Changes In Dynamic Characteristics Research Articles

Effect of scour on the fatigue life of offshore wind turbines and its prevention through passive structural control

Abstract. Offshore wind turbine (OWT) support structures are exposed to the risk of fatigue damage and scour, and this risk can be effectively mitigated by installing structural control devices such as tuned mass dampers (TMDs). However, time-varying scour altering OWTs' dynamic characteristics has an impact on the TMD design and fatigue life, which has rarely been studied before. In this paper, a simplified modal model is used to investigate the influence of scour and a TMD on the fatigue life evaluation of a 5 MW OWT's support structure, and a traditional method and a newly developed optimization technique are both presented to obtain TMD parameters. This optimization technique aims at finding optimal parameters of the TMD which maximize the fatigue life of a hotspot at the mudline, and the effect of time-varying scour can be considered. This study assumes that the TMD operates in the fore–aft (FA) direction, while the vibration in the side–side (SS) direction is uncontrolled. Results show that scour can decrease the fatigue life by about 24.1 % and that the TMD can effectively suppress vibration and increase the fatigue life. When the scour depth reaches 1.3 times the pile diameter, the TMD with a mass ratio of 1 % can increase the fatigue life of an OWT's support structure by about 64.6 %. Further, it is found that the fatigue life can be extended by 25 % with the TMD optimized by the proposed optimization technique rather than using a traditional design method which does not take the change in dynamic characteristics into account.

Dynamic Characterization of Grease-Lubricated Ball Screws

According to the lubrication characteristics of grease and lubrication mechanism, concerning the Hamrock-Dowson minimum film thickness formula, this paper analyses the trend and size of oil film thickness change of grease-lubricated ball screw sub under different aviation working conditions to identify the lubrication status. ABAQUS software is used to carry out dynamic simulation and the friction coefficient is selected according to the lubrication state and Stribeck curve to define the contact conditions to obtain the friction torque change curve and the fluctuation curve of axial velocity of the nut under different aerospace working conditions. Finally, a test bench is set up to test and calculate the friction torque of grease-lubricated ball screws to analyze the influence of different aviation working conditions on the dynamic characteristics of grease-lubricated ball screws and to investigate the reasons for the change of dynamic characteristics.

Dynamic variation in the aroma characteristics of Rhus chinensis honey at different stages after capping

The ripening characteristics after capping of honey are favourable for improving its quality. However, research on the variation and formation of aroma characteristics of honey in this process is lacking. Therefore, the present study was carried out with different stages of Rhus chinensis honeys (RCHs) after capping and identified 192 volatiles with varying levels of concentration. “Fruity” was the main aroma characteristic of RCHs at different stages after capping, mainly contributed by (E)-β-damascenone. Methyl salicylate might be a potential indicator for differentiating RCHs at different stages after capping. The metabolic pathway analyses revealed that the aroma compounds in RCHs undergo transformation at different stages after capping, which subsequently affects its aroma characteristics formation. This work is the first to study the dynamic changes in honey aroma characteristics after capping from multiple perspectives, and the results are of great significance for understanding the aroma characteristics after capping and quality control of honey.

Impacts of Spatio-Temporal Changes in Anthropogenic Disturbances on Landscape Patterns in the Nandu River Basin, China

We explored the characteristics of landscape pattern (LP) changes in the Nandu River Basin (NRB) and its dynamic response mechanism to anthropogenic disturbance (AD). This is important for ecological protection and for land use decision-making in the basin in the context of the construction of a free trade port. Land use and land cover change (LULCC) data of 1990, 2000, 2010, and 2020 were analyzed with the help of the LP index, moving window method, hemeroby index, geo-information atlas, and geographic information system (GIS) spatial analysis to reveal the dynamic changes in LP characteristics in the NRB. Furthermore, this paper discusses into the correlation between LP and AD. The results indicate that over the past three decades, the NRB showed a staggered LP, dominated by forestland and cropland, whose total area has decreased by 25.27 km2 and 62.75 km2, respectively. On the other hand, the built-up land increased by 91.37%. The overall landscape fragmentation, landscape patch homogeneity, and landscape diversity have increased in the NRB. AD is the main reason for the dramatic changes in the LP of urban agglomerations centered in Haikou city. The area of minor disturbance (over 34%) occupies the largest proportion of the land, followed by higher (about 13~25%) and moderate disturbances (about 17~22%). The area of minor and strong disturbances has increased significantly, whereas those of moderate and higher disturbances have significantly decreased. The spatial distribution pattern of AD is gradually increasing from the southwest (natural landscape) to the northeast (human landscape). A transition in areas of low disturbance levels to higher levels is obvious. The area of the atlas that has transitioned from “minor → lighter disturbance (12)” and “higher → minor disturbance (41)” changed changed most significantly during 2000 to 2010 and from 2010 to 2020, occupying 26.79% and 11.99% of the transfer atlas, respectively. All regions encountering disturbances were significantly correlated with the largest patch index (LPI) from 1990 to 2020. The overall AD in the NRB has increased, especially in Haikou. Urbanization is the main factor for an increase in AD. The ecological and environmental management and monitoring in the basin need to be strengthened.

Dynamic changes in metabolomics and flavoromics during industrial scale fermentation of Chinese traditional soy sauce

Flavor substances are crucial to the quality of soy sauce and closely related to the intermediate metabolites. This study systematically explored the dynamic changes in physicochemical characteristics, metabolomics and flavoromics during traditional Chinese soy sauce fermentation. The results indicated that the amino acid nitrogen gradually increased to 0.95 g/100 mL on the 13th day and then stabilized, and the changes of reducing sugars increased to 66.40 mg/mL on the 7th day and then slowly decreased. A total of 90 volatile compounds and 1172 non-volatile metabolites were detected. In the early fermentation period (1–7 day), alcohols, aldehydes and ketones were the main volatile compounds, but as fermentation proceeded, phenols and esters gradually accumulated. The total content of volatile compounds, mainly alcohols and phenols, reached the highest value on the 23rd day. Non-volatile metabolites were mainly amino acids, organic acids, lipids and carbohydrates, and the content and types of varied with fermentation time. KEGG analysis indicates there were significant changes in the proline and arginine metabolism in the middle and late periods (7–28 day) compared to the early fermentation period. Correlation analysis indicating a delicate balance between the transformation of metabolites and the formation of volatile compounds in traditional Chinese soy sauce.

Dynamics of Berry Characteristics, Biochemical Composition, and Physiological Responses Across Ripening Stages: Investigating the Impact of Pollinizer Varieties on Physiological Femaleness in Bozcaada Çavuşu (Vitis vinifera L. cv)

AbstractUnderstanding the dynamic changes in grape characteristics during ripening is crucial for enhancing grape quality, which, in turn, influences overall viticulture practices. This study aimed to investigate the temporal and cultivar-specific variations in grape characteristics, focusing on BAs, phenolic compounds, antioxidant enzymes, and organic acids. Our results revealed that Bozcaada Çavuşu*Kuntra and Kuntra grapes exhibited the most significant growth in size, weight, and maturity index at the final developmental stage (EL-38), while Vasilâki showed a nuanced maturation pattern with significant increases in berry width but not weight. Across all varieties, the highest maturity index and Total Soluble Solids percentages were observed at EL-38. The investigation of BAs revealed a significant decrease in Put levels from 2.62 at EL-32 to 2.04 mg L−1 at EL-38, contrasting with an increasing trend in Agm concentrations from 0.25 at EL-29 to 0.37 mg L−1 at EL-38. Bozcaada Çavuşu*Kuntra stood out with the highest Cad concentration at 2.96 mg L−1. The analysis of phenolic compounds highlighted a distinct temporal pattern for gallic acid, increasing from 1.60 at EL-29 to 3.77 g L−1 at EL-32 and maintaining stability at 3.74 g L−1 at EL-38. Bozcaada Çavuşu*Vasilâki consistently exhibited higher concentrations of phenolic compounds, such as epicatechin (5.69 g L−1) and tyrosol (7.00 g L−1). Antioxidant enzymes like catalase and superoxide dismutase in grape cultivars showed significant temporal variations, indicating a dynamic oxidative stress response during berry ripening. Catalase activity decreased from 14.04 to 11.20 EU/gr berry between EL-29 and EL-38. The multifaceted regulation of superoxide dismutase by sampling time and cultivar highlighted the complexity of antioxidant dynamics in grapevine physiology. In conclusion, this comprehensive study sheds light on the intricate interplay of temporal and cultivar-specific factors influencing grape characteristics, providing valuable insights for optimizing viticulture practices and enhancing overall grape quality.

Dynamic characteristics changes of masonry arches exposed to elevated temperature

In this study, the changes in the dynamic characteristics of masonry arches exposed to elevated temperatures were investigated experimentally and numerically. Firstly, the material properties were analyzed at different temperatures, ranging from 200°C to 800°C, through experimental tests. The constructed arch specimens were then subjected to heat to investigate the effects of elevated temperatures on their dynamic characteristics. Ambient vibration tests were performed before and after heating to identify natural frequencies and mode shapes. Furthermore, numerical models of the arches were developed, and a model updating procedure was implemented to minimize the differences between the numerical and experimental data. The findings indicated that elevated temperatures led to notable decreases in the compressive strengths of both the stone and the mortar. This decrease significantly degraded the stiffness of the masonry arch samples, consequently having a profound effect on their dynamic properties.

Antibiotic resistance, biofilm formation, and molecular epidemiology of Staphylococcus aureus in a tertiary hospital in Xiangyang, China.

Staphylococcus aureus is a common clinical pathogen that causes various human infections. The aim of this study was to investigate the antibiotic susceptibility pattern, molecular epidemiological characteristics, and biofilm formation ability of S. aureus isolates from clinical specimens in Xiangyang and to analyze the correlation among them. A total of 111 non-duplicate S. aureus isolates were collected from the Affiliated Hospital of Hubei University of Arts and Science. All isolates were tested for antibacterial susceptibility. Methicillin-resistant S. aureus (MRSA) was identified by the mecA gene PCR amplification. All isolates were analyzed to determine their biofilm-forming ability using the microplate method. The biofilm-related gene was determined using PCR. SCCmec, MLST, and spa types of MRSA strains were performed to ascertain the molecular characteristics. Among the 111 S. aureus isolates, 45 (40.5%) and 66 (59.5%) were MRSA and MSSA, respectively. The resistance of MRSA strains to the tested antibiotics was significantly stronger than that of MSSA strains. All isolates were able to produce biofilm with levels ranging from strong (28.9%, 18.2%), moderate (62.2%, 62.1%), to weak (8.9%, 19.7%). Strong biofilm formation was observed in MRSA strains than in MSSA strains, based on percentages. There were dynamic changes in molecular epidemic characteristics of MRSA isolates in Xiangyang. SCCmecIVa-ST22-t309, SCCmecIVa-ST59-t437, and SCCmecIVa-ST5-t2460 were currently the main epidemic clones in this region. SCCmecIVa-ST5-t2460 and SCCmecIVa/III-ST22-t309 have stronger antibiotic resistance than SCCmecIVa-ST59-t437 strains, with resistance to 6 ~ 8 detected non-β-lactam antibiotics. The molecular epidemic and resistance attributes of S. aureus should be timely monitored, and effective measures should be adopted to control the clinical infection and spread of the bacteria.

Mapping Extracellular Space Features of Viral Encephalitis to Evaluate the Proficiency of Anti-Viral Drugs.

The extracellular space (ECS) is an important barrier against viral attack on brain cells, and dynamic changes in ECS microstructure characteristics are closely related to the progression of viral encephalitis in the brain and the efficacy of antiviral drugs. However, mapping the precise morphological and rheological features of the ECS in viral encephalitis is still challenging so far. Here, a robust approach is developed using single-particle diffusional fingerprinting of quantum dots combined with machine learning to map ECS features in the brain and predict the efficacy of antiviral encephalitis drugs. These results demonstrated that this approach can characterize the microrheology and geometry of the brain ECS at different stages of viral infection and identify subtle changes induced by different drug treatments. This approach provides a potential platform for drug proficiency assessment and is expected to offer a reliable basis for the clinical translation of drugs.

Designing a Model Predictive Controller for Displacement Control of Axial Piston Pump

Variable displacement hydraulic pumps are widely used for energy efficiency, and they often have a mechanical feedback mechanism to ensure target tracking control performance and stability of tilt angle control. Furthermore, there are many examples which add electronic control to realize higher tracking control performance. However, in such cases, the control performance is significantly affected by the dynamic characteristics of the mechanical feedback mechanism, and this problem prevent its widespread use. Additionally, tilt angle control is susceptible to changes in dynamic characteristics and load pressure depending on the operating point, and there are constraints on the tilt angle. Hence, high control performance cannot be obtained without considering these nonlinearities. In this study, the variable displacement pump without mechanical feedback mechanism is focused on, and the objective of this study is to design a displacement control system for a hydraulic pump based on a model predictive control (MPC) that can consider various constraints on the design step. An adaptive system, which handles changes in dynamic characteristics and the effects of load pressure, is introduced. Additionally, the control performance of adaptive MPC is compared to adaptive model matching-based MPC with inverse optimization that can optimally design the weight matrices of the evaluation function without trial and error. Furthermore, in order to improve the transient response, a variable control input constraints are added in these two control systems. Experimental results of control performance have shown that the proposed method achieved a high tracking performance and short settling time, which confirmed the effectiveness of the variable control input constraints.

Conceptualizing psychological well‐being as a dynamic process: Implications for research on mobile health interventions

AbstractWe introduce a theoretical framework for conceptualizing Psychological Well‐Being (PWB) as a process that unfolds over short and longer time‐scales. We argue that this framework can be especially useful for studying the change mechanisms in PWB within the context of mobile Health (mHealth) interventions. Four lines of research are considered within this framework to inform the scientific exploration of PWB in the context of mHealth interventions. First, we explore key dynamic characteristics of change in PWB functioning. Second, we discuss PWB intervention response as a learning process (i.e., meaningful and transformational changes in state), reflected as change in key dynamic characteristics of PWB. Third, we explain mechanisms of change in PWB intervention practices through an underlying process of skill development. Fourth, we discuss intervention response heterogeneity within this framework. The approach we outline is intended to articulate currently unanswered, process‐oriented research questions about PWB interventions, how they work, and a methodological path forward for exploring them.

Seismic vulnerability assessment of historical minarets in Cairo

IntroductionMasonry minarets in Old Cairo are highly susceptible to earthquake damage, particularly those not designed or updated to withstand seismic loads. Therefore, regular monitoring is necessary to ensure their safety and detect any deterioration or reduction in seismic performance. The direct loss of a minaret can lead to the collapse or severe damage to the structure itself. The cascading impacts of partial or complete minaret failure can have significant consequences for the immediate vicinity and the broader community. By studying the effects of earthquakes on minarets and developing mitigation strategies, countries can take proactive measures to protect these structures and ensure the safety of people.ObjectiveThis study focuses on a specific type of Islamic architecture: the historic minarets in Cairo. The research aims to evaluate the seismic vulnerability of eight cultural heritage minarets in Cairo, identifying the parameters influencing their seismic behaviour and susceptibility to earthquake damage.MethodsThe research utilizes empirical seismic vulnerability methods and ambient vibration measurements on eight minarets. An empirical approach compatible with the nature and style of the minarets is employed to evaluate their vulnerability using index values and curves. The method's validity is assessed, and areas of conformity and limitations are identified. Ambient vibration tests (AVTs) are also conducted using a temporary seismic network installed at various heights inside each minaret to determine their dynamic characteristics.ResultsThe seismic vulnerability Index (I_V) is calculated for the selected minarets based on the state of each vulnerability parameter. The contribution of each parameter to the final I_V values of the minarets are presented. Vulnerability curves are developed for each minaret, interpreting the conventional vulnerability indexes in terms of mean damage grades for seismic events with varying intensity on the EMS-98 scale. These mean damage grades can also indicate the expected damage levels of structural and non-structural minaret elements for events with different seismic intensity levels. AVTs are conducted at various heights on the selected minarets, and the dynamic characteristics are extracted from the recorded data. Variations in these characteristics are considered significant for structural health monitoring analysis. The peak-picking method is employed to directly extract each minaret's natural frequencies and mode shapes, as changes in dynamic characteristics are relevant to health monitoring analyses.ConclusionsThe recent study examined the seismic vulnerability assessment of eight masonry minarets in the historic Old Cairo district. The assessment revealed vulnerability index values ranging from 10.3 to 26.1, indicating a concerning susceptibility to seismic events among these structures. Vulnerability curves were constructed for each minaret, visually representing potential damage scenarios across different levels of the EMS-98 intensity scale. These outcomes are significant as they facilitate prioritizing interventions to safeguard the most vulnerable minarets. Additionally, a novel empirical period equation was introduced to estimate the fundamental period of minarets in Old Cairo based on their heights. The equation was validated against field measurements and data from the literature. The study is limited by its focus on a specific category of minarets, specifically the historical masonry minarets in Old Cairo. Furthermore, limitations arise from the need for detailed finite element models to capture these minarets' dynamic responses accurately. Therefore, ongoing research involves the development of detailed finite element models and calibrating fundamental periods for the selected minarets. The anticipated results hold the potential to enhance our understanding of the structural dynamics of historical minarets, ultimately guiding the formulation of tailored seismic retrofitting and preservation strategies. These strategies, aimed at preserving these cherished cultural heritage assets, represent our collective commitment to ensure the endurance of these timeless landmarks for future generations.

Abnormal changes of dynamic topological characteristics in patients with major depressive disorder

BackgroundMost studies have detected abnormalities of static topological characteristics in major depressive disorder (MDD). However, whether dynamic alternations in brain topology are influenced by MDD remains unknown. MethodsAn approach was proposed to capture the dynamic topological characteristics with sliding-window and graph theory for a large data sample from the REST-meta-MDD project. ResultsIt was shown that patients with MDD were characterized by decreased nodal efficiency of the left orbitofrontal cortex. The temporal variability of topological characteristics was focused on the left opercular part of inferior frontal gyrus, and the right part of middle frontal gyrus, inferior parietal gyrus, precuneus and thalamus. LimitationsFuture studies need larger and diverse samples to explore the relationship between dynamic topological network characteristics and MDD symptoms. ConclusionsThe results support that the altered dynamic topology in cortex of frontal and parietal lobes and thalamus during resting-state activity may be involved in the neuropathological mechanism of MDD.

Cyber–Physical–Social Model of Community Resilience by Considering Critical Infrastructure Interdependencies

Each year, several disasters occur, resulting in enormous human, infrastructural, and economic losses. To minimize losses and ensure an adequate emergency response, it is vital to prepare the community for greater shock absorption and recovery after an occurrence. This raises the concept of community resilience and also demands appropriate metrics and prediction models for improved preparedness and adaptability. While a community is impacted in three main ways during a disaster-namely social, physical, and cyber-there are currently no tools to model their interrelationship. Thus, this paper presents a multi-agent cyber-physical-social model of community resilience, taking into account the interconnection of power systems, emergency services, social communities, and cyberspace. To validate the model, we used data on two hurricanes (Irma and Harvey) collected from Twitter, GoogleTrends, FEMA, power utilities, CNN, and Snopes (a fact-checking organization). We also describe methods for quantifying social metrics such as the level of anxiety, risk perception, and cooperation using social sensing, natural language processing, and text mining tools. We examine the suggested paradigm through three different case studies: 1) hurricanes Irma and Harvey; 2) a group of nine agents; and 3) a society comprised of six distinct communities. According to the results, cooperation can positively change individual behavior. Relationships within a community are so crucial that a smaller population with greater empathy may be more resilient. Similar dynamic changes in social characteristics occur when two empathetic communities share resources after a disaster.

Detection of changes in dynamic characteristics of composite structures using Kriging metamodeling procedure: Experimental and computational analysis

To ensure the quality, safety, and long-term durability of fiber-reinforced composite components, it is necessary to explore approaches for monitoring and detecting defects or damage. Nondestructive detection techniques based on dynamic properties and structural response, such as natural frequency, damping, and modal shape. This study presents a numerical-experimental methodology based on dynamic analysis of structures made of composite materials. The methodology utilizes a surrogate model to establish a design envelope through a Kriging metamodel and to assess a damage index for structures affected by impact damage. The Latin Hypercube method is employed to generate values for the input variables, while the finite element method is utilized to calculate the natural frequencies. The Kriging metamodel is then employed to generate a numerical model, which is optimized using the Efficient Global Optimization algorithm and the expected improvement metric to minimize computational costs. The methodology yields a frequency range and determines a design envelope to evaluate the manufacturing quality of the structure. A damage index is used to identify structures with defects or impact damage, allowing for the assessment of severity. Additionally, the study evaluates the impact of incorporating metrics into the Latin Hypercube method to further reduce computational costs. Finally, this proposed approach contributes to the development of monitoring systems for assessing the manufacturing quality of composite structures and detecting impact damage through dynamic analysis. By utilizing this methodology, it becomes possible to effectively identify and evaluate the severity of defects and damage in composite structures, thus enhancing quality evaluation processes.

Developing a Pixel-Scale Corrected Nighttime Light Dataset (PCNL, 1992–2021) Combining DMSP-OLS and NPP-VIIRS

The spatial extent and values of nighttime light (NTL) data are widely used to reflect the scope and intensity of human activities, such as extracting urban boundaries, spatializing population density, analyzing economic development levels, etc. DMSP-OLS and NPP-VIIRS are widely used global NTL datasets, but their severe inconsistencies hinder long-time series studies. At present, global coverage, long time series, and public NTL products are still rare and have room for improvement in terms of pixel-scale correction, temporal and spatial consistency, etc. We proposed a set of inter-correction methods for DMSP-OLS and NPP-VIIRS based on two corrected DMSP-OLS and NPP-VIIRS products, i.e., CCNL-DMSP and VNL-VIIRS, with the goal of temporal and spatial consistency at the pixel-scale. A pixel-scale corrected nighttime light dataset (PCNL, 1992–2021) that met the needs of pixel-scale studies was developed through outlier removal, resampling, masking, regression, and calibration processes, optimizing spatial and temporal consistency. To examine the quality of PCNL, we compared it with two existing global long time series NTL products, i.e., LiNTL and ChenNTL, in terms of overall accuracy, spatial consistency, temporal consistency, and applicability in the socio-economic field. PCNL demonstrates great overall accuracy at both the pixel-scale (R2: 0.93) and the city scale (R2: 0.98). In developing, developed, and war regions, PCNL shows excellent spatial consistency. At global, national, urban, and pixel-scales, PCNL has excellent temporal consistency and can portray stable trends in stable developing regions and abrupt changes in areas experiencing sudden development or disaster. Globally, PCNL has a high correlation coefficient with GDP (r: 0.945) and population (r: 0.971). For more than half of the countries, the correlation coefficients of PCNL with GDP and population are higher than the results of ChenNTL and LiNTL. PCNL can analyze the dynamic changes in socio-economic characteristics over the past 30 years at global, regional, and pixel-scales.

Heterogeneity in Adolescents' Non-Suicidal Self-Injury Behaviour Trajectories Based on the Group-Based Trajectory Model and a Decision Tree Analysis of Family-Related Determinants.

Non-suicidal self-injury (NSSI) is a global public health problem. While some studies have noted the importance of behavioural development patterns in NSSI, most NSSI research is based on cross-sectional survey data. Few studies explore the time-series heterogeneity of trajectories of NSSI symptoms and family-related influencing factors of NSSI. The purpose of the study was to identify the heterogeneity in trajectories of adolescents' NSSI behaviour and their family-related influencing factors. The group-based trajectory model (GBTM) was used to identify the heterogeneity in the NSSI behaviour trajectories of 208 adolescents in China. Next, the decision tree model (DTM) was used to analyse which family related factors influence the trajectory type. The GBTM revealed two heterogeneous trajectories of NSSI behaviour: the high-risk and low-risk NSSI behaviour groups. Next, DTM's average accuracy was 83.2%. A total of seven independent variables were used for the DTM: gender, number of NSSIs in the past month, and family economic, family structure, family conflict, parental psychological control, parental behavior control and family intimacy risks. Family conflict risk was located at the root node and was the most important factor. Heterogeneity within the population should be considered in the management of adolescents' NSSI behaviours. Further, from the perspective of family system theory and cumulative risk, focusing on the adverse effect of multiple risk factors on adolescents' NSSI addiction is more meaningful rather than the impact of single risk factors. Studies that use time series data should focus on the trend of dynamic changes in NSSI addiction characteristics over time.

OPTIMIZATION OF THE DYNAMIC PARAMETERS OF AN OBJECT IN A MATHEMATICAL MODEL OF SEISMO-ACOUSTIC MONITORING OF NATURAL AND ENGINEERING OBJECTS

The article is devoted to the mathematical modeling approach of seismo-acoustic monitoring of objects and structures of sizes whose own frequencies and emission signals are from seismic and the bottom part of acoustic ranges. The structural analysis and identification of dynamic parameters of such structures are extremely important in their monitoring to predict essential changes in dynamic characteristics. Moreover, the method of dynamic identification provides an opportunity to investigate the dynamic behavior of the given structure or source of signal origin by researching investigated objects' to study informative characteristics. The article enters methodology for identifying the main structural parameters, such as main intrinsic frequencies, and the decrement in these frequencies. Particular interest represents seismo-acoustic monitoring of objects with sources of emission signals whose parameters are subject to definition and are characteristic of structure or signal origin. Emissions can carry both irregular and regular character. The latter case can be modeled as a flow with the likelihood characteristics and subject definitions. The result of the analysis of the data received in seismo-acustic monitoring of such signals is reduced to an estimation of parameters of an emission signal, which fluctuates from a signal to a signal. A practical method for analyzing natural and man-made objects, whose natural frequencies lie in the seismic and lower part of the acoustic frequency ranges, based on monitoring their dynamics, is proposed. A new approach is proposed for identifying the state of such objects. A non-traditional model of the natural background of the monitored object is proposed in the form of a superposition of Berlage impulses. Such a model makes it possible to estimate such an essential parameter in the description of an object as its quality factor, the dynamics of which can give an idea of its structural changes. To predict the behavior of natural and engineering objects to prevent undesirable consequences of the behavior of the object under study, seismo-acoustic monitoring systems are used. The mathematical model and algorithm proposed by the authors can be integrated into the system of seismo-acoustic monitoring of natural and man-made objects.

Dynamic changes in chemical composition and microbial community characteristics during pile-fermentation process of Phyllanthus emblica Linn. fruit

Pile-fermentation is a common processing step for Phyllanthus emblica L. fruit (PEF) in its producing area. This process enhances its flavor, reduces astringency, and increases its health benefits. However, the mechanism behind pile-fermentation and the key factors impacting PEF quality remain unknown, becoming an urgent challenge that limits its further application. To address this issue, 87 volatile compounds were analyzed by HS-SPME/GC-QQQ-MS/MS and identified acetic acid and ethyl acetate as distinguishing markers before and after fermentation. The results found that 2-methoxy-3-isobutylpyrazine contributes to the differences in odor after fermentation based on the odor intensity characteristic spectrum. Illumina Miseq sequencing of ITS1 region and 16SrDNA V4 region was performed to investigate the microbial succession during the pile-fermentation. A total of 4 phyla 34 genera of fungi and 15 phyla 61 genera of bacteria were detected in all samples. The results showed that the dominant bacteria had significant differences due to different habitats before fermentation, and the diversity increased after fermentation, while the fungal diversity exhibited the opposite trend. Aspergillus and the Unclassified_f_Necriaceae genus emerged as dominant genera after fermentation. Additionally, through UPLC-QTOF-MS analysis, we identified 18 differential components before and after fermentation. Among these, 5 compounds, such as 2-O-galloyl-1,4-galactolactone and 1-methyl-2-gallate galactose ester, showed a downward trend, whereas 13 compounds, including corilagin and chebulitic acid, exhibited an upward trend. These changes weakened astringency while improving sourness and aftertaste sweetness. The results of this study hold significant importance in clarifying the fermentation mechanism and improving the quality standards of PEF.

Dynamic Analysis of Coupled Train and Cracked Bridge Systems Using Multiscale Finite Element Modeling

Cracking frequently encountered in railway bridges can lead to significant changes in bridge dynamic characteristics and further dynamic performance of train–bridge interaction (TBI) system. It is desirable to develop an effective method to understand the dynamic behavior of coupled train and cracked bridge systems. This paper proposes a framework for coupled vibration analysis of train and cracked bridge systems using multiscale finite element modeling. A multiscale bridge model adopting frictional surface–surface contact to characterize nonlinear breathing phenomenon of the crack is incorporated into the three-dimensional coupled TBI model. Subsequently, a multiloop numerical solution strategy is formulated to solve the established dynamic equation of coupled train and cracked bridge systems. The proposed framework is used to analyze the cracked beams presented in the literature, and the obtained and literature data are compared. Moreover, an actual heavy-haul railway bridge is taken as an illustrative example, in which vehicle dynamic response, bridge vibration, and train running safety index are calculated considering various crack types, train speeds, and track conditions. The results show that apart from the bridge displacement and acceleration, the presence of crack can have a large influence on the vehicle acceleration response, derailment factor, and offload factor. Differences larger than ±10% in the maximum dynamic indices associated with the intact and cracked bridges are observed, indicating the necessity of considering the crack damage in train–bridge coupled dynamic analysis.