兰州城市学院

Due to their excellent anti-sliding performance and efficient construction advantages,Portal-type Double-Row Anti-Slide Piles are extensively utilized in large-scale soil landslide control projects.However,existing analytical methods inadequately account for the distribution mechanism of landslide thrust exerted by the horizontal soil arch between piles in the loaded section.To address this issue,a simplified calculation method for landslide thrust distribution in the region behind the arch formed by horizontal soil arches between piles was proposed,based on the limit equilibrium method.Next,considering the slip surface as the boundary,the portal-type double-row anti-slide piles are divided into a load-bearing segment and an embedded segment.A calculation model for the reinforcement of soil landslides by portal-type double-row anti-slide piles is established,which takes into account the distribution effect of the inter-pile horizontal soil arch.By incorporating rigid and semi-rigid connection conditions between the pile top and the crown beam,the force method was adopted to solve the model and derive a corresponding calculation method for the internal forces and deformations of the pile shaft.Utilizing the proposed method,a case study was conducted to verify its accuracy through comparison with numerical simulation results,alongside a sensitivity analysis of key parameters.The study yields several conclusions:there is a significant difference in the pile top bending moment between the front and rear row piles,the rear row piles exhibit a sheltering effect on the front row piles.As the stiffness ratio between the crown beam and the pile body increases,the pile top horizontal displacement and the maximum bending moment of the pile shaft for both the front and rear row piles decrease non-linearly,and increasing the horizontal subgrade reaction coefficient of the embedded segment can effectively reduce the pile top horizontal displacement without significantly affecting the bending moment of the pile shaft.

With the digital transformation of the tourism industry,intelligent services have become an important part of modern travel.However,existing recommendation and Q&A systems remain limited in terms of knowledge coverage and reasoning capabilities,making it difficult to meet diverse user demands.To this end,this study constructs a high-quality knowledge-injection dataset for tourism-oriented large models,focusing on the Gansu region and covering the three core dimensions:attractions,hotels,and cuisine.The dataset was constructed through multi-platform data collection,manual curation and strict quality control procedures,including data source selection,consistency checking and manual review,to ensure the accuracy,comprehensiveness and relevance of the data.After processing,the final dataset comprises 810,793 triples,30,045 entities,and 14 relationship types,organized in the form of a knowledge graph.To facilitate intuitive display and exploration of multi-dimensional data associations,Neo4j is used as the storage and visualization tool.The release of this dataset provides strong data support for smart tourism and promote knowledge sharing and the development of intelligent systems in tourism domain.

This study constructed a dataset of online media in Gansu Province from 2013 to 2022,drawing data from five major online media platforms in Linxia Hui Autonomous Prefecture and Gannan Tibetan Autonomous Prefecture:Linxia Prefecture Government Website,Minzu Daily,China Linxia Website,Shambhala Online and China Gannan Website.The dataset covers a wide range of social,cultural,and linguistic content from the ethnic areas in Gansu,spanning a decade,with all entries consisting of Chinese-language news reports and commentaries.For each ear,neologism extraction was performed,and the resulting neologisms were analyzed in terms of word frequency,lexicality,word number,cohesion,degree of freedom and neologism probability.The dataset was constructed with strict quality control measures,including manual proofreading,noise filtering,de-duplication processing and language annotation,to ensure the accuracy and completeness of the data.This dataset provides a critical resource for studying language use,socio-cultural dynamics,and bilingual education development in ethnic areas,and has broad applicability in policy analyses,social opinion monitoring and language policy research.

In order to improve the molten salt corrosion resistance of the plasma arc welds of the nickel-based alloy N6,the welds were subjec-ted to tensile deformation and heat treatment(referred to as GBE samples).The grain boundary character distribution(GBCD)was analyzed using Electron Backscatter Diffraction(EBSD)and Orientation Imaging Microscopy(OIM).A constant-temperature corrosion test at 900° C was conducted to study the effect of the grain boundary character distribution on the welds'resistance to molten salt corrosion.Results showed that after the weld samples underwent 6％tensile deformation,annealing at 1 000 ℃,and an annealing time of 15 min,recrystallization oc-curred,resulting in grain refinement.The heat treatment process generated a large number of annealing twins,and the proportion of low ∑CSL grain boundaries in the welds increased to 57.3％.The welds underwent oxidation and sulfidation reactions in a high-temperature 75％Na2SO4-25％NaCl molten salt mixture.The surface corrosion characteristics of the weld samples were predominantly intergranular corrosion.The hot corrosion rate of the untreated samples(Non-GBE)was faster[0.848 4 mg/(cm2·h)]than that of the GBE samples[0.339 7 m g/(cm2·h)].The molten salt corrosion resistance of the nickel-based alloy N6 welds was significantly enhanced through tensile deformation and heat treatment.

High Entropy Alloys (HEA) are a new type of metal material with broad application prospects in the high-end equipment manufacturing industry.Due to the unique phase structure and “four major effects” of high entropy alloys， which endow them with excellent mechanical properties such as strength，hardness，toughness and wear resistance，high entropy alloys have become a research hotspot in the field of materials.Corrosion is a common and unavoidable form of failure in metallic materials，and high entropy alloys are widely used in industrial fields due to their excellent corrosion resistance.Thus， it is necessary to focus on studying the corrosion resistance performance， corrosion resistance mechanism and laws of high entropy alloys for better developing high-performance high entropy alloys.This article firstly briefly described the definition and classification of high entropy alloys， then summarized the preparation methods of high entropy alloys， and provided a detailed overview of the research status of high entropy alloy corrosion resistance.Different preparation processes and process parameters had a direct impact on the microstructure of high entropy alloys， and high entropy alloy components had broad design space.Therefore， by adjusting the preparation process parameters and component composition， the corrosion resistance of high entropy alloys could be further optimized.At last，the research topics and ideas for future high entropy alloys were discussed.