IARD 2022 The 13th Biennial Conference on Classical and Quantum Relativistic Dynamics of Particles and Fields

PrefaceThe International Association for Relativistic Dynamics was organized in February 1998 in Houston, Texas, with John R. Fanchi as president. Although the subject of relativistic dynamics has been explored, from both classical and quantum mechanical points of view, since the work of Einstein and Dirac, its most striking development has been in the framework of quantum field theory. The very accurate calculations of spectral and scattering properties, for example, of the anomalous magnetic moment of the electron and the Lamb shift in quantum electrodynamics, and many qualitative features of the strong and electroweak interactions, demonstrate the very great power of description achieved in this framework. Yet, many fundamental questions remain to be clarified, such as the structure of classical relativistic dynamical theories on the level of Hamilton and Lagrange in Minkowski space as well as on the curved manifolds of general relativity. There, moreover, remain the important questions of the covariant classical description of systems at high energy for which particle production effects are not large, such as discussed in Synge's book, The Relativistic Gas, and in Balescu's book on relativistic statistical mechanics, and the development of a consistent single and many body relativistic quantum theory. In recent years, highly accurate telescopes and advanced facilities for computation have brought a high level of interest in cosmological problems, such as the structure of galaxies (dark matter) and the apparently anomalous expansion of the universe (dark energy). Some of the papers reported here deal with these problems, as well as other fundamental related issues.It was for this purpose, to bring together researchers from a wide variety of fields, such as particle physics, astrophysics, cosmology, foundations of relativity theory, and mathematical physics, with a common interest in relativistic dynamics, to investigate fundamental questions of this type, that this Association was founded. The second meeting took place in 2000 at Bar Ilan University in Israel, the third, in 2002, at Howard University in Washington, D.C., and the fourth, in 2004, in Saas Fee, Switzerland. Subsequent meeting took place in 2006 at the University of Connecticut Storrs, in 2008 at Aristotle University of Thessalonica, in 2010 at National Dong Hwa University, Hualien, Taiwan, in 2012 at the Galileo Galilei Institute for Theoretical Physics (GGI) in Florence, in 2014 as the University of Connecticut Storrs, Connecticut, in 2016 at Jožef Stefan Institute in Ljubljana, Slovenia, and in 2018 in Mérida, Yucatán, Mexico, under the sponsorship of the Instituto Politécnic Nacional. The 2020 meeting, planned for Czech Technical University in Prague, was successfully held online at the height of the Covid-19 pandemic, and the physical meeting in Prague was delayed to 2022.The 2022 meeting forms the basis for the Proceedings that are recorded in this issue of the Journal of Physics: Conference Series. Along with the work of some of the founding and newer but already much engaged members of the Association, we were fortunate to have lecturers from application areas that provided strong challenges for further developments in quantum field theory, cosmological problems, and in the dynamics of systems subject to accelerations and the effects of general relativity. Topics treated in this issue include studies in general relativity and astrophysics, relativistic dynamics and electrodynamics, quantum theory and particles, and foundations of relativistic dynamics.This first physical meeting of the Covid-19 era took place 6 - 9 June at Czech Technical University in Prague, as originally planned for 2020. The meeting was divided into seven plenary sessions over four days. As a result of continued travel restrictions in some areas, a small number of talks were delivered by videoconferencing. The papers presented in this volume represent extensions and refinements to the conference talks, building on feedback and discussions associated with the lect re . We once again express our gratitude to Czech Technical University, and especially the local conference chair Petr Jizba, for their generous hospitality.List of Scientific Advisory Committee, International Organizing Committee and Editorial Board of the proceedings, Dedication are available in this Pdf.

Systemic risks in supply chains: a need for system-level governance

PurposeGlobal and interconnected supply chains are increasingly exposed to systemic risks, whereby individual failures propagate across firms, sectors and borders. Systemic risks have emerged from the decisions of individual firms, e.g., outsourcing and buffer reduction, and are now beyond their control. This paper aims to identify appropriate approaches to mitigating those risks.Design/methodology/approachSystemic risks require analyzing supply chains beyond a dyadic perspective. This study approaches the problem through the lenses of complex systems and network theories. Drawing on the lessons learned from other systemic-risk-prone systems, e.g. energy and financial networks, both in research and practice, this study analyzes the adequate level of governance to monitor and manage systemic risks in supply chains.FindingsThe authors argue that governance institutions should be mandated to overview and reduce systemic risks in supply chains from the top down, as central bankers do for the financial system. Using firm-level data and tools from network analysis and system dynamics, they could quantify systemic risks, identify risk-prone interconnections in supply chains and design mitigating measures. This top-down approach would complement the bottom-up supply chain management approach and could help insurers design policies for contingent business interruptions.Originality/valueInstead of looking at supply chains purely from the firms' angle, the perspective of insurers and governments is brought in to reflect on the governance of risks.

The Role of Personal Characteristics in Shaping Gender-Biased Job Losses during the COVID-19 Pandemic: The Case of South Africa

This paper contributes to the literature on the effects of adverse economic conditions on gender differences in the labour market by assessing how COVID-19, a global trigger for a critical adverse condition, impacted gender differences in the labour market in a country with pronounced discrimination and inequality in the labour market. In fact, the paper investigates how the personal characteristics of women and men affected their likelihood of losing jobs during and before COVID-19 in South Africa. Using the database of the National Income Dynamics Study-Coronavirus Rapid Mobile Survey (NIDS-CRAM) and NIDS wave 5 dataset and based on logit regression, the paper finds that personal characteristics such as tertiary education had a negative effect on job losses among females. Moreover, the results show that, compared to male workers, female workers were the most affected by the pandemic due to the lockdown regulation that affected many households' behaviour.

Thermal Comfort Analysis Using System Dynamics Modeling—A Sustainable Scenario Proposition for Low-Income Housing in Brazil

As a riveting example of social housing in Brazil, the Minha Casa Minha Vida program was set in 2009 to diminish the 6-million-home housing deficit by offering affordable dwellings for low-income families. However, recurrent thermal discomfort complaints occur among dwellers, especially in the Baltimore Residential sample in Uberlândia City. To avoid negative effects of energy poverty, such as family budget constraints from the purchase of electric appliances and extra costs from power consumption, a simulation based on system dynamics modeling shows a natural ventilation strategy with a mixed combination of sustainable and energy-efficient materials (tilting window with up to 100% opening, green tempered glass, and expanded polystyrene wall) to observe the internal room temperature variation over time. With a 50% window opening ratio combined with a 3 mm regular glass window and a 12.5 cm rectangular 8-hole brick wall, this scenario presents the highest internal room temperature value held during the entire period. From the worst to the best-case scenario, a substantial reduction in the peak temperature was observed from window size variation, demonstrating that natural ventilation and constructive elements of low complexity and wide availability in the market contribute to the thermal comfort of residential rooms.

Numerical Study on the Impact of Large Air Purifiers, Physical Distancing, and Mask Wearing in Classrooms

The risk of COVID-19 infection from virulent aerosols is particularly high indoors. This is especially true for classrooms, which often do not have pre-installed ventilation and are occupied by a large number of students at the same time. It has been found that precautionary measures, such as the use of air purifiers (AP), physical distancing, and the wearing of masks, can reduce the risk of infection. To quantify the actual effect of precautions, it is not possible in experimental studies to expose subjects to virulent aerosols. Therefore, in this study, we develop a computational fluid dynamics (CFD) model to evaluate the impact of applying the aforementioned precautions in classrooms on reducing aerosol concentration and potential exposure in the presence of index or infected patients. A CFD-coupled Wells–Riley model is used to quantify the infection probability (IP) in the presence of index patients. Different cases are simulated by varying the occupancy of the room (half/full), the volumetric flow rate of the AP, two different locations of the AP, and the effect of wearing masks. The results suggest that using an AP reduces the spread of virulent aerosols and thereby reduces the risk of infection. However, the risk of the person sitting adjacent to the index patient is only marginally reduced and can be avoided with the half capacity of the class (physical distancing method) or by wearing face masks of high efficiencies.

Building a system dynamics model to analyze scenarios of COVID-19 policymaking in tourism-dependent developing countries: A case study of Cambodia

To control the COVID-19 pandemic, various policies have been implemented to restrict the mobility of people. Such policies, however, have resulted in huge damages to many economic sectors, especially the tourism sector and its auxiliary services. Focusing on Cambodia, this study presents a system dynamics (SD) model for assessing and selecting effective policy responses to contain the spread of COVID-19, while maintaining tourism development. Policies targeted in this study include international and domestic transportation bans, quarantine policy, tourist-centered protection measures, and enterprise-led protection measures. Two types of scenario analyses are conducted: one targets each policy separately and the other combines different policies. Among all scenarios, quarantine policy is evaluated to be the most effective policy as it balances the containment of the spread of COVID-19 and support for tourism development. This study provides a new way of guiding COVID-19 policymaking and exploring effective policies in the context of tourism.

Transmission Dynamics of COVID-19 with Saturated Treatment: A Case Study of Spain

In this paper, an epidemic compartmental model with saturated type treatment function is presented to investigate the transmission dynamics of COVID-19 with a case study of Spain (in Europe). We obtain the basic reproduction number of the model which plays a very important role in disease spreading. We show that if the basic reproduction number is less than unity then the disease-free equilibrium point is locally asymptotically stable, but making the basic reproduction number less than unity is not sufficient to eradicate COVID-19 infection which is shown through backward bifurcation. The model is validated with the real COVID-19 data of Spain (in Europe), Algeria (in Africa), and India (in Asia) and also estimated important model parameters in all cases. The effect of an important model parameter for controlling the disease spreading is also investigated for the infection scenario of Spain only. We establish that the asymptomatic class plays a very important role for spreading this pandemic disease. The effective reproduction number has been estimated which varies in time in Spain. Finally, the model is reformulated as an optimal control problem which shows that the social distancing due to adapting a partial lockdown by some countries is highly effective for controlling COVID-19.

Polarised social media discourse during COVID-19 pandemic: evidence from YouTube

The onset of the COVID-19 pandemic has attracted significant attention on social media platforms as these platforms provide users unparalleled access to ‘information' from around the globe. In spite of demographic differences, people have been expressing and shaping their opinions using social media on topics ranging from the plight of migrant workers to vaccine development. However, the social media induced polarisation owing to selective online exposure to information during the COVID-19 pandemic has been a major cause of concern for countries across the world. In this paper, we analyse the temporal dynamics of polarisation in online discourse related to the COVID-19. We use random network theory-based simulation to investigate the evolution of opinion formation in comments posted on different COVID-19-related YouTube videos. Our findings reveal that as the pandemic unfolded, the extent of polarisation in the online discourse increased with time. We validate our experimental model using real-world complex networks and compare consensus formation on these networks with equivalent random networks. This study has several implications as polarisation around socio-cultural issues in crises such as pandemic can exacerbate the social divide. The framework proposed in this study can aid regulatory agencies to take required actions and mitigate social media-induced polarisation.

System dynamics modeling and robustness analysis for capital-constrained supply chain under disruption

PurposeThe purpose of this study is to explore mitigation measures for cash flow interruption during the epidemic and provide decision support to ensure the regular operation and robustness of the supply chain (SC).Design/methodology/approachConsidering the scenarios of production capacity and demand disruption during the epidemic, the authors adopt system dynamics (SD) to construct a three-echelon SC financial system consisting of a core manufacturer, a capital-constrained retailer and the customer. In different interruption scenarios, through the decision adjustments of stakeholders, the differences in performance are compared to explore solutions for SC robust optimization.FindingsThe results show that partial credit guarantee (PCG) could solve cash flow interruption and maintain the regular operation of the SC. During epidemic, with the product price increases, the revenue of stakeholders and the robustness are generally negatively correlated. But when the manufacturer's production capacity is fully interrupted, increasing product price is the right decision for the retailer and could simultaneously promote performance and robustness.Originality/valueThis paper primarily focuses on the PCG under the cash flow interruption caused by epidemics. The authors adopt the supply chain finance (SCF) theory and SD method to supplement and expand existing research on interruption management of SC. It is a pioneering study to explore the robustness of the SC financial system under disruptions.

Supply Chain Resilience of Mineral Resources Industry in China

Improving the supply chain resilience of the mineral resources industry is crucial for ensuring national economic security in China. Based on the supply and demand data of China's mineral resources industry from 2002 to 2018, this study adopts system dynamics model to simulate the supply chain resilience of the mineral resources industry, the mining industry, and the smelting and processing industry under the scenario of steady economic development and the scenario of supply chain crisis. From the simulation results, the reserves of the mineral resources industry and the smelting and processing industry under the two scenarios are nearly the same, indicating that they are weakly affected by the foreign market, and both have strong resilience. The mining industry has a high dependence on imports and a lack of supply chain resilience. Under the condition of steady economic development, the output of the mining industry needs to develop at a low speed to reduce production capacity. More attention should be paid to the high level of import dependence and insufficient supply chain resilience of the mining industry. In the stable international trade situation, reserves of important minerals should be increased to alleviate the resource shortage during the supply chain crisis.

Large-eddy simulations to define building-specific similarity relationships for natural ventilation flow rates

Natural ventilation can play an important role towards preventing the spread of airborne infections in indoor environments. However, quantifying natural ventilation flow rates is a challenging task due to significant variability in the boundary conditions that drive the flow. In the current study, we propose and validate an efficient strategy for using computational fluid dynamics to assess natural ventilation flow rates under variable conditions, considering the test case of a single-room home in a dense urban slum. The method characterizes the dimensionless ventilation rate as a function of the dimensionless ventilation Richardson number and the wind direction. First, the high-fidelity large-eddy simulation (LES) predictions are validated against full-scale ventilation rate measurements. Next, simulations with identical Richardson numbers, but varying dimensional wind speeds and temperatures, are compared to verify the proposed similarity relationship. Last, the functional form of the similarity relationship is determined based on 32 LES. Validation of the surrogate model against full-scale measurements demonstrates that the proposed strategy can efficiently inform accurate building-specific similarity relationships for natural ventilation flow rates in complex urban environments.

Is technology neutral for MSEs? Interdependencies, information transparency and power imbalances in e-commerce ecosystems: Journal international de la gestion technologique

Despite the evident upsurge of e-commerce (EC) over the past decades, the peak of online demand caused by the COVID-19 pandemic, and the huge involvement of micro and small enterprises (MSEs) in the online businesses to survive, the extant literature has neglected to analyse how MSEs orchestrate their resources between internal and external investments. Past studies, also in the case of SMEs, have tended to adopt a more firm-centric perspective focusing on the organisational conditions that determine firms' performance after the usage of EC, failing to explore the inter-organisational relations between MSEs and other actors in their ecosystem. Indeed, as MSEs may suffer from liability of smallness and lack of resources, they may rely more than other actors on the nexus of relations that emerge within the digital ecosystem generated through the usage of EC platforms. By relying on 37 interviews with owners or managers of MSEs operating in the food and beverage industry, we investigate the dynamics of resource distribution between MSEs and the other actors in the EC ecosystem. We identified the changes in interdependencies, the information asymmetries, and the power imbalances related to the interplay between MSEs and other actors within the EC ecosystem.

Global Dynamics of a Within-Host COVID-19/AIDS Coinfection Model with Distributed Delays

Acquired immunodeficiency syndrome (AIDS) is a spectrum of conditions caused by infection with the human immunodeficiency virus (HIV). Among people with AIDS, cases of COVID-19 have been reported in many countries. COVID-19 (coronavirus disease 2019) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this manuscript, we are going to present a within-host COVID-19/AIDS coinfection model to study the dynamics and influence of the coinfection between COVID-19 and AIDS. The model is a six-dimensional delay differential equation that describes the interaction between uninfected epithelial cells, infected epithelial cells, free SARS-CoV-2 particles, uninfected CD4+ T cells, infected CD4+ T cells, and free HIV-1 particles. We demonstrated that the proposed model is biologically acceptable by proving the positivity and boundedness of the model solutions. The global stability analysis of the model is carried out in terms of the basic reproduction number. Numerical simulations are carried out to investigate that if COVID-19/AIDS coinfected individuals have a poor immune response or a low number of CD4+ T cells, then the viral load of SARS-CoV-2 and the number of infected epithelial cells will rise. On the contrary, the existence of time delays can rise the number of uninfected CD4+ T cells and uninfected epithelial cells, thus reducing the viral load within the host.

Estimates of Power Shortages and Affected Populations during the Initial Period of the Ukrainian-Russian Conflict

Since the outbreak of the Ukrainian-Russian conflict on 24 February 2022, Ukraine’s economy, society, and cities have been devastated and struck on multiple fronts, with large numbers of refugees fleeing to neighboring countries. The lighting systems in Ukrainian cities have been severely restricted due to Russian missile bombing and curfew policies. The power shortages adversely affected the livelihoods of the Ukrainian residents dramatically. For a timely assessment of the power shortages’ extent and the affected population in Ukraine, this study tracked the dynamics of nighttime light emissions in Ukraine based on the newly developed daily Black Marble product (VNP46A2) from NASA. The results show that the average light radiance in Ukrainian urban areas has decreased by about 37% since the eruption of the war, with Kiev city being the most dramatic region, having a post-conflict decrease of about 51%. In addition, by introducing near-real-time population data, we have implemented a survey of the affected population in Ukraine suffering from war-induced power shortages. Estimates show that about 17.3 million Ukrainian residents were affected by power shortages. In more detail, the number of children under 10 years old was about 2.35 million (about 5.24% of the total population), while the number of elderly people over 60 years old was about 3.53 million (about 7.86% of the total population). Generally, the results of this study could contribute positively to the timely assessment of the impact of the conflict and the implementation of humanitarian relief.

The Stability Analysis and Transmission Dynamics of the SIR Model with Nonlinear Recovery and Incidence Rates

In the present paper, the SIR model with nonlinear recovery and Monod type equation as incidence rates is proposed and analyzed. The expression for basic reproduction number is obtained which plays a main role in the stability of disease-free and endemic equilibria. The nonstandard finite difference (NSFD) scheme is constructed for the model and the denominator function is chosen such that the suggested scheme ensures solutions boundedness. It is shown that the NSFD scheme does not depend on the step size and gives better results in all respects. To prove the local stability of disease-free equilibrium point, the Jacobean method is used;however, Schur–Cohn conditions are applied to discuss the local stability of the endemic equilibrium point for the discrete NSFD scheme. The Enatsu criterion and Lyapunov function are employed to prove the global stability of disease-free and endemic equilibria. Numerical simulations are also presented to discuss the advantages of NSFD scheme as well as to strengthen the theoretical results. Numerical simulations specify that the NSFD scheme preserves the important properties of the continuous model. Consequently, they can produce estimates which are entirely according to the solutions of the model.

Assessing Risks in Dairy Supply Chain Systems: A System Dynamics Approach

Due to the dynamic nature of the food supply chain system, food supply management could suffer because of, and be interrupted by, unforeseen events. Considering the perishable nature of fresh food products and their short life cycle, fresh food companies feel immense pressure to adopt an efficient and proactive risk management system. The risk management aspects within the food supply chains have been addressed in several studies. However, only a few studies focus on the complex interactions between the various types of risks impacting food supply chain functionality and dynamic feedback effects, which can generate a reliable risk management system. This paper strives to contribute to this evident research gap by adopting a system dynamics modelling approach to generate a systemic risk management model. The system dynamics model serves as the basis for the simulation of risk index values and can be explored in future work to further analyse the dynamic risk’s effect on the food supply chain system’s behaviour. According to a literature review of published research from 2017 to 2021, nine different risks across the food supply chain were identified as a subsection of the major risk categories: macro-level and operational risks. Following this stage, two of the risk groups identified first were integrated with a developed system dynamics model to conduct this research and to evaluate the interaction between the risks and the functionality of the three main dairy supply chain processes: production, logistics, and retailing. The key findings drawn from this paper can be beneficial for enhancing managerial discernment regarding the critical role of system dynamics models for analysing various types of risks across the food supply chain process and improving its efficiency.

Wagner’s Law vs. Keynesian Hypothesis: Dynamic Impacts

This study analyzes the dynamics between public expenditure and economic growth in Peru for 1980Q1–2021Q4. We used quarterly time series of real GDP, public consumption expenditure, public expenditure, and the share of public expenditure to output. The variables were transformed into natural logarithms, wherein only the logarithm of public expenditure to output ratio is stationary and the others are non-stationary I1. The study of stationary time series assesses whether Wagner’s law, the Keynesian hypothesis, the feedback hypothesis, or the neutrality hypothesis is valid for the Peruvian case according to Granger causality. We found cointegration between real GDP and public expenditure, and public consumption expenditure and real GDP. Estimating error correction and autoregressive distributed lag models, we concluded that Wagner’s law and the Keynesian hypothesis are valid in the Peruvian case, expressed as dynamic processes that allow us to obtain short-run and long-run impacts, permitting the mutual sustainability of economic growth and public expenditure.

Analysis and dynamics of a mathematical model to predict unreported cases of COVID-19 epidemic in Morocco

In December 2019, in Wuhan, China, a new disease was detected, and the virus easily spread throughout other nations. March 2, 2020, Morocco announced 1st infection of coronavirus. Morocco verified a total of 653,286 cases, 582,692 recovered, 60,579 active case, and 10,015 as confirmatory fatalities, as of 4 August 2021. The objective of this article is to study the mathematical modeling of undetected cases of the novel coronavirus in Morocco. The model is shown to have disease-free and an endemic equilibrium point. We have discussed the local and global stability of these equilibria. The parameters of the model and undiscovered instances of COVID-19 were assessed by the least squares approach in Morocco and have been eliminated. We utilized a Matlab tool to show developments in undiscovered instances in Morocco and to validate predicted outcomes. Like results, until August 4, 2021, the total number of infected cases of COVID-19 in Morocco is 24,663,240, including 653,286 confirmed cases, against 24,009,954 undetected. Further, our approach gives a good approximation of the actual COVID-19 data from Morocco and will be used to estimate the undetected cases of COVID-19 in other countries of the world and to study other pandemics that have the same nature of spread as COVID-19.

Intraday Price Discovery between Spot and Futures Markets of NIFTY 50: An Empirical Study during the Times of COVID-19

The current study investigates the intraday dynamics of futures and spot markets in India. By analyzing one-minute data of Nifty 50 and the associated futures index, the study finds that both the markets are cointegrated. The results of the VECM reveal that any disequilibrium between the spot and futures market is restored by the spot market. Granger causality tests reveal that the spot and futures markets have a bidirectional causal relationship. Common factor weights and Hasbrouck’s information share (IS) reveal the greater role of the futures market in price discovery. Gonzalo and Granger's common factor model indicates that the permanent factor is made up of futures series only. Using the BEK-GARCH model, we found two-way volatility spillovers between the spot and futures markets. The futures market is found to have a greater impact in terms of volatility spillovers also. The findings of our research are relevant to investors, money managers, traders, and policymakers.

CFD Analysis of Airflow Patterns and Flow Path of Airborne Contaminants in Indoor Spaces-A Concept of Aerodynamic Containment

The purpose of a ventilation system for indoor spaces is to create a safe environment for the occupants by diluting the concentration levels of hazardous contaminants and to minimize the risk of infection due to spread of airborne pathogens. The effectiveness of ventilation system depends on several inter related factors including the supply airflow rate, number and locations of supply diffusers, and number and locations of return grilles. With the help of Computational Fluid Dynamics (CFD) analyses, this study systematically evaluates the impact of three different HVAC configurations on the airflow patterns, distribution of contaminant, and the risk of infection in a small office space with two cubicles. The HVAC configuration with a single supply and a single return can create adverse airflow patterns which can promote spread of contaminants and increase the risk of infection farther from the source. When an additional supply diffuser is introduced with the same single return, the zone of high risk of infection remained in the vicinity of the source. However, the overall risk of infection in the space remained the same. Addition of another return created aerodynamic containment zones in the space which provided easy path for the contaminated air to leave the space and reduced the overall risk of infection. Since the location of an infected individual is not known a priori, the aerodynamic containment with distributed supply and distributed return can be the best strategy for reducing the probability of infection in indoor spaces. These studies demonstrate that CFD analyses can help in identifying the potential risk of high infection due to poor airflow distribution into a space and can provide valuable insights for developing appropriate mitigation strategies to create safe indoor environment.