• Title/Summary/Keyword: Random Yield

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Optimization of the whole extract of Zarawand Mudaharaj (Aristolochia rotunda L.) root by Response Surface Methodology (RSM)

  • Ansari, MD Zakir;Sofi, Ghulamuddin;Hamiduddin, Hamiduddin;Ahmad, Haqeeq;Basri, Rabia;Alam, Abrar
    • CELLMED
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    • v.11 no.3
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    • pp.15.1-15.9
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    • 2021
  • The chemical constitution of a drug has been accepted as an important basis for pharmacological action in Unani medicine. Various dosage forms have been developed on this concept, such as decoctions (Joshanda), infusions (Khesanda), extract (Rub / Usara), and syrup. Zarawand Mudaharaj (ZM.) / Aristolochia rotunda L. root was subjected to extraction process using Soxhlet's apparatus by using Response Surface Methodology (RSM) to design the number of random runs of the extracts with variation in the factors of temperature, the concentration of ethanol in water, time for extraction, for optimizing and maximizing the yield concentration. The data obtained, was analyzed with regression equation and ANOVA two-way summary to interpret the interaction of the factors for yield maximization. Minitab version 18 was used to design and analyze data. Validation of the optimum conditions for maximum yield of the whole extract of ZM. Root was carried out by re-run of the extract using the optimized conditions. The maximum yield percentage thus obtained using RSM was 20.87% whereas using these optimum conditions 21.35 % yield was obtained thereby validating the method. The association between the response functions and the process variables was identified by a three-factor recorded Box-Behnken design. In the present study RSM is used because itis a cheap and affordable method to optimize maximum yield percentage which may be reliably used by researchers. The study set in the surface conditions for ZM. root extraction by the Soxhlet apparatus for maximizing the yield percentage.

Genetic parameters of milk and lactation curve traits of dairy cattle from research farms in Thailand

  • Pangmao, Santi;Thomson, Peter C.;Khatkar, Mehar S.
    • Animal Bioscience
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    • v.35 no.10
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    • pp.1499-1511
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    • 2022
  • Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

Reliability Analysis of Gas Turbine Engine Blades (가스터빈 블레이드의 신뢰성 해석)

  • Lee, Kwang-Ju;Rhim, Sung-Han;Hwang, Jong-Wook;Jung, Yong-Wun;Yang, Gyae-Byung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.12
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    • pp.1186-1192
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    • 2008
  • The reliability of gas turbine engine blades was studied. Yield strength, Young’s modulus, engine speed and gas temperature were considered as statistically independent random variables. The failure probability was calculated using five different methods. Advanced Mean Value Method was the most efficient without significant loss in accuracy. When random variables were assumed to have normal, lognormal and Weibull distributions with the same means and standard deviations, the CDF of limit state equation did not change significantly with the distribution functions of random variables. The normalized sensitivity of failure probability with respect to standard deviations of random variables was the largest with gas temperature. The effect of means and standard deviations of random variables was studied. The increase in the mean of gas temperature and the standard deviation of engine speed increased the failure probability the most significantly.

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle

  • Naserkheil, Masoumeh;Miraie-Ashtiani, Seyed Reza;Nejati-Javaremi, Ardeshir;Son, Jihyun;Lee, Deukhwan
    • Asian-Australasian Journal of Animal Sciences
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    • v.29 no.12
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    • pp.1682-1687
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    • 2016
  • The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage ($0.213{\pm}0.007$). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

Probabilistic analysis of spectral displacement by NSA and NDA

  • Devandiran, P.;Kamatchi, P.;Rao, K. Balaji;Ravisankar, K.;Iyer, Nagesh R.
    • Earthquakes and Structures
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    • v.5 no.4
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    • pp.439-459
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    • 2013
  • Main objective of the present study is to determine the statistical properties and suitable probability distribution functions of spectral displacements from nonlinear static and nonlinear dynamic analysis within the frame work of Monte Carlo simulation for typical low rise and high rise RC framed buildings located in zone III and zone V and designed as per Indian seismic codes. Probabilistic analysis of spectral displacement is useful for strength assessment and loss estimation. To the author's knowledge, no study is reported in literature on comparison of spectral displacement including the uncertainties in capacity and demand in Indian context. In the present study, uncertainties in capacity of the building is modeled by choosing cross sectional dimensions of beams and columns, density and compressive strength of concrete, yield strength and elastic modulus of steel and, live load as random variables. Uncertainty in demand is modeled by choosing peak ground acceleration (PGA) as a random variable. Nonlinear static analysis (NSA) and nonlinear dynamic analysis (NDA) are carried out for typical low rise and high rise reinforced concrete framed buildings using IDARC 2D computer program with the random sample input parameters. Statistical properties are obtained for spectral displacements corresponding to performance point from NSA and maximum absolute roof displacement from NDA and suitable probability distribution functions viz., normal, Weibull, lognormal are examined for goodness-of-fit. From the hypothesis test for goodness-of-fit, lognormal function is found to be suitable to represent the statistical variation of spectral displacement obtained from NSA and NDA.

Performance Characteristics of a Regenerative Heat Exchanger Depending on Its Porous Structure (스털링 엔진용 재생 열교환기의 다공체 구조에 따른 성능 특성)

  • Shin, Myung-Chul;Ahn, Joon;Kang, Byung-Ha
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.24 no.5
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    • pp.415-421
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    • 2012
  • Stirling engine is an external combustion engine, whose efficiency approaches that of Carnot engine with the help of a regenerator. The regenerator is a heat exchanger composed of porous medium, whose performance is dependent on the pore structure. Three types of pore structures are considered in the present study. They are wire screen, random wire and composite structure, i.e. a combination of wire screens with different hydraulic diameters. The porosity more highly affects the performance of a regenerator compared to the hydraulic diameter. The random wire can yield high effectiveness even at a high porosity. The composite mesh gives better performance when the hydraulic diameter decreases in the direction from hot side to cold side.

Widely Tunable Adaptive Resolution-controlled Read-sensing Reference Current Generation for Reliable PRAM Data Read at Scaled Technologies

  • Park, Mu-hui;Kong, Bai-Sun
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.17 no.3
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    • pp.363-369
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    • 2017
  • Phase-change random access memory (PRAM) has been emerged as a potential memory due to its excellent scalability, non-volatility, and random accessibility. But, as the cell current is reducing due to cell size scaling, the read-sensing window margin is also decreasing due to increased variation of cell performance distribution, resulting in a substantial loss of yield. To cope with this problem, a novel adaptive read-sensing reference current generation scheme is proposed, whose trimming range and resolution are adaptively controlled depending on process conditions. Performance evaluation in a 58-nm CMOS process indicated that the proposed read-sensing reference current scheme allowed the integral nonlinearity (INL) to be improved from 10.3 LSB to 2.14 LSB (79% reduction), and the differential nonlinearity (DNL) from 2.29 LSB to 0.94 LSB (59% reduction).

Genetic Variation and Correlation Studies of Some Carcass Traits in Goats

  • Das, S.;Husain, S.S.;Hoque, M.A.;Amin, M.R.
    • Asian-Australasian Journal of Animal Sciences
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    • v.14 no.7
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    • pp.905-909
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    • 2001
  • Three groups of wethers viz. Jamunapari ♂$\times$Black Bengal ♀ (JBB), Selected Black Bengal ♂$\times$Selected Black Bengal ♀ (SBB) and Random Black Bengal ♂$\times$Random Black Bengal ♀ (RBB) of 1 year old were evaluated for pre-slaughter traits and carcass characteristics. The correlations between pre-slaughter traits and carcass traits were computed. It was found that the preslaughter weights of JBB and SBB were almost similar in yielding hot and chilled carcass as well as dressing percentage (DP). RBB wethers were lighter (p<0.05) than JBB and SBB in pre- and post-slaughter weights and also inferior (p<0.05) in DP. SBB wethers were found to produce more visceral fat compared to JBB and RBB. Other variety meats appeared erratic in yield.l. Correlations were compared by Z statistic among three genetic groups and the value of Z did not differ (p>0.05) between groups.

Large-System Analyses of Multiple-Antenna System Capacities

  • Biglieri, Ezio;Taricco, Giorgio
    • Journal of Communications and Networks
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    • v.5 no.2
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    • pp.96-103
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    • 2003
  • Asymptotic theorems are very commonly used in probability. For systems whose performance depends on a set of n random parameters, asymptotic analyses for n${\to}{\infty}$ are often used to simplify calculations and obtain results yielding useful hints at the behavior of the system for finite n. These asymptotic analyses are especially useful whenever the convergence to the asymptotic results is so fast that even for moderate n they yield results close to the true values. This tutorial paper illustrates this principle by applying it to capacity calculations of multiple-antenna systems.

Sire Evaluation of Count Traits with a Poisson-Gamma Hierarchical Generalized Linear Model

  • Lee, C.;Lee, Y.
    • Asian-Australasian Journal of Animal Sciences
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    • v.11 no.6
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    • pp.642-647
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    • 1998
  • A Poisson error model as a generalized linear mixed model (GLMM) has been suggested for genetic analysis of counted observations. One of the assumptions in this model is the normality for random effects. Since this assumption is not always appropriate, a more flexible model is needed. For count traits, a Poisson hierarchical generalized linear model (HGLM) that does not require the normality for random effects was proposed. In this paper, a Poisson-Gamma HGLM was examined along with corresponding analytical methods. While a difficulty arises with Poisson GLMM in making inferences to the expected values of observations, it can be avoided with the Poisson-Gamma HGLM. A numerical example with simulated embryo yield data is presented.