ALBERT

Description: Background: Pesticide poisoning is an important issue in rural China, and is also a major public health problem that affects the health of farmers. The purpose of this paper is to explore the epidemiology of pesticide poisoning in Jiangsu Province, and to put forward the relevant suggestions on the logical and discerning utilization of the pesticides. Methods: According to the data of the pesticide poisoning report card established by the health hazard detection information system, the cases of pesticide poisoning in Jiangsu Province from 2006 to 2018 were exported to Excel, and the database of pesticide poisoning was established. Furthermore, the imported data was screened and collected. A descriptive statistical analysis had been employed on this data utilizing SPSS 20.0. Results: Between the years 2006 and 2018, 38,513 pesticide poisoning cases were registered in Jiangsu Province, with a downward trend. Meanwhile, 77.83% of poisoning cases involved insecticide poisoning, followed by herbicide and rodenticide. The greater part of the diverse sorts of studied insecticide poisoning cases involved people aged between 30 and 59 years (57.51%). Poisoning cases caused by rodenticide accounted for a large proportion of people aged between 0 and 14 years (23.72%) in non-occupational pesticide poisoning. Regarding seasons, it was distinguished that more insecticide cases were reported in autumn (46.95% of the total number of cases). Pesticide poisoning was reported in 13 cities of Jiangsu Province, and among these, insecticide poisoning was reported mainly from the northern Jiangsu area, which was the same as rodenticide and herbicide. Conclusions: Although there is a decreased risk for pesticide poisoning among farmworkers in Jiangsu Province, the number of farmworkers with pesticide poisoning is still high. Further management of the pesticide utilization is necessary, especially insecticide. More attention ought to be paid to the protection of vulnerable groups, including children and the elderly.

Description: Unmanned aerial vehicles (UAVs) equipped with dual-band crop-growth sensors can achieve high-throughput acquisition of crop-growth information. However, the downwash airflow field of the UAV disturbs the crop canopy during sensor measurements. To resolve this issue, we used computational fluid dynamics (CFD), numerical simulation, and three-dimensional airflow field testers to study the UAV-borne multispectral-sensor method for monitoring crop growth. The results show that when the flying height of the UAV is 1 m from the crop canopy, the generated airflow field on the surface of the crop canopy is elliptical, with a long semiaxis length of about 0.45 m and a short semiaxis of about 0.4 m. The flow-field distribution results, combined with the sensor’s field of view, indicated that the support length of the UAV-borne multispectral sensor should be 0.6 m. Wheat test results showed that the ratio vegetation index (RVI) output of the UAV-borne spectral sensor had a linear fit coefficient of determination (R2) of 0.81, and a root mean square error (RMSE) of 0.38 compared with the ASD Fieldspec2 spectrometer. Our method improves the accuracy and stability of measurement results of the UAV-borne dual-band crop-growth sensor. Rice test results showed that the RVI value measured by the UAV-borne multispectral sensor had good linearity with leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW); R2 was 0.62, 0.76, and 0.60, and RMSE was 2.28, 1.03, and 10.73, respectively. Our monitoring method could be well-applied to UAV-borne dual-band crop growth sensors.

Description: Shared electric vehicles (SEVs) are becoming a new way for urban residents to travel because of their environmental protection, energy saving, and sustainable development. However, at present, the operation mode of shared electric vehicles has the problem that the vehicle cannot be utilized efficiently. For this reason, this paper studied the mode of SEVs with ride-sharing (MSEVRS) and SEVs routing optimization under this mode. Firstly, the operation principle of MSEVRS is presented, which includes the collection of user demand information and SEVs information and the routing optimization of SEVs, both of which are completed by the user and SEVs management center. Secondly, the routing optimization model of SEVs with ride-sharing is proposed, in which the SEVs operation cost, user time cost, user rental cost, and user ride-sharing bonus are taken into account. And the genetic algorithm is designed to solve the model. Finally, a case study is carried out to illustrate the effectiveness of the proposed model. The results show that the proposed routing optimization model achieves the optimal SEVs route, realizes the MSEVRS, and improves the utilization rate of SEVs. Compared with the current SEVs mode (CSEVM), the MSEVRS reduces the number of vehicles, user rental cost, the total cost of users, and the total cost of user and company of SEVs. And the total distance is reduced, which means saving energy. Moreover, it shows that MSEVRS obtains a better cost performance and service for users and has a better application prospect.

Description: A new fractional two-dimensional triangle function combination discrete chaotic map (2D-TFCDM) with the discrete fractional difference is proposed. We observe the bifurcation behaviors and draw the bifurcation diagrams, the largest Lyapunov exponent plot, and the phase portraits of the proposed map, respectively. On the application side, we apply the proposed discrete fractional map into image encryption with the secret keys ciphered by Menezes-Vanstone Elliptic Curve Cryptosystem (MVECC). Finally, the image encryption algorithm is analysed in four main aspects that indicate the proposed algorithm is better than others.