Dynamic Analysis Method Research Articles

Visual Analysis Method for Traffic Trajectory with Dynamic Topic Movement Patterns Based on the Improved Markov Decision Process

The visual analysis of trajectory topics is helpful for mining potential trajectory patterns, but the traditional visual analysis method ignores the evolution of the temporal coherence of the topic. In this paper, a novel visual analysis method for dynamic topic analysis of traffic trajectory is proposed, which is used to explore and analyze the traffic trajectory topic and evolution. Firstly, the spatial information is integrated into trajectory words, calculating the dynamic trajectory topic model based on dynamic analysis modeling and, consequently, correlating the evolution of the trajectory topic between adjacent time slices. Secondly, in the trajectory topic, a representative trajectory sequence is generated to overcome the problem of the trajectory topic model not considering the word order, based on the improved Markov Decision Process. Subsequently, a set of meaningful visual codes is designed to analyze the trajectory topic and its evolution through the parallel window visual model from a spatial-temporal perspective. Finally, a case evaluation shows that the proposed method is effective in analyzing potential trajectory movement patterns.

Dynamic risk analysis for oil and gas exploration operations based on HFACS model and Bayesian network

Oil and gas exploration (OGE) is an important part of the petroleum industry. How to predict and prevent risks of OGE accidents in a targeted way is still a challenge, while few researchers have focused on this issue because of the lack of data from the worksite. Therefore, the accident cases for decades of years in a globally operated OGE company are collected as a basis, a dynamic risk analysis method combining the human factors analysis and classification system (HFACS) and the Bayesian network (BN) has been proposed in this article. First, identify the accident cases, analysis, and divided the risk factors into four levels and 27 classification categories, and setup a HFACS-OGE model. Then, map the factors to the BN and identify the correlation of the secondary level factors. Finally, setup a BN model with the Genie software. Through posterior probability analysis and sensitivity analysis, we conclude the major and sensitive factors leading to OGE accidents. According to the conclusion, administrators could decide on corresponding management and control methods. This method can hopefully provide an effective quantitative basis for the identification and prediction of the factors that may lead to OGE accidents.

Impact of Variable Parameters of Expansion Joints and Bearing Supports on the Vehicle-Induced Vibration of Curved Girder Bridges

To study how varying the parameters of expansion joints and bearing supports (E-B parameters) affects the dynamic response of a coupled vehicle–bridge system for curved girder bridges, a dynamic response analysis method for the coupled vehicle–joint (bearing)–bridge system, which takes into account centrifugal forces, was proposed and verified. Subsequently, taking a continuous curved box girder bridge as the prototype, the influence of the E-B parameters on the vehicle-induced dynamic response of the curved girder bridge was explored. The results showed that the dynamic amplification factor (DAF) of the middle beam of the expansion joint (DAF-EJ) and the main girder of the curved bridge (DAF-MG) were both significantly influenced by the E-B parameters. When there were height differences between the middle beam and side beam in the EJ, the DAF-EJ obviously varied, and the DAF-MG increased. When the EJ was damaged, the impact effect of the vehicle on the bearing support increased. The DAF-EJ and DAF-MG both increased with the decrease of the vertical support stiffness of the bearing support. The DAF-EJ was greatly affected by the single-support void at the near-slit end of the lane. The DAF-MGs at the beam end, the 1/4 point and 1/2 point of the first span, and the 1/2 point of the second span, were significantly affected by the single-support void near the measuring point. Compared with the single-support void, the DAF-EJ and DAF-MG more significantly increased under the double-support void. Variation in the height difference of the EJ had a more significant effect on the DAF-EJ and DAF-MG at the beam end, while a vertical stiffness reduction in the bearing support had a more significant effect on the DAF-MG.

Study of the Impact Irregular Concrete Facilities with the Shear Walls Based: The Effect of Soil-Structure Interaction with ABAQUS Software

In the present study, the effect of irregularity of structures of the concrete with special shear walls has been analyzed and modeled by considering the effect of soil-structure interaction by dynamic analysis method with ABAQUS software. The results are presented in the form of diagrams with different soil interaction conditions, the effect of the number of layers was investigated for different soils. The results showed that the bearing system of the flexural frame and the concrete shear wall under the lateral load of the earthquake have good strength and ductility, which makes this issue. This structural system should be used for cities with very high earthquake risk. As the number of floors increases, the effect of the shear walls on increasing the bearing capacity decreases. As the number of floors increases, the final displacement of the frame increases. The results showed that for soil type 1(hard soil which Vs=1000 m/s, v=0.15, q=50000 Kg/m2, P=2000 Kg/m3, r=0.5 m) structural system of concrete shear walls with better displacement, maximum structural stiffness, better behavior was observed in the structure. Three-story frame with concrete shear wall has a significant increase compared to similar frames with more floors, which shows the good performance of this system in structures with fewer floors.

Amphipterygium adstringens (cuachalalate) extract by supercritical CO2

This study delineates the empirical findings derived from the extraction of Sarsasapogenin from Amphipterygium Adstringens, commonly known as Cuachalalate, utilizing supercritical carbon dioxide (CO2) as a solvent. The experiments were conducted within a temperature spectrum of 314 to 328.4 K and a pressure range of 8–22 MPa. The operational duration was set at 90 min with a CO2 solvent flow rate oscillating between 40 and 50 mL/min. The equipment employed was predicated on the dynamic-analytical method. The extract´s qualitative determination was performed using a liquid chromatograph interfaced with a mass spectrometer (HPLC-MS). In contrast, the quantitative analysis was executed employing Ultraviolet Visible spectroscopy (UV–Vis) and Fourier Transform Infrared Spectroscopy (FTIR). Sarsasapogenin was identified as the representative compound in the Cuachalalate bark extract. The quantitative evaluations revealed that the maximum extract yield, amounting to 26.56 mg, was obtained under optimal operating conditions. Furthermore, this study investigated the influence of pressure and temperature variations on the extract´s yield.

A Simplified Approach of Analytical Seismic Fragility Analysis Using the Endurance Time Method

ABSTRACT The endurance time (ET) method is an effective dynamic analysis method for seismic response analysis of structures. It has been recently used for analytical fragility analysis. However, the available ET-based fragility analysis methods have two limitations: 1) the prediction error of the structural median responses estimated by the ET method is ignored; and 2) the record-to-record variability inherent earthquake ground motions is not well considered. To overcome the above limitations, another ET-based fragility analysis method is proposed, where only three times of ET nonlinear analyses are required. To do this, three specific endurance time excitation functions (ETEFs) are generated in correspondence to the mean and 16% and 84% percentile of response spectra of a selected suite of ground motion records (i.e. ETE F m , ETE F v 1 and ETE F v 2 , respectively). The structural response under ETE F m is used to estimate the median response of structures under the selected suite of ground motion. Moreover, the structural responses under ETE F v 1 and ETE F v 2 are used to quantify the record-to-record variability in earthquake ground motions. The fragility relationships are developed by both point and interval estimate methods since another logarithmic standard deviation is introduced to account for the difference between the median responses predicted using ETE F m and those predicted by the dynamic analysis. To validate the proposed method, two RC frame structures with six and nine stories are taken as the study cases. The fragility results based on the proposed ET-based method and those based on the cloud method are compared. It is found that the proposed ET-based fragility analysis method could generate reliable fragility estimation, whereas requiring limited computation cost. The proposed method would provide another simplified way for the rapid fragility assessment of structures.

Damage Spectra of SDOF Structures Under Tsunami Actions Considering the Nonlinear Dynamic Analysis Method

This paper studies the damage spectra of single-degree-of-freedom (SDOF) systems for tsunami loading. The 2011 Tohoku tsunami wave traces are computed and obtained by adopting the Cornell Multi-grid Coupled Tsunami (COMCOT) model and are further verified by the Tohoku Tsunami Joint Survey (TTJS) data. The tsunami response analyses of SDOF systems are conducted taking into account the dynamic analysis method. The classical ductility damage is considered as the damage performance. The damage spectra are computed for five force reduction factors and 791 tsunami loadings. The effects of inundation depths, hysteretic model, post-yield stiffness ratio, [Formula: see text], viscous damping ratio, [Formula: see text], are explored and interpreted scientifically and statistically. The results demonstrate that the effect of the hysteretic model, force reduction factor, R, post-yield stiffness ratio, [Formula: see text], viscous damping ratio, [Formula: see text], on the damage of the structure is evident. Comparison with the static method and influence analysis of structural damping indicate the necessity for the application of the dynamic method. A simplified predictive formulation is developed for the evaluation of structural damage for tsunami loadings.

Incremental dynamic analysis method application in the seismic vulnerability of infilled wall frame structures

To reasonably evaluate the overall seismic performance of infilled wall frames, a corresponding nonlinear analysis model is constructed with infilled wall frames as the research object. It quantifies the failure levels of structural and non-structural components and proposes a method for extracting structural overall performance indicators. The vulnerability of the case frame structure is analyzed using the Incremental Dynamic Analysis (IDA) method. The results showed that the seismic performance of the infilled wall frame and the ordinary frame met the seismic fortification requirements, and the seismic capacity of the infilled wall frame was better. After implementing a 7-degree seismic fortification, the cumulative probability of basic integrity, minor damage, and moderate damage for infill wall frames reached 99.15 %, surpassing the fortification target of 1.5 g. However, the seismic capacity of ordinary frames was overestimated, as their cumulative probability of basic intact, minor damage, and moderate damage under a 7-degree seismic fortification was 99.7 %. Neglecting its impact, ordinary frames exhibited lower seismic performance compared to other structures, with a basic intact probability of only 48.49 % under frequent earthquake actions at 7 degrees. The research utilizes effective methods for evaluating the seismic vulnerability of infilled wall frames.

Installation performance of torpedo anchor at different installation heights under the action of currents: The example of T98 torpedo anchor

The deep-sea torpedo anchor is an innovative and cost-effective anchorage foundation. However, marine environmental loads such as currents have a significant impact on the free-fall installation of torpedo anchors in water, often leading to the failure of installation due to excessive inclination or large deviations from the installation location. Therefore, taking the T98 torpedo anchor commonly used in practical engineering as an example, this paper systematically investigates its installation characteristics under the action of currents. First, based on OpenFOAM®, a 3D numerical model is established to simulate the underwater falling process of torpedo anchors via dynamic model analysis method. Using the validated model, the influence of currents on the installation performance of torpedo anchors is then explored. Based on the findings, the installation conditions of T98 anchors at different installation heights are recommended. Finally, a semi-empirical method for estimating the anchor inclination and deviation of torpedo anchors under current action is proposed, which may facilitate the assessment of installation inclination and determine the installation release point of torpedo anchors.

Nonlinear Dynamic Granger Causality Analysis Framework for Root-Cause Diagnosis of Quality-Related Faults in Manufacturing Processes

Root-cause diagnosis of quality-related faults plays a crucial role in ensuring stable product quality and high-efficient production for modern manufacturing processes. However, there exists complex nonlinear and dynamic sequential characteristics for process and quality data before and after faults, which contain important fault information. How to fully explore and use this information to locate the root-cause and identify the propagation path is a hot topic. Thus, a new nonlinear dynamic Granger causality analysis method is developed for root-cause diagnosis, which will provide timely and useful reference information to take reasonable measures for field engineers. First, an optimal variable division based on minimal redundancy maximal relevance algorithm is presented to get the quality-related variables. Then, a new attention-based random disturbance gated recurrent unit is designed for nonlinear dynamic Granger causality analysis, aiming at locating the root-cause and identifying the propagation path of quality-related faults. A typical manufacturing process, the hot strip mill process is used for verification. The results show the practicability of the proposed method, and its strong robustness to noise. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Reasonable and feasible root-cause diagnosis technology will provide timely reference information for field operators to take maintenance measures. However, the nonlinear and dynamic characteristics of time-series data before and after quality-related faults have brought great challenges to the traditional root-cause diagnosis techniques. To address this issue, a practical nonlinear dynamic Granger causality analysis method is proposed, which is purely data driven without knowing complex mechanism knowledge. It will provide feasible solutions for safety monitoring of hot strip mill process as the representative of manufacturing processes.

Analysis and Design of an Unsymmetrical Multi-storey building with floating columns in a seismic zone using ETABS

Most high-rise structures today are designed with floating columns for aesthetic purposes and the need for efficient use of space. Lattice columns are vertical load-bearing elements that do not extend the entire height of the building, they are usually located on one or more intermediate floors and support beams. These design innovations have benefits such as increased architecture and space allocation. Loads include load and side load. Heavy loads, including dead loads and live loads, are evaluated to determine the overall load distribution. Lateral loads resulting from earthquakes and wind forces are calculated based on local building codes. In seismic design, multistorey buildings with floating columns are analysed at different levels on curved planes to determine safe floating column locations. Structures can be analysed with symmetric information and dynamic analysis methods such as response spectrum or potential time. Preliminary analysis and equivalent static analysis using ETABS 2022. A 3D structural model was created to accurately represent the geometry of the building and its behavior under different load combinations was used to compare the building's response to seismic forces. The result is the behavior of the structure: shear strength, bending moment, deflection, and displacement. The results are obtained in the form of tables and graphs. The structures were built with M30 concrete and various types of steel. Reinforcement spacing and detailing is done in CSI Detail.

Dynamic behaviors analysis of fraction-order neural network under memristive electromagnetic induction

The dynamic behaviors of coupled neurons with different mathematical representations have received more and more attention in recent years. The coupling among heterogeneous neurons can show richer dynamic phenomena, which is of great significance in understanding the function of the human brain. In this paper, we present a fraction-order heterogeneous network with three neurons, which is built by coupling an FN neuron with two HR neurons. Complex electromagnetic surroundings have meaningful physical influence on the electrical activities of neurons. To imitate the effects of electromagnetic induction on the three-neuron heterogeneous network, we introduce a fraction-order locally active memristor in the neural network. The characteristics of this memristor are carefully analyzed by pinched hysteresis loops and its locally active characteristic is proved by the power-off plot and the DC &lt;i&gt;v-i&lt;/i&gt; plot. Then, the parameter-dependent dynamic activities are investigated numerically by using several dynamical analysis methods, such as the phase diagrams, bifurcation diagrams, Lyapunov exponent spectra, and attraction basins. In addition, the network also reveals rich dynamic behaviors, including coexisting activities, anti-monotonicity phenomena, transient chaos and firing patterns, providing support for further investigating the firing patterns of the human brain. In particular, complex dynamics, including coexisting attractors, anti-monotonicity, and firing patterns, can be influenced by the order and strength of electrical synaptic coupling and electromagnetic induction. The control of the bistable state can be realized through the time feedback control method, so that the bistable state can be transformed into an ideal monostable state. The study of the fraction-order memristive neural network may expand the field of view for understanding the collective behaviors of neurons. Finally, based on the ARM platform, we give a digital implementation of the fraction-order memristive neural network, which can verify the consistency with the numerical simulation results. In the future, we will explore more interesting memristive neural networks and study different types of methods to control the firing behaviors of the networks.

A Comprehensive Study of Efficient and Accurate Malware Detection Using Static and Dynamic Analysis Methods.

A Comprehensive Study of Efficient and Accurate Malware Detection Using Static and Dynamic Analysis Methods.

Studying Microtubule Dynamics in Human Neurons: Two-Dimensional Microtubule Tracing and Kymographs in iPSC- and SH-SY5Y-Derived Neurons for Tau Research.

The study of microtubule (MT) dynamics is essential for the understanding of cellular transport, cell polarity, axon formation, and other neurodevelopmental mechanisms. All these processes rely on the constant transition between assembly and disassembly of tubulin polymers to/from MTs, known as dynamic instability. This process is well-regulated, among others, by phosphorylation of microtubule-associated proteins (MAP), including the Tau protein. Protein kinases, in particular the microtubule affinity regulating kinase (MARK), regulate the MT-Tau interaction, inducingTau dissociation by phosphorylation. Phosphorylated Tau dissociates from microtubules forming insoluble aggregates known as neurofibrillary tangles. These accumulations of hyperphosphorylated Tau in the neurons disrupt the physiological MT-based transport machinery within the cell and can potentially lead to the development of neurodegenerative disorders, such as Alzheimer's disease (AD) and related tauopathies. Further investigations on the MT cytoskeleton dynamics are essential as they may elucidate pathomechanisms of neurodegenerative diseases - particularly tauopathies - as well as fundamental neurodevelopmental processes.The study of thedynamic assembly and disassembly of the MT network requires live-cell imaging rather than conventional immunocytochemistry based on fixed samples. To investigate MT dynamics, we perform live-cell imaging of neurons transfected with a fluorescently tagged version of the microtubule plus-end tracking protein (+TIP) EB3. This protein associates with the growing ends of MTs and thus visualizes MT growth in real time. Our imaging analysis protocol allows the determination of quantity, orientation, and velocity of MT growth in the soma and neurites of transfected neurons,using ImageJ-based tracking software and kymographs. Furthermore, functional effects of Tau and MARK kinases on the MT cytoskeleton can be assessed by overexpression or downregulation experiments of the respective protein prior to the live imaging assay. We use two different human neuronal cell models, naive and differentiated SH-SY5Y neuroblastoma cells, and neurons derived from induced pluripotent stem cells (iPSCs), both of which have shown success as models to study Tau-related pathologies.This protocol describes an optimized method for analysis of microtubule dynamics using fluorescent tagged EB3 protein as microtubule plus end marker. In this chapter, we outline the process of neuronal transfection, live-cell imaging, and necessary time-lapse image analysis based on ImageJ in two human-derived neuronal systems, which are suitable for the analysis of Tau trafficking and sorting studies.

МОДЕЛИРОВАНИЕ ДИНАМИКИ ВЗАИМОДЕЙСТВУЮЩИХ ПОПУЛЯЦИЙ ТИПА «ХИЩНИК–ЖЕРТВА» ПРИ ПОСТОЯННОЙ МИГРАЦИИ ОСОБЕЙ С СОПРЕДЕЛЬНЫХ ТЕРРИТОРИЙ

The article deals with the research of the dynamics of a local predator-prey community with constant migration of individuals from neighboring territories. We studied several models with a constant inflow of individuals into both predator and prey populations. It is shown that changes in the overall dynamics are significantly influenced by the number of predator migrants: their large influx leads to the rapid and almost complete extinction of preys. The model considering only a constant prey inflow is successfully applied to modeling of various processes based on the principles of predator-prey population interactions, for example, when studying the consumption of difficult-to-renewable or nonrenewable natural resources. The study of the model provides allows getting estimations of the resources use efficiency and and the degree of modernization of the consumer sector. It is shown that two-dimensional models - modifications of the basic Volterra and Bazykin models, lead to structurally stable fluctuation regimes corresponding to the focus and limit cycle. We found that these models also contain fast-slow periodic dynamics, corresponding to a maximum limit cycle with strong spikes and smoother declines in the population size. The emergence of such regimes corresponds to the alternation of periods of active extinctions of prey, accompanied by an increase in the number of predators, and periods of long-term restoration of the prey, during which there is no harvesting of prey. We used methods of dynamic systems analysis to study the models. The construction of two-dimensional parametric portraits shows that, to get stable dynamics of the basic models of two interacting biological species, no complication is required, for example, by adding nonlinear terms. Stable regimes are also observed in simpler models, such as the original Lotka-Volterra or Bazikin models, where the recovery rate of prey population is a constant value.

ВИРОБНИЦТВО ЦУКРОВИХ БУРЯКІВ В УКРАЇНІ: СТАТИСТИКО-ПРОГНОСТИЧНА ОЦІНКА

The article discusses the theoretical, methodological and applied aspects of using statistical instruments to assess the state, tendencies and prospects of beet growing, forecasting production of beet and sugar subcomplex. Using of integrated and synergistic approaches to studied issues ensure the reliability of the results of statistical analysis. The current state and dynamics of the sugar beet production in Ukraine are analyzed. In recent years, there has been a negative trend in the reduction of sugar beet acreage and production volumes. For the period of 2003–2022, the average annual absolute decrease in sugar beet acreage was 30,5 thousand hectares. As a result, sugar beet production volumes are decreasing, and the availability of raw materials for sugar factories is decreasing. The tendencies and prospects of sugar beet production were assessed using economic and mathematical methods and models. Both simple methods of dynamic series analysis and construction of linear/non-linear trendy models were used to identify the tendency of the effective indicators of sugar beet production. The effective factor of intensity of development of beet growing, increase of volumes of beet production is the yield of sugar beet. The linear, exponential and parabolic trend models of sugar beet yield are built. Using the standard deviation and coefficient of variation, the linear and parabolic trend equations are estimated. The closeness of the analytical series to the empirical series of dynamics was established by the calculated bond density indicators. It was found that the parabolic trend model accurately reflects the sugar beet yield trend. Statistical instruments were used to forecast sugar beet production in the form of a dynamic system and reproduce this system in the short term with a certain level of probability. The parabolic trend model was used to make predictive calculations of sugar beet yield in Ukraine. The forecast level of sugar beet yield in Ukraine in 2024 will be in the range from 436,4 dt/ha to 576,1 dt/ha.

Research on the Model Construction and Analysis of the Enterprise E-commerce Service Capability

Abstract The customer-oriented and situational nature of e-commerce requires companies to build up service capabilities. However, few scholars have studied this capability systematically. Most scholars see it as a ‘black box’ and give different 'black box' elements depending on the purpose of the study. So, in the context of e-commerce, what should a company's service capabilities include? How are they formed? What impact do they have on a firm's competitive advantage? How can service capabilities be established and improved? Based on the above background and questions, this paper investigates the service capabilities of e-commerce platforms by applying customer value theory in conjunction with the background characteristics of e-commerce transactions. Through case studies, a conceptual model of e-commerce service capability is proposed and its formation mechanism is studied. On this basis, the paper investigates how to measure e-commerce service capability. The aim is to provide theoretical guidance for enterprises' capability planning on e-commerce platforms and to facilitate the transformation from ‘commodity management’ to ‘capability management’. A combination of probability sampling and non-probability sampling was used to select the sample by distributing questionnaires to manufacturing companies in Taizhou, Hangzhou and Shaoxing, Zhejiang Province. For the mail survey, this study uses a snowball method to select the sample. This paper constructs service capability measurement indexes for e-commerce enterprises based on customer's perception of the transaction process, and uses dynamic factor analysis method to analyze enterprises' e-commerce strategic capability, e-commerce management capability and e-commerce technical resources, thus bringing constructive suggestions for the improvement of e-commerce service capability. The findings show that these three competencies are key components of e-business capabilities and together determine the establishment, cultivation and maintenance of an enterprise's e-business capabilities. Enterprises need to focus on these three areas and continuously modify and improve them to ultimately acquire e-business service capabilities.

Brain Temporal-Spectral Functional Variability Reveals Neural Improvements of DBS Treatment for Disorders of Consciousness.

Deep brain stimulation (DBS) is establishing itself as a promising treatment for disorders of consciousness (DOC). Measuring consciousness changes is crucial in the optimization of DBS therapy for DOC patients. However, conventional measures use subjective metrics that limit the investigations of treatment-induced neural improvements. The focus of this study is to analyze the regulatory effects of DBS and explain the regulatory mechanism at the brain functional level for DOC patients. Specifically, this paper proposed a dynamic brain temporal-spectral analysis method to quantify DBS-induced brain functional variations in DOC patients. Functional near-infrared spectroscopy (fNIRS) that promised to evaluate consciousness levels was used to monitor brain variations of DOC patients. Specifically, a fNIRS-based experimental procedure with auditory stimuli was developed, and the brain activities during the procedure from thirteen DOC patients before and after the DBS treatment were recorded. Then, dynamic brain functional networks were formulated with a sliding-window correlation analysis of phase lag index. Afterwards, with respect to the temporal variations of global and regional networks, the variability of global efficiency, local efficiency, and clustering coefficient were extracted. Further, dynamic networks were converted into spectral representations by graph Fourier transform, and graph energy and diversity were formulated to assess the spectral global and regional variability. The results showed that DOC patients under DBS treatment exhibited increased global and regional functional variability that was significantly associated with consciousness improvements. Moreover, the functional variability in the right brain regions had a stronger correlation with consciousness enhancements than that in the left brain regions. Therefore, the proposed method well signifies DBS-induced brain functional variations in DOC patients, and the functional variability may serve as promising biomarkers for consciousness evaluations in DOC patients.

Seismic Fragility Analysis of Arch Dam Based on IDA and ETA Methods

In the assessment of the seismic performance of ultrahigh‐arch dams, challenges such as complex structural models, extensive degrees of freedom, and extended computation times are commonly encountered. Consequently, there is a pressing need to develop a more streamlined and effective approach for investigating the seismic behavior of ultrahigh‐arch dams. The endurance time method, a novel approach in seismic analysis, is increasingly favored for the dynamic analysis of large structures. In this study, the dynamic damage characteristics of an ultrahigh‐arch dam are analyzed based on the endurance time method, and the seismic fragility analysis is evaluated. Utilizing a case study of an ultrahigh‐arch dam in southwest China, a comprehensive three‐dimensional nonlinear model encompassing dam, bedrock, and water interactions is developed. This model incorporates considerations of dam and bedrock damage, cracking, dynamic behavior of contraction joints, and the interaction between the dam and reservoir water. The nonlinear least‐squares function is used to generate three endurance time acceleration functions (ETAFs) based on the response spectra of the hydraulic structure seismic design standard. The dynamic analysis of the above model is carried out by using the endurance time method and the incremental dynamic analysis (IDA) method. The results indicate that the endurance time method can well reflect the fragility of ultrahigh‐arch dams under different intensities of ground motions, with significant computational efficiency.

Abnormal Static and Dynamic Local Functional Connectivity in First-Episode Schizophrenia: A Resting-State fMRI Study.

Dynamic functional connectivity (FC) analyses have provided ample information on the disturbances of global functional brain organization in patients with schizophrenia. However, our understanding about the dynamics of local FC in never-treated first episode schizophrenia (FES) patients is still rudimentary. Dynamic Regional Phase Synchrony (DRePS), a newly developed dynamic local FC analysis method that could quantify the instantaneous phase synchronization in local spatial scale, overcomes the limitations of commonly used sliding-window methods. The current study performed a comprehensive examination on both the static and dynamic local FC alterations in FES patients (N = 74) from healthy controls (HCs, N = 41) with resting-state functional magnetic resonance imaging using DRePS, and compared the static local FC metrics derived from DRePS with those calculated from two commonly used regional homogeneity (ReHo) analysis methods that are defined based on Kendall's coefficient of concordance (KCC-ReHo) and frequency coherence (Cohe-ReHo). Symptom severities of FES patients were assessed with a set of clinical scales. Cognitive functions of FES patients and HCs were assessed with the MATRICS consensus cognitive battery. Group-level analysis revealed that compared with HCs, FES patients exhibited increased static local FC in right superior, middle temporal gyri, hippocampus, parahippocampal gyrus, putamen, and bilateral caudate nucleus. Nonetheless, the dynamic local FC metrics did not show any significant differences between the two groups. The associations between all local FC metrics and clinical characteristics manifested scores were explored using a relevance vector machine. Results showed that the Global Assessment of Functioning score highest in past year and the Brief Visuospatial Memory Test-Revised task score were statistically significantly predicted by a combination of all static and dynamic features. The diagnostic abilities of different local FC metrics and their combinations were compared by the classification performance of linear support vector machine classifiers. Results showed that the inclusion of zero crossing ratio of DRePS, one of the dynamic local FC metrics, alongside static local FC metrics improved the classification accuracy compared to using static metrics alone. These results enrich our understanding of the neurocognitive mechanisms underlying schizophrenia, and demonstrate the potential of developing diagnostic biomarker for schizophrenia based on DRePS.