Determination of the optimum process parameters using taguchis approach to extract the boron from colemanite ore in potassium bisulfate solutions
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(2) © by PSP. Volume 27 ± No. 6/2018 pages 3873-3877. Fresenius Environmental Bulletin. FEB-EDITORIAL BOARD CHIEF EDITOR: Prof. Dr. Dr. H. Parlar Parlar Research & Technology-PRT Vimy Str.1e 85354 Freising, Germany CO-EDITORS: Environmental Spectroscopy Prof. Dr. A. Piccolo 8QLYHUVLWDGL1DSROL³)UHGHULFR,,´ Dipto. Di Scienze Chemica Agrarie Via Universita 100, 80055 Portici, Italy Environmental Biology Prof. Dr. G. Schuurmann UFZ-Umweltzentrum Sektion Chemische Ökotoxikologie Leipzig-Halle GmbH, Permoserstr.15, 04318 04318 Leipzig, Germany Prof. Dr. I. Holoubek Recetox-Tocoen Kamenice126/3, 62500 Brno, Czech Republic Prof. Dr. M. Hakki Alma Igdir Universitesi 76000, Igdir, Turkey Environmental Analytical Chemistry Prof. Dr. M. Bahadir Lehrstuhl für Ökologische Chemie und Umweltanalytik TU Braunschweig Lehrstuhl für Ökologische Chemie Hagenring 30, 38106 Braunschweig, Germany Dr. D. Kotzias Via Germania29 21027 Barza(Va), Italy Advisory Board K. Bester, K. Fischer, R. Kallenborn DCG. Muir, R. Niessner,W.Vetter, A. Reichlmayr-Lais, D. Steinberg, J. P. Lay, J. Burhenne, L. O. Ruzo. MANAGING EDITOR: Dr. P. Parlar Parlar Research & Technology PRT, Vimy Str.1e 85354 Freising, Germany Environmental Management Dr. K. I. Nikolaou Env.Protection of Thessaloniki OMPEPT-54636 Thessaloniki Greece Environmental Toxicology Prof. Dr. H. Greim Senatkommision ± DFG / TUM 85350 Freising, Germany Environmental Proteomic Dr. A. Fanous Halal Control GmbH Kobaltstr. 2-4 D-65428 Rüsselsheim, Germany Environmental Education Prof. Dr. C. Bayat Esenyurt Üniversitesi 34510 Esenyurt, Istanbul, Turkey Environmental Medicine Prof. Dr. I. Tumen Bartin Üniversitesi 74100, Bartin, Turkey. Marketing Manager Cansu Ekici, B. of B.A. PRT-Research and Technology Vimy Str 1e 85354 Freising, Germany E-Mail: parlar@wzw.tum.de parlar@prt-parlar.de Phone: +49/8161887988. 5631.
(3) © by PSP. Volume 27 ± No. 6/2018 pages 3873-3877. Fresenius Environmental Bulletin. Fresenius Environmental Bulletin is abstracted/indexed in: Biology & Environmental Sciences, BIOSIS, CAB International, Cambridge Scientific abstracts, Chemical Abstracts, Current Awareness, Current Contents/Agriculture, CSA Civil Engineering Abstracts, CSA Mechanical & Transportation Engineering, IBIDS database, Information Ventures, NISC, Research Alert, Science Citation Index (SCI), Scisearch, Selected Water Resources Abstracts. 5632.
(4) © by PSP. Volume 27 ± No. 6/2018 pages 3873-3877. Fresenius Environmental Bulletin. CONTENTS ORIGINAL PAPERS. % #&
(5) . 3878. Fatmir Faiku, Arben Haziri, Ibrahim Mehmeti, Arben Mehmeti, Gjylije Hoti ' . 3884. Rovsen Guliyev, Murat Yesilyurt D/ZK/>,Zd Z/d/KEK&^WKZd&/>/d/ ^E,/>Z E͛^
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(9) . 3891. Sinan Ayan, Mustafa Gulhan, Sedat Kaygusuz, Aysun Ergene
(10) % . 3896. Elzbieta Rolka, Radoslaw Szostek, Lukasz Grzybowski, Zdzislaw Ciecko . . 3906. Shun Shang, Zhaotang Shang, Jian Yu, Xuhui Zhang, Jing Wu, Dong Jiang . 3914. Khwaza Vuyolwethu, Mike O Ojemaye, Adebola O Oyedeji, Francis B Lewu, Opeoluwa O Oyedeji $ ! . % -.& . 3920. Alexandre Konate, Xiao He, Peng Zhang, Yuhui Ma, Jie Yang, Gibson Maswayi Alugongo, Yukui Rui, Zhiyong Zhang #. 3936. Burcu Cetin, Betul Kurtulus . 3941. Nasir Ahmed Rajput, Muhammad Atiq, Nazir Javed, Yong-Hao Ye, Zhijian Zhao, Rehana Naz Syed, Abdul Mubeen Lodhi, Babar Khan, Owais Iqbal, Daolong Dou $
(11) . 3950. Huiwen Guo, Shuqin Zhang, Dajun Ren, Shuyue Guo, Jie Gong, Tao Feng %. &$ %. & " ! . 3958. Guvenc Gorgulu, Bulent Dede $ !
(12) $ . 3965. Ying Zhang, Jianjun Du, Liming Ma, Xiaodi Pan, Jinglu Wang, Xinyu Guo . . 3970. Stanislaw Sienkiewicz, Jadwiga Wierzbowska, Peter Kovacik, Slawomir Krzebietke, Piotr Zarczynski
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(14) ! . 3977. Zaib-un-Nisa Burhan, Pirzada Jamal Ahmed Siddiqui, Seema Shafique, Nafisa Shoaib
(15) . Ali Ben Saeed, Amir Abbas Kamanbedast, Ali Reza Masjedi, Mohammad Heidarnejad, Amin Bordbar . 3873. 3986.
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(17) ! . 3999. Jiantao Fu, Donglei Sun, Dongmei Cheng, Zhixiang Zhang . 4006. Fenglin Zhong, Xiangzhu Zhou, Yongwen Lin, Xian Chen, Ru Xu, Shubing Wang, Yizhang Lin, Jie Pang, Shuang Wu . 4014. Tatjana Ratknic, Mihailo Ratknic, Tatjana Cirkovic-Mitrovic, Ljiljana Brasanac-Bosanac ! . 4023. Pouran Morovati, Aliasghar Valipour, Sahar Geravandi, Azimeh Karimyan, Hamid Reza Adeli Behrooz, Mohammad Javad Mohammadi %
(18) & . 4029. Naime Zulal Elekcioglu .
(19) . 4037. Debin Jia, Longjiao Qian, Jing Jian . #.
(20) . 4047. Kadriye Ozcan, Tuba Acet . 4052. Kerem Mertoglu, Onur Ileri, Yasin Altay $ . 4061. Jiang Fuqiang, Zhang Xinlu, Liu Xiaoyu
(21) . 4068. Nuray Bas, H Gonca Coskun, Sinasi Kaya, Bulent Bayram, Hakan Celik ! !,*+.. 4076. Chang Jiang, Xiufeng He, Yang Le, Yuxin Bao, Binghui Liu, Xuejian Li, Deyu Wang . 4084. Elisabetta Loffredo, Eren Taskin . 4093. Eray Aykin, Burcu Omuzbuken, Asli Kacar $ . 4104. Fazilet Ozlem Cekic, Seyda Yilmaz . . 4112. Liu Yu, Li Wenping, Wang Qiqing, Liu Shiliang ! $ !
(22) . 4120. Aysenur Gurgen, Sibel Yildiz, Zehra Can, Sana Tabbouche, Ali Osman Kilic . 4132. Sercan Gulci, Abdullah E Akay, Raffaele Spinelli, Natascia Magagnotti " !͞/>>h^^hd/>/^/>>h^Dz>K>/Yh &/ E^͟! . 4139. Burak Demirhan, Fatma Tugce Guragac, Buket Er-Demirhan, Hakki Tastan, Esra KupeliAkkol . Tariq Al Najjar, Mohammad Al Tawaha, Mohammad Wahsha, Ahmad Abu Hilal 3874. 4149.
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(24) . . 4156. Sifa Xu, Libin Zeng, Cuifeng Li, Mengdan Bian, Zhe Wang
(25) " . 4162. Hasan Gokhan Dogan, Gungor Karakas . 4169. Aygul Kucukgulmez, Ali Eslem Kadak, Mehmet Celik, Yasemen Yanar, Osman Gulnaz $ $ . 4174. Selim Tangoz, Mehmet Ilhan Ilhak, Selahaddin Orhan Akansu, Nafiz Kahraman . 4186. Esin Dadasoglu, Aykut Oztekin, Fatih Dadasoglu . 4192. Kursat Korkmaz, Aysegul Kirli, Mehmet Akgun, Ozbay Dede ! % #&
(26) . 4198. Emre Demirer-Durak !
(27) . 4206. Emre Demirer-Durak, Erkol Demirci . 4212. Cihan Karaca, Begum Tekelioglu, Dursun Buyuktas, Ruhi Bastug % &
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(30) . 4220. Humeyra Nergiz, Atilla Durmus . . 4224. Selvinaz Yakan, Yucel Unal %+303& . 4232. Elif Tozlu, Nasibe Tekiner, Recep Kotan $ $ . 4239. Yongkuan Chi, Kangning Xiong, Hua Xiao, Hu Chen, Denghong Huang, Yaqin Wen, Xiaoyun Shen ,Zd Z/d/KEK&KͲh>dhZ/E'D/ZKKZ'E/^D^&KZ^/Dh>dE Kh^ 'Zd/KEK&ɴͲzW ZD d,Z/EEϯͲ W, EKyz EK//. 4249. Jiayuan Zhao, Xueli Li, Yuanlong Chi, Dongying Jia, Kai Yao % " " &. 4258. Huseyin Cetin, Onder Ser, Suha Kenan Arserim, Yesim Polat, Tulay Ozbek, Mehmet Civril, Ilker Cinbilgel, Yusuf Ozbel . 4263. Hakki Akdeniz, Ali Koc, Mohammad Sohidul Islam, Ayman El Sabahg . 4270. Lutfiye Yilmaz-Ersan, Tulay Ozcan, Arzu Akpinar-Bayizit, Buse Usta, Mervenur Kandil, Ezgi Eroglu %
(31) & ! Tariq Al-Najjar, Nashat Dahiyat, Maroof Khalaf, Nida Sharari, Mohammad Wahsha . 3875. 4277.
(32) © by PSP. Volume 27 ± No. 6/2018 pages 3873-3877. Fresenius Environmental Bulletin. ! . 4285. Ahmet Ufuk Komuroglu, Fatmagul Yur, Ismail Hakki Ekin ZzKZ/W/>>Z/^;,͘ͿZKKΘ͘,t<^t͘ ydZd&Zd/KE^,s WKd EdEd/D/ZK/>d/s/dz/E>/Yh/Ͳ hdEKd/E^K>/D /. 4293. Yalcin Karagoz, Kenan Karagoz, Fatih Dadasoglu, Berna Ozturk-Karagoz . 4298. Saud Alarifi, Daoud Ali, Saad Alkahtani, Mansour Almansour . 4307. Rong Wang, Ying Wang $ . 4318. Dilek Yalcin-Duygu, Belgin Erdem, Tulay Ozer, Ilkay Acikgoz-Erkaya . 4325. Ibrahim Jusufranic, Slobodan Neskovic, Sonja Ketin, Rade Biocanin $ . 4332. Zhao Lei $0. 4337. Mei-qin Wang, Xiao-juan Hao, Yan-ping Yao, Min Xu . . . . 4343. Salih Alkan, Umit Turgut, Ilhan Irende, Ali Riza Kul $ " . 4349. Mohammad Hossein Kaveh,Fatemeh Darabi, Farideh Khalajabadi-Farahani Mehdi Yaseri, Mohammad Hossein Kaveh Mohammad Javad Mohammadi, Hamid Reza Adeli Behrooz, Davoud Shojaeizadeh, Alireza Rohban
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(35) . 4357. Tugba Memisoglu, H Ebru Colak . 4367. Engin Yol ! % #& % " &. 4373. Ayse Usanmaz-Bozhuyuk, Saban Kordali, Memis Kesdek, Duygu Simsek, Mahmut Alper Altinok, Hacer Handan Altinok Amanmohammad Komaki $
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(37) +/*+ . 4381. YuFeng Xie, XueMei Han, HaiKuan Wang, FuPing Lu . ! %!+2,.& % " &. 4389. Ayse Usanmaz-Bozhuyuk, Saban Kordali . 4402. Chunjing Guo, Qian Lou, Gang Ge . 4413. Chenyang Zhao, Dazhong Ren, Wei Sun, Yunyun Bai, Jin Han + . 4423. Kursat Kargun, Sefa Senol, Ozlem Secen, Berrin Ayaz-Tuylu %! +23,&% !! &
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(39) © by PSP. Volume 27 ± No. 6/2018 pages 3873-3877. Fresenius Environmental Bulletin. z/ >E Zd/EWKDK>K'/>,Zd Z/^d/^K&KZ'E/>>z'ZKtE͞>zE<͟E͞,^E z͟WZ/Kd^ % #&. 4433. Mehmet Polat . 4440. Sevda Turkis, Emire Elmas !
(40) . 4448. Nergiz Yildiz-Yorgun, Filiz Gur-Filiz, Omer Faruk Ozdemir, Berna Oto . 4455. Qiong Li, Guoyang Ma, Leishan Chen, Yanbo Wang . 4460. Xinqing Zhang $ . 4469. Hulya Celik, Mehmet Maman, Aynur Babagil . 4483. Si Qingmin, Wang Yanxia, Li Xuewei, Niu Linqing, Zhang Guohui " . 4488. WenXuan Li, HaiZhen Kong, XueLi Wang, YuMing Song % " & . 4493. Derya Bostanci, Serdar Yedier % !+12,&
(41) . 4502. Nur Melike Gozacan, Zehra Arzu Becer . 4511. Esengul Ozdemir, Ugur Gozel . 4518. Yue Xie, Zuliang Zhang, Feiyue Li, Xingjun Fan, Xin Xiao, Jianfei Wang . . 4524. Nurtac Oz, Esra Ozkan % . 4532. Huseyin Ok, Sule Orman . 4543. Gozde Turkoz-Bakirci %& !
(42) $ . 4559. Ibrahim Aytekin, Ecevit Eyduran, Ismail Keskin
(43) ! ! . Meixia Tao, Hu Hu, Lanwen Hu, Quan Yang, Ming Chen. 3877. 4566.
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(46) "" "$"' " ! $ "&" "! . . % % ! $ (:408(02; 8),5(?080 )8(/04 ,/4,:0 8),5 ,/4,:0 1>301,6:0 . 1. Faculty of Natural Sciences, Department of Chemistry, University of Prishtina “Hasan Prishtina”, Prishtina, Kosovo 2 Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway 3 Faculty of Agriculture and Veterinary, University of Prishtina “Hasan Prishtina”, Prishtina, Kosovo. !" ". " #" " (L.) is a medicinal plant that is known as Yarrow [1]. The herb is very common during May and June and it grows in all parts of Kosovo. " (L.) has been traditionally used in Kosovo against skin inflammations and gastrointestinal complaints. In some countries "(L.) has been used internally as an herbal tea and externally in lotions and herbal medications [13]. Plants with potential antimicrobial activity should be tested against an appropriate microbial model to confirm its activity [4]. The antimicrobial effect of the plant extracts has been studied by a number of researchers in different parts of the world [5-12]. Aerial parts of the "(L.) are very rich with sesquiterpene lactones and alkaloids [13]. "(L.) flower extract are more effective against certain microorganisms than (L.) leaves and stems extracts [14-16]. Our research group was interested to analyze the chemical profile of different medicinal plants, which are growing wild in the region of Kosovo and Albania [17-26]. The aim of this study was to investigate the antibacterial activity of Kosovo`s "(L.) extracts, which were grown wild in Kosovo.. Now is known that organic extracts of medicinal plants can be used as antibacterial agents. Effectiveness of extract on inhibition of bacterial growth depends from sort of medicinal plant. In this research we have focused in medicinal plant " (L.) growing wild in Kosovo. The plant "(L.) was used for a long time against bacterial infections. Antibacterial efficiency of "(L.) were examined by using methanol, ethyl acetate, acetone, diethyl ether, water and chloroform extracts and tested against three Gram positive bacteria ! % " " " (food isolate), ! % " " " (clinical isolate), ! %! (clinical isolate) and Gram negative bacteria (clinical isolate). The antibacterial activity was determined by using agar disc diffusion method. The zones of inhibition from extracts were compared to that of penicillin G as standard. More pronounced activity was shown by water, diethyl ether and ethyl acetate extracts of the " (L.). The extracts of ethyl acetate and diethyl ether showed antibacterial activity against " " (clinical isolate) and %! . The water extract showed antibacterial activity against " " (food isolate) and %! . Also methanol and chloroform extracts of the " (L.) showed a stronger antibacterial activity as penicillin G against bacteria (extract of methanol) and " " (food isolate) (extract of chloroform). The antibacterial activity of the "(L.) was due to the presence of various secondary metabolites such as phenols and flavonoids. Hence, this plant can be used to discover bioactive natural products that may serve as leads in the development of new pharmaceuticals. . " ! " ! 3(5: 4(:,80(39 The aerial part of "(L.), growing wild in east part of Kosovo, was collected in May of 2014. Voucher specimens were deposited in the herbarium of the Department of Plant Protection, University of Prishtina. The plant material was air dried and ground in a mixer. 8,7(8(:0656-73(5:68.(50*,=:8(*:9A portion of the finely powdered material (100 g) was extracted three times with 70% methanol (MeOH, 2 L) during a 24-h period. After removal of MeOH under reduced pressure, the aqueous phase was successively extracted with four solvents of increasing polarity (methanol, ethyl acetate, diethyl ether, water,. '% ! " (L.), Extract, Antibacterial activity Gram positive bacteria, Gram negative bacteria.. . 3878.
(47) #". $ . . . !
(48) . (clinical isolate) " " (food isolate), %! (clinical isolate). The antibacterial activity was determined by using agar disc diffusion method. The zones of inhibition of the extracts were compared to that of penicillin G as standard as shown in Table 2. " '0,3+96-,=:8(*:96):(05,+-86473(5: . chloroform and acetone). The extraction was carried out until a colorless extract was obtained. The residue was the aqueous extract. The solvents were evaporated by vacuum rotary evaporator (EYELA N-1000, Japan). The extraction process yielded methanol (10.39 g), ethyl acetate (4.0 g), acetone (6.64 g) diethyl ether (6.24 g), water (12.68 g) and chloroform (5.75 g) extracts. Solvents (analytical grade) for extraction were obtained from commercial sources (Sigma–Aldrich, Merck).. =:8(*: Methanol Ethyl acetate Acetone Diethyl ether Water Chloroform. 5:0)(*:,80(3(*:0<0:>The antibacterial activity of the extracts methanol, ethyl acetate, acetone, diethyl ether, water and chloroform of " (L.) were determined applying the Kirby-Bayer method [27] or disk method (d=5.5 mm, maximum capacity 10 mg). Organic extracts samples were tested #! against bacterial strains; " " (food isolate), " " (clinical isolate), %! (clinical isolate) and (clinical isolate). Discs were previously wetted with dimethylformamide (DMF) solution of the organic extracts with three different concentrations, 1, 3 and 5 mg/mL and then placed in a Petri dish (d=15 cm). The disks were incubated at 37 0C for 48 h; the control was also maintained with penicillin G dissolved in DMF in a similar manner.. '0,3+ 10.39 4.0 6.64 6.24 12.68 5.75. Extracts of methanol (1, 3 and 5 mg/mL), acetone (1 and 3 mg/mL), diethyl ether (5 mg/mL), chloroform (1 and 3 mg/mL) and water with concentration 5 mg/mL shows antibacterial activities against (Table 2). The extract of methanol with concentration of 5 mg/mL resulted in a lower activity (6 mm) than the penicillin G of the same concentration. The extracts of methanol, acetone and chloroform with concentration of 3 mg/mL have the same inhibition zone as the standard (6 mm). The extracts of methanol, acetone and chloroform with concentration 3 mg/mL created an inhibition zone higher (6 mm) than the penicillin G with the same concentration (4 mm). Other extracts such as ethyl acetate (1, 3 and 5 mg/mL), acetone (5 mg/mL), diethyl ether (1 and 3 mg/mL), water (1 and 3 mg/mL) and chloroform with concentration 5 mg/mL do not create any inhibition zone, in other words they do not show activity (Table 2 and Figure 1).. !#"! !#!! "/,>0,3+96-,=:8(*:9+,80<,+-86473(5: (Table 1). In this study, the antibacterial activity of different extracts of this plant was evaluated on: " " (clinical isolate), . " 5:0)(*:,80(3(*:0<0:0,96- 68.(50*,=:8(*:9 Extract Methanol. Concentration (mg/mL). 1 3 5 Ethyl acetate 1 3 5 Acetone 1 3 5 Diethyl ether 1 3 5 Water 1 3 5 Chloroform 1 3 5 Penicillin 1 3 5 (-) no inhibition zone. Inhibition zones diameters (mm) (c. i.) %! (c. i.) 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 2 6 6 8 10. 3879. " " (f. i.) 6 6 6 6 6 6 6 6 6 6 6 6 4 8 10. " " (c. i.) 6 6 6 6 6 6 6 6 2 6 8.
(49) #". $ . . . !
(50) . . # 5:0)(*:,80(3(*:0<0:>6-+0--,8,5:,=:8(*:6- (.(059:)(*:,80( *3050*(30963(:,. # 5:0)(*:,80(3(*:0<0:>6-+0--,8,5:,=:8(*:6- (.(059:)(*:,80( ! *3050*(30963(:,. The extracts of ethyl acetate, acetone and diethyl ether with concentration of 5 mg/mL (6 mm) resulted in a lower activity against " " (positive Gram bacteria) isolated in the clinical way, than the standard with the same concentration (inhibition zone of 8 mm). The extracts of methanol, ethyl acetate and diethyl ether with concentration of 1 mg/mL resulted in a higher activity (6 mm) than the penicillin G (2 mm). The extracts of ethyl acetate and diethyl ether with concentration of 3 mg/mL have the same inhibition zone as the standard (6 mm). The extracts of ethyl acetate and diethyl ether of the " shows a stronger antibacterial activity to bacteria " " isolated in the clinical way. The other extracts such as methanol (3 and 5 mg/mL), acetone (1 and 3 mg/mL), water and chloroform with concentration 1, 3 and 5 mg/mL do not create any inhibition zone (Table 2 and Figure 3).. The extracts of methanol (3 mg/mL), ethyl acetate, water and diethyl ether with concentration 1, 3 and 5 mg/mL shows antibacterial activity against %! (Table 2). The extracts of ethyl acetate, diethyl ether and water with concentration of 1 mg/mL resulted in a higher activity (6 mm) than the penicillin G (2 mm). The extracts of methanol, ethyl acetate, diethyl ether and water with concentration of 3 mg/mL have the same inhibition zone as the standard (6 mm). The extracts of ethyl acetate, diethyl ether and water with concentration of 5 mg/L (6 mm) resulted in lower activity than the standard penicillin G with the same concentration 5 mg/L (10 mm). The other extracts such as methanol (1 and 5mg/mL), acetone and water with concentration 1, 3 and 5 mg/mL did not create any inhibition zone (Table 2 and Figure 2).. 3880.
(51) #". $ . . . !
(52) . . # 5:0)(*:,80(3(*:0<0:>6-+0--,8,5:,=:8(*:6- (.(059:)(*:,80( *3050*(30963(:,. #
(53) 5:0)(*:,80(3(*:0<0:>6-+0--,8,5:,=:8(*:6- (.(059:)(*:,80( -66+0963(:, The extracts of methanol, ethyl acetate, water and chloroform with concentration of 1 mg/mL created a higher inhibition zone (6 mm) compared to penicillin G (4 mm) with the same concentration to the " " isolated in food. The extracts of ethyl acetate, diethyl ether, water and chloroform with concentration of 3 mg/mL resulted in a lower activity (6 mm) than the standard of the same concentration with inhibition zone of 8 mm. The extracts of water and chloroform showed activity in all the concentrations 1, 3 and 5 mg/mL. The extracts of methanol (3 and 5 mg/mL), ethyl acetate (5 mg/mL), acetone (1 and 3 mg/L) and diethyl ether with concentration 1 mg/mL did not show activity on bacteria " " isolated in food (Table 2 and Figure 4).. eastern part of Kosovo, and extracted with cold solvents: methanol, ethyl acetate, acetone, diethyl ether, water and chloroform. Extracts were prepared with concentration 1, 3 and 5 mg/mL and antibacterial activities were determined by measuring the diameter of inhibition zone against both Gram positive and Gram negative bacteria using the paper agar disc diffusion method. The water extract of " (L.) shows higher antibacterial activities compared with other organic extracts. Results for antibacterial activity obtained from water extracts are logical, based on previous studies where this extract is known for the large amounts of secondary metabolites such as flavonoids and phenols.. #! . !. The antibacterial activity of different extracts of the plant " (L.) was evaluated against a Gram negative bacteria (clinical isolate) and three Gram positive bacteria %! (clinical isolate), " " (food isolate) and " " (clinical isolate). Plant material was collected in. [1] Benedek, B., Rothwangl, K.W., Rozema, E., Gjoncaj, N. and Reznicek, G. (2008) Yarrow ( " L. s.I.). Pharmaceutical quality of commercial samples, Pharmazi. 63, 23-26.. 3881.
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(55) . [14]Gordana, S., Niko, R., Toshihiro, H. and Radosav, P. (2008) In vitro antimicrobial activity of extracts of four species: The composition of # L. (Asteraceae) extract. Journal of Ethnopharmacology. 101, 185190. [15]Elsayed, M. and A. Elshafei, A. (2011) Antimicrobial activity of roselle (Hibiscus sabdariffa) calyces and clove (Syzygiumaromaticum) budswater extracts using different extraction conditions. Advances in Food Sciences. 33, 141–145. [16]Bekkara, F.A., Benhammou, N. and Panovska, T.K. (2008) Biological activities of the essential oil and ethanolic extract of Inulaviscosa from the Tlemcen region of Algeria. Advances in Food Sciences. 30, 132-139. [17]Faiku, F. and Haziri, A. (2013) Total Lipids, Proteins, Minerals and Essential Oils of $ " (L.) Growing Wild in Kosovo. Journal of Pharmaceutical and Phytopharmacological Research. 3, 254-257. [18]Faiku, F., Haziri, A., Gashi, F., Troni, N. and Faiku, H. (2015) Total lipids, proteins, minerals and essential oils of " Arnold and " %# ! growing wild in Kosovo. European Chemical Bulletin. 4, 331-334. [19]Faiku, F. and Haziri, A. (2015) Total lipid, proteins, minerals, essential oils and antioxidant activity of organic extracts of
(56) ! (L.) growing wild in Kosovo. European Chemical Bulletin. 4, 432-435. [20]Faiku, F., Haziri, A., Domozeti, B. and Mehmeti, A. (2012) Total lipids, proteins, minerals and essential oils of " (L.) from south part of Kosova. European Journal of Experimental Biology. 2, 1273-1277. [21]Haziri, A., Aliaga, N., Ismaili, M., Govori, S., Leci, O., Faiku, F., Arapi, A. Haziri, I. (2010) Secondary Metabolites in Essential of " (L.) Growing Wild in East Part of Kosovo. American Journal of Biochemistry and Biotechnology. 6, 32-34. [22]Haziri, A., Faiku, F., Mehmeti, A., Govori ,S., Abazi, S., Daci, M., Haziri, I., Bytyqi-Damoni, A. and Mele, A. (2013) Antimicrobial properties of the essential oil of " " " (L.) growing wild in east part of Kosovo. American Journal of Pharmacology and Toxicology. 8, 128-133. [23]Haziri, A., Govori, S., Ismaili, M., Faiku, F. and Haziri, I. (2009) Essential oil of !" ! " (L.) from east part of Kosova. American Journal of Biochemistry and Biotechnology. 5, 226-228.. [2] Smelcorevic, A., Lamshoeft, M., Radulovic, N., Ilic, D. and Palic, R. (2010) LCMS analysis of the essential oils of " and ! . Chromatographia. 71, 113-116. [3] Baser, K., Demirci, B., Demirci, F., Kocak, S. and Akinci, C. (2002) Composition an antimicrobial activity of the essential oil of "!. Planta Medica. 68, 941-943. [4] Nair, R., Kaalariye, T. and Chanda, S. (2005) Antimicrobial activity of some selected Indian medicinal floraTurkish Journal of Biology. 29, 41- 47. [5] Rasha, N.H. (2011) Antibacterial Activity of Water and Alcoholic Crude Extract of Flower " Rafidain Journal of Science. 22, 11-20. [6] Masumeh, M., Seyedeh, Z.M. and Mohammad, P. (2013) Essential oil composition and antibacterial activity of " L. from different regions in North east of Iran. Journal of Medical Plants Research. 7, 1063-1069. [7] Ates, A. and Erdogrul, O.T. (2003) Antimicrobial activities of various medicinal and commercials plant extracts. Turkish Journal of Biology. 27, 157-162. [8] Eilyad, I., Mohammad, T. and Babak, A. (2012) Antimicrobial effects of yarrow ( ") essential oils against Staphylococcus species. African Journal of Pharmacy and Pharmacology. 6, 2895-2899. [9] Meryem, S., Hatice, Ö., Ahmet, A., Fikrettin, S., Ayfle, A.K., Isa, K. and Medine, G. (2005) Antimicrobial Effects of Verbascumgeorgicum Bentham Extract. Turkish Journal of Biology. 29, 105-110. [10]Candan, F., Unlu, M., Tepe, B., Daferera, D., Pollissiou, M., Sökmen, A., Akpulat, H.A. (2003) Antioxidant and antimicrobial activity of the essential oil and methanol extracts of " subsp.
(57) "Afan. (Asteraceae). Journal of Ethnopharmacology. 87, 215220. [11]Kumar, V.P., Chauhan, N.S., Padh, H. and Rajani, M. (2006) Search for antimicrobial and antifungal agents from selected Indian medicinal plants. Journal of Ethnopharmacology. 107, 182-188. [12]Mathabe, M.C., Nikolova, R.V. and Nyazema N.Z. (2006) Antimicrobial activities of medicinal plants used for the treatment of diarrhea in Limpopo Province, South Africa, Journal of Ethnopharmacology. 107, 286-293. [13]Muller, J.B., Breu, W., Probstle, A. (1994) In vitro inhibition of cyclooxygenase and 5-lipoxygenase by alkamides from Echinacea and species. Planta Medica. 60, 37-40.. 3882.
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(59) . [24]Faiku, F., Haziri, A., Mehmeti, I., Bajrami, D. and Haziri, I. (2016) Evaluation of Antibacterial Activity of Different Solvent Extracts of " !%" (L.) Growing Wild in East Part of Kosovo. The Journal Animal & Plant Sciences. 261486-149. [25]Faiku, F., Haziri, A., Mehmeti, A. and Recica, B. (2017) Antioxidant activity of the organic extracts of "#" (L.) growing wild in Kosovo. Fresen. Environ. Bull. 26, 1440-1446. [26]Xhaxhiu, K., Kllogjeri, A. and Keçi, E. (2013) A study of the inhibitory effect of six essential oils toward Klebsiella pneumoniae. Advances in Food Science. 35, 104-109. [27]Barry, A.L. (1991) Procedure and Theoretical Consideration for Testing Antimicrobial Agents in Agar Media. 5th edition, 53105. Baltimore, MD: William Wilkins Baltimore.. ,*,0<,+ **,7:,+ ! #" 8),5(?080 Faculty of Natural Sciences, Department of Chemistry, University of Prishtina “Hasan Prishtina”, Prishtina – Kosovo e-mail: arbeni77chem@hotmail.com. 3883.
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(64) . . . " # !"! . . ! ! ! !" ! " !" ! %! !! ! ! " "! "! 285*17/.:*874'6&*5./:746 . 1. Ardahan University, Department of Environmental Engineering, 75000, Ardahan, Turkey 2 Ataturk University, Department of Chemical Engineering, 25240 Erzurum, Turkey. ! !. of the most used boron compounds. It is mainly produced from the reaction of colemanite with sulfuric acid according to following reaction [2]: Ca2B6O11.5H2O(s) + 2 H2SO4(aq) + 6 H2O (1) 6 H3BO3(aq) + 2 CaSO4.2H2O(s) Gypsum is formed as a by-product through the reaction. After filtration of gypsum, crystallization of boric acid in high purity and efficiency is very important. Because the sulphuric acid has a strong acid, it dissolves the colemanite together with the other gang minerals in the boron ore, which leads to the product contamination. In this respect, we thought to dissolve colemanite ore with potassium bisulfate. The reaction between colemanite and potassium bisulfate can be given as follows: 2CaO.3B2O3.5H2O(s) + 4KHSO4(aq) + 6H2O(l) → 2(CaSO4.2H2O)(s) + 6H3BO3 (aq)+ 2K2SO4(aq) (2) Various dissolution studies of boron ores in different medium have been found in the literature [3, 10]. In a study [11] done on the extraction of boric acid with nitric acid from colemanite, optimum working conditions were found as reaction temperature: 94 oC, solid-to-liquid ratio: 0.25 g.mL-1, particle size: 2.4 mm, acid concentration: 2.2 M, stirring speed: 500 rpm and reaction time: 11 minutes. Under these optimum conditions, the boric acid extraction efficiency from colemanite was 99.66 %. In another study [12], Taguchi method was used to determine the optimum conditions for the dissolution of Na2O·2CaO·5B2O3·16H2O in NH4Cl solutions and the optimum levels were found to be reaction temperature: 87 oC, solid-to-liquid ratio: 0.05 g.mL-1, NH4Cl concentration: 4 M, particle size: -300+212 mesh, and reaction time: 18 minutes. Under these conditions, the dissolution percentage of boron was found to be 98.37. Although there are many studies on dissolution of boron ores, there has not been any study on optimization of dissolution of colemanite ore in potassium hydrogen sulfate solutions in the literature up to now. Thus, the aim of the present study was to determine the optimum working conditions by using Taguchi approach. Taguchi statistical method developed by Genichi Taguchi to improve the quality of manufac-. The aim of the study was to determine the optimum levels of the parameters for the dissolution of colemanite ore in potassium hydrogen sulfate (KHSO4) solutions in a mechanical agitation system by using Taguchi approach and to declare an alternative reactant to produce boric acid. The investigated parameters and their optimum levels for the dissolution process were determined as: solid-to-liquid ratio: 1/10 g/mL, reaction temperature: 50 oC, particle size: -80 mesh, reaction time: 15 minutes, and stirring speed: 600 rpm. While the solid-to-liquid ratio and particle size had the greatest effect, reaction temperature and stirring speed had virtually less effect on the dissolution process. Under the determined conditions, extraction efficiency of the boron from colemanite ore was 100 %. Because potassium hydrogen sulfate has a less acidic character than sulfuric acid, some useful ways to use it as dissolving agent are as follows: 1) It helps the selective dissolution of boron from colemanite ore 2) It requires cheaper process equipment and 3) Potassium sulfate formed as a by-product in this process can be reacted with the stoichiometric quantities of sulfuric acid to form potassium hydrogen sulfate. This solution can be recycled to dissolution vessel. &$ Colemanite Ore, Taguchi statistical approach, dissolution, potassium hydrogen sulfate. ! "! Turkey has the largest boron reserves in the world. Some of Turkey’s most common commercially boron reserves are colemanite (Ca2B6O11.5H2O), ulexite (NaCaB5O6(OH)6.5H2O), and tincal (Na2B4O7.10H2O). Although the boron is not used directly, its compounds are widely consumed in the production of various materials including glass, fibers, fire retardant materials, catalysis, detergents, etc. [1]. Commercially, boric acid is one. 3884.
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(69) . . . " # !"! . change the settings of the various process parameters (Table 3). The experimental results were evaluated by Taguchi approach which is regarded as the robust parameter design. This method focuses on minimizing variation and/or sensitivity to noise. In robust parameter design, the primary goal is to find factor settings minimizing response variation, while adjusting (or keeping) the process on target. After being determined which factors affect variation, one can try to find settings for controllable factors that will either reduce the variation, make the product insensitive to changes in uncontrollable (noise) factors, or both. A process designed with this goal will produce more consistent output. A product designed with this goal will deliver more consistent performance regardless of the environment in which it is used. In this experimentation, we tried to find an optimal combination of the control factor settings that achieve robustness against noise factors. For this purpose, we used Taguchi’s signal-to-noise ratio(S/N) formula for “the larger the better” criteria. S/N ratio provides a measure of robustness. We graphed the values of S/N ratios vs. the levels of parameters investigated (Fig. 1). By setting those factors at their optimal levels, the process can be made robust to changes in operating and environmental conditions. The formula of the S/N ratio for desired characteristic is;. tured goods, and more recently also applied to, engineering, biotechnology, marketing and advertising [13-17]. There are many ways to design a test and one of them is a full factorial experiment. It is very time-consuming when there are many factors. In order to minimize the number of tests required, fractional factorial experiments (FFEs) were developed. FFEs use only a portion of the total possible combinations to estimate the effects of main factors and the effects of some of the interactions. Taguchi developed a family of FFE matrices which could be utilized in various situations. These matrices reduce the experimental number but still obtain reasonably rich information. The advantage of Taguchi method on the conventional experimental design methods, in addition to keeping the experimental cost at a minimum level, is that it minimizes the variation in product response while keeping the mean response on target. Its other advantage is that the optimum working conditions determined from the laboratory work can also be reproduced in the real production environment [18, 20]. ! ! The colemanite samples used in the experiments were obtained from Eti Mine Company located in Emet town of Kütahya province, Turkey. The sample was crushed, ground and sieved by using ASTM standard sieves to obtain -20, -40, -60, and 80 mesh size fractions. The chemical composition of colemanite ore was given in Table 1. All the other chemicals used in the experiments and analysis were purchased in reagent grade from Merck. The dissolution process of the colemanite ore was carried out in a 250 mL spherical glass reactor equipped with a mechanical stirrer having a digital controller unit. A thermostat for controlling the reaction temperature and a back cooler to avoid the loss of solution by evaporation were used. First, 100 mL of potassium bisulfate solution at 1.5 M concentration was put into the reactor. Then, when the solution reached the desired temperature, the sample was added into the solution while the content of reactor was being stirred. As soon as the process finished, the contents were filtrated, and boron in the solution was analyzed by volumetric method [21]. In order to determine the optimum conditions for the dissolution process, orthogonal array (OA) experimental design was used. The OA designs were balanced, that is, no factor is weighted more or less in an experiment, thus allowing factors to be analyzed independently from each other. The investigated experimental parameters and their levels were given in Table 2. Because it was the most suitable design for the conditions being investigated five parameters, each with four levels were considered, OA16(45) experimental design was conducted to. ⎧1 1 ⎫ / = −10 log ⎨ ∑ 2 ⎬ ⎭ 10 ⎩ . (3). for the n observations y in each trial. When the analysis of some experimental results has indicated the optimal settings for the studied parameters, estimation of the process’s future performance under optimal conditions is usually required. This method suggests an estimation formula based on individual differences between the average of the chosen factor levels and the overall mean. For example, suppose we are interested in estimating the average yield of a process, on the basis of the results of an experimental which indicated that factors A and B were significant with optimal levels A (1) and B (2). The process average under the optimal levels can be estimated by .
(70) (4) where μ = process average, = grand average of all experimental results, β = coefficient of grand average and each parameter ( defined by. 1−. 1 ( , ). ,. ( , )= F- ratio of each parameter. (note that when it is ( ) , then ( ) =. . with. representing the ratio of the sum of squares to the total number of all observations and. 3885. error.
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(75) . . . " # !"! . variance),. 1=. For the evaluation of the effect of each parameter on the optimization criteria, the main effect plots for the S/N ratio have been drown (Fig. 1). These plots show how each factor affects the response characteristic. This criteria is present when different levels of a factor affect the characteristic differently. For a factor with four levels, we may find that one level increases the mean compared to the other levels. We look at the line to determine whether or not an effect is present for a parameter. When the line is horizontal (parallel to the x-axis), then there is no or less effect present. When the line is not horizontal, then there is an effect present. The greater the difference in the vertical position of the plotted points, the greater the magnitude of the main effect. By comparing the slopes of the lines, one can compare the relative magnitude of the factor effects. We try to deduce experimental conditions for graphs given in these figures. Let us look at Figure 1 for reaction temperature (B), which shows variation of the performance statistics with temperature. Now let us try to determine the experimental conditions for the first data point. The reaction temperature for this point is at the first level (50 oC) for this parameter. Now let us look at the Table 3 and find the experiments for the first level of reaction temperature. It is seen from Table 3 that experiments for which column reaction temperature is 1 are the ones with experiment numbers 1,5,9 and 13. The experimental conditions for the second data point thus are the conditions of the experiments for which column reaction temperature is 2, and so on. Optimal levels of these factors are the levels with the maximum performance statistics (S/N), that is, with minimum variability. The optimal levels of these factors are 4,2,4,4, and 4 for solid-to-liquid ratio, reaction temperature, particle size, reaction time, and stirring speed, respectively. Because of the economic factors, we manipulated the second levels of solid-to-liquid ratio and reaction time. The optimum working conditions were determined as solid-to-liquid ratio: 1/10 g/mL, reaction temperature: 50oC, particle size: -80 mesh, reaction time: 15 minutes, and stirring speed: 600. If the experimental plan given in table 3 is studied carefully, it can be seen that 2,2,4,2,4 combination of the factor levels was not one of the 16 combinations tried in experiment. This is to be expected because of the high fractionality of the experimental design used (16 out of 45= 1024 possible combinations). Using Taguchi’s estimation formula based on the level averages (Table 4) and the associated ‘ β coefficients’, an estimate of the performance for μ under the optimal conditions is given by formula (4), which yields. average yield at level (1) and. 2= average yield at level (2) . Clearly, μ is only an estimate of the real process average under the selected conditions. To determine whether results of the confirmation experiments are meaningful or not, the confidence limits for μ must be evaluated. (100 - α) % confidence limits can be obtained using the formula. μ ± F(1, df e ; α ). . -1. (5). , F(1, df e ; α )and represent degrees of freedom at level of α , critical value from where. the F-tables and effective number of replications, respectively. General formula for the effective number of replications is as follows:. =. 1 + ∑ ( ) where. (6). is the size of the experiment and. ∑ () is the total effective number of degrees of freedom. For example, if parameter A is a k-level factor, then = − 1. Always a confirmatory experiment at the determined optimum conditions should be run to check the predicted results. If the predicted results are in good agreement with experimental results, the suggested optimum working conditions will adopt the real conditions. "! " During the dissolution of colemanite in KHSO4 solutions, the reaction can be represented as follows; 4KHSO4(aq.) → 4K+(aq.) + 4HSO4-1(aq.) (7) 4HSO4-1(aq.) + 4H2O(l) ↔ 4H3O+(aq.) + 4SO4-2(aq) (8) 2CaO.3B2O3.5H2O(s) + 4H3O+(aq) → 2Ca+(aq) + 6H3BO3 (aq) (9) + 2H2O(l) 2Ca+2(aq) + 2SO4-2(aq) → 2(CaSO4.2H2O)(s) (10). General reaction is: 2CaO.3B2O3.5H2O(s)+4KHSO4(aq)+6H2O(l) 2(CaSO4.2H2O)(s)+6H3BO3(aq.)+2K2SO4(aq). → (11). In this process KHSO4 can be readily produced by mixing the potassium sulfate formed as a byproduct, with an equivalent number of moles of sulfuric acid, (K2SO4 + H2SO4 → 2KHSO4). The potassium bisulfate can be re-cycled to the dissolution vessel and reacted with colemanite ore to form the corresponding products according to reaction 11. The schema of the process proposed has been given in Figure 2. This dissolution has been performed according to the process conditions given in Tables 2 and 3.. μ = × β ( ) + ( 2 − ) × β ( ) + ( 2 − ) × β ( ) + ( 4 − ) × β ( ) + ( 2 − ) × β () +. ( 4 − ) × β ( ) 3886.
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(80) . . . " # !"! . . (grand average) =84.88 with. we can find. β ( )= 1 −. also from the Table 5,. 1 1 ≅ 1, β ( )=1= 0.93, 675.6 14.6 1 β ( )=1≅ 1,0.985, 301.9 1 β ()=1= 0.99, β ( )=1107.2 1 = 0.99 Therefore, 107.2. β ( )= 1 −. 1 ( ). where ( ). =. . =. 2 (44.92 + .... + 89.91) / 32 = 2716 2 230527 and = 1.94 1.94 1 so β ( )=1≅1 230527. μ = 84,88 × 1 + (87.3 − 84,88) × 1 + (86 − 84,88) × 0.93 + (94 − 84,88) × 1 + (84.12 − 84.88) × 1 +. (90 − 84.88) × 0.98 = 101.7. ! -*0.('/(20325.6.212+24*75*) Component %. CaO 24.42. B2O3 43.52. H2O 18.9. SiO2 and others 13.16. . ! '4'0*6*45'1)6-*.4/*8*/575*).16-**93*4.0*165 Levels. Parameters A B C D E. 1 0.2 50 -20 5 300. Solid-to-liquid ratio (g/mL) Reaction Temperature(oC) Particle size (mesh) Reaction time (min) Stirring Speed (rpm). 2 0.1 60 -40 15 400. 3 0.07 70 -60 25 500. B2O3 extracted (%) 1st trial 2nd trial 44.92 44.46 65.04 64.02 68.28 70.88 87.77 88.45 89.16 90.31 80.04 81.18 87.55 90.71 87.77 91.37 94.81 93.52 98.10 99.46 82.05 82.73 78.84 80.55 100 99.99 100 99.92 99.69 99.22 85.34 89.91 Grand average. Mean 44.69 64.53 69.58 88.11 89.74 80.61 89.13 89.57 94.17 98.78 82.39 79.70 100 99.96 99.46 87.63 84.88. 4 0.05 80 -80 35 600. ! 93*4.0*16'/)*5.,175*). Exp No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16. A 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4. Parameters and Levels B C D E 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 1 2 3 4 2 1 4 3 3 4 1 2 4 3 2 1 1 3 4 2 2 4 3 1 3 1 2 4 4 2 1 3 1 4 2 3 2 3 1 4 3 2 4 1 4 1 3 2. 3887. S/N 33 36.1 36.8 38.9 39.0 38.1 38.9 39.0 39.4 39.8 38.3 38.0 39.9 39.9 39.9 38.8.
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(85) . . . " # !"! . . " '.1++*(65 /26+24 '6.25 . " (-*0'2+6-*342(*55342325*) ! *8*/'8*4',*5+246-*).552/76.21342(*55 . the confidence limits on the above estimate can be calculated using formula (4) and (5). μ ± F(1, df e ; α ). . -1 where . =1.94. (1, ;α ). and. =. =. Levels 1 2 3 4. (1,16;5%) = 4.49. 18 =2 1+ 2 + 2 + 2 + 2. μ ± F(1, df e ; α ). . -1. A 66.73 87.26 88.76 96.76. B 82.15 85.97 85.14 86.25. C 73.83 83.35 88.32 94.00. D 78.37 84.12 86.43 90.59. E 83.12 83.86 82.47 90.05. !
(86) #'1'/:5.5+24 *964'(6.21. =. μ ± 4.49 × 1.94 × 2 −1. = μ ± 2.09 Therefore, a 95 % confidence interval for dissolution process was given by 101.7±2.09, that was anything from 99.61 % to 100 %. To test the predicted results, confirmation experiments were carried out at optimum working conditions. The boric acid extraction obtained from confirmation experiment was 100 %. This value was acceptable within the calculated confidence interval, it could be said that experimental results were in good agreement with predicted results within ± 5% in error.. A B C D E. 3888. Source Solid-to-liquid ratio Reaction Temperature Particle size Reaction time Stirring speed Error Total. DF. SS. MSS. F-ratio. 3. 3930.6. 1310.2. 675.6. 3. 84.8. 28.3. 14.6. 3 3 3 16 31. 1756.2 623.4 293.2 31.0 6719.2. 585.4 207.8 97.7 1.9. 301.9 107.2 50.4.
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(91) . . . " # !"! . " The aim of the study was to determine the optimum dissolution conditions of colemanite ore in potassium hydrogen sulfate solutions and to declare an alternative reactant to produce boric acid. Based on the results obtained in this research, the major conclusions derived from the present work were as follows: • In this study, Taguchi Method assisted the determination of the optimum working conditions for the dissolution of colemanite in KHSO4 solutions. The optimum values of parameters were determined as solid-to-liquid ratio: 1/10 g/mL, reaction temperature: 50oC, particle size: -80 mesh, reaction time: 15 minutes, and stirring speed: 600 rpm. Under these optimum conditions, boric acid extraction from colemanite ore was 100%. • The performance measures and ANOVA analysis on the boric acid extraction indicated that the significance order of the parameters were solidto-liquid ratio, particle size, reaction time, stirring speed, and reaction temperature, respectively. • Since H2SO4 is a strong mineral acid, it also dissolves other gang minerals besides boron in the ore. This leads the contamination in the final product. But KHSO4 is much weaker than the sulfuric acid, this reactant helps the selective dissolution of boron compounds from other gang minerals. • KHSO4 can be readily produced by mixing the potassium sulfate formed as a by-product, with an equivalent number of moles of sulfuric acid and this solution can be recycled to the dissolution vessel. • Using KHSO4 as a dissolving reactant also has an advantage in terms of preservation of device corrosion. [1] Garrett, D.E. (1998) Borates. Academic Press. San Diego, CA., 401-405. [2] Çetin, E., Eroğlu, İ., Özkar, S. (2001) Kinetics of Gypsum Formation and Growth During the Dissolution of Coleminite in Sulfuric Acid. J. Cryst. Growth. 231, 559-567. [3] Ceyhun, I., Kocakerim, M.M., Saraç, H., Çolak, S. (1999) Dissolution Kinetics of Colemanite in Chlorine Saturated Water. Theor. Found. Chem. Eng. 33(3), 253-257. [4] Davies, T.W., Çolak, S., Hooper, R.M. (1991) Boric Acid Production by the Calcination and Leaching of Powdered Colemanite. Powder Technol. 65, 433-440. [5] Guliyev, R., Kuslu, S., Calban, T., Colak, S., (2012) Leaching Kinetics of Colemanite in Potassium Hydrogen Sulphate Solutions. J. Ind. and Eng. Chem. 18(1), 38-44.. [6] Imamutdinova, V.M. (1967) Rates of Dissolution of Native Borates in H3PO4 Solutions. Zh. Prikl. Khim.40, 2596-2598. [7] Kocakerim, M.M., Alkan, M. (1998) Dissolution Kinetics of Colemanite in SO2-Saturated Water. Hydrometallurgy. 19, 385-392. [8] Mergen, A., Demirhan, M.H. (2009) Dissolution Kinetics of Probertite in Boric Acid Solution. Int. J. Miner. Process. 90, 16-20. [9] Temur, H., Yartaşı, A., Çopur, M., Kocakerim, M.M. (2000) The Kinetics of Dissolution of Colemanite in H3PO4 Solutions. Ind. Eng. Chem. Res.39(11), 4114-4119. [10]Yesilyurt, M., Çolak, S., Çalban, T. and Genel, Y. (2005) Determination of the Optimum Conditions for the Dissolution of Colemanite in H3PO4 Solutions. Ind. Eng. Chem. Res44(10), 3761-3765. [11]Yesilyurt, M. (2004) Determination of the Optimum Conditions for Boric Acid Extraction from Colemanite Ore in HNO3 Solutions. Chem. Eng. Process. 43(10), 1189-1194. [12]Küçük, Ö. (2006) Application of Taguchi Method in the Optimization of Dissolution of Ulexite in NH4Cl Solutions. Korean J. Chem. Eng. 23(1), 21-27. [13]Abalı, Y., Çolak, S., Yapıcı, S. (1997) The Optimization of the Dissolution of Phosphate Rock with Cl2-SO2 Gas Mixtures in Aqueous Medium. Hydrometallurgy. 46, 27-35. [14]Bese, A.V., Borulu, N., Çopur, M., Çolak, S., Ata, O.N. (2010), Optimization of Dissolution of Metals from Waelz Sintering Waste (WSW) by Hydrochloric Acid Solutions. Chem. Eng. J. 162(2), 718-722. [15]Çopur, M., Pekdemir, T., Çelik, C., Çolak, S., (1997) Determination of the Optimum Conditions for the Dissolution of Stibnite in HCl Solutions. Ind. Eng. Chem. Res.36(3), 682-687. [16]Rao, R.S., Kumar, C.G., Prakasham, R.S., Hobbs, P.J., (2008) Taguchi Methodology as A Statistical Tool for Biotechnological Applications: A critical Appraisal. J. Biotechnol. 3(4), 510-523. [17]Rosa, J.L., Robin, A., Silva, M.B., Baldan, C.A., Peres, M.P. (2009) Electrodeposition of Copper on Titanium Wires: Taguchi Experimental Design Approach. Journal Mater. Process. Technol. 209(3), 1181-1188. [18]Logothetis, N. (1992) Managing for Total Quality from Deming to Taguchi and SPC. Prentice Hall. Englewood Cliffs, NJ., 145-168. [19]Ross, P.J. (1987) Taguchi Techniques for Quality Engineering. McGraw-Hill, New York, 98123. [20]Roy, R. (1990) A Primer on Taguchi Methods. Van Nostrand Reinhold, New York, 65-78.. 3889.
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(96) . . . " # !"! . [21]Greenberg, A.E., Trussell, R.R., Clesceri, L.S., (1985) Standard Methods for the Examination of Water and wastewater. American Public Health Association. Washington, DC, 415-422.. *(*.8*) ((*36*) . . "! 74'6&*5./:746 Atatürk University Engineering Faculty Chemical Engineering Department 25240, Erzurum – Turkey e-mail: myesilyurt@hotmail.com. 3890.
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(100) . . . " # !"! . . $ : # ! ! # -0%08%0645%*%6.,%0 )(%5%8+646984603+)0) . 2. 1 Faculty of Education, Kirikkale University, Kirikkale, 71450 Turkey, Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Kirikkale University, Kirikkale, 71450 Turkey 3 Faculty of Science and Literature, Department of Biology, Kirikkale University, Kirikkale, 71450 Turkey. . respiratory tract infections), or transmitted by direct contact with contaminated pools or fields (sepsis, leptospirosis, tetanus), or by indirect contact with contaminated equipment, towels and clothes (herpes, fungal infections) [3]. Especially skin infections caused by direct contact, blood-borne infections, epidemics that can happen during organizations in which athletes stay together and infections that may happen after injuries pose a risk for athletes. Considering the infections that may happen during sports such as bacterial skin and soft tissue, bone infections, environmental contamination poses a special risk. For instance, erysipelas, which is a skin infection, is transmitted by a person’s contacting the infected area by hand. # $*# ! is generally found in lakes, rivers and soil and causes infection by entering through a laceration area while a person is swimming [4]. In previous studies, it was reported that there were many sport injuries that came up in international organizations like world championships and Olympic Games. According to the data from Helsinki 2012 European Athletics Championship, there were 133 injury cases in total5. In a study in which FIFA world championships between 2002-2010 were examined, especially fouls were reported as the most important risk factor for the potential injuries [5]. Infections after such injuries inevitably develop. Factors of infections that can occur after sport injuries can be expected to be transmitted through direct contact with such areas [6]. Sport health comes up as a result of sports branches such as judo, wrestling, football, rugby which involve direct contact with the opponent and involves direct contact that may result in injuries and may cause injuries. Collins et al. explored the epidemics that occurred in sport branches like these which involves competition between 2005-2010 and reported that the most frequent epidemic was skin and soft tissue infection epidemics and %!* &$&#&$ (33%) and fungus (29%) are the most frequent causes of them [7].
(101) #!$ % #& caused by herpes simplex virus is the primary microorganism that leads to sport infections. It was reported to be correlated with. The aim of this study was to determine the microorganisms in playgrounds and sport complexes and to offer solutions for prevention methods. For this reason, equipment used by many people and toys in the playgrounds, especially the parts that handled and contacting to body, and swimming pools were preferred. The samples were put into bloody EMB and Sabouraud Medium, waited in 37 degree incubator and they were evaluated after 24, 48 and 72 hours. As a result of the study 218 (77,03 %) microorganisms were reproduced (217 bacteria and 1 fungus). The surfaces that bacteria were obtained from: 50 from plastic surfaces, 46 from ceramic surfaces, 43 from rubber surfaces, 31 from metallic surfaces, 25 from wooden surfaces, 17 from swimming pools, and 6 from others. 175 (80,64 %) reproduced bacteria were specified as human pathogen. The bacteria that reproduced the most were %!* &$ $$$! $(17). As a group, the bacteria group that reproduced the most was again $%!* &$ (67). Cleaning these areas regularly and inspecting them are very important in terms of infection risk. While doing sport personal precautions like wearing gloves should be considered in order to be protected from such kind of infections. #" Sport Facilities, playground, hygiene, Kırıkkale, Gram positive bacteria, Gram negative bacteria. ! Sport activities are important in terms of a healthy life. Especially in diseases such as coronary artery, obesity, hyperglycemia, diabetes they were reported to have several benefits [1, 2]. Although they are important for a healthy life, there is the probability of occurrence of a variety of illnesses throughout the sport activities. That is why sport health has gained currency. Among these diseases there are contagious infections that can be transmitted by the people contacted during sport (HBV, HIV,. 3891.
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(105) . . . " # !"! . %/2.-0+1*4%/2.)4Samples were collected from various sports facilities, playgrounds, swimming pools and schools in Kırıkkale. Samples are taken particularly from the areas where people have contact with. For this reason, especially the handheld and bodily contacted parts of multiple-user sports equipment and toys at the playgrounds and the waters of swimming pools were preferred. All the samples were transported under refrigerated conditions into the Infection Diseases and Clinical Microbiology Laboratory, Faculty of Medicine, Kırıkkale University and analyzed within the same day of sampling.. especially rugby in which athletes have direct contact frequently. It was also reported that sports equipment could be the cause of contagion. %!* &$ %#!% &$ and $& $ that are present at especially sports fields and sports equipment after sport injuries were reported to have a place in sport injuries. Also, particularly in sports competitions like box, taekwondo and judo, since both athletes have bleedings, blood-borne infections such as HBV and HIV pose a risk [8]. The bacteria isolated from skin and soft tissue infections, %!* &$&#&$ being in the first place, are generally gram positive bacteria. Other frequent gram positive bacteria are group A $%#!% &$, group B $%#!% &s, viridans $%#!% &$and %# &$ $ Less frequently isolated bacteria are gram negative bacteria such as %# %#,
(106) & +$%&# & % , #& $ and % %#$[4]. The microorganisms isolated from bone infections are no different than the ones from skin and soft tissue infections. In their study, Prieto-Pérez et al., similarly, reported %!* &$ &#&$ as the most frequent microorganism they isolated. Apart from this, they reported that they isolated gram positive cocci like coagulase negative staphylococcus and also gram negative bacillary in small quantities. The bone infections caused by these microorganisms are quite difficult to treat. Occasionally, surgical interventions as serious as amputations are necessary. 53, 84 % of the patients involved in the same study and who had acute osteomyelitis were reported to require surgical intervention [9]. Our study has been aimed to determine the microorganisms available in playgrounds and sport complexes that are harmful for human health and offer solutions and prevention methods.. -'31&-1.1+-'%. %0%.84-4 Blood EMB and Sabouraud agar were used for the cultivation of samples. The samples that are kept at 37 °C in the incubator were evaluated at 24th, 48th, and 72nd hours. The ones reproduced were put into process. The ones that did not reproduce were discarded after 72 hours. Every colony detected in agar were evaluated. Gram staining was applied to each microorganism. Microorganisms were specified as gram positive, gram negative and fungus. The specified factors were identified by using Vitek 2 (Biomerieux, France) device and GP, GN, YST cards. ! ! 283 samples were collected in total. While collecting these samples the parts that might be in contact with people’s bodies were preferred. Surfaces were chosen mostly among the hand contact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