Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) has spread rapidly throughout the world. SARS-CoV-2 is an enveloped, plus-stranded RNA virus with a single-stranded RNA genome of ...approximately 30,000 nucleotides. The SARS-CoV-2 genome encodes 29 proteins, including 16 nonstructural, 4 structural and 9 accessory proteins. To date, over 1,228 experimental structures of SARS-CoV-2 proteins have been deposited in the Protein Data Bank (PDB), including 16 protein structures, two functional domain structures of nucleocapsid (N) protein, and scores of complexes. Overall, they exhibit high similarity to SARS-CoV proteins. Here, we summarize the progress of structural and functional research on SARS-CoV-2 proteins. These studies provide structural and functional insights into proteins of SARS-CoV-2, and further elucidate the daedal relationship between different components at the atomic level in the viral life cycle, including attachment to the host cell, viral genome replication and transcription, genome packaging and assembly, and virus release. It is important to understand the structural and functional properties of SARS-CoV-2 proteins as it will facilitate the development of anti-CoV drugs and vaccines to prevent and control the current SARS-CoV-2 pandemic.
Floods caused by breaches of embankment and landslide dams are not only a tremendous geological disaster, destroying people's lives and property, they also strongly shape the appearance of the ...landscape in the inundation area. This review addresses embankment and landslide dam breaches, with a particular focus on documented failure cases, laboratory and field experiments, as well as empirically and physically based models. The state of the art of physical and mathematical modeling technologies of underlying breach mechanisms and processes are also reviewed. First, the distribution, breach parameters, and failure modes of documented failure cases are analyzed. Second, based on physical model tests at different scales around the world, the breach processes of embankment and landslide dams caused by overtopping or piping/seepage are studied in depth. The breach characteristics for each type of dam are summarized. Third, typical empirically or physically based mathematical models are reviewed with a focus on artificially formed dams (i.e., earthfill, clay core rockfill, and concrete face rockfill dams) or naturally formed dams (i.e., landslide dams). Both uncertainties and limitations associated with formulations and calculating parameters of these mathematical models are also discussed. Finally, recommendations toward a better understanding of breach mechanisms and further development of mathematical models are proposed.
The accurate and rapid prediction of landslide dam stability is of great significance for emergency response planning. However, current rapid prediction methods for the landslide dam cannot ...quantitatively consider the influence of landslide debris grain size distribution. A database was established based on 1434 documented historical landslide dams, including formed-unstable and formed-stable cases from around the world. The logistic regression method was utilized to develop new methods for the rapid prediction of landslide dam stability, which can consider the morphological characteristics and particle composition of the landslide dams as well as the hydrodynamic conditions of the upstream dammed lake. According to the available information on landslide debris particle composition, the newly proposed rapid prediction methods were classified as either detailed or simplified based on 27 and 150 cases, respectively. Based on the database, several typical methods for the rapid prediction of landslide dam stability were chosen to compare with the newly proposed methods. The performances of each method testify to the rationality of the new methods.
On October 10 and November 3, 2018, two successive landslides occurred at Baige village, the border between Sichuan Province and Tibet Autonomous Region, in China, which totally dammed the Jinsha ...River on both occasions. Due to the rapid rise in water level in the “10·10” dammed lake, on October 12, the landslide dam breached naturally with the peak breach flow of about 10,000 m
3
/s. The residual landslide dam was stacked by the subsequent landslide on November 3, resulting in an even larger dammed lake. Fortunately, the height from the water level in the lake to the dam crest made it possible to construct a spillway to drain the water in the dammed lake to a relatively low level. On November 12, the drainage process began with the peak breach flow of 31,000 m
3
/s. In this study, based on the detailed records of the breach process of the “11·03” Baige landslide dam and using the developed physically based numerical method, a back analysis was conducted. The numerical method was developed based on the overtopping-induced breach mechanism of landslide dams. An iterative time step algorithm was used to simulate the breach evolution and the hydrograph coupling. The major highlights of the numerical method are the consideration of the breach mechanism of landslide dam, such as the breach morphology evolution process along the streamwise and transverse directions, as well as the variation of soil erodibility with depth and the influence of the presence and absence of a spillway. Comparison of the measured and the calculated results indicated that the numerical method developed in this study can reproduce reasonable breach hydrograph and breach evolution process. The sensitivity analysis showed that the soil erodibility coefficient and the residual dam height significantly influenced the landslide dam breaching process. In addition, it was determined that constructing a spillway before landslide dam breaching is an effective flood hazard mitigation measure for large dammed lakes. However, the availability of the construction conditions and the shape of the spillway should be judged comprehensively according to the rising rate of water level and construction capacity.
Timely prediction of a landslide dam breach is particularly important for assessments of expected disaster consequences and to plan emergency responses. However, due to the complex composition and ...specific geotechnical properties of the landslide dam material, such a prediction is challenging. In this study, geological survey results and landslide dam breach mechanisms were used to develop a numerical model for overtopping-induced landslide dam breaches, considering variation of soil erodibility with depth. The model included a hydrodynamic process module, a soil erosion module, and a breach evolution module. Moreover, a time step iteration algorithm was adopted to simulate the soil and water coupling process during dam breach. A comparison of calculated and measured breach hydrographs, variations of dammed lake water level, breach sizes, as well as two other typical models were used to validate the rationality of the numerical model, by considering the Baige landslide breach case of November 3, 2018 with detailed measured data. Parameter sensitivity analysis showed that the soil erodibility coefficient exerted an important influence on the breach process, while soil critical shear stress had a relatively small influence (which remained within ±15% for output parameters when it was multiplied by 0.5, 1.0, and 2.0). Furthermore, spillway excavation was found to significantly reduce the peak breach flow if the dammed lake has a large storage capacity, thus identifying it as an effective measure for disaster mitigation.
•Mechanisms of landslide dam breach due to overtopping failure are summarized.•A numerical model was proposed for predicting landslide dam breach.•The proposed model considered variations of soil erodibility with depth.•The proposed model reflected the evolution of downstream slope angle.•Back analysis was performed for Baige landslide dam breach on Jinsha River, China.
The performance of different filtering algorithms combined with 3D-mapping-aided (3DMA) techniques is investigated in this paper. Several single- and multi-epoch filtering algorithms were implemented ...and then tested on static pedestrian navigation data collected in the City of London using a u-blox EVK M8T GNSS receiver and vehicle navigation data collected in Canary Wharf, London, by a trial van with a Racelogic Labsat 3 GNSS front-end. The results show that filtering has a greater impact on mobile positioning than static positioning, while 3DMA GNSS brings more significant improvements to positioning accuracy in denser environments than in more open areas. Thus, multi-epoch 3DMA GNSS filtering should bring the maximum benefit to mobile positioning in dense environments. In vehicle tests at Canary Wharf, 3DMA GNSS filtering reduced the RMS horizontal position error by approximately 68% and 57% compared to the single-epoch 3DMA GNSS and filtered conventional GNSS, respectively.
Membranous glomerulonephritis (MGN) is a leading cause of nephrotic syndrome in adults. Diosgenin (DG) has been reported to exert antioxidative and anti-inflammatory effects.
To investigate the ...renoprotective activity of DG in a cationic bovine serum albumin-induced rat model of MGN.
Fourty male Sprague-Dawley rats were randomized into four groups. The MGN model was established and treated with a DG dose (10 mg/kg) and a positive control (TPCA1, 10 mg/kg), while normal control and MGN groups received distilled water by gavage for four consecutive weeks. At the end of the experiment, 24 h urinary protein, biochemical indices, oxidation and antioxidant levels, inflammatory parameters, histopathological examination, immunohistochemistry and immunoblotting were evaluated.
DG significantly ameliorated kidney dysfunction by decreasing urinary protein (0.56-fold), serum creatinine (SCr) (0.78-fold), BUN (0.71-fold), TC (0.66-fold) and TG (0.73-fold) levels, and increasing ALB (1.44-fold). DG also reduced MDA (0.82-fold) and NO (0.83-fold) levels while increasing the activity of SOD (1.56-fold), CAT (1.25-fold), glutathione peroxidase (GPx) (1.55-fold) and GSH (1.81-fold). Furthermore, DG reduced Keap1 (0.76-fold) expression, Nrf2 nuclear translocation (0.79-fold), and induced NQO1 (1.25-fold) and HO-1 (1.46-fold) expression. Additionally, DG decreased IL-2 (0.55-fold), TNF-α (0.80-fold) and IL-6 (0.75-fold) levels, and reduced protein expression of NF-κB p65 (0.80-fold), IKKβ (0.93-fold), p-IKKβ (0.89-fold), ICAM-1 (0.88-fold), VCAM-1 (0.91-fold), MCP-1 (0.88-fold) and E-selectin (0.87-fold), and also inhibited the nuclear translocation of NF-κB p65 (0.64-fold).
The results suggest a potential therapeutic benefit of DG against MGN due to the inhibition of the NF-κB pathway, supporting the need for further clinical trials.
An elastoplastic constitutive model that takes into account the stress–strain relationship and creep-induced hardening behavior of rockfill materials is proposed in light of previous experimental ...observations. It is assumed that the mechanical response during loading and the final amounts of creep strains under a constant stress state are independent of the strain rate. The focus of the proposed model is the coupling effect between loading and creep, including the influence of loading history on subsequent creep strains and the influence of creep history on subsequent loading behavior. An extended yield function, which allows flexible control over the shape of yield surfaces, is used not only to distinguish among loading, unloading, and neutral loading, but also to manipulate the creep-induced hardening using a plastic strains–based hardening parameter. A stress-dependent dilatancy equation is used, instead of a plastic potential function, to define the directions of plastic strains during loading. The hardening law is established based on three different types of experimental results. Only routine experiments are required for calibration of model parameters, and the model can be used in a reduced form according to the available test results. The model is verified using typical experimental data and is found to be capable of capturing important behavior of rockfill materials, such as pressure-dependent strength, shear contraction and dilation, and creep-induced stiffening.
Automatic welding penetration recognition is a significant and challenging research direction to improve the manufacturing quality and intelligence level of gas tungsten arc welding (GTAW). In this ...paper, a data-driven deep learning approach based on vision transformer (ViT) is proposed to implement welding penetration recognition. To meet the requirement of the model training on data, a large weld pool image dataset composed of four penetration categories is constructed. Twelve ViT models with different architectures are constructed and trained from scratch to explore their feasibility for penetration recognition. Then, pretrained on ImageNet, a state-of-art ViT-B/16 model, is employed, which alleviates the issue of modeling complexity and data insufficiency and improves the validation accuracy by 4.45%. The transfer learning results demonstrate a 98.11% as the test accuracy for the ViT model. Compared with the other conventional recognition methods, the proposed model has fewer misclassifications and superior generalization performance due to self-attention. Furthermore, the attention rollout method is applied to visualize the image region of interest (ROI), confirming the reliability and effectiveness of the developed approach. This study expands the application scope of the ViT to penetration recognition and achieves remarkable effects, laying a reliable foundation for automated welding quality optimization in GTAW.
The existing empirical models do not consider the influence of material composition of landslide deposits on the peak breach flow due to the uncertainty in the material composition and the randomness ...of its distribution. In this study, based on the statistical analyses and case comparison, the factors influencing the peak breach flow were comprehensively investigated. The highlight is the material composition-based classification of landslide deposits of 86 landslide cases with detailed grain-size distribution information. In order to consider the geometric morphology of landslide dams and the potential energy of dammed lakes, as well as the material composition of landslide deposits in an empirical model, a multiple regression method was applied on a database, which comprises of 44 documented landslide dam breach cases. A new empirical model for predicting the peak breach flow of landslide dams was developed. Furthermore, for the same 44 documented landslide dam failures, the predicted peak breach flow obtained by using the existing empirical models for embankment and landslide dams and that obtained by using the newly developed model were compared. The comparison of the root mean square error (
E
rms
) and the multiple coefficient of determination (
R
2
) for each empirical model verifies the accuracy and rationality of the new empirical model. Furthermore, for fair validation, several landslide dam breach cases that occurred in recent years in China and have reliable measured data were also used in another comparison. The results show that the new empirical model can reasonably predict the peak breach flow, and exhibits the best performance among all the existing empirical models for embankment and landslide dam breaching.
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