Since reform and opening-up in 1978, changes in China's industrial structure have generally followed the pattern of "Kuznets facts" but still exhibits some unique characteristics, which led us to raise t...Since reform and opening-up in 1978, changes in China's industrial structure have generally followed the pattern of "Kuznets facts" but still exhibits some unique characteristics, which led us to raise the following three questions regarding China's structural transformation:(1) Why did the share of China's agricultural and manufacturing employment reduce/increase intermittently rather than continuously?(2) Why did the share of China's agricultural employment increase during certain periods? When the share of manufacturing employment reduced, why did the workforce reversely flow into agriculture rather than move to the service sector?(3) Why did growth in the share of China's service sector employment decelerate before reaching its peak? Why did the share of employment in the industrial sector suddenly increase after an abrupt decline? This paper creates a multisector economic growth model that contains non-homothetic preferences and differentiated productivity, and incorporates the "two drivers" therein for a demand-side estimation and analysis. The result shows that China's economic growth model driven by net export and investment is a critical factor for explaining the three questions regarding its structural transformation. This paper believes that only by implementing supply-side structural reforms, reducing the dependence on net export and investment, and achieving sustainable endogenous economic growth will China be able to expedite its industrial restructuring.展开更多
Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of ...Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of this species,it is important to have accurate and precise projections over time to make efficient decisions for forest management and greenfield investments in afforestation projects,especially for permanent carbon forests.Future projections of any natural resource systems rely on modeling;however,the acceleration of climate change makes future projections of yield less certain.These challenges also impact national expectations of the contribution planted forests will provide to address climate change and meet international commitments under the Paris Agreement.Using a large national-scale set of contemporary ground-measured data(2013–2023),this study investigates the performance of two growth models developed over 30 years ago that are widely used by NZ plantation growers:1)the Pumice Plateau Model 1988(PPM88)and 2)the 300-index(including a model variant of regional drift).Model simulations were made using the FORECASTER modeling suite with geographic boundaries to adjust for drift in space and time.Basal area(BA,m^(2)⋅ha^(-1))and volume(m^(3)⋅ha^(-1))were simulated,and standard errors and goodness-of-fit metrics calculated up to a typical rotation age of 30 years.Model residuals were then separated and analysed for the main plantation growing regions.The models overpredicted observed growth by between 6.8%and 16.2%,but model predictions and errors varied significantly between regions.The results of this study provided clear evidence of divergence between the outputs of both models and the measured data.Finally,this study suggests future measures to address challenges posed by these discrepancies that will provide better information for forest management and investment decisions in a changing climate.展开更多
Background:Hepatocellular carcinoma(HCC)is a highly lethal malignancy driven by both intrinsic oncogenic pathways and immune microenvironmental regulation.Emerging evidence suggests that DNASE1L3 may influence tumor b...Background:Hepatocellular carcinoma(HCC)is a highly lethal malignancy driven by both intrinsic oncogenic pathways and immune microenvironmental regulation.Emerging evidence suggests that DNASE1L3 may influence tumor biology and immune responses;however,its specific roles in HCC progression and macrophage-mediated regulation remain unclear.This study aimed to elucidate the biological functions of DNASE1L3 in HCC and to determine how it modulates tumor behavior and immune interactions.Methods:Bioinformatics analyses of the GSE41804 and Cancer Genome Atlas-Liver Hepatocellular Carcinoma(TCGA-LIHC)datasets were used to identify hub genes.Functional assays assessed the impact of DNASE1L3 on HCC cell proliferation,migration,invasion,and cell cycle progression.The effects of DNASE1L3 on macrophage polarization and the Wnt/β-catenin signaling pathway were examined using a co-culture system.An HCC organoid model was established to further validate its regulatory function.Results:Eight prognostic signature genes were identified,with deoxyribonuclease I-like 3(DNase I-like 3)selected as the hub gene.DNASE1L3 overexpression suppressed HCC cell growth,inhibited migration and invasion,induced G1 arrest,and modulated epithelial-mesenchymal transition(EMT)markers.DNASE1L3 knockdown promoted M2-like macrophage polarization.Mechanistically,DNASE1L3 interacted withβ-catenin to enhance its ubiquitination and degradation,thereby inhibiting Wnt/β-catenin signaling and reducing PD-L1 expression.DNASE1L3 overexpression similarly restricted organoid growth and suppressed pathway activity.Conclusion:DNASE1L3 acts as a negative regulator of HCC progression by targeting the Wnt/β-catenin pathway and reducing PD-L1 expression,thereby influencing both tumor cell behavior and macrophage-mediated immune responses.展开更多
Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Reg...Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.展开更多
In order to investigate the damage tolerance of a metastable Ti-5Al-3V-3Mo-2Cr-2Zr-1Nb-1Fe(Ti5321)alloy with bimodal microstructure using void growth quantification and micromechanical modeling,in situ tensile testing...In order to investigate the damage tolerance of a metastable Ti-5Al-3V-3Mo-2Cr-2Zr-1Nb-1Fe(Ti5321)alloy with bimodal microstructure using void growth quantification and micromechanical modeling,in situ tensile testing was performed during X-ray microtomography experiments.Compared with investigations of surface voids by traditional two-dimensional(2D)methods involving post-mortem characterization,three-dimensional(3D)information on void evolution inside optically opaque samples obtained through X-ray microtomography is essential.The Rice and Tracey model and Huang model were applied to predict void growth and show good agreement with experimental data using calibration of the damage parameterα.The void growth kinetics of Ti5321 with bimodal microstructure was analyzed by comparing theαvalue with that of Ti64 for different microstructure morphologies.The damage mechanism of ductile fracture of Ti5321 with bimodal microstructure is discussed.It was found that the size of the voids apparently increases with the triaxiality of stress.Post-mortem scanning electron microscopy(SEM)was also used to demonstrate this damage mechanism of ductile fracture of Ti5321.展开更多
This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor gro...This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.展开更多
Localized rock failures,like cracks or shear bands,demand specific attention in modeling for solids and structures.This is due to the uncertainty of conventional continuum-based mechanical models when localized inelas...Localized rock failures,like cracks or shear bands,demand specific attention in modeling for solids and structures.This is due to the uncertainty of conventional continuum-based mechanical models when localized inelastic deformation has emerged.In such scenarios,as macroscopic inelastic reactions are primarily influenced by deformation and microstructural alterations within the localized area,internal variables that signify these microstructural changes should be established within this zone.Thus,localized deformation characteristics of rocks are studied here by the preset angle shear experiment.A method based on shear displacement and shear stress differences is proposed to identify the compaction,yielding,and residual points for enhancing the model's effectiveness and minimizing subjective influences.Next,a mechanical model for the localized shear band is depicted as an elasto-plastic model outlining the stress-displacement relation across both sides of the shear band.Incorporating damage theory and an elasto-plastic model,a proposed damage model is introduced to replicate shear stressdisplacement responses and localized damage evolution in intact rocks experiencing shear failure.Subsequently,a novel nonlinear mathematical model based on modified logistic growth theory is proposed for depicting the shear band's damage evolution pattern.Thereafter,an innovative damage model is proposed to effectively encompass diverse rock material behaviors,including elasticity,plasticity,and softening behaviors.Ultimately,the effects of the preset angles,temperature,normal stresses and the residual shear strength are carefully discussed.This discovery enhances rock research in the proposed damage model,particularly regarding shear failure mode.展开更多
The continuous growth behavior of austenite grain in 20Cr peritectic steel was analyzed by experiment and theoretical modeling.The peculiar casting experiment with different cooling rates was achieved by multigradient...The continuous growth behavior of austenite grain in 20Cr peritectic steel was analyzed by experiment and theoretical modeling.The peculiar casting experiment with different cooling rates was achieved by multigradient operation scheme,and different morphologies in austenite grain were observed at the target location.The increase in austenite grain size with increasing cooling rate was firstly revealed in steels.The anomalous grain growth theoretically results from the mechanism of peritectic transformation transiting from the diffusional to massive type,and the additional energy storage stimulates the grain boundary migration.A new kinetic model to predict the growth behavior of austenite grain during continuous cooling process was developed,and the energy storage induced by massive type peritectic transformation was novelly taken into account.The parameters in the model were fitted by multiphase field modeling and experimental results.The kinetic model was finally verified by austenite grain size in laboratory test as well as the trial data at different locations in continuously cast bloom.The coarsening behavior of austenite grain during continuous casting was predicted based on the simulated temperature history.It is found that the grain coarsening occurs generally in the mold zone at high temperature for 20Cr steel and then almost levels off in the following process.The austenite finish transformation temperature Tγand primary cooling intensity show great influence on the grain coarsening.As Tγdecreases by 1℃,the austenite grain size decreases by 4μm linearly.However,the variation of Tγagainst heat flux is in a nonlinear relationship,suggesting that low cooling rate is much more harmful for austenite grain coarsening in continuous casting.展开更多
This study investigated forest recovery in the Atlantic Rainforest and Rupestrian Grassland of Brazil using the diffusive-logistic growth(DLG)model.This model simulates vegetation growth in the two mountain biomes con...This study investigated forest recovery in the Atlantic Rainforest and Rupestrian Grassland of Brazil using the diffusive-logistic growth(DLG)model.This model simulates vegetation growth in the two mountain biomes considering spatial location,time,and two key parameters:diffusion rate and growth rate.A Bayesian framework is employed to analyze the model's parameters and assess prediction uncertainties.Satellite imagery from 1992 and 2022 was used for model calibration and validation.By solving the DLG model using the finite difference method,we predicted a 6.6%–51.1%increase in vegetation density for the Atlantic Rainforest and a 5.3%–99.9%increase for the Rupestrian Grassland over 30 years,with the latter showing slower recovery but achieving a better model fit(lower RMSE)compared to the Atlantic Rainforest.The Bayesian approach revealed well-defined parameter distributions and lower parameter values for the Rupestrian Grassland,supporting the slower recovery prediction.Importantly,the model achieved good agreement with observed vegetation patterns in unseen validation data for both biomes.While there were minor spatial variations in accuracy,the overall distributions of predicted and observed vegetation density were comparable.Furthermore,this study highlights the importance of considering uncertainty in model predictions.Bayesian inference allowed us to quantify this uncertainty,demonstrating that the model's performance can vary across locations.Our approach provides valuable insights into forest regeneration process uncertainties,enabling comparisons of modeled scenarios at different recovery stages for better decision-making in these critical mountain biomes.展开更多
The growth of Sakhalin fir(Abies sachalinen-sis)seedlings,an important forest tree species in northern Hokkaido,Japan,is significantly affected by competition from surrounding vegetation,especially evergreen dwarf bam...The growth of Sakhalin fir(Abies sachalinen-sis)seedlings,an important forest tree species in northern Hokkaido,Japan,is significantly affected by competition from surrounding vegetation,especially evergreen dwarf bamboo.In this study,we investigated the height and root collar diameter(RCD)growth of Sakhalin fir seedlings under various degrees of cover by deciduous vegetation and evergreen dwarf bamboo.Generalized additive models were used to quantify the effects of canopy cover and forest floor cover on the relative growth rates of these two parameters.The canopy cover of Sakhalin fir seedlings had a nonlin-ear negative effect on both the height growth of seedlings in the subsequent year and the RCD growth in the current year,given the general growth pattern in this species,where height growth ceases in early summer and RCD growth con-tinues until autumn.Height growth declined sharply after the canopy cover rate exceeded 50%,while RCD growth declined rapidly between 0 and 50%canopy cover rate.The forest floor cover had a greater negative impact on RCD growth than on height growth.These results suggested that Sakhalin fir seedlings respond to vegetative competition by prioritizing height growth for light acquisition at the expense of diameter growth and possibly root growth for below-ground competition.The cover of evergreen dwarf bamboo reduced the height growth of fir seedlings significantly more than the cover of deciduous vegetation.This difference is likely due to the timing of light availability.When competing with deciduous vegetation,Sakhalin fir seedlings exposed to light during the post-snow melt and early spring before the development of the deciduous vegetation canopy can photosynthesize more effectively,leading to greater height growth.The results of this study highlighted the importance of vegetation control considering the type of vegetation for successful Sakhalin fir reforestation.Adjusting the intensity and timing of weeding based on the presence and abundance of dwarf bamboo and other competing vegetation could potentially reduce weeding costs and increase biodiversity in reforested areas.展开更多
BACKGROUND Syngeneic orthotopic tumor models offer an optimal functional tumor–immune interface for hepatocellular carcinoma research.Yet,unpredictable growth kinetics and spontaneous regression pose major obstacles....BACKGROUND Syngeneic orthotopic tumor models offer an optimal functional tumor–immune interface for hepatocellular carcinoma research.Yet,unpredictable growth kinetics and spontaneous regression pose major obstacles.Efficient induction protocols and continuous monitoring are therefore essential.Routine exploratory surgeries are ethically untenable,making non-invasive imaging modalities attractive alternatives.High-resolution magnetic resonance imaging and microcomputed tomography deliver detailed insights but incur substantial equipment costs,radiation risks,time demands,and require specialized expertise—challenges that limit their routine use.In contrast,ultrasound(US)imaging emerges as a cost-effective,radiation-free,and rapid approach,facilitating practical and ethical longitudinal assessment of tumor progression in preclinical studies.AIM To optimize the orthotopic hepatocellular carcinoma model and evaluate the potential of US imaging for accurate and cost-effective tumor monitoring.METHODS Hepatocellular carcinoma was induced in 28 Sprague Dawley rats by implanting 5×10^(6) N1S1 cells into the left lateral hepatic lobe.Tumor progression was monitored weekly via US.Upon reaching 100-150 mm^(3),an experimental group(n=14)received Sorafenib(40 mg/kg)orally on alternate days for 28 days;efficacy was compared to untreated controls.US accuracy was validated against micro-computed tomography,gross caliper measurements and histopathological analysis.Reliability and operator proficiency in US assessment were also evaluated.RESULTS US images procured 7-day post-surgery revealed a well-defined hypoechoic nodule at the left liver lobe tip,confirming successful tumor induction(mean volume 130±39 mm^(3)).Only three animals exhibited spontaneous regression by week 2,underscoring the model’s stability.Sorafenib treatment elicited a marked tumor reduction(678±103 mm^(3))vs untreated control(6005±1760 mm^(3)).US assessment demonstrated robust intra and interobserver reproducibility with high sensitivity and specificity for tumor detection.Moreover,US derived volumes correlated strongly with gross caliper measurements,histopathological analysis,and microcomputed tomography imaging,validating its reliability as a non-invasive monitoring tool in preclinical hepatocellular carcinoma studies.CONCLUSION The results demonstrate that US imaging is a reliable,cost-effective,and animal sparing approach with an easy tomaster protocol,enabling monitoring of tumor progression and therapeutic response in orthotopic liver tumor models.展开更多
Intra-annual climatic variability plays a critical role in regulating wood formation dynamics during the growing season,particularly in seasonally arid regions—such as the Qinling Mountains,China,and Mediterranean fo...Intra-annual climatic variability plays a critical role in regulating wood formation dynamics during the growing season,particularly in seasonally arid regions—such as the Qinling Mountains,China,and Mediterranean forests—where trees exhibit bimodal radial growth patterns as an adaptive response to water stress.While these growth patterns reflect immediate climatic conditions,the role of ecological memory,specifically vegetation growth carryover(VGC)and lagged climate effects(LCEs),remains poorly quantified.We employed the Vaganov–Shashkin(VS)model to analyze intra-annual bimodal growth patterns in two regions and used a vector autoregressive model with impulse response functions to assess the duration and intensity of VGC and LCE on tree-ring growth and remote sensing vegetation indices(leaf area index(LAI)and gross primary productivity(GPP)).Our results revealed bimodal growth patterns with spring and autumn peaks,but the autumn peak occurred earlier in the Qinling Mountains(August–October)than in Mediterranean forests(late September–October).VGC exerted the strongest influence on tree-ring growth in the first year,diminishing significantly after eight years in both regions(p<0.01).Tree-ring growth exhibited positive LCE responses to precipitation and soil moisture but negative responses to temperature(p<0.05).Remote sensing indices(LAI and GPP)displayed stronger VGC effects in the Qinling Mountains than in Mediterranean forests.While both LAI and GPP responded positively to soil moisture,temperature-induced LCE was positive in the Qinling Mountains but negative in the Mediterranean forests(p<0.05).Overall,VGC was the dominant ecological memory effect in both regions.Our results suggest that coupling the VGC and LCE of multiple vegetation growth indicators at multiple scales has the potential to improve the accuracy of global dynamic vegetation models.展开更多
Tree plantations are globally significant,and therefore,growth-related challenges cannot be ignored.Canopy structure and light environment influence the growth of plantations,but the precise relationship remains uncle...Tree plantations are globally significant,and therefore,growth-related challenges cannot be ignored.Canopy structure and light environment influence the growth of plantations,but the precise relationship remains unclear.We selected seven-year-old poplar plantations of varying cultivars planted various densities and measured their growth,canopy structure,and light environment.The findings indicate that poplar plantations of different cultivars and at different planting densities showed variations in leaf area index(LAI),average leaf angle(ALA),crown length(CL),length ratio(CLR),roundness(CR)and surface area(CSA),which directly or indirectly affect growth,resulting in disparities in their growing conditions.Crown roundness directly impacted growth,while LAI,CLR and ALA influenced growth indirectly by affecting intercellular carbon dioxide concentration.LAI and CLR had a positive effect;ALA had a negative one.Crown length and surface area directly and indirectly influenced growth by affecting photo synthetically active radiation and net photo synthetic rate,with direct impacts being more pronounced.This research has clarified the regulatory role of canopy structure in plantations growth,providing valuable insights for developing more effective management strategies.展开更多
As the global economy navigates through a complex landscape of uncertainty and shifting dynamics,the Chinese economy stands out for its remarkable resilience,inherent vitality,and steadfast commitment to a transformat...As the global economy navigates through a complex landscape of uncertainty and shifting dynamics,the Chinese economy stands out for its remarkable resilience,inherent vitality,and steadfast commitment to a transformative,high-quality development path.The latest economic indicators,strategic policy guidance from the Central Economic Work Conference,and a surge in international confidence collectively present a picture of an economy not merely recovering,but actively building its new growth engines.China is transitioning towards a more sustainable and innovation-driven model,with new quality productive forces playing an increasingly prominent role.展开更多
Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in ...Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in order to estimate biomass according to relationship between biomass and backscattering coefficients from SAR data. Based on cost function, parameters of growth model were optimized as per conjugate gradient method, minimizing the differences between estimated biomass and inversion values from SAR data. The results indicated that the simulated biomass using the revised growth model with SAR data was consistent with the measured one in time distribution and even higher in accuracy than that without SAR data. Hence, the key parameters of crop growth model could be revised by real-time growth information from SAR data and accuracy of the simulated biomass could be improved accordingly.展开更多
A mathematical model combined projection algorithm with phase-field method was applied. The adaptive finite element method was adopted to solve the model based on the non-uniform grid, and the behavior of dendritic gr...A mathematical model combined projection algorithm with phase-field method was applied. The adaptive finite element method was adopted to solve the model based on the non-uniform grid, and the behavior of dendritic growth was simulated from undercooled nickel melt under the forced flow. The simulation results show that the asymmetry behavior of the dendritic growth is caused by the forced flow. When the flow velocity is less than the critical value, the asymmetry of dendrite is little influenced by the forced flow. Once the flow velocity reaches or exceeds the critical value, the controlling factor of dendrite growth gradually changes from thermal diffusion to convection. With the increase of the flow velocity, the deflection angle towards upstream direction of the primary dendrite stem becomes larger. The effect of the dendrite growth on the flow field of the melt is apparent. With the increase of the dendrite size, the vortex is present in the downstream regions, and the vortex region is gradually enlarged. Dendrite tips appear to remelt. In addition, the adaptive finite element method can reduce CPU running time by one order of magnitude compared with uniform grid method, and the speed-up ratio is proportional to the size of computational domain.展开更多
The authors constructed a simplified model of spring wheat (Triticum aestivum L.) carbon assimilation and dry matter accumulation (DMA) process which consisted of two independent variables, day length (L) and total...The authors constructed a simplified model of spring wheat (Triticum aestivum L.) carbon assimilation and dry matter accumulation (DMA) process which consisted of two independent variables, day length (L) and total daily radiation (TDR). Leaf water potential (Ψ) was incorporated into the simplified growth model based on the assumption that both light use efficiency (α) and CO 2 conductance of assimilation (g c) were depressed by water limitation. Finally,Ψ was estimated from a regression equation in which the independent variables were relative soil water content in the upper 80 cm (θ R,80 ), ambient temperature (T a), vapor pressure deficit (VPD), the cumulative leaf water potential below thresholds of -1.5 MPa (Ψ c,1.5 ). Some applications in research program of field experiment of atmosphere_land surface processes in Heihe River region were tested. The simulated data agreed well with the data observed at Linze oasis in 1989 for various levels of water supply and at Zhangye oasis in 1992 in the field. The analysis and simulation using the model demonstrated that the simplified growth model could describe very well the DMA process of spring wheat with and without water limitation in the region of HEIFE (Heihe field experiment).展开更多
Growth model is an efficient way to study growing process of some factors of plants quantitatively. Height growth of Korean pine (Pinus koraiensis) was studied by using Hyperbola equation, Logistic equation, Richards ...Growth model is an efficient way to study growing process of some factors of plants quantitatively. Height growth of Korean pine (Pinus koraiensis) was studied by using Hyperbola equation, Logistic equation, Richards equation with three parameters, and Richards equation with four parameters in this paper. The results showed that Richards equation with four parameters was the most suitable and could be turned into other theoretical equations when some parameters were given different value. The maximum height of trees could be given in advance when using Richards equation with four parameters, and it was even more corresponding to reality. In addition, a height growth model with real height of fixed age as a parameter was discussed in this paper. This kind of growth model could be used to calculate height growth of a given tree effectively.展开更多
The stand growth and yield dynamic models for Larch in Jilin Province were developed based on the forest growth theories with the forest continuous inventory data. The results indicated that the developed models had h...The stand growth and yield dynamic models for Larch in Jilin Province were developed based on the forest growth theories with the forest continuous inventory data. The results indicated that the developed models had high precision, and they could be used for the updating data of inventory of planning and designing and optimal decision of forest management.展开更多
文摘Since reform and opening-up in 1978, changes in China's industrial structure have generally followed the pattern of "Kuznets facts" but still exhibits some unique characteristics, which led us to raise the following three questions regarding China's structural transformation:(1) Why did the share of China's agricultural and manufacturing employment reduce/increase intermittently rather than continuously?(2) Why did the share of China's agricultural employment increase during certain periods? When the share of manufacturing employment reduced, why did the workforce reversely flow into agriculture rather than move to the service sector?(3) Why did growth in the share of China's service sector employment decelerate before reaching its peak? Why did the share of employment in the industrial sector suddenly increase after an abrupt decline? This paper creates a multisector economic growth model that contains non-homothetic preferences and differentiated productivity, and incorporates the "two drivers" therein for a demand-side estimation and analysis. The result shows that China's economic growth model driven by net export and investment is a critical factor for explaining the three questions regarding its structural transformation. This paper believes that only by implementing supply-side structural reforms, reducing the dependence on net export and investment, and achieving sustainable endogenous economic growth will China be able to expedite its industrial restructuring.
基金funded by Scion's Strategic Science Investment Fund(SSIF)the Forest Growers Levy Trust(FGLT)through the Resilient Forests Programme(Task No.A89220)。
文摘Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of this species,it is important to have accurate and precise projections over time to make efficient decisions for forest management and greenfield investments in afforestation projects,especially for permanent carbon forests.Future projections of any natural resource systems rely on modeling;however,the acceleration of climate change makes future projections of yield less certain.These challenges also impact national expectations of the contribution planted forests will provide to address climate change and meet international commitments under the Paris Agreement.Using a large national-scale set of contemporary ground-measured data(2013–2023),this study investigates the performance of two growth models developed over 30 years ago that are widely used by NZ plantation growers:1)the Pumice Plateau Model 1988(PPM88)and 2)the 300-index(including a model variant of regional drift).Model simulations were made using the FORECASTER modeling suite with geographic boundaries to adjust for drift in space and time.Basal area(BA,m^(2)⋅ha^(-1))and volume(m^(3)⋅ha^(-1))were simulated,and standard errors and goodness-of-fit metrics calculated up to a typical rotation age of 30 years.Model residuals were then separated and analysed for the main plantation growing regions.The models overpredicted observed growth by between 6.8%and 16.2%,but model predictions and errors varied significantly between regions.The results of this study provided clear evidence of divergence between the outputs of both models and the measured data.Finally,this study suggests future measures to address challenges posed by these discrepancies that will provide better information for forest management and investment decisions in a changing climate.
基金funded by Shanghai Science and Technology Innovation Action Plan Project(22140901100)Shanghai Key Laboratory of Molecular Imaging(18DZ2260400)Shanghai University of Medicine and Health Science Seed Fund(SSF-24-21-01).
文摘Background:Hepatocellular carcinoma(HCC)is a highly lethal malignancy driven by both intrinsic oncogenic pathways and immune microenvironmental regulation.Emerging evidence suggests that DNASE1L3 may influence tumor biology and immune responses;however,its specific roles in HCC progression and macrophage-mediated regulation remain unclear.This study aimed to elucidate the biological functions of DNASE1L3 in HCC and to determine how it modulates tumor behavior and immune interactions.Methods:Bioinformatics analyses of the GSE41804 and Cancer Genome Atlas-Liver Hepatocellular Carcinoma(TCGA-LIHC)datasets were used to identify hub genes.Functional assays assessed the impact of DNASE1L3 on HCC cell proliferation,migration,invasion,and cell cycle progression.The effects of DNASE1L3 on macrophage polarization and the Wnt/β-catenin signaling pathway were examined using a co-culture system.An HCC organoid model was established to further validate its regulatory function.Results:Eight prognostic signature genes were identified,with deoxyribonuclease I-like 3(DNase I-like 3)selected as the hub gene.DNASE1L3 overexpression suppressed HCC cell growth,inhibited migration and invasion,induced G1 arrest,and modulated epithelial-mesenchymal transition(EMT)markers.DNASE1L3 knockdown promoted M2-like macrophage polarization.Mechanistically,DNASE1L3 interacted withβ-catenin to enhance its ubiquitination and degradation,thereby inhibiting Wnt/β-catenin signaling and reducing PD-L1 expression.DNASE1L3 overexpression similarly restricted organoid growth and suppressed pathway activity.Conclusion:DNASE1L3 acts as a negative regulator of HCC progression by targeting the Wnt/β-catenin pathway and reducing PD-L1 expression,thereby influencing both tumor cell behavior and macrophage-mediated immune responses.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd..(Grant No.H20230317)。
文摘Influenced by complex external factors,the displacement-time curve of reservoir landslides demonstrates both short-term and long-term diversity and dynamic complexity.It is difficult for existing methods,including Regression models and Neural network models,to perform multi-characteristic coupled displacement prediction because they fail to consider landslide creep characteristics.This paper integrates the creep characteristics of landslides with non-linear intelligent algorithms and proposes a dynamic intelligent landslide displacement prediction method based on a combination of the Biological Growth model(BG),Convolutional Neural Network(CNN),and Long ShortTerm Memory Network(LSTM).This prediction approach improves three different biological growth models,thereby effectively extracting landslide creep characteristic parameters.Simultaneously,it integrates external factors(rainfall and reservoir water level)to construct an internal and external comprehensive dataset for data augmentation,which is input into the improved CNN-LSTM model.Thereafter,harnessing the robust feature extraction capabilities and spatial translation invariance of CNN,the model autonomously captures short-term local fluctuation characteristics of landslide displacement,and combines LSTM's efficient handling of long-term nonlinear temporal data to improve prediction performance.An evaluation of the Liangshuijing landslide in the Three Gorges Reservoir Area indicates that BG-CNN-LSTM exhibits high prediction accuracy,excellent generalization capabilities when dealing with various types of landslides.The research provides an innovative approach to achieving the whole-process,realtime,high-precision displacement predictions for multicharacteristic coupled landslides.
基金supported by the China Postdoctoral Science Foundation(No.2022M720399).
文摘In order to investigate the damage tolerance of a metastable Ti-5Al-3V-3Mo-2Cr-2Zr-1Nb-1Fe(Ti5321)alloy with bimodal microstructure using void growth quantification and micromechanical modeling,in situ tensile testing was performed during X-ray microtomography experiments.Compared with investigations of surface voids by traditional two-dimensional(2D)methods involving post-mortem characterization,three-dimensional(3D)information on void evolution inside optically opaque samples obtained through X-ray microtomography is essential.The Rice and Tracey model and Huang model were applied to predict void growth and show good agreement with experimental data using calibration of the damage parameterα.The void growth kinetics of Ti5321 with bimodal microstructure was analyzed by comparing theαvalue with that of Ti64 for different microstructure morphologies.The damage mechanism of ductile fracture of Ti5321 with bimodal microstructure is discussed.It was found that the size of the voids apparently increases with the triaxiality of stress.Post-mortem scanning electron microscopy(SEM)was also used to demonstrate this damage mechanism of ductile fracture of Ti5321.
基金National Natural Science Foundation of China(Project No.:12371428)Projects of the Provincial College Students’Innovation and Training Program in 2024(Project No.:S202413023106,S202413023110)。
文摘This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.
基金supported by the China Scholarship Council Program(Grant No.202008320274)it is also supported by Technical University of Munich.
文摘Localized rock failures,like cracks or shear bands,demand specific attention in modeling for solids and structures.This is due to the uncertainty of conventional continuum-based mechanical models when localized inelastic deformation has emerged.In such scenarios,as macroscopic inelastic reactions are primarily influenced by deformation and microstructural alterations within the localized area,internal variables that signify these microstructural changes should be established within this zone.Thus,localized deformation characteristics of rocks are studied here by the preset angle shear experiment.A method based on shear displacement and shear stress differences is proposed to identify the compaction,yielding,and residual points for enhancing the model's effectiveness and minimizing subjective influences.Next,a mechanical model for the localized shear band is depicted as an elasto-plastic model outlining the stress-displacement relation across both sides of the shear band.Incorporating damage theory and an elasto-plastic model,a proposed damage model is introduced to replicate shear stressdisplacement responses and localized damage evolution in intact rocks experiencing shear failure.Subsequently,a novel nonlinear mathematical model based on modified logistic growth theory is proposed for depicting the shear band's damage evolution pattern.Thereafter,an innovative damage model is proposed to effectively encompass diverse rock material behaviors,including elasticity,plasticity,and softening behaviors.Ultimately,the effects of the preset angles,temperature,normal stresses and the residual shear strength are carefully discussed.This discovery enhances rock research in the proposed damage model,particularly regarding shear failure mode.
基金supported by the Fundamental Research Funds for the Central Universities(No.FRF-TP-19-017A3)National Natural Science Foundation of China(No.51874026).
文摘The continuous growth behavior of austenite grain in 20Cr peritectic steel was analyzed by experiment and theoretical modeling.The peculiar casting experiment with different cooling rates was achieved by multigradient operation scheme,and different morphologies in austenite grain were observed at the target location.The increase in austenite grain size with increasing cooling rate was firstly revealed in steels.The anomalous grain growth theoretically results from the mechanism of peritectic transformation transiting from the diffusional to massive type,and the additional energy storage stimulates the grain boundary migration.A new kinetic model to predict the growth behavior of austenite grain during continuous cooling process was developed,and the energy storage induced by massive type peritectic transformation was novelly taken into account.The parameters in the model were fitted by multiphase field modeling and experimental results.The kinetic model was finally verified by austenite grain size in laboratory test as well as the trial data at different locations in continuously cast bloom.The coarsening behavior of austenite grain during continuous casting was predicted based on the simulated temperature history.It is found that the grain coarsening occurs generally in the mold zone at high temperature for 20Cr steel and then almost levels off in the following process.The austenite finish transformation temperature Tγand primary cooling intensity show great influence on the grain coarsening.As Tγdecreases by 1℃,the austenite grain size decreases by 4μm linearly.However,the variation of Tγagainst heat flux is in a nonlinear relationship,suggesting that low cooling rate is much more harmful for austenite grain coarsening in continuous casting.
基金financial support from the Brazilian National Council for Scientific and Technological Development(CNPq)and the Federal University of Ouro PretoFinancial support from the Minas Gerais Research Foundation(FAPEMIG)under grant number APQ-06559-24 is also gratefully acknowledged。
文摘This study investigated forest recovery in the Atlantic Rainforest and Rupestrian Grassland of Brazil using the diffusive-logistic growth(DLG)model.This model simulates vegetation growth in the two mountain biomes considering spatial location,time,and two key parameters:diffusion rate and growth rate.A Bayesian framework is employed to analyze the model's parameters and assess prediction uncertainties.Satellite imagery from 1992 and 2022 was used for model calibration and validation.By solving the DLG model using the finite difference method,we predicted a 6.6%–51.1%increase in vegetation density for the Atlantic Rainforest and a 5.3%–99.9%increase for the Rupestrian Grassland over 30 years,with the latter showing slower recovery but achieving a better model fit(lower RMSE)compared to the Atlantic Rainforest.The Bayesian approach revealed well-defined parameter distributions and lower parameter values for the Rupestrian Grassland,supporting the slower recovery prediction.Importantly,the model achieved good agreement with observed vegetation patterns in unseen validation data for both biomes.While there were minor spatial variations in accuracy,the overall distributions of predicted and observed vegetation density were comparable.Furthermore,this study highlights the importance of considering uncertainty in model predictions.Bayesian inference allowed us to quantify this uncertainty,demonstrating that the model's performance can vary across locations.Our approach provides valuable insights into forest regeneration process uncertainties,enabling comparisons of modeled scenarios at different recovery stages for better decision-making in these critical mountain biomes.
基金supported by the Ministry of Agriculture,Forestry,and Fisheries of Japan (25093 C)JSPS KAKENHI (JP23H02262)
文摘The growth of Sakhalin fir(Abies sachalinen-sis)seedlings,an important forest tree species in northern Hokkaido,Japan,is significantly affected by competition from surrounding vegetation,especially evergreen dwarf bamboo.In this study,we investigated the height and root collar diameter(RCD)growth of Sakhalin fir seedlings under various degrees of cover by deciduous vegetation and evergreen dwarf bamboo.Generalized additive models were used to quantify the effects of canopy cover and forest floor cover on the relative growth rates of these two parameters.The canopy cover of Sakhalin fir seedlings had a nonlin-ear negative effect on both the height growth of seedlings in the subsequent year and the RCD growth in the current year,given the general growth pattern in this species,where height growth ceases in early summer and RCD growth con-tinues until autumn.Height growth declined sharply after the canopy cover rate exceeded 50%,while RCD growth declined rapidly between 0 and 50%canopy cover rate.The forest floor cover had a greater negative impact on RCD growth than on height growth.These results suggested that Sakhalin fir seedlings respond to vegetative competition by prioritizing height growth for light acquisition at the expense of diameter growth and possibly root growth for below-ground competition.The cover of evergreen dwarf bamboo reduced the height growth of fir seedlings significantly more than the cover of deciduous vegetation.This difference is likely due to the timing of light availability.When competing with deciduous vegetation,Sakhalin fir seedlings exposed to light during the post-snow melt and early spring before the development of the deciduous vegetation canopy can photosynthesize more effectively,leading to greater height growth.The results of this study highlighted the importance of vegetation control considering the type of vegetation for successful Sakhalin fir reforestation.Adjusting the intensity and timing of weeding based on the presence and abundance of dwarf bamboo and other competing vegetation could potentially reduce weeding costs and increase biodiversity in reforested areas.
基金Supported by Amrita Vishwa Vidyapeetham Seed Grant,No.K-PHAR-24-722DST INSPIRE Fellowship,No.IF190226.
文摘BACKGROUND Syngeneic orthotopic tumor models offer an optimal functional tumor–immune interface for hepatocellular carcinoma research.Yet,unpredictable growth kinetics and spontaneous regression pose major obstacles.Efficient induction protocols and continuous monitoring are therefore essential.Routine exploratory surgeries are ethically untenable,making non-invasive imaging modalities attractive alternatives.High-resolution magnetic resonance imaging and microcomputed tomography deliver detailed insights but incur substantial equipment costs,radiation risks,time demands,and require specialized expertise—challenges that limit their routine use.In contrast,ultrasound(US)imaging emerges as a cost-effective,radiation-free,and rapid approach,facilitating practical and ethical longitudinal assessment of tumor progression in preclinical studies.AIM To optimize the orthotopic hepatocellular carcinoma model and evaluate the potential of US imaging for accurate and cost-effective tumor monitoring.METHODS Hepatocellular carcinoma was induced in 28 Sprague Dawley rats by implanting 5×10^(6) N1S1 cells into the left lateral hepatic lobe.Tumor progression was monitored weekly via US.Upon reaching 100-150 mm^(3),an experimental group(n=14)received Sorafenib(40 mg/kg)orally on alternate days for 28 days;efficacy was compared to untreated controls.US accuracy was validated against micro-computed tomography,gross caliper measurements and histopathological analysis.Reliability and operator proficiency in US assessment were also evaluated.RESULTS US images procured 7-day post-surgery revealed a well-defined hypoechoic nodule at the left liver lobe tip,confirming successful tumor induction(mean volume 130±39 mm^(3)).Only three animals exhibited spontaneous regression by week 2,underscoring the model’s stability.Sorafenib treatment elicited a marked tumor reduction(678±103 mm^(3))vs untreated control(6005±1760 mm^(3)).US assessment demonstrated robust intra and interobserver reproducibility with high sensitivity and specificity for tumor detection.Moreover,US derived volumes correlated strongly with gross caliper measurements,histopathological analysis,and microcomputed tomography imaging,validating its reliability as a non-invasive monitoring tool in preclinical hepatocellular carcinoma studies.CONCLUSION The results demonstrate that US imaging is a reliable,cost-effective,and animal sparing approach with an easy tomaster protocol,enabling monitoring of tumor progression and therapeutic response in orthotopic liver tumor models.
基金supported by the National Natural Science Foundation of China(Nos.42277448,42330501,41971104,and 41807431)。
文摘Intra-annual climatic variability plays a critical role in regulating wood formation dynamics during the growing season,particularly in seasonally arid regions—such as the Qinling Mountains,China,and Mediterranean forests—where trees exhibit bimodal radial growth patterns as an adaptive response to water stress.While these growth patterns reflect immediate climatic conditions,the role of ecological memory,specifically vegetation growth carryover(VGC)and lagged climate effects(LCEs),remains poorly quantified.We employed the Vaganov–Shashkin(VS)model to analyze intra-annual bimodal growth patterns in two regions and used a vector autoregressive model with impulse response functions to assess the duration and intensity of VGC and LCE on tree-ring growth and remote sensing vegetation indices(leaf area index(LAI)and gross primary productivity(GPP)).Our results revealed bimodal growth patterns with spring and autumn peaks,but the autumn peak occurred earlier in the Qinling Mountains(August–October)than in Mediterranean forests(late September–October).VGC exerted the strongest influence on tree-ring growth in the first year,diminishing significantly after eight years in both regions(p<0.01).Tree-ring growth exhibited positive LCE responses to precipitation and soil moisture but negative responses to temperature(p<0.05).Remote sensing indices(LAI and GPP)displayed stronger VGC effects in the Qinling Mountains than in Mediterranean forests.While both LAI and GPP responded positively to soil moisture,temperature-induced LCE was positive in the Qinling Mountains but negative in the Mediterranean forests(p<0.05).Overall,VGC was the dominant ecological memory effect in both regions.Our results suggest that coupling the VGC and LCE of multiple vegetation growth indicators at multiple scales has the potential to improve the accuracy of global dynamic vegetation models.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFD2201203)the financial support of the National Natural Science Foundation of China(32001311)。
文摘Tree plantations are globally significant,and therefore,growth-related challenges cannot be ignored.Canopy structure and light environment influence the growth of plantations,but the precise relationship remains unclear.We selected seven-year-old poplar plantations of varying cultivars planted various densities and measured their growth,canopy structure,and light environment.The findings indicate that poplar plantations of different cultivars and at different planting densities showed variations in leaf area index(LAI),average leaf angle(ALA),crown length(CL),length ratio(CLR),roundness(CR)and surface area(CSA),which directly or indirectly affect growth,resulting in disparities in their growing conditions.Crown roundness directly impacted growth,while LAI,CLR and ALA influenced growth indirectly by affecting intercellular carbon dioxide concentration.LAI and CLR had a positive effect;ALA had a negative one.Crown length and surface area directly and indirectly influenced growth by affecting photo synthetically active radiation and net photo synthetic rate,with direct impacts being more pronounced.This research has clarified the regulatory role of canopy structure in plantations growth,providing valuable insights for developing more effective management strategies.
文摘As the global economy navigates through a complex landscape of uncertainty and shifting dynamics,the Chinese economy stands out for its remarkable resilience,inherent vitality,and steadfast commitment to a transformative,high-quality development path.The latest economic indicators,strategic policy guidance from the Central Economic Work Conference,and a surge in international confidence collectively present a picture of an economy not merely recovering,but actively building its new growth engines.China is transitioning towards a more sustainable and innovation-driven model,with new quality productive forces playing an increasingly prominent role.
基金Supported by National High-tech R & D Program of China (863 Program)(2007AA12Z174)~~
文摘Biomass from SAR data was assimilated into crop growth model to describe relationship between crop biomass and crop growth time to improve estimation accuracy of biomass. In addition, inverse model was established in order to estimate biomass according to relationship between biomass and backscattering coefficients from SAR data. Based on cost function, parameters of growth model were optimized as per conjugate gradient method, minimizing the differences between estimated biomass and inversion values from SAR data. The results indicated that the simulated biomass using the revised growth model with SAR data was consistent with the measured one in time distribution and even higher in accuracy than that without SAR data. Hence, the key parameters of crop growth model could be revised by real-time growth information from SAR data and accuracy of the simulated biomass could be improved accordingly.
基金Projects(51161011,11364024)supported by the National Natural Science Foundation of ChinaProject(1204GKCA065)supported by the Key Technology R&D Program of Gansu Province,China+1 种基金Project(201210)supported by the Fundamental Research Funds for the Universities of Gansu Province,ChinaProject(J201304)supported by the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China
文摘A mathematical model combined projection algorithm with phase-field method was applied. The adaptive finite element method was adopted to solve the model based on the non-uniform grid, and the behavior of dendritic growth was simulated from undercooled nickel melt under the forced flow. The simulation results show that the asymmetry behavior of the dendritic growth is caused by the forced flow. When the flow velocity is less than the critical value, the asymmetry of dendrite is little influenced by the forced flow. Once the flow velocity reaches or exceeds the critical value, the controlling factor of dendrite growth gradually changes from thermal diffusion to convection. With the increase of the flow velocity, the deflection angle towards upstream direction of the primary dendrite stem becomes larger. The effect of the dendrite growth on the flow field of the melt is apparent. With the increase of the dendrite size, the vortex is present in the downstream regions, and the vortex region is gradually enlarged. Dendrite tips appear to remelt. In addition, the adaptive finite element method can reduce CPU running time by one order of magnitude compared with uniform grid method, and the speed-up ratio is proportional to the size of computational domain.
文摘The authors constructed a simplified model of spring wheat (Triticum aestivum L.) carbon assimilation and dry matter accumulation (DMA) process which consisted of two independent variables, day length (L) and total daily radiation (TDR). Leaf water potential (Ψ) was incorporated into the simplified growth model based on the assumption that both light use efficiency (α) and CO 2 conductance of assimilation (g c) were depressed by water limitation. Finally,Ψ was estimated from a regression equation in which the independent variables were relative soil water content in the upper 80 cm (θ R,80 ), ambient temperature (T a), vapor pressure deficit (VPD), the cumulative leaf water potential below thresholds of -1.5 MPa (Ψ c,1.5 ). Some applications in research program of field experiment of atmosphere_land surface processes in Heihe River region were tested. The simulated data agreed well with the data observed at Linze oasis in 1989 for various levels of water supply and at Zhangye oasis in 1992 in the field. The analysis and simulation using the model demonstrated that the simplified growth model could describe very well the DMA process of spring wheat with and without water limitation in the region of HEIFE (Heihe field experiment).
基金Great Item National Natural Science Foundation of China (39899370) and National Natural Science Foundation of China (NSFC39970123) and Changbai Mountain Open Research Station.
文摘Growth model is an efficient way to study growing process of some factors of plants quantitatively. Height growth of Korean pine (Pinus koraiensis) was studied by using Hyperbola equation, Logistic equation, Richards equation with three parameters, and Richards equation with four parameters in this paper. The results showed that Richards equation with four parameters was the most suitable and could be turned into other theoretical equations when some parameters were given different value. The maximum height of trees could be given in advance when using Richards equation with four parameters, and it was even more corresponding to reality. In addition, a height growth model with real height of fixed age as a parameter was discussed in this paper. This kind of growth model could be used to calculate height growth of a given tree effectively.
文摘The stand growth and yield dynamic models for Larch in Jilin Province were developed based on the forest growth theories with the forest continuous inventory data. The results indicated that the developed models had high precision, and they could be used for the updating data of inventory of planning and designing and optimal decision of forest management.
