Synthetic dye decolorization by three sources of fungal laccase

Decolorization of six synthetic dyes using three sources of fungal laccase with the origin of Aspergillus oryzae, Trametes versicolor, and Paraconiothyrium variabile was investigated. Among them, the enzyme from P. variabile was the most efficient which decolorized bromophenol blue (100%), commassie brilliant blue (91%), panseu-S (56%), Rimazol brilliant blue R (RBBR; 47%), Congo red (18.5%), and methylene blue (21.3%) after 3 h incubation in presence of hydroxybenzotriazole (HBT; 5 mM) as the laccase mediator. It was also observed that decolorization efficiency of all dyes was enhanced by increasing of HBT concentration from 0.1 mM to 5 mM. Laccase from A. oryzae was able to remove 53% of methylene blue and 26% of RBBR after 30 min incubation in absence of HBT, but the enzyme could not efficiently decolorize other dyes even in presence of 5 mM of HBT. In the case of laccase from T. versicolor, only RBBR was decolorized (93%) in absence of HBT after 3 h incubation. © 2012 Forootanfar et al.; licensee BioMed Central Ltd

An evolutionary approach to modelling concrete degradation due to sulphuric acid attack

Concrete corrosion due to sulphuric acid attack is known to be one of the main contributory factors for degradation of concrete sewer pipes. This paper proposes to use a novel data mining technique, namely, evolutionary polynomial regression (EPR), to predict degradation of concrete subject to sulphuric acid attack. A comprehensive dataset from literature is collected to train and develop an EPR model for this purpose. The results show that the EPR model can successfully predict mass loss of concrete specimens exposed to sulphuric acid. Parametric studies show that the proposed model is capable of representing the degree to which individual contributing parameters can affect the degradation of concrete. The developed EPR model is compared with a model based on artificial neural network (ANN) and the advantageous of the EPR approach over ANN is highlighted. In addition, based on the developed EPR model and using an optimisation technique, the optimum concrete mixture to provide maximum resistance against sulphuric acid attack has been identified

Halotolerant Ability and α-Amylase Activity of Some Saltwater Fungal Isolates

Four halotolerant fungal isolates originating from the saltwater Lake Urmia in Iran were selected during a screening program for salt resistance and α-amylase activity. The isolates were identified based on sequencing the ITS region and a part of the β-tubulin gene, as Penicillium chrysogenum (isolate U1; CBS 132820), Fusarium incarnatum (isolate U2; CBS 132821), and Penicillium polonicum (isolate U3; CBS 132822, and isolate U4; CBS 132823). The growth of these isolates was determined by measuring the colony diameter and mycelia dry weight in Sabouraud dextrose agar and yeast nitrogen base medium supplemented with NaCl, KCl, and LiCl. Isolate U4 showed a growth up in 15% NaCl and U1 was the only isolate that could grow in 20% KCl. None of the strains grew in a media containing LiCl. The salt supplemented medium did not increase the size of colony diameter in all isolates (p > 0.05). The ability of the selected isolates for amylase production was quantitatively tested and showed that P. polonicum isolate U4 was the most potent producer of amylase with a yield of 260.9 U/L after 60 h, whereas P. polonicum isolate U3 was the lowest one with a production level of 97.9 U/L after 48 h. P. polonicum isolate U4 could be a suitable candidate for production of amylase on an industrial scale after optimization. © 2013 by School of Pharmacy

Size-dependent compressive strength properties of hard rocks and rock-like cementitious brittle materials

Rock engineering projects have always been constructed on different (from micro to macro) scales. This makes understanding rock behaviour at different scales essential. In previous statistical studies on igneous hard rocks, the correlation of uniaxial compressive strength (UCS) values in different diameters with estimations of specimen size effect models was weak. In view of this knowledge gap, the present research proposed a model of appropriate size effect in igneous hard rocks. This research also aimed at discussing the effect of specimen size and grain size on the UCS of concrete specimens. To achieve these aims, studies were conducted in parallel on the previous and new experimental data. Non-linear regression analysis on igneous hard rocks indicated that there is a better agreement between the outputs of the multi-fractal scaling model and the specimen size effect model using the fracture energy theory and the results of previous laboratory tests. In addition, in the experimental study, the grain size effect on the predictions of specimen size effect models was exhibited. The results of this research can be used for designing engineering projects at different scales

Effects of exercise on physical fitness and blood factors of addicted persons who have quitted drugs for two months.

BANITALEBI, E.; FARAMARZI, M.; NURI, R.; KHOSROZADEH, J.; GHAFOORIAN, M. Effect of exercise training on health-related physical fitness factors and blood lipids profile of former addicted persons. Brazilian Journal of Biomotricity, v. 4, n. 3, p. 190-197, 2010. Dysfunctional eating patterns and excessive weight gains have been observed during recovery from drug and alcohol addictions. The purpose of this study was to determine the effect of exercise training on health-related physical fitness factors and blood lipids profile of former addicted persons. Thirty seven males who were 23-49 years old, and had one-year quitting history were selected and randomized (exercise group, n= 18 and control, n= 19). Thirty eight individuals completed the entire study; 16 persons were in exercise group and 15 persons were in control group. Exercise training was consisted primarily of some game-based aerobic exercise. Exercise training duration progressed from 20 minutes at the baseline to 45 minutes at the end of weeks 12th, and intensity of exercise progressed from 50% of heart rate reserve of baseline to 70 % at 12 weeks. Weight, BMI and WHR were measured. Muscle endurance, flexibility and Vo2Peak were measured using by pull up, Sit -and -Rich test and one-mile Rockport walk test, respectively. Body composition was assessed using the sum of three skin-fold measurement specific for males (chest, abdomen, and tight). Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) were measured enzymatically using diagnostic Pars kits. All variables were measured at baseline. Data analyzed by using ANCOVA analysis. There were no significant differences in weight (p=0.208), BMI (P=0.2631), CT (P=0.428), HDL (0.833), LDL (0.396), VLDL (P=0.169), TG (P=0.283), Vo2peak (p=0.884), flexibility (P=0.923) and Pull-up (P=0.44) after 12 weeks exercise training between two groups, but there was significant difference in WHR (p=0.044). It appears that, exercise training can prevent weight gain after quitting drugs and substances

Artificial neural network for non-intrusive electrical energy monitoring system

This paper discusses non-intrusive electrical energy monitoring (NIEM) system in an effort to minimize electrical energy wastages. To realize the system, an energy meter is used to measure the electrical consumption by electrical appliances. The obtained data were analyzed using a method called multilayer perceptron (MLP) technique of artificial neural network (ANN). The event detection was implemented to identify the type of loads and the power consumption of the load which were identified as fan and lamp. The switching ON and OFF output events of the loads were inputted to MLP in order to test the capability of MLP in classifying the type of loads. The data were divided to 70% for training, 15% for testing, and 15% for validation. The output of the MLP is either ‘1’ for fan or ‘0’ for lamp. In conclusion, MLP with five hidden neurons results obtained the lowest average training time with 2.699 seconds, a small number of epochs with 62 iterations, a min square error of 7.3872×10-5, and a high regression coefficient of 0.99050

Effects of β -hydroxy- β -methylbutyrate on kidney parameters and body composition in untrained males after 8 weeks combination resistance training

زمینه و هدف: مطالعات علمی دقیق در مورد بی خطر بودن بتاهیدروکسی بتامتیلبوتیرات (HMB) در انسان تاکنون انجام نشده است و تنها مطالعات اندکی در مورد تاثیر این مکمل بر شاخص های مرتبط با سلامت در حیوانات انجام شده است. این مطالعه با هدف بررسی تاثیر 8 هفته تمرین مقاومتی به همراه مصرف مکمل بتا- هیدروکسی بتا- متیل بوتیرات (HMB) بر شاخص های کارکرد کلیوی و ترکیب بدنی مردان غیر ورزشکار انجام شد. روش بررسی: در این کارآزمایی بالینی 24 دانشجوی پسر غیر ورزشکار انتخاب و به صورت تصادفی به دو گروه کنترل (دارو نما، 14نفر) و تجربی (مکمل، 10 نفر) تقسیم شدند. هر دو گروه 8 هفته تمرین مقاومتی را به صورت 3 جلسه در هفته، اجرا کردند. از آزمودنی ها یک روز قبل و 2 روز بعد از برنامه تمرینی، نمونه خون و ادرار در حالت ناشتا گرفته شد و برای تمام نمونه ها اوره و کراتینین اندازه گیری و میزان فیلتراسیون گلومرولی نیز محاسبه گردید. ترکیب بدنی، وزن آزمودنی ها و قدرت بالا تنه و پایین تنه اندازه گیری شد. تجزیه و تحلیل داده ها با استفاده از آزمون های آماری t زوجی و t مستقل انجام گرفت. یافته ها: گروه مکمل افزایش معنادار در توده خالص بدنی (002/0P=) و کاهش معناداری در توده چربی بدن (006/0P=) داشت. همچنین، مکمل سبب کاهش معنادار غلظت ازت اوره ادرار (036/0P=) شد ولی تاثیر معناداری بر غلظت ازت اوره خون، کراتینین خون، کراتینین ادرار و میزان فیلتراسیون گلومرولی نداشت. نتیجه گیری: مصرف مکمل بتا- هیدروکسی بتا- متیل بوتیرات باعث افزایش توده خالص بدنی و قدرت یک تکرار بیشینه و کاهش چربی بدن در افراد غیر ورزشکار می شود. ولی تاثیر زیان آوری بر عملکرد کلیوی در مدت مصرف شده در این مطالعه ندارد

Gas bubbles investigation in contaminated water using optical tomography based on independent component analysis method

This paper presents the results of concentration profiles for gas bubble flow in a vertical pipeline containing contaminated water using an optical tomography system. The concentration profiles for the bubble flow quantities are investigated under five different flows conditions, a single bubble, double bubbles, 25% of air opening, 50% of air opening, and 100% of air opening flow rates where a valve is used to control the gas flow in the vertical pipeline. The system is aided by the independent component analysis (ICA) algorithm to reconstruct the concentration profiles of the liquid-gas flow. The behaviour of the gas bubbles was investigated in contaminated water in which the water sample was prepared by adding 25 mL of colour ingredients to 3 liters of pure water. The result shows that the application of ICA has enabled the system to detect the presence of gas bubbles in contaminated water. This information provides vital information on the flow inside the pipe and hence could be very significant in increasing the efficiency of the process industries