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    Combined effects of some chemicals on ?-galactosidase activity using a new semiparametric errors in variables model
    (Banats Univ Agricultural Sciences & Veterinary Medicine Timisoara, 2019) Yalaz, Secil; Matpan Bekler, Fatma; Acer, Omer
    The combined effects of some chemicals on beta-galactosidase activity by Anoxybacillus sp. FMB1 were studied using semiparametric errors in variables methodology when the error has an unknown distribution. An experimental design was chosen to explain six chemicals, dithiothreitol (DTT), phenylmethylsulfonyl fluoride (PMSF), N-ethylmaleimide (NEM), iodoacetamide (lod A), beta-Mercaptoethanol (beta-Mer) and 1,10-phenanthroline (phen) and to investigate the results. This technique constrained the number of real experiments performed while considering conceivable interactions between six chemicals. The optimal combinations of chemical concentration for maximum beta-galactosidase activity was determined as 8 mM DTT, 8 mM PMSF, 8 mM NEM, 8 mM lod A, 2 mM beta-Mer and 2 mM phen. We also compared the no measurement error case and errors in variables case. The proposed estimator shown has better performances.
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    Evaluation of antibacterial effects of some traditional plants against pathogen microorganisms
    (Banats Univ Agricultural Sciences & Veterinary Medicine Timisoara, 2020) Guven, Kemal; Matpan Bekler, Fatma; Yalaz, Secil; Gul Guven, Reyhan; Demirtas Aksu, Merve; Ipekci, Mert; Tusar, Firdevs Rozan
    Antimicrobial resistance has been an increasing problem in public health around the world. Natural plants can be utilised as an important source for antimicrobial agents to be used in place of synthetic drugs due to their costs and side effects. Thus, it is essential to find out new, effective, safer natural antimicrobial products. In the present study, in vitro antibacterial activities of different traditional plants against pathogen microorganisms were tested. The extracts of all plants were prepared in four different solvents (ethanolic, methanolic, hexane and aqueous) and then used for disc-diffusion method. Each assay was repeated in triplicate. The analysis was carried out using two-way analysis of variance (ANOVA). The highest antimicrobial activities were obtained by methanolic extracts of Sorbus domestica against E. coli, while Methanolic Extracts of Epilobium angustifolium were effective against Staphylococcus aureus, Klebsiella pneumoniae and Pseudomonas aeruginosa. In addition, Hexanic Extract of Tragacanth gum and S. domestica had high antibacterial activity against K. pneumoniae and P. aeruginosa, respectively.
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    Kernel estimator and predictor of partially linear mixed-effect errors-in-variables model
    (Taylor & Francis Ltd, 2021) Yalaz, Secil; Kuran, Ozge
    This paper considers the partially linear mixed-effect model relating a response Y to predictors (X, Z, T) with mean function X-T beta + Z(T)b + g(T) which is a combination of the linear mixed-effect model and the nonparametric smooth function. The proposed model contains an additive measurement error in X. Taavoni and Arashi (Kernel estimation in semiparametric mixed-effect longitudinal modelling. Statist Papers. 2019. Available from: https://doi.org/10.1007/s00362019-01125-8.) approximated the nonparametric function by the profile kernel method, and made use of the weighted least squares to estimate the regression coefficients when measurement error was ignored. We derive a simple modification of their estimators by correction for attenuation stems from measurement error and demonstrate that the linear parts estimator is asymptotically normal.
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    Molecular characterisation and numerical analysis of novel moderately thermophile Anoxybacillus sp. FMB1
    (Ars Docendi, 2018) Bekler, Fatma Matpan; Yalaz, Secil; Guven, Kemal
    A moderately thermophilic bacteria was isolated from the water sample collected from Yozgat, in the Central Anatolia Region of Turkey. Morphological, physiological and biochemical characteristics of thermophilic isolate were determined in comparison to standard type strains, and they were all identified and classified into homogenous groups by using fundamental principles of numerical taxonomy. The UPGMA method was used for numerical taxonomy and the phenogram was drawn with MATLAB. Phylogenetic analyses were also performed by the neighbour-joining and UPGMA methods. According to the numerical definition result and 16S rRNA analysis, the strain FMB1 was most closely related to Anoxybacillus ayderensis AB04(T). The results showed that MATLAB computer program using UPGMA method can be used as an alternative or additional method in bacterial classification, before 16S rRNA analysis performed.
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    Multivariate partially linear regression in the presence of measurement error
    (Springer, 2019) Yalaz, Secil
    In this paper, multivariate partially linear model with error in the explanatory variable of nonparametric part, where the response variable is m dimensional, is considered. By modification of local-likelihood method, an estimator of parametric part is driven. Moreover, the asymptotic normality of the generalized least square estimator of the parametric component is investigated when the error distribution function is either ordinarily smooth or super smooth. Applications in the Engel curves are discussed and through Monte Carlo experiments performances of n are investigated.
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    A new kernel two-parameter prediction under multicollinearity in partially linear mixed measurement error model
    (Taylor & Francis Ltd, 2024) Yalaz, Secil; Kuran, Ozge
    A Partially linear mixed effects model relating a response Y to predictors $ (X,Z,T) $ (X,Z,T) with the mean function $ X<^>{T}\beta +Zb+g(T) $ XT beta+Zb+g(T) is considered in this paper. When the parametric parts' variable X are measured with additive error and there is ill-conditioned data suffering from multicollinearity, a new kernel two-parameter prediction method using the kernel ridge and Liu regression approach is suggested. The kernel two parameter estimator of beta and the predictor of b are derived by modifying the likelihood and Henderson methods. Matrix mean square error comparisons are calculated. We also demonstrate that under suitable conditions, the resulting estimator of beta is asymptotically normal. The situation with an unknown measurement error covariance matrix is handled. A Monte Carlo simulation study, together with an earthquake data example, is compiled to evaluate the effectiveness of the proposed approach at the end of the paper.
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    PURIFICATION OF THERMOSTABLE ?-GALACTOSIDASE FROM ANOXYBACILLUS SP KP1 AND ESTIMATION OF COMBINED EFFECT OF SOME CHEMICALS ON ENZYME ACTIVITY USING SEMIPARAMETRIC ERRORS IN VARIABLES MODEL
    (Parlar Scientific Publications (P S P), 2017) Bekler, Fatma Matpan; Yalaz, Secil; Acer, Omer; Guven, Kemal
    The thermostable beta-galactosidase from thermophilic Anoxybacillus sp. KP1 was partially purified by Sephadex G-75 gel permeation chromatography with a fold purification of 14.4 and a yield of 11.8%, respectively. The optimal activity of purified beta-galactosidase was pH 9.0 and a temperature of 60 degrees C. The enzyme was stable at pH 9.0. Thermostability of the enzyme was also 60 degrees C. The molecular weight of the enzyme was determined as 68 kDa by SDS-PAGE. The partially purified thermostable alkaline beta-galactosidase was significantly inhibited by various divalent cations, including Hg2+ and Cu2+ while Ca2+ and Mg2+ ions activated the enzyme activity. The combined effects of some chemicals on beta-galactosidase activity by Anoxybacillus sp. KP1 were studied using semiparametric errors in variables methodology. The optimal combinations of chemicals concen-tration for maximum beta-galactosidase activity was determined as 4 mM DTT, 4 mM PMSF, 4 mM NEM, 4 mM Iod A, 4 mM beta-Mer and 10 mM phen.