Pub Date : 2019-06-30DOI: 10.24246/IJPNA.V4I2.39-44
Sista Dyah Wijaya, Bagaswoto Poedjomartono, Y. Sardjono
BNCT is an alternate therapy for treating cancer. The principle of BNCT involves a neutron boron uptake and a fission reaction that produce alpha particles and Li ions with a high level of linear energy transfer in the tissue. It is effective in killing tumor cells. To administer boron in the tumor cells, a boron delivery agent is needed. Thus far, there are a variety of boron delivery agents that have been developed. To date, just two main boron-based drugs, BPA and BSH, have been used for clinical studies. Many other boron delivery agents have been evaluated in vivo and in vitro but have not been evaluated clinically. Therefore, the other boron delivery agents have not been used in BNCT clinical studies.
{"title":"In Vitro and In Vivo Test of Boron Delivery Agent for BNCT","authors":"Sista Dyah Wijaya, Bagaswoto Poedjomartono, Y. Sardjono","doi":"10.24246/IJPNA.V4I2.39-44","DOIUrl":"https://doi.org/10.24246/IJPNA.V4I2.39-44","url":null,"abstract":"BNCT is an alternate therapy for treating cancer. The principle of BNCT involves a neutron boron uptake and a fission reaction that produce alpha particles and Li ions with a high level of linear energy transfer in the tissue. It is effective in killing tumor cells. To administer boron in the tumor cells, a boron delivery agent is needed. Thus far, there are a variety of boron delivery agents that have been developed. To date, just two main boron-based drugs, BPA and BSH, have been used for clinical studies. Many other boron delivery agents have been evaluated in vivo and in vitro but have not been evaluated clinically. Therefore, the other boron delivery agents have not been used in BNCT clinical studies.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114509296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.24246/IJPNA.V4I2.58-65
Y. Sardjono
Based Studies were carried out to analyze the internal dose of radiation for workers at Boron Neutron Capture Therapy (BNCT) facility base on Cyclotron 30 MeV with BSA and a room that was actually designed before. This internal dose analyzation included interaction between neutrons and air. The air contained N2 (72%), O2 (20%), Ar (0.93%), CO2, Neon, Kripton, Xenon, Helium and Methane. That internal dose to the worker should be below the dose limit for radiation workers which is an amount of 20 mSv/years. From the particles that are present in the air, only Nitrogen and Argon can change into radioactive element. Nitrogen-14 activated to Carbon-14, Nitrogen-15 activated to Nitrogen-16, and Argon-40 activated to Argon-41. Calculation using tally facility in Monte Carlo N Particle version Extended (MCNPX) program for calculated Neutron flux in the air 3.16x107 Neutron/cm2s. The room design in the cancer facility has a measurement of 200 cm in length, 200 cm in width, and 166.40 cm in height. Neutron flux can be used to calculate the reaction rate which is 80.1x10-2 reaction/cm3s for carbon-14 and 8.75x10-5 reaction/cm3s. The internal dose exposed to the radiation worker is 9.08E-9 µSv.
{"title":"MONTE CARLO N PARTICLE EXTENDED (MCNPX) RADIATION SHIELD MODELLING ON BORON NEUTRON CAPTURE THERAPY FACILITY USING D-D NEUTRON GENERATOR 2.4 MeV","authors":"Y. Sardjono","doi":"10.24246/IJPNA.V4I2.58-65","DOIUrl":"https://doi.org/10.24246/IJPNA.V4I2.58-65","url":null,"abstract":"Based Studies were carried out to analyze the internal dose of radiation for workers at Boron Neutron Capture Therapy (BNCT) facility base on Cyclotron 30 MeV with BSA and a room that was actually designed before. This internal dose analyzation included interaction between neutrons and air. The air contained N2 (72%), O2 (20%), Ar (0.93%), CO2, Neon, Kripton, Xenon, Helium and Methane. That internal dose to the worker should be below the dose limit for radiation workers which is an amount of 20 mSv/years. From the particles that are present in the air, only Nitrogen and Argon can change into radioactive element. Nitrogen-14 activated to Carbon-14, Nitrogen-15 activated to Nitrogen-16, and Argon-40 activated to Argon-41. Calculation using tally facility in Monte Carlo N Particle version Extended (MCNPX) program for calculated Neutron flux in the air 3.16x107 Neutron/cm2s. The room design in the cancer facility has a measurement of 200 cm in length, 200 cm in width, and 166.40 cm in height. Neutron flux can be used to calculate the reaction rate which is 80.1x10-2 reaction/cm3s for carbon-14 and 8.75x10-5 reaction/cm3s. The internal dose exposed to the radiation worker is 9.08E-9 µSv.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130777165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.24246/IJPNA.V4I2.33-38
T. H. Susanto
The purpose of this study is to determine the characteristics of the cooling system on the new design of the Kartini Reactor plate fuel based on numerical calculations (Computational Fluid Dynamics). The fuel plate model was simplified and made in 3D. The model dimensions are 17.3 mm x 68 mm x 900 mm. The space between the two plates called the narrow rectangular channels has a gap of 2 mm. On these simulations a heat flux of 10612,7 watt/m2 was used which was obtained from the MCNP calculation program. Simulations were conducted in a steady state condition and single-phase model laminar flow of an incompressible fluid through the gap between the two fuel plates. This simulation uses UDF (User Define Function) to approach heat flux behaviour that follows the neutron distribution in the reactor core. The simulation results show that the maximum temperature that occur at a flow rate of 0.01 m/s was 43.5 °C.
{"title":"COMPUTATIONAL FLUID DYNAMICS SIMULATION OF KARTINI REACTOR FUELED PLATE","authors":"T. H. Susanto","doi":"10.24246/IJPNA.V4I2.33-38","DOIUrl":"https://doi.org/10.24246/IJPNA.V4I2.33-38","url":null,"abstract":"The purpose of this study is to determine the characteristics of the cooling system on the new design of the Kartini Reactor plate fuel based on numerical calculations (Computational Fluid Dynamics). The fuel plate model was simplified and made in 3D. The model dimensions are 17.3 mm x 68 mm x 900 mm. The space between the two plates called the narrow rectangular channels has a gap of 2 mm. On these simulations a heat flux of 10612,7 watt/m2 was used which was obtained from the MCNP calculation program. Simulations were conducted in a steady state condition and single-phase model laminar flow of an incompressible fluid through the gap between the two fuel plates. This simulation uses UDF (User Define Function) to approach heat flux behaviour that follows the neutron distribution in the reactor core. The simulation results show that the maximum temperature that occur at a flow rate of 0.01 m/s was 43.5 °C.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129185949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-26DOI: 10.24246/IJPNA.V3I3.89-94
D. Kusnandar, N. N. Debataraja, Shantika Marthal
Copula is a method that examines the relationship pattern between variables. Copula is characterized as a nonparametric method with several benefits, i.e., it is independent of the assumption of the distribution, accommodates nonlinear relationship among variables, and is convenient in building joint distribution. This study investigates the relationship and prediction analysis using the copula approach. The method is applied to the monthly data of oil palm production and the amount of rainfall. The results show that the model of Frank Copula is the best model for rainfall and oil palm production relationship.
{"title":"COPULA MODELING IN ANALYSIS OF DEPENDENCY OF OIL PALM PRODUCTION AND RAINFALL","authors":"D. Kusnandar, N. N. Debataraja, Shantika Marthal","doi":"10.24246/IJPNA.V3I3.89-94","DOIUrl":"https://doi.org/10.24246/IJPNA.V3I3.89-94","url":null,"abstract":"Copula is a method that examines the relationship pattern between variables. Copula is characterized as a nonparametric method with several benefits, i.e., it is independent of the assumption of the distribution, accommodates nonlinear relationship among variables, and is convenient in building joint distribution. This study investigates the relationship and prediction analysis using the copula approach. The method is applied to the monthly data of oil palm production and the amount of rainfall. The results show that the model of Frank Copula is the best model for rainfall and oil palm production relationship.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131964791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-26DOI: 10.24246/ijpna.v3i3.83-88
Iklas Sanubary
A study of brain tumor detection has been done by making use of backpropagation neural networks with Gray Level Co-Occurrence Matrix (GLCM) feature extraction. CT-Scan images of the brain consist of 12 normal and 13 abnormal (tumor) brain images are analyzed. The preprocessing stage begins with cropping the image to a 256 x 256 pixels picture, then converting the colored images into grayscale images, and equalizing the histogram to improve the quality of the images. GLCM is used to calculate statistical features determined by 5 parameters i.e., contrast, correlation, energy and homogeneity for each direction. In these backpropagation neural networks, the [12 2 1] architecture is used. The correlation coefficient between the target and the output for the training data is 0.999, while the correlation coefficient for the testing data is 0.959 with an accuracy of 70%. The results of this research indicate that backpropagation neural networks can be used for the detection of brain tumors.
利用灰度共生矩阵(GLCM)特征提取的反向传播神经网络进行了脑肿瘤检测研究。脑ct扫描图像由12张正常和13张异常(肿瘤)脑图像组成。预处理阶段首先将图像裁剪为256 x 256像素的图像，然后将彩色图像转换为灰度图像，并均衡直方图以提高图像质量。GLCM用于计算每个方向上由对比度、相关性、能量和均匀性5个参数决定的统计特征。在这些反向传播神经网络中，使用了[12 21]架构。训练数据的目标与输出的相关系数为0.999，测试数据的相关系数为0.959，准确率为70%。研究结果表明，反向传播神经网络可以用于脑肿瘤的检测。
{"title":"BRAIN TUMOR DETECTION USING BACKPROPAGATION NEURAL NETWORKS","authors":"Iklas Sanubary","doi":"10.24246/ijpna.v3i3.83-88","DOIUrl":"https://doi.org/10.24246/ijpna.v3i3.83-88","url":null,"abstract":"A study of brain tumor detection has been done by making use of backpropagation neural networks with Gray Level Co-Occurrence Matrix (GLCM) feature extraction. CT-Scan images of the brain consist of 12 normal and 13 abnormal (tumor) brain images are analyzed. The preprocessing stage begins with cropping the image to a 256 x 256 pixels picture, then converting the colored images into grayscale images, and equalizing the histogram to improve the quality of the images. GLCM is used to calculate statistical features determined by 5 parameters i.e., contrast, correlation, energy and homogeneity for each direction. In these backpropagation neural networks, the [12 2 1] architecture is used. The correlation coefficient between the target and the output for the training data is 0.999, while the correlation coefficient for the testing data is 0.959 with an accuracy of 70%. The results of this research indicate that backpropagation neural networks can be used for the detection of brain tumors.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116279846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-26DOI: 10.24246/IJPNA.V3I3.95-101
Kholidah Hasyim, Y. Sardjono, Y. Sumardi
This research was aimed at discovering the optimum concentration of Boron-10 in concentrations range 20 µgram/gram until 35 µgram/gram with Boron Neutron Capture Therapy (BNCT) methods and the shortest time irradiation for cancer therapy. The research about dose analysis of Boron Neutron Capture Therapy (BNCT) to the brain cancer (Glioblastoma Multiform) using MCNPX-Code with a neutron source from Collimated Thermal Column Kartini Research Nuclear has been conducted. This research was a simulation-based experiment using MCNPX, and the data was arranged on a graph using OriginPro 8. The modelling was performed with the brain that contains cancer tissue as a target and the reactor as a radiation source. The variations of Boron concentrations in this research was on 20, 25, 30 and 35 μg/gram tumours. The outputs of MCNP were neutron scattering dose, gamma ray dose and neutron flux from the reactor. Neutron flux was used to calculate the doses of alpha, proton and gamma rays produced by the interaction of tissue material and thermal neutrons. Based on the calculations, the optimum concentration of Boron-10 in tumour tissue was for a 30 µg/gram tumour with the radiation dose in skin at less than 3 Gy. The irradiation times required were 2.79 hours for concentration 20 μg/gram ; 2.78 hours for concentration 25 μg/gram ; 2.77 hours for concentration 30 μg/gram ; 2.8 hours for concentration 35 μg/gram.
{"title":"THE DOSE ANALYSIS OF BORON NEUTRON CAPTURE THERAPY (BNCT) TO THE BRAIN CANCER (GLIOBLASTOMA MULTIFORM) USING MCNPX-CODE WITH NEUTRON SOURCE FROM COLLIMATED THERMAL COLUMN KARTINI RESEARCH NUCLEAR","authors":"Kholidah Hasyim, Y. Sardjono, Y. Sumardi","doi":"10.24246/IJPNA.V3I3.95-101","DOIUrl":"https://doi.org/10.24246/IJPNA.V3I3.95-101","url":null,"abstract":"This research was aimed at discovering the optimum concentration of Boron-10 in concentrations range 20 µgram/gram until 35 µgram/gram with Boron Neutron Capture Therapy (BNCT) methods and the shortest time irradiation for cancer therapy. The research about dose analysis of Boron Neutron Capture Therapy (BNCT) to the brain cancer (Glioblastoma Multiform) using MCNPX-Code with a neutron source from Collimated Thermal Column Kartini Research Nuclear has been conducted. This research was a simulation-based experiment using MCNPX, and the data was arranged on a graph using OriginPro 8. The modelling was performed with the brain that contains cancer tissue as a target and the reactor as a radiation source. The variations of Boron concentrations in this research was on 20, 25, 30 and 35 μg/gram tumours. The outputs of MCNP were neutron scattering dose, gamma ray dose and neutron flux from the reactor. Neutron flux was used to calculate the doses of alpha, proton and gamma rays produced by the interaction of tissue material and thermal neutrons. Based on the calculations, the optimum concentration of Boron-10 in tumour tissue was for a 30 µg/gram tumour with the radiation dose in skin at less than 3 Gy. The irradiation times required were 2.79 hours for concentration 20 μg/gram ; 2.78 hours for concentration 25 μg/gram ; 2.77 hours for concentration 30 μg/gram ; 2.8 hours for concentration 35 μg/gram.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128925477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-23DOI: 10.24246/IJPNA.V3I3.76-82
R. Chiang
The Cs-134 to Cs-137 activity ratio of the Cs-134 and Cs-137 fission products released from failed fuel rods into primary coolant is very useful to identify the exposure along with the fuel batch of the failed fuel. The calculated and measured Cs-137 to Cs-134 radioactivity ratios of failed BWR and PWR fuels are compared and analyzed for better understanding of their relationship. Moreover, the impacts of power uprate and fuel reload outage on calculated Cs-137 to Cs-134 activity ratios are studied and the physics behind the impacts are provided.
{"title":"ANALYSIS OF CS-137 TO CS-134 ACTIVITY RATIO FOR FAILED FUEL EXPOSURE ESTIMATION","authors":"R. Chiang","doi":"10.24246/IJPNA.V3I3.76-82","DOIUrl":"https://doi.org/10.24246/IJPNA.V3I3.76-82","url":null,"abstract":"The Cs-134 to Cs-137 activity ratio of the Cs-134 and Cs-137 fission products released from failed fuel rods into primary coolant is very useful to identify the exposure along with the fuel batch of the failed fuel. The calculated and measured Cs-137 to Cs-134 radioactivity ratios of failed BWR and PWR fuels are compared and analyzed for better understanding of their relationship. Moreover, the impacts of power uprate and fuel reload outage on calculated Cs-137 to Cs-134 activity ratios are studied and the physics behind the impacts are provided.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127320760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-22DOI: 10.24246/IJPNA.V3I3.102-112
I. Maulana
One of the most common causes of death in the world is cancer. Scientists have been trying to find the best cure for cancer ever since it was discovered. There are some ways that are used to treat cancer patients. Lately, scientists have developed a new way in treating cancer, it’s called Boron Neutron Capture Therapy (BNCT). BNCT is a selective cancer therapy, it only selects the cancer cells to be treated and leaves the normal cell untouched. It may have no effect or only a little effect on normal cells. As new knowledge that needs to be known by all people, what is the best way to introduce BNCT? What is the best media to introduce BNCT? Is it enough to just read it in a newspaper or in a book? How about using advanced technology such as animation to introduce BNCT? The use of animation as a form of media to introduce something new is already being done in many fields. Can animation be used as a form of media to introduce BNCT too? Will it be effective? By this study, the author gives information about the effect of using animation as a tool to explain and understand BNCT more.
{"title":"ANIMATION OF BORON NEUTRON CAPTURE CANCER THERAPY","authors":"I. Maulana","doi":"10.24246/IJPNA.V3I3.102-112","DOIUrl":"https://doi.org/10.24246/IJPNA.V3I3.102-112","url":null,"abstract":"One of the most common causes of death in the world is cancer. Scientists have been trying to find the best cure for cancer ever since it was discovered. There are some ways that are used to treat cancer patients. Lately, scientists have developed a new way in treating cancer, it’s called Boron Neutron Capture Therapy (BNCT). BNCT is a selective cancer therapy, it only selects the cancer cells to be treated and leaves the normal cell untouched. It may have no effect or only a little effect on normal cells. As new knowledge that needs to be known by all people, what is the best way to introduce BNCT? What is the best media to introduce BNCT? Is it enough to just read it in a newspaper or in a book? How about using advanced technology such as animation to introduce BNCT? The use of animation as a form of media to introduce something new is already being done in many fields. Can animation be used as a form of media to introduce BNCT too? Will it be effective? By this study, the author gives information about the effect of using animation as a tool to explain and understand BNCT more.","PeriodicalId":383123,"journal":{"name":"Indonesian Journal of Physics and Nuclear Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126910561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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