, stability, number, position, and amplitude of each limit cycle are quantitatively analysed. The homoclinic and heteroclinic bifurcations were also predicted using the above analytical relationships. Additionally, analytical approximate solutions for this oscillator were calculated using the proposed method. All results obtained in this study were subsequently confirmed numerically to demonstrate their feasibility and validity. Consequently, the proposed method can be considered an effective supplement to perturbation-based methods. This also implies that the work presented in this paper has a certain theoretical significance and application value in the research area of quantitative analysis methods for strongly nonlinear oscillators.

Follow the money: a global analysis of funding dynamics for global health security.

Global financing for health security was dramatically impacted by COVID-19. Here, we provide an empirical analysis of how that funding changed. Using data from Global Health Security (GHS) Tracking (tracking.ghscosting.org), we analyzed disbursements of direct financial assistance for GHS from 2016 to 2022 to compare pre-pandemic funding (2016-2019) to post-pandemic funding (2020-2022) for preparedness and response during each of the seven World Health Organization-declared public health emergencies of international concern (PHEICs) from 2009 to 2022. Over $165B was disbursed for capacity-building and preparedness activities between January 2016 and December 2022, and over $76B was provided for PHEIC response. Preparedness funding remained evenly distributed since 2016 across regions, with the African region receiving about 70% of total preparedness funding. Indeed, how capacity-building and preparedness funding is distributed has changed remarkably little since 2016, despite unprecedented changes to the funding environment-including markedly increased spending-in response to COVID-19. This suggests we now have a unique opportunity to restructure how funds are tracked for accountability and assessing return on investment moving forward.

World‐makers and social justice: Strategies of (in)action?

AbstractThis article applies a Bourdieusian lens to a critical analysis of global power dynamics to argue that a field framework is useful for studying praxis and (in)action in complex and dynamic global spaces of decision‐making. It is argued that individuals with global power can interact strategically to change their actions for improved social and economic justice, but it requires resisting dominant practices that may maintain existing inequalities. By exploring the interrelations between positions within the global spaces of the World Social Forum and the World Economic Forum, we offer an original contribution to the field of strategic change. We show how the actors in these global spaces have the potential to provoke greater social justice but also risk perpetuating a status quo that continues to favor the few over the many. Participants are world‐makers who wield symbolic power and can create disruption in the “rules of the game,” but the strength of those who seek to defend the status quo can perpetuate inertia. The article offers a novel contribution to the research on global spaces and elite actors by critically analyzing accounts of strategic practices therein, thus offering a more nuanced understanding of world‐making in action or inaction.

Global Dynamics Analysis of Non-Local Delayed Reaction-Diffusion Avian Influenza Model with Vaccination and Multiple Transmission Routes in the Spatial Heterogeneous Environment

Global Dynamics Analysis of Non-Local Delayed Reaction-Diffusion Avian Influenza Model with Vaccination and Multiple Transmission Routes in the Spatial Heterogeneous Environment

Global marine phytoplankton dynamics analysis with machine learning and reanalyzed remote sensing.

Phytoplankton are the world's largest oxygen producers found in oceans, seas and large water bodies, which play crucial roles in the marine food chain. Unbalanced biogeochemical features like salinity, pH, minerals, etc., can retard their growth. With advancements in better hardware, the usage of Artificial Intelligence techniques is rapidly increasing for creating an intelligent decision-making system. Therefore, we attempt to overcome this gap by using supervised regressions on reanalysis data targeting global phytoplankton levels in global waters. The presented experiment proposes the applications of different supervised machine learning regression techniques such as random forest, extra trees, bagging and histogram-based gradient boosting regressor on reanalysis data obtained from the Copernicus Global Ocean Biogeochemistry Hindcast dataset. Results obtained from the experiment have predicted the phytoplankton levels with a coefficient of determination score (R2) of up to 0.96. After further validation with larger datasets, the model can be deployed in a production environment in an attempt to complement in-situ measurement efforts.

Financial sector development and renewable energy consumption nexus: Evidence from global dynamic panel threshold analysis

AbstractDecarbonizing economies requires an energy transition from conventional energy resources to renewable and clean energy resources. However, this transition largely depends upon the availability of huge investments to manage high start‐up costs and operational infrastructure. In this respect, the financial sector can play a vital role. This study explores the financial sector's role in renewable energy consumption utilizing a comprehensive measure of financial sector development constituting both financial institutions and financial markets. Moreover, the study utilizes an advanced econometric technique “dynamic panel threshold model” on panel data of 165 countries ranging from 1980 to 2019. The empirical analysis reveals the presence of a threshold value of 0.191, 0.196, and 0.008 for the overall financial development index, financial institutions index, and financial market index, respectively. This finding confirms the presence of a U‐shaped curve between financial sector development and renewable energy consumption, validating the existence of the financial Kuznets curve. Thus, initially, financial sector development results in lower renewable energy consumption while after reaching the threshold level it boosts renewable energy consumption. Furthermore, the study also shows the statistically significant role of economic growth, trade openness, and inflation in explaining renewable energy usage. The obtained outcomes suggest a pressing necessity to improve both financial institutions and markets to surpass the threshold levels of financial sector performance within the financial sector, thus supporting a rise in renewable energy consumption.

Global Dynamics of Two-Species Amensalism Model with Beddington–DeAngelis Functional Response and Fear Effect

This paper investigates a two-species amensalism model that includes the fear effect on the first species and the Beddington–DeAngelis functional response. The existence and stability of possible equilibria are investigated. Under different parameters, there exist two stable equilibria which means that this model is not always globally asymptotically stable. Together with the existence of all possible equilibria and their stability, saddle connection and close orbits, we derive some conditions for transcritical bifurcation and saddle-node bifurcation. Furthermore, global dynamics analysis of the model is performed. It is observed that under certain parameter conditions, when the intensity of the fear effect is below a certain threshold value, as the fear effect increases it will only reduce the density of the first species population and will have no influence the extinction or existence of the first species population. However, when the fear effect exceeds this threshold, the increase of the fear effect will accelerate the extinction of the first species population. Finally, numerical simulations are performed to validate theoretical results.

The effects of additional food and environmental stochasticity on the asymptotic properties of a nutrient–phytoplankton model

In this paper, we investigate the deterministic and stochastic features of an additional food provided nutrient–phytoplankton model, and discuss the effects of additional food and environmental stochasticity (noise) on its asymptotic properties. A detailed global dynamics analysis of the deterministic model is firstly provided, and then the critical conditions for persistence and extinction of phytoplankton is found. For the stochastic model, we establish some sufficient conditions for the exponential extinction of phytoplankton and the existence of stationary distribution. By solving the Fokker–Planck equation, the explicit expression of local probability density of the stochastic model is further derived. With the help of probability density, we obtain the mean, variance, skewness and kurtosis of the biomass of phytoplankton, and numerically find the additional food and stochasticity have complex effects on these statistical properties. Both theoretical and numerical findings indicate that the additional food source is favorable for the growth of phytoplankton, whereas the stochasticity is adverse to its growth. Moreover, the additional food source and stochasticity play important roles in the formation of phytoplankton bloom.

Contribution of electrical impedance tomography to personalize positive end-expiratory pressure under ECCO2R

Extracorporeal Carbon Dioxide Removal (ECCO2R) is used in acute respiratory distress syndrome (ARDS) patients to facilitate lung-protective ventilatory strategies. Electrical Impedance Tomography (EIT) allows individual, non-invasive, real-time, bedside, radiation-free imaging of the lungs, providing global and regional dynamic lung analyses. To provide new insights for future ECCO2R research in ARDS, we propose a potential application of EIT to personalize End-Expiratory Pressure (PEEP) following each reduction in tidal volume (VT), as demonstrated in an illustrative case. A 72-year-old male with COVID-19 was admitted to the ICU for moderate ARDS. Monitoring with EIT was started to determine the optimal PEEP value (PEEPEIT), defined as the intersection of the collapse and overdistention curves, after each reduction in VT during ECCO2R. The identified PEEPEIT values were notably low (< 10 cmH2O). The decrease in VT associated with PEEPEIT levels resulted in improved lung compliance, reduced driving pressure and a more uniform ventilation pattern. Despite current Randomized Controlled Trials showing that ultra-protective ventilation with ECCO2R does not improve survival, the applicability of universal ultra-protective ventilation settings for all patients remains a subject of debate. Inappropriately set PEEP levels can lead to alveolar collapse or overdistension, potentially negating the benefits of VT reduction. EIT facilitates real-time monitoring of derecruitment associated with VT reduction, guiding physicians in determining the optimal PEEP value after each decrease in tidal volume. This original description of using EIT under ECCO2R to adjust PEEP at a level compromising between recruitability and overdistention could be a crucial element for future research on ECCO2R.

Global Stability Analysis of Onchocerciasis Transmission Dynamics with Vigilant Compartment in Two Interacting Populations

A deterministic compartmental model for the transmission dynamics of onchocerciasis with vigilant compartment in two interacting populations is studied. The model is qualitatively analyzed to investigate its global asymptotic behavior with respect to disease-free and endemic equilibria. It is shown, using a linear Lyapunov function, that the disease-free equilibrium is globally asymptotically stable when the associated basic reproduction number, R0&lt;1. When the basic reproduction number R0&gt;1, under some certain conditions on the model parameters, we prove that the endemic equilibrium is globally asymptotically stable with the aid of a suitable nonlinear Lyapunov function.

An optimised equivalent modelling approach for LMRP/BOPs in the global dynamic analysis of deepwater risers

ABSTRACT Lower marine riser package/blowout preventers (LMRP/BOPs) play a crucial role in transferring the dynamic loads from the slim drilling risers to the subsea wellhead (SW). Generally, the LMRP/BOPs are usually modelled as the combination of pipe and mass elements in the finite element analysis. In this paper, an optimised equivalent modelling approach for LMRP/BOPs was proposed to improve the calculation accuracy of dynamic cyclic bending moment of SW. In the proposed methodology, the equivalent model of LMRP/BOPs was established based on the deformation analysis of the local fine model of LMRP/BOPs. Using the Newton–Raphson method, the equivalent model was optimised to acquire the optimal equivalent model of LMRP/BOPs. A case study indicated the modelling accuracy of LMRP/BOPs was improved by 14.6% compared to the conventional approach by using the proposed approach, thus the calculation accuracy of the dynamic cyclic bending moment of SW was improved accordingly.

Pattern-Moving-Modelling and Analysis Based on Clustered Generalized Cell Mapping for a Class of Complex Systems

Considering a class of complex nonlinear systems whose dynamics are mostly governed by statistical regulations, the pattern-moving theory was developed to characterise such systems and successfully estimate the outputs or states. However, since the pattern class variable is not computable directly, this study establishes a clustered generalized cell mapping (C-GCM) to reveal system characteristics. C-GCM is a two-stage approach consisting of a pattern-moving-based description and analysis method. First, a density algorithm, named density-based spatial clustering of applications with noise (DBSCAN), is designed to obtain cell space Ω and the corresponding classification guidelines; this algorithm is initiated after the initial pre-image cells, and the total number of entity cells amounts to Ns. Then, the GCM provides several image cells based on a cell mapping function that refers to the multivariate ARMAX model. The global dynamic analysis employing both searching and storing algorithms depend on the attractor, domain of attraction, and periodic cell groups. At last, simulation results of two examples emphasise the practicality as well as efficacy of the technique suggested. The chief aim of this study was to offer a new perspective for a class of complex systems that could inspire research into nonmechanistic principles modelling and application to nonlinear systems.

A hybrid approach for fatigue assessment of reinforced concrete bridge deck considering realistic bridge-traffic interaction

Reinforced concrete (RC) bridge decks are directly exposed to daily traffic loads and often experience surface cracking caused by excessive stress or fatigue accumulation. The bridge deck fatigue performance over traffic loads needs to be assessed based on accurate dynamic interaction analysis of the bridge and realistic moving vehicles. Most of existing studies on fatigue assessment focus on either the bridge global response without sufficient details about the bridge deck, or refined bridge deck modeling without considering the full dynamic interaction between moving traffic and the bridge structure realistically. A hybrid fatigue assessment approach is developed by combining mode-based global bridge-traffic dynamic interaction analysis, finite-element (FE)-based refined bridge deck model, and fatigue assessment method directly based on the vehicle loads and shear strength of the bridge deck. The proposed approach is demonstrated with a typical 3-span concrete bridge under realistic traffic and road surface conditions. Based on the dynamic interaction and stress analysis results, the fatigue damage factor is further investigated with different road surface roughness levels and heavy truck proportions. It is found that the proposed analytical approach provides a useful tool to predict the bridge deck response and potential fatigue damage under realistic traffic flow.

Analysis of global dynamics in an attraction-repulsion model with nonlinear indirect signal and logistic source

&lt;p&gt;The following chemotaxis system has been considered:&lt;/p&gt;&lt;p&gt;&lt;disp-formula&gt; &lt;label/&gt; &lt;tex-math id="FE1"&gt; \begin{document}$ \begin{equation*} \left\{ \begin{array}{ll} v_{t} = \Delta v-\xi \nabla\cdot(v \nabla w_{1})+\chi \nabla\cdot(v \nabla w_{2})+\lambda v-\mu v^{\kappa},\ &amp;amp;\ \ x\in \Omega, \ t&amp;gt;0,\\[2.5mm] w_{1t} = \Delta w_{1}-w_{1}+w^{\kappa_{1}}, \ 0 = \Delta w-w+v^{\kappa_{2}}, \ &amp;amp;\ \ x\in \Omega, \ t&amp;gt;0,\\[2.5mm] 0 = \Delta w_{2}-w_{2}+v^{\kappa_{3}}, \ &amp;amp;\ \ x\in \Omega, \ t&amp;gt;0 , \end{array} \right. \end{equation*} $\end{document} &lt;/tex-math&gt;&lt;/disp-formula&gt;&lt;/p&gt;&lt;p&gt;under the boundary conditions of $ \frac{\partial{v}}{\partial{\nu}} = \frac{\partial{w_{1}}}{\partial{\nu}} = \frac{\partial{w}}{\partial{\nu}} = \frac{\partial{w_{2}}}{\partial{\nu}} $ on $ \partial \Omega, $ where $ \Omega $ was a bounded smooth domain of $ \mathbb{R}^{n}(n\geq 1), \; \nu $ was the normal vector of $ \partial\Omega, $ and the parameters were $ \lambda, \mu, \xi, \chi, \kappa_{1}, \; \kappa_{2}, \kappa_{3} &amp;gt; 0, $ and $ \kappa &amp;gt; 1. $ In this paper, we showed that if either $ \kappa_{1}\kappa_{2} &amp;lt; \max\{\frac{2}{n}, \kappa_{3}, \kappa-1\} $ or $ \kappa_{1}\kappa_{2} = \max\{\frac{2}{n}, \kappa_{3}, \kappa-1\} $ with the coefficients and initial data satisfying appropriate conditions, then the system possessed a global classical solution. Furthermore, we also have studied the convergence of solutions to a special case of the above system with $ \kappa = \delta+1, \kappa_{1} = 1, \kappa_{2} = \kappa_{3} = \delta $ for $ \delta &amp;gt; 0. $ It has been proven that if $ \mu &amp;gt; 0 $ is large enough, then the corresponding classical solutions exponentially converged to $ ((\frac{\lambda}{\mu})^{\frac{1}{\delta}}, \frac{\lambda}{\mu}, \frac{\lambda}{\mu}, \frac{\lambda}{\mu}), $ where the convergence rate could be formally expressed by the parameters of the system.&lt;/p&gt;

Global stability analysis of transmission dynamics in a compartmental model of coronavirus disease with environmental reservoirs

This work proposes and analyzes a non-linear deterministic model which describes the outbreak of Coronavirus disease with fomites (environmental reservoirs) propagating the spread of the infection in human population. Suitable Lyapunov functions are constructed to demonstrate the Global Asymptotic Stability (GAS) of both the Endemic Equilibrium (EE) and Disease Free Equilibrium (DFE) of the system. The EE was also found to be epidemiologically relevant when the basic reproduction number of new infections is greater than unity.

Mathematical analysis of global dynamics and optimal control of treatment for an age-structured HBV infection model

Evidences show that cell-to-cell infection occurs in HBV infection and is a very efficient way which may lead to more than half of the viral infection. Hence we formulate an HBV infection model with cell-to-cell infection, meanwhile, we incorporate the infection age of infected cells. For dynamic behaviors, we firstly establish the well-posedness and asymptotic smoothness of the model; then show the global threshold dynamical behaviors, which are determined by the reproduction number; and finally perform numerical simulations not only to verify the theoretical results but also to explore effects of cell-to-cell infection on viral load and infection concentration. Our finding is that ignoring the cell-to-cell infection will underestimate the actual HBV infection status. For optimal control of treatment for HBV, we introduce two time-varying control measures and investigate the corresponding optimal control problem. We derive the characteristic expression of the optimal control and discuss effects of control costs and integrated control. The results show that high control cost will not result in better control effectiveness, while integrated optimal control can reach the best control objectives compared with the two single ones. Moreover, infection age can greatly influence HBV infection at the initial stage.