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"Li, Lingling"
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Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image
This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images. Firstly, the application effects of R-CNN (Region-Convolutional Neural Network), FRCN (Fast Region-Convolutional Neural Network), and R-FCN (Region-Based-Fully Convolutional Network) in image feature extraction are analyzed after introducing the relevant region proposal network. Secondly, YOLO-v5 algorithm is established on the basis of YOLO algorithm. Besides, the multi-scale anchor mechanism of Faster R-CNN is utilized to improve the detection ability of YOLO-v5 algorithm for small targets in the image in the process of image detection, and realize the high adaptability of YOLO-v5 algorithm to different sizes of images. Finally, the proposed detection method YOLO-v5 algorithm + R-FCN is compared with other algorithms in NWPU VHR-10 data set and Vaihingen data set. The experimental results show that the YOLO-v5 + R-FCN detection method has the optimal detection ability among many algorithms, especially for small targets in remote sensing images such as tennis courts, vehicles, and storage tanks. Moreover, the YOLO-v5 + R-FCN detection method can achieve high recall rates for different types of small targets. Furthermore, due to the deeper network architecture, the YOL v5 + R-FCN detection method has a stronger ability to extract the characteristics of image targets in the detection of remote sensing images. Meanwhile, it can achieve more accurate feature recognition and detection performance for the densely arranged target images in remote sensing images. This research can provide reference for the application of remote sensing technology in China, and promote the application of satellites for target detection tasks in related fields.
Journal Article
Microbial production of ectoine and hydroxyectoine as high-value chemicals
Ectoine and hydroxyectoine as typical representatives of compatible solutes are not only essential for extremophiles to survive in extreme environments, but also widely used in cosmetic and medical industries. Ectoine was traditionally produced by
Halomonas elongata
through a “bacterial milking” process, of which the marked feature is using a high-salt medium to stimulate ectoine biosynthesis and then excreting ectoine into a low-salt medium by osmotic shock. The optimal hydroxyectoine production was achieved by optimizing the fermentation process of
Halomonas salina
. However, high-salinity broth exacerbates the corrosion to fermenters, and more importantly, brings a big challenge to the subsequent wastewater treatment. Therefore, increasing attention has been paid to reducing the salinity of the fermentation broth but without a sacrifice of ectoine/hydroxyectoine production. With the fast development of functional genomics and synthetic biology, quite a lot of progress on the bioproduction of ectoine/hydroxyectoine has been achieved in recent years. The importation and expression of an ectoine producing pathway in a non-halophilic chassis has so far achieved the highest titer of ectoine (~ 65 g/L), while rational flux-tuning of halophilic chassis represents a promising strategy for the next-generation of ectoine industrial production. However, efficient conversion of ectoine to hydroxyectoine, which could benefit from a clearer understanding of the ectoine hydroxylase, is still a challenge to date.
Journal Article
Size and shape control of LiFePO4 nanocrystals for better lithium ion battery cathode materials
Lithium iron phosphate （LiFePO4） is a potential high efficiency cathode material for lithium ion batteries, but the low electronic conductivity and single diffusion channel for lithium ions require good particle size and shape control during the synthesis of this material. In this paper, six LiFePO4 nanocrystals with different size and shape have been successfully synthesized in ethylene glycol. The addition sequence Fe-PO4-Li helps to form LiFePO4 nanocrystals with mostly {010} faces exposed, and increasing the amount of LiOH leads to a decrease in particle size. The electrochemical performance of the six distinct LiFePO4 particles show that the most promising LiFePO4 nanocrystals either have predominant {010} face exposure or high specific area, with little iron（II） oxidation.
Journal Article
Evaluation of China’s Targeted Poverty Alleviation Policies: A Decomposition Analysis Based on the Poverty Reduction Effects
To achieve comprehensive poverty alleviation and the establishment of a “moderately prosperous society” in China, it is crucial to evaluate the targeted poverty alleviation (TPA) policies. In this study, China’s poverty alleviation statistics and the Foster-Greene-Thorbecke (FGT) indices are used to measure the poverty reduction effects of the TPA policies. A panel regression model is applied to analyze the poverty reduction mechanism while the Shapley index decomposition method is used to analyze poverty reduction effects in terms of income growth and the income gap adjustment. The paper concludes that the poverty breadth index (H index), poverty depth index (PG index), and poverty intensity index (SPG index) from 2013 to 2019 show a significant decline overall. This indicates that the poverty reduction effect of the TPA policies is significant. In addition, the regression analysis shows that the implementation of TPA policies can significantly increase the income level of residents and narrow the income gap among residents in rural areas. Results of the Shapley index decomposition analysis revealed that the income growth effect and income gap adjustment effect accounted for 92.78% and 7.22% of the poverty reduction effects, respectively. So the focus of future poverty alleviation work is to combine the rural revitalization strategy and to continue increasing the income level and the income growth rate of poor groups, which will enhance the ability of impoverished residents to increase their income, further contributing to the alleviation of poverty.
Journal Article
A comprehensive approach to parameters optimization of energy-aware CNC milling
Cutting parameters are important components in the process of computer numerical control (CNC) machining, and reasonable choice of cutting parameters can significantly affect the energy efficiency. This paper presents a multi-objective parameter optimization method for energy efficiency in CNC milling process. Firstly, the energy consumption composition characteristics and temporal characteristics in CNC milling are analyzed, respectively. The energy model of CNC milling is then established, of which the correlation coefficient is obtained through nonlinear regression fitting. Then a multi-objective optimization model is proposed to take the highest energy efficiency and the minimum production time as the optimization objectives, which is solved based on Tabu search algorithm. Finally, a case study is conducted to validate the proposed multi-objective optimization model and the optimal parameter solutions of maximum energy efficiency and minimum production time is obtained. Moreover, the parametric influence on specific energy consumption and production time are explicitly analyzed. The experiment results show that cutting depth and width are the most influential parameters for specific energy consumption, and spindle speed ranks the first for the production time.
Journal Article
Mathematical modeling the order of driver gene mutations in colorectal cancer
Tumor heterogeneity is a large obstacle for cancer study and treatment. Different cancer patients may involve different combinations of gene mutations or the distinct regulatory pathways for inducing the progression of tumor. Investigating the pathways of gene mutations which can cause the formation of tumor can provide a basis for the personalized treatment of cancer. Studies suggested that KRAS, APC and TP53 are the most significant driver genes for colorectal cancer. However, it is still an open issue regarding the detailed mutation order of these genes in the development of colorectal cancer. For this purpose, we analyze the mathematical model considering all orders of mutations in oncogene, KRAS and tumor suppressor genes, APC and TP53, and fit it on data describing the incidence rates of colorectal cancer at different age from the Surveillance Epidemiology and End Results registry in the United States for the year 1973–2013. The specific orders that can induce the development of colorectal cancer are identified by the model fitting. The fitting results indicate that the mutation orders with KRAS → APC → TP 53, APC → TP 53 → KRAS and APC → KRAS → TP 53 explain the age–specific risk of colorectal cancer with very well. Furthermore, eleven pathways of gene mutations can be accepted for the mutation order of genes with KRAS → APC → TP 53, APC → TP 53 → KRAS and APC → KRAS → TP 53, and the alternation of APC acts as the initiating or promoting event in the colorectal cancer. The estimated mutation rates of cells in the different pathways demonstrate that genetic instability must exist in colorectal cancer with alterations of genes, KRAS, APC and TP53.
Journal Article
The fourth crystallographic closest packing unveiled in the gold nanocluster crystal
Metal nanoclusters have recently attracted extensive interest not only for fundamental scientific research, but also for practical applications. For fundamental scientific research, it is of major importance to explore the internal structure and crystallographic arrangement. Herein, we synthesize a gold nanocluster whose composition is determined to be Au
60
S
6
(SCH
2
Ph)
36
by using electrospray ionization mass spectrometry and single crystal X-ray crystallography (SCXC). SCXC also reveals that Au
60
S
6
(SCH
2
Ph)
36
consists of a fcc-like Au
20
kernel protected by a pair of giant Au
20
S
3
(SCH
2
Ph)
18
staple motifs, which contain 6 tetrahedral-coordinate
μ
4
-S atoms not previously reported in the Au–S interface. Importantly, the fourth crystallographic closest-packed pattern, termed 6H left-handed helical (6HLH) arrangement, which results in the distinct loss of solid photoluminescence of amorphous Au
60
S
6
(SCH
2
Ph)
36
, is found in the crystals of Au
60
S
6
(SCH
2
Ph)
36
. The solvent-polarity-dependent solution photoluminescence is also demonstrated. Overall, this work provides important insights about the structure, Au–S bonding and solid photoluminescence of gold nanoclusters.
Metal nanoclusters are explored for their precise structures and compelling properties. Here, the authors synthesize a gold cluster with unique structural features, including giant staple motifs, tetrahedral-coordinate
μ
4
-S atoms, and a helical closest-packed crystallographic pattern that influences the cluster’s photoluminescence.
Journal Article
Effects of Straw Mulching and Reduced Tillage on Crop Production and Environment: A Review
Taking sustainable agriculture measures is critical to effectively cope with the effect of the increasing population on water shortage. Straw mulching and reduced tillage are the most successful measures adopted in arid and semi-arid regions which affect crop production by changing the crop environment. This review focuses on the effects of tillage and mulching on the soil environment, including soil organic matter, soil moisture, soil temperature, soil microorganisms, soil enzyme activity, soil fertility, soil carbon emissions, pests, weeds, and soil erosion. In addition, water use efficiency and crop production are discussed under different tillage measures. Straw mulching can increase soil organic matter content, adjust soil moisture, and prevent water loss and drought; however, it can also lead to an increase in pests and diseases, and change the structure of the soil microbial community. Straw mulching can significantly enhance WUE (water use effectively) and yield. Reducing tillage maintains soil integrity, which is conducive to soil and water conservation, but could negatively impact crop yield and WUE. Precise field management measures, taken according to crop varieties and local conditions, not only ensure the high yield of crops but also protect the environment.
Journal Article
A Remaining Useful Life Prognosis of Turbofan Engine Using Temporal and Spatial Feature Fusion
The prognosis of the remaining useful life (RUL) of turbofan engine provides an important basis for predictive maintenance and remanufacturing, and plays a major role in reducing failure rate and maintenance costs. The main problem of traditional methods based on the single neural network of shallow machine learning is the RUL prognosis based on single feature extraction, and the prediction accuracy is generally not high, a method for predicting RUL based on the combination of one-dimensional convolutional neural networks with full convolutional layer (1-FCLCNN) and long short-term memory (LSTM) is proposed. In this method, LSTM and 1- FCLCNN are adopted to extract temporal and spatial features of FD001 andFD003 datasets generated by turbofan engine respectively. The fusion of these two kinds of features is for the input of the next convolutional neural networks (CNN) to obtain the target RUL. Compared with the currently popular RUL prediction models, the results show that the model proposed has higher prediction accuracy than other models in RUL prediction. The final evaluation index also shows the effectiveness and superiority of the model.
Journal Article