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| 1 | Spatial and temporal change patterns of net primary productivity and its response to climate change in the Qinghai–Tibet Plateau of China from 2000 to 2015显示文摘The vegetation ecosystem of the Qinghai–Tibet Plateau in China,considered to be the′′natural laboratory′′of climate change in the world,has undergone profound changes under the stress of global change.Herein,we analyzed and discussed the spatial-temporal change patterns and the driving mechanisms of net primary productivity(NPP)in the Qinghai–Tibet Plateau from 2000 to 2015 based on the gravity center and correlation coefficient models.Subsequently,we quantitatively distinguished the relative effects of climate change(such as precipitation,temperature and evapotranspiration)and human activities(such as grazing and ecological construction)on the NPP changes using scenario analysis and Miami model based on the MOD17A3 and meteorological data.The average annual NPP in the Qinghai–Tibet Plateau showed a decreasing trend from the southeast to the northwest during 2000–2015.With respect to the inter-annual changes,the average annual NPP exhibited a fluctuating upward trend from 2000 to 2015,with a steep increase observed in 2005 and a high fluctuation observed from 2005 to 2015.In the Qinghai–Tibet Plateau,the regions with the increase in NPP(change rate higher than 10%)were mainly concentrated in the Three-River Source Region,the northern Hengduan Mountains,the middle and lower reaches of the Yarlung Zangbo River,and the eastern parts of the North Tibet Plateau,whereas the regions with the decrease in NPP(change rate lower than–10%)were mainly concentrated in the upper reaches of the Yarlung Zangbo River and the Ali Plateau.The gravity center of NPP in the Qinghai–Tibet Plateau has moved southwestward during 2000–2015,indicating that the increment and growth rate of NPP in the southwestern part is greater than those of NPP in the northeastern part.Further,a significant correlation was observed between NPP and climate factors in the Qinghai–Tibet Plateau.The regions exhibiting a significant correlation between NPP and precipitation were mainly located in the central and eastern Qinghai–Tibet Plateau,and the regions exhibiting a significant correlation between NPP and temperature were mainly located in the southern and eastern Qinghai–Tibet Plateau.Furthermore,the relative effects of climate change and human activities on the NPP changes in the Qinghai–Tibet Plateau exhibited significant spatial differences in three types of zones,i.e.,the climate change-dominant zone,the human activity-dominant zone,and the climate change and human activity interaction zone.These research results can provide theoretical and methodological supports to reveal the driving mechanisms of the regional ecosystems to the global change in the Qinghai–Tibet Plateau. | GUO Bing ZANG Wenqian YANG Fei HAN Baomin CHEN Shuting LIU Yue YANG Xiao HE Tianli CHEN Xi LIU Chunting GONG Rui | 2020 | Journal of Arid Land2020，12，1： | 12 |
| 2 | Deer Body Adaptive Threshold Segmentation Algorithm Based on Color Space显示文摘In large-scale deer farming image analysis,K-means or maximum between-class variance(Otsu)algorithms can be used to distinguish the deer from the background.However,in an actual breeding environment,the barbed wire or chain-link fencing has a certain isolating effect on the deer which greatly interferes with the identification of the individual deer.Also,when the target and background grey values are similar,the multiple background targets cannot be completely separated.To better identify the posture and behaviour of deer in a deer shed,we used digital image processing to separate the deer from the background.To address the problems mentioned above,this paper proposes an adaptive threshold segmentation algorithm based on color space.First,the original image is pre-processed and optimized.On this basis,the data are enhanced and contrasted.Next,color space is used to extract the several backgrounds through various color channels,then the adaptive space segmentation of the extracted part of the color space is performed.Based on the segmentation effect of the traditional Otsu algorithm,we designed a comparative experiment that divided the four postures of turning,getting up,lying,and standing,and successfully separated multiple target deer from the background.Experimental results show that compared with K-means,Otsu and hue saturation value(HSV)+K-means,this method is better in performance and accuracy for adaptive segmentation of deer in artificial breeding scenes and can be used to separate artificially cultivated deer from their backgrounds.Both the subjective and objective aspects achieved good segmentation results.This article lays a foundation for the effective identification of abnormal behaviour in sika deer. | Yuheng Sun Ye Mu Qin Feng Tianli Hu He Gong Shijun Li Jing Zhou | 2020 | Computers, Materials & Continua2020，，8： | 5 |
| 3 | A Novel Hybrid Tag Identification Protocol for Large-Scale RFID Systems显示文摘Radio frequency identification technology is one of the main technologies of Internet of Things(IoT).Through the transmission and reflection of wireless radio frequency signals,non-contact identification is realized,and multiple objects identification can be realized.However,when multiple tags communicate with a singleton reader simultaneously,collision will occur between the signals,which hinders the successful transmissions.To effectively avoid the tag collision problem and improve the reading performance of RFID systems,two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha(AMTS)based on the characteristics of Aloha-based and Query tree-based algorithms are proposed.In AMTS,the reader firstly uses the framed slotted Aloha protocol to map the tag set to different time slots,and then identify the collided tags using binary search method based on collision factor or mapping table.Both performance analysis and extensive experimental results indicate that our proposed algorithms significantly outperforms most existing anti-collision approaches in tag dense RFID systems. | Ye Mu Ruiwen Ni Yuheng Sun Tong Zhang Ji Li Tianli Hu He Gong Shijun Li Thobela Louis Tyasi | 2021 | Computers, Materials & Continua2021，，8： | 1 |
| 4 | Hydrogen Sulfide-Specific and NIR-Light-Controllable Synergistic Activation of Fluorescent Theranostic Prodrugs for Imaging-Guided Chemo- Photothermal Cancer Therapy显示文摘Theranostic prodrugs are promising for cancer medicine;however,the inability to activate these systems exclusively at the desired tumor location compromises the specificity and efficacy of cancer treatment.Here,we developed a fluorescent theranostic nanoprodrug with synergistic hydrogen-sulfidespecific and near-infrared(NIR)-light-controllable activation for imaging-guided chemo-photothermal cancer therapy.This nanoprodrug system was fabricated by the inclusion of hydrogen sulfide(H2S)-activatable small molecule to the theranostic prodrug and a photothermal transducer in the interior of a NIR-light-responsive container. | Ge Xu Wei Guo Xianfeng Gu Zhijun Wang Rongchen Wang Tianli Zhu He Tian Chunchang Zhao | 2020 | CCS Chemistry2020，2，4： | 1 |
| 5 | A Lightweight Model of VGG-U-Net for Remote Sensing Image Classification显示文摘Remote sensing image analysis is a basic and practical research hotspot in remote sensing science.Remote sensing images contain abundant ground object information and it can be used in urban planning,agricultural monitoring,ecological services,geological exploration and other aspects.In this paper,we propose a lightweight model combining vgg-16 and u-net network.By combining two convolutional neural networks,we classify scenes of remote sensing images.While ensuring the accuracy of the model,try to reduce the memory of themodel.According to the experimental results of this paper,we have improved the accuracy of the model to 98%.The memory size of the model is 3.4 MB.At the same time,The classification and convergence speed of the model are greatly improved.We simultaneously take the remote sensing scene image of 64×64 as input into the designed model.As the accuracy of the model is 97%,it is proved that the model designed in this paper is also suitable for remote sensing images with few target feature points and low accuracy.Therefore,the model has a good application prospect in the classification of remote sensing images with few target feature points and low pixels. | Mu Ye Li Ji Luo Tianye Li Sihan Zhang Tong Feng Ruilong Hu Tianli Gong He Guo Ying Sun Yu Thobela Louis Tyasi Li Shijun | 2022 | Computers, Materials & Continua2022，，12： | 1 |
| 6 | Alkaline Phosphatase-Initiated Sensitive Responsiveness of Activatable Probes to Hydrogen Sulfide for Accurate Cancer Imaging and Differentiation显示文摘Optical imaging with molecular probes is becoming an essential tool for advancing biological research and clinical applications.However,most currently available molecular probes show limited sensitivity,specificity,and accuracy due to their typical responsiveness to a single stimulation for biomarker-based imaging.In this study,we develop a novel molecular probe that shows alkaline phosphatase(ALP)-instructed sensitive responsiveness to hydrogen sulfide for accurate cancer imaging and differentiation.This designed probe in an aggregated state under physiological conditions bears negatively charged surfaces,giving poor optical response to H_(2)S.The ALP-mediated dephosphorylation reaction yields an assembled product with a positively charged surface,affording significantly aggregation-enhanced responsiveness to H_(2)S with light-up NIR fluorescence at 755 nm.Such charge reversal of assembled probe from negative to positive plays a vital role in allowing precise visualization and differentiation of cancers based on differences in ALP upregulation and H_(2)S content.We envisage that our charge-reversal strategy for multiple-parameter-activated molecule probes will facilitate boosting the specificity and precision of cancer imaging. | Rongchen Wang Kai Yin Muye Ma Tianli Zhu Jinzhu Gao Jie Sun Xuemei Dong Chengjun Dong Xianfeng Gu He Tian Chunchang Zhao | 2022 | CCS Chemistry2022，4，12： | 0 |
| 7 | Segmentation of Remote Sensing Images Based on U-Net Multi-Task Learning显示文摘In order to accurately segment architectural features in highresolution remote sensing images,a semantic segmentation method based on U-net network multi-task learning is proposed.First,a boundary distance map was generated based on the remote sensing image of the ground truth map of the building.The remote sensing image and its truth map were used as the input in the U-net network,followed by the addition of the building ground prediction layer at the end of the U-net network.Based on the ResNet network,a multi-task network with the boundary distance prediction layer was built.Experiments involving the ISPRS aerial remote sensing image building and feature annotation data set show that compared with the full convolutional network combined with the multi-layer perceptron method,the intersection ratio of VGG16 network,VGG16+boundary prediction,ResNet50 and the method in this paper were increased by 5.15%,6.946%,6.41%and 7.86%.The accuracy of the networks was increased to 94.71%,95.39%,95.30%and 96.10%respectively,which resulted in high-precision extraction of building features. | Ni Ruiwen Mu Ye Li Ji Zhang Tong Luo Tianye Feng Ruilong Gong He Hu Tianli Sun Yu Guo Ying Li Shijun Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，11： | 0 |
| 8 | Stereodivergently asymmetric synthesis of chiral phosphorus compounds by synergistic combination of ion-pair catalyst and base显示文摘Stereodivergently constructing the designed products having adjacent multi-stereocenters via a given reaction,with excellent control of both absolute and relative configurations,presents one of the substantial hurdles in asymmetric catalysis.Herein,we report a precisely stereodivergent asymmetric protocol by synergistic combination of phosphonium-involved ion-pair catalysis and base for accessing to chiral phosphorus compounds bearing two adjacent chiral centers particularly containing an acidic protonated enantioenriched carbon atom,having broad functional group compatibility in both dynamic and thermodynamic processes under mild reaction conditions.Two keys for the success in constructing these stereoisomers with high levels of regio-,diastereo-,and enantioselectivities were contained:firstly,the precise stereo-control in providing dynamic products was enabled by bifunctional phosphonium salt catalyst with semi-enclosed cavity;secondly,the readily stereospecific transformation of adducts from dynamic to thermodynamic version was initiated by achiral base.All four stereoisomers could be readily accessed even in gram-scale in high yields with maintaining excellent stereoselectivities,illustrating the potential of this synergistic catalytic methodology in organic synthesis.Moreover,mechanistic studies including density functional theory(DFT)calculations and control experiments provide insights into the mechanism. | Hui-Lin Hu Xiaoyu Ren Jiajia He Lixiang Zhu Siqiang Fang Zhishan Su Tianli Wang | 2022 | Science China Chemistry2022，65，12： | 0 |
| 9 | Sika Deer Facial Recognition Model Based on SE-ResNet显示文摘The scale of deer breeding has gradually increased in recent years and better information management is necessary,which requires the identification of individual deer.In this paper,a deer face dataset is produced using face images obtained from different angles,and an improved residual neural network(ResNet)-based recognition model is proposed to extract the features of deer faces,which have high similarity.The model is based on ResNet-50,which reduces the depth of the model,and the network depth is only 29 layers;the model connects Squeeze-and-Excitation(SE)modules at each of the four layers where the channel changes to improve the quality of features by compressing the feature information extracted through the entire layer.A maximum pooling layer is used in the ResBlock shortcut connection to reduce the information loss caused by messages passing through the ResBlock.The Rectified Linear Unit(ReLU)activation function in the network is replaced by the Exponential Linear Unit(ELU)activation function to reduce information loss during forward propagation of the network.The preprocessed 6864 sika deer face dataset was used to train the recognition model based on SEResnet,which is demonstrated to identify individuals accurately.By setting up comparative experiments under different structures,the model reduces the amount of parameters,ensures the accuracy of the model,and improves the calculation speed of the model.Using the improved method in this paper to compare with the classical model and facial recognition models of different animals,the results show that the recognition effect of this research method is the best,with an average recognition accuracy of 97.48%.The sika deer face recognition model proposed in this study is effective.The results contribute to the practical application of animal facial recognition technology in the breeding of sika deer and other animals with few distinct facial features. | He Gong Lin Chen Haohong Pan Shijun Li Yin Guo Lili Fu Tianli Hu Ye Mu Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，9： | 0 |
| 10 | Sika Deer Behavior Recognition Based on Machine Vision显示文摘With the increasing intensive and large-scale development of the sika deer breeding industry,it is crucial to assess the health status of the sika deer by monitoring their behaviours.A machine vision-based method for the behaviour recognition of sika deer is proposed in this paper.Google Inception Net(GoogLeNet)is used to optimise the model in this paper.First,the number of layers and size of the model were reduced.Then,the 5×5 convolution was changed to two 3×3 convolutions,which reduced the parameters and increased the nonlinearity of the model.A 5×5 convolution kernel was used to replace the original convolution for extracting coarse-grained features and improving the model’s extraction ability.A multi-scale module was added to the model to enhance the multi-faceted feature extraction capability of the model.Simultaneously,the Squeeze-and-Excitation Networks(SE-Net)module was included to increase the channel’s attention and improve the model’s accuracy.The dataset’s images were rotated to reduce overfitting.For image rotation,the angle wasmultiplied by 30°to obtain the dataset enhanced by rotation operations of 30°,60°,90°,120°and 150°.The experimental results showed that the recognition rate of this model in the behaviour of sika deer was 98.92%.Therefore,the model presented in this paper can be applied to the behaviour recognition of sika deer.The results will play an essential role in promoting animal behaviour recognition technology and animal health monitoring management. | He Gong Mingwang Deng Shijun Li Tianli Hu Yu Sun Ye Mu Zilian Wang Chang Zhang Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，12： | 0 |
| 11 | Flexible Strain Sensor Based on 3D Electrospun Carbonized Sponge显示文摘Flexible strain sensor has attracted much attention because of its potential application in human motion detection.In this work,the prepared strain sensor was obtained by encapsulating electrospun carbonized sponge(CS)with room temperature vulcanized silicone rubber(RTVS).In this paper,the formation mechanism of conductive sponge was studied.Based on the combination of carbonized sponge and RTVS,the strain sensing mechanism and piezoresistive properties are discussed.After research and testing,the CS/RTVS flexible strain sensor has excellent fast response speed and stability,and the maximum strain coefficient of the sensor is 136.27.In this study,the self-developed CS/RTVS sensor was used to monitor the movements of the wrist joint,arm elbow joint and fingers in real time.Research experiments show that CS/RTVS flexible strain sensor has good application prospects in the field of human motion monitoring. | He Gong Zilian Wang Zhiqiang Cheng Lin Chen Haohong Pan Daming Zhang Tianli Hu Thobela Louis Tyasi | 2022 | Computers, Materials & Continua2022，，12： | 0 |
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