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甘蓝型高油分杂交油菜新品种宝油187的选育与应用

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贵州农业科学 2024年第7期52卷 1-4页

作者：晏伟杨德政秦信蓉程尚明赵军王丹丹罗雯鲍坤喻时周贵州省油菜研究所贵州贵阳550008 贵州禾睦福种子有限公司贵州长顺550700 长顺县摆所镇农业综合服务中心贵州长顺550700 长顺县长寨街道农业综合服务中心贵州长顺550700

【目的】培育高产、高油及耐密植油菜新品种,为高油高产优质油菜品种的应用提供种质选择。【方法】贵州省油菜研究所利用隐性核不育两系D418AB作母本,以恢复系YD84R作父本,于2023年育成高油分双低杂交油菜新品种宝油187(农业农村部登记... 详细信息

【目的】培育高产、高油及耐密植油菜新品种,为高油高产优质油菜品种的应用提供种质选择。【方法】贵州省油菜研究所利用隐性核不育两系D418AB作母本,以恢复系YD84R作父本,于2023年育成高油分双低杂交油菜新品种宝油187(农业农村部登记编号:GPD油菜〔2023〕520162)。【结果】宝油187在长江上游区域试验中平均产量207.7 kg/667m^(2),比对照(蓉油18)增产4.09%;平均产油量104.6 kg/667m^(2),比对照增产22.18%;平均生育期215 d。在长江中游区域试验中宝油187平均产量210.3 kg/667m^(2),比对照(华油杂50)增产7.32%;平均产油量107.6 kg/667m^(2),比对照增产10.29%;平均生育期215 d。经农业农村部油料及制品质量监督检验测试中心检测,宝油187芥酸为0.05%,硫甙为20.45μmol/g饼,含油量为51.94%。【结论】宝油187中抗菌核病,丰产性好,耐密植,高油分,适宜在贵州、四川、重庆、湖南、湖北和江西等冬油菜区推广应用。

关键词：甘蓝型油菜宝油187 高油分新品种隐性核不育芥酸硫甙

Classification with ensembles and case study on functional magnetic resonance imaging

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Digital Communications and Networks 2022年第1期8卷 80-86页

作者： Adnan OM.Abuassba Zhang dezheng Hazrat Ali Fan Zhang Khan Ali Department of Computer Science Arab Open University-PalestineRamallahPalestine Department of Computer Science and Communication Engineering University of Science and Technology BeijingChina and Beijing Key Laboratory of Knowledge Engineering for Materials ScienceBeijing100083China Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabadPakistan

The ensemble is a technique that strategically combines basic models to achieve better accuracy ***,combination methods,and selection topology are the main factors determining ensemble ***,it is a challenging task to design an efficient ensemble *** though numerous paradigms have been proposed to classify ensemble schemes,there is still much room for *** paper proposes a general framework for creating ensembles in the context of ***,the ensemble framework consists of four stages:objectives,data preparing,model training,and model *** is comprehensive to design diverse *** proposed ensemble approach can be used for a wide variety of machine learning *** validate our approach on real-world *** experimental results show the efficiency of the proposed approach.

关键词： Classification Ensemble learning Extreme learning machine

GP‐FMLNet:A feature matrix learning network enhanced by glyph and phonetic information for Chinese sentiment analysis

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 960-972页

作者： Jing Li dezheng Zhang Yonghong Xie Aziguli Wulamu Yao Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijingChina Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology BeijingBeijingChina University of Alberta EdmontonAlbertaCanada

Sentiment analysis is a fine‐grained analysis task that aims to identify the sentiment polarity of a specified *** methods in Chinese sentiment analysis tasks only consider sentiment features from a single pole and scale and thus cannot fully exploit and utilise sentiment feature information,making their performance less than *** resolve the problem,the authors propose a new method,GP‐FMLNet,that integrates both glyph and phonetic information and design a novel feature matrix learning process for phonetic features with which to model words that have the same pinyin information but different glyph *** method solves the problem of misspelling words influencing sentiment polarity prediction ***,the authors iteratively mine character,glyph,and pinyin features from the input comments ***,the authors use soft attention and matrix compound modules to model the phonetic features,which empowers their model to keep on zeroing in on the dynamic‐setting words in various positions and to dispense with the impacts of the deceptive‐setting ***-periments on six public datasets prove that the proposed model fully utilises the glyph and phonetic information and improves on the performance of existing Chinese senti-ment analysis algorithms.

关键词： aspect‐level sentiment analysis deep learning feature extraction glyph and phonetic feature matrix compound learning

Relationships between In SAR Seismic Deformation and Fault Motion Sense,Fault Strike,and Ascending/Descending Modes

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Acta Geologica Sinica(English Edition) 2017年第1期91卷 93-108页

作者： QU Chunyan SHAN Xinjian ZHAO dezheng ZHANG Guohong SONG Xiaogang Key Laboratory of Earthquake Dynamics Institute of Geology China Earthquake Administration Beijing 100029

Based on the working principle of satellite radars, the earthquake deformation field measured by interferometric synthetic aperture（InSAR） is the projection of ground displacement associated with the seismogenic fault in the line of sight（LOS） of the satellite. However, LOS projections are complex, and are not only related to the ascending/descending modes and incidence angles of SAR data, but also related to the strike and motion senses of the fault. Even for the same earthquake, the LOS deformation derived from different ascending/descending data can be almost identical in one case, but quite different in another case, which makes the interpretation of InSAR seismic deformation and its comparison with field observations difficult. In this study, we undertook a quantitative analysis of the relationships between LOS observation sensitivity of InSAR and fault strike, fault motion sense, and ascending/descending modes, as well as 3D deformation fields. We studied the features and differences of the LOS deformation fields in different types of earthquakes using ascending/descending modes, with a particularly detailed analysis of the relations for a strikeslip type of earthquake. We also summarized the characteristics of LOS deformation fields of faults with different strikes and optimal observational data modes. Taking the strike-slip Yushu earthquake and the normal Gaize event as examples, we used SAR data of the ascending/descending modes to verify the results of quantitative calculations. These analyses will not only provide a more reasonable interpretation of InSAR seismic deformation fields and but also help understand the differences of seismic deformation fields revealed by data with different observational modes, therefore promoting the application of InSAR technology in seismology.

关键词： InSAR fault earthquake deformation ascending/descending modes

Mn incorporated RuO_(2) nanocrystals as an efficient and stable bifunctional electrocatalyst for oxygen evolution reaction and hydrogen evolution reaction in acid and alkaline

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Chinese Chemical Letters 2024年第10期35卷 194-200页

作者： Jing Cao dezheng Zhang Bianqing Ren Ping Song Weilin Xu State Key Laboratory of Electroanalytical Chemistry Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022China University of Science and Technology of China Hefei 230026China

The development of efficient and stable bifunctional overall water-splitting is a crucial goal for clean and renewable energy,which is a challenging ***,we report an Mn-incorporated RuO_(2)(MnRuO_(2))catalyst for highly efficient electrocatalytic oxygen evolution reaction(OER)and hydrogen evolution reaction(HER)in acid and alkaline *** from a more electrochemical active area with the incorporation of Mn,the Mn-RuO_(2)required an overpotential of 200 mV to attain a current density of 10 mA/cm^(2)for OER in *** result indicates that the doping of Mn into RuO_(2)can enhance the OER *** acidic overall water-splitting electrolyzer with good stability constructed by bifunctional Mn-RuO_(2)only requires a cell voltage of 1.50 V to afford 10 m A/cm^(2)and can operate stably for 50 h at50 mA/cm^(2),which is better than the state-of-the-art Ru-based ***,the Mn-Ru O_(2)exhibits excellent HER and OER activity in alkaline media,and it shows superior activity and durability for overall water-splitting,only needing a cell voltage of 1.49 V to attain 10 m A/cm^(2).The present work provides an efficient approach to designing and constructing efficient Ru-based electrocatalysts for overall water-splitting.

关键词： RuO_(2)-based solid solution electrocatalysts Oxygenevolution reaction Hydrogen evolution reaction Overall watersplitting Acid andalkaline

Auxiliary Diagnosis Based on the Knowledge Graph of TCM Syndrome

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Computers, Materials & Continua 2020年第10期65卷 481-494页

作者： Yonghong Xie Liangyuan Hu Xingxing Chen Jim Feng dezheng Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Amphenol Global Interconnect Systems San JoseCA 95131USA

As one of the most valuable assets in China,traditional medicine has a long history and contains pieces of *** diagnosis and treatment of Traditional Chinese Medicine(TCM)has benefited from the natural language processing *** paper proposes a knowledge-based syndrome reasoning method in computer-assisted *** method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning *** to this reasoning path,we could infer the path from the symptoms to the syndrome and get all possibilities via the relationship between symptoms and ***,this study applies the Term Frequency-Inverse Document Frequency(TF-IDF)idea to the computer-assisted diagnosis of TCM for the score of syndrome ***,combined with symptoms,syndrome,and causes,the disease could be confirmed comprehensively by voting,and the experiment shows that the system can help doctors and families to disease diagnosis effectively.

关键词： Knowledge graph reinforcement learning auxiliary diagnosis inference path

A Heterogeneous Ensemble of Extreme Learning Machines with Correntropy and Negative Correlation

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Tsinghua Science and Technology 2017年第6期22卷 691-701页

作者： Adnan O.M.Abuassba Yao Zhang Xiong Luo dezheng Zhang Wulamu Aziguli School of Computer and Communication Engineering University of Science and Technology Beijing(USTB)Beijing 100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083China School of Engineering New York UniversityBrooklynNY 11201USA

The Extreme Learning Machine（ELM） is an effective learning algorithm for a Single-Layer Feedforward Network（SLFN）. It performs well in managing some problems due to its fast learning speed. However, in practical applications, its performance might be affected by the noise in the training data. To tackle the noise issue, we propose a novel heterogeneous ensemble of ELMs in this article. Specifically, the correntropy is used to achieve insensitive performance to outliers, while implementing Negative Correlation Learning（NCL） to enhance diversity among the ensemble. The proposed Heterogeneous Ensemble of ELMs（HE2 LM） for classification has different ELM algorithms including the Regularized ELM（RELM）, the Kernel ELM（KELM）, and the L2-norm-optimized ELM（ELML2）. The ensemble is constructed by training a randomly selected ELM classifier on a subset of the training data selected through random resampling. Then, the class label of unseen data is predicted using a maximum weighted sum approach. After splitting the training data into subsets, the proposed HE2 LM is tested through classification and regression tasks on real-world benchmark datasets and synthetic datasets. Hence, the simulation results show that compared with other algorithms, our proposed method can achieve higher prediction accuracy, better generalization, and less sensitivity to outliers.

关键词： Extreme Learning Machine(ELM) ensemble classification correntropy negative correlation

Recent advances on catalysts for preferential oxidation of CO

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Nano Research 2023年第4期16卷 4399-4410页

作者： Huimin Liu dezheng Li Jiawen Guo Yuqiao Li Aidi Liu Yitong Bai Dehua He School of Chemical and Environmental Engineering Liaoning University of TechnologyJinzhou 121001China Innovative Catalysis Program Key Lab of Organic Optoelectronics&Molecular Engineering of Ministry of EducationDepartment of ChemistryTsinghua UniversityBeijing 100084China

The trace amount of CO in H2-rich gas poisons Pt electrode when it is adopted as feedstock for proton-exchange-membrane fuel *** oxidation of CO(PROX)is a promising approach to selectively oxidize the trace amount of CO while keeping H2 *** plays important roles in *** date,enormous catalysts have been developed for *** the catalysts developed for PROX and unveiling the reaction mechanism could definitely advance this research ***,in this review,according to the nature of the active sites on the catalysts,we classify the catalysts into group VIII metal-based catalyst,group IB metal-based catalysts,group VIII-group IB bimetallic catalysts,transitional metal oxide catalysts as well as others,describe the progress of the catalysts in PROX in the latest five years,and extract the underlying reaction mechanism,with the aim to provide guidance for the rational design of efficient catalysts in the future.

关键词： preferential oxidation of CO group VIII metal-based catalysts group IB metal-based catalysts bimetallic catalysts mechanism exploration

Heterostructured Pt-Ni_(3)Mo_(3)N formed via ammonia-containing polyoxometalates for highly efficient electrocatalytic hydrogen evolution in acid medium

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Journal of Energy Chemistry 2024年第5期92卷 698-704页

作者： Bianqing Ren Xue Gong Jing Cao dezheng Zhang Zizhun Wang Ping Song Ce Han Weilin Xu State Key Laboratory of Electroanalytical Chemistry Jilin Province Key Laboratory of Low Carbon Chemical PowerChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022JilinChina School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefei 230026AnhuiChina Key Laboratory of Automobile Materials MOE School of Materials Science&EngineeringJilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy MaterialsElectron Microscopy Centerand International Center of Future ScienceJilin UniversityChangchun 130012JilinChina

Constructing heterostructured nanohybrid is considered as a prominent route to fabricate alternative electrocatalysts to commercial Pt/C for hydrogen evolution reaction(HER).In this work,(NH_(4))_(4)[NiH_(6)Mo_(6)O_(4)]·5H_(2)O polyoxometalates(NiMo_(6))are adopted as the cluster precursors for simple fabrication of heterostructured Pt-Ni_(3)Mo_(3)N nanohybrids supported by carbon black(Pt-Ni_(3)Mo_(3)N/C)without using additional N *** improved porosity and enhanced electronic interaction of Pt-Ni_(3)Mo_(3)N/C should be attributed to the integration of Pt with NiMo_(6),which favors the mass transport,promotes the formation of exposed catalytic sites,and benefits the regulation of intrinsic ***,the as-obtained Pt-Ni_(3)Mo_(3)N/C exhibits impressive and durable HER performance as indicated by the low overpotential of 13.7 mV at the current density of 10 mA cm^(-2) and the stable overpotential during continuous working at 100 mA cm^(-2) for 100 *** work provides significant insights for the synthesis of new highly active heterostructured electrocatalysts for renewable energy devices.

关键词： Polyoxometalates Cluster precursors Heterostructured nanohybrids Hydrogen evolution reaction Electrocatalysis