Estimating included animal species in mixed crude drugs derived from animals using massively parallel sequencing

We developed a method that can detect each animal species of origin for crude drugs derived from multiple animal species based on massively parallel sequencing analysis of mitochondrial genes. The crude drugs derived from animals investigated in this study were Cervi Parvum Cornu and Trogopterorum feces, which are derived from a mix of different animal species, two chopped cicada sloughs, and two commercial Kampo drugs. The mitochondrial 12S rRNA, 16S rRNA, and cytochrome oxidase subunit I gene regions were amplified and sequenced using MiSeq. The ratios of haplotype to total number of sequences reads were calculated after sequence extraction and trimming. Haplotypes that exceeded the threshold were defined as positive haplotypes, which were compared with all available sequences using BLAST. In the Cervi Parvum Cornu and Trogopterorum feces samples, the haplotype ratios corresponded roughly to the mixture ratios, although there was a slight difference from mixture ratios depending on the gene examined. This method could also roughly estimate the compositions of chopped cicada sloughs and Kampo drugs. This analysis, whereby the sequences of several genes are elucidated, is better for identifying the included animal species. This method should be useful for quality control of crude drugs and Kampo drugs.

Reduction of Free Fatty Acid in Low Free Fatty Acid of Mixed Crude Palm Oil (LMCPO): Optimization of Esterification Parameters

The objective of this research was to study the optimum condition of esterified oil production from low free fatty acid of mixed crude palm oil (LMCPO) by using a response surface methodology (RSM) with esterification reaction in a batch mode. LMCPO obtained from a vacuum refining process of mixed crude palm oil (MCPO) to extract the partial FFA in oil which was used as a raw materials in a food production. Therefore, remaining FFA of 6.170 wt.% in LMCPO should be reduced to less than 1 wt.% by using esterification when required these oils to use as feedstock for producing biodiesel. After esterification process, FFA in esterified oil was studied to optimize the four independent variables of methanol (5-25 vol.%), sulfuric acid (0.5-4.5 vol.%), reaction time (5-65 min) and speed of stirrer (100-500 rpm). The results showed that the optimal condition of 25 vol.% methanol, 2 vol.% sulfuric acid, 500 rpm speed of stirrer, and 30 min reaction time at 60°C reaction temperature can decreased the FFA level to less than 0.212 wt.%. However, it was found out that the high consumptions of methanol and sulfuric acid required for reducing FFA to lowest value. Thus, the selected condition of 17.4% methanol, 1.6% sulfuric acid, 300 rpm speed of stirrer, and 35 min reaction time was chosen to save the chemical contents because this condition achieved to reduce FFA to acceptable level of 1 wt.%. For the actual experiment, FFA can be decreased to 0.212 wt.%, and 1.028 wt.% respectively. The yields of 96.67 wt.% for crude esterified oil and 94.22 wt.% for pure esterified oil were achieved based on LMCPO under the selected condition.

Application of Nonlinear Parameters Predictive Model Based on LS-SVM in Pipeline of Mixed Transportation

In order to meet the refinery’s requirements on the properties of raw materials, improve the hydraulic stability of pipeline transporting process, and reduce the energy consumption, it’s necessary to mix up different crude oils transported in pipeline. The traditional method to obtain the physical properties of mixed crude oil, especially the nonlinear parameters such as viscosity and pour point, is experiment test or empirical formula, but the disadvantage is the heavy workload or limited use conditions. In this paper, a nonlinear parameters prediction model based on LS-SVM is put forward for transporting mixed crude oil in pipeline. The modeling method of the nonlinear parameters prediction based on LS-SVM : 1 normalize the different batch sample data; 2 the kernel function of SVM is Gaussian RBF; 3 regress coefficients by genetic algorithm; 4 train parameters and then obtain the nonlinear parameters prediction model. The nonlinear parameters prediction model based on LS-SVM has superiority in aspects of reliability, modeling efficiency, universality and adaptability. It can adapt to the dynamic requirements of refinery on crude oil properties, make full use of the accumulated mixed crude oils’ physical properties and their mixing ratio. The prediction accuracy of non-linear parameters model can be improved continuously. And then, the rationality and efficiency of online mixed transportation in pipeline can be improved effectively.

Metabolism of glycerol in pigs fed diets containing mixed crude glycerin and β-adrenergic agonist

The optimised use of mixed crude glycerin (MCG) and ractopamine hydrochloride (RH) in diets for finishing pigs requires a better understanding of glycerol metabolism. Therefore, the present study evaluated the performance, blood parameters, metabolite concentrations in the Longissimus lumborum muscle and the activity of enzymes in the liver, subcutaneous adipose tissue and kidney of pigs fed diets containing MCG and/or RH. According to the initial weight, 64 barrows were distributed in a 4 × 2 factorial design, corresponding to four concentrations of MCG (0, 100, 150, and 200 g/kg) in diets containing 0 or 10 mg/kg of RH. There was no MCG × RH interaction for any of the evaluated parameters (P > 0.05). Moreover, there was no isolated effect of dietary MCG or RH on the weight gain and the blood concentrations of glucose, insulin, triacylglycerols, total cholesterol, total protein, albumin, creatinine, cortisol and lactate (P > 0.05). There was a higher rate of phosphorylation of glycerol in the liver, stimulation of lipogenesis in adipose tissue and a likely increase in the utilisation of glycerol by muscle fibres in response to an increased concentration of circulating glycerol from the diet (P < 0.05). In contrast, when the diet contained up to 200 g/kg MCG and 10 mg/kg RH, there were indications of a lower utilisation of glycerol for the synthesis of triacylglycerols in muscle, liver and adipose tissue, in addition to increased oxidation of amino acids in the liver followed by improved feed conversion of pigs (P < 0.05).

Optimization of Planning and Scheduling of Refinery Product Based on Downstream Requirements

The disconnect between the optimization systems of upstream production and downstream demand poses a legitimate problem for China’s refined oil industry in terms of overproduction waste. Established methods only partially model the refinery system and are unable to integrate detailed production plans or meet market demands. Therefore, the research on production scheduling optimization combined with the demand of downstream pipeline network has very real applications that not only reduce the consumption of human/material resources, but also increase economic efficiency. This paper aims to optimize the production scheduling of refined oil transportation based on the demand of downstream product pipelines by analyzing the relationships between crude oil supply, refinery facility capacities and refinery tanks storage. The new model will minimize the refined production surplus therefore minimizing refinery costs and wastage. This is done by implementing models custom designed to optimize the three subsystems of the overall process: oil product blending scheduling optimization, producing and processing equipment scheduling optimization, and mixed crude oil scheduling optimization. We first analyzed the relationship between all the production units from the crude oil to the distributional destinations of oil products. A mathematical model of the refinery production scheduling was then built with minimum total surplus inventory as the objective function. We assumed a known downstream demand and used a step by step model to optimize oil stocks. The oil blending plan, production scheduling, amount of crude oil, and refined oil mixing ratios were all derived from the model using three methods: a nonlinear method called Particle Swarm Optimization (PSO), the simplex method and the enumeration method. The evidence laid out in this paper verifies our models functionality and suggests that systems can be significantly optimized by using these methods which can provide solutions for industries with similar challenges. Optimization of the refinery’s overall production process is achieved by implementing models for each of the three distinguished subsystems: oil blending model, plant scheduling model, and the mixed crude oil refining model. The demand dictates the final production quantities. From those figures we are able to place constraining limits on the input crude oil. The refined oil production scheme is continuously enhanced by determining the amount of constituent feed on the production equipment according to the results of previous production cycle. After optimization, the minimum surplus inventory of the five oil components approach their lower limits that were calculated using our models. We compare the literature on scheduling optimization challenges both in China and abroad while providing a detailed discussion of the present situation of Chinese refineries. The interrelationships of production processes on each other are revealed by analyzing the system and breaking it down to three fundamental parts. Basing the final production predictions on the downstream demand, we are able to achieve a minimum refinery surplus inventory by utilizing a comprehensive refinery scheduling model composed of three sub-models.

Moringa oleifera as Sustainable Source for Energetic Biomass

This work investigated the biomasses (seeds, seed husks, oilseed grains, crude and purified oils, cakes by pressing and by hexane extraction and methyl biodiesel the oil) of Moringa oleifera Lamarck, starting with its seedpods (ripe and dry fruits) in energetic application. The oil obtained from the grains by mechanical pressing had an average yield of 11.36% and of 36.48% by hexane extraction. The moringa biomasses presented calorific values between 15.87 and 37.53 MJ/kg, being suitable as renewable biofuels. The mixed crude oil (1:4) was refined in four steps: degumming, neutralization, washing and drying. The crude and refined oils were characterised by acidity index, peroxide index, water content, turbidity, specific mass, kinematic viscosity, power calorific higher, calorific power below and ash content. The crude oils by pressing and by solvent extraction were characterised through of the saponification index and iodine value. The purified biodiesel presented specific mass of 889 kg/m3 (20 oC), kinematic viscosity of 5.5 m2/s (40 oC), content of ester of 86.2% and 98.23% (in microscale, ratifying the viability of the method), acidity index of 0.43 mg KOH/g and water content of 615.8 mg/kg. The solid moringa biomasses (seeds, cakes (or pies) and the seed husks) show high potential for the production of briquettes or ecological firewood due to its content energy expressed as lower calorific value (between 15.87 and 23.31 MJ/kg) and simple and accessible technological production. The results show that moringa is an easily exploitable plant in sustainable energy, especially from its seedpods and seeds.