A simplified order-reduced sub-region model and the analysis method are proposed to analyze structural damage caused by local failure under sudden disasters. The method firstly divides a complex ...building into sub-regions. Secondly it evaluates the failure degree of sub-regions according to the state of internal components, then analyzes the failure process from macro regional perspective. Finally it summarizes the law of collapse evolution so as to provide guidance for emergency management.
Catastrophic landslides occur frequently at large waste dumps, causing huge losses of lives and environmental degradation. In this study, Zhujiabaobao iron mine waste dump was surveyed and found to ...be unstable during a field investigation in April 2016. A failure potential assessment was undertaken for the waste dump; this is crucial for the prediction and mitigation of landslides hazards. Reconnaissance, geomorphological analysis, and laboratory experiments were carried out to provide basic data, and a three-dimensional waste dump model was constructed. To consider ground cracks in the waste dump and acquire information about potential sliding mass, an extended finite element model (XFEM) based on strength reduction technique was applied. An analysis shows that the factor of safety (FOS) of waste dump is 1.22, not very stable according to “The technical code for building slope engineering (GB50330-2013)” published by Chinese ministry of Housing and Urban-Rural Development, and the potential failure volume is 45 × 104 m3. Then, the potential landslide and debris flow due to slope failure were simulated using the software SFLOW based on a free-surface shallow water model (SWM). The landslide simulation considers different water contents of sliding mass, reflected in parameter Cv (sediment concentration by volume), whereas debris flow simulation was designed for 20, 50, 100, and 200-year return periods. The results show that with the decrease in Cv, the speed of sliding mass increases, and the run-out distance of landslide increases. However, even the farthest influence distance does not reach downstream buildings. The debris flow can pile up in front of gully mouth and even run into the Jinsha River. Therefore, once a landslide has occurred or when a lot of loose material is present, corresponding management measures (such as cleaning the material or setting the retaining wall) and a forewarning system should be developed to prevent huge damage caused by debris flow.
•A method combining FEM and SWM for assessing waste dump failure potential.•The cracks have been considered in the model of stability analysis via XFEM.•The numerical model can fully consider real topographical conditions.
Abstract
Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, ...few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations. Totally, we identified 1017 nonsynonymous and 512 synonymous mutations with alignment to reference genome NC_045512, none of which were observed in the receptor-binding domain (RBD) of the spike protein. On average, each of the strains could have about 1.75 new mutations each month. The current mutations may have few impacts on antibodies. Although it shows the purifying selection in whole-genome, ORF3a, ORF8 and ORF10 were under positive selection. Only 36 mutations occurred in 1% and more virus strains were further analyzed to reveal linkage disequilibrium (LD) variants and dominant mutations. As a result, we observed five dominant mutations involving three nonsynonymous mutations C28144T, C14408T and A23403G and two synonymous mutations T8782C, and C3037T. These five mutations occurred in almost all strains in April 2020. Besides, we also observed two potential dominant nonsynonymous mutations C1059T and G25563T, which occurred in most of the strains in April 2020. Further functional analysis shows that these mutations decreased protein stability largely, which could lead to a significant reduction of virus virulence. In addition, the A23403G mutation increases the spike-ACE2 interaction and finally leads to the enhancement of its infectivity. All of these proved that the evolution of SARS-CoV-2 is toward the enhancement of infectivity and reduction of virulence.
The objective of this study was to identify the areas that are most susceptible to landslide occurrence, and to find the key factors associated with landslides along Jinsha River and its tributaries ...close to Derong and Deqin County. Thirteen influencing factors, including (a) lithology, (b) slope angle, (c) slope aspect, (d) TWI, (e) curvature, (f) SPI, (g) STI, (h) topographic relief, (i) rainfall, (j) vegetation, (k) NDVI, (l) distance-to-river, (m) and distance-to-fault, were selected as the landslide conditioning factors in landslide susceptibility mapping. These factors were mainly obtained from the field survey, digital elevation model (DEM), and Landsat 4–5 imagery using ArcGIS software. A total of 40 landslides were identified in the study area from field survey and aerial photos’ interpretation. First, the frequency ratio (FR) method was used to clarify the relationship between the landslide occurrence and the influencing factors. Then, the principal component analysis (PCA) was used to eliminate multiple collinearities between the 13 influencing factors and to reduce the dimension of the influencing factors. Subsequently, the factors that were reselected using the PCA were introduced into the logistic regression analysis to produce the landslide susceptibility map. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the logistic regression analysis model. The landslide susceptibility map was divided into the following five classes: very low, low, moderate, high, and very high. The results showed that the ratios of the areas of the five susceptibility classes were 23.14%, 22.49%, 18.00%, 19.08%, and 17.28%, respectively. And the prediction accuracy of the model was 83.4%. The results were also compared with the FR method (79.9%) and the AHP method (76.9%), which meant that the susceptibility model was reasonable. Finally, the key factors of the landslide occurrence were determined based on the above results. Consequently, this study could serve as an effective guide for further land use planning and for the implementation of development.
Although advances in single-cell technologies have enabled the characterization of multiple omics profiles in individual cells, extracting functional and mechanistic insights from such information ...remains a major challenge. Here, we present scapGNN, a graph neural network (GNN)-based framework that creatively transforms sparse single-cell profile data into the stable gene–cell association network for inferring single-cell pathway activity scores and identifying cell phenotype–associated gene modules from single-cell multi-omics data. Systematic benchmarking demonstrated that scapGNN was more accurate, robust, and scalable than state-of-the-art methods in various downstream single-cell analyses such as cell denoising, batch effect removal, cell clustering, cell trajectory inference, and pathway or gene module identification. scapGNN was developed as a systematic R package that can be flexibly extended and enhanced for existing analysis processes. It provides a new analytical platform for studying single cells at the pathway and network levels.
Type 2 Diabetes Mellitus (T2DM) is a chronic disease. The molecular diagnosis should be helpful for the treatment of T2DM patients. With the development of sequencing technology, a large number of ...differentially expressed genes were identified from expression data. However, the method of machine learning can only identify the local optimal solution as the signature.
The mutation information obtained by inheritance can better reflect the relationship between genes and diseases. Therefore, we need to integrate mutation information to more accurately identify the signature.
To this end, we integrated Genome-Wide Association Study (GWAS) data and expression data, combined with expression Quantitative Trait Loci (eQTL) technology to get T2DM predictive signature (T2DMSig-10). Firstly, we used GWAS data to obtain a list of T2DM susceptible loci. Then, we used eQTL technology to obtain risk Single Nucleotide Polymorphisms (SNPs), and combined with the pancreatic β-cells gene expression data to obtain 10 protein-coding genes. Next, we combined these genes with equal weights.
After Receiver Operating Characteristic (ROC), single-gene removal and increase method, gene ontology function enrichment and protein-protein interaction network were used to verify the results showed that T2DMSig-10 had an excellent predictive effect on T2DM (AUC=0.99), and was highly robust.
In short, we obtained the predictive signature of T2DM, and further verified it.
•A model for partly and fully saturated soils using water balance method is developed.•The field capacity is modified to represent the impact of the capillary rise.•The capillary fringe is stable to ...soil type and not sensitive to boundary conditions.•The model uses easily available parameters and is suitable for large-scale problems.
Accurate estimation of soil water content and water table depth is important for making irrigation measures and rational groundwater use in arid agricultural areas with shallow water table depth. Soil water balance models are widely used due to their high computational efficiency, while they are less applicable in areas with shallow water table depths because they usually ignore the matric potential. In addition, the effect of capillary rise on soil water state is also ignored. To address these problems, a flow model for partly and fully saturated soil, referred to as modified UBMOD, was developed in this study based on UBMOD and the water table depth fluctuation analysis. UBMOD is a soil water balance model that differs from other water balance models by considering soil water movement driven by matric potential. In the modified UBMOD, soil water flow and groundwater recharge rate are calculated using the original UBMOD algorithm, and water table depth is calculated using the water table depth fluctuation analysis. The field capacity used in the modified UBMOD was considered as a variable related to the water table depth to reflect the impact of capillary rise, which helps to obtain accurate water flux across the saturated–unsaturated interface. Two synthetic cases, simulated with HYDRUS, were used to test the sensitivities of the model parameters and specifications. Two real-world cases were used to show the fidelity of the model to the observed data. The results demonstrated that the model could solve the unsaturated–saturated problems based on more readily available parameters, without stringent requirements on spatial and time steps, with a full guarantee of water balance and low computational cost. This study provides an effective tool for hydrodynamic studies in areas with shallow water table depths.
Accurate estimation of seepage losses in large-scale canal systems and identification of their impact factors are important for improving water conveyance efficiency in agricultural districts. ...However, seepage losses can vary widely across different regions and periods, making it difficult to obtain a complete understanding of the variation process based solely on local scale studies. In addition, although there are currently some complex numerical models available for large-canal systems in agricultural districts, they are rarely used in practice due to their complexity. This study evaluated the regional-scale spatio-temporal seepage processes of the Zaohuo canal, a 55 km’s sub-main earthen canal located in the Hetao Irrigation District, China, under current and future water-saving conditions using MODFLOW-SWR. In addition, a pre-processing tool was developed to process spatial geographic data and spatial topology between different canals. Furthermore, the sensitivity of different influencing factors, such as the permeability of canal bed sediments, surface and groundwater level, and local lining, was also investigated. The optimal relationship between lining areas when partial lining is used and seepage losses was also investigated. The calculated water conveyance efficiency coefficient is 0.7871, which fits well with the reported results and proves the reliability of the simulation. In addition, it was found that seepage losses are most sensitive to the surface water level of the canal, followed by the permeability of canal bed sediments and then the groundwater level. Moreover, new hybrid lining can reduce the seepage losses by about 92.02%, but ongoing maintenance is vital. When lining the key portion of the canal, the seepage losses will be significantly reduced with the increase of lining area. The seepage losses reduction factor increases by 5.8% for every 1 × 105 m2 increase in lining area when the lining area is below 1 × 106 m2, while the effect is not significant when that limitation is exceeded. This study can support decision-making for water-saving projects in large water conveyance canals in regional-scale agriculture districts.
•The regional-scale spatio-temporal seepage losses in large canal have been evaluated.•Seepage losses were calculated based on surface-subsurface model MODFLOW-SWR.•Seepage losses are more sensitive to surface water levels than groundwater levels.•Lining can reduce seepage losses substantially, but ongoing maintenance is vital.•The optimal relationship between lining areas and seepage losses is investigated.
In recent years, the development of pumped-storage hydroelectricity has seen a very rapid increase, and lots of stations have been proposed to be built in China to adjust the energy structure of ...production and alleviate electrical energy shortages. The site of pumped-storage hydroelectric power plants is usually chosen in the mountain area, which can conveniently provide headwaters and height difference for the proper functioning of hydroelectric power station; however, geological disasters such as debris frequently flows in the mountain areas, posing great threat to the safety of plants and staff. A large pumped-storage hydroelectric power station will be built in the Taihang Mountains in the northwest of Yi County, Hebei province. To predict the potential scale of debris flow hazard, the shallow-water model based on the finite volume method (SFLOW model) is used. During the work, reconnaissance, geomorphological analysis, and laboratory experiment are carried out for model construction and data input. Then the debris flow designed for 20-, 50-, 100-, and 200-year return periods and the flood caused by dam break are simulated. The simulation study shows that the potential debris flow hazard will greatly harm the reservoir area, and if debris flows destroy the dam, floods could affect the residents of a maximum of 1.21 million square meters downstream. To prevent debris flows, retaining walls in the SFLOW model are set, and the results show that they can effectively reduce the hazard area of debris flow, ensuring the safety of the reservoir area. In general, the SFLOW model can accurately and efficiently solve the problem of fluid flow on irregular terrain and can be applied to similar engineering projects.
With the development of more/all electric aircraft, replacement of the traditional hydraulic servo actuator (HSA) with an electromechanical actuator (EMA) is becoming increasingly attractive in the ...aerospace field. This paper takes an EMA for a trimmable horizontal stabilizer as an example and focuses on how to establish a system model with an appropriate level of complexity to support the model-based system engineering (MBSE) approach. To distinguish the nonlinear effects that dominate the required system performance, an incremental approach is proposed to progressively introduce individual nonlinear effects into models with different complexity levels. Considering the special design and working principle of the mechanical power transmission function for this actuator, the nonlinear dynamics, including friction and backlash from the no-back mechanism, and the nonlinear compliance effect from the mechanical load path are mainly taken into consideration. The modelling principles for each effect are addressed in detail and the parameter identification method is utilized to model these nonlinear effects realistically. Finally, the responses from each model and experimental results are compared to analyze and verify how each individual nonlinearity affects the system’s performance.
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