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Prediction of Apple Fruit Quality by Soil Nutrient Content and Artificial Neural Network 被引量:1
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作者 mengyao yan Xianqi Zeng +5 位作者 Banghui Zhang Hui Zhang Di Tan Binghua Cai Shenchun Qu Sanhong Wang 《Phyton-International Journal of Experimental Botany》 SCIE 2023年第1期193-208,共16页
The effect of soil nutrient content on fruit yield and fruit quality is very important.To explore the effect of soil nutrients on apple quality we investigated 200 fruit samples from 40 orchards in Feng County,Jiangsu... The effect of soil nutrient content on fruit yield and fruit quality is very important.To explore the effect of soil nutrients on apple quality we investigated 200 fruit samples from 40 orchards in Feng County,Jiangsu Province.Soil mineral elements and fruit quality were measured.The effect of soil nutrient content on fruit quality was analyzed by artificial neural network(ANN)model.The results showed that the prediction accuracy was highest(R2=0.851,0.847,0.885,0.678 and 0.746)in mass per fruit(MPF),hardness(HB),soluble solids concentrations(SSC),titratable acid concentration(TA)and solid-acid ratio(SSC/TA),respectively.The sensitivity analysis of the prediction model showed that soil available P,K,Ca and Mg contents had the greatest impact on the quality of apple fruit.Response surface method(RSM)was performed to determine the optimum range of the available P,K,Ca,and Mg contents in orchards In Feng County,which were 10∼20 mg⋅kg^(−1),170∼200 mg⋅kg^(−1),1000∼1500 mg⋅kg^(−1),and 80∼200 mg⋅kg^(−1),respectively.The research also concluded that improving the content of available P and available Ca in orchard soil was crucial to improve apple fruit quality in Feng County,Jiangsu Province. 展开更多
关键词 APPLE soil nutrients fruit quality artificial neural network sensitivity analysis response surface methodology analysis
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Gut liver brain axis in diseases:the implications for therapeutic interventions
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作者 mengyao yan Shuli Man +4 位作者 Benyue Sun Long Ma Lanping Guo Luqi Huang Wenyuan Gao 《Signal Transduction and Targeted Therapy》 SCIE CSCD 2024年第1期79-104,共26页
Gut-liver-brain axis is a three-way highway of information interaction system among the gastrointestinal tract,liver,and nervous systems.In the past few decades,breakthrough progress has been made in the gut liver bra... Gut-liver-brain axis is a three-way highway of information interaction system among the gastrointestinal tract,liver,and nervous systems.In the past few decades,breakthrough progress has been made in the gut liver brain axis,mainly through understanding its formation mechanism and increasing treatment strategies.In this review,we discuss various complex networks including barrier permeability,gut hormones,gut microbial metabolites,vagus nerve,neurotransmitters,immunity,brain toxic metabolites,β-amyloid(Aβ)metabolism,and epigenetic regulation in the gut-liver-brain axis.Some therapies containing antibiotics,probiotics,prebiotics,synbiotics,fecal microbiota transplantation(FMT),polyphenols,low FODMAP diet and nanotechnology application regulate the gut liver brain axis.Besides,some special treatments targeting gut-liver axis include farnesoid X receptor(FXR)agonists,takeda G protein-coupled receptor 5(TGR5)agonists,glucagon-like peptide-1(GLP-1)receptor antagonists and fibroblast growth factor 19(FGF19)analogs.Targeting gut-brain axis embraces cognitive behavioral therapy(CBT),antidepressants and tryptophan metabolism-related therapies.Targeting liver-brain axis contains epigenetic regulation and Aβmetabolism-related therapies.In the future,a better understanding of gut-liver-brain axis interactions will promote the development of novel preventative strategies and the discovery of precise therapeutic targets in multiple diseases. 展开更多
关键词 METABOLISM THERAPEUTIC IMMUNITY
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Pattern-reconfigurable antenna-assisted secret key generation from multipath fading channels
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作者 Zheng WAN mengyao yan +4 位作者 Kaizhi HUANG Zhou ZHONG Xiaoming XU Yajun CHEN Fan WU 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2023年第12期1803-1814,共12页
Physical layer key generation(PKG)technology leverages reciprocal channel randomness to generate shared secret keys.However,multipath fading at the receiver may degrade the correlation between legitimate uplink and do... Physical layer key generation(PKG)technology leverages reciprocal channel randomness to generate shared secret keys.However,multipath fading at the receiver may degrade the correlation between legitimate uplink and downlink channels,resulting in a low key generation rate(KGR).In this paper,we propose a PKG scheme based on the pattern-reconfigurable antenna(PRA)to boost the secret key capacity.First,we propose a reconfigurable intelligent surface(RIS)based PRA architecture with the capability of flexible and reconfigurable antenna patterns.Then,we present the PRA-based PKG protocol to improve the KGR via mitigation of the effects of multipath fading.Specifically,a novel algorithm for estimation of the multipath channel parameters is proposed based on atomic norm minimization.Thereafter,a novel optimization method for the matching reception of multipath signals is formulated based on the improved binary particle swarm optimization(BPSO)algorithm.Finally,simulation results show that the proposed scheme can resist multipath fading and achieve a high KGR compared to existing schemes.Moreover,our findings indicate that the increased degree of freedom of the antenna patterns can significantly increase the secret key capacity. 展开更多
关键词 Physical layer security Secret key generation Reconfigurable intelligent surface Multipath fading Pattern-reconfigurable antenna
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