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Kimura, Yoshiki; Yamaguchi, Tomoki
Radioisotopes, 74(3), p.251 - 264, 2025/11
Radioisotope identification (RIID) by gamma-ray spectral analysis has been widely used, and accurate identification of radioisotopes is an important issue in various fields. Handheld instruments are commonly used for on-site RIID but often suffer from limited performance. This paper proposes a spectral deconvolution using unsupervised neural network models for RIID with handheld instruments in field use. This approach allows optimization of the neural network for deconvolution based on a measured spectrum combined with an energy-broadening matrix, and it does not require extensive training datasets or the precise modeling of the detector and measurement conditions. The performance of the proposed approach was examined in simulated and measured spectra, assuming the measurements of several radioisotopes with CsI(Tl) spectrometers. It was demonstrated that the unsupervised neural network models can improve the peak resolution more significantly compared to conventional deconvolution algorithms and contribute to RIID performance in the low energy resolution spectra.
Shikaze, Yoshiaki
Radioisotopes, 74(3), p.273 - 287, 2025/11
The previous method used the data during the stable period for the position and attitude angles of the unmanned helicopter as a countermeasure to improve the measurement data analysis of the Compton camera system mounted on the unmanned helicopter. However, this reduced the number of events used for analysis, allowing statistical accuracy to be improved in future. Therefore, all event data were corrected and used this time. The scintillator coordinates of two layers fixed in the previous analysis were replaced with those corrected for the ever-changing positions and tilts for each event. I reconstructed gamma-ray images using the corrected events to improve their statistical accuracy and spatial resolution. I compared the ground measurement results to evaluate the improvement in the accuracy of the reconstructed images of gamma-ray intensity. As for the effect of the improved statistics, a decrease in the residual sum of squares (RSS) was noted after improvement, indicating the effectiveness of this method through good correlations with the ground-measured values. Moreover, from the RSS value comparison, compared to changing from the previous method to the improved method, expanding the range of averaging the measured values was confirmed to be more effective, showing better correlations with the ground-measured values.
Sato, Tatsuhiko
Radioisotopes, 74(2), p.183 - 188, 2025/07
no abstracts in English
Kinase, Masami
Radioisotopes, 74(2), p.233 - 238, 2025/07
no abstracts in English
Sato, Yuki
Radioisotopes, 74(1), p.141 - 148, 2025/03
no abstracts in English
Okita, Shoichiro; Abe, Yutaka*; Tasaki, Seiji*; Fukaya, Yuji
Radioisotopes, 73(3), p.233 - 240, 2024/11
Kimura, Yoshiki; Tsuchiya, Kenichi*
Radioisotopes, 72(2), p.121 - 139, 2023/07
Rapid and precise radioisotope identification in the scene of nuclear detection and nuclear security incidents is one of the challenging issues for the prompt response on the detection alarm or the incidents. A radioisotope identification algorithm using a deep artificial neural network model applicable to handheld gamma-ray detectors has been proposed in the present paper. The proposed algorithm automatically identifies gamma-emitting radioisotopes based on the count contribution ratio (CCR) from each of them estimated by the deep artificial neural network model trained by simulated gamma-ray spectra. The automated radioisotope identification algorithm can support first responders of nuclear detection and nuclear security incidents without sufficient experience and knowledge in radiation measurement. The authors tested the performance of the proposed algorithm using two different types of deep artificial neural network models in application to handheld detectors having high or low energy resolution. The proposed algorithm showed high performance in identifying artificial radioisotopes for actually measured gamma-ray spectra. It was also confirmed that the algorithm is applicable to identifying 
U and automated uranium categorization by analyzing estimated CCRs by the deep artificial neural network models. The authors also com-pared the performance of the proposed algorithm with a conventional radioisotope identification method and discussed promising ways to improve the performance of the algorithm using the deep artificial neural network.
Hagiwara, Kenta*; Ochi, Kotaro; Koike, Yuya*
Radioisotopes, 70(4), p.227 - 237, 2021/05
Behavior of radioactive caesium in river water and sediment in Tama river was investigated during 2012-2016. Concentrations of radioactive caesium in river water and sediment were decreased with time exponentially. Concentrations of suspended radioactive caesium, and radioactive caesium in sediment temporarily increased when sediments were resuspended due to rain. On the other hand, dissolved radioactive caesium was not easily impacted by this factor. Sequential extraction, elemental and crystal phase analysis were performed on the sediments and examined the chemical state of radioactive caesium as well as the adsorption mechanism. Radioactive caesium in sediment was present in a stable chemical form, and there is possibility that radioactive caesium was incorpolated in biotite.
Hasebe, Noriko*; Sueoka, Shigeru; Tagami, Takahiro*
Radioisotopes, 70(3), p.117 - 130, 2021/03
no abstracts in English
Fukuda, Shoma; Sueoka, Shigeru; Tagami, Takahiro*
Radioisotopes, 70(3), p.173 - 187, 2021/03
Thermochronometric studies (e.g., fission-track thermochronometry) on major orogenic belts, such as collision zones and/or cratons have been successfully conducted since 1970s. However, such studies in arc-trench systems were limited so far. According to the development of thermochrology in three decades, the applicability for these regions has been identified. Thus, recent thermochronometric studies in an island arc setting have been proceeding. This paper introduces the current status of thermochronometric studies for mountain building process on arc-trench settings, especially in island arcs.
Sueoka, Shigeru; Shimada, Koji; Hasebe, Noriko*; Tagami, Takahiro*
Radioisotopes, 70(3), p.189 - 207, 2021/03
no abstracts in English
Ogata, Manabu; Sueoka, Shigeru
Radioisotopes, 70(3), p.159 - 172, 2021/03
no abstracts in English
Kowatari, Munehiko; Tanimura, Yoshihiko; Kessler, P.*; Neumaier, S.*; R
ttger, A.*
Radioisotopes, 70(1), p.1 - 18, 2021/01
-ray spectrometryYamada, Takashi*; Asai, Masato; Yonezawa, Chushiro*; Kakita, Kazutoshi*; Hirai, Shoji*
Radioisotopes, 69(9), p.287 - 297, 2020/09
We have confirmed that the commercially available Japanese "standard" gamma-ray analysis programs do not consider the effect of sample volume in calculating true coincidence summing (TCS) corrections, which results in underestimation of 
Cs radioactivity in cylindrical volume samples. In this work, we have developed and examined a practical TCS correction method for general Ge detectors which consider the effect of sample volume properly, and have confirmed that this method can reduce the Cs radioactivity underestimation to less than 1%.
Tsujimura, Norio
Radioisotopes, 69(8), p.253 - 261, 2020/08
The Japan Coast Guard observation vessel Takuyo encountered nuclear fallout originating from a U.S. nuclear weapon test detonated at Bikini Atoll on July 12, 1958. The exposure occurred two days after the detonation when the vessel was sailing southbound, about 300 km west of the danger area set up around the test site. From a small amount of rain sampled at the beginning of a rainsquall, a gross beta radioactivity of 16 kBq/L was observed, but no total precipitation measurement was made at that time. Therefore, the total amount of gross beta activity surface deposition density was alternatively derived based on an indication of a NaI(Tl) scintillation detector placed 0.3-m above the after deck of the Takuyo. By combining the maximum measured dose rate of 3.1 
Sv/h aboard with the results of Monte Carlo simulations, the surface deposition density on the Takuyo was estimated to be 2 PBq/km
, about 10 times higher than the past maximum observed in Japan in 1966. The resultant effective dose to crew members was also estimated to be below 100 Sv over the entire period of the voyage.
Kowatari, Munehiko; Yoshitomi, Hiroshi
Radioisotopes, 68(9), p.595 - 603, 2019/09
Kitatsuji, Yoshihiro
Radioisotopes, 67(10), p.483 - 493, 2018/10
Electrochemical reactions and redox properties of actinides such as uranium and neptunium are outlined. The flow electrolysis enables rapid and high-efficient treatment. It was demonstrated to measure slow processes of actinide redox. Experimental results of electrolysis of actinide ions and the preparation method of oxidation state of the ions based on the fundamental data are described. Mediator reaction and catalysis observed in the process of electrolysis of actinide ions are also explained.
Nagame, Yuichiro
Radioisotopes, 67(10), p.507 - 526, 2018/10
Recent studies of the chemical separation and characterization experiments of the first three transactinide elements, rutherfordium (Rf), dubnium (Db) and seaborgium (Sg), conducted atom-at-a-time in liquid phases, are reviewed. A short description on experimental techniques based on partition methods, specifically automated rapid chemical separation systems, as well as on assessment of role of relativistic effects is also given. Perspectives for liquid phase chemistry experiments on heavier elements are briefly discussed.
Kambe, Shinsaku
Radioisotopes, 67(8), p.389 - 401, 2018/08
no abstracts in English
Koura, Hiroyuki
Radioisotopes, 67(6), p.267 - 275, 2018/06
no abstracts in English
