Based on the Pathfinder sea surface temperature(PFSST),the surface axis and its pattern of the Yellow Sea Warm Current(YSWC) are discussed.A structure of double-warm-tongue is found in February and it varies in differ...Based on the Pathfinder sea surface temperature(PFSST),the surface axis and its pattern of the Yellow Sea Warm Current(YSWC) are discussed.A structure of double-warm-tongue is found in February and it varies in different years.Two indexes are calculated to represent the westward shift(WSI) and northward extension(NEI) of the warm water in the Yellow Sea(YS).Wavelet analysis illustrates that the WSI and NEI have prominent periods of 3-6 years and 3-4 years,respectively.The Empirical Orthogonal Function(EOF) decomposition is applied to the winter wind stress curl and the Kuroshio Current(KC) transport,which are believed to play important roles in forcing the variability of the YSWC surface axis.Statistics shows that the WSI is significantly related with the second EOF mode of the wind stress curl in February,which may force the YSWC surface axis moving westward and maintaining the double warm tongues because of its opposite curl in the YSWC domain.The first EOF mode of wind stress curl in January is propitious for inducing the warm tongue in the YS to advance more northward.Hence,the wind stress curls both in January and in February could force variations of the YSWC surface axis;however,the effect of the January wind stress curl is relatively weaker than that of the February.The relationship between the NEI and the KC transport is remarkable,and it seems that the stronger KC supplies more power to push the YSWC northward against the southward wind.展开更多
The South China Sea warm pool interacts vigorously with the summer monsoon which is active in the region. However, there has not been a definition concerning the former warm pool which is as specific as that for the l...The South China Sea warm pool interacts vigorously with the summer monsoon which is active in the region. However, there has not been a definition concerning the former warm pool which is as specific as that for the latter. The seasonal and inter-annual variability of the South China Sea warm pool and its relations to the South China Sea monsoon onset were analyzed using Levitus and NCEP/NCAR OISST data. The results show that, the seasonal variability of the South China Sea warm pool is obvious, which is weak in winter, develops rapidly in spring, becomes strong and extensive in summer and early autumn, and quickly decays from mid-autumn. The South China Sea warm pool is 55 m in thickness in the strongest period and its axis is oriented from southwest to northeast with the main section locating along the western offshore steep slope of northern Kalimantan-Palawan Island. For the warm pools in the South China Sea, west Pacific and Indian Ocean, the oscillation, which is within the same large scale air-sea coupling system, is periodic around 5 years. There are additional oscillations of about 2.5 years and simultaneous inter-annual variations for the latter two warm pools. The intensity of the South China Sea warm pool varies by a lag of about 5 months as compared to the west Pacific one. The result also indicates that the inter-annual variation of the intensity index is closely related with the onset time of the South China Sea monsoon. When the former is persistently warmer (colder) in preceding winter and spring, the monsoon in the South China Sea usually sets in on a later (earlier) date in early summer. The relation is associated with the activity of the high pressure over the sea in early summer. An oceanic background is given for the prediction of the South China Sea summer monsoon, though the mechanism through which the warm pool and eventually the monsoon are affected remains unclear.展开更多
The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea ...The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea Surface Temperature (SST) indices [Indian Ocean Dipole (IOD) and El-Ni?o Southern Oscillation (ENSO) at NINO3.4 region] from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The data covered a period of 40 years from1981 to 2020. The methods of cumulative of daily mean rainfall, percentage of onset date departure (PODD), Mann-Kendall (MK) trend test, student t-test, and correlation were applied in the analysis. The results showed that early onset with dry spell (WDS) consideration frequently occurs in Uganda between the first and second dekads of September, while late rainfall onset WDS occurs in the first and second dekads of December over central and Northern Kenya as well as in the Northeastern highlands, parts of the northern coast and unimodal regions in Tanzania. Rainfall onset with no dry spell (WnDS) portrayed an average of 10 days before the occurrence of true onset WDS, with maximum onset departure days (ODD) above 30 days across the Rift Valley area in Kenya and the Northeastern highlands in Tanzania. The high chance of minimum ODD is seen over entire Uganda and the area around Lake Victoria. However, few regions, such as Nakuru (Kenya) Gulu and Kibale (Uganda), and Gitega (Burundi), revealed a slight positive linear trend while others showed negative trend. Significant positive patterns for correlation between onset WDS and SST indices (IOD and NINO 3.4) were discovered in Northern and Northeastern Kenya, as well as areas along the Indian Ocean (over Tanzania’s Northern Coast). Inter-annual relationship between onset dates WDS and IOD (NINO3.4) indices exhibits a high correlation coefficient r = 0.23 (r = 0.48) in Uganda and r = 0.44 (r = 0.36) in Kenya. On the other hand, a negative correlation was revealed over Burundi and Tanzania (over a unimodal region). A high percentage of PODD was observed, ranging from 40% to 70% over the Rift Valley in Kenya and at the Northeastern highlands in Tanzania. However, a strong PODD above 70% was observed over Tanga and the Northern Pwani Region in Tanzania. These findings will help farmers to understand the appropriate time for crop planting, as well as help other socio-economic activities that strongly depend on rainfall.展开更多
A time series dataset spanning 39 years(1981-2018) on red tide events in Zhejiang coastal waters was used to study the characteristics of inter-annual spatial and temporal variations. A distinct inter-annual pattern c...A time series dataset spanning 39 years(1981-2018) on red tide events in Zhejiang coastal waters was used to study the characteristics of inter-annual spatial and temporal variations. A distinct inter-annual pattern characterized by low frequency, explosive growth and fluctuating decline stages was found over the studied time scale. Most red tide events occurred in parallel to the bathymetric contour, and 95.4% were located to the west of the 50 m isobath. Additionally, the high-incidence area of red tides is expanding southward. In this paper, local sea surface temperature(SST), mariculture area and secondary industry growth rate are introduced and identified as the main factors influencing the nutrient and hydrometeorological conditions. A multivariate nonlinear regression equation based on these factors was constructed, and the goodness of fit coefficient was 0.907. The causes of the annual variation and high-frequency area in the southward expansion were quantitatively analyzed based on the proposed regression model. Finally, the results indicated that 68.7% of the annual occurrence variation of red tide was due to the SST and mariculture area, which are the main impact factors;however,secondary industry growth could compensate for the nutrient deficiency caused by the sharp mariculture area reduction and decreased SST. The background nutrient level, which is elevated by coastal economic development, especially secondary industry, is the main determinant of the southward expansion. Although the trend of the southward expansion of high-frequency areas has not changed, the red tide frequency in coastal cities has decreased by half and remained at a stable level after 2010 due to substantial economic restructuring and environmental protection.展开更多
Based on rotational empirical orthogonal function(REOF),max-entropy and Mexico-hat wavelet transform techniques,monthly SSTA of the tropical Pacific,Atlantic and Indian Oceans (32.5°S—32. 5°N)is investigate...Based on rotational empirical orthogonal function(REOF),max-entropy and Mexico-hat wavelet transform techniques,monthly SSTA of the tropical Pacific,Atlantic and Indian Oceans (32.5°S—32. 5°N)is investigated.It is shown that the inter-decadal variability and inter-annual variability take on global scale,and there exist their own significance areas.Moreover,through the total time series,the intensity of the variabilities is time-variable.And in fact,both the variabilities are usually coexistent.In significance areas of each of the variabilities,another variability is sometimes quite strong.展开更多
Climate variability has become a decisive factor for the crop yields in Sub-Saharan African countries. Inter-annual variability in rainfall has been the key climatic element that determines the success of agriculture ...Climate variability has become a decisive factor for the crop yields in Sub-Saharan African countries. Inter-annual variability in rainfall has been the key climatic element that determines the success of agriculture in this region.From an analysis of recent rainfall conditions in West Africa,FAO(2001) concluded that a long-term change in rainfall has occurred in the semi-arid and sub-humid zones of West Africa.Thus,this study aims at assessing the vulnerability of crop yields to inter-annual variability in rainfall in sub-Saharan African countries taking Nigeria as a case study.A time series of the averaged value of the 12-Month Weighted Anomaly Standardized Precipita-展开更多
In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random vari...In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.展开更多
In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence...In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence,asymptotic behavior and blow-up of solutions with initial energy J(u_(0))≤d.Moreover,we estimate the upper bound of the blow-up time for J(u_(0))≤0.展开更多
In this article,we prove the boundedness for commutators of fractional Hardy and Hardy-Littlewood-Pólya operators on grand p-adic variable Herz spaces,where the symbols of the commutators belong to Lipschitz spaces.
This study investigates the reduction in polarization measurement accuracy caused by varying in-cident angles in a liquid crystal variable retarder(LCVR).The phase delay characteristics of the LCVR were examined,with ...This study investigates the reduction in polarization measurement accuracy caused by varying in-cident angles in a liquid crystal variable retarder(LCVR).The phase delay characteristics of the LCVR were examined,with particular emphasis on the influence of different two-dimensional incident angles on phase delay behavior.Building upon the calibration of phase delay under normal incidence,a phase delay calibra-tion model was developed to account for variations in incident angle and driving voltage.A mathematical re-lationship was established between phase delay and the azimuth angle(α)and pitch angle(β).Experimental validation was conducted under three conditions:α=20°,β=0°;α=0°,β=20°;and an arbitrary angle whereα=5°,β=15°.The results demonstrated that the maximum average deviation between theoretical pre-dictions and experimental measurements did not exceed 0.059 rad.The proposed calibration method proved to be both accurate and practical.This approach offers robust support for LCVR parameter calibration and performance optimization in optical systems,particularly in polarization imaging applications.展开更多
Indian Summer Monsoon Rainfall （ISMR） exhibits a prominent inter-annual variability known as troposphere biennial oscillation.A season of deficient June to September monsoon rainfall in India is followed by warm sea...Indian Summer Monsoon Rainfall （ISMR） exhibits a prominent inter-annual variability known as troposphere biennial oscillation.A season of deficient June to September monsoon rainfall in India is followed by warm sea surface temperature （SST） anomalies over the tropical Indian Ocean and cold SST anomalies over the westem Pacific Ocean.These anomalies persist until the following monsoon,which yields normal or excessive rainfall.Monsoon rainfall in India has shown decadal variability in the form of 30 year epochs of alternately occurring frequent and infrequent drought monsoons since 1841,when rainfall measurements began in India.Decadal oscillations of monsoon rainfall and the well known decadal oscillations in SSTs of the Atlantic and Pacific oceans have the same period of approximately 60 years and nearly the same temporal phase.In both of these variabilities,anomalies in monsoon heat source,such as deep convection,and middle latitude westerlies of the upper troposphere over south Asia have prominent roles.展开更多
Background:Studies have shown that heart rate variability(HRV)is a predictor of the prognosis of cardiovascular diseases.Contact heartbeat monitoring equipment is widely used,especially in hospitals,and benefits from ...Background:Studies have shown that heart rate variability(HRV)is a predictor of the prognosis of cardiovascular diseases.Contact heartbeat monitoring equipment is widely used,especially in hospitals,and benefits from the rapidity and accuracy of the detection of physiological health indicators.However,long-term contact with equipment has many adverse effects.The purpose of this study was to improve the accuracy of HRV detection via noncontact equipment,thus enabling HRV to be assessed in various scenarios.Methods:A novel deep learning approach was proposed for measuring heartbeats through camera videos.First,we performed facial segmentation and divided the face into 16 grid cells with different light balance scores.After the trend is filtered by the Hamming window,a transformer-based neural network is used to further filter the signal.Finally,heart rate(HR)and HRV are estimated.Results:We used 1 million synthetic data points for pretraining and a public dataset in combination with a dataset that we constructed for task training.The final results were obtained on a test dataset that we constructed.The accuracy for HR with a low light balance score(0.867-0.983)was greater than that with a high score(0.667-0.750).Our method had higher accuracy in estimating HR than traditional filtering methods(0.167-0.417)and state-of-the-art neural network filtering methods(0.783-0.917)did.The root mean square error of the HRV from the time domain was the lowest,and the correlation index score was the highest for the HRV from the frequency domain estimated by our method compared with those estimated by two neural networks.Conclusions:Light balance,large sample training,and two-stage training can improve the accuracy of HRV estimation.展开更多
The Moroccan populations of Alnus glutinosa(L.)Gaertn.(Betulaceae)They are located at the southern limit of the species'distribution and are represented by tetraploid cytotypes.Assessing phenotypic variability in ...The Moroccan populations of Alnus glutinosa(L.)Gaertn.(Betulaceae)They are located at the southern limit of the species'distribution and are represented by tetraploid cytotypes.Assessing phenotypic variability in reproductive traits is crucial for understanding the persistence,evolution,and range dynamics of plant populations.However,no previous studies have analyzed the relative importance of variability in explaining inter-or intra-population differences in reproductive traits.To address this gap,we investigated phenotypic variation in reproductive organs by examining 10 traits in 3.600 male catkins,3.600 female catkins,and seeds from 12 populations across the Moroccan Rif Mountains.Our results highlighted the significance of inter-population variability.However,we found that the contribution of within-tree variation to total phenotypic variability was greater than that of both inter-and intra-population variation.Principal component analysis(PCA)revealed a phenotypic gradient among populations,primarily driven by female catkin size,though this gradient was not associated with geographic conditions.This finding was further supported by Mantel test results,which showed no correlation between phenotypic variability and population conditions.These findings have important implications for the genetic improvement,conservation,and resource management of Alnus glutinosa in the future.展开更多
Tree growth variability is a key determinant of forest stabilities.Previous studies have shown that recent climate change has increased variability in tree growth,while others have challenged this viewpoint,leading to...Tree growth variability is a key determinant of forest stabilities.Previous studies have shown that recent climate change has increased variability in tree growth,while others have challenged this viewpoint,leading to ongoing debate in this field.Moreover,gaps remain in understanding the climatic mechanisms driving increased tree growth variability,particularly for species simultaneously limited by multiple climate factors.In this study,we assessed the temporal trends in variability of Picea purpurea radial growth and its linkage with growth-climate sensitivity utilizing dendrochronological methods.Our results revealed a significant increase in P.purpurea radial growth variability from 1960 to 2020,as indicated by continuous rises in the standard deviation,coefficient of variation,and mean sensitivity of tree-ring width indices.The increased frequency of extreme growth declines further supported this finding.Furthermore,moisture condition in July was identified as a key limiting factor of P.purpurea growth.Notably,the strengthening relationship between tree-ring width indices and vapor pressure deficit(VPD)suggests that the moisture sensitivity for P.purpurea growth has increased over the period 1960-2020.This enhanced sensitivity to VPD,whose interannual variability has also increased synchronously,may have contributed to the rise in P.purpurea growth variability.Additionally,the maximum temperature in May was positively correlated with P.purpurea growth;however,there is little evidence that this factor contributed to the observed increase in growth variability.These findings provide new insights into P.purpurea growth trends and improve our understanding of the potential future impacts of climate change on forest ecosystems.展开更多
As a vital food crop,rice is an important part of global food crops.Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy...As a vital food crop,rice is an important part of global food crops.Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy decisions related to rice.With the increasing application of satellite remote sensing technology in crop monitoring,remote sensing for rice cultivation has emerged as a novel approach,offering new perspectives for monitoring rice planting.This paper briefly outlined the current research and development status of satellite remote sensing for monitoring rice cultivation both at home and abroad.Foreign scholars have made innovations in data sources and methodologies for satellite remote sensing monitoring,and utilized multi-source satellite information and machine learning algorithms to enhance the accuracy of rice planting monitoring.Scholars in China have achieved significant results in the study of satellite remote sensing for monitoring rice cultivation.Their research and application in monitoring rice planting areas provide valuable references for agricultural production management.However,satellite remote sensing monitoring of rice still faces challenges such as low spatiotemporal resolution and difficulties related to cloud cover and data fusion,which require further in-depth investigation.Additionally,there are shortcomings in the accuracy of remote sensing monitoring for fragmented farmland plots and smallholder farming.To address these issues,future efforts should focus on developing multi-source heterogeneous data fusion analysis technologies and researching monitoring systems.These advancements are expected to enable high-precision large-scale acquisition of rice planting information,laying a foundation for future smart agriculture.展开更多
Thermal-mechanical damage and deformation at the interface between shotcrete linings and the surrounding rock of tunnels under high-temperature and variable-temperature conditions are critical to the safe construction...Thermal-mechanical damage and deformation at the interface between shotcrete linings and the surrounding rock of tunnels under high-temperature and variable-temperature conditions are critical to the safe construction and operation of tunnel engineering.This study investigated the thermo-mechanical damage behavior of the composite interface between alkali-resistant glass fiber-reinforced concrete(ARGFRC)and granite,focusing on a plateau railway tunnel.Laboratory triaxial tests,laser scanning,XRD analysis,numerical simulations,and theoretical analyses were employed to investigate how different initial curing temperatures and joint roughness coefficient(JRC)influence interfacial damage behavior.The results indicate that an increase in interface roughness exacerbates the structural damage at the interface.At a JRC of 19.9 and a temperature of 70℃,crack initiation in granite was notably restrained when the confining pressure rose from 7 MPa to 10 MPa.Roughness-induced stress distribution at the interface was notably altered,although this effect became less pronounced under high confining pressure conditions.Additionally,during high-temperature curing,thermal stress concentration at the tips of micro-convex protrusions on the granite surface induced microcracks in the adjacent ARGFRC matrix,followed by deformation.These findings provide practical guidelines for designing concrete support systems to ensure tunnel structural safety in high-altitude regions with harsh thermal environments.展开更多
Quantile regression(QR)has become an important tool to measure dependence of response variable's quantiles on a number of predictors for heterogeneous data,especially heavy-tailed data and outliers.However,it is q...Quantile regression(QR)has become an important tool to measure dependence of response variable's quantiles on a number of predictors for heterogeneous data,especially heavy-tailed data and outliers.However,it is quite challenging to make statistical inference on distributed high-dimensional QR with missing data due to the distributed nature,sparsity and missingness of data and nondifferentiable quantile loss function.To overcome the challenge,this paper develops a communicationefficient method to select variables and estimate parameters by utilizing a smooth function to approximate the non-differentiable quantile loss function and incorporating the idea of the inverse probability weighting and the penalty function.The proposed approach has three merits.First,it is both computationally and communicationally efficient because only the first-and second-order information of the approximate objective function are communicated at each iteration.Second,the proposed estimators possess the oracle property after a limited number of iterations without constraint on the number of machines.Third,the proposed method simultaneously selects variables and estimates parameters within a distributed framework,ensuring robustness to the specified response probability or propensity score function of the missing data mechanism.Simulation studies and a real example are used to illustrate the effectiveness of the proposed methodologies.展开更多
In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zer...In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zero-points distribution of the solutions and separate the single valued analytic branch of the solutions with square roots,then convert the problem to a Riemann boundary value problem in variable exponent Lebesgue spaces and discuss the singularity of solutions at individual zeros belonging to curve.We consider two types of cases those where the coefficient is Hölder and those where it is piecewise Hölder.Then we solve the Hilbert boundary value problem with square roots in variable exponent Lebesgue spaces.By discussing the distribution of the odd-order zero-points for solutions and the method of symmetric extension,we convert the Hilbert problem to a Riemann boundary value problem.The equivalence of the transformation is discussed.Finally,we get the solvable conditions and the direct expressions of the solutions in variable exponent Lebesgue spaces.展开更多
Cerebral ischemia restricts cerebral blood flow(CBF),leading to unstable hemodynamics.Past studies of ischemia mainly focused on cortical CBF reduction.However,its impact on hemodynamic changes,especially temporal var...Cerebral ischemia restricts cerebral blood flow(CBF),leading to unstable hemodynamics.Past studies of ischemia mainly focused on cortical CBF reduction.However,its impact on hemodynamic changes,especially temporal varying characteristics,remains poorly understood.Here,we collected cortical resting-state CBF in rats with left carotid artery blockage during occlusion–reperfusion,and measured the temporal variability and changes in laterality using a novel state-space method.This method was also applied to stroke EEG datasets to validate its effectiveness.After arterial occlusion,the left marginal motor,sensory,auditory,and visual cortices exhibited severe temporal variability impairments.The laterality analysis indicated that affected left regions showed inferior unilateral mean,inter-hemispheric transition probability,time fraction,and laterality duration,while the right side had a higher laterality time fraction and duration.These impairments recovered partially following blood flow restoration.Besides,the ischemic state-space metrics were positively correlated with the pre-occlusion baseline appearance.Stroke patients exhibited impaired temporal variability in the affected ischemic hemisphere.The state-space analysis revealed damaged CBF temporal variability during cerebral ischemia and predicted baseline-ischemia connections.展开更多
Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial fe...Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial features.To address the limitations,the paper proposes a TimeXer-based numerical forecast correction model optimized by an exogenous-variable attention mechanism.The model treats target forecast values as internal variables,and incorporates historical temporal-spatial data and seven-day numerical forecast results from traditional models as external variables based on the embedding strategy of TimeXer.Using a self-attention structure,the model captures correlations between exogenous variables and target sequences,explores intrinsic multi-dimensional relationships,and subsequently corrects endogenous variables with the mined exogenous features.The model’s performance is evaluated using metrics including MSE(Mean Squared Error),MAE(Mean Absolute Error),RMSE(Root Mean Square Error),MAPE(Mean Absolute Percentage Error),MSPE(Mean Square Percentage Error),and computational time,with TimeXer and PatchTST models serving as benchmarks.Experiment results show that the proposed model achieves lower errors and higher correction accuracy for both one-day and seven-day forecasts.展开更多
基金Supported by the National Basic Research Program of China (973 Program) (No 2005C B422308)the National High-tech Research and Development Program (863 Program) (No 2006AA09Z149)the China International Science and Technology Cooperation Program (No2006DFB21250)
文摘Based on the Pathfinder sea surface temperature(PFSST),the surface axis and its pattern of the Yellow Sea Warm Current(YSWC) are discussed.A structure of double-warm-tongue is found in February and it varies in different years.Two indexes are calculated to represent the westward shift(WSI) and northward extension(NEI) of the warm water in the Yellow Sea(YS).Wavelet analysis illustrates that the WSI and NEI have prominent periods of 3-6 years and 3-4 years,respectively.The Empirical Orthogonal Function(EOF) decomposition is applied to the winter wind stress curl and the Kuroshio Current(KC) transport,which are believed to play important roles in forcing the variability of the YSWC surface axis.Statistics shows that the WSI is significantly related with the second EOF mode of the wind stress curl in February,which may force the YSWC surface axis moving westward and maintaining the double warm tongues because of its opposite curl in the YSWC domain.The first EOF mode of wind stress curl in January is propitious for inducing the warm tongue in the YS to advance more northward.Hence,the wind stress curls both in January and in February could force variations of the YSWC surface axis;however,the effect of the January wind stress curl is relatively weaker than that of the February.The relationship between the NEI and the KC transport is remarkable,and it seems that the stronger KC supplies more power to push the YSWC northward against the southward wind.
基金A comprehensive study on the activities of the South China Sea summer monsoon and its influence"- a major project of the Chines
文摘The South China Sea warm pool interacts vigorously with the summer monsoon which is active in the region. However, there has not been a definition concerning the former warm pool which is as specific as that for the latter. The seasonal and inter-annual variability of the South China Sea warm pool and its relations to the South China Sea monsoon onset were analyzed using Levitus and NCEP/NCAR OISST data. The results show that, the seasonal variability of the South China Sea warm pool is obvious, which is weak in winter, develops rapidly in spring, becomes strong and extensive in summer and early autumn, and quickly decays from mid-autumn. The South China Sea warm pool is 55 m in thickness in the strongest period and its axis is oriented from southwest to northeast with the main section locating along the western offshore steep slope of northern Kalimantan-Palawan Island. For the warm pools in the South China Sea, west Pacific and Indian Ocean, the oscillation, which is within the same large scale air-sea coupling system, is periodic around 5 years. There are additional oscillations of about 2.5 years and simultaneous inter-annual variations for the latter two warm pools. The intensity of the South China Sea warm pool varies by a lag of about 5 months as compared to the west Pacific one. The result also indicates that the inter-annual variation of the intensity index is closely related with the onset time of the South China Sea monsoon. When the former is persistently warmer (colder) in preceding winter and spring, the monsoon in the South China Sea usually sets in on a later (earlier) date in early summer. The relation is associated with the activity of the high pressure over the sea in early summer. An oceanic background is given for the prediction of the South China Sea summer monsoon, though the mechanism through which the warm pool and eventually the monsoon are affected remains unclear.
文摘The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea Surface Temperature (SST) indices [Indian Ocean Dipole (IOD) and El-Ni?o Southern Oscillation (ENSO) at NINO3.4 region] from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The data covered a period of 40 years from1981 to 2020. The methods of cumulative of daily mean rainfall, percentage of onset date departure (PODD), Mann-Kendall (MK) trend test, student t-test, and correlation were applied in the analysis. The results showed that early onset with dry spell (WDS) consideration frequently occurs in Uganda between the first and second dekads of September, while late rainfall onset WDS occurs in the first and second dekads of December over central and Northern Kenya as well as in the Northeastern highlands, parts of the northern coast and unimodal regions in Tanzania. Rainfall onset with no dry spell (WnDS) portrayed an average of 10 days before the occurrence of true onset WDS, with maximum onset departure days (ODD) above 30 days across the Rift Valley area in Kenya and the Northeastern highlands in Tanzania. The high chance of minimum ODD is seen over entire Uganda and the area around Lake Victoria. However, few regions, such as Nakuru (Kenya) Gulu and Kibale (Uganda), and Gitega (Burundi), revealed a slight positive linear trend while others showed negative trend. Significant positive patterns for correlation between onset WDS and SST indices (IOD and NINO 3.4) were discovered in Northern and Northeastern Kenya, as well as areas along the Indian Ocean (over Tanzania’s Northern Coast). Inter-annual relationship between onset dates WDS and IOD (NINO3.4) indices exhibits a high correlation coefficient r = 0.23 (r = 0.48) in Uganda and r = 0.44 (r = 0.36) in Kenya. On the other hand, a negative correlation was revealed over Burundi and Tanzania (over a unimodal region). A high percentage of PODD was observed, ranging from 40% to 70% over the Rift Valley in Kenya and at the Northeastern highlands in Tanzania. However, a strong PODD above 70% was observed over Tanga and the Northern Pwani Region in Tanzania. These findings will help farmers to understand the appropriate time for crop planting, as well as help other socio-economic activities that strongly depend on rainfall.
基金The National Basic Research Program of China under contract No. 2016YFC1401900the Open Research Funds of Key Laboratory of Marine Ecological Monitoring and Restoration Technologies under contract No. MATHAB201703。
文摘A time series dataset spanning 39 years(1981-2018) on red tide events in Zhejiang coastal waters was used to study the characteristics of inter-annual spatial and temporal variations. A distinct inter-annual pattern characterized by low frequency, explosive growth and fluctuating decline stages was found over the studied time scale. Most red tide events occurred in parallel to the bathymetric contour, and 95.4% were located to the west of the 50 m isobath. Additionally, the high-incidence area of red tides is expanding southward. In this paper, local sea surface temperature(SST), mariculture area and secondary industry growth rate are introduced and identified as the main factors influencing the nutrient and hydrometeorological conditions. A multivariate nonlinear regression equation based on these factors was constructed, and the goodness of fit coefficient was 0.907. The causes of the annual variation and high-frequency area in the southward expansion were quantitatively analyzed based on the proposed regression model. Finally, the results indicated that 68.7% of the annual occurrence variation of red tide was due to the SST and mariculture area, which are the main impact factors;however,secondary industry growth could compensate for the nutrient deficiency caused by the sharp mariculture area reduction and decreased SST. The background nutrient level, which is elevated by coastal economic development, especially secondary industry, is the main determinant of the southward expansion. Although the trend of the southward expansion of high-frequency areas has not changed, the red tide frequency in coastal cities has decreased by half and remained at a stable level after 2010 due to substantial economic restructuring and environmental protection.
基金National Key Project-Studies on Short-Term Climate Prediction Systems in China
文摘Based on rotational empirical orthogonal function(REOF),max-entropy and Mexico-hat wavelet transform techniques,monthly SSTA of the tropical Pacific,Atlantic and Indian Oceans (32.5°S—32. 5°N)is investigated.It is shown that the inter-decadal variability and inter-annual variability take on global scale,and there exist their own significance areas.Moreover,through the total time series,the intensity of the variabilities is time-variable.And in fact,both the variabilities are usually coexistent.In significance areas of each of the variabilities,another variability is sometimes quite strong.
文摘Climate variability has become a decisive factor for the crop yields in Sub-Saharan African countries. Inter-annual variability in rainfall has been the key climatic element that determines the success of agriculture in this region.From an analysis of recent rainfall conditions in West Africa,FAO(2001) concluded that a long-term change in rainfall has occurred in the semi-arid and sub-humid zones of West Africa.Thus,this study aims at assessing the vulnerability of crop yields to inter-annual variability in rainfall in sub-Saharan African countries taking Nigeria as a case study.A time series of the averaged value of the 12-Month Weighted Anomaly Standardized Precipita-
文摘In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.
基金Supported by NSFC(No.12101482)the Natural Science Foundation of Shaanxi Province,China(No.2018JQ1052)。
文摘In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence,asymptotic behavior and blow-up of solutions with initial energy J(u_(0))≤d.Moreover,we estimate the upper bound of the blow-up time for J(u_(0))≤0.
基金Supported by Chizhou University High Level Talent Research Start up Fund (No.CZ2025YJRC52)。
文摘In this article,we prove the boundedness for commutators of fractional Hardy and Hardy-Littlewood-Pólya operators on grand p-adic variable Herz spaces,where the symbols of the commutators belong to Lipschitz spaces.
文摘This study investigates the reduction in polarization measurement accuracy caused by varying in-cident angles in a liquid crystal variable retarder(LCVR).The phase delay characteristics of the LCVR were examined,with particular emphasis on the influence of different two-dimensional incident angles on phase delay behavior.Building upon the calibration of phase delay under normal incidence,a phase delay calibra-tion model was developed to account for variations in incident angle and driving voltage.A mathematical re-lationship was established between phase delay and the azimuth angle(α)and pitch angle(β).Experimental validation was conducted under three conditions:α=20°,β=0°;α=0°,β=20°;and an arbitrary angle whereα=5°,β=15°.The results demonstrated that the maximum average deviation between theoretical pre-dictions and experimental measurements did not exceed 0.059 rad.The proposed calibration method proved to be both accurate and practical.This approach offers robust support for LCVR parameter calibration and performance optimization in optical systems,particularly in polarization imaging applications.
基金the European Commission(Project INDO-MARECLIM)the Norwegian Research Council(Project INDIA-CLIM)for providing financial support for this study
文摘Indian Summer Monsoon Rainfall （ISMR） exhibits a prominent inter-annual variability known as troposphere biennial oscillation.A season of deficient June to September monsoon rainfall in India is followed by warm sea surface temperature （SST） anomalies over the tropical Indian Ocean and cold SST anomalies over the westem Pacific Ocean.These anomalies persist until the following monsoon,which yields normal or excessive rainfall.Monsoon rainfall in India has shown decadal variability in the form of 30 year epochs of alternately occurring frequent and infrequent drought monsoons since 1841,when rainfall measurements began in India.Decadal oscillations of monsoon rainfall and the well known decadal oscillations in SSTs of the Atlantic and Pacific oceans have the same period of approximately 60 years and nearly the same temporal phase.In both of these variabilities,anomalies in monsoon heat source,such as deep convection,and middle latitude westerlies of the upper troposphere over south Asia have prominent roles.
基金National Natural Science Foundation of China,Grant/Award Number:72204169Department of Science and Technology of Sichuan Province,Grant/Award Number:2021YFS0393。
文摘Background:Studies have shown that heart rate variability(HRV)is a predictor of the prognosis of cardiovascular diseases.Contact heartbeat monitoring equipment is widely used,especially in hospitals,and benefits from the rapidity and accuracy of the detection of physiological health indicators.However,long-term contact with equipment has many adverse effects.The purpose of this study was to improve the accuracy of HRV detection via noncontact equipment,thus enabling HRV to be assessed in various scenarios.Methods:A novel deep learning approach was proposed for measuring heartbeats through camera videos.First,we performed facial segmentation and divided the face into 16 grid cells with different light balance scores.After the trend is filtered by the Hamming window,a transformer-based neural network is used to further filter the signal.Finally,heart rate(HR)and HRV are estimated.Results:We used 1 million synthetic data points for pretraining and a public dataset in combination with a dataset that we constructed for task training.The final results were obtained on a test dataset that we constructed.The accuracy for HR with a low light balance score(0.867-0.983)was greater than that with a high score(0.667-0.750).Our method had higher accuracy in estimating HR than traditional filtering methods(0.167-0.417)and state-of-the-art neural network filtering methods(0.783-0.917)did.The root mean square error of the HRV from the time domain was the lowest,and the correlation index score was the highest for the HRV from the frequency domain estimated by our method compared with those estimated by two neural networks.Conclusions:Light balance,large sample training,and two-stage training can improve the accuracy of HRV estimation.
文摘The Moroccan populations of Alnus glutinosa(L.)Gaertn.(Betulaceae)They are located at the southern limit of the species'distribution and are represented by tetraploid cytotypes.Assessing phenotypic variability in reproductive traits is crucial for understanding the persistence,evolution,and range dynamics of plant populations.However,no previous studies have analyzed the relative importance of variability in explaining inter-or intra-population differences in reproductive traits.To address this gap,we investigated phenotypic variation in reproductive organs by examining 10 traits in 3.600 male catkins,3.600 female catkins,and seeds from 12 populations across the Moroccan Rif Mountains.Our results highlighted the significance of inter-population variability.However,we found that the contribution of within-tree variation to total phenotypic variability was greater than that of both inter-and intra-population variation.Principal component analysis(PCA)revealed a phenotypic gradient among populations,primarily driven by female catkin size,though this gradient was not associated with geographic conditions.This finding was further supported by Mantel test results,which showed no correlation between phenotypic variability and population conditions.These findings have important implications for the genetic improvement,conservation,and resource management of Alnus glutinosa in the future.
基金funded by the Science and Technology Program of Gansu Province(25JRRA487)the National Natural Science Foundation of China(42101072)the Key Research and Development Program of Gansu Province(22YF7FA029).
文摘Tree growth variability is a key determinant of forest stabilities.Previous studies have shown that recent climate change has increased variability in tree growth,while others have challenged this viewpoint,leading to ongoing debate in this field.Moreover,gaps remain in understanding the climatic mechanisms driving increased tree growth variability,particularly for species simultaneously limited by multiple climate factors.In this study,we assessed the temporal trends in variability of Picea purpurea radial growth and its linkage with growth-climate sensitivity utilizing dendrochronological methods.Our results revealed a significant increase in P.purpurea radial growth variability from 1960 to 2020,as indicated by continuous rises in the standard deviation,coefficient of variation,and mean sensitivity of tree-ring width indices.The increased frequency of extreme growth declines further supported this finding.Furthermore,moisture condition in July was identified as a key limiting factor of P.purpurea growth.Notably,the strengthening relationship between tree-ring width indices and vapor pressure deficit(VPD)suggests that the moisture sensitivity for P.purpurea growth has increased over the period 1960-2020.This enhanced sensitivity to VPD,whose interannual variability has also increased synchronously,may have contributed to the rise in P.purpurea growth variability.Additionally,the maximum temperature in May was positively correlated with P.purpurea growth;however,there is little evidence that this factor contributed to the observed increase in growth variability.These findings provide new insights into P.purpurea growth trends and improve our understanding of the potential future impacts of climate change on forest ecosystems.
基金Supported by Natural Science Foundation General Project of Heilongjiang Province(C2018050).
文摘As a vital food crop,rice is an important part of global food crops.Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy decisions related to rice.With the increasing application of satellite remote sensing technology in crop monitoring,remote sensing for rice cultivation has emerged as a novel approach,offering new perspectives for monitoring rice planting.This paper briefly outlined the current research and development status of satellite remote sensing for monitoring rice cultivation both at home and abroad.Foreign scholars have made innovations in data sources and methodologies for satellite remote sensing monitoring,and utilized multi-source satellite information and machine learning algorithms to enhance the accuracy of rice planting monitoring.Scholars in China have achieved significant results in the study of satellite remote sensing for monitoring rice cultivation.Their research and application in monitoring rice planting areas provide valuable references for agricultural production management.However,satellite remote sensing monitoring of rice still faces challenges such as low spatiotemporal resolution and difficulties related to cloud cover and data fusion,which require further in-depth investigation.Additionally,there are shortcomings in the accuracy of remote sensing monitoring for fragmented farmland plots and smallholder farming.To address these issues,future efforts should focus on developing multi-source heterogeneous data fusion analysis technologies and researching monitoring systems.These advancements are expected to enable high-precision large-scale acquisition of rice planting information,laying a foundation for future smart agriculture.
基金funded by the National Natural Science Foundation of China(Nos.52209130 and 52379100)Shandong Provincial Natural Science Foundation(No.ZR2024ME112).
文摘Thermal-mechanical damage and deformation at the interface between shotcrete linings and the surrounding rock of tunnels under high-temperature and variable-temperature conditions are critical to the safe construction and operation of tunnel engineering.This study investigated the thermo-mechanical damage behavior of the composite interface between alkali-resistant glass fiber-reinforced concrete(ARGFRC)and granite,focusing on a plateau railway tunnel.Laboratory triaxial tests,laser scanning,XRD analysis,numerical simulations,and theoretical analyses were employed to investigate how different initial curing temperatures and joint roughness coefficient(JRC)influence interfacial damage behavior.The results indicate that an increase in interface roughness exacerbates the structural damage at the interface.At a JRC of 19.9 and a temperature of 70℃,crack initiation in granite was notably restrained when the confining pressure rose from 7 MPa to 10 MPa.Roughness-induced stress distribution at the interface was notably altered,although this effect became less pronounced under high confining pressure conditions.Additionally,during high-temperature curing,thermal stress concentration at the tips of micro-convex protrusions on the granite surface induced microcracks in the adjacent ARGFRC matrix,followed by deformation.These findings provide practical guidelines for designing concrete support systems to ensure tunnel structural safety in high-altitude regions with harsh thermal environments.
基金supported by the National Key R&D Program of China under Grant No.2022YFA1003701the Open Research Fund of Yunnan Key Laboratory of Statistical Modeling and Data Analysis,Yunnan University under Grant No.SMDAYB2023004。
文摘Quantile regression(QR)has become an important tool to measure dependence of response variable's quantiles on a number of predictors for heterogeneous data,especially heavy-tailed data and outliers.However,it is quite challenging to make statistical inference on distributed high-dimensional QR with missing data due to the distributed nature,sparsity and missingness of data and nondifferentiable quantile loss function.To overcome the challenge,this paper develops a communicationefficient method to select variables and estimate parameters by utilizing a smooth function to approximate the non-differentiable quantile loss function and incorporating the idea of the inverse probability weighting and the penalty function.The proposed approach has three merits.First,it is both computationally and communicationally efficient because only the first-and second-order information of the approximate objective function are communicated at each iteration.Second,the proposed estimators possess the oracle property after a limited number of iterations without constraint on the number of machines.Third,the proposed method simultaneously selects variables and estimates parameters within a distributed framework,ensuring robustness to the specified response probability or propensity score function of the missing data mechanism.Simulation studies and a real example are used to illustrate the effectiveness of the proposed methodologies.
基金supported by the National Natural Science Foundation of China(11601525)the Natural Science Foundation of Hunan Province(2024JJ5412),the Changsha Municipal Natural Science Foundation(kq2402193).
文摘In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zero-points distribution of the solutions and separate the single valued analytic branch of the solutions with square roots,then convert the problem to a Riemann boundary value problem in variable exponent Lebesgue spaces and discuss the singularity of solutions at individual zeros belonging to curve.We consider two types of cases those where the coefficient is Hölder and those where it is piecewise Hölder.Then we solve the Hilbert boundary value problem with square roots in variable exponent Lebesgue spaces.By discussing the distribution of the odd-order zero-points for solutions and the method of symmetric extension,we convert the Hilbert problem to a Riemann boundary value problem.The equivalence of the transformation is discussed.Finally,we get the solvable conditions and the direct expressions of the solutions in variable exponent Lebesgue spaces.
基金supported by the National Natural Science Foundation of China(82250410380 and 62171101)the Natural Science Foundation of Sichuan Province(24NSFSC6257)the China MOST2030 Brain Project(2022ZD0208500).
文摘Cerebral ischemia restricts cerebral blood flow(CBF),leading to unstable hemodynamics.Past studies of ischemia mainly focused on cortical CBF reduction.However,its impact on hemodynamic changes,especially temporal varying characteristics,remains poorly understood.Here,we collected cortical resting-state CBF in rats with left carotid artery blockage during occlusion–reperfusion,and measured the temporal variability and changes in laterality using a novel state-space method.This method was also applied to stroke EEG datasets to validate its effectiveness.After arterial occlusion,the left marginal motor,sensory,auditory,and visual cortices exhibited severe temporal variability impairments.The laterality analysis indicated that affected left regions showed inferior unilateral mean,inter-hemispheric transition probability,time fraction,and laterality duration,while the right side had a higher laterality time fraction and duration.These impairments recovered partially following blood flow restoration.Besides,the ischemic state-space metrics were positively correlated with the pre-occlusion baseline appearance.Stroke patients exhibited impaired temporal variability in the affected ischemic hemisphere.The state-space analysis revealed damaged CBF temporal variability during cerebral ischemia and predicted baseline-ischemia connections.
基金supported by the National Key Research and Development Program Project(2023YFC3107804)Planning Fund Project of Humanities and Social Sciences Research of the Ministry of Education(24YJA880097)the Graduate Education Reform Project in North China University of Technology(217051360025XN095-17)。
文摘Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial features.To address the limitations,the paper proposes a TimeXer-based numerical forecast correction model optimized by an exogenous-variable attention mechanism.The model treats target forecast values as internal variables,and incorporates historical temporal-spatial data and seven-day numerical forecast results from traditional models as external variables based on the embedding strategy of TimeXer.Using a self-attention structure,the model captures correlations between exogenous variables and target sequences,explores intrinsic multi-dimensional relationships,and subsequently corrects endogenous variables with the mined exogenous features.The model’s performance is evaluated using metrics including MSE(Mean Squared Error),MAE(Mean Absolute Error),RMSE(Root Mean Square Error),MAPE(Mean Absolute Percentage Error),MSPE(Mean Square Percentage Error),and computational time,with TimeXer and PatchTST models serving as benchmarks.Experiment results show that the proposed model achieves lower errors and higher correction accuracy for both one-day and seven-day forecasts.
