No abstract

5-hydroxymethyl-2-furaldehyde (5-HMF) is an important substance that affect quality of honey and shows toxicity for humans and honey bees. The pathway of 5-HMF formation in honey is still unknown. In this study, we tested the effect of thermal treatment (at 90°C for 4 h) on the formulation of 5-HMF formulation in rapeseed with varied honey composition. 5-HMF content of honey increased at higher water content, Ca 2? and Mg 2? content and lower pH. However, the formation of 5-HMF was not significantly influenced by glucose, fructose, Na ? , or K ? contents. Furthermore, different content of proline, the most abundant amino acid in honey (a substance in Maillard reaction), had no effect on 5-HMF formation. Free acids in honey can catalyze fructose and glucose to form 5-HMF. These results suggest that dehydration of glucose or fructose, instead of the Maillard reaction, is the main pathway of 5-HMF formation in honey. This study gives new insights for the mechanisms of 5-HMF formation and provides method for reducing 5-HMF formation during honey processing.

Satellite image semantic segmentation, including extracting road, detecting building, and identifying land cover types, is essential for sustainable development, agriculture, forestry, urban planning, and climate change research. Nevertheless, it is still unclear how to develop a refined semantic segmentation model in an efficient and elegant way. In this paper, we propose attention dilation-LinkNet (AD-LinkNet) neural network that adopts encoder-decoder structure, serial-parallel combination dilated convolution, channel-wise attention mechanism, and pretrained encoder for semantic segmentation. Serial-parallel combination dilated convolution enlarges receptive field as well as assemble multi-scale features for multiscale objects, such as long-span road and small pool. The channel-wise attention mechanism is designed to advantage the context information in the satellite image. The experimental results on road extraction and surface classification data sets prove that the AD-LinkNet shows a significant effect on improving the segmentation accuracy. We defeated the D-Linknet algorithm that won the first place in the CVPR 2018 DeepGlobe road extraction competition.

Visibility affects all forms of traffic: roads, sailing, and aviation. Visibility prediction is meaningful in guiding production and life. Different from weather prediction, which relies solely on atmosphere factors, the factors that affect meteorological visibility are more complicated, such as the air pollution caused by factory exhaust emission. However, the current prediction of visibility is mostly based on the numerical prediction method similar to the weather prediction. We proposed a method using multimodal fusion to build a weather visibility prediction system in this paper. An advanced numerical prediction model and a method for emission detection were used to build a multimodal fusion visibility prediction system. We used the most advanced regression algorithm, XGBoost, and LightGBM, to train the fusion model for numerical prediction. Through the estimation of factory emission by the traditional detector in the satellite image, we propose to add the result of estimation based on Landsat-8 satellite images to assist the prediction. By testing our numerical model in atmosphere data of various meteorological observation stations in Beijing-Tianjin-Hebei region from 2002 to 2018, our numerical prediction model turns out to be more accurate than other existing methods, and after fusing with emission detection method, the accuracy of our visibility prediction system has been further improved.

To provide stable and high data rate wireless access for passengers in the train, it is necessary to properly deploy base stations along the railway. We consider this issue from the perspective of service, which is defined as the integral of the time-varying instantaneous channel capacity. With large-scale fading assumption, it will be shown that the total service of each base station is inversely proportional to the velocity of the train. Besides, we find that if the ratio of the service provided by a base station in its service region to its total service is given, the base station interval (i.e., the distance between two adjacent base stations) is a constant regardless of the velocity of the train. On the other hand, if a certain amount of service is required, the interval will increase with the velocity of the train. The aforementioned results apply not only to simple curve rails, like line rail and arc rail, but also to any irregular curve rail, provided that the train is traveling at a constant velocity. Furthermore, the new developed results are applied to analyze the on-off transmission strategy of base stations.