Austrian Journal of Technical and Natural Sciences № 7–8 2020 July– August PREMIER Publishing Vienna 2020 Austrian Journal of Technical and Natural Sciences Scientific journal № 7–8 2020 (July– August) ISSN 2310-5607 Editor-in-chief Ogirko Igor Vasilievich, Ukraine, Doctor of Engineering Sciences Platov Sergey Iosifovich, Russia, Doctor of Engineering Sciences Rayiha Amenzade, Azerbaijan, Doctor of architecture Shakhova Irina Aleksandrovna, Uzbekistan, Doctor of Medicine Skopin Pavel Igorevich, Russia, Doctor of Medicine Suleymanov Suleyman Fayzullaevich, Uzbekistan, Ph.D. of Medicine Tegza Alexandra Alexeevna, Kazakhstan, Doctor of Veterinary Medicine Zamazy Andrey Anatolievich, Ukraine, Doctor of Veterinary Medicine Zhanadilov Shaizinda, Uzbekistan, Doctor of Medicine Hong Han, China, Doctor of Engineering Sciences International editorial board Andronov Vladimir Anatolyevitch, Ukraine, Doctor of Engineering Sciences Bestugin Alexander Roaldovich, Russia, Doctor of Engineering Sciences S.R.Boselin Prabhu, India, Doctor of Engineering Sciences Frolova Tatiana Vladimirovna, Ukraine, Doctor of Medicine Inoyatova Flora Ilyasovna, Uzbekistan, Doctor of Medicine Kambur Maria Dmitrievna, Ukraine, Doctor of Veterinary Medicine Kurdzeka Aliaksandr, Russia, Doctor of Veterinary Medicine Khentov Viktor Yakovlevich, Russia, Doctor of Chemistry Kushaliyev Kaisar Zhalitovich, Kazakhstan, Doctor of Veterinary Medicine Mambetullaeva Svetlana Mirzamuratovna, Uzbekistan, Doctor of Biological Sciences Manasaryan Grigoriy Genrihovich, Armenia, Doctor of Engineering Sciences Martirosyan Vilena Akopovna, Armenia, Doctor of Engineering Sciences Miryuk Olga Alexandrovna, Kazakhstan, Doctor of Engineering Sciences Nagiyev Polad Yusif, Azerbaijan, Ph.D. of Agricultural Sciences Nemikin Alexey Andreevich, Russia, Ph.D. of Agricultural Sciences Nenko Nataliya Ivanovna, Russia, Doctor of Agricultural Sciences Proofreading Kristin Theissen Cover design Andreas Vogel Stephan Friedman Additional design Editorial office Premier Publishing s.r.o. 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Printed by Premier Publishing s.r.o., Vienna, Austria on acid-free paper. SCREENING GARCINIA ZEYLANICA FOR IN-VITRO ANTIMICROBIAL ACTIVITY AND ANTI-OXIDANT ACTIVITY Section 1. Biology https://doi.org/10.29013/AJT-20-7.8-3-10 Wanigasekara Dharani Nirasha, B. Sc (Hons) in Microbiology, Graduate Research Assistant, Department of Biochemistry, Faculty of Medicine, University of Ruhuna, Sri Lanka E-mail: dharaninirasha@gmail.com Karunarathne Chandani, Chief Technical Officer, Gampaha Wickramarachchi Ayurveda Institute, University of Kelaniya, Sri Lanka E-mail: weuda9@gmail.com Dasanayaka Mudiyanselage Rasika Sanjeewani, Rasika Sanjeewani, MBA, Deputy Registrar, Gampaha Wickramarachchi Ayurveda Institute, University of Kelaniya, Sri Lanka E-mail: drgwai@kln.ac.lk Perera Ruwan Tharanga, B. Sc (Hons) in Chemistry, Graduate Research Assistant, Department of Chemistry, Faculty of Science, University of Kelaniya, Sri Lanka E-mail: 2017_perera@kln.ac.lk Weerakoon Tharindra, B. Sc (Hons) in Biochemistry, Graduate Research Assistant, Department of Chemistry, Faculty of Science, University of Kelaniya, Sri Lanka E-mail: tharindraweerakoon@yahoo.com Sudesh Hemal, Laboratory Technical Officer, Gampaha Wickramarachchi Ayurveda Institute, University of Kelaniya, Sri Lanka E-mail: sudeshvamp@gmail.com SCREENING GARCINIA ZEYLANICA FOR IN-VITRO ANTIMICROBIAL ACTIVITY AND ANTI-OXIDANT ACTIVITY Abstract. Garcinia zeylanica is an endemic plant of Sri Lanka which is extensively used as a culinary spice in native cuisine and used to treat wounds and gum diseases in indigenous medicine. This 3 Section 1. Biology study was conducted to assess the antimicrobial potency and the antioxidant activity of G. zeylanica. Methanolic extracts prepared from the dried fruit rind and leaves of G. zeylanica were tested for their antimicrobial effect against 5 bacterial species (Escherichia coli, Staphylococcus aureus, Methicillin resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa and Streptococcus pyogenes) and a yeast (Candida albicans) using agar well diffusion method. The methanolic extracts exhibited significant inhibition on the growth of the tested microorganisms. The overall results of antimicrobial assay provide promising primary information for the potential of using crude extract of the dried fruit rind of G. zeylanica in the treatment of infections caused by bacteria and fungi. Antioxidant activity of dried fruit rind of G. zeylanica, the edible part used as a spice was determined using FRAP assay and ABTS assay. The extract showed interesting antioxidant activity. Owing to the elevated levels of antioxidants, G. zeylanica fruit can be considered as a valuable spice. Hence, G. zeylanica is better candidate source to discover new antimicrobial drugs. Keywords: Garcinia zeylanica, antimicrobial effect, antioxidant activity. Introduction Infectious diseases account for one of the main challenges that modern world had to face these last few decades. Although the high proportion of effective antibiotics available, the emergence of antibiotic resistant pathogens has lowered the potency of existing antibiotics [1]. These problem lead to seek the alternative strategies to combat infectious diseases. Investigation of the efficacy of herbal extracts and formulations that have been used in folk medicinal systems could be a solution for the antibiotic resistance crisis. In Sri Lanka, many plants of Clusiaceae family are used as herbal medicines in indigenous medicine [2]. Among the plants of Clusiaceae family, plants of Garcinia genus, found in Africa and Asia have been reported to have antimicrobial properties [1; 3; 4]. Flavonoids and Xanthones were reported as the major phytochemicals responsible for the therapeutic potential associated with Garcinia species [5; 6; 7]. In Southeast Asian countries including Sri Lanka, sundried, smoked fruit rinds of Garcinia species such as Garcinia zeylanica (Ela goraka) and Garcinia quaesita (Rathu goraka) are extensively used as culinary spices [8]. G. zeylanica which is endemic to Sri Lanka [17] is distinguished from G. quaesita using its yellow rind of ripen fruit whereas the rind of G. quaesita is orange to red in color [2, 9]. In indigenous medicinal practices, 4 both G. zeylanica and G. quaesita rind extracts are used to treat gum disease, ulcers, chronic dyspepsia, asthma, diabetes mellitus and hyperlipidemia as well as to enhance digestibility [10]. Although the antibacterial activity of dried fruit rind extract of G. zeylanica was reported in our previous publication [3], antimicrobial potential of the crude leaf extract and the antioxidant activity of G. zeylanica fruit rind have not been documented to the best of our knowledge. This study therefore focuses on the antimicrobial potential of the leaf and dried fruit rind extract and the antioxidant activity of fruit rind of G. zeylanica. Apart from that, antioxidant capability of the G. zeylanica methanolic extract was analyzed considering as a valuable spice for cooking. Nowadays antioxidants have become an ongoing topic due to the anti-ageing properties of them. Most of the food categories contain medium to high level of antioxidants. These categories include berries and berry products, fruits and nuts, cereals, spices, herbs etc. Compared to animal based food products, plant based food products have generally higher antioxidant content. Among foods with plant origin, spices are well known source of antioxidants which can be included in human diet [25]. Hence, another intend was to comment on the significance of the usage of G. zeylanica as a spice by analyzing antioxidant capacity with appropriate protocols. SCREENING GARCINIA ZEYLANICA FOR IN-VITRO ANTIMICROBIAL ACTIVITY AND ANTI-OXIDANT ACTIVITY Experimental procedure Determination of the antimicrobial activity Preparation of the samples Sun-dried fruit rinds (50 g) and dried leaves (50 g) of G. zeylanica was extracted using Soxhlet extraction apparatus separately with methanol (200 mL) as the solvent. The solvent was evaporated using rotary evaporator (40 º C, 90 rpm). Extracts were stored at 40C until the assays carried out. Preparation of microbial cultures Esherichia coli (ATCC8739), Staphylococcus aureus (ATCC25922), Methicillin resistant Staphylococcus aureus, Streptococcus pyogenes (ATCC19615), Pseudomonas aeruginosa (ATCC27853) and clinically isolated Candida albicans were obtained from the Central Laboratory, Gampaha Wickramarachchi Ayurveda Institute, University of Kelaniya, Sri Lanka. One-day old cultures of all test organisms were prepared by adjusting the turbidity to McFarland 0.5 standard using normal saline as the diluent. Agar well diffusion method 100 µL of each prepared bacterial culture was pipetted out onto Mueller Hinton Agar (Oxoid, UK) plates separately and spread evenly using sterile cotton swabs to obtain a uniform lawn. Wells were cut on the inoculated agar plates using sterile cork borer (diameter-8 mm). Wells were loaded with dried fruit rind extract and leaf extract accordingly (50 µL each). Amoxicillin(10 mg/mL, 50 µL) was used as the positive control for MRSA, S. aureus, E.coli and S. pyogenes and Ciprofloxacin (10 mg/mL, 50 µL) was used so for P. aeruginosa while sterile distilled water (50 µL) was added as the negative control. Same procedure was carried out for C. albicans on Sabouraud Dextrose Agar. Fluconazole (2.5 mg/mL, 50 µL) was used as the positive control for C. albicans. Then the plates were incubated at 37 ºC for 24 hours. After incubation, the diameter of inhibition zones measured and recorded in millimeters. The experiment was performed in five replicates. Determination of antioxidants Preparation of test sample G. zeylanica sun-dried fruit rind Powder (1.0g) was taken and ethanol: water (7:3 v/v, 5ml) was added 1mL per time. Mixture was vortexed (40Hz, 1 min) each time. The contents were centrifuged and the extract was collected Ferric reducing antioxidant power assay (FRAP) This was conducted according to the procedure explained by Oyaizu, 1998 [18]. To prepare the FRAP reagent, acetate buffer (25.0 mL, 300 mM, pH 3.6) was mixed with freshly made Triphenyltetrazolium chloride (TPTZ) (2.5 mL, 10 mM) solution. Dilute hydrochloric acid (100mL, 40 mM) and freshly made FeCl3(2.5 mL, 20 mM) solutions were added to the mixture. Prepared extract (20.0 µl) was taken and FRAP reagent (280.0 µL) was added and shake for 10 seconds. Mixture was incubated at 37 °C for 4 minutes and absorbance was measured at 593nm using Multiscan Go spectrophotometer (Thermo scientific) against a reagent blank. (20.0 µl of distilled water + +280.0 µl of FRAP reagent). The assay was performed similarly for a concentration series of 20–80 µg /mL solution of Butylated hydroxyl toluene (BHT). The reducing power was calculated according to the following formula. Reducing power% = [(A1/A0)–1] × 100(A1 = Absorbance of reaction mixture with serum or BHT), A0 = Absorbance of the reaction mixture with the solvent system instead of serum or BHT) ABTS assay Free radical scavenging activity of plant samples was determined by ABTS radical cation decolorization assay. ABTS° + cation radical was produced by the reaction between ABTS (7mM) in water and K2S2O8 (2.45 mM) in 1:1 ratio. Mixture was stored in the dark place at room temperature for 12 hours. Mixture was then diluted with methanol to obtain an absorbance of 0.700 at 734 nm. After the addition of the extract (2.5 µL) and ABTS solution 5 Section 1. Biology (247.5 µL) absorbance was measured after 30 min of mixing at 734 nm. Percentage inhibition of absorbance at 734nm was calculated using the formula, ABTS + Scavenging effect (%) = ((AB-AA)/ AB) × 100, where AB is absorbance of ABTS radi- cal + methanol; AA is absorbance of ABTS radical + sample/ standard. Trolox was used as standard substance. Results and discussion Table 1. – Inhibition zone diameters exhibited by G. zeylanica leaf extract, G. zeylanica dried fruit rind extract and standard antibiotics Inhibition zone diam- Inhibition zone diameter (mm) Inhibition zone diameter eter (mm) of leaf extract of dried fruit rind extract (mm) of antibiotic MRSA 19.000 (± 1.000) 28.800 (± 0.837) 11.200 (± 0.447) P. aeruginosa 15.800 (± 0.447) 24.000 (± 0.000) 38.800 (± 1.095) MSSA 17.600 (± 0.548) 29.200 (± 1.095) 39.200 (± 1.095) S. pyogenes 18.600 (± 0.548) 31.200 (± 0.837) 37.400 (± 0.548) E.coli 8739 14.200 (± 0.447) 20.800 (± 1.095) 29.600 (± 0.548) C. albicans 0.000 18.200 (± 0.447) 25.000 (± 0.000) Organism Table 2. – Inhibition zone diameters exhibited by G. zeylanica leaf extract, G. zeylanica dried fruit rind extract and standard antibiotics, Data is expressed as Mean ± Standard Deviation in the same column with different alphabet is significantly different (p < 0.05) While Mean ± Standard Deviation in the same column with the same alphabet is not significantly different. (According to the Tukey’ test) Organism MRSA P. aeruginosa MSSA S. pyogenes E.coli 8739 C. albicans Inhibition zone diam19.000(±1.000)b 15.800(0.447)c 17.600(0.548)c 18.600(0.548)c 14.200(0.447)c 0.000(0.000)c eter (mm) of leaf extract Inhibition zone diameter (mm) 28.800(0.837)a 24.000(0.000)b 29.200(1.095)b 31.200(0.837)b 20.800(1.095)b 18.200(0.447)b of dried fruit rind extract Inhibition zone diam11.200(0.447)c 38.800(1.095)a 39.200(1.095)a 37.400(0.548)a 29.600(0.548)a 25.000(0.000)a eter (mm) of antibiotic Table 1 describes the antibacterial activities of the G. zeylanica leaf extract, G. zeylanica dried fruit rind extract and standard antibiotics against selected pathogenic bacteria species. According to that significant antibacterial capabilities were shown by antibiotic against all selected species except the MRSA. Dried fruit rind extract of G. zeylanica shows consid6 erable activity against the MRSA. Statistical evaluations depict that there is a significant different among inhibition zone’s diameters of G. zeylanica leaf extract, G. zeylanica dried fruit rind extract and standard antibiotic against selected bacteria species (Table 2). Methanolic extracts of both G. zeylanica dried fruit rind and leaves showed significant inhibitory SCREENING GARCINIA ZEYLANICA FOR IN-VITRO ANTIMICROBIAL ACTIVITY AND ANTI-OXIDANT ACTIVITY effects on the growth of Methicillin Resistant Staphylococcus aureus (MRSA) compared to the standard antibiotic (Table 1). All test organisms except C. albicans were susceptible to leaf extract whereas all tested microorganisms were inhibited by G. zeylanica dried fruit rind extract. Further investigation of responsible metabolite groups present in the plant extracts could eventually explain the inhibition potential of the methanolic extract of the G. zeylanica towards the test organisms. The reported antimicrobial activity could also be used to explain the use of this plant in folk remedies for ulcers and wounds. Figure 1. The inhibition exhibited by G. zeylanica dried fruit rind extract Figure 2. The inhibition exhibited by G. zeylanica leaf extract Number of studies have reported the antimicrobial efficacy of the crude extracts of genus Garcinia as well their respective antimicrobial components. Mackeen et al, [11] stated the antibacterial and antifungal effects of crude methanolic extracts of different parts of Garcinia atroviridis. Considerable antifungal effect of G. atroviridis against Cladosporium herbarum was notably observed with the fruit and the leaf extracts [11]. The respective antimicrobial components of this genus were found to be 7 Section 1. Biology xanthones such as cowaxanthones present in Garcinia cowa [12], parvifolixanthones isolated from Garcinia parvifolia [13], dulcisxanthones obtained from Garcinia dulcis [14], tetraprenylated xanthones, known as scortechinones present in Garcinia scortechinii [15] and phloroglucinols present in G. parvifolia [13]. In addition, α-mangostin, found in the stem bark of Garcinia mangostana was effective against methicillin resistant Staphylococcus aureus and vancomycin resistant enterococci [16]. The antimicrobial potency of crude methanolic extracts of G. zeylanica corroborate with their findings. Table 3. – Results obtained for the antioxidant assays of G. zeylanica fruit rind (mmol/g) FRAP assay 201.0 ± 0.03% ABTS 198.2 ± 0.45% Antioxidant activity is characterized as a compound’s ability to inhibit oxidative degradation, for example lipid peroxidation. The Ferric reducing power assay (FRAP) is a good indicator of potential antioxidant activity. It is based on electron transfer process rather than hydrogen atom transfer. The reducing properties are generally associated with the presence of different reductants [19]. The antioxidant action of reductant is mainly dependent on the breaking of the free radical chain by donating a hydrogen atom [20]. According to the FRAP assay G. zeylanica extract showed antioxidant capacity of 201.0 (± 0.03)% while Butylated hydroxyl toluene (BHT) was used as the standard. When considering the ferric reducing capacity of the rind of the G. zeylanica fruit, it depicts to have a considerable capacity compared to other plant extracts [21]. Reducing capability and using the properties of electron donors to neutralize free radicals through the creation of stable materials. The effect of the reduction is to stop the radical chain reactions, which otherwise could be very damaging [22]. ABTS assay is technically simple and has been widely used for screening and routine determina8 tions. ABTS•+ is soluble in both water and organic solvents, which enables the antioxidant capacity of both hydrophilic and lipophilic compounds to be determined with the same basic methodology. Radical scavenging capacities were determined using ABTS. According to the ABTS assay G. zeylanica dried fruit rind showed 198.2(± 0.45)% antioxidant where Trolox was used as the standard substance. If an antioxidant is applied to the radicals, the presence of antioxidants induces a degree of depolarization, which reverses the formation of radical [23]. Free radicals are produced by the cells in the human body as waste substances and if they are unable to mitigate from the body, oxidative stress will be generated and reactive oxygen species can harm to the cells and body function augmenting the cancer cell production risk. According to the results, G. zeylanica possess a significant amount of antioxidant content. The obtained antioxidant capacity values can be compared with well-known antioxidant rich medicinal herbal remedies. For instance, Triphala, Amalaki (Phylanthus emblica) and Arjuna (Terminalia arjuna) used in Ayurveda and Goshuyu-tou (Tetradium ruticarpum), used as a medicinal herb in traditional Kampo medicine in Japan are well known antioxidant rich medicinal plants which have antioxidant values of 132.6 to 706.3 mmol/100 g [24], whereas G. zeylanica contains 201.0 mmol/g which can be considered as a significant antioxidant. Hence, G. zeylanica can be recognized as a culinary spice which contains elevated levels of antioxidants. Conclusions Antimicrobial potential of G. zeylanica against antibiotic resistant bacteria can be considered as a promising perspective of new antimicrobial drug discovery using plant sources. Apart from that, dried rind of fruit of G. zeylanica contains exalted amount of antioxidants proving as a healthful spice. Further, it should be focused on the bioactive phytochemical constituents of G. zeylanica fruit for medicinal applications. SCREENING GARCINIA ZEYLANICA FOR IN-VITRO ANTIMICROBIAL ACTIVITY AND ANTI-OXIDANT ACTIVITY References: 1. Kuete V., Komguem J., Beng V. P., Meli A. L., Tangmouo J. G., Etoa F. X. and Lontsi D. Antimicrobial components of the methanolic extract from the stem bark of Garcinia smeathmannii Oliver (Clusiaceae). South African Journal of Botany, 73(3). 2007. – P. 347–354. 2. Hewageegana A. U., Hewageegana H. G. S. P. and Arawwawala L. D. A. M. Comparison on phytochemical and physicochemical parameters of Garcinia cambogia (Gaertn.) Desr. and Garcinia zeylanica Linn fruit rinds. Journal of Pharmacognosy and Phytochemistry, 7(2). 2018. – P. 2532–2535. 3. Sudesh A. D.H., Wanigasekara D. N. and Karunarathne E. D. C. Antimicrobial activity of dried fruit rind extract of Garcinia zeylanica. 4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, – Sri Lanka. 2019. – 50 p. 4. Gunasekara T. D. C. P., Radhika N. D. M., Ragunathan K. K., Gunathilaka D. P. P., Weerasekera M. M., Hewageegana H. G. S. P., Arawwawala L. A. D. M. and Fernando S. S. N. Determination of antimicrobial potential of five herbs used in ayurveda practices against Candida albicans, Candida parapsilosis and methicillin resistant Staphylococcus aureus. Ancient science of life, 36(4). 2017. – 187 p. 5. Minami H., Takahashi E., Kodama M. and Fukuyama Y. Three xanthones from Garcinia subelliptica. Phytochemistry, 41(2). 1996. – P. 629–633. 6. Waterman P. G. and Hussain R. A. Major xanthones from Garcinia quadrifaria and Garcinia staudtii stem barks. Phytochemistry, 21(8). 1982. – P. 2099–2101. 7. Iwu M. M., Igboko A. O., Okunji C. O., Tempesta S. M. 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Journal of Ethnopharmacology, 72(3). 2000. – P. 395–402. 12. Panthong K., Pongcharoen W., Phongpaichit S. and Taylor W. C. Tetraoxygenated xanthones from the fruits of Garcinia cowa. Phytochemistry, 67(10). 2006. – P. 999–1004. 13. Rukachaisirikul V., Naklue W., Phongpaichit S., Towatana N. H. and Maneenoon K. Phloroglucinols, depsidones and xanthones from the twigs of Garcinia parvifolia. Tetrahedron, 62(36). 2006.– P. 8578–8585. 14. Deachathai S., Mahabusarakam W., Phongpaichit S., Taylor W. C., Zhang Y. J. and Yang C. R. Phenolic compounds from the flowers of Garcinia dulcis. Phytochemistry, 67(5). 2006. – P. 464–469. 15. Rukachaisirikul V., Kaewnok W., Koysomboon S., Phongpaichit S. and Taylor W. C. Caged-tetraprenylated xanthones from Garcinia scortechinii. Tetrahedron, 56(43). 2000. – P. 8539–8543. 16. Sakagami Y., Iinuma M., Piyasena K. G. N. P. and Dharmaratne H. R. W. Antibacterial activity of α-mangostin against vancomycin resistant Enterococci (VRE) and synergism with antibiotics. Phytomedicine, 12(3). 2005. – P. 203–208. 9 Section 1. Biology 17. Nimanthika W. J. and Kaththriarachchi H. S. Systematics of genus Garcinia L. (Clusiaceae) in Sri Lanka: new insights from vegetative morphology. Journal of the National Science Foundation of – Sri Lanka, 38(1). 2010. 18. Oyaizu M. Studies on products of browning reaction. The Japanese journal of nutrition and dietetics, 44(6). 1986. – P. 307–315. 19. Duh P. D., Tu Y. Y. and Yen G. C. Antioxidant activity of water extract of Harng Jyur (Chrysanthemum morifolium Ramat). LWT-Food Science and Technology, 32(5). 1999. – P. 269–277. 20. Mahapatra S. K., Chakraborty S. P. and Roy S. Aqueous extract of Ocimum gratissimum Linn and ascorbic acid ameliorate nicotine–induced cellular damage in murine peritoneal macrophage. Asian Pacific Journal of Tropical Medicine, 3(10). 2010. – P. 775–782. 21. Dudonne S., Vitrac X., Coutiere P., Woillez M. and Mérillon J. M. Comparative study of antioxidant properties and total phenolic content of 30 plant extracts of industrial interest using DPPH, ABTS, FRAP, SOD, and ORAC assays. Journal of agricultural and food chemistry, 57(5). 2009. – P. 1768–1774. 22. Gülçin I., Mshvildadze V., Gepdiremen A. and Elias R. Screening of antiradical and antioxidant activity of monodesmosides and crude extract from Leontice smirnowii tuber. Phytomedicine, 13(5). 2006.– P. 343–351. 23. Halliwell B., Aeschbach R. Loliger J. and Aruoma O. I. The characterization of antioxidants. Food Chem. Toxicol. 33. 1995. – P. 601–617. 24. Wood J., Rogina B., Lavu S., Howitz K. Sirtuin activatorsmimic calories restriction and delay ageing in metazoans. Nature, 430. 2004. – P. 686–689. 25. Monica H., Bnete L. The total antioxidant content of more than 3100 foods, beverages, spices, herbs and supplements use worldwide. 2010. 10 EVOLUTION OF REFACTORING Section 2. Information technology https://doi.org/10.29013/AJT-20-7.8-11-16 Struzik Vladislav, Software engineer, Persha Ukrayinska Lizynhova Kompaniya Ltd., Kyiv, Ukraine E-mail: struzik.vladislav@gmail.com Hrybkov Serhii, PhD, Associate Professor, Department of Information Systems, National University of Food Technologies, Kyiv, Ukraine E-mail: sergio_nuft@i.ua Chobanu Valeriia, Student, Faculty of Automation and Computer Systems, National University of Food Technologies, Kyiv, Ukraine E-mail: sundhoff15@gmail.com EVOLUTION OF REFACTORING Abstract. The stages of development of refactoring are described and analyzed in the paper, as well as its impact on the process of development software. The authors proposed the mathematical represent of the refactoring process. The probable evolution of refactoring was predicted after the analysis – next step is the appearance of network refactoring, which will include operations for introducing changes in the topology of the computer network. Keywords: code refactoring, database refactoring, access refactoring, network refactoring, refactoring formalization, software. Introduction Today, information systems are closely connected with many areas of human activity. The rapid development of the modern world means that it is very important to choose an approach to the development of information systems that will make it possible to implement changes as quickly and easily as possible in accordance with new business requirements. Due to the constant introduction of changes to bring the software in accordance with business requirements, there are problems with the support of the software code. Such problems are called technical debt. In order to reduce the technical debt and improve the operational process, developers resort to one of the techniques of extreme programming methodology – refactoring. The main idea of refactoring is to bring the design of the program in a more understandable and adaptive way by mass of small changes in the code. In most cases, the refactoring process itself is iterative. Each iteration should make minimal and integral changes in the software. 11 Section 2. Information technology It is important to understand that refactoring does not involve the addition of new functionality, but only the reorganization of the existing one. In other words, after refactoring the behavioral semantics of the code should remain the same. The use of refactoring makes it easier to understand the code. During refactoring, the programmer can better understand how the information system works and change the code so that it better corresponds to its purpose. It should be noted that in some cases refactoring may not be appropriate. Refactoring should be performed only when the code is mostly stable [1, 49]. Refactoring Development Timeline The initial stage in the development and popularization of refactoring was Robert S. Arnold’s Software restructuring article [2], which was published in 1986, where the author describes the advantages and disadvantages, as well as the possibilities of software restructuring technology. In general, the author describes the restructuring process as a gradual introduction of changes in software in order to manage the complexity that is constantly increasing. Later on, this approach to restructuring was called refactoring. The term “refactoring” was first mentioned in scientific literature in 1990 by William F. Opdyke and Ralph E. Johnson “Refactoring: an aid in designing application frameworks and evolving object-oriented systems” [3]. In 1991, William G. Griswold discussed functional and procedural program restructuring in his PhD thesis “Program Restructuring as an Aid of Software Maintenance” [4]. In 1992, William F. Opdyke reviewed the restructuring of functional and procedural programs in his Ph.D. thesis on “Refactoring object-oriented frameworks” [5], in which he described restructuring operations of software that support the design, development, and reuse of object-oriented frameworks and named such operations refactoring. William F. Opdyke defines refactoring as a way to 12 preserve the behavior when matching a set of invariants. The fundamental work that described refactoring in detail was Martin Fowler’s Refactoring: Improving the Design of Existing Code [1], published in 1999 with the participation of Kent Beck, John Brant, William Opdyke, Don Roberts. In his work, the author describes refactoring as a way to systematically clean up the code with a minimum chance of new errors. According to Martin Fowler, refactoring should be used for several purposes: • refactoring improves software composition; • refactoring makes the software easier to understand; • refactoring helps to find errors; • refactoring allows writing programs faster. Before refactoring, it is necessary to check whether changes are really necessary and whether they are worth the effort. Martin Fowler, in collaboration with Kent Beck, has created a catalogue of recommendations describing exactly when refactoring is appropriate. This catalogue is named Сode Smell. In [1, 75–235], the author divided refactoring methods into six main categories: composing methods, moving features between objects, organizing data, simplifying conditional expressions, simplifying method calls, and dealing with generalizations. The article [1, 47–48] includes the use of refactoring in databases, but no detailed description was made. In 2002, Scott J. Ambler, in his Refactoring for Fitness [6] first mentioned refactoring data. Further, Scott J. Ambler calls refactoring, described by Martin Fowler, as code refactoring, and data refactoring gets a new name – database refactoring [7]. In 2006, Scott J. Ambler in collaboration with Pramod J. Sadalage published work: Database refactoring: evolutionary design [8]. According to this work, database refactoring appears to be structural or functional changes in the database schema in order to improve its structure, preserving the semantics without changing its functionality. EVOLUTION OF REFACTORING The authors [8, 25] noted that one should not hope that during the first design of the database schema it is possible to take into account everything and will not make any further changes. It is worth paying attention to the fact that when performing structural refactoring on the database schema, there is also a need to change any external applications, working in conjunction with the database. The more architectural relationships in a system, the more complex operations will be performed during refactoring and the more likely it is that changes in one part will cause changes in the other. The complexity of database refactoring is directly proportional to the number of architectural relationships. Similarly to Code Smell by Martin Fowler and Kent Beck, Scott J. Ambler introduces the concept of Database Schema Smells – a catalogue that includes the main signs of the need for database refactoring. Overall, Scott J. Ambler and Pramod J. Sadalage proposed six categories of database refactoring [8, 97–299]: Structural; Data quality; Referential integrity; Architectural; Method; Non-refactoring transformations. In 2020 refactoring received a new development phase. In his work [9] Vladislav Struzik first proposed the category of access refactoring. Later, Vladislav Struzik together with the authors described in detail the access refactoring category in his work [10]. The access refactoring category was proposed as one of the database refactoring categories and is aimed at making changes in the access restriction part when administering the database management system. The need to create the access refactoring category has arisen in the analysis of transitions between the monolithic and microservice templates of the architecture, allocation of a bottleneck in a separate database, restriction of access to data, and so on. In a separate case of using access refactoring operations, the author [9] specifies events related to the enterprise security policy, such as rotation of passwords, compromising passwords, increasing or decreasing authentication requirements. The category of access refactoring includes seven operations: changing authentication attributes; narrowing the visibility of database objects; expanding the visibility of database objects; narrowing access privileges; extending access privileges; highlighting the database schema; merging database schemas. Refactoring formalization It is important to note that refactoring should be done in small steps – each operation is performed separately. Thus, in the case of any error, it will be easier to find the cause of the violation in the work, because it is likely to be associated with the part of the code or database schema, which was changed last. At present, refactoring has not been defined from a mathematical point of view. However, based on the analysis, the authors of this work have determined that for specialists in industries other than information technology, it is difficult to understand how changes are made to the code and database schema during refactoring. Therefore, the authors of this work proposed a mathematical representation of refactoring. Information system Sv at any stage of the life cycle will be presented as a tuple of set characteristics: (1) Sv pm ,db (t ,tr ,r , w , sp ,�d , per ) ,� f , where pm is a set of software modules; db is a database that consists of a set of tables t , a set of triggers tr , a set of relations between tables r , a view set w , a set of stored procedures and functions sp , data stored in the database d , a set of users and permissions per ; f – is a set of system functions; v – is the system version. The formalized full refactoring process, which includes code refactoring and database refactoring, shall be presented as follows: refactoring (2) → Svn … , where Svn ⊃ is a system after refactoring with vn version number. The refactoring process is shown in Figure 1. Sv … 13 Section 2. Information technology Figure 1. Full refactoring process Considering that code refactoring is to change the program code without changing its semantic meaning in order to improve the reading and understanding of the code by the software developer, let’s present it this way: code � refactoring Sv … → Svn … , , (3) where Svn pm ′,db (t ,tr ,r , w , sp,�d , per ) ,� f is the system after code refactoring; pm' – is a set of program modules that were changed during code refactoring; а; db – is a database that consists of a set of tables t , of triggers set tr , set of relations between tables r , selection set w , set of stored procedures and functions sp , data stored in the database d , set of users and access permissions; f – is a set of system functions which cannot be changed in any way, since this contradicts the definition of refactoring;; v – is the initial system version; vn – is the system version, which reflects the changes made after the refactoring.. In its turn, database refactoring is a change in the database schema to improve its design, which does not lead to changes in the behavioral and informational semantics of the database. Let us present the refactoring of the database as follows: database � refactoring � Sv … → Svn … , (4) where Svn pm ,db ' (t ′,tr ′,r ′, w ′, sp′,�d , per ′ ) ,� f is the system after database refactoring; pm – is a set of program modules without changes; 14 db ' – is the database after the refactoring, where the data d is in no way changed, but one or more of its elements is changed: a set of tables t ' , if there was no change in the tables, then t ' = t ; a set of triggers tr ' , if there was no change in the triggers, then tr ' = tr ; a set of relations between tables r ' , if there was no change in the relations, then r ' = r ; a views set w ' , if there was no change in the views, then w ' = w ; a set of stored procedures and functions sp' , if there was no change in the stored procedures and functions, then sp ' = sp , a set of users and permissions per ' , if there was no changes in users and permissions, then per ' = per ; f – is a set of system functions that remained the same; v – is the initial version of the system; vn – is the version of the system that reflects the changes after refactoring. With this view, it is possible to understand the refactoring process without using an example that an interested person may not understand due to lack of knowledge in the field of information technology Network Refactoring Emergence Consider the scheme (Fig. 2), which shows the coverage of the application by refactoring operations. It should be noted that within a software application, code refactoring is used, within a database – database refactoring, and within the AAA (Authentication, Authorization, Accounting) DBMS service – access refactoring, but at the same time, for the part that concerns the computer network, there is no refactoring operation. EVOLUTION OF REFACTORING Figure 2. Coverage of an application by refactoring Based on this, we can conclude that the further development of refactoring as a method of acceptance in software development will occur network refactoring, which will gather the operations to introduce changes in the computer network topology of the software product. The mass use of cloud technologies, as well as virtualization and containerization technologies will contribute to the early appearance of network refactoring. Conclusion In conclusion, it should be noted that the analysis of refactoring development revealed the specifics of each stage. Also, it should be noted that the next stage of refactoring development is likely to be the appearance of network refactoring. Identification of gaps in application coverage by refactoring provides direction for improving tools of developers and software development in general. Besides, the process of refactoring is formalized by the authors of this work. The formal system, in its turn, allows evaluating the components of a software product involved in refactoring, which helps to determine the boundaries of refactoring, its complexity and resource intensity. References: 1. Fowler Martin. Refactoring: Improving the Design of Existing Code, With Kent Beck, John Brant, William Opdyke, and Don Roberts. 1999. – Addison-Wesley – ISBN0-201-48567-2. 2. Arnold R. S. “Software restructuring,” in Proceedings of the IEEE, – Vol. 77. – No. 4. – April, 1989. – P. 607– 617. Doi: 10.1109/5.24146. 3. Opdyke W., Johnson R. Refactoring: an aid in designing application frameworks and evolving objectoriented systems. 1990. URL: https://www.semanticscholar.org/paper/Refactoring%3A-an-aid-indesigning-application-and-Opdyke-Johnson/547fcfb419745f70bc927182717c598eba55706b 4. William G. Griswold. Thesis Ph. D. Program Restructuring as an Aid to Software Maintenance. 1991. – University of Washington. 5. William F. Opdyke. Thesis Ph. D. Refactoring Object-Oriented Frameworks. 1992. – University of Illinois at Urbana-Champaign. 15 Section 2. Information technology 6. Scott Ambler. Refactoring for Fitness. 2002. URL: https://www.drdobbs.com/refactoring-forfitness/184414821?cid=Ambysoft 7. Scott Ambler. The Process of Database Refactoring: Strategies for Improving Database Quality. URL: http://www.agiledata.org/essays/databaseRefactoring.html 8. Scott W. Ambler, Pramodkumar J. Sadalage. Refactoring Databases: Evolutionary Database Design. 2006. – Addison Wesley Professional. ISBN0-321-29353-3. 9. Vladislav Struzik. Access Refactorings Category. – International Scientific Young Scientists Conference. “Computer Sciences, Information Technologies And Management Systems”.– Ivano-Frankivsk, 2019. – P. 20–21. 10. Struzik V., Hrybkov S., Chobanu V. Access Refactoring Category. – Scientific works of the National University of Food Technologies. 2020. – P. 31–49. 16 CONSTRUCTION OF INFINITE ALGEBRAIC K- THEORY OF P I Section 3. Mathematics https://doi.org/10.29013/AJT-20-7.8-17-19 Dergachev Victor Mikhaylovich, associate professor, candidate physical. mat. sciences. Moscow polytechnical university Lelyavin Sergey Nikitovich, associate professor, candidate physical. mat. Sciences The Moscow state technical university of N. E. Bauman E-mail: lelyavin.s@yandex.ru CONSTRUCTION OF INFINITE ALGEBRAIC K- THEORY OF P I Abstract. The geometric realization of stable simplistic complexes is considered, and the theorem that the simplistic complex is weakly homotopically trivial is proved. Keywords: simplex, attachment, proobraz, homotopia, module, semi-disc. Theorem 1. There is a simplistic attachment:  such that W : Vk ,n ( A ) ⊗ γ 3 → Vk ,n +k ( A ) , l � ɶ ⋅ g 3 (bi ) = bɵ� 1 , W � ɶ ⋅ g 3 σ Vl = σ V Wɶ ⋅ g 3 (b0 ) = bɵ 0 ,� W ( ) [1,7–10]. Theorem 2. The simplistic complex V ( A ) is weakWɶ b0 ⊗ γ 3 = Wɶ (1) bɶ0 = bɵ 0 ,Wɶ bi ⊗ γ 3 = Wɶ (1) bɶi = b , = ly homotopically trivial: π i V( A ) ==0,0i,i== ,0,1, 2,.. Wɶ 1 bɶi = bɵ i ,i = 1,...,ll , [3, 17–20], (prove that the complex V k ( A ) is tightened for any). Where W (1) denotes a path consisting of a ( ( ) ) ( ) ( ) (( )) ( ) composition of three one-dimensional simplexes W 1 ⋅W 2 ⋅W 3 : 0   1k 1k 0   1k 1k 0   1k 1k     0   −1k 1k 0   0 1k 0 ,  0 1k  0 0 1  0 0 1n −k   0 0 1n −k  n −k    where 1k denotes a unit matrix of dimension k, and this path begins from top b0 , and action of a matrix product W 1 ⋅W 2 ⋅W 3 = W (1) on top b0 , is under- stood as action of this work on the following vector from modules: {e1 ,...,e k } ⊕ {u1 ,...,uk } ⊕ {e k +1 ,...,e n } = e n } = A n +k , where e1 ,...,e k – basis of the module P0 ,� �e k +1 ,...,e n – basis of the module Q0 ,� u � 1 ,...,uk – basis of the free module A k ,W ⋅ g 0 (b0 ) =  ek ,  0 �  ⋅ g 0 (bi ) = bi , ( 0 ) = b0 ,W i� = 1,...,� l , W �  ⋅ g 0 σ Vl = σVl , ( ) Proof We stabilize the complex by the second com�V �  k ,n ( A ) pound [2, 20–22], i. e. consider V k ( A ) = lim   n and by virtue of theorem 1. There is a simplistic attachment: W : Vk ,n ( A ) ⊗ γ 3 → Vk ,n +k ( A ) . Above each complex Vk ,n ( A ) is constructed a simplistic cone (due to homotopia W ) in the complex Vk ,n +k ( A ) , i.e. any finite sub-complex Vk ,n ( A ) is tightened in the complex V k ( A ) = lim �V �  k ,n ( A ) ,   ( ) , then π i V k ( A ) = 0,i = 0,1, 2,..., n The theorem is proven. Definition 1. Let be σ n = (a 0 ,a1 ,...,an ) a dimen  ,� sional ⋅ geometric simplex where a 0 ,a1 ,...,an its vertices. Through the designation St (σ n ) of the “cup” of the 17 Section 3. Mathematics simplex σ n , which is obtained from the simplex σ n by ejecting one of its (n − 1)– dimensional faces σ n −1 and its interior σ 0n ⊂ σ n , i.e. St (σ n ) = σ n \ (σ 0n σ n −1 ) . the “Simplistic thickening” of the cup St (σ n ), we will denote as St (σ 1n ) , it will have the form: St (σ 1n ) =  (σ in × D +n −k ), where σ in –any n – the dii ,k mensional subsimplex of the “cup” St (σ n )and D +n −k is (n − k ) – the dimensional open half-disc. Definition 2. Let σ n = St (σ 1n ) = σ 1n – “thickening” σ n ,� � � � j : σ 1n → σ n – the mapping of the tightening “simplistic thickening” σ 1n into a simplex, σ n , i. e. resulting by pulling on itself all half-faces D +n −k , of all faces σ k ⊂ St (σ 1k ) . Let the B -simplium complex, then f denotes a mapping that matches each n – dimensional geometric simplex σ n , n – dimensional simplex in the complex B. The composition of the mappings f and j denote via f , i.e. f = fɶ  j . It sets the mapping f : σ in → B , matching the “thickening” n – dimensional geometric simplex n – dimensional simplex σ Bn in the complex B. One variant of defining a covering homotopia to map the simplistic sets is the following statement. Statement Let p : E → B the mapping of the simplistic sets be such that for any simplex σ n and g 0 : St (σ 1n ) → E the mapping of the “thickening” of the cup St (σ 1n ) to the simplistic set E, wherein p  g 0 = f |St σ , f |St σ the constraint of mapping ( ) ( ) n f to a subset St (σ 1 ) , exists such mapping g from σ 1n to E : g : σ 1n → E , that p  g 0 = f , then for mapping p there is an exact sequence of the pair: n 1 n 1 Proof Let p  g 0 = f |St (σ ) , you continue displaying, g 0 , where g 0 : σ 1n → E , until displaying g : σ 1n → E , such that p  g 0 = f . Limit the display g 0 to the cup, i. e. put g 0 |St σ = h0 . ( ) If we continue h0 to such a display h : σ n → E , that p  h = f |σ , the remark will be proven, as then g 0 automatically glues with h and gives the required display g . Consider a direct product σ n −1 × I , I = [0,1] and a mapping Φ : σ n −1 × I → σ n , which on σ n −1 × {0} is identical, i. e. Φ = Id : σ n −1 × {0} → σ n , and σ n −1 × {1} maps to cup St (σ n ) . At that, display Φ is mutually unambiguous everywhere on σ n −1 × I except for set Γ × I ⊂ σ n −1 × I , where Γ – limit of simplex σ n −1 . On a set Γ × I we define Φ as follows: if and Then Φ ( x ,t ) = x . ( x ,t ) ∈ Γ × I n n −1 n f  Φ : σ × I → σ B , the mapping where σ B the simplex in the complex B, is the homotopia of the mapping f 1 to the mapping f 2 where f 1 = f  Φ |σ ×{0} : σ n −1 × {0} → σ Bn −1 , σ Bn −1 is the boundary σ Bn ,� � � f 2 = f  Φ |σ ×{1} : σ n −1 × {1} → σ Bn −1 . This homotopia we need to raise in E, i.e. construct the mapping R : σ n −1 × I → E such that p  R = f  Φ. The mapping f  Φ is partly already raised: 1) Display f  Φ on set σ n −1 × {1} equals display n 1 n n n −1 n −1 R1 = h0  Φ. 2) There is already a display Γ on the edge σ n −1 of the face g 0 |Γ = h 0. Let ‘s define the mapping R1 on a set Γ × I : if ... → π i ( F ) → π i ( E ) → π i ( E , F ) → π i −1 ( F ) → π i −1 E ( x ,t ) ∈ Γ × I , then R1 ( x ,t ) = g 0 . The condition p  R = f  Φ to display R1 is met π i −1 ( F ) → π i −1 ( E ) → ..., where F is the simplistic subset in because for ( x ,t ) ∈ Γ × I we have p  R1 ( x ,t ) = p  g 0 = E being the pattern of the marked point from E.  1 , = pof g 0 = f ( x ) , and in force Φ ( x ,t ) = x : f  Φ ( x ,t ) = f ( x ) . Remark Let p : F × B → B – the presentation In addition, the display R1 is consistent on a set the product of simplistic complexes: F and B in B, n −1 this case the conditions of statement are obviously of Γ × I σ × {1} =Γ × {1}. Consider continuing the display R1 : Γ × I → E , fulfilled, i. e. in the direct product of complexes before the display R : σ n −1 × I → E , so that “glass” is always filled. 18 , CONSTRUCTION OF INFINITE ALGEBRAIC K- THEORY OF P I p  R = f  Φ and on the set Γ × I R |Γ×I = R1 . we have Let ‘s build the following mapping h : σ → E , for any point y ∈ σ n , y ∉ Γ there is a single section n belonging to σ n −1 × I relative to display Φ, i. e. Φ ( x ,t ) = y . Let h ( y ) = R ( y ,t ) , if y ∈ Γ, that h ( y ) = h0 ( y ) , as prove a statement. References: 1. Dergachev V., Lelyavin S. Creation of stable simplicial complexes of the p. II Austrian Journal of Technical and Natural Sciences, Vienna. – No. 7–8. ( July – August), 2019. – P. 7–10. 2. Dergachev V., Lelyavin S. Creation of stable simplicial complexes of the p. I Austrian Journal of Technical and Natural Sciences, Vienna. – No. 7–8. ( July – August). 2018. – P. 20–22. 3. Dergachev V., Lelyavin S. Creation of the infinite algebraic K – functors of the p. II. Austrian Journal of Technical and Natural Sciences, Vienna. – No. 3–4. (March – April), 2018. – Р. 17–20. 19 Section 4. Medical science Section 4. Medical science https://doi.org/10.29013/AJT-20-7.8-20-25 Venger Andrii, PhD (biology), associate professor Odessa national medical university E-mail: venger87@ukr.net Venger Olga, PhD (biology), junior scientific researcher Plant breeding and genetics Institute – National center of seed and cultivar investigation Lapkin Andrii, student, Odessa national medical university Novozhen Oksana, PhD (medicine), lecturer, The state institution South Ukrainian National Pedagogical University named after K. D. Ushynsky Glushchenko Viktoriia, PhD (medicine), lecturer, The state institution South Ukrainian National Pedagogical University named after K. D. Ushynsky Kucherenko Mykola, PhD (medicine), lecturer, The state institution South Ukrainian National Pedagogical University named after K. D. Ushynsky POLYMORPHISM OF INTERLEUKIN 10 – ENCODING GENE AND ITS ROLE IN CYTOKINE RELEASE SYNDROME Abstract. Relationship between polymorphism of cytokine-encoding genes and level of interleukin 10 in Cytokine release syndrome was researched. The algorithm of detection of predisposition of Il10 producing was conducted. Keywords: Cytokine release syndrome, gene polymorphism, IL 10. Introduction. Cytokine release syndrome (CRS) is caused by a large, rapid release of cytokines into the blood from immune cells affected by the immunotherapy [5, 56]. Cytokines are immune substances that have many different actions in the 20 body. Signs and symptoms of cytokine release syndrome include fever, nausea, headache, rash, rapid heartbeat, low blood pressure, and trouble breathing. Most patients have a mild reaction, but sometimes, the reaction may be severe or life threatening. Inter- POLYMORPHISM OF INTERLEUKIN 10 – ENCODING GENE AND ITS ROLE IN CYTOKINE RELEASE SYNDROME leukin 10 (IL10) is a one of the most important cytokines in human [3, 121]. The changing of cytokine level in organism can cause immunodeficiency and CRS. Detection of predisposition of IL10 producing in reaction of foreign antigen integration can help doctor in correct diagnosis and treatment choosing. It is more important for people with genetic inhering disease. The genetic aspects of IL10 producing are unknown [2, 149–50]. The knowledge about influence of gene variability on immune properties may explain the nature of some types of immune disorders such as CRS [5, 56]. The high level of IL10 normally must be 1.5 pg/mL. But it was possible to detect the possibility of IL10 producing only after foreign antigen [1, 554–7]. Correlation between the gene polymorphism and possibility of IL10 producing was still unknown. One is the most popular models of IL10 detection is analysis of patients’ blood after infection by viruses [4, 323–335]. Nucleotide sequence of IL10encoding gene was described [6, 37; 7, 4]. But the associated with DNA variability and possibility to IL10 producing was not described yet. The aim of research is to detect relationship between polymorphism of cytokine-encoding genes and level of interleukin 10 in CRS and to conduct the algorithm of detection of predisposition of IL10 producing, if correlation between IL10 level and polymorphism of IL10-encoding gene is detected. Material. 63 patients infected by Epstein-Barr virus were analyzed. Methods: 1) Detection of interleukin 10 levels in 63 patients infected by Epstein-Barr virus (on the second day after the onset of symptoms) by ELISA test. 2) Identifying of interleukin 10 levels in 63 patients infected by Epstein-Barr virus after convalescence by (ELISA).test. 3) Development of primers and temperaturetime conditions for polymorphic regions of cytokine-encoding genes by VECTORNTI11 program. 4) Detection of polymorphism of cytokineencoding genes in 63 patients by polymerase chain reaction (PCR). 5) Identifying of relationship between polymorphism of cytokine-encoding genes and level of interleukin 10 by Spearman rank correlation coefficient. 6) Test and evaluation will be provided on DNA sequences of human cytokine-encoding genes obtained from National Centre of Biotechnological Information by VECTORNTI11 program [8]. 7) In case if statistical error is more than 30%, relationship will be defined as insignificant. Results. In order to detect the effect of allele combination on the possibility to produce IL10 there were used statistics methods. Each allele was encoded by the following Latin symbols: 512 bp – G; 521 bp – S; 530 – Y; 340 bp – K; 666 bp – R; 672 bp – D; 688 bp– C; 690 bp – Q (tab. 1). Table 1. – Allele condition of examined patients Number Product of PR1 Product of PR2 Product of PR3 Product of PR4 of patient primers, (base pair) primers, (base pair) primers, (base pair) primers, (base pair) 1 2 3 4 5 1N* R, R C, Q Y, Y G, G 2N D, D C, C Y, Y G, S 3H** R, D C, Q Y, K G, S 4N R, D C, C Y, Y G, S 5N R, R C, C Y, Y G, G 6N R, R C, Q Y, Y G, S 7N R, R C, C Y, Y G, S 8N R, R C, C Y, Y G, S 21 Section 4. Medical science 1 9N 10N 11N 12N 13N 14H 15N 16N 17N 18N 19N 20N 21N 22N 23N 24H 25N 26N 27N 28N 29N 30H 31N 32N 33H 34N 35N 36N 37H 38N 39N 40N 41N 42N 43N 44H 45N 46N 47N 48N 22 2 R, R R, D D, D R, R R, R R, D D, D D, D R, D R, R R, D R, D R, D R, R R, D R, R R, D R, R R, R R, R R, R R, R R, R R, R R, D D, D R, R R, R D, D R, R R, R R, D R, R R, R R, R D, D R, R R, R D, D R, D 3 C, C C, C C, Q C, C C, C C, Q C, C C, C C, Q C, C C, C C, Q C, Q C, C C, C C, C C, C C, C C, C C, C C, C C, C C, Q C, C C, C C, Q C, C C, Q C, Q C, C C, C C, C C, C C, Q C, C C, Q C, C C, Q C, C C, Q 4 Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y Y, K Y, Y Y, Y Y, Y Y, Y Y, Y Y, K Y, Y Y, Y K, K Y, Y Y, Y Y, Y Y, K Y, Y Y, Y Y, Y Y, Y Y, Y Y, Y K, K Y, Y Y, Y Y, Y Y, Y 5 G, S G, S G, S G, G G, S G, S G, S G, S G, G G, S G, S G, G G, S G, G G, S G, S G, S G, S G, S G, S G, S G, G G, S G, S G, S G, S G, S G, S G, S G, S G, S G, S G, S G, S G, S G, G G, S G, S G, S G, S POLYMORPHISM OF INTERLEUKIN 10 – ENCODING GENE AND ITS ROLE IN CYTOKINE RELEASE SYNDROME 1 2 3 49H R, R C, C 50N R, R C, C 51H D, D C, Q 52N R, R C, C 53N R, R C, C 54N R, D C, Q 55N D, D C, Q 56N R, R C, C 57H R, R C, Q 58N R, R C, C 59H R, D C, Q 60N D, D C, Q 61N R, R C, Q 62N R, D C, C 63N R, D C, C * H – level of interleukin 10 is > 1.5 pkg/ml. ** N – level of interleukin 10 is < 1.5 pkg/ml. 4 Y, K Y, Y Y, K Y, Y Y, Y Y, Y Y, Y Y, Y Y, K Y, Y K, K Y, Y Y, Y Y, Y Y, Y 5 G, S G, S G, S G, S G, S G, G G, S G, G G, S G, S G, S G, S G, S G, S G, S Results of IL10 detection are present in (tab. 2) Table 2. – Results of ELISA test Number of patient 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Difference of levels of interleukin 10 after the onset of symptoms and after convalescence (pkg/ml) 2 0.9 1.3 2.5 1.0 1.4 1.3 1.4 1.4 1.2 1.0 0.8 1.4 1.2 1.7 1.1 1.3 1 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 2 0.9 1.4 1.1 1.3 1.3 1.1 1.2 2.8 1.3 1.2 1.0 1.3 0.7 2.6 1.2 1.3 3.1 0.9 1.3 1.2 23 Section 4. Medical science 1 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 2 2.3 1.2 1.1 1.3 1.0 0.8 1.1 4.0 1.2 1.4 0.7 1.1 2.1 1.4 1.9 1.2 1.3 1.3 0.8 1.1 2.6 1.3 4.1 1.2 1.3 1.2 1.0 Identifying of relationship between polymorphism of cytokine-encoding genes and level of interleukin 10 was provided by Spearman rank correlation coefficient. There were two rank parameters: high tendency to release interleukin 10 (if difference of levels of interleukin 10 after the onset of symptoms and after convalescence is 1.5 pkg/ml or more) and low tendency to release interleukin 10 (if difference of levels of interleukin 10 after the onset of symptoms and after convalescence is less than 1.5 pkg/ml). As result of statistical analysis there was detected that Spearman’s rank correlation coefficient was p = 0.881. Critical point Tcr = 0.190. | p | > Tcr – null hypothesis is not confirmed, rank correlation between traits is significant. Critical point of the bilateral critical region t (α, k) = 1.734. Confidence interval r = (0.79; 0.97) Error 18% Conclusion. Therefore, the relationship between levels of IL10 after the onset of symptoms and after convalescence, and polymorphism of cytokineencoding genes is straight forward, significant and within the confidence interval. The detection of IL10 in human is very important as it possesses high antiinflammatory properties which play a central role in limiting host immune response to pathogens, thereby preventing damage to the host and maintaining normal tissue homeostasis. It is known that dysregulation of IL10 is associated with enhanced immunopathology in response to infection as well as increased risk for development of many autoimmune diseases. Thus a fundamental understanding of IL10 gene expression is critical for our comprehension of disease progression and resolution of host inflammatory response. References: 1. Alig S. K., Dreyling M., Seppi B., Aulinger B., Witkowski L., Rieger C. T. Eur J. Severe cytokine release syndrome after the first dose of Brentuximab Vedotin in a patient with relapsed systemic anaplastic large cell lymphoma (sALCL): a case report and review of literature // Haematol. 2015. – Vol. 94(6). – P. 554–7. 2. Elgert K. D. Immunology: Understanding the Immune System. John Wiley & Sons. 2009. – P. 149–50. 3. Liu D., Zhao J. Cytokine release syndrome: grading, modeling, and new therapy // J Hematol Oncol. – Vol. 11. 2018.– 121 p. 24 POLYMORPHISM OF INTERLEUKIN 10 – ENCODING GENE AND ITS ROLE IN CYTOKINE RELEASE SYNDROME 4. Riegler L., Jones G., Lee D. Current approaches in the grading and management of cytokine release syndrome after chimeric antigen receptor T-cell therapy // Ther Clin Risk Manag. – Vol. 15. 2019. – P. 323–335. 5. Shimabukuro-Vornhagen A., Gödel P., Subklewe M., Stemmler H. J., Schlößer H. A., Schlaak M., Kochanek M., Böll B., von Bergwelt-Baildon M. Cytokine release syndrome // J Immunother Cancer. – Vol. 6. 2018. – 56 p. 6. Trifunović J., Miller L., Debeljak Z., Horvat V. Pathologic patterns of interleukin 10 expression // Biochem Med (Zagreb). – Vol. 25(1). 2015. – P. 36–48. 7. Wang Z., Han W. Biomarkers of cytokine release syndrome and neurotoxicity related to CAR-T cell therapy // Biomark Res. – Vol. 6. 2018.– 4 p. 8. URL: http://www.ncbi.nlm.nih.gov 25 Section 5. Food processing industry Section 5. Food processing industry https://doi.org/10.29013/AJT-20-7.8-26-30 Ismatova Shakhnoza Nusratulloyevna, research worker of “Food Technology” Department Bukhara Engineering Technological Institute Е-mail: shaxnoza.ismatova89@mail.ru Isabaev Ismoil Babadjanovich, Doctor of Technical Sciences, professor of “Food Technology” Department Bukhara Engineering Technological Institute Е-mail: isabayev_63@mail.ru Ergasheva Khusnirabo Bobonazarovna, Candidate of Technical Sciences, Associate Professor of “Food Technology” Department Bukhara Engineering Technological Institute Yuldasheva Shabon Djumaevna, Assistant of “Food Technology” Department Bukhara Engineering Technological Institute PROSPECTS OF THE USE OF QUINOA AND AMARANTH FOR EXPANDING OF FOOD RESERVE OF POULTRY FARMING Abstract. In this article it’s considered the issue of advisability of using quinoa and amaranth, as perspective crops for arid regions of Central Asia, as part of animal feed. It was performed comparative analysis of nutritional value of components of quinoa and amaranth (grain, seeds, green mass) with grain of fodder wheat and alfalfa wheat. It is substantiated possibility of replacing latter in the composition of feed with the studied raw materials. Keywords: food reserve, quinoa, amaranth, fodder wheat, alfalfa, nutritional value. One of the main objectives facing the combined feed industry is further improvement of technology that ensures increase in the nutritional value of combined feed with all-round resource conservation. This is especially important at the present time, when the industry is pressed by shortage of basic raw materials, primarily in traditional cereals and legumes. In the composition of animal feed there is grain raw materials up to 30.0%, which 26 confirms the fact of its inefficient use as a strategic product. Significant reserve for saving grain in feed mixtures can be maximum increase in alternative sources of raw materials, and its use will expand raw material reserve and reduce cost of feed products [1–4]. This problem is especially important for regions with dry and hot climate, including Uzbekistan, therefore, special attention is paid to high-yielding, PROSPECTS OF THE USE OF QUINOA AND AMARANTH FOR EXPANDING OF FOOD RESERVE OF POULTRY FARMING salt- and drought-resistant crops, in particular quinoa and amaranth. Quinoa is a Latin word Chenopōdium quīnoa (other name: orach), which has unique amino acid, fatty acid, vitamin and mineral composition, smells of fresh grass, pleasant neutral, vegetable taste with nutty notes. This plant is able to perfectly adapt to agricultural and environmental conditions: it grows at 40.0 to 88.0 percent relative humidity, withstands temperatures from –4 up to + 38 ºC and resistant to lack of moisture. Yield at sowing of 15 … 20 kg per hectare makes from 400 up to 1200 kg per hectare. Plants reach physiological maturity in a month and a half [5–7]. Another perspective crop for arid regions is amaranth. Among the actively studied raw sources rich in protein, as well as a number of other biologically active substances it should be distinguished amaranth (Latin Amarantháceae) or redroot, as well as products of its processing (oilcake). Amaranth is distinguished by increased adaptive properties, under conditions of high insolation and temperature, it has a large leaf and seed productivity [8; 9]. As a result of the tests, there were noted high yield, drought resistance, rapid growth, high nutritional value of grain and green mass, as well as other advantages of amaranth [10]. These crops are able to adapt to weather changes and save water, which makes them excellent alternative to cereals in the context of growing problems in food and feed production in Central Asia [11]. Goal of this research is to study nutritional value and substantiate possibility and feasibility of using grain (seeds) and vegetative organs of quinoa and amaranth in combined feed. Objects of the research: quinoa, amaranth. Objects of comparison: grain of fodder wheat and alfalfa wheat. According to the set goal, there were performed comprehensive researches on nutritional value of grain (seeds) and green mass of quinoa and amaranth. During the work we used Barusha quinoa sort and universal amaranth of Kharkov-1 sort [12] that are districted in different agro-ecological zones of Uzbekistan. In the researched raw materials, we determined Mass concentration of dry matter according to GOST 31640–2012 “Feed. Methods for determining dry matter content”, the Mass concentration of albumin and protein – according to GOST 13496.4–93 “Feed, combined feed, combined feed raw materials. Methods for determining the content of nitrogen and crude protein”, fat – in according to GOST 13496.15–2016 “Feed, combined feed, combined feed raw materials. Methods for determination of crude fat content”, fiber – according to GOST 31675–2012 “Feed. Methods for determining content of crude fiber”, ash – according to GOST 26226–95 “Feed, combined feed, feed raw materials. Methods for determination of raw ash”, nitrogen-free extractable substances (NFES) were determined by calculation method [13]. Amino acid composition of quinoa was determined using “Chromospect” automatic analyzer; fatty acid composition was determined by gas-liquid chromatography (GLC); Mass concentration of vitamins was determined by method of chromatographic separation of sample previously purified from proteins on thin layer of silica gel with further development in ultraviolet light and quantitative spectrophotometry; mineral composition was determined using atomic absorption spectrophotometer AAS-1 (Germany) according to instructions for the device. Exchange energy (EE) was determined by calculation method [14]. Results of analyzes are indicated in figure and in (tables 1, 2). It was found that Mass concentration of inflorescences in quinoa is, at the average, 1.3 times higher than in amaranth. In this case, green mass of amaranth exceeds the same value in quinoa by 1.1 times at the average. Based on the data of specialized references [4–12] and results of this research, we made a 27 Section 5. Food processing industry comparative analysis and grading of nutritional value of fruits (grain) of quinoa and amaranth seeds with fodder wheat grain (Table 1), as well as aerial part (green mass) of these crops with alfalfa (table 2). Figure 1. We did research composition of aerial parts of quinoa and amaranth; Composition of aerial part: 1 – quinoa; 2 – amaranth From the data in (table 1), it follows that the studied types of raw materials have relatively high nutritional value. At the same time, grain of fod- der wheat and quinoa have the same grade value (23 points), i. e., they are characterized by almost equal nutritional value. Table 1. – Nutritional value of grain (seeds) of researched raw materials (average data) Substances Crude protein Crude fat Crude fiber Crude ash Nitrogen-free extractable substances (NFES) Amino acids: – lysine – methionine + cystine Minerals: – calcium – phosphorus – sodium Exchange energy, kcal Total grade, point Mass concentration of substances in% per 100 g. of dry substance / grade Fodder wheat quinoa amaranth 14.39/3 16.38/1 15.93/2 2.69/3 6.69/2 7.91/1 4.09/3 7.96/2 9.77/1 3.86/1 3.57/2 3.35/3 74.97/1 65.40/2 63.04/3 0.46/3 0.48/2 0.62/2 0.45/3 0.85/1 0.51/1 0.05/3 0.55/2 0.13/1 452/1 23 0.06/2 0.52/3 0.01/2 444/2 23 0.31/1 0.63/1 0.10/2 452/1 17 The grade of amaranth seeds is 6 points less than other objects of research, which characterizes it as a product with higher nutritional value relative to the reference samples. 28 Exchange energy index of wheat and amaranth is the same (452 kcal), which confirms that suggestion about possible and advisable to use it as alternative to grain crops in feed production. PROSPECTS OF THE USE OF QUINOA AND AMARANTH FOR EXPANDING OF FOOD RESERVE OF POULTRY FARMING It should be noted that in amaranth we also found such anti-nutritional substances like: trypsin inhibitor and tannins in small amounts (0.06%) and effectively inactivated during wet-heat treatment [15; 16]. In addition to grain (seeds) of quinoa and amaranth, their vegetative organs: roots, stems and leaves are also perspective feed materials. However, heavy metals and nitrates are adsorbed from soil in the root system, so their use in feed is inadmissible. Special attention of specialists is attracted by leaves and stems, and presence of valuable biologically active substances in them predetermines perspectivity of their use in composition of feed. The aerial part of quinoa is branching stem of 1.5 to 4.0 m height with large simple three-lobed leaves. After blossoming, it forms high candle-like brushes or panicles of individual clusters. Amaranth is herbaceous branchy bush with thick stem up to 2.5 m high with leaves elongated at the base into petiole and pointed top. It allows you to get up to 200 tons of green mass per 1 hectare and up to 5 tons of grain. The maximum content of biologically active substances in the leaves of these plants was noted in the phase of budding and waxy ripeness. Therefore, nutritional values of aerial parts of quinoa and amaranth were studied precisely in this period. Green mass of alfalfa served as reference sample. Results of the research are shown in (table 2) below. According to the results of the research and grading, nutritional value of aerial part of objects of study is practically not inferior to data of comparison sample, which once again confirms expediency of their use in feed. Table 2. – Nutritional value of aerial part of the researched raw materials during the period of milky-wax ripeness (averaged data) Substances Crude protein Crude fat Crude fiber Crude ash Nitrogen-free extractable substances (NFES) Amino acids: – lysine – methionine + cystine Minerals: – calcium – phosphorus – sodium Exchange energy, kcal Total grade, point Massconcentrationofsubstances in%per100g.ofdrysubstance/grade Fodderwheat quinoa amaranth 20.00/1 12.64/3 14.92/2 3.26/2 3.08/3 4.21/1 24.49/2 26.32/1 22.80/3 10.20/3 12.33/1 10.97/2 42.05/3 45.63/2 47.10/1 0.94/1 0.37/1 0.51/3 0.23/3 0.81/2 0.35/2 1.67/1 0.24/3 0.01/3 263/1 21 1.62/2 0.39/2 0.09/1 247/2 23 1.58/3 0.44/1 0.08/2 247/2 21 Thus, quinoa fruits and amaranth seeds, in addition to food needs, can be used as alternative to cereals in animal and bird feeds, as well as their green biomass and crop residues. The positive experience of growing these crops in the climatic conditions of Uzbekistan and their high biological productivity create need to expand the field of application of quinoa and amaranth, as well as their processed 29 Section 5. Food processing industry products for enrichment of feed with protein and other biologically valuable substances. Moreover, scientists do recommend to use amaranth for protection of environment, since it is able to intensively and in large amount join atmospheric carbon dioxide (C-4 type of photosynthesis) and adsorb heavy metals and nitrates from soil (in the root system, which not used in feed). References: 1. Popov V. Wheat in feeding of animals and birds / V. Popov // Combined feed. 2010. – No. 5. – P 53–56. 2. Fisinin V. I. Modern approaches to poultry feeding / V. I. Fisinin, I. F. Egorov // Poultry. 2011. – No. 3. – P. 7–9. 3. Maximkin A. A. Improving manufacturing technology of combined feeds of high nutritional value based on soybean processing products [Text]: dissertation thesis of Candidate of Technical Sciences: 05.18.01 / A. A. Maximkin. – Moscow, 2017. – 110 p. 4. Jacob J. P. Comparison of Metabolic Energy Content of Organic Cereal Grains for Chickens and Turkeys/ J. P. Jacob S. L. Noll J. A. Brannon// The Journal of Applied Poultry Research. – Vol. 17. – Issue 4. 2008. – P. 540–544. 5. Quinoa in the kitchen/Chiara Cauda, Camilla Micheletti, Bianca Minerdoetc. –Turin: G. Ganale & C. Spa Borgaro Torinese, 2013. – 95р. 6. Abdullaeva M. S. Evaluation of food value of quinoa culture / M. S. Abdullaeva, L. A. Nadtochiy // Symbol of Science International scientific journal, 2016. – P. 9–10. 7. Merkulova N. Yu., Nalivayko D. S. Chemical composition of quinoa seeds as an indicator of quality and functional purpose / N. Yu. Merkulova, D. S. Nalivayko // Collection of articles of International scientific and practical conference: Food market: state, prospects, threats. 2015. – P. 48–53. 8. Gins M. S. Biologically active substances of amaranth. Amarantine: properties, mechanism of action and practical use / M. S. Gins, – M.: Publishing house of Russian University of Peoples’ Friendship, 2002. – 183 p. 9. Jeleznov A. V. Amaranth – perspective food and fodder culture of multi–purpose use for Western Siberia / A. V. Jeleznov, L. P. Solonenko, N. B. Jeleznova // Food. Ecology. Quality. – Novosibirsk, 2001. – P. 44–45. 10. Vavilov N. I. The problem of new cultures / N. I. Vavilov // Selected works.– M., 1965.– Vol. 5.– P. 537–563. 11. Orach for saline and drought-prone lands [Electronic resource]. – Access mode: URL: http://agronews. uz/uz/information/rastenievodstvo/zernovye–kultury / (date of application June 18, 2020). 12. Vegetable, grain and fodder amaranth – sorts and photos [Electronic resource]. – Access mode: URL: http://den–dachnika.ru/?p=2223/ (date of application March, 06, 2019). 13. Popov A. V. Fundamentals of biological chemistry and zootechnical analysis / A. V. Popov, M. S. Kovyndikov, S. Ya. Senik. – M.: Kolos, 1973. – 303 p. 14. Kirilov M. P. Methods of calculating metabolic energy in feed on basis of the content of raw nutrients / M. P. Kirilov, E. A. Makhaev, N. G. Pervov [and others] – Dubovitsy: All-Russian Research Institute of Animal breeding at Russian Agricultural Academy, 2008. – 28 p. 15. Abramov I. A. Amaranth: chemical composition, biochemical properties and processing methods / I. A. Abramov, N. E. Eliseeva, V. V. Kolpakova, T. I. Piskun // Storage and processing of agricultural raw materials. 2011. – No. 6. – P 44–48. 30 FUZZY MULTI–CRITERIA MODEL FOR CONSTRUCTION PROJECT SELECTION IN CONDITIONS OF UNCERTAINTY Section 6. Technical sciences https://doi.org/10.29013/AJT-20-7.8-31-36 Vlasenko Tetiana, PhD student, E-mail: tatiana.vlasenko3@gmail.com Tuhai Oleksii, Doctor of Technical Sciences, Kyiv National University of Construction and Architecture FUZZY MULTI–CRITERIA MODEL FOR CONSTRUCTION PROJECT SELECTION IN CONDITIONS OF UNCERTAINTY Abstract. The article examines the task of construction project selection. The existing methods of selecting construction projects are studied and a list of criteria that can influence the choice of a construction project is given. The experience has shown that the more reliable the methods of construction project evaluation are the greater the reliability of technological, organizational, managerial and economic solutions. A review of relevant literature shows that there is a limited number of studies to select projects in the construction industry. The article demonstrates a systematic procedure of preliminary evaluation based on fuzzy sets theory. Keywords: construction project selection, uncertainty, multi-criteria optimization, pre-investment phase, construction industry, criteria analysis. Introduction Construction works are a complex, long and labor-intensive process that requires the interaction of construction participants, the use of significant financial, material and other resources. Complexity, dynamic character and uncertainty in the construction industry complicate the ways of achieving the goals of construction participants. This business is very exposed to various risks and adverse conditions of the construction industry, which determines its the final result. Under conditions of external environment variability, construction projects do not always achieve expected results in terms of time, cost and quality. One of the main reasons for such inefficiency is that a significant number of risk factors are not taken into account in the planning process [1]. The construction projects practice shows that the influence of uncertainty factors leads to unpredictable situations, which in its turn leads to unexpected costs. Therefore, the analysis of construction projects in conditions of uncertainty is relevant. Preliminary analysis of projects is an important part of construction work. For project managers who are going to manage construction projects in the future, and for investors who are investing, it is important to know how to select a construction project in order to achieve success and profit. Project selection based on the analysis conducted during the pre-investment phase of the construction is a process 31 Section 6. Technical sciences of evaluating individual projects in order to select the best project [2] and is extremely important for the successful achievement of the goals of the construction participants [3]. Consequently, making the right decisions in accordance with various criteria is one of the main conditions for achieving the planned objectives and qualitative completion of the construction project within the specified time frame. Models for selection construction projects Correct project selection analysis is one of the first and most important factors leading to successful achievement of the goal of any significant project. Selecting a project among a multitude of possible alternatives, taking into account a multitude of conflicting factors in the construction industry, is a complex task faced by a decision-maker [4]. The complexity of the decision-making process is due to the existence of many uncertain, inaccurate and incomplete information, which is influenced by many critical factors. Uncertainty can be defined as the occurrence of events that cannot be controlled [5]. Williamson [6] believes that uncertainty is one of the main root causes of conflict between construction participants. When evaluating, it is important to take into account unfavorable and often uncertain preferences of various parties involved. Since conflicts are common in almost all construction projects and incorrect resolution of such conflicts can lead to overspending of funds and delays [7]. Uncertainty about construction projects is therefore an important factor to be properly managed as it can have a significant impact on overall construction results. Zavadskas et al. (2010) [8] applied TOPSIS gray and COPRAG-S methods to assess the risks of construction projects. Risk assessment attributes are chosen taking into account the interests and goals of the parties involved, as well as factors affecting the efficiency of the construction process and real estate value. Taylan et al. (2014) [9] proposed an integrated methodology of fuzzy analytical hierarchy process (AHP) and fuzzy technique to prefer an order of simi32 larity to the ideal solution (TOPSIS) for construction project evaluation. Fuzzy AHP was used to determine weights for fuzzy linguistic variables in the overall risk of a construction project, while fuzzy TOPSIS was used to make the final selection decision. Dikmen et al. (2007) [10] presented a decision making model based on ANP to show how the project selection process can be carried out taking into account both quantitative and qualitative criteria as well as their interrelationship instead of classical B/C analysis. In order to overcome inaccuracy and uncertainty in the selection of a construction project, Ebrahimnejad et al. [11] presented a two-phase group decision making (GDM) approach. This approach combines a modified analytic network process (ANP) and an improved compromise ranking method, known as VIKOR. ANP is introduced to solve the problem of dependence as well as feedback between conflicting criteria and determine their relative importance, and VIKOR expands the potential project ranking based on their overall performance. Ravanshadnia et al. [12] proposed a construction project selection model that took into account the impact of the company’s current projects and used a multi-step method of fuzzy Multiple Attribute Decision Making (MADM). Mohanty [13] developed a Multiple Attribute Decision Making (MCDM) to evaluate project proposals. The model is a structured sequential heuristics for evaluation of acceptability indices, which includes identifying project selection options, identifying internal and external criteria, analyzing and accepting these criteria, and pairwise comparison of these criteria with reference to project selection. A review of relevant literature shows that the choice of projects in the construction industry has not received sufficient attention from researchers. Criteria for construction project selection Project evaluation and selection include solutions that are critical to the profitability, growth and survival of project management organizations in an increasingly competitive global environment. Such FUZZY MULTI–CRITERIA MODEL FOR CONSTRUCTION PROJECT SELECTION IN CONDITIONS OF UNCERTAINTY solutions are often complex because they require identification, examination and analysis of many criteria [14]. Knowledge of these criteria can provide a suitable foundation for customers, contractors, managers and decision-makers to achieve their construction project goals. Many criteria have been suggested for the analysis of construction projects and are considered during the selection of construction projects in the pre-investment phase of construction activity [12; 15–21]. The most important factor in construction projects is the completion of the project in accordance with the scope of work to the satisfaction of the customer within the budget and the execution of works in a reasonable time to achieve a certain goal of the customer. On the basis of many sources, the authors of this article has analyzed the criteria for evaluation of construction projects compiled by different researchers and selected the following basic criteria for construction project selection: 1. Technical capacity; 2. Stakeholders-related factors; 3. External environment; 4. Socio-economic situation; 5. Political situation; 6. Organizational capability; 7. Management ability; 8. Technological factors. Each criterion for more effective assessment should be broken down into sub-criteria. Since this article was not intended to provide sub-criteria, this list is not provided. Research Methodology Evaluation of construction projects can be considered as a multi-criteria problem of decision-making, since alternative projects are evaluated according to a common set of criteria. Selection of a rational construction project in conditions of uncertainty with a variety of criteria should be based on a multi-component method of preliminary assessment, which can take into account each of the significant factors, their interaction, process uncertainty and environmental variability. According to Fetz et al. [22], fuzzy sets theory provides the basis for solving this problem. The strength of fuzzy sets theory lies in the fact that it allows to formalize fuzzy data, to present their fuzziness, which can be included in calculations, and theoretical interpretation. A tool based on fuzzy sets theory allows to take into account uncertain phenomena, allowing to qualify inaccurate information, to reason and to make decisions based on uncertain and incomplete data [23]. This article presents a model for solving the choice of construction projects based on fuzzy sets theory. First, a set of criteria for evaluation of alternative construction projects is established taking into account the set goals of the participants of construction activity and all factors that affect the adequate performance of the project. The decision making criteria are broken down into sub-criteria to achieve effective selection of a construction project, after which a hierarchical structure of criteria is created. The criteria do not have the same importance, so each criterion is given a weight reflecting its importance. To calculate the weight of each criterion, decisionmakers must present their comparative judgment on the relative importance of one criterion in relation to another. In paired comparison, there is a lot of inaccurate, incomplete and uncertain information that is difficult to determine by the decision makers’ judgments. Therefore, assessments are subjectively described by linguistic terms such as “important”, “average”, “unimportant”, etc. This set of linguistic terms is designed to help decision makers assess the relative importance of criteria. The next step is to evaluate several alternative construction projects by selected criteria based on the TOPSIS (The Technique for Order Preference by Similarity to the Ideal Solution). The application of TOPSIS allows to calculate the most preferred alternative that takes into account the relative importance of each criterion compared to other criteria, 33 Section 6. Technical sciences as well as the correspondence of each criterion with the closest proximity to the ideal solution and to be further from the unacceptable solution [24]. Each of these criteria has its own dimension and distribution, and they are difficult to compare or operate directly. As a result, the initial data of criteria evaluation should be dimensionless method of normalization. Step 1. the normalized fuzzy solution matrix can be presented   as [25]: S = � Sij  � ,i = 1, 2,…,m ; j = 1, 2,…,n ,� (1) mxn where matrix entry [Šij] are calculated as follows:        Sij  sija sijb sijd Sij �� = + =  + ,� +� , + S j  s j s j s j S j+ = max sij � (2) when Sj is the benefit criteria;  S j−  s j− s j− s j− Sij �� = =  d ,� b� , a Sij  sij sij sij S j− = min sij � (3) when Sj is the cost criteria. Step 2: the weighted normalized decision matrix is determined by multiplying the normalized decision matrix by the weights associated with it [26]:  (4) v ij = w j ⊕ Sij  where w j is the weight of j-th criterion, Sij is the elements of the normalized decision matrix. TOPSIS approach favors an alternative that is closest to the fuzzy positive ideal solution (FPIS) and the farthest to the fuzzy negative ideal solution (FNIS). FPIS consists of the best performance values for each alternative, while FNIS consists of the worst performance values [25]. Step 3: calculate the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS) using the following formulas [24]: ) FPIS = V1+ ,V2+ ,… ,Vn+ , ( where V j+ = max Vij , j ∈ J 1 ; minVij , j ∈ J 2 34 m m − j ) (5) ) ( where V = minVij , j ∈ J 1 ;max Vij , j ∈ J 2 m m ) (6) where J1 and J2 are sets of benefit criteria and cost criteria. Step 4: determine the distances of each alternative project from PIS and NIS [25]: n d j+ = ∑dv Vij ,V j+ ,�i = 1, 2,…,m � ( ) (7) j =1 n d j− = ∑dv Vij ,V j− ,�i = 1, 2,…,m � ( ) (8) j =1 Step 5: the proximity coefficient is calculated to determine the order of ranking of all alternative projects after calculation of d j+ and d j− for each alternative: CC j =     �   ( ( NPIS = V1− ,V2− ,… ,Vn− , d j− d j+ + d j− (9) Consequently, the order of ranking of all alternative projects can be determined according to the proximity coefficient and the best of alternative can be selected. Conclusion Construction is an activity with an increased level of risk caused by the uncertainty of a large number of factors. Therefore, the tasks to be solved at the pre-investment phase of construction and forming the basis for analysis of construction projects are quite diverse and complex. To solve such tasks, the article suggested a methodological approach to preliminary selection of construction projects based on fuzzy approach with the use of linguistic assessment and project evaluation by selected criteria based on TOPSIS. Complex consideration of the influence of these factors at the stage of selection of construction projects will contribute to improving the efficiency of the process of implementation of the construction project and the successful achievement of the goals of construction participants. FUZZY MULTI–CRITERIA MODEL FOR CONSTRUCTION PROJECT SELECTION IN CONDITIONS OF UNCERTAINTY References: 1. Odimabo O. O., Oduoza C. F. Risk Assessment Framework for Building Construction Projects’ in Developing Countries. International Journal of Construction Engineering and Management, 2(5). 2013. – P. 143–154. 2. Powers G., Ruwanpura J., Dolhan G., & Chu M. Simulation based project selection decision analysis tool. Proceedings of the Winter Simulation Conference, 2, – Vol. 2. 2002. – P. 1778–1785. 3. Boskers N. D., Abou Rizk S. M. Modeling Scheduling Uncertainty in Capital Construction Projects. Proceedings of the 2005 Winter Simulation Conference. Association for Computing Machinery, – New York, 2005. – P. 1500–1507. 4. PMBOK Guide. A guide to the project management body of know, Sixth Edition, 2017. – P. 5–8. 5. Mays W. L. and Tung Y. K. Hydro Systems Engineering and Management. McGraw-Hill, – New York, 1992. – 530 p. 6. Williamson O. Transaction cost economics: The governance of contractual relations. The Journal of Law and Economics, 22, 1979. – P. 233–261. 7. Kassab M., Hipel K., & Hegazy T. Uncertainty analysis in construction conflict resolution using Information-Gap theory. 2007 IEEE International Conference on Systems, Man and Cybernetics, 2007. – P. 1842–1847. 8. Zavadskas E. K., Turskis Z., & Tamošaitiene J. Risk assessment of construction projects. Journal of Civil Engineering and Management, 16(1). 2010. – P. 33–46. 9. Taylan O., Bafail A. O., Abdulaal R. M., & Kabli M. R. Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing, 17, 2014. – P. 105–116. 10. Dikmen I., Birgonul M. T., & Ozorhon B. Project appraisal and selection using the analytic network process. Canadian Journal of Civil Engineering, 34(7). 2007. – P. 786–792. 11. Ebrahimnejad S., Mousavi S. M., Tavakkoli-Moghaddam R., Hashemi H., & Vahdani B. A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling, 36(9), 2012. – P. 4197–4217. 12. Ravanshadnia M., Rajaie H., & Abbasian H. R. Hybrid fuzzy MADM project-selection model for diversified construction companies. Canadian Journal of Civil Engineering, 37(8). 2010.– P. 1082–1093. 13. Mohanty R. Project selection by a multiple-criteria decision-making method: an example from a developing country. International Journal of Project Management, 10(1). 1992. – P. 31–38. 14. Dodangeh J. and Mojahed M. Best project selection by using of Group TOPSIS method, International Association of Computer Science and Information Technology-Spring Conference 2009. IACSITSC’09. April, 2009. – 5053 p. 15. Vahdani B., Mousavi S. M., Hashemi H., Mousakhani M., & Ebrahimnejad S. A New Hybrid Model Based on Least Squares Support Vector Machine for Project Selection Problem in Construction Industry. Arabian Journal for Science and Engineering, 39. 2014. – P. 4301–4314. 16. Prascevic N., Prascevic Z. Application of FUZZY AHP for ranking and selection of alternatives in construction project management. Journal of Civil Engineering and Management, 23(8). 2017.– P. 1123–1135. 17. Shokri-Ghasabeh M., Chileshe N., & Zillante G. From construction project success to integrated construction project selection. In Construction Research Congress, Alberta, – Canada, 2010. – P. 1020–1029. 35 Section 6. Technical sciences 18. Mojahed M., Yusuff R. M., & Reyhani M. Determining and ranking essential criteria of Construction Project Selection in Telecommunication of North Khorasan-Iran. International Journal of Environmental Science and Development, 1(1). 2010. – P. 79–84. 19. Chan A. P.C., Scott D., & Chan A. P. L. Factors Affecting the Success of a Construction Project. Journal of Construction Engineering and Management, 130(1). 2004. – P. 153–155. 20. Baldwin J. R.; Manthei J. M., Causes of delays in the construction industry. ASCE Journal of the Construction Division, 97(2). 1971. – P. 177–187. 21. Ali Z., Zhu F., & Hussain S. Identification and Assessment of Uncertainty Factors that Influence the Transaction Cost in Public Sector Construction Projects in Pakistan. Buildings, 8 (11). 2018. – 157 p. 22. Fetz T., Oberguggenberger M., Jager J., Koll D., Krenn G., Lessmann H., & Stark R. F. Fuzzy Models in Geotechnical Engineering and Construction Management. Computer-aided Civil and Infrastructure Engineering, 14. 1999. – P. 93–106. 23. Zadeh L. A. The concept of a linguistic variable and its application to approximate reasoning, Information Sciences 8(3). 1975. – P. 199–249. 24. Tan Y., Shen L., Langston C., & Liu Y. Construction project selection using fuzzy TOPSIS approach. Journal of Modelling in Management, 5(3). 2010. – P. 302–315. 25. Sodhi B., and Prabhakar T. V. (2012). A Simplified Description of Fuzzy TOPSIS. [pdf] Available at: URL: http://arxiv.org/pdf/1205.5098v1.pdf// (Accessed: 11 August, 2020). 26. Mahmoodzadeh S., Shahrabi J., Pariazar M., & Zaeri M. Project selection by using FUZZY AHP and TOPSIS technique. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 1, 2007. – P. 270–275. 36 DEVELOPMENT OF CARBAMIDE-FORMALDEGIDE SMOLA-BASED GLUE COMPOSITIONS MODIFIED WITH SILICON ORGANIC COMPOUNDS Section 7. Chemistry https://doi.org/10.29013/AJT-20-7.8-37-41 Eshmurodov Khurshid Esanberdievich, Termez State University, Termez E-mail: khurshid.eshmurodov.86@mail.ru Turaev X., Termez State University, Termez, Tashkent Djalilov A., Tashkent Research Institute of Chemical Technology, Tashkent Geldiev Yu., Termez State University, Termez, Tashkent Babamuratov B., Termez State University, Termez, Tashkent DEVELOPMENT OF CARBAMIDE-FORMALDEGIDE SMOLA-BASED GLUE COMPOSITIONS MODIFIED WITH SILICON ORGANIC COMPOUNDS Abstract. In this study, modified adhesive compositions based on urea-formaldehyde resin with siliconorganic compounds were developed. Composite plates are made on the basis of the obtained glue and crushed reeds. The effect of the modifier on the physical and mechanical properties of the plates was studied. Keywords: urea-formaldehyde resin (UFR), tetraethoxysilane (TES), liquid glass, cane, reed plate. Introduction Today, as the demand for wood products around the world increases, so does the demand for its alternative types. In particular, the furniture and construction industries cannot be imagined without wood and its alternative types. Reforestation, which is declining year by year, will take hundreds of years, a great deal of labor and expense. Preserving them is very important from an environmental point of view. In our country, great attention is paid to the construction industry, in particular, the production of wood-chipboard. It is determined by the Resolution of the President of the Republic of Uzbekistan dated February 20, 2019 No PP-4198 “On measures to radically improve and comprehensively develop the construction materials industry”, ie by 2021 to increase the production of chipboard (DSP) – 380 thousand cubic meters 8 of the summary indicators of promising projects in the construction materials industry in 2019–2021 in Annex 3 to the Resolution of the Government of the Republic of Uzbekistan dated May 23, 2019 No. PQ-4335 “On additional measures for the 37 Section 7. Chemistry accelerated development of the construction materials industry” -clause – “Project for the organization of production of wood-chipboard (DSP) from cotton stalks, reeds, straw, and other plant stalks” and the Cabinet of Ministers of the Republic of Uzbekistan dated April 11, 2019 No. 297 “Further development of production of wood-chipboard and their alternatives” On additional measures to – It is planned to increase the production of chipboard based on local alternative wood raw materials. Research work is underway to develop an innovative technology for the production of formaldehyde-free wood-chip boards from cotton stalks, reeds, straw and other plant stems on the basis of local raw materials. In the production of wood-chip boards were studied the processes of extraction of local raw materials – cotton stalks, reeds, straw and other plant stalks, separation into large and small fractions, mixing with glue and bonding. Inexpensive, environmentally friendly and environmentally friendly ingredients based on local raw materials were selected for the preparation of the glue. Phenol-formaldehyde (PFR) and urea-formaldehyde resins (UFR) are widely used products. They are widely used in the production of wood shavings, mineral fiber boards and similar building materials, despite a number of disadvantages such as high toxicity of vapors, flammability, hydrophilicity, short-term storage of resin. The cheapness of formaldehyde and the lack of a substitute have led to an increase in usage over the last half century [1–2]. Alternative types of wood, such as wood chipboard, wood fiberboard, medium-density wood fiberboard – MDF (MDF-Medium Density Fibreboard), laminated medium-density wood fiberboard – LMDF, etc. are mainly used in the production of phenol-formaldehyde or urea – formaldehyde resins are used. These resins release formaldehyde, which does not react during production and when used as an adhesive, and is formed as a result of partial decomposition. In particular, when the amount of formaldehyde in the air is 0,5 mg / m3, it is known 38 to cause serious damage to the eyes, nose, respiratory system, causing skin diseases [3–5]. In the study, plates were prepared on the basis of glue modified urea-formaldehyde resin with alkaline solutions of silicates, organic monomers, organosilicon compounds. Their physical and mechanical properties were studied. In this case, the siliconorganic part is consumed in small quantities. The main mass of the glue is urea-formaldehyde resin. When new resins are used, there is almost no need to change the existing technology [6–9]. Research methods and tools In the experiment, formalin, urea, sodium silicate (liquid glass), tetraethoxysilane (TEOS), methyl methacrylate, acrylic acid, tetrafurfurylsylan, polyacrylamide, n-toluene sulfoxic acid; thermopress, viscometer, “fire tube” method was used. Experimental part It has been performed the follow the experiment, 205 g of 36,9% (pH = 3.6) formalin and 8.4 g of 26.9% ammonia solution were added to a 500 ml four mouth flask and mixed for 10 min. While stirring, 120 g of urea was added and stirred for another 20 min until the urea was completely dissolved (pH = 9.1). After the mixture was heated for another 1.5 h at 80–90 °C, a 5 g aqueous solution of sodium silicate with a density of 1,474 g/cm3 and a modulus of silicate of 1,08 was added (pH = 8,2). The reaction mixture was cooled to a temperature of 70 °C while stirring. 18 g of modifier and another 24 g of urea were then added to the reactor and the mixture was kept at 60–65 °C for 40 min. It was then cooled to a temperature of 30 °C. The modifier is in an aqueous dispersed state and contains 10% methyl methacrylate, 7.2% acrylic acid, 12% tetraethoxylane, 4% tetrafurfurylsylane and 6.8% polyacrylamide. The viscosity of the finished modifier (pH = 8.0) is 48 s when measured on a viscometer VZ-246 with a diameter of 4 mm [10]. A plate measuring 100x100 mm was prepared and tested on the basis of the obtained glue and crushed reeds of 10/2 fraction. 0.1% n-toluene sulfoxic acid DEVELOPMENT OF CARBAMIDE-FORMALDEGIDE SMOLA-BASED GLUE COMPOSITIONS MODIFIED WITH SILICON ORGANIC COMPOUNDS relative to the glue mass was used as a hardener in the preparation of the plate. The plate was prepared in a thermopress for 8 minutes at a pressure of 2 MPa, at 180 °C. The thickness of the prepared slab is 16 mm, the density is 850 kg/m3. Physical and mechanical properties of the obtained slab were determined in accordance with GOST 10634–78, GOST 10635–78, GOST 10636– 78. Flammability was determined on the basis of the mass loss in combustion by the method of “Flame Pipe”, as a percentage of water absorption and permeability thickness [11–12]. To determine the strength of the samples, their resistance to perpendicular stress was tested after soaking in cold water for 24 h. Outcome analysis The results of the study of the main technological properties of the modified glue are given in (table 1). Table 1. – Basic technological properties of modified glue Percentage of The surface tension Wetting modifier,% of the glue, mN/m angle, grad. 0 1 2 3 4 5 6 66 57 55 53 52 51 50 68 64 61 58 55 54 55 As can be seen from Table 1, the technological properties of the removable adhesive vary depending on the amount of modifier. Viscosity according to ВЗ-246 with a nozzle diameter of 4 mm, с 74 77 80 85 91 98 105 pH Gelatinization time, 150 °C, с 7.93 7.59 7.48 7.39 7.31 7.25 7.20 60 57 53 50 47 45 44 The physical and mechanical properties of the plates obtained on the basis of modified glue are given in (table 2). Table 2. – Physical and mechanical properties of the obtained plates Percentage of modifier in glue composition,% 0 1 2 3 4 5 6 Static crush resistance, MPa 10.5 12.3 13.5 15.1 16.8 18.0 18.5 Resistance to perpendicular stress, MPa 0.22 0.29 0.34 0.39 0.43 0.48 0.50 As can be seen from (table 2), its physical and mechanical properties are optimal when the amount of modifier is 5% of the glue mass. Swelling in thickness,% 32.6 28.2 25.3 22.0 19.9 16.7 16.1 Bulk swell,% Water absorption,%. 32.49 26.42 25.63 24.88 23.56 22.91 21.96 78.6 72.4 64.7 58.3 52.8 49.0 48.1 Figure 1. shows the dependence of the mass loss (%) of the obtained slab samples on the amount of modifier in the “Fire Pipe” for 3 minutes. 39 Section 7. Chemistry Figure 1. Dependence of the mass loss (%) on the amount of modifier in the “Flame tube” for 3 minutes of the obtained slab samples Figure 2. shows the dependence of the time taken for the 30% mass loss in the “fire pipe” on the amount of modifier. As can be seen from (figure 1), the combustion mass loss of the plate has the lowest value (12%) when the modifier content is 5%. When the amount of modifier is higher than this, the mass loss rate in combustion is almost unchanged. From (figure 2) it can be seen that it took 15 minutes for 30% mass loss when the modifier amount was 5%. There was no significant difference when the modifier content was 6%. It was proved that the optimal amount of the modifier is 5%. Conclusion The results show that the new type of glue modified with sodium silicate and silicon-organic compounds in many respects does not lag behind phenol-formaldehyde and urea-formaldehyde res- Figure 2. Dependence of the time spent on 30% mass loss in the “fire pipe” on the amount of modifier ins. Wood panels based on it are resistant to fire and moisture, and their strength is not inferior to other similar types of boards. The amount of modifier based on the obtained silicon-organic compound was found to have a significant effect on the strength of the product. As the amount of modifier increases, water resistance and durability increase. It was found that 5% modifier was the most acceptable amount relative to the total mass of glue, and that the strength and water resistance of the resulting product changed very little when the percentage was higher. Based on the results of the study, it can be said that the use of modified adhesives based on organosilicon compounds for the production of environmentally safe wood shavings will lead to a major change in the industry. This will reduce the use of toxic substances in the production of wood chipboard. References: 1. Kondratyev V. P. Synthetic adhesives for wood materials / V. P. Kondratyev and V. I. Kondrashchenko. – M.: Scientific world, 2004. – 520 p. 2. Azarov V. I. Chemistry of wood and synthetic polymers: textbook / V. I. Azarov, A. V. Burov, A. V. Obolenskaya. – SPb.: Lan, 2010. – 624 p. 3. Sokolova E. G. “Modification of phenol-formaldehyde resin with melamine-urea-formaldehyde resin for gluing plywood” Systems Methods Technologies 2018. – No. 2 (38). – P. 111–115. 4. Ugryumov S. A. “Modification of urea-formaldehyde resin for the production of kostroplit” / S. А. Ugryumov, V. E. Tsvetkov // Woodworking industry. 2008. – No. 3. – P. 16–18. 5. Yu. G. Doronin S. N., Miroshnichenko M. M. Svitkina. Synthetic resins in woodworking. – M.: Forest industry, 1987. – 159 p. 40 DEVELOPMENT OF CARBAMIDE-FORMALDEGIDE SMOLA-BASED GLUE COMPOSITIONS MODIFIED WITH SILICON ORGANIC COMPOUNDS 6. Ugryumov S. A. Methods of modification of phenolformaldehyde resins used in the manufacture of laminated wood materials. Review //Adhesives. Sealing. Technologies. 2017. – No. 5. P. 14–19. 7. Rusakov D. S., Varankina G. S., Chubinskij A. N. Modification of phenolic resins and urea-formaldehyde resins byproducts of pulp production // Adhesives. Sealing. Technologies. 2017. – No. 6. – P. 16–20. 8. Zeli Que. Takeshi Furuno, Sadanobu Katoh, Yoshihiko Nishino. Effects of urea-formaldehyde resin mole ratio on the properties of particleboard. Building and Environment, 2007. – Vol. 42. – P. 1257–1263. DOI: 10.1016/j.buildenv.2005.11.028 9. Fedotov A. A. Investigation of the properties of chipboards based on synthetic resins with various proportions of furan resin additives // A. A. Fedotov, S. A. Ugryumov // Adhesives. Sealants. Technology. 2012. – No. 12. – P. 16–19. 10. Ugryumov S. A., Osetrov A. V. “Analysis of the chemical composition and properties of wood-based panels based on modified adhesive compositions” Lesnoy Vestnik 4/2016. – P. 40–43. 11. RF patent № 2059663 C1, 08 G 12/12. 12. RF patent No. 2114870 C1, C08 G 12/40, C08 J 9/06. 41 Contents Section 1. Biology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 Wanigasekara Dharani Nirasha, Karunarathne Chandani, Dasanayaka Mudiyanselage Rasika Sanjeewani, Perera Ruwan Tharanga, Weerakoon Tharindra, Sudesh Hemal SCREENING GARCINIA ZEYLANICA FOR IN-VITRO ANTIMICROBIAL ACTIVITY AND ANTI-OXIDANT ACTIVITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 Section 2. Information technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Struzik Vladislav, Hrybkov Serhii, Chobanu Valeriia EVOLUTION OF REFACTORING. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Section 3. Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Dergachev Victor Mikhaylovich, Lelyavin Sergey Nikitovich CONSTRUCTION OF INFINITE ALGEBRAIC K- THEORY OF P I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Section 4. Medical science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Venger Andrii, Venger Olga, Lapkin Andrii, Novozhen Oksana, Glushchenko Viktoriia, Kucherenko Mykola POLYMORPHISM OF INTERLEUKIN 10 – ENCODING GENE AND ITS ROLE IN CYTOKINE RELEASE SYNDROME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Section 5. Food processing industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Ismatova Shakhnoza Nusratulloyevna, Isabaev Ismoil Babadjanovich, Ergasheva Khusnirabo Bobonazarovna, Yuldasheva Shabon Djumaevna PROSPECTS OF THE USE OF QUINOA AND AMARANTH FOR EXPANDING OF FOOD RESERVE OF POULTRY FARMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Section 6. Technical sciences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Vlasenko Tetiana, Tuhai Oleksii FUZZY MULTI–CRITERIA MODEL FOR CONSTRUCTION PROJECT SELECTION IN CONDITIONS OF UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Section 7. Chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Eshmurodov Khurshid Esanberdievich, Turaev X., Djalilov A., Geldiev Yu., Babamuratov B. DEVELOPMENT OF CARBAMIDE-FORMALDEGIDE SMOLA-BASED GLUE COMPOSITIONS MODIFIED WITH SILICON ORGANIC COMPOUNDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 42