A Level考试素有“英国高考”之称。其制度演进大致经历了发轫与探索、扩张与调适、回归与重塑三个阶段,其主要变革内容包括四个方面:组织形式从年终末考的线性考试模式发展为一年多考的模块化考试,再回归线性考试模式;考试评价从常模...A Level考试素有“英国高考”之称。其制度演进大致经历了发轫与探索、扩张与调适、回归与重塑三个阶段,其主要变革内容包括四个方面:组织形式从年终末考的线性考试模式发展为一年多考的模块化考试,再回归线性考试模式;考试评价从常模参照转变为标准参照,评价手段逐步优化;考试要求从注重学科深度转变为强调知识广度,再发展为追求广度和深度并重;考试内容从偏重学术性转变为普职并重,再发展为职普融通和强调基础学科。变革的动因既有来自外部的国际竞争加剧和国内政党轮替,也有来自内部的文化价值观驱动和考试选才效度追求。A Level考试制度对我国高考改革有一定启发,我国可结合国情,以基础学科为支点、职普融通为路径、多样化的考试选择为依托、预测效度为导向,开展本土化探索。展开更多
The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the...The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.展开更多
Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fati...This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.展开更多
Hainan Province in south China is the country’s second-largest island and the largest free trade port by area.It has entered a historic phase in China’s drive to promote high-level institutional opening up.On 18 Dec...Hainan Province in south China is the country’s second-largest island and the largest free trade port by area.It has entered a historic phase in China’s drive to promote high-level institutional opening up.On 18 December 2025,Hainan officially launched island-wide special customs operations,commonly referred to as“customs closure.”From that date,goods entering or leaving the island,except those traded with the Chinese mainland,are subject to simplified customs procedures and potentially reduced or zero tariffs.展开更多
During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once ag...During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.展开更多
Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi...Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi-head Self-attention mechan-ism(MSAM-GRU)to simulate GWLs in both confined and unconfined aquifers simultaneously.The model innovatively captures the lag times between GWLs in the unconfined aquifer and precipitation,as well as between GWLs in the confined aquifer and the upper aquifer.We have assessed the effectiveness of the proposed model using a case study in the Beijing Plain,China from January 2005 to December 2020.With the consideration of lag times,the results indicated that the MSAM-GRU model exhibits a maximum 67%and 73%reduction in RMSE compared to the Attention mechanism-GRU(AM-GRU)and GRU model,respectively.MSAM-GRU model exhibited a 31%reduction in RMSE and a 0.12 increase in R^(2) compared to the same model that do not account for lag time.In Region I,the shortest lag time of GWL in the unconfined aquifer was two months,while that in the confined aquifer was three months,indicating a longer delayed response in the confined aquifer.MSAM-GRU model considering lag time,was then applied to simulate the GWLs in the unconfined aquifer under different scenarios and to analyze whether GWL fluctuations affect subway operations.The simulation res-ults showed that under the scenario 1,the GWL in the unconfined aquifer would rise above the depth of subway station floor,threaten-ing the operation of subways.This study can provide reliable technical support for the accurate simulation of GWLs in multi-aquifer systems.展开更多
Metallogenic research on structural levels can reveal vertical patterns of mineralization and facilitate the deep exploration of economic minerals.However,research focusing on the correlation between structural levels...Metallogenic research on structural levels can reveal vertical patterns of mineralization and facilitate the deep exploration of economic minerals.However,research focusing on the correlation between structural levels and mineralization remains limited.In this study,we summarize the deformation patterns and associated mineral deposits observed at different crustal levels(i.e.,surface,shallow,middle,and deep structural levels,corresponding to depths of<2,2-8,8-15,and>15 km,respectively).Furthermore,we examine the genetic association between structural levels and metallogenesis,demonstrating that distinct structural levels are linked to specific types of mineralization.Key factors that vary across crustal levels include temperature,pressure,and fluid circulation.Ore-forming processes involve interactions between structures and fluids under varying temperatures and pressures.Structural levels influence mineralization by controlling the temperatures,pressures,and deformation mechanisms that drive the activation,migration,and enrichment of ore-forming materials.展开更多
The Thwaites Glacier in western Antarctica(Fig. 1) keeps glaciologists and climate scientists awake at night. The 120 kmwide glacier loses about 45 billion tonnes of ice each year, accounting for about 4% of global se...The Thwaites Glacier in western Antarctica(Fig. 1) keeps glaciologists and climate scientists awake at night. The 120 kmwide glacier loses about 45 billion tonnes of ice each year, accounting for about 4% of global sea level rise [1]. If it melted completely, sea levels would climb 65 cm, and follow-on effects could lead to a 3 m increase [2]. But if some scientists' vision becomes reality, in 10–15 years construction crews will sail into the Amundsen Sea off Antarctica to begin building an 80 km long underwater curtain that will shield the glacier from the warm currents that are accelerating its decline [3].展开更多
Quantifying spatiotemporal variations in water levels and their responses to external drivers(e.g.,morphology,river discharge,and sea level)is critical for sustainable water resource management.However,simple methods ...Quantifying spatiotemporal variations in water levels and their responses to external drivers(e.g.,morphology,river discharge,and sea level)is critical for sustainable water resource management.However,simple methods for distinguishing the impacts of upstream river discharge,downstream sea level,and morphological changes on estuarine water levels remain limited.This study applied a revised triple linear regression model to reconstruct historical water levels(1965-2017)in the highly human-modified Zhujiang River Estuary(ZRE).The strong agreement between reconstructed and observed water levels(root mean square error<0.17 m;coefficient of determination>0.90)confirms the model reliability in quantifying drivers of water level variations.Results show morphological evolution as the dominant factor,causing an average water level decrease of 0.13 m,with declines increasing upstream from the estuary mouth.Sea level rise moderately elevated water levels by approximately 0.08 m on average.Reservoir regulation altered flow distribution and seasonal discharge patterns,weakening river discharge effects on downstream water levels in the lower West River,yet strengthening effects in the lower North River,averaging a 0.09 m water level decrease.These alterations further modified spatial water level slopes:reduced slopes in the lower West River primarily resulted from discharge changes,while morphological evolution dominated in the lower North River.Scenario simulations revealed significant water level responses to extreme events:an upstream discharge increase from 25000 m^(3)/s to 55000 m^(3)/s elevated upstream water levels by 3.47 m on average;relative sea level rise during storm surges from 1.50 m to 3.00 m increased downstream water levels by 1.34 m.These findings provide valuable guidance for flood prevention and water resource management in the ZRE and similarly modified estuaries worldwide.展开更多
BackgroundIt's crucial to study the effect of changes in thresholds(T)and most comfortable levels(M)on behavioral measurements in young children using cochlear implants.This would help the clinician with the optim...BackgroundIt's crucial to study the effect of changes in thresholds(T)and most comfortable levels(M)on behavioral measurements in young children using cochlear implants.This would help the clinician with the optimization and validation of programming parameters.ObjectiveThe study has attempted to describe the changes in behavioral responses with modification of T and M levels.MethodsTwenty-five participants in the age range 5 to 12 years using HR90K/HiFocus1J or HR90KAdvantage/HiFocus1J with Harmony speech processors participated in the study.A decrease in T levels,a rise in T levels,or a decrease in M levels in the everyday program were used to create experimental programs.Sound field thresholds and speech perception were measured at 50 dBHL for three experimental and everyday programs.ConclusionThe results indicated that only reductions of M levels resulted in significantly(p<0.01)poor aided thresholds and speech perception.On the other hand,variation in T levels did not have significant changes in either sound field thresholds or speech perception.The results highlight that M levels must be correctly established in order to prevent decreased speech perception and audibility.展开更多
Hybrid level of detail （LOD） （HLOD） algorithm based on discrete LOD and continuous LOD is presented for real-time rendering of large-scale terrains. There are n HLOD models created off-line, which form a pyramid w...Hybrid level of detail （LOD） （HLOD） algorithm based on discrete LOD and continuous LOD is presented for real-time rendering of large-scale terrains. There are n HLOD models created off-line, which form a pyramid with n layers. Each of these models contains countless versions of the model at various levels of detail. When rendering, the corresponding models in some layer will be chosen. As the viewer＇s moves, either the continuous LOD algorithm will be applied to the selected models, or the visible models in another layer will be selected. An experiment on a triangular irregular network（TIN） terrain model was performed respectively using discrete LOD, continuous LOD and HLOD. The experimental results show that the HLOD algorithm exceeds the other two kinds of LOD in frame rate without reduction of terrain＇s fidelity.展开更多
Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based ...Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms.By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method and fuzzy entropy(FE)with the new and highly efficient Runge–Kuta optimizer(RUN),adaptive parameter optimization for the support vector machine(SVM)and radial basis function neural network(RBFNN)algorithms was achieved.Regression prediction was conducted on the two reconstructed sequences using SVM and RBFNN according to their respective features.This approach improved the accuracy and stability of predictions.In terms of accuracy,the combined model outperformed single models,with the determination coefficient,root mean square error,and mean absolute error values of 0.9975,0.2418 m,and 0.1616 m,respectively.In terms of stability,the model predicted more consistently in training and testing periods,with stable overall prediction accuracy and a better adaptive ability to complex datasets.The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels,leveraged the strength of each predictive method,compensated for their limitations,and clarified the impacts of environmental factors on reservoir water levels.展开更多
To explore water level variations and their dynamic influence on the water quality of Huayang Lakes,the water level from 1967 to 2023 and water quality from 2015 to 2023 were analyzed using the Mann–Kendall trend tes...To explore water level variations and their dynamic influence on the water quality of Huayang Lakes,the water level from 1967 to 2023 and water quality from 2015 to 2023 were analyzed using the Mann–Kendall trend test,box plots,and violin plots.The results show a notable hydrological rhythm of water level alternation between dry and flood seasons in Huayang Lakes,with an average water level of 12.82 m and a monthly range of 11.21–17.24m.Since 2017,the water level of Huayang Rivers has shown a decreasing trend of–0.02 m/a.Total phosphorus(TP)has become the primary pollutant.The TP concentrations in Longgan Lake(the largest lake)during the dry,rising,flood,and retreating seasons from 2015 to 2023were 0.083,0.061,0.050,and 0.059 mg/L,respectively.The effect of water level on TP was mainly observed during the low-water period.When the water level in the dry season rose to 12.25 and 13.00 m,the percentage of TP exceeding 0.1 mg/L in Longgan Lake decreased to 55.8%and 33.3%,respectively.During the dry season,wind and wave disturbances caused the release of endogenous phosphorus in Huayang Lakes.This led to drastic fluctuations in TP concentration,reducing the correlation between water level and TP.When external control is limited,the water level during the dry season should be maintained between 12.25 and 13.0 m.Additionally,it is necessary to accelerate the restoration of submerged macrophyte species(such as Hydrilla verticillata and Vallisneria natans)in the Huayang Rivers.展开更多
For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation characteristics.These models typically fall into two categories:data-driven models...For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation characteristics.These models typically fall into two categories:data-driven models and physical models,each offering unique advantages but also facing limitations.Physics-informed neural networks(PINNs)provide a robust framework to integrate data-driven models with physical principles,ensuring consistency with underlying physics while enabling generalization across diverse operational conditions.This study introduces a PINN-based approach to reconstruct open circuit voltage(OCV)curves and estimate key ageing parameters at both the cell and electrode levels.These parameters include available capacity,electrode capacities,and lithium inventory capacity.The proposed method integrates OCV reconstruction models as functional components into convolutional neural networks(CNNs)and is validated using a public dataset.The results reveal that the estimated ageing parameters closely align with those obtained through offline OCV tests,with errors in reconstructed OCV curves remaining within 15 mV.This demonstrates the ability of the method to deliver fast and accurate degradation diagnostics at the electrode level,advancing the potential for precise and efficient battery health management.展开更多
Fluvial systems play a crucial role in coastal and riverine ecosystems, making it essential to understand their responses to sea level changes for preserving biodiversity and managing natural resources. The evolution ...Fluvial systems play a crucial role in coastal and riverine ecosystems, making it essential to understand their responses to sea level changes for preserving biodiversity and managing natural resources. The evolution of the modern Indus River Delta offers a rare opportunity to study the interplay between sea level fluctuations, tectonism, sediment supply, and the corresponding fluvial responses. This study employs the ‘SedSim' stratigraphic forward model to simulate the delta's evolution from 200 kyr to the next5 kyr, drawing on data from field observations, Landsat imagery, digital elevation models, and previous studies. The model consists of 205 layers, each representing a 1-kyr time step, covering the last two glacial-interglacial cycles. Between 200 kyr and 130 kyr, during a lowstand period, sedimentation on the delta plain continued due to partial flow from the Indus River. During the last interglacial(130–60 kyr), rising sea levels led to peak sediment deposition, characteristic of a highstand phase. From 60 kyr to 18 kyr, sea levels dropped to their lowest during the Last Glacial Maximum(LGM), resulting in extensive erosion and minimal deposition on the delta plain. From 18 kyr to the present, rapidly rising sea levels, coupled with intensified monsoon activity, increased sedimentation rates and triggered avulsion and aggradation processes. The model accurately predicted depositional thickness across the delta plain, indicating a maximum of ca. 200 m at the shoreline platform, ca. 175 m in the northeastern delta, and ca. 100 m in the central delta. The study underscores the delta's vulnerability to future sea level rise, which–at a projected rate of 1 m/kyr–could significantly influence the densely populated, low-lying delta plain. These findings offer valuable insights into the geomorphic evolution of the Indus Delta and emphasize the socioeconomic implications of sea level change, underscoring the importance of proactive management and adaptation strategies.展开更多
基金supported by the China National Science Foundation(No.42130506,42071031)the Special Technology Innovation Fund of Carbon Peak and Carbon Neutrality in Jiangsu Province(BK20231515)+1 种基金the Spanish Government grant PID2022-140808NB-I00 funded by MICIU/AEI/https://doi.org/10.13039/501100011033the Catalan Government grants SGR 2021-1333 and AGAUR2023 CLIMA 00118.
文摘The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
基金supported by National Natural Science Foundation of China[NO.11932013].
文摘This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.
文摘Hainan Province in south China is the country’s second-largest island and the largest free trade port by area.It has entered a historic phase in China’s drive to promote high-level institutional opening up.On 18 December 2025,Hainan officially launched island-wide special customs operations,commonly referred to as“customs closure.”From that date,goods entering or leaving the island,except those traded with the Chinese mainland,are subject to simplified customs procedures and potentially reduced or zero tariffs.
文摘During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.
基金Under the auspices of the National Key Research and Development Program of China(No.2024YFC3713102)。
文摘Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi-head Self-attention mechan-ism(MSAM-GRU)to simulate GWLs in both confined and unconfined aquifers simultaneously.The model innovatively captures the lag times between GWLs in the unconfined aquifer and precipitation,as well as between GWLs in the confined aquifer and the upper aquifer.We have assessed the effectiveness of the proposed model using a case study in the Beijing Plain,China from January 2005 to December 2020.With the consideration of lag times,the results indicated that the MSAM-GRU model exhibits a maximum 67%and 73%reduction in RMSE compared to the Attention mechanism-GRU(AM-GRU)and GRU model,respectively.MSAM-GRU model exhibited a 31%reduction in RMSE and a 0.12 increase in R^(2) compared to the same model that do not account for lag time.In Region I,the shortest lag time of GWL in the unconfined aquifer was two months,while that in the confined aquifer was three months,indicating a longer delayed response in the confined aquifer.MSAM-GRU model considering lag time,was then applied to simulate the GWLs in the unconfined aquifer under different scenarios and to analyze whether GWL fluctuations affect subway operations.The simulation res-ults showed that under the scenario 1,the GWL in the unconfined aquifer would rise above the depth of subway station floor,threaten-ing the operation of subways.This study can provide reliable technical support for the accurate simulation of GWLs in multi-aquifer systems.
基金supported by National Key Research and Development Program of China(Grant Nos.2022YFF0800903 and 2024YFC2909905)the National Natural Science Foundation of China(NSFC)(Grant Nos.42261144669,42262026,and 42273073).
文摘Metallogenic research on structural levels can reveal vertical patterns of mineralization and facilitate the deep exploration of economic minerals.However,research focusing on the correlation between structural levels and mineralization remains limited.In this study,we summarize the deformation patterns and associated mineral deposits observed at different crustal levels(i.e.,surface,shallow,middle,and deep structural levels,corresponding to depths of<2,2-8,8-15,and>15 km,respectively).Furthermore,we examine the genetic association between structural levels and metallogenesis,demonstrating that distinct structural levels are linked to specific types of mineralization.Key factors that vary across crustal levels include temperature,pressure,and fluid circulation.Ore-forming processes involve interactions between structures and fluids under varying temperatures and pressures.Structural levels influence mineralization by controlling the temperatures,pressures,and deformation mechanisms that drive the activation,migration,and enrichment of ore-forming materials.
文摘The Thwaites Glacier in western Antarctica(Fig. 1) keeps glaciologists and climate scientists awake at night. The 120 kmwide glacier loses about 45 billion tonnes of ice each year, accounting for about 4% of global sea level rise [1]. If it melted completely, sea levels would climb 65 cm, and follow-on effects could lead to a 3 m increase [2]. But if some scientists' vision becomes reality, in 10–15 years construction crews will sail into the Amundsen Sea off Antarctica to begin building an 80 km long underwater curtain that will shield the glacier from the warm currents that are accelerating its decline [3].
基金The National Natural Science Foundation of China under contract Nos 52279080,42076171,42376164,and 42406159.
文摘Quantifying spatiotemporal variations in water levels and their responses to external drivers(e.g.,morphology,river discharge,and sea level)is critical for sustainable water resource management.However,simple methods for distinguishing the impacts of upstream river discharge,downstream sea level,and morphological changes on estuarine water levels remain limited.This study applied a revised triple linear regression model to reconstruct historical water levels(1965-2017)in the highly human-modified Zhujiang River Estuary(ZRE).The strong agreement between reconstructed and observed water levels(root mean square error<0.17 m;coefficient of determination>0.90)confirms the model reliability in quantifying drivers of water level variations.Results show morphological evolution as the dominant factor,causing an average water level decrease of 0.13 m,with declines increasing upstream from the estuary mouth.Sea level rise moderately elevated water levels by approximately 0.08 m on average.Reservoir regulation altered flow distribution and seasonal discharge patterns,weakening river discharge effects on downstream water levels in the lower West River,yet strengthening effects in the lower North River,averaging a 0.09 m water level decrease.These alterations further modified spatial water level slopes:reduced slopes in the lower West River primarily resulted from discharge changes,while morphological evolution dominated in the lower North River.Scenario simulations revealed significant water level responses to extreme events:an upstream discharge increase from 25000 m^(3)/s to 55000 m^(3)/s elevated upstream water levels by 3.47 m on average;relative sea level rise during storm surges from 1.50 m to 3.00 m increased downstream water levels by 1.34 m.These findings provide valuable guidance for flood prevention and water resource management in the ZRE and similarly modified estuaries worldwide.
文摘BackgroundIt's crucial to study the effect of changes in thresholds(T)and most comfortable levels(M)on behavioral measurements in young children using cochlear implants.This would help the clinician with the optimization and validation of programming parameters.ObjectiveThe study has attempted to describe the changes in behavioral responses with modification of T and M levels.MethodsTwenty-five participants in the age range 5 to 12 years using HR90K/HiFocus1J or HR90KAdvantage/HiFocus1J with Harmony speech processors participated in the study.A decrease in T levels,a rise in T levels,or a decrease in M levels in the everyday program were used to create experimental programs.Sound field thresholds and speech perception were measured at 50 dBHL for three experimental and everyday programs.ConclusionThe results indicated that only reductions of M levels resulted in significantly(p<0.01)poor aided thresholds and speech perception.On the other hand,variation in T levels did not have significant changes in either sound field thresholds or speech perception.The results highlight that M levels must be correctly established in order to prevent decreased speech perception and audibility.
基金the Ministerial Level Advanced Research Foundation(413040402)
文摘Hybrid level of detail （LOD） （HLOD） algorithm based on discrete LOD and continuous LOD is presented for real-time rendering of large-scale terrains. There are n HLOD models created off-line, which form a pyramid with n layers. Each of these models contains countless versions of the model at various levels of detail. When rendering, the corresponding models in some layer will be chosen. As the viewer＇s moves, either the continuous LOD algorithm will be applied to the selected models, or the visible models in another layer will be selected. An experiment on a triangular irregular network（TIN） terrain model was performed respectively using discrete LOD, continuous LOD and HLOD. The experimental results show that the HLOD algorithm exceeds the other two kinds of LOD in frame rate without reduction of terrain＇s fidelity.
基金supported by the National Key R&D Program of China(Grant No.2022YFC3005401)the National Natural Science Foundation of China(Grant No.52239009)。
文摘Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms.By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method and fuzzy entropy(FE)with the new and highly efficient Runge–Kuta optimizer(RUN),adaptive parameter optimization for the support vector machine(SVM)and radial basis function neural network(RBFNN)algorithms was achieved.Regression prediction was conducted on the two reconstructed sequences using SVM and RBFNN according to their respective features.This approach improved the accuracy and stability of predictions.In terms of accuracy,the combined model outperformed single models,with the determination coefficient,root mean square error,and mean absolute error values of 0.9975,0.2418 m,and 0.1616 m,respectively.In terms of stability,the model predicted more consistently in training and testing periods,with stable overall prediction accuracy and a better adaptive ability to complex datasets.The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels,leveraged the strength of each predictive method,compensated for their limitations,and clarified the impacts of environmental factors on reservoir water levels.
基金The Joint Research Project for Yangtze River Conservation,No.2022-LHYJ-02-0504-05-08Anhui Provincial Scientific Research Project for Universities,China No.2023AH050508。
文摘To explore water level variations and their dynamic influence on the water quality of Huayang Lakes,the water level from 1967 to 2023 and water quality from 2015 to 2023 were analyzed using the Mann–Kendall trend test,box plots,and violin plots.The results show a notable hydrological rhythm of water level alternation between dry and flood seasons in Huayang Lakes,with an average water level of 12.82 m and a monthly range of 11.21–17.24m.Since 2017,the water level of Huayang Rivers has shown a decreasing trend of–0.02 m/a.Total phosphorus(TP)has become the primary pollutant.The TP concentrations in Longgan Lake(the largest lake)during the dry,rising,flood,and retreating seasons from 2015 to 2023were 0.083,0.061,0.050,and 0.059 mg/L,respectively.The effect of water level on TP was mainly observed during the low-water period.When the water level in the dry season rose to 12.25 and 13.00 m,the percentage of TP exceeding 0.1 mg/L in Longgan Lake decreased to 55.8%and 33.3%,respectively.During the dry season,wind and wave disturbances caused the release of endogenous phosphorus in Huayang Lakes.This led to drastic fluctuations in TP concentration,reducing the correlation between water level and TP.When external control is limited,the water level during the dry season should be maintained between 12.25 and 13.0 m.Additionally,it is necessary to accelerate the restoration of submerged macrophyte species(such as Hydrilla verticillata and Vallisneria natans)in the Huayang Rivers.
基金supported by the Beijing Natural Science Foundation(Grant No.L223013)。
文摘For the diagnostics and health management of lithium-ion batteries,numerous models have been developed to understand their degradation characteristics.These models typically fall into two categories:data-driven models and physical models,each offering unique advantages but also facing limitations.Physics-informed neural networks(PINNs)provide a robust framework to integrate data-driven models with physical principles,ensuring consistency with underlying physics while enabling generalization across diverse operational conditions.This study introduces a PINN-based approach to reconstruct open circuit voltage(OCV)curves and estimate key ageing parameters at both the cell and electrode levels.These parameters include available capacity,electrode capacities,and lithium inventory capacity.The proposed method integrates OCV reconstruction models as functional components into convolutional neural networks(CNNs)and is validated using a public dataset.The results reveal that the estimated ageing parameters closely align with those obtained through offline OCV tests,with errors in reconstructed OCV curves remaining within 15 mV.This demonstrates the ability of the method to deliver fast and accurate degradation diagnostics at the electrode level,advancing the potential for precise and efficient battery health management.
基金the Science and Technology Innovation Project of the Laoshan Laboratory (No. LSKJ202203402)the Major Research Project on the Tethys Geodynamic System from the National Science Foundation of China (No. 92055204)。
文摘Fluvial systems play a crucial role in coastal and riverine ecosystems, making it essential to understand their responses to sea level changes for preserving biodiversity and managing natural resources. The evolution of the modern Indus River Delta offers a rare opportunity to study the interplay between sea level fluctuations, tectonism, sediment supply, and the corresponding fluvial responses. This study employs the ‘SedSim' stratigraphic forward model to simulate the delta's evolution from 200 kyr to the next5 kyr, drawing on data from field observations, Landsat imagery, digital elevation models, and previous studies. The model consists of 205 layers, each representing a 1-kyr time step, covering the last two glacial-interglacial cycles. Between 200 kyr and 130 kyr, during a lowstand period, sedimentation on the delta plain continued due to partial flow from the Indus River. During the last interglacial(130–60 kyr), rising sea levels led to peak sediment deposition, characteristic of a highstand phase. From 60 kyr to 18 kyr, sea levels dropped to their lowest during the Last Glacial Maximum(LGM), resulting in extensive erosion and minimal deposition on the delta plain. From 18 kyr to the present, rapidly rising sea levels, coupled with intensified monsoon activity, increased sedimentation rates and triggered avulsion and aggradation processes. The model accurately predicted depositional thickness across the delta plain, indicating a maximum of ca. 200 m at the shoreline platform, ca. 175 m in the northeastern delta, and ca. 100 m in the central delta. The study underscores the delta's vulnerability to future sea level rise, which–at a projected rate of 1 m/kyr–could significantly influence the densely populated, low-lying delta plain. These findings offer valuable insights into the geomorphic evolution of the Indus Delta and emphasize the socioeconomic implications of sea level change, underscoring the importance of proactive management and adaptation strategies.
