Cyclic Dynamics Research Articles

Deterrence Measure: A Cause for Promoting Regional Instability in South Asia

Deterrence policies are adopted to promote stability; however, in South Asia they have worked against the notion. Instead, they have pushed the participating countries, both regional and global, into an arms race, thereby promoting regional instability. This paper therefore makes an attempt to provide narratives to explain how deterrence policies of India and Pakistan have complicated the securitization process in South Asia, and have made deterrence less unstable. In this regard, first this paper examines deterrence within a conceptual framework and the historical anecdotes that have driven both Pakistan and India into the brink of chaos. Here, we also apply Buzan and Waever’s Regional Security Complex Theory to explain the existing security complexity in the region. Next, the paper examines the deterrence policies adopted by both the nations to protect their national interests. Then the paper shows how the deterrence policies adopted by these countries have encouraged the great powers to penetrate into the region to pacify their security interests. The paper presents a cyclical dynamics to explore the interests of the regional and great powers. Finally, the paper discusses the trickle-down effect of this security complexity on regional stability, followed by actionable recommendations and a conclusion.

Is time a cyclic dimension? Canonical quantization implicit in classical cyclic dynamics

If “quantization is an art” then it can be greatly refined by adopting cyclic time formalism. In past papers we have proven the effectiveness of a formulation of physics based on cyclic relativistic time. Now we are able to demonstrate in a general way, by using theorems of Geometric Quantization, that the Poisson brackets of intrinsically cyclic time dynamics directly imply the ordinary canonical commutation relations and the other Dirac’s rules of canonical Quantum Mechanics. In other words, according to our result, the canonical quantization is an implicit way of imposing intrinsically cyclic time dynamics without explicitly saying that time is a cyclic dimension.

Genetic slippage after sex maintains diversity for parasite resistance in a natural host population.

Although parasite-mediated selection is a major driver of host evolution, its influence on genetic variation for parasite resistance is not yet well understood. We monitored resistance in a large population of the planktonic crustacean Daphnia magna over 8 years, as it underwent yearly epidemics of the bacterial pathogen Pasteuria ramosa. We observed cyclic dynamics of resistance: Resistance increased throughout the epidemics, but susceptibility was restored each spring when hosts hatched from sexual resting stages. Host resting stages collected across the year showed that largely resistant host populations can produce susceptible sexual offspring. A genetic model of resistance developed for this host-parasite system, based on multiple loci and strong epistasis, is in partial agreement with our findings. Our results reveal that, despite strong selection for resistance in a natural host population, genetic slippage after sexual reproduction can be a strong factor for the maintenance of genetic diversity of host resistance.

Mixotrophic chain elongation with syngas and lactate as electron donors.

Feeding microbial communities with both organic and inorganic substrates can improve sustainability and feasibility of chain elongation processes. Sustainably produced H2 , CO2 , and CO can be co-fed to microorganisms as a source for acetyl-CoA, while a small amount of an ATP-generating organic substrate helps overcome the kinetic hindrances associated with autotrophic carboxylate production. Here, we operated two semi-continuous bioreactor systems with continuous recirculation of H2 , CO2 , and CO while co-feeding an organic model feedstock (lactate and acetate) to understand how a mixotrophic community is shaped during carboxylate production. Contrary to the assumption that H2 , CO2 , and CO support chain elongation via ethanol production in open cultures, significant correlations (p < 0.01) indicated that relatives of Clostridium luticellarii and Eubacterium aggregans produced carboxylates (acetate to n-caproate) while consuming H2 , CO2 , CO, and lactate themselves. After 100 days, the enriched community was dominated by these two bacteria coexisting in cyclic dynamics shaped by the CO partial pressure. Homoacetogenesis was strongest when the acetate concentration was low (3.2g L-1 ), while heterotrophs had the following roles: Pseudoramibacter, Oscillibacter, and Colidextribacter contributed to n-caproate production and Clostridium tyrobutyricum and Acidipropionibacterium spp. grew opportunistically producing n-butyrate and propionate, respectively. The mixotrophic chain elongation community was more efficient in carboxylate production compared with the heterotrophic one and maintained average carbon fixation rates between 0.088 and 1.4g CO2 equivalents L-1 days-1 . The extra H2 and CO consumed routed 82% more electrons to carboxylates and 50% more electrons to carboxylates longer than acetate. This study shows for the first time long-term, stable production of short- and medium-chain carboxylates with a mixotrophic community.

Counter-surveillant organizing during the secessionist cycle of contention in Catalonia

ABSTRACT The literature on repression in social movement studies focuses mainly on protest behavior and neglects other aspects of activism. This paper expands this literature by looking at how surveillance as a covert form of repression affects organizational practices in social movements. The secessionist mobilizations around the 1 October 2017 referendum in Catalonia serve as a case study to explore this question. Semi-structured interviews with organizers from the Catalan independence movement were used to identify two surveillance threats. Organizers feared the monitoring of their digital communication and the infiltration of their assemblies. They responded to these threats with five moves of counter-surveillant organizing: encryption, face-to-face communication, analogizing meetings, committee decision making, and closingoff assemblies. How organizers perceived surveillance and responded was closely connected to the cyclical dynamics of contention over time. The five moves allowed the movement to resist surveillance at least in the short term without moderating their claims or going underground. However, they were also harmful to the Catalan independence movement’s organizing culture based on inclusivity and horizontality. These findings suggest that the consequences of repression for social movements go well beyond protest behavior and have a profound impact on their organizational practices.

Irregular population cycles driven by environmental stochasticity and saddle crawlbys

Despite considerable study of population cycles, the striking variability of cycle periods in many cyclic populations has received relatively little attention. Mathematical models of cyclic population dynamics have historically exhibited much greater regularity in cycle periods than many real populations, even when accounting for environmental stochasticity. We contend, however, that the recent focus on understanding the impact of long, transient but recurrent epochs within population oscillations points the way to a previously unrecognized means by which environmental stochasticity can create cycle period variation. Specifically, consumer–resource cycles that bring the populations near a saddle point (a combination of population sizes toward which the populations tend, before eventually transitioning to substantially different levels) may be subject to a slow passage effect that has been dubbed a ‘saddle crawlby'. In this study, we illustrate how stochasticity that generates variability in how close predator and prey populations come to saddles can result in substantial variability in the durations of crawlbys and, as a result, in the periods of population cycles. Our work suggests a new mechanistic hypothesis to explain an important factor in the irregular timing of population cycles and provides a basis for understanding when environmental stochasticity is, and is not, expected to generate cyclic dynamics with variability across periods.

Mismatch Cycles

This paper studies the cyclical dynamics of skill mismatch and quantifies its impact on labor productivity. We build a tractable directed search model, in which workers differ in skills along multiple dimensions and sort into jobs with heterogeneous skill requirements. Skill mismatch arises because of information frictions and is prolonged by search frictions. Estimated to the United States, the model replicates salient business cycle properties of mismatch. Job transitions in and out of bottom job rungs, combined with career mobility, are key to account for the empirical fit. The model provides a novel narrative for the scarring effect of unemployment.

Influence of delayed density and ultraviolet radiation on caterpillar baculovirus infection and mortality.

Infectious disease is an important potential driver of population cycles but must occur through delayed density-dependent infection and resulting fitness effects. Delayed density-dependent infection by baculoviruses can be caused by environmental persistence of viral occlusion bodies (OBs), which can be influenced by environmental factors. Specifically, ultraviolet radiation is potentially important in reducing the environmental persistence of viruses by inactivating OBs. Delayed density-dependent viral infection has rarely been observed empirically at the population level although theory predicts that it is necessary for pathogens to drive population cycles. Similarly, field studies have not examined the effects of ultraviolet radiation on viral infection rates in natural animal populations. We tested if viral infection is delayed density-dependent with the potential to drive cyclic dynamics and if ultraviolet radiation influences viral infection levels. We censused 18 Ranchman's tiger moth (Arctia virginalis) populations across 9° of latitude over 2 years and quantified the effects of direct and delayed density and ultraviolet radiation on proportion infected by baculovirus, infection severity and survival to adulthood. Caterpillars were collected from field populations and reared in the laboratory. Baculovirus has not previously been described infecting A. virginalis, and we used genetic methods to confirm the identity of the virus. We found that proportion infected, infection severity and survival to adulthood exhibited delayed density dependence. Ultraviolet radiation in the previous summer decreased infection severity, which increased caterpillar survival probability. Structural equation modelling indicated that the effect of lagged density on caterpillar survival was mediated through proportion infected and infection severity and was 2.5-fold stronger than the indirect effect of ultraviolet. We successfully amplified polh, lef-8 and lef-9 viral genes from caterpillars, and BLAST results confirmed that the virus was a nucleopolyhedrovirus. Our findings provide clear evidence that delayed density-dependent mortality can arise through viral infection rate and severity in insects, which supports the role of viral disease as a mechanism, among others, that may drive insect population cycles. Furthermore, our findings support predictions that ultraviolet radiation can modify viral disease dynamics in insect populations, most likely through attenuating viral persistence in the environment.

Investigation of the cyclic dynamics in the misfire and partial burn regime in a dilute spark-ignition engine and the role of the residual

This study compares the cycle-to-cycle dynamics in heat release between the misfire and partial burn regime in a highly lean-operated spark-ignition engine. The cyclic dynamics in these two regimes are generally deterministic as misfires and partial burns are often followed by a higher-energy cycle due to the feed-forward mechanism present in the residual gases. Both short and long-term patterns are investigated by converting the sequences into association rules. Using association rules, as opposed to symbol sequencing, allowed additional insight into the differences in the dynamics when operating in each regime. The influence of the residual amount and residual temperature on the next-cycle dynamics is also investigated using association rules. Results show there exists similar short-term dynamics between the misfire and partial burn regime. Results also indicate the residual amount impacts the next cycle more than the residual gas temperature. Understanding of the differences in the dynamics between the misfire and partial burn regime and how the residual plays a role could impact the control method used.

A Better Framework for the Assessment of Performance and Stability of Co-Adaptive Myoelectric Systems.

Co-adaptive myoelectric human-machine systems are a fairly recent, but promising, advancement in pattern recognition-based myoelectric control. Their performance and stability, however, are not fully understood due in part to a lack of proper assessment tools. Time-series based analyses are typically used despite the availability of techniques used in other fields that can robustly measure stability and performance. In this research, we leverage the success achieved by lower limb systems to improve the assessment framework of co-adaptive myoelectric systems by exploiting a key feature common between the two systems. The cyclical dynamics found in lower limbs are also apparent in co-adaptive myoelectric systems, allowing us to analyze their behavior using Poincaré maps. A 10-day experiment was designed and conducted to observe the effects of algorithm adaptation and myoelectric experience level on the performance of a co-adaptive myoelectric control system. Through Poincaré maps, we were able to identify learning effects, as well as oscillations and uncertainty in performance. Assessment of these seemingly random variations in performance led to the inference that co-adaptive systems can be chaotic. Modelling co-adaptive myoelectric systems as cyclical leads to the application of an improved framework to better assess and describe their dynamics and performance.

Experts vs. policymakers in the COVID-19 policy response

We build an evolutionary game-theoretic model of the interaction between policymakers and experts in shaping the policy response to the COVID-19 pandemic. Players’ decisions concern two alternative strategies of pandemic management: a “hard” approach, enforcing potentially unpopular measures such as strict confinement orders, and a “soft” approach, based upon voluntary and short-lived social distancing. Policymakers’ decisions may also rely upon expert advice. Unlike experts, policymakers are sensitive to a public consensus incentive that makes lifting restrictions as soon as possible especially desirable. This incentive may conflict with the overall goal of mitigating the effects of the pandemic, leading to a typical policy dilemma. We show that the selection of strategies may be path-dependent, as their initial distribution is a crucial driver of players’ choices. Contingent on cultural factors and the epidemiological conditions, steady states in which both types of players unanimously endorse the strict strategy can coexist with others where experts and policymakers agree on the soft strategy, depending on the initial conditions. The model can also lead to attractive asymmetric equilibria where experts and policymakers endorse different strategies, or to cyclical dynamics where the shares of adoption of strategies oscillate indefinitely around a mixed strategy equilibrium. This multiplicity of equilibria can explain the coexistence of contrasting pandemic countermeasures observed across countries in the first wave of the outbreak. Our results suggest that cross-country differences in the COVID-19 policy response need not be the effect of poor decision making. Instead, they can endogenously result from the interplay between policymakers and experts incentives under the local social, cultural and epidemiological conditions.

Impact of local timescales in a cellular automata model of excitable media

A cellular automata system known as the Greenberg-Hastings cellular automata (GHCA), with cyclic and excitable individual dynamics, provides a useful paradigm for modeling emergent phenomena in an excitable medium. Most past studies of GHCA have investigated the asymptotic dynamics of the system, assuming fixed extents for the active and passive dynamical phases. This study is a systematic investigation of the relationship between the dynamical properties of individual cells of a small system implementing excitable dynamics, and the emergent system wide asymptotic state. The impact of the temporal extents of individual dynamical phases (τa, τp), on the probability of persistence P(τa,τp), defined as the fraction of initial configurations which sustain spatiotemporal oscillations asymptotically, is examined for each unique configuration of the system. The main result obtained is that the probability of persistence P(τa, τp) assumes a characteristic sigmoidal form, as the dynamical behaviour of the system transitions from absolute quiescence to persistent spatiotemporal oscillations, with respect to the parameters (τa, τp). A plot of the numerical findings in the (τa, τp) space provides a consolidated view of their impact on the emergent behaviour of the system. In conclusion, some implications of the methods and results presented in this work, to the study of emergent phenomena in excitable systems, are discussed.

Factors of Economic Growth in 2011–2021 and Their Reflection in Macroeconomic Models

The article examines factors of economic growth in Russia over more than a decade (2011–2021). The focus is on evaluating new factors, including specific ones, which have influenced the development dynamics of the period under review. Models of cyclic dynamics and macroeconomic factor models are used as research tools.The authors consider possibilities for estimating potential GDP using two approaches: through the selection and elimination of short-term cyclic fluctuations and based on the construction of factor models. The paper discusses the matter of substantiating potential GDP, taking into account changes in the ratio of factors that form it, including the external economic factor. It is noted that for a more detailed analysis of specific factors, there has to be a transition to monthly and quarterly data treatment, which is done using the example of cyclic dynamics models and factor models. The nature of the impact of specific factors by specified periods, including the post-crisis period of 2011–2014, the 2014 to 2017 period, when Western countries imposed sanctions, as well as the impact in 2020–2021 of the factor associated with the coronavirus pandemic, are revealed. To be specific, for the latest period of development of the domestic economy, the paper demonstrates how three waves of COVID-19 correlate with the three waves of its impact on economy. Meanwhile, despite the increase of the coronavirus waves up to the fourth wave, their direct and conjugated impact decreased exponentially. At the same time, the impact was differentiated by industry sectors. A number of industry sectors during this period gained a significant impetus to accelerate development, which will affect the subsequent change in the structure of production.Strengthening the role of new specific factors now enhances the relevance and need to apply and develop these methods, including the active use and development of import matrices as part of the input-output tables. In this regard, the authors consider some directions in development of methods for addressing new factors at the present stage.

On the destabilizing nature of capital gains taxes

Policymakers around the world impose some form of capital gains taxes to foster the stability of financial markets. Unfortunately, there is no clarity on the effects of capital gains taxes. Based on a stylized behavioral asset-pricing model highlighting the trading activity of extrapolating speculators, we show that policymakers may involuntary destabilize financial markets by imposing capital gains taxes. Most importantly, we find that the imposition of capital gains taxes may trigger endogenous cyclical asset price dynamics occurring around inflated price levels. A number of robustness checks in which we allow for interactions between speculators who use extrapolative and regressive expectation rules confirm our main results.

Effects of intake charge temperature and relative air-fuel ratio on the deterministic characteristics of cyclic combustion dynamics of a HCCI engine

Homogenous charge compression ignition (HCCI) combustion can significantly reduce automotive pollution and increase the thermal efficiency of the engine. However, combustion phasing control is a major challenge in HCCI engines due to severe cyclic combustion variations. This study investigates the cyclic combustion dynamics of the HCCI engine using nonlinear dynamic methods such as return maps, recurrence plots (RPs), and recurrence quantitative analysis (RQA). Combustion stability and cyclic variations of HCCI combustion parameters were investigated on a modified four-stroke diesel engine. The experiments were conducted by varying relative air-fuel ratios ([Formula: see text]) and intake air temperatures ([Formula: see text]) at two engine speeds. In-cylinder pressure data of 2000 consecutive engine combustion cycles is logged for each test condition. In this study, deterministic characteristics of combustion phasing (CA50) and crank angle position of maximum cylinder pressure ([Formula: see text]) are investigated and compared by employing nonlinear dynamical methods. Return maps revealed that [Formula: see text] is having distinct and more frequently observed deterministic characteristics in comparison to CA50. Patterns in RPs showed a more persistent and sudden change in the combustion dynamics at higher engine speeds. Recurrence plot-based analysis found the existence of deterministic features in the combustion dynamics irrespective of the operating conditions. It was found using RQA parameters that the deterministic nature becomes stronger with a decrease in [Formula: see text] and any deviation in intermediate values of [Formula: see text]. Additionally, RQA measures advocate that CA50 has more deterministic characteristics at higher engine speed while [Formula: see text] at lower engine speed. Strong coupling and synchronization between [Formula: see text] and CA50 is indicated by cross-recurrence plots and CPR index when engine operated with a comparatively richer mixture.

Asymmetric host movement reshapes local disease dynamics in metapopulations

Understanding how the movement of individuals affects disease dynamics is critical to accurately predicting and responding to the spread of disease in an increasingly interconnected world. In particular, it is not yet known how movement between patches affects local disease dynamics (e.g., whether pathogen prevalence remains steady or oscillates through time). Considering a set of small, archetypal metapopulations, we find three surprisingly simple patterns emerge in local disease dynamics following the introduction of movement between patches: (1) movement between identical patches with cyclical pathogen prevalence dampens oscillations in the destination while increasing synchrony between patches; (2) when patches differ from one another in the absence of movement, adding movement allows dynamics to propagate between patches, alternatively stabilizing or destabilizing dynamics in the destination based on the dynamics at the origin; and (3) it is easier for movement to induce cyclical dynamics than to induce a steady-state. Considering these archetypal networks (and the patterns they exemplify) as building blocks of larger, more realistically complex metapopulations provides an avenue for novel insights into the role of host movement on disease dynamics. Moreover, this work demonstrates a framework for future predictive modelling of disease spread in real populations.

The “power-property” concept: Pro et contra

The analysis of the “power-property” concept and its critics shows that the question in issue is not the phenomenon itself but its intensity in a certain historical period in a certain country. Therefore, methods of theoretical history are necessary for positive knowledge accumulation in Eastern historical studies of problems of laissez-faire and dirigisme during the transition to modern economic growth. It enables to overcome the metaphysical character of reasoning, which is especially typical for the Marxists. Their conceptual framework, however, should not be applied by default — only as a metatheoretical basis for forthcoming research. The paper points out another range of issues related to both “materialistic” and “institutionalist” explanations of the “power-property” phenomenon; it is suggested to separate such issues as the origin of the phenomenon and its further reproduction. The argumentation is based on the data of the historiography of China, as well as on the key concepts of historical sociology relating to the studies of the cyclic dynamics of traditional societies.

Revisiting Paul de Grauwe’s Chaotic Exchange Rate Model: New Analytical Insights and Agent-Based Explorations

We apply recent stability and bifurcation results to provide an analytical characterization of Paul de Grauwe’s chaotic exchange rate model. We prove that the model’s fundamental steady state becomes unstable due to a Neimark-Sacker bifurcation when chartists extrapolate past exchange rate trends too strongly, a phenomenon that gives rise to cyclical exchange rate dynamics. In contrast, fundamentalists’ mean reversion strength only has a stabilizing effect on the model’s dynamics when the exchange rate is out of equilibrium. We also show that agent-based versions of Paul de Grauwe’s exchange rate model may produce endogenous exchange rate dynamics, too.

Wavelet analysis for cyclic combustion dynamics of a multi-cylinder CRDI diesel engine fuelled with a blending of argemone biodiesel-diesel oil.

Higher cyclic variability in combustion adversely influences emissions, efficiency, and driveability of internal combustion engines. In this paper, we used wavelet transform techniques to investigate the dynamical characteristics of a combustion process in numerous combustion parameters of a 4-cylinder turbocharged common rail direct injection (CRDI) diesel engine fuelled with Argemone mexicana biodiesel (AGB)/diesel blended fuel. In addition, statistical analysis is described to validate the results of the wavelet spectrum methods for cyclic variation in the diesel engine. The results show that the cyclic variations in IMEP and Pmax are sensitive to the engine load and fuel properties. The coefficient of variation of both combustion parameters decreases as engine load increases for all tested fuels. Moreover, adding Argemone mexicana biodiesel (AGB) into diesel fuel up to 20% (AB20) reduces cyclic variations in combustion parameters at all tested engine loads. Furthermore, the global wavelet spectrum and wavelet power spectrum are utilized to identify the dominant oscillatory combustion modes. The cycle-to-cycle fluctuations in combustion parameters (i.e., IMEP and Pmax) exhibit multi-scale dynamics for all experimental conditions. Compared to long and intermediate oscillations in diesel fuel, AB10 and AB20 fuel showed short and intermittent period fluctuations. The findings of this experimental work will be helpful to optimize engine control strategies for AGB/diesel blended fueled multi-cylinder CRDI diesel engines.

Application of delay embedding and recurrence analysis to a noisy nonlinear map for cyclic combustion dynamics of SI engines

A noisy nonlinear dynamical (NND) model available for cyclic variations in SI engines is examined using nonlinear time series methods. Heat release time series computed from this model is analyzed by employing bifurcation diagrams, return maps, recurrence plots, and recurrence quantitative analysis techniques. The analysis methodology is at first applied to a noisy Logistic map to optimize the necessary parameters, and later the same is used for the NND map. The presence of noise hides the local patterns of the dynamics and higher periodic orbits, making the bifurcation diagrams look fuzzy for both maps. An increase in the noise level and uncombusted residuals in the NND map advance the onset point of bifurcations toward a higher equivalence ratio. The application of the NND model is extended to represent the SI engine combustion dynamics for a higher amount of internal EGR as it is favored for cycle-resolved control due to its feedback period of one combustion cycle. The combined effect of lean charge and internal EGR leads to a more complex dynamical nature. The addition of a higher amount of internal EGR adds some complex chaotic-like regions in the bifurcation diagrams. For a low level of fluctuations in the NND map, more than four noisy periodic orbits are observed for such operating conditions. The geometry of phase space trajectories for the low-level noisy model data with a high level of internal EGR resembles a chaotic system. Bifurcation diagrams, recurrence plots, and quantitative recurrence analysis indicate an intermittent route to chaos at a highly lean and diluted charge. The presence of deterministic chaotic characteristics in combustion dynamics, along with effort-saving techniques of data acquisition and estimating combustion phasing, depicts the possibilities of practical application in active onboard control of engine systems.