Cercosporin was developed as a green and efficient organophotocatalyst for a wide range of selective oxidations with reactive oxygen species.

No abstract

Three-phase induction motors (TPIMs) are prone to numerous faults due to their complicated stator and rotor conditions and require a fast response, accurate, and intelligent diagnostic system. Recently developed fault diagnostic systems for induction motors are based on machine learning approaches, but their complex structure typically results in long training time. Moreover, they need to be retrained from scratch if the system is not accurate. We apply incremental broad learning (IBL) method to the diagnosis of TPIM faults. The IBL can train and retrain the network efficiently due to its flexible structure. The new diagnostic framework also consists of feature extraction techniques (empirical mode decomposition and sample entropy) and a non-negative matrix factorization (NMF) IBL approach. The experimental results demonstrate that the IBL system is superior to some algorithms, such as deep belief networks, convolutional neural networks, and extreme learning machine. Moreover, the IBL simplified by NMF is more accurate than the IBL without NMF. INDEX TERMS Fault diagnosis, feature extraction, incremental board learning, non-negative matrix factorization, three-phase induction motor.

This study develops a model to study household energy use behavior that can impose common preferences for feasible demand estimation with multiple discrete technology choices and multiple continuous energy consumption uses. The model imposes fixed proportions production and additivity of uses for plausible estimation feasibility while adopting a second-order translog flexible functional form to focus on flexibility in identification of consumer preferences that determine interactions among energy uses and between short-run and long-run choices. Using a unique household-level dataset from California, the model is applied to estimate short-run household demand for electricity and natural gas and the long-run technology choices with respect to clothes washing, water heating, space heating, and clothes drying. The estimation results support commonality of underlying preferences except in one case that is explained by an unavailable variable.

No abstract

Direct conversion of the tremendous and ubiquitous low-grade thermal energy into electricity by thermogalvanic cells is a promising strategy for energy harvesting. The environment is one of the richest and renewable low-grade thermal source. However, critical challenges remain for all-day electricity generation from environmental thermal energy due to the low frequency and small amplitude of temperature fluctuations in the environment. In this work, we report a tandem device consisting of a polypyrrole (PPy) broadband absorber/radiator, thermogalvanic cell, and thermal storage material (Cu foam/PEG1000) that integrates multiple functions of heating, cooling, and recycling of thermal energy. The thermogalvanic cell enables continuous utilization of environmental thermal energy at both daytime and nighttime, yielding maximum outputs as high as 0.6 W m-2 and 53 mW m-2, respectively. As demonstrated outdoors by a large-scale prototype module, this design offers a feasible and promising approach to all-day electricity generation from environmental thermal energy.

No abstract

A new frequency domain method for random fatigue life estimation in a wide‐band stationary Gaussian random process was proposed for application in fatigue analysis. Simulations of the power spectral densities of different types were firstly performed; the simulated results showed that the accuracy and applicability for the current frequency domain methods are not only related to the spectral type but also associated with the types of the analysed materials. Compared with the current methods, the proposed method, in which the rain‐flow amplitude obeys Nakagami distribution, has better universality and could significantly reduce the error for the random fatigue life estimation with simulated and actual spectra. Verified application in cast‐steel fatigue life analysis were performed between random fatigue life and constant amplitude fatigue life. It is shown that the fatigue life analysis under random load cannot be ignored and the proposed new method can serve as a recommended method.