A Novel SAR Image Ship Small Targets Detection Method

To satisfy practical requirements of high real-time accuracy and low computational complexity of synthetic aperture radar (SAR) image ship small target detection, this paper proposes a small ship target detection method based on the improved You Only Look Once Version 3 (YOLOv3). The main contributions of this study are threefold. First, the feature extraction network of the original YOLOV3 algorithm is replaced with the VGG16 network convolution layer. Second, general convolution is transformed into depthwise separable convolution, thereby reducing the computational cost of the algorithm. Third, a residual network structure is introduced into the feature extraction network to reuse the shallow target feature information, which enhances the detailed features of the target and ensures the improvement in accuracy of small target detection performance. To evaluate the performance of the proposed method, many experiments are conducted on public SAR image datasets. For ship targets with complex backgrounds and small ship targets in the SAR image, the effectiveness of the proposed algorithm is verified. Results show that the accuracy and recall rate improved by 5.31% and 2.77%, respectively, compared with the original YOLOV3. Furthermore, the proposed model not only significantly reduces the computational effort, but also improves the detection accuracy of ship small target.

Development Situations and Countermeasures of Gastrodia elata Industry in Zhaotong City

With the rapid development of technology,people's living standards have been greatly improved,and more and more people have started to care more about the theory and health preservation function of TCM.Gastrodia elata,as a precious Chinese herbal medicine,is harmless to human health.Due to the high economic benefits and real benefits for farmers,the G.elata industry has developed rapidly.Zhaotong is the hometown of G.elata f.glauca in China,but the current situation of the G.elata industry lags behind other producing areas.Through field survey and literature review,this paper comprehensively analyzed the development status of the G.elata industry in Zhaotong City.Combined with the natural conditions,policy conditions,and socio-economic conditions of the G.elata industry in Zhaotong City to find countermeasures and recommendations to promote the further development of the G.elata industry in Zhaotong and provide recommendations for the sustainable development of G.elata industry.

Microbial electrochemistry for bioremediation

Lack of suitable electron donors or acceptors is in many cases the key reason for pollutants to persist in the environment.Externally supplementation of electron donors or acceptors is often difficult to control and/or involves chemical additions with limited lifespan,residue formation or other adverse side effects.Microbial electrochemistry has evolved very fast in the past years–this field relates to the study of electrochemical interactions between microorganisms and solid-state electron donors or acceptors.Current can be supplied in such so-called bioelectrochemical systems(BESs)at low voltage to provide or extract electrons in a very precise manner.A plethora of metabolisms can be linked to electrical current now,from metals reductions to denitrification and dechlorination.In this perspective,we provide an overview of the emerging applications of BES and derived technologies towards the bioremediation field and outline how this approach can be game changing.

土壤中抗生素的环境风险及污染土壤的生物修复技术

抗生素的广泛使用导致其在环境中普遍存在,所引发的抗性基因问题已对全球公共卫生构成重大威胁。土壤是环境中抗生素的重要汇,抗生素暴露会对土壤生物带来危害,甚至会间接对人体健康造成潜在风险,因此需采取有效手段修复抗生素污染的土壤。文中综述了抗生素对土壤植物表型生长指标、土壤动物生理特征及群落分布、微生物群落组成与功能的影响,以及抗生素抗性基因在土壤生物间的传播风险等;总结了利用耐受土壤植物、动物、微生物以及其互作关系修复抗生素污染土壤的潜力与前景,指出了已有土壤中抗生素环境风险和生物修复研究中尚存在的问题,展望了未来的研究方向。

Carbon turnover times shape topsoil carbon difference between Tibetan Plateau and Arctic tundra

The Tibetan Plateau(TP)and Arctic permafrost constitute two large reservoirs of organic carbon,but processes which control carbon accumulation within the surface soil layer of these areas would differ due to the interplay of climate,soil and vegetation type.Here,we synthesized currently available soil carbon data to show that mean organic carbon density in the topsoil(0-10 cm)in TP grassland(3.12±0.52 kg C m^(-2))is less than half of that in Arctic tundra(6.70±1.94 kg C m^(-2)).Such difference is primarily attributed to their difference in radiocarbon-inferred soil carbon turnover times(547 years for TP grassland versus 1609 years for Arctic tundra)rather than to their marginal difference in topsoil carbon inputs.Our findings highlight the importance of improving regional-specific soil carbon turnover and its controlling mechanisms across permafrost affected zones in ecosystem models to fully represent carbon-climate feedback.