Interactions In Complex Systems Research Articles

Precipitation Variations in the Central Qilian Mountains since the 7th Century and Regional Differences: Evidence from Tree-Ring Data

The Qilian Mountains, located in northwest China and serving as a crucial water recharge area, have exhibited significant regional differences in precipitation patterns in recent decades. However, the limited temporal coverage of instrumental data has hindered a deep understanding of hydroclimate variations and regional differences. Further investigation into their long-term spatial and temporal precipitation characteristics is urgently needed. In this study, a new tree-ring-width chronology spanning 1743 years was established in the central Qilian Mountains using Qilian juniper (Juniperus przewalskii Kom.) samples. Significant correlations were found between the tree-ring indices and precipitation during both the growing and pre-growing seasons. Based on these correlations, annual precipitation from August of the previous year to July of the current year was reconstructed. The reconstruction model successfully explains 34.5% of the variation in precipitation during the calibration period. The analysis of the reconstructed series reveals notable interannual to multi-decadal dry–wet variability during the period from 614 AD to 2016 AD. The mid- to late-15th century emerges as the longest-lasting dry period, while the last decade stands out as the wettest. Comparative analysis with other precipitation reconstructions in the eastern and western Qilian Mountains reveals that regional drought events tend to be more pronounced and enduring. Low-frequency fluctuations on decadal to century scales show distinct wet and dry periods in the 12th–18th centuries in both the eastern and western parts of the Qilian Mountains, with weaker fluctuations in subsequent centuries. However, the central part of the Qilian Mountains exhibits opposite trends, possibly due to the complex interactions of multiple circulation systems.

Higher-Order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes

Despite the recent successes of vanilla Graph Neural Networks (GNNs) on various tasks, their foundation on pairwise networks inherently limits their capacity to discern latent higher-order interactions in complex systems. To bridge this capability gap, we propose a novel approach exploiting the rich mathematical theory of simplicial complexes (SCs) - a robust tool for modeling higher-order interactions. Current SC-based GNNs are burdened by high complexity and rigidity, and quantifying higher-order interaction strengths remains challenging. Innovatively, we present a higher-order Flower-Petals (FP) model, incorporating FP Laplacians into SCs. Further, we introduce a Higher-order Graph Convolutional Network (HiGCN) grounded in FP Laplacians, capable of discerning intrinsic features across varying topological scales. By employing learnable graph filters, a parameter group within each FP Laplacian domain, we can identify diverse patterns where the filters' weights serve as a quantifiable measure of higher-order interaction strengths. The theoretical underpinnings of HiGCN's advanced expressiveness are rigorously demonstrated. Additionally, our empirical investigations reveal that the proposed model accomplishes state-of-the-art performance on a range of graph tasks and provides a scalable and flexible solution to explore higher-order interactions in graphs. Codes and datasets are available at https://github.com/Yiminghh/HiGCN.

Generalized decomposition of multivariate information.

Since its introduction, the partial information decomposition (PID) has emerged as a powerful, information-theoretic technique useful for studying the structure of (potentially higher-order) interactions in complex systems. Despite its utility, the applicability of the PID is restricted by the need to assign elements as either "sources" or "targets", as well as the specific structure of the mutual information itself. Here, I introduce a generalized information decomposition that relaxes the source/target distinction while still satisfying the basic intuitions about information. This approach is based on the decomposition of the Kullback-Leibler divergence, and consequently allows for the analysis of any information gained when updating from an arbitrary prior to an arbitrary posterior. As a result, any information-theoretic measure that can be written as a linear combination of Kullback-Leibler divergences admits a decomposition in the style of Williams and Beer, including the total correlation, the negentropy, and the mutual information as special cases. This paper explores how the generalized information decomposition can reveal novel insights into existing measures, as well as the nature of higher-order synergies. We show that synergistic information is intimately related to the well-known Tononi-Sporns-Edelman (TSE) complexity, and that synergistic information requires a similar integration/segregation balance as a high TSE complexity. Finally, I end with a discussion of how this approach fits into other attempts to generalize the PID and the possibilities for empirical applications.

Detangling Solvatochromic Effects by the Effective Fragment Potential Method.

Understanding molecular interactions in complex systems opens avenues for the efficient design of new materials with target properties. Energy decomposition methods provide a means to obtain a detailed picture of intermolecular interactions. This work introduces a molecular modeling approach for decomposing the solvatochromic shifts of the electronic excited states into the contributions of the individual molecular fragments of the environment surrounding the chromophore. The developed approach is implemented for the QM/EFP (quantum mechanics/effective fragment potential) model that provides a rigorous first-principles-based description of the electronic states of the chromophores in complex polarizable environments. On the example of two model systems, water pentamer and hydrated uracil, we show how the decomposition of the solvatochromic shifts into the contributions of individual solvent water molecules provides a detailed picture of the intermolecular interactions in the ground and excited states of these systems. The analysis also demonstrates the nonadditivity of solute-solvent interactions and the significant contribution of solute polarization to the total values of solvatochromic shifts.

Heat Inactivation of Nipah Virus for Downstream Single-Cell RNA Sequencing Does Not Interfere with Sample Quality.

Single-cell RNA sequencing (scRNA-seq) technologies are instrumental to improving our understanding of virus-host interactions in cell culture infection studies and complex biological systems because they allow separating the transcriptional signatures of infected versus non-infected bystander cells. A drawback of using biosafety level (BSL) 4 pathogens is that protocols are typically developed without consideration of virus inactivation during the procedure. To ensure complete inactivation of virus-containing samples for downstream analyses, an adaptation of the workflow is needed. Focusing on a commercially available microfluidic partitioning scRNA-seq platform to prepare samples for scRNA-seq, we tested various chemical and physical components of the platform for their ability to inactivate Nipah virus (NiV), a BSL-4 pathogen that belongs to the group of nonsegmented negative-sense RNA viruses. The only step of the standard protocol that led to NiV inactivation was a 5 min incubation at 85 °C. To comply with the more stringent biosafety requirements for BSL-4-derived samples, we included an additional heat step after cDNA synthesis. This step alone was sufficient to inactivate NiV-containing samples, adding to the necessary inactivation redundancy. Importantly, the additional heat step did not affect sample quality or downstream scRNA-seq results.

Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management

Organizations are increasingly leveraging the ability of artificial intelligence to analyze and resolve complex problems. This can potentially reshape the interdependencies and interactions of complex systems, leading to our research question: To what extent and in which direction is the literature on Artificial Intelligence (AI) and System Dynamics (SD) converging within the business and management landscape? We conducted an extensive literature review using bibliometric and topic modeling methods to address this question. Through a bibliometric analysis, we identified the areas in which academic papers referred to both SD and AI literature. However, bibliometrics do not show a clear path towards convergence. The top modeling analysis highlights more details on how convergence is structured, providing insights into how SD and AI may be integrated. Two trajectories are identified. In the “soft convergence,” AI supports system dynamics analysis and modeling more deeply characterized by social interaction. In the “hard convergence,” AI shapes innovative ways of rethinking system design, dynamics, and interdependencies. Our analysis suggests that while soft convergence is more visible in the business and management landscape, hard convergence may well represent a new frontier in studying system dynamics with the potential to reshape the landscape.

Hierarchical data synchronous interaction in nonlinear complex systems

Nonlinear complex systems are widely used in various industries, and the complexity and dynamism of the systems pose enormous challenges to data synchronization and interaction. This study proposes a method based on signal synchronization for data synchronization and interaction in nonlinear complex systems. The synchronization interaction path of data was analyzed, and signals were used as the carrier for data synchronization. The data synchronization interaction was carried out by combining the main synchronization signal and the auxiliary synchronization signal. Furthermore, mean filtering was introduced for signal filtering, and the main synchronization process was divided into two parts: coarse and fine tuning. The experimental results showed that the main synchronization frequency deviation of the research method was 303 Hz when the main synchronization completion rate was 100% in a −15 dB signal-to-noise ratio environment. In the analysis of data synchronization success rate, the research method achieved a highest success rate of 99.7% when the data transmission density was 50 pieces per minute. The experiment shows that the research method can effectively improve the quality and efficiency of data synchronization and interaction in nonlinear complex systems.

Simultaneous adsorption of amoxicillin and ciprofloxacin on agricultural soils and by-products used as bio-adsorbents: Unraveling the interactions in complex systems

The presence of pharmaceuticals in agricultural soils, like amoxicillin (AMX) and ciprofloxacin (CIP), poses a significant environmental challenge with potential implications for ecosystems and human well-being. This study explores the simultaneous adsorption of AMX and CIP on crop soils and bio-adsorbents, focusing on competitive adsorption dynamics. Tests were conducted with varying pharmaceutical concentrations in six soils and three bio-adsorbents. CIP consistently exhibited higher adsorption than AMX, particularly at higher concentrations. In the binary system, AMX's adsorption exceeded the individual system at higher concentrations, implying a synergistic effect. Bio-adsorbents, especially pine bark and oak ash, displayed superior adsorption capacities compared to soils. Some soils exhibited enhanced adsorption and retention of both antibiotics simultaneously, aligning with the cooperative adsorption model. Freundlich's adsorption model described the competitive adsorption systems well. These findings have implications for addressing antibiotic contamination in agricultural ecosystems, offering insights into complex interactions in soil environments amid rising pharmaceutical concerns.

Regarding the specifics of the definition of "medical insurance" and "insurance medicine" in the legal field

The use of the terms “health insurance” and “medical insurance” is quite widespread, sometimes without an understanding of the essential differences in terminological constructs. This vague usage is facilitated by the limited or absent (regarding health insurance) normative documents in which these categories would be treated as legal concepts. Confusion in understanding the concepts of medical insurance and health insurance generates a substitution of concepts and a shift of emphasis, where features characteristic of the public legal field are attributed to the private legal relationship of personal insurance. The article distinguishes between the concepts of “medical insurance” and “health insurance.” It highlights the existing problems of providing medical services based on insurance principles and concepts. The differences in the legal nature of the terminological constructs “medical insurance” and “health insurance” are analyzed The given definition of the “healthcare sphere” refers to a system of social relations that arise between government authorities and local self-government bodies, businesses, institutions, and organizations, as well as individuals and the population as a whole, concerning the prevention of illnesses, the preservation of health, the development of rehabilitation assistance, and the attainment of the highest possible level of physical and mental well-being in the human body. These social relations can be organized into a complex system of interactions based on the mechanism of medical insurance, which is subsequently referred to as “health insurance.” Therefore, we agree that “health insurance” is a term used to denote the organization of the healthcare sphere, and “medical insurance” is one of the mechanisms of such organization.

Globalisation of Culture in the Context of Dynamics of Socio-Cultural Systems

The purpose of the article is to examine the processes of globalisation in the field of culture in the context of the dynamics of socio-cultural systems, also mediated by the effects of globalism. Research methodology. The principles of the dialectical method are the basis of the research methodology. The study of globalisation in the field of culture and the analysis of the dynamics of socio-cultural systems is carried out using an interdisciplinary approach. In the study of globalisation as an open, self-developing system, the synergistic method is applied. The study also uses the methods of theoretical generalisation, analysis, and synthesis; structural and systemic methods, as well as cultural methods, which allowed for a comprehensive consideration of the specified problem and achievement of the relevant research results. The scientific novelty lies in the systematisation and generalisation of the main trends of the globalisation of culture and the dynamics of socio-cultural systems mediated by globalisation influences. Conclusions. Globalisation is one of the most pressing issues of contemporary research, due to both the interdisciplinary nature of the concept of globalisation and the multidimensionality and multifacetedness of this phenomenon. The dialectic of the complex interaction of all systems and components of social interaction leads to a configuration where a universal global culture is formed in parallel with the preservation of a wide and heterogeneous set of local cultures, which are non-linear processes. Globalisation generates new demarcation lines, new localities that do not coincide with the traditional ones – local, regional, national, ethnic, and others. Historically complex multi-level interrelationships, being the source of the development of globalisation processes, form its dialectical nature: on the one hand, internationalisation and globalisation are expanding and deepening, and on the other hand, processes of the opposite direction are actively developing. The dynamics of socio-cultural systems in the context of globalisation is determined by synergistic interactions of open complex systems, which, in the presence of external and internal determinants, are capable of qualitative transformations and changes within the system, producing the corresponding dynamics of transformational changes.
 Key words: globalisation, glocalisation, socio-cultural systems, culture system, nonlinearity, synergy.

The Antioxidant and Prebiotic Activities of Mixtures Honey/Biomimetic NaDES and Polyphenols Show Differences between Honeysuckle and Raspberry Extracts.

In our previous research, we demonstrated that honey and its biomimetic natural deep eutectic solvent (NaDES) modulate the antioxidant activity (AOA) of the raspberry extract (RE). In this study, we evaluated the AOA behaviour of the mixture honey/NaDES-honeysuckle (Lonicera caprifolium, LFL) extract and compared it with the mixture honey/NaDES-RE. These two extracts have similar major flavonoids and hydroxycinnamic acid compounds but differ in their total content and the presence of anthocyanins in RE. Therefore, it was of interest to see if the modulation of the LFL polyphenols by honey/NaDES was similar to that of RE. We also evaluated the prebiotic activity of these mixtures and individual components on Limosilactobacillus reuteri DSM 20016. Although honey/NaDES modulated the AOA of both extracts, from synergism to antagonism, the modulation was different between the two extracts for some AOA activities. Honey/NaDES mixtures enriched with LFL and RE did not show significant differences in bacterial growth stimulation. However, at a concentration of 45 mg/mL, the honey -LFL mixture exhibited a higher effect compared to the honey-RE mixture. The antioxidant and prebiotic properties of mixtures between honey and polyphenol-rich extracts are determined by multiple interactions in complex chemical systems.

The Connection Between Circadian Disruption and Cancer Risks

The circadian rhythm is an essential biological mechanism that uses the 24-hour geophysical cycle to regulate thebody’s physiological and behavioral processes. It operates on a complex molecular interaction system that coordinatesgene expression, protein synthesis, and post-translational modifications. Disruption of this rhythm due to jet lag, shiftwork, and other unhealthy lifestyles has been linked to various health disorders, including cancer. Recent studies havesuggested a strong association between circadian disruption and development cancers, such as breast cancer, lungcancer, and glioblastoma. Understanding the connection between circadian disruption and cancer and the mechanismsunderlying this connection is essential for developing new cancer therapies. In this review, we provide an updatedaccount of key circadian mechanisms and their regulations on human health. We examine the adverse impact ofcircadian disruption on health using lung cancer and glioblastoma as case studies. Finally, we also discuss the potentiallypromising cancer treatment of chronotherapy, which targets components of the circadian cycle. We believe that futureresearch into circadian rhythm and cancer would encourage the progression into a new era of cancer medicine.

Effective Brain Connectivity Extraction by Frequency-Domain Convergent Cross-Mapping (FDCCM) and Its Application in Parkinson's Disease Classification.

Inferring causal or effective connectivity between measured timeseries is crucial to understanding directed interactions in complex systems. This task is especially challenging in the brain as the underlying dynamics are not well-understood. This paper aims to introduce a novel causality measure called frequency-domain convergent cross-mapping (FDCCM) that utilizes frequency-domain dynamics through nonlinear state-space reconstruction. Using synthesized chaotic timeseries, we investigate general applicability of FDCCM at different causal strengths and noise levels. We also apply our method on two resting-state Parkinson's datasets with 31 and 54 subjects, respectively. To this end, we construct causal networks, extract network features, and perform machine learning analysis to distinguish Parkinson's disease patients (PD) from age and gender-matched healthy controls (HC). Specifically, we use the FDCCM networks to compute the betweenness centrality of the network nodes, which act as features for the classification models. The analysis on simulated data showed that FDCCM is resilient to additive Gaussian noise, making it suitable for real-world applications. Our proposed method also decodes scalp-EEG signals to classify the PD and HC groups with approximately 97% leave-one-subject-out cross-validation accuracy. We compared decoders from six cortical regions to find that features derived from the left temporal lobe lead to a higher classification accuracy of 84.5% compared to other regions. Moreover, when the classifier trained using FDCCM networks from one dataset was tested on an independent out-of-sample dataset, it attained an accuracy of 84%. This accuracy is significantly higher than correlational networks (45.2%) and CCM networks (54.84%). These findings suggest that our spectral-based causality measure can improve classification performance and reveal useful network biomarkers of Parkinson's disease.

Design for Narrative Change. A Pedagogical Model for Interactive Digital Narratives

AbstractNarratives mirror shared interpretations of the world. Still, dominant narratives prevail, pushing non‐hegemonic narratives in the corner. A change in the creation, interaction and distribution of narratives can support the design of counter‐narratives able to feed social change. Interactive Digital Narrative (IDN) can be considered an emerging experimental context in which designers, researchers and practitioners from various domains operate to develop story‐based content addressing relevant social or societal issues. The IDN social constructivist role in encouraging or influencing individuals and collectivities towards social change is a relevant design issue especially from an educational perspective. Specifically, it features methodologies and praxis not yet systematised, in need of exploration and formalisation. Recognising the contribution of an approach combining transdisciplinary methods and tools, the article presents a pedagogical model for designing IDNs as complex interactive systems able to impact culture and society based on empirical study from a design course in the higher education context. Composed of theoretical and operational frameworks, the pedagogical model orients the multilayered design process for building engaging, interactive narrative artefacts systematising and operationalising knowledge from the domains of Communication for Social Change, storytelling and IDN in an iterative design process.

Describing complex interactions of social-ecological systems for tipping point assessments: an analytical framework

Humans play an interconnecting role in social-ecological systems (SES), they are part of these systems and act as agents of their destruction and regulation. This study aims to provide an analytical framework, which combines the concept of SES with the concept of tipping dynamics. As a result, we propose an analytical framework describing relevant dynamics and feedbacks within SES based on two matrixes: the “tipping matrix” and the “cross-impact matrix.” We take the Southwestern Amazon as an example for tropical regions at large and apply the proposed analytical framework to identify key underlying sub-systems within the study region: the soil ecosystem, the household livelihood system, the regional social system, and the regional climate system, which are interconnected through a network of feedbacks. We consider these sub-systems as tipping elements (TE), which when put under stress, can cross a tipping point (TP), resulting in a qualitative and potentially irreversible change of the respective TE. By systematically assessing linkages and feedbacks within and between TEs, our proposed analytical framework can provide an entry point for empirically assessing tipping point dynamics such as “tipping cascades,” which means that the crossing of a TP in one TE may force the tipping of another TE. Policy implications: The proposed joint description of the structure and dynamics within and across SES in respect to characteristics of tipping point dynamics promotes a better understanding of human-nature interactions and critical linkages within regional SES that may be used for effectively informing and directing empirical tipping point assessments, monitoring or intervention purposes. Thereby, the framework can inform policy-making for enhancing the resilience of regional SES.

FEATURES OF SOCIO-CULTURAL ANALYSIS OF THE PHENOMENON OF MULTIMEDIA IN THE MODERN INFORMATION SPACE

The article examines the socio-cultural aspects of multimedia development, gives a general idea of various information products and means of their development, the use of multimedia technologies in many fields of activity, reveals their essence and internal content. They are considered as a complex, open and flexible system with its own specific aspects that determine the specifics of the multimedia phenomenon in culture, and internal and external system-forming factors that determine its self-regulation, isolation and development, attempts are made to pay attention to its applied significance. Consideration of the specifics of multimedia culture is carried out through the interaction of complex systems with the fruits of complex, human creative possibilities, such as culture, art, in which there is a special product of society and spiritual being. The paper reflects the necessity and possibility of optimizing the multimedia system, which is beginning to take its special place in cultural and social life. According to the results of the study, it is concluded that multimedia is not just a product of the technological revolution, but a new form of artistic creativity that acts as a digital expression of ideas that have existed in countless forms of art and activity for thousands of years.

Communication system between Russian energy companies and the Indigenous peoples of the North

The regions of activity of energy companies are also the traditional areas of residence of the Indigenous peoples of the North (IPN). Commercial activities in these territories violate the environment and adversely impact the lives of the IPN. This study seeks to fill a gap regarding the position the IPN take while communicating with energy companies and the representative image the energy companies hold of the IPN. We consider the complex process of communication between oil companies and the IPN; the role assigned to the IPN in this process; the strategies adopted to preserve the IPN and why these strategies are prioritized; and the implications of the concept of “traditional life” of the IPN for each of the participants in the communication process. We analyzed the period 2010–2020 as it reflects the current situation.We applied the hermeneutic method by comparing data from the reports of Gazprom, Lukoil, and Rosneft; analyzed documents related to the socio-economic development of the respective Russian regions; and used information from the official websites of organizations representing the interests of the IPN.In the complex system of interaction between energy companies and the IPN, the latter, on the one hand, acts as a homogeneous unity, as differentiation between groups of people is rarely carried out. On the other hand, the interpretation of the identity of the IPN occurs through “traditional culture,” which is gradually equated to something that is worthy of a place in a museum. This trend is a matter of concern, as real socio-economic challenges run the risk of being overlooked in the process of musealization of Indigenous peoples. Rosneft, Gazprom and Lukoil communicate with IPN as with an ethnic unit, which considered to be preserved as an ethnic-cultural unit.

HAT: Hypergraph analysis toolbox.

Recent advances in biological technologies, such as multi-way chromosome conformation capture (3C), require development of methods for analysis of multi-way interactions. Hypergraphs are mathematically tractable objects that can be utilized to precisely represent and analyze multi-way interactions. Here we present the Hypergraph Analysis Toolbox (HAT), a software package for visualization and analysis of multi-way interactions in complex systems.

Comprehensive energy footprint benchmarking of commercial electrified powertrains

This work presents a comprehensive energy management framework applied to electrified commercial powertrains with in-depth energy footprint analysis. We use our recently proposed algorithm, validated real-world powertrain system models, and Pareto-optimal analysis to optimize fuel consumption and harmful pollutant emissions. The approach involves dynamic optimization of 13 states and 4 control levers capturing complex subsystem interactions in parallel P2 and series range-extender commercial medium-duty electrified trucks. These subsystems exhibit vehicular (eco-driving), thermal, electrical, and mechanical dynamics at different time scales, and contain kinematic and combinatorial constraints, integer- and real-valued variables, interpolated look-up tables, and data maps. A Pareto-optimal solution is found by carefully optimizing fuel and NOx emissions to understand the energy footprint. Presented results exhibit rich powertrain behavior to unearth up to 6% improvement in energy demand, 2% in fuel economy and 18% in pollutant NOx reduction when compared to Dynamic Programming baseline from a coarsely modeled powertrain system. Furthermore, internal energy flow in the powertrains is analyzed to benchmark the optimal energy consumption and realize the multi-objective trade-off. Finally, a transient study problem is presented comparing cold versus warm after-treatment start conditions. It optimizes engine switching, eco-driving, and powersplit controls revealing adequate dynamic response and complex system interactions.

A controlled transfer entropy approach to detect asymmetric interactions in heterogeneous systems

Transfer entropy is emerging as the statistical approach of choice to support the inference of causal interactions in complex systems from time-series of their individual units. With reference to a simple dyadic system composed of two coupled units, the successful application of net transfer entropy-based inference relies on unidirectional coupling between the units and their homogeneous dynamics. What happens when the units are bidirectionally coupled and have different dynamics? Through analytical and numerical insights, we show that net transfer entropy may lead to erroneous inference of the dominant direction of influence that stems from its dependence on the units’ individual dynamics. To control for these confounding effects, one should incorporate further knowledge about the units’ time-histories through the recent framework offered by momentary information transfer. In this realm, we demonstrate the use of two measures: controlled and fully controlled transfer entropies, which consistently yield the correct direction of dominant coupling irrespective of the sources and targets individual dynamics. Through the study of two real-world examples, we identify critical limitations with respect to the use of net transfer entropy in the inference of causal mechanisms that warrant prudence by the community.