Complex System Research Articles

The control costs of human brain dynamics

Abstract The human brain is a complex system with high metabolic demands and extensive connectivity that requires control to balance energy consumption and functional efficiency over time. How this control is manifested on a whole-brain scale is largely unexplored, particularly what the associated costs are. Using network control theory, here we introduce a novel concept, time-averaged control energy (TCE), to quantify the cost of controlling human brain dynamics at rest, as measured from functional and diffusion MRI. Importantly, TCE spatially correlates with oxygen metabolism measures from positron emission tomography, providing insight into the bioenergetic footing of resting state control. Examining the temporal dimension of control costs, we find that brain state transitions along a hierarchical axis from sensory to association areas are more efficient in terms of control costs and more frequent within hierarchical groups than between. This inverse correlation between temporal control costs and state visits suggests a mechanism for maintaining functional diversity while minimizing energy expenditure. By unpacking the temporal dimension of control costs, we contribute to the neuroscientific understanding of how the brain governs its functionality while managing energy expenses.

Control of the Motion of an Inverted Spherical Pendulum on a Moving Base. Hybrid Impact Approach

A new hybrid method for the construction of control actions of a linear control system with constant coefficients is considered in this paper. It is assumed in this paper that a part of the discussed system meets some conditions. Some states of the main system are considered to be control actions for a subsystem for which and LQR stabilizer is acquired. Then, those control actions of the subsystem are used to construct the control actions for the main system. In the problem of controlling the motion of a complex linear system of an inverted spherical pendulum on a moving base, a new approach to the construction of control actions (hybrid action method) was used. It is assumed that a component of the complex system under discussion satisfies certain conditions. The inertial forces at the center of mass of the base of the composite system are considered to be the controlling influences on the inversion of the pendulum, for which the LQR stabilizer was purchased. The determined internal control actions on the inverted pendulum are then used to construct external control actions on the base of the composite system. In the end, a numerical analysis was carried out.

Polyvinyl fluoride: Predicting polarization in a complex soft matter system

We use first-principle density functional theory (DFT) to predict properties for semicrystalline polyvinyl fluoride (PVF) and compare with polyvinylidiene fluoride. We note that the crystalline regions of PVF are complex in the sense that we lack a complete experimental characterization of the detailed atomic organization. We therefore turn to DFT to predict both the structure and associated materials properties, illustrating a possible work flow for complex soft-matter modeling. We rely on the nonempirical consistent-exchange van der Waals density functional version [K. Berland and P. Hyldgaard, ] and identify plausible ground-state and excited-state motifs. From there we predict the elastic response of the crystalline motifs, and an upper limit estimate of the PVF polarization at room temperature. Published by the American Physical Society 2024

Automated control complex of agrotechnology in precision farming

The paper presents a project of an automated complex for managing agricultural technology. The complex consists of two inseparable components, a control unit and an executive robotic technological machine. The control unit implements the modern theory of controlling a complex dynamic system, which is an agricultural field with sowing crops. The main distinctive feature of the proposed management theory is that the object of management is an agrocenoses, which includes sowing crops and weeds. This feature is transferred to the executive technological machine, through which the simultaneous application of mineral fertilizers and herbicide treatment is carried out. At the same time, the formation of optimal technological operations is carried out on the basis of Earth remote sensing data. Based on these data, the parameters of the state of the agrocenoses are assessed, and the resulting estimates are system-wide feedback through which agricultural technology is managed. The presented complex is of interest to specialists developing individual components of modern precision farming systems.

Enhanced Frequency/Voltage Control in Multi-Source Power System Using CES and SSA-Optimized Cascade TID-FOPTID Controller

The stability and reliability of modern power systems, especially those with several renewable energy sources, strongly rely on load frequency control (LFC) and automatic voltage regulation (AVR) for frequency and voltage control under inconstant load demands. In this study, a new cascade tilt integral derivative-fractional order proportional tilt integral derivative (TID-FOPTID) controller is presented that is polished through the salp swarm algorithm (SSA) for LFC of a multi-area power system with AVR in all control areas. The system integrates capacitive energy storage (CES) and deals with governor dead-band and generation rate constraint nonlinear effects in a thermal-hydro-gas three-area multi-source power system (TAMSPS). The analysis of results, due to the SSA-based TID-FOPTID controller compared to TID-FOTID and TID-FOTID + 1 shows a positive outcome. Integrating CES brings additional improvement in the system performance, the overshoot/undershoot, and settling time are minimized. Finally, the sensitivity analysis reveals that the suggested controller will be effective and reliable for enhancing the frequency stability of the complex power system with a high RES integration level.

Psychological Responses to Home-Working Practices: A Network Analysis of Relationships with Health Behaviour and Wellbeing

Working at home, rather than in the workplace, has been suggested to affect office-based workers’ health and wellbeing. This exploratory, cross-sectional study sought to identify discrete psychological responses to home-working practices and investigate their relationship with engagement in health-related behaviours and wellbeing. A sample of 491 home-workers completed a survey assessing ten psychological responses to home-working (e.g., the ability to ‘switch off’ from work), ten health behaviour indices (e.g., sleep trouble), and seven wellbeing indices. Network Analysis modelled relationships between these variables. Results showed four clusters of psychological responses to home-working practices (representing ‘home-working independence’, ‘home-work transition’, ‘daily work pressure’, and ‘work-day forecasting’). Variables within these clusters linked to health behaviour and wellbeing: perceptions of workload manageability, ability to switch off from work, homeworking autonomy, and planning and organising a home-working day had cascading influences on indicators of health, health behaviours, and wellbeing. The findings point to a complex system of potential health and wellbeing consequences of working from home. Further evidence is needed to establish truly causal relationships; nonetheless, our findings call for the development of public health initiatives and organisational policies to support the adoption of home-working practices to benefit the health and wellbeing of home-workers.

Dynamic analysis and application of network structure control in risk conduction in the industrial chain

According to control theory, a dynamical system is controllable if, with a suitable choice of inputs, it can be driven from any initial state to any desired final state within a finite time. Most dynamic characteristics of real networks are nonlinear, so achieving target control is more practical and necessary. The network’s control energy is also a problem that must be considered. Whether and how to control the complex system of the industrial chain has high theoretical and practical significance. In this study, we use the GARCH model, DCC model, and network structure control theory comprehensively to study the price fluctuation risk of the mining stock market from the perspective of the industry chain and network control dynamics and obtain interesting results. (1) Risk conduction among stocks has a prominent industry-driving effect, and the risk conduction ability of upper and middle stocks is stronger. (2) The risk regulation cost, time cost, and node number cost of the whole-industry chain are all higher than those of the two-tier chain, which indicates that the correlation complexity of the network has a positive relationship with risk control. (3) Key risk nodes play an essential role in risk control, so monitoring key stocks from the industrial chain perspective is necessary to control risks in time. This work can provide valuable suggestions for market regulators and policy-makers in terms of risk management and control.

Neuromorphic Computing for Smart Agriculture

Neuromorphic computing has received more and more attention recently since it can process information and interact with the world like the human brain. Agriculture is a complex system that includes many processes of planting, breeding, harvesting, processing, storage, logistics, and consumption. Smart devices in association with artificial intelligence (AI) robots and Internet of Things (IoT) systems have been used and also need to be improved to accommodate the growth of computing. Neuromorphic computing has a great potential to promote the development of smart agriculture. The aim of this paper is to describe the current principles and development of the neuromorphic computing technology, explore the potential examples of neuromorphic computing applications in smart agriculture, and consider the future development route of the neuromorphic computing in smart agriculture. Neuromorphic computing includes artificial synapses, artificial neurons, and artificial neural networks (ANNs). A neuromorphic computing system is expected to improve the agricultural production efficiency and ensure the food quality and safety for human nutrition and health in smart agriculture in the future.

Organizational Rigidity and Demands: A Qualitative Study on Nursing Work in Complex Organizations

Background/Objectives: The nursing work environment is a critical element in healthcare delivery and a strong predictor of both patient and nurse outcomes. Understanding the complexity and multifaceted nature of this environment is essential for improving nursing practices and optimizing healthcare systems. This study aimed to gain insights into the perceived characteristics of the nursing work environment, considering it as a complex and multifaceted system. Methods: A qualitative research approach was employed, involving 42 semi-structured interviews with 43 nurses and managers from academic, teaching, and general hospitals in The Netherlands. Data were collected between July 2020 and August 2021 through convenience sampling. Thematic coding was conducted to identify key patterns and themes. Results: The findings revealed that nurses demonstrated flexibility and a strong commitment to high-quality care, despite grappling with rigorous organizational tasks and processes. Four key themes emerged: (1) direct patient care as a standard feature of nursing work; (2) nurses’ flexibility for hospital productivity; (3) interdependencies, which decrease autonomous nursing practices; and (4) organizational structures that determine how nurses can shape their work. Nurses found it difficult to balance direct care with broader tasks due to organizational rigidity, revealing a gap between ideal nursing practices and daily reality. Conclusions: This study highlighted the challenges within the nursing work environment, particularly in balancing direct care with organizational demands. Addressing this gap between ideal nursing practice and reality requires a systems approach. This includes autonomous practices, supportive management, and flexible structures, allowing nurses to shape their work and enhance job satisfaction and care quality.

СУЧАСНІ КОНЦЕПТУАЛЬНІ ПІДХОДИ ДО КАТЕГОРІЇ «АГРОСФЕРА»

An analysis of contemporary scientific approaches to defining the category of «agrosphere» has been conducted. The features of its content, components, and main aspects of sustainable development have been examined. The importance of the agrosphere for ensuring food security, economic growth, social well-being, and environmental preservation has been substantiated. Based on the aforementioned approaches, an author's definition of the researched category has been formulated, according to which the agrosphere is a complex system that integrates land use and agro-production, their economic, social, and environmental aspects, functioning based on sustainable land management, aimed at ensuring food security, sustainable development, and societal well-being. The agrosphere should include: all elements of agricultural production; the economic component; the social component; the environmental direction; and the institutional aspect. It is important to understand that the agrosphere is not static but continuously evolves under the influence of various factors. For the sustainable development of the agrosphere, it is necessary to implement innovative technologies and practices, invest in infrastructure and human capital, create favorable conditions for the development of the agro-industrial complex, and ensure compliance with environmental norms and standards. Only through the combined efforts of the state, business, and the public can a stable and promising agrosphere be created. Being a life-supporting system, it ideally corresponds to the principles of the sustainable development concept. And it is precisely on the foundations of sustainability that its progress should occur.

INFORMATION SYSTEM OF STREET LIGHTING CONTROL IN A SMART CITY

Context. In the context of the rapid development of technologies and the implementation of the concept of smart cities, smart lighting becomes a key element of a sustainable and efficient urban environment. The research covers the analysis of aspects of the use of sensors, intelligent lighting control systems with the help of modern information technologies, in particular such as the Internet of Things. The use of such technologies makes it possible to automate the regulation of lighting intensity depending on external conditions, the movement of people or the time of a day. This contributes to the efficient use of electricity and the reduction of emissions into the atmosphere. Objective. The purpose of the paper is to analyze the procedures for creating an information system as a tool for monitoring and evaluating the level of illumination in a smart city with the aim of improving energy efficiency, safety, comfort and effective lighting management. The implementation of a smart lighting system for Lviv will help improve energy efficiency and community safety. Method. A content analysis of scientific publications was carried out, in which the results of research on the creation of street lighting monitoring systems in real urban environments were presented. The collection and analysis of data on street lighting in the city, such as energy consumption, illumination level, lamp operation schedules, and others, was carried out. Machine learning methods were used to analyze data and predict lighting needs. Using the UML methodology, the conceptual model of the street lighting monitoring information system was developed based on the identified needs and requirements. Results. The role of data processing technologies in creating effective lighting management strategies for optimal use of resources and meeting the needs of citizens is highlighted. The study draws attention to the challenges and opportunities of implementing smart lighting in cities, maximizing the positive impact of smart lighting on modern urban environments. The peculiarities of the development and use of an information system for controlling street lighting in a smart city are analyzed. The potential advantages and limitations of using the developed system are determined. Conclusions. The project on the creation of an information system designed to provide an energy-efficient lighting system in a smart city will contribute to increasing security, particularly, ensuring the safety of the community through integration with security systems, reducing energy consumption, through minimizing the electricity usage in periods when the need for lighting is not necessary. It has been determined that to implement an information system for remote monitoring and lighting control in a smart city, it is advisable to consider the possibility of using a complex lighting control system. Calculations were made on the example of Lviv for the city’s lighting needs. The use of motion sensors to determine the need to turn on lighting was analyzed. A conceptual model of the information system was developed using the object-oriented methodology of the UML notation. The main functionality of the information system is defined.

Navigating the digital frontier: transforming endodontic diagnosis through digitization. part 1

The current advances and innovations in material technology and armamentaria help to negate the difficulties faced by clinicians in diagnosing and treating patients. Oral healthcare contributes much to the wellbeing of a person. However, the oral cavity is a small and difficult area in which to work since it is filled with vascularized mobile tissues and various shaped teeth, and connected to sinuses, nerve canals, lungs and the gastrointestinal tract via the trachea and pharynx. Moreover, each tooth has a complex root canal system that must be explored if it is infected or inflamed. Root canal treatment can be compared to entering a blind tunnel and treating something unseen. Endodontics is a field in dentistry where a clinician must use their tactile sense and correlate it with clinical knowledge, as well as skill, to treat dental infections. Digital evolution has simplified diagnosis, treatment planning, documentation and communication with patients, rendering more predictable outcomes and providing evidence for the healing or non-healing of disease. The evolution of digital radiography has offered us the best technology available. The present review discusses various helpful digital tools that are currently available, and future technologies that may guide clinicians in better diagnosis. CPD/Clinical Relevance: Advances in diagnostic tools have improved accuracy in identifying and treating dental pathologies, thereby achieving more predictable outcomes and enhancing patient care.

Research on Driver Emotion Monitoring and Regulation System in Intelligent Assisted Driving

Abstract. With the rapid development of smart connected vehicles, the influence, recognition and regulation of driver's emotions are crucial for intelligent cockpits with "emotional interaction". This review aims to provide a comprehensive analysis of driver emotion monitoring systems in intelligent assisted driving. By summarizing and analyzing related literature, the structure and application of emotion monitoring systems are introduced, their principles and evaluation criteria are discussed in depth, and the advantages and limitations of the three sub-systems, namely, detection, decision-making and regulation, are analyzed in detail. The results show that although emotion monitoring and modulation technologies perform well in enhancing driving safety and comfort, their practical applications still face challenges in terms of technology maturity, cost control, and privacy protection. In addition, the reliability and accuracy of current emotion monitoring systems in complex driving environments have yet to be improved. Future research should focus on interdisciplinary cooperation to integrate the latest achievements in psychology, computer science and engineering. At the same time, it is necessary to develop unified technical standards and evaluation guidelines to promote compatibility and interoperability between different systems and enhance research on privacy protection measures to ensure the security and confidentiality of user data. Through these efforts, the field of intelligent driving is expected to achieve comprehensive development and wide application, further enhancing driver safety and user experience.

The Evolution of Angular Momentum from Terrestrial Planets during their Planetary Formation

Abstract. It has been a long run on searching for the angular momentum development and its origin for the terrestrial planets, in contrast to a general theory or equation that can write the whole picture of the angular momentum development. Generally, planetary angular momentum is built up by numerous rocky or dust contributors fused together and affected by later interactions of different sources. In other words, it requires tremendous calculation on the demotion of each debris on a complex system, meaning various theories to study the physics and fit into present observational data. The case of terrestrial planets is studied by computer simulation with models that contain different strategies of interacting bodies inside the space, and these simulations are conducted under various initial conditions, for instance, the number of involving bodies and the sizes of the rocky debris. This article briefly gives a picture of the theories simulating and predicting the development and origin of terrestrial planets by literature view of listed references, aiming to summarize and discuss the differences of several simulations and their conditions.

An evacuation model considering pedestrian group behavior under violent attacks

In recent years, violent attacks have garnered significant attention from the international community and gradually evolved into a global issue. In responding to such emergencies, effective emergency evacuation is an essential means to ensure public safety. In order to explore the pedestrian evacuation dynamics in violent attacks and understand the behavioral characteristics of individuals and the dynamic interactions of groups during the evacuation process, this paper proposes an agent-based cellular automata evacuation model. First, each agent is assigned several internal attributes such as life value, panic value, and movement speed, and the assignments fully take into account the heterogeneity of individuals. Next, by setting the attack strategy of attackers and the evacuation mechanism of pedestrians, the complex system is modeled from a microscopic perspective. Finally, the effects of critical factors on the pedestrian evacuation process, such as panic coefficient, crowd structure, group ratio, attack distance and intensity, attacker location and number, and counterattack probability, are discussed through simulation. The results show that the tension caused by moderate panic is beneficial, but excessive panic will lead to increased evacuation time and fatalities. Meanwhile, the group behavior among pedestrians causes them to move relatively lagging, and the evacuation efficiency decreases as the group scale increases. Additionally, increases in attack intensity, attack distance, and attacker number all result in more casualties, and the consequences are most severe when multiple attackers operate separately, but counterattacks by pedestrians can significantly improve the overall safety of evacuation. Our study can provide some reference and basis for emergency management under violent attacks.

Supersaturated drug delivery system of albendazole salt-polymer complex for improving oral bioavailability and efficacy anti-secondary E. multilocularis

Based on the supersaturation theory, this study devised two albendazole (ABZ) salt-polymer complexes that enhance the oral bioavailability and efficacy of secondary hepatic alveolar echinococcosis (HAE) in rats. Solid characteristics, microstructure, and stability of ABZ benzenesulfonate (ABZ-BSA) and ABZ methanesulfonate (ABZ-MSA) were evaluated. The equilibrium solubility and intrinsic dissolution rate of salt were measured across different pH environments to determine its potential for generating supersaturation. Polymer crystallization inhibitors were subsequently introduced to assess their impact on sustaining supersaturation. The pharmacokinetics and anti-echinococcosis effects of ABZ were evaluated in healthy SD and HAE rats. The characteristic peaks corresponding to amino acid esters and benzimidazole in the ABZ salt structure either shifted or disappeared, corroborated by PXRD, signifying successful ABZ salt preparation. Furthermore, reductions in the melting point and enthalpy of the salts were observed, along with discernible differences in microstructure compared to ABZ. The drug salts exhibited a significant increase in apparent solubility and intrinsic dissolution rate of ABZ, thus laying the groundwork for supersaturation. Stability assessments indicated that salts were susceptible to moisture absorption, necessitating stringent humidity control measures. Notably, HPMC-AS demonstrated promising capabilities in sustaining supersaturation. Finally, pharmacokinetic analyses revealed a substantial increase in the AUC of ABZ-BSA-H and ABZ-MSA-H by 7.6 and 20.3 times, respectively, compared to ABZ in vivo. After a 30-day once-daily oral administration of the Salts and ABZ to SD rats with hepatic alveolar echinococcosis, the ABZ-BSA-H and ABZ-MSA-H formulation demonstrated a cysts inhibition effect 9.2-fold and 15.3-fold greater than that of ABZ. The salt-HPMC-AS complex could potentially be developed into an improved anti-AE drug therapy. Therefore, the salt-HPMC-AS complex could be developed into an enhanced anti-AE drug therapy.

Discovery of anti-tumor agent targeted MetAP-2 using a special turn-on fluorescent probe

Methionine aminopeptidase 2 (MetAP-2) catalyzes the removal of methionine from the amino-terminus of proteins or peptides and is a known target for anti-tumor therapy. In this study, we developed an enzyme-activated fluorescent probe, DDAO-BMT, specifically for the real-time detection of endogenous MetAP-2. This probe enables the determination of extracellular MetAP-2 activity and visual monitoring of intracellular MetAP-2. Additionally, Sappan Lignum was identified as an active herbal medicine against MetAP-2, with brazilin identified as its key active constituent. Brazilin also exhibited a significant anti-tumor effect, including the inhibition on proliferation, migration, and invasion of tumor cells, and the preliminary mechanism of its activity against cancer has been elucidated. The use of this probe facilitates the monitoring of endogenous MetAP-2 in complex biological system, aiding in the discovery of novel active compounds for cancer treatment.

Vibration source inversion-based fault diagnosis: approach and application

The gear transmission system of industrial equipment is characterized by a highly integrated structure, non-stationary operating conditions, and large loads. Therefore, the attenuation of fault signal characteristics and the complexity of operating conditions in gear transmission systems significantly affect the effectiveness of vibration signal-based fault diagnosis. This paper proposes a unified diagnostic framework based on vibration source inversion for two typical transmission component fault signal phenomena: meshing frequency modulation sidebands and equally spaced fault characteristic frequency interval harmonic clusters. This approach incorporates the vibration transfer path analysis of passive subsystems and identifies bearing dynamic forces, followed by their decomposition, reconstruction, and sensitive frequency band localization. It enables accurate diagnosis of complex gear transmission systems under non-stationary conditions with limited vibration testing. The effectiveness and advantages of this method over existing mainstream signal processing techniques are validated through actual cases of gear and weak bearing fault diagnosis on a complex planetary gear transmission system test bench.

Decoding aging and cognitive functioning through spatiotemporal EEG patterns: Introducing spatiotemporal information-based similarity analysis.

Exploring spatiotemporal patterns of high-dimensional electroencephalography (EEG) time series generated from complex brain system is crucial for deciphering aging and cognitive functioning. Analyzing high-dimensional EEG series poses challenges, particularly when employing distance-based methods for spatiotemporal dynamics. Therefore, we proposed an innovative methodology for multi-channel EEG data, termed as Spatiotemporal Information-based Similarity (STIBS) analysis. The core of this method is to first perform state space compression of multi-channel EEG time series using global field power, which can provide insight into the dynamic integration of spatiotemporal patterns between the steady states and non-steady states of brain. Subsequently, we quantify the pairwise differences and non-randomness of spatiotemporal patterns using an information-based similarity analysis. Results demonstrated that this method holds the potential to serve as a distinguishing marker between young and elderly on both pairwise differences and non-randomness indices. Young individuals and those with higher cognitive abilities exhibit more complex macrostructure and non-random spatiotemporal patterns, whereas both aging and cognitive decline lead to more randomized spatiotemporal patterns. We further extended the proposed analytics to brain regions adversarial STIBS (bra-STIBS), highlighting differences between young and elderly, as well as high and low cognitive groups. Furthermore, utilizing the STIBS-based XGBoost model yields superior recognition accuracy in aging (93.05%) and cognitive functioning (74.29%, 64.19%, and 80.28%, respectively, for attention, memory, and compatibility performance recognition). STIBS-based methodology not only contributes to the ongoing exploration of neurobiological changes in aging but also provides a powerful tool for characterizing the spatiotemporal nonlinear dynamics of the brain and their implications for cognitive functioning.

Quantitative Analysis of Complex Aluminum Electrolytes by X-Ray Fluorescence.

The future production of electrolytic aluminum will be characterized by low temperature, low carbon emissions, and environmental friendliness, which will result in a more complex electrolyte system. Real-time analysis of electrolytes can significantly enhance the efficiency of the electrolytic process. However, accurately analyzing the composition of complex aluminum electrolytes online has been a technical challenge. This research primarily focuses on determining the ingredient contents of complex aluminum electrolytes based on elemental concentrations measured using X-ray fluorescence (XRF) according to an applicable standard. Calibration curves were established based on 53 standard samples of complex aluminum electrolytes to establish relationships between XRF fluorescence intensity and real concentrations. Analysis conducted on industrial complex electrolytes confirms that these newly constructed curves effectively reduce relative errors to less than 3%. Additionally, a feasible solution is proposed for determining the cryolite ratio (CR) in aluminum electrolytes using XRF. Results demonstrate an average deviation as low as approximately 0.02, fully meeting industrial production requirements. This technique offers numerous benefits including rapid analysis, ease of use, and cost savings.