Experience of Foreign Higher Education Service Trade and Its Enlightenment to China

With China’s entry into WTO, China’s trade in higher education services has developed rapidly. In addition to the highly developed economy, the broad market prospect has attracted more and more foreign students. However, China’s current trade in higher education services is still at the initial stage of development, showing an obvious trade deficit. From the perspective of international comparison, this study combs the development process of education service trade in major developed countries, summarizes the general rules and basic modes of its development, discusses various factors that affect the competitiveness of its national education service trade, thus analyzing the development characteristics and international competitiveness of education service trade in major developed countries, and summarizing the relevant experience and enlightenment of the development of education service trade in major developed countries. On this basis, the current situation of China’s higher education service trade is comprehensively combed, the main problems existing in China’s higher education service trade are analyzed, and reasonable ways to improve the competitiveness of China’s higher education service trade are put forward from aspects of perfecting the legislative content of higher education service trade, formulating development plans and policies, and strengthening the construction of education service institutions themselves

Research on the Training Mechanism of Top-Notch Innovative Talents Based on Interdisciplinary

The construction of interdisciplinary top-notch innovative talent training mechanism is conducive to the cultivation of high-level interdisciplinary talents in my country, especially after the establishment of interdisciplinary categories, it puts forward new requirements for the integration of interdisciplinary development and talent training in universities. On the basis of the existing research, this paper puts forward the construction of five aspects of the training mechanism of interdisciplinary graduate student enrollment mechanism, interdisciplinary tutor allocation mechanism, interdisciplinary course setting mechanism, interdisciplinary expert organization and interdisciplinary quality assurance mechanism, in order to provide a certain basis for standardizing the cultivation of interdisciplinary top-notch innovative talents

HTP: Exploiting Holistic Temporal Patterns for Sequential Recommendation

Sequential recommender systems have demonstrated a huge success for next-item recommendation by explicitly exploiting the temporal order of users' historical interactions. In practice, user interactions contain more useful temporal information beyond order, as shown by some pioneering studies. In this paper, we systematically investigate various temporal information for sequential recommendation and identify three types of advantageous temporal patterns beyond order, including absolute time information, relative item time intervals and relative recommendation time intervals. We are the first to explore item-oriented absolute time patterns. While existing models consider only one or two of these three patterns, we propose a novel holistic temporal pattern based neural network, named HTP, to fully leverage all these three patterns. In particular, we introduce novel components to address the subtle correlations between relative item time intervals and relative recommendation time intervals, which render a major technical challenge. Extensive experiments on three real-world benchmark datasets show that our HTP model consistently and substantially outperforms many state-of-the-art models. Our code is publically available at https://github.com/623851394/HTP/tree/main/HTP-mai

Stochastic assessment of landslide influence zone by material point method and generalized geotechnical random field theory

In landslide analysis, reliable prediction of landslide’s influence zone is significantly difficult due to inherent heterogeneity of soils and their spatially varying geological properties. In this paper, a probabilistic framework is proposed to evaluate the landslide hazard zoning through prediction of their influence zone considering the effects of heterogeneous soil properties. Material point method is used to simulate the large deformations during landslide failure. The spatial variation in the shear strength parameters of soils at undrained conditions is modeled by random fields, which are discretized by Cholesky matrix decomposition method to incorporate the effects of the soil spatial heterogeneity on the post-failure deformations. Furthermore, a practical landslide hazard zoning is conducted to quantitively evaluate the level of disaster for facilities or structures located in the vicinity of the slope by using the exceedance probability of influence distance and runout distance. Five categories based on different thresholds of exceedance probability are used to visualize the area potentially affected by the landslide. To demonstrate the capability of the stochastic assessment framework, a benchmark example of heterogeneous clayey slope is simulated, and the associated hazard zone is predicted and discussed; it presents a practical procedure for improving the landslide influence zone prediction and provides new insights for hazard zoning

Description and Application of a Mathematical Method for the Analysis of Harmony

Harmony issues are widespread in human society and nature. To analyze these issues, harmony theory has been proposed as the main theoretical approach for the study of interpersonal relationships and relationships between humans and nature. Therefore, it is of great importance to study harmony theory. After briefly introducing the basic concepts of harmony theory, this paper expounds the five elements that are essential for the quantitative description of harmony issues in water resources management: harmony participant, harmony objective, harmony regulation, harmony factor, and harmony action. A basic mathematical equation for the harmony degree, that is, a quantitative expression of harmony issues, is introduced in the paper: HD=ai − bj, where a is the uniform degree, b is the difference degree, i is the harmony coefficient, and j is the disharmony coefficient. This paper also discusses harmony assessment and harmony regulation and introduces some application examples

Stability analysis of heterogeneous infinite slopes under rainfall-infiltration by means of an improved Green-Ampt model

Rainfall infiltration analysis has a great significance to the mitigation and risk assessment of rainfall-induced landslides. The original Green-Ampt (GA) model ignored the fact that a transitional layer exists in infiltration regions of soils under the rainfall permeation, therefore it cannot effectively analyze the rainfall-infiltrated heterogeneous slope considering the spatial variability of saturated hydraulic conductivity (ks). In this paper, an improved GA model is proposed for the rainfall-infiltration analysis of heterogeneous slopes. Four common slope cases are investigated to validate the effectiveness of the proposed model. An infinite slope model is taken as an illustrative example to investigate the distributions of volumetric water content and slope stability under the rainfall infiltration. The results show that the distributions of volumetric water content and factors of safety (Fs) obtained from the proposed model are in very good agreement with the numerical results of Richards equation. In contrast, the modified GA model obtains biased distributions of volumetric water content and smaller Fs for the same cases. The results show that the proposed GA model can accurately identify the location of critical slip surface of the slope, and as such it provides an efficient method for risk control analysis of slopes susceptible to landslide

Uncertainty quantification of landslide runout motion considering soil interdependent anisotropy and fabric orientation

Natural soils often exhibit an anisotropic fabric pattern as a result of soil deposition, weathering, or filling. This paper aims to investigate the effect of soil interdependent anisotropy and fabric orientation on runout motions of landslides and evaluate the most critical fabric orientation for the post-failure behavior. The shear strength properties of soil deposit (i.e., cohesion c and friction angle φ) are modeled as negatively cross correlated bivariate random fields. The results reveal that the spatial variability and the negative cross-correlation of c and φ notably influence the post-failure behavior. In addition, the rotation of soil layer orientation significantly affects the runout motion. Based on the analyses, the deposition orientation of 30∘ is identified to produce the highest mean value and standard deviation of the runout distance. The findings from this study highlight the importance of considering the orientation of soil stratification, rather than only the magnitude of shear strength, in assessing the post-failure behavior of a landslide

Study of a high-precision complex 3D geological modelling method based on a fine KNN and kriging coupling algorithm: a case study for Jiangsu, China

A high-precision, complex, three-dimensional (3D) geological model can directly express the attributes of stratum thickness, geological structure, lithology and spatial form, which can provide a reliable basis for the development and utilization of underground space and planning decisions. However, it is difficult to perform accurate modelling due to the lack of basic data. As such, this paper proposes coupling a machine learning algorithm (K-nearest neighbour (KNN)) with the kriging algorithm to construct the topological relationship between the Delaunay triangle and the Thiessen polygon in order to perform the simulation and prediction of virtual drilling. Based on KNN, support vector machine (SVM) and neural network algorithms as well as the virtual borehole encryption data, data standardization processing and analysis are carried out. Through model verification, algorithm optimization is realized, and the optimal modelling method is explored. The results show that the fine KNN algorithm improved by Bayesian optimization can effectively improve the modelling accuracy through 0.1-m encryption, standardization processing and 5-fold cross-validation. Stratum modelling combined with the fine KNN and kriging algorithms can obtain a more accurate modelling without adding virtual boreholes. The improved levels of upper and lower hybrid modelling with an appropriate number of profile boreholes can also effectively optimize model accuracy. Both modelling accuracy and efficiency can be significantly improved by using Delaunay triangles and Thiessen polygons with virtual boreholes. Stratum modelling can effectively express the geological pinch-out in areas with adequate degrees of stratification, and hybrid modelling performs well in irregular geological bodies such as karsts and lenses

MMP11 is associated with the immune response and immune microenvironment in EGFR-mutant lung adenocarcinoma

BackgroundHigh expression of matrix metalloproteinase-11 (MMP11) is associated with various tumors and immune microenvironments. Conversely, poor response to immunotherapy in epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma (LUAD) patients is closely related to the characteristics of immune microenvironment.MethodsThe Cancer Genome Atlas (TCGA)-LUAD database and our gathered clinical LUAD samples were used to examine the relationship between MMP11 expression and EGFR mutation. Then the correlation between MMP11 and immune response and the difference of immune cell infiltration in different groups were analyzed. Compared the differences in the immune microenvironment between the MMP11-positive and MMP11-negative expression groups using immunohistochemistry (IHC) and multiplex immunohistochemistry.ResultsThe expression of MMP11 in samples with exon 19 deletions, exon 21 L858R or de novo exon 20 T790M mutations was higher than wild type, but there was no difference between the samples with uncommon mutation and the wild-type. The high MMP11 expression group had a higher Tumor Immune Dysfunction and Exclusion (TIDE) score. Pathways associated with enrichment in the extracellular matrix (ECM) were the main biological functions of differential genes between the high and low MMP11 groups. The IHC score of MMP11 in the EGFR-mutant group was higher than in the EGFR-wild group. In TCGA-LUAD, the high MMP11 group had a lower proportion of T cell CD8+ and NK cells activated. In the clinical samples, the infiltration levels of T cell CD8+ and NK cells in the tumor parenchyma of EGFR-mutant LUAD was lower in the MMP11-positive than in the MMP11-negative group. The expression levels of tumor cell PD-L1 were higher in the MMP11-positive expression group than in the MMP11-negative expression group, and the proportion of PD1+CD8+ T cells infiltrated was reduced in the MMP11-positive group compared to the MMP11-negative group.ConclusionsHigh expression of MMP11 was associated with EGFR mutations. Patients with EGFR-mutant LUAD with high expression of MMP11 responded poorly to immunotherapy, and the percentage of T cell CD8+ and NK cells in immune cell infiltration was lower in MMP11. Consequently, MMP11 is related to the immunological microenvironment of EGFR-mutant lung adenocarcinoma, which may be a predictor of possible immunotherapeutic response

A parametric study of 3D printed polymer gears

The selection of printing parameters for 3D printing can dramatically affect the dynamic performance of components such as polymer spur gears. In this paper, the performance of 3D printed gears has been optimised using a machine learning process. A genetic algorithm (GA)–based artificial neural network (ANN) multi-parameter regression model was created. There were four print parameters considered in 3D printing process, i.e. printing temperature, printing speed, printing bed temperature and infill percentage. The parameter setting was generated by the Sobol sequence. Moreover, sensitivity analysis was carried out in this paper, and leave-one cross validation was applied to the genetic algorithm-based ANN which showed a relatively accurate performance in predictions and performance optimisation of 3D printed gears. Wear performance of 3D printed gears increased by 3 times after optimised parameter setting was applied during their manufacture