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The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

The electromechanical planetary transmission system has the advantages of high transmission power and fast running speed, which is one of the important development directions in the future. However, during the operation of the electromechanical planetary transmission system, friction and other factors will lead to an increase in gear temperature and thermal deformation, which will affect the transmission performance of the system, and it is of great significance to study the influence of the temperature effect on the nonlinear dynamics of the electromechanical planetary system.

The effects of temperature change, motor speed, time-varying meshing stiffness, meshing damping ratio and error amplitude on the nonlinear dynamic characteristics of electromechanical planetary systems are studied by using bifurcation diagrams, time-domain diagrams, phase diagrams, Poincaré cross-sectional diagrams, spectra, etc.

The results show that when the temperature rise is less than 70 °C, the system will exhibit chaotic motion. When the motor speed is greater than 900r/min, the system enters a chaotic state. The changes in time-varying meshing stiffness, meshing damping ratio, and error amplitude will also make the system exhibit abundant bifurcation characteristics.

Based on the principle of thermal deformation, taking into account the temperature effect and nonlinear parameters, including time-varying meshing stiffness and tooth side clearance as well as comprehensive errors, a dynamic model of the electromechanical planetary gear system was established.

Effective agricultural product price regulation policies depend on market integration and the degree of symmetry in the transmission of agricultural product price signals. This study analyzes the transmission and asymmetry of the price series between the Ouagadougou consumer market and assembly markets considering three primary cereal products in Burkina Faso.

This study applies the nonlinear autoregressive distributed lag (NARDL) econometric model, which is an asymmetric extension of the ARDL cointegration model. The price series examined covers the period extending from January 2005 to December 2020.

Our analysis provides novel insights regarding short- and long-term asymmetric effects in the transmission of price signals between assembly markets and the consumer market. We also determine that the effects of negative shocks are more persistent than those of positive shocks in several markets.

For markets that exhibit symmetrical responses of assembly market prices to consumer market prices, the results could reflect the continuous efforts of market players, particularly the government, to eliminate market failures and ensure the long-term efficiency of cereal markets. To this end, an agricultural market information system can have a crucial role in easing information access for all market players.

This study provides new evidence regarding the nature of the transmission and asymmetry of price information on primary cereal products in the largest markets in Burkina Faso. Applying the NARDL model makes it possible to simultaneously estimate short- and long-term asymmetry.

This study akims to investigate the effectiveness of expansionary monetary policy for Islamic capital markets by studying the impact of decrease in policy rates on seven Islamic equity indices for the period 1996–2019. The transmission mechanism may be different for sampled indices, as they are exposed to Shariah screening that discards certain business sectors and puts limit on debt in capital structure.

This study uses Markov Switching dynamic regression approach of Hamilton (1988).

The results show little effectiveness of expansionary monetary policy in both Bear and Bull states, for most of the sample indices.

To the best of the authors’ knowledge, no study has made use of dynamic models to assess the association between monetary policy rate and Islamic index prices. Similarly, the authors found no work exploring the effectiveness of expansionary monetary policy actions in different regime for Islamic Indices. This investigation is important in unraveling whether, in the presence of limitations on selection of business activity and choice of capital structure, monetary policy can change the market sentiment, or it will be ineffective. The present study fills this gap.

During the operation of a wet clutch, there are fluctuations in speed and torque, which have an impact on the stability of the clutch and the strength of the friction plate and the spline pair of the dual steel plate. The purpose of this study is to investigate the vibration characteristics of the wet clutch and the dynamic load characteristics of the spline pairs.

The spline pair model is established by the piecewise linear function method, and on this basis, dynamic equations considering the spline pair of dual steel plates and friction plates are established. Considering that the wet clutch has multiple spline pairs, an equivalent model of the number of teeth and the equivalent model of the tooth width were proposed, and the Runge-Kutta numerical method was used for the wet clutch for these two models.

The research results show that the equal tooth number model has greater meshing stiffness and smaller fluctuation than the constant tooth width model, which shows that increasing the meshing stiffness of the system is beneficial to reduce system fluctuation and improve system stability.

The friction plate has the system that multiple splines are independent of each other, which is relatively complicated. Therefore, an equivalent calculation is performed on multiple pairs of steel plates (friction plates) to simplify the calculation of the spline pairs.

This paper provides a theoretical basis for further dynamic characteristics analysis of wet clutch and reducing fluctuation of speed and torque.

Dynamic equation considering the spline pair of the dual steel plates and the friction plates is established to study the vibration characteristics of the wet clutch and the dynamic load characteristics of the spline pair, etc.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2023-0078/

This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video surveillance in public spaces.

This study examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Based on the requirements, this study proposes a CFL framework to gradually adapt AI models’ knowledge while reducing personal data transmission and retention. The framework uses three different federated learning strategies to rapidly learn from different new data sources while minimizing personal data transmission and retention to a central machine.

The findings confirm that the proposed CFL framework can help minimize the use of personal data without compromising the AI model's performance. The gradual learning strategies help develop AI-enabled video surveillance that continuously adapts for long-term deployment in public spaces.

This study makes two specific contributions to advance the development of AI-enabled video surveillance in public spaces. First, it examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Second, it proposes a CFL framework to minimize data transmission and retention for AI-enabled video surveillance. The study provides comprehensive experimental results to evaluate the effectiveness of the proposed framework in the context of facial expression recognition (FER) which involves large-scale datasets.

The purpose of this work is to study the connections generated between stock market indices, representing firms whose practices focus on fighting climate change and several global risk factors in accordance with the sustainability objectives defined in the 2030 Agenda. An endogenous perspective is adopted, considering the spillovers generated within the low carbon stock market sector, as well as the latter’s exposure to exogenous shocks of an economic and financial nature.

This work uses a multivariate model of dynamic correlation (GARCH-corrected dynamic conditional correlation [cDCC]), which can accompany the correlations generated over time.

Considering five low carbon indices, representing various parts of the world, and four global macro-economic and financial variables, over a period of approximately eight years, it was possible to understand that the variables studied transmit between each other a statistically significant spillover. The period of the pandemic crisis shows a sharp increase in the information transmission process. It was also possible to conclude that some global variables are risk factors, performing the role of transmission channels for the spillover effects to low carbon indices, increasing the risk of contagion and reducing the possibilities of diversifying the investment portfolio.

Firstly, this work analyses the connection and spillover effects between low carbon indices. Secondly, considers an extended sample covering different market phases, particularly that of the pandemic crisis and the Ukrainian War, creating conditions to compare connection patterns between those indices. Thirdly, it studies the variable influence over time of global risk factors in the transmission of spillover between low carbon indices.

The susceptible-infectious-susceptible (SIS) infectious disease models without spatial heterogeneity have limited applications, and the numerical simulation without considering models’ global existence and uniqueness of classical solutions might converge to an impractical solution. This paper aims to develop a robust and reliable numerical approach to the SIS epidemic model with spatial heterogeneity, which characterizes the horizontal and vertical transmission of the disease.

This study used stability analysis methods from nonlinear dynamics to evaluate the stability of SIS epidemic models. Additionally, the authors applied numerical solution methods from diffusion equations and heat conduction equations in fluid mechanics to infectious disease transmission models with spatial heterogeneity, which can guarantee a robustly stable and highly reliable numerical process. The findings revealed that this interdisciplinary approach not only provides a more comprehensive understanding of the propagation patterns of infectious diseases across various spatial environments but also offers new application directions in the fields of fluid mechanics and heat flow. The results of this study are highly significant for developing effective control strategies against infectious diseases while offering new ideas and methods for related fields of research.

Through theoretical analysis and numerical simulation, the distribution of infected persons in heterogeneous environments is closely related to the location parameters. The finding is suitable for clinical use.

The theoretical analysis of the stability theorem and the threshold dynamics guarantee robust stability and fast convergence of the numerical solution. It opens up a new window for a robust and reliable numerical study.

This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020.

This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets.

Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric.

The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios.

The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.

Despite being a flexible tool that can address several macroeconomic issues, Dynamic Stochastic General Equilibrium (DSGE) models have been rarely used to analyse the interaction between monetary and fiscal policy until the post-financial crisis, leaving a gap in the analysis of how government consumption affects the transmission mechanism of monetary policy. This motivates this paper to analyse how government consumption affects the dynamics of a small open economy, once the former is included in a non-separable form to the utility function. To the best of the authors' knowledge, this issue has not been addressed by the literature, and the authors aim to do so in this paper.

A standard New Keynesian model for a small open economy is used to allow for the presence of non-separable government consumption in the utility function. The model is supported by panel regressions.

The inclusion of Government consumption dampens the transmission mechanism of monetary policy. The degree of openness dampens the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it. Empirical estimates for 35 OECD countries support the theoretical findings of the model.

The effect of government consumption on the transmission mechanism of MP has not been addressed in the literature. This paper contributes to the literature by addressing this issue.

• • The inclusion of Government consumption dampens the transmission mechanism of monetary policy.

• • The degree of openness alleviates the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it.

• • Empirical estimates for 35 OECD countries support the theoretical findings of the model.

• The inclusion of Government consumption dampens the transmission mechanism of monetary policy.

• The degree of openness alleviates the crowding out effect of fiscal policy to monetary policy, as the exchange rate channel empowers it.

• Empirical estimates for 35 OECD countries support the theoretical findings of the model.