FOLT: Fast Multiple Object Tracking from UAV-captured Videos Based on Optical Flow

Multiple object tracking (MOT) has been successfully investigated in computer vision. However, MOT for the videos captured by unmanned aerial vehicles (UAV) is still challenging due to small object size, blurred object appearance, and very large and/or irregular motion in both ground objects and UAV platforms. In this paper, we propose FOLT to mitigate these problems and reach fast and accurate MOT in UAV view. Aiming at speed-accuracy trade-off, FOLT adopts a modern detector and light-weight optical flow extractor to extract object detection features and motion features at a minimum cost. Given the extracted flow, the flow-guided feature augmentation is designed to augment the object detection feature based on its optical flow, which improves the detection of small objects. Then the flow-guided motion prediction is also proposed to predict the object's position in the next frame, which improves the tracking performance of objects with very large displacements between adjacent frames. Finally, the tracker matches the detected objects and predicted objects using a spatially matching scheme to generate tracks for every object. Experiments on Visdrone and UAVDT datasets show that our proposed model can successfully track small objects with large and irregular motion and outperform existing state-of-the-art methods in UAV-MOT tasks.Comment: Accepted by ACM Multi-Media 202

MePAL6 regulates lignin accumulation to shape cassava resistance against two-spotted spider mite

IntroductionThe two-spotted spider mite (TSSM) is a devastating pest of cassava production in China. Lignin is considered as an important defensive barrier against pests and diseases, several genes participate in lignin biosynthesis, however, how these genes modulate lignin accumulation in cassava and shape TSSM-resistance is largely unknown.MethodsTo fill this knowledge gap, while under TSSM infestation, the cassava lignin biosynthesis related genes were subjected to expression pattern analysis followed by family identification, and genes with significant induction were used for further function exploration.ResultsMost genes involved in lignin biosynthesis were up-regulated when the mite-resistant cassava cultivars were infested by TSSM, noticeably, the MePAL gene presented the most vigorous induction among these genes. Therefore, we paid more attention to dissect the function of MePAL gene during cassava-TSSM interaction. Gene family identification showed that there are 6 MePAL members identified in cassava genome, further phylogenetic analysis, gene duplication, cis-elements and conserved motif prediction speculated that these genes may probably contribute to biotic stress responses in cassava. The transcription profile of the 6 MePAL genes in TSSM-resistant cassava cultivar SC9 indicated a universal up-regulation pattern. To further elucidate the potential correlation between MePAL expression and TSSM-resistance, the most strongly induced gene MePAL6 were silenced using virus-induced gene silencing (VIGS) assay, we found that silencing of MePAL6 in SC9 not only simultaneously suppressed the expression of other lignin biosynthesis genes such as 4-coumarate--CoA ligase (4CL), hydroxycinnamoyltransferase (HCT) and cinnamoyl-CoA reductase (CCR), but also resulted in decrease of lignin content. Ultimately, the suppression of MePAL6 in SC9 can lead to significant deterioration of TSSM-resistance.DiscussionThis study accurately identified MePAL6 as critical genes in conferring cassava resistance to TSSM, which could be considered as promising marker gene for evaluating cassava resistance to insect pest

Effect of graphene nanoplatelets on the mechanical and gas barrier properties of woven carbon fibre/epoxy composites

From Springer Nature via Jisc Publications RouterHistory: received 2021-05-14, accepted 2021-08-14, registration 2021-08-23, pub-electronic 2021-09-05, online 2021-09-05, pub-print 2021-12Publication status: PublishedFunder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/K016946/1Abstract: Carbon-fibre-reinforced polymer (CFRP) composites are promising materials for non-metallic pipe applications in the oil and gas industry owing to their high corrosion resistance, specific strength and stiffness. However, CFRP has poor gas barrier performance meaning that a liner has to be inserted. Graphene-based nanomaterials have been demonstrated to improve gas barrier properties in thermoplastic polymers, and thus, a CFRP–graphene hybrid composite could provide an alternative to lined pipes. In this work, a method combining spray coating with vacuum-assisted resin infusion was developed to fabricate CFRP hybrid composites with preferred in-plane aligned graphene nanoplatelets. Tensile and flexural properties, as well as CO2 gas permeability, were evaluated. It was illustrated that both tensile and flexural properties performed better under relatively low GNP loadings (< 0.2 vol%), while gas barrier property was significantly improved with the increasing GNP loadings which fits the Nielsen model with an effective GNP aspect ratio of 350. Graphical abstract

Multi-Objective Joint Optimal Operation of Reservoir System and Analysis of Objectives Competition Mechanism: A Case Study in the Upper Reach of the Yangtze River

The multi-objective optimal operation and the joint scheduling of giant-scale reservoir systems are of great significance for water resource management; the interactions and mechanisms between the objectives are the key points. Taking the reservoir system composed of 30 reservoirs in the upper reaches of the Yangtze River as the research object, this paper constructs a multi-objective optimal operation model integrating four objectives of power generation, ecology, water supply, and shipping under the constraints of flood control to analyze the inside interaction mechanisms among the objectives. The results are as follows. (1) Compared with single power generation optimization, multi-objective optimization improves the benefits of the system. The total power generation is reduced by only 4.09% at most, but the water supply, ecology, and shipping targets are increased by 98.52%, 35.09%, and 100% at most under different inflow conditions, respectively. (2) The competition between power generation and the other targets is the most obvious; the relationship between water supply and ecology depends on the magnitude of flow required by the control section for both targets, and the restriction effect of the shipping target is limited. (3) Joint operation has greatly increased the overall benefits. Compared with the separate operation of each basin, the benefits of power generation, water supply, ecology, and shipping increased by 5.50%, 45.99%, 98.49%, and 100.00% respectively in the equilibrium scheme. This study provides a widely used method to analyze the multi-objective relationship mechanism, and can be used to guide the actual scheduling rules

A Practical Approach for Environmental Flow Calculation to Support Ecosystem Management in Wujiang River, China

To promote ecosystem protection in the Wujiang River, this paper proposes a practical approach for calculating the environmental flow. The proposed approach combines the idea of the &ldquo;guarantee rate&rdquo; of the flow duration curve (FDC) method and the grading idea of the Tennant method. A daily flow series of the Wujiang River was compiled from 1956 to 2019 and used to compare the effect of the proposed approach versus the traditional approaches in four selected sections along the river. The results show that the environmental flow of the Wujiang River can be divided into five levels by the T-FDC method, with a level-by-level disparity, and all levels can capture the temporal and spatial variability of river flow. Additionally, the calculated basic environmental flow process ranges between the historical minimum and second minimum monthly average flow, and the threshold width of the optimal flow is more reasonable than the Tennant method. The T-FDC method can provide technical support for Wujiang River ecosystem management and sustainable development

Automatic Detection of Track and Fields in China from High-Resolution Satellite Images Using Multi-Scale-Fused Single Shot MultiBox Detector

Object detection is facing various challenges as an important aspect in the field of remote sensing&mdash;especially in large scenes due to the increase of satellite image resolution and the complexity of land covers. Because of the diversity of the appearance of track and fields, the complexity of the background and the variety between satellite images, even superior deep learning methods have difficulty extracting accurate characteristics of track and field from large complex scenes, such as the whole of China. Taking track and field as a study case, we propose a stable and accurate method for target detection. Firstly, we add the &ldquo;deconvolution&rdquo; and &ldquo;concat&rdquo; module to the structure of the original Single Shot MultiBox Detector (SSD), where Visual Geometry Group 16 (VGG16) is served as a basic network, followed by multiple convolution layers. The two modules are used to sample the high-level feature map and connect it with the low-level feature map to form a new network structure multi-scale-fused SSD (abbreviated as MSF_SSD). MSF-SSD can enrich the semantic information of the low-level feature, which is especially effective for small targets in large scenes. In addition, a large number of track and fields are collected as samples for the whole China and a series of parameters are designed to optimize the MSF_SSD network through the deep analysis of sample characteristics. Finally, by using MSF_SSD network, we achieve the rapid and automatic detection of meter-level track and fields in the country for the first time. The proposed MSF_SSD model achieves 97.9% mean average precision (mAP) on validation set which is superior to the 88.4% mAP of the original SSD. Apart from this, the model can achieve an accuracy of 94.3% while keeping the recall rate in a high level (98.8%) in the nationally distributed test set, outperforming the original SSD method