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Two-decadal shifts in phytoplankton functional taxa (2002–2022) in response to extreme marine heatwaves

Optics Express 2025年第10期33卷 21961-21978页

作者： Ronglong Chen Deyong Sun Shengqiang Wang Yongjun Jia Muhammad Bilal Shuyan Lang Zhenghao Li State Key Laboratory of Climate System Prediction and Risk Management Nanjing University of Information Science and Technology Nanjing 210044 China School of Marine Sciences Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Space Ocean Remote Sensing and Application Ministry of Natural Resources Beijing 100081 China National Satellite Ocean Application Service Beijing 100081 China Architecture and City Design Department College of Design and Built Environment King Fahd University of Petroleum and Minerals (KFUPM) Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Aviation & Space Exploration (IRC-ASE) King Fahd University of Petroleum and Minerals (KFUPM) Dhahran 31261 Saudi Arabia

Phytoplankton play a crucial role in the primary productivity of ocean ecosystems, rendering changes in their populations particularly consequential. The effects of extreme sea surface temperature (SST) on phytoplankton are noteworthy. However, the direct characterization of total biomass by chlorophyll for analysis is inaccurate for phytoplankton functional taxa (PFTs) with different sensitivity to SST. Through the method of Diagnostic pigment analysis (DPA), these organisms can be classified into six primary functional taxa based on their distinctive pigments, which play a vital role in elucidating their ecological functions and dynamics. This study employed optical remote sensing to reconstruct daily concentrations and occupancy of six PFTs in the Eastern China Marginal Sea (ECMS) over the past 20 years. Causal analyses were conducted to identify regions with varying sensitivity to SST changes and further explore the corresponding impacts on phytoplankton concentrations. Results revealed that high-causality areas in the Bohai Sea (BS) and Yellow Sea (YS) were primarily located in nearshore waters. In contrast, high-causality regions in the East China Sea (ECS) were farther offshore, while nearshore areas exhibited lower causality. The high-causality subregions experienced significant fluctuations in phytoplankton concentrations, particularly during marine heatwave (MHW) events, with a prevailing trend of decline in taxon concentrations driven by elevated SST. In comparison, low-causality subregions displayed weaker synchronization with SST changes, as other factors influenced taxa concentrations more prominently. Notably, while phytoplankton concentrations fluctuated significantly during extreme MHW events, they eventually reverted to baseline levels. However, with the increasing frequency and intensity of MHWs due to global warming, the capacity for phytoplankton to recover under such repeated stress remains uncertain. This study emphasizes the necessity of furt

关键词： Absorption coefficient Optical absorption Optical properties Remote sensing Spatial resolution Strain

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DCCT-Net: A Network Combined Dynamic CNN and Transformer for Image Compressive Sensing

DCCT-Net: A Network Combined Dynamic CNN and Transformer for...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Lijuan Xu Haixiao Mei Fenghua Tong Dawei Zhao Fuqiang Yu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Recent end-to-end image compressive sensing networks primarily use Convolutional Neural Networks (CNNs) and Transformers, each with distinct limitations: CNNs struggle with global feature capture, while Transformers lack local feature extraction. We propose a novel network, DCCT-Net, which combines Dynamic CNN (DCNN) and Transformer. This integration leverages DCNN’s local feature strengths and the Transformer’s global representation capabilities, resulting in superior image reconstruction quality. To further enhance the network’s performance, we propose a Feature Dynamic Augment Module (FDAM), which dynamically extracts features based on the saliency of segmented image regions, thereby amplifying the CNN’s local feature expression. Additionally, we design a Weighted Fusion Module (WFM), which optimizes the combination of local and global features extracted by the DCNN and Transformer, respectively. Extensive experiments demonstrate that our proposed DCCT-Net significantly outperforms most existing state-of-the-art methods in the field.

关键词： Image segmentation Image coding Signal processing Transformers Feature extraction Sensors Convolutional neural networks Speech processing Compressed sensing Image reconstruction

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Enhanced Adaptive Disturbance Observer for Sensorless Control of PMSM With Multi-harmonics Suppression Characteristics

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Qin, Qinghai Yi, Xinqiang Yu, Zhongjun Yu, Haitao Fang, Shuhua Southeast University School of Electrical Engineering Nanjing210096 China Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan430033 China East Lake Laboratory Wuhan430202 China

The inverter nonlinearity and spatial flux harmonics inevitably result in the back electromotive force (BEMF) harmonics in permanent magnet synchronous motor (PMSM), which deteriorates the performance of the model-based sensorless control. To settle the problem, this article proposes an enhanced adaptive disturbance observer by reconstructing the observer structure based on the pre-designed enhanced complex coefficient filter (ECCF). An ECCF with specific harmonic filtering capability based on conventional complex coefficient filter and multi-frequency suppression module is pre-constructed. Based on the reverse design method, the structure of the conventional disturbance observer is reconstructed into the desired ECCF structure. Multi-harmonics can be suppressed without cascading additional filtering networks after the conventional BEMF observers. The sensorless control algorithm studied is verified by the comparative experiments on a 1 kW PMSM platform. © 2013 IEEE.

关键词： Sensorless control

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Bandwidth-Efficient Two-Server ORAMs with O(1) Client Storage

arXiv

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arXiv 2025年

作者： Wang, Wei Zhang, Xianglong Xu, Peng Chen, Rongmao Yang, Laurence Tianruo School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Distributed System Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Jinyinhu Laboratory Wuhan430040 China School of Computer National University of Defense Technology Changsha410073 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China Department of Computer Science St. Francis Xavier University AntigonishNSB2G 2W5 Canada

Oblivious RAM (ORAM) allows a client to securely retrieve elements from outsourced servers without leakage about the accessed elements or their virtual addresses. Two-server ORAM, designed for secure two-party RAM computation, stores data across two non-colluding servers. However, many two-server ORAM schemes suffer from excessive local storage or high bandwidth costs. To serve lightweight clients, it is crucial for ORAM to achieve concretely efficient bandwidth while maintaining O(1) local storage. Hence, this paper presents two new client-friendly two-server ORAM schemes that achieve practical logarithmic bandwidth under O(1) local storage, while incurring linear symmetric key computations. The core design features a hierarchical structure and a pairwise-area setting for the elements and their tags. Accordingly, we specify efficient read-only and write-only private information retrieval (PIR) algorithms in our schemes to ensure obliviousness in accessing two areas respectively, so as to avoid the necessity of costly shuffle techniques in previous works. We empirically evaluate our schemes against LO13 (TCC’13), AFN17 (PKC’17), and KM19 (PKC’19) in terms of both bandwidth and time cost. The results demonstrate that our schemes reduce bandwidth by approximately 2 ∼ 4× compared to LO13, and by 16 ∼ 64× compared to AFN17 and KM19. For a database of size 214 blocks, our schemes are over 64× faster than KM19, while achieving similar performance to LO13 and AFN17 in the WAN setting, with a latency of around 1 second. Copyright © 2025, The Authors. All rights reserved.

关键词： Virtual addresses

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Variable stiffness design optimization of fiber-reinforced composite laminates with regular and irregular holes considering fiber continuity for additive manufacturing

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Chinese Journal of Aeronautics 2025年第3期38卷 334-354页

作者： Yi LIU Zunyi DUAN Chunping ZHOU Yuan SI Chenxi GUAN Yi XIONG Bin XU Jun YAN Jihong ZHU School of Mechanics Civil Engineering&ArchitectureNorthwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518063China Key Lab for Airborne Hi-performance Electro-magnetic Window RISACJinan 130012China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian 116024China State IJR Center of Aerospace Design and Additive Manufacturing MIIT Lab of Metal Additive Manufacturing and Innovative DesignNorthwestern Polytechnical UniversityXi’an 710072China

Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples cons

关键词： Variable stiffness composite laminates Discrete material interpolation scheme Normal distribution fiber optimization Discrete fiber continuous filtering strategy Additive manufacturing of composite laminates

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A Peridynamic Approach for the Evaluation of Metal Ablation under High Temperature

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Computer Modeling in Engineering & sciences 2023年第3期134卷 1997-2019页

作者： Hui Li Liping Zhang Yixiong Zhang Xiaolong Fu Xuejiao Shao Juan Du Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu610200China

In this paper,the evaluations of metal ablation processes under high temperature,i.e.,the Al plate ablated by a laser and a heat carrier and the reactor pressure vessel ablated by a core melt,are studied by a novel peridynamic *** all,the peridynamic formulation for the heat conduction problem is obtained by Taylor’s expansion ***,a simple and efficient moving boundary model in the peridynamic framework is proposed to handle the variable geometries,in which the ablated states of material points are described by an additional scalar ***,due to the automatic non-interpenetration properties of peridynamic method,a contact algorithm is established to determine the contact relationship between the ablated system and the additional heat *** addition,the corresponding computational procedure is listed in ***,several numerical examples are carried out and the results verify the validity and accuracy of the present method.

关键词： Peridynamics metal ablation moving boundary model contact algorithm reactor pressure vessel

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Enhanced strength-ductility synergy in laser directed energy deposited IN718 superalloys through heterogeneous deformation nanostructures

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International Journal of Machine Tools and Manufacture 2025年 208卷

作者： Li, Yao Li, Mengyang Yang, Hao Dang, Xiaofeng Cui, Luqing Jiao, Yang Sun, Zhiping Guo, Ting He, Weifeng School of Materials Science and Engineering Chang'an University Shaanxi Xi'an710064 China Key Laboratory of Road Construction Technology & Equipment of Ministry of Education Chang'an University Shaanxi Xi'an710064 China Chongqing Academy of Metrology and Quality Inspection Chongqing401121 China School of Mechanical Engineering Xi'an Shiyou University Shaanxi Xi'an710065 China National Key Lab of Aerospace Power System and Plasma Technology Xi'an Jiaotong University Shaanxi Xi'an710049 China Unit 95821of PLA Gansu Jiuquan735000 China National Key Lab of Aerospace Power System and Plasma Technology Air Force Engineering University Shaanxi Xi'an710038 China

Laser directed energy deposition (LDED) shows great promise for repairing superalloy components of aeroengines but often results in coarse microstructures, porosity, and tensile residual stresses. Herein, post-process ultrasonic impact treatment (UIT) is adopted to effectively regulate the surface microstructure and residual stresses in LDED-fabricated IN718 superalloys, enhancing the strength-ductility synergy. The UIT process optimization is achieved through a systematic investigation of the effect of output powers on surface roughness, porosity, deformation microstructure, microhardness distribution, residual stress profile, and tensile behavior. Particularly, a finite element model for simulating residual stress field induced by ultrasonic impact is established, showcasing excellent agreement with experimental measurements. UIT-induced substantial dislocation and twinning activities result in depth-dependent heterogeneous deformation nanostructures, including alternating nano-grains and nano-laminated composite structures on the top surface ( © 2025 Elsevier Ltd

关键词： Surface roughness

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Artificial Intelligence in reactor Physics: Current Status and Future Prospects

arXiv

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arXiv 2025年

作者： Zhang, Ruizhi Zhu, Shengfeng Wang, Kan She, Ding Argaud, Jean-Philippe Bouriquet, Bertrand Li, Qing Gong, Helin School of Mathematical Sciences Shanghai Key Laboratory of Pure Mathematics and Mathematical Practice East China Normal University Shanghai200241 China Department of Engineering Physics Tsinghua University Beijing100084 China Électricité de France R&D 7 boulevard Gaspard Monge Palaiseau91120 France Électricité de France DQI 2 rue Ampère Saint-Denis93206 France Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai200240 China

reactor physics is the study of neutron properties, focusing on using models to examine the interactions between neutrons and materials in nuclear reactors. Artificial intelligence (AI) has made significant contributions to reactor physics, e.g., in operational simulations, safety design, real-time monitoring, core management and maintenance. This paper presents a comprehensive review of AI approaches in reactor physics, especially considering the category of Machine Learning (ML), with the aim of describing the application scenarios, frontier topics, unsolved challenges and future research directions. From equation solving and state parameter prediction to nuclear industry applications, this paper provides a step-by-step overview of ML methods applied to steady-state, transient and combustion problems. Most literature works achieve industry-demanded models by enhancing the efficiency of deterministic methods or correcting uncertainty methods, which leads to successful applications. However, research on ML methods in reactor physics is somewhat fragmented, and the ability to generalize models needs to be strengthened. Progress is still possible, especially in addressing theoretical challenges and enhancing industrial applications such as building surrogate models and digital twins. Copyright © 2025, The Authors. All rights reserved.

关键词： Nuclear industry

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Study on hydrogen stratification and erosion process in Chinese SMR containment under severe accident scenario

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International Journal of Advanced Nuclear reactor design and technology 2020年 2卷 43-51页

作者： Fan, Yang Songwei, Li Wei, Zeng Zhifang, Qiu Jian, Deng Science and Technology on Reactor System Design Technology Laboratory NPIC China Design and Research Sub-institute NPIC China

During postulated severe accident, large amount of hydrogen-vapor mixture will be released into the containment and inflammable gas mixture may form. Once the gas will be ignited, the generated pressure loads can jeopardize the integrity of the internal structures. As the local accumulation of high content hydrogen related much to the stratification and erosion mechanism, it is therefore of interest whether a stratification of gas layers will form within small containment. In this study, a stratification/erosion experiment is performed and the criteria under which the steady stratification will be destroyed by steam jet discussed. Then the simulation method is validated by the experimental data. At last, several severe accident scenarios for Chinese SMR performed and one of them is adopted for containment hydrogen CFD analysis. It is shown that high content of hydrogen will form in the upper part of the containment, and clear gas stratification will form, such stratification will be enhanced due to the condensation effect of steel containment wall. © 2020

关键词： Hydrogen

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Carbon emission peaks in countries worldwide and their national drivers

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Carbon Research 2025年第1期4卷 1-16页

作者： Wu, Qian Chen, Yujie Huang, Chaoqing Zhang, Lu He, Chao School of Resource and Environmental Sciences Wuhan University Wuhan China Collaborative Innovation Center for Emissions Trading System Co-Constructed By the Province and Ministry Wuhan China Key Laboratory of Geographic Information System Ministry of Education Wuhan University Wuhan China School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China Guangdong Eco-Engineering Polytechnic Guangdong Province Guangzhou China State Key Laboratory of Freshwater Ecology and Biotechnology Institute of Hydrobiology Chinese Academy of Sciences Wuhan China National Science Library (Wuhan) Chinese Academy of Sciences Wuhan China

Estimating the characteristics of CO2 emission peaks through decoupling relationships is crucial for understanding global CO2 emissions and mitigating climate change. This study investigated the spatiotemporal patterns and primary sources of global CO2 emissions from 1990 to 2020. Using the Mann–Kendall test and decoupling index, we identified emission peak characteristics across countries worldwide. Furthermore, the geographically temporally weighted regression (GTWR) model was employed to examine the effects of various factors on CO2 emissions. The results indicate that global CO2 emissions increased steadily over the study period, with the power industry contributing the most (34.54%–38.62%). Countries were categorized into four groups: no-declined, plateau, passively emission declined, and proactively peaked, comprising 99, 48, 20, and 26 countries, respectively. Notably, 65.4% of proactively peaked countries were developed nations, while 65% of passively emission declined countries were developing nations. CO2 emissions exhibited positive correlations with carbon intensity, GDP per capita, and the secondary industry but negative correlations with population density, the primary and tertiary industries. These findings provide valuable insights into global CO2 emission dynamics, highlighting emission peaks and decoupling relationships. This study also offers robust scientific support for policymakers to effectively design tailored strategies for reducing carbon emissions.

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