Dynamic Element Research Articles

Shared and distinct electroencephalogram microstate abnormalities across schizophrenia, bipolar disorder, and depression.

Microstates of an electroencephalogram (EEG) are canonical voltage topographies that remain quasi-stable for 90 ms, serving as the foundational elements of brain dynamics. Different changes in EEG microstates can be observed in psychiatric disorders like schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). However, the similarities and disparatenesses in whole-brain dynamics on a subsecond timescale among individuals diagnosed with SCZ, BD, and MDD are unclear. This study included 1112 participants (380 individuals diagnosed with SCZ, 330 with BD, 212 with MDD, and 190 demographically matched healthy controls [HCs]). We assembled resting-state EEG data and completed a microstate analysis of all participants using a cross-sectional design. Our research indicates that SCZ, BD, and MDD exhibit distinct patterns of transition among the four EEG microstate states (A, B, C, and D). The analysis of transition probabilities showed a higher frequency of switching from microstates A to B and from B to A in each patient group compared to the HC group, and less frequent transitions from microstates A to C and from C to A in the SCZ and MDD groups compared to the HC group. And the probability of the microstate switching from C to D and D to C in the SCZ group significantly increased compared to those in the patient and HC groups. Our findings provide crucial insights into the abnormalities involved in distributing neural assets and enabling proper transitions between different microstates in patients with major psychiatric disorders.

Using cultural-historical activity theory to describe a university-wide blended learning initiative

Institution-wide evaluations of Blended Learning implementations are rare. Even less common are evaluations that report the sociocultural context of the implementation. Recently, an Australian university in the western region of Victoria embarked on an initiative to blend all course units over a three-year period. Stemming from a rigorous analysis of reporting documents and participantresearcher observations, an attempt has been made to describe the sociocultural context of this blended learning initiative through the lens of Engestrom’s Cultural-historical Activity Theory (CHAT). This description, along with the challenges surfaced will serve as a precursor to the university-wide impact evaluation of this blended learning initiative. The objective of the analysis was to reify the complex processes, intricate relationships and dynamic environmental elements, which tend not to be captured by impact evaluations. Understanding what exactly is going on will enable the University to situate evaluation findings in the context of factors that might have helped or hampered the achievement of outcomes, and remediate process-related problems in a timely manner. Amidst the flurry of focused and coordinated blended learning activities, eight key process-related challenges emerged: Staff Capacity, Engagement, Deployment, Workload, Technological Issues, Project Management, Communication and Unit Stability. These challenges could potentially make or break ‘the Blend’ if not adequately addressed. This paper highlights the value of process evaluations for online and blended learning implementations and argues for such evaluations to be grounded in ontological realities reflected on accountability reports and observational data.

Navigating Ritual Resilience: The Interplay of Change and Continuity in the Shaolin Monastery During the COVID-19 Pandemic

The global upheaval caused by the COVID-19 pandemic introduced considerable perturbations to the religious life and ritual observances within most religious communities around the world. This article delves into the resilience and adaptability of ritual practices within the Shaolin Monastery of China during the five-month COVID-19 quarantine spanning from 23 January to 22 June, 2020. Employing ethnographic methods and grounded in anthropological theory, the study examines the interplay between ritual as a static social fact and as a dynamic, adaptable process, within the context of the Shaolin monastic life. It underlines the intricate interplay between static and dynamic elements in ritual practice, casting light on the Shaolin community’s response to the pandemic. The study discerns dichotomies responsible for the critical forces underlying complex dynamics intrinsic to the Shaolin community’s religious life, namely: religious–secular, isolation–social engagement, discipline–freedom, tradition–innovation, and individual–collective. Tracking the evolutions and consistencies within these dual relationships enabled casting light on the transformative processes that were set in motion and identifying the elements of the religious life that have undergone change and those that have remained constant. This exploration offers a unique glimpse into the mechanisms through which resilience was enacted with the strategies that enabled the community to maintain, adjust and innovate its ritual practices amidst the tribulations presented by the crisis.

Evolution of the national theory of cooperation in the conditions of gradual development of the agrarian sector of Belarus

Evolution of the national theory of cooperation in the conditions of gradual development of the agrarian sector of Belarus

Dynamic traffic graph based risk assessment of multivehicle lane change interaction scenarios

Vehicles' lane-changing behavior can potentially result in traffic conflicts and crash risks, particularly in scenarios with interactions among multiple vehicles. To assess the crash risk of multi-vehicle interaction lane-changing (MILC) scenarios, this study presents a dynamic traffic graph-based risk assessment method. First, a method for constructing dynamic scene graphs is proposed, along with graph-based indicators for assessing scene and scenario risks. Second, the Gaussian mixture model-latent Dirichlet allocation (GMM-LDA) algorithm is utilized to cluster risk sequences of MILC scenarios, enabling the classification of scenario risks into different levels. The method considers both dynamic and static elements in these scenarios, as well as the spatial relationships among these elements. A case study was conducted to illustrate this approach at a weaving area in China. The findings reveal that diverging segments have the highest probability of high-risk MILC scenarios. Furthermore, the likelihood of high-risk scenarios involving consecutive lane-changing maneuvers is higher compared to single lane changes. Left lane-changing behavior exhibits a higher probability of high-risk scenarios compared to right lane-changing. The proposed risk assessment method facilitates the identification and construction of high-risk MILC scenarios. It also enables the exploration of the risk evolution process.

Statistical Survey of Thin Current Sheets in Earth's Magnetotail: MMS Observations

AbstractThin current sheets (TCS) formed in Earth's magnetotail and hosting magnetic field line reconnection are important element of magnetospheric dynamics. In this paper, a statistical survey of 163 TCS crossing events in Earth's magnetotail using observations by MMS during 2017–2020 is performed. We find that magnetotail TCSs typically have a very strong current density primarily carried by electrons, with a thickness of a few ion inertial lengths. Our statistical results reveal different characteristics between TCSs located on the duskside and dawnside. Specifically, we find that TCSs on the duskside have a smaller thickness, higher current density, and stronger Hall electric field than on the dawnside. Our results also show that there is a correlation between the TCS thickness and the Hall electric field magnitude, with a stronger Hall electric field present in thinner TCSs. Our statistics results confirm previously reported key TCS dawn‐dusk asymmetries, with the main advance of directly measurable plasma currents. TCS characteristics of the presented data set will be useful for initialization of realistic numerical simulations and theoretical investigations of TCS instabilities resulted in various dynamical models of the magnetotail.

Innovative features of corporate identity development

In 2024, a clear and recognisable visual identity becomes a key factor for success for any brand. Traditional approaches to developing a corporate style are no longer as effective as they once were, so there is a need for fresh and innovative solutions. This research aims to elucidate the interrelationships between various elements of corporate identity. The methodology encompasses generalisation, identification of common patterns based on acquired data, and logical analysis of existing knowledge. The research methods employed include a comprehensive analysis of specific works to isolate fundamentally similar operations. Furthermore, model the commonality of corporate style and its components as an integrated system to identify the forms of new elements. This study involves an in-depth examination of theoretical materials and a detailed analysis of case studies, focusing on key features that render the development of corporate identity innovative. These include visual identity, flexibility, storytelling, authenticity, universal design, personalisation, VR, AR, AI, and sustainability. Visual identity ensures brands are recognisable and memorable. Flexibility allows brands to adjust their visual elements across various platforms, maintaining consistency. Storytelling and authenticity build trust and loyalty by conveying a brand’s history and values. Universal design enhances reach by being inclusive. Personalisation tailours identity to individual preferences, creating relevant experiences. VR and AR offer immersive experiences, enhancing brand engagement. AI facilitates dynamic brand elements that evolve based on real-time data. A sustainable approach aligns brands with consumer demand for eco-friendly practices. In summary, the innovative development of corporate identity is characterised by a multifaceted approach that integrates visual identity, adaptability, storytelling, inclusivity, personalisation, immersive technologies, AI, and sustainability. Each of these elements contributes to a cohesive and compelling brand presence that resonates with contemporary consumers. Implementing these innovative principles to carry out projects will help create a unique and dynamic corporate style that stands out in the competitive market, emotionally influences the audience, and contributes to success

Modelling of aero-mechanical response of wind turbine blade with damages by computational fluid dynamics, finite element analysis and Bayesian network

Computational Fluid Dynamics and Finite Element Analysis structural models are developed for generation of large datasets of high-fidelity aerodynamic loading, displacement and stress for the NREL 5 MW wind turbine blade. Based on the datasets, analysis of structural responses of the turbine blade and their possible shifts with respect to a change in the operating conditions, e.g. rotor plane tilting and yawing, are performed. A Bayesian Network model is trained to produce ranges of values and likelihoods of occurrence of abnormal structural response or the most likely damage in the blade from inputs of operating conditions. The numerical analysis showed that yawing and tilting of rotor plane has very strong influence on the performance of a wind turbine. The out-of-plane bending is the dominant mode of the rotor blade while twisting and other complex modes of displacement could be more significant during some operating conditions such as at high tilt and yaw angles. The Bayesian Network is capable of computing probability mass functions of mechanical stress or displacement of the blade given a rotor rotation speed and a type of damage or vice versa, identifying a type of damage given a measured stress distribution level.

Magnetostriction enhanced self-powered nanofiber sheet as cardiac patch with magnetoelectric synergistic effect on actuating Na+ k+-ATPase

Cardiac tissue engineering has great promise in the treatment of heart disease. Aiming to develop the novel magnetoelectric cardiac patch for improving the non-conduction of injured myocardium after myocardial infarction, the self-powered nanofiber sheet was electro-spun by doping magnetostrictive CoFe2O4 in piezoelectric Poly (vinylidene fluoride) (PVDF). The piezoelectric ratios increased several folds with the doping of CoFe2O4 due to the increased β phase and crystallinity of CoFe2O4-PVDF confirmed by experimental data. Molecular Dynamics and Finite Element Simulation demonstrated that non-β phase transformed to β phase of PVDF with doping CoFe2O4 and the deformation of CoFe2O4 enhanced the piezoelectric effect of PVDF, respectively. The proliferation and spread area of Doxorubicin-induced oxidative stress injured cardiomyocytes, H9c2 cells, were significantly improved under magnetoelectric cue compared with those without magnetoelectric cue when co-cultured with CoFe2O4-PVDF. Importantly, a new mechanism pathway of magnetoelectric cue on cardiomyocytes has been found, including up-regulating of steroid hormone biosynthesis, enhancing of sodium–potassium enzyme, and increasing of intracellular Ca2+, which would trigger the cardiomyocyte contraction to overcome the non-conduction of injured cardiomyocytes by RNA-seq transcriptome sequencing, Polymerase Chain Reaction and downstream expression analysis. Hence, this CoFe2O4-PVDF composite nanofiber sheet would be potentially used as the magnetoelectric cardiac patch to treat injured myocardium after myocardial infarction clinical.

An overview of education at middle and high schools in Iraq: A summary on the case of mathematics

This brief investigation dives into the landscape of general education and mathematics instruction in Iraq's middle and high schools to provide insight into many facets of the educational system. The talk covers essential educational themes by giving an overview of general education and mathematics teaching and learning, emphasizing the issues faced and untapped potential within the Iraqi school system. This review aims to delve into the complexities of the current condition of general and mathematics teaching in these institutions, offering significant insights that go beyond surface-level examination. This investigation aims to identify existing barriers and prospective areas for reform and progress. This results in a better knowledge of the dynamic elements impacting general education and mathematics instruction in Iraq's middle and high schools

In situ high-temperature transmission electron microscopy investigation of dynamic element migration for Sm-Co-Fe-Cu-Zr sintered magnets

The investigation delved into the dynamic migration of elements and the evolution of interface structures within the Sm(CobalFe0.09Cu0.09Zr0.03)7.2 magnet as temperature increased, employing high-temperature transmission electron microscopy. Notably, the Cu distribution exhibited temperature susceptibility. Elevating the temperature from room temperature (RT) to 400 °C led to a notable expansion in the distribution width of Cu, ranging from 28.5 to 50.8 nm. Simultaneously, the average Cu content at the cell boundaries decreased from 14.4 to 11.6 at.%. According to the high-temperature in-situ experimental results of the transmission electron microscopy thin-film samples, the derived diffusion coefficients, D300°Cand D400°C, were determined as 0.0525 nm2/s and 1.414 nm2/s, respectively. The significantly higher D400°C compared to D300°C underscores the considerable influence of temperature on Cu element diffusion behavior. The simulation results demonstrate that the trend of magnetic properties variation at different temperatures closely aligns with the observed trend. Subsequent calculation of the temperature coefficient of intrinsic coercivity (β) reveals that |β300–400°C| is notably higher than |βRT-300°C|. This suggests a substantial impact of Cu diffusion-induced deterioration on the β. Moreover, micromagnetic simulation results delineated the reverse magnetization process for magnets at varying temperatures, revealing that the presence of the Cu diffusion region diminished the pinning effect of the cell boundary phase. Furthermore, a wider Cu diffusion region facilitated easier magnetic moment reversal at the cell boundary phase, resulting in a marked deterioration of intrinsic coercivity. This elucidates that the formation of the Cu diffusion region stands as one of the primary reasons for the sharp decline in magnetic properties of Sm2Co17-type magnets under high-temperature conditions.

Pocket Parks in Urban Design: Enhancing Urban Environment and Community Well-being

As urban environments become increasingly dense, pocket parks have emerged as essential elements in enhancing the urban environment and improving the quality of life in densely populated areas. These compact, strategically designed spaces offer a range of benefits, extending from ecological enrichment to fostering social connections. This paper explores the concept and significance of pocket parks in urban design, examining their contributions to both ecological diversity and community well-being. Central to their success is a commitment to innovative design principles that emphasize efficient space utilization, contextual integration, and ecological sensitivity. These principles ensure that pocket parks are not only practical and visually appealing but also resonate with local community needs and the surrounding environment. This study aims to highlight the transformative potential of pocket parks in creating more livable, sustainable, and inclusive urban environments, underlining their role as dynamic elements in contemporary urban development.

Spatter-flow interaction behavior under protective gas flow parameters and scanning directions

Spattering is a common issue in selective laser melting (PBF-LB), causing contamination of the powder bed and negatively affecting product quality. One solution to this problem is introducing an inert gas flow that can remove spatter particles. The gas flow's characteristics and interaction with spatter particles depend on process parameters and involve a multi-physical field coupling process. However, current research mainly focuses on spattering behavior under single process conditions and lacks systematic exploration of gas flow characteristics and their interaction with spattering. This paper investigates the gas flow-spatter interaction process in PBF-LB, constructing a coupled model of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM). The model investigates the effects of inlet height, inlet flow velocity and laser scanning direction on the deposition and removal of spattered particles. The study reveals that flow velocity and inlet height affect the dynamic behavior of spattering by altering the flow distribution, while the laser scanning direction influences spatter dynamics by changing the direction of spatter ejects. The rate of spatter removal increases as the angle between the scanning direction and flow direction, and the flow velocity, increase. Conversely, it decreases as the inlet height increases. This work provides theoretical understanding of the interaction between gas flow characteristics and spattering, which is significant for optimizing printing process parameters and improving printing quality.

Time, ties, transactions: temporality and relational work in economic exchange

This paper explores the intersection of time and relational economic sociology. Building on Viviana Zelizer’s relational framework, I argue that analyzing the temporal dimensions of exchange provides insight into how social ties gain meaning through economic practices. The paper shows time’s dual role as both an organizing structure bounding action, and a dynamic element that actors leverage to shape transactional contexts. As structure, time offers culturally-available templates like schedules and rhythms that facilitate coordination and signify predictable social meanings befitting particular relational categories. Yet time also constitutes relational work itself; strategic timing, duration, pacing, and sequencing of interactions signal context, manage expectations, and sustain bonds amidst entanglements. Synchronization through temporal agency prevents mismatches between transactions and social contexts that could strain ties. This agency in time ranges from passive adherence to dominant structures to active assertions of power resistance, enabling both domination and defiance across economic contexts. Analyzing shared temporal infrastructure within circuits of commerce further illuminates how actors distinguish those spheres of exchange at various scale from the impersonal market. Ultimately, incorporating temporality strengthens relational economic sociology by identifying a key mechanism through which practices of exchange become relationally meaningful.

K-Track-Covid: interactive web-based dashboard for analyzing geographical and temporal spread of COVID-19 in South Korea.

The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present 'K-Track-Covid,' an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrates regional data to offer tailored visual displays. The dashboard allows users to customize their data views by selecting specific time frames, geographic regions, and demographic groups. This customization enables the generation of charts and statistical summaries pertinent to both daily fluctuations and cumulative counts of COVID-19 cases, as well as mortality statistics. Additionally, the dashboard offers a simulation model based on mathematical models, enabling users to make predictions under various parameter settings. The dashboard is designed to assist researchers, policymakers, and the public in understanding the spread and impact of COVID-19, thereby facilitating informed decision-making. All data and resources related to this study are publicly available to ensure transparency and facilitate further research.

ASPECTS OF RESPONSE TO INCIDENTS ARE CAUSED BY ANOMALIES IN THE FUNCTIONING AND MAINTENANCE OF COMPUTER SYSTEMS

Digital services in modern computer systems are a key element for ensuring efficient and reliable functioning of various applications. The increase in the amount of data and the complexity of software solutions makes the task of monitoring and managing functional anomalies of such services in distributed systems urgent. In this way, consideration of issues of distribution of digital services, in particular their optimization based on monitoring of functional anomalies, which can allow the development and improvement of anomaly detection methods, strategies for the distribution of computing resources, and response to detected anomalies in distributed computer systems. Taking into account the constant growth of data volumes and the complexity of the interaction of services in a distributed environment, there is a need to conduct research on large-scale distributed systems, focusing on joint activities and anomaly management. In the course of which it is advisable to pay attention to the aspects of time, coherence, coordination and computing costs for the mentioned processes. An important focus is the area of ​​critical digital infrastructure, which examines changes in software development, the transition to cloud computing, and incident response strategies, including analysis of data sources, their availability, and investigation of incident response patterns. In addition, it is necessary to pay attention to adaptive choreography, where the results of preparatory studies, elements of choreography and dynamics of coordination in incident management are considered.

Influence of Prestress on Vibration Frequency of Beam String Structures Based on Exact Matrix Stiffness Method

Beam string structures (BSS) are frequently employed in large-span spatial structures due to their high load-carrying efficiency and elegant appearance. Owing to the neglect of the influence of prestress, the natural frequency of the BSS is often overestimated which could be crucial to the dynamic behavior of BSS. This paper presents an exact matrix stiffness analysis method (MSM) for investigating the relationship between prestress and the natural frequency of the planar BSS. A novel dynamic stiffness matrix of beam–columns considering the natural frequency and axial force is used to develop the MSM. The dynamic analysis of the structural vibration stability of BSS is performed by using the global structural stiffness matrix which is assembled from the element stiffness matrices in the global coordinate system. The proposed MSM with the exact dynamic element stiffness matrix for the dynamic analysis of the BSS is verified by comparing with previous results based on the finite element method. The illustrative examples demonstrate that the prestress in the cable has a negative effect on the natural frequency of the BSS and should be considered in the dynamic analysis. As the axial force increases from zero to the buckling load [Formula: see text], the natural frequency of the BSS decreases from the maximum vibration frequency to zero. The influence of prestress on the vibration frequencies of BSS is particularly significant when the prestress to balance the loads is large, especially in the case of large dead and live loads (e.g. floor slabs).

How would autonomous vehicles behave in real-world crash scenarios?

Autonomous Vehicles (AVs) have the potential to revolutionize transportation systems by enhancing traffic safety. Safety testing is undoubtedly a critical step for enabling large-scale deployment of AVs. High-risk scenarios are particularly important as they pose significant challenges and provide valuable insights into the driving capabilities of AVs. This study presents a novel approach to assess the safety of AVs using in-depth crash data, with a particular focus on real-world crash scenarios. First, based on the high-definition video recording of the whole process prior to the crash occurrences, 453 real-world crashes involving 596 passenger cars from China In-depth Mobility Safety Study-Traffic Accident (CIMSS-TA) database were reconstructed. Pertinent static and dynamic elements needed for the construction of the testing scenarios were extracted. Subsequently, 596 testing scenarios were created via each passenger car’s perspective within the simulation platform. Following this, each of the crash-involved passenger cars was replaced with Baidu Apollo, a famous automated driving system (ADS), for counterfactual simulation. Lastly, the safety performance of the AV was assessed using the simulation results. A logit model was utilized to identify the fifteen crucial scenario elements that have significant impacts on the test results. The findings demonstrated that the AV could avoid 363 real-world crashes, accounting for approximately 60.91% of the total, and effectively mitigated injuries in the remaining 233 unavoidable scenarios compared to a human driver. Moreover, the AV maintain a smoother speed in most of the scenarios. The common feature of these unavoidable scenarios is that the AV is in a passive state, and the crashes are not caused by the AV violating traffic rules, but rather caused by abnormal behavior exhibited by the human drivers. Additionally, seven specific scenarios have been identified wherein AVs are unable to avoid a crash. These findings demonstrate that, compared to human drivers, AVs can avoid crashes that are difficult for humans to avoid, thereby enhancing traffic safety.

An entropy‐based model for quantifying multi‐dimensional traffic scenario complexity

AbstractQuantifying the complexity of traffic scenarios not only provides an essential foundation for constructing the scenarios used in autonomous vehicle training and testing, but also enhances the robustness of the resulting driving decisions and planning operations. However, currently available quantification methods suffer from inaccuracies and coarse‐granularity in complexity measurements due to issues such as insufficient specificity or indirect quantification. The present work addresses these challenges by proposing a comprehensive entropy‐based model for quantifying traffic scenario complexity across multiple dimensions based on a consideration of the essential components of the traffic environment, including traffic participants, static elements, and dynamic elements. In addition, the limitations of the classical information entropy models applied for assessing traffic scenarios are addressed by calculating magnitude entropy. The proposed entropy‐based model is analyzed in detail according to its application to simulated traffic scenarios. Moreover, the model is applied to real world data within a naturalistic driving dataset. Finally, the effectiveness of the proposed quantification model is illustrated by comparing the complexity results obtained for three typical traffic scenarios with those obtained using an existing multi‐factor complexity quantification method.

Community-based postnatal care model: Catalyst for management of mothers and neonates.

Early postnatal discharge is perceived as a factor that contributes to the possibilities of the maternal, neonatal complications and deaths. The implementation of the community-based postnatal care model is crucial to mitigate the morbidity and mortality of postnatal women and neonates during the first weeks of delivery. A community-based postnatal care model was developed for the management of neonates during the postnatal care period in the community. The study aims to share the developed community-based postnatal care model that could assist postnatal women in the management of neonates. Empirical findings from the main study formed the basis for model development. The model development in this study was informed by the work of Walker and Avant; Chinn and Kramer Dickoff, James and Wiedenbach; and Chinn and Jacobs. The results indicated that there was no community-based postnatal care model developed to manage neonates. The model is described using the practice theory of Dickoff, James and Wiedenbach elements of agents, recipients, context, process, dynamics and outcomes within the community context of the postnatal care period. The model was further described by Chinn and Krammer following the assumptions of the model, concept definition, relation statement and nature of structure. The utilisation of the model is critical and facilitates the provision of an enabling and supportive community-based context by primary caregivers for the effective management of neonates.Contribution:This study provides a reference guide in the provision of community-based postnatal care by postnatal women after discharge from healthcare facilities.