This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANFIS technique were embedded in a new fuzzy inference system to simultaneously encompass the impact of temperature and pH level on the activity of β-glucosidase. The required base rules for the developed fuzzy inference system were created to describe the antecedent (pH and temperature) implication to the consequent (enzyme activity), using the singleton Sugeno fuzzy inference technique. The simulation results from the developed models achieved high accuracy. The neuro-fuzzy approach performed very well in predicting β-glucosidase activity through comparative analysis. The proposed approach may be used to predict enzyme kinetics for several nonlinear biosynthetic processes.
In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit
... Show MoreIn this research , phthallic anhydride ring is opened with 4-methyl aniline and acetone as a solvent to results the compound [I] that reacted with dimethyl sulphate and anhydrous sodium carbonate formation to phathalate ester [II], while the acid hydrazide compound [III], was obtained from mixed the compound [II]with hydrazine hydrate, Synthesis four type of shiff bases[IV]a-d was synthesized from the reaction of acid hydrazide [III] with aromatic aldehyde or ketone , when reacted Shiff bases with phthalic anhydride or naphthalicanhydride,I get eight derivatives of oxazepine [V]a-d , [VI]a-d. The bacterial activity of the new compounds studied by four species of bacteria: Esherichia Coli, Enterobactecloacae (Gram negative) and staphylococcu
... Show MoreBackground: Isoxazoles are an important class of five-membered unsaturated heterocyclic compounds. They show several applications in diverse areas such as pharmaceuticals, agrochemistry and industry. Isoxazoles are also found in natural sources showing insecticidal, plant growth regulation and pigment functions. Current study was conducted for synthesis of twenty five new Isoxazole derivatives and to evaluate the in vitro antibacterial activities of these derivatives. Methods: Benzaldoxime and their substituted [I] ae were prepared via addition-elimination reactions between aromatic aldehyde and hydroxylamine hydrochloride. In a second step, para-or meta-substituted benzaldoximes [I] ae were reacted with N-chlorosucceinimide in DMF to yield
... Show MoreThis research was aimed to the purification and characterization of cytosine deaminase as a medically important enzyme from locally isolated Escherichia coli; then studying its cytotoxic anticancer effects against colon cancer cell line. Cytosine deaminase was subjected to three purification steps including precipitation with 90% ammonium sulfate saturation, ion exchange chromatography on DEAE-cellulose column, and gel filtration chromatography throughout Sephadex G-200 column. Specific activity of the purified enzyme was increased up to 9 U/mg with 12.85 folds of purification and 30.85% enzyme recovery. Characterization study of purified enzyme revealed that the molecular weight of cytosine deaminase produced by E. coli was about 48 KDa,
... Show MoreThe formation and structural investigation of three new Mannich bases are reported. The synthesis of these compounds was accomplished via a multicomponent one-pot reaction using CaCl2 as a catalyst. The reaction of the benzaldehyde, m-bromoaniline and cyclohexanone or 4-methylcyclohexanone resulted in the formation of L1 and L3, respectively. The synthesis of L2 was achieved by mixing benzaldehyde, o-bromoaniline and cyclohexanone. The isolated compounds were characterised using a range of analytical and spectroscopic techniques. These include; NMR (1H and 13C-NMR), ESMS, FTIR, electronic spectroscopy, microanalyses and melting points. The NMR data for L1 and L2 indicated the presence of one isomer in solutions, on the NMR time scale. How
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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