Visual Place Recognition in Changing Environments

Localization is an essential capability of mobile robots and place recognition is an important component of localization. Only having precise localization, robots can reliably plan, navigate and understand the environment around them. The main task of visual place recognition algorithms is to recognize based on the visual input if the robot has seen previously a given place in the environment. Cameras are one of the popular sensors robots get information from. They are lightweight, affordable, and provide detailed descriptions of the environment in the form of images. Cameras are shown to be useful for the vast variety of emerging applications, from virtual and augmented reality applications to autonomous cars or even fleets of autonomous cars. All these applications need precise localization. Nowadays, the state-of-the-art methods are able to reliably estimate the position of the robots using image streams. One of the big challenges still is the ability to localize a camera given an image stream in the presence of drastic visual appearance changes in the environment. Visual appearance changes may be caused by a variety of different reasons, starting from camera-related factors, such as changes in exposure time, camera position-related factors, e.g. the scene is observed from a different position or viewing angle, occlusions, as well as factors that stem from natural sources, for example seasonal changes, different weather conditions, illumination changes, etc. These effects change the way the same place in the environments appears in the image and can lead to situations where it becomes hard even for humans to recognize the places. Also, the performance of the traditional visual localization approaches, such as FABMAP or DBow, decreases dramatically in the presence of strong visual appearance changes. The techniques presented in this thesis aim at improving visual place recognition capabilities for robotic systems in the presence of dramatic visual appearance changes. To reduce the effect of visual changes on image matching performance, we exploit sequences of images rather than individual images. This becomes possible as robotic systems collect data sequentially and not in random order. We formulate the visual place recognition problem under strong appearance changes as a problem of matching image sequences collected by a robotic system at different points in time. A key insight here is the fact that matching sequences reduces the ambiguities in the data associations. This allows us to establish image correspondences between different sequences and thus recognize if two images represent the same place in the environment. To perform a search for image correspondences, we construct a graph that encodes the potential matches between the sequences and at the same time preserves the sequentiality of the data. The shortest path through such a data association graph provides the valid image correspondences between the sequences. Robots operating reliably in an environment should be able to recognize a place in an online manner and not after having recorded all data beforehand. As opposed to collecting image sequences and then determining the associations between the sequences offline, a real-world system should be able to make a decision for every incoming image. In this thesis, we therefore propose an algorithm that is able to perform visual place recognition in changing environments in an online fashion between the query and the previously recorded reference sequences. Then, for every incoming query image, our algorithm checks if the robot is in the previously seen environment, i.e. there exists a matching image in the reference sequence, as well as if the current measurement is consistent with previously obtained query images. Additionally, to be able to recognize places in an online manner, a robot needs to recognize the fact that it has left the previously mapped area as well as relocalize when it re-enters environment covered by the reference sequence. Thus, we relax the assumption that the robot should always travel within the previously mapped area and propose an improved graph-based matching procedure that allows for visual place recognition in case of partially overlapping image sequences. To achieve a long-term autonomy, we further increase the robustness of our place recognition algorithm by incorporating information from multiple image sequences, collected along different overlapping and non-overlapping routes. This allows us to grow the coverage of the environment in terms of area as well as various scene appearances. The reference dataset then contains more images to match against and this increases the probability of finding a matching image, which can lead to improved localization. To be able to deploy a robot that performs localization in large scaled environments over extended periods of time, however, collecting a reference dataset may be a tedious, resource consuming and in some cases intractable task. Avoiding an explicit map collection stage fosters faster deployment of robotic systems in the real world since no map has to be collected beforehand. By using our visual place recognition approach the map collection stage can be skipped, as we are able to incorporate the information from a publicly available source, e.g., from Google Street View, into our framework due to its general formulation. This automatically enables us to perform place recognition on already existing publicly available data and thus avoid costly mapping phase. In this thesis, we additionally show how to organize the images from the publicly available source into the sequences to perform out-of-the-box visual place recognition without previously collecting the otherwise required reference image sequences at city scale. All approaches described in this thesis have been published in peer-reviewed conference papers and journal articles. In addition to that, most of the presented contributions have been released publicly as open source software

EVALUATION OF HORMONAL AND METABOLIC PARAMETERS, ALONG WITH CARDIOVASCULAR RISK FACTORS IN WOMEN WITH NON-ALCOHOLIC FATTY LIVER DISEASE COMBINED WITH SUBCLINICAL HYPOTHYROIDISM DEPENDING ON AGE

Patients with NAFLD (non-alcoholic fatty liver disease) and subclinical hypothyroidism are at risk of cardiovascular complications that cause cardiometabolic changes, thus enabling to broaden our understanding of the cardiovascular events risk in a comorbid patient. The aim: The study of hormonal and metabolic indicators and cardiovascular risk factors in women from NAFLD combined with SH (subclinical hypothyroidism) depending on the age. Materials and methods: 128 patients with NAFLD were studied, which were divided into 2 groups: І group – patients with NAFLD and level of thyroid-stimulating hormone (TSH) – 4 to 10 mIU/mL (n=45), ІІ group - patients with NAFLD and level of TSH >10 mIU/mL (n=49). The control group consisted of 34 NAFLD patients without SH. Depending on the level of TSH and age, degree of cardiovascular risk, indicators of carbohydrate and lipid metabolism, as well as the indicators that reflect ED were evaluated. Results: Comparison of metabolic parameters in two groups showed a significant difference (p<0.01 between indicators depending on the TSH level, where patients were below 50 years of age: HbA1c, LDL cholesterol, HDL cholesterol, gamma-glutamyltranspeptidase (GGTP). The levels of CDEC (circulating desquamated endothelial cells), VEGF (vascular endothelial growth factor), CRP (C-reactive protein) and TNF-α (tumor necrosis factor-α) were dependent not only on TSH, but also on age. Significant differences (p=0.001) were obtained in patients aged ≤ 50 years: CDEC; VEGF, CRP; TNF-α. Conclusions: Patients from NAFLD combined with SH have hormonal-metabolic disorders, and their degree depends on the TSH level. Early cardiometabolic changes in women are formed already at the age under 50 years, which indicates the formation of early atherosclerotic vascular change

Деякі аспекти еконебезпеки внаслідок видобування урану

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Yaderna ta radiatsiina bezpeka, 4, 51–54. 5. Dudar,T.V.,Lysychenko,G.V., Buhera,M.A.,2018.Uranium resources of Ukraine: geology, mineralogy, and some mining aspects: monograph. Riga: Lambert Publishing House. – 100 p. 6. Dudar, T. V., 2019. Uranium mining and milling facilities legacy sites: Ukraine case study. Environmental Problems, Volume 4, Number 4, 212–218. DOI: 10.23939/ep2019.04.212 7. Dudar, T. V., Verkhovtsev, V. G., Tyshchenko, Yu.Ye., Ky- selevych L. S., Buglak O. V., 2019. Radon-prone Areas: the Ukrainian Shield case study / European Association of Geoscientists & Engineers. Confer- ence Proceedings, 18th International Conference on Geoinformatics – Theoretical and Applied Aspects. 1–6. DOI: 10.3997/2214-4609.201902034 8. Dudar, T. V., Titarenko, O.V., Nekos, A.N., Vysotska, O.V., Porvan, A.P., 2020. Geospatial modeling of radon- prone areas. Nuclear and radiation safety. Kyiv, Vyp. 3 (87), 28-37. Doi: https://doi.org/10.32918/nrs.2020.3(87).04 9. EC Council Directive 2013/59/Euratom, 2014. Laying down basic safety standards for protection against the dangers arising from exposure to ionising radi- ation. Official J. Eur. Union. 2014; 57 (L13):1–73. 10. European Atlas of Natural Radiation, 2019. European Com- mission, Joint Research Centre – Cinelli, G., De Cort, M. & Tollefsen, T. (Eds.), Publication Office of the European Union, Luxembourg, doi:10.2760/520053, Catalogue number KJ-02-19-425-EN-C, EUR 19425 EN. Printed by Bietlot in Belgium 2019– 190. Pp. 30.1 cm– 42.4 cm. DOI: 10.2760/520053 11. Fomin, Yu. O., Demikhov, Yu. O., Verk- hovtsev, V. G., Dudar, T. V., 2019. Formy znakhodzennya elementiv-suputnykiv uranu u albititakh Ukrainskogo shchita [Forms of finding uranium satellite elements in albitites of the Ukrainian Shield]. Geokhimiya technogeneza: zb. nauk. prats IGNS NAN Ukrainy. Kyiv, Vyp. 2 (30), 106–118. DOI: 10.15407/geo-tech2019.30.106. 12. Fomin, Yu.O., Demikhov Yu.M., Verkhovtsev, V.G., Dudar, T.V., Borisova, Z.M., Kravchuk, Z.M., 2019. Elementy-suputnyky uranovogo zrudeninnya albiti- tovoi formatsii Ukrainskogo shchita ta ikh vplyv na navkolyshne seredovyshche [Рathfinder elements of uranium mineralization from albitite formation of the Ukrainian shield and their impact on the environment]. Ekologichna bezpeka ta pryrodo-korystyvannya: zb. nauk. prats, 33, No 1, 42–58. DOI: 10.32347/2411-4049.2020.1.42-58 13. IAEA, 2018. Map of World distribution of Uranium De- posits. Retrieved from URL: https://www.iaea. org/publications/12314/world-distribution-of- uranium-deposits 14. Kalashnyk, G.A., 2017. Radioekologichna sytuatsiya v misti Kropyvnytskyi – tsentri uranodobuvnoi promyslovosti Ukrainy [Radioecological situation in the city of Kropyvnytskyi – the center of uranium mining of Ukraine]. Mineralni resursy Ukrainy, 2, 43-49. 15. Koshyk, Yu.I., Kryvchykov, V.A., Khudoshina, N.A., 2013. Otsenka vozdeistviya na okruzayushchuyu sredu. Zavod po proizvodstvu yadernogo topliva. Proekt. Tom 8. Zeltie Vodi: GP “UkrNIIpromtech- nologii”, 273. 16. Kovalenko, G.D., 2013. Radioekologiya Ukrainy [Radioecology of Ukraine] Kharkiv: ID “Inzhek”. – 344 p. (in Russian) 17. Lyashenko, V.I., Topolnyi, F.F., Mostipan, M.I., Lisova, T.S., 2011. Ekologichna bezpeka uranovogo vy- robnytstva [Environmental safety of uranium mining]. Monograph. Ed. by F.F. Topolnyi. Kiro- vograd: “KOD”. 240. (in Ukrainian) 18. Mikhailichenko, O.M., 2018. Zvit pro regionalne geo- logichne vyvchennya terytorii Ukrainy “Skladan- nya karty uranovogo i torievogo zrudeninnya Ukrainskogo Shchita masshtabu 1:500 000” [Re- port on the Regional Geological Survey of the Territory of Ukraine “Mapping of the Uranium and Thorium Ore Manifestations of the Ukrai- nian Shield 1: 500,000”]. State-owned Enterprise ‘Kirovgeologiya’. 150. (in Ukrainian) 19. Natsionalnyi Atlas Ukrainy. Rudenko L.G. (Ed.) [National Atlas of Ukraine]. Kyiv: DNVP “Kartographiya”. 435. (in Ukrainian and English) 20. NRBU-97. Normy radiatsiinoi bezpeky Ukrainy – 1997/ D-2000 (DGN 6.6.1-6.5.061-2000) [Norms of Radiation Safety in Ukraine – 1997/D-2000]. Zatverdzeno postanovoyu Golovnogo derzavno- go sanitarnogo likarya Ukrainy vid 12.07.2000 N 116. (in Ukrainian) 21. Podulyakh, S., 2017. Yaderne sertse Ukrainy [Nuclear he- art of Ukraine]. Atomprom Ukrainy. 2, 6-8. (in Ukrainian) 22. Stankevich, S.A., Kharytonov, N.N., Dudar, T.V., Kozlo- va A.A. (2016). Risk Assessment of Land Deg- radation Using Satellite Imagery and Geospa- tial Modelling in Ukraine. In book: Land Degradation and Desertification - a Global Crisis. Edited by Abuid Kaswamila, ISBN 978-953- 51-2707-9, Print ISBN 978-953-51-2706-2, 122 pages, Publisher: InTech . Chapter 3. p.53- 77. DOI: 10.5772/62403 23. Stankevich, S.A., Kharytonov, M.M., Kozlova, A.A., Ko- rovin, V.Yu, Svidenyuk, M.O., Valyaev, A.M., 2018. Soil Contamination Mapping with Hyperspectral Imagery: Pre -Dnieper Chemi- cal Plant (Ukraine) Case Study, Hyperspectral Imaging in Agriculture, Food and Environment, Alejandro Isabel Luna Maldonado, Humberto Rodríguez Fuentes and Juan Antonio Vi- dales Contreras, IntechOpen, DOI: 10.5772/ intechopen.72601. https://www.intechopen.com/ books/hyperspectral-imaging-in-agriculture- food-and-environment/soil-contamination- mapping-with-hyperspectral-imagery-pre-dnieper-chemical-plant-ukraine-case-study 24. Stankevich, S.A., Dudar, T.V., Svideniuk, M.O., 2019. Zastosuvannya bagatochasovoi radarnoi interferomet- rii dlya vyyavlennya zmishchennya zemnoi poverkhni dlya terrytorii uranobydobuvannya v Ukraini [Radar interferometry time series analysis for land surface displacement detection within the uranium mining area in Ukraine]. Ecologichna bezpeka, 2/2019(28), 18–23. DOI: 10.30929/2073- 5057.2019.2.18-23 25. Shumlyanskyi, V.O., Subbotin, A.G., Bakarziev, A.H. et al., 2003. Tekhnogenne zabrudnennya radioaktyvnymy elementamy na rodovyshchakh korysnykh kopalyn [Tecnogenic contamination with radioactive elements on the mineral deposits] Kyiv: Znannya Ukrainy. – 133. (in Ukrainian) 26. Shumlyanskyi, V.O., Makarenko, M.M., Kolyabina, I.L. et al., 2007. Monitoryng pryrodnogo seredovyshcha pislya dobuvannya uranu sposobom pidzemnogo vylugovuvannya: monographiya [Monitoring of natural environment after uranium mining through underground leaching: monograph]. Instytut fundamentalnykh doslidzen Ukrainskoi naukoboi asotsiatsii. Kyiv: Logos. 27. Sushchuk, K.G., Verkhovtsev, V.G., 2019. Metalogeniya uranu v fanerozoi planformenoi chastyny Ukrainy [Metalogey of uranium in Phanerozoe of the platfor part of the Ukrainian Shield]. Geochimiya tekhno- genezu. Kyiv, 2 (30), 56-69. 28. TENORM, 2007. Technologically Enhanced Naturally Occurring Radioactive Materials from Uranium Mining. U.S. Environmental Protection Agency. Published on-line as Vol. 2 of EPA 402-R-05-007. Retrieved from URL: https://www.epa.gov/sites/ production/files/2015-05/documents/402-r-08- 005-v2.pdf 29. Verkhovtsev, V.G., Zabulonov et al., 2014. Perspektyvy rozvytku uranovoi syrovynnoi bazy yadernoi energetyky Ukrainy [Prospects for the development of uranium resource base of nuclear power of Ukraine]. Kyiv: Naukova Dumka. 355. (in Ukrainian) 30. WNA, 2020. World Nuclear Association. World Nuclear Reactors and Uranium Requirements, September 2020. Retrieved from URL: http://www.world- nuclear.org/information-library/facts-and-figures. aspxSome aspects of environmental hazard within uranium mining areas are considered. The uranium content in the environment components (rocks, soils, underground and surface waters) of the central part of the Ukrainian Shield within and beyond the uranium mining area is analyzed on the example of the Michurinske ore field. It is emphasized that man-made sources of natural origin should be considered more broadly than just waste dumps from uranium mining and processing enterprises. These are sources of ionizing radiation of natural origin, which have been subjected to concentration or their accessibility has been increased because of anthropogenic activity. Additional irradiation to the natural radiation background is formed. Waste dumps of uranium mining are considered as sources of potential dust pollution in the surface layers of atmosphere with fine dust containing uranium, its decay products and associated elements. The area of waste dumps is calculated using space images. Uranium accumulates in the dusty fraction, where its content is 0.01-0.06%. Taking into account the geological and geochemical characteristics of uranium deposits, radioactive elements, heavy metals and other associated elements of uranium mineralization are car- ried out of the dumps by winds and atmospheric waters with their subsequent migration into environment components. A mathematical model of potential dust air pollution in the area of long-term operation of the oldest uranium mine is presented for the summer 2019. In total, 15 factors influencing the potential threat of air dust pollution are considered and analyzed. The mathematical model is developed on the basis of the method of discriminant functions. To assess the degree of the model parameters informativeness, one-factor covariance analysis is used. It allows assessing the degree of a single sign influence on the prediction result. The developed model takes into account the area of waste dumps, uranium content in the dust fraction and wind direction southeast and/or east as the most hazardous for the study area. The model allows determining correctly the level of potential threat of air dust pollution in 96.3% ± 3.6% of all cases.Розглянуто деякі аспекти екологічної небезпеки в районі видобутку урану та за його межами. Проаналізовано вміст урану в компонентах довкілля (породах, ґрунтах, підземних та поверхневих водах) центральної частини Українського щита на прикладі Мічурінського рудного поля. Наголошено, що техногенно-підсилені джерела природного походження слід розглядати ширше, ніж просто відходи урановидобувних і переробних підприємств. Це джерела іонізуючого випромінювання природного походження, які в результаті антропогенної діяльності були піддані концентруванню або збільшилася їхня доступність, внаслідок чого утворилося додаткове до природного радіаційного фону опромінювання. Породні відвали урановидобування розглядаються як джерела потенційної запиленості приземних шарів атмосфери дрібнодисперсним пилом, який містить уран, продукти його розпаду та супутні елементи. Площа породних відвалів розраховується з використанням космічних знімків. Уран накопичується у пилуватій фракції, де його вміст складає 0.01-0.06%. З урахуванням геолого-геохімічних характеристик уранових родовищ радіоактивні елементи, важкі метали та інші елементи-супутники уранового зруденіння виносяться з відвалів вітрами та атмосферними водами з подальшою їх міграцією у компоненти довкілля. Розроблено математичну модель потенційного пилового забруднення повітря в районі довготривалого функціонування найстарішої урановидобувної шахти, за літній період 2019 року. Загалом розглянуто та проаналізовано 15 факторів, що впливають на потенційну загрозу запиленості повітря. Математичну модель розроблено на базі методу дискримінантних функцій. Для оцінки ступеня інформативності параметрів моделі був використаний однофакторний дисперсійний аналіз, що дозволяє оцінити ступінь впливу окремо взятої ознаки на результат прогнозування. Розроблена модель, що враховує площу відвалів, вміст урану в пилуватій фракції та напрям вітру південно-східний та/або східний як найбільш небезпечний для досліджуваної території, коректно дозволяє визначити рівень потенційної загрози запиленості повітря у 96,3%±3,6% усіх випадкі

Results of the COVID-19 mental health international for the general population (COMET-G) study.

INTRODUCTION: There are few published empirical data on the effects of COVID-19 on mental health, and until now, there is no large international study. MATERIAL AND METHODS: During the COVID-19 pandemic, an online questionnaire gathered data from 55,589 participants from 40 countries (64.85% females aged 35.80 ± 13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively. STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses and Factorial Analysis of Variance (ANOVA) tested relations among variables. RESULTS: Probable depression was detected in 17.80% and distress in 16.71%. A significant percentage reported a deterioration in mental state, family dynamics and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (31.82% vs. 13.07%). At least half of participants were accepting (at least to a moderate degree) a non-bizarre conspiracy. The highest Relative Risk (RR) to develop depression was associated with history of Bipolar disorder and self-harm/attempts (RR = 5.88). Suicidality was not increased in persons without a history of any mental disorder. Based on these results a model was developed. CONCLUSIONS: The final model revealed multiple vulnerabilities and an interplay leading from simple anxiety to probable depression and suicidality through distress. This could be of practical utility since many of these factors are modifiable. Future research and interventions should specifically focus on them

US e-learning course adaptation to the Ukrainian context: lessons learned and way forward

Abstract Background Access to continuing education opportunities is limited for Ukrainian healthcare workers, and the need is acute in order to support healthcare reform efforts currently underway in Ukraine. Online learning is a cost-effective mechanism for continuing education since healthcare workers can remain on the job during training. It also provides a means of keeping health professionals up to date on their knowledge and skills in rapidly changing and increasingly complex healthcare environments. Methods This paper describes the process of adapting an existing e-learning course from a US institution to the Ukrainian setting. Course participants’ feedback was used to evaluate the effectiveness of the adapted version that was piloted twice in 2016–2017 with 53 participants in total, 46 of whom completed the course and contributed to the evaluation. Results This was the first fully online course on Leadership and Management in Health (LMiH) to be offered in Ukraine. Several lessons were learned during course adaptation when multiple aspects of the Ukrainian environment were taken into account including 1) linguistic accessibility, 2) access to the Internet, 3) computer literacy, and 4) novelty of online learning. Based on these findings, course material was first adapted by translating it from English to Ukrainian with the emphasis on cultural adjustment of idioms and real life examples. Then, using the first pilot results and participants suggestions, videotaped interviews with local healthcare management experts were added in order to further enhance cultural suitability as well as relevance and applicability of the course concepts. The last but not least lesson learned consisted in the fact that enhancing, transitioning, and sustaining online learning to new contexts required engagement of key stakeholders, national level support, and technical assistance through implementation and beyond yet turned out to be both cost-effective and sustainable investment of limited resources. Formative evaluation confirmed that the adaptation efforts resulted in a course relevant and acceptable to healthcare professionals in Ukraine. Conclusion Transition of the course to local ownership was accomplished in partnership with the Ukrainian Family Medicine Training Center in the Bogomolets National Medical University in Kyiv: LMiH is now certified for continuing medical education credit and offered twice a year by this institution. Lessons learned from this experience provide a roadmap for rapidly increasing access to new knowledge and skills for healthcare workers by adapting existing online resources to local needs; they are used to facilitate rapid expansion of other continuing education offerings in Ukraine: additional online courses from the University of Washington (UW) are planned for adaptation

Efficient Traversability Analysis for Mobile Robots using the Kinect Sensor

Abstract — For autonomous robots, the ability to classify their local surroundings into traversable and non-traversable areas is crucial for navigation. In this paper, we address the problem of online traversability analysis for robots that are only equipped with a Kinect-style sensor. Our approach processes the depth data at 10 fps-25 fps on a standard notebook computer without using the GPU and allows for robustly identifying the areas in front of the sensor that are safe for navigation. The component presented here is one of the building blocks of the EU project ROVINA that aims at the exploration and digital preservation of hazardous archeological sites with mobile robots. Real world evaluations have been conducted in controlled lab environments, in an outdoor scene, as well as in a real, partially unexplored, and roughly 1700 year old Roman catacomb. I

Efficient traversability analysis for mobile robots using the Kinect sensor

For autonomous robots, the ability to classify their local surroundings into traversable and non-traversable areas is crucial for navigation. In this paper, we address the problem of online traversability analysis for robots that are only equipped with a Kinect-style sensor. Our approach processes the depth data at 10 fps-25 fps on a standard notebook computer without using the GPU and allows for robustly identifying the areas in front of the sensor that are safe for navigation. The component presented here is one of the building blocks of the EU project ROVINA that aims at the exploration and digital preservation of hazardous archeological sites with mobile robots. Real world evaluations have been conducted in controlled lab environments, in an outdoor scene, as well as in a real, partially unexplored, and roughly 1700 year old Roman catacomb. © 2013 IEEE

Possible Factors of Poplar Susceptibility to Large Poplar Borer Infestation

Poplars (Populus spp.) are of significant ecological and economic importance. Long-term breeding efforts were aimed mainly at obtaining fast-growing and productive plants and less considered resistance to pests. This study aimed to identify patterns of susceptibility or resistance to Saperda carcharias (Linnaeus, 1758) (Coleoptera: Cerambycidae) infestation among clones of Populus hybrids and pure species, focusing on the influence of their placement, seasonal development, stem diameter, height increment, and crossing combinations. Among 34 clones of poplar species and hybrids of Ukrainian and foreign selection, in 2019–2023 S. carcharias infested 14 clones every year. Six clones (‘Ivantiivska’, ‘Kytaiska × pyramidalna’, ‘Volosystoplidna’, ‘Novoberlinska-3’, ‘Robusta’, and ‘Lada’) were the most susceptible to the infestation by S. carcharias. The clones of all presented poplar sections and their crossing combinations, except the Tacamahaca and Leucoides cross, were infested. Greater height increment promoted the infestation by S. carcharias. Ambiguous results were obtained regarding the susceptibility of Populus hybrids compared to pure species to S. carcharias infestations. Considering infestation by S. carcharias and plant placement in the site, it can be concluded that the clones ‘Sakrau45-51’, ‘Deltopodibna’, ‘Rosijska’, ‘Slava Ukrayiny’, ‘Lubenska’, ‘Rohanska’, and ‘Nocturne’ are resistant to this pest. Selecting native species clones or creating mixed clone plantations could enhance the resilience of poplar plantations to pest threats

Геопросторове моделювання радононебезпечної території

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Eastern-European Journal of Enterprise Technologies, 10(96), 64-75. doi: 10.15587/1729-4061.2018.150273. Marija J. Norušis (2011). IBM SPSS Statistics 19 Guide to Data Analysis. Pearson Prentice Hall, 651. Balym, Y., Georgiyants, M., Vуsotska, O., Pecherska, A., Porvan, A. (2017). Mathematical modeling of the colorimetric parameters for remote control over the state of natural bioplato. Eastern-European Journal of Enterprise Technologies. 10(88), 29-36. doi: 10.15587/1729-4061.2017.108415.Methods for identification of potentially radon-prone areas using geospatial analysis in ArcGIS 10.6 software environment and mathematical modeling in SPSS 19.0 on the example of high background radiation area have been developed. High level of natural radioactivity associated with uranium content in environment objects and natural uranium occurrences, and also the spatial density of faults (reliable and unreliable) and lineaments were taken into account as well as the distance from uranium mine located nearby. The method of linear discriminant functions was used to make a math model for determining the level of radon hazard. To do this, data on all locations were divided into training and test samples. Determination of predictors of the mathematical model was performed using Fisher's criterion by their sequential inclusion in discriminant equations. Among the considered 13 factors of radon hazard, seven of them turned out to be informative. For them, canonical coefficients were calculated using the least squares method for first- and second- order polynomials. Based on the values of discriminant functions, a territorial map was constructed to assign the new location to a certain level of radon hazard. The maps obtained present the correlation of the radon-prone areas with the zones of high spatial density of faults and lineaments, and confirmed by the data of direct indoor radon measurements. In a limited number of measurements, the methods might get a good help in prioritization for round-the-country radon survey. As far as the model for identification of potentially radon-prone areas is mainly based on geological studies, the further research is supposed to be directed to its approbation for a different geological environment of the Ukrainian shield.Розроблено методику ідентифікації потенційно радононебезпечних територій з використанням геопросторового аналізу в програмному середовищі ArcGIS 10.6 та математичного моделювання в програмному середовищі SPSS 19.0 на прикладі території з високим рівнем природної радіоактивності. Основними параметрами для початкового етапу картування пропонується просторова щільність розломів та просторова щільність лінеаментів 3-4 порядків. Інші параметри додаються для більш детального аналізу, залежно від конкретної локації, що розглядається. Отримані карти показують позитивну кореляцію радононебезпечних ділянок із зонами високої просторової щільності розломів та лінеаментів та підтверджуються даними безпосередніх замірів радону в приміщеннях. За умови обмеженої кількості вимірювань, ця методика може бути корисною у визначенні пріоритетності для радонової зйомки по країні