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Journal of Contemporary Educational Research 2022年第12期6卷 30-37页

作者： Huiping Han China University of Geosciences(Beijing) Beijing 100083China

The“3060”goal demonstrates china’s responsibility in actively responding to global climate,enhances china’s voice and influence in climate governance,and sets an example of energy conservation and emission reduction for developing countries.As the main institutions that educate people for the Party and the country,colleges and universities have the responsibility to explore the realization path of carbon peak and carbon neutralization against the new problems encountered in the practice of energy conservation and emission reduction in colleges and universities.In response to the national strategy and the action plan of the Ministry of Education,taking the carbon practice of China University of Geosciences(Beijing)as the starting point,this paper conducts benchmarking research on the path of carbon peak and carbon neutralization in universities through the ecological factor method,campus carbon footprint,and questionnaire analysis.

关键词： Carbon peak Carbon neutralization Colleges and universities Conserve energy Reduce emissions Benchmarking research

Campus Vibration in Nanwangshan Campus,China University of Geosciences at Wuhan Monitored by Short-Period Seismometers

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Journal of Earth Science 2020年第5期31卷 950-956页

作者： Lihui Wu Dun Wang Ziguang Lei Jing Fu Shuai Min Xianbing Xu Sarina Bao School of Management Hubei University of EducationWuhan 430205China Institute of Supply Chain Operation and Service Innovation Hubei University of EducationWuhan 430205China State Key Laboratory of Geological Processes and Mineral Resources School of Earth SciencesChina University of GeosciencesWuhan 430074China Department of Environmental Science and Policy University of CaliforniaCA 95616USA

Continuous seismic observations can record seismic waveforms, and ambient noise, for the purposes of earthquake researches and other applications. Here we deploy three digital seismometers(EPS-2) in and around the Nanwangshan Campus of the China University of Geosciences(Wuhan). This network was running from April 9 to May 9 of 2018. During this period, the seismometers recorded the May 4, 2018 M6.9 Hawaii earthquake. From the recorded waveforms, we could observe clearly the P and S arrivals, and the corresponding particle motions. Analysis of continuous observations of ambient noise shows obvious fluctuation of vibration intensity inside of the campus. The campus is quietest from 0 to 5 am. From 5 am on, the vibration intensity increases, and reaches the peak of entire day at 12 am. The amplitude then decreases to a very low level at 19:30 to 20:00 pm, and reaches another strong noisy time at 21:00 to 21:30 pm. After 21:30 pm, the intensity goes down slowly. We also observed seismic signals that were generated by the interaction of speed-control hump cars and ground. By taking the envelope and smooth operations, we observe different characteristics for different car speeds, which suggests that seismic monitoring approaches can be used for speed measurement of cars. This kind of small seismic network running in a real time fashion, would greatly help understanding of the sources of ambient noise at high frequency bands in interested areas. Analysis of a long-term observed dataset, and real time illustration will help to strengthen campus security and high-precision laboratory deployments, and also contribute to research atmosphere in earthquake science.

关键词： ambient noise vibration intensity seismic waves seismometers human activity

Learning from crowds with robust support vector machines

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Science china(Information Sciences) 2023年第3期66卷 133-149页

作者： Wenjun YANG Chaoqun LI Liangxiao JIANG School of Mathematics and Physics China University of Geosciences School of Computer Science China University of Geosciences

Crowdsourcing system provides an easy way to obtain labeled training data. However, the labels provided by non-expert labelers often appear low quality. So in practice, each sample usually obtains a multiple label set from multiple different labelers. Learning-from-crowds(LFC) aims to design ground truth inference algorithms to infer the unknown true labels of data from multiple label sets. Despite their proper statistical foundations, the existing ground truth inference algorithms show limited performance when the number of labelers is small. However, more labelers mean higher costs. This paper tries to propose a novel ground truth inference algorithm which can maintain moderate performance and simultaneously reduce labeling costs. This paper addresses LFC from a point of view of robust classifiers and presents a new label noise robust support vector machine inference(RSVMI) algorithm. We prove that only one convex quadratic programming problem needs to be solved to build a robust support vector machine. Furthermore,in order to apply the robust support vector machine to crowdsourced data, two methods are proposed to estimate the noise level of integrated labels. By transforming the original LFC problem into a robust classifier learning problem, our algorithm shows good performance when the number of labelers is very small. In our experiments, the minimum number of labelers is set to 3. In terms of both label quality and model quality,the experimental results on benchmark data sets and real-world data sets show the effectiveness of RSVMI.

关键词： crowdsourcing learning ground truth inference integrated labels label noise robust support vector machines

Three-dimensional magnetotelluric modeling in the spherical and Cartesian coordinate systems:A comparative study

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Earth and Planetary Physics 2023年第4期7卷 499-512页

作者： Qi Han XiangYun Hu School of Geophysics and Geomatics China University of GeosciencesWuhan 430074China China University of Geosciences Press Wuhan 430074China

With the increase in the coverage area of magnetotelluric data,three-dimensional magnetotelluric modeling in spherical coordinates and its differences with respect to traditional Cartesian modeling have gradually attracted attention.To fully understand the influence of the Earth’s curvature and map projection deformations on Cartesian modeling,qualitative and quantitative analyses based on realistic three-dimensional models need to be examined.Combined with five representative map projections,a type of model conversion method that transforms the original spherical electrical conductivity model to Cartesian coordinates is described in this study.The apparent resistivity differences between the spherical western United States electrical conductivity model and the corresponding five Cartesian models are then compared.The results show that the cylindrical equal distance map projection has the smallest error.A meridian convergence correction resulting from the deformation of the map projection is introduced to rotate the Cartesian impedance tensor from grid north to geographic north,which reduces differences from the spherical results.On the basis of the magnetotelluric field data,the applicability of the Cartesian coordinate system to western and contiguous United States models is quantitatively evaluated.Precise interpretations of the contiguous United States model were found to require spherical coordinates.

关键词： spherical magnetotelluric modeling model conversion realistic electrical conductivity model quantitative evaluation

Attribute augmentation-based label integration for crowdsourcing

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Frontiers of Computer Science 2023年第5期17卷 41-51页

作者： Yao ZHANG Liangxiao JIANG Chaoqun LI School of Computer Science China University of GeosciencesWuhan 430074China School of Mathematics and Physics China University of GeosciencesWuhan 430074China

Crowdsourcing provides an effective and low-cost way to collect labels from crowd workers.Due to the lack of professional knowledge,the quality of crowdsourced labels is relatively low.A common approach to addressing this issue is to collect multiple labels for each instance from different crowd workers and then a label integration method is used to infer its true label.However,to our knowledge,almost all existing label integration methods merely make use of the original attribute information and do not pay attention to the quality of the multiple noisy label set of each instance.To solve these issues,this paper proposes a novel three-stage label integration method called attribute augmentation-based label integration(AALI).In the first stage,we design an attribute augmentation method to enrich the original attribute space.In the second stage,we develop a filter to single out reliable instances with high-quality multiple noisy label sets.In the third stage,we use majority voting to initialize integrated labels of reliable instances and then use cross-validation to build multiple component classifiers on reliable instances to predict all instances.Experimental results on simulated and real-world crowdsourced datasets demonstrate that AALI outperforms all the other stateof-the-art competitors.

关键词： crowdsourcing label integration attribute aug-mentation instance filtering

Antimony transformation and mobilization from stibnite by an antimonite oxidizing bacterium Bosea sp. AS-1

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Journal of Environmental Sciences 2022年第1期34卷 273-281页

作者： Li Xiang Chaoyang Liu Deng Liu Liyuan Ma Xuan Qiu Hongmei Wang Xiaolu Lu School of Environmental Studies China University of Geosciences(Wuhan)Wuhan 430074China State Key Laboratory of Biogeology and Environmental Geology China University of Geosciences(Wuhan)Wuhan 430074China

Soils and waters are heavily contaminated by antimony in Xikuangshan(XKS)mine area.It is widely accepted that oxidative dissolution of sulfide minerals and aqueous dissolution are the most prevalent geochemical mechanisms for the release of Sb to the environment.Bosea sp.AS-1 is an antimonite-oxidizer isolated from the mine slag in Xikuangshan Sb mine.Whole genome sequencing revealed the presence of multiple sulfur-oxidizing genes,antimony(Sb)metabolism genes and carbon fixation genes in AS-1 s genome.We therefore hypothesized that under oxic conditions,AS-1 could mediate the oxidation of sulfide and Sb(Ⅲ)in stibnite(Sb_(2)S_(3))and lead to the release of Sb.Indeed,strain AS-1 was discovered as an autotrophic Sb(Ⅲ)-oxidizer.Antimony mobilization studies conducted with strain AS-1showed significantly enhanced mobilization of Sb,and complete oxidation of released Sb and sulfur to Sb(V)and sulfate.In addition,AS-1 induced a faster release of Sb under heterotrophic condition,and new acicular minerals might form.These findings support the hypothesis that microorganisms play an important role in the mobilization and transformation of Sb in XKS mine area and may contribute to our further understanding of the Sb biogeochemical redox cycle in natural environment.

关键词： Antimonite oxidation Bosea sp.AS-1 Stibnite Antimony mobilization Xikuangshan mine area

Magma Generation of Magnetite-Rich Intermediate-Mafic Rocks and Its Mantle Processes in the Southwestern Alxa Block,NW china

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Journal of Earth Science 2022年第1期33卷 161-176页

作者： Lu Tao Hongfei Zhang Jing Wu Xiaochun Zhou Liqi Zhang State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430074China School of Earth Sciences China University of GeosciencesWuhan 430074China Gemmological Institute China University of GeosciencesWuhan 430074China Faculty of Earth Resources China University of GeosciencesWuhan 430074China

Many studies focus on mineralization of huge magnetite ore deposits and petrogenesis of their large-volume host rocks.However,magma generation of those small-scale intrusions with enrichment of magnetite is poorly reported and paid attention to.We here carry out an integrated study of magnetite chemistry,U-Pb zircon dating,geochemistry,and Sr-Nd-Hf isotopes for the magnetite-rich intermediate-mafic rocks from the Helishan pluton in the southwestern Alxa Block,Northwest china.This,together with several previously reported magnetite/iron-rich intrusions nearby,is capable of providing some constraints on magma generation of magnetite/iron-rich intrusive rocks.The Helishan pluton,dated at ca.290 Ma,consists of hornblende gabbro,diorite,and quartz monzodiorite with~3%-5%magnetite in all the lithologies.Study on magnetite chemistry manifests a magmatic origin for them.All the lithologies display high TFeO/MgO ratio (1.71-1.89),weakly fractionated REE patterns((La/Yb)_(N)=1.82-10.17),enrichment of Rb,Sr,and Pb,and depletion of high field strength elements.They have (^(87)Sr/^(86)Sr)_(i) values of 0.705 2 to 0.705 8,ε_(Nd)(t) values of+0.03 to+0.64,and zircon ε_(Hf)(t) values of +6.5 to+12.0.We propose that they were derived from partial melting of iron-rich metasomatized lithospheric mantle.The systematic variations of Sr/Y ratios and Nd-Hf isotopic compositions with time for the Paleozoic igneous rocks at the southwestern Alxa Block indicate ever existence of thinning and rebirth of lithospheric mantle.This geodynamic process could be the potential mechanism to give rise to the iron-rich signature of the reborn mantle sources of the Helishan pluton.For intermediatemafic intrusions at subduction zones,they are unlikely to form considerable magnetite ore deposits since their modest magmatic flux and early fractional crystallization of magnetite at a high oxygen fugacity and H_(2)O condition.

关键词： geochemishtry magnetite-rich intrusion mantle source petrogenesis lithospheric process Alxa Block Northwest china

A New Machine-Learning Extracting Approach to Construct a Knowledge Base: A Case Study on Global Stromatolites over Geological Time

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地球科学学刊:英文版 2023年第5期34卷 1358-1373页

作者： Xiaobo Zhang Hao Li Qiang Liu Zhenhua Li Claire E.Reymond Min Zhang Yuangeng Huang Hongfei Chen Zhong-Qiang Chen School of Computer China University of GeosciencesWuhan 430078China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China School of Earth Resources China University of GeosciencesWuhan 430074China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430078China

Within any scientific disciplines, a large amount of data are buried within various literature depositories and archives, making it difficult to manually extract useful information from the datum swamps. The machine-learning extraction of data therefore is necessary for the big-data-based studies. Here, we develop a new text-mining technique to reconstruct the global database of the Precambrian to Recent stromatolites, providing better understanding of secular changes of stromatolites though geological time. The step-by-step data extraction process is described as below. First, the PDF documents of stromatolite-containing literatures were collected, and converted into text formation. Second, a glossary and tag-labeling system using NLP(Natural Language Processing) software was employed to search for all possible candidate pairs from each sentence within the papers collected here. Third, each candidate pair and features were represented as a factor graph model using a series of heuristic procedures to score the weights of each pair feature. Occurrence data of stromatolites versus stratigraphical units(abbreviated as Strata), facies types, locations, and age worldwide were extracted from literatures, respectively, and their extraction accuracies are 92%/464, 87%/778, 92%/846, and 93%/405 from 3 750 scientific abstracts, respectively, and are 90%/1 734, 86%/2 869, 90%/2 055 and 91%/857 from 11 932 papers, respectively. A total of 10 072 unique datum items were identified. The newly obtained stromatolite dataset demonstrates that their stratigraphical occurrences reached a pronounced peak during the Proterozoic(2 500 – 541 Ma), followed by a distinct fall during the Early Phanerozoic, and overall fluctuations through the Phanerozoic(541–0 Ma). Globally, seven stromatolite hotspots were identified from the new dataset, including western United States, eastern United States, western Europe, India, South Africa, northern china, and southern china. The proportional occurrences of inland aquatic stromatolites remain rathe

关键词： machine learning knowledge base construction stromatolites Precambrian knowledge graph

Fact-condition statements and super relation extraction for geothermic knowledge graphs construction

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Geoscience Frontiers 2023年第5期14卷 384-395页

作者： Qizhi Chen Hong Yao Shengwen Li Xinchuan Li Xiaojun Kang Wenwen Lai Jian Kuang School of Computer Science China University of GeosciencesWuhan 430074China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China School of Geography and Information Engineering China University of GeosciencesWuhan 430074China

Researchers utilize information from the geoscience literature to deduce the regional or global geological evolution.Traditionally this process has relied on the labor of researchers.As the number of papers continues to increase,acquiring domain-specific knowledge becomes a heavy burden.Knowledge Graph(KG)is proposed as a new knowledge representation technology to change this situation.However,the super relation is not considered in the previous KG,which bridges the geological phenomenon(fact)and its precondition(condition).For instance,in the statement(“the late Archean was a crucial transition period in the history of global geodynamics”),the condition statement(“crucial transition for global geodynamics”)works as the complementary fact statement(“the late Archean was a crucial transition period”),which defines the scale of crucial transition accurately in the late Archean.In this study,fact-condition statement extraction is introduced to construct a geological knowledge graph.A rule-based multi-input multi-output model(R-MIMO)is proposed for information extraction.In the R-MIMO,fact-condition statements and their super relation are considered and extracted for the first time.To verify its performances,a GeothCF dataset with 1455 fact tuples and 789 condition tuples is constructed.In experiments,the R-MIMO model achieves the best performance by using BERT as encoder and LSTM-d as decoder,achieving F180.24%in tuple extraction and F170.03%in tag prediction task.Furthermore,the geothermic KG with super relation is automatically constructed for the first time by trained R-MIMO,which can provide structured data for further geothermic research.

关键词： Fact-condition statements Super relation Knowledge graph Rule-based multi-input multi-output model

Exploring a Promising Region and Enhancing Decision Space Diversity for Multimodal Multi-Objective Optimization

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Tsinghua Science and Technology 2024年第2期29卷 325-342页

作者： Fei Ming Wenyin Gong School of Computer Science China University of GeosciencesWuhan 430074China

During the past decade,research efforts have been gradually directed to the widely existing yet less noticed multimodal multi-objective optimization problems(MMOPs)in the multi-objective optimization community.Recently,researchers have begun to investigate enhancing the decision space diversity and preserving valuable dominated solutions to overcome the shortage caused by a preference for objective space convergence.However,many existing methods still have limitations,such as giving unduly high priorities to convergence and insufficient ability to enhance decision space diversity.To overcome these shortcomings,this article aims to explore a promising region(PR)and enhance the decision space diversity for handling MMOPs.Unlike traditional methods,we propose the use of non-dominated solutions to determine a limited region in the PR in the decision space,where the Pareto sets(PSs)are included,and explore this region to assist in solving MMOPs.Furthermore,we develop a novel neighbor distance measure that is more suitable for the complex geometry of PSs in the decision space than the crowding distance.Based on the above methods,we propose a novel dual-population-based coevolutionary algorithm.Experimental studies on three benchmark test suites demonstrates that our proposed methods can achieve promising performance and versatility on different MMOPs.The effectiveness of the proposed neighbor distance has also been justified through comparisons with crowding distance methods.

关键词： multimodal multi-objective optimization evolutionary algorithms promising region neighbor distance decision space coevolution