Response Of System Research Articles

Research on the nonlinear resonance response of the high-speed spindle system supported by preloaded ball bearings

Research on the nonlinear resonance response of the high-speed spindle system supported by preloaded ball bearings

Metabolomic Analysis Reveals the Linkage between Sleep-Enhancing Effects and Metabolite Biomarkers and Pathways of Different Casein Hydrolysates in Chronic Unpredictable Mild Stressed Mice.

Casein hydrolysates have been proven to exert varying sleep-enhancing and anxiolytic effects due to their distinct release of potential peptides. However, their underlying sleep-enhancing mechanisms at the metabolic level remain unclear. This study aims to investigate the potential sleep-enhancing mechanism of casein hydrolysates through an integrated approach of untargeted and targeted metabolomics in CUMS-induced anxiety mice for the first time. The results showed seven potential biomarkers were identified and screened using orthogonal partial least-squares discriminant analysis, random forest model, and pathway analysis, including ornithine, l-proline, l-prolinamide, inhibitory neurotransmitters gamma-aminobutyric acid, 5-HIAA, fumaric acid, and 4-oxoglutaramate. Moreover, casein hydrolysates exerted sleep-enhancing effects through multiple metabolic pathways, mainly including the GABAergic system, tryptophan metabolism, and cAMP response signaling pathway, which was validated by targeted metabolomics and vital protein expressions. It was interesting that casein hydrolysates with diverse representative peptide compositions exhibited varying activity, which could be attributed to distinct alterations in metabolites via different pathways.

A temperature-ultrasound sensitive nanoparticle delivery system for exploring central neuroinflammation mechanism in stroke-heart syndrome

BackgroundCardiovascular events secondary to stroke–collectively classified as stroke-heart syndrome–greatly impair the patient’s prognosis, however its underlying mechanism has yet to be determined. To investigate the mechanism of central neuroinflammation and its effects on stroke-heart syndrome, a temperature-ultrasound responsive brain-targeted drug delivery system, DATS/MION-LPE, was synthesized to specifically study neuroinflammation in the mouse middle cerebral artery occlusion (MCAO) model.ResultsThe specific polymer of DATS/MION-LPE can close the nanoparticle pores at 37 °C, restricting drug release in the circulation. After the nanoparticles were targeted to brains, the polymer can be cleaved under external ultrasound irradiation, reopening the nanoparticle pores and allowing drug release, therefore directly managing the neuroinflammation. After a stroke, a significant cerebral inflammation occurred, with elevated IL-1β and pyrin domain-containing 3 (NLRP3) inflammasome. Accordingly, significantly increased histone deacetylase 6 (HDAC6) and decreased sirtuin 1 (SIRT1) were observed. An antagonistic relationship between HDAC6 and SIRT1 was found, which can jointly regulate the cerebral NLRP3 expression. The systemic IL-1β and ATP levels were increased after the stroke, accompanied by a significant heart injury including contractile dysfunction, elevated IL-1β levels, and oxidative stress. Meanwhile, neuroinflammation can trigger sympathetic nervous overexcitation with associated heart damage. DATS/MION-LPE can targetedly effect on ischemic brain, exhibiting cerebral and cardiac protective effects including downregulated cerebral NLRP3 and HDAC6 expressions, upregulated SIRT1 expressions in brain, reduced IL-1β and ATP in circulation, and alleviated cardiac impairment.ConclusionThis study introduced the key role of neuroinflammation in stroke-heart syndrome and first investigated the crucial HDAC6/SIRT1-NLRP3 circuit in this process. Heart injury secondary to stroke is mediated by neuroinflammation induced systemic inflammatory responses and sympathoexcitation. DATS/MION-LPE is a unique tool and effective therapeutic agent, which provides new insights into combinational heart and cardiac protection.Graphical

The Impact of Education Management Systems on the Success of Implementing Islamic Curriculum in Indonesian Higher Education Institutions

Islamic education is equally important in a Muslim's life as any other level of education. To assess the successful inclusion of Islamic education in Indonesian higher education institutes, this study looked into the successful execution of the Islamic education curriculum via the education management system. The study used a qualitative research approach, with higher education institutes inside Indonesia's demographic boundaries being investigated and data collected. Semi-structured interviews were used to obtain data from higher authorities and administrative workers who interact with the Islamic curriculum in higher education establishments. The data was analysed using thematic analysis, which resulted in various themes indicating several potential constructs that defined the successful implementation of the Islamic education curriculum, such as systematic approaches, cultural alignment, structured decision making, agile response systems, and so on. The contributions, limits, and future ideas are discussed in the peripheral portions of the study.

Safety, clinical activity, pharmacodynamics, and pharmacokinetics of IMU-856, a SIRT6 modulator, in coeliac disease: a first-in-human, randomised, double-blind, placebo-controlled, phase 1 trial

IMU-856 is an orally available and systemically acting small molecule modulator of sirtuin 6 (SIRT6), a protein that serves as a transcriptional regulator of bowel epithelium regeneration. We aimed to evaluate the safety, clinical activity, pharmacodynamics, and pharmacokinetics of IMU-856 in healthy participants and in patients with coeliac disease. This study reports the results from a completed first-in-human, three-part, double-blind, randomised, placebo-controlled, clinical trial of IMU-856 in healthy participants and patients with coeliac disease done in Australia and New Zealand. In part A, healthy participants were enrolled in six cohorts and randomly assigned (3:1) using a block randomisation algorithm to receive single ascending doses of IMU-856 ranging from 10 mg to 160 mg or matching placebo. Based on the results from part A, three doses were selected for part B to evaluate the safety, tolerability, and pharmacokinetics of IMU-856 once daily for 14 days using the same randomisation algorithm. Part C enrolled patients with well controlled coeliac disease. Participants were centrally randomised 1:1:1 using an interactive web response system to receive either low dose or high dose of IMU-856 or placebo once daily for 28 days that included a 15-day gluten challenge starting on day 14. The primary objective was safety and tolerability of IMU-856. Safety analyses were done on all patients who received at least one dose of the study drug. The trial is registered with the ANZCTR registry (ACTRN12620000901909). Between July 27, 2020, and Oct 28, 2022, 71 healthy participants were enrolled in part A and B and assigned to either placebo (n=19) or IMU-856 (n=52). In part A and B, the IMU-856 doses were 10 mg (n=6), 20 mg (n=6), 40 mg (n=13), 80 mg (n=12), 120 mg (n=4), 160 mg (n=11). 43 patients with coeliac disease were enrolled in part C and assigned to either placebo (n=14), IMU-856 80 mg (n=14), or IMU-856 160 mg (n=15). Treatment-emergent adverse events (TEAEs) occurred in 24 (73%) of 33 participants in part A and 15 (79%) of 19 participants in part B receiving any dose of IMU-856 compared with six (50%) of 12 participants in part A and five (71%) of seven participants in part B with placebo. TEAEs were mainly mild in severity. In part C, TEAEs occured in 26 (90%) of 29 patients on any dose of IMU-856 and ten (71%) of 14 receiving placebo; the most common TEAEs with any dose of IMU-856 by preferred term were headache (13 [45%] of 29), nausea (nine [31%]), diarrhoea (eight [28%]), and abdominal distension (seven [24%]). Two serious adverse events occurred with IMU-856 treatment (one in part B [bacterial myocarditis] and one in part C [biliary colic]), both of which were unrelated to IMU-856. No dose-limiting toxicities, systematic safety laboratory changes, or deaths occurred during the study. In part C, mean decrease in villous height was -20·9 μm (SD 34·8) among patients who received IMU-856 80 mg, -22·5 μm (51·1) among those who received IMU-856 160 mg, and -60·3 μm (52·2) among those who received placebo. The favourable safety profile, along with preliminary activity, suggests that IMU-856 should be studied in future trials of coeliac disease. Immunic Australia.

Bioinformatic Workflows for Deriving Transcriptomic Points of Departure: Current status, Data Gaps, and Research Priorities.

There is a pressing need to increase the efficiency and reliability of toxicological safety assessment for protecting human health and the environment. While conventional toxicology tests rely on measuring apical changes in vertebrate models, there is increasing interest in the use of molecular information from animal and in vitro studies to inform safety assessment. One promising and pragmatic application of molecular information involves the derivation of transcriptomic points of departure (tPODs). Transcriptomic analyses provide a snapshot of global molecular changes that reflect cellular responses to stressors and progression toward disease. A tPOD identifies the dose level below which a concerted change in gene expression is not expected in a biological system in response to a chemical. A common approach to derive such a tPOD consists of modeling the dose-response behavior for each gene independently and then aggregating the gene-level data into a single tPOD. While different implementations of this approach are possible, as discussed in this manuscript, research strongly supports the overall idea that reference doses produced using tPODs are health protective. An advantage of this approach is that tPODs can be generated in shorter term studies (e.g., days) compared to apical endpoints from conventional tests (e.g., 90-day sub-chronic rodent tests). Moreover, research strongly supports the idea that reference doses produced using tPODs are health protective. Given the potential application of tPODs in regulatory toxicology testing, rigorous and reproducible wet and dry laboratory methodologies for their derivation are required. This review summarizes the current state of the science regarding the study design and bioinformatics workflows for tPOD derivation. We identify standards of practice and sources of variability in tPOD generation, data gaps, and areas of uncertainty. We provide recommendations for research to address barriers and promote adoption in regulatory decision making.

A Health Economics Inquiry into Regulatory Constraints on the European Tobacco Market.

Despite the implementation of significant measures by European countries in recent years, smoking rates in Europe remain persistently high. TheEuropean Commission is currently undertaking a comprehensive review of itstobacco regulations. This article aims to address critical inquiries that arise during the amendment of the regulatory framework. We evaluate the effectiveness of existing tobacco control methods and observe a diminishing impact on promoting smoking cessation. Additionally, we explore how individuals of varying genders respond to the regulatory environment. We propose a comprehensive and evidence-based framework for implementing a taxation system in response to the proliferation of emerging products, including e-cigarettes and heated tobacco. This system is designed to align effectively with health policy objectives, providing a strategic approach to curbing tobacco use and promoting public health.

Inoculation with multifunctional Bacillus sp. NEAU-DCB1-2 mitigates chromium toxicity in pakchoi (Brassica rapa ssp. chinensis) through a multi-level mechanism

Soil chromium (Cr) accumulation is escalating, severely hindering plant growth and development. Plant growth-promoting bacteria (PGPB) have shown potential in enhancing plant tolerance to heavy metals. However, the role and mechanisms of Cr(VI)-reducing PGPB strains in improving the growth of pakchoi under Cr toxicity remain unclear. This study aimed to isolate a Cr(VI)-reducing PGPB strain from Cr-contaminated soil, evaluate its effect on pakchoi growth under Cr(VI) stress, and investigate the mechanisms involved. Our findings showed that Bacillus sp. NEAU-DCB1–2 effectively reduce Cr(VI) to Cr(III) and produced indole-3-acetic acid and siderophores. Under Cr(VI) stress, inoculation with NEAU-DC1–2 significantly promoted seed germination and early growth of pakchoi. In pot experiments, NEAU-DCB1–2 significantly increased biomass accumulation, plant height, and root length of Cr(VI)-treated pakchoi seedlings, while reducing the Cr(VI) content in root, shoot and soil. Moreover, NEAU-DCB1–2 greatly increased catalase, superoxide dismutase, peroxidase, and ascorbate peroxidase activities in seedlings under Cr(VI) stress, thereby reducing malondialdehyde content. Transcriptome analysis indicated substantial alterations in gene expression patterns after inoculation with NEAU-DCB1–2 under Cr(VI) stress. Further analyses revealed that NEAU-DCB1–2 mainly affected the responses of antioxidant system, metal chelation and transport, together with auxin, abscisic acid, and jasmonic acid signaling to Cr(VI) stress. Conclusively, the Cr(VI)-reducing PGPB strain NEAU-DCB1–2 significantly enhances the growth and Cr tolerance of pakchoi through multiple mechanisms, offering a valuable microbial resource for mitigating the adverse effects of heavy metal contamination in agricultural soils on the yield and safety of vegetable crops.

Study on improved control strategy of virtual synchronous generator

Virtual synchronous generator (VSG) control technology for photovoltaic, energy storage, wind power, and other new energy to provide flexibility in the grid interface characteristics, is conducive to improving the stability of the power system, and has been widely considered by many scholars. Firstly, an improved VSG control method is proposed through simulation and analysis, which realizes the complete decoupling of the frequency response time constant and the inertia quantity of the active power control loop and reduces the complexity of the parameter design of the VSG system. Secondly, to avoid the frequent action of the VSG system caused by small-scale frequency change perturbation, this study proposes a VSG frequency optimization control method for VSG frequency control with rated angular velocity ωset feedforward composed of multivariate factors when considering a primary frequency regulation dead zone. Thirdly, the impact of VSG parameter design on the system is investigated through the system response characteristics of power scheduling, primary frequency regulation at the grid connection, and the small-signal dynamic characterization of the improved VSG. Finally, Simulation and experimental verification yielded an active power overshoot of 7% and a maximum frequency deviation of 0.17 Hz for the improved system. The improved control method resulted in an improvement of 0.1 s in the frequency response time and a reduction of 0.15 Hz in the oscillation amplitude. The response speed of the improved control method is much better, while the oscillation amplitude is reduced to meet the grid's regulation requirements. The simulation and experimental analysis verify the feasibility of the improved VSG control method.

System response time and optimal path

Abstract In this work we study, in general terms, the optimal path for an out-of-equilibrium process from a geometric perspective constructed from a probability density function belonging to the exponential family (PDFE). With this objective we have constructed the speed of entropy production for a system out of equilibrium. This speed of entropy production is not determined with respect to the clock time t but rather with respect to a dimensionless time ξ t associated with a characteristic response time of each system λ t . In this context, we demonstrate that the constant entropy production speed condition leads to the system moving on a geodesic of the manifold constructed from the probability density function. In the last part of this work we apply our general results to study the Ornstein–Uhlenbeck process (OU), which is a well-known stochastic process that strictly speaking describes the velocity of a Brownian particle under the influence of friction. As the system evolves we find that dimensionless time ξ t passes slower than clock time t.

A Geometric Numerical Integration with Simple Cell Mapping for Global Analysis of Nonlinear Dynamical Systems

In order to improve the efficiency in computing the global properties of nonlinear systems, some effective methods have been proposed for the global analysis of these systems. However, there are only few investigations focusing on the numerical algorithms of the system response trajectories. This paper presents a higher-efficiency geometric numerical integration method with simple cell mapping for solving the basins of attraction of nonlinear systems. This numerical algorithm is based on the rule of Lie derivative, using it to calculate the trajectories of the nonlinear systems. Then, the global structure is studied by the numerical algorithm associated with a simple cell mapping method. Compared with the traditional Runge–Kutta methods of orders 4 and 5, it is demonstrated that the proposed Lie derivative iterative algorithm has significant advantages in efficiency.

Modular parametric PGD enabling online solution of partial differential equations

In the present work, a new methodology is proposed for building surrogate parametric models of engineering systems based on modular assembly of pre-solved modules. Each module is a generic parametric solution considering parametric geometry, material and boundary conditions. By assembling these modules and satisfying continuity constraints at the interfaces, a parametric surrogate model of the full problem can be obtained. In the present paper, the PGD technique in connection with NURBS geometry representation is used to create a parametric model for each module. In this technique, the NURBS objects allow to map the governing boundary value problem from a parametric non-regular domain into a regular reference domain and the PGD is used to create a reduced model in the reference domain. In the assembly stage, an optimization problem is solved to satisfy the continuity constraints at the interfaces. The proposed procedure is based on the offline–online paradigm: the offline stage consists of creating multiple pre-solved modules which can be afterwards assembled in almost real-time during the online stage, enabling quick evaluations of the full system response. To show the potential of the proposed approach some numerical examples in heat conduction and structural plates under bending are presented.

The Impact of Perfluorooctanoic Acid (PFOA) on the Mussel Mytilus galloprovincialis: A Multi-Biomarker Evaluation

Perfluorooctanoic acid (PFOA) has been widely studied due to its environmental persistence and bioaccumulation potential, raising concerns about its effects on aquatic life. This research evaluates the impact of PFOA on the antioxidant defenses and stress response systems of the mussel Mytilus galloprovincialis. Mussels were exposed to three concentrations of PFOA (1, 10, and 100 µg·L−1) over 28 days. Several biomarkers, including glutathione S-transferase (GST), superoxide dismutase (SOD), catalase (CAT), lipid peroxidation (LPO), total antioxidant capacity (TAC), vitellogenin (VTG), ubiquitin (UBI), and caspase-3 (CASP) were analyzed. The results suggest stress responses, particularly in animals exposed to higher concentrations, as shown by GST and SOD activities which increased according to PFOA concentrations. Additionally, oxidative stress markers such as MDA and CAT showed variable responses depending on the exposure concentration tested. This study underscores the need for further investigation into the effects of PFOA on mollusks but also the need to unveil gender-specific responses in aquatic organisms exposed to this contaminant. The concentrations of PFOA used in our research are lower than those examined in previous studies, providing crucial insights into the impacts of even minimal exposure levels. It highlights the potential of M. galloprovincialis as a bioindicator in environmental monitoring programs, providing crucial insights for environmental management and policymaking regarding regulating and monitoring PFOA in marine settings. Consequently, in a country where seafood consumption is the second largest in Europe, implementing environmental policies and regulatory measures to manage and monitor PFOA levels in marine environments is crucial.

Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change.

Dynamic behavior of high-speed maglev guideway girders with quadratically-varied cross-section

This study focuses on the numerical investigation on the coupling vibration responses of high-speed maglev vehicle-guideway system incorporated with guideway girders with quadratically-varied cross-section and the new generation high-speed maglev trains. Finite element model for the coupling vibration responses analysis of maglev vehicle-guideway system was established and validated against the existing field test results. With the verified model and program, a total of 5292 numerical models were included to comprehensively investigate the influences of cross-sectional geometries and span length of the guideway girder as well as the vehicle speed on the coupling vibration responses of high-speed maglev vehicle-guideway system. The coupling vibration responses, including impact coefficient, maximum suspension gap and maximum displacement of bogie as well as maximum displacement of the car-body, were analyzed. Recommendation on the dynamic performance indicator was proposed for the guideway girders with quadratically-varied cross-section. Prediction models regarding the impact coefficient and mid-span maximum acceleration of guideway girders with quadratically-varied cross-section were developed based on the Artificial Neural Network analysis method.

Cytometry masked autoencoder: An accurate and interpretable automated immunophenotyper.

Single-cell cytometry data are crucial for understanding the role of the immune system in diseases and responses to treatment. However, traditional methods for annotating cytometry data face challenges in scalability, robustness, and accuracy. We propose a cytometry masked autoencoder (cyMAE), which automates immunophenotyping tasks including cell type annotation. The model upholds user-defined cell type definitions, facilitating interpretability and cross-study comparisons. The training of cyMAE has a self-supervised phase, which leverages large amounts of unlabeled data, followed by fine-tuning on specialized tasks using smaller amounts of annotated data. The cost of training a new model is amortized over repeated inferences on new datasets using the same panel. Through validation across multiple studies using the same panel, we demonstrate that cyMAE delivers accurate and interpretable cellular immunophenotyping and improves the prediction of subject-level metadata. This proof of concept marks a significant step forward for large-scale immunology studies.

Maximal exercise capacity, peripheral muscle strength, sleep quality, and quality of life in adult patients with stable asthma

Objective The prevalence of asthma is increasing gradually worldwide. The pathophysiological process of asthma causes some alterations in the respiratory system and decreases oxygen-carbon dioxide exchange and respiration volume. These alterations may affect maximal exercise capacity, peripheral muscle strength, sleep quality, and disease-specific quality of life but have yet to be comprehensively investigated. To compare maximal exercise capacity, pulmonary function, peripheral muscle strength, dyspnea, sleep quality, and quality of life in adult patients with asthma, healthy controls were aimed. Methods Forty-one adult stable asthmatic patients (GINA I–III) and 41 healthy subjects were compared. Exercise capacity (cardiopulmonary exercise test [CPET]), pulmonary function (spirometry), peripheral muscle strength (dynamometer), dyspnea (modified Medical Research Council [mMRC] dyspnea scale), quality of life (Asthma Quality of Life Questionnaire [AQLQ]) and sleep quality (Pittsburgh Sleep Quality Index [PSQI]) were evaluated. Results Peak VO2, VO2kg, MET, VE, HR, %VE, %HR, VCO2 parameters of CPET, FVC, FEV1, FEF25–75%, and FEV1/FVC and quadriceps femoris, shoulder abductors, and hand grip muscle strength were significantly decreased in patients with asthma (p < 0.05). MMRC dyspnea scale score was increased, and AQLQ and PSQI scores decreased in asthma patients (p < 0.05). Conclusions Cardiac and pulmonary system responses to peak exercise worsened, and maximal exercise capacity and peripheral muscle strength decreased in adult patients with stable asthma. In addition, dyspnea during daily activities increases, and quality of life and sleep quality are impaired. A variety of exercise training that would benefit asthmatic patients’ outcomes should be investigated.

A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty

Abstract Inverse uncertainty quantification commonly uses the well established Bayesian framework. Recently, alternative interval methodologies have been introduced. However, in their current state of the art implementation, both techniques suffer from a large and usually unpredictable computational effort. Thus, both techniques are not applicable in a real-time context. To achieve a low-cost, real-time solution to this inverse problem, we introduce a deep-learning framework consisting of unsupervised auto-encoders and a shallow neural network. This framework is trained by means of a numerically generated dataset that captures typical relations between the model parameters and selected measured system responses. The performance and efficacy of the technique is illustrated using two distinct case studies. The first case involves the DLR AIRMOD, a benchmark case that has served as reference case for the inverse uncertainty quantification problem. The results demonstrate that the achieved accuracy is on par with the existing interval method found in literature, while requiring only a fraction of its computational resources. The second case study examines a resistance pressure welding process, which is known to require extremely fast monitoring and control due to the high process throughput. Based on the proposed method, and with only a limited selection of simulated responses of the process, it is possible to identify the interval uncertainty of the crucial parameters of the process. The computational cost in this case makes it possible for an inverse uncertainty quantification in a real-time setting.

Adaptive Management of Multi-Scenario Projects in Cybersecurity: Models and Algorithms for Decision-Making

In recent years, cybersecurity management has increasingly required advanced methodologies capable of handling complex, evolving threat landscapes. Scenario network-based approaches have emerged as effective strategies for managing uncertainty and adaptability in cybersecurity projects. This article introduces a scenario network-based approach for managing cybersecurity projects, utilizing fuzzy linguistic models and a Takagi–Sugeno–Kanga fuzzy neural network. Drawing upon L. Zadeh’s theory of linguistic variables, the methodology integrates expert analysis, linguistic variables, and a continuous genetic algorithm to predict membership function parameters. Fuzzy production rules are employed for decision-making, while the Mamdani fuzzy inference algorithm enhances interpretability. This approach enables multi-scenario planning and adaptability across multi-stage cybersecurity projects. Preliminary results from a research prototype of an intelligent expert system—designed to analyze project stages and adaptively construct project trajectories—suggest the proposed approach is effective. In computational experiments, the use of fuzzy procedures resulted in an over 25% reduction in errors compared to traditional methods, particularly in adjusting project scenarios from pessimistic to baseline projections. While promising, this approach requires further testing across diverse cybersecurity contexts. Future studies will aim to refine scenario adaptation and optimize system response in high-risk project environments.

Fully coupled thermal-structural-vibration characteristics of 3-axis machine tools with complex hybrid linear axis-spindle systems considering structural nonlinearities

For machine tools composed of functional components bonded by joints with structural nonlinearities, the load- and temperature-dependent nonlinear restoring force,stiffness, and frictional heat generationfrom the jointdetermine its complex dynamic fully coupled thermal-structural-vibration characteristics. In response, in this work, considering the vibration feedback dominated by the structural vibration and employing a partition-based closed-loop iterative algorithm, a fully coupled thermal-structural-vibration model that characterizes the nonlinear coupling between temperature and mechanical fields is developed with the joint as the link. The multi-body dynamics model of the whole machine tool, considering the flexibility of the screw shaft, spindle, and joint nonlinearity, characterizes the milling dynamics influenced by structural vibration and regeneration effects. The global thermal resistance network model with dynamic heat flux, viscosity-temperature effect, and time-varying thermal resistanceis establishedto characterize the thermal characteristics. The partition-based closed-loop iterative algorithm is employed to realize the multi-field coupling and consider the moving heat source and the load distribution change caused by the reciprocating moving joint. Considering the changes in contact angle and contact deformation caused by preload, dynamic load, and thermal effect, load- and temperature-dependent nonlinear joint restoring force and stiffnessare developed. Based on the viscosity-temperature effects and the change of contact friction caused by thermal expansion and dynamic load, the load- and temperature-dependent nonlinear joint frictional heat generation is calculated. The milling load from tool-workpiece interaction is calculated, and the influence of multi-field coupling on regenerative chatter is explored. The proposed model was experimentally verified, andthe effectof parameterswas numerically investigated. The results show that the dynamic milling load excites the whole machine tool vibration, and for every 10 μm increase in cutting depth, the radial amplitude of the tool nose increased by at least 1 μm. The nonlinear coupling between temperature and mechanical field significantly affects the system response, and the joint contact stiffness dominates the multi-field coupling behavior.