GC-MS结合电子鼻技术对不同茶区茉莉花茶香气的差异比较

为探究不同产区茉莉花茶香气差异,采用气相色谱-质谱(GasChromatography-Mass Spectrometry,GC-MS)结合电子鼻(Electronic Nose,E-nose)技术对西南、华南、江南三大茶区的8种茉莉花茶进行香气研究。结果表明,8个样品共鉴定出香气成分58种,其中西南、江南、华南茶区分别为45种、51种、47种。江南茶区香气化合物总量最高。共有香气成分主要包括邻氨基苯甲酸甲酯、顺式-3-己烯醇苯甲酸酯、乙酸苄酯、水杨酸甲酯、芳樟醇、吲哚等。其中水杨酸甲酯在江南茶区含量最高(22.32μg/g),分别较华南、西南茶区高33.96%、68.01%;邻氨基苯甲酸甲酯(67.39μg/g)和吲哚(43.84μg/g)含量在华南茶区最高。茉莉花茶香气评价指数(JasmineTea Flavor Index,JTF index)分析表明西南茶区样品等级最高。香气聚类分析将共有香气成分分为3类,分别呈花香、茉莉花香和草木香。通过电子鼻技术可知样品香气物质变化与硫化物、碳氢化合物、芳香化合物有关,并能有效区别样品香气。综上,三大茶区样品香气种类差异不明显,但各香气成分含量差异显著(P<0.05),江南和华南茶区的样品特征性香气成分含量较高,西南茶区样品综合指数高。

京津冀地区碳排放时空格局变化及其驱动因子

人类对陆地生态系统的改变是碳排放增加的主要原因。在“双碳”目标背景下探索土地利用变化与碳排放的动态关系,有助于区域土地低碳可持续利用。研究基于土地利用转移视角,采用重心-标准差椭圆方法揭示了京津冀地区土地利用碳排放时空格局演化特征,评估了碳排放与生态环境、社会经济发展的协调程度,并借助改进的Kaya模型和LMDI分解模型定量分析了土地利用变化对碳排放的影响程度。结果表明:(1)建设用地的转入是土地利用碳排放增加的主要来源,引起碳排放量增加15844.36万t;耕地、草地向林地、水域的转变促进了地区固碳能力的提升。(2)土地利用碳排放空间分布格局呈现出东北-西南方向向中心进一步聚集的趋势,并且东-西向聚集趋势大于南-北向。(3)京津冀地区整体碳排放与生态环境的协调性呈向好趋势发展,但大部分地区碳排放与社会经济发展出现失衡现象,地区间碳生产力差异逐渐增大。(4)经济水平是促进碳排放增加的最显著因素,单位GDP用地强度是抑制碳排放增加的最主要因素。分析结果表明,严格控制建设用地的无序扩张是促进低碳土地利用的基础,低碳经济发展是促进地区减碳的重要途径。

Probabilistic analysis of tunnel face seismic stability in layered rock masses using Polynomial Chaos Kriging metamodel

Face stability is an essential issue in tunnel design and construction.Layered rock masses are typical and ubiquitous;uncertainties in rock properties always exist.In view of this,a comprehensive method,which combines the Upper bound Limit analysis of Tunnel face stability,the Polynomial Chaos Kriging,the Monte-Carlo Simulation and Analysis of Covariance method(ULT-PCK-MA),is proposed to investigate the seismic stability of tunnel faces.A two-dimensional analytical model of ULT is developed to evaluate the virtual support force based on the upper bound limit analysis.An efficient probabilistic analysis method PCK-MA based on the adaptive Polynomial Chaos Kriging metamodel is then implemented to investigate the parameter uncertainty effects.Ten input parameters,including geological strength indices,uniaxial compressive strengths and constants for three rock formations,and the horizontal seismic coefficients,are treated as random variables.The effects of these parameter uncertainties on the failure probability and sensitivity indices are discussed.In addition,the effects of weak layer position,the middle layer thickness and quality,the tunnel diameter,the parameters correlation,and the seismic loadings are investigated,respectively.The results show that the layer distributions significantly influence the tunnel face probabilistic stability,particularly when the weak rock is present in the bottom layer.The efficiency of the proposed ULT-PCK-MA is validated,which is expected to facilitate the engineering design and construction.

Asymmetric Drying and Wetting Trends in Eastern and Western China

As an important factor that directly affects agricultural production, the social economy, and policy implementation,observed changes in dry/wet conditions have become a matter of widespread concern. However, previous research has mainly focused on the long-term linear changes of dry/wet conditions, while the detection and evolution of the non-linear trends related to dry/wet changes have received less attention. The non-linear trends of the annual aridity index, obtained by the Ensemble Empirical Mode Decomposition(EEMD) method, reveal that changes in dry/wet conditions in China are asymmetric and can be characterized by contrasting features in both time and space in China. Spatially, most areas in western China have experienced transitions from drying to wetting, while opposite changes have occurred in most areas of eastern China. Temporally, the transitions occurred earlier in western China compared to eastern China. Research into the asymmetric spatial characteristics of dry/wet conditions compensates for the inadequacies of previous studies, which focused solely on temporal evolution;at the same time, it remedies the inadequacies of traditional research on linear trends over centennial timescales. Analyzing the non-linear trend also provides for a more comprehensive understanding of the drying/wetting changes in China.

Effects of drip and flood irrigation on carbon dioxide exchange and crop growth in the maize ecosystem in the Hetao Irrigation District,China

Drip irrigation and flood irrigation are major irrigation methods for maize crops in the Hetao Irrigation District,Inner Mongolia Autonomous Region,China.This research delves into the effects of these irrigation methods on carbon dioxide(CO_(2))exchange and crop growth in this region.The experimental site was divided into drip and flood irrigation zones.The irrigation schedules of this study aligned with the local commonly used irrigation schedule.We employed a developed chamber system to measure the diurnal CO_(2)exchange of maize plants during various growth stages under both drip and flood irrigation methods.From May to September in 2020 and 2021,two sets of repeated experiments were conducted.In each experiment,a total of nine measurements of CO_(2)exchange were performed to obtain carbon exchange data at different growth stages of maize crop.During each CO_(2)exchange measurement event,CO_(2)flux data were collected every two hours over a day-long period to capture the diurnal variations in CO_(2)exchange.During each CO_(2)exchange measurement event,the biological parameters(aboveground biomass and crop growth rate)of maize and environmental parameters(including air humidity,air temperature,precipitation,soil water content,and photosynthetically active radiation)were measured.The results indicated a V-shaped trend in net ecosystem CO_(2)exchange in daytime,reducing slowly at night,while the net assimilation rate(net primary productivity)exhibited a contrasting trend.Notably,compared with flood irrigation,drip irrigation demonstrated significantly higher average daily soil CO_(2)emission and greater average daily CO_(2)absorption by maize plants.Consequently,within the maize ecosystem,drip irrigation appeared more conducive to absorbing atmospheric CO_(2).Furthermore,drip irrigation demonstrated a faster crop growth rate and increased aboveground biomass compared with flood irrigation.A strong linear relationship existed between leaf area index and light utilization efficiency,irrespective of the irrigation method.Notably,drip irrigation displayed superior light use efficiency compared with flood irrigation.The final yield results corroborated these findings,indicating that drip irrigation yielded higher harvest index and overall yield than flood irrigation.The results of this study provide a basis for the selection of optimal irrigation methods commonly used in the Hetao Irrigation District.This research also serves as a reference for future irrigation studies that consider measurements of both carbon emissions and yield simultaneously.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Association between childhood obesity and gut microbiota:16S rRNA gene sequencing-based cohort study

BACKGROUND This study aimed to identify characteristic gut genera in obese and normal-weight children(8-12 years old)using 16S rDNA sequencing.The research aimed to provide insights for mechanistic studies and prevention strategies for childhood obesity.Thirty normal-weight and thirty age-and sex-matched obese children were included.Questionnaires and body measurements were collected,and fecal samples underwent 16S rDNA sequencing.Significant differences in body mass index(BMI)and body-fat percentage were observed between the groups.Analysis of gut microbiota diversity revealed lowerα-diversity in obese children.Differences in gut microbiota composition were found between the two groups.Prevotella and Firmicutes were more abundant in the obese group,while Bacteroides and Sanguibacteroides were more prevalent in the control group.AIM To identify the characteristic gut genera in obese and normal-weight children(8-12-year-old)using 16S rDNA sequencing,and provide a basis for subsequent mechanistic studies and prevention strategies for childhood obesity.METHODS Thirty each normal-weight,1:1 matched for age and sex,and obese children,with an obese status from 2020 to 2022,were included in the control and obese groups,respectively.Basic information was collected through questionnaires and body measurements were obtained from both obese and normal-weight children.Fecal samples were collected from both groups and subjected to 16S rDNA sequencing using an Illumina MiSeq sequencing platform for gut microbiota diversity analysis.RESULTS Significant differences in BMI and body-fat percentage were observed between the two groups.The Ace and Chao1 indices were significantly lower in the obese group than those in the control group,whereas differences were not significant in the Shannon and Simpson indices.Kruskal-Wallis tests indicated significant differences in unweighted and weighted UniFrac distances between the gut microbiota of normal-weight and obese children(P<0.01),suggesting substantial disparities in both the species and quantity of gut microbiota between the two groups.Prevotella,Firmicutes,Bacteroides,and Sanguibacteroides were more abundant in the obese and control groups,respectively.Heatmap results demonstrated significant differences in the gut microbiota composition between obese and normal-weight children.CONCLUSION Obese children exhibited lowerα-diversity in their gut microbiota than did the normal-weight children.Significant differences were observed in the composition of gut microbiota between obese and normal-weight children.

A phenology-based vegetation index for improving ratoon rice mapping using harmonized Landsat and Sentinel-2 data

Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.

Three-dimensional choroidal vascularity index and choroidal thickness in fellow eyes of acute and chronic primary angle-closure using swept-source optical coherence tomography

AIM:To compare the three-dimensional choroidal vascularity index(CVI)and choroidal thickness between fellow eyes of acute primary angle-closure(F-APAC)and chronic primary angle-closure glaucoma(F-CPACG)and the eyes of normal controls.METHODS:This study included 37 patients with unilateral APAC,37 with asymmetric CPACG without prior treatment,and 36 healthy participants.Using swept-source optical coherence tomography(SS-OCT),the macular and peripapillary choroidal thickness and three-dimensional CVI were measured and compared globally and sectorally.Pearson’s correlation analysis and multivariate regression models were used to evaluate choroidal thickness or CVI with related factors.RESULTS:The mean subfoveal CVIs were 0.35±0.10,0.33±0.09,and 0.29±0.04,and the mean subfoveal choroidal thickness were 315.62±52.92,306.22±59.29,and 262.69±45.55μm in the F-APAC,F-CPACG,and normal groups,respectively.All macular sectors showed significantly higher CVIs and choroidal thickness in the F-APAC and F-CPACG eyes than in the normal eyes(P<0.05),while there were no significant differences between the F-APAC and F-CPACG eyes.In the peripapillary region,the mean overall CVIs were 0.21±0.08,0.20±0.08,and 0.19±0.05,and the mean overall choroidal thickness were 180.45±54.18,174.82±50.67,and 176.18±37.94μm in the F-APAC,F-CPACG,and normal groups,respectively.There were no significant differences between any of the two groups in all peripapillary sectors.Younger age,shorter axial length,and the F-APAC or F-CPACG diagnosis were significantly associated with higher subfoveal CVI and thicker subfoveal choroidal thickness(P<0.05).CONCLUSION:The fellow eyes of unilateral APAC or asymmetric CPACG have higher macular CVI and choroidal thickness than those of the normal controls.Neither CVI nor choroidal thickness can distinguish between eyes predisposed to APAC or CPACG.A thicker choroid with a higher vascular volume may play a role in the pathogenesis of primary angle-closure glaucoma.

Predictive model using four ferroptosis-related genes accurately predicts gastric cancer prognosis

BACKGROUND Gastric cancer(GC)is a common malignancy of the digestive system.According to global 2018 cancer data,GC has the fifth-highest incidence and the thirdhighest fatality rate among malignant tumors.More than 60%of GC are linked to infection with Helicobacter pylori(H.pylori),a gram-negative,active,microaerophilic,and helical bacterium.This parasite induces GC by producing toxic factors,such as cytotoxin-related gene A,vacuolar cytotoxin A,and outer membrane proteins.Ferroptosis,or iron-dependent programmed cell death,has been linked to GC,although there has been little research on the link between H.pylori infection-related GC and ferroptosis.AIM To identify coregulated differentially expressed genes among ferroptosis-related genes(FRGs)in GC patients and develop a ferroptosis-related prognostic model with discrimination ability.METHODS Gene expression profiles of GC patients and those with H.pylori-associated GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus(GEO)databases.The FRGs were acquired from the FerrDb database.A ferroptosis-related gene prognostic index(FRGPI)was created using least absolute shrinkage and selection operator–Cox regression.The predictive ability of the FRGPI was validated in the GEO cohort.Finally,we verified the expression of the hub genes and the activity of the ferroptosis inducer FIN56 in GC cell lines and tissues.RESULTS Four hub genes were identified(NOX4,MTCH1,GABARAPL2,and SLC2A3)and shown to accurately predict GC and H.pylori-associated GC.The FRGPI based on the hub genes could independently predict GC patient survival;GC patients in the high-risk group had considerably worse overall survival than did those in the low-risk group.The FRGPI was a significant predictor of GC prognosis and was strongly correlated with disease progression.Moreover,the gene expression levels of common immune checkpoint proteins dramatically increased in the highrisk subgroup of the FRGPI cohort.The hub genes were also confirmed to be highly overexpressed in GC cell lines and tissues and were found to be primarily localized at the cell membrane.The ferroptosis inducer FIN56 inhibited GC cell proliferation in a dose-dependent manner.CONCLUSION In this study,we developed a predictive model based on four FRGs that can accurately predict the prognosis of GC patients and the efficacy of immunotherapy in this population.

Association between triglyceride-glucose index and colorectal polyps:A retrospective cross-sectional study

BACKGROUND Colorectal polyps(CPs)are frequently occurring abnormal growths in the colorectum,and are a primary precursor of colorectal cancer(CRC).The triglyceride-glucose(TyG)index is a novel marker that assesses metabolic health and insulin resistance,and has been linked to gastrointestinal cancers.AIM To investigate the potential association between the TyG index and CPs,as the relation between them has not been documented.METHODS A total of 2537 persons undergoing a routine health physical examination and colonoscopy at The First People's Hospital of Kunshan,Jiangsu Province,China,between January 2020 and December 2022 were included in this retrospective cross-sectional study.After excluding individuals who did not meet the eligibility criteria,descriptive statistics were used to compare characteristics between patients with and without CPs.Logistic regression analyses were conducted to determine the associations between the TyG index and the prevalence of CPs.The TyG index was calculated using the following formula:Ln[triglyceride(mg/dL)×glucose(mg/dL)/2].The presence and types of CPs was determined based on data from colonoscopy reports and pathology reports.RESULTS A nonlinear relation between the TyG index and the prevalence of CPs was identified,and exhibited a curvilinear pattern with a cut-off point of 2.31.A significant association was observed before the turning point,with an odds ratio(95% confidence interval)of 1.70(1.40,2.06),P<0.0001.However,the association between the TyG index and CPs was not significant after the cut-off point,with an odds ratio(95% confidence interval)of 0.57(0.27,1.23),P=0.1521.CONCLUSION Our study revealed a curvilinear association between the TyG index and CPs in Chinese individuals,suggesting its potential utility in developing colonoscopy screening strategies for preventing CRC.

Renal resistive index measurements by ultrasound in patients with liver cirrhosis:Magnitude and associations with renal dysfunction

BACKGROUND The hemodynamic alterations seen in liver cirrhosis lead to renal vasoconstriction,ultimately causing acute kidney injury(AKI).The renal resistive index(RRI)is the most common Doppler ultrasound variable for measuring intrarenal vascular resistance.AIM To evaluate the association of the RRI with AKI in patients with liver cirrhosis and to identify risk factors for high RRI.METHODS This was a prospective observational study,where RRI was measured using Doppler ultrasound in 200 consecutive hospitalized patients with cirrhosis.The association of RRI with AKI was studied.The receiver operating characteristic(ROC)curve analysis was utilized to determine discriminatory cut-offs of RRI for various AKI phenotypes.Multivariate analysis was conducted to determine the predictors of high RRI.RESULTS The mean patient age was 49.08±11.68 years,with the majority(79.5%)being male;the predominant etiology of cirrhosis was alcohol(39%).The mean RRI for the study cohort was 0.68±0.09,showing a progressive increase with higher Child-Pugh class of cirrhosis.Overall,AKI was present in 129(64.5%)patients.The mean RRI was significantly higher in patients with AKI compared to those without it(0.72±0.06 vs 0.60±0.08;P<0.001).A total of 82 patients(41%)had hepatorenal syndrome(HRS)-AKI,29(22.4%)had prerenal AKI(PRA),and 18(13.9%)had acute tubular necrosis(ATN)-AKI.The mean RRI was significantly higher in the ATN-AKI(0.80±0.02)and HRS-AKI(0.73±0.03)groups than in the PRA(0.63±0.07)and non-AKI(0.60±0.07)groups.RRI demonstrated excellent discriminatory ability in distinguishing ATN-AKI from non-ATN-AKI(area under ROC curve:93.9%).AKI emerged as an independent predictor of high RRI(adjusted odds ratio[OR]:11.52),and high RRI independently predicted mortality among AKI patients(adjusted OR:3.18).CONCLUSION In cirrhosis patients,RRI exhibited a significant association with AKI,effectively differentiated between AKI phenotypes,and predicted AKI mortality.

Influence of vapor pressure deficit on vegetation growth in China

Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric water demand,VPD has implications for global water resources,and its significance extends to the structure and functioning of ecosystems.However,the influence of VPD on vegetation growth under climate change remains unclear in China.This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit(CRU)Time-Series version 4.06(TS4.06)and European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis 5(ERA-5).Vegetation growth status was characterized using three vegetation indices,namely gross primary productivity(GPP),leaf area index(LAI),and near-infrared reflectance of vegetation(NIRv).The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test.Furthermore,the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model.The results indicated an overall negative correlation between VPD and vegetation indices.Three VPD intervals for the correlations between VPD and vegetation indices were identified:a significant positive correlation at VPD below 4.820 hPa,a significant negative correlation at VPD within 4.820–9.000 hPa,and a notable weakening of negative correlation at VPD above 9.000 hPa.VPD exhibited a pronounced negative impact on vegetation growth,surpassing those of temperature,precipitation,and solar radiation in absolute magnitude.CO_(2) contributed most positively to vegetation growth,with VPD offsetting approximately 30.00%of the positive effect of CO_(2).As the rise of VPD decelerated,its relative contribution to vegetation growth diminished.Additionally,the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China.This research provides a theoretical foundation for addressing climate change in China,especially regarding the challenges posed by increasing VPD.

Spatio-temporal evolution analysis of landscape pattern and habitat quality in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 based on InVEST model

Habitat quality is an important indicator for evaluating the quality of ecosystem.The Qinghai Province section of the Yellow River Basin plays an important role in the ecological protection of the upper reaches of the Yellow River Basin.To comprehensively analysis the alterations of habitat quality in the Qinghai Province section of the Yellow River Basin,this study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model to calculate the habitat quality index and analyze the spatio-temporal variation characteristics of habitat quality in the study area from 2000 to 2022,and calculated seven landscape pattern indices(number of patches,patch density,largest patch index(LPI),landscape shape index(LSI),contagion index(CONTAG),Shannon diversity index,and Shannon evenness index)to research the variation of landscape pattern in the study area.The results showed that the number of patches,patch density,LPI,LSI,Shannon diversity index,and Shannon evenness index increased from 2000 to 2022,while the CONTAG decreased,indicating that the landscape pattern in the Qinghai Province section of the Yellow River Basin changed in the direction of distribution fragmentation,shape complexity,and heterogeneity.The average value of the habitat quality index in the Qinghai Province section of the Yellow River Basin from 2000 to 2022 was 0.90.Based on the value of habitat quality index,we divided the level of habitat quality into five categories:lower(0.00-0.20),low(0.20-0.40),moderate(0.40-0.60),high(0.60-0.80),and higher(0.80-1.00).Most areas were at the higher habitat quality level.The lower habitat quality patches were mainly distributed in Longyang Gorge and Yellow River-Huangshui River Valley.From 2000 to 2022,the habitat quality in most areas was stable;the increase areas were mainly distributed in Guinan County,while the decrease areas were mainly distributed in Xining City,Maqen County,Xinghai County,Qumarleb County,and Darlag County.To show the extent of habitat quality variation,we calculated Sen index.The results showed that the higher habitat quality area had a decrease trending,while other categories had an increasing tendency,and the decreasing was faster than increasing.The research results provide scientific guidance for promoting ecological protection and high-quality development in the Qinghai Province section of the Yellow River Basin.

New indices to balanceα-diversity against tree size inequality

The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.

Development of endemicity and conservation importance indices for tropical forests and the floral diversity assessment of Mt.Natoo in Benguet,Philippines

The scientific community faces the challenge of measuring progress toward biodiversity targets and indices have been traditionally used.However,recent inventories in secondary tropical mountain forests using traditional biodiversity indices have yielded results that are indistinct with primary ones.This shows the need to develop complementary indices that goes beyond species count but integrates the distribution and conservation status of the species.This study developed endemicity and conservation importance index for tropical forest that incorporated the distribution and conservation status of the species.These indices were applied to Mt.Natoo,a remnant primary mossy forest in Buguias,Benguet,Philippines,that resulted to endemicity index of 81.07 and conservation importance index of 42.90.Comparing these with secondary forest sites with comparable Shannon-Wiener,Simpson,Evenness and Margalef’s indices,our endemicity and conservation indices clearly differentiates primary forest(our study site)with higher values from secondary forests with much lower values.Thus,we are proposing these indices for a direct but scientifically-informed identification of specific sites for conservation and protection in tropical forests.Additionally,our study documented a total of 168 vascular plant species(79 endemic and 12 locally threatened species)in Mt.Nato-o.Majority are of tropical elements for both generic and species levels with some temperate elements that could be attributed to the site's high elevation and semi-temperate climate.These are important baseline information for conservation plans and monitoring of tropical mossy forests.

On traceable iterated line graph and hamiltonian path index

Xiong and Liu[21]gave a characterization of the graphs G for which the n-iterated line graph L^(n)(G)is hamiltonian,for n≥2.In this paper,we study the existence of a hamiltonian path in L^(n)(G),and give a characterization of G for which L^(n)(G)has a hamiltonian path.As applications,we use this characterization to give several upper bounds on the hamiltonian path index of a graph.

Assessment on eco-environmental quality of the Yellow River Basin by considering desertification index

Desertification has had a significant impact on the ecological environment of the Yellow River Basin(YRB)in China.However,previous studies on the evaluation of the ecological environment quality(EEQ)in the YRB have paid limited attention to the indicator of desertification.It is of great significance to incorporate the desertification index into the spatiotemporal assessment of the EEQ in the YRB in order to protect the ecological environment in the region.In this study,based on multi-source remote sensing data from 91 cities in the YRB,this article proposes a desertification remote sensing ecological index(DRSEI)model,which builds upon the traditional Remote Sensing Ecological Index(RSEI)model,to analyze the spatiotemporal changes in the EEQ in the YRB from 2001 to 2021.Furthermore,using the geographic detector(GD),and geographically and temporally weighted regression(GTWR)model,the study assesses the impact of human and natural factors on the EEQ in the YRB.The research findings indicate that:(1)Compared to the traditional RSEI,the improved DRSEI shows a decreasing trend in the evaluation results of the EEQ.Among the 24 cities,the change in DRSEI exceeds 0.05 compared to RSEI,accounting for 26.37%of the YRB.The remaining 67 cities have changes within a range of less than 0.05,accounting for 73.63%of the YRB.(2)The results of the GD for individual and interactive effects reveal that rainfall and elevation have significant individual and interactive effects on the EEQ.Furthermore,after the interaction with natural factors,the explanatory power of human factors gradually increases over time.The spatial heterogeneity results of GTWR demonstrate that rainfall has a strong direct positive impact on the EEQ,accounting for 98.90%of the influence,while temperature exhibits a more pronounced direct inhibitory effect,accounting for 76.92%of the influence.Human activities have a strong negative impact on the EEQ and a weak positive impact.

Response of vegetation variation to climate change and human activities in the Shiyang River Basin of China during 2001-2022

Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.

Effect of titanium on the sticking of pellets based on hydrogen metallurgy shaft furnace:Behavior analysis and mechanism evolution

Direct reduction based on hydrogen metallurgical gas-based shaft furnace is a promising technology for the efficient and low-carbon smelting of vanadium-titanium magnetite.However,in this process,the sticking of pellets occurs due to the aggregation of metal-lic iron between the contact surfaces of adjacent pellets and has a serious negative effect on the continuous operation.This paper presents a detailed experimental study of the effect of TiO2 on the sticking behavior of pellets during direct reduction under different conditions.Results showed that the sticking index(SI)decreased linearly with the increasing TiO2 addition.This phenomenon can be attributed to the increase in unreduced FeTiO3 during reduction,leading to a decrease in the number and strength of metallic iron interconnections at the sticking interface.When the TiO2 addition amount was raised from 0 to 15wt%at 1100°C,the SI also increased from 0.71%to 59.91%.The connection of the slag phase could be attributed to the sticking at a low reduction temperature,corresponding to the low sticking strength.Moreover,the interconnection of metallic iron became the dominant factor,and the SI increased sharply with the increase in re-duction temperature.TiO2 had a greater effect on SI at a high reduction temperature than at a low reduction temperature.