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Nutrient transport following water transfer through the world's largest water diversion channel

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Journal of Environmental Sciences 2024年第1期135卷 703-714页

作者： Yuanhui Cheng Hong Zhang wei Yin State Key Laboratory of Environmental Aquatic Chemistry Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085 China Changjiang Water Resources Protection Institute Wuhan 430051China University of Chinese Academy of Sciences Beijing 100049China

Nutrient levels in the artificial channel constructed for the Middle Route Project are significant indicators of water quality safety and aquatic ecological integrity for this large,interbasin ***,the distribution and transport of nutrients along the channel were poorly *** on a time-series dataset as well as mass balance and material flow analysis methods,the water and nutrient transport fluxes in the Middle Route of the South-to-North Water Diversion Project were identified in this *** results indicate that the nutrient concentrations varied considerably with time,but there was no significant difference among the 30 stations of the main *** temperature difference was the major factor in the large fluctuations of water quality indicators over *** nutrient loadings varied with the water volume outputs from the main channel to the waterreceiving *** deposition was an important source of nutrients in the main channel,accounting for 9.13%,20.6%,and 0.635%of the nitrogen,phosphorus,and sulfur input from the Danjiangkou Reservoir,*** 2021,a net accumulation of 988 tons of N,29 tons of P,and 2,540 tons of S,respectively,were present in the main *** increase of these external and internal nutrient loadings would cause water quality fluctuation and deterioration in some local sections of the main *** study quantified the spatial and temporal patterns of nutrient transport in the Middle Route and revealed the ecological effects on the aquatic environment,assisting authorities on the project to develop effective water conservation strategies.

关键词： Nutrient transport Spatiotemporal patterns The Middle Route The South-to-North Diversion Project Hydro-ecological effects Water-receiving cities

An extended numerical model of the first exothermic peak for three dimensional printed cement-based materials

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Frontiers of Structural and Civil Engineering 2024年第1期18卷 80-88页

作者： wei JIANG Wenqian LI Xi CHEN School of Materials Science and Engineering Tongji UniversityShanghai 200092China School of Civil Engineering Tongji UniversityShanghai 200092China

The first exothermic peak of cement-based material occurs a few minutes after mixing,and the properties of three dimensional(3D)printed concrete,such as setting time,are very sensitive to *** this background,based on the classical Park cement exothermic model of hydration,we propose and construct a numerical model of the first exothermic peak,taking into account the proportions of C_(3)S,C_(3)A and quicklime in *** calculated parameters are calibrated by means of relevant published exothermic test *** is found that this developed model offers a good simulation of the first exothermic peak of hydration for C_(3)S and C_(3)A proportions from 0 to 100% of cement clinker and reflects the effect of quicklime content at 8%-10%.The unique value of this research is provision of an important computational tool for applications that are sensitive to the first exothermic peak of hydration,such as 3D printing.

关键词： 3D printed cement-based materials cement hydration the first exothermic peak liquid quick-setting agent numerical model

Theoretical study on the stability of nanobubbles and its verification in molecular dynamics simulation

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Particuology 2024年第4期87卷 99-105页

作者： Sheng Mi Chaofeng Hou wei Ge School of Chemical Engineering and Technology Tianjin UniversityTianjin300072China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing.100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China

The stability of vapor nanobubbles in bulk liquid was investigated theoretically and the critical bubble size was derived from macroscale thermodynamic equations,below which the system destabilizes with sharp drop in *** critical size was quantitatively verified in molecular dynamic simulation using the Lennard-Jones model of argon,where stronger attraction between the molecules at lower density is found to contribute most to the drop of system pressure and,as the Laplace pressure on the curved bubble interface fails to balance the pressure difference across the interface,the bubbles become *** theoretical model could be extended to other systems where reliable equations of state and interfacial tension are available.

关键词： Nanobubble Stability Phase diagram Critical size

The First Five Years of a Phase Theory for Complex Systems and Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1728-1743页

作者： Dan Wang wei Chen Li Qiu Division of Decision and Control Systems KTH Royal Institute of TechnologyStockholm 10044Sweden Department of Mechanics and Engineering Science&the State Key Laboratory for Turbulence and Complex Systems Peking UniversityBeijing 100871China Hong Kong University of Science and Technology Hong KongChinaand also with the Southern University of Science and TechnologyShenzhen 518055China

In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase *** the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.

关键词： Consensus and synchronization matrix phases multi-agent systems phase theory sectored real lemma small phase theorem.

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

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Advances in Atmospheric Sciences 2024年第7期41卷 1326-1341页

作者： Lu LI Yongjiu DAI Zhongwang wei wei SHANGGUAN Nan wei Yonggen ZHANG Qingliang LI Xian-Xiang LI School of Atmospheric Sciences Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Guangzhou 510275China Institute of Surface-Earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China College of Computer Science and Technology Changchun Normal UniversityChangchun 130123China

Accurate soil moisture(SM)prediction is critical for understanding hydrological ***-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface *** addition to PB models,deep learning(DL)models have been widely used in SM predictions ***,few pure DL models have notably high success rates due to lacking physical ***,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM *** this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM *** performances of the proposed hybrid models were investigated and compared with two existing hybrid *** results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid ***,the ensemble model performed best among all hybrid models at all forecast time scales and different soil *** is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day *** findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

关键词： soil moisture forecasting hybrid model deep learning ConvLSTM attention mechanism

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

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Journal of Systems Engineering and Electronics 2024年第2期35卷 361-373页

作者： CHEN Chen QUAN wei SHAO Zhuang School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced ***, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

关键词： target threat assessment gated recurrent unit(GRU) self-attention(SA) fractional Fourier transform(FRFT)

Proximal Femur Bionic Nail (PFBN): A Panacea for Unstable Intertrochanteric Femur Fracture

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Engineering 2024年第6期37卷 152-158页

作者： Kaixuan Zhang wei Chen Yingze Zhang School of Medicine Nankai UniversityTianjin 300071China Department of Orthopedic Surgery of Hebei Province The Third Hospital of Hebei Medical UniversityShijiazhuang 050051China Key Laboratory of Biomechanics of Hebei Province Orthopaedic Research Institute of Hebei ProvinceShijiazhuang 050051China National Health Commission(NHC)Key Laboratory of Intelligent Orthopeadic Equipment The Third Hospital of Hebei Medical UniversityShijiazhuang 050051China Chinese Academy of Engineering Beijing 100088China

With the aging population,intertrochanteric femur fracture in the elderly has become one of the most serious public health issues and a hot topic of research in trauma *** to the limitations of internal fixation techniques and the insufficient mechanical design of nails,the occurrence of complications delays patient recovery after surgical *** of a proximal femur bionic nail(PFBN)based on Zhang’s N triangle theory provides triangular supporting fixation,which dramatically decreases the occurrence of complications and has been widely used for clinical treatment of unstable intertrochanteric femur fracture *** this work,we developed an equivalent biomechanical model to analyze improvement in bone remodeling of unstable intertrochanteric femur fracture through PFBN *** results show that compared with proximal femoral nail antirotation(PFNA)and InterTan,PFBN can dramatically decrease the maximum strain in the proximal *** on Frost’s mechanostat theory,the local mechanical environment in the proximal femur can be regulated into the medium overload region by using a PFBN,which may render the proximal femur in a state of physiological overload,favoring post-operative recovery of intertrochanteric femur fracture in the *** work shows that PFBN may constitute a panacea for unstable intertrochanteric femur fracture and provides insights into improving methods of internal fixation.

关键词： Intertrochanteric femur fracture Internal fixation Proximal femur bionic nail(PFBN) Biomechanics Bone remodeling

Transient Response and Ionic Dynamics in Organic Electrochemical Transistors

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Nano-Micro Letters 2024年第11期16卷 191-223页

作者： Chao Zhao Jintao Yang wei Ma State Key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong UniversityXi′an 710049People’s Republic of China

The rapid development of organic electrochemical transistors(OECTs)has ushered in a new era in organic electronics,distinguishing itself through its application in a variety of domains,from high-speed logic circuits to sensitive biosensors,and neuromorphic devices like artificial synapses and organic electrochemical random-access *** recent strides in enhancing OECT performance,driven by the demand for superior transient response capabilities,a comprehensive understanding of the complex interplay between charge and ion transport,alongside electron–ion interactions,as well as the optimization strategies,remains *** review aims to bridge this gap by providing a systematic overview on the fundamental working principles of OECT transient responses,emphasizing advancements in device physics and optimization *** review the critical aspect of transient ion dynamics in both volatile and non-volatile applications,as well as the impact of materials,morphology,device structure strategies on optimizing transient *** paper not only offers a detailed overview of the current state of the art,but also identifies promising avenues for future research,aiming to drive future performance advancements in diversified applications.

关键词： Organic electrochemical transistors Transient response Ion dynamics Electronic dynamics Volatility and non-volatility

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

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Defence Technology（防务技术） 2024年第2期32卷 271-284页

作者： Yiwen Zhang wei Zheng Zongqiang Liu Qian Xuesen Laboratory of Space Technology China Academy of Space TechnologyBeijing 100094China China Academy of Aerospace Science and Innovation Beijing 100176China State Key Laboratory of Space-Ground Integrated Information Technology Beijing Institute of Satellite Information EngineeringBeijing 100194China

Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater *** present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically ***,GNSS-R satellite constellations that meet the global altimetry needs to be ***,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric ***,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is ***,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is ***,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.

关键词： GNSS-R satellite constellations Sea surface altimetric precision Underwater navigation Multilayer feedforward neural network