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中国发展 2009年第1期9卷 76-83页

作者：黄坤明施祖麟车文辉中共浙江省委宣传部浙江杭州310025

城乡一体化发展是求解"三农"问题的根本途径。改善城乡关系,推进城乡一体化,一方面要进一步重视政府的主导作用,加大政府制度供给和制度创新的力度;另一方面,也要重视优化民本制度创新的环境,提升农村的地位、重视农民的主体作用。

关键词：民本自发政府自觉城乡一体化

废弃茶叶渣负载纳米铁去除水中六价铬的动力学及作用机制

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生态环境学报 2020年第10期29卷 2081-2090页

作者：黄坤明周洁琼刘威谢莹莹文震卢桂宁韩山师范学院化学与环境工程学院广东潮州521041 深圳大学化学与环境工程学院广东深圳518060 华南理工大学环境与能源学院/工业聚集区污染控制与生态修复教育部重点实验室广东广州510006

如何绿色高效地实现水体中六价铬[Cr(Ⅵ)]的去除是解决水环境中铬污染的关键问题。以废弃茶叶渣为基础材料,通过沉积法负载纳米铁,制备出茶叶渣负载纳米铁的复合材料(nZVI@TW),采用牺牲实验的方法探究在不同环境条件下nZVI@TW去除Cr(Ⅵ... 详细信息

如何绿色高效地实现水体中六价铬[Cr(Ⅵ)]的去除是解决水环境中铬污染的关键问题。以废弃茶叶渣为基础材料,通过沉积法负载纳米铁,制备出茶叶渣负载纳米铁的复合材料(nZVI@TW),采用牺牲实验的方法探究在不同环境条件下nZVI@TW去除Cr(Ⅵ)的影响因素,以及阐明nZVI@TW对水中Cr(Ⅵ)的去除机理。结果表明,茶叶渣的含量越高,nZVI@TW湿投加量越大,Cr(Ⅵ)溶液初始浓度越低,以及较低的初始溶液pH,越有利于nZVI@TW去除六价铬。当pH=3.5,Cr(Ⅵ)的初始浓度为10 mg·L^−1时,nZVI@TW对六价铬去除率可达到99.1%,该反应符合伪一级动力学模型。添加金属螯合剂聚天冬氨酸没有明显提高去除率,但可将反应速率由原来0.216 min−1可提高至0.269 min−1。SEM表征结果说明在pH为3.5时反应后的固体产物呈现凝聚片状结构且夹杂着小针状物质。FTIR结果表明此反应过程中羧基络合重金属的存在。XPS再一次验证了络合的存在以及还原铬的过程中伴随着生成的Cr和Fe复合体包裹于产物表面。nZVI@TW去除Cr(Ⅵ)的机理可以概括为还原耦合吸附共沉淀多反应共存的固定机制。研究结果可为含Cr(Ⅵ)废水的修复治理提供技术参考。

关键词：六价铬纳米铁动力学去除机制铁基材料

Spatial pattern recognition for near-surface high temperature increases in mountain areas using MODIS and SRTM DEM

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Journal of Mountain Science 2024年第6期21卷 2025-2042页

作者： WANG Yanxia YANG Lisha huang Xiaoyuan ZHOU Ruliang School of Soil and Water Conservation Southwest Forestry UniversityKunming 650224China School of Economics and Management Southwest Forestry UniversityKunming 650224China

Abrupt near-surface temperature changes in mountainous areas are a special component of the mountain climate *** and accurate measurements of the locations,intensity,and width of the near-surface changes are necessary but highly difficult due to the complicated environmental conditions and instrumental *** paper develops a spatial pattern recognition method to measure the near-surface high temperature increase(NSHTI),one of the lesser-attended ***,raster window measurement was proposed to calculate the temperature lapse rate using MODIS land surface temperature and SRTM DEM *** fully considers the terrain heights of two neighboring cells on opposite or adjacent slopes with a moving window of 3×3 cell ***,a threshold selection was performed to identify the NSHTI cells using a threshold of-0.65℃/100 ***,the NSHTI strips were parameterized through raster vectorization and spatial *** Yunnan,a mountainous province in southwestern China,as the study area,the results indicate that the NSHTI cells concentrate in a strip-like pattern along the mountains and valleys,and the strips are almost parallel to the altitude contours with a slight northward ***,they are located mostly at a 3/5 height of high mountains or within 400 m from the valley floors,where the controlling topographic index is the altitude of the terrain trend surface but not the absolute elevation and the topographic uplift height and cutting ***,the NSHTI intensity varies with the geographic locations and the proportions increase with an exponential trend,and the horizontal width has a mean of about 1000 m and a maximum of over 5000 *** result demonstrates that the proposed method can effectively recognize NSHTI boundaries over mountains,providing support for the modeling of weather and climate systems and the development of mountain resources.

关键词： High temperature increase Mountain areas MODIS Spatial pattern recognition Raster window measurement Threshold selection

Semantic-aware entity alignment for low resource language knowledge graph

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Frontiers of Computer Science 2024年第4期18卷 97-106页

作者： Junfei TANG Ran SONG Yuxin huang Shengxiang GAO Zhengtao YU Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming 650500China

Entity alignment(EA)is an important technique aiming to find the same real entity between two different source knowledge graphs(KGs).Current methods typically learn the embedding of entities for EA from the structure of KGs for *** EA models are designed for rich-resource languages,requiring sufficient resources such as a parallel corpus and pre-trained language ***,low-resource language KGs have received less attention,and current models demonstrate poor performance on those low-resource ***,researchers have fused relation information and attributes for entity representations to enhance the entity alignment performance,but the relation semantics are often *** address these issues,we propose a novel Semantic-aware Graph Neural Network(SGNN)for entity ***,we generate pseudo sentences according to the relation triples and produce representations using pre-trained ***,our approach explores semantic information from the connected relations by a graph neural *** model captures expanded feature information from *** results using three low-resource languages demonstrate that our proposed SGNN approach out performs better than state-of-the-art alignment methods on three proposed datasets and three public datasets.

关键词： graph neural network knowledge graph entity alignment low-resource language

基于API序列和卷积神经网络的恶意代码检测

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信息安全研究 2020年第3期6卷 212-219页

作者：王兴凤黄琨茗张文杰四川大学网络空间安全学院成都610065

卷积神经网络(convolutional neural network,CNN)在诸多领域得到了广泛应用,Windows API序列在结构上存在前后依赖关系,仅仅使用卷积神经网络实现恶意代码检测将忽略词的上下文语义,因此使用了词向量模型来训练API序列,并且融合5个大... 详细信息

卷积神经网络(convolutional neural network,CNN)在诸多领域得到了广泛应用,Windows API序列在结构上存在前后依赖关系,仅仅使用卷积神经网络实现恶意代码检测将忽略词的上下文语义,因此使用了词向量模型来训练API序列,并且融合5个大小不同的卷积核来弥补传统卷积网络丢失序列时序信息和语法信息的缺点.在Cuckoo沙箱中运行样本文件,提取动态API序列并进行去重处理,预训练得到词向量,输入到多核融合的CNN网络中训练恶意代码检测模型.最后使用测试集测试模型的有效性,测试集的正确率值达到了98.1%,结果表明所提出的方法能有效地检测恶意代码.

关键词：恶意代码 API序列词嵌入多核融合卷积神经网络

In situ anchoring in carbon matrix of Bi_(2)O_(2)CO_(3) as a high-performance anode material for Li-ion batteries

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Rare Metals 2024年第8期43卷 3634-3646页

作者： Pu-Qiang He Jun Guo Hui huang Zhong-Cheng Guo Faculty of Metallurgy and Energy Engineering Kunming University of Science and TechnologyKunming 650093China Research Center of Metallurgical Electrode Materials Engineering Technology Kunming 650106China kunming Hendera Science and Technology Co. Ltd.Kunming 650106China

Bismuth-based anode materials have been regarded as promising Li-ion batteries due to their high theoretical ***,their low conductivity and associated volume expansion inhabited their *** this work,Bi_(2)O_(2)CO_(3)@C composites were successfully synthesized by in situ anchoring of flower-like Bi_(2)O_(2)CO_(3) nanosheets on a carbon-based substrate via *** unique composited structure of Bi_2O_(2)-CO_(3)@C leads to a stable specific capacity of 547 mAh·g^(-1)after 100 cycles at a current density of 0.1 A·g^(-1).Notably,it demonstrates excellent rate capability with a specific capacity of 210 mAh·g^(-1)at 5 A·g^(-1).After 550 cycles at a current density of 0.5 A·g^(-1),a high reversible capacity of nearly 400 mAh·g^(-1)was ***,in situ X-ray diffraction measurements clearly demonstrate the conversion between Bi and Li_(3)Bi during alloying/dealloying,confirming the good electrochemical reversibility of the materials for Li *** reaction kinetics of Bi_(2)O_(2)CO_(3)@C were further investigated using galvanostatic intermittent titration ***,Bi_2O_(2)-CO_(3)@C exhibited excellent long-term stability,maintaining its high reversible capacity for over 200 cycles at a current density of 0.5 A·g^(-1)in a full cell configuration using Li_(1.20)Mn_(0.54)Ni_(0.13)Co_(0.13)O_(2) as the cathode *** result further underscores its promising potential for lithium-ion *** work may provide inspiration for the design of alloy-type negative electrode materials for high-performance rechargeable batteries.

关键词： Bi_(2)O_(2)CO_(3) Composite materials Anode materials Full batteries

Research progress of heterogeneous structure magnesium alloys:A review

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Journal of Magnesium and Alloys 2024年第6期12卷 2147-2181页

作者： Xiang Chen Junlei Zhang Min Wang Weizhang Wang Di Zhao Haiming huang Qi Zhao Xiaofei Xu Hongxia Zhang Guangsheng huang Hubei Longzhong Laboratory Wuhan University of Technology Xiangyang Demonstration ZoneXiangyang 441000China College of Materials Science and Engineering Hubei University of Automotive TechnologyShiyan 442002China College of Materials Science and Engineering Kunming University of Science and TechnologyKunming 650093China Hubei Key Laboratory of Energy Storage and Power Battery(Hubei University of Automotive Technology) Shiyan 442002China College of Materials Science and Engineering Chongqing UniversityChongqing 400044China School of Mechanical Engineering Suzhou University of Science and TechnologySuzhou 215009China

In recent years,a new class of metallic materials featuring heterogeneous structures has *** materials consist of distinct soft and hard domains with significant differences in mechanical properties,allowing them to maintain high strength while offering superior ***(Mg)alloys,renowned for their low density,high specific strength,exceptional vibration damping,and electromagnetic shielding properties,exhibit tremendous potential as lightweight and functional *** their advantageous properties,high-strength Mg alloys often suffer from limited ***,the emergence of heterogeneous materials provides a fresh perspective for the development of Mg alloys with both high strength and *** article provided a fundamental overview of heterostructured materials and systematically reviewed the recent research progress in the design of Mg alloys with strength-ductility balance based on heterostructure *** review encompassed various aspects,including preparation methods,formation mechanisms of diverse heterostructures,and mechanical properties,both within domestic and international *** this basis,the article discussed the challenges encountered in the design and fabrication of heterostructured Mg alloys,as well as the urgent issues that require attention and resolution in the future.

关键词： Mg alloys Heterogeneous structure Processing techniques Strength and ductility Hetero-deformation induced stress Strain gradient

Retrospective and prospective review of the generalized nonlinear strength theory for geomaterials

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International Journal of Minerals,Metallurgy and Materials 2024年第8期31卷 1767-1787页

作者： Shunchuan Wu Jiaxin Wang Shihuai Zhang Shigui huang Lei Xia Qianping Zhao Faculty of Land Resource Engineering Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area MNRKunming 650093China Yunnan Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area Kunming 650093China School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China School of Civil and Resource Engineering University of Science and Technology BeijingBeijing 100083China

Strength theory is the basic theory for calculating and designing the strength of engineering materials in civil,hydraulic,mechanical,aerospace,military,and other engineering ***,the comprehensive study of the generalized nonlinear strength theory(GNST)of geomaterials has significance for the construction of engineering rock *** paper reviews the GNST of geomaterials to demonstrate the research status of nonlinear strength characteristics of geomaterials under complex stress ***,it systematically summarizes the research progress of GNST(classical and empirical criteria).Then,the latest research the authors conducted over the past five years on the GNST is introduced,and a generalized three-dimensional(3D)nonlinear Hoek‒Brown(HB)criterion(NGHB criterion)is proposed for practical *** criterion can be degenerated into the existing three modified HB criteria and has a better prediction *** strength prediction errors for six rocks and two in-situ rock masses are 2.0724%-3.5091%and 1.0144%-3.2321%,***,the development and outlook of the GNST are expounded,and a new topic about the building strength index of rock mass and determining the strength of in-situ engineering rock mass is *** summarization of the GNST provides theoretical traceability and optimization for constructing in-situ engineering rock mass strength.

关键词： rock mechanics rock mass strength strength theory failure criterion Hoek-Brown criterion intermediate principal stress deviatoric plane smoothness and convexity

Enhancing low-resource cross-lingual summarization from noisy data with fine-grained reinforcement learning

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 121-134页

作者： Yuxin huang Huailing GU Zhengtao YU Yumeng GAO Tong PAN Jialong XU Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650504China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming 650504China

Cross-lingual summarization(CLS)is the task of generating a summary in a target language from a document in a source ***,end-to-end CLS models have achieved impressive results using large-scale,high-quality datasets typically constructed by translating monolingual summary corpora into CLS ***,due to the limited performance of low-resource language translation models,translation noise can seriously degrade the performance of these *** this paper,we propose a fine-grained reinforcement learning approach to address low-resource CLS based on noisy *** introduce the source language summary as a gold signal to alleviate the impact of the translated noisy target ***,we design a reinforcement reward by calculating the word correlation and word missing degree between the source language summary and the generated target language summary,and combine it with cross-entropy loss to optimize the CLS *** validate the performance of our proposed model,we construct Chinese-Vietnamese and Vietnamese-Chinese CLS *** results show that our proposed model outperforms the baselines in terms of both the ROUGE score and BERTScore.

关键词： Cross-lingual summarization Low-resource language Noisy data Fine-grained reinforcement learning Word correlation Word missing degree

High-performance formaldehyde prediction for indoor air quality assessment using time series deep learning

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Building Simulation 2024年第3期17卷 415-429页

作者： Liu Lu Xinyu huang Xiaojun Zhou Junfei Guo Xiaohu Yang Jinyue Yan School of Human Settlements and Civil Engineering Xi’an Jiaotong UniversityXi’anChina Department of Building Environment and Energy Engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina Future Energy Profile School of BusinessSocietyand EngineeringMälardalen UniversityVästeråsSweden

Indoor air pollution resulting from volatile organic compounds(VOCs),especially formaldehyde,is a significant health concern needed to predict indoor formaldehyde concentration(Cf)in green intelligent building *** study develops a thermal and wet coupling calculation model of porous fabric to account for the migration of formaldehyde molecules in indoor air and cotton,silk,and polyester fabric with heat flux in Harbin,Beijing,Xi’an,Shanghai,Guangzhou,and kunming,*** time-by-time indoor dry-bulb temperature(T),relative humidity(RH),and Cf,obtained from verified simulations,were collated and used as input data for the long short-term memory(LSTM)of the deep learning model that predicts indoor multivariate time series Cf from the secondary source effects of indoor fabrics(adsorption and release of formaldehyde).The trained LSTM model can be used to predict multivariate time series Cf at other emission times and *** LSTM-based model also predicted Cf with mean absolute percentage error(MAPE),symmetric mean absolute percentage error(SMAPE),mean absolute error(MAE),mean square error(MSE),and root mean square error(RMSE)that fell within 10%,10%,0.5,0.5,and 0.8,*** addition,the characteristics of the input dataset,model parameters,the prediction accuracy of different indoor fabrics,and the uncertainty of the data set are *** results show that the prediction accuracy of single data set input is higher than that of temperature and humidity input,and the prediction accuracy of LSTM is better than recurrent neural network(RNN).The method’s feasibility was established,and the study provides theoretical support for guiding indoor air pollution control measures and ensuring human health and safety.

关键词： multivariate time series formaldehyde concentration deep learning heat-humidity coupling mass transfer secondary source effect