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Phosphorus fertilization alters complexity of paddy soil dissolved organic matter

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Journal of Integrative Agriculture 2020年第9期19卷 2301-2312页

作者： ZHANG Zhi-jian wang xian-zhe LIANG Lu-yi HUANG En TAO Xing-hua College of Environmental and Resource Science Zhejiang UniversityHangzhou 310058P.R.China China Academy of West Region Development Zhejiang UniversityHangzhou 310058P.R.China Hangzhou Gusheng Agricultural Technology Company Limited Hangzhou 311108P.R.China

The structural complexity of soil dissolved organic matter(DOM)may reflect soil biogeochemical processes due to its spectral ***,the features of DOM structural complexity in paddy soil amended with long-term chemical P fertilization are still unclear,which may limit understanding of nutrient-related soil C *** collected soil samples from field experiments receiving application of 0,30,60,and 90 kg P ha–1 yr–1 to assess the effect of exogenous P on the complexity of soil DOM ***-dimensional excitation-emission matrix fluorescence analysis and enzymatic activity assay were used to determine the features of soil DOM molecular structure and the associated microbial *** results showed that P input increased the biodegradability of DOM,indicating by the increased lower molecular weight components and decreased humic degree in the DOM.P input also reduced the structural complexity of DOM with blue shifts of fluorescent *** fluorescence index andβ/αindex of DOM increased with increasing P application by 4–5%and 3–11%,respectively,while humification index decreased by 8–13%.The P input increased the abundance of bacteria and fungi by 34–167%and 159–964%,respectively,while 29–54%increments were found for theβ-1,4-glucosidase *** results implicated that P fertilization accelerated the soil DOM cycle,although the structural complexity of DOM declined,which potentially benefits soil C sequestration in paddy fields and may be a C sequestration mechanism in the P-dependent paddy.

关键词： soil carbon fertilization fluorescence humification agroecosystem

Hyperspectral image super resolution using deep internal and self-supervised learning

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 128-141页

作者： zhe Liu xian-Hua Han Graduate School of Science and Technology for Innovation Yamaguchi UniversityYamaguchiJapan Graduate School of Artificial Intelligence and Science Rikkyo UniversityTokyoJapan

By automatically learning the priors embedded in images with powerful modelling ca-pabilities,deep learning-based algorithms have recently made considerable progress in reconstructing the high-resolution hyperspectral(HR-HS)*** previously collected large-amount of external data,these methods are intuitively realised under the full supervision of the ground-truth ***,the database construction in merging the low-resolution(LR)HS(LR-HS)and HR multispectral(MS)or RGB image research paradigm,commonly named as HSI SR,requires collecting corresponding training triplets:HR-MS(RGB),LR-HS and HR-HS image simultaneously,and often faces dif-ficulties in *** learned models with the training datasets collected simultaneously under controlled conditions may significantly degrade the HSI super-resolved perfor-mance to the real images captured under diverse *** handle the above-mentioned limitations,the authors propose to leverage the deep internal and self-supervised learning to solve the HSI SR *** authors advocate that it is possible to train a specific CNN model at test time,called as deep internal learning(DIL),by on-line preparing the training triplet samples from the observed LR-HS/HR-MS(or RGB)images and the down-sampled LR-HS ***,the number of the training triplets extracted solely from the transformed data of the observation itself is extremely few particularly for the HSI SR tasks with large spatial upscale factors,which would result in limited reconstruction *** solve this problem,the authors further exploit deep self-supervised learning(DSL)by considering the observations as the unlabelled training ***,the degradation modules inside the network were elaborated to realise the spatial and spectral down-sampling procedures for transforming the generated HR-HS estimation to the high-resolution RGB/LR-HS approximation,and then the reconstruction errors of the observations were formulated for mea

关键词： computer vision deep learning deep neural networks hyperspectral image enhancement

Microstructure Evolution and Nanomechanical Behavior of Micro-Area in Molten Pool of Selective Laser Melting(CoCrNi)_(82)Al_(9)Ti_(9)High-Entropy Alloy

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Acta Metallurgica Sinica(English Letters) 2024年第6期37卷 1019-1033页

作者： Hong-Wei Zhang Li-Wei Lan zhe-Yu Yang Chang-Chun Li Wen-xian wang College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan030024China Ministry of Education Key Laboratory of Interface Science and Engineering in Advanced MaterialsTaiyuan University of TechnologyTaiyuan030024China Shanxi-zhejiang University New Materials and Chemical Research Institute Taiyuan030032China

In this work,the phase evolution mechanism and nanomechanical properties of(CoCrNi))(82)Al_(9)Ti_(9)high-entropy alloy(HEA)prepared by selective laser melting(SLM)in the molten pool were *** HEA contains multiple primary elements and undergoes high-temperature gradient and rapid cooling during *** leads to significant inhomogeneity of nano-scale microstructure characteristics and instability of *** optimizing process parameters,the microstructure evolution at the optimal parameter volume energy density of 440 J/mm^(3)was studied.A phase transition from BCC to FCC occurred in the melt *** the micro-area of the melt pool results in a temperature rise and the combustion-induced loss of Al ***,the Ni element content increases significantly outside the melt *** process enhances the phase stability of FCC and facilitates phase ***,rapid cooling leads to the formation of distinctive ultrafine equiaxial crystals inside the melt pool,accompanied by the generation of intracrystalline needle-like nano-scale *** the melt pool,the accumulation of energy results in the formation of coarse ***,the nano-hardness inside the molten pool is remarkably high at 11.79 GPa,while the outside the molten pool is reduced to 9.58 *** the fracture toughness outside the melt pool also *** with inside the melt pool,the residual stress outside the melt pool changed from compressive to tensile stress and decreased from 603.28 to 322.84 MPa.

关键词： High-entropy alloys Selective laser melting Microstructure evolution Nanoindentation

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混合式教学策略在有机化学课程教学中的应用

白城师范学院学报 2024年第5期38卷 120-123页

作者：李亮亮于海丰刘宾宾邱景波王先哲白城师范学院化学学院吉林白城137000

高校教师如何进行教学改革提高学生学习效率、综合能力以及核心素养已成为目前教育转型亟待解决的问题之一.学生专业能力的培养、高阶思维的建立、学习内驱力的激发是有机化学课程教学改革的重要内容.文章以此为切入点阐述了混合式教学... 详细信息

高校教师如何进行教学改革提高学生学习效率、综合能力以及核心素养已成为目前教育转型亟待解决的问题之一.学生专业能力的培养、高阶思维的建立、学习内驱力的激发是有机化学课程教学改革的重要内容.文章以此为切入点阐述了混合式教学在有机化学课程教学中的作用,分析了有机化学课程教学存在的问题,在此基础上,从资源与案例辅助混合式教学、三阶梯教学方法的应用以及考核评价方式多元化三个方面,探讨了混合式教学的实施策略,以期提高有机化学课程的教学质量.

关键词：混合式教学教学改革有机化学

Track correlation algorithm based on CNN-LSTM for swarm targets

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Journal of Systems Engineering and Electronics 2024年第2期35卷 417-429页

作者： CHEN Jinyang wang Xuhua CHEN xian Research Institute for National Defense Engineering Academy of Military SciencesLuoyang 471023China Information Engineering University Zhengzhou 450001China School of Computer Science and Technology Xidian UniversityXi’an 710071China

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for *** this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm ***, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

关键词： track correlation correlation accuracy rate swarm target convolutional neural network(CNN) long short-term memory(LSTM)neural network

Optimal retrofitting scenarios of multi-objective energy-efficient historic building under different national goals integrating energy simulation,reduced order modelling and NSGA-II algorithm

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Building Simulation 2024年第6期17卷 933-954页

作者： Hailu Wei Yuanhao Jiao zhe wang Wei wang Tong Zhang School of Architecture Southeast UniversityNanjingJiangsu Province210096China Key Laboratory of Urban and Architectural Heritage Conservation(Southeast University) Ministry of EducationNanjingChina Department of Civil and Environmental Engineering The Hong Kong University of Science and TechnologyHong KongChina HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute FutianShenzhenChina

Retrofitting a historic building under different national goals involves multiple objectives,constraints,and numerous potential measures and packages,therefore it is time-consuming and challenging during the early design *** study introduces a systematic retrofitting approach that incorporates standard measures for the building envelope(walls,windows,roof),as well as the heating,cooling,and lighting *** retrofit objectives are delineated based on prevailing Chinese *** retrofit measures function as genes to optimize energy-savings,carbon emissions,and net present value(NPV)by employing a log-additive decomposition approach through energy simulation techniques and NSGA-II,yielding 185,163,and 8 ***,a weighted sum method is proposed to derive optimal solutions across multiple *** framework is applied to a courtyard building in Nanjing,China,and the outcomes of the implementation are scrutinized to ascertain the optimal retrofit package under various *** this retrofit,energy consumption can be diminished by up to 63.62%,resulting in an NPV growth of 151.84%,and maximum rate of 60.48%carbon *** three result values not only indicate that the optimal values are achieved in these three aspects of energy saving,carbon reduction and economy,but also show the possibility of possible equilibrium in this multi-objective optimization *** framework proposed in this study effectively addresses the multi-objective optimization challenge in building renovation by employing a reliable optimization algorithm with a computationally efficient reduced-order *** provides valuable insights and recommendations for optimizing energy retrofit strategies and meeting various performance objectives.

关键词： historic building energy-efficient retrofitting building energy simulation log-additive decomposition approach NSGA-II

Hemoglobin loss method calculates blood loss during pancreaticoduodenectomy and predicts bleeding-related risk factors

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World Journal of Gastrointestinal Surgery 2024年第2期16卷 419-428页

作者： Chao Yu Yi-Min Lin Guo-zhe xian Department of Hepatobiliary Surgery Shandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinan 250021Shandong ProvinceChina

BACKGROUND The common clinical method to evaluate blood loss during pancreaticoduoden-ectomy(PD)is visual inspection,but most scholars believe that this method is extremely subjective and ***,there is no accurate,objective me-thod to evaluate the amount of blood loss in PD *** retrospectively analyzed the clinical data of 341 patients who underwent PD in Shandong Provincial Hospital from March 2017 to February *** to different surgical methods,they were divided into an open PD(OPD)group and a laparoscopic PD(LPD)*** differences and correlations between the in-traoperative estimation of blood loss(IEBL)obtained by visual inspection and the intraoperative calculation of blood loss(ICBL)obtained using the Hb loss method were ***,IEBL and perioperative calculation of blood loss(PCBL)were compared between the two groups,and single-factor regression analysis was *** There was no statistically significant difference in the preoperative general patient information between the two groups(P>0.05).PD had an ICBL of 743.2(393.0,1173.1)mL and an IEBL of 100.0(50.0,300.0)mL(P200μmol/L(95%CI:7.09-644.26;P=0.045)were independent risk factors for *** ICBLs of the LPD group and OPD group were 767.7(435.4,1249.0)mL and 663.8(347.7,1138.2)mL,respectively(P>0.05).The IEBL of the LPD group 200.0(50.0,200.0)mL was slightly greater than that of the OPD group 100.0(50.0,300.0)mL(P>0.05).PCBL was greater in the LPD group than the OPD group[1061.6(612.3,1632.3)mL vs 806.1(375.9,1347.6)mL](P<0.05).CONCLUSION The ICBL in patients who underwent PD was greater than

关键词： Pancreaticoduodenectomy Hemoglobin loss Calculated blood loss Estimated blood loss

Full lifetime demonstration of a Micro-Cathode-Arc thruster evolution characteristics

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Chinese Journal of Aeronautics 2024年第6期37卷 38-49页

作者： zhe ZHANG Zijing ZHAO xiangyang LIU Ningfei wang School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China

Ground lifetime test is the most crucial experiment to assess the performance,*** flight qualification of electric propulsion,and it can bring new insights for understanding the operation *** work demonstrates a full lifetime test of 140000 cycles on a Micro-Cathode-Arc Thruster(μCAT)with 160μs charging time and 86 mJ charging energy.A four-probe resistivity measurement method is utilized to investigate variations in the conductive film thickness and resistivity throughout the thruster *** film parameters show that the lifetime of theμCAT can be divided into three *** the initial stage,the film thickness decreases by 1.2μm and the resistivity increases significantly due to the high discharge intensity and intense film ablation;In the steady stage,the change of the film thickness is within 5%,and the resistivity of the film increases slowly from 0.050Ω·mm to 0.223Ω·*** the end stage,the resistivity exponentially increases from 0.223Ω·mm to 1.176Ω·mm,with the increase accounting for 81%,ultimately resulting in the failure of the thruster open ***,the evolution of discharge parameters,and the variation of plume parameters are measured throughout the *** discharge characteristics also show significant differences in the duration of voltage and current in these three *** results of plume shape and plasma parameters are also well con-sistent with the discharge parameters and film *** results suggest that,for evaluating the steady stage lifetime of thrusters,the film thickness is the best indicator compared to the variations in resistivity and voltage-current *** the end stage,the plasma plume *** duration,and plume parameters can conveniently and clearly characterize the thruster failures and irregularity.

关键词： Electric propulsion Lifetime test Micro-Cathode-Arc Thruster(uCAT) Conductive film Discharge characteristics Plasma parameters

Cognitive Navigation for Intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui zhe Liu Hesheng wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation