A survey of methods for handling initial state shifts in iterative learning control

This paper introduces three types of controllers: a PID-type iterative learning controller, an adaptive iterative learning controller, and an optimal iterative learning controller, and reviews the history and research status of initial shifts rectifying algorithms. Initial state shifts have attracted research attention because they affect both the tracking performance and system stability. This study focuses on the current common initial shifts rectifying methods and analyzes the underlying mechanism in detail. To verify the effectiveness of the presented initial shifts rectifying algorithms, we simulated those using ideal first- and second-order systems. Finally, directions for the future development of iterative learning control (ILC) and some challenging topics related to initial shifts rectifying for ILC are presented. This article aims to introduce recent developments and advances in initial shifts rectifying algorithms and discuss the directions for their further exploration.

Does reflective equilibrium help us converge?

I address the worry that reflective equilibrium is too weak as an account of justification because it fails to let differing views converge. I take up informal aspects of convergence and operationalise them in a formal model of reflective equilibrium. This allows for exploration by the means of computer simulation. Findings show that the formal model does not yield unique outputs, but still boosts agreement. I conclude from this that reflective equilibrium is best seen as a pluralist account of justification that cannot be accused of resulting in an "anything goes" relativism.

Green total-factor energy efficiency and its convergence of industrial sub-sectors in China

Existing literature ignores to consider multiple types of pollutants when analyzing energy efficiency and its convergence. Under this background, using SuperSBM-GML model, the improved entropy method, and convergence model, this paper calculates the green total-factor energy efficiency and its evolution trend of 35 China's industrial sub-sectors considering multiple pollutants, and analyzes its convergence. The results indicate that the average score of industrial green total-factor energy efficiency is low, and there are significant differences among sub-sectors: "Utilization of waste resources" is the highest, while "Manufacture of paper and paper products" is the lowest. The green total-factor energy efficiency shows an overall upward trend from 2006 to 2021, the main driving force comes from technological progress, but numerous sub-sectors have not sufficiently caught up with existing cutting-edge technologies. Specifically, the growth rate of green total-factor energy efficiency in high-energy-consumption sub-sectors is higher than low-to-medium-energy-consumption sub-sectors. There are both σ-convergence and β-convergence in low-to-medium-energy-consumption group, indicating that development of sub-sectors is stable and outstanding. Nevertheless, the high-energy-consumption group only exhibits conditional β-convergence, revealing an imbalance in energy efficiency development. Consequently, formulating the benchmark level of energy efficiency and developing energy efficiency "leader" system are suggested for low-to-medium and high-energy-consumption sub-sectors, respectively.

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.

Club convergence analysis of fossil fuels material footprint at the global level

Material footprint is vital for playing a role in increasing the pace of climate change and the sustainability of development efforts. Fossil fuels material footprint (FFMF) remains a critical indicator of environment-friendly economic development. Fossil fuels have also retained their dominance as prominent drivers of global growth since the Industrial Revolution. FFMF levels show considerable variations in economic growth worldwide as awareness of sustainability and climate change propagates. Although biomass/carbon emission convergence have been discussed extensively in the existing literature, FFMF convergence is still scanty despite its vital role in climate change. Hence, this study adds to the existing literature by examining the convergence of FFMF for 154 countries for the period from 1970 to 2019 using club convergence analysis. The results show that FFMF converges to a single steady state, stating a symmetric decline in FFMF growth. Further, the findings from sigma and beta tests are consistent with the main results. Thus, the demonstrated convergence of FFMF directs that global efforts regarding FFMF control should be continued. Moreover, future climate change policies should also be formulated to enhance the awareness of FFMF and long-term sustainability.

Convergence analysis on a tracking differentiator used in active disturbance rejection control

This paper presents convergence analysis for a tracking differentiator of an active disturbance rejection control method which is widely applied but lacks theoretical analysis. Since a nonlinear piecewise function is used in the tracking differentiator, the convergence analysis is difficult for tracking errors. Convergence proof processes of the tracking differentiator are divided into three situations based on the nonlinear piecewise function. Tracking errors of the tracking differentiator are proved to be uniformly ultimately bounded considering three situations, and relationships between upper bounds of tracking errors and adjustment parameters are founded by a Lyapunov approach, which provides a basis for parameters adjustment. Finally, simulation and experiment results verify the effectiveness of the proposed convergence analysis.

Research on the dynamic evolution and convergence of collaborative capacity of pollution control and carbon reduction: from the perspective of whole-process governance

Under the strategic goals of achieving peak carbon neutrality, deepening the battle against pollution, and building a beautiful China, improving the collaborative capacity of pollution control and carbon reduction is an important means to achieve comprehensive green and low-carbon transformation of the social economy. Starting from the essential requirements of improving the collaborative capacity of pollution control and carbon reduction, based on the whole-process governance perspective of "source-process-end-of-pipe," build an evaluation index system, measure the collaborative capacity, quantify the spatial differences, analyze the evolution characteristics, and explore the improvement path. The study found that China's collaborative capacity of pollution control and carbon reduction is characterized by homogeneous agglomeration and unbalanced regional development. Intra-regional differences are the main source of the differences, sorting by contribution is "Eastern > Western > Central > Northeast." After taking into account the factors of green transformation of industry, the input of scientific and technological elements, and opening to the outside world, the differences have gradually narrowed. Among them, the green transformation of industry is instrumentally in bridging the gap in eastern, central, and northeastern, the input of scientific and technological elements is instrumentally in bridging the gap between regions and the eastern and northeast, and opening to the outside world is instrumentally in bridging the gap between regions and the western. The scientific measurement and improvement of this capacity will provide the factual basis and path choice for achieving the task goal of "significantly improving China's collaborative capacity of pollution control and carbon reduction by 2030," which is of great practical significance for building a higher-quality, more sustainable, and greener pattern of the collaborative capacity of pollution control and carbon reduction.

Error estimates and physics informed augmentation of neural networks for thermally coupled incompressible Navier Stokes equations

Physics Informed Neural Networks (PINNs) are shown to be a promising method for the approximation of partial differential equations (PDEs). PINNs approximate the PDE solution by minimizing physics-based loss functions over a given domain. Despite substantial progress in the application of PINNs to a range of problem classes, investigation of error estimation and convergence properties of PINNs, which is important for establishing the rationale behind their good empirical performance, has been lacking. This paper presents convergence analysis and error estimates of PINNs for a multi-physics problem of thermally coupled incompressible Navier-Stokes equations. Through a model problem of Beltrami flow it is shown that a small training error implies a small generalization error. Posteriori convergence rates of total error with respect to the training residual and collocation points are presented. This is of practical significance in determining appropriate number of training parameters and training residual thresholds to get good PINNs prediction of thermally coupled steady state laminar flows. These convergence rates are then generalized to different spatial geometries as well as to different flow parameters that lie in the laminar regime. A pressure stabilization term in the form of pressure Poisson equation is added to the PDE residuals for PINNs. This physics informed augmentation is shown to improve accuracy of the pressure field by an order of magnitude as compared to the case without augmentation. Results from PINNs are compared to the ones obtained from stabilized finite element method and good properties of PINNs are highlighted.

Spatiotemporal divergence and convergence test of green total factor productivity of grain in China: based on the dual perspective of carbon emissions and surface source pollution

The topic of grain production and quality has always been a fundamental issue for the country's livelihood. With the purpose of contributing to high-quality grain development and ensuring national food security, this paper explores the spatial and temporal evolution, regional differences and convergence of grain green total factor productivity (GTFP) in the main grain-producing regions of China from the dual perspectives of carbon emissions and surface pollution with the help of EBM-GML model, kernel density function estimation and convergence methods. The results show that (1) Grain GTFP has generally shown a positive growth trend, although there exists obvious spatial differences. (2) In terms of decomposition indices, technological progress is the source of the increase in grain GTFP. (3) There are σ convergence, absolute β convergence and conditional β convergence in the main producing region as well as in the Yellow River basin and the Yangtze River basin; there are only absolute β convergence and conditional β convergence in the Songhua River basin. Grain GTFP has a single high-efficiency convergence point, and the grain GTFP is enhancing year by year in each province, and the inter-provincial gap is shrinking.

Speed of convergence in global value chains: Forward or backward linkage

The COVID-19 pandemic is creating uncertainty that potentially causes a decline in global trade. It hampers the catching-up processes of developing countries because they are already connected through global value chains (GVCs). This study investigates the speed of convergence in GVC participation. Furthermore, we propose a forward and backward GVC participation approach to trace domestic and foreign value-added contributions and to overcome overvaluation in gross exports. We compare forward and backward linkages and determine countries' convergence speeds. We scrutinize stochastic, σ, and β-convergence using the system generalized method of moments; additionally, we use this method to address potential endogeneity issues. Using a dynamic panel approach, we investigate global convergence countries in GVCs and possible foreign direct investment (FDI) factors that may influence convergence. In addition, we analyze the early effect of the COVID-19 pandemic on the convergence rate using the recent Asian Development Bank multi-regional input-output database that covers the period 2010-2019. The results illustrate convergence in both forward and backward GVC participation; however, the convergence speed varies among group countries. A group comprising countries in the Association of Southeast Asian Nations and other countries experiences faster convergence than advanced countries in forward GVC participation. In contrast, advanced countries experience faster convergence in backward GVC participation. Furthermore, the results reveal that FDI plays a significant role in GVC participation. Overall, The COVID-19 pandemic has decreased GVC participation on average.

The Progress of the Development of a Climate-smart Agriculture in Europe: Is there Cohesion in the European Union?

The development of climate-smart agriculture (CSA) is crucial in ensuring the creation of a low-carbon society and mitigation of climate change. These tasks require concerted actions from multiple stakeholders since the very concept of CSA is rather complex and requires multi-dimensional consideration. This study defines and applies various indicators to evaluate the development of CSA in the European Union (EU). To do this, three different multi-criteria decision-making methods, namely Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR; multi-criteria optimization and compromise solution), were employed for the construction of a composite indicator. A combination of both objective (entropy) and subjective (Analytic Hierarchy Process) weighting techniques was utilized to derive the weights of the indicators. The leaders in the EU in terms of CSA are Austria, Denmark and the Netherlands, whereas the countries with the lowest levels of CSA development are Cyprus, Greece and Portugal. This study also revealed divergence in the development of these practices in the EU-24 for the period 2004-2019. Thus, a more inclusive approach is needed to ensure the spread of climate-smart ideas in European agriculture sectors.

Analysis of regional differences and spatial spillover effects of agricultural carbon emissions in China

In order to realize "double carbon" target in agriculture and high-quality development of the rural economy in China, it is crucial to study the regional differences and spatial spillover effects of agricultural carbon emissions (ACE). This paper measures ACE using panel data of 31 Chinese provinces from 2005 to 2020, examines the spatio-temporal evolution characteristics，the convergence of agricultural carbon emissions, compares and analyzes regional differences, and investigates the spatial correlation and spatial spillover effects. The study found that: (1) Total agricultural carbon emissions over the research period exhibit a rising and then reducing trend, the spatial distribution of total agricultural carbon emissions is described as high in east-central and low in west. The gap of agricultural carbon emissions is gradually declining in the east, and will eventually reach their respective steady-state levels in the west and northeast. (2) There is a strong spatial interprovincial link of ACE, which has a beneficial knock-on effect on the convergence of adjacent provinces. (3) Agricultural industrial structure, urbanization level, the size of the agricultural labor force, and the intensity of the agricultural machinery input all directly affect ACE in this province and indirectly affect ACE in adjacent provinces, with the exception of the negligible coefficient of economic development level on ACE. Hence, pertinent policy suggestions are put out to serve as a guide for reducing ACE.

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, whilst 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), whilst 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 non-synonymous 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 four [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.

Phase field modeling and computation of vesicle growth or shrinkage

We present a phase field model for vesicle growth or shrinkage induced by an osmotic pressure due to a chemical potential gradient. The model consists of an Allen-Cahn equation describing the evolution of the phase field parameter that describes the shape of the vesicle and a Cahn-Hilliard-type equation describing the evolution of the ionic fluid. We establish conditions for vesicle growth or shrinkage via a common tangent construction using free energy curves. During the membrane deformation, the model ensures total mass conservation of the ionic fluid, and we weakly enforce a surface area constraint of the vesicle. We develop a stable numerical scheme and an efficient nonlinear multigrid solver to evolve the phase and concentration fields, and we use this to evolve the fields to near equilibrium for 2D vesicles. Convergence tests confirm an [Formula: see text] accuracy for our scheme and near-optimal convergence for our multigrid solver. Numerical results reveal that the diffuse interface model captures the main features of cell shape dynamics: for a growing vesicle, there exist circle-like equilibrium shapes if the concentration difference across the membrane and the initial osmotic pressure are large enough; while for a shrinking vesicle, there exists a rich collection of finger-like equilibrium morphologies.

Physician density: will we ever close the gap?

OBJECTIVE

Physician density is a crucial element of a well-functioning health system. Previous research has investigated factors affecting country-level physician supply. To date, however, no evidence has been provided about the patterns of convergence in physician density among countries. This paper thus tested club convergence in physician density in 204 countries worldwide from 1990 to 2019. A nonlinear time-varying factor model was adopted to identify potential clubs, wherein groups of countries tend to converge towards the same level of physician density. Our primary purpose was to document the potential long-lasting disparity in future global physician distribution.

RESULTS

Despite physician density increasing in all regions globally from 1990 to 2019, we found no evidence in favor of the hypothesis of global convergence. Conversely, the clustering algorithm successfully identified three main patterns (i.e., three final clubs). With few exceptions, the results indicated an uneven physician distribution between the majority of North and Sub-Saharan African countries (where physician density would remain well below the estimated threshold of at least 70% of the Universal Health Coverage Services Index) and the rest of the world. These findings support the WHO's global strategy to reverse the chronic under-investment in human resources for health.

Spatio-temporal efficiency of fiscal environmental expenditure in reducing CO2 emissions in China's cities

Although market-based CO₂ emission control measures (e.g., carbon tax and carbon trading market) have been deeply discussed, government-based measures have received limited attention. This has led to increased uncertainty regarding the formulation of targeted emission reduction policies. Using a unique dataset, the non-radial directional distance function, a proposed spatial meta-frontier analysis method, and the log t convergence model, this study comprehensively investigates the spatio-temporal trends in fiscal environmental expenditure efficiency (FE) and corresponding causes for in a case study for 106 Chinese cities over 2007-2019. The results show that city-level FE presented a slow upward trend at a relatively low level, with a clearly skewed distribution. The technology gap effect between city groups and the overall best production technology, and the efficiency gap effect within city groups were the main drivers widening the overall FE gap. Convergence analysis indicated that three convergence clubs of FE were found, which were distributed across the country. This study highlights that, when constructing fiscal environmental expenditure policies, the government should focus on balancing the regional gap of FE while comprehensively improving FE.

Health outcome convergence in Africa: the roles of immunization and public health spending

BACKGROUND

Reducing health outcomes disparities in Africa is a major concern for policymakers. Inter-country disparities in Africa is well documented. However, little is known about the accurate trajectory of these disparities over time. Thus, this paper investigates the convergence hypothesis in health outcomes in 40 African countries using data from the World Development Indicators. The study used panel data from 2000 to 2019.

METHOD

The study employs a nonlinear time-varying factor model to test the convergence hypothesis on infant mortality rate, under-five mortality, and life expectancy at birth. Then, we use the marginal effects of the ordered logit regression model to investigate the factors that explain club memberships.

RESULTS

The findings showed the absence of overall convergence for the three variables of interest. However, we identified the presence of convergence clubs. Moreover, we observed substantial gaps between the estimated clubs. The marginal effect results reveal that real GDP per capita, population structure, urbanization, trade, access to basic sanitation, and external health expenditure are essential to club formation. In addition, DTP immunization and the general government health expenditure as a percentage of the general government expenditure (our Abuja Declaration instrument) also play a significant role in explaining the club membership.

CONCLUSION

The findings suggest that policymakers should develop and implement targeted club-specific health policies. Furthermore, interventions to promote increased immunization, particularly among children, should be encouraged. Governments should also make substantial efforts to increase the share of their national budget allocated to the health sector by at least 15 percent.

Energy poverty and the convergence hypothesis across EU member states

Energy poverty is an emerging issue towards global affairs. Currently, the development of energy-related policies is becoming essential, with regard to new societies, social inclusion and social rights. In this paper, we examine the dynamic patterns of energy poverty among 27 EU member states between 2005 and 2020. We use the log-t regression test to investigate the convergence hypothesis, and the P&S data-driven algorithm to detect potential convergence clubs. The empirical results of energy poverty indicators are mixed, and the convergence hypothesis of the states is rejected. Instead, convergence clubs are exhibited, implying that groups of countries converge to different steady states in the long run. In view of the convergence clubs, we suggest that the affordability of heating services is potentially explained by structural conditions of housing, climate conditions and energy costs. Besides, the adverse financial and social conditions for the European households have significantly triggered the arrears on utility bills. Moreover, a significant proportion of households do not have basic sanitation services.

The approximate functional equation of some Diophantine series

We prove that a family of Diophantine series satisfies an approximate functional equation. It generalizes a result by Rivoal and Roques and proves an extended version of a conjecture posed in their paper. We also characterize the convergence points.

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 (Δ P ). 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.

Convergence of per capita ecological footprint among BRICS-T countries: evidence from Fourier unit root test

In recent years there has been a great deal of research into environmental pollution using a variety of techniques in response to growing environmental concerns. Convergence analysis, one of these techniques, helps determine whether the developing countries will catch up with the rich countries in pollution using unit root tests. However, the vast majority of the research in the field has generally used conventional unit root tests. Since many economic series contain structural breaks, using unit root tests that account for structural breaks is essential for accurate prediction. More specifically, if the series has a fractional process, conventional unit root tests may erroneously conclude that the departure from linearity is permanent. Moreover, the existing literature mainly uses gas emissions, such as carbon dioxide, which represent pollution weakly. Therefore, we use per capita ecological footprint (EF hereafter) as a more comprehensive pollution indicator of environmental degradation. In this direction, the study aims to determine whether BRICS-T countries' EF converges to the average of the BRICS-T for the 1992-2017 period. Besides the ADF unit root test, we employed the Fourier ADF unit root test, which considers the structural breaks, and the Fractional Frequency Fourier ADF unit root test, which accounts for structural breaks by considering fractional values. Our results showed that EF converges in Russia and Turkey according to the conventional ADF test, in China and Russia according to the Fourier ADF test, and in Brazil and China according to the Fractional Fourier Frequency test.

Health expenditure convergence and the roles of trade and governance in Africa

This study investigates the convergence hypothesis in health expenditures in 40 African countries over the 2000-2019 period. The new non-linear dynamic factor model is used on panel data extracted from the World Development Indicator and the World Governance Indicator. We consider two categories of health expenditures: the domestic general government health expenditure as a percentage of government expenditure and the domestic general government health expenditure per capita. The results show the absence of full panel convergence for the two indicators used. However, there is evidence of convergence clubs. The overall marginal effect of the control variables is consistent with the existing literature. The results further show a strong influence of trade in attaining convergence among the clubs for both models. However, governance quality only affects the probability of converging in a club for the general government health expenditure as a percentage of government expenditure model. The findings suggest that policies on promoting health expenditure convergence should pursue initiatives that encourage trade. Efforts should also be targeted to improve the quality of governance.

A direct discretization recurrent neurodynamics method for time-variant nonlinear optimization with redundant robot manipulators

Discrete time-variant nonlinear optimization (DTVNO) problems are commonly encountered in various scientific researches and engineering application fields. Nowadays, many discrete-time recurrent neurodynamics (DTRN) methods have been proposed for solving the DTVNO problems. However, these traditional DTRN methods currently employ an indirect technical route in which the discrete-time derivation process requires to interconvert with continuous-time derivation process. In order to break through this traditional research method, we develop a novel DTRN method based on the inspiring direct discrete technique for solving the DTVNO problem more concisely and efficiently. To be specific, firstly, considering that the DTVNO problem emerging in the discrete-time tracing control of robot manipulator, we further abstract and summarize the mathematical definition of DTVNO problem, and then we define the corresponding error function. Secondly, based on the second-order Taylor expansion, we can directly obtain the DTRN method for solving the DTVNO problem, which no longer requires the derivation process in the continuous-time environment. Whereafter, such a DTRN method is theoretically analyzed and its convergence is demonstrated. Furthermore, numerical experiments confirm the effectiveness and superiority of the DTRN method. In addition, the application experiments of the robot manipulators are presented to further demonstrate the superior performance of the DTRN method.

Earth Systems to Anthropocene Systems: An Evolutionary, System-of-Systems, Convergence Paradigm for Interdependent Societal Challenges

Humans have made profound changes to the Earth. The resulting societal challenges of the Anthropocene (e.g., climate change and impacts, renewable energy, adaptive infrastructure, disasters, pandemics, food insecurity, and biodiversity loss) are complex and systemic, with causes, interactions, and consequences that cascade across a globally connected system of systems. In this Critical Review, we turn to our "origin story" for insight, briefly tracing the formation of the Universe and the Earth, the emergence of life, the evolution of multicellular organisms, mammals, primates, and humans, as well as the more recent societal transitions involving agriculture, urbanization, industrialization, and computerization. Focusing on the evolution of the Earth, genetic evolution, the evolution of the brain, and cultural evolution, which includes technological evolution, we identify a nested evolutionary sequence of geophysical, biophysical, sociocultural, and sociotechnical systems, emphasizing the causal mechanisms that first formed, and then transformed, Earth systems into Anthropocene systems. Describing how the Anthropocene systems coevolved, and briefly illustrating how the ensuing societal challenges became tightly integrated across multiple spatial, temporal, and organizational scales, we conclude by proposing an evolutionary, system-of-systems, convergence paradigm for the entire family of interdependent societal challenges of the Anthropocene.

Self-Generated Motives of Social Casino Gamers

Social casino games have achieved widespread popularity, and are accessed by more than 85 million people each day. Yet, why people play social casino games is largely unknown. To address this gap, an inductive approach was taken to better understand the motives for playing social casino games, as well as the motives for transitioning from social casino gaming to gambling and vice versa. To this end, 269 social casino gamers were asked to provide a ranked list of their motives for playing social casino games. Additionally, we asked participants their motivations for transitioning from gambling to social casino gaming (n = 202) or vice versa (n = 67). A total of 795, 605, and 201 unique responses describing motives for playing social casino games, transitioning from social casino gaming to gambling, and transitioning from gambling to social casino gaming, respectively, were analyzed using a thematic content analysis. The most frequently endorsed motive for playing social casino games was for enhancement (e.g., fun, challenge). Participants also noted playing to earn rewards, including money, and for social reasons. Several motives linked social casino game play to gambling. These included: to hone gambling-related 'skills', a desire to transition to gambling to win real money, and as a gambling harm-reduction strategy. Motives for playing social casino games did not differ significantly between those who first gambled and then transitioned to social casino gaming and vice versa, suggesting that once people begin playing social casino games, they have similar motives for continued engagement. The present study contributes to understanding the immense popularity of social casino games and their links to gambling.