With the rapid economic development and continuous expansion of human activities,forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threat...With the rapid economic development and continuous expansion of human activities,forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threats to ecosystem stability.Understanding the current status of forest degradation and assessing potential carbon stocks in China are of strategic importance for making forest restoration efforts and enhancing carbon sequestration capacity.In this study,we used the national forest inventory data from 2009 to 2018 to develop a set of standard measures for assessing degraded forests across China,based on five key indicators:forest accumulation growth rate(FAGR),forest recruitment rate(FRR),tree species reduction rate(TSRR),forest canopy cover reduction rate(FCCRR),and forest disaster level(FDL).Additionally,we estimated standing carbon stock,potential carbon stock,and theoretical space to grow by developing a stand growth model,which accounts for stand density across different site classes,to evaluate the restoration potential of degraded forests.The results indicate that degraded forest area in China is 36.15 million hectares,accounting for 20.10% of a total forest area.Standing carbon stock and potential carbon stock of degraded forests in China are 23.93 million tons and 61.90 million tons,respectively.Overall,degraded forest varies significantly across different regions.The results highlight the important trade-offs among environmental factors,policy decisions,and forest conditions,providing a robust foundation for developing measures to enhance forest quality.展开更多
Hatchery release is a common and effective practice for protecting and restoring wild resources,and the success of the practice is commonly assessed using mark-recapture technology.We investigated the use of different...Hatchery release is a common and effective practice for protecting and restoring wild resources,and the success of the practice is commonly assessed using mark-recapture technology.We investigated the use of different dimensional X-ray imaging techniques for the strontium(Sr)marking of fish fin rays for stocking.Megalobrama amblycephala juveniles were marked by culturing specimens in 800-mg/L SrCl_(2)·6 H_(2)O solution,the cross-sections of dorsal fin rays were subsequently obtained,and the concentrations Sr was analyzed by 2 D imaging using an electron probe X-ray microanalyzer.Our preliminary findings indicate that the immersion marking method is effective for the Sr marking of fin rays in experimental fish.Moreover,we generated a bird’s-eye-view 3 D mesh image of the Sr concentrations,which can provide a more comprehensive information for fish stocking than that using normal 2 D imaging.展开更多
Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and complexity.This paper introduces a generative adversarial network model that incorporates an attent...Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and complexity.This paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price prediction.Firstly,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock price.The discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock prices.Secondly,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation study.The results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.展开更多
Sacred forests play a valuable role in the conservation of local biodiversity and provide numerous ecosystem services in Cameroon. The aim of this study was to estimate floristic diversity, stand structures and carbon...Sacred forests play a valuable role in the conservation of local biodiversity and provide numerous ecosystem services in Cameroon. The aim of this study was to estimate floristic diversity, stand structures and carbon stocks in the sacred forests of Bandrefam and Batoufam (western Cameroon). The floristic inventory and the stand structures were carried out in 25 m × 25 m plots for individuals with diameters greater than 10 cm;5 m × 5 m for individuals with diameters less than 10 cm. Carbon stocks were estimated using the non-destructive method and allometric equations. The floristic inventory identified 65 species divided into 57 genera and 30 families in the Bandrefam sacred forest and 45 species divided into 42 genera and 27 families in the Batoufam sacred forest. In the Bandrefam, the most important families are Phyllanthaceae (53.98%), Moraceae (21.69%), Lamiaceae (20.15%). At Batoufam, the most important families are Phyllanthaceae (39.73%), Fabaceae (28.47%), Araliaceae (23.77%). Malacantha alnifolia (55.14%), Vitex grandifolia (18.43%), Bosqueia angolensis (15.06%) were the most important species in Bandrefam. Otherwise, Malacantha alnifolia (28%), Polyscias fulva (22.73%), Psychotria sp. (21.28%) were the most important in Batoufam. The Bandrefam sacred forest has the highest tree density (2669 stems/ha). Total carbon stock is 484.88 ± 2.28 tC/ha at Batoufam and 313.95 ± 0.93 tC/ha at Bandrefam. The economic value varies between 5858.04 ± 27.62 USD/ha in Batoufam sacred forest and 3788.51 ± 11.26 USD/ha in Bandrefam sacred forest. The number of individuals and small-diameter trees has little influence on the carbon stocks in the trees. Medium-diameter trees store the most carbon, and very large-diameter trees, which are very poorly represented, store less carbon. In another way, wood density and the basal areas influence the carbon storage of the trees.展开更多
Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The ma...Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The main objective of our work is to predict the market performance of the Dhaka Stock Exchange (DSE) on day closing price using different Deep Learning techniques. In this study, we have used the LSTM (Long Short-Term Memory) network to forecast the data of DSE for the convenience of shareholders. We have enforced LSTM networks to train data as well as forecast the future time series that has differentiated with test data. We have computed the Root Mean Square Error (RMSE) value to scrutinize the error between the forecasted value and test data that diminished the error by updating the LSTM networks. As a consequence of the renovation of the network, the LSTM network provides tremendous performance which outperformed the existing works to predict stock market prices.展开更多
Collaborative forest management (CFM) is a form of forest governance in which local communities are involved in the management and decision-making processes related to forest resources. It is believed that forests und...Collaborative forest management (CFM) is a form of forest governance in which local communities are involved in the management and decision-making processes related to forest resources. It is believed that forests under such management are better in tree diversity and conservation status and thus hold more carbon stocks. The study assessed the impact of CFM on carbon stocks, tree species diversity & tree species density in Mabira Central Forest Reserve. Data were collected from plots that were systematically laid in the different purposively selected forest areas. The study findings show that there is no difference in stem density and carbon stocks between CFM and non-CFM areas. CFM areas had lower species richness compared to non-CFM areas. CFM areas, however, exhibited more species diversity than non-CFM areas. Climax colonization may favor a few dominant species over others, hence lowering species diversity despite the number of species being many in the understory, hence at the same time increasing species richness. Likewise, disturbance in CFM area may affect natural colonization and favor the emergency of many species either naturally or through assisted regeneration by reforestation, hence increasing diversity, whereas artificial selection of preferred species through harvesting may lower species richness, as observed. Recommendations for improving collaborative forest management (CFM) areas include implementing targeted interventions to enhance carbon sequestration, such as promoting reforestation and afforestation with high-carbon-storing species and strengthening monitoring and evaluation frameworks to assess carbon stock changes over time. Additionally, efforts should focus on enhancing biodiversity conservation by implementing more stringent protection measures and reducing human disturbance while encouraging community participation in biodiversity monitoring and conservation education.展开更多
Tibetan Plateau,as one of the most carbon intensive regions in China,is crucial in the carbon cycle,and accurately estimating its vegetation carbon density(C_(VEG))is essential for assessing regional and national carb...Tibetan Plateau,as one of the most carbon intensive regions in China,is crucial in the carbon cycle,and accurately estimating its vegetation carbon density(C_(VEG))is essential for assessing regional and national carbon balance.However,the spatial distribution of regional C_(VEG)is not available remains highly uncertain due to lack of systematic research,especially for different organs.Here,we investigated the spatial distribution patterns and driving factors of C_(VEG)among different plant organs(leaf,branch,trunk and root)by systematically field grid-sampling 2040 field-plots of plant communities over the Tibetan Plateau from 2019 to 2020.The results showed that the carbon content of plant organs ranged from 255.53 to 515.58 g kg^(-1),with the highest in branches and the lowest in roots.Among the different plant functional groups,the highest C_(VEG)was found in evergreen coniferous forests,and the lowest in desert grasslands,with an average C_(VEG)of 1603.98 g m^(-2).C_(VEG)increased spatially from northwest to southeast over the Tibetan Plateau,with MAP being the dominant factor.Furthermore,the total vegetation carbon stock on the Tibetan Plateau was estimated to be 1965.62 Tg for all vegetation types.Based on the comprehensive field survey dataset,the Random Forest model effectively predicted and mapped the spatial distribution of C_(VEG)(including aboveground,belowground,and the total biomass carbon density)over the Tibetan Plateau with notable accuracy(validation R2 values were 71%,56%,and 64%for C_(AGB),C_(BGB),and C_(VEG),respectively)at a spatial resolution of 1 km×1 km.Our findings can help improve the accuracy of regional carbon stock estimations and provide parameters for carbon cycle model optimization and remote sensing calibration in the future.展开更多
Agroforestry,as a platform for harmonizing agriculture and forestry is a win-win approach for the farming community and environmental sustainability.However,its potential is not well studied and quantified in Northwes...Agroforestry,as a platform for harmonizing agriculture and forestry is a win-win approach for the farming community and environmental sustainability.However,its potential is not well studied and quantified in Northwestern highland.Thus,this study aimed to investigate the woody species diversity,and carbon stock potential of traditional agroforestry practices in Northwestern Highlands(NWH)of Ethiopia.A total of 120 households were selected using stratified sampling for household(HH)surveys,and vegetation inventory was conducted in the winter season of 2023 on systematically laid 400 m2 sample quadrats.Shannon-Weiner diversity index(H’),Simpson’s diversity index(1-D)and Shannon evenness(E)were calculated to estimate woody species diversity.Variation in species diversity and carbon stock within and between agroforestry practices was assessed by 1-way ANOVA and rank differences were separated by post-hoc,Tukey HSD multiple comparison test.The result showed that four different agroforestry practices were identified,consisting of 44 woody species belonging to 23 families.Homegarden was the richest in terms of woody species composition(30),followed by boundary planting(25),while parkland agroforestry had the poorest species composition(12).The total carbon stock of the agroforestry practices in the study ranged from 92.51±29.21 to 143.52±47.83 Mg/ha),with soil organic carbon accounting for about 57.66%,followed by aboveground biomass carbon with 32.1%.Homegardens agroforestry had contributed more to the total carbon stocks than the other agroforestry practices.The total CO_(2)sequestration by above and below ground biomass of woody species in the traditional agroforestry practices of the NWH was estimated to be 519.97 and 104.01 Mg/ha,respectively.The study confirmed that the traditional agroforestry practices of the NWH of Ethiopia maintain a high diversity of woody species and are remarkably important for biodiversity conservation and climate change mitigation.展开更多
This study selected 45 A-share listed companies that have paid dividends for five consecutive years from 2019 to 2024,with an average dividend yield of at least 3%,as the sample.Using a panel data model,the effect of ...This study selected 45 A-share listed companies that have paid dividends for five consecutive years from 2019 to 2024,with an average dividend yield of at least 3%,as the sample.Using a panel data model,the effect of the cash dividend ratio on stock pricing was analyzed.The empirical results indicated a significant positive relationship between the cash dividend ratio and stock price.Furthermore,stocks with high dividend payouts demonstrated greater resilience during macroeconomic downturns,while notable differences were observed across industries.These findings provide a theoretical foundation for investors in making informed decisions and offer practical guidance for listed companies in formulating effective dividend policies.展开更多
Pelagic fish are the most abundant species in upwelling regions,contributing 25%of total global fisheries production.Climate-driven changes in the marine environment play a crucial role in their population dynamics.Us...Pelagic fish are the most abundant species in upwelling regions,contributing 25%of total global fisheries production.Climate-driven changes in the marine environment play a crucial role in their population dynamics.Using Chilean jack mackerel(Trachurus murphyi)as an example,this study conducted simulations to quantify the impacts of environmental variations on the stock assessment.A habitat-based surplus production model was developed by integrating suitable habitat area into the model parameters carrying capacity(K)and intrinsic growth rate(r),with a suitable habitat area serving as the proxy for the environmental conditions for Chilean jack mackerel in the Southeast Pacific Ocean.The dynamics of Chilean jack mackerel stock and fisheries data were simulated,and four assessment models with different configurations were built to fit simulated data,with or without considering environmental effects.The results indicated that Joint K-r model,which integrated both parameters with the suitable habitat area index,outperformed the others by coming closest to the‘true'population dynamics.Ignoring habitat variations in the estimation model tended to overestimate biomass and underestimate harvest rate and reference points.Without observation and process error,the results were estimated with bias,while FMSY is relatively sensitive.This research illustrates the importance to consider random errors and environmental influences on populations,and provides foundation guidelines for future stock assessment.展开更多
Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protectiv...Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.展开更多
The study determined the carbon stocks and litter nutrient concentration in tropical forests along the ecological gradient in Kenya.This could help understand the potential of mitigating climate change using tropical ...The study determined the carbon stocks and litter nutrient concentration in tropical forests along the ecological gradient in Kenya.This could help understand the potential of mitigating climate change using tropical forest ecosystems in different ecological zones,which are being affected by climate change to a level that they are becoming carbon sources instead of sinks.Stratified sampling technique was used to categorize tropical forests into rain,moist deciduous and dry zone forests depending on the average annual rainfall received.Simple random sampling technique was used to select three tropical forests in each category.Modified consistent sampling technique was used to develop 10 main 20 m×100 m plots in each forest,with 202 m×50 m sub-plots in each plot.Systematic random sampling technique was used in selecting 10 sub-plots from each main plot for inventory study.Non-destructive approach based on allometric equations using trees’diameter at breast height(DBH),total height and species’wood specific gravity were used in estimating tree carbon stock in each forest.Soil organic carbon(SOC)and litter nutrient concentration(total phosphorus and nitrogen)were determined in each forest based on standard laboratory procedures.The results indicated that,whilst trees in rain forests recorded a significantly higher(p<0.001)DBH(20.36 cm)and total tree height(12.1 m),trees in dry zone forests recorded a significantly higher(p<0.001)specific gravity(0.67 kg m^(−3)).Dry zone tropical forests stored a significantly lower amount of total tree carbon of 73 Mg ha^(−1),compared to tropical rain forests(439.5 Mg ha^(−1))and moist deciduous tropical forests(449 Mg ha^(−1)).The SOC content was significantly higher in tropical rainforests(3.9%),compared to soils from moist deciduous(2.9%)and dry zone forests(1.8%).While litter from tropical rain forests recorded a significantly higher amount of total nitrogen(3.4%),litter from dry zone forests recorded a significantly higher concentration of total phosphorus(0.27%).In conclusion,ecological gradient that is dictated by the prevailing temperatures and precipitation affects the tropical forests carbon stock potential and litter nutrient concentration.This implies that,the changing climate is having a serious implication on the ecosystem services such as carbon stock and nutrients cycling in tropical forests.展开更多
The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of...The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of abnormal stock price movements.Traditional sentiment measurement methods suffer from limitations such as lag,high misjudgment rates,and the inability to distinguish confounding factors.To more accurately explore the dynamic correlation between investor sentiment and stock price fluctuations,this paper proposes a sentiment analysis framework based on large language models(LLMs).By constructing continuous sentiment scoring factors and integrating them with a long short-term memory(LSTM)deep learning model,we analyze the correlation between investor sentiment and stock price fluctuations.Empirical results indicate that sentiment factors based on large language models can generate an annualized excess return of 9.3%in the CSI 500 index domain.The LSTM stock price prediction model incorporating sentiment features achieves a mean absolute percentage error(MAPE)as low as 2.72%,significantly outperforming traditional models.Through this analysis,we aim to provide quantitative references for optimizing investment decisions and preventing market risks.展开更多
Understanding livestock performance in typical steppe ecosystems is essential for optimizing grassland-livestock interactions and minimizing environmental impact.To assess the effects of different stocking rates on th...Understanding livestock performance in typical steppe ecosystems is essential for optimizing grassland-livestock interactions and minimizing environmental impact.To assess the effects of different stocking rates on the growth performance,energy and nitrogen utilization,methane(CH_(4))emissions,and grazing behavior of Tan sheep,a 2-year grazing experiment in the typical steppe was conducted.The grazing area was divided into 9 paddocks,each 0.5 ha,with 3 spatial replicates for each stocking rate treatment(4,8,and 13 sheep per paddock),corresponding to 2.7,5.3,and 8.7 sheep ha^(–1).The results showed that the neutral detergent fiber(NDF)and acid detergent fiber(ADF)contents of herbage varied between grazing years(P<0.05),with a positive correlation between stocking rate and crude fiber content in the herbage(P<0.05).Dry matter intake(DMI)decreased with increasing stocking rate(P<0.05),and the average daily gain(ADG)was highest at 2.7 sheep ha^(–1)(P<0.05).Compared to 2.7 and 8.7 sheep ha^(–1),the5.3 sheep ha^(–1)treatment exhibited the lowest nutrient digestibility for dry matter,nitrogen,and ether extract(P<0.05).Fecal nitrogen was lowest at 8.7 sheep ha^(–1)(P<0.05),while retained nitrogen as a proportion of nitrogen intake was highest.Digestive energy(DE),metabolic energy(ME),and the ratios of DE to gross energy(GE)and ME to GE were highest at 8.7 sheep ha^(–1)(P<0.05).In contrast,CH_4 emissions,CH_4 per DMI,and CH_(4)E as a proportion of GE were highest at 2.7 sheep ha^(–1)(P<0.05).Stocking rate and grazing year did not significantly affect rumen fermentation parameters,including volatile fatty acids,acetate,propionate,and the acetate/propionate ratio.At 8.7sheep ha^(–1),daily grazing time and inter-individual distance increased,while time allocated to grazing,walking,and ruminating/resting decreased as stocking rates increased(P<0.05).This study highlights the importance of adjusting stocking rates based on the nutritional value of forage and grazing year to optimize grazing management.展开更多
Although the application of straw decomposing microorganism inoculants(SDMI)can accelerate straw decomposition,the underlying mechanisms affecting soil organic carbon(SOC)under different scenarios remain unclear.We co...Although the application of straw decomposing microorganism inoculants(SDMI)can accelerate straw decomposition,the underlying mechanisms affecting soil organic carbon(SOC)under different scenarios remain unclear.We conducted a meta-analysis using 226 observations from 86 studies on SOC changes under straw return with or without SDMI applications.Overall,our results indicated that straw with SDMI application increased the SOC stock by 1.51%at an initial carbon-to-nitrogen ratio(ICNR)>25(P<0.05),while the effect of ICNR≤25was insignificant.In particular,at ICNR>25,application of SDMI-treated straw increased SOC stocks in northern temperate continental areas(NTC)higher than in subtropical monsoon regions(STM).Furthermore,the straw with SDMI application increased higher SOC stocks in soils with pH>7.5 than those with pH≤7.5.In terms of agricultural management practices,SOC stocks were significantly higher in straw buried(SB),the experimental duration of straw return(EDSR)≥1 year,the straw return amount(SRA)>6,000 kg ha^(–1),and the SDMI application rate(SDMIR)>30 kg ha^(–1)conditions.The effect of straw with SDMI on SOC stocks under straw burying(SB)was significantly higher than that under straw mulching(SM)at ICNR≤25.At ICNR>25,EDSR,SDMIR,and the mean annual precipitation(MAP)were the main drivers of the effect of SDMI addition to straw on SOC stocks.Straw with SDMI induced SOC stock increases which increased with EDSR and decreased with increasing MAP.These findings provide a scientific basis for decision-makers and stakeholders to improve soil C management via the application of SDMI-amended straw at both regional and large scales.展开更多
Based on the financial data and stock price information of Bengang Steel Plates Co.Ltd.from 2004 to 2023,this paper uses SPSS 26 software,combined with DuPont Analysis and Wall Score Method,to explore the correlation ...Based on the financial data and stock price information of Bengang Steel Plates Co.Ltd.from 2004 to 2023,this paper uses SPSS 26 software,combined with DuPont Analysis and Wall Score Method,to explore the correlation between stock price and nine key financial indicators selected from three dimensions:profitability,development capability,and operating capability,including fixed asset growth rate,price-to-book ratio(P/B ratio),and gross profit margin.Through correlation analysis,multiple regression analysis,and curve fitting,the study finds that:fixed asset growth rate,P/B ratio,and gross profit margin show a significant positive correlation with stock price;return on equity(ROE),operating income,and accounts receivable turnover days show a significant negative correlation with stock price;earnings per share(EPS)and net profit growth rate do not show a significant correlation with stock price.The research results indicate that the stock price of Bengang Steel Plates Co.Ltd.is greatly affected by its asset scale and market valuation,while some profitability indicators have not been effectively transmitted to the stock price.Finally,countermeasures and suggestions are put forward from the aspects of cost control,technological innovation,market expansion,and financial structure optimization,so as to provide references for corporate operation and investment decisions.展开更多
Urban areas face environmental pollution and greenhouse emissions challenges,demand collaborative efforts to mitigation.Urban forests play a crucial role in absorbing CO_(2) emissions and contributing to carbon seques...Urban areas face environmental pollution and greenhouse emissions challenges,demand collaborative efforts to mitigation.Urban forests play a crucial role in absorbing CO_(2) emissions and contributing to carbon sequestration potential,but they also release biogenic volatile organic compounds(BVOCs),which contribute to the formation of tropospheric ozone and secondary organic aerosols(SOA).This study aimed to understand the role of urban forests in carbon stock and BVOCs emission by establishing optimal biomass models for six typical tree species(Robinia pseudoacacia,Quercus,Populus,Pinus tabulaeformis,Betula platyphylla,and Larix gmelinii)in Beijing.Biomass models were developed using field surveys and remote sensing data,with R^(2) values ranging from 0.364 to 0.921.Applying these models to forest resource inventory data,carbon stock and BVOCs emission models were constructed.In 2021,the total carbon stock for these pure forest tree species was estimated at 5.638 million tons,with a carbon density of 58.86 t/ha.The carbon density ranking for pure forest tree species was:Robinia pseudoacacia>Populus tomentosa>Betula platyphylla>Quercus Linn>Pinus tabulaeformis>Larix gmelinii.Total BVOCs emission in 2021 from the studied species were calculated at 25,789.72 t,with an average emission of 0.27 t/ha.Populus tomentosa had the highest BVOCs emission per unit area,followed by Robinia pseudoacacia,and Larix gmelinii had the smallest.Betula platyphylla and Robinia pseudoacacia were identified as species with high carbon stock and low BVOCs emissions in Beijing,offering insights for future urban forest planning and eco-friendly urban environment development strategies.展开更多
This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Acc...This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Accounting Research Database(CSMAR)for empirical analysis.By examining the impact of CSR performance on stock price crash risk,this study identifies key relationships and further investigates the moderating role of media promotion and communication as an intermediary to explore the transmission mechanisms and influence between the two.The empirical results indicate that CSR performance is significantly negatively correlated with stock price crash risk,suggesting that strong CSR performance can effectively reduce the likelihood of a stock price crash.Furthermore,additional analysis reveals that media plays a moderating role in the relationship between CSR performance and stock price crash risk.This study aims to contribute to the understanding of the formation mechanisms and analytical paradigms of factors influencing stock price crash risk while providing theoretical support and reference value for risk prevention strategies.展开更多
Polynyas and their adjacent seasonal ice zones(SIZs)represent the most productive regions in the Southern Ocean,supporting unique food webs that are highly sensitive to climate change.Understanding the dynamics of phy...Polynyas and their adjacent seasonal ice zones(SIZs)represent the most productive regions in the Southern Ocean,supporting unique food webs that are highly sensitive to climate change.Understanding the dynamics of phytoplankton and the carbon pool in these areas is crucial for assessing the role of the Southern Ocean in global carbon cycling.During the late stage of an algal bloom,seawater samples at 14 stations were collected in the Amundsen Sea Polynya(ASP)and adjacent SIZ.Using nutrients,phytoplankton pigments,organic carbon(OC),remote sensing data,and physicochemical measurements,as well as CHEMTAX model simulations,we investigated the response of the phytoplankton crops,taxonomic composition,and OC pool to environmental factors.Our analyses revealed that hydrodynamic regimes of the polynya,adjacent SIZs and open sea were regulated by the regionally varying intrusion of Circumpolar Deep Water,photosynthetically active radiation and sea ice melt water.The ASP exhibited the highest seasonal nutrient utilization rates[ΔN=(1059±386)mmol/m^(2),ΔP=(50±17)mmol/m^(2) andΔSi=(956±904)mmol/m^(2)],while the open sea had lower rates.The integrated chlorophyll a(Chl a)concentration at depths of 0–200 m ranged from 20.4 mg/m^(2) to 1420.0 mg/m^(2) and peaked in the polynya.In the study area,Haptophytes Phaeocystis antarctica was the dominant functional group(34%±27%),and diatoms acted as a secondary contributor(23%±14%).The major functional group and particulate OC(POC)contributor varied from diatoms(36%±12%)in the open sea to haptophytes(48%±31%)in the polynya waters.Strong light conditions and microelement limitations promoted the dominance of P.antarctica(low Fe forms)dominance in the ASP.The strong correlations between the POC and Chl a depth-integrated concentration suggest that the POC was primarily derived from phytoplankton,while dissolved OC(DOC)was influenced by consumer activity and water mass transport.In addition,the transport of OC in the upper 200 m of the water column within the ASP was quantified,revealing the predominantly westward fluxes for both DOC[9.0 mg/(m^(2)·s)]and POC[7.2 mg/(m^(2)·s)].The latitudinal transport exhibited the northward transport of DOC[8.1 mg/(m^(2)·s)]and southward transport of POC[4.3 mg/(m^(2)·s)]movement.These findings have significant implications for enhancing our understanding of how hydrodynamics influence OC cycling in polynya regions.展开更多
Driven by the accelerating global aging population and increasing health consciousness, compression stocking market is experiencing rapid growth. According to the latest data from Grand View Research, the global compr...Driven by the accelerating global aging population and increasing health consciousness, compression stocking market is experiencing rapid growth. According to the latest data from Grand View Research, the global compression therapy market reached $4.25 billion in 2024, with medical compression stockings, as a core segment, boasting a compound annual growth rate(CAGR) of nearly 6%.展开更多
基金supported by National Key Research and Development Program of China(No.2021YFD2200405(S.R.L.))Natural Science Foundation of China(Grant No.31971653).
文摘With the rapid economic development and continuous expansion of human activities,forest degradation—characterized by reduced forest stock within the forest including declining carbon storage—poses significant threats to ecosystem stability.Understanding the current status of forest degradation and assessing potential carbon stocks in China are of strategic importance for making forest restoration efforts and enhancing carbon sequestration capacity.In this study,we used the national forest inventory data from 2009 to 2018 to develop a set of standard measures for assessing degraded forests across China,based on five key indicators:forest accumulation growth rate(FAGR),forest recruitment rate(FRR),tree species reduction rate(TSRR),forest canopy cover reduction rate(FCCRR),and forest disaster level(FDL).Additionally,we estimated standing carbon stock,potential carbon stock,and theoretical space to grow by developing a stand growth model,which accounts for stand density across different site classes,to evaluate the restoration potential of degraded forests.The results indicate that degraded forest area in China is 36.15 million hectares,accounting for 20.10% of a total forest area.Standing carbon stock and potential carbon stock of degraded forests in China are 23.93 million tons and 61.90 million tons,respectively.Overall,degraded forest varies significantly across different regions.The results highlight the important trade-offs among environmental factors,policy decisions,and forest conditions,providing a robust foundation for developing measures to enhance forest quality.
基金Supported by the National Key Research and Development Program of China(No.2022 YFF 0608203)the Graduate Student Scientific Research Innovation Projects in Jiangsu Province(No.KYCX 22-0706)。
文摘Hatchery release is a common and effective practice for protecting and restoring wild resources,and the success of the practice is commonly assessed using mark-recapture technology.We investigated the use of different dimensional X-ray imaging techniques for the strontium(Sr)marking of fish fin rays for stocking.Megalobrama amblycephala juveniles were marked by culturing specimens in 800-mg/L SrCl_(2)·6 H_(2)O solution,the cross-sections of dorsal fin rays were subsequently obtained,and the concentrations Sr was analyzed by 2 D imaging using an electron probe X-ray microanalyzer.Our preliminary findings indicate that the immersion marking method is effective for the Sr marking of fin rays in experimental fish.Moreover,we generated a bird’s-eye-view 3 D mesh image of the Sr concentrations,which can provide a more comprehensive information for fish stocking than that using normal 2 D imaging.
基金funded by the project supported by the Natural Science Foundation of Heilongjiang Provincial(Grant Number LH2023F033)the Science and Technology Innovation Talent Project of Harbin(Grant Number 2022CXRCCG006).
文摘Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and complexity.This paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price prediction.Firstly,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock price.The discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock prices.Secondly,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation study.The results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.
文摘Sacred forests play a valuable role in the conservation of local biodiversity and provide numerous ecosystem services in Cameroon. The aim of this study was to estimate floristic diversity, stand structures and carbon stocks in the sacred forests of Bandrefam and Batoufam (western Cameroon). The floristic inventory and the stand structures were carried out in 25 m × 25 m plots for individuals with diameters greater than 10 cm;5 m × 5 m for individuals with diameters less than 10 cm. Carbon stocks were estimated using the non-destructive method and allometric equations. The floristic inventory identified 65 species divided into 57 genera and 30 families in the Bandrefam sacred forest and 45 species divided into 42 genera and 27 families in the Batoufam sacred forest. In the Bandrefam, the most important families are Phyllanthaceae (53.98%), Moraceae (21.69%), Lamiaceae (20.15%). At Batoufam, the most important families are Phyllanthaceae (39.73%), Fabaceae (28.47%), Araliaceae (23.77%). Malacantha alnifolia (55.14%), Vitex grandifolia (18.43%), Bosqueia angolensis (15.06%) were the most important species in Bandrefam. Otherwise, Malacantha alnifolia (28%), Polyscias fulva (22.73%), Psychotria sp. (21.28%) were the most important in Batoufam. The Bandrefam sacred forest has the highest tree density (2669 stems/ha). Total carbon stock is 484.88 ± 2.28 tC/ha at Batoufam and 313.95 ± 0.93 tC/ha at Bandrefam. The economic value varies between 5858.04 ± 27.62 USD/ha in Batoufam sacred forest and 3788.51 ± 11.26 USD/ha in Bandrefam sacred forest. The number of individuals and small-diameter trees has little influence on the carbon stocks in the trees. Medium-diameter trees store the most carbon, and very large-diameter trees, which are very poorly represented, store less carbon. In another way, wood density and the basal areas influence the carbon storage of the trees.
文摘Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The main objective of our work is to predict the market performance of the Dhaka Stock Exchange (DSE) on day closing price using different Deep Learning techniques. In this study, we have used the LSTM (Long Short-Term Memory) network to forecast the data of DSE for the convenience of shareholders. We have enforced LSTM networks to train data as well as forecast the future time series that has differentiated with test data. We have computed the Root Mean Square Error (RMSE) value to scrutinize the error between the forecasted value and test data that diminished the error by updating the LSTM networks. As a consequence of the renovation of the network, the LSTM network provides tremendous performance which outperformed the existing works to predict stock market prices.
文摘Collaborative forest management (CFM) is a form of forest governance in which local communities are involved in the management and decision-making processes related to forest resources. It is believed that forests under such management are better in tree diversity and conservation status and thus hold more carbon stocks. The study assessed the impact of CFM on carbon stocks, tree species diversity & tree species density in Mabira Central Forest Reserve. Data were collected from plots that were systematically laid in the different purposively selected forest areas. The study findings show that there is no difference in stem density and carbon stocks between CFM and non-CFM areas. CFM areas had lower species richness compared to non-CFM areas. CFM areas, however, exhibited more species diversity than non-CFM areas. Climax colonization may favor a few dominant species over others, hence lowering species diversity despite the number of species being many in the understory, hence at the same time increasing species richness. Likewise, disturbance in CFM area may affect natural colonization and favor the emergency of many species either naturally or through assisted regeneration by reforestation, hence increasing diversity, whereas artificial selection of preferred species through harvesting may lower species richness, as observed. Recommendations for improving collaborative forest management (CFM) areas include implementing targeted interventions to enhance carbon sequestration, such as promoting reforestation and afforestation with high-carbon-storing species and strengthening monitoring and evaluation frameworks to assess carbon stock changes over time. Additionally, efforts should focus on enhancing biodiversity conservation by implementing more stringent protection measures and reducing human disturbance while encouraging community participation in biodiversity monitoring and conservation education.
基金supported by CAS Project for Young Scientists in Basic Research(YSBR-037)the National Natural Science Foundation of China(42141004,32430067)by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP,2019QZKK060602).
文摘Tibetan Plateau,as one of the most carbon intensive regions in China,is crucial in the carbon cycle,and accurately estimating its vegetation carbon density(C_(VEG))is essential for assessing regional and national carbon balance.However,the spatial distribution of regional C_(VEG)is not available remains highly uncertain due to lack of systematic research,especially for different organs.Here,we investigated the spatial distribution patterns and driving factors of C_(VEG)among different plant organs(leaf,branch,trunk and root)by systematically field grid-sampling 2040 field-plots of plant communities over the Tibetan Plateau from 2019 to 2020.The results showed that the carbon content of plant organs ranged from 255.53 to 515.58 g kg^(-1),with the highest in branches and the lowest in roots.Among the different plant functional groups,the highest C_(VEG)was found in evergreen coniferous forests,and the lowest in desert grasslands,with an average C_(VEG)of 1603.98 g m^(-2).C_(VEG)increased spatially from northwest to southeast over the Tibetan Plateau,with MAP being the dominant factor.Furthermore,the total vegetation carbon stock on the Tibetan Plateau was estimated to be 1965.62 Tg for all vegetation types.Based on the comprehensive field survey dataset,the Random Forest model effectively predicted and mapped the spatial distribution of C_(VEG)(including aboveground,belowground,and the total biomass carbon density)over the Tibetan Plateau with notable accuracy(validation R2 values were 71%,56%,and 64%for C_(AGB),C_(BGB),and C_(VEG),respectively)at a spatial resolution of 1 km×1 km.Our findings can help improve the accuracy of regional carbon stock estimations and provide parameters for carbon cycle model optimization and remote sensing calibration in the future.
基金financed by Debre Markose University Burie Campus.
文摘Agroforestry,as a platform for harmonizing agriculture and forestry is a win-win approach for the farming community and environmental sustainability.However,its potential is not well studied and quantified in Northwestern highland.Thus,this study aimed to investigate the woody species diversity,and carbon stock potential of traditional agroforestry practices in Northwestern Highlands(NWH)of Ethiopia.A total of 120 households were selected using stratified sampling for household(HH)surveys,and vegetation inventory was conducted in the winter season of 2023 on systematically laid 400 m2 sample quadrats.Shannon-Weiner diversity index(H’),Simpson’s diversity index(1-D)and Shannon evenness(E)were calculated to estimate woody species diversity.Variation in species diversity and carbon stock within and between agroforestry practices was assessed by 1-way ANOVA and rank differences were separated by post-hoc,Tukey HSD multiple comparison test.The result showed that four different agroforestry practices were identified,consisting of 44 woody species belonging to 23 families.Homegarden was the richest in terms of woody species composition(30),followed by boundary planting(25),while parkland agroforestry had the poorest species composition(12).The total carbon stock of the agroforestry practices in the study ranged from 92.51±29.21 to 143.52±47.83 Mg/ha),with soil organic carbon accounting for about 57.66%,followed by aboveground biomass carbon with 32.1%.Homegardens agroforestry had contributed more to the total carbon stocks than the other agroforestry practices.The total CO_(2)sequestration by above and below ground biomass of woody species in the traditional agroforestry practices of the NWH was estimated to be 519.97 and 104.01 Mg/ha,respectively.The study confirmed that the traditional agroforestry practices of the NWH of Ethiopia maintain a high diversity of woody species and are remarkably important for biodiversity conservation and climate change mitigation.
文摘This study selected 45 A-share listed companies that have paid dividends for five consecutive years from 2019 to 2024,with an average dividend yield of at least 3%,as the sample.Using a panel data model,the effect of the cash dividend ratio on stock pricing was analyzed.The empirical results indicated a significant positive relationship between the cash dividend ratio and stock price.Furthermore,stocks with high dividend payouts demonstrated greater resilience during macroeconomic downturns,while notable differences were observed across industries.These findings provide a theoretical foundation for investors in making informed decisions and offer practical guidance for listed companies in formulating effective dividend policies.
基金supported by the National Key Research and Development Program of China(No.2019YFD0901404)。
文摘Pelagic fish are the most abundant species in upwelling regions,contributing 25%of total global fisheries production.Climate-driven changes in the marine environment play a crucial role in their population dynamics.Using Chilean jack mackerel(Trachurus murphyi)as an example,this study conducted simulations to quantify the impacts of environmental variations on the stock assessment.A habitat-based surplus production model was developed by integrating suitable habitat area into the model parameters carrying capacity(K)and intrinsic growth rate(r),with a suitable habitat area serving as the proxy for the environmental conditions for Chilean jack mackerel in the Southeast Pacific Ocean.The dynamics of Chilean jack mackerel stock and fisheries data were simulated,and four assessment models with different configurations were built to fit simulated data,with or without considering environmental effects.The results indicated that Joint K-r model,which integrated both parameters with the suitable habitat area index,outperformed the others by coming closest to the‘true'population dynamics.Ignoring habitat variations in the estimation model tended to overestimate biomass and underestimate harvest rate and reference points.Without observation and process error,the results were estimated with bias,while FMSY is relatively sensitive.This research illustrates the importance to consider random errors and environmental influences on populations,and provides foundation guidelines for future stock assessment.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1300203)the National Natural Science Foundation of China(Grant No.42371329s).
文摘Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.
基金funded by the Kenya National Research Fund(NRF-Kenya,2018).
文摘The study determined the carbon stocks and litter nutrient concentration in tropical forests along the ecological gradient in Kenya.This could help understand the potential of mitigating climate change using tropical forest ecosystems in different ecological zones,which are being affected by climate change to a level that they are becoming carbon sources instead of sinks.Stratified sampling technique was used to categorize tropical forests into rain,moist deciduous and dry zone forests depending on the average annual rainfall received.Simple random sampling technique was used to select three tropical forests in each category.Modified consistent sampling technique was used to develop 10 main 20 m×100 m plots in each forest,with 202 m×50 m sub-plots in each plot.Systematic random sampling technique was used in selecting 10 sub-plots from each main plot for inventory study.Non-destructive approach based on allometric equations using trees’diameter at breast height(DBH),total height and species’wood specific gravity were used in estimating tree carbon stock in each forest.Soil organic carbon(SOC)and litter nutrient concentration(total phosphorus and nitrogen)were determined in each forest based on standard laboratory procedures.The results indicated that,whilst trees in rain forests recorded a significantly higher(p<0.001)DBH(20.36 cm)and total tree height(12.1 m),trees in dry zone forests recorded a significantly higher(p<0.001)specific gravity(0.67 kg m^(−3)).Dry zone tropical forests stored a significantly lower amount of total tree carbon of 73 Mg ha^(−1),compared to tropical rain forests(439.5 Mg ha^(−1))and moist deciduous tropical forests(449 Mg ha^(−1)).The SOC content was significantly higher in tropical rainforests(3.9%),compared to soils from moist deciduous(2.9%)and dry zone forests(1.8%).While litter from tropical rain forests recorded a significantly higher amount of total nitrogen(3.4%),litter from dry zone forests recorded a significantly higher concentration of total phosphorus(0.27%).In conclusion,ecological gradient that is dictated by the prevailing temperatures and precipitation affects the tropical forests carbon stock potential and litter nutrient concentration.This implies that,the changing climate is having a serious implication on the ecosystem services such as carbon stock and nutrients cycling in tropical forests.
文摘The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of abnormal stock price movements.Traditional sentiment measurement methods suffer from limitations such as lag,high misjudgment rates,and the inability to distinguish confounding factors.To more accurately explore the dynamic correlation between investor sentiment and stock price fluctuations,this paper proposes a sentiment analysis framework based on large language models(LLMs).By constructing continuous sentiment scoring factors and integrating them with a long short-term memory(LSTM)deep learning model,we analyze the correlation between investor sentiment and stock price fluctuations.Empirical results indicate that sentiment factors based on large language models can generate an annualized excess return of 9.3%in the CSI 500 index domain.The LSTM stock price prediction model incorporating sentiment features achieves a mean absolute percentage error(MAPE)as low as 2.72%,significantly outperforming traditional models.Through this analysis,we aim to provide quantitative references for optimizing investment decisions and preventing market risks.
基金supported by the National Natural Science Foundation of China(32161143028)the Key Technology of Grassland Ecological Civilization Demonstration Area in Ningxia Hui Autonomous Region,China(20210239)the Northwest Shelterbelt Construction Bureau of the National Forestry and Grassland Administration,China。
文摘Understanding livestock performance in typical steppe ecosystems is essential for optimizing grassland-livestock interactions and minimizing environmental impact.To assess the effects of different stocking rates on the growth performance,energy and nitrogen utilization,methane(CH_(4))emissions,and grazing behavior of Tan sheep,a 2-year grazing experiment in the typical steppe was conducted.The grazing area was divided into 9 paddocks,each 0.5 ha,with 3 spatial replicates for each stocking rate treatment(4,8,and 13 sheep per paddock),corresponding to 2.7,5.3,and 8.7 sheep ha^(–1).The results showed that the neutral detergent fiber(NDF)and acid detergent fiber(ADF)contents of herbage varied between grazing years(P<0.05),with a positive correlation between stocking rate and crude fiber content in the herbage(P<0.05).Dry matter intake(DMI)decreased with increasing stocking rate(P<0.05),and the average daily gain(ADG)was highest at 2.7 sheep ha^(–1)(P<0.05).Compared to 2.7 and 8.7 sheep ha^(–1),the5.3 sheep ha^(–1)treatment exhibited the lowest nutrient digestibility for dry matter,nitrogen,and ether extract(P<0.05).Fecal nitrogen was lowest at 8.7 sheep ha^(–1)(P<0.05),while retained nitrogen as a proportion of nitrogen intake was highest.Digestive energy(DE),metabolic energy(ME),and the ratios of DE to gross energy(GE)and ME to GE were highest at 8.7 sheep ha^(–1)(P<0.05).In contrast,CH_4 emissions,CH_4 per DMI,and CH_(4)E as a proportion of GE were highest at 2.7 sheep ha^(–1)(P<0.05).Stocking rate and grazing year did not significantly affect rumen fermentation parameters,including volatile fatty acids,acetate,propionate,and the acetate/propionate ratio.At 8.7sheep ha^(–1),daily grazing time and inter-individual distance increased,while time allocated to grazing,walking,and ruminating/resting decreased as stocking rates increased(P<0.05).This study highlights the importance of adjusting stocking rates based on the nutritional value of forage and grazing year to optimize grazing management.
基金supported by the Key Science and Technology Project of Anhui Province,China(2023n06020056)the National Natural Science Foundation of China(32071628)the Colleges and Universities Science Foundation of Anhui Province,China(2024AH020002)。
文摘Although the application of straw decomposing microorganism inoculants(SDMI)can accelerate straw decomposition,the underlying mechanisms affecting soil organic carbon(SOC)under different scenarios remain unclear.We conducted a meta-analysis using 226 observations from 86 studies on SOC changes under straw return with or without SDMI applications.Overall,our results indicated that straw with SDMI application increased the SOC stock by 1.51%at an initial carbon-to-nitrogen ratio(ICNR)>25(P<0.05),while the effect of ICNR≤25was insignificant.In particular,at ICNR>25,application of SDMI-treated straw increased SOC stocks in northern temperate continental areas(NTC)higher than in subtropical monsoon regions(STM).Furthermore,the straw with SDMI application increased higher SOC stocks in soils with pH>7.5 than those with pH≤7.5.In terms of agricultural management practices,SOC stocks were significantly higher in straw buried(SB),the experimental duration of straw return(EDSR)≥1 year,the straw return amount(SRA)>6,000 kg ha^(–1),and the SDMI application rate(SDMIR)>30 kg ha^(–1)conditions.The effect of straw with SDMI on SOC stocks under straw burying(SB)was significantly higher than that under straw mulching(SM)at ICNR≤25.At ICNR>25,EDSR,SDMIR,and the mean annual precipitation(MAP)were the main drivers of the effect of SDMI addition to straw on SOC stocks.Straw with SDMI induced SOC stock increases which increased with EDSR and decreased with increasing MAP.These findings provide a scientific basis for decision-makers and stakeholders to improve soil C management via the application of SDMI-amended straw at both regional and large scales.
基金Innovation Team Project of Liaoning Institute of Science and Technology:“Smart Economy Practice and Innovation Team”College Students’Innovation and Entrepreneurship Training Program Projects:“Research on the Application of Big Data Analysis Tools”and“Zhice Quantitative Investment Studio”+2 种基金Teaching and Research Project:“Research on the Path of AI-Enabled Undergraduate Education and Teaching Reform Based on the Needs of Liaoning’s Revitalization and Development(Project No.:LKJY202510)”Teaching Reform Project:“Research and Practice on the Evaluation of Digital Talents in Application-Oriented Universities(Project No.:LNKJ202412)”Project of Liaoning Federation of Social Sciences:“Research on the Key Elements and Practical Paths of Educational Digital Transformation(Project No.:2025lslybkt-050)”。
文摘Based on the financial data and stock price information of Bengang Steel Plates Co.Ltd.from 2004 to 2023,this paper uses SPSS 26 software,combined with DuPont Analysis and Wall Score Method,to explore the correlation between stock price and nine key financial indicators selected from three dimensions:profitability,development capability,and operating capability,including fixed asset growth rate,price-to-book ratio(P/B ratio),and gross profit margin.Through correlation analysis,multiple regression analysis,and curve fitting,the study finds that:fixed asset growth rate,P/B ratio,and gross profit margin show a significant positive correlation with stock price;return on equity(ROE),operating income,and accounts receivable turnover days show a significant negative correlation with stock price;earnings per share(EPS)and net profit growth rate do not show a significant correlation with stock price.The research results indicate that the stock price of Bengang Steel Plates Co.Ltd.is greatly affected by its asset scale and market valuation,while some profitability indicators have not been effectively transmitted to the stock price.Finally,countermeasures and suggestions are put forward from the aspects of cost control,technological innovation,market expansion,and financial structure optimization,so as to provide references for corporate operation and investment decisions.
基金supported by the National Natural Science Foundation of China(No.42077454)the Xiong'an New Area Science and Technology Innovation Project(No.2022XACX1000)the 5·5 Engineering Research&Innovation Team Project of Beijing Forestry University(No.BLRC2023B04).
文摘Urban areas face environmental pollution and greenhouse emissions challenges,demand collaborative efforts to mitigation.Urban forests play a crucial role in absorbing CO_(2) emissions and contributing to carbon sequestration potential,but they also release biogenic volatile organic compounds(BVOCs),which contribute to the formation of tropospheric ozone and secondary organic aerosols(SOA).This study aimed to understand the role of urban forests in carbon stock and BVOCs emission by establishing optimal biomass models for six typical tree species(Robinia pseudoacacia,Quercus,Populus,Pinus tabulaeformis,Betula platyphylla,and Larix gmelinii)in Beijing.Biomass models were developed using field surveys and remote sensing data,with R^(2) values ranging from 0.364 to 0.921.Applying these models to forest resource inventory data,carbon stock and BVOCs emission models were constructed.In 2021,the total carbon stock for these pure forest tree species was estimated at 5.638 million tons,with a carbon density of 58.86 t/ha.The carbon density ranking for pure forest tree species was:Robinia pseudoacacia>Populus tomentosa>Betula platyphylla>Quercus Linn>Pinus tabulaeformis>Larix gmelinii.Total BVOCs emission in 2021 from the studied species were calculated at 25,789.72 t,with an average emission of 0.27 t/ha.Populus tomentosa had the highest BVOCs emission per unit area,followed by Robinia pseudoacacia,and Larix gmelinii had the smallest.Betula platyphylla and Robinia pseudoacacia were identified as species with high carbon stock and low BVOCs emissions in Beijing,offering insights for future urban forest planning and eco-friendly urban environment development strategies.
基金R&D Program of Beijing Municipal Education Commission(Grant No.SM202210005007)。
文摘This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Accounting Research Database(CSMAR)for empirical analysis.By examining the impact of CSR performance on stock price crash risk,this study identifies key relationships and further investigates the moderating role of media promotion and communication as an intermediary to explore the transmission mechanisms and influence between the two.The empirical results indicate that CSR performance is significantly negatively correlated with stock price crash risk,suggesting that strong CSR performance can effectively reduce the likelihood of a stock price crash.Furthermore,additional analysis reveals that media plays a moderating role in the relationship between CSR performance and stock price crash risk.This study aims to contribute to the understanding of the formation mechanisms and analytical paradigms of factors influencing stock price crash risk while providing theoretical support and reference value for risk prevention strategies.
基金The National Polar Special Program under contract Nos IRASCC 01-01-02 and IRASCC 02-02the National Natural Science Foundation of China under contract Nos 41976228,42276255,41976227,42176227,and 42076243+1 种基金the International Cooperation Key Project of the Ministry of Science and Technology under contract No.2022YFE0136500the Scientific Research Fund of the Second Institute of Oceanography,Ministry of Natural Resources,under contract Nos JG2011,JG2211,JG2013,and JG1805.
文摘Polynyas and their adjacent seasonal ice zones(SIZs)represent the most productive regions in the Southern Ocean,supporting unique food webs that are highly sensitive to climate change.Understanding the dynamics of phytoplankton and the carbon pool in these areas is crucial for assessing the role of the Southern Ocean in global carbon cycling.During the late stage of an algal bloom,seawater samples at 14 stations were collected in the Amundsen Sea Polynya(ASP)and adjacent SIZ.Using nutrients,phytoplankton pigments,organic carbon(OC),remote sensing data,and physicochemical measurements,as well as CHEMTAX model simulations,we investigated the response of the phytoplankton crops,taxonomic composition,and OC pool to environmental factors.Our analyses revealed that hydrodynamic regimes of the polynya,adjacent SIZs and open sea were regulated by the regionally varying intrusion of Circumpolar Deep Water,photosynthetically active radiation and sea ice melt water.The ASP exhibited the highest seasonal nutrient utilization rates[ΔN=(1059±386)mmol/m^(2),ΔP=(50±17)mmol/m^(2) andΔSi=(956±904)mmol/m^(2)],while the open sea had lower rates.The integrated chlorophyll a(Chl a)concentration at depths of 0–200 m ranged from 20.4 mg/m^(2) to 1420.0 mg/m^(2) and peaked in the polynya.In the study area,Haptophytes Phaeocystis antarctica was the dominant functional group(34%±27%),and diatoms acted as a secondary contributor(23%±14%).The major functional group and particulate OC(POC)contributor varied from diatoms(36%±12%)in the open sea to haptophytes(48%±31%)in the polynya waters.Strong light conditions and microelement limitations promoted the dominance of P.antarctica(low Fe forms)dominance in the ASP.The strong correlations between the POC and Chl a depth-integrated concentration suggest that the POC was primarily derived from phytoplankton,while dissolved OC(DOC)was influenced by consumer activity and water mass transport.In addition,the transport of OC in the upper 200 m of the water column within the ASP was quantified,revealing the predominantly westward fluxes for both DOC[9.0 mg/(m^(2)·s)]and POC[7.2 mg/(m^(2)·s)].The latitudinal transport exhibited the northward transport of DOC[8.1 mg/(m^(2)·s)]and southward transport of POC[4.3 mg/(m^(2)·s)]movement.These findings have significant implications for enhancing our understanding of how hydrodynamics influence OC cycling in polynya regions.
文摘Driven by the accelerating global aging population and increasing health consciousness, compression stocking market is experiencing rapid growth. According to the latest data from Grand View Research, the global compression therapy market reached $4.25 billion in 2024, with medical compression stockings, as a core segment, boasting a compound annual growth rate(CAGR) of nearly 6%.
