The quantitative relationship between modern pollen and vegetation provides a critical foundation for reconstructing past vegetation,with relative pollen productivity(RPP)serving as a key calibration parameter.However...The quantitative relationship between modern pollen and vegetation provides a critical foundation for reconstructing past vegetation,with relative pollen productivity(RPP)serving as a key calibration parameter.However,in subtropical evergreen broadleaved forests(SEBFs)in China,RPP studies remain scarce,and the impact of human disturbances on RPP estimates has yet to be adequately assessed,limiting the accuracy of quantitative palaeovegetation reconstructions.This study was conducted in Dinghu Mountain Nature Reserve and its surrounding areas in Zhaoqing,Guangdong Province,and included 31 sampling sites.We performed pollen analysis alongside detailed vegetation surveys and utilized ERV submodel 2 and Prentice’s model to estimate the RPP of 9 common plant taxa in the southern SEBFs.There was a particular focus on evaluating the interference effects of bamboo plantations on the estimation of RPP.The results indicate that bamboo within the family Poaceae contributes minimally to surface soil Poaceae pollen because of its unique flowering characteristics,such as long flowering cycles and monocarpic reproduction.The incorporation of bamboo into the Poaceae vegetation coverage in the analysis led to excessively high RPP values for the other taxa.When bamboo coverage was removed from the Poaceae family,the recalculated RPP values aligned closely with those reported in previous studies.The RPP values,ranked from highest to lowest,were as follows:Castanopsis(12.33±0.03)>Araliaceae(1.60±0.03)>Mallotus(1.53±0.26)>Pinus(1.47±0.03)>Rosaceae(1.07±0.02)>Poaceae(1±0)>Euphorbiaceae(0.44±0.03)>Anacardiaceae(0.26±0.03)>Theaceae(0.15±0).Notably,the RPP values for Mallotus,Araliaceae,Theaceae,and Euphorbiaceae represent the first estimates for China’s subtropical region.Differences between certain RPP estimates and those of previous studies may be attributed to factors such as species composition,vegetation structure,and model selection.The findings of this study highlight that due to the widespread distribution of artificial bamboo forests in China’s subtropical regions,future RPP studies should carefully consider the influence of Poaceae.This consideration is essential for improving the accuracy of the application of fossil pollen for quantitative paleo-vegetation reconstruction in these regions.展开更多
Dissecting quantitative traits into Mendelian factors is a great challenge in genetics.Apple fruit storability is a complex trait controlled by multi-genes with unequal effects.We previously identified62 quantitative ...Dissecting quantitative traits into Mendelian factors is a great challenge in genetics.Apple fruit storability is a complex trait controlled by multi-genes with unequal effects.We previously identified62 quantitative trait loci(QTLs)associated with apple fruit storability and genomics-assisted prediction(GAP)models were trained using 56 QTLbased markers.Here,three candidate genes,Md NAC83,Md BPM2,and Md RGLG3,were screened from the regions of QTLs with large G'value and large genetic effects.Both a 216-bp deletion and an SNP934 T/C at the promoter of Md NAC83 were associated with higher Md NAC83expression but an SNP388 G/A at the coding region significantly reduced the activity to activate the expression of the target genes Md ACO1,Md MANA3,and Md XTH28.Md BPM2 and Md RGLG3 participated in the ubiquitination of Md NAC83.SNP657 T/A of Md BPM2 and SNP167C/G of Md RGLG3 caused a reduction in the activity to ubiquitinate Md NAC83.By the addition of functional markers to the Geno Baits SNP array,the prediction accuracy of the updated GAP models increased to 0.7723/0.6231 and 0.5639/0.5345 for flesh firmness/crispness at harvest and flesh firmness/crispness retainability,respectively.The variation network involving eight simple Mendelian variations in six genes helps to gain insight into the molecular quantitative genetics,to improve breeding strategy,and to provide targets for future genome editing.展开更多
Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the ...Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.展开更多
Sulfur dioxide(SO_(2)) and its derivatives have been recognized as harmful environmental pollutants.However,they are often produced during the processing of traditional Chinese medicines,potentially compromising the q...Sulfur dioxide(SO_(2)) and its derivatives have been recognized as harmful environmental pollutants.However,they are often produced during the processing of traditional Chinese medicines,potentially compromising the quality of these medicinal materials and contributing to various health issues.Due to a lack of effective monitoring and imaging tools,the physiological effects of excessive SO_(2) residues in traditional Chinese medicine remain unclear.Therefore,developing a rapid and effective tool for detecting SO_(2) is crucial for understanding its metabolic pathways and effects in vivo.In this study,we developed a near infrared(NIR) and ratiometric fluorescent probe,NIR-RS,which exhibits high sensitivity,selectivity,and rapid response for SO_(2) detection.Notably,NIR-RS accurately quantifies SO_(2) contents in Pinelliae rhizoma(P.rhizoma) samples,with recovery rates from 98.46 % to 102.40 %,and relative standard deviations(RSDs)< 5.0 %.For bioimaging applications,NIR-RS has low cytotoxicity and good mitochondrial-targeting ability,making it suitable for imaging exogenous and endogenous SO_(2) in mitochondria.Additionally,NIR-RS was successfully applied to image SO_(2) content of P.rhizoma samples within cells,revealing that high SO_(2) residue elevated mitochondria adenosine triphosphate(ATP) content,these findings reveal that P.rhizoma with excessive SO_(2) can affect the organism's growth mechanisms through alterations in ATP pathways.In vivo,SO_(2) was found to predominantly accumulate in the liver following gavage with P.rhizoma solution,with accumulation levels increasing in proportion to SO_(2) residue concentration.High SO_(2) concentrations in P.rhizoma can cause pulmonary fibrosis and gastric mucosal damage.This work provides a valuable tool for regulating SO_(2) content in P.rhizoma and may help researcher better understand the metabolism of SO_(2) derivatives and explore their physiological roles in biological systems.展开更多
Quantitative structure-retention relationship(QSRR)is an important tool in chromatography.QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation.This...Quantitative structure-retention relationship(QSRR)is an important tool in chromatography.QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation.This approach involves developing models for predicting the retention time(RT)of analytes,thereby accelerating method development and facilitating compound identification.In addition,QSRR can be used to study compound retention mechanisms and support drug screening efforts.This review provides a comprehensive analysis of QSRR workflows and applications,with a special focus on the role of artificial intelligence-an area not thoroughly explored in previous reviews.Moreover,we discuss current limitations in RT prediction and propose promising solutions.Overall,this review offers a fresh perspective on future QSRR research,encouraging the development of innovative strategies that enable the diverse applications of QSRR models in chromatographic analysis.展开更多
This study utilizes two complementary models,the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz(TVP-VAR-DY)and the Time-Varying Parameter Vector Autoregressive Barunik–Křehlik(TVP-VAR-BK),to investigate...This study utilizes two complementary models,the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz(TVP-VAR-DY)and the Time-Varying Parameter Vector Autoregressive Barunik–Křehlik(TVP-VAR-BK),to investigate the dynamic volatility transmission between exchange rates and stock returns in major commodity-exporting and-importing countries.The analysis focuses on periods of quantitative easing(QE)and quantitative tightening(QT)from March 15,2020 to December 30,2022.The countries examined are Canada and Australia(major commodity exporters)and the UK and Germany(major commodity importers).An essential contribution of this paper is new empirical insights into the dynamics of stock market returns and the transmission of volatility between these markets and exchange rates during the QE and QT periods.The results reveal that causality primarily flows from stock markets to exchange rates,especially during the QT period across all investment horizons.The Toronto Stock Exchange(TSX)emerges as the principal net driver among the markets under study.Furthermore,the Canadian exchange rate(USDCAD)and the Australian Stock Exchange(ASX)are the most significantly affected indices within the network across various investment horizons(excluding the long-term).These findings underscore the importance for investors and policymakers to consider the interplay between exchange rates and stock market returns,particularly in the context of the QE and QT periods,as well as other economic,political,and health-related events.Our findings are relevant to various stakeholders,including governments,traders,portfolio managers,and multinationals.展开更多
Quantitative structure-biodegradability relationships （QSBRs） were established to develop predictive models and mechanistic explanations for acid dyestuffs as well as biological activities. With a total of four desc...Quantitative structure-biodegradability relationships （QSBRs） were established to develop predictive models and mechanistic explanations for acid dyestuffs as well as biological activities. With a total of four descriptors, molecular weight （MW）, energies of the highest occupied molecular orbital （EHOMO）, the lowest unoccupied molecular orbital （ELUMO）, and the excited state （EES）, calculated using quantum chemical semi-empirical methodology, a series of models were analyzed between the dye biodegradability and each descriptor. Results showed that EHOMO and Mw were the dominant parameters controlling the biodegradability of acid dyes. A statistically robust QSBR model was developed for all studied dyes, with the combined application of EHOMO and Mw. The calculated biodegradations fitted well with the experimental data monitored in a facultative-aerobic process, indicative of the reliable prediction and mechanistic character of the developed model.展开更多
The amidoximated polyacrylonitrile （PAN） fiber Fe complexeswere prepared and used as the heterogeneous Fenton catalysts for thedegradation of28 anionicwater soluble azodyes inwater under visible irradiation. The mul...The amidoximated polyacrylonitrile （PAN） fiber Fe complexeswere prepared and used as the heterogeneous Fenton catalysts for thedegradation of28 anionicwater soluble azodyes inwater under visible irradiation. The multiple linear regression （MLR） methodwas employed todevelop the quantitative structure property relationship （QSPR） model equations for thedecoloration and mineralization of azodyes. Moreover, the predictive ability of the QSPR model equationswas assessed using Leave-one-out （LOO） and cross-validation （CV） methods. Additionally, the effect of Fe content of catalyst and the sodium chloride inwater on QSPR model equationswere also investigated. The results indicated that the heterogeneous photo-Fentondegradation of the azodyeswithdifferent structureswas conducted in the presence of the amidoximated PAN fiber Fe complex. The QSPR model equations for thedyedecoloration and mineralizationwere successfullydeveloped using MLR technique. MW/S （molecularweightdivided by the number of sulphonate groups） and N N=N （the number of azo linkage） are considered as the most importantdetermining factor for thedyedegradation and mineralization, and there is a significant negative correlation between MW/S or N N=N anddegradation percentage or total organic carbon （TOC） removal. Moreover, LOO and CV analysis suggested that the obtained QSPR model equations have the better prediction ability. The variation in Fe content of catalyst and the addition of sodium chloridedid not alter the nature of the QSPR model equations.展开更多
An investigation was carried out in the Huanghai Sea and the East China Sea to study the quantitative relationship between the abundance of flagellates and the density of suspended particles in the summer of 2001. The...An investigation was carried out in the Huanghai Sea and the East China Sea to study the quantitative relationship between the abundance of flagellates and the density of suspended particles in the summer of 2001. The results show that the abundance of flagellates varies from 44-12 600 cell/cm^3, and flagellates sometimes constitutes a significant part of suspended particles. The size-spectra of suspended particles can be divided into four categories： flat spectrum, humped spectrum, plankton spectrum and mixed spectrum. In general, the abundance of flagellates varies in proportion to the density of suspended particles. However, their quantitative relations reveal different characteristics in the seawater samples of different types of particle-size spectrum. This is only a preliminary study of the quantitative relationship between flagellates and suspended particles, which might lead to a potential convenient approach to the estimation of flagellate abundance in the sea.展开更多
The molecular electronegativity interaction vector （MEIV） was used to describe the molecular structure of 30 selected esters. Two excellent QSTR models were built up by using multiple linear regression （MLR） and p...The molecular electronegativity interaction vector （MEIV） was used to describe the molecular structure of 30 selected esters. Two excellent QSTR models were built up by using multiple linear regression （MLR） and partial least-squares regression （PLS）. The correlation coefficients （R） of the two models were 0.945 and 0.941, respectively. The models were evaluated by performing the cross validation with the leave-one-out （LOO） procedure. The cross-verification correlation coefficients （RCV） of the two models were 0.921 and 0.919, respectively. The results showed that the models constructed in this work could provide estimation stability and favorable predictive ability.展开更多
Fatty acids and derivatives(FADs)are resources for natural antimicrobials.In order to screen for additional potent antimicrobial agents,the antimicrobial activities of FADs against Staphylococcus aureus were examined ...Fatty acids and derivatives(FADs)are resources for natural antimicrobials.In order to screen for additional potent antimicrobial agents,the antimicrobial activities of FADs against Staphylococcus aureus were examined using a microplate assay.Monoglycerides of fatty acids were the most potent class of fatty acids,among which monotridecanoin possessed the most potent antimicrobial activity.The conventional quantitative structure-activity relationship(QSAR)and comparative molecular field analysis(CoMFA)were performed to establish two statistically reliable models(conventional QSAR:R2=0.942,Q 2 LOO=0.910;CoMFA:R 2=0.979,Q 2=0.588,respectively).Improved forecasting can be achieved by the combination of these two models that provide a good insight into the structureactivity relationships of the FADs and that may be useful to design new FADs as antimicrobial agents.展开更多
The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations. In thi...The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations. In this study, a real-time adjustment to the radar reflectivity rainfall rates （Z R） relationship scheme and the gauge-corrected, radar-based, estimation scheme with inverse distance weighting interpolation was devel- oped. Based on the characteristics of the two schemes, the two-step correction technique of radar quantitative precipitation estimation is proposed. To minimize the errors between radar quantitative precipitation es- timations and rain gauge observations, a real-time adjustment to the Z R relationship scheme is used to remove systematic bias on the time-domain. The gauge-corrected, radar-based, estimation scheme is then used to eliminate non-uniform errors in space. Based on radar data and rain gauge observations near the Huaihe River, the two-step correction technique was evaluated using two heavy-precipitation events. The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.展开更多
The recent year's monitor results of Beijing indicated that the pollution level of fine particles PM 2.5 showed an increasing trend. To understand pollution characteristics of PM 2.5 and its relationship...The recent year's monitor results of Beijing indicated that the pollution level of fine particles PM 2.5 showed an increasing trend. To understand pollution characteristics of PM 2.5 and its relationship with the meteorological conditions in Beijing, a one-year monitoring of PM 2.5 mass concentration and correspondent meteorological parameters was performed in Beijing in 2001. The PM 2.5 levels in Beijing were very high, the annual average PM 2.5 concentration in 2001 was 7 times of the National Ambient Air Quality Standards proposed by US EPA. The major chemical compositions were organics, sulfate, crustals and nitrate. It was found that the mass concentrations of PM 2.5 were influenced by meteorological conditions. The correlation between the mass concentrations of PM 2.5 and the relative humidity was found. And the correlation became closer at higher relative humidity. And the mass concentrations of PM 2.5 were negtive-correlated to wind speeds, but the correlation between the mass concentration of PM 2.5 and wind speed was not good at stronger wind.展开更多
A new set of descriptors, HSEHPCSV （component score vector of hydrophobic, steric, and electronic properties together with hydrogen bonding contributions）, were derived from principal component analyses of 95 physic...A new set of descriptors, HSEHPCSV （component score vector of hydrophobic, steric, and electronic properties together with hydrogen bonding contributions）, were derived from principal component analyses of 95 physicochemical variables of 20 natural amino acids separately according to different kinds of properties described, namely, hydrophobic, steric, and electronic properties as well as hydrogen bonding contributions. HSEHPCSV scales were then employed to express structures of angiotensin-converting enzyme inhibitors, bitter tasting thresholds and bactericidal 18 peptide, and to construct QSAR models based on partial least square （PLS）. The results obtained are as follows： the multiple correlation coefficient （R2cum） of 0.846, 0.917 and 0.993, leave-one-out cross validated Q2cm of 0.835, 0.865 and 0.899, and root-mean-square error for estimated error （RMSEE） of 0.396, 0.187and 0.22, respectively. Satisfactory results showed that, as new amino acid scales, data of HSEHPCSV may be a useful structural expression methodology＇for the studies on peptide QSAR （quantitative structure-activity relationship） due to many advantages such as plentiful structural information, definite physical and chemical meaning and easy interpretation.展开更多
Deep-water navigation channels in the tidal reaches of the lower Yangtze River are affected by water and sediment fluxes that produce complex shoals and unstable channel conditions.The Fujiangsha reach is particularly...Deep-water navigation channels in the tidal reaches of the lower Yangtze River are affected by water and sediment fluxes that produce complex shoals and unstable channel conditions.The Fujiangsha reach is particularly difficult to manage,as it has many braided channels within the tidal fluctuation zone.In this study,hydrologic and topographic data from the Fujiangsha reach from 2012 to 2017 were used to examine the variations in deposition and erosion,flow diversion,shoals,and channel conditions.Since the Three Gorges Dam became operational and water storage was initiated,the Fujiangsha reach has shown an overall tendency toward erosion.Channels deeper than 10 m accounted for 83.7% of the total erosion of the Fujiangsha reach during 2012-2017.Moreover,the dominant channel-forming sediments have gradually changed from suspended sediments to a mixed load of suspended and bed-load sediments.Deposition volumes of these sediments has varied significantly among different channels,but has mainly occurred in the Fubei channel.Furthermore,periodic variations in the Jingjiang point bar have followed a deposition-erosion-deposition pattern,and the downstream Shuangjian shoal mid-channel bar has been scoured and shortened.Approximately 44.0% of the bed load from the upstream Fujiangsha reach is deposited within the 12.5-m deep Fubei channel.The increased erosion and river flow from the Jingjiang point bar and the Shuangjian shoal during the flood season constituted 59.3% and 40.7%,respectively,of the total amount of siltation in the Fubei channel.展开更多
Carotenoids are a family of effective active oxygen scavengers, which can reduce the danger of occurrence of chronic diseases such as cardiovascular disease, cataract, cancer, and so on. The quantitative structure-act...Carotenoids are a family of effective active oxygen scavengers, which can reduce the danger of occurrence of chronic diseases such as cardiovascular disease, cataract, cancer, and so on. The quantitative structure-activity relationship （QSAR） equation between carotenoids and antioxidant activity was established by quantum chemistry AM1, molecular mechanism （MM＋） and stepwise regression analysis methods, and the model was evaluated by leave-one-out approach. The results showed that the significant molecular descriptors related to the antioxidant activity of carotenoids were the energy difference （E_HL） between the lowest unoccupied molecular orbital （LUMO） and the highest occupied molecular orbital （HOMO） and ionization energy （Eiso）. The model showed a good predictive ability （Q^2 〉 0.5）.展开更多
With the artificial neural network（ANN） method combined with the multiple linear regression（MLR）,based on a series of quantum chemical descriptors and molecular connectivity indexes,quantitative structure-activity...With the artificial neural network（ANN） method combined with the multiple linear regression（MLR）,based on a series of quantum chemical descriptors and molecular connectivity indexes,quantitative structure-activity relationship（QSAR） models to predict the acute toxicity（-lgEC50） of substituted aromatic compounds to Photobacterium phosphoreum were established.Four molecular descriptors that appear in the MLR model,namely,the second order valence molecular connectivity index（2XV）,the energy of the highest occupied molecular orbital（EHOMO）,the logarithm of n-octyl alcohol/water partition coefficient（logKow） and the Connolly molecular area（MA）,were inputs of the ANN model.The root-mean-square error（RMSE） of the training and validation sets of the ANN model are 0.1359 and 0.2523,and the correlation coefficient（R） is 0.9810 and 0.8681,respectively.The leave-one-out（LOO） cross validated correlation coefficient（Q L2OO） of the MLR and ANN models is 0.6954 and 0.6708,respectively.The result showed that the two methods are complementary in the calculations.The regression method gave support to the neural network with physical explanation,and the neural network method gave a more accurate model for QSAR.In addition,some insights into the structural factors affecting the acute toxicity and toxicity mechanism of substituted aromatic compounds were discussed.展开更多
Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecul...Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecular structure without any experimental effort, they provide a simple and straightforward method for property prediction. In this work the flash point of alkanes was modeled by a set of molecular connectivity indices （Х）, modified molecular connectivity indices （ ^mХ^v ） and valance molecular connectivity indices （ ^mХ^v ）, with ^mХ^v calculated using the hydrogen perturbation. A stepwise Multiple Linear Regression （MLR） method was used to select the best indices. The predicted flash points are in good agreement with the experimental data, with the average absolute deviation 4.3 K.展开更多
Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Ab...Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.展开更多
Grain yield and heading date are key factors determining the commercial potential of a rice variety. Mapping of quantitative trait loci （QTLs） in rice has been advanced from primary mapping to gene cloning, and head...Grain yield and heading date are key factors determining the commercial potential of a rice variety. Mapping of quantitative trait loci （QTLs） in rice has been advanced from primary mapping to gene cloning, and heading date and yield traits have always attracted the greatest attention. In this review, genomic distribution of QTLs for heading date detected in populations derived from intra-specific crosses of Asian cultivated rice （Oryza sativa） was summarized, and their relationship with the genetic control of yield traits was analyzed. The information could be useful in the identification of QTLs for heading date and yield traits that are promising for the improvement of rice varieties.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42407595&41630753)the National Key Research and Development Program of China(Grant No.2022YFF0801501).
文摘The quantitative relationship between modern pollen and vegetation provides a critical foundation for reconstructing past vegetation,with relative pollen productivity(RPP)serving as a key calibration parameter.However,in subtropical evergreen broadleaved forests(SEBFs)in China,RPP studies remain scarce,and the impact of human disturbances on RPP estimates has yet to be adequately assessed,limiting the accuracy of quantitative palaeovegetation reconstructions.This study was conducted in Dinghu Mountain Nature Reserve and its surrounding areas in Zhaoqing,Guangdong Province,and included 31 sampling sites.We performed pollen analysis alongside detailed vegetation surveys and utilized ERV submodel 2 and Prentice’s model to estimate the RPP of 9 common plant taxa in the southern SEBFs.There was a particular focus on evaluating the interference effects of bamboo plantations on the estimation of RPP.The results indicate that bamboo within the family Poaceae contributes minimally to surface soil Poaceae pollen because of its unique flowering characteristics,such as long flowering cycles and monocarpic reproduction.The incorporation of bamboo into the Poaceae vegetation coverage in the analysis led to excessively high RPP values for the other taxa.When bamboo coverage was removed from the Poaceae family,the recalculated RPP values aligned closely with those reported in previous studies.The RPP values,ranked from highest to lowest,were as follows:Castanopsis(12.33±0.03)>Araliaceae(1.60±0.03)>Mallotus(1.53±0.26)>Pinus(1.47±0.03)>Rosaceae(1.07±0.02)>Poaceae(1±0)>Euphorbiaceae(0.44±0.03)>Anacardiaceae(0.26±0.03)>Theaceae(0.15±0).Notably,the RPP values for Mallotus,Araliaceae,Theaceae,and Euphorbiaceae represent the first estimates for China’s subtropical region.Differences between certain RPP estimates and those of previous studies may be attributed to factors such as species composition,vegetation structure,and model selection.The findings of this study highlight that due to the widespread distribution of artificial bamboo forests in China’s subtropical regions,future RPP studies should carefully consider the influence of Poaceae.This consideration is essential for improving the accuracy of the application of fossil pollen for quantitative paleo-vegetation reconstruction in these regions.
基金financially supported by the National Natural Science Foundation of China(32202431)the National Key R&D Program of China(2022YFD1200503)+2 种基金China Postdoctoral Science Foundation(2022M713408)the Earmarked Fund for CARS-27the Key Research and Development Program of Hebei(21326308D)。
文摘Dissecting quantitative traits into Mendelian factors is a great challenge in genetics.Apple fruit storability is a complex trait controlled by multi-genes with unequal effects.We previously identified62 quantitative trait loci(QTLs)associated with apple fruit storability and genomics-assisted prediction(GAP)models were trained using 56 QTLbased markers.Here,three candidate genes,Md NAC83,Md BPM2,and Md RGLG3,were screened from the regions of QTLs with large G'value and large genetic effects.Both a 216-bp deletion and an SNP934 T/C at the promoter of Md NAC83 were associated with higher Md NAC83expression but an SNP388 G/A at the coding region significantly reduced the activity to activate the expression of the target genes Md ACO1,Md MANA3,and Md XTH28.Md BPM2 and Md RGLG3 participated in the ubiquitination of Md NAC83.SNP657 T/A of Md BPM2 and SNP167C/G of Md RGLG3 caused a reduction in the activity to ubiquitinate Md NAC83.By the addition of functional markers to the Geno Baits SNP array,the prediction accuracy of the updated GAP models increased to 0.7723/0.6231 and 0.5639/0.5345 for flesh firmness/crispness at harvest and flesh firmness/crispness retainability,respectively.The variation network involving eight simple Mendelian variations in six genes helps to gain insight into the molecular quantitative genetics,to improve breeding strategy,and to provide targets for future genome editing.
基金supported by the Science and Technology Research and Development Program Project of China Railway Group Limited (Grant No.2022-Major-17)the National Natural Science Foundation of China (Grant Nos.52578619,52178180)+2 种基金the National Key Research and Development Program of China (Grant No.2022YFC3004304)the Frontier Cross Research Project of Central South University (Grant No.2023QYJC006)the Natural Science Foundation of Hunan Province Funding Project (Grant No.2023JJ40724)。
文摘Under earthquake action, different site conditions have a notable impact on the dynamic response of high-speed railway bridges after earthquakes, which in turn poses a threat to the running stability of trains in the post-earthquake period. Therefore, establishing a calculation method for the post-earthquake train speed threshold that considers the influence of different site characteristics is of great engineering significance. Taking the CRTS Ⅲ slab track as the research object, this study is based on the track irregularity root mean square rate(TRR), which the authors proposed earlier to quantify the track regularity level. Using the nonlinear least squares fitting method, the mapping relationship between the TRR and the postearthquake train running performance indicators on bridges is established. Furthermore, the influence of laws governing site categories and train speeds on post-earthquake train running performance on bridges is analyzed, and a train speed threshold for bridges based on running performance under random site conditions is proposed. The research results indicate that all train running performance indicators increase significantly with the increase of train operating speed;different site categories have a significant impact on post-earthquake track residual deformation and train running stability. The greater the amplitude of postearthquake track alignment residual deformation, the lower the threshold for the stable running speed of trains after the earthquake, with the speed threshold decreasing by up to 20%. The research outcomes can provide technical references for the post-earthquake safe operation and maintenance of high-speed railway bridges under complex site conditions, as well as the formulation of targeted train speed control schemes.
基金supported by the Natural Science Foundation of Hubei Province (Nos.2023AFB376 and 2024AFD287)National Key Research and Development Program (No.2023YFC3503804)the National Natural Science Foundation of China (No.22077044)。
文摘Sulfur dioxide(SO_(2)) and its derivatives have been recognized as harmful environmental pollutants.However,they are often produced during the processing of traditional Chinese medicines,potentially compromising the quality of these medicinal materials and contributing to various health issues.Due to a lack of effective monitoring and imaging tools,the physiological effects of excessive SO_(2) residues in traditional Chinese medicine remain unclear.Therefore,developing a rapid and effective tool for detecting SO_(2) is crucial for understanding its metabolic pathways and effects in vivo.In this study,we developed a near infrared(NIR) and ratiometric fluorescent probe,NIR-RS,which exhibits high sensitivity,selectivity,and rapid response for SO_(2) detection.Notably,NIR-RS accurately quantifies SO_(2) contents in Pinelliae rhizoma(P.rhizoma) samples,with recovery rates from 98.46 % to 102.40 %,and relative standard deviations(RSDs)< 5.0 %.For bioimaging applications,NIR-RS has low cytotoxicity and good mitochondrial-targeting ability,making it suitable for imaging exogenous and endogenous SO_(2) in mitochondria.Additionally,NIR-RS was successfully applied to image SO_(2) content of P.rhizoma samples within cells,revealing that high SO_(2) residue elevated mitochondria adenosine triphosphate(ATP) content,these findings reveal that P.rhizoma with excessive SO_(2) can affect the organism's growth mechanisms through alterations in ATP pathways.In vivo,SO_(2) was found to predominantly accumulate in the liver following gavage with P.rhizoma solution,with accumulation levels increasing in proportion to SO_(2) residue concentration.High SO_(2) concentrations in P.rhizoma can cause pulmonary fibrosis and gastric mucosal damage.This work provides a valuable tool for regulating SO_(2) content in P.rhizoma and may help researcher better understand the metabolism of SO_(2) derivatives and explore their physiological roles in biological systems.
基金supported by the Shanghai Sailing Program,China(Grant No.:23YF1413300).
文摘Quantitative structure-retention relationship(QSRR)is an important tool in chromatography.QSRR examines the correlation between molecular structures and their retention behaviors during chromatographic separation.This approach involves developing models for predicting the retention time(RT)of analytes,thereby accelerating method development and facilitating compound identification.In addition,QSRR can be used to study compound retention mechanisms and support drug screening efforts.This review provides a comprehensive analysis of QSRR workflows and applications,with a special focus on the role of artificial intelligence-an area not thoroughly explored in previous reviews.Moreover,we discuss current limitations in RT prediction and propose promising solutions.Overall,this review offers a fresh perspective on future QSRR research,encouraging the development of innovative strategies that enable the diverse applications of QSRR models in chromatographic analysis.
文摘This study utilizes two complementary models,the Time-Varying Parameter Vector Autoregressive Diebold–Yilmaz(TVP-VAR-DY)and the Time-Varying Parameter Vector Autoregressive Barunik–Křehlik(TVP-VAR-BK),to investigate the dynamic volatility transmission between exchange rates and stock returns in major commodity-exporting and-importing countries.The analysis focuses on periods of quantitative easing(QE)and quantitative tightening(QT)from March 15,2020 to December 30,2022.The countries examined are Canada and Australia(major commodity exporters)and the UK and Germany(major commodity importers).An essential contribution of this paper is new empirical insights into the dynamics of stock market returns and the transmission of volatility between these markets and exchange rates during the QE and QT periods.The results reveal that causality primarily flows from stock markets to exchange rates,especially during the QT period across all investment horizons.The Toronto Stock Exchange(TSX)emerges as the principal net driver among the markets under study.Furthermore,the Canadian exchange rate(USDCAD)and the Australian Stock Exchange(ASX)are the most significantly affected indices within the network across various investment horizons(excluding the long-term).These findings underscore the importance for investors and policymakers to consider the interplay between exchange rates and stock market returns,particularly in the context of the QE and QT periods,as well as other economic,political,and health-related events.Our findings are relevant to various stakeholders,including governments,traders,portfolio managers,and multinationals.
基金Project supported by the Natural Science Foundation of Shanghai, China(No. 06ZR14002).
文摘Quantitative structure-biodegradability relationships （QSBRs） were established to develop predictive models and mechanistic explanations for acid dyestuffs as well as biological activities. With a total of four descriptors, molecular weight （MW）, energies of the highest occupied molecular orbital （EHOMO）, the lowest unoccupied molecular orbital （ELUMO）, and the excited state （EES）, calculated using quantum chemical semi-empirical methodology, a series of models were analyzed between the dye biodegradability and each descriptor. Results showed that EHOMO and Mw were the dominant parameters controlling the biodegradability of acid dyes. A statistically robust QSBR model was developed for all studied dyes, with the combined application of EHOMO and Mw. The calculated biodegradations fitted well with the experimental data monitored in a facultative-aerobic process, indicative of the reliable prediction and mechanistic character of the developed model.
基金supported by the Research Program of Application Foundation and Advanced Technology from the Tianjin Municipal Science and Technology Committee(No.11JCZDJ24600)the Natural Science Foundationof China(No.20773093)
文摘The amidoximated polyacrylonitrile （PAN） fiber Fe complexeswere prepared and used as the heterogeneous Fenton catalysts for thedegradation of28 anionicwater soluble azodyes inwater under visible irradiation. The multiple linear regression （MLR） methodwas employed todevelop the quantitative structure property relationship （QSPR） model equations for thedecoloration and mineralization of azodyes. Moreover, the predictive ability of the QSPR model equationswas assessed using Leave-one-out （LOO） and cross-validation （CV） methods. Additionally, the effect of Fe content of catalyst and the sodium chloride inwater on QSPR model equationswere also investigated. The results indicated that the heterogeneous photo-Fentondegradation of the azodyeswithdifferent structureswas conducted in the presence of the amidoximated PAN fiber Fe complex. The QSPR model equations for thedyedecoloration and mineralizationwere successfullydeveloped using MLR technique. MW/S （molecularweightdivided by the number of sulphonate groups） and N N=N （the number of azo linkage） are considered as the most importantdetermining factor for thedyedegradation and mineralization, and there is a significant negative correlation between MW/S or N N=N anddegradation percentage or total organic carbon （TOC） removal. Moreover, LOO and CV analysis suggested that the obtained QSPR model equations have the better prediction ability. The variation in Fe content of catalyst and the addition of sodium chloridedid not alter the nature of the QSPR model equations.
文摘An investigation was carried out in the Huanghai Sea and the East China Sea to study the quantitative relationship between the abundance of flagellates and the density of suspended particles in the summer of 2001. The results show that the abundance of flagellates varies from 44-12 600 cell/cm^3, and flagellates sometimes constitutes a significant part of suspended particles. The size-spectra of suspended particles can be divided into four categories： flat spectrum, humped spectrum, plankton spectrum and mixed spectrum. In general, the abundance of flagellates varies in proportion to the density of suspended particles. However, their quantitative relations reveal different characteristics in the seawater samples of different types of particle-size spectrum. This is only a preliminary study of the quantitative relationship between flagellates and suspended particles, which might lead to a potential convenient approach to the estimation of flagellate abundance in the sea.
基金supported by the Youth Foundation of Education Bureau, Sichuan Province (09ZB036)Technology Bureau, Sichuan Province (2006j13-141)
文摘The molecular electronegativity interaction vector （MEIV） was used to describe the molecular structure of 30 selected esters. Two excellent QSTR models were built up by using multiple linear regression （MLR） and partial least-squares regression （PLS）. The correlation coefficients （R） of the two models were 0.945 and 0.941, respectively. The models were evaluated by performing the cross validation with the leave-one-out （LOO） procedure. The cross-verification correlation coefficients （RCV） of the two models were 0.921 and 0.919, respectively. The results showed that the models constructed in this work could provide estimation stability and favorable predictive ability.
基金Project(No.31071501)supported by the National Natural Science Foundation of China
文摘Fatty acids and derivatives(FADs)are resources for natural antimicrobials.In order to screen for additional potent antimicrobial agents,the antimicrobial activities of FADs against Staphylococcus aureus were examined using a microplate assay.Monoglycerides of fatty acids were the most potent class of fatty acids,among which monotridecanoin possessed the most potent antimicrobial activity.The conventional quantitative structure-activity relationship(QSAR)and comparative molecular field analysis(CoMFA)were performed to establish two statistically reliable models(conventional QSAR:R2=0.942,Q 2 LOO=0.910;CoMFA:R 2=0.979,Q 2=0.588,respectively).Improved forecasting can be achieved by the combination of these two models that provide a good insight into the structureactivity relationships of the FADs and that may be useful to design new FADs as antimicrobial agents.
基金supported bythe Special Fund for Basic Research and Operation of the Chinese Academy of Meteorological Sciences (GrantNo. 2011Y004)the Research and Development Special Fund for Public Welfare Industry (Meteorology+2 种基金Grant No.GYHY201006042)the National Natural Science Foundation of China (Grant No. 40975014)the Open Research Fund for State Key Laboratory of Hydroscience and Engineering of Tsinghua University (the search of basin QPE and QPF based on new generation of weather and numerical models)
文摘The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations. In this study, a real-time adjustment to the radar reflectivity rainfall rates （Z R） relationship scheme and the gauge-corrected, radar-based, estimation scheme with inverse distance weighting interpolation was devel- oped. Based on the characteristics of the two schemes, the two-step correction technique of radar quantitative precipitation estimation is proposed. To minimize the errors between radar quantitative precipitation es- timations and rain gauge observations, a real-time adjustment to the Z R relationship scheme is used to remove systematic bias on the time-domain. The gauge-corrected, radar-based, estimation scheme is then used to eliminate non-uniform errors in space. Based on radar data and rain gauge observations near the Huaihe River, the two-step correction technique was evaluated using two heavy-precipitation events. The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.
文摘The recent year's monitor results of Beijing indicated that the pollution level of fine particles PM 2.5 showed an increasing trend. To understand pollution characteristics of PM 2.5 and its relationship with the meteorological conditions in Beijing, a one-year monitoring of PM 2.5 mass concentration and correspondent meteorological parameters was performed in Beijing in 2001. The PM 2.5 levels in Beijing were very high, the annual average PM 2.5 concentration in 2001 was 7 times of the National Ambient Air Quality Standards proposed by US EPA. The major chemical compositions were organics, sulfate, crustals and nitrate. It was found that the mass concentrations of PM 2.5 were influenced by meteorological conditions. The correlation between the mass concentrations of PM 2.5 and the relative humidity was found. And the correlation became closer at higher relative humidity. And the mass concentrations of PM 2.5 were negtive-correlated to wind speeds, but the correlation between the mass concentration of PM 2.5 and wind speed was not good at stronger wind.
基金Supported by the National High Technology Research and Development Program of China (863 Program, No. 2006AA02Z312)
文摘A new set of descriptors, HSEHPCSV （component score vector of hydrophobic, steric, and electronic properties together with hydrogen bonding contributions）, were derived from principal component analyses of 95 physicochemical variables of 20 natural amino acids separately according to different kinds of properties described, namely, hydrophobic, steric, and electronic properties as well as hydrogen bonding contributions. HSEHPCSV scales were then employed to express structures of angiotensin-converting enzyme inhibitors, bitter tasting thresholds and bactericidal 18 peptide, and to construct QSAR models based on partial least square （PLS）. The results obtained are as follows： the multiple correlation coefficient （R2cum） of 0.846, 0.917 and 0.993, leave-one-out cross validated Q2cm of 0.835, 0.865 and 0.899, and root-mean-square error for estimated error （RMSEE） of 0.396, 0.187and 0.22, respectively. Satisfactory results showed that, as new amino acid scales, data of HSEHPCSV may be a useful structural expression methodology＇for the studies on peptide QSAR （quantitative structure-activity relationship） due to many advantages such as plentiful structural information, definite physical and chemical meaning and easy interpretation.
基金National Natural Science Foundation of China,No.51809131,No.U2040203Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,No.2017491211Fundamental Research Funds for Central Welfare Research Institutes,No.TKS20200404,No.TKS20200312。
文摘Deep-water navigation channels in the tidal reaches of the lower Yangtze River are affected by water and sediment fluxes that produce complex shoals and unstable channel conditions.The Fujiangsha reach is particularly difficult to manage,as it has many braided channels within the tidal fluctuation zone.In this study,hydrologic and topographic data from the Fujiangsha reach from 2012 to 2017 were used to examine the variations in deposition and erosion,flow diversion,shoals,and channel conditions.Since the Three Gorges Dam became operational and water storage was initiated,the Fujiangsha reach has shown an overall tendency toward erosion.Channels deeper than 10 m accounted for 83.7% of the total erosion of the Fujiangsha reach during 2012-2017.Moreover,the dominant channel-forming sediments have gradually changed from suspended sediments to a mixed load of suspended and bed-load sediments.Deposition volumes of these sediments has varied significantly among different channels,but has mainly occurred in the Fubei channel.Furthermore,periodic variations in the Jingjiang point bar have followed a deposition-erosion-deposition pattern,and the downstream Shuangjian shoal mid-channel bar has been scoured and shortened.Approximately 44.0% of the bed load from the upstream Fujiangsha reach is deposited within the 12.5-m deep Fubei channel.The increased erosion and river flow from the Jingjiang point bar and the Shuangjian shoal during the flood season constituted 59.3% and 40.7%,respectively,of the total amount of siltation in the Fubei channel.
基金Supported by the Chinese National Key Technologies R & D Program of 11th Five-year Plan (2006BAD27B06)Education Foundation of Innovative Engineering Key Project of Education Department (707034)
文摘Carotenoids are a family of effective active oxygen scavengers, which can reduce the danger of occurrence of chronic diseases such as cardiovascular disease, cataract, cancer, and so on. The quantitative structure-activity relationship （QSAR） equation between carotenoids and antioxidant activity was established by quantum chemistry AM1, molecular mechanism （MM＋） and stepwise regression analysis methods, and the model was evaluated by leave-one-out approach. The results showed that the significant molecular descriptors related to the antioxidant activity of carotenoids were the energy difference （E_HL） between the lowest unoccupied molecular orbital （LUMO） and the highest occupied molecular orbital （HOMO） and ionization energy （Eiso）. The model showed a good predictive ability （Q^2 〉 0.5）.
基金supported by the Natural Science Foundation of Fujian Province (D0710019)the Natural Science Foundation of Overseas Chinese Affairs Office of the State Council (06QZR09)
文摘With the artificial neural network（ANN） method combined with the multiple linear regression（MLR）,based on a series of quantum chemical descriptors and molecular connectivity indexes,quantitative structure-activity relationship（QSAR） models to predict the acute toxicity（-lgEC50） of substituted aromatic compounds to Photobacterium phosphoreum were established.Four molecular descriptors that appear in the MLR model,namely,the second order valence molecular connectivity index（2XV）,the energy of the highest occupied molecular orbital（EHOMO）,the logarithm of n-octyl alcohol/water partition coefficient（logKow） and the Connolly molecular area（MA）,were inputs of the ANN model.The root-mean-square error（RMSE） of the training and validation sets of the ANN model are 0.1359 and 0.2523,and the correlation coefficient（R） is 0.9810 and 0.8681,respectively.The leave-one-out（LOO） cross validated correlation coefficient（Q L2OO） of the MLR and ANN models is 0.6954 and 0.6708,respectively.The result showed that the two methods are complementary in the calculations.The regression method gave support to the neural network with physical explanation,and the neural network method gave a more accurate model for QSAR.In addition,some insights into the structural factors affecting the acute toxicity and toxicity mechanism of substituted aromatic compounds were discussed.
文摘Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecular structure without any experimental effort, they provide a simple and straightforward method for property prediction. In this work the flash point of alkanes was modeled by a set of molecular connectivity indices （Х）, modified molecular connectivity indices （ ^mХ^v ） and valance molecular connectivity indices （ ^mХ^v ）, with ^mХ^v calculated using the hydrogen perturbation. A stepwise Multiple Linear Regression （MLR） method was used to select the best indices. The predicted flash points are in good agreement with the experimental data, with the average absolute deviation 4.3 K.
基金Supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0082)
文摘Breast cancer is presently one of the most common malignancies worldwide,with a higher fatality rate.In this study,a quantitative structure-activity relationship(QSAR)model of compound biological activity and ADMET(Absorption,Distribution,Metabolism,Excretion,Toxicity)properties prediction model were performed using estrogen receptor alpha(ERα)antagonist information collected from compound samples.We first utilized grey relation analysis(GRA)in conjunction with the random forest(RF)algorithm to identify the top 20 molecular descriptor variables that have the greatest influence on biological activity,and then we used Spearman correlation analysis to identify 16 independent variables.Second,a QSAR model of the compound were developed based on BP neural network(BPNN),genetic algorithm optimized BP neural network(GA-BPNN),and support vector regression(SVR).The BPNN,the SVR,and the logistic regression(LR)models were then used to identify and predict the ADMET properties of substances,with the prediction impacts of each model compared and assessed.The results reveal that a SVR model was used in QSAR quantitative prediction,and in the classification prediction of ADMET properties:the SVR model predicts the Caco-2 and hERG(human Ether-a-go-go Related Gene)properties,the LR model predicts the cytochrome P450 enzyme 3A4 subtype(CYP3A4)and Micronucleus(MN)properties,and the BPNN model predicts the Human Oral Bioavailability(HOB)properties.Finally,information entropy theory is used to validate the rationality of variable screening,and sensitivity analysis of the model demonstrates that the constructed model has high accuracy and stability,which can be used as a reference for screening probable active compounds and drug discovery.
基金funded by the Chinese High-Yielding Transgenic Program (Grant No. 2011ZX08001-004)the National High-Tech Research and Development Program (Grant No. 2011AA10A101)the Research Funding of China National Rice Research Institute(Grant No. 2009RG002)
文摘Grain yield and heading date are key factors determining the commercial potential of a rice variety. Mapping of quantitative trait loci （QTLs） in rice has been advanced from primary mapping to gene cloning, and heading date and yield traits have always attracted the greatest attention. In this review, genomic distribution of QTLs for heading date detected in populations derived from intra-specific crosses of Asian cultivated rice （Oryza sativa） was summarized, and their relationship with the genetic control of yield traits was analyzed. The information could be useful in the identification of QTLs for heading date and yield traits that are promising for the improvement of rice varieties.
