Dynamic Analysis Method Research Articles

ASSESSING THE EFFECTIVENESS OF SUPPORT FOR SMALL AND MEDIUM-SIZED BUSINESSES

The article assesses the effectiveness of state support policies for small businesses in conditions of federal budget deficit in the Russian Federation. The subject of the study is a methodology to assess the effectiveness of supporting small and medium-sized businesses. The purpose of the study is to develop a system to evaluate the effectiveness of state support for SMEs. The objectives of the study: to analyze the approaches to assess the effectiveness in Russia at large and abroad, to assess the effectiveness of state support measures for SMEs in Russia and abroad, to propose their own options for assessing the effectiveness of support measures, to present the practical application of the proposed methods. Research methodology: methods of system analysis, generalization, systematization, methods of statistical, dynamic, structural and comparative analysis. Research results: the article develops a system to evaluate the effectiveness of state support for small businesses, which includes several main indicators for evaluating the effectiveness (survival rate of recipients of state support by year; dynamics of average income; dynamics of the average number of employed; dynamics of the average amount of taxes paid by SMEs), as well as an algorithm to conduct an assessment based on a comparison of selected indicators for a group of SMEs that received support with indicators of small and medium-sized enterprises that were not participants in the relevant government programs. Using the proposed assessment system based on the statistical data of the Federal Tax Service of the Russian Federation, an analysis of the effectiveness of state support measures for SMEs in general and in the context of individual forms of support in the period 2019- 2022 was carried out. Based on the significant deviation of the selected indicators of SME recipients of support from the average values in the whole SME sector (and/or in relation to SMEs that did not receive support), a conclusion is made about the high efficiency of state support for SMEs. It is also established that the impact of various forms of state support on the functioning of SMEs is different.

Dynamic Analysis of Street Trees in Vehicle-mounted LiDAR Point Clouds

Street trees, as key elements of urban road scenes, play a significant role in the overall ecological environment and aesthetics of city roads through their dynamic growth and changes. With the continuous development of urban roads, the growth conditions of street trees are also constantly changing. Therefore, studying how to infer the dynamic changes of roads through the variations in street trees is a highly valuable technical issue. This paper delves into several critical parameters of street trees, including diameter at breast height (DBH), tree height, trunk height, crown volume, and crown spread. By updating these parameters, determining transplantation and replanting decisions, and analyzing growth states, we comprehensively analyze the dynamic changes of street trees. To achieve this goal, we integrated multiple parameters into the analysis process of street trees and established a comprehensive analysis system centered on the DBH parameter. Combining this with data visualization technology, we provide an intuitive dynamic analysis method. Experimental results indicate that, compared to single-parameter analysis methods, the multi-parameter comprehensive analysis method demonstrates higher accuracy and stronger persuasive power in the study of dynamic changes in street trees, thereby validating the superiority and practicality of the proposed research algorithm. This research can provide more scientific and reliable references for urban road planning and management.

A dynamic topology analysis method for multi-ship encounters based on multi time-space network trees

This paper innovatively proposes a novel approach of topological analysis in the dynamic time-space domain of ship encounters under the joint action of multi-space network structural elements, based on the GIS spatial information platform and spatial topology analysis theory. The proposed method based on the ship's navigational motion information, encounter dynamic mode, relative time-space position distribution, etc., the method divides and intersects the time-space domain of the ship's encounter dynamics, and establishes an encountering dynamic time-space network tree in which space and attribute elements are collaboratively associated during the navigation. From the perspective of network topology analysis, the high-precision analysis of the spatial coupling characteristics and time-space trends of potential encountered dangers during ships dynamic navigation is achieved. To verify the effectiveness of the method, real encounter scenarios of M/T SANCHI and M/V CF Crystal were used as analysis cases. The results showed that the proposed method can precisely extract spatial relationships and spatio-temporal coupling feature information of potential hazards encountered between ships, with an average error of about 2.54% and an overall error between 1.94% and 3.53%.Simultaneously, the method's time efficiency results are thoroughly studied and compared, and it is discovered that the proposed method has good stability.

Coupling a nonlinear finite element mooring model with an overset CFD solver for dynamic analysis of floating structures in waves

An accurate prediction of motion responses of a moored floating structure requires high-fidelity coupled analysis between the structure and its mooring system in waves, which involves both mooring line dynamics and fluid dynamics. In this paper, we develop a nonlinear finite element dynamic mooring analysis module that allows large axial stretching of mooring lines under the open source CFD framework OpenFOAM, and couple it with an Overset CFD solver to establish a fully coupled finite element mooring-CFD analysis model for floating structures. The coupled model is advantageous over existing models in that it is able to deal with large axial mooring stretching and complex mesh motions induced by significant structure responses under severe operating conditions. The developed dynamic mooring analysis method is firstly validated against publicly available data. In order to validate the coupled model, a series of experimental tests were carried out for a semi-submersible platform moored by eight catenary lines under different operating conditions, including free decay, regular and irregular wave tests. The dynamic responses of the floating structure and mooring tension are analyzed and compared with experimental data. Results show that numerically predicted structure responses and mooring tension are generally in good agreement with experimental measurements. Meanwhile, the strongly nonlinear large-amplitude resonant motions generated by the interaction of irregular waves with the moored floating structure are also investigated. Comparisons reveal that the coupled model can accurately predict the resonant spectral peaks of the structure responses, indicating that the it is capable of simulating large-amplitude motions of moored floating structures. The coupled model developed in this paper can be further applied to study the survivability of moored floating structures under harsh sea conditions.

3D dynamic contact analysis of tyre internal deformation using 2D image sensor

Due to the increasing weight of electric vehicles, advanced tyre technology is urgently needed. In particular, there is a need for dynamic contact analysis to determine the energy interaction between tyres and road surfaces. However, the methods developed to date are limited in that they require either numerous contact patches inside the tyre or sensor devices on the ground. In this study, we propose a new method for dynamic tyre-ground contact analysis that overcomes these limitations. By installing a two-dimensional image sensor inside the tyre, deformations can be observed and quantified three-dimensionally during vehicle operation. This method advances tyre engineering through innovative analysis of tyre deformation during operation.

Mineral resource rents, fintech technological innovation, digital transformation, and environmental quality in BRI countries: An insight using panel NL-ARDL

The prime objective of the current study is to investigate the impact of mineral resource rents, fintech technological innovation, and digital transformation on the environmental quality of 50 BRI countries. The panel data from the twenty years from 2000 to 2019 of the sample countries are used in the analysis of this study. The study has employed the Panel NL-ARDL to achieve the research objectives. Meanwhile, the current study has employed conventional unit root tests based on Augmented Dickey-Fuller (ADF) unit root tests, such as the LLC and IPS tests. This study employs the method of heterogeneous dynamic panel analysis. The results obtained from the FMOLS regression analysis provide a detailed comprehension of the complex connections between Mineral Resource Rent, Fintech, Digital Transformation, and CO₂ emissions; these findings indicate that countries with advanced financial technology or heavy reliance on Mineral resources are more likely to observe the favorable impacts of digital transformation on the environment. The study results imply that policymakers should investigate all-encompassing policies that exploit these interactions, recognizing that a complete approach can produce substantial and enduring environmental advantages. The interaction variables (NRRDTT and FNTINDTT) demonstrate the negative coefficients that emphasize the combined impact of Mineral resource rent, Finetch, and digital transformation. Policymakers in resource-dependent economies should consider strategies incorporating digitalization and financial technology to optimize their potential impact on environmental sustainability.

International container intermodal competitiveness: An empirical study from Chinese hub ports

The global energy crisis and environmental degradation have prompted ports to strive for green transformation. Intermodal transport, as a green and efficient form of organization in the transport sector, currently has a lot of room for development. How can the competitiveness of intermodal transport be enhanced while realizing the green sustainability of ports? This study objectively evaluates the competitiveness of international container intermodal competitiveness of hub ports and analyzes the characteristics of 16 Chinese ports from 2011 to 2020. The obstacle degree model (ODM) and the panel Tobit model considering random effects are utilized to explore the complex multidimensional elements affecting the competitiveness of intermodal transport in ports. In addressing the imbalanced characteristics of intermodal transport in ports, a variety of augmentation pathways are devised using the dynamic multi-time period fuzzy-sets qualitative comparative analysis (fsQCA) method. The results found that: (1) The competitiveness of intermodal transport in ports shows a “three echelons” structure, requiring the implementation of appropriate augmentation strategies. (2) Elements affecting the competitiveness of intermodal transport in ports are multidimensional, underscoring the significance of holistically considering internal and external elements. (3) The key to enhancing the competitiveness of intermodal transport in ports lies in striking a balance between economic development and prudent attention to multiple dimensions to ensure sustainability. This study enriches the empirical research on intermodal transport in ports. It provides valuable references for ports seeking new avenues of growth and for governments with effective management practices.

Seismic vulnerability analysis of a high‐rise steel frame structure equipped with novel displacement‐amplified viscoelastic dampers

SummaryThe energy dissipation capacity of conventional viscoelastic dampers (VEDs) cannot be fully exerted due to the relatively small inter‐story displacement of building structures. Thus, a novel VED with a displacement amplification mechanism based on the lever principle is developed in this study to achieve small displacement but high energy dissipation ability. First, the structural layout of an amplified viscoelastic damper (AVED) system is briefly introduced, and then the displacement amplification effect is described in detail. According to the working principle of the AVED and the relationship of force and geometric displacement in an actual frame structure, the restoring force theoretical formula of the corresponding amplified damper is derived. Based on the restoring force of the AVED and in combination with the secondary development function of the ABAQUS unit, a VUEL subroutine suitable for the explicit algorithm is programmed with the FORTRAN language. Then, the correctness of the subroutine is verified through a comparative analysis of the ABAQUS simulation and theoretically calculated results. Consequently, the vulnerability analysis of a high‐rise steel frame structure is conducted by using the incremental dynamic analysis (IDA) method, and the influence of the AVED on the seismic performance of the steel frame structure is quantitatively analyzed from the perspective of probability statistics. The analysis results show that compared with the VED structure, the failure probability of the AVED‐2 and AVED‐3 structures reaching the ultimate failure state at all levels is reduced by approximately 43% and 57%, respectively, and the collapse margin ratio (CMR) of structures under large earthquakes is increased by approximately 35% and 68%, respectively. This indicates that the AVED structures with displacement‐amplified dampers have a better effect on the seismic stability of tall steel frame structures under random seismic excitations. This study aims to provide comprehensive information for the seismic‐resistant design of tall buildings in earthquake‐prone regions.

Multi-dimension-precision chaotic encryption mechanism for Internet of Things

The massive amount of information processed in the Internet of Things(IoT) environment requires effective encryption schemes to ensure secure transmission. However, traditional encryption methods such as Elliptic Curve Cryptography (ECC) or Data Encryption Standard (DES) are not suitable for IoT environments where large amounts of data need to be quickly encrypted. In this paper, a multi-precision encryption mechanism based on multi-dimensional chaotic system is proposed. Firstly, the proposed scheme uses floating-point, 32-bit, 24-bit, and 16-bit data accuracy respectively, which can effectively reduce the complexity through fixed-point calculation. Secondly, aiming at the problem that traditional chaotic dynamic analysis methods such as the Lyapunov index cannot be applied, an analysis scheme based on complexity measure is proposed. Finally, a free dimension encryption mechanism based on Logistic, Tent, and PWLCM is proposed. By adding random disturbance to a one-dimensional chaotic map, the weak randomness of the single chaotic sequence is overcome effectively. Finally, the security analysis of the encryption scheme is carried out, and the result proves that the scheme can effectively resist the common attack means. In the 3D chaotic system, the encryption effect of 24-bit data accuracy is close to floating point accuracy, which is suitable for the IoT environment with large data volume, high encryption efficiency, and vulnerability.

Integrated CFD and MBD methods for dynamic performance analysis of a high-speed train transitioning through varied windbreak corridor designs

With increasing train speeds, the wind environment along routes has become complex, variable, and extreme. Constructing windbreak facilities is an effective strategy to enhance train operational safety in windy zones. Various windbreak designs exhibit notable differences in improving train dynamic performance, and economic considerations are also crucial. Utilizing the non-constant compressible Reynolds time-averaged equation URANS (Unsteady Reynold-averaged Navier–Stokes) alongside the shear-stress transport (SST) k-ω turbulence model, this study simulates the non-constant aerodynamic characteristics of a 350 km/h high-speed train traversing through different forms of windbreak corridors in a 30 m/s wind zone. The train's dynamic response was captured using a combined CFD–MBD (Computational Fluid Dynamics and Multi-Body Dynamics) offline time-domain simulation, the accuracy of which was verified experimentally. Results indicate that vortices of various positions and shapes form in the flow field along the windbreak corridor depending on the size of the openings. Using the no-windbreak corridor (Case 1) and the fully enclosed corridor (Case 4) as control groups, it was observed that smaller openings lead to more stable airflow, enhancing peak damping and fluctuation effects, albeit with varying stages of aerodynamic load fluctuation. The 1/3-opening windbreak corridor (Case 3) effectively mitigated the sudden aerodynamic load changes at the wind zone transition of the 2/3-opening windbreak corridor (Case 2), with the primary fluctuation area in Case 3 being the wind section. Dynamic analyses revealed that Case 2 exhibited insufficient lateral aerodynamic performance, raising derailment concerns. In contrast, Case 3 ensured travel safety and comfort effectively, while Case 4 offered excessive protective capacity. This study's findings serve as a valuable reference for designing windbreak corridors and ensuring the safe operation of trains in windy regions.

Factor analysis method for delay dynamics in Nigerian Tin Can Island Port for sustainable development

The effect of efficient and effective port system on the economy viability of any nation cannot be over emphasis. This study investigated factors that could be termed as delay causative factors in Nigerian ports industry using TIN CAN Island port complex as a case study. A well-structured questionnaire was developed for this research and 72 respondents, who are port users (custom officers, employees, and customers), were asked to rank the variables perceived to be causing delay at the port according to their respective perception of the effect of each factor on delay factors at the port. The validity of the research instrument was done using Cronbach Alpha. There are several factors that were thought to be working together in reducing efficiency in Nigerian ports and these factors were analyzed using factor analysis method. It was discovered from the analysis that Lack of Government Authority, Ullage Constraint, Inadequate Berthing, Logistics Delay, Financial Constraint and Equipment Breakdown are major factors that cause delay at Tin Can Island Port Lagos. These highlighted factors should be paid special attention in order to reduce delay in Tin Can Island port which will in turns lead to more revenue for the country.

An innovative booster-assisted dynamically installed fish anchor and its installation characteristics considering the action of ocean currents

The fish anchor is an economically viable offshore foundation engineering technology that has been proposed in recent years. By fish anchor, we mean a fish-shaped dynamically installed anchor that can penetrate into the seabed through water by its own weight. However, the existing research studies seldom consider the hydrodynamic characteristics of its free fall installation, resulting in uncertainties regarding its underwater installation characteristics. Therefore, based on OpenFOAM, this study first investigated the directional stability of fish anchors during its underwater falling process through the static model analysis method and dynamic model analysis method. The findings indicated that the directional stability of fish anchors was insufficient, rendering them suitable only for release and installation at low heights (i.e., less than 4.2 times the anchor length) without marine environmental loads. Furthermore, the anchor inclination angle during installation is significant, thereby impacting its penetration depth and pull-out capacity in the seabed. To solve this problem, the concept of an innovative booster-assisted fish anchor is proposed, which can significantly enhance the directional stability of conventional fish anchors. Results show that the maximum installation height of the new booster-assisted fish anchor is increased by 2.4 times compared to the original design, thereby enhancing both the penetration speed and uplift capacity. Based on the findings, recommended installation and construction conditions are provided. Finally, a predictive formula for the installation height and verticality of the new booster-assisted fish anchor under current action is presented to offer guidance for engineering applications.

Hydrodynamic and bearing behaviors of two typical deepwater dynamically installed anchors: torpedo anchor and fish anchor

Dynamically installed anchors, such as torpedo and fish anchors, are innovative and cost-effective anchorage foundations. In this study, the advantages and disadvantages of these two types of dynamically installed anchors are discussed by comparing the hydrodynamic and bearing characteristics of torpedo and fish anchors commonly used in practical engineering. First, based on OpenFOAM, 3D numerical models were established to investigate the directional stability and simulate the underwater free-fall process of anchors using static and dynamic model analysis methods. Using the validated model, the hydrodynamic performances (i.e., inclination angle, installation offset distance, penetration velocity, and drag coefficient) of torpedo and fish anchors were explored and compared. Based on these findings, the installation height of each anchor was recommended. Finally, the bearing performances of the torpedo and fish anchors were investigated using ABAQUS, and the selection principles of these two types of dynamically installed anchors were presented based on their hydrodynamic and bearing behaviors.

Inspiratory Neural Network Complexity Quantified by Approximate Entropy (ApEn) Analysis in SN 6-OHDA-induced Rat Model of Parkinson’s Disease

Parkinson’s disease (PD) is a multifaceted chronic and progressive neurodegenerative disease that includes a broad range of motor and non-motor symptoms (NMS). Breathing abnormalities are a common NMS in PD, and despite respiratory dysfunction being a major problem in PD as well as respiratory complications being the most common cause of death in PD patients, this NMS receives little attention. Over the last decade, a number of preclinical experimental rat models of PD generated by nigrostriatal site-targeted administration of the neurotoxin 6-hydroxydopamine (6-OHDA) have been used to evaluate various aspects of ventilatory control in PD. While all of these models have been shown to exhibit basal and chemical control of breathing abnormalities that are consistent with those in clinical reports, no studies have assessed the complex intrinsic dynamics that are associated with the central inspiratory neural network in PD. Since preclinical rat models of PD have also been shown exhibit neuroanatomical changes in brainstem regions involved in ventilatory control, it is likely that changes in inspiratory neural network dynamics, which can be assessed using nonlinear dynamical analysis methods, are also present in PD. To begin to assess this possibility, we quantified the complexity of 20 consecutive inspiratory (diaphragm EMG) bursts recorded during basal breathing in urethane-anesthetized spontaneously breathing adult female rats at 4-weeks after unilateral injection of 6-OHDA (n=18) or vehicle (VEH; n=14) directly into the substantia nigra (SN). For these analyses, we calculated approximate entropy (ApEn), which provides a statistical measure of regularity (orderliness) of a signal in the time domain, with values for the embedding dimension m and the tolerance r set to m=3 and r=0.44 SD. ApEn values were significantly higher in 6-OHDA-injected rats compared to VEH-injected rats (0.6169±0.0069 vs 0.5894±0.0087; P=0.017) albeit TI and Tpeak/TI were similar in both groups (TI: 305.8±9.5 vs 300.0±12.7 ms, P=0.713; Tpeak/TI: 51.0±1.3 vs 51.3±1.1%, P=0.904). Other significant differences in temporal features included higher breathing frequencies (93.4±2.4 vs 82.0±3.2 bpm; P=0.007), reduced TE (in ms: 334.7±12.7 vs 445.5±27.4; P=0.001), and decreased inspiratory duty cycle (in %: 47.2±1.1 vs 40.8±2.0; P=0.006) in 6-OHDA (compared to VEH)-injected rats. These observations suggest that respiratory dysfunction in PD is also accompanied by reorganization of the central inspiratory neural network that is associated with greater irregularity or less system order. Additional experiments are needed to identify the precise neural mechanisms underlying this higher system complexity. NIH NS101737; Thomas Hartman Center for Parkinson's Disease Research at Stony Brook University. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Test and Analysis on High-pressure Turbine Tip Clearance Measurement of Turbofan Engine

The tip clearance of high-pressure turbine rotor is a key parameter for the performance and control of turbofan engine. It is of great significance to master the variation law of tip clearance for evaluating the working efficiency and performance attenuation of turbofan engine. The high-frequency dynamic analysis method based on time-frequency analysis is established. The variation law of high-pressure turbine tip clearance with engine state is obtained, and the influencing factors are analysed by simulation. The test results show that the variation law of the tip clearance of the high-pressure is consistent with the design, that is about 0∼3mm. The tip clearance of the high-pressure turbine is greatly affected by the rotor vibration. It means that we can monitor vibration of the rotor by monitoring changes in tip clearance. Real-time measurement and control adjustment should be carried out in the flight test to improve the working efficiency of the engine.

Influence of frequency characteristics of seismic ground motion on the fragility of an RC frame structure

Ground-motion frequency characteristics have a significant impact on structural damage. A quantitative description of the impact of ground-motion spectral features on structures is an urgent topic that requires solutions. In this study, the ratio of peak displacement to peak acceleration (R d2a ) is used as a representative index of the ground-motion spectral characteristics. The seismic records collected from the Kik-net strong-motion array in Japan are grouped according to their R d2a values. By adopting the incremental dynamic analysis method, the seismic fragility curves of a six-story RC frame structure loaded by inputting seismic records with different R d2a values are calculated using the OpenSees platform. The influence of R d2a values on the structural fragility is analyzed. Ground-motion records of liquefied sites are collected, and the peak ratios of seismic records at the liquefied sites are analyzed to reveal the differences in the fragility of the six-story RC structures at liquefied and non-liquefied sites. The results of this study are expected to serve as a reference for the evaluation of structural fragility and to understand the effect of ground-motion frequency characteristics on the fragility of RC frame structures.

IMPLEMENTATION OF DYNAMIC METHOD FOR MALWARE DETECTION IN EMAIL PHISHING ATTACKS ON LET'S DEFEND

In the rapidly evolving landscape of cybersecurity threats, the need for robust defenses against phishing attacks has become paramount. This study explores the efficacy of malware detection in phishing email attacks using dynamic analysis on the Letsdefend.io platform. Leveraging the insights provided by the Deloitte Center for Controllership regarding the escalating frequency of cyber adversaries targeting organizational data, this research investigates the effectiveness of the Letsdefend.io platform, particularly utilizing the SOC 146 rule, in identifying and mitigating phishing threats. Through a comprehensive analysis process encompassing dynamic malware analysis techniques, such as those employed by VirusTotal and URLHaus, alongside detailed examination of suspicious email attachments using the Mailbox feature, this study aims to provide insights into the evolving tactics of phishing attackers, specifically those utilizing Excel 4.0 Macros. The research methodology involves collecting malware samples for analysis, configuring sandbox environments with tools like Process Monitor and Regshot, and utilizing sophisticated analysis tools like ProcDot to visualize malware behavior. Additionally, the study examines the effectiveness of the Letsdefend.io platform in detecting phishing URLs and malicious domains reported by AnyRun and URLHaus databases. The findings reveal promising results in the detection and identification of phishing threats, shedding light on the potential of dynamic analysis methods in bolstering cybersecurity defenses against evolving phishing techniques. This research contributes to the ongoing efforts to enhance cybersecurity measures and protect organizational assets from the pervasive threat of phishing attacks.

A simplified weak coupling dynamic analysis method for running safety evaluation of train on bridges under earthquake excitation

This study proposes a simplified analysis method that couples the bridge and train-track subsystem in a weak form to facilitate the dynamic analysis of the train-track-bridge coupled system (TTBS) under earthquakes. The method includes three main steps: (i) performing dynamic analysis of the bridge under seismic conditions to obtain the response of the bridge deck; (ii) interpolating the bridge displacement beneath each wheelset based on the train's velocity, departure time, and the initial positions of the wheelsets; and (iii) assessing the running safety of the train by incorporating the interpolated bridge response as track irregularity into the train-track coupled system. Steps (i) and (iii) can be analyzed separately using finite element and multibody dynamics software, eliminating the need to create a complex TTBS model that is challenging to achieve within a single software platform. Additionally, based on the method’s assumptions, the earthquake excitation on the train can be separated into the seismic inertial effect and seismic-induced bridge deformation, enabling a quantitative analysis of the impact of these two types of excitations on train safety. Taking a 10-span simply supported bridge and a long-span cable-stayed bridge as examples, the proposed method’s assumptions are verified by comparing its results with those obtained from a complex TTBS model. Furthermore, the impact characteristics of inertial effects and seismic-induced bridge deformation on train safety for these two types of bridges are analyzed. The proposed method offers robust support for seismic design of bridges and facilitates a comprehensive analysis of the mechanisms through which seismic excitations affect train safety.

Bursting oscillation characteristics and adaptive high‐order differential feedback controller of doubly fed induction generator system

SummaryTo address the problem of bursting oscillations in doubly fed induction generator (DFIG) systems under external disturbances, an analysis method based on fast‐slow dynamics and a control strategy based on an adaptive high‐order differential feedback controller (AHODFC) is proposed. The fast‐slow dynamics analysis method was adopted to reveal the formation mechanism of bursting oscillations from the DFIG system owing to the multi‐timescale coupling effect of perturbation, that is, the oscillation is in the form of a bursting oscillation with alternating large‐amplitude oscillation and micro‐amplitude oscillation. A control strategy based on the AHODFC with a high‐order differentiator (HOD) was proposed to address the problem of bursting oscillations in the DFIG system. The control strategy of the AHODFC has smooth control‐rate characteristics, does not depend on the exact mathematical model of the controlled system, and has good applicability and robustness to various types of bursting oscillations caused by different disturbance amplitudes and system parameters. Our simulations verified the feasibility and effectiveness of the proposed method.

Unraveling the dynamic transcriptomic changes during the dimorphic transition of Talaromyces marneffei through time-course analysis.

Systemic dimorphic fungi pose a significant public health challenge, causing over one million new infections annually. The dimorphic transition between saprophytic mycelia and pathogenic yeasts is strongly associated with the pathogenesis of dimorphic fungi. However, despite the dynamic nature of dimorphic transition, the current omics studies focused on dimorphic transition primarily employ static strategies, partly due to the lack of suitable dynamic analytical methods. We conducted time-course transcriptional profiling during the dimorphic transition of Talaromyces marneffei, a model organism for thermally dimorphic fungi. To capture non-uniform and nonlinear transcriptional changes, we developed DyGAM-NS (dynamic optimized generalized additive model with natural cubic smoothing). The performance of DyGAM-NS was evaluated by comparison with seven other commonly used time-course analysis methods. Based on dimorphic transition induced genes (DTIGs) identified by DyGAM-NS, cluster analysis was utilized to discern distinct gene expression patterns throughout dimorphic transitions of T. marneffei. Simultaneously, a gene expression regulatory network was constructed to probe pivotal regulatory elements governing the dimorphic transitions. By using DyGAM-NS, model, we identified 5,223 DTIGs of T. marneffei. Notably, the DyGAM-NS model showcases performance on par with or superior to other commonly used models, achieving the highest F1 score in our assessment. Moreover, the DyGAM-NS model also demonstrates potential in predicting gene expression levels throughout temporal processes. The cluster analysis of DTIGs suggests divergent gene expression patterns between mycelium-to-yeast and yeast-to-mycelium transitions, indicating the asymmetrical nature of two transition directions. Additionally, leveraging the identified DTIGs, we constructed a regulatory network for the dimorphic transition and identified two zinc finger-containing transcription factors that potentially regulate dimorphic transition in T. marneffei. Our study elucidates the dynamic transcriptional profile changes during the dimorphic transition of T. marneffei. Furthermore, it offers a novel perspective for unraveling the underlying mechanisms of fungal dimorphism, emphasizing the importance of dynamic analytical methods in understanding complex biological processes.