The chemical characteristics of different sodium iron ethylenediaminetetraacetate sources and their relative bioavailabilities for broilers fed with a conventional corn‑soybean meal diet

Background Our previous studies demonstrated that divalent organic iron(Fe)proteinate sources with higher complexation or chelation strengths as expressed by the greater quotient of formation(Qf)values displayed higher Fe bioavailabilities for broilers.Sodium iron ethylenediaminetetraacetate(NaFeEDTA)is a trivalent organic Fe source with the strongest chelating ligand EDTA.However,the bioavailability of Fe when administered as NaFeEDTA in broilers and other agricultural animals remains untested.Herein,the chemical characteristics of 12 NaFeEDTA products were determined.Of these,one feed grade NaFeEDTA(Qf=2.07×10^(8)),one food grade NaFeEDTA(Qf=3.31×10^(8)),and one Fe proteinate with an extremely strong chelation strength(Fe-Prot ES,Qf value=8,590)were selected.Their bioavailabilities relative to Fe sulfate(FeSO_(4)·7H_(2)O)for broilers fed with a conventional corn-soybean meal diet were evaluated during d 1 to 21 by investigating the effects of the above Fe sources and added Fe levels on the growth performance,hematological indices,Fe contents,activities and gene expressions of Fe-containing enzymes in various tissues of broilers.Results NaFeEDTA sources varied greatly in their chemical characteristics.Plasma Fe concentration(PI),transferrin saturation(TS),liver Fe content,succinate dehydrogenase(SDH)activities in liver,heart,and kidney,catalase(CAT)activity in liver,and SDH mRNA expressions in liver and kidney increased linearly(P<0.05)with increasing levels of Fe supplementation.However,differences among Fe sources were detected(P<0.05)only for PI,liver Fe content,CAT activity in liver,SDH activities in heart and kidney,and SDH mRNA expressions in liver and kidney.Based on slope ratios from multiple linear regressions of the above indices on daily dietary analyzed Fe intake,the average bioavailabilities of Fe-Prot ES,feed grade NaFeEDTA,and food grade NaFeEDTA relative to the inorganic FeSO_(4)·7H_(2)O(100%)for broilers were 139%,155%,and 166%,respectively.Conclusions The bioavailabilities of organic Fe sources relative to FeSO_(4)·7H_(2)O were closely related to their Qf values,and NaFeEDTA sources with higher Qf values showed higher Fe bioavailabilities for broilers fed with a conventional corn-soybean meal diet.

An aerial ammunition ad hoc network collaborative localization algorithm based on relative ranging and velocity measurement in a highly-dynamic topographic structure

In the internet of battlefield things, ammunition is becoming networked and intelligent, which depends on location information. Therefore, this paper focuses on the self-organized network collaborative localization of munitions with an aerial three-dimensional(3D) highly-dynamic topographic structure under a satellite denied environment. As for aerial networked munitions, the measurement of munitions is objectively incomplete due to the degenerated and interrupted link of munitions. For this reason, a cluster-oriented collaborative localization method is put forward in this paper. Multidimensional scaling(MDS) was first integrated with a trilateration localization method(TLM) to construct a relative localization algorithm for determining the relative location of a mobile cluster network. The information related to relative velocity was then combined into a collaborative localization framework to devise a TLM-vMDS algorithm. Finally, an iterative refinement algorithm based on scaling by majorizing a complicated function(SMACOF) was employed to effectively eliminate the influence of incomplete link observation on localization accuracy. Compared with the currently available advanced algorithms, the proposed TLM-vMDS algorithm achieves higher localization accuracy and faster convergence for a cluster of extensively networked munitions, and also offers better numerical stability and robustness for highspeed motion models.

Attention-relation network for mobile phone screen defect classification via a few samples

How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.

Serum proteins differentially expressed in gestational diabetes mellitus assessed using isobaric tag for relative and absolute quantitation proteomics

BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.

Impacts of high temperature,relative air humidity,and vapor pressure deficit on the seed set of contrasting maize genotypes during flowering

Heat stress is a major constraint to current and future maize production at the global scale.Male and female reproductive organs both play major roles in increasing seed set under heat stress at flowering,but their relative contributions to seed set are unclear.In this study,a 2-year field experiment including three sowing dates in each year and 20 inbred lines was conducted.Seed set,kernel number per ear,and grain yield were all reduced by more than 80%in the third sowing dates compared to the first sowing dates.Pollen viability,silk emergence ratio,and anthesis-silking interval were the key determinants of seed set under heat stress;and their correlation coefficients were 0.89^(***),0.65^(***),and-0.72^(***),respectively.Vapor pressure deficit(VPD)and relative air humidity(RH)both had significant correlations with pollen viability and the silk emergence ratio.High RH can alleviate the impacts of heat on maize seed set by maintaining high pollen viability and a high silk emergence ratio.Under a warming climate from 2020 to 2050,VPD will decrease due to the increased RH.Based on their pollen viability and silk emergence ratios,the 20 genotypes fell into four different groups.The group with high pollen viability and a high silk emergence ratio performed better under heat stress,and their performance can be further improved by combining the improved flowering pattern traits.

Evaluation of internal void related defects in reinforced concrete slab using electromagnetic wave properties

This study aims to develop a damage-detection algorithm based on the electromagnetic wave properties inside a reinforced concrete structure.The proposed method involves employing two algorithms based on data measured using ground-penetrating radar—a common electromagnetic wave method in civil engineering.The possible defect area was identified based on the energy dissipated by the damage in the frequency-wavenumber domain,with the damage localized using the calculated relative permittivity of the measurements.The proposed method was verified through a finite difference time-domain-based numerical analysis and a testing slab with artificial damage.As a result of verification,the proposed method quickly identified the presence of damage inside the concrete,especially for honeycomb-like defects located at the top of the rebar.This study has practical significance in scanning structures over a large area more quickly than other non-destructive testing methods,such as ultrasonic methods.

Optimal investment based on relative performance and weighted utility

This paper studies the optimal portfolio allocation of a fund manager when he bases decisions on both the absolute level of terminal relative performance and the change value of terminal relative performance comparison to a predefined reference point. We find the optimal investment strategy by maximizing a weighted average utility of a concave utility and an Sshaped utility via a concavification technique and the martingale method. Numerical results are carried out to show the impact of the extent to which the manager pays attention to the change of relative performance related to the reference point on the optimal terminal relative performance.

Relative orbit determination algorithm of space targets with passive observation

Angles-only relative orbit determination for space non-cooperative targets based on passive sensor is subject to weakly observable problem of the relative state between two spacecraft. Previously, the evidence for angles-only observability was found by using cylindrical dynamics, however, the solution of orbit determination is still not provided. This study develops a relative orbit determination algorithm with the cylindrical dynamics based on differential evolution. Firstly, the relative motion dynamics and line-of-sight measurement model for nearcircular orbit are established in cylindrical coordinate system.Secondly, the observability is qualitatively analyzed by using the dynamics and measurement model where the unobservable geometry is found. Then, the angles-only relative orbit determination problem is modeled into an optimal searching frame and an improved differential evolution algorithm is introduced to solve the problem. Finally, the proposed algorithm is verified and tested by a set of numerical simulations in the context of highEarth and low-Earth cases. The results show that initial relative orbit determination(IROD) solution with an appropriate accuracy in a relative short span is achieved, which can be used to initialize the navigation filter.

Relative peripheral refraction in school children with different refractive errors using a novel multispectral refraction topographer

AIM:To compare relative peripheral refraction(RPR)in Chinese school children with different refractive errors using multispectral refraction topography(MRT).METHODS:A total of 713 eyes of primary school children[172 emmetropia(E),429 low myopia(LM),80 moderate myopia(MM),and 32 low hypermetropia(LH)]aged 10 to 13y were analyzed.RPRs were measured using MRT without mydriasis.MRT results showed RPR at 0-15°(RPR 0-15),15°-30°(RPR 15-30),and 30°-45°(RPR 30-45)annular in the inferior(RPR-I),superior(RPR-S),nasal(RPR-N),and temporal(RPR-T)quadrants.Spherical equivalent(SE)was detected and calculated using an autorefractor.RESULTS:There were significant differences of RPR 15-30 between groups MM[0.02(-0.12;0.18)]and LH[-0.13(-0.36;0.12)](P<0.05),MM and E[-0.06(-0.20;0.10)](P<0.05),and LM[-0.02(-0.15;0.15)]and E(P<0.05).There were also significant differences of RPR 30-45 between groups MM[0.45(0.18;0.74)]and E[0.29(-0.09;0.67)](P<0.05),and LM[0.44(0.14;0.76)]and E(P<0.001).RPR values increased from the hyperopic to medium myopic group in each annular.There were significant differences of RPR-S between groups MM[-0.02(-0.60;0.30)]and E[-0.44(-0.89;-0.04)](P<0.001),and LM[-0.28(-0.71;0.12)]and E(P<0.05).There were also significant differences of RPR-T between groups MM[0.37(0.21;0.78)]and LH[0.14(-0.52;0.50)](P<0.05),LM[0.41(0.06;0.84)]and LH(P<0.05),and LM and E[0.29(-0.10;0.68),P<0.05].A Spearman’s correlation analysis showed a negative correlation between RPR and SE in the 15°-30°(P=0.005),30°-45°(P<0.05)annular(P=0.002),superior(P<0.001),and temporal(P=0.001)quadrants.CONCLUSION:Without pupil dilation,values for RPR 15-30,30-45,RPR-S,and T shows significant differences between myopic eyes and emmetropia,and the differences are negatively correlated with SE.

Relative peripheral refractive errors in Chinese children with myopic anisometropia

AIM:To compare relative peripheral refractive errors(RPREs)in Chinese children with and without myopic anisometropia(MAI)and to explore the relationship between RPRE and myopia.METHODS:This observational cross-sectional study included 160 children divided into two groups according to the interocular spherical equivalent refraction(SER)difference≥1.0 D in the MAI group(n=80)and<1.0 D in the non-MAI group(n=80).The MAI group was further divided into two subgroups:ΔSER<2.0 D group and ΔSER≥2.0 D group.Basic ocular biometric parameters of axial length(AL),average keratometry(Ave K),cylinder(CYL),surface regularity index(SRI),and surface asymmetry index(SAI)were recorded.In addition,multispectral refraction topography was performed to measure RPRE,and the parameters were recorded as total refraction difference value(TRDV),refraction difference value(RDV)0-10,RDV10-20,RDV20-30,RDV30-40,RDV40-53,RDV-superior(RDV-S),RDV-inferior(RDV-I),RDV-temporal(RDV-T)and RDV-nasal(RDV-N).RESULTS:In the non-MAI group,the interocular differences of all parameters of RPRE were not significant.In the MAI group,the interocular differences of TRDV,RDV10-53,RDV-S,RDV-I,RDV-T,and RDV-N were significant.In subgroup analysis,the interocular differences of TRDV,RDV30-53,RDV-I,and RDV-T were significant in ΔSER<2.0 D group and ΔSER≥2.0 D group,but the interocular differences of RDV10-30,RDV-S and RDV-N were only significant in the ΔSER≥2.0 D group.In correlation analysis,ΔTRDV,ΔRDV 10-53,ΔRDV-S,and ΔRDV-N were negatively correlated with ΔSER but positively correlated with ΔAL.CONCLUSION:The more myopic eyes have larger hyperopic RPRE in Chinese children with MAI in certain retinal range,and partialΔRPRE is closely associated with ΔSER and ΔAL.

An Experimental Study on the Effect of a Nanofluid on Oil-Water Relative Permeability

The low porosity and low permeability of tight oil reservoirs call for improvements in the current technologies for oil recovery.Traditional chemical solutions with large molecular size cannot effectively flow through the nanopores of the reservoir.In this study,the feasibility of Nanofluids has been investigated using a high pressure high temperature core-holder and nuclear magnetic resonance(NMR).The results of the experiments indicate that the specified Nanofluids can enhance the tight oil recovery significantly.The water and oil relative permeability curve shifts to the high water saturation side after Nanofluid flooding,thereby demonstrating an increase in the water wettability of the core.In the Nanofluid flooding process the oil recovery was enhanced by 15.1%,compared to waterflooding stage.The T2 spectra using the NMR show that after Nanofluid flooding,a 7.18%increment in oil recovery factor was gained in the small pores,a 4.9%increase in the middle pores,and a 0.29%increase in the large pores.These results confirm that the Nanofluids can improve the flow state in micro-sized pores inside the core and increase the ultimate oil recovery factor.

Genome-wide association with transcriptomics reveals a shade-tolerance gene network in soybean

Shade tolerance is essential for soybeans in inter/relay cropping systems.A genome-wide association study(GWAS)integrated with transcriptome sequencing was performed to identify genes and construct a genetic network governing the trait in a set of recombinant inbred lines derived from two soybean parents with contrasting shade tolerance.An improved GWAS procedure,restricted two-stage multi-locus genome-wide association study based on gene/allele sequence markers(GASM-RTM-GWAS),identified 140 genes and their alleles associated with shade-tolerance index(STI),146 with relative pith cell length(RCL),and nine with both.Annotation of these genes by biological categories allowed the construction of a protein–protein interaction network by 187 genes,of which half were differentially expressed under shading and non-shading conditions as well as at different growth stages.From the identified genes,three ones jointly identified for both traits by both GWAS and transcriptome and two genes with maximum links were chosen as beginners for entrance into the network.Altogether,both STI and RCL gene systems worked for shade-tolerance with genes interacted each other,this confirmed that shadetolerance is regulated by more than single group of interacted genes,involving multiple biological functions as a gene network.

Graph Convolutional Networks Embedding Textual Structure Information for Relation Extraction

Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,sentiment analysis and question-answering systems.However,previous studies ignored much unusedstructural information in sentences that could enhance the performance of the relation extraction task.Moreover,most existing dependency-based models utilize self-attention to distinguish the importance of context,whichhardly deals withmultiple-structure information.To efficiently leverage multiple structure information,this paperproposes a dynamic structure attention mechanism model based on textual structure information,which deeplyintegrates word embedding,named entity recognition labels,part of speech,dependency tree and dependency typeinto a graph convolutional network.Specifically,our model extracts text features of different structures from theinput sentence.Textual Structure information Graph Convolutional Networks employs the dynamic structureattention mechanism to learn multi-structure attention,effectively distinguishing important contextual features invarious structural information.In addition,multi-structure weights are carefully designed as amergingmechanismin the different structure attention to dynamically adjust the final attention.This paper combines these featuresand trains a graph convolutional network for relation extraction.We experiment on supervised relation extractiondatasets including SemEval 2010 Task 8,TACRED,TACREV,and Re-TACED,the result significantly outperformsthe previous.

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.

Relative Efficiencies of Optimal Designs in Four Dimensions Constructed Using Balanced Incomplete Block Designs

Experimentally, the best design gives estimates of the desired effects and contrasts with maximum precision. Efficiency as a discriminating factor enables comparison of designs. The goal of Response Surface Methodology (RSM) is the determination of the best settings of the in-put variables for a maximum (or a minimum) response within a region of interest, R. This calls for fitting a model that adequately represents the mean response since such a model, is then used to locate the optimum. D-, A-, E- and T-Optimal designs of a rotatable design of degree two in four dimensions constructed using balanced incomplete block designs (BIBD) when the number of replications is less than three times the number of pairs of treatments occur together in the design and their relative efficiencies to general designs are presented. D-optimal design had 88 runs after replicating the factorial part twice and the axial part thrice with an optimal variance of 0.6965612 giving an efficiency of 97.7% while for A- and T-optimal designs they are formed with 112 runs each obtained by replicating the factorial part two times and axial part six times. Their optimal variances are 0.05798174 and 1.29828 respectively, with efficiency of 71.8% for A-optimal and 87.5% for T-optimal design. E-optimal design was found to be the most efficient design with an only 32 runs comprising only of the factorial part and with an optimal variance of 0.4182000, attaining an efficiency of approximately 1%. This study proposes the adoption of the E-optimal design in estimating the parameters of a rotatable second-order degree model constructed using BIBD for less costs and time saving.

Prediction of Low Heating Value of Sugar Cane Bagasse as a Fuel for Industrial Boilers in the High Relative Humidity Region: Case of Cameroon

Many attempts have been made to estimate calorific value of bagasse using mathematical equations, which were created based on data from proximate, ultimate, physical and chemical analysis. Questions have been raised on the applicability of these equations in different parts of the globe. This study was initiated to tackle these problems and also check the most suited mathematical models for the Law Heating Value of Cameroonian bagasse. Data and bagasse samples were collected at the Cameroonian sugarcane factory. The effects of cane variety, age of harvesting, source, moisture content, and sucrose on the LHV of Cameroon bagasse have been tested. It was shown that humidity does not change within a variety, but changes from the dry season to the rainy season;the sugar in the rainy season is significantly different from that collected in the dry season. Samples of the same variety have identical LHV. LHV in the dry season is significantly different from LHV in the rainy season. According to the fact that this study was done for cane with different ages of harvesting, the maturity of Cameroonian sugarcane does not affect LHV of bagasse. Tree selected models are much superior tool for the prediction of the LHV for bagasse in Cameroon compared to others. The standard deviation of these validated models is around 200 kJ/kg compared to the experimental. Thus, the models determined in foreign countries, are not necessarily applicable in predicting the LHV of bagasse in other countries with the same accuracy as that in their native country. There was linear relationship between humidity, ash and sugar content in the bagasse. It is possible to build models based on data from physical composition of bagasse using regression analysis.

Analysis of Factors Related to Vasovagal Response in Apheresis Blood Donors and the Establishment of Prediction Model Based on BP Neural Network Algorithm

Objective:To analyze the factors related to vessel vasovagal reaction(VVR)in apheresis donors,establish a mathematical model for predicting the correlation factors and occurrence risk,and use the prediction model to intervene in high-risk VVR blood donors,improve the blood donation experience,and retain blood donors.Methods:A total of 316 blood donors from the Xi'an Central Blood Bank from June to September 2022 were selected to statistically analyze VVR-related factors.A BP neural network prediction model is established with relevant factors as input and DRVR risk as output.Results:First-time blood donors had a high risk of VVR,female risk was high,and sex difference was significant(P value<0.05).The blood pressure before donation and intergroup differences were also significant(P value<0.05).After training,the established BP neural network model has a minimum RMS error of o.116,a correlation coefficient R=0.75,and a test model accuracy of 66.7%.Conclusion:First-time blood donors,women,and relatively low blood pressure are all high-risk groups for VVR.The BP neural network prediction model established in this paper has certain prediction accuracy and can be used as a means to evaluate the risk degree of clinical blood donors.

Inverse Electromagnetic Scattering by a Penetrable Chiral Object

We consider the inverse electromagnetic scattering problem of determining the shape of a perfectly conducting core inside a penetrable chiral body. We prove the well-posedness of the corresponding direct scattering problem by the variational method. We focus on a uniqueness result for the inverse scattering problem that is under what conditions an obstacle can be identified by the knowledge of the electric far-field pattern corresponding to all time-harmonic incident planes waves with a fixed wave number. To this end, we establish a chiral mixed reciprocity relation that connects the electric far-field pattern of a spherical wave with the scattered field of a plane wave.

Validation and Spatiotemporal Distribution of GEOS-5-Based Planetary Boundary Layer Height and Relative Humidity in China

Few studies have specifically focused on the validation and spatiotemporal distribution of planetary boundary layer height （PBLH） and relative humidity （RH） data in China. In this analysis, continuous PBLH and surface-level RH data simulated from GEOS-5 between 2004 and 2012, were validated against ground-based observations. Overall, the simulated RH was consistent with the statistical data from meteorological stations, with a correlation coefficient of 0.78 and a slope of 0.9. However, the simulated PBLH was underestimated compared to LIDAR data by a factor of approximately two, which was primarily because of poor simulation in late summer and early autumn. We further examined the spatiotemporal distribution characteristics of two factors in four regions--North China, South China, Northwest China, and the Tibetan Plateau. The results showed that the annual PBLH trends in all regions were fairly moderate but sensitive to solar radiation and precipitation, which explains why the PBLH values were ranked in order from largest to smallest as follows： Tibetan Plateau, Northwest China, North China, and South China. Strong seasonal variation of the PBLH exhibited high values in summer and low values in winter, which was also consistent with the turbulent vertical exchange. Not surprisingly, the highest RH in South China and the lowest RH in desert areas of Northwest China （less than 30%）. Seasonally, South China exhibited little variation, whereas Northwest China exhibited its highest humidity in winter and lowest humidity in spring, the maximum values in the other regions were obtained from July to September.