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Leveraging ROTI map derived from Indonesian GNSS receiver network for advancing study of Equatorial Plasma Bubble in Southeast/East Asia

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Earth and Planetary Physics 2025年第1期9卷 101-116页

作者： Prayitno Abadi Ihsan N.Muafiry Teguh N.Pratama Angga Y.Putra Suraina Gatot H.Pramono Sidik T.Wibowo Febrylian F.Chabibi Umar A.Ahmad Wildan P.Tresna Asnawi research center for Climate and Atmosphere Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia School of Electrical engineering Telkom UniversityBandungIndonesia Directorate of Laboratory Management Facilities and Science and technology Park Indonesian National Research and Innovation Agency(BRIN)PontianakIndonesia Geophysics Laboratory Master Program in PhysicsUniversitas Gadjah Mada(UGM)YogyakartaIndonesia research center for Space Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia Indonesian Geospatial information Agency(BIG) JakartaIndonesia research center for Photonics Indonesian National Research and Innovation Agency(BRIN)Tangerang SelatanIndonesia Department of Earth and Planetary Sciences Hokkaido UniversitySapporoJapan

This paper highlights the crucial role of Indonesia’s GNSS receiver network in advancing Equatorial Plasma Bubble(EPB)studies in Southeast and East Asia,as ionospheric irregularities within EPB can disrupt GNSS signals and degrade positioning *** by the Indonesian Geospatial information Agency(BIG),the Indonesia Continuously Operating Reference Station(Ina-CORS)network comprises over 300 GNSS receivers spanning equatorial to southern low-latitude ***-CORS is uniquely situated to monitor EPB generation,zonal drift,and dissipation across Southeast *** provide a practical tool for EPB research,by sharing two-dimensional rate of Total Electron Content(TEC)change index(ROTI)derived from this *** generate ROTI maps with a 10-minute resolution,and samples from May 2024 are publicly available for further scientific *** preliminary findings from the ROTI maps of Ina-CORS are ***,the Ina-CORS ROTI maps reveal that the irregularities within a broader EPB structure persist longer,increasing the potential for these irregularities to migrate farther ***,we demonstrate that combined ROTI maps from Ina-CORS and GNSS receivers in East Asia and Australia can be used to monitor the development of ionospheric irregularities in Southeast and East *** have demonstrated the combined ROTI maps to capture the development of ionospheric irregularities in the Southeast/East Asian sector during the G5 Geomagnetic Storm on May 11,*** observed simultaneous ionospheric irregularities in Japan and Australia,respectively propagating northwestward and southwestward,before midnight,whereas Southeast Asia’s equatorial and low-latitude regions exhibited irregularities *** sharing ROTI maps from Indonesia and integrating them with regional GNSS networks,researchers can conduct comprehensive EPB studies,enhancing the understanding of EPB behavior across Southeast and East Asia and contributing significantly to ionosphe

关键词： Equatorial Plasma Bubble(EPB) GNSS receivers’network Indonesia Continuously Operating Reference Station(Ina-CORS) ionospheric map Rate of TEC change index(ROTI)map

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India research Institute of the University of Bucharest Bucharest050663Romania national Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil engineering Transilvania University of BrasovBrasov500152Romania Danube Delta national Institute for research and Development Tulcea820112Romania Marwadi University research center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Understanding the local structure and thermophysical behavior of Mg-La liquid alloys via machine learning potential

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 439-449页

作者： Jia Zhao Taixi Feng Guimin Lu national engineering research center for Integrated Utilization of Salt Lake Resource East China University of Science and TechnologyShanghai 200237China Joint International Laboratory for Potassium and Lithium Strategic Resources East China University of Science and TechnologyShanghai 200237China

The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.

关键词： magnesium-lanthanum liquid alloys local structure macroscopic properties thermodynamic behavior deep potential mo-lecular dynamic simulation

Mechanism of inflammatory response and therapeutic effects of stem cells in ischemic stroke:current evidence and future perspectives

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Neural Regeneration research 2025年第1期20卷 67-81页

作者： Yubo Wang Tingli Yuan Tianjie Lyu Ling Zhang Meng Wang Zhiying He Yongjun Wang Zixiao Li Vascular Neurology Department of NeurologyBeijing Tiantan HospitalCapital Medical UniversityBeijingChina China national Clinical research center for Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Shanghai engineering research center of Stem Cells Translational Medicine ShanghaiChina national center for Healthcare Quality Management in Neurological Diseases Beijing Tiantan HospitalCapital Medical UniversityBeijingChina Institute for Regenerative Medicine Shanghai East HospitalSchool of Life Sciences and TechnologyTongji UniversityShanghaiChina Chinese Institute for Brain research BeijingChina research Unit of Artificial Intelligence in Cerebrovascular Disease Chinese Academy of Medical SciencesBeijingChina Beijing engineering research center of Digital Healthcare for Neurological Diseases BeijingChina

Ischemic stroke is a leading cause of death and disability worldwide,with an increasing trend and tendency for onset at a younger ***,in particular,bears a high burden of stroke *** recent years,the inflammatory response after stroke has become a research hotspot:understanding the role of inflammatory response in tissue damage and repair following ischemic stroke is an important direction for its *** review summarizes several major cells involved in the inflammatory response following ischemic stroke,including microglia,neutrophils,monocytes,lymphocytes,and ***,we have also highlighted the recent progress in various treatments for ischemic stroke,particularly in the field of stem cell ***,understanding the complex interactions between inflammation and ischemic stroke can provide valuable insights for developing treatment strategies and improving patient *** cell therapy may potentially become an important component of ischemic stroke treatment.

关键词： cell therapy immune cell inflammatory ischemic stroke stem cell

Image acquisition system for agricultural context-aware computing

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International Journal of Agricultural and Biological engineering 2014年第4期7卷 75-80页

作者： Xiao Boxiang Wang Chuanyu Guo Xinyu Wu Sheng Beijing research center for information technology in agriculture Beijing 100097China national engineering research center for information technology in agriculture Beijing 100097China

Context-aware computing is a new mode originated from ubiquitous *** emergence brings a substantial change to traditional computing and related *** is a pervasive tool for context awareness.A large number of applications are developed based on images *** this paper,an image acquisition system is presented for agricultural context-aware *** potential use of the system includes production evaluation,precise management and assistant *** system includes four modules:the camera system,the control system,mechanism,and *** system can be easily installed in target crop *** camera system is composed of a binocular stereo camera and a color *** cubic images and a corresponding texture image are collected for each plant in the process of data *** accessorial software system is developed to control and manage the capture *** show that the presented system is effective for image acquisition of agricultural context-aware computing.

关键词： image acquisition agriculture context-aware computing

3D tomographic analysis of equatorial plasma bubble using GNSS-TEC data from Indonesian GNSS Network

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Earth and Planetary Physics 2025年第1期9卷 127-136页

作者： Ihsan Naufal Muafiry Prayitno Abadi Teguh N.Pratama Dyah R.Martiningrum Sri Ekawati Yuandhika GWismaya Febrylian FChabibi Gatot HPramono research center for Climate and Atmosphere Indonesian National Research and Innovation Agency(BRIN)BandungIndonesia Indonesian Geospatial information Agency(BIG) JakartaIndonesia Dept.of Physics Faculty of ScienceUniversiti Teknologi MalaysiaJohor BahruMalaysia Dept.Earth Planet Sci. Hokkaido UniversitySapporoJapan School of Electrical engineering Telkom UniversityBandungIndonesia

Equatorial Plasma Bubbles(EPBs)are ionospheric irregularities that take place near the magnetic *** most commonly occur after sunset during the equinox months,although they can also be observed during other *** phenomenon significantly disrupts radio wave signals essential to communication and navigation *** national network of Global Navigation Satellite System(GNSS)receivers in Indonesia(>30°longitudinal range)provides an opportunity for detailed EPB *** explore this,we conducted preliminary 3D tomography of total electron content(TEC)data captured by GNSS receivers following a geomagnetic storm on December 3,2023,when at least four EPB clusters occurred in the Southeast Asian *** and extracted TEC depletion with a 120-minute running average were then used as inputs for a 3D tomography *** 2D spatial distribution consistently captured the four EPB clusters over *** tomography results were validated through a classical checkerboard test and comparisons with other ionospheric data sources,such as the Global Ionospheric Map(GIM)and International Reference Ionosphere(IRI)*** of the results demonstrates the capability of the Indonesian GNSS network to measure peak ionospheric *** findings highlight the potential for future three-dimensional research of plasma bubbles in low-latitude regions using existing GNSS networks,with extensive longitudinal coverage.

关键词： EPB Indonesian GNSS Network 3D tomography

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia

Application of Internet of Things to agriculture—The LQ-FieldPheno Platform:A High-Throughput Platform for Obtaining Crop Phenotypes in Field

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research 2023年第3期6卷 17-33页

作者： Jiangchuan Fan Yinglun Li Shuan Yu Wenbo Gou Xinyu Guo Chunjiang Zhao Bejing Key Laboratory of Digital Plant National Engineering Research Center for Information Technology in AgricultureBeijing 100097China Beijing research center for information technology in agriculture.Beijing Academy of agriculture and Forestry Sciences Bejing 100097China China nationalengineering research center for information technology in agriculture(NERCITA) Beijing 100097China

The lack of efficient crop phenotypic measurement methods has become a bottleneck in the field of breeding and precision ***,high-throughput and accurate phenotypic measurement could accelerate the breeding and improve the existing cultivation management *** view of this,this paper introduces a high-throughput crop phenotype measurement platform named the LQ-FieldPheno,which was developed by China national Agricultural information engineering technology research *** proposed platform represents a mobile phenotypic high-throughput automatic acquisition system based on a field track platform,which introduces the Internet of Things(IoT)into agricultural *** proposed platform uses the crop phenotype multisensor central imaging unit as a core and integrates different types of equipment,including an automatic control system,upward field track,intelligent navigation vehicle,and environmental ***,it combines an RGB camera,a 6-band multispectral camera,a thermal infrared camera,a 3-dimensional laser radar,and a deep *** software is developed to control motions and sensors and to design run *** wireless sensor networks and mobile communication wireless networks of IoT,the proposed system can obtain phenotypic information about plants in their growth period with a high-throughput,automatic,and high time ***,the LQ-FieldPheno has the characteristics of multiple data acquisition,vital timeliness,remarkable expansibility,high-cost performance,and flexible *** LQ-FieldPheno has been operated in the 2020 maize growing season,and the collected point cloud data are used to estimate the maize plant *** with the traditional crop phenotypic measurement technology,the LQ-FieldPheno has the advantage of continuously and synchronously obtaining multisource phenotypic data at different growth stages and extracting different plant *** proposed platform could contrib

关键词： IoT networks Platform

Estimating Wheat Grain Protein Content Using Multi-Temporal Remote Sensing Data Based on Partial Least Squares Regression

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Journal of Integrative agriculture 2012年第9期11卷 1445-1452页

作者： LI Cun-jun WANG Ji-hua WANG Qian WANG Da-cheng SONG Xiao-yu WANG Yan HUANGWen-jiang Beijing research center for information technology in agriculture Beijing 100097 P.R.China national engineering research center for information technology in agriculture Beijing 100097 P.R.China

Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.

关键词： grain protein content agronomic parameters multi-temporal Landsat partial least squares regression