An in-situ method for assessing soil aggregate stability in burned landscapes

Due to soil repellency in burned areas, slope runoff and soil erodibility escalates following forest fires, increasing the vulnerability to post-fire debris flows. Soil aggregate stability is a critical determinant of soil infiltration capacity and erosion susceptibility. The prevalent method of assessing soil aggregate stability in burned areas, the counting the number of water drop impacts (CND) method, is time-intensive and impractical for in-situ measurements. In response, this study introduces a novel technique based on the shock and vibration damage (SVD) effect for evaluating soil aggregate stability in burned areas. Thirteen distinct soil aggregate types were meticulously prepared for indoor simulated fire testing, with due consideration to factors such as bulk weight, organic matter content, and water repellency, which influence stability of soil aggregates. Employing a custom-built test apparatus, the mass loss rate (MLR) of soil aggregates was determined through orthogonal experiments using the SVD method and compared against the standard CND technique's quantification of water droplet-induced aggregate destruction. The findings demonstrated that SVD method, employing Test Scheme 6 (testing 20 aggregates, 1-meter impact height, 40% water content, and five impacts), exhibits excellent agreement (Kendall coefficient = 0.797) and correlation (R2 = 0.634) with CND method outcomes. This testing scheme, characterized by rapid determination and effective discrimination, is identified as the optimal testing approach. The SVD testing apparatus is straightforward, portable, and easily disassembled, rendering it suitable for on-site use. It can be used to distinguish the stability level of soil aggregates swiftly and quantitatively under various fire intensities in burned areas in situ, which is an important guiding significance for the study of soil erosion, erosion control, and post-fire debris flow initiation mechanism in burned areas

Surface charging phenomena on HVDC spacers for compressed SF6 insulation and charge tailoring strategies

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MPM-based mechanism and runout analysis of a compound reactivated landslide

Understanding the entire process of hydraulic-related landslide reactivations is crucial for risk assessment, which includes initiation and runout evolves from a small-deformation in the pre-failure stage to large-deformation after failure, with complex interactions between the materials in solid and liquid phases. This paper reproduces the entire process of a reactivated landslide using Material Point Method (MPM). The accuracy of MPM is validated in comparison to Limit Equilibrium Method (LEM) and Finite Element Method (FEM). The effects of antecedent rainfall and pre-existing groundwater on landslide runout and the deposits morphology are discussed. Results show that the antecedent rainwater rises the groundwater level and saturates the front edge of slope where the initial failure occurred. Three computed spatio-temporal distributions of pore water pressure show good agreement and match well with field evidence. The kinematic characteristics show that the landslide has different moving features with different microtopography, which reveals retrogressive failure in front and middle part of slope initially and compound retro- and pro-gressive failures occur at the rear edge. The results of unsaturated two-phase MPM are in better agreement with the measured morphology than full-saturated MPM. The antecedent rainfall and the pre-existing groundwater are the main contributing factors to the landslide runout

Kerker Effects and Bound States in the Continuum in PT-Symmetric Dielectric Metasurfaces

We investigate the light transmission and reflection spectra of parity-time (PT) symmetric dielectric metasurfaces composed of high refractive index nanostructures with in-plane gain-loss modulation through the scattering matrix and semianalytical Cartesian multipoles methods. We find that the Kerker effects, i.e., the strong forward-to-backward asymmetric scattering originating from overlapping the electric and magnetic multipolar resonances, can be tailored by the gain and loss. In addition, we observe another kind of high-Q resonances, i.e., quasi-bound states in the continuum which couple to the electric and magnetic multipolar radiations, in the transmission and reflection spectra with different incident polarizations lights by manipulating the gain and loss in the metasurfaces. Our results suggest the ways to achieve Kerker effects and engineer the resonances in non-Hermitian metasurfaces for many practical applications in nanophotonics

Variation in the Pore Structure of Coal after Hydraulic Slotting and Gas Drainage

The integration of hydraulic slotting and gas drainage techniques has become a mainstream technique for enhancing permeability in coal seams with low permeability. However, the mechanism of action of this process is unclear. In this paper, field experiment and laboratory tests are described that aim at elucidating this process. Given the sensitivity and accuracy of test methods and their corresponding determination principles, a combination of mercury intrusion porosimetry and nitrogen gas adsorption was proposed as a complementary technique and the pore-size distribution (PSD) was obtained. It is shown that the proportion of minipores decreases remarkably, whereas that of the macropores gradually increases with the decrease in the distance from the slotted borehole. By contrast, the mesopores and micropores present insignificant changes. Meanwhile, the adsorption pore and the seepage pore show a similar variation in tendency with the minipores and macropores, respectively. Moreover, the specific surface area decreases substantially with the decrease in borehole distances. The integration of hydraulic slotting and gas drainage can lower the gas-adsorption properties and enhance the gas-seepage capacity within the disturbed zone significantly. The paper highlights the guiding factors for improving the enhanced coal bed methane recovery

NU7441 Enhances the Radiosensitivity of Liver Cancer Cells

Objective: Radiation therapy, one of the major treatments for liver cancer, causes DNA damage and cell death. Since the liver cancer cells have a strong capacity to repair irradiative injury, new medicines to enhance this treatment are urgently required. In this study, we investigated the effect of NU7441, a synthetic small-molecule compound, as a specific inhibitor of DNA-dependent protein kinase (DNA-PK) in radiosensitization of hepatocellular carcinoma HepG2 cells. Methods: Cell Counting Kit-8 (CCK-8) was first used to evaluate the proliferation of HepG2 cells under NU7441 treatment. SDS-PAGE and Western blot were then performed to study the protein expression leading to the DNA damage repair. Further, neutral single cell gel electrophoresis and immunofluorescence assay were carried out to assess DNA repair. Finally, flow cytometry was implemented to examine the changes in cell cycle. Results: NU7441 reduced the CCK-8 counts in the HepG2 culture, further enhanced 60Coγ radiation injury to HepG2 cells, which was manifested by decreasing the DNA-PKcs (S2056) protein expression, increasing γH2AX foci number, prolonging the tail moment of the comet cells, and inducing cell cycle arrest at G2/M phase. Conclusion: NU7441 inhibited the growth of liver cancer cells, enhanced the radiosensitization of these cancer cells by interfering with the DNA repair and cell cycle checkpoint. These data implicate NU7441 as a potential radiotherapy sensitizer for the treatment of liver cancer

Enhancing grain drying methods with hyperspectral imaging technology: A visualanalysis

This study proposes a recognition model for different drying methods of grain using hyperspectral imaging technology (HSI) and multivariate analysis. Fresh harvested grain samples were dried using three different methods: rotating ventilation drying, mechanical drying, and natural drying. Hyperspectral images of the samples were collected within the 388–1065 nm band range. The spectral features of the samples were extracted using principal component analysis (PCA), while the texture features were extracted using second-order probability statistical filtering. Partial least squares regression (PLSR) drying models with different characteristics were established. At the same time, a BPNN (Back-propagation neural network, BPNN) based on spectral texture fusion features was established to compare the recognition effects of different models. Texture analysis indicated that the mean-image had the clearest contour, and the texture characteristics of mechanical drying were smaller than those of rotating ventilation drying and natural drying. The BPNN model established using spectral-texture feature variables showed the best performance in distinguishing grain in different drying modes, with a prediction model obtained based on the correlation coefficients of special variables. The spectral and texture feature values were fused for pseudo-color visualization expression, and the three drying methods of grain showed different colors. This study provides a reference for non-destructive and rapid detection of grain with different drying methods