Alkaline sulphide leaching was adopted to extract tellurium from tellurium-bearing gold concentrate for the first time. The tellurium leaching kinetics were studied. The influence of average particle size, stirring speed, leaching temperature, Na2S concentration, and NaOH concentration on the tellurium extraction were investigated. It was found that tellurium extraction could reach 79.14% under the optimum conditions: 17.77 μηι average particle size, 500 r/min stirring speed, 80 g/L Na2S concentration, 30g/L NaOH concentration, 80°C leaching temperature, 4:1 liquid to solid ratio, and 180 minutes leaching time. The interface transfer and diffusion through the product layer or insoluble substance layer were the rate-controlling steps. The leaching kinetics equation was established, and the activation energy was 34.384 kJ/mol.

ABSTRACT This study has the objective of investigating the effects of traditional Chinese medicine prescriptions (TCM) on serum lipid, abdominal and hepatic fat percentage, cholesterol content in eggs, and mRNA expression of genes apoA I and apoB100. One hundred and thirty five healthy (300-day-old) layers were randomly assigned to three treatments. The hens in control group were fed with the basal diet. The hens in the experimental groups (TCM 1 and TCM 2) were fed with the basal diet supplemented with 1% TCM 1 and 1% TCM 2 respectively over a period of 60 days. Laying performance and the serum parameters relevant to fat metabolism were measured. The results showed that no significant differences were found in average daily feed intake and egg weight among three treatments. Average daily laying rate in TCM treatments was increased, and the cholesterol content in eggs was decreased. The serum triglyceride (TG), total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels in experimental treatments were decreased (p<0.05), while the serum high-density lipoprotein cholesterol (HDL-C) level was increased (p<0.05) compared to the control group. Additionally, abdominal fat percentage decreased in TCM 1 treatment (p<0.05), and hepatic fat percentage decreased in both TCM treatments (p<0.05). The expression of apolipoproteinA I (apoA I) and apolipoproteinB100 (apoB100) mRNA in the liver increased in both TCM treatments (p<0.05). These results suggest that the diet supplemented with TCM could increase the expression of apoA I and apoB100 mRNA in the liver, and decrease lipid content in the serum, and reduce egg cholesterol in layers.

Cyanobacteria are responsible for many problems in drinking water treatment works (DWTW) because of their ability to produce cyanotoxins that potentially can have an adverse effect on consumer health. Therefore, the monitoring of cyanobacteria in source waters entering DWTW has become an essential part of drinking water treatment management. Managers of DWTW rely heavily on results from physical, chemical and biological water quality analyses, from grab samples, for their management decisions. However, results of water quality analyses may be delayed from 3 h to 14 days depending on a magnitude of factors such as sampling, distance and accessibility to laboratory, laboratory sample turnaround times, specific methods used in analyses, etc. Therefore, the benefit to managers and production chemists to be able to forecast future events of high cyanobacterial cell concentrations in the source water is evident. During this study, physical, chemical and biological water quality data from samples taken from 2000 to 2009 in the Vaal Dam, supplying South Africa's largest bulk drinking water treatment facility, were used to develop models for the prediction of the cyanobacterium Microcystis sp. in the source water (real-time prediction together with 7, 14 and 21 days in advance). Water quality data from the Vaal Dam from 2010-2012 were used to test these models. The model showing the most promising results for incorporation into a 'Cyanobacterial Incident Management Protocol' is the one predicting Microcystis sp. 7 days in advance. This model showed a square correlation coefficient (R²) of 0.90 when tested with the testing dataset (chosen by bootstrapping from the 2000-2009 input dataset) and a R²of 0.53 when tested with the 3-year 'unseen' dataset from 2010-2012.