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Spatiotemporal Variability of Precipitation Concentration and Its Rate of Contribution to Meteorological Drought in Mainland China

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Journal of Hydrologic engineering 2025年第4期30卷

作者： Xu, Pengcheng Wang, Dong Wang, Yuankun Ju, Xiaopei Singh, Vijay P. College of Hydraulic Science and Engineering Yangzhou Univ. Yangzhou225009 China Key Laboratory of Surficial Geochemistry Ministry of Education Dept. of Hydrosciences School of Earth Sciences and Engineering State Key Laboratory of Pollution Control and Resource Reuse Nanjing Univ. Nanjing210023 China School of Water Resources and Hydropower Engineering North China Electric Power Univ. Beijing102206 China Dept. of Biological and Agricultural Engineering Zachry Dept. of Civil & Environmental Engineering Texas A & M Univ. College StationTX77843 United States National Water and Energy Center United Arab Emirates Univ. Al Ain United Arab Emirates

Climate change has increased the frequency and intensity of hydrometeorological extreme events all over the world. Uneven precipitation patterns, both spatially and temporally, have triggered more frequent and devastating droughts and floods. To assess these variations and their impact on drought, this study analyzed grid-based meteorological data to calculate the concentration index (CI) and precipitation concentration index (PCI) in mainland China from 1961 to 2022. Monthly temperature and precipitation data were also used to derive the standardized precipitation evapotranspiration index (SPEI) using Hargreaves equation. The nonparametric Pettitt's test was investigated to identify the turn and change points for CI and PCI across mainland China. Sen's slope from the Mann-Kendall method calculated trends before and after these turn points (YTPs) and the overall drought trend. A structural equation model (SEM) provided qualitative and quantitative evaluations of how the annual PCI contributes to annual drought severity. High CI values are predominantly observed in the southern and northeastern parts of the Pearl River Basin (PRB), as well as in the central areas of the Yellow River Basin (YRB), Haihe River Basin (HaRB), and Huaihe River Basin (HuRB). The SEM approach enables the study to disentangle and quantify the direct and indirect contributions of precipitation concentration to drought, providing a deeper understanding of how uneven rainfall distribution influences annual drought severity across different regions. Finally, the study provides region-specific findings, identifying key areas where PCI is the dominant factor influencing drought variability, with contribution rates exceeding 50% in over half of mainland China. These insights not only enhance the understanding of the linkage between precipitation distribution and drought but also offer actionable guidance for water resource management and drought mitigation strategies. © 2025 American Society of Civi

关键词： Drought

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A Survey on Quantum Cryptography

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Chinese Journal of Electronics 2018年第2期27卷 223-228页

作者： LI Jian LI Na ZHANG Yu WEN Shuang DU Wei CHEN Wei MA Wenping School of Computer Science Beijing University of Posts and Telecommunications Jilin Medical University School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Department of Optics and Optical Engineering University of Science and Technology of China School of Telecommunications Engineering Xidian University

Quantum cryptography(QC) as an important technology to protect the security of the future network communication, has gained extensive attention from both academia and industry in recent years. This paper provides a concise up-to-date review of QC, including Quantum key distribution(QKD), Quantum authentication, Quantum public-key cryptography(QPKC), and so on. Our aim is to pave a comprehensive and solid starting ground for interested readers. We firstly clarify the definition of QC. Secondly, we present the current understanding of QC from different levels, including the basic knowledge of quantum information processing, QC protocols and the attacks in QC. Finally, we discuss the challenges and opportunities in this hopeful field.

关键词： Quantum cryptography Quantum key distribution Quantum authentication Quantum publickey cryptography

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Sub-Picosecond-Level Laser-Based Underwater Transfer of Radio Frequency with Optical Phase Compensation

Sub-Picosecond-Level Laser-Based Underwater Transfer of Radi...

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International Conference on Communication Technology (ICCT)

作者： Bisong Pan Haopengyu Li Dong Hou Jianye Zhao School of Automation Engineering Univ. of Electronic Science and Technology of China Chengdu China College of Elec. Engineering and Computer Science Peking University Beijing China

ISBN: (数字)9781728181417

ISBN: (纸本)9781728181424

We demonstrated a sub-picosecond laser-based underwater frequency transfer with an optical phase compensation. With this transfer technique, a highly-stable 500 MHz radio-frequency (RF) signal was disseminated over a 5-m underwater link for 5000 s, and the characteristic of the timing fluctuation and instability for the transfer was analyzed and measured. The experimental results show the total root-mean-square (RMS) timing fluctuation of the transferred RF signal with compensation is about 162 fs with a fractional frequency instability on the order of 2.8 × 10 -13 at 1 s and 2.7 × 10 -16 at 1000 s. The laser-based underwater frequency transfer proposed in this paper has a potential application of transferring atomic clock in water environment as its instability is less than the currently-used commercial Cs or H-master clocks.

关键词： Timing Laser beams Fluctuations Optical transmitters RF signals Optical fiber communication Optical reflection

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Differentiable Programming for Differential Equations: A Review

arXiv

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arXiv 2024年

作者： Sapienza, Facundo Bolibar, Jordi Schäfer, Frank Groenke, Brian Pal, Avik Boussange, Victor Heimbach, Patrick Hooker, Giles Pérez, Fernando Persson, Per-Olof Rackauckas, Christopher Department of Statistics University of California Berkeley United States Univ. Grenoble Alpes CNRS IRD G-INP Institut des Géosciences de l’Environnement Grenoble France TU Delft Department of Geosciences and Civil Engineering Delft Netherlands CSAIL Massachusetts Institute of Technology Cambridge United States TU Berlin Department of Electrical and Computer Engineering Berlin Germany Helmholtz Centre for Environmental Research Leipzig Germany Swiss Federal Research Institute WSL Birmensdorf Switzerland Oden Institute for Computational Engineering and Sciences University of Texas Austin United States Jackson School of Geosciences University of Texas Austin United States Department of Statistics and Data Science University of Pennsylvania United States Department of Mathematics University of California Berkeley United States Massachusetts Institute of Technology Cambridge United States JuliaHub Cambridge United States

The differentiable programming paradigm is a cornerstone of modern scientific computing. It refers to numerical methods for computing the gradient of a numerical model’s output. Many scientific models are based on differential equations, where differentiable programming plays a crucial role in calculating model sensitivities, inverting model parameters, and training hybrid models that combine differential equations with data-driven approaches. Furthermore, recognizing the strong synergies between inverse methods and machine learning offers the opportunity to establish a coherent framework applicable to both fields. Differentiating functions based on the numerical solution of differential equations is nontrivial. Numerous methods based on a wide variety of paradigms have been proposed in the literature, each with pros and cons specific to the type of problem investigated. Here, we provide a comprehensive review of existing techniques to compute derivatives of numerical solutions of differential equations. We first discuss the importance of gradients of solutions of differential equations in a variety of scientific domains. Second, we lay out the mathematical foundations of the various approaches and compare them with each other. Third, we cover the computational considerations and explore the solutions available in modern scientific software. Last but not least, we provide best-practices and recommendations for practitioners. We hope that this work accelerates the fusion of scientific models and data, and fosters a modern approach to scientific *** Codes 34-04, 49K40, 65D25, 65L09, 65M32, 86A22, 90C31 © 2024, CC BY.

关键词： Differential equations

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Effects of Unbalanced Data on Radiometric Transforming Model Fitting for Relative Radiometric Normalization

Effects of Unbalanced Data on Radiometric Transforming Model...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Wenxia Gan Jing Geng Yu Wang Jinying Xu Weihang Yu Huanning Yuan Rongjun Qin School of Civil Engineering and Architecture Wuhan Institute of Technology Wuhan China Institute of E-Government Beijing Institute of Technology Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China Geospatial Data Analytics Laboratory

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Most of the existing (Relative Radiometric Normalization) RRN research focus on the automatic sample selection, while unbalanced data effect on the regression is not noted and the pre-selected sample set like the Pseudo-invariant Features (PIFs), or homogeneous pixels are directly used to solve the radiometric transforming models without considering the representativeness of the sample set. In this paper, we investigated the effects of unbalanced data, specifically on two aspects: 1) statistical properties of the estimated model parameters, 2) the normalizing accuracy of the fitted model. To make the work thoroughly, four regression methods are investigated, including Least Square Regression (LSQ), Theil-Sen estimator (TSR), Support vector machine regression (SVR), and Random forest regression (RFR). And Monte-Carlo Simulation is used to generated various sample sets with different distributions. It is demonstrated that the LSQ and the TSR are vulnerable to data unbalance, in terms of both the estimated model parameters and the normalizing accuracy of the fitted radiometric transforming model, whereas the SVR and RFR are not sensitive.

关键词： Radiometry Data models Remote sensing Fitting Support vector machines Stability analysis Monte Carlo methods

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A Simulation Study on the Reentrant Waves in the Pacing Ventricular Tissues

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Journal of Physics: Conference Series 2021年第6期1748卷

作者： Yue Zhang Xibo Shi Dong Sui College of Computer Science and Technology Harbin Engineering University China School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture China

The aim of the study is to investigate the relationship between the reentrant waves and IK1, and probe the effect of IK1 on the reentrant waves. Firstly, based on the TNNP06 model, the single pacing cell is derived by depressing IK1. And then, a 400 cells ×400 cells 2D tissue is developed by coupling the pacing cells together. Thirdly, the S1-S2 protocol is applied to inspire the reentrant waves. Next, the processes of the reentrant waves in the tissue corresponding to different IK1 are analysed. In addition, the action potentials of the cells in special locations are recorded and discussed. With the decrease of the IK1, the reentrant waves spin slowly and the period of reentrant waves increases. Meanwhile, the range of the action potential of the cells becomes larger when IK1 becomes smaller. The results suggest that with the decrease of IK1, the reentrant wave is weakened, and the systolic and diastolic functions of the tissue are enhanced at the same time.

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Spintronic foundation cells for large-scale integration

Nature Reviews Electrical Engineering

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Nature Reviews Electrical engineering 2024年 694-695页

作者： Qiming Shao Kevin Garello Jianshi Tang Department of Electronic and Computer Engineering & Physics Hong Kong University of Science and Technology Hong Kong China Univ. Grenoble Alpes CEA CNRS Grenoble INP SPINTEC Grenoble France School of Integrated Circuits Tsinghua University Beijing China

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Optimal Allocation of Water Resources in the Manas River Irrigation District Based on the Metaheuristic Algorithm

SSRN

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SSRN 2023年

作者： Pan, Yue Tian, Hao Gu, Xinchen Heng, Tong Hermansen, Cecilie de Jonge, Lis Wollesen He, Xinlin Li, Fadong Gao, Yongli Yang, Guang Tian, Lijun College of Water Conservancy & Architectural Engineering Shihezi University Shihezi Xinjiang832000 China Key Laboratory of Cold and Arid Regions Eco-Hydraulic Engineering of Xinjiang Production & Construction Corps Shihezi Xinjiang832000 China State Key Laboratory of Hydraulic Engineering Simulation and Safety School of Civil Engineering Tianjin University Tianjin300072 China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing100044 China Dep. of Agroecology Faculty of Science and Technology Aarhus Univ. Blichers Allé 20 P.O. Box 50 TjeleDK-8830 Denmark Institute of Geographic Sciences and Natural Resources Research Beijing100101 China College of Resource and Environment University of Chinese Academy of Sciences Beijing100049 China Department of Earth and Planetary Sciences University of Texas San AntonioTX78249 United States Key Laboratory of Cenozoic Geology Environment Institute of Geology and Geophysics Chinese Academy of Sciences Beijing100029 China Key Laboratory of Cold and Arid Regions Eco-Hydraulic Engineering of Xinjiang Production & Construction Corps Shihezi Xinjiang832000 China

In this study, an optimal water resource allocation model based on a metaheuristic algorithm was applied to the Manas River Irrigation District in Xinjiang, China. First, a multiobjective water resource optimization allocation model was established according to the future development of the population and ecological environment in a dry oasis irrigation district, which was in line with the actual situation of the region under the constraints of the total water resources. Second, the multiobjective problem was solved with a metaheuristic algorithm (MOBWO), considering the model calculation time and definition domain, and the multiobjective solution set was generated. Finally, the objective solution set obtained after 100 iterations was determined as the basis for the subsequent search for the optimal solution. The findings of this study suggest that: (1) The solution sets obtained by applying the MOBWO algorithm to solve the multiobjective optimal allocation model for the irrigation water resources in each subirrigation district (Shihezi, Mosouwan, and Xiayedi Irrigation Districts) of the Manas River Irrigation District for four types of water users (agriculture, industry, household, and ecology water) all satisfied the range of the total water resources index of the irrigation district. (2) Selecting the calculation for the Shihezi Irrigation District in 2030 as an example, the binary comparison method was used to determine the weight of each objective as (0.43, 0.35, 0.22), and the multiobjective fuzzy preference model was used to filter the solution set to determine the solution with the highest degree of superiority (ui=0.979) as the optimal solution. (3) The economic objective of the optimal solution for the Shihezi Irrigation District in 2030 under this scenario is 14912.91 million yuan, the social objective is 1186.77 million m³, and the ecological target is 1.22 million m³. The results corresponding to this scenario can be used as a reference for decision mak

关键词： Decision making

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A Stacked Ensemble Learning Framework with Heterogeneous Feature Combinations for Predicting ncRNA-Protein Interaction

A Stacked Ensemble Learning Framework with Heterogeneous Fea...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Qiguo Dai Zhaowei Wang Jinmiao Song Xiaodong Duan Maozu Guo Zhen Tian School of Computer Science and Engineering Dalian Minzu University Dalian China Key Laboratory of Big Data Applied Technology State Ethnic Affairs Commission Dalian Minzu University Dalian China School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China School of Information Engineering Zhengzhou University Zhengzhou China

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

The interaction between ncRNA and protein is a kind of crucial molecular activities in a cell. Developing computational methods to predict ncRNA-protein interactions has attracted increasing attentions in recent years. In this work, a novel stacked ensemble learning framework is presented for predicting ncRNA-protein interaction based on heterogeneous feature combinations, named HFC-RPI. Firstly, the compositional features of k-mer with different orders were extracted from the primary sequence and secondary structure of RNA and protein respectively. Secondly, we trained a set of base learners using a variety of heterogeneous combinations of the extracted features respectively. Thirdly, the prediction results of these base learners were employed to train the stacked learner, which output the final prediction result at the higher layer in HFC-RPI. Moreover, in order to improve the generalization of HFC-RPI, when training the base learners, a cross-validation based method was applied. Extensive experimental results showed that the proposed learning framework HFC-RPI was effective and feasible for predicting the interaction of ncRNA and protein. By comparing with state-of-the-art methods, HFC-RPI was superior to them on most performance evaluation metrics.

关键词： Proteins Feature extraction RNA Training Predictive models Protein engineering Deep learning

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Sustainable fill solutions: recycling EPS waste in shredded EPS-clayed soil composites for improved mechanical and compaction behaviour

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Transportation Geotechnics 2025年 54卷

作者： Muhammad Haseeb Zain Maqsood Muhammad Baqir Sofia Sarwar Badee Alshameri Waqas Hassan Abbas Haider Lin Wenli Mehtab Alam Jiren Xie Liu Ang Muhammad Umar Bidding Professionals LLC NY 14602 USA National University of Sciences and Technology Islamabad 44000 Pakistan Water and Sanitation Agency (WASA) Rawalpindi 46000 Pakistan Brunel University of London Beijing China School of Transportation Southeast University Nanjing 211189 China Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Topi 23640 District Swabi Khyber Pakhtunkhwa Pakistan Department of Geotechnical Engineering College of Civil Engineering Tongji University Shanghai 200092 China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China Department of Civil Engineering Central South University Changsha 410075 China Dept. of Geological Engineering Nanjing Tech Univ. Nanjing 211800 China Department of Civil Engineering National University of Computer & Emerging Science Lahore Pakistan

The disposal and recycling of expanded polystyrene (EPS) waste pose significant challenges. Although previous research has explored the engineering characteristics of coarse-grained soils mixed with EPS waste for lightweight fill materials, limited attention has been given to fine-grained clayey soils. This study investigates the compaction, strength, and deformation behavior of three types of clayey soils with varying plasticity, mixed with 0.5% to 3.0% shredded EPS content. Experimental results indicate that the addition of shredded EPS to all three clayey soils significantly reduced the maximum dry density (MDD), making them suitable for lightweight fill applications. Direct shear tests revealed a decrease in cohesion and an increase in the angle of internal friction as the shredded EPS content increased. The unconfined compressive strength (UCS) initially increased with EPS content, then decreased after reaching an optimal EPS proportion. The addition of shredded EPS also enhanced the workability of the clayey soils, as evidenced by a reduction in their plasticity indices. Based on these findings, a framework is proposed to determine the optimum shredded EPS content, which provides the best balance between strength and reduced unit weight for different clayey soils. This research highlights the potential of EPS waste as a sustainable additive for improving the properties of clayey soils, making them more efficient and eco-friendly for construction purposes, particularly in transportation geotechnics for road embankments and subgrade stabilization.

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