A roadmap for triggering the convergence of global ESG disclosure standards: lessons from the IFRS foundation and stakeholder engagement

PurposeMotivated by the growing and urgent demands for a unified set of internationally accepted, and high-quality environmental, social and governance (hereafter ESG) disclosure standards, this exploratory study aims to propose a roadmap for setting out the proper technical groundwork for global ESG disclosure standards. Design/methodology/approachAn exploratory study is conducted to gain initial understanding and insights into establishing a worldwide set of standards for reporting on sustainability, as this topic has not been extensively studied. This study examines the viewpoints of various stakeholders, including sustainability practitioners, academics and organizations focused on ESG issues, to generate knowledge that is more solid than knowledge produced when one group of stakeholders work alone. FindingsThe results revealed that there is an ongoing and incompatible debate regarding several conceptual and practical challenges for setting a unified set of ESG disclosure standards. Practical implicationsThe study results provide multidimensional insights for regulatory parties and standard-setters to develop a high-quality package of global ESG reporting standards. This, in turn, enables different groups of stakeholders to understand the firm's impact on the environment, society and economy. Originality/valueResearch into this timely and relevant global issue is considered an appealing area of study and deserves significant attention. Thereby, working on this topic merits remarkable attention. Furthermore, this exploratory article provides valuable and informative suggestions for creating a unified and high-quality set of internationally accepted sustainability reporting standards.

Computational Investigation of Hand Foot Mouth Disease Dynamics with Fuzziness

The first major outbreak of the severely complicated hand, foot and mouth disease (HFMD), primarily caused by enterovirus 71, was reported in Taiwan in 1998. HFMD surveillance is needed to assess the spread of HFMD. The parameters we use in mathematical models are usually classical mathematical parameters, called crisp parameters, which are taken for granted. But any biological or physical phenomenon is best explained by uncertainty. To represent a realistic situation in any mathematical model, fuzzy parameters can be very useful. Many articles have been published on how to control and prevent HFMD from the perspective of public health and statistical modeling. However, few works use fuzzy theory in building models to simulate HFMD dynamics. In this context, we examined an HFMD model with fuzzy parameters. A Non Standard Finite Difference (NSFD) scheme is developed to solve the model. The developed technique retains essential properties such as positivity and dynamic consistency. Numerical simulations are presented to support the analytical results. The convergence and consistency of the proposed method are also discussed. The proposed method converges unconditionally while the many classical methods in the literature do not possess this property. In this regard, our proposed method can be considered as a reliable tool for studying the dynamics of HFMD.

Identification of Evolutionary Trajectories Shared across Human Betacoronaviruses.

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, although the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), although a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1, and SARS-CoV-2), we developed a methodological pipeline to classify shared nonsynonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection and draw upon protein structure data to identify potential biological implications. We find 30 candidate mutations, from which 4 (codon sites 18121 [nsp14/residue 28], 21623 [spike/21], 21635 [spike/25], and 23948 [spike/796]; SARS-CoV-2 genome numbering) further display evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

Regional Differences, Dynamic Evolution and Convergence of Public Health Level in China.

People's health is a necessary condition for the country's prosperity. Under the background of the COVID-19 pandemic and frequent natural disasters, exploring the spatial and temporal distribution, regional differences and convergence of China's provincial public health level is of great significance to promoting the coordinated development of China's regional public health and achieving the strategic goal of a "healthy China". Based on China's provincial panel data from 2009 to 2020, this paper constructs an evaluation index system for China's public health level from five dimensions: the popularization of a healthy life, optimization of health services, improvement of health insurance, construction of a healthy environment, and development of a health industry. In this paper, the entropy method, Dagum Gini coefficient, Kernel density function and spatial econometric model are used to analyze the spatiotemporal distribution, regional differences, dynamic evolution and convergence of China's public health level since the new medical reform. The study found that, first, China's public health level is generally low, structural contradictions are prominent and the construction of a healthy environment has become a shortcoming hindering the improvement of China's public health level since the new medical reform. The public health level of the four major regions showed a spatial distribution pattern of "high in the eastern, low in the northeastern, central and western" areas. Second, the overall Gini coefficient of China's public health level showed a "V-shaped" trend of first decreasing and then rising, but the overall decrease was greater than the increase, among which the regional difference was the main source of regional differences in China's public health level, but its contribution rate showed a downward trend. Third, except for the basic maintenance of a healthy environment, the Kernel density curves of China's public health level and its sub-dimensions have shifted to the right to a certain extent, and there is no polarization phenomenon. Finally, the level of public health in China has a significant spatial correlation. Except for the northeast region, the growth rate of low-level public health provinces in China and the other three major regions is higher than that of high-level public health provinces, showing a certain convergence trend. In addition, the impact of economic development, financial pressure, and urbanization on the convergence of public health levels in the four major regions is significantly heterogeneous.

A multiconsistent computational methodology to resolve a diffusive epidemiological system with effects of migration, vaccination and quarantine.

BACKGROUND: We provide a compartmental model for the transmission of some contagious illnesses in a population. The model is based on partial differential equations, and takes into account seven sub-populations which are, concretely, susceptible, exposed, infected (asymptomatic or symptomatic), quarantined, recovered and vaccinated individuals along with migration. The goal is to propose and analyze an efficient computer method which resembles the dynamical properties of the epidemiological model. MATERIALS AND METHODS: A non-local approach is utilized for finding approximate solutions for the mathematical model. To that end, a non-standard finite-difference technique is introduced. The finite-difference scheme is a linearly implicit model which may be rewritten using a suitable matrix. Under suitable circumstances, the matrices representing the methodology are M-matrices. RESULTS: Analytically, the local asymptotic stability of the constant solutions is investigated and the next generation matrix technique is employed to calculate the reproduction number. Computationally, the dynamical consistency of the method and the numerical efficiency are investigated rigorously. The method is thoroughly examined for its convergence, stability, and consistency. CONCLUSIONS: The theoretical analysis of the method shows that it is able to maintain the positivity of its solutions and identify equilibria. The method's local asymptotic stability properties are similar to those of the continuous system. The analysis concludes that the numerical model is convergent, stable and consistent, with linear order of convergence in the temporal domain and quadratic order of convergence in the spatial variables. A computer implementation is used to confirm the mathematical properties, and it confirms the ability in our scheme to preserve positivity, and identify equilibrium solutions and their local asymptotic stability.

Dying together: A convergence analysis of fatalities during COVID-19.

Governments implemented countermeasures to mitigate the spread of the COVID-19 virus. This had a severe effect on the economy. We examine convergence patterns in the evolution of COVID-19 deaths across countries. We aim to investigate whether countries that implemented different measures managed to limit the number of COVID-19 deaths. We extend the most recent macro-growth convergence methodology to examine convergence of COVID-19 deaths. We combine a long memory stationarity framework with the maximal clique algorithm. This provides a rich and flexible club formation strategy that goes beyond the stationary/non stationary approach adopted in the previous literature. Our results suggest that strict measures (even belated) or an aggressive vaccination scheme can confine the spread of the disease while maintaining the strictness of the measures steady can lead to a burst of the virus. Finally, we observe that fiscal measures did not have an effect on the containment of the virus.

Navigating COVID-19 linguistic landscapes in Vancouver's North Shore: official signs, grassroots literacy artefacts, monolingualism, and discursive convergence

This article describes the changing linguistic landscape on the North Shore of Vancouver, British Columbia, Canada, during the first three months of the COVID-19 pandemic. I present an account of the visual representation of change along the area's parks and trails, which remained open for socially-distanced exercise during the province's lockdown. Following the principles of visual, walking ethnography, I walked through numerous locations, observing and recording the visual representations of the province's policies and discourses of lockdown and social distancing. Examples of change were most evident in the rapid addition to social space of top-down signs, characterised mainly by multimodality and monolingualism, strategically placed in ways that encouraged local people to abide by social-distancing. However, through this process of observation and exploration, I noticed grassroots semiotic artefacts such as illustrated stones with images and messages that complemented the official signs of the provincial government. As was the case with the official signs and messages, through a process of discursive convergence, these grassroots artefacts performed a role of conveying messages and discourses of social distancing, public pedagogy, and community care.

Tackling Challenges of COVID-19: An Assessment of the Convergence- Divergence Debates from the Global South-India

The World Health Organization (WHO) officially announced COVID-19 as a global pandemic in March 2020 which in effect transformed the society, economy, the politics and indeed our everyday life. Such a transformation of power geometries across all manner of spaces and their geographies disrupted the finite balance and wellbeing and continues to displace norms of equanimity, sanity, and hope amidst the catalogue of errors, blunders and inactivity. In India the first COVID-19 case was registered on January 30, 2020. The response of 29 States and 7 Union Territories of India has varied depending on their health, community, law and order and legislative infrastructure. This chapter will attempt to situate an analysis of coronavirus pandemic within the demographic transition framework of India. We examine the critical role of civil societies across the states, divergence of policies and practices relating to social distancing, contact tracing, and differential Public Health Agency infrastructures in operation across the States of India. What began as a stigma, followed by populist rhetoric quickly faded into intense struggle for survival even as oxygen, essential medicines and of course hospital beds became a premium in the most affluent parts of any given city. The grim reaper became a great leveller cutting across socially constructed boundaries of class, gender, age, caste and religion. The management of this pandemic and the established protocols for treatment remain tentative even as we learn lessons from yet another mutant strain. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

CONVERGENCE DETERMINANTS AND CLUB FORMATION IN THE EU OVER 1999-2021

Within the EU, the applied decomposition of the GDP per capita over 1999-2021 reveals that labour productivity is a dominant contributor to economic growth, followed by employment, though the impact of each factor is largely non-uniform among countries. Although the fast-converging economies benefit from productivity gains, the core EA countries have lost some of their long-term growth capacity. Despite the implemented measures, almost all EU countries experience an aggravating age structure. In 2020, digitalization was evidenced to have mitigated the negative effects of COVID-19 on productivity and employment. The estimated panel model accounts for these developments by including other relevant convergence factors such as human capital, regulatory quality and debt. The investments are empirically inferred to be a transmission channel of the positive impact of higher institutional quality and the adverse influence of higher debt stock on economic growth. While in times of high indebtedness, the expenditures on education are found to be crowded out by interests, the low debt is not necessarily associated with greater spending on education. Eventually, these inferences are graphically supported by the three-club formation derived through the K-means clustering algorithm. Although such distribution is generally in line with the neoclassical growth theory, it also reveals disturbing EU heterogeneity due to worsening demographic dynamics, rising indebtedness and insufficient regulatory quality. The derived club formation is not tightly related to EMU membership. Overall, to enhance the speed and quality of the convergence, the EU countries have to strengthen their institutional and fiscal framework. © 2023, Bulgarska Akademiya na Naukite. All rights reserved.

A Time Series Forecast of COVID-19 Infections, Recoveries and Fatalities in Nigeria

The study investigated COVID-19 pandemic infections, recoveries, and fatalities in Nigeria to forecast future values of infections, recoveries, and fatalities and thus ascertain the extent to which the pandemic appeared to be converging with time. The prediction of COVID-19 infections, recoveries, and fatalities was necessitated by the impact that the pandemic had exerted in world economies since its outbreak in late 2019. The quantitative method was employed, and a longitudinal research design was applied. Data were obtained from the Nigeria Centre for Disease Control (NCDC). The least-squares test and autoregressive distributed lag (ARDL) tests were performed to forecast infections, recoveries, and fatalities. The results of the predicted infections for the last five months of the year (August–December 2020) shows that the cases of infections will narrow down within the period. The need for policymakers to implement complete unlocking of the economy for speedy economic recovery was suggested, among others.

Regulatory Competition, Coordination and Polity Convergence in the Covid Ecosystemic Crisis: A Policy Approach

The paper briefly sketches different "adaptations” possible to address the Covid crisis and then advances three possible avenues for future policy analysis of Covid-related measures, each of these avenues being based on a "conjecture”, respectively an evolutionary, a critical, and a cosmopolitan, and conjecture. The evolutionary conjecture implies regulatory transplants, the critical conjecture elicits competition of Covid-related measures, and the cosmopolitan conjecture assumes coordination of policies. The paper discusses how these conjectures based on pre-Covid literature could explain the regulatory dynamics and then asserts that growing evidence shows that regulatory measures appear to naturally lead to a "polity convergence” based on a common core of "Covid-biopower” and "Covid-biopolitics”. This convergence defies the initial expectations that the fragmented reactions to the Covid crisis could be explained by using the traditional research tools and also poses unprecedented critical issues that demand an expansion of the horizon of policy research.

The convergence epidemic volatility index (cEVI) as an alternative early warning tool for identifying waves in an epidemic.

This manuscript introduces the convergence Epidemic Volatility Index (cEVI), a modification of the recently introduced Epidemic Volatility Index (EVI), as an early warning tool for emerging epidemic waves. cEVI has a similar architectural structure as EVI, but with an optimization process inspired by a Geweke diagnostic-type test. Our approach triggers an early warning based on a comparison of the most recently available window of data samples and a window based on the previous time frame. Application of cEVI to data from the COVID-19 pandemic data revealed steady performance in predicting early, intermediate epidemic waves and retaining a warning during an epidemic wave. Furthermore, we present two basic combinations of EVI and cEVI: (1) their disjunction cEVI + that respectively identifies waves earlier than the original index, (2) their conjunction cEVI- that results in higher accuracy. Combination of multiple warning systems could potentially create a surveillance umbrella that would result in early implementation of optimal outbreak interventions.

MOCOVIDOA: a novel multi-objective coronavirus disease optimization algorithm for solving multi-objective optimization problems.

A novel multi-objective Coronavirus disease optimization algorithm (MOCOVIDOA) is presented to solve global optimization problems with up to three objective functions. This algorithm used an archive to store non-dominated POSs during the optimization process. Then, a roulette wheel selection mechanism selects the effective archived solutions by simulating the frameshifting technique Coronavirus particles use for replication. We evaluated the efficiency by solving twenty-seven multi-objective (21 benchmarks & 6 real-world engineering design) problems, where the results are compared against five common multi-objective metaheuristics. The comparison uses six evaluation metrics, including IGD, GD, MS, SP, HV, and delta p (ΔP). The obtained results and the Wilcoxon rank-sum test show the superiority of this novel algorithm over the existing algorithms and reveal its applicability in solving multi-objective problems.

Sparse and risk diversification portfolio selection.

Portfolio risk management has become more important since some unpredictable factors, such as the 2008 financial crisis and the recent COVID-19 crisis. Although the risk can be actively managed by risk diversification, the high transaction cost and managerial concerns ensue by over diversifying portfolio risk. In this paper, we jointly integrate risk diversification and sparse asset selection into mean-variance portfolio framework, and propose an optimal portfolio selection model labeled as JMV. The weighted piecewise quadratic approximation is considered as a penalty promoting sparsity for the asset selection. The variance associated with the marginal risk regard as another penalty term to diversify the risk. By exposing the feature of JMV, we prove that the KKT point of JMV is the local minimizer if the regularization parameter satisfies a mild condition. To solve this model, we introduce the accelerated proximal gradient (APG) algorithm [Wen in SIAM J. Optim 27:124-145, 2017], which is one of the most efficient first-order large-scale algorithm. Meanwhile, the APG algorithm is linearly convergent to a local minimizer of the JMV model. Furthermore, empirical analysis consistently demonstrate the theoretical results and the superiority of the JMV model.

The short-term influences of paediatric smartphone use on the eye

The aim of this study is to comprehensively evaluate the effect of smartphone use on the eye. Twenty-two children, aged 8-16 years, participated in this study. A self-administered questionnaire about smartphone usage time, outdoor activities, and sleep time to obtain dry eye was applied to the child and parents. An ocular surface disease index (OSDI), tear break-up time (TBUT), blink time, autorefractometer, optical biometry, accommodation, contrast sensitivity, and optical coherence tomography tests were applied before a 5-min video watching, and during the video session we counted the complete -incomplete blinks. After video watching, we did the tests. After the tests, we again applied a 5-min video watching and after the video we tested all the parameters again, and finally, following a 5-min resting period, we tested the parameters again. We found no difference between the groups in terms of OSDI scores. Children with punctate epithelial erosions and time spent on the phone have a statistical relation. TBUT also differs statistically before and after test periods (p = .014), since complete blinks did not differ but incomplete blinks differed before and after video watching. The nearpoint of convergence also differs after video watching (p = .008) and anterior chamber depth (ACD) decreases even after the short-time video watching period. On the contrary, we did not find any effect of short-time smartphone watching on auto-keratometer values and retinal-choroidal thickness. This is the first comprehensive study on the short-term effects of smartphone on the paediatric age group. Even 10 min of smartphone can have an effect on TBUT, incomplete blinks, nearpoint of convergence break-recovery, and ACD. During this coronavirus disease 2019 pandemic, we must be mindful of the time our children spend on the phone and keep in mind that even 10 min can have ocular effects.

Short-term exit from pandemic restrictions: did European countries' speed converge?

Concurrently with the end of the second wave of the coronavirus pandemic, European democracies have progressively relaxed the restrictions on social mobility following the decrease in disease indexes. Did the exit speed from pandemic restrictions substantially differ across governments? This paper intends to analyze this intriguing issue, by investigating whether any convergent response of EU countries did emerge. To this aim, a convergence log-t test is performed on a panel of 25 European countries. Five different clubs emerge which suggest spatially distributed trends for relaxing stringency measures, suggesting the absence of a common European strategy to escape from the first wave pandemic. Additionally, we provide evidence of the role that economic, political, and health variables exert on these different exit strategies.

New Trends in Fuzzy Modeling Through Numerical Techniques

Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-to -person contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contra-dictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is consid-ered in this study. The equilibrium analysis and reproductive number are studied with fuzziness. Two numerical schemes forward Euler method and a nonstandard finite difference (NSFD) approach, are developed for the learned model, and the results of numerical simulations are presented. The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to support decision-making to design and develop control strategies.

Competitive Epidemic Spreading Over Networks

In this letter, we consider an epidemic model for two competitive viruses spreading over a metapopulation network, termed the 'bivirus model' for convenience. The dynamics are described by a networked continuous-time dynamical system, with each node representing a population and edges representing infection pathways for the viruses. We survey existing results on the bivirus model beginning with the nature of the equilibria, including whether they are isolated, and where they exist within the state space with the corresponding interpretation in the context of epidemics. We identify key convergence results, including the conclusion that for generic system parameters, global convergence occurs for almost all initial conditions. Conditions relating to the stability properties of various equilibria are also presented. In presenting these results, we also recall some of the key tools and theories used to secure them. We conclude by discussing the various open problems, ranging from control and network optimization, to further characterization of equilibria, and finally extensions such as modeling three or more viruses.

Pricing Strategy in an Interval-Valued Production Inventory Model for High-Tech Products under Demand Disruption and Price Revision

Due to continuous development in technology, new and updated products are launching in the market more frequently in the area of some high-tech products such as smartphones, laptops, etc. It is noticed that after a certain period of releasing a new product by a particular company some other company develops a similar type of product at a lesser selling price. Customers generally become attracted to buy that updated product causing a sudden disruption in the demand for the first product. The demand for a normal product may also suddenly vanish as we have experienced during the COVID-19 lock down period. The manufacturer is then compelled to reduce the selling price to sell the remaining products. This paper aims at developing a single period production inventory model addressing this particular market condition. This paper also considers carbon emissions from different inventory processes and examines the optimal inventory policies under the cap and trade regulatory policy. Again, in a real-life production system, the various inventory cost components and the carbon emission rates from different inventory processes are not fixed always. To incorporate this issue, the proposed model considers these quantities as interval numbers. The resulting optimization problem is thus also interval-valued and has been solved by using the quantum-behaved particle swarm optimization technique. A numerical illustration is provided to validate the proposed model. Finally, a sensitivity analysis with respect to key inventory parameters is performed to derive some key managerial implications. It is found that the frequency of launching new products is inversely proportional to the optimum profit of the manufacturer. Also, a higher carbon tax rate is found to be beneficial from an environmental point of view.

COVID Keynesianism: locating inequality in the Anglo-American crisis response

COVID Keynesianism evaluates the USA and UK's economic response to the COVID-19 pandemic and compares it to the previous iterations of the Anglo-American policy response template. The analysis details the morbid character of neoliberal state intervention by tracing the distributional routes of monetary and fiscal measures into global corporations and across the domestic economy. The comparative findings show the degree to which emergency economic relief measures, despite their size and early success, have amplified the fault lines of inequality. The argument is that monetary flows generated windfall wealth gains for the already wealthy, while fiscal flows provided temporary gains and provisions for those on low-incomes and in deprived regions. Neoliberal efforts to protect wealth-holdings are discussed with reference to the structural conditions that generate permanent crises.