21 research outputs found
Effect Of Exogenous Leptin Administration On Testicular Function In Adult Male Sprague Dawley Rats [QP572.L48 N737 2008 f rb].
Kajian ini mengkaji kesan pemberian leptin terhadap berat organ reproduktif, aras serum gonadotrofin, kiraan dan morfologi sperma, histologi testis, berat badan serta pengambilan makanan dan minuman tikus.
This study examines the effect of exogenous leptin administration on reproductive organ weight, serum gonadotrophins, sperm count and morphology, testis histology, body weight, food and water intake in the rat
Effect of short-term bee bread on testicular cell development and testosterone level in male Sprague Dawley rats
Bee bread has been widely traditionally used for male fertility enrichment although limited scientific data are available on its effectiveness. Hence, the aim of this study was to determine the effect of bee bread on testicular cell development and testosterone level in male Sprague Dawley rats. In this study, 24 adult male Sprague-Dawley rats were selected and divided equally into four treatment groups (n = 6/group) which were Control (C: 0 g of bee bread/kg body weight), Treatment 1 (T1: 1 g of bee bread /kg body weight), Treatment 2 (T2: 2 g of bee bread /kg body weight) and Treatment 3 (T3: 3 g of bee bread /kg body weight). The bee bread was administered daily and orally according to the designated treatment groups using oral gavage for 28 days. After 28 days of treatment, rats were euthanised and testicular cell development and testosterone level were measured. Results showed that rats in the T2 group had thicker (P<0.05) seminiferous tubular diameter (STD) than the control group and higher (P<0.05) seminiferous epithelial height (SEH) compared to C and T1 groups. The testosterone level in the T1, T2 and T3 groups was significantly higher (P<0.05) compared to control. In conclusion, this study suggests that supplemented with 2 g of bee bread per kg body weight is likely to give a positive effect by improving testicular cells development and testosterone level in male Sprague Dawley rats
ETR 300 : E.S.A. Enterprise / Mohd. Zamree Mohd. Zain... [et al.]
E.S.A. Enterprise adalah perniagaan alat pengganti kenderaan. Ia bertujuan membaiki, membuat semula, memasang dan menjual penghidup elektrik kenderaan terpakai. Perniagaan ini beralamat di Lot 10 & 11, Kawasan Perindustrian Kecil Mergong, 05150 Alor Setar, Kedah
Predictive Modeling of TiN Coating Roughness
In this paper, an approach in modeling surface roughness of Titanium Nitrite (TiN) coating
using Response Surface Method (RSM) is implemented. The TiN coatings were formed using
Physical Vapor Deposition (PVD) sputtering process. N2 pressure, Argon pressure and turntable speed were selected as process variables. Coating surface roughness as an important coating characteristic was characterized using Atomic Force Microscopy (AFM) equipment. Analysis of variance (ANOVA) is used to determine the significant factors influencing resultant TiN coating roughness. Based on that, a quadratic polynomial model equation represented the process variables and coating roughness was developed. The result indicated that the actual coating roughness of validation runs data fell within the 90% prediction interval (PI) and the residual errors were very low. The findings from this study suggested that Argon pressure, quadratic term of N2 pressure, quadratic term of turntable speed, interaction between N2 pressure and turntable speed, and interaction between Argon pressure and turntable speed influenced the TiN coating surface roughness
Water quality assessment of Matang Mangrove Forest
The study on river water quality was carried out in Matang Mangrove and its vicinity during the scientific expedition from 20 – 25th October 2002. Thirty sampling locations were chosen based on accessibility and usage and eleven water quality parameters were analyzed; DO, EC, temperature, pH, BOD, Ammoniacal-Nitrogen (NH3-N), turbidity, TSS, salinity, natrium and TDS.
From the study, the rivers were classified into classes based on DOE-WQI and the classifications of the rivers were then mapped accordingly to its classes. The results showed that all sampling locations were influenced by the sea water with a range of salinity from 0.0 to 19 ppt except for the inland most area (ST 26, ST 28, ST 29 and ST 30). Based on water quality index interpretation (BOD, DO, TSS, NH3-N), the range of classes fall within Class I to III while the value of pH fall under Class II.
From the field observation and scientific analysis, activities within the Matang Mangrove and its vicinity such as aquaculture, cockle harvesting, navigation and river settlement are the main factors that contribute towards degradation of river water quality status
Determination of substantial chemical compounds of agarwood oil for quality grading
Agarwood is a resin saturated heartwood producing its ownessential oil. This oil comprises of a complex mixture of chromone derivatives, oxygenated sesquiterpenes and sesquiterpene hydrocarbons. This mixture has a heavy woody scentand is one of the contributors to the Agarwood oil quality. In this paper, a study that focuses on the approach to select the substantial chemical compounds for Agarwood quality grading was carried out. GC-MS analysis was used to extract the chemical compounds from the Agarwood oil. The data were then pre-processed using techniques such as missing values ratio, natural logarithm and min. max. normalization. Next, synthetic data were generated using MUNGE to fulfil the passing condition of sampling adequacy test. To determine the substantial compounds, PCA and Pearson’s correlation were used. This approach was successful in determining three substantial compounds namely β-agarofuran, α-agarofuran and 10-epi-γ-eudesmol. These substantial chemical compounds will be used later to predict the quality of Agarwood oil
Effect of extraction solvents and drying conditions on total phenolic content and antioxidant properties of watermelon rind powder
The objective of the present study was to determine the total phenolic content (TPC), total flavonoid content (TFC) and antioxidant properties, i.e. 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay and ferric reducing antioxidant potential (FRAP) assay, of red- and yellow-fleshed watermelon rind powders prepared using different drying conditions (hot-air oven drying at 40 and 60°C and freeze drying). All the samples were subjected to four different solvent extract using water, methanol, ethanol and acetone prior analyses. Water extract from red- and yellow-fleshed watermelon rind powders presented highest value for TPC and TFC. However, methanol extract samples showed highest value for antioxidant properties (DPPH and FRAP) followed by acetone, ethanol and water extract. By comparing the drying conditions, all samples dried using hot-air dryer at 40 and 60°C had significantly higher (p<0.05) in TPC value than the samples dried using freeze dryer. However, samples dried using freeze dryer showed highest in DPPH and FRAP values. The present obtained results would be useful to the food and pharmaceutical industries for developing of functional ingredients
Application of ANFIS in Predicting of TiAlN Coatings Hardness
In this paper, a new approach in predicting the hardness of Titanium Aluminum Nitrite
(TiAlN) coatings using Adaptive Neuro-Fuzzy Inference System (ANFIS) is implemented. TiAlN
coated cutting tool is widely used in machining due to its excellent properties. The TiAlN coatings
were formed using Physical Vapor Deposition (PVD) magnetron sputtering process. The substrate
sputtering power, bias voltage and temperature were selected as the input parameters and the hardness
as an output of the process. A statistical design of experiment called Response Surface Methodology
(RSM) was used in collecting optimized data. The ANFIS model was trained using the limited
experimental data. The triangular, trapezoidal, bell and Gaussian shapes of membership functions
were used for inputs as well as output. The results of ANFIS model were validated with the testing
data and compared with fuzzy and nonlinear RSM hardness models in terms of the root mean square
error (RMSE) and model prediction accuracy. The result indicated that the ANFIS model using 3-3-3
triangular shapes membership function obtained better result compared to the fuzzy and nonlinear
RSM hardness models. The result also indicated that the ANFIS model could predict the output
response in high prediction accuracy even using limited training data
Modeling of TiN Coating Thickness Using RSM Approach
In this paper, modeling of Titanium Nitrite (TiN) coating thickness using Response Surface Method (RSM) is implemented. Insert cutting tools were coated with TiN using Physical Vapor Deposition (PVD) sputtering process. N2 pressure, Argon pressure and turntable speed were
selected as process variables while the coating thickness as output response. The coating thickness as an important coating characteristic was measured using surface profilometer equipment. Analysis of variance (ANOVA) was used to determine the significant factors influencing TiN coating thickness. Then, a polynomial linear model represented the process variables and coating thickness was
developed. The result indicated that the actual validation data fell within the 90% prediction interval(PI) and the percentage of the residual errors were low. Findings from this study suggested that Argon pressure, N2 pressure and turntable speed influenced the TiN coating thicknes