Semi-quantitative study on the secondary compression characteristics of municipal solid waste in aerobic and anaerobic bioreactors.

Aeration plays a crucial role in accelerating the secondary compression of municipal solid waste (MSW) for the scientific implementation of aerobic bioreactor technology. There are few comparative reports on the secondary compaction characteristics of MSW in aerobic and anaerobic bioreactors. In this study, six long-term compression tests were conducted to analyze the impact of aeration on MSW compression characteristics, considering two degradation conditions (i.e. aerobic and anaerobic conditions) and three overburden stresses (i.e. 30, 50 and 100 kPa). Model-fitting analysis was employed to examine the data from the tests and exiting literatures. The results showed that aeration effectively increased the rate of secondary compression, and slightly enhanced the steady-state secondary compression strain. In addition, these enhancements tended to decrease with increasing stresses. The increment ratio of the secondary compression rate constant (Rk) was concentrated in the range of 25 % to 100 %, and increases with the increase of aeration rate. The increment ratio of the steady-state secondary compression strain (Rε) ranged from 10 % to 90 %, for the MSW with higher content of paper and wood exhibited higher Rε. The advance ratio of the secondary compression stabilization time (Rt) fell within the range of 20-50 %, and Rt is higher when the moisture content is in the range of 50-65 %. These findings provide valuable guidance on the accelerated stabilization in aerobic bioreactors, providing practical references for the application of aerobic technology to informal landfills.

The use of the impedance measurements to distinguish between fresh and frozen-thawed chicken breast muscle.

An impedance system was built to differentiate fresh chicken breasts from those that had been frozen and thawed. Inserting needle electrode pairs of the detecting probe aligned with the longitudinal direction of muscle myofibers (PL) gave more satisfactory results. Learning vector quantization neural network (LVQNN) and partial least square-discriminant analysis (PLS-DA) were employed to acquire the prediction accuracy. The results demonstrated that the model using LVQNN achieved a satisfactory prediction accuracy, with a discrimination accuracy for fresh breasts of 100%. Additionally, the recognition results for a single frozen-thawed cycle were greater than 90%, and for two cycles were greater than 88%. The values obtained from PLS-DA were somewhat lower than for LVQNN, being 100% for fresh samples, in excess of 90% for single frozen-thawed cycle and more than 84% for those that had been multiple frozen-thawed. In conclusion, these results showed that the impedance system is a simple and effective application for the discrimination of fresh chicken breasts from frozen-thawed ones.