Cimaterol and clenbuterol residue analysis by HPLC-HPTLC in liver.

A method has been developed for the analysis of cimaterol and clenbuterol residues in liver, with detection limits of 0.25 micrograms/kg and 0.5 micrograms/kg, respectively. The recovery varied from 55% to 60%. After extraction, a clean-up procedure with Baker-spe C-18 columns was performed. The two chemical compounds of interest were eluted with methanol. Cimaterol and clenbuterol were quantitatively determined by high-performance liquid chromatography (HPLC) using an RP-Select B (5 microns) column and a post-column reaction procedure. The positive results were confirmed by high-performance thin-layer chromatography (HPTLC) as this technique reaches the same level of sensitivity as the HPLC method.     

Magnetic resonance findings in skeletal muscle tears

Magnetic resonance (MR) images of skeletal muscle tears can clearly delineate the severity of muscle injury. Although MR imaging is seldom necessary in patients with acute muscle trauma, it can be helpful in deciding on clinical management. The two major MR findings in acute muscle tears are deformity of the muscle and the presence of abnormal signal reflecting hemorrhage and edema. In acute tears, methemoglobin within the extravascular blood causes high-signal areas on both T1- and T2-weighted images. With partial tears, the blood may dissect in a distinctive linear pattern along the muscle bundles and fibers. As healing begins, the muscle signal diminishes, first on the T1-weighted images and then on the T2-weighted images. When there is residual abnormal signal on images obtained more than several months after the injury, it is presumed to represent hemorrhage from recurrent tears. In patients with a questionable history of a remote injury, the clinical presentation may be that of persistent pain or a soft tissue mass. In these cases MR imaging may identify the cause of the pain and can exclude a neoplasm by proving that the mass is a hypertrophied or retracted muscle. Thus, MR imaging has a limited, but occasionally important role in selected patients with skeletal muscle tears.     

Application of artificial neural networks to the analysis of two‐dimensional fluorescence spectra in recombinant E coli fermentation processes

A two‐dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E coli for the production of 5‐aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyzed using artificial neural networks, ie self‐organizing map (SOM) and feedforward backpropagation neural network (BPNN). The SOM‐based classification of the whole spectral data has made it possible to qualitatively associate some process parameters with the normalized weights and variances, and to select some useful combinations of excitation and emission wavelengths. Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process's performance, eg forecasting the process's performance. Copyright © 2005 Society of Chemical Industry     

Validation and modification of WAVE spray model for diesel combustion simulation

In CFD simulation of diesel combustion, the predictive capabilities of the spray model play the most important role. Consequently, under the strict guidelines of the V&V, a method to adjust parameters of diesel spray model WAVE to accompany with the in-cylinder physical progress has been investigated in this paper. Moreover, the simulation of the spray has been validated by high-speed photography experiments and verified by the equation proposed by Hiroyasu. Finally, a modified setup for the WAVE spray model has been proposed and applied in the spray and combustion simulation for Deutz1013 diesel in different engine speed.