Dynamic State Research Articles

Metastable Supramolecular Assembly of Simple Monomers Enabled by Confinement: Towards Aqueous Phase Room Temperature Phosphorescence.

The application of supramolecular assembly (SA) with room temperature phosphorescence (RTP) in aqueous phase has the potential to revolutionize numerous fields. However, using simple molecules with crystalline RTP to construct SA with aqueous phase RTP is hardly possible from the standpoint of forces. The reason lies in that the transition from crystal to SA involves a structure transformation from highly stable to more dynamic state, leading to increased non-radiative deactivation pathways and silent RTP signal. Here, with the benefit of the confinement from the layered double hydroxide (LDH), various simple molecules (benzene derivatives) can successfully form metastable SA with aqueous phase RTP. The maximum of RTP lifetime and efficiency can reach 654.87 ms and 5.02 %, respectively. Mechanistic studies reveal the LDH energy trap can strengthen the intermolecular interaction, providing the prerequisite for the existence of metastable SA and appearance of aqueous phase RTP. The universality of this strategy will usher exploration into other multifunctional monomer, facilitating the development of SAs with aqueous phase RTP.

Dynamic swarms regulate the morphology and distribution of soft membrane domains.

We study the dynamic structure of lipid domain inclusions embedded within a phase-separated reconstituted lipid bilayer in contact with a swarming flow of gliding filamentous actin. Passive circular domains transition into highly deformed morphologies that continuously elongate, rotate, and pinch off into smaller fragments, leading to a dynamic steady state with ≈23× speedup in the relaxation of the intermediate scattering function compared with passive membrane domains driven by purely thermal forces. To corroborate experimental results, we develop a phase-field model of the lipid domains with two-way coupling to the Toner-Tu equations. We report phase domains that become entrained in the chaotic eddy patterns, with oscillating waves of domains that correlate with the dominant wavelengths of the Toner-Tu flow fields.

Nonlinear Dynamics of Silicon-Based Epitaxial Quantum Dot Lasers under Optical Injection

For silicon-based epitaxial quantum dot lasers (QDLs), the mismatches of the lattice constants and the thermal expansion coefficients lead to the generation of threaded dislocations (TDs), which act as the non-radiative recombination centers through the Shockley–Read–Hall (SRH) recombination. Based on a three-level model including the SRH recombination, the nonlinear properties of the silicon-based epitaxial QDLs under optical injection have been investigated theoretically. The simulated results show that, through adjusting the injection parameters including injection strength and frequency detuning, the silicon-based epitaxial QDLs can display rich nonlinear dynamical states such as period one (P1), period two (P2), multi-period (MP), chaos (C), and injection locking (IL). Relatively speaking, for a negative frequency detuning, the evolution of the dynamical state with the injection strength is more abundant, and an evolution path P1-P2-MP-C-MP-IL has been observed. Via mapping the dynamical state in the parameter space of injection strength and frequency detuning under different SRH recombination lifetime, the effects of SRH recombination lifetime on the nonlinear dynamical state of silicon-based epitaxial QDLs have been analyzed.

Dynamic Functional Connectivity Correlates of Trait Mindfulness in Early Adolescence

BackgroundTrait mindfulness—the tendency to attend to present-moment experiences without judgment—is negatively correlated with adolescent anxiety and depression. Understanding the neural mechanisms that underlie trait mindfulness may inform the neural basis of psychiatric disorders. However, few studies have identified brain connectivity states that are correlated with trait mindfulness in adolescence, and they have not assessed the reliability of such states. MethodsTo address this gap in knowledge, we rigorously assessed the reliability of brain states across 2 functional magnetic resonance imaging scans from 106 adolescents ages 12 to 15 (50% female). We performed both static and dynamic functional connectivity analyses and evaluated the test-retest reliability of how much time adolescents spent in each state. For the reliable states, we assessed associations with self-reported trait mindfulness. ResultsHigher trait mindfulness correlated with lower anxiety and depression symptoms. Static functional connectivity (intraclass correlation coefficients 0.31–0.53) was unrelated to trait mindfulness. Among the dynamic brains states that we identified, most were unreliable within individuals across scans. However, one state, a hyperconnected state of elevated positive connectivity between networks, showed good reliability (intraclass correlation coefficient = 0.65). We found that the amount of time that adolescents spent in this hyperconnected state positively correlated with trait mindfulness. ConclusionsBy applying dynamic functional connectivity analysis on over 100 resting-state functional magnetic resonance imaging scans, we identified a highly reliable brain state that correlated with trait mindfulness. This brain state may reflect a state of mindfulness, or awareness and arousal more generally, which may be more pronounced in people who are higher in trait mindfulness.

Experimental Study on the Dynamic Response and Damage State of Steel Square Tubular Structural Components by Near-field Explosions

Experimental Study on the Dynamic Response and Damage State of Steel Square Tubular Structural Components by Near-field Explosions

Remaining Useful Life for Heavy-Duty Railway Cast Steel Knuckles Based on Crack Growth Behavior with Hypothetical Distributions

The current research on the integrity of critical structures of rail vehicles mainly focuses on the design stage, which needs an effective method for assessing the service state. This paper proposes a framework for predicting the remaining useful life (RUL) of in-service structures with and without visible cracks. The hypothetical distribution and delay time models were used to apply the equivalent crack growth life data of heavy-duty railway cast steel knuckles, which revealed the evolution characteristics of the crack length and life scores of the knuckle under different fracture failure modes. The results indicate that the method effectively predicts the RUL of service knuckles in different failure modes based on the cumulative failure probability curves for different locations and surface crack lengths. This study proposes an RUL prediction framework that supports the dynamic overhaul and state maintenance of knuckle fatigue cracks.

Experimental analysis of enhanced finite set model predictive control and direct torque control in SRM drives for torque ripple reduction

The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC.

Dynamic STEM-EELS for single-atom and defect measurement during electron beam transformations.

This study introduces the integration of dynamic computer vision-enabled imaging with electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). This approach involves real-time discovery and analysis of atomic structures as they form, allowing us to observe the evolution of material properties at the atomic level, capturing transient states traditional techniques often miss. Rapid object detection and action system enhances the efficiency and accuracy of STEM-EELS by autonomously identifying and targeting only areas of interest. This machine learning (ML)-based approach differs from classical ML in that it must be executed on the fly, not using static data. We apply this technology to V-doped MoS2, uncovering insights into defect formation and evolution under electron beam exposure. This approach opens uncharted avenues for exploring and characterizing materials in dynamic states, offering a pathway to increase our understanding of dynamic phenomena in materials under thermal, chemical, and beam stimuli.

Shallow-water redox evolution from the Ediacaran to the early Cambrian: Linkages to the early animal innovations

The oceanic oxygenation from the Ediacaran to the early Cambrian (ca. 635–520 Ma) has been commonly linked with the radiation or innovation of early metazoans. However, in this period, the spatio-temporal changes in redox states have not been well constrained for shallow seawater that is proposed to be potential habitats for most metazoans. Here, we report new iodine (I) concentration and Cerium anomaly (Ce/Ce*) data from two Ediacaran–Cambrian carbonate successions in South China. Combined with published data, the new database provides more insights into the evolution of shallow-water redox states on the continental margin. Overall low I/(Ca + Mg) (0.07–1.092 μmol/mol) and high Ce/Ce* (0.64–0.91) indicate frequent presence of low oxygen waters on the Yangtze margin in the early-middle Ediacaran (ca. 635–575 Ma). The initial increases of shallow-water oxygen levels occur from the middle Ediacaran (< ca. 575 Ma), coincident with the rise of the Ediacara biota. However, large variabilities of I/(Ca + Mg) (0.003–4.53) and Ce/Ce* (0.1–0.92) through different sections from the late Ediacaran to the early Cambrian (ca. 575–520 Ma) suggest highly dynamic redox states on both spatial and temporal scales before the Cambrian explosion in a narrow sense. The new I/(Ca + Mg) and Ce/Ce* data bolster the case that the Ediacaran–Cambrian oceans have much lower oxygenation levels than recent fully oxygenated oceans, and frequent redox fluctuations in habitats may have stimulated the early animal innovations.

Method of Equivalent Error as a Criterion of the Assessment of the Algorithms Used for Estimation of Synchrophasor Parameters Taken from the Power System.

The development of digital techniques in control engineering leads to the creation of innovative algorithms for measuring specific parameters. In the field of electric power engineering these parameters may be amplitude, phase and frequency of voltage or current occurring in the analyzed electric grid. Thus, the algorithms mentioned, applied in relation to the quoted parameters, may provide precise and reliable measurement results in the electric grid as well as ensure better grid monitoring and security. Signal analysis regarding its identification due to the type of interference is very difficult because the multitude of information obtained is very large. In order to indicate the best method for determining errors in measuring synchronous parameters of the measured current or voltage waveforms, the authors propose in this paper a new form of one error for all testing functions, which is called an equivalent error. This error is determined for each error's value defined in the applicable standards for each of selected 15 methods. The use of the equivalent error algorithm is very helpful in identifying a group of methods whose operation is satisfactory in terms of measurement accuracy for various types of disturbances (both in the steady state and in the dynamic state) that may occur in the power grid. The results are analyzed for phasor measurement unit (PMU) devices of class P (protection) and M (measurement).

Freezing-Tolerant Supramolecular Adhesives from Tannic Acid-Based Low-Transition-Temperature Mixtures.

Natural polyphenols like tannic acid (TA) have recently emerged as multifunctional building blocks for designing advanced materials. Herein, we show the benefits of having TA in a dynamic liquid state using low-transition-temperature mixtures (LTTMs) for developing freezing-tolerant glues. TA was combined with betaine or choline chloride to create LTTMs, which direct the self-assembly of guanosine into supramolecular viscoelastic materials with high adhesion. Molecular dynamics simulations showed that the structural properties of the material are linked to strong hydrogen bonding in TA-betaine and TA-choline chloride mixtures. Notably, long-term and repeatable adhesion was achieved even at -196 °C due to the binding ability of TA's catechol and gallol units and the mixtures' glass transition temperature. Additionally, the adhesives demonstrated injectability and low toxicity against fibroblasts in vitro. These traits reveal the potential of these systems as bioadhesives for tissue repair, opening new avenues for creating multifunctional soft materials with bioactive properties.

Identifying core IoT technologies using ARM and FCM: A comprehensive data-driven method

The internet of things (IoT) technology has garnered significant attention in recent years due to its wide-ranging applications. IoT, with its high connectivity capabilities, integrates various industrial, domestic, and agricultural devices into a smart and remotely controllable software and hardware platform. The field of IoT technology is expansive and encompasses a multitude of sub-technologies. Identifying core technologies in this domain is crucial for guiding research and development efforts by companies. Given the interrelation of these core technologies and their combination with recent decision-making approaches, network-based strategies have recently received special attention. The developed methods are based on static conditions and the assumption of stability, while in emerging technologies like IoT, the pace of changes over time is high. This leads to changes in the importance of technologies under various scenarios.In this study, in order to analyze the extracted patent data, association rule mining (ARM) algorithms were applied to identify the relationships between technologies and social network analysis was used to analyze the relationships between technologies and estimate their initial weights. Finally, fuzzy cognitive map (FCM) were used to estimate the final weights of technologies and rank them. The fcm approach allows for simultaneous modeling of both static and dynamic states of the system and, on the other hand, by calculating under various scenarios, suggests a core technology that is sustainable.The research results show that digital information transmission technologies, digital or electrical data processing, and wireless communication networks are the most important sub-technologies of Internet of things.

Symmetric periodic Reeb orbits on the sphere

A long standing conjecture in Hamiltonian Dynamics states that every contact form on the standard contact sphere S 2 n + 1 S^{2n+1} has at least n + 1 n+1 simple periodic Reeb orbits. In this work, we consider a refinement of this problem when the contact form has a suitable symmetry and we ask if there are at least n + 1 n+1 simple symmetric periodic orbits. We show that there is at least one symmetric periodic orbit for any contact form and at least two symmetric closed orbits whenever the contact form is dynamically convex.

Weibull distribution as a criterion of emergency levels

In the exploitation of machinery and equipment, one of the most important parameters is the dynamic state of the object. Observing residual processes is the most popular method of assessing the dynamic state. In particular, dynamic residual processes are a carrier of diagnostic information. Measuring the vibrations and noise of working mini-mining machines provides knowledge about the dynamics of the assessed machinery. Many years of knowledge and experience have allowed for the creation of diagnostic procedures. Within most machines used in the industry, the procedures considered standard allow for an effective diagnostic assessment and optimal management of mini-mining machine exploitation. The applicability of these standards is quite wide. However, there are machines with parameters that prevent the application of said standards. Mini-mining machines used in subterranean mining are one of these machines. In the case of diagnostic assessment of continuous miners, chain conveyors, as well as other machinery used in the technological chain, the usage of assessment brackets consistent with adopted standards is incorrect. In the diagnostic assessment of these types of mini-mining machines, an analysis of long-term trends is often used. The determination of acceptable vibration levels is obtained heuristically through observations of the damage up to the state of emergency. In the article, methods of mini mining machines state assessment using models of machine degradation, using Weibull distribution, are presented. The presented method has been used in real results of vibration measurement of underground machinery used in a coal mine. The analyses showed a large effectiveness of the presented method.

Emergent patterns in shape-asymmetric Quincke rollers

This study investigates the Quincke rolling phenomenon of snowman-shaped colloidal particles. These chiral rollers exhibit individual and collective dynamic states that depend upon the population and driving field strength. In addition to the previously identified dynamic states, such as spinning and vortex states, we identify the standing and bounded motion of the particles. The bounded motion involves the confined orbiting of particles around the center of mass due to hydrodynamic interactions at low particle area fractions. Our findings provide valuable insights into the behavior of active systems and the fabrication of active materials, emphasizing emergent order and adaptability as key guiding principles.

Eligibility traces in an autonomous soccer robot with obstacle avoidance and navigation policy

As the thematic literature of machine learning suggests, reinforcement learning falls between the two methods of supervised learning and unsupervised learning. In this method, the learning agent receives a reward or punishment from the environment according to its action. Therefore, the learning agent interacts with the environment through trial and error and learns to choose the optimal action to achieve its goal. In the meantime, the eligibility traces are considered as one of the main mechanisms of reinforcement learning in receiving delayed rewards. In the use of conventional reinforcement learning methods, when the learning agent achieves a goal, only the value function of the last state-action pair changes, but all the trace states are affected based on the eligibility traces. In other words, the delayed rewards are distributed throughout the trace. Like the ant pheromone effect, this method can increase learning speed empirically to some extent. A soccer robot on the field encounters moving obstacles such as balls, rival robots, and home robots, and fixed obstacles such as gates and flags, so its environment is in a very dynamic state. Therefore, due to the dynamic environment, it is an important issue for autonomous soccer robots to avoid obstacles and should be considered in real play. The main idea of this study is to determine the appropriate traces for the robot to move towards the ball and ultimately to score with the approach of avoiding obstacles in simulating a real soccer match. The desired results obtained from a game played indicate a high level of online experience and decision-making power in the face of new situations.

Floating wind-integrated PV system yield analysis considering AHSE dynamics & solar azimuth effects

Floating Photovoltaic (FPV) systems face dual challenges of structural reliability and high electricity costs in offshore deployments, hindering their widespread adoption. Integrating FPV with Floating Offshore Wind Turbines (FOWT) offers a promising solution to these challenges. A hybrid wind-solar system is proposed, leveraging mathematical modelling and simulation, with FPV system inheriting dynamic states from FOWT and employing a shared DC bus for power generation. Key findings reveal reduced power variation as solar elevation angle increases, with photovoltaic efficiency declining near the complementary angle of PV tilt offset. The FPV system demonstrates resilience to platform movements, ensuring over 97% efficiency even under significant wave heights. Additionally, greater pitch motion enhances power complementary effects between wind and solar energy. A proposed tilt offset control strategy effectively compensates for power fluctuations, particularly at lower wind-solar azimuth angles and higher solar elevation angles. Real-world based simulation in the Taiwan Strait validates these findings, emphasizing the potential of wind-solar coupled platforms for optimizing renewable energy performance in coastal regions.

Structure Evolution of 2D Covalent Organic Frameworks Unveiled by Single-Crystal X-ray Diffraction.

We report 9 crystal structures of a two-dimensional (2D) covalent organic framework (COF), including the parent Py-1P, 5 derivatives formed by chemical reactions, and 3 dynamic states by solvent exchange/loss. Structure details of these porous crystals, including stacking mode, interlayer distance, pore aperture, and incline angle, before, during, and after conversion processes in solution, were unveiled by single-crystal X-ray diffraction with resolutions up to 0.85 Å. The structure evolution is triggered by stepwise conformational transformation of the molecular building blocks in 2D COF, while their long-range ordering remained unsacrificed.

Research on control parameter optimization of LCC-HVDC system based on zero-pole optimal position distribution

The proportional-integral (PI) control is widely adopted as the leading controllers of the line-commutated converter high-voltage direct current transmission system (LCC-HVDC), while unreasonable coefficients setting will result in the DC system instability and aggravate system dynamic performance. In order to improve the overall response performance of the system, a tuning method of the controller parameters guided by the linearized zero-pole transfer function of the DC system is proposed. Firstly, the small signal analysis method is used to formulate the closed-loop transfer function model at the stable operating point. According to the position of zero and pole, the objective function which can quantitatively reflect the dynamic and steady state characteristics of the DC system is derived. Furthermore, combined with the particle swarm optimization (PSO) intelligent optimization algorithm, the multi-group control parameters of the system are optimized. Finally, by comparing the time domain numerical simulation results before and after parameter optimization, it is verified that the proposed tuning method can effectively improve the dynamic and steady-state characteristics of the DC system.

Interaction of acoustic pressure and heat release rate fluctuations in a model rocket engine combustor.

We experimentally clarify the interaction of acoustic pressure and heat release rate fluctuations during a transition to high-frequency combustion instability in a model rocket engine combustor. The dynamical state of acoustic pressure fluctuations undergoes a transition from high-dimensional chaotic oscillations to strongly correlated limit cycle oscillations. The coherent structure in the heat release rate field emerges with the initiation of weakly correlated limit cycle oscillations. The effect of the heat release rate on acoustic pressure fluctuations predominates during high-dimensional chaotic oscillations. In contrast, the effect of acoustic pressure on the heat release rate fluctuations markedly increases during the correlated limit cycle oscillations. These are reasonably shown by an ordinal pattern-based analysis involving the concepts of information theory, synchronization, and complex networks.