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Psychological distress and posttraumatic stress, including anxiety, severely influence life quality. Previously, we reported that interleukin-18 (IL-18) was involved in pyroptosis-induced emotional changes in a rodent model of hemorrhagic shock and resuscitation (HSR). Here, we aimed to continue our investigation on the role of IL-18 binding protein (IL-18BP), which exhibits excellent anti-inflammatory effects as an IL-18 negative regulator. Mice were administered with an intraperitoneal injection of IL-18BP after HSR exposure and anxiety-like behavior was examined using the open-field test and elevated plus maze test. Moreover, the following variables post-HSR were measured: (1) the activation of astrocytes; (2) pyroptosis-associated factors including cleaved caspase-1, GSDMD, IL-18; (3) the roles of IL-18 receptor (IL-18R)-NOD-like receptor pyrin domain-containing-3 (NLRP3) signal with the application of the NLRP3 specific agonist or astrocyte-specific NLRP3 knockout mice. IL-18BP administration remarkably alleviated HSR-induced anxiety-like behavior, astrocytic activation, and increases in pyroptosis-associated factors, while NLRP3 agonist nigericin partially reversed IL-18BP-induced neuroprotective effects. Astrocyte-specific NLRP3 knockout mice exhibited relatively less anxiety-like behavior. Similarly, IL-18BP exhibited an anti-pyroptosis effect in astrocytes in an in vitro model of low oxygen-glucose deprivation. These findings offer unique perspectives on HSR-induced posttraumatic stress and indicate that inhibition of IL-18R-NLRP3 signal via IL-18BP can attenuate astrocytic activation and pyroptosis, broadening the therapeutic landscape for patients with psychological distress and posttraumatic stress.

Slope reliability analysis can effectively account for uncertainties involved in a slope system. However, commonly used slope reliability analysis methods often require huge computational cost, especially in large-scale problems, which hinders its wide application to engineering practice. This paper proposes an efficient slope reliability analysis method based on the active learning support vector machine (SVM) and Monte Carlo simulation (MCS). The proposed method makes use of an active learning function and cross-validation techniques to select the most suitable training samples to update the SVM model. The selected training samples are associated with a small distance to the limit state surface of the slope stability model and a large local uncertainty, which are more informative to gradually tune the SVM model to approximate the actual slope performance function. As a result, the proposed method can estimate the slope reliability with a small number of evaluations of the slope performance function, thus improving the efficiency significantly. Four slope examples are employed to demonstrate the effectiveness of the proposed method. The presented approach is also compared with some other commonly used surrogate models in slope reliability analysis. It is shown that the proposed method performs better in terms of computational efficiency to obtain similar estimation accuracy of the failure probability for the investigated examples.

Integrating borehole and piezocone penetration test (CPTU) data in site characterization helps to achieve a more comprehensive understanding of ground conditions. However, soil types at CPTU and nearby borehole locations may not always be consistent. The presence of noisy data or thin layers will mislead the interpretation of CPTU data in soil type classification and soil property evaluation. This study proposes a coupled machine learning method to integrate the borehole and CPTU data under a rigorous Bayesian framework and to identify and separate the noisy CPTU data without subjective judgment, which contributes to more reliable soil classification and property evaluation. The borehole-reported soil type and CPTU data are treated as two types of evidence of the authentic soil type. A lateral transition of soil type from the CPTU location to the borehole location is allowed to capture the discrepancy of soil types. The proposed approach is applied to the marine site characterization of the Hong Kong-Zhuhai-Macao Bridge that crosses the Pearl River Estuary of China. The soil seams embedded in the dominant soil strata are successfully detected, producing a more reliable soil profile and interpreting more compatible soil properties with engineering practice. Additionally, the integration of borehole and CPTU data significantly reduces the stratification uncertainty in site characterization.

Recently, a new handheld ultrasound-based device, called Accuro, has been commercialized with a real-time automated interpretation of lumbar ultrasound images. We hypothesized that the handheld ultrasound device would improve the efficacy and safety of combined spinal-epidural anesthesia (CSEA) for cesarean delivery in obese parturients. Eighty parturients with a body mass index > 30 kg∙m−2 scheduled for elective cesarean delivery were randomly allocated equally (palpation group and ultrasound group). The primary outcome was the first insertion success rate. Secondary outcomes were the time taken to identify the needle puncture site, duration of CSEA procedure, the total time, the rate of parturients who require needle redirections, the number of skin punctures, changes in the intended interspace, and the incidence of complications. Compared to the palpation group, the first insertion success rate was significantly higher (72.5% vs. 40.0%; P = 0.003), and time taken to identify the needle puncture site was less (30 [26–36] vs. 39 [32–49] seconds; P = 0.001) in the ultrasound group. The rate of parturients who required needle redirections (40.0% vs. 72.5%; P = 0.003) and the incidence of paresthesia were both lower (7.5% vs. 45.0%; P

We investigated S. alterniflora saltmarshes in 10 regions to distinguish the major sources of soil organic carbon (SOC) and provide data for SOC content in Chinese coastal wetlands under exotic invasion. We collected soil and plant samples. We analyzed the soil properties for SOC content, recalcitrant organic carbon (RC), labile organic carbon (LC), total nitrogen (TN), total phosphorus (TP), total salinity and water content, as well as stable isotopic carbon composition (δ13C) in the SOC and RC. SOC and RC were determined using a Shimadzu TOC analyzer. We used δ13C values and C/N ratios of the SOC to identify carbon source inputs. The δ13C of the SOC and RC was measured using a Sercon Integra CN isotope ratio mass spectrometer. The results showed that the S. alterniflora saltmarsh SOC pool properties differed significantly between study areas, dependent upon local circumstances and carbon exchanges. The δ13C values of SOC in surface sediments from Tianjin to Guangxi were from −25.16 to −20.64‰, RC from −27.82 to −23.1‰, and C/N ratios between 11.36 and 19.00. These samples had SOC values of 14.77–23.95 g kg−1, RC values of 11.98–21.44 g kg−1, and LC values of 0.44–4.08 g kg−1. The SOC and RC of surface sediments were positively correlated with TN and TP. S. alterniflora saltmarsh SOC is derived from multiple carbon inputs including from marine and land sources and its formation is driven by complicated factors. TN and TP inputs increase SOC in coastal wetlands. Generally, terrigenous carbon inputs dominate the SOC composition in Chinese coastal wetlands, although marine-derived organic carbon (OC) inputs to sediment increase from northern to southern areas.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s12906-020-2834-8.

Following hepatic ischemia-reperfusion injury, Kupffer cells could be activated by inflammatory factors released from damaged hepatocytes. Carbon monoxide (CO)-releasing molecule (CORM)-3, a water-soluble transition metal carbonyl, exhibits excellent anti-inflammatory and anti-pyroptosis properties. We investigated whether CORM-3 attenuated hemorrhagic shock and resuscitation (HSR)-induced pyroptosis of Kupffer cells through the soluble guanylate-cyclase (sGC)-cyclic guanosine monophosphate (cGMP) signal pathway. NS2028 (10 mg/kg), a blocker of sGC, was administrated at the onset of hemorrhage, but CORM-3 (4 mg/kg) was infused after resuscitation via femoral vein. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST) levels, tumor necrosis Factor-α (TNF-α), and interleukin-1β (IL-1β) were measured at 3, 6, 12, and 24 h after HSR, respectively. Six hours post-HSR, liver injury, pyroptosis of Kupffer cells, and expressions in total caspase-1, cleaved caspase-1, gasdermin D (GSDMD) N-terminal fragment, IL-1β, and IL-18 were measured by hematoxylin-eosin (H&E), immunofluorescence and western blot assays, respectively (Fig. 1). The rats exposed to HSR exhibited significant upregulated levels of serum ALT, AST, TNF-α, and IL-1β, elevated liver injury score, increased pyroptosis of Kupffer cells, and accumulated expressions of pyroptosis-associated protein including cleaved caspase-1, GSDMD N-terminal fragment, IL-1β, and IL-18 than sham-treated rats. However, CORM-3 administration markedly reduced liver injury and pyroptosis of Kupffer cells, whereas these protective effects could be partially blocked by NS2028. CORM-3 can mitigate pyroptosis of Kupffer cells in a blood loss and re-infusion model of rats via sGC-cGMP signal pathway.

Landslide susceptibility is the likelihood of a landslide occurring in an area. The logistic regression (LR) method is one of the most popular methods for landslide susceptibility assessment. For rainfall-induced landslides, yearly or monthly rainfall is commonly used to establish a landslide susceptibility model by the LR method. It is a static susceptibility model, which limits the application to predict future landslide probability under potential rainfall event. This study presents a revised logistic regression method to achieve dynamic landslide susceptibility prediction under cumulative daily rainfall. Five kinds of cumulative daily rainfall are used in the landslide susceptibility assessment. The latest landslide events are used to update the landslide susceptibility model. The receiver operation characteristic curve and area under curve are utilized to evaluate the prediction reliability. The landslide susceptibility assessment in Shenzhen is taken as an illustration of the proposed method. The result indicates the method is capable to achieve a high accuracy of 91.9% when the landslide susceptibility model is updated using seven extreme rainfall events in the past 10 years. This method provides an advance prediction of the potential geo-hazards for a large area using the future rainfall forecast.

Floating plants are widespread in aquatic ecosystems. Most floating plants are clonal and their clones can be easily fragmented as a result of natural events or human activities. Such clonal fragmentation may decrease the growth and thus the competitive ability of floating plants. We tested these hypotheses with the widespread floating, clonal plant Salvinia natans. We simulated disturbance-mediated fragmentation of S. natans clones at two levels (low or high) by cutting clones initially consisting of six connected ramets into two fragments with three connected ramets each or six fragments with one ramet each), with no fragmentation as the control. These fragmented or intact clones were grown under two nutrient levels (low or high) in the presence or absence of the floating plant S. polyrhiza. High nutrient availability significantly increased the biomass and ramet number of S. natans, and the presence of S. polyrhiza reduced them. Furthermore, the negative effect of competition of S. polyrhiza on S. natans was greater under high than under low nutrient availability. Clonal fragmentation of S. natans significantly decreased its growth, but did not affect its competitive response or effect. Thus, nutrient availability can affect competition between S. natans and S. polyrhiza, but clonal fragmentation cannot. Our results suggest that clonal fragmentation and decreasing nutrient availability can decrease the spread of some clonal floating plants in aquatic ecosystems and that increasing disturbance to fragment clones and reducing nutrient load in water could be efficient at controlling the spread of some floating plants.

Landslide dams are extremely dangerous because dammed rivers can inundate upstream areas with rising water levels and flood downstream areas after dam breaching. The longevity of landslide dams, which is uncertain, is of great significance for dam failure prevention and mitigation since it determines the time available to take mitigation measures. In this study, the full longevity of landslide dams is divided into three stages (infilling, overflowing and breaching) for better estimation. The influences of dam characteristic parameters (triggers, dam materials and geometric/hydrological parameters) on the full longevity of landslide dams (the period from landslide dam formation to the end of dam failure) as well as on each of the three stages are analysed based on the database. Based on eight dimensionless variables, regression models for estimating the full longevity of landslide dams are developed with a R2 value of 0.781, and regression models for the three-stage longevity (the longevity as the sum of the periods of the three stages) by considering infilling, overflowing and breaching are established with a R2 value of 0.938. It is found that the landslide dam longevity cannot be predicted by one or two influencing factors since it is affected by multiple factors. The relative importance of each control variable is evaluated based on sensitivity analysis: the trigger is the most significant variable in the breaching stage since it affects the size of dam particles, the water content and the inflow rate (e.g. the rainfall trigger results in a larger inflow rate); the lake volume coefficient is more significant in the overflowing stage because it indicates the potential volume of water eroding the dam; and the average annual discharge coefficient is the most important factor in the infilling stage because it controls the time to impound water. The longevity predicted by different models are compared. The models developed in this paper show better accuracy due to the consideration of more parameters based on more cases. In particular, the three-stage longevity regression model shows better accuracy than that of other models because it considers the particular influencing factors for each stage. Three case studies (the “10·10” Baige, Hsiaolin and Tangjiashan landslide dams) are presented to show the application of the regression models developed in this paper. The dam longevity can be predicted more precisely if the timely inflow rate can be estimated by site monitoring or multi-temporal remote sensing images and pre-event digital elevation model (DEM).

The Yangtze River is one of the most important rivers in China due to its large basin size, the large population along the river, and the numerous large dams and reservoirs on the river. The Jinsha River, the upper reach of the Yangtze River, was dammed twice recently at Baige, Tibet, one on 10 October 2018 and the other on 3 November 2018 (UTC + 8). Accordingly, two large landslide dams, 61 m and 96 m in height to the lowest dam crest, were formed in a 3-week interval. Due to the large inflow rates at the time of damming, the barrier lake level rose rapidly, posing huge risks to the downstream residents and properties. In managing the landslide dam risk, one of the important tasks is to predict the dam breaching flood beforehand. This paper focuses on rapid prediction of the dam breaching hydrograph and breach geometric parameters of the two landslide dams. The predictions were made timely before the breaching of the two landslide dams using both erosion-based empirical equations and numerical simulation and were refined based on detailed field investigation at the site after breaching. Comprehensive field investigations were conducted to determine the geological structures of the landslide dams, characterize the erodibility of dam materials, and measure the final beach dimensions. The simulated dam breaching processes, outflow hydrographs, lake water level changes, and final breach dimensions were validated by field observations. Compared with the hypothetical scenario without a diversion channel on the second landslide dam, a diversion channel 15 m in depth successfully lowered the peak flood discharge by about one third and helped to mitigate the flood risk significantly. The analysis outcome serves as basis for warning and evacuation of the downstream residents and making appropriate engineering risk mitigation plans.

Urban landslides always occur where development has taken place on pre-existing unstable land. Due to rapid urbanization, human activities expand onto sloping terrain and disturb the geological environment, increasing the urban landslide risk. When a rapid flow-like landslide occurs, the landslide mobility can be affected by the presence of buildings located along its flow path. In this paper, the effect of building blockage on landslide mobility and the associated energy dissipation mechanisms are evaluated based on a well-documented landslide, which happened on 20 December 2015 in Shenzhen, China. The landslide flow process is reproduced by three-dimensional terrain analyses using LS-DYNA, considering three scenarios; namely, green field, movable buildings, and fixed buildings. Simulations show that the presence of densely located buildings significantly affects flow pattern, travel distance, deposition, and energy transfer mechanism. A fully developed debris fan in the flat area is observed in the green field case. The buildings in the runout path decelerate the flow process, leading to lower landslide mobility and less volume deposited in the accumulation zone. The shortest runout distance and widest and thickest deposits are observed in the fixed buildings case. The debris fan in the movable buildings case is closer to reality. Fixed buildings pose more constraint on surface moving material, leading to the largest deformation, largest internal energy, and smallest kinetic energy of the soil mass. The dissipation of the largest frictional energy occurs in the movable buildings case due to the long sliding distance of the damaged buildings. The internal energy of the landslide mass dominates the energy transfer mechanism. The results presented here indicate the need to consider building clusters when conducting urban landslide hazard mapping and risk assessment.

Flow slide is a flow-type landslide, which has high mobility and is destructive to the downstream infrastructures and buildings. In this study, a numerical method is presented to simulate the runout process of flow slide, and the interactions between flow slide and buildings on three-dimensional terrain considering the destruction process. In this proposed method, the flow slide is simulated by smoothed particle hydrodynamics (SPH) and the buildings are simulated by the finite element method (FEM). A node-to-surface contact algorithm is adopted to transfer displacements and contact forces between the flow slide and the buildings. An element erosion algorithm is adopted to simulate the destruction process. The method is validated using an analytical solution to dam break problem and the experimental results in two flume tests. A catastrophic flow slide involving building destruction is then simulated to further test the model performance. The flow depth, flow velocity, deposition area, and building damage degree are all reasonably simulated. The typical destruction process of buildings and patterns of the flow slide are also identified. The method will contribute to a better understanding of flow-structure interactions and is a promising tool for hazard analysis and mitigation.

Debris flows can cause severe loss of human lives and damage to property, especially on densely populated hilly terrains. In the changing climate, the frequency of debris flows is on a rising trend. Therefore, it is important to forecast possible scenarios of debris flows under extreme weather conditions. Previous numerical studies often deal with one individual debris flow in one analysis. Yet a large number of debris flows can occur in a large storm. This paper presents a physically based model to predict likely debris flow clusters on Hong Kong Island with an area of approximately 80 km2 considering the influence of the changing climate. Firstly, a slope stability analysis is conducted, and unstable cells and landslide deposition areas are predicted. Then clusters of debris flows initiating from these landslides are simulated considering hillslope erosion. The models are validated with historical debris flows triggered by a rainstorm in 2008. Finally, debris flow clusters under three reference extreme rainstorms (i.e. 44%, 65% and 85% of the 24-h probable maximum precipitation, PMP) are predicted. With the increase of rainstorm magnitude, numerous debris flows can occur simultaneously and merge, posing much greater threat to society. The consequences of debris flows grow dramatically when the magnitude reaches a certain extent, i.e. 65% of the 24-h PMP.

Obsequent rock slopes are often thought to be more stable than consequent slopes and passive sliding is unlikely to occur under earthquake loading. However, failures in obsequent rock slopes were indeed observed in recent large earthquakes. This paper presents a time–frequency solution to the seismic stability of obsequent rock slopes fully considering the time–frequency characteristics of earthquake waves. Large-scale shaking table tests were conducted to illustrate the application of the time–frequency method to an obsequent rock slope containing multiple weak layers with a small dip angle. The seismic stability of the obsequent rock slope is analyzed combining the time–frequency method, outcomes from the shaking table test, and conventional pseudo-static and dynamic numerical analyses. The results show that passive sliding can develop in the obsequent rock slope when taking the time–frequency components of the earthquake waves and the vertical seismic force into account. The middle–upper part of the obsequent rock slope is more vulnerable to seismic damage. The slope bulges under the earthquake loading; the maximum permanent surface displacement occurs at the middle–upper part of the slope, rather than the slope crest. Additionally, the response of seismic safety factor lags behind the responses of acceleration and surface displacement.

Buildings are the most concerned element in landslide risk assessment. A weak link in landslide risk analysis is the evaluation of building response and vulnerability when impacted by a landslide. In this paper, failure mechanisms and processes of typical reinforced concrete buildings upon landslide impacts are discovered through an explicit time integration analysis in LS-DYNA. The Arbitrary Lagrangian–Eulerian formulation, which allows automatic rezoning, is applied to simulate the landslide flow dynamics and the impact into the building. Three landslide intensity levels are considered. Progressive collapse of the building is observed in the high-impact intensity case. The frontal walls are firstly destroyed due to its low out-of-plane flexural capacity, followed by the progressive failure of columns at the ground floor. The collapse of building occurs when the remaining load-bearing components cannot resist the superstructure loadings. Two plastic hinge failure mechanisms are observed on the damaged columns when the ultimate bending moments of the columns are exceeded at both ends. Finally, a five-class classification system is proposed to evaluate building damage states based on field observations and the numerical simulation results. The analysis helps robust building design and assessment of building vulnerability to landslides.

Physical space, defined by its volume and shape, is considered a resource for plant growth, as a plant can be limited by physical space even when other resources (e.g., light, water and nutrients) are unlimited. However, the effect of physical space limitation on intraspecific competition of plants, especially floating plants, is not well understood. Here we tested the hypothesis that physical space affects the growth and intraspecific competition of floating plants, which is further influenced by the volume and surface area of the containers in which these plants are grown. We grew either one or four clonal fragments of a floating clonal fern, Azolla imbricata, in cylindrical containers differing in diameter and height (and thus surface area and volume) and filled with solutions containing the same or different nutrient concentrations. Biomass and number of clonal fragments of A. imbricata were higher in the container with the larger diameter and thus water surface area, but were not significantly affected by the height/volume of the container. Biomass and number of clonal fragments were reduced by intraspecific competition and tended to increase first and then decreased with increasing nutrient concentration. Increasing nutrient concentration inhibited the growth and then reduced intraspecific competition of A. imbricata, but the diameter or height/volume of the container had no effect. Our findings suggest that nutrient levels can alter intraspecific competition of plants, but physical space may not.

Background Catechins, caffeine, and theanine as three important metabolites in the tea leaves play essential roles in the formation of specific taste and shows potential health benefits to humans. However, the knowledge on the dynamic changes of these metabolites content over seasons, as well as the candidate regulatory factors, remains largely undetermined. Results An integrated transcriptomic and metabolomic approach was used to analyze the dynamic changes of three mainly metabolites including catechins, caffeine, and theanine, and to explore the potential influencing factors associated with these dynamic changes over the course of seasons. We found that the catechins abundance was higher in Summer than that in Spring and Autumn, and the theanine abundance was significantly higher in Spring than that in Summer and Autumn, whereas caffeine exhibited no significant changes over three seasons. Transcriptomics analysis suggested that genes in photosynthesis pathway were significantly down-regulated which might in linkage to the formation of different phenotypes and metabolites content in the tea leaves of varied seasons. Fifty-six copies of nine genes in catechins biosynthesis, 30 copies of 10 genes in caffeine biosynthesis, and 12 copies of six genes in theanine biosynthesis were detected. The correlative analysis further presented that eight genes can be regulated by transcription factors, and highly correlated with the changes of metabolites abundance in tea-leaves. Conclusion Sunshine intensity as a key factor can affect photosynthesis of tea plants, further affect the expression of major Transcription factors (TFs) and structural genes in, and finally resulted in the various amounts of catechins, caffeine and theaine in tea-leaves over three seasons. These findings provide new insights into abundance and influencing factors of metabolites of tea in different seasons, and further our understanding in the formation of flavor, nutrition and medicinal function.

Background Oxidative stress mediates the nerve injury during the pathogenesis of Alzheimer’s disease (AD). Protecting against oxidative stress damage is an important strategy to prevent and treat AD. Di-Huang-Yi-Zhi (DHYZ) is a Chinese medicine used for the treatment of AD, but its mechanism remains unknown. This study is aimed to investigate the effect of DHYZ on H2O2 induced oxidative damage in PC12 cells. Methods PC12 cells were treated with H2O2 and DHYZ. Cell proliferation was detected by Cell counting kit-8 (CCK-8) assay. Cytotoxicity of H2O2 was measured by lactate dehydrogenase (LDH) release assay. Apoptosis were identified by Annexin V-FITC/PI staining. Caspase 3 activity was detected by commercial kit. Mitochondrial membrane potential (MMP) was detected by JC-1 staining. Reactive oxygen species (ROS) was 2′, 7′-Dichlorodihydrofluorescein diacetate (DCFH-DA) staining. Protein expression and phosphorylation was identified by western blot. Results The results showed that DHYZ antagonized H2O2-mediated cytotoxicity and proliferation inhibition. DHYZ reduced ROS production, stabilize mitochondrial membrane potential, inhibit Caspase-3 activity and apoptosis induced by H2O2. In addition, DHYZ inhibited the phosphorylation of ASK1, JNK1/2/3 and p38 MAPK which were up-regulated by H2O2. Conclusions The present study suggested that DHYZ protected PC12 cells from H2O2-induced oxidative stress damage and was related to inhibition of ROS production and ASK1-JNK/p38 MAPK signaling. The present study provides experimental evidence for the application of DHYZ for the management of oxidative stress damage and AD.

An assessment of soil properties at unsampled locations is a common requirement during the design of a geotechnical structure/system. Such an assessment is challenging due to inherent soil variability and the limited number of in situ tests currently available. Here we present a three-dimensional conditioned random field approach for the estimation of anisotropic soil resistance at unsampled locations based only on data from a limited number of cone penetration tests (CPT). The novelty of this work is that the measured CPT data at arbitrary locations can be combined with random field theory to update the estimated soil properties in three dimensions. The accuracy of the estimation can be improved significantly using the proposed method. A case study in Australia is conducted to illustrate the procedure and to assess the capability of the method. The results indicate that the mean values of the conditioned random fields are good estimates of the soil resistance at unsampled locations. The prediction error of the normalized cone penetration resistance is about 0.08 when there are only six CPT tests. A unique feature of this method is its ability to obtain high-resolution results of soil properties in three-dimensional space using a limited number of CPT tests.

In this work, 3D discrete element method modeling of drained shearing tests with gap-graded soils after internal erosion is carried out based on published experimental results. The erosion in the model is achieved by randomly deleting fine particles, mimicking the salt dissolving process in the experiments. The present model successfully simulates the stress–strain behavior of the physical test by employing the roll resistance and lateral membrane. The case without erosion shows a strain-softening and dilative response, while strain-hardening and contractive response starts to occur as the degree of erosion increases. The dilative to contractive transition is mainly caused by the increase in void ratio due to the loss of fine particles. The change from dilative behavior to contractive behavior is more abrupt for the specimen with larger fine particle percentage because the soil skeleton is mainly controlled by the fine particles instead of by the coarse soil particles. The transition from “fines in sand” to “sand in fines” might be associated with the rapid increasing in the contacts associated with fine particles in the specimen as the percentage of fine content increases. The erosion scenario based on the hydraulic gradient is also modeled by deleting the fine particles based on the ranking of the contact force. Compared with the scenario based on random deletion, the remaining fine particles for the erosion scenario based on the ranking of contact force are more dispersedly distributed, which might benefit the small strain stiffness but result in a smaller strength. This work provides some insights for better understanding the mechanism behind the internal erosion and the associated stress–strain behavior of soil. The gradient of the critical state line increases with more loss of fine particles denoting that the fine particles are helpful for holding the structure of the soils from larger deformation.

Rain-induced landslides are recognized as one of the most catastrophic hazards on hilly terrains. To develop strategies for landslide risk assessment and management, it is necessary to estimate not only the rainfall threshold for the initiation of landslides, but also the likely magnitudes of landslides triggered by a storm of a given intensity. In this study, the frequency distributions of both open hillside landslides and channelized debris flows in Hong Kong are established on the basis of the Enhanced Natural Terrain Landslide Inventory (ENTLI) with 19,763 records in Hong Kong up to 2013. The landslide magnitudes are measured in terms of the number, scar area, volume, or density of landslides. The mean values of the scar areas and volumes are 55.2 m2 and 102.0 m3, respectively, for the open hillside landslides and 91.3 m2 and 166.5 m3, respectively, for the channelized debris flows. Empirical correlations between the numbers, scar areas, and volumes of hillside landslides or channelized debris flows and the maximum rolling rainfall intensities of different periods have been derived. The maximum rolling 4- to 24-h rainfall amounts provide better predictions compared with those with the maximum rolling 1-h rainfall. Maximum rolling rainfall intensity-duration thresholds identifying the likely rainfall conditions that yield natural terrain landslides or debris flows of different magnitudes are also proposed. The initiation rainfall thresholds are identified as 75, 90, 100, 120, 150, 180, and 200 mm for the maximum rolling 1-, 2-, 4-, 6-, 8-, 12-, and 24-h rainfall, respectively.

Heavy rainfall is a key cause of shallow landslides in red-bed terrains with steep topography and residual soils of degradable strength. In this study, laboratory model tests were carried out to examine the characteristics of rainfall infiltration, deformation, and failures of slopes in the red-bed area of Sichuan. The hydrological response and deformation of the slope soil during rainfall are addressed. Based on a modified Green–Ampt infiltration model, ponding along the bedrock surface is incorporated. A physically based model for shallow landslides caused by rainfall is developed. The theoretical analysis and the model test results indicate that the slope failures are related to erosion in the shallow soil layer and rainwater infiltration, particularly along preferential seepage channels. The process of rainfall-induced shallow landslides can be separated into three stages: erosion at the slope toe, tension crack formation at the slope crest, and shallow sliding. When initial underground water level is located at the bedrock surface or the preferential seepage flow quickly reaches the bedrock surface, it is easier for the soil slopes to slide along the bedrock surface than along the wetting front.

Based on the Hilbert–Huang Transform and its marginal spectrum, an energy-based method is proposed to analyse the dynamics of earthquake-induced landslides and a case study is presented to illustrate the proposed method. The results show that the seismic Hilbert energy in the sliding mass of a landslide is larger than that in the sliding bed when subjected to seismic excitations, causing different dynamic responses between the sliding mass and the sliding bed. The seismic Hilbert energy transits from the high-frequency components to the low-frequency components when the seismic waves propagate through the weak zone, causing a nonuniform seismic Hilbert energy distribution in the frequency domain. Shear failure develops first at the crest and toe of the sliding mass due to resonance effects. Meanwhile, the seismic Hilbert energy in the frequency components of 3–5 Hz, which is close to the natural frequency of the slope, is largely dissipated in the initiation and failure processes of the landslide. With the development of dynamic failure, the peak energy transmission ratios in the weak zone decrease gradually. This study offers an energy-based interpretation for the initiation and progression of earthquake-induced landslides with the shattering-sliding failure type.

Rock mass quality classification is essential in rock engineering. In practical engineering the parameters of rock mass vary with sampling disturbance and testing instruments, however obey a certain distribution. In other words, the classification of rock mass quality includes an uncertainty caused by the randomness of the parameters of the rock mass in geological formations. Traditional rock mass classification methods ignore the effect of this parameter uncertainty. In this paper, we propose a new method for evaluating rock mass quality considering the effect of parameter uncertainty through a rigorous reliability analysis. The weights of the classification system indexes are obtained using the game theory, combined with the technique for order preference by similarity to ideal solution (TOPSIS) in determining the limit-state function for reliability analysis. Stochastic uncertainty analysis is performed based on Monte Carlo simulation (MCS) and the limit-state function established by TOPSIS. The rock mass quality classification grade is obtained based on the probability calculation. The TOPSIS model with accurate game theory weighting is evaluated using 25 sets of samples. The results confirmed the reliability of the model. In a case study of rock mass surrounding a cavern, we verified the proposed rock quality classification method using certainty and uncertainty methods in MATLAB. The results demonstrate that the MCS–TOPSIS coupled model is efficient and accurate for classifying rock mass quality, and this approach is easy to implement.

Sedimentation and resuspension processes, are known to govern nutrient cycling and lake metabolic processes, but have not been well studied in littoral zones with multi-ecotypes of shallow wind-disturbed lakes. This time-series study used sediment traps to estimate the spatiotemporal changes in sedimentation and resuspension rates, during the four seasonal continuous deployment periods, in the littoral zone of Lake Taihu. The effect of sedimentation processes on nutrient accumulation was also investigated. Results showed that the sedimentation rates at six observation sites were highly variable, with gross sedimentation rates ranging from 184.83 to 2150.74 g m−2 day−1. Almost 88% of the total observed sedimentation originated from sediment resuspension. Cyanobacterial blooms coupled with the frequently changeable wind conditions in the littoral zone, were the key factors in lacustrine sediment redistribution and a large pool of organic material accumulated during cyanobacterial blooms. Moreover, the contribution of resuspended total phosphorous and total nitrogen to the water column, were 0.22 mg L−1 and 0.46 mg L−1, respectively. The high rate of rapid nutrient cycling observed at the sediment water interface due to resuspension, may be a key factor in maintaining eutrophication in large and shallow lakes, which is of high relevance to the future management of aquatic ecosystems.

Adjacent debris flows may interact in many ways: two or more concurrent debris flows may merge; one debris flow can run out over an existing debris flow fan. Such interactions may cause debris flow properties to change in the mixing process as well as more severe adverse effects than those caused by a single debris flow. This paper aims to investigate the interactions among channelized debris flows originated from adjacent catchments. Both concurrent and successive debris flows are considered. If several debris flows originate from different locations concurrently and merge, the volumetric sediment concentration (i.e., the ratio of the volume of solid material to the total volume of debris flow), C v, is a good index to capture the mixing process of these debris flows. The change in C v reflects where mixing occurs and the mixing degree. The debris flow properties (e.g., yield stress and dynamic viscosity) evolve in the mixing process and can be captured by the change in C v. The debris flow with a larger volume dominates the mixing process, and the properties of the mixed debris flow are more similar to those of the larger debris flow. The inundated areas and runout distances of successive debris flows are smaller than those of concurrent debris flows of the same total volume due to the smaller scales of the individual events and blockage by the earlier debris flows. However, the deposit depth in the interacting part of the debris flow fans of successive debris flows can be much larger than that of concurrent debris flows, leading to more destructive cascading hazards (e.g., the formation of debris barrier lakes). The sequence of successive debris flows not only significantly influences the runout characteristics of the debris flows but also substantially affects the cascading hazards.

An Ms 6.5 earthquake shocked the Ludian County, Yunnan Province, China, on 3 August 2014 and triggered the Hongshiyan landslide dam. The dam, with a height of 83 m and a lake capacity of 260 × 106 m3, threatened more than 10,000 people. A unique feature of this landslide dam was that it formed between a man-made dam and a hydropower plant. An existing drainage tunnel connecting the lake and the hydropower plant became a natural drainage conduit for the landslide dam, which played an important role in the mitigation of the landslide dam risks. This paper reports a quantitative risk assessment for the Hongshiyan landslide dam considering both engineering and non-engineering risk mitigation measures. The risk assessment is divided into three stages according to the implementation of two engineering measures: construction of a diversion channel and excavation of a branch drainage tunnel. The dam breaching hydrographs, flood zones, population at risk, and likely fatalities in each of the three stages are analysed. The optimum evacuation strategy in each stage is also studied based on the principle of minimum total consequence. It is found that the diversion channel decreases the dam breaching peak discharge and the associated risks significantly. The branch drainage tunnel prevent the landslide dam from overtopping failure in non-flooded period; however, the landslide dam may fail by overtopping in a future flood if the inflow rate is larger than the outflow rate through the drainage tunnels, resulting in serious losses of lives and properties. The dam breaching risks in all the three stages could be largely reduced by the optimal evacuation decision, which shows that timely evacuation is vital to save life and properties. The study provides a scientific basis for decision making in landslide dam risk management.

Grass cover is considered as a sustainable means of controlling soil erosion and enhancing durability of soil slopes. A number of grass species are commonly available for soil bioengineering in Hong Kong, but their capacities to control soil erosion have not been characterized quantitatively. The main objectives of this paper are to study the influence of soil density on characteristics of grass roots, to measure the erodibility parameters of the root-permeated soils at two growth stages, and to select the proper Hong Kong grass species that effectively control soil erosion. Three types of Hong Kong turf grass including Cynodon Dactylon, Paspalum Notatum, and Zoysia Matrella were planted on three soil grounds with degrees of compaction of 80, 90, and 100 %, respectively. The featural parameters of grass roots on each compacted ground, including root mass density, root volume density, and root depth, were measured in two growth stages. A jet index apparatus was applied to measure two erodibility properties (i.e., coefficient of erodibility and critical shear stress) of these vegetated soils in the two test stages. Cynodon Dactylon and Zoysia Matrella have higher root mass density values than Paspalum Notatum does, and reduce the susceptibility of soil erosion more effectively. Therefore, the two grass species are suggested for soil bioengineering in Hong Kong.

Random finite element method (RFEM) provides a rigorous tool to incorporate spatial variability of soil properties into reliability analysis and risk assessment of slope stability. However, it suffers from a common criticism of requiring extensive computational efforts and a lack of efficiency, particularly at small probability levels (e.g., slope failure probability P f

The seepage, deformation and stability in unsaturated soil slopes under rainfall infiltration are important issues in geotechnical engineering. Based on multi-field coupling theory, a finite element code, COMSOL, is employed to solve the coupled partial differential equations for soil slopes under rainfall infiltration. The coefficient of permeability is a variable in the three-phase coupled model. The water seepage, air migration, deformation and stability in a soil slope due to precipitation are studied. The effect of the wetting front caused by the migration of pore-air and the deformation of soil are explored, and the impact of soil anisotropy is analysed. The results indicate that the effect of anisotropy on the pore-water pressure is related to the depth and position of the unsaturated soil slope. The factor of safety of the partially saturated slope is relatively high when the lateral coefficient of permeability of the slope is greater than the coefficient of permeability in the vertical direction. The factor of safety is a function of the degree of anisotropy.

Disturbance of immunity is an important factor to modulate inflammatory responses after severe shock. Post-shock mesenteric lymph (PSML) return plays an adverse role in multiple organ injuries induced by the hemorrhagic shock, and the inflammatory factors are involved in this process. However, whether the PSML can exacerbate immune dysfunctions that modulate inflammatory response to the hemorrhagic shock remains unknown. In the present study, the effects of PSML drainage on the distribution of T lymphocyte subgroup, the release of inflammatory factors, and apoptosis of thymocytes were investigated; the effect of PSML on the specific parameters of cellular immune function was also determined. Results showed that PSML drainage reduced the increased levels of CD3+, CD3 + CD4+, CD4 + CD25+ lymphocytes, IFN-γ, and the ratios of CD3 + CD4+/CD3 + CD4− in blood of the shocked rats at 3 h after resuscitation; PSML drainage also abolished the decreased IL-4 level and restored the higher ratio of IFN-γ/IL-4 to normal levels. Tissue injury, including enlarged intermembrance space and edema with congestion in the medulla, increased apoptotic cells and bax expression, decreased number of cells in the S phase, and bcl-2 expression were observed in the thymus after hemorrhagic shock. PSML drainage reversed these effects. In particular, PSML drainage increased the proliferation index and decreased p53 expression of thymocytes. These results suggest that hyperimmunity occurred at early stages of hemorrhagic shock with resuscitation and that PSML drainage could markedly improve cellular immune function that is responsible for the reduced inflammatory responses.

Throughout the history, many lives have been lost due to landslides. Understanding the process of human flight during landslide events is important in assessing the risks posed by future landslides. This study proposes a model for simulating human flight from a quick shallow landslide along a road, quantifies the flight success rate, and identifies the crucial variables that impact flight efficiency. A questionnaire survey was undertaken along a stretch of highway near Yingxiu, China to collect information regarding human responses and behavior in the face of landslide events. The factors influencing human flight are classified into factors related to the evacuees, the landslide intensity, and the flight path. Subsequently, a flight model is proposed to simulate the movements of people randomly located along a road threatened by landslides. Various components of “available time” and “demand time” for escaping from the landslide affected area are treated as random variables. Based on this model, probability analysis is conducted to estimate the flight success rates of the people at risk when fleeing from landslides of various intensities. Sensitivity analysis shows that the pre-failure time and the response time are the most important factors in the flight process. Finally, comparison between the flight success rates from two existing methods and those from the new model is made.

The temperature and pH stability of proteases have been extensively investigated. A neutral protease produced by Aspergillus oryzae was thermodynamically characterized at high-salt environment. When the protease was tested at 24% NaCl and 60 o C, its half-life was increased to 30.0 min, 111% longer than that of control. Its Gibbs free energy and activation energy for denaturation in high NaCl concentration solutions were higher than in low salt solutions and increased by 2.1 and 4.75 kJ/mol, respectively. The protease exhibited higher thermal stability in higher salt conditions. This feature is beneficial to soybean sauce fermentation by enhancing the protease performance and taste of the product. Analysis by far- ultraviolet circular dichroism (far-UV CD) spectroscopy revealed that α-helix conformation in the protease increased from 3.2 to 31.7%, respectively, when the NaCl concentration increased from 0 to 18%, in agreement with the results deduced by thermodynamic calculations.

On 13 August 2010, a catastrophic debris flow with a volume of 1.17 million m3 occurred in Xiaojiagou Ravine near Yingxiu town of Wenchuan county in Sichuan Province, China. The main source material was the landslide deposits retained in the ravine during the 2008 Wenchuan earthquake. This paper describes a two-dimensional hybrid numerical method that simulates the entire process of the debris flow from initiation to transportation and finally to deposition. The study area is discretized into a grid of square zones. A two dimensional finite difference method is then applied to simulate the rainfall-runoff and debris flow runout processes. The analysis is divided into three steps; namely, rainfall-runoff simulation, mixing water and solid materials, and debris flow runout simulation. The rainfall-runoff simulation is firstly conducted to obtain the cumulative runoff near the location of main source material and at the outlet of the first branch. The water and solid materials are then mixed to create an inflow hydrograph for the debris flow runout simulation. The occurrence time and volume of the debris flow can be estimated in this step. Finally the runout process of the debris flow is simulated. When the yield stress is high, it controls the deposition zone. When the yield stress is medium or low, both yield stress and viscosity influence the deposition zone. The flow velocity is largely influenced by the viscosity. The estimated yield stress by the equation, τ y = ρghsin θ, and the estimated viscosity by the equation established by Bisantino et al. (2010) provide good estimates of the area of the debris flow fan and the distribution of deposition depth.

A large number of debris flows occurred in the Wenchuan earthquake zone after the 12 May 2008 earthquake. The risks posed by these debris flows were rather high. An appropriate model is required to predict the possible runout distance and impacted area. This paper describes a study on the runout characteristics of the debris flows that occurred in the Wenchuan earthquake zone over the past four years. A total of 120 debris flows are analyzed. Separate multivariate regression models are established for the runout distances of hil l-slope debris flows and channelized debris flows. The control variables include type of debris flow, debris flow volume, and elevation difference . Comparison of the debris flows occurring before and after the earthquake shows that the runout distance increased after the earthquake due to sufficient material supply and increased mobility of the source materials. In addition, the runout distances of annual debris flow events in 2008, 2010 and 2011 are analyzed and compared. There is a tendency that the runout distance decreases over time due to the decreasing source material volume and possible changes of debris flow type. Comparison between the debris flows in the earthquake zone and the debris flows in Swiss Alps, Canada, Austria, and Japan shows that the former have a smaller mobility.

Unsaturated layered soils are common in nature and engineering practices, including highway embankments and waste landfills. Based on the principle of effective stresses and considering the deformation in unsaturated porous medium and changes in permeability with the stress state during rainfall, a one-dimensional model for simulating coupled seepage and deformation in layered unsaturated porous medium is established. A finite element program was written in FlexPDE to analyze the hydro-mechanical coupled process of rainfall infiltration into a two-layer unsaturated porous medium. The factor of safety as a function of the wetting front depth is discussed based on a simple infinite slope analysis. The numerical results demonstrate that the coupling of seepage and deformation plays a significant role in the movement of wetting front, the distribution of pore-water pressure, and the slope stability. The coupling of seepage and deformation should be taken into account when analyzing the rainfall infiltration into the layered unsaturated porous medium, especially for a combination of a short-duration heavy rain and high initial suctions.

Mechanical properties of methane hydrate-bearing-sediments (MHBS) are basic parameters for safety analysis of hydrate exploration and exploitation. Young’s modulus, cohesion, and internal friction angle of hydrate-bearing sediments synthesized in laboratory, are investigated using tri-axial tests. Stress-strain curves and strength parameters are obtained and discussed for different compositions and different hydrate saturation, followed by empirical expressions related to the cohesion, internal friction angle, and modulus of MHBS. Almost all tested MHBS samples exhibit plastic failure. With the increase of total saturation of ice and methane hydrate (MH), the specimens’ internal friction angle decreases while the cohesion increases.

The Tangjiashan landslide dam was formed during the Ms8.0 Wenchuan earthquake in 2008 and posed high risks to 1.2 million people downstream the dam. A human risk analysis model (HURAM) reported in the companion paper is applied to evaluate the human risk in the Tangjiashan landslide dam failure. The characteristics of this landslide dam are introduced first. The breaching parameters in two cases (i.e., the actual case and a high erodibility case) are predicted with a physically based model, and the flood routing processes in these two cases are simulated using numerical analysis. The population at risk downstream of the landslide dam is then obtained based on the results of the flood routing simulations. Subsequently, the human risks are analyzed with HURAM using Bayesian networks. Fourteen influence parameters and their interrelationships are considered in a systematic structure in the case study. A change in anyone of them may affect the other parameters and leads to loss of life. HURAM allows not only cause-to-result inference, but also result-to-cause inference by updating the Bayesian network with specific information from the study case. The uncertainties of the parameters and their relationships are studied both at the global level using multiple sources of information and at the local level by updating the prior probabilities.

A soil deposit subjected to seismic loading can be viewed as a binary system: it will either liquefy or not liquefy. Generalized linear models are versatile tools for predicting the response of a binary system and hence potentially applicable to liquefaction prediction. In this study, the applicability of four generalized linear models (i.e., logistic, probit, log–log, and c-log–log) for liquefaction potential evaluation is assessed and compared. Eight liquefaction models based on the four generalized linear models and two sets of explanatory variables are evaluated. These models are first calibrated with past liquefaction performance data. A weighted-likelihood function method is used to consider the sampling bias in the calibration database. The predicted liquefaction probabilities from various models are then compared. When liquefaction probability is small, the predicted liquefaction probability is sensitive to the regression models used. The effect of sampling bias is more marked in the high cyclic stress ratio region. The eight models are finally ranked using a Bayesian model comparison method. For the generalized linear models examined, the logistic and c-log–log regression models are most supported by the past performance data. On the other hand, the probit and c-log–log regression models are much less applicable to liquefaction prediction.

Dam breaks have catastrophic consequences for human lives. This paper presents a new human risk analysis model (HURAM) using Bayesian networks for estimating human risks due to dam-break floods. A Bayesian network is constructed according to a logic structure of loss-of-life mechanisms. The nodes (parameters) and the arcs (inter-relationships) of the network are quantified with historical data, existing models and physical analyses. A dataset of 343 dam-failure cases with records of fatality is compiled for this purpose. Comparison between two existing models and the new model is made to test the new model. Finally, sensitivity analysis is conducted to identify the important parameters that lead to loss of life. The new model is able to take into account a large number of important parameters and their inter-relationships in a systematic structure; include the uncertainties of these parameters and their inter-relationships; incorporate information derived from physical analysis, empirical models and historical data; and update the predictions when information in specific cases is available. The application of this model to the study of human risks in a specific dam-break case is presented in a companion paper.

Knowledge about model error or model uncertainty is essential for liquefaction analysis. Model uncertainty characterization is generally not easy due to the presence of a large number of uncertain model input parameters. The Bayesian network is a versatile tool for analyzing problems involving a large number of uncertain variables. In this paper, a Bayesian network is developed to determine the model uncertainty of liquefaction evaluation models considering the parameter uncertainties. An approximate variable elimination algorithm is suggested to reduce the computational work in model uncertainty characterization. A weighted likelihood function is used to consider the sampling bias in the calibration database. The model uncertainty of a liquefaction model is studied to illustrate the proposed method. It is found that the model is on average biased towards the conservative side. Ignoring the model uncertainty is a convenient assumption, but it may result in either overestimation or underestimation of the reliability index.

Salt-tolerant aromatic yeast is an important microorganism arising from the solid state fermentation of soy sauce. The fermentation kinetics of volatile esters by Candida etchellsii was studied in a batch system. The data obtained from the fermentation were used for determining the kinetic parameters of the model. Batch experimental results at four NaCl levels (180, 200, 220, and 240 g/L) were used to formulate the parameter estimation model. The kinetic parameters of the model were optimized by specifically designed Runge-Kutta Genetic Algorithms (GA). The resulting mathematical model for volatile ester production, cell growth and glucose consumption simulates the experimental data well. The resulting new model was capable of explaining the behavior of volatile ester fermentation. The optimized parameters (µo, Xmax, Ki, α, β, YX/S, m, and YP/S) were characterized by a correlation of functions assuming salinity dependence. The kinetic models optimized by GA describe the batch fermentation process adequately, as demonstrated by our experimental results.

The 2008 Wenchuan earthquake induced a large number of landslides, and a vast amount of loose landslide materials deposited on steep hill slopes or in channels. Such loose materials can become sources of deadly debris flows once triggered by storms. On 13 August 2010, a storm swept Yingxiu and its vicinity, triggering a catastrophic debris flow with a volume of 1.17 million m3 in Xiaojiagou Ravine. The debris flow buried 1,100 m of road, blocked a river and formed a debris flow barrier lake. A detailed field study was conducted to understand the initiation mechanisms and runout characteristics of this debris flow. Two types of debris flows are identified, namely hill-slope debris flow and channelized debris flow. The hill-slope debris flow was triggered in the forms of firehose effect, rilling and landsliding, whereas the channelized debris flow was triggered in the form of channel-bed failure. This debris flow was a water–rock flow since most particles were gravel, cobble or larger rocks and the fraction of silt and clay was less than 2%. Grain contact friction, pore-pressure effects and inertial grain collision were the three most important physical interactions within the debris flow. Such interactions yielded a smaller runout distance (593 m) compared with those of mud–rock flows of similar size.

A bridge pier supported on two drilled shafts collapsed due to the impact by a 130-ton rock in a landslide event. A series of static and dynamic numerical simulations is conducted using a nonlinear finite element analysis program to investigate the bearing behavior and responses of the bridge foundation under rock impact. The rock impact load is evaluated according to the site conditions. The deflection histories at the striking point and the internal forces in the drilled shafts during rock impacts in different directions are analyzed. The bridge pier exhibits significant system effects: the failure of the bridge pier is initiated by the failure of one pier column or one drilled shaft first, followed by the failure of the entire pier. The effects of impact loading direction, striking location, and characteristics of impact load on the behavior of the bridge pier are examined through a parametric study. The capacities of the pier along different loading directions are different due to differences in the group effects of the drilled shafts. The bridge pier is strongest when the impact load is along the 45° direction with respect to the shaft row, and weakest when the impact load is perpendicular to the shaft row.

Objective To observe the effect of electroacupuncture on serum cortisol (CORT) and adrenocorticotropic hormone (ACTH) of rats with chronic stress-induced depression, and to investigate the mechanism of acupuncture in treating depression.