Relaxed 2-D Principal Component Analysis by LpL_p Norm for Face Recognition

A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optimal $L_p$-norms are selected in a reasonable range. Numerical experiments on practical face databased indicate that the R2DPCA has high generalization ability and can achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure

Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

The long-term effects of alfalfa on soil water content in the Loess Plateau of northwest China

Soil desiccation is the most serious problem in forest vegetations and grassland, which lead to widespread land degradation in the Loess Plateau of China. The soil water variations at 0 to 1000 cm depth of different vegetations were studied to explore the hydrological effects of vegetations and determine the optimal length of alfalfa (Medicago sativa L.) phase at the Zhenyuan Agri-ecological Station of the Loess Plateau in China. Eight treatments were designed in this study: waste land, wheat land and six continuous growing alfalfa treatments, including 4-year-old (4 year), 6-year-old (6 year), 8- year-old (8 year), 12-year-old (12 year), 18-year-old (18 year) and 26-year-old (26 year) alfalfa grasslands.  Results showed that the wheat field had the best soil water content and no dry soil layer, while slightly dry soil layer occurred in wasteland and 4, 6 and 8 year alfalfa grasslands. After alfalfa grew for > 8 years, moderately dry soil layer appeared in the grassland and expanded beyond 500 cm soil depth. The result also showed that wheat field, wasteland and the alfalfa grasslands growing for 4, 6 and 8 years had no unfavorable impacts on the ecological environments of the soil moisture but the grasslands for 12, 18 and 26 years did exert relatively stronger unfavorable influences on the hydrological effects. Considering all the factors, this study recommends that the optimal length of alfalfa phase should be 8 years.Key words: Different vegetation, alfalfa grasslands, soil water content, ecological effect, soil desiccation, Loess Plateau of China

Effects of rumen-protected tryptophan on performance, nutrient utilization and plasma tryptophan in cashmere goats

Thirty-six Liaoning cashmere goat wethers (28.72 ± 0.59 kg) were used to  determine the effects of rumen-protected tryptophan (RPT) on performance, nutrient utilization and plasma tryptophan (Trp) during the cashmere fast-growing period. The goats were randomly assigned to the following treatments: Control (without RPT), LRPT (RPT – low), MRPT (RPT– medium) and HRPT (RPT – high) at RPT levels of 0, 2.0, 4.0 and 6.0 g per goat per day, respectively. RPT-medium supplementation improved average daily gain and feed efficiency (P < 0.05) when compared with the control and HRPT. RPT supplementation increased (P < 0.05) the length and growth rate of cashmere fiber, whereas no differences were observed among the LRPT, MRPT and HRPT treatment groups (P > 0.05). RPT-medium supplementation decreased urinary nitrogen (N) excretion and increased N retention when compared with other groups (P < 0.05). Plasma Trp concentration was higher for HRPT treatment group when compared with other treatments (P < 0.05). In conclusion, RPT supplementation potentially improved growth performance, N utilization and cashmere fibre growth in Liaoning cashmere goats. In the experimental conditions of the current trial, the optimum RPT supplementation level was 4.0 g per goat per day during the cashmere fast-growing period.Key words: Rumen-protected tryptophan, growth performance, fibre characteristics, nutrient utilization, plasma tryptophan, cashmere goats