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Atmosphere
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Intelligent Modeling of the Ionosphere and Troposphere for Radio Application
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Intelligent Modeling of the Ionosphere and Troposphere for Radio Application

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 9271

Special Issue Editors

Dr. Jian Wang

E-Mail Website
Guest Editor
School of Microelectronics, Tianjin University, Tianjin 300072, China
Interests: space weather; intelligent modeling; radio propagation; wireless communication
Dr. Yu Zheng

E-Mail Website
Guest Editor
College Electronic Information, Qingdao University, Qingdao 266071, China
Interests: ionospheric monitoring; space environment; radio propagation; inverse problem
Dr. Jieqing Fan

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Interests: intelligent modeling; radio propagation; THz communication

Special Issue Information

Dear Colleagues,

Since the latter half of the 20th century, the rapid advancement of wireless communication technology has profoundly influenced every facet of daily life, creating an imperative and practical demand for comprehending space weather in the cognitive realm and acquiring expertise in the principles of radio wave propagation. In recent decades, substantial achievements have been made in space weather science and radio wave propagation research. However, complex challenges persist due to this field's interdisciplinary nature and extensive investigation scope, awaiting resolution. Moreover, introducing artificial intelligence technology has further invigorated space weather science and radio wave propagation, positioning them as vibrant and burgeoning disciplines.

This Special Issue aims to improve our understanding of the characteristics of the electromagnetic environment and electromagnetic wave propagation in the ionosphere and troposphere for radio applications using intelligent modeling techniques. To develop a deeper insight into coupling processes between the electromagnetic environment and electromagnetic wave propagation, this Special Issue will focus on observations, models, simulations, innovative algorithms, and intelligent modeling techniques applied in the solar activity cycle, the ionosphere, the troposphere, and multi-physics coupling.

This Special Issue welcomes papers that discuss innovative multidisciplinary and multiparameter methods and applications for the modeling of phenomena in the solar activity cycle, the ionosphere, and the troposphere, as well as the possible interactions and indications of electromagnetic effects.

Dr. Jian Wang
Dr. Yu Zheng
Dr. Jieqing Fan
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ionosphere
  • troposphere
  • solar activity
  • space weather
  • radio propagation
  • ground-based and satellite observations
  • intelligent modeling
  • multi-physics coupling
  • natural geo-hazard

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Published Papers (11 papers)

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Research

14 pages, 2190 KiB  
Article
Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
by Jing Peng, Yunbin Yuan, Yanwen Liu, Hongxing Zhang, Ting Zhang, Yifan Wang and Zelin Dai
Atmosphere 2024, 15(8), 958; https://doi.org/10.3390/atmos15080958 - 12 Aug 2024
Viewed by 229
Abstract
The ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based [...] Read more.
The ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based on GNSS-TEC data from 2015 and 2019. The electron density profiles and NmF2 calculated by the IRI-2016 model (upda-IRI-2016) driven by the updated IG12 value (IG-up) were evaluated for their accuracy using ionosonde observations and COSMIC inversion data. The experiments show that both the electron density profiles and NmF2 calculated by upda-IRI-2016 driven by IG-up show significant optimization effects, compared to the IRI-2016 model driven by IG12. For electron density, the precision improvement (PI) for both MAE and RMSE at the Beijing station exceed 31.2% in January 2015 and 16.0% in January 2019. While the PI of MAE and RMSE at the Wuhan station, which is located at a lower latitude, both exceed 32.5% in January 2015, both exceed 42.1% in January 2019, which is significantly higher than that of the Beijing station. In 2015, the PI of MAE and RMSE compared with COSMIC are both higher than 20%. For NmF2, the PI is greater for low solar activity years and low latitude stations, with the Wuhan station showing a PI of more than 11.7% in January 2019 compared to January 2015. The PI compared to COSMIC was higher than 17.2% in 2015. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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13 pages, 2327 KiB  
Article
Polynomial Fitting-Based Noise Reduction for Correlation Functions in Medium-Frequency Radar
by Jinsong Chen, Yang Zhang, Liming Wang, Guoqin Kang, Na Li and Junfeng Wei
Atmosphere 2024, 15(8), 899; https://doi.org/10.3390/atmos15080899 - 27 Jul 2024
Viewed by 283
Abstract
In the theoretical calculation of atmospheric wind fields using the cross-correlation analysis method of Medium-Frequency radar, it is necessary to compute a series of correlation parameters from the received echo signals, such as autocorrelation and cross-correlation functions, within the main lobe range of [...] Read more.
In the theoretical calculation of atmospheric wind fields using the cross-correlation analysis method of Medium-Frequency radar, it is necessary to compute a series of correlation parameters from the received echo signals, such as autocorrelation and cross-correlation functions, within the main lobe range of the antenna array to retrieve atmospheric parameters. However, both theoretical analysis and practical applications have shown that the shape of correlation functions can be affected by atmospheric conditions and receiver noise, leading to significant biases in the estimated correlation parameters within the main lobe range. In this study, we theoretically analyze the influence of noise on the amplitude of autocorrelation and cross-correlation functions. We propose a noise reduction method based on the characteristics of correlation functions at the zero-delay point to calculate the noise factor and process the correlation functions within the main lobe range. Furthermore, we conduct simulation analysis to evaluate the performance of this noise reduction method and summarize the effects of the number of fitting points and fitting methods on the noise reduction performance. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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17 pages, 3539 KiB  
Article
Investigation and Validation of Short-Wave Scattering in the Anisotropic Ionosphere under a Geomagnetic Field
by Zhigang Zhang, Jingyi She, Hongwei Fu, Lin Zhao and Shengyun Ji
Atmosphere 2024, 15(7), 767; https://doi.org/10.3390/atmos15070767 - 27 Jun 2024
Viewed by 343
Abstract
Short-wave communication, operating within the frequency range of 3–30 MHz, is extensively employed for long-distance communication because of its extended propagation range and robustness. The ionosphere undergoes complex transformations when influenced by the geomagnetic field, evolving into an uneven and anisotropic electromagnetic medium. [...] Read more.
Short-wave communication, operating within the frequency range of 3–30 MHz, is extensively employed for long-distance communication because of its extended propagation range and robustness. The ionosphere undergoes complex transformations when influenced by the geomagnetic field, evolving into an uneven and anisotropic electromagnetic medium. This complex property makes the transmission of electromagnetic fields within the ionosphere extremely complex, posing significant challenges for accurately evaluating electromagnetic scattering phenomena. To address the aforementioned challenges, this paper proposes a new method for calculating short-wave ionospheric scattering based on a complex anisotropic multilayer medium transmission matrix. Firstly, by utilizing the characteristic changes of ionospheric electron density with height, the ionization layer is divided into multiple horizontal thin layers, each with an approximately uniform electron density, forming a multilayer horizontal anisotropic structure. Subsequently, the scattering characteristics of electromagnetic waves in the ionosphere were calculated using the transmission matrix approach. The results calculated using this method are consistent with actual measurement values and superior to traditional short-wave ionospheric transmission calculation methods. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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11 pages, 2338 KiB  
Article
A Short-Term Forecasting Method for High-Frequency Broadcast MUF Based on LSTM
by Shengyun Ji, Guojin He, Qiao Yu, Yafei Shi, Jun Hu and Lin Zhao
Atmosphere 2024, 15(5), 569; https://doi.org/10.3390/atmos15050569 - 7 May 2024
Viewed by 712
Abstract
This paper proposes a short-term forecasting method for high-frequency broadcast Maximum Usable Frequency (MUF) based on Long Short-Term Memory (LSTM) to meet the demand for refined and precise high-frequency broadcast coverage. Based on the existing infrastructure of broadcast and television stations, we established [...] Read more.
This paper proposes a short-term forecasting method for high-frequency broadcast Maximum Usable Frequency (MUF) based on Long Short-Term Memory (LSTM) to meet the demand for refined and precise high-frequency broadcast coverage. Based on the existing infrastructure of broadcast and television stations, we established an experimental verification system to collect data for approximately three years. Two links were selected based on data quality: Urumqi to Lhasa and Lanzhou to Lhasa. A short-term forecast of MUF was conducted using the data from these two links. Comparison and analysis were conducted between the forecasting results of our model and those of the REC533 model. Our proposed method outperforms the REC533 forecasting results overall, with a reduction in root mean square error (RMSE) of 0.66 MHz and an improvement in forecast accuracy of 14.77%. The comparison result demonstrates the feasibility and accuracy of our model. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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19 pages, 17966 KiB  
Article
Improved Ionospheric Total Electron Content Maps over China Using Spatial Gridding Approach
by Fucheng Song and Shuangshuang Shi
Atmosphere 2024, 15(3), 351; https://doi.org/10.3390/atmos15030351 - 13 Mar 2024
Viewed by 914
Abstract
Precise regional ionospheric total electron content (TEC) models play a crucial role in correcting ionospheric delays for single-frequency receivers and studying variations in the Earth’s space environment. A particle swarm optimization neural network (PSO-NN)-based model for ionospheric TEC over China has been developed [...] Read more.
Precise regional ionospheric total electron content (TEC) models play a crucial role in correcting ionospheric delays for single-frequency receivers and studying variations in the Earth’s space environment. A particle swarm optimization neural network (PSO-NN)-based model for ionospheric TEC over China has been developed using a long-term (2008–2021) ground-based global positioning system (GPS), COSMIC, and Fengyun data under geomagnetic quiet conditions. In this study, a spatial gridding approach is utilized to propose an improved version of the PSO-NN model, named the PSO-NN-GRID. The root-mean-square error (RMSE) and mean absolute error (MAE) of the TECs estimated from the PSO-NN-GRID model on the test data set are 3.614 and 2.257 TECU, respectively, which are 7.5% and 5.5% smaller than those of the PSO-NN model. The improvements of the PSO-NN-GRID model over the PSO-NN model during the equinox, summer, and winter of 2015 are 0.4–22.1%, 0.1–12.8%, and 0.2–26.2%, respectively. Similarly, in 2019, the corresponding improvements are 0.5–13.6%, 0–10.1%, and 0–16.1%, respectively. The performance of the PSO-NN-GRID model is also verified under different solar activity conditions. The results reveal that the RMSEs for the TECs estimated by the PSO-NN-GRID model, with F10.7 values ranging within [0, 80), [80, 100), [100, 130), [130, 160), [160, 190), [190, 220), and [220, +), are, respectively, 1.0%, 2.8%, 4.7%, 5.5%, 10.1%, 9.1%, and 28.4% smaller than those calculated by the PSO-NN model. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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13 pages, 3439 KiB  
Article
Novel Intelligent Methods for Channel Path Classification and Model Determination Based on Blind Source Signals
by Li-Feng Cao, Cheng-Guo Liu, Run-Sheng Cheng, Guang-Pu Tang, Tong Xiao, Li-Feng Huang and Hong-Guang Wang
Atmosphere 2024, 15(3), 280; https://doi.org/10.3390/atmos15030280 - 26 Feb 2024
Viewed by 969
Abstract
In this paper, the urban signal propagation characteristics based on the location of blind sources are investigated. To address the issue of blind electromagnetic radiation sources in complex urban environments, intelligent methods for propagation channel path classification, and model determination are brought forth [...] Read more.
In this paper, the urban signal propagation characteristics based on the location of blind sources are investigated. To address the issue of blind electromagnetic radiation sources in complex urban environments, intelligent methods for propagation channel path classification, and model determination are brought forth based on field test data. The intelligent classification method distinguishes between the Line-of-Sight (LoS) path channel and a direct path, the LoS multipath channel with a direct path and other multiple paths, and the Non-Line-of-Sight (NLoS) multipath channel without a direct path from the source to the test point. The modeling aspect determines the model type to which the received signal belongs based on the statistical model derived from the tested data of a specific source. A validation measurement system was constructed for the FM broadcasting band, and validation campaigns were conducted in the city of Wuhan. The process and analysis of the data using this method demonstrate the accurate distinction of the different propagation path channels and models and involve the construction of a statistical model for the FM band in Wuhan’s urban area. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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15 pages, 10042 KiB  
Article
The Influence of PE Initial Field Construction Method on Radio Wave Propagation Loss and Tropospheric Duct Inversion
by Run-Sheng Cheng, Cheng-Guo Liu, Li-Feng Cao, Tong Xiao, Guang-Pu Tang, Li-Feng Huang and Hong-Guang Wang
Atmosphere 2024, 15(1), 46; https://doi.org/10.3390/atmos15010046 - 29 Dec 2023
Cited by 1 | Viewed by 1121
Abstract
Parabolic equations (PE) are commonly employed for calculating the spatial propagation loss of wireless signals. The initial field is a crucial factor. To investigate the impact of construction accuracy on the calculation of radio wave propagation loss, we selected the half-wave dipole antenna [...] Read more.
Parabolic equations (PE) are commonly employed for calculating the spatial propagation loss of wireless signals. The initial field is a crucial factor. To investigate the impact of construction accuracy on the calculation of radio wave propagation loss, we selected the half-wave dipole antenna and its Gaussian approximation to examine the influence of wide-angle PE modeling. We analyzed the disparities between the actual antenna pattern and the Gaussian beam approximation, as well as the discrepancies in the corresponding initial field and the calculation of radio wave propagation loss in PE modeling. The simulation results indicate that the error of the Gaussian approximation increases as the angle of departure from the antenna main beam increases, with a relative error of approximately 30% in the initial field. A comparison between the experimental test of the broadcast signal and the simulation calculation reveals that the model based on the actual antenna aligns more closely with the measured value on a flat underlying surface. However, in mountainous areas with significant fluctuations, the simulation results are consistent with each other and higher than the measured value. The inversion results obtained through the particle swarm optimization algorithm demonstrate that the model based on the actual antenna exhibits superior inversion accuracy for the tropospheric atmospheric duct structure. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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13 pages, 2259 KiB  
Article
Oscillations of GW Activities in the MLT Region over Mid-Low-Latitude Area, Kunming Station (25.6° N, 103.8° E)
by Na Li, Jinsong Chen, Jianyuan Wang, Lei Zhao, Zonghua Ding and Guojin He
Atmosphere 2023, 14(12), 1810; https://doi.org/10.3390/atmos14121810 - 11 Dec 2023
Cited by 1 | Viewed by 901
Abstract
Gravity wave (GW) activities play a prominent role in the complex coupling process of wave–wave and wave–background circulation around mid-low-latitude and equatorial areas. The wavelengths are wide, from about 10 m to 100 km, with a period from minutes to hours. However, the [...] Read more.
Gravity wave (GW) activities play a prominent role in the complex coupling process of wave–wave and wave–background circulation around mid-low-latitude and equatorial areas. The wavelengths are wide, from about 10 m to 100 km, with a period from minutes to hours. However, the oscillations of GW activities are apparently different between the period bands of 0.1 to 1 h (HF) and 1 to 5 h (LF). To further understand the characteristics of GW activities, the neutral winds during 2008–2009 with a resolution of 3 min obtained from a medium-frequency (MF) radar in Kunming (25.6° N, 103.8° E) were analyzed. Using two numerical filters, the HF and LF GWs were estimated. Interestingly, the power spectral density grows larger as the frequency increases. It linearly falls with decreasing frequency when the period is less than 2 h. The seasonal variations in both HF and LF GWs are strongly demonstrated in August–September, November, and February–March with maximum meridional variances of 1100 m2 s−2 and 500 m2 s−2 and maximum zonal variances of 800 m2 s−2 and 350 m2 s−2 in, respectively. The turbulent velocity was also calculated and shows similar oscillations with GW activities. Furthermore, the GW propagation direction exhibits strong seasonal variations, which may be dependent on the location of the motivating source and background wind. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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13 pages, 2359 KiB  
Article
Variation of Electron Density in the D-Region Using Kunming MF Radar under Low Solar Activity
by Zhimei Tang, Na Li, Jianyuan Wang, Zonghua Ding, Liandong Dai, Lei Zhao and Jinsong Chen
Atmosphere 2023, 14(12), 1764; https://doi.org/10.3390/atmos14121764 - 29 Nov 2023
Cited by 2 | Viewed by 883
Abstract
So far, the least is known about the D-region ionosphere out of the entire ionosphere due to the lack of a conventional detecting method and continuous data accumulation. Medium frequency (MF) radar is an important conventional tool for understanding the D-region ionosphere by [...] Read more.
So far, the least is known about the D-region ionosphere out of the entire ionosphere due to the lack of a conventional detecting method and continuous data accumulation. Medium frequency (MF) radar is an important conventional tool for understanding the D-region ionosphere by measuring the electron density (Ne) within the height range of 60–90 km. To investigate the statistical variation of the D-region, especially at the mid-low latitude area, this study presents the statistical variations in the D-region Ne with the solar zenith angle (SZA), season, and altitude observed by Kunming MF radar (25.6° N, 103.8° E) under low solar activity (2008–2009). The diurnal variation of Ne behaves like typical diurnal changes, which are closely consistent with the SZA. The outstanding feature, the diurnal asymmetry phenomenon, significantly appears in different seasons and at different altitudes. The Ne has obvious semi-annual characteristics, and is larger in summer and fall and the smallest in winter. Compared to other seasons, the variation in the Ne with altitude is the most stable in summer. Due to the impacts of the highest SZA, the value of Ne in winter is the smallest, with a maximum value of less than 300 electrons/cm3, and the largest in summer and fall, with a maximum of 472 electrons/cm3. Particularly, the peaks of Ne above 76 km do not always appear at the time when the SZA is the smallest (at noon). Both the simulations by the International Reference Ionosphere (IRI2016) and observations using MF radar present a strong positive correlation with solar radiation. Meanwhile, it cannot be ignored that there were still large differences between the simulations and observations. To quantitatively analyze the differences between the observations and simulations, the observed value was subtracted from the simulated value. The results show that the maximum value between them was up to 350 electrons/cm3, and the minimum difference appeared at around 72 km, with a value less than 100 electrons/cm3. However, below 66 km, the observations were larger than the simulations, which were, on the contrary, above 76 km. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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14 pages, 3516 KiB  
Communication
Design and Verification of Assessment Tool of Shortwave Communication Interference Impact Area
by Guojin He, Shengyun Ji, Rongjun Wu, Qiao Yu, Yanan Liu, Yafei Shi and Na Li
Atmosphere 2023, 14(12), 1728; https://doi.org/10.3390/atmos14121728 - 24 Nov 2023
Viewed by 912
Abstract
In the field of electronic communication warfare, accurately predicting the range and intensity of shortwave interference signals presents a significant challenge due to the complex interplay between the ionospheric parameters and the electromagnetic environment. To address this challenge, we designed a novel tool [...] Read more.
In the field of electronic communication warfare, accurately predicting the range and intensity of shortwave interference signals presents a significant challenge due to the complex interplay between the ionospheric parameters and the electromagnetic environment. To address this challenge, we designed a novel tool to assess the interference impact area of shortwave interference signals in a dynamically changing ionospheric environment. Considering sophisticated ionospheric radio wave propagation models and innovative spatial grid methods, this tool finishes the comprehensive spatial distribution of the interference impact area and delivers grid-based insights into the interference intensity. Furthermore, the test verification of the tool demonstrated a mean error of 8.42 dB between the measured and simulated results, underscoring the efficacy and reliability of this tool. This pioneering work is poised to make substantial contributions to the field of communication electronic warfare and holds significant promise for guiding the development of interference countermeasures. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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12 pages, 5540 KiB  
Article
A Reconstruction Method for Ionospheric foF2 Spatial Mapping over Australia
by Yiran Liu, Qiao Yu, Yafei Shi, Cheng Yang and Jian Wang
Atmosphere 2023, 14(9), 1399; https://doi.org/10.3390/atmos14091399 - 5 Sep 2023
Cited by 1 | Viewed by 856
Abstract
To improve the accuracy of predicting the ionospheric critical frequency of the F2 layer (foF2), a reconstruction method for the spatial map of the ionospheric foF2 based on modified geomagnetic dip coordinates is proposed. Based [...] Read more.
To improve the accuracy of predicting the ionospheric critical frequency of the F2 layer (foF2), a reconstruction method for the spatial map of the ionospheric foF2 based on modified geomagnetic dip coordinates is proposed. Based on the strong correlation between the ionospheric foF2 and geomagnetic coordinates, the variation function of ionospheric distance is built. In the end, the spatial map of the ionospheric foF2 is predicted by solving the Kriging equation. The results show that the regional characteristics of the ionospheric foF2 analyzed by the proposed method are consistent with the observations. Compared with the reconstructed value of foF2 using traditional geographic coordinates, the root-mean-square error (RMSE) in high solar activity years decreased by 0.43 MHz, and the relative RMSE decreased by 5.48%; The RMSE decreased by 0.35 MHz during low solar activity which is 5.99% lower to relative RMSE. The research results provide support for high-frequency communication frequency selection. Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
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