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Corrigendum to "Intensifying heatwave events affect snow phenology over the Tibetan Plateau" [J. Hydrol. 659 (2025) 133293] (Journal of Hydrology (2025) 659, (S0022169425006316), (10.1016/***.2025.133293))

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Journal of Hydrology 2025年 656卷

作者： Deng, Gang Zhang, Tongchang Liu, Xiuguo He, Yan Chen, He Shen, Qikai Chen, Qihao Tang, Zhiguang School of Geography and Information Engineering China University of Geosciences Wuhan430074 China National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology Hunan University of Science and Technology Xiangtan411201 China

The authors regret that the following minor errors appeared in the original article: (1) The postal code of the second affiliation was missing. The correct and complete affiliation should be: b National-Local Joint Engineering laboratory of geo-spatial information technology, Hunan University of Science and technology, Xiangtan 411201, China. (2) In Section "2.3.4 Structural equation model (SEM)", the beginning of the second paragraph should be revised to "six hypothetical pathways" instead of "four hypothetical pathways". The authors would like to apologise for any inconvenience caused. © 2025 Elsevier B.V.

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Silicon-Organic Hybrid Modulators Based on a Coupled One-Dimensional Photonic Crystal Slot Resonator Waveguide

IEEE Photonics Journal

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IEEE Photonics Journal 2025年第3期17卷

作者： Li, Yanmei Yan, Likang Feng, Yang Wang, Jinzhao Li, Rui Yao, Weiming Yao, Yong Xu, Xiaochuan Harbin Institute of Technology School of Information Science and Technology Shenzhen518055 China Xili University Town National Key Laboratory of Laser Spatial Information Guangdong Provincial Key Laboratory of Integrated Photonic-Electronic Chip Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Harbin Institute of Technology campus Guangdong Shenzhen518055 China

High-speed and energy-efficient optical interconnects critically rely on electro-optical (EO) modulators, whose performance metrics struggle to meet the exponentially increasing demands of the near future. Silicon-organic hybrid (SOH) modulators present a promising solution due to the favorable electro-optic coefficients and fast response times of EO organic materials. However, the waveguide's nature limits the effective interaction between photons and EO materials. Although this interaction can be enhanced by utilizing advanced structures such as slot waveguides and slow-light techniques, new challenges arise, including strong dispersion that compromises bandwidth. In this paper, we propose a novel low-dispersion, slow-light waveguide structure based on a coupled one-dimensional photonic crystal slot resonator waveguide (coupled 1D PC SROW). By cascading multiple coupled resonators, the structure creates a low-dispersion, slow-light region within the photonic bandgap. Combining the strong optical field confinement of the slot with the slow-light enhancement in the time domain, modulation efficiency, quantified by VπL, can be significantly improved. As an example, we demonstrate that a VπL of 0.57 Vmm can be achieved for a low-dispersion wavelength range of 2.55 nm. The improvement in modulation efficiency allows for a reduction in the phase shifter length to 119 μm, overcoming the bandwidth limitations imposed by spatial walk-off between the electrical and optical waves and enabling a bandwidth of 108 GHz, a value challenging for conventional approaches. This study presents a viable alternative for realizing compact, ultra-broadband, and energy-efficient optical modulators. © 2009-2012 IEEE.

关键词： Light modulators

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All-optical anti-interference light-induced thermoelastic spectroscopy gas sensor based on normalized harmonic demodulation

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IEEE Sensors Journal 2025年

作者： Lang, Ziting Qiao, Shunda He, Ying Ma, Yufei Harbin Institute of Technology National Key Laboratory of Laser Spatial Information Harbin150000 China Harbin Institute of Technology Zhengzhou Research Institute Zhengzhou450000 China

An all-optical anti-interference light-induced thermoelastic spectroscopy (LITES) gas sensor is proposed for the first time. In this all-optical LITES gas sensor, the Fabry-Perot (F-P) sensing technology was applied to demodulate the vibration of quartz tuning fork (QTF), replacing the measurement of piezoelectric signal in traditional LITES sensors. To overcome the F-P detection instability caused by the environmental interference, the wavelength modulation spectroscopy with the second harmonic normalized by the first harmonic (WMS-2f/1f) demodulation method was adopted for F-P sensing. Acetylene (C2H2) was chosen as the target gas to verify the performance of the proposed sensor. Theoretical analyses and experimental validations demonstrated that this novel F-P-based WMS-2f/1f demodulation method is immune to the disturbance of excitation laser, probe laser, and F-P cavity length. Moreover, it exhibits excellent long-term stability with an improvement of over 60 times compared to traditional 2f demodulation. This all-optical anti-interference LITES gas sensor is expected to play an important role in remote and non-contact gas sensing. © 2001-2012 IEEE.

关键词： Laser excitation

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Parts-per-quadrillion level gas molecule detection: CO-LITES sensing

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Light: Science and Applications 2025年第1期14卷 1-11页

作者： Sun, Haiyue Qiao, Shunda He, Ying Sun, Xiaorong Ma, Yufei National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin150001 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou450000 China

Highly sensitive gas detection plays a crucial role in advanced scientific and technological fields. This paper presents a parts-per-quadrillion (ppq) level ultra-highly sensitive light-induced thermoelectric spectroscopy (LITES) sensor for the first time. The artificial fish swarm algorithm auto-designed multi-pass cell (MPC) with double helix pattern, and the polymer modified round-head quartz tuning fork (QTF) with low-resonant frequency (f0) were adopted to improve the gas absorption and QTF’s detection ability. The obtained MPC, with a long optical path length (OPL) of 25.8 m and a small volume of 165.8 ml, is beneficial for increasing gas absorption while keeping the sensor compact. The novel QTF was structurally optimized to obtain low f0 (~9.5 kHz) and modified by polydimethylsiloxane (PDMS) to reduce heat diffusion and enhance vibration amplitude. A strong absorption line of carbon monoxide (CO) located in the mid-infrared region (4.59 μm) was chosen as the target line. The signal-to-noise ratio (SNR) of CO-LITES sensor based on the novel QTF was improved by 10.59 times, reaching the highest level when compared to the commercial QTF. The corresponding minimum detection limit (MDL) was calculated to be 23 ppt. When the integration time of the sensor system was increased to 500 s, the MDL could be improved to 920.7 ppq. Compared to the reported spectroscopy techniques for CO gas detection, the LITES sensor in this study offers an excellent result in terms of detection sensitivity. © The Author(s) 2025.

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Multiregion full-waveform inversion for ground-penetrating radar common-offset data

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geophysics 2025年第3期90卷 B121-B130页

作者： Hu, Rong Li, Jing Liu, Hui Jilin University College of Geo-exploration Science and Technology Changchun China Key Laboratory of Earth Information Detection Instruments Ministry of Education Changchun China

Ground-penetrating radar full-waveform inversion (GPR-FWI) is a high-resolution inversion technique that quantitatively estimates the subsurface physical parameters (permittivity and conductivity) by matching waveform amplitude and phase. However, the requirement to meet stability conditions forces the grid dimensions during wave propagation to be at the centimeter level, resulting in significant memory usage when discretizing the full radar wavefield. This makes it challenging to apply the FWI method on large-scale 2D or 3D GPR data sets. Furthermore, most commercial GPR systems record common-offset gathers (COG), so most GPR field data do not need to calculate the full model-space wavefield during the FWI iteration procedure. This work develops a multiregion full-waveform inversion approach (MR-FWI) for common-offset GPR data. The core strategy is to divide the model space into multiple grid regions and dynamically adjust these grids according to the requirements. By focusing on a given spatial range of the wavefield and model gradient, the computational steps are optimized, significantly reducing memory consumption and computational cost. A synthetic model and two field GPR data examples validate that the multiregion strategy can reduce the computational burden without sacrificing inversion accuracy. Our MR-FWI is particularly suitable for limited computing resources and large-scale data sets, which provides a robust and high-resolution approach for most field common-offset GPR applications. © 2025 Society of Exploration geophysicists. All rights reserved.

关键词： geological surveys

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A review of solar concentration technology applications in deep space exploration: Environmental adaptability and performance comparison

Space Solar Power and Wireless Transmission

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Space Solar Power and Wireless Transmission 2025年第1期2卷 43-53页

作者： Yanlong Zhang Pengzhen Guo Mengfan Tian Huazhi Chen Rongqiang Liu Zongquan Deng Lifang Li National Key Laboratory of Aerospace Mechanism Harbin Institute of Technology Harbin 150001 PR China National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin 150001 PR China National Key Laboratory of Space Environment and Matter Behaviors Harbin Institute of Technology Harbin 150001 PR China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 PR China

Deep space exploration missions and the construction of planetary research stations impose strict demands on energy self-sufficiency systems. Solar energy, due to its abundant availability and sustainability, has become the preferred solution. However, extreme environmental conditions in space – including drastic temperature fluctuations, vacuum environments, high-energy particles, and intense radiation – pose significant challenges to the performance and lifespan of solar energy systems. Concentration technology, which enhances photoelectric and photothermal conversion efficiency by focusing sunlight, is crucial for space missions. This review examines the primary environmental factors affecting the performance of solar concentrators, including solar irradiance, thermal cycling, vacuum-induced outgassing, radiation effects, and impacts from micrometeoroids and orbital debris. The analysis focuses on three types of high-temperature concentrators: Fresnel lenses, Scheffler concentrators, and parabolic dish concentrators. Fresnel lenses are characterized by low cost and simple structure but are susceptible to optical degradation at high temperatures. Scheffler concentrators utilize geometric optimization to improve uniformity of light distribution, while parabolic dish concentrators achieve high optical efficiency, making them suitable for high-energy applications though requiring precise solar tracking. Performance comparisons in the thermal power range of 0 to 25 kW reveal that parabolic dish concentrators excel in high-power scenarios with greater efficiency and smaller aperture sizes. Conversely, Fresnel lenses and Scheffler concentrators are more effective in medium to low-temperature applications. Based on these findings, this review emphasizes the need to select concentrators according to mission requirements and outlines future research directions. These include the development of advanced materials, optimized optical designs, and improvements in system integr

关键词： Deep space exploration Solar concentrators Extreme environmental conditions

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geomorphic and geologic controls on large-scale landslides in the Himalayan region of China

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Landslides 2025年第5期22卷 1725-1741页

作者： Wang, Yu-Feng Chen, Peng-Hai Qian, Jia-Zhen Cheng, Qian-Gong Ming, Jie Li, Chuan-Bao Department of Geological Engineering Southwest Jiaotong University Sichuan Chengdu610031 China Key Laboratory of High-Speed Railway Engineering Ministry of Education Sichuan Chengdu610031 China State-Province Joint Engineering Laboratory of Spatial Information Technology of High-Speed Rail Safety Sichuan Chengdu610031 China Zhejiang Huadong Geotechnical Investigation & Design Institute Co Ltd Zhejiang Hangzhou310030 China China Railway Economic and Planning Research Institute Beijing100038 China

Catastrophic large-scale landslides frequently occur in the Himalayan region, causing significant damage to infrastructure and loss of life. However, studies on the occurrence of such landslides are limited, and the main factors controlling their spatial and size distributions are unclear, which greatly restrict disaster prevention. In this study, a new and detailed inventory of large-scale landslides in the Chinese Himalayas is conducted through artificial interpretation of remote sensing imagery and field surveys, with 794 landslides having volumes ≥ 106 m3 identified. Furthermore, a comprehensive analysis of the spatial and size distributions of landslides under the control of 7 key geomorphic and geologic factors is carried out. Our observations indicate that large-scale landslides display clustering characteristics with four high-kernel-density areas. The distribution of landslides is related primarily to specific lithological units, which consist of thick hard sedimentary rocks and Neoproterozoic-Cambrian gneiss. Additional preferred controls on the landslide distribution are distances to faults and rivers, with slope being the third dominant factor and the preferred slope being 30–40°. Glaciers appear largely to influence the volumes of landslides by intensively fracturing their bedrock, resulting in a more concentrated distribution of slope angles and volumes for the glacial affected landslides than for nonglacial affected landslides. The contributions of elevation and aspect to the occurrence of large-scale landslides are minor. Focusing on large-scale landslides in the Himalayan region of China, a new and systematic analysis of their complex spatial and size distributions is conducted, with new insights into the possible geomorphic and geologic controls on them being reached. With this study, we hope to provide more insights for future geological hazard assessments and management strategies. © Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Landslides

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An Encoder-Based Framework for Privacy-Preserving Machine Learning 24th

An Encoder-Based Framework for Privacy-Preserving Machine L...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Wu, Jiayun Ren, Wei Zhang, Xianchao Zheng, Xianghan School of Computer Science China University of Geosciences Wuhan430074 China State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR CASM Beijing China Ministry of Education Chengdu China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing China Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province Jiaxing University Jiaxing China College of Computer and Big Data Fuzhou University Fujian Fuzhou China School of Information and Intelligent Engineering Sanya College Hainan China

ISBN: (纸本)9789819615506

As a data-driven science, machine learning requires vast amounts of training data and computational resources. However, for highly privacy-sensitive data, it is crucial to protect the privacy of the data during both the training and utilization of machine learning models. In this paper, we propose a privacy-preserving machine learning approach using autoencoders and differential privacy mechanisms to safeguard data privacy while minimizing the impact on data availability. Specifically, we augment logistic regression and ResNet18 models with different architectures of autoencoders to perform data encryption? without compromising the machine learning tasks. Additionally, we employ differential privacy mechanisms to introduce gradient perturbations in the encoding part of the autoencoder, enhancing the algorithm’s security and further protecting data privacy. We also design the cosine similarity between the encoded and original data as a metric for evaluating data privacy, considering model performance, privacy budget, and data privacy collectively to balance data availability and privacy. Extensive experiments conducted on MNIST, CIFAR-10, PathMNIST, and BloodMNIST datasets demonstrate that for simple logistic regression models handling easily classifiable datasets, employing simple autoencoder structures can enhance classification accuracy, with significant performance impact after adding differential privacy. For ResNet18, utilizing convolutional autoencoders for data encryption generally has minimal impact on model classification performance and can even improve accuracy in most cases. Adding differential privacy has minor effects on model classification performance. Selecting appropriate model structures and privacy budgets for different usage scenarios can ensure both data availability and privacy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Provincial anthropogenic emission inventory of carbonyl sulfide (COS) in China from 2015 to 2021

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Journal of geographical Sciences 2025年第5期35卷 923-940页

作者： Jiang, Yunhao Chen, Bin Wang, Shaoqiang Li, Tingyu Chen, Shiliang Wang, Lunche Wang, Lizhe School of Future Technology China University of Geosciences Wuhan China Key Laboratory of Regional Ecology and Environmental Change School of Geography and Information Engineering China University of Geosciences Wuhan China Engineering Technology Innovation Center for Intelligent Monitoring and Spatial Regulation of Land Carbon Sinks Ministry of Natural Resources Wuhan China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research CAS Beijing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China

Carbonyl sulfide (COS) is an effective tracer for estimating Gross Primary Productivity (GPP) in the carbon cycle. As the largest contribution to the atmosphere, anthropogenic COS emissions must be accurately quantified. In this study, an anthropogenic COS emission inventory from 2015 to 2021 was constructed by applying the bottom-up approach based on activity data from emission sources. China’s anthropogenic COS emissions increased from approximately 171 to 198 Gg S yr−1 from 2015–2021, differing from the trends of other pollutants. Despite an initial decline in COS emissions across sectors during the early stage of the COVID-19 pandemic, a rapid rebound in emissions occurred following the resumption of economic activities. In 2021, industrial sources, coal combustion, agriculture and vehicle exhaust accounted for 76.8%, 12.3%, 10.5% and 0.4% of total COS emissions, respectively. The aluminum industry was the primary COS emitter among industrial sources, contributing 40.7% of total emissions. Shandong, Shanxi, and Zhejiang were the top three provinces in terms of anthropogenic COS emissions, reaching 39, 21 and 17 Gg S yr−1, respectively. Provincial-level regions (hereafter province) with high COS emissions are observed mainly in the eastern and coastal regions of China, which, together with the wind direction, helps explain the pattern of high COS concentrations in the Western Pacific Ocean in winter. The Green Contribution Coefficient of COS (GCCCOS) was used to assess the relationship between GDP and COS emissions, highlighting the disparity between GDP and COS contributions to green development. As part of this analysis, relevant recommendations are proposed to address this disparity. The COS emission inventory in our study can be used as input for the Sulfur Transport and Deposition Model (STEM), reducing uncertainties in the atmospheric COS source–sink budget and promoting understanding of the atmosphere sulfur cycle.

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Morphotectonic Analyses of LiDAR-Derived DEMs:Insights into Tectonic Activity of the Xinhua Fault within the Three Gorges Area(Central China)

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Journal of Earth Science 2025年第2期36卷 823-829页

作者： Xiaofeng Wang Xiaohan Yin Tonghui Liu Xuan Li Hongming Wang Yaqi Zhong Gang Rao School of Computer and the Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences(Wuhan)Wuhan 430078China School of Geoscience and Technology Southwest Petroleum UniversityChengdu 610500China School of Earth Sciences China University of Geosciences(Wuhan)Wuhan 430074China Hubei Communications Planning and Design Institute Co. Ltd.Wuhan 430051China School of Economics and Management Shandong Jiaotong UniversityJinan 250357China

0 *** global availability of digital elevation model(DEM)data,such as 90-m Shuttle Radar Topography Mission(SRTM)DEM and 30-m Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM),has been extensively utilized in morphotectonic analyses(e.g.,Wang et al.,2024;Cheng et al.,2018;Pérez-Pe?a et al.,2010;El Hamdouni et al.,2008).

关键词： xinhua fault morphotectonic analyses egwang three gorges area digital elevation model aster lidar derived dems tectonic activity morphotectonic analyses digital elevation model dem datasuch

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