Eco-friendly triboelectric nanogenerator based on degradable rape straw powder for monitoring human movement.

Green energy from the surrounding environment has great potential for reducing environmental pollution and sustainable development. Triboelectric nanogenerators (TENGs) are of great interest as they can easily harvest mechanical energy from the environment. Here, we present a triboelectric nanogenerator (RS-TENG) based on rape straw (RS), which was developed from a film composed of waste RS and polyvinyl alcohol (PVA). Due to the high content of carbonyl, hydroxyl and amino acid functional groups in RS, the ability of RS/PVA to lose electrons is increased. The proposed RS-TENG device with a size of 6.25 cm2exhibits open circuit voltage (78 V), short circuit current (5.3µA) performance under uniform external stress at a frequency of 3.5 Hz and 10 N in the cylinder motor. 104.5µW was obtained with a load resistance of 25 MΩ. Results obtained from degradability tests revealed that the RS/PVA film was able to degrade over a period of 30 d (In PBS solution). The RS-TENG produces a significantly high current signal under conditions of finger bending, elbow movements, and foot tapping. Practical tests of the RS-TENG have shown that it is a promising sensing device that will be widely used in the future.

Location Property of Convolutional Neural Networks for Image Classification.

When doing image classification, the core task of convolutional neural network (CNN)-based methods is to learn better feature representation. Our analysis has shown that a better feature representation in the layer before softmax operation (BSM-layer) means a better feature embedding location that has a larger distance to the separating hyperplane. By defining this property "Location Property" of CNN, the core task of CNN-based methods can be regarded as to find out the optimal feature embedding location in the BSM-layer. In order to achieve this, in this work, we first propose two feature embedding directions, principal embedding direction (PE-direction) and secondary embedding direction (SE-direction). And then, we further propose a loss-based optimization framework, location property loss (LP-loss), which can make feature representation move in the PE-direction and the SE-direction simultaneously during the training phase. LP-loss consists of two parts, LPPE and LPSE, where LPPE focuses on PE-direction, and LPSE focuses on SE-direction. Any loss function focusing on these two embedding directions can be chosen as LPPE and LPSE. Based on the analysis that softmax, L-softmax, and AM softmax can make the feature representation move in PE-direction to a different extent, any of them can be chosen as LPPE. Since there is no existing works can fulfill the purpose of LPSE, a novel loss, secondary optimal feature plane loss (S-OFP loss), is developed. S-OFP loss is designed to make feature representations belonging to the same category embed onto their corresponding S-OFP. It is proved that S-OFP loss is the optimal feature plane in the SE-direction. Experiments are done with shallow, moderate, and deep models on four benchmark data sets, including the MNIST, SVHN, CIFAR-10, and CIFAR-100, and results demonstrate that CNN models can obtain remarkable performance improvements with LPsoftmax, S-OFP and LPAM softmax, S-OFP, which verify the effectiveness of location property.

Nonlinear optical properties of sodium copper chlorophyllin in aqueous solution.

BACKGROUND: Sodium copper chlorophyllin (SCC), as one of the derivatives of chlorophyll - with its inherent green features; good stability for heat, light, acids and alkalies; unique antimicrobial capability; and particular deodori zation performance - is widely applied in some fields such as the food industry, medicine and health care, daily cosmetic industry etc. SCC, as one of the metal porphyrins, has attracted much attention because of its unique electronic band structure and photon conversion performance. To promote the application of SCC in materials science; energy research and photonics, such as fast optical communications; and its use in nonlinear optical materials, solar photovoltaic cells, all-optical switches, optical limiters and saturable absorbers, great efforts should be dedicated to studying its nonlinear optical (NLO) properties. METHODS: In this study, the absorption spectra and NLO properties of SCC in aqueous solution at different concentrations were measured. The Z-scan technique was used to determine NLO properties. RESULTS: The results indicated that the absorption spectra of SCC exhibit 2 characteristic absorption peaks located at the wavelengths 405 and 630 nm, and the values of the peaks increase with increasing SCC concentration. The results also showed that SCC exhibits reverse saturation absorption and negative nonlinear refraction (self-defocusing). CONCLUSIONS: It can be seen that SCC has good optical nonlinearity which will be convenient for applications in materials science, energy research and photonics.