Dynamic Link Research Articles

Dynamic Coupling Between Intensified Physical Erosion and Asian Dust Activity Under Late Cenozoic Global Cooling

AbstractDistinguishing the independent contributions of tectonic denudation and climate‐driven erosion on the production and supply of clastic materials of Chinese eolian deposits is important in understanding the dynamic links between global climate changes, tectonics, and Asian dust emission. Here, multi‐proxy rock magnetic records of detrital fractions of Chinese eolian deposits since ∼6 Ma, combined with further comparison with dust accumulation rates and geochemical data, suggest that limited production and supply of clastic materials of Chinese eolian deposits were observed between 5.6 and 4.4 Ma in a warmer climate, and thereafter an increasing trend is evident during a cooler world. We propose that intense physical erosion under cooler conditions caused increasing production of fresh detrital components, exerting dominant influences on the sediment supply to Asian eolian deposits. This study provides direct evidence of dynamic coupling between intensified physical erosion and Asian dust activity under late Cenozoic global cooling.

The privilege to play: race, gender, & SES advantages in boys’ high school athletic opportunities

ABSTRACT In this study, with an exploratory sequential mixed-methods design, we considered the components and implications of a habitus that (re)produces racial/ethnic, social class, and gender differences in US interscholastic sport participation. We drew from independently collected qualitative (N = 19 men and 47 total college athletes) and quantitative (N = 4,097 high school boys) data and noted and investigated dynamic links between individual choices; family, community, and school contexts; and power structures that inform interscholastic athletics. Findings positioned sports as offering valuable institutionalized cultural capital but being rife with reproductive struggles. Schools serve as fields that co-construct unequal athletic opportunity structures by nurturing and rewarding a cultivated athletic habitus associated with masculinity, whiteness, and affluent dispositions. These processes situate athletic advantages and successes as purely meritorious but restrict who is most likely to receive the individual and social benefits of high school sports participation.

Multidimensional employment trajectories and dynamic links with mental health: Evidence from the UK Household Longitudinal Study.

Low-quality and precarious employment have been associated with adverse mental health and wellbeing. More evidence is needed on how the quality of employment trajectories - including transitions in and out of unemployment, inactivity, and employment of varying quality - are associated with individuals' mental health over time. This paper aimed to derive a typology of multidimensional employment trajectories and assess associations with mental health in the UK. Data from waves 1-9 of the UK Household Longitudinal Study were used (2009-2019). Individuals aged 30-40 at baseline were included (N=1603). Using multichannel sequence and clustering analyses, we derived a typology of employment trajectories across employment statuses and four employment quality indicators. We assessed associations with subsequent psychological distress, accounting for baseline mental health. Changes in average General Health Questionnaire scores are described. A typology of five trajectory clusters highlighted stable and secure and precarious/low-quality trajectories for both men and women. Women who reported being economically inactive at most waves had higher odds of experiencing psychological distress than did women in 'standard' trajectories, regardless of baseline mental health. Women's scores of psychological distress in the 'precarious' group on average increased along their trajectories characterized by instability and transitions in/out of unemployment, before a move into employment. Men who likely moved in and out of unemployment and economic inactivity, with low probability of paid employment, reported increased psychological distress at the end of follow-up. This may partly be due to pre-existing mental ill-health. This paper shows the importance of high-quality employment for individuals' mental health over time. Researchers need to consider dynamic associations between employment quality and mental health across the life-course.

Exploring the Dynamic Link Between Trade Openness, External Debt, and Economic Growth in Sub-Saharan Africa: Challenges and Considerations

This study investigates the dynamic relationship between trade openness, external debt, and economic growth in Sub-Saharan Africa, focusing on the period from 1990 to 2023. The research examines how trade openness and external debt impact regional economic performance by employing Panel Autoregressive distributed lag (ARDL) techniques utilizing the pool mean group and mean group estimator’s approach. The analysis reveals that while trade openness does not stimulate economic growth, external debt similarly has significant challenges, often hindering long-term development prospects within Sub-Saharan African countries. The findings underscore the importance of managing debt sustainably and aligning trade policies with growth-enhancing strategies. Additionally, human capital and institutional quality are essential endogenous growth factors that significantly influence economic growth in Sub-Saharan Africa. The study recommends that while trade openness alone may not directly drive economic growth, its benefits can be amplified by complementary strategies such as investing in human capital, technological adoption, and industrial policy. The study concludes with policy recommendations to enhance economic resilience and foster sustainable growth, such as attracting foreign direct investment, combined with infrastructure development and sound fiscal management.

Insight into a new perspective on the complex propagation processes in networks: dynamic link equations

Insight into the spread of epidemics under different transmission mechanisms in networks has long been an important research question in the field of complex network dynamics. Currently, under simple transmission mechanisms, our analysis of the dynamic processes in networks starts only from the node level, considering the scale of infected nodes in the network. However, the information provided by this lowest-order approach to considering dynamic processes in networks is very limited. Most importantly, it is not applicable to the analysis of dynamic processes in networks under more common complex transmission mechanisms, as it neglects the interactions between nodes. Therefore, in this article, we propose a set of closed link dynamic equations to gain insight into complex propagation processes from a microscopic perspective. Fundamentally, we have developed a set of analytical tools for analyzing complex dynamic behaviors at the link level, enabling us to reexamine the complex dynamic processes on networks from a higher-order perspective. Additionally, we apply the proposed analytical framework to complex SIS epidemiological models on two real and synthetic networks, and extensive numerical simulation results demonstrate the feasibility and effectiveness of the proposed method.

The Effects of Dynamic Link Between Sustainable Development Goals (SDGs) And Medical Tourism: A Study of Medical Tourist Intention in Malaysia and Indonesia

Purpose: The study attempts to examine the behavioural intention of the medical tourist in choosing Malaysia and Indonesia as medical tourism destination. Theoretical framework: There are three determinants (behavior intention, perceived destination image, perceive value and trust as mediator are included in the current study. The theory of Planned Behavior shall form the basis of the conceptual framework for this study. Design/methodology/approach: This descriptive study aims to investigate the phenomenon of medical tourism through questionnaires. It assesses measurement scales for reliability and validity, and explores relationships between perceived destination image, perceived value, and behavioral intention, ultimately seeking to generalize findings to the broader population. Findings: This study illustrates that all the variables are vital in influencing Malaysia and Indonesia as destination for medical tourism. Based on the theory of Planned Behavior have form the basis of the variables. Hence, all antecedent factors need to be taken into consideration which will influence the medical tourists. Research, Practical & Social implications: Future research should focus on the comparative discussion for public hospitals and private hospitals in order to improve Malaysia’s and Indonesia’s performance in competing with other country as well as building trust among the medical tourists so that we (Malaysia and Indonesia) will be their first choice for medical tourism. Originality/value: By understanding the relationships between behavioral intention, destination image, perceived value and trust, the destination country would have a better idea how to and improve their marketing efforts in attracting as many medical tourists as possible.

Dynamic Link Prediction in Jujube Sales Market: Innovative Application of Heterogeneous Graph Neural Networks

Dynamic Link Prediction in Jujube Sales Market: Innovative Application of Heterogeneous Graph Neural Networks

A dynamic link between respiration and arousal.

Viewing brain function through the lense of other physiological processes has critically added to our understanding of human cognition. Further advances though may need a closer look at the interactions between these physiological processes themselves. Here we characterise the interplay of the highly periodic, and metabolically vital respiratory process and fluctuations in arousal neuromodulation, a process classically seen as non-periodic. In data of three experiments (N = 56 / 27 / 25 women and men) we tested for covariations in respiratory and pupil size (arousal) dynamics. After substantiating a robust coupling in the largest dataset, we further show that coupling strength decreases during task performance compared with rest, and that it mirrors a decreased respiratory rate when participants take deeper breaths. Taken together, these findings suggest a stronger link between respiratory and arousal processes than previously thought. Moreover, these links imply a stronger coupling during periods of rest, and the effect of respiratory rate on the coupling suggests a driving role. As a consequence, studying the role of neuromodulatory arousal on cortical function may also need to consider respiratory influences.Significance statement We characterise the interplay of the respiratory rhythm and pupil diameter dynamics as a well-known proxy for arousal. Although we consistently find respiratory modulation of pupillary changes, they were most pronounced during periods of rest (compared to during task performance) and dependent on respiratory rate (deep vs. normal breathing).

Dynamic Laser Inter-Satellite Link Scheduling Based on Federated Reinforcement Learning: An Asynchronous Hierarchical Architecture

Dynamic Laser Inter-Satellite Link Scheduling Based on Federated Reinforcement Learning: An Asynchronous Hierarchical Architecture

Redundant Telemetry Link System for Uncrewed Aerial Vehicles

Thanks to their flexibility in research, prototyping, and development, Uncrewed Aerial Vehicles (UAV) are seeing increasing use in agriculture, healthcare, logistics, and other industries. With the increase in the use of UAV in civilian sectors, comes an increase in the possibility of errors in telemetry connections. Issues with the telemetry connection may be catastrophic and cause accidents and crashes and may also adversely affect the performance of the subsystems connected to the telemetry. In this study, a low-cost software-based redundant telemetry link system for UAV is proposed. The proposed system minimises the received packet loss using packet deduplication and is compared with a dynamic link switching method. In the proposed system, both fault tolerance and robustness are introduced into the UAV telemetry link. The analysis is performed using the ArduPilot UAV Simulation environment as a producer and a Golang implementation of the proposed methods.

ESG ratings and female corporate leadership: Evidence from African firms

Despite increasing scholarly research on the dynamic causal link between environmental, social, and governance (ESG) drive and female corporate leadership, limited knowledge exists regarding the African context. This study decreases this research dearth and uncovers bidirectional causality within African firms between 2010 and 2022. Empirical results indicate that female leadership significantly influences future ESG ratings, and ESG implementation negatively affects female leadership. Ceteris paribus, managerial myopia will likely maintain this negative outcome. These findings lead to managerial and policy implications aligned with the United Nations’ Sustainable Development Goals and the African Union Agenda 2063.

To Starve the Beast or Not to Starve the Beast? Evidence from Debt-Distressed Region

ABSTRACT The elimination of budgetary disequilibrium remains a contentious issue, with scholars and policymakers debating the efficacy of tax alterations versus limiting government outlays. This topic has garnered significant attention, although research on the spending-revenue nexus is noticeably skewed against Africa, which presents an intriguing research opportunity. The International Monetary Fund (IMF) reported a concerning rise in public debt across Africa, highlighting the urgent need for public finance consolidation. In contrast to the extant literature, this study examines the dynamic link between revenues and expenditures from 1990 to 2022. Applying wavelet decomposition to account for temporary variations, our analysis reveals dynamic patterns in the revenue-expenditure nexus. Our findings support the institutional separation hypothesis in the short run, suggesting a distinct relationship between revenues and outlay. However, in the medium-to long-run, our results support the fiscal synchronization hypothesis, accentuating a more intertwined association between revenues and expenditures. This study sheds light on the nuanced dynamics of budgetary equilibrium in Africa, providing insights that can inform policy priorities and decision-making. Finally, by focusing on the unique context of Africa and using advanced techniques, this study contributes to the existing literature on budgetary equilibrium, filling a crucial gap in our knowledge of the public finance dynamics in the region.

Context propagation based influence maximization model for dynamic link prediction

Influence maximization (IM) in dynamic social networks is an optimization problem to analyze the changes in social networks for different periods. However, the existing IM methods ignore the context propagation of interaction behaviors among users. Hence, context-based IM in multiplex networks is proposed here. Initially, multiplex networks along with their contextual data are taken as input. Community detection is performed for the network using the Wilcoxon Hypothesized K-Means (WH-KMA) algorithm. From the detected communities, the homogeneous network is used for extracting network topological features, and the heterogeneous networks are used for influence path analysis based on which the node connections are weighted. Then, the influence-path-based features along with contextual features are extracted. These extracted features are given for the link prediction model using the Parametric Probability Theory-based Long Short-Term Memory (PPT-LSTM) model. Finally, from the network graph, the most influencing nodes are identified using the Linear Scaling based Clique (LS-Clique) detection algorithm. The experimental outcomes reveal that the proposed model achieves an enhanced performance.

Dynamic links between daily anxiety symptoms and young adults’ daily well-being

ABSTRACT Background Anxiety disorders are prevalent among youth and adults. Increasing studies examined the dynamic associations between momentary fluctuations of anxiety and well-being, primarily focusing on the severity of general anxiety. Scant research has explored the co-fluctuations between different anxiety symptoms and mental health outcomes. Method The current study evaluated the multi-level factor structure and assessed the subclinical symptoms of generalized anxiety disorder (GAD), social phobia (SP), and panic disorder (PD) in a sample of non-clinical young adults (N = 271, Mage = 18 years, 72% female, 68% non-White) who participated in a 30-day daily diary study. Results Between persons, GAD, SP, and PD were positively correlated with depressive symptoms, stress, as well as emotional and peer problems. Within persons, both SP and PD were positively associated with stress, peer and emotional problems on the same day. Across days, there was positive reciprocal relation between PD and stress, whereas negative reciprocal link was observed between SP and emotional problems. Conclusions Current findings showed dynamic and distinct patterns in the associations between different anxiety symptoms and several mental health outcomes, which emphasizes the need to disentangle between- and within-person variation of anxiety symptoms with intensive longitudinal designs.

Independent repeated mutations within the alphaviruses Ross River virus and Barmah Forest virus indicates convergent evolution and past positive selection in ancestral populations despite ongoing purifying selection.

Ross River virus (RRV) and Barmah Forest virus (BFV) are arthritogenic arthropod-borne viruses (arboviruses) that exhibit generalist host associations and share distributions in Australia and Papua New Guinea (PNG). Using stochastic mapping and discrete-trait phylogenetic analyses, we profiled the independent evolution of RRV and BFV signature mutations. Analysis of 186 RRV and 88 BFV genomes demonstrated their viral evolution trajectories have involved repeated selection of mutations, particularly in the nonstructural protein 1 (nsP1) and envelope 3 (E3) genes suggesting convergent evolution. Convergent mutations in the nsP1 genes of RRV (residues 248 and 441) and BFV (residues 297 and 447) may be involved with catalytic enzyme mechanisms and host membrane interactions during viral RNA replication and capping. Convergent E3 mutations (RRV site 59 and BFV site 57) may be associated with enzymatic furin activity and cleavage of E3 from protein precursors assisting viral maturation and infectivity. Given their requirement to replicate in disparate insect and vertebrate hosts, convergent evolution in RRV and BFV may represent a dynamic link between their requirement to selectively 'fine-tune' intracellular host interactions and viral replicative enzymatic processes. Despite evidence of evolutionary convergence, selection pressure analyses did not reveal any RRV or BFV amino acid sites under strong positive selection and only weak positive selection for nonstructural protein sites. These findings may indicate that their alphavirus ancestors were subject to positive selection events which predisposed ongoing pervasive convergent evolution, and this largely supports continued purifying selection in RRV and BFV populations during their replication in mosquito and vertebrate hosts.

Influencing Factors and Mechanisms of Value Co-Creation in Artificial Intelligence-Driven Human Resource Management: A System Dynamics Simulation

In the era of artificial intelligence, human resource management has undergone significant changes compared to traditional approaches regarding value creation methods and influencing factors. This research aims to utilize grounded theory to comprehensively explore the influencing factors of value co-creation in enterprise human resource management within the context of artificial intelligence. Additionally, this research seeks to capture the dynamic relationships, causal links, and evolutionary patterns among the various elements within the system by constructing a system dynamics model. The results indicated that (1) Environmental factors primarily play a regulatory role, organizational factors serve a supportive role, and participant factors act as the driving force in influencing value co-creation in human resource management. (2) In the context of artificial intelligence, both hardware infrastructure and software capabilities can significantly impact value co-creation in human resource management. This research complements current research on the influencing factors of value co-creation in enterprise human resource management. It offers new perspectives and frameworks for the theoretical development and practical application of value co-creation in this area, supporting companies in effectively managing and developing value co-creation in human resource management.

Data driven origin–destination matrix estimation on large networks—A joint origin–destination-path-choice formulation

This paper presents a novel approach to data-driven time-dependent origin–destination (OD) estimation using a joint origin–destination-path choice formulation, inspired by the well-known equivalence of doubly constraint gravity models and multinomial logit models for joint O–D choice. This new formulation provides a theoretical basis and generalizes an earlier contribution. Although including path choice increases the dimensionality of the problem, it also dramatically improves the quality of the data one can directly use to solve it (e.g. measured path travel times versus coarse centroid-to-centroid travel times); and opens up possibilities to combine different assimilation techniques in a single framework: (1) fast shortest path set computation using static (e.g. road type) and dynamic (speed, travel time) link properties; (2) predicting a “prior OD matrix” using the resulting path-shares and (estimated or measured) production and attraction totals; and (3) scaling/constraining this prior using link flows (informative of demand). If the resulting system of equations has insufficient rank, we use principal component analysis to reduce the dimensionality, solve this reduced problem, and transform that solution back to a full OD matrix. Comprehensive tests and sensitivity analysis on 7 networks with different sizes and characteristics give an empirical underpinning of the extended equivalence principle; demonstrate good accuracy and reliability of the OD estimation method overall; and suggest that the method is robust with respect to major assumptions and contributing factors.

Assessment of the Dynamical Linkages and Flow Evolution Governing Multiple Extreme Weather Events over Western North America in February 2019

Abstract We present an extended case study analysis based on observed extreme weather events (EWEs) and the planetary- and synoptic-scale variability of a persistent flow regime spanning the month of February 2019 across the North Pacific (NPAC) basin and western North America. The EWEs are clustered into two periods during February 2019: record cold and kona low conditions over Hawaii, lower elevation snow across Washington, and heavy AR-related rainfall in Southern California from 9 to 15 February; and heavy snow in Arizona and Oregon and heavy rainfall in Northern California from 21 to 28 February. From a weather regime perspective, the NPAC flow was dominated by a persistent ridge around 150°W, a retracted NPAC jet stream, repeated western NPAC (WPAC) cyclogenesis events, and frequent positively tilted troughs in the eastern NPAC and over western North America. Dynamically relevant features on the subseasonal-to-seasonal (S2S) time scale include a slowly propagating MJO signal in phases 6 and 7, a rapid NPAC jet retraction around 9 February, and subsequent eastward extension toward a climatological jet position around 21 February. On synoptic time scales, Rossby wave breaking on the southern flank of the NPAC jet and within the aforementioned persistent ridge led to the kona low formation and many of the positively tilted troughs responsible for the extreme precipitation events. In addition, frequent cyclogenesis west of the date line helped to maintain the persistent ridge strength and location through favorable heat and vorticity fluxes. The chronology and complex linkages between these aforementioned features and mechanisms are explained in depth in this paper. Significance Statement This study identified several extreme cold, rain, and snow events across the western contiguous United States and Hawaii, showed how these events are all connected to a persistent weather pattern upstream over the North Pacific basin, and identified key mechanisms for why the weather pattern was so persistent. Some of the physical mechanisms for keeping the weather pattern stagnant include anomalous convection within the tropics off the east coast of Asia, breaking waves in the atmosphere like waves breaking on a beach, and repeated cyclone development off the coast of Russia and Alaska. We hope that the results of this paper encourage others to look for similar mechanisms for similar stagnant weather patterns in a more holistic manner.

Design of real-time & historical database for photovoltaic power plant

Abstract The real-time & historical database of photovoltaic power plant monitoring system is used to store and manage the real-time and historical data, including power plant parameters, environmental data, and photovoltaic unit data and so on. Analyzing of this data is helpful for monitoring the status of the plant equipment, performing maintenance, and enhancing the operational efficiency of the power plant. The data models and database function of the database is designed. The data models include tags, data processing, and data storage models. Database function include the modules of the collection, storage, compression, and index query. The data collection module utilizes dynamic link libraries to access database data and configures parameters through a comprehensive data collection framework. The storage strategies involve in a combination of in-memory databases and disk-based historical databases, incorporating secondary caching technology and cloud server storage techniques. The data compression module is achieved through secondary compression methods. The index query module encompass time index files and the secondary index files to improve query speed and real-time system performance. The designed elements collectively establish an efficient monitoring system database.

Dynamic Graph Representation Learning via Coupling-Process Model.

Representation learning based on dynamic graphs has received a lot of attention in recent years due to its wide range of application scenarios. Although many discrete or continuous dynamic graph representation learning methods have been proposed, many of them ignore the role of edge types. Through the observation of dynamic graphs in the real world, it is found that the types of various edges are very different in nature. They are roughly divided into two categories according to the frequency of occurrence: evolutive edges that appear infrequently and interactive edges that appear frequently. For both types of edges, we propose a coupling-process model (DyCPM) to capture the dynamic mechanisms of them. The model not only generates low-dimensional embedding vectors of nodes, but also aggregates the structural information and temporal information of two kinds of edges. In particular, we design a neural network parameterized discrete process to depict the change law of the topology of evolutive edges and a neural network parameterized temporal point process (TPP) to characterize the temporal dynamic rule of interactive edges. More importantly, we propose a coupling mechanism to transfer the information of the two processes through a shared embedding matrix and finally generate an embedding matrix that aggregates the topology information and temporal information of the two kinds of edges for the dynamic link prediction task. We evaluate our model and several baselines on real datasets. The experimental results show that our model can better aggregate the topology information and temporal information of the two kinds of edges according to their properties and outperforms several state-of-the-art baselines in the performance of dynamic link prediction.