Vol. 9, 2024

Table of contents

Radiation Technologies in Industry and Environment

GEOCHEMICAL ASPECT OF CAAPUCU HEIGHT AT SOUTHEASTER PARAGUAY BY X-RAY FLUORESCENCE AND NEUTRON ACTIVATION ANALYSIS

Peter Kump, Julio Cabello(♰), Juan F. Facetti Masulli

Pages: 1-5

DOI: 10.37392/RapProc.2024.01

Abstract | References | Full Text (PDF)

The Precambrian in eastern Paraguay is present mainly in two areas in the north and in the south; at the Apa High in the former and at the Caapucu Height in the latter which is constituted by Rio Tebicuary complex; to the north of this river is exposed the Caapucu Hight (Jaguarete Kua plug). Recently, geochemical studies were performed in the Precambrian plug of Fuerte San Carlos, near the Apa River providing analytical data in this regard. In this work hand specimen of granitoid rocks from the southern Jaguarete kua outcrops are studied in some of their major, minor and trace elements aiming to look for relationships with the northern outcrops and their provenance as well as the granitoid type. The analyzed elements were Na, Al, Si, K, Ca, Ti, Mn, Fe, Cu, Zn, Ga, Pb, Rb, Sr, Th, Y, Zr, Nb, Ba, La, Ce, Pr, Nd. Analyses were carried out by EDXRF except for sodium that was analyzed by Neutron Activation. The XRF experiments were carried out using the facility of Josef Stefan Institute in Ljubljana, whereas NAA was done with an Am‐ Be neutron source with a flux of 5 x107ns -1 at the Facultad de Química (UNA), Paraguay. The results of analysis allow to establish inter alia indexes, ratios which are related with crystallization, granitoid type etc. The spidergrams standardized to primordial mantle of refractory elements content, show an enrichment of incompatible elements in the samples. Besides, they resemble to those found in Precambrian (Neoproterozoic) outcrops from the northern area (eastern and the Paraguayan Chaco), as well as from Brazil.
  1. F. Albarede, Geochemistry, Cambridge, UK: Cambridge University Press, 2004.
  2. M. Menzies, N. Rodger, A. Tindle, A. C. Hawkesworth, “Metasomatic and enrichment processes in lithospheric peridotites, an effect of asthenosphere-lithosphere,” in Mantle Metasomatism, M. Menzies. A. C. Hawkesworth, Eds., London, UK: London Academic Press, 1987, ch. 8, pp. 313 – 359.
  3. B. Bonin, Magmatisme et Roches Magmatiques, 2da ed de Petrologie endogene, Paris, France: Dunod, 2004, pp. 208 – 217.
    (B. Bonin, Magmatism and Magmatic Rocks, 2nd ed. Endogenous Petrology, Paris, France: Dunod, 2004, pp. 208 – 217.)
  4. B. W. Chappell, A. J. R. White, “Two contrasting granite types”, Pacific Geology, vol. 8, pp. 173 – 174, 1974.
  5. R. D. Raju, “I-, M-, A- and S-type Granitoids: their attributes and mineralization, with Indian examples,” J. Econ. Geol. Georesource Management, vol. 5, no. 1 – 2, pp. 1 – 23, 2008.
    Retrieved from: https://www.researchgate.net/publication/321992577_I-_M-_A-_and_S-type_Granitoids_Their_Attributes_and_Mineralization_with_Indian_Examples
    Retrieved on: Nov. 15, 2023
  6. K. Breiter, N. Gardenova, V. Kanicky, T. Vaculovic, “Gallium and germanium geochemistry during magmatic fractionation and post magmatic alteration in different types of granitoids: a case of study from Bohemian Massif,” Geol. Carpath, vol. 64, no. 3, pp. 171 – 180, Jun. 2013.
    DOI: 10.2478/geoca-2013-0018
  7. E. B. Eckel, Geology and Mineral resources of Paraguay, Geol. Survey Professional Paper 327, US printing Office, Washington, D.C., USA, 1959.
    DOI: 10.3133/pp327
  8. G. Vera Morinigo, J. F. Facetti Masulli, “El Precàmbrico en el Paraguay,” Rev. Soc. Cient. Paraguay, vol. 9, pp. 19 – 22, 1968.
    (G. Vera Morinigo, J. F. Facetti Masulli, “Precambrian in Paraguay,” J. Sci. Soc. Paraguay, vol. 9, pp. 19 – 22, 1968.)
  9. C. De Barros Gomes, P. Comin-Chiaramonti, V. F. Velázquez, “The Mesoproterozoic rhyolite occurrences of Fuerte Olimpo and Fuerte San Carlos, Northern Paraguay,” Braz. J. Geosci., vol. 30, no. 4, pp. 785 – 788, Dec. 2000.
    DOI: 10.25249/0375-7536.2000304785788
  10. A. Kanzler, “The Southern Precambrian in Paraguay - Geological Inventory and age relations,” Central J. Geol. Palaontol. Pt. 1, no. 7/8, pp. 753 – 765, Sep. 1987.
    Retrieved from: https://www.geologiadelparaguay.com.py/The-Southern-Precambrian-in-Paraguay-Kanzler.pdf
    Retrieved on: Nov. 15, 2023
  11. R. Boettner, “Estudio Geológico desde Fonciere hasta Toledo cué,” Rev. Fac. Quimica, n. 6 – 7, p. 9 – 14, 1947.
    (R. Boettner, “Geological Study from Fonciere to Toledo cue,” Chem. Fac. Magazine, no. 6 – 7, pp. 9 – 14, 1947.)
  12. M. M. Pimentel, R. A. Fuck, C. J. Alvarenga, “Post-Brasiliano (Pan-African) high-K granitic magmatism in Central Brazil: the role of late Precambrian-early Palaeozoic extension,” Precambrian Res., vol. 80, no. 3 – 4, pp. 217 – 238, Dec. 1996.
    DOI: 10.1016/S0301-9268(96)00016-2
  13. M. M. Pimentel, M. J. Whitehouse, Maria das G. Viana, R. A. Fuck, N. Machado, “The Mara Rosa Arch in the Tocantins Province: further evidence for Neoproterozoic crustal accretion in Central Brazil,” Precambrian Res., vol. 81, no. 3 – 4, pp. 299 – 310, Feb. 1997.
    DOI: 10.1016/S0301-9268(96)00039-3
  14. F. Ohana, A. S. Ruiz, M. Z. Aguiar de Sousa, M. E. Fróes Batata, J. M. Lafon, “Geology, petrology, U-Pb (shrimp) geochronology of the Morrinhos granite -Paraguá terrane, SW Amazonian craton: implications for the magmatic evolution of the San Ignácio orogeny,” Braz. J. Geol., vol. 44, no. 3, pp. 415 – 432, Jul.-Sep. 2014.
    DOI: 10.5327/Z2317-4889201400030006
  15. M. M. Pimentel, R. A. Fuck, N. F. Botelho, “Granites and the geodynamic history of the neoproterozoic Brası́lia belt, Central Brazil: a review,” Lithos, vol. 46, no. 3, pp. 463 – 483, Mar. 1999.
    DOI: 10.1016/S0024-4937(98)00078-4
  16. P. Comin-Chiaramonti et al., “Potassic and Sodic Igneous Rocks from Eastern Paraguay: their Origin from the Lithospheric Mantle and Genetic Relationships with the Associated Paraná flood tholeiites,” J. Petrol., vol 38, no. 4, pp. 495 – 528, Apr. 1997.
    DOI: 10.1093/petroj/38.4.495
  17. W. F. Hillebrand, G. E. F. Lundell, H. A. Brigt, J. I. Hoffman, Applied Inorganic Analysis, 2nd ed., New York (NY), USA: J. Wiley and Sons, 1962.
  18. R. B. Firestone, V. S. Shirley, Table of Isotopes, vol. II, 8th ed., New York (NY), USA: J. Wiley and Sons, 1996.
  19. J. Hoste, Isotopic Neutron Sources for Neutron Activation Analysis, IAEA-TECDOC-465, Vienna, Austria, 1988, p. 115.
  20. T. Uckan, J. March-Leuba, D. Powell, J. D. White, J. Glaser, 241-Am-Be Sealed Neutron Source Assessment Studies for the Fissile Mass Flow Monitor, ORNL/TM Publications, Oak Ridge (TN), USA, 2003.
  21. P. Van Espen, H. Nullens, F. Adams, “A Computer Analysis of X-Ray Fluorescence Spectra,” Nucl. Instrum. Meth., vol. 142, no. 1 – 2, pp. 243 – 250, Apr. 1977.
    DOI: 10.1016/0029-554X(77)90834-5
  22. P. Kump, QAES Instruction Manual, Josef Stefan Institute, Ljubljana, Slovenia, 1988.
  23. A. Dávalos, P. Kump, J. F. Facetti Masulli, “Biogeochemical aspects of selected elemental content in Ilex paraguayensis S.H from Eastern Paraguay,” IJOEAR, vol. 7, no. 7, pp. 10 – 20, Jul. 2021.
    DOI: 10.5281/zenodo.5149731
  24. P. Comin Chiaramonti et al., “Tertiary nephelinitic magmatism in Eastern Paraguay: Petrology, Sr-Nd isotopes and genetic relationships with associated spinel-peridotite xenoliths,” Eur. J. Mineral., vol. 3, no. 3, pp. 507 – 525, Jun. 1991.
    DOI: 10.1127/ejm/3/3/0507
  25. B. R. Frost et al., “A Geochemical Classification for Granitic Rocks,” J. Petrol., vol. 42, no. 11, pp. 2033 – 2048, Nov. 2001.
    DOI: 10.1093/petrology/42.11.2033
  26. B. E. John, J. Wooden, “Petrology and geochemistry of the metaluminous to peraluminous Chemehuevi Mountains Plutonic suite, southeastern California,” in The Nature and Origin of Cordilleran Magmatism, vol. 174, J. L. Anderson, Eds., Boulder (CO), USA: GSA Memoirs, 1990, ch. 5, pp. 71 – 98.
    DOI: 10.1130/MEM174-p71
  27. J. B. Whalen, K. L. Currie, B. W. Chappell, “A-type granites: geochemical characteristics, discrimination and petrogenesis,” Contrib. Mineral. Petrol., v. 95, p. 407-419, 1987.
  28. R. De Argollo, J.-G. Schilling, “Ge-Si and Ga-AI fractionation in Hawaiian volcanic rocks,” Geochim. Cosmochim. Acta, vol. 42, no. 6, pp. 623 – 630, Jun. 1978.
    DOI: 10.1016/0016-7037(78)90007-8
  29. S.-S. Sun, W. F. McDonough, “Chemical and isotopic systematics of oceanic basalts: implications for mantle composition and processes,” in Magmatism in the Ocean Basins, A. D. Saunders, M. J. Norry, Eds., London, UK: Special Publication, Geological Society of London,1989, pp. 313 – 345.
    DOI: 10.1144/GSL.SP.1989.042.01.19
  30. L. M. de Araújo, A. M. Godoy, “Magmatismo do Batólito RAPAKIVI Rio Branco, SW do Cráton Amazônico (MT)”, Geociências, v. 30, n. 2, p. 173 – 195, Apr. 2011.
    (L. M. de Araújo, A. M. Godoy, “Magmatism of the RAPAKIVI Rio Branco Batholith, SW of the Amazon Craton (MT)”, Geosci., vol. 30, no. 2, pp. 173 – 195, Apr. 2011.)

Radon and Thoron

PARALLEL HALF-YEAR-LONG RADON CONCENTRATION MEASUREMENT AT TCAS IN ZRENJANIN, SERBIA

Iris Borjanović Trusina, Milica Rajačić

Pages: 6-9

DOI: 10.37392/RapProc.2024.02

Abstract | References | Full Text (PDF)

Radon is a radioactive gas originating from the ground which can permeate enclosed spaces and pose serious health risks for humans when inhaled chronically. At the Technical College of Applied Sciences in Zrenjanin continuous measurements of radon concentration were undertaken during the summer and autumn of 2023. Radon concentrations were monitored in four rooms located in the basement and ground floor levels, covering an area of approximately 4000 m2, where previous short-term tests had indicated the highest radon concentrations. Detectors were positioned approximately 1 meter above the ground and away from doors, windows, walls and heating sources. These rooms remained in normal use throughout the measurement period. Two types of detectors were utilised simultaneously, placed in close proximity to each other. Radon concentrations were assessed using active-type radon detectors branded as Airthings, alongside CR39 track detectors. The radon concentration values obtained with CR39 detectors demonstrated good agreement with the results obtained using Airthings detectors. The statistical Z-test was employed for analysis.
  1. Sources and effects of ionizing radiation, vol. 1, UNSCEAR Report (A/63/46), UNSCEAR, New York (NY), USA, 2010.
    Retrieved from: https://www.unscear.org/docs/reports/2008/09-86753_Report_2008_Annex_B.pdf
    Retrieved on: Apr. 11, 2024
  2. D. Nikezić, “Radon, glavni radioaktivni kontaminant čovekove okoline,” uJoniyujuća zrečenja iz prirode, M. Kovačević, Ur., Beograd, Jugoslavija: Jugoslovensko društvo za zaštitu od zračenja, 1995, poglavlje 11, str. 145 – 190.
    (D. Nikezić, “Radon, main radioactive contaminant of environment” inIonizing radiation from nature, M. Kovačević, Eds., Belgrade, Yugoslavia: Yugoslav association for radiation protection, 1995, ch. 11, pp. 145 – 190.)
    Retrieved from: https://dzz.org.rs/wp-content/uploads/2013/06/1995-JDZZ-Beograd-Jonizujuca-zracenja-iz-prirode.pdf
    Retrieved on: Apr. 11, 2024
  3. Health Effects of Exposure to Radon, Rep. X820576-01-0, Committee on Health Risks of Exposure to Radon (BEIR VI), Washinton D.C., USA, 1999.
    Retrieved from: http://www.nap.edu/catalog/5499.html
    Retrieved on: Apr. 11, 2024
    DOI: 10.17225/5499
  4. WHO Handbook on indoor radon: a public health perspective, WHO, Geneva, Switzerland, 2009.
    Retrieved from: https://iris.who.int/bitstream/handle/10665/44149/9789241547673_eng.pdf?sequence=1
    Retrieved on: Apr. 11, 2024
  5. I. Borjanović, L. Manojlović, M. Kovačević, “Seasonal measurements of radon concentration level in the period of spring at Technical College of Applied Sciences in Zrenjanin,” inBook of Abstr. 10th Jubilee Int. Conf. Radiation in Various Fields of Research (RAD 2022) - summer edition, Herceg-Novi, Montenegro, 2022, p. 124.
    Retrieved from: https://www.rad-conference.org/RAD_2022_Summer_Book_of_Abstracts.pdf
    Retrieved on: Apr. 12, 2024
  6. I. Borjanović, A. Rajić, Ž. Eremić, “Seasonal Measurements of Indoor Radon Concentration Level in the Period of Summer at Technical College of Applied Sciences in Zrenjanin,” in Proc. 11th Int. Conf. Balcan Physical Union (BPU11 PoS), Belgrade, Serbia, 2022, PoS(BPU11)025.
    Retrieved from: https://pos.sissa.it/427/
    Retrieved on: Apr. 12, 2024
  7. I. Borjanović, M. Rajačić, I. Vukanac, “Winter Measurements of Radon Concentration at TCAS,” in Proc. 11 th Int. Conf. Physical Aspects of Environment (ICPAE 2023), Zrenjanin, Serbia, 2023, pp. 194 – 199.
    Retrieved from: http://www.nirs.qst.go.jp/rd/reports/proceedings/pdf/2nd_International_Symposium_2016.pdf
    Retrieved on: Apr. 12, 2024
  8. I. Borjanović, M. Rajačić, I. Vukanac, “Jesenja merenja nivoa radona na Visokoj tehničkoj školi strukovnih studija u Zrenjaninu,” DIT naučno-stručni časopis, br. 39, str. 53 – 57, Mar. 2023.
    (I. Bojanović, M. Rajačić, I. Vukanac, “Autumn Measurements of Radon Level at Technical College of Applied Sciences in Zrenjanin,” DIT Scientific and Professional Journal, no. 39, pp. 53 – 57, Mar. 2023)
    Retrieved from: http://www.diz.org.rs/images/casopis/dit39.pdf
    Retrieved on: Apr. 12, 2024
  9. How we make The Correntium Home Radon Detectors, Airthings, Oslo, Norway, 2022.
    Retrieved from: https://www.airthings.com/resources/radon-detector
    Retrieved on: Apr. 22, 2024
  10. Correntium Home Radon Detector User Manual, Airthings, Oslo, Norway, 2022.
    Retrieved from: https://cdn2.hubspot.net/hubfs/4406702/Website/Manuals/Home/1-043-Corentium-Home-manual-60x77.pdf
    Retrieved on: Apr. 22, 2024
  11. View Plus Radon Detector User Manual, Airthings, Oslo, Norway, 2022.
    Retrieved from: https://www.airthings.com/view-series-manul
    Retrieved on: Apr. 22, 2024
  12. FIDO Track, Niton, Milano, Italy, 2022.
    Retrieved from: https://www.niton.it/fidotrack/
    Retrieved on: Apr. 22, 2024
  13. Sources and effects of ionizing radiation,vol. 1, UNSCEAR Report (A/55/46), UNSCEAR, New York (NY), USA, 2000.
    Retrieved from: https://www.unscear.org/docs/publications/2000/UNSCEAR_2000_Report_Vol.I.pdf
    Retrieved on: Apr. 22, 2024
  14. N. Todorović, S. Forkapić, J. Papuga, I. Bikit, J. Slivka, “Analiza uticaja faktora na koncentraciju aktivnosti radona u zatorenim prostorijama,” Prirodno-matematički fakultet - Departman za fiziku, Novi Sad, Srbija, 2009.
    (N. Todorović, S. Forkapić, J. Papuga, I. Bikit, J. Slivka, “Analysis of factors which influence radon concentration in closed spaces,” Faculty of Sciences – Physics Department, Novi Sad, Serbia, 2009.)
    Retrieved from: https://inis.iaea.org/collection/NCLCollectionStore/_Public/41/131/41131350.pdf
    Retrieved on: Apr. 22, 2024
  15. S. Forkapić et al., “Methods of Radon Measurement,” Facta universitatis - series Phys. Chem. Technol., vol. 4, no. 1, pp. 1 – 10, Jan. 2006.
    DOI: 10.2298/FUPCT0601001F
  16. G. K. Kanji, 100 Statistical Tests, 3rd ed., London, UK: Sage Publications, 2006.
  17. M. Živanović, “Optimizacija merenja koncentracije radona u zatvorenom prostoru metodom ugljenih filtera,” doktorska disertacija, Univerzitet u Beogradu, Fakultet za fizičku hemiju, Beograd, Srbija, 2016.
    (M. Živanović, “Optimisation of Indoor Radon Concentration Measurements by Means of Charcoal Canisters,” Ph.D. dissertation, Belgrade University, Faculty of Physical Chemistry, Belgrade, Serbia, 2016.)
    Retrieved from: http://lotos.ffh.bg.ac.rs/Aktuelno/Dokumenta/Doktorska%20teza%20-%20Milos%20Zivanovic.pdf
    Retrieved on: Apr. 22, 2024
  18. Vlada Republike Srbije. (Nov. 18, 2011., Jun. 29, 2018). Službeni Glasnik RS 86/11 i Službeni Glasnik RS 50/18. Pravilnik o granicama izlaganja jonizujućim zračenjima i merenjima radi procene nivoa izlaganja jonizujućim zračenjima.
    (Government of the Republic of Serbia. (Nov. 18, 2011, Jun. 29, 2018). Official Gazette RS 86/11 and Official Gazette RS 50/18. Rulebook on Limits of Exposure to Ionizing Radiation and Measurements for Assessment of the Exposure Level.)
    Retrieved from: https://www.srbatom.gov.rs/srbatomm/wp-content/uploads/2019/11/Pravilnik-o-granicama-izlaganja_50_2018.pdf
    Retrieved on: Apr. 23, 2024
  19. The Council of European Union. (Dec. 5, 2013). Council Directive 2013/59/EURATOM laying down basic safety standards for protection against the dangers arising from exposure to ionising radiation, and repealing Directives 89/618/Euratom, 90/641/Euratom, 96/29/Euratom, 97/43/Euratom and 2003/122/Euratom.
    Retrieved from: https://eur-lex.europa.eu/eli/dir/2013/59/oj
    Retrieved on: Apr. 23, 2024

Radiochemistry

NEW DEVELOPMENT OF RADIUM-226 ANALYSIS IN WATER SAMPLES USING MnO2 RESIN AND ALPHA SPECTROMETRY

Aishah Alboloushi

Pages: 10-12

DOI: 10.37392/RapProc.2024.03

Abstract | References | Full Text (PDF)

A time-saving and optimum procedure for determining Radium in water has been implemented in Kuwait. This new development has been reached including radiochemical separation using manganese dioxide (MnO2) resin and α spectrometry measurements. Radium is separated and retained by the MnO2 resin, then it is extracted by 5 M HCL/15%H2O2 solution. Barium sulfate is precipitated onto the resolve filter followed by α measurement of Radium-226 (226Ra), in addition to γ measurement of Barium-133 (133Ba) to calculate chemical recovery%. IAEA proficiency test sample 2 was analyzed similarly, and the generated value of Radium-226 (226Ra) was in agreement with the reference value as well as the γ result analyzed in the same laboratory. The newly developed radium analysis procedure is more efficient for water samples than other radio-analytical techniques due to the low detection limit of α spectrometry compared to γ spectrometry.
  1. Radium, ScienceDirect, Amsterdam, Netherlands.
    Retrieved from: https://www.sciencedirect.com/topics/chemistry/radium
    Retrieved on: Jun. 19, 2023
  2. Analytical methodology for the determination of radium isotopes in environmental samples, IAEA/AQ/19, IAEA, Vienna, Austria, 2010.
    Retrieved from: https://www-pub.iaea.org/MTCD/Publications/PDF/IAEA-AQ-19_web.pdf
    Retrieved on: Jun. 19, 2023
  3. A procedure for the rapid determination of 226Ra and 228Ra in drinking water by liquid scintillation counting, IAEA/AQ/39, IAEA, Vienna, Austria, 2014.
    Retrieved from: https://www-pub.iaea.org/MTCD/Publications/PDF/IAEA-AQ-39_web.pdf
    Retrieved on: Jun. 19, 2023
  4. J. C. Lozano, F. Fernandez, J. M. G. Gomez, “Determination of radium isotopes by BaSO 4 coprecipitation for the preparation of alpha-spectrometric sources,” J. Radioanal. Nucl. Chem., vol. 223, no. 1 – 2, pp. 133 – 137, Sep. 1997.
    DOI: 10.1007/BF02223373
  5. Radium-226/228 in water, Analytical Procedure, Eichrom, Lisle (IL), USA, 2014.
    Retrieved from: https://www.eichrom.com/wp-content/uploads/2018/02/raw04-11_ra-water.pdf
    Retrieved on: May 1, 2023
  6. D. S. Moon, W. C. Burnett, S. Nour, P. Horwitz, A. Bond, “Preconcentration of radium isotopes from natural waters using MnO2 resin,” Appl. Radiat. Isot., vol. 59, no. 4, pp. 255 – 262, Oct. 2003.
    DOI: 10.1016/s0969-8043(03)00193-3
    PMid: 14522233

Biomedicine

GENDER PREDICTION BASED ON QUANTITATIVE ANALYSIS OF THE MASTOID PROCESS

Aida Sarač – Hadžihalilović, Edin Hojkurić

Pages: 13-17

DOI: 10.37392/RapProc.2024.04

Abstract | References | Full Text (PDF)

Osteoscopy and classic morphometric analysis of the skull can determine gender with an accuracy of 92%. The aim of our study was to determine the degree of accuracy in determining the gender of the skull based on the classic morphometric analysis of the mastoid process. The research was conducted on a sample of 100 macerated and degreased skulls of known gender and age from the second half of the 20th century, including the population of Bosnia and Herzegovina, which belong to the osteological collection of the Anatomy Department of the Faculty of Medicine, University of Sarajevo. It is a prospectively designed, osteometric study, where 3 diameters of the mastoid process were measured on each skull using a sliding compass (Schubler) on both sides: mastoid length, width and antero-posterior diameter. The size of the mastoid process was calculated according to the given formula. The antero-posterior diameter of the mastoid process was shown to be a significant predictor for the differentiation of skull gender p=0.0001. If the antero-posterior diameter of the mastoid process increases by 1 mm, the odds ratio (chance ratio) that it is a female skull decreases by 41% in our sample, while in the general population the chance ranges between 50-30%. The size of the mastoid process proved to be a significant predictor for the gender differentiation of the skull p=0.0001. If the size of the mastoid process increases by 1 mm3, the odds ratio (chance ratio) that it is a female skull decreases by 41% in our sample, while in the general population the chance ranges between 50-30%. Increasing values of length, width, antero-posterior diameter and size of the mastoid process increase the probability that the skull is classified as male. By multivariate binary logistic regression, the antero-posterior diameter of the mastoid process was singled out as statistically significant for the differentiation of skull gender.
  1. A. Sarač – Hadžihalilović et al., “Model “P” in gender prediction based on mastoid process,” Med. Glas. (Zenica), vol. 17, no. 2, pp. 279 – 284, Aug. 2020.
    DOI: 10.17392/1145-20
    PMid: 32483958
  2. P. V. Sumati, V. V. G. Patnaik, A. Phatak, “Determination of Sex from Mastoid Process by Discriminant Function Analysis,” J. Anat. Soc. India, vol. 59, no. 2, pp. 222 – 228, Dec. 2010.
    DOI: 10.1016/S0003-2778(10)80030-9
  3. D. R. Johnson, P. O`Higgins, W. J. Moore, T. J. McAndrew, “Determination of race and sex of the human skull by discriminant function analysis of linear and angular dimensions — an appendix,” Forensic Sci. Int., vol. 45, no. 1 – 2, pp. 41 – 53, Apr. – May. 1989.
    DOI: 10.1016/0379-0738(89)90234-x
    PMid: 2636546
  4. I. C. Suazo Galdames, D. A. Zavando Matamala, R. L. Smith, “Sex Determination Using Mastoid Process Measurements in Brazilian Skulls,” Int. J. Morphol., vol. 26, no. 4, pp. 941 – 944, Dec. 2008.
    DOI: 10.4067/S0717-95022008000400025
  5. A. Ibrahim, A. Alias, M. S. Shafie, S. Das, F. Mohd Nor, “Osteometric estimation of sex from mastoid triangle in Malaysian population,” Asian J. Pharm. Clin. Res., vol. 11, no. 7, pp. 303 – 307, Jul. 2018.
    DOI: 10.22159/ajpcr.2018.v11i7.25986
  6. A. Manivanan, K. Saraswathi Gopal, S. Archana, “Osteometric Assessment of the Mastoids for Gender Determination: A Retrospective CBCT Study,” Am. J. Otolaryngol. Head and Neck Surg., vol. 2, no. 3, 1044, Mar. 2019.
    Retrieved from: https://www.remedypublications.com/open-access/osteometric-assessment-of-the-mastoids-for-gender-determination-a-retrospective-cbct-study-407.pdf
    Retrieved on: Dec. 15, 2023
  7. S. B. Sukre, P. R. Chavan, S. N. Shewale, “Morphometric analysis of mastoid process for sex determination among Marathwada population,” MIJOANT, vol. 1, no. 2, pp. 27 – 32, Feb. 2017.
    Retrieved from: https://www.medpulse.in/Anatomy/Article/Volume1Issue2/Anatomy_1_2_2.pdf
    Retrieved on: Dec. 15, 2023
  8. Z. Ajanović, A. Sarač – Hadžihalilović, “Multivariate analysis of Cranioscopic and Craniometric parameters in gender determination of skulls,” HealthMED, vol. 12, no. 3, pp. 75 – 84, Feb. 2018.
    Retrieved from: https://www.researchgate.net/publication/330797365_Multyvariate_analysis_of_Cranioscopic_and_Craniometric_parameters_in_gender_determination_of_skulls
    Retrieved on: Jan. 20, 2024
  9. S. K. Mittal, S. Jaleswararao, J. Goyal, L. Mittal, B. Goyal, “Sex determination using mastoid process of dry skull”, IJBAMR, vol. 7, no. 3, pp. 404 – 408, Jun. 2018.
    Retrieved from: https://www.ijbamr.com/assets/images/issues/pdf/June%202018%20404%20-%20408.pdf.pdf
    Retrieved on: Jan. 20, 2024
  10. H. Jung, E. J. Woo, “Evaluation of Mastoid Process as Sex Indicator in Modern White Americans using Geometric Morphometrics,” J. Forensic. Sci., vol. 61, no. 4, pp. 1029 – 1033, Jul. 2016.
    DOI: 10.1111/1556-4029.13079
    PMid: 27364284
  11. A. Kemkes, T. Göbel, “Metric Assessment of the “Mastoid Triangle” for Sex Determination: Validation Study,” J. Forensic. Sci., vol. 51, no. 5, pp. 985 – 989, Sep. 2006.
    DOI: 10.1111/j.1556-4029.2006.00232.x
    PMid: 17018073
  12. T. Nagaoka et al., “Sex determination using mastoid process measurements: standards for Japanese human skeletons of the medieval and early modern periods,” Anthropol. Sci., vol. 116, no. 2, pp. 105 – 113, Aug. 2008.
    DOI: 10.1537/ase.070605

Radiation Measurements

Thermoluminescence of beta-irradiated YBO3 :Nd3+ phosphor synthesized by combustion method: A preliminary study

Sibel Akça Özalp, Z. Gizem Portakal Uçar, Y. Ziya Halefoğlu, Mustafa Topaksu

Pages: 18-22

DOI: 10.37392/RapProc.2024.05

Abstract | References | Full Text (PDF)

This study aims to investigate the thermoluminescence (TL) properties of the YBO3 sample doped with Nd3+, which is known to be an important candidate luminescence material. The Nd3+-doped YBO3 phosphor was synthesized at various concentrations (wt%) utilizing the combustion method. The optimal dopant concentration and optical filter combination for the Nd3+-doped YBO3 samples were determined through analysis of their TL glow curves. Consequently, TL emissions of the specified YBO3: Nd3+ (0.5%) samples were examined using the IRSL-TL 410 nm filter combination. The YBO3: Nd3+ (0.5%) sample displayed two distinct maxima at approximately 210oC and 390oC, with a linear heating rate of 2 oCs-1, and when the beta dose response of the sample was examined within the range of 0.1-20 Gy, a consistent linearity (b = 0.946, R2= 0.999) was observed between 0.1-5 Gy. Following 12 cycles of reusability testing, the integrated TL intensity exhibited no significant alterations. A short-term fading experiment of the TL emission of the sample was carried out, and the results showed that up to 7 days, the 1st maxima faded very little, the 2nd maxima almost did not fade at all, but around the 7th day, the intensity of this maxima increased greatly.
  1. C. Furetta, M. Prokic, R. Salamon, V. Prokic, G. Kitis, “Dosimetric characteristics of tissue equivalent thermoluminescent solid TL detectors based on lithium borate,” Nucl. Instrum. Methods Phys. Res. A, vol. 456, no. 3, pp. 411 – 417, Jan. 2001.
    DOI: 10.1016/S0168-9002(00)00585-4
  2. L.H. Jiang et al., “Thermoluminescence studies of LiSrBO3:RE3+(RE=Dy, Tb, Tm and Ce),” Appl. Radiat. Isot., vol. 68, no. 1, pp. 196 – 200, Jan. 2010.
    DOI: 10.1016/j.apradiso.2009.10.001
    PMid: 19884017
  3. B. Ramesh et al., “Determination of strain, site occupancy, photoluminescent, and thermoluminescent-trapping parameters of Sm3+-doped NaSrB5O 9 microstructures,” Ceram. Int., vol. 42, no. 1, pp. 1234 – 1245, Jan. 2016.
    DOI: 10.1016/j.ceramint.2015.09.055
  4. C. Wang, B. Yan, “Sol–gel synthesis and photoluminescence of RE3BO6: Eu3+/Tb3+(RE = Y, Gd) microcrystalline phosphors from hybrid precursors,” J. Non-Cryst. Solids, vol. 354, no. 10 – 11, pp. 962 – 969, Feb. 2008.
    DOI: 10.1016/j.jnoncrysol.2007.08.029
  5. X. Zhang et al., “Tunable photoluminescence and energy transfer of YBO3:Tb3+, Eu 3+ for white light emitting diodes,” J. Mater. Chem. C, vol. 1, no. 43, pp. 7202 – 7207, Nov. 2013.
    DOI: 10.1039/C3TC31200C
  6. R.G. Nair et al., “YBO 3 versus Y3BO 6 host on Tb 3+ luminescence,” J. Lumin., vol. 195, pp. 271 – 277, Mar. 2018.
    DOI: 10.1016/j.jlumin.2017.11.038
  7. L. J. Q. Maia, A. L. Moura, V. Jerez, C. B. de Araújo, “Structural properties and near infrared photoluminescence of Nd 3+ doped YBO 3 nanocrystals,” Opt. Mater., vol. 95, 109227, Sep. 2019.
    DOI: 10.1016/j.optmat.2019.109227
  8. R. Balakrishnaiah et al., “Enhanced luminescence properties of YBO3:Eu 3+ phosphors by Li-doping,” Mater. Res. Bull., vol. 46, no. 4, pp. 621 – 626, Apr. 2011.
    DOI: 10.1016/j.materresbull.2010.09.012
  9. V. Dubey, J. Kaur, S. Agrawal, N. S. Suryanarayana, K. V. R. Murthy, “Effect of Eu 3+ concentration on photoluminescence and thermoluminescence behavior of YBO3:Eu 3+ phosphor,” Superlattice Microst., vol. 67, pp. 156 – 171, Mar. 2014.
    DOI: 10.1016/j.spmi.2013.12.026
  10. V. Dubey, N. V. Dubey, S. J. Dhoble, H. C. Swart, “TL glow curve analysis and kinetics of UV, β and γ irradiated YBO3: Eu 3+ and Y2O3: Eu 3+ phosphors,” J. Mater. Sci: Mater. Electron., vol. 28, pp. 13565 – 13578, May 2017.
    DOI: 10.1007/s10854-017-7196-8
  11. S. Akça, “Thermoluminescence behavior of YBO 3 synthesized by combustion reaction versus beta radiation,” in Book of Abstr. 3rdInt. Conf. Materials Science, Mechanical and Automotive Engineerings and Technology (IMSMATEC`20), İstanbul, Turkey, 2020, pp. 377 – 377.
    Retrieved from: http://www.imsmatec.org/
    Retrieved on: Jun. 20, 2024
  12. S. Akça, “Kinetic Parameters of Thermoluminescence Dosimetric Peak of YBO 3 Phosphor,” Süleyman Demirel University Faculty of Arts and Sciences J. Sci., vol. 15, no. 1, pp. 100 – 109, May 2020.
    DOI: 10.29233/sdufeffd.705417
  13. S. Akça, Z. G. Portakal Uçar, Y. Z. Halefoğlu, M. Topaksu, “Variation of thermoluminescence behavior of doped (Nd 3+ and Eu3+) yttrium borate phosphor produced by a combustion process,” in Proc. 1st Int. Conf. Sensor, Detector, Materials Science and Technologies (SensDeTech), Bolu, Turkey, 2023, pp. 12 – 16.
    Retrieved from: https://senstech.ibu.edu.tr/Files/ckFiles/senstech-ibu-edu-tr/AbstractBook/SensDeTech-Proceedings.pdf
    Retrieved on: Jun. 20, 2024
  14. Y. Z. Halefoglu, “Luminescent properties and characterisation of LaB3O6:Eu 3+ phosphor synthesized using the combustion method,” Appl. Radiat. Isot., vol. 148, pp. 40 – 44, Jun. 2019.
    DOI: 10.1016/j.apradiso.2019.03.011
    PMid: 30921615
  15. S. Akca et al., “Thermoluminescence analysis of beta irradiated ZnB2O4: Pr 3+ phosphors synthesized by a wet-chemical method,” Radiat. Phys. Chem., vol. 160, pp. 105 – 111, Jul. 2019.
    DOI: 10.1016/j.radphyschem.2019.03.033
  16. V. Pagonis, G. Kitis, C. Furetta, “TL Dose Response Models”, in Numerical and Practical Exercises in Thermoluminescence, 1st ed., New York (NY), USA: Springer, 2006, ch. 4, p. 121.
    DOI: 10.1007/0-387-30090-2
  17. S. Del Sol Fernández et al., “Thermoluminescent characteristics of LiF:Mg, Cu, P and CaSO4:Dy for low dose measurement,” Appl. Radiat. Isot., vol. 111, pp. 50 – 55, May 2016.
    DOI: 10.1016/j.apradiso.2016.02.011
    PMid: 26922395
  18. Z. G. Portakal-Uçar et al., “A thermoluminescence study of Tb 3+ doped LaB3O6: dosimetric characteristics and kinetic parameters,” J. Lumin., vol. 253, 119493, Jan. 2023.
    DOI: 10.1016/j.jlumin.2022.119493
  19. M. Oglakci et al., “Thermoluminescence behavior of Ce 3+ doped lanthanum tri-borate phosphor for dosimetry applications,” Ceram. Int., vol. 49, no. 22, pp. 36092 – 36102, Nov. 2023.
    DOI: 10.1016/j.ceramint.2023.08.288
  20. G. Kitis, F. Hasan, S. Charalambous, “Regenerated thermoluminescence: some new data,” Nucl. Tracks Radiat. Meas., vol. 10, no. 4 – 6, pp. 565 – 570, 1985.
    DOI: 10.1016/0735-245X(85)90058-4

Nuclear Forensics

APPLICATION OF DISPERSION MODELS OF ESTE FOR MODELLING OF THE RADIOLOGICAL IMPACT OF RELEASED Cs-137 IN A SPECIFIC URBAN ENVIRONMENT

Jozef Sabol, Ľudovít Lipták, Jan Bajura, Eva Fojcíková, Peter Čarný

Pages: 23-28

DOI: 10.37392/RapProc.2024.06

Abstract | References | Full Text (PDF)

The software ESTE was used to assess the spread of contaminated air in terms of parameters that calculate radiation exposure to affected individuals. The computer simulation proved to be a reliable tool for obtaining relevant radiation protection quantities and their dependence on parameters such as the initial source activity, its position, wind direction, and wind velocity. An essential condition for accurate dispersion modelling in urban areas is the evaluation of urban wind fields specific to various environments and atmospheric conditions. The location, structure, and layout of buildings are reflected in the simulation of the behaviour and movement of radioactive air. The modelling considers external exposures, expressed in ambient dose equivalent, and internal exposures, leading to committed effective dose. The ESTE dispersion models have proven extremely useful in obtaining essential parameters for predicting the impact of dispersed radioactivity on individuals in the investigated areas. These data can help implement effective protection measures for people in such areas, where exposure also depends on the configuration of the building structures, which can be taken into account when adopting measures to minimise the exposure of individuals present or moving around. The ESTE code was applied to model the dispersion of Cs-137 in a specific urban environment.
  1. L. Lipták, E. Fojcíková, M. Krpelanová, V. Fabová, P. Čarný, “The ESTE decision support system for nuclear and radiological emergencies: Atmospheric dispersion models”, Atmosphere, vol. 12, no. 2, 204, Feb. 2021.
    DOI: 10.3390/atmos12020204
  2. E. Fojcíková, Ľ. Lipták, M. Krpelanová, M. Chylý, P. Čarný, “ESTE—Decision support system for nuclear and radiological accidents,” Radiat. Prot. Dosimetry, 2019, vol. 186, no. 2 – 3, pp. 321 – 325, Dec. 2019.
    DOI: 10.1093/rpd/ncz226
    PMid: 31711210
  3. Radionuclide Basics: Cesium-137, United States Environmental Protection Agency (EPA), Washington D.C., USA, 2024.
    Retrieved from: https://www.epa.gov/radiation/radionuclide-basics-cesium-137
    Retrieved on: Jan. 22, 2024
  4. A. G. Marzo, “Atmospheric transport and deposition of radionuclides released after the Fukushima Dai-chi accident and resulting effective dose,” Atmos. Environ.,vol. 94, pp. 709 – 722, Sep. 2014.
    DOI: 10.1016/j.atmosenv.2014.06.009
  5. L. Lipták et al., “Dispersion and radiation modelling in ESTE system using urban LPM,” Atmoshere, vol. 14, no. 7, 1077, Jul. 2023.
    DOI: 10.3390/atmos14071077
  6. CIMERA – Comprehensive Hazard Identification and Monitoring System for Urban Areas, EU Horizon Project no. 101121342, European Union, Brussels, Belgium, 2022.
  7. P. Čarný et al., Simulácia událostí pomocou DSS ESTE CBRN v Prahe a Varšave, May 2024.
    (P. Čarný et al., Simulation of events using DSS ESTE in Prague and Warsaw, May 2024.)
  8. Přehled dosavadního vývoje jaderné havárie v Japonsku, Státní úřad pro jadernou bezpečnost, Praha, ČR, 2011.
    (An overview of the nuclear accident in Japan, State Office for Nuclear Safety, Prague, Czech Republic, 2011.)
    Retrieved from: https://sujb.gov.cz/aktualne/detail/prehled-dosavadniho-vyvoje-jaderne-havarie-v-japonsku/
    Retrieved on: Jan. 22, 2024
  9. J. Sabol, “Difficulties in using the present system of quantifying radiation exposure. Problems of the unified system of quantities in radiation protection for the risk assessment due to external and internal exposure,” in Proc. 6th European Congress on Radiation Protection (IPRA 2022), Budapest, Hungary, 2022.

Medical Physics

THE APPLICATION OF AI-BASED TECHNIQUES FOR EARLY DETECTION OF BREAST CANCER

Dafina Xhako, Elda Spahiu, Suela Hoxhaj, Niko Hyka

Pages: 29-35

DOI: 10.37392/RapProc.2024.07

Abstract | References | Full Text (PDF)

Breast cancer is a type of tumor that occurs in breast tissue. It continues to remain one of the most prevalent and life-threatening diseases globally, becoming the second leading cause of cancer-related deaths among women. Breast cancer begins when malignant and cancerous cells begin to grow from the breast cells. Self-tests and periodic clinical examinations help in early diagnosis and significantly improve survival chances. Early diagnosis of breast cancer, when it is small and has not spread, can make the disease easier to treat, thus increasing the patient’s chances of survival. Due to the medical importance of breast cancer examinations, Computer-Aided Detection methods have been developed to detect anomalies such as calcifications, masses, architectural distortions, and bilateral asymmetry. Micro calcifications are nothing but tiny mineral deposits within the breast tissue. They look like small white colored spots. They may or may not be caused by cancer. This is one reason why breast cancer detection is difficult with mammogram because the mammogram results vary greatly depending on the patient’s age, breast density, and the type of lesion present. Breast density can lead to differences in the contrast of malignant regions and can lead to incorrect conclusions. Our study describes an AI approach of adaptive median filter which performs spatial processing to determine which pixels in an image have been affected by noise. To detect a tumor at different stages we use neural network with different learning techniques to get Gaussian Mixed Model (GMM) segmentation. The Artificial Neural Network (ANN) model is based on convolutional neural networks (CNN) and as input data we have selected 260 mammogram images classifying them into three categories: normal mammogram, mammogram with benign and mammogram with cancer. After the training process, we used a CNN model named ResNet50 to compare the results. Due to the low processing capacity, we have chosen a small dataset. Our results show that a CNN model with 3*3 convolutional layer performed better compared with Gaussian Mixed Model segmentation.
  1. H. Sung et al., “Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries,” CA Cancer J. Clin., vol. 71, no. 3, pp. 209 – 249, May 2021.
    DOI: 10.3322/caac.21660
    PMid: 33538338
  2. A. Y. Ng et al., “Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer,” Nat. Med., vol. 29, no. 12, pp. 3044 – 3049, Dec. 2023.
    DOI: 10.1038/s41591-023-02625-9
    PMid: 37973948
    PMCid: PMC10719086
  3. J. S. Ahn et al., “Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine,” J. Breast Cancer, vol. 26, no. 5, pp. 405 – 435, Oct. 2023.
    DOI: 10.4048/jbc.2023.26.e45
    PMid: 37926067
    PMCid: PMC10625863
  4. J. Tang, R. M. Rangayyan, J. Xu, I. El Naqa, Y. Yang, “Computer-aided detection and diagnosis of breast cancer with mammography: recent advances,” IEEE Trans. Inf. Technol. Biomed., vol. 13, no. 2, pp. 236 – 251, Mar. 2009.
    DOI: 10.1109/TITB.2008.2009441
    PMid: 19171527
  5. I. Kim, K. Kang, Y. Song, T.-J. Kim, “Application of artificial intelligence in pathology: trends and challenges,” Diagnostics, vol. 12, no. 11, 2794, Nov. 2022.
    DOI: 10.3390/diagnostics12112794
    PMid: 36428854
    PMCid: PMC9688959
  6. N. Houssami, G. Kirkpatrick-Jones, N. Noguchi, C. I. Lee, “Artificial Intelligence (AI) for the early detection of breast cancer: a scoping review to assess AI’s potential in breast screening practice,” Expert Rev. Med. Devices, vol. 16, no. 5, pp. 351 – 362, May 2019.
    DOI: 10.1080/17434440.2019.1610387
    PMid: 30999781
  7. L. Shen et al., “Deep Learning to improve breast cancer early detection on screening mammography,” Sci. Rep., vol. 9, no. 1, 12495, Aug. 2019.
    DOI: 10.1038/s41598-019-48995-4
    PMid: 31467326
    PMCid: PMC6715802
  8. C. Leibig et al., “Combining the strengths of radiologists and AI for breast cancer screening: A retrospective analysis,” Lancet Digit. Health, vol. 4, no. 7, pp. e507 – e519, Jul. 2022.
    DOI: 10.1016/S2589-7500(22)00070-X
    PMid: 35750400
    PMCid: PMC9839981
  9. Y. Qiu et al., “A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology,” J. Xray Sci. Technol., vol. 25, no. 5, pp. 751 – 763, Jan. 2017.
    DOI: 10.3233/XST-16226
    PMid: 28436410
    PMCid: PMC5647205
  10. D. Ribli, A. Horváth, Z. Unger, P. Pollner, I. Csabai, “Detecting and classifying lesions in mammograms with deep learning,” Sci. Rep., vol. 8, no. 1, 4165, Mar. 2018.
    DOI: 10.1038/s41598-018-22437-z
    PMid: 29545529
    PMCid: PMC5854668
  11. N. Houssami, C. I. Lee, D. S. M. Buist, D. Tao, “Artificial intelligence for breast cancer screening: opportunity or hype?” Breast, vol. 36, pp. 31 – 33, Dec. 2017.
    DOI: 10.1016/j.breast.2017.09.003
    PMid: 28938172
  12. D. Zheng, X. He, J. Jing, “Overview of artificial intelligence in breast cancer medical imaging,” J. Clin. Med., vol. 12, no. 2, 419, Jan. 2023.
    DOI: 10.3390/jcm12020419
    PMid: 36675348
    PMCid: PMC9864608
  13. M. Ghassemi et al., “A review of challenges and opportunities in machine learning for health,” deposited at arXiv, Dec. 5, 2019. arXiv:1806.00388
  14. R. Agarwal, O. Diaz, X. Lladó, M. H. Yap, R. Martí, “Automatic mass detection in mammograms using deep convolutional neural networks,” J. Med. Imaging, vol. 6, no. 3, 031409, Jul. 2019.
    DOI: 10.1117/1.JMI.6.3.031409
    PMid: 35834317
    PMCid: PMC6381602
  15. C. R. Taylor, N. Monga, C. Johnson, J. R. Hawley, M. Patel, “Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions,”Diagnostics, vol. 13, no. 12, 2041, Jun. 2023.
    DOI: 10.3390/diagnostics13122041
    PMid: 37370936
    PMCid: PMC10296832
  16. J. W. Li et al., “Artificial intelligence in breast imaging: Potentials and challenges,” Phys. Med. Biol., vol. 68, no. 23, 23TR01, Nov. 2023.
    DOI: 10.1088/1361-6560/acfade
    PMid: 37722385
  17. A. Yala, C. Lehman, T. Schuster, T. Portnoi, R. Barzilay, “A deep learning mammography-based model for improved breast cancer risk prediction,” Radiology, vol. 292, no. 1, pp. 60 – 66, Jul. 2019.
    DOI: 10.1148/radiol.2019182716
    PMid: 31063083
  18. D. Xhako, S. Hoxhaj, N. Hyka, E. Spahiu, P. Malkaj, “Artificial Intelligence in Medical Image Processing,” Int. J. Intell. Syst. Appl. Eng., vol. 12, no. 8s, pp. 549 – 552, Dec. 2023.
    Retrieved from: https://ijisae.org/index.php/IJISAE/article/view/4186
    Retrieved on: Feb. 10, 2024
  19. D. Xhako, N. Hyka, “Artificial neural networks application in medical images,” Int. J. Health Sci., vol. 6, no. S2, pp. 10632 – 10639, May 2022.
    DOI: 10.53730/ijhs.v6nS2.7829
  20. N. Dhungel, G. Carneiro, A. P. Bradley, “A deep learning approach for the analysis of masses in mammograms with minimal user intervention,” Med. Image Anal., vol. 37, pp. 114 – 128, Apr. 2017.
    DOI: 10.1016/j.media.2017.01.009
    PMid: 28171807
  21. D. Xhako, E. Spahiu, N. Hyka, S. Hoxhaj, P. Malkaj, “Integration of DCNN Model for Brain Tumor Detection with PPIR Simulator,” Int. J. Intell. Syst. Appl. Eng., vol. 12, no. 8s, pp. 534 – 538, Dec. 2023.
    Retrieved from: https://ijisae.org/index.php/IJISAE/article/view/4184
    Retrieved on: Feb. 10, 2024
  22. F. Valdora, N. Houssami, F. Rossi, M. Calabrese, A. S. Tagliafico, “Rapid review: Radiomics and breast cancer,” Breast Cancer Res. Treat., vol. 169, no. 2, pp. 217 – 229, Jun. 2018.
    DOI: 10.1007/s10549-018-4675-4
    PMid: 29396665
  23. W. L. Bi. et al., “Artificial intelligence in cancer imaging: Clinical challenges and applications,” CA Cancer J. Clin., vol. 69, no. 2, pp. 127 – 157, Mar. 2019.
    DOI: 10.3322/caac.21552
    PMid: 30720861
    PMCid: PMC6403009
  24. S. B Shamir, A. L. Sasson, L. R. Margolies, D. S. Mendelson, “New Frontiers in Breast Cancer Imaging: The Rise of AI,” Bioengineering, vol. 11, no. 5, 451, May 2024.
    DOI: 10.3390/bioengineering11050451
    PMid: 38790318
    PMCid: PMC11117903

Medical Physics

CANCER RISK EVALUATION FOR HIGH-DOSE CHEST CT EXAMINATION DURING THE COVID-19 PANDEMIC

Dafina Xhako, Suela Hoxhaj, Elda Spahiu, Niko Hyka

Pages: 36-40

DOI: 10.37392/RapProc.2024.08

Abstract | References | Full Text (PDF)

High-dose chest CT exams were performed significantly more frequently during the Covid-19 pandemic to diagnose and treat patients. While critical for patient care, there are concerns about the potential increase in cancer risk linked with this ionizing radiation exposure. Based on the radiation dose, age, sex, and organ exposure, this study examines the cancer risk linked to high-dose thorax CT during the pandemic in Albania. This study is to evaluate the possible cancer risk associated with high-dose CT exams of the thorax for Covid patients. As a method for calculating the incidence of cancer linked to radiation exposure, the idea of Lifetime Attributable Risk (LAR) is investigated through data collection from Covid 19 patient for the period 2020 -2022. The study's methodology includes a thorough analysis of radiation exposure from CT scans, with a particular emphasis on the risks associated with cancer from thorax imaging techniques. The cancer risks significantly increased linearly with radiation dose of CT scans, with the highest risks for doses greater than 50 mSv. The lifetime attributable risk (LAR) of cancer for adults following CT scans was inordinately increased. This study also investigates how the Covid-19 pandemic has affected the need for and frequency of thoracic CT scans, considering the increasing use of imaging in the diagnosis and monitoring of respiratory diseases during this global health emergency. The results of this study emphasize how crucial it is to weigh the possible long-term hazards of radiation-induced cancer against the diagnostic advantages of high-dose thoracic CT scans. Using the patient's age, sex, and effective dose value, the risk factors from BEIR VII tables for more than 2000 patients, analyzing other complex factors that contribute to the risk of cancer, we found there is a low cancer risk estimation considering as an important factor the age of patients.
  1. C. Huang et al., “Clinical features of patients infected with 2019 novel coronavirus in Wuhan,” Lancet, vol. 395, no. 10223, pp. 497 – 506, Feb. 2020.
    DOI: 10.1016/s0140-6736(20)30183-5
    PMid: 31986264
    PMCid: PMC7159299
  2. Y. Yang et al., “Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections,” deposited at medRxiv, Feb. 17, 2020.
    DOI: 10.1101/2020.02.11.20021493
  3. T. Ai et al., “Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease (COVID-19) in China: “A Report of 1014 Cases,” Radiology, vol. 296, no. 2, pp. E32 – E40, Aug. 2020.
    DOI: 10.1148/radiol.2020200642
    PMid: 32101510
    PMCid: PMC7233399
  4. D. Caruso et al., “Chest CT Features of COVID-19 in Rome. Italy,” Radiology,vol. 296, no. 2, pp. E79 – E85, Aug. 2020.
    DOI: 10.1148/radiol.2020201237
    PMid: 32243238
    PMCid: PMC7194020
  5. Y. Fang et. al., “Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR,”Radiology, vol. 296, no. 2, pp. E115 – E117, Aug. 2020.
    DOI: 10.1148/radiol.2020200432
    PMid: 32073353
    PMCid: PMC7233365
  6. J. P. Kanne, B. P. Little, J. H. Chung, B. M. Elicker, L. H. Ketai, “Essentials for Radiologists on COVID-19: An Update- Radiology Scientific Expert Panel,” Radiology,vol. 296, no. 2, pp. E113 – E114, Aug. 2020.
    DOI: 10.1148/radiol.2020200527
    PMid: 32105562
    PMCid: PMC7233379
  7. M. P. Revel et al., “European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI). COVID-19 patients and the radiology department - advice from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI),” Eur. Radiol., vol. 30, no. 9, pp. 4903 – 4909, Sep. 2020.
    DOI: 10.1007/s00330-020-06865-y
    PMid: 32314058
    PMCid: PMC7170031
  8. N. Sverzellati et al., “Integrated Radiologic Algorithm for COVID-19 Pandemic,” J. Thorac. Imaging, vol. 35, no 4, pp. 228 – 233, Jul. 2020.
    DOI: 10.1097/RTI.0000000000000516
    PMid: 32271278
    PMCid: PMC7253044
  9. Z. Kang, X. Li, S. Zhou, “Recommendation of low-dose CT in the detection and management of COVID-2019,” Eur. Radiol.,vol. 30, no. 8, pp. 4356 – 4357, Aug. 2020.
    DOI: 10.1007/s00330-020-06809-6
    PMid: 32193637
    PMCid: PMC7088271
  10. C Ghetti, O. Ortenzia, F. Palleri, M. Sireus, “Definition of Local Diagnostic Reference Levels in a Radiology DepartmentUsing a Dose Tracking Software,” Radiat. Prot. Dosimetry, vol. 175, no. 1, pp. 38 – 45, Jun. 2017.
    DOI: 10.1093/rpd/ncw264
    PMid: 27614299
  11. F. Palorini, D. Origgi, C. Granata, D. Matranga, S. Salerno, “Adult exposures from MDCT including multiphase studies: first Italian nationwide survey,” Eur. Radiol., vol. 24, no. 2, pp. 469 – 483, Feb. 2014.
    DOI: 10.1007/s00330-013-3031-7
    PMid: 24121713
  12. N. Hyka, D. Xhako, G. Halilaj, F. Nela, “How chest CT radiation dose of patients with confirmed COVID-19 will impact the cancer risk in the future,” Phys. Med., vol. 92, suppl. S1, pp. S230 – S231, Dec. 2021.
  13. D. Xhako, N. Hyka, S. Hoxhaj, E. Spahiu, P. Malkaj, “An Overview of Protocol for Quality Control Tests for Diagnostic Radiology Applied By Albmedtech,” J. Jilin University (Engineering and Technol. Edition), vol. 42, no. 11, pp. 72 – 84, Nov. 2023.
    DOI: 10.5281/zenodo.10081328
  14. N. Hyka, D. Xhako, K. Sallabanda, P. Malkaj, “Using Deep Convolutional Neural Network to Create a DCNN Model for Brain Tumor Detection,” Eur. Chem. Bull., vol. 12, spec. issue 7, pp. 4979 – 4989, Jul. 2023.
    DOI: 10.48047/ecb/2023.12.si7.430

Radiation Detectors

YAG:Ce SCINTILLATOR DETECTOR FOR GAMMA RADIATION

Madalina Cruceru, Alin Serban, Liviu Ciolacu

Pages: 41-43

DOI: 10.37392/RapProc.2024.09

Abstract | References | Full Text (PDF)

A new detector with Cerium-doped yttrium garnet (YAG:Ce) scintillator crystal plate is reported. The crystal of YAG:Ce, made in China at Hangzhou Yong Hee Photonics Co. Ltd has 0.2% Cerium activator and was grown by Bridgeman method. Since the maximum of the peak emission of YAG:Ce is situated at 550nm, the readout can be made with a PIN photodiode. The dimensions of the crystal plate are 18x18x10mm3. The photodiode used in this experiment was of type S3204-08, made in Japan by Hamamatsu, with an active area of 18x18mm2, which is not affected by magnetic field. The signal from this detector was fed into a charge sensitive amplifier. Two positron sources of 48V (with energies of 511 keV, 983.5 keV, 1312.1 keV) and 22Na (511keV, 1274 keV) were used to measure the energy resolution obtained. We find a value 12%, bigger than the energy resolution obtained for CsI(Tl)(6.7%) with the same PIN photodiode readout and the same charge sensitive preamplifier. Also, the YAG:Ce crystal was polished on all faces and then was wrapped with black paper on lateral faces. The YAG:Ce crystal is non-hygroscopic in comparison with NaI(Tl) and CsI(Tl) crystals, and so it can be used in high temperature and ultra-high vacuum conditions for a long time. The decay time of 70ns for YAG:Ce is smaller than the decay time for CsI(Tl), which makes it a fast detector. Indeed, the YAG:Ce crystal is very good for replacing the old crystals used in gamma radiation detectors from a positron emission tomography (PET) scanner and from other types of end detectors used for high energy experiments.
  1. M. Khoshakhlagh, J. P. Islamian, S. M. Abedi, B. Mahmoudian, “Development of scintillators in nuclear medicine,” World J. Nucl. Med., vol. 14, no. 3, pp. 156 – 159, Sep.-Dec. 2015.
    DOI: 10.4103/1450-1147.163241
    PMid: 26420984
    PMCid: PMC4564916
  2. M. C. Rao, “Applications of Nd:YAG Lasers in material processing: Fundamental approach,” IJAPBC, vol. 2, no. 3, pp. 518 – 522, Jul.-Sep. 2013.
    Retrieved from: https://www.ijapbc.com/files/17-2316.pdf
    Retrieved on: Feb. 22, 2024
  3. C. W. E van Eijk, “Development of inorganic scintillators,” Nucl. Instr. Meth. Phys. Res. A, vol. 392, no. 1 – 3, pp. 285 – 290, Jun. 1997.
    DOI: 10.1016/S0168-9002(97)00239-8
  4. J. Andriessen, P. Dorenbos, C. W. E. van Eijk, “Calculation of energy levels of cerium in inorganic scintillator crystals,” Mater. Res. Soc. Symp. Proc., vol. 348, pp. 355 – 365, Jun. 1994.
    DOI: 10.1557/PROC-348-355
  5. M. Cruceru, I. Cruceru, O. G. Duliu, “On the spectroscopic properties of highly doped CsI(Tl) scintillators,” Rom. Rep. Phys., vol. 63, no. 3, pp. 693 – 699, 2011.
    Retrieved from: https://rrp.nipne.ro/2011_63_3/art07Cruceru.pdf
    Retrieved on: Feb. 22, 2024
  6. M. Moscynski, T. Ludziejewski, D. Wolski, W. Klamra, L. O. Norlin, “Properties of the YAG:Ce scintillator,” Nucl. Instr. Meth. Phys. Res. A, vol. 345, no. 3, pp. 461 – 467, Jul. 1994.
    DOI: 10.1016/0168-9002(94)90500-2
  7. R. Bougault et al., “The FAZIA project in Europe: R&D phase,” Eur. Phys. J. A, vol. 50, 47, Feb. 2014.
    DOI: 10.1140/epja/i2014-14047-4
  8. E. Aker et al., “The Crystal Barrel Spectrometer at LEAR,” Nucl. Instr. Meth. Phys. Res. A, vol. 321, no. 1 – 2, 69 – 108, Sep. 1992.
    DOI: 10.1016/0168-9002(92)90379-I
  9. C. Bebek, “A Cesium Iodide Calorimeter with Photodiode Readout for {CLEO}-{II},” Nucl. Instr. Meth. Phys. Res. A, vol. 265, no. 1 – 2, pp. 258 – 265, Mar. 1988.
    DOI: 10.1016/0168-9002(88)91079-0
  10. Y. Ohshima et al., “Beam test of the CsI(Tl) calorimeter for the BELLE detector at the KEK B factory,” Nucl. Instr. Meth. Phys. Res. A, vol. 380, no. 3, pp. 517 – 523, Oct. 1996.
    DOI: 10.1016/0168-9002(96)00706-1
  11. A. Stahl, “The BaBaR Electromagnetic calorimeter,” Nucl. Instr. Meth. Phys. Res. A, vol. 409, no. 1 – 3, pp. 615 – 617, May 1998.
    DOI: 10.1016/S0168-9002(97)01335-1

Radiation Detectors

FABRICATION AND FIRST ELECTRICAL TESTS OF SILICON-BASED PIN PHOTODIODES FOR RADIATION APPLICATIONS

E. Yilmaz, E. Doganci, O. Yilmaz, U. Gurer, A. Kahraman, A. Mammadli, C. Abbasova, N. Suleymanova, S. Nuruyev, R. Akbarov, A. Mutale, E. Budak, A. Aktag, H. Karacali

Pages: 44-47

DOI: 10.37392/RapProc.2024.10

Abstract | References | Full Text (PDF)

Silicon-based PIN photo diodes with 3 x 3 mm2 sensitive regions were successfully fabricated in this work. The electrical properties of PIN diodes were investigated intensively. The dark current of Silicon PIN photodiodes has been found to be 200nA at a reverse voltage of -70V. The PIN photo diodes have also been found to reach the full depletion mode and a capacitance value of 5.5 pF has been achieved at -40V. When the photo- sensitive region of the photo diode was illuminated with a help of 450 nm LED light. The photon current of 310 nA was obtained at a reverse voltage of -70V by using 450nm LED light. As the results of first evaluation, the experimental results also showed high dark current value and low photocurrent efficiency. The problems affecting the electrical performance of PIN diodes have been addressed in this research work. Additionally, all the results were carried out at room temperature.
  1. G. F. Dalla Betta, S. Ronchin, A. Zoboli, N. Zorzi, “High-performance PIN photodiodes on TMAH thinned silicon wafers,” Microelectron. J., vol. 39, no. 12, pp. 1485 – 1490, Dec. 2008.
    DOI: 10.1016/j.mejo.2008.04.009
  2. I. B. Chistokhin, K. B. Fritzler, “The Influence of the Conditions of Getter Formation in High-Resistivity Silicon on the Characteristics of PIN Photodiodes,” Tech. Phys. Lett., vol. 46, no. 11, pp. 1057 – 1059, Nov. 2020.
    DOI: 10.1134/S1063785020110048
  3. P. Buzhan et al., “An Advanced Study of Silicon Photomultiplier,” ICFA Ins. Bull., vol. 23, Fall Issue, pp. 28 – 41, 2001.
    Retrieved from: https://www.slac.stanford.edu/pubs/icfa/
    Retrieved on: Nov. 15, 2024
  4. M. Holik et al., “Miniaturized read-out interface ‘Spectrig MAPD’ dedicated for silicon photomultipliers,” Nucl. Inst. Meth. Phys. Res. A, vol. 978, 164440, Oct. 2020.
    DOI: 10.1016/j.nima.2020.164440
  5. Y. J. Feng et al., “Scalability of dark current in silicon PIN photodiode,” Chin. Phys. B, vol. 27, no. 4, 048501, Apr. 2018.
    DOI: 10.1088/1674-1056/27/4/048501
  6. E. Doǧanci et al., “Fabrication and characterization of Si-PIN photodiodes,” Turk. J. Phys., vol. 43, no. 6, pp. 556 – 562, 2021.
    DOI: 10.3906/fiz-1905-16
  7. S. C. Lee, H. B. Jeon, K. H. Kang, H. Park, “Study of silicon PIN diode responses to low energy gamma-rays,” J. Korean Phys. Soc., vol. 69, no. 10, pp. 1587 – 1590, Nov. 2016.
    DOI: 10.3938/jkps.69.1587
  8. K.-S. Park et al., “Estimates of the Photo-Response Characteristics of a Non-Fully-Depleted Silicon p-i-n Photodiode for the Near Infrared Spectral Range and the Experimental Results,” J. Korean Phys. Soc., vol. 50, no. 4, pp. 1156 – 1162, Apr. 2007.
    DOI: 10.3938/jkps.50.1156
  9. R. Kumar, S. D. Sharma, A. Philomina, A. Topkar, “Dosimetric characteristics of a PIN diode for radiotherapy application,” Technol. Cancer Res. Treat., vol. 13, no. 4, pp. 361 – 367, Aug. 2014.
    DOI: 10.7785/tcrt.2012.500388
    PMid: 24325130
  10. M. Kunst, O. Abdallah, F. W. Unsch, “Passivation of silicon by silicon nitride films,” Sol. Energy Mater. Sol. Cells, vol. 72, no. 1 – 4, pp. 335 – 341, Apr. 2002.
    DOI: 10.1016/S0927-0248(01)00181-7
  11. Z. Sadygov et al., “Model of single-electron performance of micro-pixel avalanche photo-diodes,” deposited at arXiv, Oct. 9, 2014.
    arXiv: 1410.2619
  12. A. Sadigov et al., “An Iterative Model of Performance of Micropixel Avalanche Photodiodes,” IJARPS, vol. 3, no. 2, pp. 9 – 19, Feb. 2016.
    Retrieved from: www.arcjournals.org
    Retrieved on: Nov. 15, 2024
  13. C. G. Kang et al., “Correlation between Guard Ring Geometry and Reverse Leakage Current of Si PIN Diode for Radiation Detector,” in Proc. Trans. Korean Nuc. Soc. Autumn Meeting, Gyeongju, Korea, 2017.
    Retrieved from: https://www.kns.org/files/pre_paper/38/17A-175%EA%B0%95%EC%B0%BD%EA%B5%AC.pdf
    Retrieved on: Nov. 15, 2024
  14. P. Jursinic, “PIN diodes for radiation therapy use: Their construction, characterization, and implementation,” Phys. Med., vol. 59, pp. 86 – 91, Mar. 2019.
    DOI: 10.1016/j.ejmp.2019.02.021
  15. M. Menichelli, L. Servoli, N. Wyrsch, “Status and perspectives of hydrogenated amorphous silicon detectors for MIP detection and beam flux measurements,” Front. Phys., vol. 10, Oct. 2022.
    DOI: 10.3389/fphy.2022.943306
  16. Z. Sadygov, A. Olshevski, I. Chirikov, I. Zheleznykh, A. Novikov, “Three advanced designs of micro-pixel avalanche photodiodes: Their present status, maximum possibilities, and limitations,” Nucl. Instrum. Methods Phys. Res. A, vol. 567, no. 1, pp. 70 – 73, Nov. 2006.
    DOI: 10.1016/j.nima.2006.05.215
  17. A. B. Rosenfeld, “Electronic dosimetry in radiation therapy,” Radiat. Meas., vol. 41, suppl. 1, pp. S134 – S153, Dec. 2006.
    DOI: 10.1016/j.radmeas.2007.01.005
  18. Y. Yamashita, H. Tadano, “Numerical modeling of reverse recovery characteristic in silicon pin diodes,” Solid State Electron., vol. 145, pp. 8 – 18, Jul. 2018.
    DOI: 10.1016/j.sse.2018.02.014
  19. A. B. Rosenfeld, “Advanced Semiconductor dosimetry in radiation therapy,” AIP Conf. Proc., vol. 1345, no. 1, pp. 48 – 74, May 2011.
    Retrieved from: https://ro.uow.edu.au/eispapers
    Retrieved on: Nov. 15, 2024
  20. R. A. Akbarov et al., “Scintillation readout with MAPD array for gamma spectrometer,” JINST, vol. 15, no. 1, C01001, Jan. 2020.
    DOI: 10.1088/1748-0221/15/01/C01001
  21. G. Ahmadov et al., “Gamma-ray spectroscopy with MAPD array in the readout of LaBr3 scintillator,” JINST, vol. 16, no. 7, P07020, Jul. 2021.
    DOI: 10.1088/1748-0221/16/07/P07020
  22. F. Ahmadov et al., “Investigation of parameters of new MAPD-3NM silicon photomultipliers,” JINST, vol. 17, no. 1, C01001, Jan. 2022.
    DOI: 10.1088/1748-0221/17/01/C01001
  23. M Holik et al., “Gamma ray detection performance of newly developed MAPD-3NM-II photosensor with LaBr3(Ce) crystal,” Sci. Rep., vol. 12, no. 1, 15855, Sep. 2022.
    DOI: 10.1038/s41598-022-20006-z
  24. A. Z. Sadigov et al., “Improvement of parameters of micro-pixel avalanche photodiodes,” J. Instrum., vol. 17, no. 7, P07021, Jul. 2022.
    DOI: 10.1088/1748-0221/17/07/P07021
  25. A. Sadigov et al., “Performance of styrene polymerized plastic scintillator with micropixel avalanche photodiode,” Radiat. Meas., vol. 171, 107061, Feb. 2024.
    DOI: 10.1016/j.radmeas.2024.107061
  26. S. Nuruyev et al., “Neutron/gamma scintillation detector for status monitoring of accelerator-driven neutron source IREN,” Nucl. Eng. Technol., vol. 56, no. 5, pp. 1667 – 1671, May 2024.
    DOI: 10.1016/j.net.2023.12.020
  27. A. N. Buynin, V. V. Osiko, Z. Z. Sadygov, V. G. Shangurov, “Microchannel avalanche photodetectors on Si/YSZ and Si/Si structures,” in Proc. 29th Workshop on Compound Semiconductor Devices and Integrated Circuits held in Europe (WOCSDICE), Cardiff, UK, 2005.
    Retrieved from: https://www.researchgate.net/publication/257873810
    Retrieved on: Nov. 15, 2024
  28. Z. Z. Sadygov et al., “A new low-noise avalanche photodiode with micro-pixel structure,” Physics, vol. X, no. 4, pp. 79 – 80, 2004.
    Retrieved from: https://www.researchgate.net/publication/237496809
    Retrieved on: Nov. 15, 2024
  29. M. Menichelli et al., “Fabrication of a hydrogenated amorphous silicon detector in 3-d geometry and preliminary test on planar prototypes,” Instruments, vol. 5, no. 4, 32, Dec. 2021.
    DOI: 10.3390/instruments5040032
  30. J. C. Gallagher et al., “Effect of GaN Substrate Properties on Vertical GaN PiN Diode Electrical Performance,” J. Electron. Mater., vol. 50, no. 6, pp. 3013 – 3021, Jun. 2021.
    DOI: 10.1007/s11664-021-08840-9

Radiation Measurements

ASSESSING GAMMA DOSE RATES: AIRBORNE NATURAL RADIOACTIVITY MEASUREMENTS IN ALBANIA

Jurgen Shano, Elida Bylyku, Dritan Prifti, Kozeta Tushe, Brunilda Daci

Pages: 48-52

DOI: 10.37392/RapProc.2024.11

Abstract | References | Full Text (PDF)

Our study’s main objective is to evaluate gamma dose rates in the air across the Republic of Albania. The Institute of Applied Nuclear Physics set up six monitoring stations in different parts of the country to measure how much radiation is present each month and year, and to figure out the total yearly exposure to natural radioactivity in the air. The monitoring system employed for gamma radiation is the GMT-based Gamma Dose Rate Monitoring System. The research has shown that the average radiation level for Albania is about 1.61 µSv ± 0.010 µSv/h, and the yearly estimate is around 587 µSv ±0.01 µSv/h. One interesting finding is that for three years in a row, Elbasan had the highest radiation reading, reaching up to 3,477 µSv. This number changed depending on the time of year, with the highest levels often happening during rainy days. These findings provide a baseline for monitoring environmental radioactivity and informing public health policies.
  1. K. S. V. Nambi et al., Natural background radiation and population dose distribution in India, Bhabha Atomic Research Centre, Bombay, India, 1986.
    Retrieved from: https://inis.iaea.org/collection/NCLCollectionStore/_Public/20/084/20084715.pdf
    Retrieved on: Aug. 8, 2023
  2. Atlas of Albania, Commons Wikimedia, a, San Francisco (CA), USA, 2022.
    Retrieved from: https://commons.wikimedia.org/wiki/Atlas_of_Albania
    Retrieved on: Jan. 16, 2022
  3. Copernicus: 2022 was a year of climate extremes, with record high temperatures and rising concentrations of greenhouse gases, ECMWF/ Copernicus Climate Change Service, 2022.
    Retrieved from: https://climate.copernicus.eu/copernicus-2022-was-year-climate-extremes-record-high-temperatures-and-rising-concentrations
    Retrieved on: Apr. 1, 2022
  4. Qeveria e Shqipërisë. (Nëntor 21, 2018). Vendim nr. 700 për miratimin e rregullores “për përgatitjen dhe reagimin në rast emergjence radiologjike për mbrojtjen e punonjësve dhe të publikut”.
    (Government of Albania. (Nov. 21, 2018). Decision no. 700 for the approval of the regulation “for the preparation and response in the case radiological emergency for the protection of employees and the public” )
    Retrieved from: https://shendetesia.gov.al/wp-content/uploads/2019/02/VKM-nr.-700-date-21.11.2018.pdf
    Retrieved on: Apr. 1, 2022
  5. G. Cinelli et al., “Digital version of the European Atlas of natural radiation,” J. Environ. Radioact., vol. 196, pp. 240 – 252, Jan. 2019.
    DOI: 10.1016/j.jenvrad.2018.02.008
    PMid: 29496295
    PMCid: PMC6290173
  6. Weather in Tirana in April 2022, World Weather, 2022.
    Retrieved from: https://world-weather.info/forecast/albania/tirana/april-2022
    Retrieved on: Apr. 1, 2022
  7. N. Kadhim, Radioactivity, ResearchGate, Berlin, Germany, 2020.
    Retrieved from: https://www.researchgate.net/publication/339831191_Radioactivity
    Retrieved on: Aug. 8, 2023
  8. D. Shahbazi-Gahrouei, M. Gholami, S. Setayandeh, “A review on natural background radiation,” Adv. Biomed. Res., vol. 2, no. 1, p. 65, 2013.
    DOI: 10.4103/2277-9175.115821
  9. S. S. Duhan, P. Khyalia, J. S. Laura, “A comprehensive analysis of health risk due to natural outdoor gamma radiation in Southeast Haryana, India,” Curr. Sci., vol. 123, no. 2, pp. 169 – 176, Jul. 2022.
    DOI: 10.18520/cs/v123/i2/169-176
  10. D. Patel, M. K. Jindal, P. S. Pamidimukkala, D. Chakraborty, “Gamma radiation dose rate distribution in the Anand, Bharuch, Vadodara, and Narmada districts of Gujarat, India,” Environ. Sci. Pollut. Res., vol. 30, no. 49, pp. 107104 – 107117, Oct. 2023.
    DOI: 10.1007/s11356-023-25711-4
    PMid: 36807856
  11. J. F. Mercier et al., “Increased environmental gamma-ray dose rate during precipitation: A strong correlation with contributing air mass,” J. Environ. Radioact., vol. 100, no. 7, pp. 527 – 533, Jul. 2009.
    DOI: 10.1016/j.jenvrad.2009.03.002
    PMid: 19403214
  12. G. Cortes, J. Sempau, X. Ortega, “Automated measurement of radon daughters Bi-214 and Pb-214 in rainwater,” Nukleonika, vol. 46, no. 4, pp. 161 – 164, 2001.
    Retrieved from: http://www.ichtj.waw.pl/ichtj/nukleon/back/full/vol46_2001/v46n4p161f.pdf
    Retrieved on: Aug. 8, 2023

Radon and Thoron

LESSONS LEARNED FROM THE 2022 CAMPAIGN OF THE MEASUREMENT OF INDOOR RADON CONCENTRATION IN DWELLINGS IN ALBANIA

Gerti Xhixha, Blerim Rrakaqi, Kozeta Tushe, Merita Xhixha (Kaçeli), Njomza Elezaj, Ylli Kaçiu, Nazim Gashi

Pages: 53-56

DOI: 10.37392/RapProc.2024.12

Abstract | References | Full Text (PDF)

Indoor radon concentration in Albania has been investigated to study the influence of measuring indoor radon concentration between living room and bedroom using the CR-39 Solid State Nuclear Track Detectors (SSNTDs). Approximately 60% (out of 69 measurement locations) of the indoor radon measurements were performed in houses, while the remainder in apartments. The average bedroom-living room indoor radon concentration in houses were found to vary from 13 to 454 Bq/m3 with an arithmetic mean of 68 Bq/m3 (median 49 Bq/m3), while in apartments from 24 to 144 Bq/m3 with an arithmetic mean of 54 Bq/m3 (median 47 Bq/m3). The relatively lower concentrations found in apartments is mainly due to apartment floor height, varying from 1st to 7th floor. The ratio of radon concentrations between bedroom/living rooms showed values varying from 0.3 to 4.1 in houses and 0.5 to 3.7 in apartments. The distribution is positively skewed with median value of 1.0 in houses and 1.1 in apartments. The slight difference between houses and apartments can be an indication that the lifestyle is a factor determining bedroom radon concentrations. However, these results support our proposal that radon concentration measured in living room and/or bedroom is representative for the determination of environmental radon exposure of the population in dwellings.
  1. Sources and effects of ionizing radiation, vol. 1, UNSCEAR Report (A/55/46), UNSCEAR, New York (NY), USA, 2000.
    Retrieved from: https://www.unscear.org/docs/publications/2000/UNSCEAR_2000_Report_Vol.I.pdf
    Retrieved on: Jan. 10, 2024
  2. K. B. Tushe et al., “First step toward the geographical distribution of indoor radon in dwellings in Albania,” Radiat. Prot. Dosim., vol. 172, no. 4, pp. 488 – 495, Dec. 2016.
    DOI: 10.1093/rpd/ncv494
  3. Qeveria e Shqipërisë. (Nëntor 25, 2015). Vendim nr. 957 për miratimin e rregullores “Për nivelet e lejuara të përqendrimit të radonit në ndërtesa dhe në ujë, nivelet drejtuese të radionuklideve në materialet e ndërtimit, si dhe nivelet e lejuara të radionuklideve në produktet ushqimore dhe kozmetike”.
    (Government of Albania. (Nov. 25, 2015). Decision no. 957 on the approval of the regulation “On the permitted levels of radon concentration in buildings and water, the guiding levels of radionuclides in building materials, as well as the permitted levels of radionuclides in food and cosmetic products”.)
  4. The Council of European Union. (Dec. 5, 2013). Council Directive 2013/59/EURATOM laying down basic safety standards for protection against the dangers arising from exposure to ionising radiation, and repealing Directives 89/618/Euratom, 90/641/Euratom, 96/29/Euratom, 97/43/Euratom and 2003/122/Euratom.
    Retrieved from: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2014:013:0001:0073:EN:PDF
    Retrieved on: Jan. 10, 2024
  5. F. Bochicchio et al., “Annual average and seasonal variations of residential radon concentration for all the Italian Regions,” Radiat. Meas., vol. 40, no. 2 – 6, pp. 686 – 694, Nov. 2005.
    DOI: 10.1016/j.radmeas.2004.12.023
  6. P. Bossew, H. Lettner, “Investigations on indoor radon in Austria, Part 1: Seasonality of indoor radon concentration,” J. Environ. Radioact., vol. 98, no. 3, pp. 329 – 345, Dec. 2007.
    DOI: 10.1016/j.jenvrad.2007.06.006
  7. Z. Daraktchieva, “New correction factors based on seasonal variability of outdoor temperature for estimating annual radon concentrations in UK,” Radiat. Prot. Dosim., vol. 175, no. 1, pp. 65 – 74, Jun. 2017.
    DOI: 10.1093/rpd/ncw270
  8. K. Kozak et al., “Correction factors for determination of annual average radon concentration in dwellings of Poland resulting from seasonal variability of indoor radon,” Appl. Radiat. Isot., vol. 69, no. 10, pp. 1459 – 1465, Oct. 2011.
    DOI: 10.1016/j.apradiso.2011.05.018
  9. V. Giagias, D. Burghele, C. Cosma, “Seasonal variation of indoor radon in dwellings from Athens, Greece,” Rom. J. Phys., vol. 60, no. 9 – 10, pp. 1581 – 1588, 2015.
    Retrieved from: https://rjp.nipne.ro/2015_60_9-10/RomJPhys.60.p1581.pdf
    Retrieved on: Jan. 10, 2024
  10. Z. Stojanovska et al., “Seasonal indoor radon concentration in FYR of Macedonia,” Radiat. Meas., vol. 46, no. 6 – 7, pp. 602 – 610, Jun.-Jul. 2011.
    DOI: 10.1016/j.radmeas.2011.04.022
  11. G. Cinelli, “Digital version of the European Atlas of natural radiation,” J. Environ. Radioact., vol. 196, pp. 240 – 252, Jan. 2019.
    DOI: 10.1016/j.jenvrad.2018.02.008
  12. H. A. Ghany, “Variability of radon levels in different rooms of Egyptian dwellings,” Indoor and Built Environ., vol. 15, no. 2, pp. 193 – 196, Apr. 2006.
    DOI: 10.1177/1420326X06063218
  13. S.U. Rahman, J. Anwar, M. Matiullah, “Measurement of indoor radon concentration levels in Islamabad, Pakistan,” Radiat. Meas., vol. 43, suppl. 1, pp. S401 – S404, Aug. 2008.
    DOI: 10.1016/j.radmeas.2008.04.046
  14. H. J. Jeon et al., “A preliminary study for conducting a rational assessment of radon exposure levels,” Environ. Sci. Pollut. Res., vol. 24, pp. 14491 – 14498, Jun. 2017.
    DOI: 10.1007/s11356-017-9030-5
  15. K. Badhan, R. Mehra, R. G. Sonkawade, “Studying the variation of indoor radon levels in different dwellings in Hoshiarpur district of Punjab, India,” Indoor and Built Environ., vol. 21, no. 4, pp. 601 – 606, Aug. 2012.
    DOI: 10.1177/1420326X11419983