Search

Due to the complex and non-linear characteristics of landslide evolution, the deformation law of landslides is always hard to be predicted. Considering the dynamical evolution process of landslide physical mechanism, a Physics-Informed Data Assimilation (PIDA) method is first proposed for landslide displacement forecasting. It can enhance the prediction ability of the physical forecasting model, and solves the problem of ignoring the physical significance of landslides in mathematical prediction model. Additionally, the superiority of Particle Filter (PF) in nonlinear and non-Gaussian system determines its application in complex problem. Aiming at the hydrodynamic pressure-driven landslide, the Sliding Zone Deterioration (SZD) model is constructed as the state equation of the PF algorithm. And the observation equation is formed by the relationship between landslide deformation and monitoring datasets. The physics-informed landslide displacement prediction model serves as a bridge, consisting of the shear strength parameter dynamic updated model and physical mechanism analysis model, for key parameters feedback, modification, and update. Comparing the results to traditional Long Short-Term Memory (LSTM) and Back Propagation Neural Network (BPNN) methods, the PIDA method combining triggering and instability mechanisms performs better in accuracy. Moreover, it enables dynamic and reliable landslide deformation prediction. [ABSTRACT FROM AUTHOR]

Abstract: Three reconstruction methods based on Tikhonov regularization are used to solve the ill-posed inverse problem when incorporating Monte Carlo calculations into the β-ray induced X-ray spectrometry (BIXS) for analyzing the tritium content and depth distribution in the material surface. These methods are implemented by the GENEREG, CONTIN and REGUTOOLS codes, respectively. The tritium sample is assumed to be a molybdenum slab of 5μm thickness, and an argon gas of 5mm thickness is filled in front of the molybdenum slab. The Monte Carlo code PENELOPE is used to simulate the X-ray energy spectra induced by tritium’s β-decays. The reconstruction results for tritium depth distributions by these three codes are compared and the comparison shows that the code GENEREG can give satisfactory results. Some discussions are made. [Copyright &y& Elsevier]

Abstract: An enzyme incubation–water extraction (EI–WE) method was developed and optimised for the extraction of the natural antioxidant taxifolin and of the total flavonoids from wood sawdust of Larix gmelini (Rupr.) Rupr. A factorial design and a central composite design approach were used for method optimisation. Optimal conditions were 0.5mg/ml cellulase and 0.5mg/ml pectinase, a pH of 5.0, a temperature of 32°C and 18h incubation time. The flavonoids and taxifolin were extracted in hot water at 50°C for 30min, with a solid to liquid ratio of 1:20. Under optimised conditions, the yields of taxifolin and total flavonoids increased from 1.06±0.08 to 1.35±0.04mg/g and 4.13±0.17 to 4.96±0.29mg/g, respectively. DPPH and BHT assays revealed that the EI–WE samples had 1.8- and 1.68-fold higher antioxidant activities than the controls. SEM results revealed the structural disruption of wood sawdust with enzyme incubation. [ABSTRACT FROM AUTHOR]

Abstract: Monte Carlo calculations, instead of the analytical method, are incorporated into the β-ray induced X-ray spectrometry for analyzing the tritium content and depth distribution in the near surface. This improvement makes the β-ray induced X-ray spectrometry for tritium analysis be able to take into account the physics processes more accurately and be utilized more flexibly. The inverse problem involved is treated by using the Tikhonov regularization method and classical molecular dynamics method. The results concerned are discussed. [Copyright &y& Elsevier]