Long-term Monitoring Research Articles

A Magnetic Particle Imaging Approach for Minimally Invasive Imaging and Sensing With Implantable Bioelectronic Circuits.

Minimally-invasive and biocompatible implantable bioelectronic circuits are used for long-term monitoring of physiological processes in the body. However, there is a lack of methods that can cheaply and conveniently image the device within the body while simultaneously extracting sensor information. Magnetic Particle Imaging (MPI) with zero background signal, high contrast, and high sensitivity with quantitative images is ideal for this challenge because the magnetic signal is not absorbed with increasing tissue depth and incurs no radiation dose. We show how to easily modify common implantable devices to be imaged by MPI by encapsulating and magnetically-coupling magnetic nanoparticles (SPIOs) to the device circuit. These modified implantable devices not only provide spatial information via MPI, but also couple to our handheld MPI reader to transmit sensor information by modulating harmonic signals from magnetic nanoparticles via switching or frequency-shifting with resistive or capacitive sensors. This paper provides proof-of-concept of an optimized MPI imaging technique for implantable devices to extract spatial information as well as other information transmitted by the implanted circuit (such as biosensing) via encoding in the magnetic particle spectrum. The 4D images present 3D position and a changing color tone in response to a variable biometric. Biophysical sensing via bioelectronic circuits that take advantage of the unique imaging properties of MPI may enable a wide range of minimally invasive applications in biomedicine and diagnosis.

Intensive Microalgal Cultivation and Tertiary Phosphorus Recovery from Wastewaters via the EcoRecover Process.

Mixed community microalgal wastewater treatment technologies have the potential to advance the limits of technology for biological nutrient recovery while producing a renewable carbon feedstock, but a deeper understanding of their performance is required for system optimization and control. In this study, we characterized the performance of a 568 m3·day-1 Clearas EcoRecover system for tertiary phosphorus removal (and recovery as biomass) at an operating water resource recovery facility (WRRF). The process consists of a (dark) mix tank, photobioreactors (PBRs), and a membrane tank with ultrafiltration membranes for the separation of hydraulic and solids residence times. Through continuous online monitoring, long-term on-site monitoring, and on-site batch experiments, we demonstrate (i) the importance of carbohydrate storage in PBRs to support phosphorus uptake under dark conditions in the mix tank and (ii) the potential for polyphosphate accumulation in the mixed algal communities. Over a 3-month winter period with limited outside influences (e.g., no major upstream process changes), the effluent total phosphorus (TP) concentration was 0.03 ± 0.03 mg-P·L-1 (0.01 ± 0.02 mg-P·L-1 orthophosphate). Core microbial community taxa included Chlorella spp., Scenedesmus spp., and Monoraphidium spp., and key indicators of stable performance included near-neutral pH, sufficient alkalinity, and a diel rhythm in dissolved oxygen.

Integrating Tensometer Measurements, Elastic Half-Space Modeling, and Long-Term Pavement Performance Data into a Mechanistic–Empirical Pavement Performance Model

Pavement performance models (PPMs) are utilized to predict pavement network conditions which is an essential part of any sustainable pavement management system (PMS). The reliability of a PMS and its outputs is proportional to the reliability of the PPM used. This article describes a mechanistic–empirical pavement performance model based on pavement response parameters—strains calculated in the pavement layers measured by tensometers embedded in the pavement surface and verified by calculations in the elastic half-space model and supplemented by empirical data from long-term pavement performance monitoring and accelerated pavement testing. Hence, the herein described PPM combines pavement serviceability evaluation, pavement bearing capacity, and the physico-mechanistic properties of paving materials. The analytical methods which were used to ascertain the physico-mechanistic characteristics, the material fatigue degradation model, and the surface degradation, unevenness in particular, are described. A comparison of the empirical PPM created in the last century used by the national road administrator to this day and the newly created PPM is presented. The comparison shows the difference in the calculated socio-economic benefits and subsequent cost–benefit analysis results. The comparison shows that the use of the old PPM may have produced false economic evaluation results that have led to poor decision making, partially explaining the unsustainable trend of road network management in our country.

Hydrological response to land use/land cover changes in Ethiopian basins: a review

Hydrological response to land use/land cover changes in Ethiopian basins: a review

Regulatory Insights for On-Board Monitoring of Vehicular NOx Emission Compliance.

Nitrogen oxide (NOx) emissions from heavy-duty diesel vehicles (HDDVs) have adverse effects on human health and the environment. On-board monitoring (OBM), which can continuously collect vehicle performance and NOx emissions throughout the operation lifespan, is recognized as the core technology for future vehicle in-use compliance, but its large-scale application has not been reported. Here, we utilized OBM data from 22,520 HDDVs in China to evaluate their real-world NOx emissions. Our findings showed that China VI HDDVs had a 73% NOx emission reduction compared with China V vehicles, but a considerable proportion still faced a significant risk of higher NOx emissions than the corresponding limits. The unsatisfactory efficiency of the emission treatment system under disadvantageous driving conditions (e.g., low speed or ambient temperature) resulted in the incompliance of NOx emissions, especially for utility vehicles (sanitation/garbage trucks). Furthermore, the observed intertrip and seasonal variability of NOx emissions demonstrated the need for a long-term continuous monitoring protocol instead of instantaneous evaluation for the OBM. With both functions of emission monitoring and malfunction diagnostics, OBM has the potential to accurately verify the in-use compliance status of large-scale HDDVs and discern the responsibility of high-emitting activities from manufacturers, vehicle operators, and driving conditions.

Sustainable And Bioengineered Concrete For Armor Units Of Low-Crested Structures

In the last two decades, Eco-engineering has emerged to mitigate and compensate the environmental impacts of man-made structures while integrates benefits to society, being concrete the most widely alternative material used to natural rocks for construction of artificial coastal structures. Over the past three decades, an extensive literature has documented different supplementary cementitious materials (SCMs) to reduce CO2 emissions from Portland cement, with common SCMs used in marine and coastal structures such as fly ashes, ground granulated blast furnace slags, pozzolanas and limestones. However, there is a need to further investigate the suitability of SCMs for the construction of Low-Crested Structures (LCS) to decrease carbon footprint from concrete production and improve the bioreceptivity of concrete armor units during the breakwater lifetime. A literature review conducted in this study shows several advantages of slag cements compared to other SCMs to reduce carbon emissions and enhance biological colonization and durability of concrete submerged in seawater, identifying surface roughness as the most effective factor in design of bioreceptive concrete. This study also highlights the importance of the type and quantity of cement used in concrete mixes to reduce carbon footprint of the manufacture of concrete armor units of LCS and the implementation of long-term monitoring plans to fully understand the functioning of local communities that develop on concrete surfaces of artificial structures, and thus, to improve the integration of environmental parameters in the field of coastal engineering.

50 Years Of Hanbar Concrete Units In Australia And New-Zealand: Lessons Learned From Physical Modelling Studies And Recently Built Structures

During the last 50 years, numerous breakwaters along the eastern coast of Australia, and more recently in New Zealand, have undergone construction, repairs, or upgrades using Hanbar concrete armour units. These units are distinct to Australasia, and there is limited information about their properties in standard coastal engineering literature. This paper first provides a survey and timeline of all known projects using Hanbars. An overview of the Hanbar concrete unit features and manufacturing method is then provided. The paper presents a summary of results of previous modelling studies of Hanbar applications to specific breakwaters, as well as recent research programs completed at WRL, and provides placement density guidelines as well as recommended damage coefficient (Hudson Kd) for design. The paper concludes with a brief overview of two recent case studies which have successfully capitalized on the economical, robustness and manufacturing simplicity of the Hanbar concrete units. The first case study is on the Opotiki Harbour Development (“OHD”) in New Zealand. The OHD scheme comprises twin 400 m long training wall breakwaters to train a dynamic river mouth. A multi-stage approach to physical modelling was adopted by conducting 2D modelling of key sections of the training wall trunks, quasi-3D modelling of the breakwater head, and full 3D modelling of complete structures. The second case study presents the results of a field trial investigating the potential for high-density geopolymer concrete (GPC) coastal armour units. This resulted in the casting and placing of thirteen 16 t GPC Hanbar units (SG 2.6) on the Port Kembla northern breakwater in NSW. The trial proved the viability of production of geopolymer armour units, and allowed long-term monitoring of the integrity of the concrete in the aggressive marine environment.

Addressing Heavy Metal Pollution in Nigeria: Evaluating Policies, Assessing Impacts, and Enhancing Remediation Strategies

Heavy metal pollution is a significant environmental concern in Nigeria, posing risks to ecological integrity and public health. This study aims to evaluate the existing policies and regulations addressing heavy metal pollution, assess their effectiveness, and propose recommendations for improvement. The analysis reveals that while Nigeria has established a robust legislative framework, challenges in implementation, enforcement, and funding persist. The impact of reducing heavy metal pollution is influenced by resource constraints, limited capacity, and the need for stronger collaboration between regulatory bodies and industries. Community involvement and education play a crucial role in managing heavy metal pollution, emphasizing the importance of awareness, sustainable practices, and local engagement. Remediation strategies, such as bioremediation and phytoremediation, offer potential solutions. However, gaps in knowledge and research exist, calling for long-term monitoring, ecological impact assessments, and comprehensive health risk assessments. To enhance the effectiveness of current policies, periodic reviews, increased funding, and community-based monitoring programs are recommended. By addressing these gaps and implementing the proposed recommendations, Nigeria can make significant strides towards mitigating heavy metal pollution and achieving environmental sustainability.

Application of Sentinel-1 InSAR to monitor tailings dams and predict geotechnical instability: practical considerations based on case study insights

Tailings storage facilities (TSFs) impound mining waste behind dams to ensure public safety, but failure incidents have prompted calls for more robust monitoring programs. Satellite-based interferometric synthetic aperture radar (InSAR) has grown in popularity due to its ability to remotely detect millimeter-scale displacements in most urban and some natural terrains. However, there remains a limited understanding of whether InSAR can be as accurate or representative as on-the-ground instruments, whether failures can be predicted in advance using InSAR, and what variables govern the quality and reliability of InSAR results. To address these gaps, we analyze open-source, medium-resolution Sentinel-1 data to undertake a ground-truth assessment at a test site and a forensic analysis of five failure cases. We use a commercial software with an automated Persistent Scatterer (PS) workflow (SARScape Analytics) for all case study sites except one and a proprietary algorithm (SqueeSAR) with a dual PS and Distributed Scatterer (DS) algorithm for the ground-truth site and one forensic case. The main goal is to deliver practical insights regarding the influence of algorithm/satellite selection, environmental conditions, site activity, coherence thresholds, satellite-dam geometry, and failure modes. We conclude that Sentinel-1 InSAR can serve as a hazard-screening tool to help guide where to undertake targeted investigations; however, most potential failure modes may not exhibit InSAR-detectable accelerations that could assist with time-of-failure prediction in real time. As such, long-term monitoring programs should ideally be integrated with a combination of remote sensing and field instrumentation to best support engineering practice and judgment.

Microplastic and other anthropogenic microparticles in Arctic char (Salvelinus alpinus) and their coastal habitat: A first-look at a central Canadian Arctic commercial fishery

In the recent monitoring guidelines released by the Arctic Monitoring and Assessment Program's Litter and Microplastic Expert Group, Arctic salmonids were recommended as an important species for monitoring plastics in Arctic ecosystems, with an emphasis on aligning microplastic sampling and analysis methods in Arctic fishes. This recommendation was based on the minimal documentation of microplastics in Northern fishes, especially Arctic salmonids. In response, we worked collaboratively with local partners to quantify and characterize microplastics in Arctic char, Salvelinus alpinus, and their habitats in a commercial fishery near Iqaluktuuttiaq (Cambridge Bay), Nunavut. We sampled Arctic char, surface water, and benthic sediments within their summer foraging habitat at Palik (Byron Bay). We found microplastics in 95 % of char with an average of 26 (SD ± 19) particles per individual. On average, surface water samples had 23 (SD ± 12) particles/L and benthic sediment <1 particles/gww. This is the first documentation of plastic pollution in Arctic char and their coastal habitats. Future work should evaluate seasonal, temporal and spatial trends for long-term monitoring of microplastics in Arctic fishes and their habitats.

Does the Artificial Enhancement and Release Activity Affect the Genetic Diversity of Marbled Rockfish Sebastiscus marmoratus in Zhoushan Waters?

Artificial enhancement and release activity is an important method in the restoration of fishery resources. In order to understand the possible genetic effect of hatchery-released populations on wild populations during the artificial enhancement and release activities of Sebastiscus marmoratus in Zhoushan waters, we utilized mitochondrial DNA control region sequences to examine the genetic diversity in four S. marmoratus populations, including one farmed population, one released population and two wild populations. A total of 68 haplotypes from 123 individuals were detected, including 3 shared haplotypes. Haplotype diversity ranged from 0.944 to 0.980, with a mean of 0.966. The nucleotide diversity ranged from 0.020 to 0.025, with a mean of 0.022. Analysis of Molecular Variance (AMOVA) indicated that the primary genetic variation occurs within populations and the index of genetic differentiation between populations (FST) among the four populations showed no differentiation. The results indicate that the current artificial enhancement and release has not impacted the S. marmoratus population in Zhoushan waters. Continued long-term monitoring is essential to protect the high-quality germplasm resources of S. marmoratus.

Establishment of a pMCAO model in SD rats and screening for behavioral indicators suitable for long-term monitoring

ABSTRACT Objective: This study aimed to establish a permanent middle cerebral artery occlusion (pMCAO) model in rats to simulate the pathological process of stroke patients with no reperfusion. And screen highly sensitive items that could be used to detect long-term behavioral abilities in rat of intraluminal suture models. Method: Established the pMCAO model then tested the rats for the bilateral asymmetry, modified neurological severity score, grid-walking, cylinder, rotating, and water maze test from week 1 to week 16. Results: The infarct volume of the model rats was stable (26.72% ±1.86%). The sensorimotor test of bilateral asymmetry, grid-walking, cylinder, and mNSS test showed significant differences from week 1 to week 16 after injury. The water maze test at week 16 showed significant differences in spatial exploration and learning ability between the two groups. We confirmed that there was no significant difference between MRI and TTC staining in detecting the degree of brain injury, which facilitated the diversity of subsequent detection methods. We also confirmed that at multiple time points, grid, cylinder and water maze test were significantly positively correlated with rat brain infarct volume. Conclusion: They are suitable for the long-term observation of behaviors in the sequela stage of stroke in rat.

Investigation of temperature effects on wide steel box girder of suspension bridge based on long-term monitoring data

The time-varying temperature distributions on bridge structures may remarkably change structural performance, which may result in differential strain/stress responses on structural members compared with the design conditions. Therefore, it is crucial to have a comprehensive understanding of temperature distributions and its effects on bridges. In this study, taking advantage of structural health monitoring technology, 1-year field monitoring data collected from a long-span suspension bridge were used to investigate the temperature distributions and their effects on the steel box girder. Specifically, the distributions and probability statistics of temperatures on the top and bottom plates were firstly analyzed. Based on which, the transverse and vertical temperature differences on the box girder were further examined, moreover, the representative values of temperature differences for various return periods were calculated by exceedance probability method. At end, a temperature prediction method was proposed to simulated the temperature field distributions during bridge life cycle, to provide substantial temperature data for estimating future operation condition. The results of this study were beneficial to structural evaluation of in-service bridges to ensure their serviceability and integrity in the life cycle.

Overview and Analysis of Ground Subsidence along China’s Urban Subway Network Based on Synthetic Aperture Radar Interferometry

Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the overall deformation situation are lacking in China. Therefore, targeting 35 Chinese cities whose subway mileage exceeds 50 km, we extracted their surface deformation along subway networks between 2018 and 2022, using spaceborne synthetic aperture radar (SAR) interferometry (InSAR) technology and Sentinel-1 satellite data. We verified the results with the continuous global navigation satellite system (GNSS) stations’ data and found that the root mean square error (RMSE) of the InSAR results was 3.75 mm/year. Statistical analysis showed that ground subsidence along the subways was more prominent in Beijing, Tianjin, and other areas in the North China Plain, namely Kunming (which is dominated by karst landforms), as well as Shanghai, Guangzhou, Qingdao, and other coastal cities. In addition, an analysis revealed that the severity of surface subsidence correlated positively with a city’s gross domestic product (GDP) with a Pearson correlation of 0.787, since the higher the GDP, the more frequent the construction and maintenance of subway, and the more commuters there are, which in turn exacerbates the disturbance to the surface. Additionally, the type of land cover also affects the ground deformation. Our findings provide a reference for constructing, operating, and maintaining the urban subway systems in China.

Examination of cardiac functions during acute attack and remission period in children with familial Mediterranean fever.

Familial Mediterranean fever (FMF) is an autosomal recessive autoinflammatory disease characterized by recurring serosal inflammation. Cardiac involvement in FMF commonly manifests as pericarditis and pericardial effusion; however, there is limited research on myocardial function. This study aimed to assess cardiac functions during active inflammation and remission periods of FMF patients and investigate the cardiac effects of inflammation during the attack period. Thirty-eight FMF patients without additional cardiac diseases were included in the study. Demographic characteristics, clinical symptoms, family history, and MEFV gene analysis results were obtained retrospectively. Blood tests, blood pressure measurements, electrocardiogram evaluations, conventional echocardiography, and speckle tracking echocardiography were performed during the attack and remission periods. Disease severity was assessed using the Pras scoring system. During the attack period, FMF patients exhibited significantly higher leukocyte count, neutrophil count, C-reactive protein, and erythrocyte sedimentation rate compared to the remission period (p < 0.005). Speckle tracking echocardiography revealed decreased function in the inferior segments of the left ventricle during the attack period (p < 0.005). Right ventricular function was more affected in the moderate disease group. FMF patients with lymphopenia during the attack demonstrated more impaired right ventricular function compared to those with normal lymphocyte count. Conclusions: FMF patients experience cardiac abnormalities during active inflammation, highlighting the importance of monitoring cardiac functions in these patients. Speckle tracking echocardiography can provide valuable insights into cardiac involvement in FMF. These findings emphasize the cardiac impact of FMF inflammation and the significance of long-term cardiac function monitoring in the management of FMF patients. What is Known: • The current literature lacks studies investigating myocardial function in the pediatric population during the attack period of this particular disease. • Our objective was to assess the alterations in cardiac function during the attack and remission periods, considering clinical manifestations, disease severity, acute phase reactant levels, and mutation type. We also evaluated the pattern of cardiac involvement and the affected cardiac areas by comparing remission and attack periods. What is New: • Several studies have demonstrated a rise in the prevalence of ischemic cardiac disease and mortality among individuals with FMF. • Investigating cardiac involvement during the attack period in FMF patients can provide valuable insights for the prevention of long-term complications.

Measurement of body size parameters and body weight prediction in beef cattle based on image analysis

The body size parameter of cattle is an important index reflecting the growth and development and health condition of cattle. The traditional manual contact measurement is not only a large workload and difficult to measure, but also prone to problems such as affecting the normal life habits of cattle. In this paper, we address this problem by proposing a contactless body size measurement method for cattle based on machine vision. Firstly, the cattle is confined to a fixed space using a position-limiting device, and images of the body of the cattle are taken from three directions: top, left, and right, using multiple cameras. Secondly, the image is segmented using a fuzzy clustering algorithm based on neighborhood adaptive local spatial information improvement, and the image is processed to extract the contour images of the top view and side view. The key points of body measurements were extracted using interval division and curvature calculation for the side view images, and the key point information was extracted using skeleton extraction and pruning for the top view images, which realized the measurements of body height(BH), rump height(RH), body slanting length(BSL), and abdominal circumference(AC) parameters of the cattle. The correlation between body size and weight data obtained by contactless methods was investigated and the modeled using one-factor linear regression, one-factor nonlinear regression, multivariate stepwise regression, RBF network fitting, BP neural network fitting, support vector machine, and particle swarm optimization-based support vector machine methods, respectively. Information on body size parameters was collected from 137 cattles, and the results showed that the maximum errors between the measured and actual values of BH, RH, BSL and AC were 5.0%, 4.4%, 3.6%, and 5.5%, respectively. Correlation of BH, RH, BSL and AC with weight obtained by non-contact methods was &gt; 0.75. The BH parameter can be selected in the single-factor growth monitoring. The multi-body scale can reflect the growth status of cattle more comprehensively, in which RH, BSL and AC are important detection parameter; the multi-factor nonlinear model can reflect the growth characteristics of cattle more comprehensively. The contactless measurement method proposed in the paper can effectively improve the work efficiency and reduce the stress reaction of cattle, which is a long-term and effective monitoring method, and is of great significance in promoting accurate and welfare cattle rearing.

Analysis of irregularly sampled stream temperature time series: challenges and solutions

Water temperature is a key physical indicator of stream health, and as such, is commonly measured as part of long-term river health monitoring programs. However, analysis of long-term stream water temperature time series can be challenging, due to typically low frequencies of sampling combined with common characteristics of data collection from streams – such as observations unevenly spaced across seasons, changes to routine sampling frequencies, or improvements in the accuracy of measurements over time – known as sampling artifacts. While there are many models regularly used to estimate trends and summary statistics in long-term stream temperature datasets, there is limited understanding of the impact that commonly encountered sampling artifacts have on the accuracy and uncertainty of their estimates. This study constructed Monte-Carlo simulations to examine the influence that common sampling artifacts and the choice of analysis model can have on trend and mean estimates from long-term stream temperature time series covering tropical, temperate and cold climates. We found that, if not appropriately accounted for during analysis, sampling artifacts may obscure true trends or summary statistics, such as site means, and lead to inaccurate or misleading estimates. However, models that included components to account for seasonal variation within the model structure could estimate trends and means with high confidence, in the presence of almost all of the sampling artifacts commonly found in long-term stream temperature datasets. Structural biases in the time-of-day of sampling, such as always sampling in the morning, or where the start and end of the record are sampled at different times of day, could make estimates highly inaccurate and uncertain, and should be avoided in data collection strategies. This work aims to facilitate the analysis of historical stream temperature datasets with confidence, through identifying models that perform reliably in the presence of common sampling artifacts. The findings will enable further global insights into stream temperature, support management decisions based on accurate analysis and assist the design of future stream sampling programs using cost-effective, low-frequency sampling strategies.

No Detectable Differences in microRNA Plasma Levels between Diabetic Hypertensive Patients with and without Incident Subclinical Atrial Fibrillation.

Background: Long-term rhythm monitoring (LTRM) can detect undiagnosed atrial fibrillation (AF) in patients at risk of AF and stroke. Circulating microRNAs (miRNAs), which have been shown to play a role in atrial electrical and structural remodelling, could help to select patients who would benefit most from LTRM. The aim of this study was to investigate whether patients with diabetes mellitus (DM) and hypertension and screen-detected subclinical AF (SCAF) using an insertable cardiac monitor (ICM) have significantly different plasma baseline levels of five selected miRNAs playing a role in the modulation of atrial electrical and structural remodelling (miR-21-5p, miR-29b-3p, miR-150-5p, miR-328-3p, and miR-432-5p) compared to those without SCAF. Methods: This study was performed at the outpatient clinic of a secondary academic teaching hospital between December 2013 and November 2015. Eligible patients were ≥65 years of age with DM and hypertension but without known heart diseases. All patients received an ICM. On the day of ICM implantation, blood samples for the measurement of plasma levels of the five miRNAs were drawn. In this post hoc analysis, we investigated their expression by reverse transcription-quantitative polymerase chain reaction. MiRNA plasma levels in patients with and without newly detected SCAF were compared. Results: We included 82 consecutive patients (median age of 71.3 years (IQR 67.4-75.1)), who were followed for a median of 588 days (IQR: 453-712 days). Seventeen patients (20.7%) had ICM-detected SCAF. Plasma levels of miR-328-3p, miR-29b-3p, miR-21-5p, miR-432-5p, and miR-150-5p were slightly but not significantly different in patients with incident SCAF compared with patients without. Conclusions: In patients with hypertension and DM, newly detected SCAF was not significantly associated with changes in expression levels of miR-21-5p, miR-29b-3p, miR-150-5p, miR-328-3p, and miR-432-5p.

Structural and Successional Dynamics of Old-Growth Mixed Oak Forests in the West Qinling Mountains

Understanding the composition and structure of forest trees is crucial to comprehending the properties and functions of forests. It also helps in implementing effective management strategies for sustainable resource utilization. Our study analyzed the structural dynamics of the old-growth mixed oak forests in the Xiaolongshan Forest region, focusing on three long-term monitoring plots (A, B, C). We examined the tree species composition, diameter distribution, mortality, and recruitment dynamics of different successional species groups, as well as the spatial distribution patterns of living and dead trees, with surveys conducted every five years. The findings indicate: (1) Plot A experienced a decline in stand density and species diversity during the survey period, with the Importance Value Index (IVI) of pioneer successional species continually decreasing in plots B and C. (2) The tree diameter distribution structure in plot A significantly differed from other plots, showing notable change between 2007 and 2012. (3) All plots exhibited lower, well-balanced community-level demographic parameters based on stem number, but a higher recruitment rate for later successional species groups based on basal area. (4) Dead individuals in plot A had a slight clustering distribution, while the other plots showed a random distribution. We conclude that the individual growth rate significantly impacts the dynamics of the natural Quercus aliena var. acuteserrata forest, with pioneer species groups being gradually replaced by early or late-successional species groups in the succession process.

The effects of precursory velocity changes on earthquake nucleation and stress evolution in dynamic earthquake cycle simulations

Seismic velocity changes in earthquake cycles have been observed over a wide range of timescales and may be a good indicator of the onset of future earthquakes. Understanding the effects of precursory velocity changes right before seismic and slow-slip events could potentially elucidate the onset and timing of fault failure. We use numerical models to simulate fully dynamic earthquake cycles in 2D strike-slip fault systems with antiplane geometry, surrounded by a narrow fault-parallel damage zone. By imposing S-wave velocity changes inside fault damage zones, we investigate the effects of these precursors on multiple stages of the seismic cycle, including nucleation, coseismic, postseismic, and interseismic stages. Our modeling results show a wide spectrum of fault slip behaviors including fast earthquakes, slow-slip events, and variable creep. One primary effect of the imposed velocity precursor is on the earthquake nucleation phase, and earlier onset of precursors causes earthquakes to nucleate sooner with a smaller nucleation size that is not predicted by theoretical equations. Furthermore, such precursors affect the nucleation of dynamic earthquakes and slow-slip events. Our results highlight the importance of short- and long-term monitoring of fault zone structures for better assessment of regional seismic hazard.