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Freeform lenses are playing a more and more important role in LED secondary optics design. In this paper, based on the lighting-energy conservation law, edge-ray principle and Snell's law, we present a freeform lens optical system design method for LED lighting. This system can achieve rectangular lighting area, and it is easier to precisely control the angle of light emitting and processing, with the advantages of uniform illumination. The software Matlab and Rhino were used to get the model of lens, and the PMMA was used as the material to design lens model. Finally, the numerical simulation results showed that the spot shape was close to the expected results.

Visible-near infrared hyperspectral images (400–1000 nm) were used for non-destructive variety discrimination and prediction of soluble solids content (SSC) and firmness of pears. An imaging spectroscopy system was assembled to acquire scattering images from pears. Spectra of 180 pear samples from three varieties were analyzed by four algorithms of principal component analysis (PCA), partial least squares (PLS), successive projections algorithm (SPA) and Fisher linear discriminant analysis (Fisher LDA) to detect SSC, firmness and varieties of pears. Then PLS models under whole spectral wavelengths were compared with SPA-PLS models under effective wavelengths. The SPA-PLS models were considered to be the best method for detecting firmness and SSC of pears. The model led to correlation coefficient (r) of 0.9977 for firmness and 0.9924 for SSC and root mean square error (RMSEP) estimated by cross-validation of 0.062653 for firmness and 0.03175 for SSC. The correct answer rate of 95.56% for variety discrimination was achieved by Fisher LDA.

This study provides a rapid method for quantification of mineral oil in rapeseed oil using near-infrared spectroscopy. The data were processed by direct orthogonal signal correction (DOSC), successive projections algorithm (SPA), partial least squares, and principal component regression (PCR). Good correlation coefficients (R) of 0.998 and root-mean-squared error (RMSE) of 0.005 were obtained, and the DOSC-SPA-PCR model was identified as the optimal method. A satisfactory accuracy with R and RMSE of prediction by DOSC-SPA-PCR of 0.990 and 0.006, was obtained. The results demonstrate that the proposed methodology is a promising method for the rapid quantitative detection of mineral oil in vegetable oil.

A method is presented for one-to-many information encryption transmission by using temporal ghost imaging and code division multiple access. In the encryption transmission process, code division multiple access technologies combine multiple information sources, and the chip sequence corresponding to each set of information is used as the first key. The transmission end loads the transmission information onto a series of temporal random patterns of temporal ghost imaging and transmits it to the receivers. A series of temporal random patterns is the second key. During the decryption, each receiver can get the same encrypted information and use the second key to obtain the transmitted information. Finally, each receiver uses the unique chip sequence to get corresponding information. This encryption transmission method realizes one-to-many information encryption transmission at the same time over the same channel. Double encryption ensures the security of information. Simulation and experiment results verify the effectiveness and security of the method. The method has strong antinoise ability and can effectively resist various attack modes. At the same time, this method solves the problem that the use of code division multiple access enlarges the signal bandwidth, and ensures that no cross talk occurs between various sources of information.

This article presents a method for rapid, credible and noninvasive identification of the type of wax on pears using hyper-spectral imaging (HSI) in the visible and near-infrared (Vis–NIR) range (400–1,026 nm). The successive projection algorithm (SPA) was used to select the most effective wavelengths for wax type identification within a calibration set of 108 pears. This set was used to build identification models based on Multiple Linear Regression (MLR) and Linear Discrimination Analysis (LDA) using the relative reflectance values of the effective wavelengths. A prediction set of 72 pears was used to verify the reliability of the models and the results of both models were compared. SPA–LDA was found to be a better model than SPA–MLR, with an identification accuracy of 99.07% for calibration and 95.83% for the prediction sets. This demonstrates that Vis–NIR HSI is a potential candidate for wax type identification in a rapid, credible and noninvasive way. Practical Applications In the international markets and packing houses, many traders will wax the surface of pears to ensure they have a fresh appearance. Most traders use edible wax, but to reduce the cost, some unscrupulous traders may use industrial wax which is harmful to people's health. In recent years, a growing number of food products contain pears, such as Perry, sweetened pear pulp and dried pear. Therefore, it is crucial that the safety of the pear's surface can be ensured. In this study, the relative reflectance values of 11 effective wavelengths were selected by the Successive Projection Algorithm (SPA) as the independent variables of Linear Discrimination Analysis (LDA) based on hyper-spectral imaging (HSI), and the obtained 11 effective wavelengths can be developed into an on-line multi-spectral system for food safety detection. This method allows nondestructive identification of the type of wax on pears and can automatically focus during the detection process.

AMP-activated protein kinase (AMPK) is a highly conserved cellular energy sensor that plays a central role in metabolic homeostasis. A recent study in Science (Egan et al., 2011) identifies ULK1 as a substrate for AMPK phosphorylation, a modification required for selective autophagy of mitochondria and cell survival during starvation.