Activated carbon-mediated arsenopyrite oxidation and arsenic immobilization: ROS formation and its role.

The oxidative dissolution of arsenopyrite (FeAsS) is a significant source of arsenic contamination in nature. Activated biochar (AC), a widely used environmental remediation agent, is prevalent in ecosystems and participated in various geochemical processes of arsenic and iron-containing sulfide minerals. However, the impact of AC-arsenopyrite association on reactive oxidation species (ROS) generation and its contribution to As transformation were rarely explored.

Operational Scheduling of Behind-the-Meter Storage Systems Based on Multiple Nonstationary Decomposition and Deep Convolutional Neural Network for Price Forecasting.

In the competitive electricity market, electricity price reflects the relationship between power supply and demand and plays an important role in the strategic behavior of market players. With the development of energy storage systems after watt-hour meter, accurate price prediction becomes more and more crucial in the energy management and control of energy storage systems. Due to the great uncertainty of electricity price, the performance of the general electricity price forecasting models is not satisfactory to be adopted in practice.

Electric Shovel Teeth Missing Detection Method Based on Deep Learning.

Electric shovels are widely used in the mining industry to dig ore, and the teeth in shovels' bucket can be lost due to the tremendous pressure exerted by ore materials during operation. When the teeth fall off and enter the crusher with other ore materials, serious damages to crusher gears and other equipment happen, which causes millions of economic loss, because it is made of high-manganese steel. Thus, it is urgent to develop an efficient and automatic algorithm for detecting broken teeth.

Adaptive Localizing Region-Based Level Set for Segmentation of Maxillary Sinus Based on Convolutional Neural Networks.

In this paper, we propose a novel method, an adaptive localizing region-based level set using convolutional neural network, for improving performance of maxillary sinus segmentation. The healthy sinus without lesion inside is easy for conventional algorithms. However, in practice, most of the cases are filled with lesions of great heterogeneity which lead to lower accuracy.