MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks

Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, bio-interpretability is partially neglected in those BP-based algorithms. Toward bio-plausible BP-based SNNs, we consider three properties in modeling spike activities: Multiplicity, Adaptability, and Plasticity (MAP). In terms of multiplicity, we propose a Multiple-Spike Pattern (MSP) with multiple spike transmission to strengthen model robustness in discrete time-iteration. To realize adaptability, we adopt Spike Frequency Adaption (SFA) under MSP to decrease spike activities for improved efficiency. For plasticity, we propose a trainable convolutional synapse that models spike response current to enhance the diversity of spiking neurons for temporal feature extraction. The proposed SNN model achieves competitive performances on neuromorphic datasets: N-MNIST and SHD. Furthermore, experimental results demonstrate that the proposed three aspects are significant to iterative robustness, spike efficiency, and temporal feature extraction capability of spike activities. In summary, this work proposes a feasible scheme for bio-inspired spike activities with MAP, offering a new neuromorphic perspective to embed biological characteristics into spiking neural networks

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

Perception of Leisure Agricultural Tourism Image Based on Wed Text Analysis: Case of Yearning Tea Plantation

With the in-depth development of online tourism platforms, the online review of products in scenic spots has become an important basis for tourism consumption decisions. Through data mining and analysis of the online review of products in scenic spots, the tourism image perceived by tourists has become an important way to study the tourism image of scenic spots. Taking the Yearning Tea Plantation as an example, the word frequency and the content of tourism image attributes were analyzed by using the ROST CM6 content mining system software to comment on the online tourism platform for the sample of tourists, to understand the tourists’ perception of the tourism image of the Yearning Tea Plantation, and to provide the basis for the improvement and improvement of the tourism image of the leisure agriculture scenic spot

Tape bonding of micro droplet generation thermoplastics devices

Microfluidics and microfluidic droplet technique is a hot topic of study in the recent years. It is crucial to a wide array of industries, with various important utilities in modern life. Microfluidic devices can improve the quality of emulsions by controlling the droplet size formed. PMMA, poly(methyl methacrylate) has low material cost, and is often used as a lightweight, shatter-resistant alternative to glass. Methods such as micro-injection molding can be used in making PMMA microfluidic substrates with open micro-channels. These micro-channels need to be sealed before the microfluidic device is rendered usable. Various bonding methods, such as bonding with heat, where plastic molecules are fused together, and bonding without heat, where adhesive and chemical solvents are used, are employed to seal the micro-channels. In this project, the effectiveness of tape bonding on PMMA microfluidic substrate was tested with air, water and oil. Transparent or highly translucent commercial tapes were obtained, and the experiments were done by increasing the pressures on these fluids in the micro channels, then noting down the delamination value. The results obtained from these pressure delamination tests were recorded and analysed. Thereafter, adhesive tests were also performed using the tape, in order to determine which tape adhesive was more resistant to both water and oil. This was to determine both the tensile and shear adhesion strength of the tape adhesion to the PMMA substrate. As these experiments cannot be conducted with existing equipment in the lab, rigs to hold the PMMA micro fluidic substrate and the tape were designed and manufactured.Bachelor of Engineering (Mechanical Engineering

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

Combined Impacts of ENSO and IOD on Streamflow: A Case Study of the Jinsha River Basin, China

This study investigated the combined impacts of the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on streamflow under four scenarios: neutral, pure ENSO, pure IOD, and a combination of ENSO and IOD. The Jinsha River Basin (JRB), at the head of the Yangtze River, was used as a case study. By using statistical methods such as coherent wavelet analysis (WTC), we are committed to studying what kind of impact the IOD will have, the difference in impact between ENSO and IOD at different stages, and the difference in impact between ENSO and IOD on the mean and extreme values of runoff, compared with traditional single ENSO event, to provide support for water resource management, especially for reservoir operation. The key results are as follows. (a) Both ENSO and IOD events affect annual and seasonal streamflow in the JRB. (b) The impact of pure IOD events on annual streamflow in the JRB was twice as great as that of pure ENSO events in developing years, whereas the opposite was true in decaying years. (c) The combined impact of ENSO and IOD led to a higher streamflow maximum than the annual or seasonal average streamflow. Conversely, their impact on the streamflow minima was less than 10% during both developing and decaying years, except at Zhimenda Station. (d) Overall, water shortages could be more serious in developing years than in neutral years, and much more attention should be given to flooding control in decaying years. These results can be used as a reference for water resource management concerning agricultural planning and ecological protection in the JRB

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 “guarantee rate” 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—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 “deconvolution” and “concat” 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