The continuous increase of human mobility combined with a relevant use of private vehicles contributes to increase the ill effects of vehicle externalities on the environment, e.g. high levels of air pollution, toxic ...The continuous increase of human mobility combined with a relevant use of private vehicles contributes to increase the ill effects of vehicle externalities on the environment, e.g. high levels of air pollution, toxic emissions, noise pollution, and on the quality of life, e.g. parking problem, traffic congestion, and increase in the number of crashes and accidents. Transport demand management plays a very critical role in achieving greenhouse gas emission reduction targets. This study demonstrates that car pooling (CP) is an effective strategy to reduce transport volumes, transportation costs and related hill externalities in agreement with EU programs of emissions reduction targets. This paper presents an original approach to solve the CP problem. It is based on hierarchical clustering models, which have been adopted by an original decision support system (DSS). The DSS helps mobility managers to generate the pools and to design feasible paths for shared vehicles. A significant case studies and obtained results by the application of the proposed models are illustrated. They demonstrate the effectiveness of the approach and the supporting decisions tool.展开更多
In January 2022,China introduced a national pooling system for pension insurance fund,With the objective of inter-regional fund surplus and deficit adjustment.With the ongoing trend of population aging,can the nationa...In January 2022,China introduced a national pooling system for pension insurance fund,With the objective of inter-regional fund surplus and deficit adjustment.With the ongoing trend of population aging,can the national pooling and adjustment system operate sustainably?What level of fiscal obligations does it entail?This is related to the long-term stability of pension insurance fund and the whole social security system.This paper employs econometric and actuarial models to assess the sustainability of the national pooling and adjustment system under five scenarios:(1)not introducing any policy interventions;(2)implementing parameter reforms such as expanding pension insurance coverage,progressively extending retirement age,and enhancing collection rates;(3)transferring state-owned capital from central state-owned enterprises to strengthen the social security fund;(4)transitioning the national pooling and adjustment system from turning over current surplus to accumulated surplus;and(5)implementing all parameter reforms,transferring state-owned capital,and turning over accumulated surpluses.The results suggest that a coordinated implementation of reform measures like pension insurance parameter adjustments,reallocation of state-owned capital to enhance social security funds,and leveraging the national pooling and adjustment system for turning over accumulated surplus can ensure the sustainability of the system and significantly alleviatefiscalpressures.展开更多
Edge deployment solutions based on convolutional neural networks(CNNs)have garnered significant attention because of their potential applications.However,traditional CNNs rely on pooling to reduce the feature size,lea...Edge deployment solutions based on convolutional neural networks(CNNs)have garnered significant attention because of their potential applications.However,traditional CNNs rely on pooling to reduce the feature size,leading to substantial information loss and reduced network robustness.Herein,we propose a more robust adaptive pooling network(APN)method implemented using memristor technology.Our method introduces an improved pooling layer that reduces input features to an arbitrary scale without compromising their importance.Different coupling coefficients of the pooling layer are stored as conductance values in arrays.We validate the proposed APN on generic datasets,demonstrating significant performance improvements over previously reported CNN architectures.Additionally,we evaluate the APN on a CAPTCHA recognition task with perturbations to assess network robustness.The results show that the APN achieves 92.6% accuracy in 4-digit CAPTCHA recognition and exhibits higher robustness.This brief presents a highly robust and novel scheme for edge computing using memristor technology.展开更多
This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Tradi...This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Traditional tool monitoring methods that rely on empirical knowledge or limited mathematical models struggle to adapt to complex and dynamic machining environments.To address this,we implement real-time tool condition recognition by introducing deep learning technology.Aiming to the insufficient recognition accuracy,we propose a pyramid pooling-based vision Transformer network(P2ViT-Net)method for tool condition recognition.Using images as input effectively mitigates the issue of low-dimensional signal features.We enhance the vision Transformer(ViT)framework for image classification by developing the P2ViT model and adapt it to tool condition recognition.Experimental results demonstrate that our improved P2ViT model achieves 94.4%recognition accuracy,showing a 10%improvement over conventional ViT and outperforming all comparative convolutional neural network models.展开更多
With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance systems.This technology plays a critical role in enhan...With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance systems.This technology plays a critical role in enhancing public safety.However,traditional methods typically process images and text separately,applying upstream models directly to downstream tasks.This approach significantly increases the complexity ofmodel training and computational costs.Furthermore,the common class imbalance in existing training datasets limitsmodel performance improvement.To address these challenges,we propose an innovative framework named Person Re-ID Network Based on Visual Prompt Technology andMulti-Instance Negative Pooling(VPM-Net).First,we incorporate the Contrastive Language-Image Pre-training(CLIP)pre-trained model to accurately map visual and textual features into a unified embedding space,effectively mitigating inconsistencies in data distribution and the training process.To enhancemodel adaptability and generalization,we introduce an efficient and task-specific Visual Prompt Tuning(VPT)technique,which improves the model’s relevance to specific tasks.Additionally,we design two key modules:the Knowledge-Aware Network(KAN)and theMulti-Instance Negative Pooling(MINP)module.The KAN module significantly enhances the model’s understanding of complex scenarios through deep contextual semantic modeling.MINP module handles samples,effectively improving the model’s ability to distinguish fine-grained features.The experimental outcomes across diverse datasets underscore the remarkable performance of VPM-Net.These results vividly demonstrate the unique advantages and robust reliability of VPM-Net in fine-grained retrieval tasks.展开更多
The organic carbon contents,carbon density and carbon storage of the soil in the Pinus koraiensis plantation ecosystem were investigated in Maoershan experimental forest farm,Shangzhi County,Heilongjiang,on the west s...The organic carbon contents,carbon density and carbon storage of the soil in the Pinus koraiensis plantation ecosystem were investigated in Maoershan experimental forest farm,Shangzhi County,Heilongjiang,on the west slope of the Zhangguangcai Mountains in northeastern China for providing data to evaluation of the carbon balance in forest ecosystem of northeastern China.These soil carbon indicators were measured in three forest types,pure P.koraiensis plantation,P.koraiensis and Betula platyphylla mixed forest,and the P.koraiensis and Quercus mongolica mixed forest.The soil carbon pool consisted of four compartments,namely L layer,F layer,H layer and B layer.With variance analysis,we found that both organic carbon content and carbon density of the soil were significantly affected by forest types,soil compartments and slope positions.The highest soil carbon density（278.63 Mg·ha^-1）.was observed in the mixed forest of P.koraiensis and Q.mongolica.The B layer had the highest carbon density（212.28 Mg·ha^-1） among all the soil compartments.In terms of slope position,the highest soil carbon density（394.18 Mg·ha^-1） presented in the low slope.Besides,soil carbon content and carbon density had a marked change with the organic matter content and vertical depth of the soil in each compartment.The results of this study implied that in the temperate humid region,the mixed ecosystem of regional Pinus koraiensis plantations and natural forest had relatively high carbon storage capability.展开更多
[Objective] This study aimed to optimize the PCR amplification conditions for random ssDNA pool in SELEX technology. [Method] L16（45） orthogonal experimental design was adopted for optimization of five important fac...[Objective] This study aimed to optimize the PCR amplification conditions for random ssDNA pool in SELEX technology. [Method] L16（45） orthogonal experimental design was adopted for optimization of five important factors affecting PCR reaction system for random single-stranded DNA pool including Mg2＋ concentration, dNTP concentration, amount of Taq DNA polymerase, primer concentration and amount of random single-stranded DNA pool at four levels. Meanwhile, the annealing temperature and number of PCR reaction cycles were optimized to establish the optimal reaction system and PCR procedure. [Result] The optimal combination of PCR reaction system for random ssDNA pool was obtained, with a total system volume of 20 μl containing 2.0 μl of 10 × Buffer, 0.5 ng of random ssDNA pool, 2.5 mmol/L Mg2＋, 0.25 mmol/L dNTP Mixture, 0.6 μmol/L upstream and downstream primers and 1.5 U of Taq DNA polymerase; the optimal annealing temperature was 68 ℃ and the optimal number of cycles was 12. Under the above conditions, clear and stable bands with high specificity for random ssDNA pool were amplified. [Conclusion] This study laid the foundation for selection of parameters with higher specificity in SELEX technology.展开更多
Soil organic carbon in forest affects nutrient availability,microbial processes,and organic matter inputs.Dominant tree species have increasingly shifted from ectomycorrhizal to arbuscular mycorrhizal associations in ...Soil organic carbon in forest affects nutrient availability,microbial processes,and organic matter inputs.Dominant tree species have increasingly shifted from ectomycorrhizal to arbuscular mycorrhizal associations in subtropical forests.However,the consequences of this shift for soil organic carbon is poorly understood.To address this,a field study was conducted across a natural gradient of arbuscular tree associations to investigate how different mycorrhizal associations affect soil organic carbon quantity,composition,chemical stability,and related soil properties.Soil organic carbon fractions,functional groups,microbial enzyme activities were analyzed.Results showed that increasing arbuscular mycorrhizal dominance was associated with declines in total soil organic carbon,particularly in recalcitrant and aromatic carbon forms.Ectomycorrhizaldominated forests exhibited higher nitrogen availability and elevated nitrogen-hydrolyzing enzyme activity,suggesting enhanced nitrogen acquisition strategies that suppress soil organic carbon decomposition and promote carbon retention.These findings indicate that mycorrhizal-mediated shifts in tree composition may significantly alter soil carbon sequestration potential.Incorporating mycorrhizal functional traits into forest management and carbon modeling could improve predictions of soil organic carbon responses under future environmental change.展开更多
The adult subventricular zone of the lateral ventricles and the subgranular zone in the hippocampal dentate gyrus(DG)are the two brain regions where neurogenesis occurs throughout life in the adult mammalian brain(Min...The adult subventricular zone of the lateral ventricles and the subgranular zone in the hippocampal dentate gyrus(DG)are the two brain regions where neurogenesis occurs throughout life in the adult mammalian brain(Ming and Song,2011).Adult quiescent hippocampal neural stem cells(NSCs)are bona fide stem cells and,when activated,give rise to newborn granule neurons in the adult brain,which play vital roles in learning,memory,mood,and affective cognition(Bonaguidi et al.,2011;Ming and Song,2011).展开更多
Partial substitution of chemical fertilizers by organic amendments is adopted widely for promoting the availability of soil phosphorus(P)in agricultural production.However,few studies have comprehensively evaluated th...Partial substitution of chemical fertilizers by organic amendments is adopted widely for promoting the availability of soil phosphorus(P)in agricultural production.However,few studies have comprehensively evaluated the effects of longterm organic substitution on soil P availability and microbial activity in greenhouse vegetable fields.A 10-year(2009–2019)field experiment was carried out to investigate the impacts of organic fertilizer substitution on soil P pools,phosphatase activities and the microbial community,and identify factors that regulate these soil P transformation characteristics.Four treatments included 100%chemical N fertilizer(4 CN),50%substitution of chemical N by manure(2 CN+2 MN),straw(2 CN+2 SN),and combined manure with straw(2 CN+1 MN+1 SN).Compared with the 4 CN treatment,organic substitution treatments increased celery and tomato yields by 6.9-13.8%and 8.6-18.1%,respectively,with the highest yields being in the 2 CN+1 MN+1 SN treatment.After 10 years of fertilization,organic substitution treatments reduced total P and inorganic P accumulation,increased the concentrations of available P,organic P,and microbial biomass P,and promoted phosphatase activities(alkaline and acid phosphomonoesterase,phosphodiesterase,and phytase)and microbial growth in comparison with the 4 CN treatment.Further,organic substitution treatments significantly increased soil C/P,and the partial least squares path model(PLS-PM)revealed that the soil C/P ratio directly and significantly affected phosphatase activities and the microbial biomass and positively influenced soil P pools and vegetable yield.Partial least squares(PLS)regression demonstrated that arbuscular mycorrhizal fungi positively affected phosphatase activities.Our results suggest that organic fertilizer substitution can promote soil P transformation and availability.Combining manure with straw was more effective than applying these materials separately for developing sustainable P management practices.展开更多
文摘The continuous increase of human mobility combined with a relevant use of private vehicles contributes to increase the ill effects of vehicle externalities on the environment, e.g. high levels of air pollution, toxic emissions, noise pollution, and on the quality of life, e.g. parking problem, traffic congestion, and increase in the number of crashes and accidents. Transport demand management plays a very critical role in achieving greenhouse gas emission reduction targets. This study demonstrates that car pooling (CP) is an effective strategy to reduce transport volumes, transportation costs and related hill externalities in agreement with EU programs of emissions reduction targets. This paper presents an original approach to solve the CP problem. It is based on hierarchical clustering models, which have been adopted by an original decision support system (DSS). The DSS helps mobility managers to generate the pools and to design feasible paths for shared vehicles. A significant case studies and obtained results by the application of the proposed models are illustrated. They demonstrate the effectiveness of the approach and the supporting decisions tool.
基金supported by the key project of National Natural Science Foundation of China titled"The Influence of National Pooling of Basic Pension Insurance for Urban Employees on Local Governments'Premium Collection Behavior:Mechanism Exploration,Empirical Test and Policy Optimization" (No.72304283)Central universities basic scientific research business funding project titled"The Impact of National Pooling on the Sustainability of Pension Insurance Fund and Policy Optimization:From the Perspective of Local Government Premium Collection Behavior" (No.2722023BY016).
文摘In January 2022,China introduced a national pooling system for pension insurance fund,With the objective of inter-regional fund surplus and deficit adjustment.With the ongoing trend of population aging,can the national pooling and adjustment system operate sustainably?What level of fiscal obligations does it entail?This is related to the long-term stability of pension insurance fund and the whole social security system.This paper employs econometric and actuarial models to assess the sustainability of the national pooling and adjustment system under five scenarios:(1)not introducing any policy interventions;(2)implementing parameter reforms such as expanding pension insurance coverage,progressively extending retirement age,and enhancing collection rates;(3)transferring state-owned capital from central state-owned enterprises to strengthen the social security fund;(4)transitioning the national pooling and adjustment system from turning over current surplus to accumulated surplus;and(5)implementing all parameter reforms,transferring state-owned capital,and turning over accumulated surpluses.The results suggest that a coordinated implementation of reform measures like pension insurance parameter adjustments,reallocation of state-owned capital to enhance social security funds,and leveraging the national pooling and adjustment system for turning over accumulated surplus can ensure the sustainability of the system and significantly alleviatefiscalpressures.
基金supported by the National Natural Science Foundation of China(Grant Nos.62274002,62304001,and 62201005)the Anhui Provincial Natural Science Foundation(Grant Nos.2308085QF213 and 2408085QF211)the Natural Science Research Project of the Anhui Educational Committee(Grant No.2023AH050072)。
文摘Edge deployment solutions based on convolutional neural networks(CNNs)have garnered significant attention because of their potential applications.However,traditional CNNs rely on pooling to reduce the feature size,leading to substantial information loss and reduced network robustness.Herein,we propose a more robust adaptive pooling network(APN)method implemented using memristor technology.Our method introduces an improved pooling layer that reduces input features to an arbitrary scale without compromising their importance.Different coupling coefficients of the pooling layer are stored as conductance values in arrays.We validate the proposed APN on generic datasets,demonstrating significant performance improvements over previously reported CNN architectures.Additionally,we evaluate the APN on a CAPTCHA recognition task with perturbations to assess network robustness.The results show that the APN achieves 92.6% accuracy in 4-digit CAPTCHA recognition and exhibits higher robustness.This brief presents a highly robust and novel scheme for edge computing using memristor technology.
基金supported by China Postdoctoral Science Foundation(No.2024M754122)the Postdoctoral Fellowship Programof CPSF(No.GZB20240972)+3 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(No.2024ZB194)Natural Science Foundation of Jiangsu Province(No.BK20241389)Basic Science ResearchFund of China(No.JCKY2023203C026)2024 Jiangsu Province Talent Programme Qinglan Project.
文摘This study focuses on tool condition recognition through data-driven approaches to enhance the intelligence level of computerized numerical control(CNC)machining processes and improve tool utilization efficiency.Traditional tool monitoring methods that rely on empirical knowledge or limited mathematical models struggle to adapt to complex and dynamic machining environments.To address this,we implement real-time tool condition recognition by introducing deep learning technology.Aiming to the insufficient recognition accuracy,we propose a pyramid pooling-based vision Transformer network(P2ViT-Net)method for tool condition recognition.Using images as input effectively mitigates the issue of low-dimensional signal features.We enhance the vision Transformer(ViT)framework for image classification by developing the P2ViT model and adapt it to tool condition recognition.Experimental results demonstrate that our improved P2ViT model achieves 94.4%recognition accuracy,showing a 10%improvement over conventional ViT and outperforming all comparative convolutional neural network models.
基金funded by the Key Research and Development Program of Hubei Province,China(Grant No.2023BEB024)the Young and Middle-aged Scientific and Technological Innova-tion Team Plan in Higher Education Institutions inHubei Province,China(GrantNo.T2023007)the key projects ofHubei Provincial Department of Education(No.D20161403).
文摘With the rapid development of intelligent video surveillance technology,pedestrian re-identification has become increasingly important inmulti-camera surveillance systems.This technology plays a critical role in enhancing public safety.However,traditional methods typically process images and text separately,applying upstream models directly to downstream tasks.This approach significantly increases the complexity ofmodel training and computational costs.Furthermore,the common class imbalance in existing training datasets limitsmodel performance improvement.To address these challenges,we propose an innovative framework named Person Re-ID Network Based on Visual Prompt Technology andMulti-Instance Negative Pooling(VPM-Net).First,we incorporate the Contrastive Language-Image Pre-training(CLIP)pre-trained model to accurately map visual and textual features into a unified embedding space,effectively mitigating inconsistencies in data distribution and the training process.To enhancemodel adaptability and generalization,we introduce an efficient and task-specific Visual Prompt Tuning(VPT)technique,which improves the model’s relevance to specific tasks.Additionally,we design two key modules:the Knowledge-Aware Network(KAN)and theMulti-Instance Negative Pooling(MINP)module.The KAN module significantly enhances the model’s understanding of complex scenarios through deep contextual semantic modeling.MINP module handles samples,effectively improving the model’s ability to distinguish fine-grained features.The experimental outcomes across diverse datasets underscore the remarkable performance of VPM-Net.These results vividly demonstrate the unique advantages and robust reliability of VPM-Net in fine-grained retrieval tasks.
基金supported by National Technology Support Project (2008BAD95B10-6)
文摘The organic carbon contents,carbon density and carbon storage of the soil in the Pinus koraiensis plantation ecosystem were investigated in Maoershan experimental forest farm,Shangzhi County,Heilongjiang,on the west slope of the Zhangguangcai Mountains in northeastern China for providing data to evaluation of the carbon balance in forest ecosystem of northeastern China.These soil carbon indicators were measured in three forest types,pure P.koraiensis plantation,P.koraiensis and Betula platyphylla mixed forest,and the P.koraiensis and Quercus mongolica mixed forest.The soil carbon pool consisted of four compartments,namely L layer,F layer,H layer and B layer.With variance analysis,we found that both organic carbon content and carbon density of the soil were significantly affected by forest types,soil compartments and slope positions.The highest soil carbon density（278.63 Mg·ha^-1）.was observed in the mixed forest of P.koraiensis and Q.mongolica.The B layer had the highest carbon density（212.28 Mg·ha^-1） among all the soil compartments.In terms of slope position,the highest soil carbon density（394.18 Mg·ha^-1） presented in the low slope.Besides,soil carbon content and carbon density had a marked change with the organic matter content and vertical depth of the soil in each compartment.The results of this study implied that in the temperate humid region,the mixed ecosystem of regional Pinus koraiensis plantations and natural forest had relatively high carbon storage capability.
基金Supported by Central University Basic Research Operating Expenses Special Fund(XDJK2011C026)Southwest University Doctoral Fund(09BSR04)~~
文摘[Objective] This study aimed to optimize the PCR amplification conditions for random ssDNA pool in SELEX technology. [Method] L16（45） orthogonal experimental design was adopted for optimization of five important factors affecting PCR reaction system for random single-stranded DNA pool including Mg2＋ concentration, dNTP concentration, amount of Taq DNA polymerase, primer concentration and amount of random single-stranded DNA pool at four levels. Meanwhile, the annealing temperature and number of PCR reaction cycles were optimized to establish the optimal reaction system and PCR procedure. [Result] The optimal combination of PCR reaction system for random ssDNA pool was obtained, with a total system volume of 20 μl containing 2.0 μl of 10 × Buffer, 0.5 ng of random ssDNA pool, 2.5 mmol/L Mg2＋, 0.25 mmol/L dNTP Mixture, 0.6 μmol/L upstream and downstream primers and 1.5 U of Taq DNA polymerase; the optimal annealing temperature was 68 ℃ and the optimal number of cycles was 12. Under the above conditions, clear and stable bands with high specificity for random ssDNA pool were amplified. [Conclusion] This study laid the foundation for selection of parameters with higher specificity in SELEX technology.
基金supported by the National Natural Science Foundation of China(grant numbers 32471851,32171759 and 32201533)Double Thousand Plan of Jiangxi Province(jxsq2023201058)Jiangxi Province Ganpo Juncai Support Plan(2024BCE50043).
文摘Soil organic carbon in forest affects nutrient availability,microbial processes,and organic matter inputs.Dominant tree species have increasingly shifted from ectomycorrhizal to arbuscular mycorrhizal associations in subtropical forests.However,the consequences of this shift for soil organic carbon is poorly understood.To address this,a field study was conducted across a natural gradient of arbuscular tree associations to investigate how different mycorrhizal associations affect soil organic carbon quantity,composition,chemical stability,and related soil properties.Soil organic carbon fractions,functional groups,microbial enzyme activities were analyzed.Results showed that increasing arbuscular mycorrhizal dominance was associated with declines in total soil organic carbon,particularly in recalcitrant and aromatic carbon forms.Ectomycorrhizaldominated forests exhibited higher nitrogen availability and elevated nitrogen-hydrolyzing enzyme activity,suggesting enhanced nitrogen acquisition strategies that suppress soil organic carbon decomposition and promote carbon retention.These findings indicate that mycorrhizal-mediated shifts in tree composition may significantly alter soil carbon sequestration potential.Incorporating mycorrhizal functional traits into forest management and carbon modeling could improve predictions of soil organic carbon responses under future environmental change.
基金supported by National Institutes of Health(R35NS137480,R35NS116843,and RF1AG079557)by Dr.Miriam and Sheldon G.Adelson Medical Research Foundation.
文摘The adult subventricular zone of the lateral ventricles and the subgranular zone in the hippocampal dentate gyrus(DG)are the two brain regions where neurogenesis occurs throughout life in the adult mammalian brain(Ming and Song,2011).Adult quiescent hippocampal neural stem cells(NSCs)are bona fide stem cells and,when activated,give rise to newborn granule neurons in the adult brain,which play vital roles in learning,memory,mood,and affective cognition(Bonaguidi et al.,2011;Ming and Song,2011).
基金supported by the China Agriculture Research System of MOF and MARA(CARS-23-B04)the National Key Research and Development Program of China(2016YFD0201001)。
文摘Partial substitution of chemical fertilizers by organic amendments is adopted widely for promoting the availability of soil phosphorus(P)in agricultural production.However,few studies have comprehensively evaluated the effects of longterm organic substitution on soil P availability and microbial activity in greenhouse vegetable fields.A 10-year(2009–2019)field experiment was carried out to investigate the impacts of organic fertilizer substitution on soil P pools,phosphatase activities and the microbial community,and identify factors that regulate these soil P transformation characteristics.Four treatments included 100%chemical N fertilizer(4 CN),50%substitution of chemical N by manure(2 CN+2 MN),straw(2 CN+2 SN),and combined manure with straw(2 CN+1 MN+1 SN).Compared with the 4 CN treatment,organic substitution treatments increased celery and tomato yields by 6.9-13.8%and 8.6-18.1%,respectively,with the highest yields being in the 2 CN+1 MN+1 SN treatment.After 10 years of fertilization,organic substitution treatments reduced total P and inorganic P accumulation,increased the concentrations of available P,organic P,and microbial biomass P,and promoted phosphatase activities(alkaline and acid phosphomonoesterase,phosphodiesterase,and phytase)and microbial growth in comparison with the 4 CN treatment.Further,organic substitution treatments significantly increased soil C/P,and the partial least squares path model(PLS-PM)revealed that the soil C/P ratio directly and significantly affected phosphatase activities and the microbial biomass and positively influenced soil P pools and vegetable yield.Partial least squares(PLS)regression demonstrated that arbuscular mycorrhizal fungi positively affected phosphatase activities.Our results suggest that organic fertilizer substitution can promote soil P transformation and availability.Combining manure with straw was more effective than applying these materials separately for developing sustainable P management practices.
