In situ nutrient removal from aquaculture wastewater by aquatic vegetable Ipomoea aquatica on floating beds

Nutrient-rich effluents caused rising concern due to eutrophication of aquatic environment by utilization of a large amount of formula feed. Nutrient removal and water quality were investigated by planting aquatic vegetable on artificial beds in 36-m(2) concrete fishponds. After treatment of 120 days, 30.6% of total nitrogen (TN) and 18.2% of total phosphorus (TP) were removed from the total input nutrients by 6-m(2) aquatic vegetable Ipomoea aquatica. The concentrations of TN, TP, chemical oxygen demand (COD) and chlorophyll a in planted ponds were significantly lower than those in non-planted ponds (P<0.05). Transparency of water in planted ponds was much higher than that of control ponds. No significant differences in the concentration of total ammonia nitrogen (TAN), nitrate nitrogen (NO3-N) and nitrite nitrogen (NO2--N) were found between planted and non-planted ponds. These results suggested that planting aquatic vegetable with one-sixth covered area of the fishponds could efficiently remove nutrient and improve water quality.

Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

Manifold covering theory in biomimetic pattern recognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite manifold covering in biomimetic pattern recognition, and study its property. Furthermore, we propose this manifold covering algorithm based on Biomimetic Pattern Recognition. At last, the experimental results for face recognition demonstrates that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

Shape evolution of CdSe nanocrystals in vegetable oils: A synergistic effect of selenium precursor

In this contribution, common vegetable oils are used as coordination solvents for synthesis of high quality CdSe nanocrystals. Various shaped nanocrystals (quantum dots, quantum rods, multipods, arc structure, etc.) can be produced free of alkylphosphonic acids. Shape evolution can be induced by three types of selenium precursors: ODE-Se, VO-Se and TOP-Se (ODE, 1-octadecene; VO, vegetable oil; TOP, trio-n-octylphosphine). The quantum yields of NCs are 15-40%. The full width at half-maximum (fwhm) of the photoluminescence spectra are 27 +/- 1 nm for quantum clots and 23 +/- 1 nm for quantum rods/multipods.