Dynamical Evolution Research Articles

Binary properties of the globular cluster 47 Tuc (NGC 104). A dearth of short-period binaries

Spectroscopic observations of binary stars in globular clusters are essential to shed light on the poorly constrained period, eccentricity, and mass ratio distributions and to develop an understanding of the formation of peculiar stellar objects. 47\,Tuc (NGC 104) is one of the most massive Galactic globular clusters, with a large population of blue stragglers and with many predicted but as-yet elusive stellar-mass black holes. This makes it an exciting candidate for binary searches. We present a multi-epoch spectroscopic survey of 47 Tuc with the VLT/MUSE integral field spectrograph to determine radial velocity variations for 21,699 stars. We find a total binary fraction in the cluster of $(2.4 consistent with previous photometric estimates, and an increased binary fraction among blue straggler stars, approximately three times higher than the cluster average. We find very few binaries with periods below three days, and none with massive dark companions. A comparison with predictions from state-of-the-art models shows that the absence of such short-period binaries and of binaries with massive companions is surprising, highlighting the need to improve our understanding of stellar and dynamical evolution in binary systems.

Delayed optical feedback-regulated artificial soliton molecule in a femtosecond optical parametric oscillator

Soliton molecules (SMs) play a crucial role in nonlinear optical systems, enriching our understanding of nonlinear science through the study of their interaction dynamics. While passively mode-locked fiber lasers offer an efficient platform for generating diverse types of SMs, the complex internal dynamics of the laser often pose challenges in achieving predetermined temporal separations between SMs. Here, we implement a delayed optical feedback technique within a femtosecond optical parametric oscillator, enabling the generation of SMs with precise and controllable temporal separations. A theoretical model, which models the intracavity iterations of the signal with a simplified Ikeda map, is proposed to study the impact of parametric gain, intracavity feedback delay, and cavity length on the internal separations of the SMs. Our experimental results confirm that adjusting the cavity length allows for producing desired temporal separations within SMs. To reveal the evolution dynamics of the SMs, we further develop a rigorous numerical model using the carrier-resolved Forward Maxwell Equation, which is capable of modeling ultra-broadband complex dynamics based on a single equation without relying on the slowly-varying envelope approximation. The numerical model unveils the rich formation dynamics of the SMs at various separations, which confirms the critical role of the gain window provided by the pump. This work opens up new opportunities for the on-demand generation of SMs and provides valuable insights into the complex dynamics in femtosecond optical parametric oscillator systems with optical delayed feedback.

Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model

Achieving sustainable development that harmonizes environmental protection with economic growth in the Yangtze River Economic Belt (YREB) remains a critical area of research. Examining green total factor productivity (GTFP) aids in pinpointing the key factors and pathways essential for fostering green economic development. On the basis of 108 prefecture-level cities in the YREB, a three-stage SBM-ML index model was constructed to measure the GTFP level from 2009 to 2022. ArcGIS software was used to analyze the spatiotemporal evolution of GTFP dynamically. Finally, the multidimensional factors affecting GTFP were systematically analyzed via the Tobit model. The study revealed that (1) GTFP exhibits notable spatial disparities among the upper, middle, and lower reaches of the YREB, with the downstream areas showing higher levels than the upstream and midstream areas do. (2) After excluding environmental factors and random errors, the true GTFP level significantly decreases, indicating a notable environmental masking effect, with a masking effect of up to 63.9%. (3) The spatial distribution of GTFP overall shows a “low-high-low-high” pattern from west to east, forming an “N”-shaped spatial pattern. (4) The Tobit model regression results show that government governance enhances GTFP, while economic growth and intergovernmental fiscal decentralization hinder real GTFP. Although urbanization was initially insignificant, it significantly boosted real GTFP post-COVID-19. Finally, policy recommendations to promote green development in river basins are proposed.

Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders

Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements.

Towards Accurate Biocompatibility: Rethinking Cytotoxicity Evaluation for Biodegradable Magnesium Alloys in Biomedical Applications

Magnesium and its alloys represent promising candidates for biomedical implants due to their biodegradability and mechanical properties, which are similar to natural bone. However, their rapid degradation process characterized by dynamic pH fluctuations and significant hydrogen gas evolution during biocorrosion adversely affects both in vitro and in vivo assessments. While the ISO 10993-5 and 12 standards provide guidelines for evaluating the in vitro biocompatibility of biodegradable materials, they also introduce testing variability conditions that yield inconsistent results. To address these inherent characteristics of Mg alloys, developing improved methods that accurately simulate the physiological environment for in vitro biocompatibility testing is essential. This study introduces two novel extraction approaches for evaluating Mg alloys: a buffered solution utilizing PBS/DMEM with quaternary dilutions and a modified ISO standard protocol employing decuple dilution of conventional unbuffered extracts. The present findings establish that controlled optimization of extraction conditions, specifically buffer composition and dilution parameters, enables reliable in vitro cytotoxicity assessment of Mg alloys, providing a robust methodology that advances the preclinical evaluation of these promising biodegradable materials.

Encourage or Reject Employee Involvement: Value Creation in Human Resource Management in the AI Era—An Evolutionary Game Analysis of Enterprises and Employees

In the context of globalization and rapid technological advancement, the introduction of Artificial Intelligence (AI) has brought new opportunities and challenges to Human Resource Management (HRM). This study constructs an evolutionary game model to explore the strategy choices and evolutionary paths of enterprises and employees in HRM value co-creation with AI involvement. We numerically simulated the dynamic evolution of strategies under different scenarios, revealing the equilibrium characteristics of strategic interactions between enterprises and employees in the AI context. The study finds that, first, the evolutionary game system between enterprises and employees converges to two equilibrium points: {cooperation, active} and {non-cooperation, passive}. Overall, the probability of the former is 2.39 times greater than that of the latter. Second, higher initial probabilities of cooperation and active involvement, along with lower costs for cooperation and active involvement, facilitate the system’s evolution towards the {cooperation, active} equilibrium. Third, enterprises are more sensitive to the benefit distribution ratio than employees. This study provides theoretical support for effectively conducting HRM practices in the AI era through systematic analysis of HRM value co-creation behavior, along with practical policy recommendations.

Revealing super-adiabatic features of interplanetary coronal mass ejections at 1 au

Interplanetary coronal mass ejections (ICMEs) are large-scale, coherent magnetic structures that play a pivotal role in heliospheric dynamics and space weather phenomena. Although thermodynamic analyses of ICME magnetic obstacles (MOs) at 1 au generally reveal adiabatic characteristics, the broader thermodynamic processes and associated plasma heating and cooling mechanisms remain insufficiently understood. In this study we analysed 473 ICME MOs observed at 1 au by the ACE spacecraft, utilising polytropic analysis to determine the polytropic index, $ for these structures. We identified 25 ICME MOs in which plasma protons exhibit a polytropic index $ 2.00$, with a mean value of $2.14 0.07$, indicating super-adiabatic behaviour. We also observed evidence of 12 isothermal ($ 1$) and 45 adiabatic ($ 5/3$) ICME MOs. Furthermore, in the case of super-adiabatic ICME MOs, we observe that all the total supplied heat is efficiently utilised to accomplish work in the surrounding environment, assuming the protons have three effective kinetic degrees of freedom. Therefore, as they expand, these ICMEs MOs cool faster than the adiabatic plasma. Our findings are critical to comprehending the dynamic evolution of ICMEs in interplanetary space and the energy-exchange mechanisms involved.

Dynamic Analysis for Enhancing Urban Resilience Against Public Health Emergencies of International Concern

The frequent occurrence of Public Health Emergencies of International Concern (PHEIC) has posed significant challenges to urban public health, economic, and social systems, exposing gaps in urban resilience. This study developed a dynamic urban resilience assessment framework against PHEIC based on the system dynamics method, integrating index analysis and the SEIR (susceptible–exposed–infectious–recovered) epidemiological model to investigate the interactions and dynamic evolution of urban subsystems in New York, Hong Kong, and Nanjing during the COVID-19 epidemic. The findings revealed significant differences in the response mechanisms and recovery capacities across subsystems. For example, the stringent lockdowns policy in New York curbed virus spread and heavily impacted economic activities; the “close to Dynamic zero of COVID-19” policy in Hong Kong demonstrated stronger resilience in balancing public health and economic recovery; the dynamic control measures in Nanjing China allowed for the rapid restoration of urban functions with minimal resilience fluctuations. Although strict control measures can effectively suppress disease spread, they can have profound economic and social impacts. More scientific strategies, such as those seen in Hong Kong and Nanjing, offer a more balanced approach to managing both epidemic control and urban function recovery, providing key insights for future PHEIC response strategies.

Prediction of Heavy Oil Production Based on Geomechanical Analysis in Entire Lifecycle of SAGD

ABSTRACTSteam‐assisted gravity drainage (SAGD) technology is an essential means of efficient development of heavy oil, super heavy oil, oil sands, and other unconventional resources in the world. Accurate prediction and evaluation of heavy oil output during SAGD production is a key step of construction optimization design and economic evaluation. The traditional prediction model of heavy oil production does not fully consider many geomechanical factors, such as rock deformation and permeability dynamic evolution. In this paper, a new mathematical model of crude oil production‐geomechanical coupling was established for three stages of the SAGD life cycle (steam chamber breakthrough stage, rising stage, and lateral dilation stage). The influence of the dynamic evolution of rock porosity and permeability on production was fully considered through the sensitivity coefficient of rock strain and permeability stress. It is found that the gap between the new model and the traditional model is larger when the strain and stress sensitivity of the reservoir body is larger. The value calculated by the conventional model is small when the reservoir dilates and large when the reservoir compresses. For Karamay heavy oil in Xinjiang, China, the steam breakout time predicted by the new model is 0.72, 1.50, 1.37, and 1.44 times the conventional model when the volumetric strain is 6%. The heavy oil production of Karamay, Xinjiang, China, Athabasca, and Cold Lake SAGD production areas in Canada was predicted. In the lateral dilation stage of the steam chamber, the predicted values of the model considering geomechanical factors were 1.44, 1.28, and 1.15 times the traditional model, respectively. This model can help field engineers obtain more accurate production of heavy oil and evaluate the significance of reservoir geomechanics in SAGD production.

Desentrañando el delito: un viaje por las principales teorías dogmáticas y los retos actuales

This article embarks on a journey through the transformative odyssey of Criminal Law Theory, tracing its dynamic and intricate evolution from a naturalistic conception of crime towards a broader and more intricate perspective, culminating in a degree of doctrinal convergence within the realm of the theory of objective imputation. In this ongoing process, the tireless efforts of legal scholars continue to generate novel propositions. Along this trajectory, both conduct and the formal conception of crime have become central subjects of debate and analysis, reflecting a quest for legal precision. While significant advancements have been made, these frameworks now confront novel and formidable challenges within the contemporary landscape of Criminal Law.

A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions

Currently, numerous intelligent maximum power point tracking (MPPT) algorithms are capable of tackling the global optimization challenge of multi-peak photovoltaic output power under partial shading conditions, yet they often face issues such as slow convergence, low tracking precision, and substantial power fluctuations. To address these challenges, this paper introduces a hybrid algorithm that integrates an improved salp swarm algorithm (SSA) with the perturb and observe (P&O) method. Initially, the SSA is augmented with a dynamic spiral evolution mechanism and a Lévy flight strategy, expanding the search space and bolstering global search capabilities, which in turn enhances the tracking precision. Subsequently, the application of a Gaussian operator for distribution calculations allows for the adaptive adjustment of step sizes in each iteration, quickening convergence and diminishing power oscillations. Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.

Quantum state transfer in a magnetic atoms chain using a scanning tunneling microscope

Abstract The electric control of quantum spin chains has been an outstanding goal for the few last years due to its potential use in technologies related to quantum information processing. In this work, we show the feasibility of the different steps necessary to perform controlled quantum state transfer and excitation transmission in a S = 1 / 2 titanium atoms chain employing the electric field produced by a scanning tunneling microscope (STM). Our results show that the initialization and transmission of a single excitation state is achievable in short times, and with high fidelity. Our study uses spin Hamiltonians to model the magnetic atoms chain, the tip of the STM, the interaction between it and the atoms chain and the electronic response to the fields applied by the tip, employing sets of parameters compatible with the latest experiments and ab initio calculations. The time dynamical evolution is considered in the full Hilbert space and the control pulses frequencies exerted by the tip of the microscope are within the reach of present day technology.

Climate Change‐Driven Long‐Term Stability Risks of Ubiquitous Moraine Dams in Glacial Lakes on Qinghai‐Tibet Plateau: A Multiphysics Coupling Evolution Perspective

AbstractGlacial lake‐moraine dam systems are widespread in cold alpine environments such as the Qinghai‐Tibet Plateau (QTP). Without climate change, the lake‐dam system exhibits stably dynamic evolution on a hydrological annual cycle. However, climate change may drive subtle alterations in the system's evolution. We developed a fully coupled Thermal‐Hydraulic‐Mechanical simulation platform considering ice‐water phase change, showing robust performance under CMIP6‐derived boundary conditions. Using this platform, we simulated climate warming‐driven multiphysics responses and dam stability evolutions of a homogeneous, simplified conceptual model of the lake‐dam system. We identified critical temperature thresholds for permanently frozen area thawing and abrupt changes in dam stability of this lake‐dam system. Considering the current slope stability situations on the QTP, the SSP 5–8.5 climate warming scenario is conservatively anticipated to pose significant geological safety risks due to potential disaster chains from glacial lake failures. Our study provides insights into profound geological process evolutions driven by climate change.

Reversible Manipulation of Polar Topologies in Oxide Ferroelectrics via Electric Fields.

Polar topologies show great potentials in memories and other nano-micro devices. To integrate with silicon conducting circuits, it is vital to understand the dynamic evolution and the transformation of different domain configurations under external stimulus. Here in situ transmission electron microscopy is performed and the electrically controlled creation and annihilation of large-scale polar flux-closure array from typical c/a domains in PbTiO3/SrTiO3 bilayers is directly observed. It is found that the transformation is reversible after removal of external electric fields. Increasing external electric fields on (PbTiO3/SrTiO3)5 multilayered films, it is further found that the flux-closure domains are nucleated and propagated via the steps of first the formation of new c domains and then connection with neighboring c domains. The transition from a/c domains to flux-closure arrays under electric fields is collaborated with evaluating energy variations by phase-field simulations in which the electrostatic energy plays an important role. These results demonstrate the polar topologies can be reversibly manipulated by external stimuli, which sheds light on further understanding the dynamics behavior of polar topologies and helps for future nanoelectric applications.

Effects of Seven-Year-Optimized Irrigation and Nitrogen Management on Dynamics of Soil Organic Nitrogen Fractions, Soil Properties, and Crop Growth in Greenhouse Production

Exploring the temporal evolution dynamics of different soil organic nitrogen (N) components under different water–N management practices is a useful approach to accurately assessing N supply and soil fertility. This information can provide a scientific basis for precise water and N management methods for greenhouse vegetable production. The objective of this study was to investigate the effects of optimized irrigation and nitrogen management on the dynamics of soil organic nitrogen fractions, soil properties, and crop growth. This research was conducted from 2017 to 2023 in a greenhouse vegetable field in North China. Four treatments were applied: (1) high chemical N application with furrow irrigation (farmers’ practice, FP); (2) no chemical N application with drip irrigation (DN0); (3) 50% N of FP with drip irrigation (DN1); and (4) 75% N of FP with drip irrigation (DN2). The volume in drip irrigation is 70% of that in furrow irrigation. The results showed that in 2023 (after seven years of field trials), compared with FP, the soil organic carbon (SOC), total N, and water use efficiency of the DN1 and DN2 treatments increased by 15.9%, 11.4%, and 11.3% and 7.7%, 47.2% and 44.6%, respectively. However, there was no significant difference in the total crop yield except in the DN0 treatment. Soil organic N was mostly in the form of acid-hydrolyzed N (AHN). After seven years of optimized irrigation and N management, the DN1 treatment significantly increased the content of ammonium N (AN) and amino sugar N (ASN) in AHN compared with the FP treatment. The results of further analysis demonstrated that SOC was the main factor in regulating AHN and non-hydrolyzable N (NHN), while the main regulatory factors for amino acid N (AAN) and ASN in the AHN component were dry biomass and water use efficiency, respectively. From a time scale perspective, optimization of the water and N scheduling, especially in DN1 (reducing the total irrigation volume by 30% and the amount of N applied by 50%), is crucial for the sustainable improvement of soil fertility and the maintenance of vegetable production.

Effect of Weld-Pass Morphology and Molten-Pool Flow on Lack of Fusion Formed in the Fully Automatic Welded Joint at 6 o’Clock Direction

Compared with traditional shielded metal arc welding and semi-automatic welding, fully automatic welding has the advantages of fast welding speed, high welding quality as well as a high qualification rate on the premise of ensuring the comprehensive performance of the girth weld joint. Meanwhile, the proportion of welding defects also changed from porosity and slag inclusion to lack of fusion. Therefore, from the view of the macroscopic and dynamic evolution behavior, the paper aims to reveal the influence of the coupling of weld-pass morphology and molten-pool flow on the formation of lack of fusion using macroscopic metallographic observation and high-speed photography. The results indicate that the weld morphology is prone to convex reinforcement and larger penetration depth in the 6 o’clock direction of the pipeline girth weld under the reference parameters. The excessive reinforcement of the pass to be welded is one of the sufficient conditions for the formation of a lack of side fusion in the 6 o’clock direction. Excessive reinforcement could lead to welding arc heat mainly used to melt the raised weld metal to be welded, which results in insufficient heat flow to both sides of the molten pool metal. Furthermore, due to the larger curvature radius at the groove and the increase of the surface tension of the molten pool with lower relative temperature, the flow resistance of the molten pool increases and the fluidity decreases.

Dynamic Characteristics of Gear System Under Compound Fault of Tooth Root Crack and Bearing Outer Ring

Research on single faults like tooth root cracks and bearing outer ring failures is well-established. However, existing studies often replace the actual crack propagation path with a simplified linear crack model, neglecting the variation in stress intensity factors. They do not account for the coupling effect between gear teeth when calculating gear mesh stiffness. In practice, gearbox failures are predominantly compound failures involving both gears and bearings. This paper simulates the actual crack propagation path based on Workbench, introduces a dual-tooth meshing zone method to address the tooth-to-tooth coupling effect, and establishes a dynamic model of a system with compound faults of tooth root cracks and bearing outer ring defects. The dynamic response of the system under different levels of deterioration is then investigated. The findings indicate that the crack propagation path exhibits a concave shape, with the curvature of the path increasing as the crack deteriorates. The time-varying mesh stiffness calculated by considering tooth-to-tooth coupling effects aligns more closely with the finite element results. By analyzing the evolution patterns of the impact components and sidebands during the deterioration process, the dynamic evolution trends of the coupling phenomenon between tooth root cracks and bearing outer ring faults are clarified.

Dynamic Evolution of the Power Structure and Contracting State Status in the Regional Trade Agreement Network and Its Trade Feedback Effects

ABSTRACT Against the backdrop of the serious setback in WTO multilateral negotiations, countries around the world have signed a large number of regional trade agreements (RTAs) to further reduce trade barriers and promote trade liberalization. These RTAs have formed a complex network of crisscrossing and mutually reinforcing dependencies that reshape the trade effects of individual RTAs. This paper uses the complex network analysis method to discuss the construction and development issues of RTAs among countries around the world and reveals the historical changes in the power structure of the economic and trade rules network and the dynamic evolution of the network status of core countries in international trade since 1995. Based on this, the feedback mechanism of the overall structure of the network and the node country status on the trade effect of RTAs is explored and tested. The analysis results show the following: (1) The global RTA network follows a power law distribution, the unbalanced characteristics of bipolarization in international economic and trade rules are very significant, and the gap in national network status is enormous. European countries are almost always in the center of the network, and China’s network status has not improved significantly. (2) The network shows obvious competitive and balancing relationships, and the pattern of international economic and trade rules has a trend toward short-term multi-polarization. (3) The test results of the trade effect feedback mechanism of the network show that the redundancy relationship of the overall network and the concentration of power structure have a negative influence on the trade effect of RTAs, while the bridging cluster function and transitivity of the overall network have a positive feedback effect on the trade effect of RTAs. The core position and control of a single country in the network form a positive feedback and high return on the trade effect of RTAs.

Unraveling the impact of SARS-CoV-2 mutations on immunity: insights from innate immune recognition to antibody and T cell responses

Throughout the COVID-19 pandemic, the emergence of new viral variants has challenged public health efforts, often evading antibody responses generated by infections and vaccinations. This immune escape has led to waves of breakthrough infections, raising questions about the efficacy and durability of immune protection. Here we focus on the impact of SARS-CoV-2 Delta and Omicron spike mutations on ACE-2 receptor binding, protein stability, and immune response evasion. Delta and Omicron variants had 3–5 times higher binding affinities to ACE-2 than the ancestral strain (KDwt = 23.4 nM, KDDelta = 8.08 nM, KDBA.1 = 4.77 nM, KDBA.2 = 4.47 nM). The pattern recognition molecule mannose-binding lectin (MBL) has been shown to recognize the spike protein. Here we found that MBL binding remained largely unchanged across the variants, even after introducing mutations at single glycan sites. Although MBL binding decreased post-vaccination, it increased by 2.6-fold upon IgG depletion, suggesting a compensatory or redundant role in immune recognition. Notably, we identified two glycan sites (N717 and N801) as potentially essential for the structural integrity of the spike protein. We also evaluated the antibody and T cell responses. Neutralization by serum immunoglobulins was predominantly mediated by IgG rather than IgA and was markedly impaired against the Delta (5.8-fold decrease) and Omicron variants BA.1 (17.4-fold) and BA.2 (14.2-fold). T cell responses, initially conserved, waned rapidly within 3 months post-Omicron infection. Our data suggests that immune imprinting may have hindered antibody and T cell responses toward the variants. Overall, despite decreased antibody neutralization, MBL recognition and T cell responses were generally unaffected by the variants. These findings extend our understanding of the complex interplay between viral adaptation and immune response, underscoring the importance of considering MBL interactions, immune imprinting, and viral evolution dynamics in developing new vaccine and treatment strategies.

Time/Event‐Triggered Exponential Stabilization for Stochastic Systems: Enhancing Nonlinearity Tolerance

ABSTRACTThis article seeks the enhancement of nonlinearity tolerance in time/event‐triggered stabilization for stochastic systems. In the related results, the controller functions are required to obey global Lipschitz condition for the suppression of sampling/execution error, and the drift and/or diffusion coefficients of the stochastic systems are restricted to polynomial or, even, linear growth. These limitations deserve overcoming for enlarged applications. To this end, a distinct framework of time/event‐triggered controls is established for stochastic systems, targeted at exponential stabilization. Specifically, inclusive Lyapunov‐type feasibility conditions are proposed by capturing the effect of sampling/execution error and distinguishing the role of system nonlinearities. Particularly, different from the related results, the evolution of sampling/execution error is subtly exploited via Lyapunov functions to reveal the dynamic interaction between the sampling/execution errors and system state. Then, time‐triggered exponential stabilization via sampled‐data controller is achieved not only in the moment sense but also in the almost sure sense. Accordingly, Lyapunov function based analysis is performed for the composite dynamics of system state and sampling error, confronted with the coupling of discontinuous and stochastic features. To further reduce execution, periodic event‐triggered control is exploited to achieve exponential stabilization for stochastic nonlinear systems, by virtue of the relation with the dynamic evolution under sampled‐data control. Through typical examples, we demonstrate the potential of our framework in handling the cases with the controller functions violating global Lipschitz condition and with the system nonlinearities beyond polynomial growth.