Intra-annual variability albedo associated with China of satellite observed surface typical land cover types in

Surface albedo is a primary causative variable associated with the process of surface energy exchange. Numerous studies have examined diurnal variation of surface albedo at a regional scale; however, few studies have analyzed the intra-annual variations of surface albedo in concurrence with different land cover types. In this study, we amalgamated surface albedo product data （MCD43） from 2001 to 2008, land-use data （in 2000 and 2008） and land cover data （in 2000）; quantitative analyses of surface albedo variation pertaining to diverse land cover types and the effect of the presence/absence of ground snow were undertaken. Results indicate that intra-annual surface albedo values exhibit flat Gaussian or triangular distributions depending upon land cover types. During snow-free periods, satellite observed surface albedo associated with the non-growing season was lower than that associated with the growing season. Satellite observed surface albedo during the presence of ground snow period was 2-4 times higher than that observed during snow-free periods. Surface albedo reference values in typical land cover types have been calculated; notably, grassland, cropland and built-up land were associated with higher surface albedo reference values than barren while ground snow was present. Irrespective of land cover types, the lowest surface albedo reference values were associated with forested areas. Proposed reference values may prove extremely useful in diverse research areas, including ecological modeling, land surface process modeling and radiation energy balance applications.

Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.

Increase in the variability of terrestrial carbon uptake in response to enhanced future ENSO modulation

El Niño-Southern Oscillation(ENSO)is a major driver of climate change in middle and low latitudes and thus strongly influences the terrestrial carbon cycle through land-air interaction.Both the ENSO modulation and carbon flux variability are projected to increase in the future,but their connection still needs further investigation.To investigate the impact of future ENSO modulation on carbon flux variability,this study used 10 CMIP6 earth system models to analyze ENSO modulation and carbon flux variability in middle and low latitudes,and their relationship,under different scenarios simulated by CMIP6 models.The results show a high consistency in the simulations,with both ENSO modulation and carbon flux variability showing an increasing trend in the future.The higher the emissions scenario,especially SSP5-8.5 compared to SSP2-4.5,the greater the increase in variability.Carbon flux variability in the middle and low latitudes under SSP2-4.5 increases by 30.9%compared to historical levels during 1951-2000,while under SSP5-8.5 it increases by 58.2%.Further analysis suggests that ENSO influences mid-and low-latitude carbon flux variability primarily through temperature.This occurrence may potentially be attributed to the increased responsiveness of gross primary productivity towards regional temperature fluctuations,combined with the intensified influence of ENSO on land surface temperatures.

Interannual variability of boreal summer intraseasonal oscillation over the northwestern Pacific influenced by the Pacific Meridional Mode

During the boreal summer,intraseasonal oscillations exhibit significant interannual variations in intensity over two key regions:the central-western equatorial Pacific(5°S-5°N,150°E-150°W)and the subtropical Northwestern Pacific(10°-20°N,130°E-175°W).The former is well-documented and considered to be influenced by the ENSO,while the latter has received comparatively less attention and is likely influenced by the Pacific Meridional Mode(PMM),as suggested by partial correlation analysis results.To elucidate the physical processes responsible for the enhanced(weakened)intraseasonal convection over the subtropical northwestern Pacific during warm(cold)PMM years,the authors employed a moisture budget analysis.The findings reveal that during warm PMM years,there is an increase in summer-mean moisture over the subtropical northwestern Pacific.This increase interacts with intensified vertical motion perturbations in the region,leading to greater vertical moisture advection in the lower troposphere and consequently resulting in convective instability.Such a process is pivotal in amplifying intraseasonal convection anomalies.The observational findings were further verified by model experiments forced by PMM-like sea surface temperature patterns.

Growth at the microscale:long term thinning effects on patterns and timing of intra-annual stem increment in radiata pine

Background: Stem radial growth in forests is not uniform. Rather, it is characterized by periods of relatively fast or slow growth, or sometimes no growth at all. These fluctuations are generally a function of varying environmental conditions(e.g. water availability) and, importantly, will also be associated with adjustments in proprties in the wood formed. Stand level conditions and forest management, particularly thinning and stand density will, thowever, also have a major influence on patterns of growth variation. We explore how different thinning histories and/or stand densities influence these dynamics of tree growth in the important commercial plantation species Pinus radiata D. Don.Methods: Daily stem size change was measured using electronic point dendrometers over two growing seasons on P. radiata trees at two sites, subjected to different thinning regimes. Timing, rates and periodicity of annual growth were calculated from these data.Results: Greater overall cross-sectional growth in thinned plots was driven mainly by two dynamics. First, the cessation of seasonal growth occurred at least 3 weeks later in the stands in which thinning had taken place. There was no difference between thinned/unthinned stands, however, in the timing of growth onset. Second, within the longer season, trees in thinned plots had more growth days(as much as 20% more) than unthinned plots. The rates of growth on days when growth occurred were not different, however. In this context, it is notable that in trees in the unthinned plots experiencing the most severe competition there were strong "pulses" of growth following drought-breaking rainfall events. Unthinned plots at high stand densities also maintained a smaller(but consistent) zone of dividing cells throughout the season than thinned plots.Conclusions: In Pinus radiata growing under conditions as in our study, conditions late in summer, particularly drought, have an important effect on the timing of cessation of growth. Early season temperature appears to have no effect in determining timing of annual growth. Limiting conditions during the season reduce growing duration, and thus total growth, more in unthinned stands than thinned stands. These findings are valuable in developing new generations of fine-scale growth and wood property models.

Responses of intra-annual runoff to forest recovery patterns in subtropical China

Forest recovery plays a critical role in regulating eco-hydrological processes in forested watersheds.However,characteristics of the intra-annual runoff variation associated with different forest recovery patterns remain poorly understood.In this study,three forest change periods were identified,the baseline period(1961-1985),reforestation period(1986-2000)and fruit tree planting period(2001-2016).We selected the magnitude of seasonal runoff(wet and dry seasons)and distribution characteristics,i.e.,non-uniformity coefficient(C_(v)),complete accommodation coefficient(C_(r)),concentration ratio(C_(n)),concentration period(C_(d)),absolute variation ratio(ΔR)and relative variation ratio(C_(max)).The pair-wise approach evaluated the intra-annual runoff variation characteristics between forest change periods.Results indicate that reforestation decreased wet season runoff and increased dry season runoff.In contrast,fruit tree planting increased wet season runoff and had no significant effect on dry season runoff.For intra-annual runoff distribution characteristics,reforestation significantly reduced the C_(v),C_(r),C_(n)and C_(max).Distribution of the intra-annual runoff in the fruit tree planting period was not significantly different from the baseline.We concluded that reforestation reduced the occurance of extreme water conditions in wet and dry seasons and effectively increased the stability of the intra-annual runoff.In contrast,fruit tree planting increased instability and fluctuation of the intra-annual runoff after reforestation.The characteristics of the intra-annual runoff to fruit tree planting was similar to those of the baseline.Therefore,adopting fruit tree planting practices to regulate intra-annual runoff characteristics may not be a practical approach,and impacts of different reforestation practices should be ascertained in our study region.The implications of this study should guide regional land-water management,and this study adds to the understanding of the impacts gained in forest cover on hydrology.

Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

The influence of resistance exercise training prescription variables on skeletal muscle mass,strength,and physical function in healthy adults:An umbrella review

Purpose:The aim of this umbrella review was to determine the impact of resistance training(RT)and individual RT prescription variables on muscle mass,strength,and physical function in healthy adults.Methods:Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines,we systematically searched and screened eligible systematic reviews reporting the effects of differing RT prescription variables on muscle mass(or its proxies),strength,and/or physical function in healthy adults aged>18 years.Results:We identified 44 systematic reviews that met our inclusion criteria.The methodological quality of these reviews was assessed using A Measurement Tool to Assess Systematic Reviews;standardized effectiveness statements were generated.We found that RT was consistently a potent stimulus for increasing skeletal muscle mass(4/4 reviews provide some or sufficient evidence),strength(4/6 reviews provided some or sufficient evidence),and physical function(1/1 review provided some evidence).RT load(6/8 reviews provided some or sufficient evidence),weekly frequency(2/4 reviews provided some or sufficient evidence),volume(3/7 reviews provided some or sufficient evidence),and exercise order(1/1 review provided some evidence)impacted RT-induced increases in muscular strength.We discovered that 2/3 reviews provided some or sufficient evidence that RT volume and contraction velocity influenced skeletal muscle mass,while 4/7 reviews provided insufficient evidence in favor of RT load impacting skeletal muscle mass.There was insufficient evidence to conclude that time of day,periodization,inter-set rest,set configuration,set end point,contraction velocity/time under tension,or exercise order(only pertaining to hypertrophy)influenced skeletal muscle adaptations.A paucity of data limited insights into the impact of RT prescription variables on physical function.Conclusion:Overall,RT increased muscle mass,strength,and physical function compared to no exercise.RT intensity(load)and weekly frequency impacted RT-induced increases in muscular strength but not muscle hypertrophy.RT volume(number of sets)influenced muscular strength and hypertrophy.

Influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel

The influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel is investigated.The DarcyBrinkman model is used to characterize the fluid flow dynamics in porous materials.The analytical solutions are obtained for the unidirectional and completely developed flow.Based on a normal mode analysis,the generalized eigenvalue problem under a perturbed state is solved.The eigenvalue problem is then solved by the spectral method.Finally,the critical Rayleigh number with the corresponding wavenumber is evaluated at the assigned values of the other flow-governing parameters.The results show that increasing the Darcy number,the Lewis number,the Dufour parameter,or the Soret parameter increases the stability of the system,whereas increasing the inclination angle of the channel destabilizes the flow.Besides,the flow is the most unstable when the channel is vertically oriented.

Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2

To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia”(WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day(or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day(or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four(ten) times larger than the ice-induced East Asian cooling in the present-day(future) experiment;the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60%(80%) to the Arctic winter warming in the present-day(future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-lossinduced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety.An active mass damper(AMD)with stroke limitations is often used to avoid collisions.However,a strokelimited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power.To solve this problem,the design approach with variable gain and limited area(VGLA)is proposed in this study.First,the boundary of variable-limited areas is calculated based on the real-time status of the moving mass.The variable gain(VG)expression at the variable limited area is deduced by considering the saturation of AMD stroke.Then,numerical simulations of a stroke-limited AMD control system with VGLA are conducted on a high-rise building structure.These numerical simulations show that the proposed approach has superior strokelimitation performance compared with a stroke-limited AMD control system with a fixed limited area.Finally,the proposed approach is validated through experiments on a four-story steel frame.

Mid-infrared Period-Luminosity Relations of Gaia DR3 Long Period Variables

Long period variable(LPV)stars are very promising distance indicators in the infrared bands.We selected asymptotic giant branch(AGB)stars in the Large and Small Magellanic Cloud(LMC and SMC)from the Gaia Data Release 3 LPV catalog,and classified them into oxygen-rich(O-rich)and carbon-rich(C-rich)AGB stars.Using the Wide-field Infrared Survey Explorer database,we determined the W1-and W2-band period-luminosity relations(PLRs)for each pulsation-mode sequence of AGB stars.The dispersion of the PLRs of O-rich AGB stars in sequences C'and C is relatively small,around 0.14 mag.The PLRs of LMC and SMC are consistent in each sequence.In the W2 band,the PLR of large-amplitude C-rich AGB stars is steeper than that of small-amplitude C-rich AGB stars,due to their more circumstellar dust.By two methods,we find that some PLR sequences of O-rich AGB stars in the LMC are dependent on metallicity.The coefficients of the metallicity effect areβ=-0.533±0.213 mag dex~1andβ=-0.767±0.158 mag dex~1for sequence C in W1 and W2 bands,respectively.The significance of the metallicity effect in W1 band for the four sequences is 2.2-3.5σ.Both of these imply that distance measurements using O-rich Mira may need to take the metallicity effect into account.

A novel variable-order fractional chaotic map and its dynamics

In recent years,fractional-order chaotic maps have been paid more attention in publications because of the memory effect.This paper presents a novel variable-order fractional sine map(VFSM)based on the discrete fractional calculus.Specially,the order is defined as an iterative function that incorporates the current state of the system.By analyzing phase diagrams,time sequences,bifurcations,Lyapunov exponents and fuzzy entropy complexity,the dynamics of the proposed map are investigated comparing with the constant-order fractional sine map.The results reveal that the variable order has a good effect on improving the chaotic performance,and it enlarges the range of available parameter values as well as reduces non-chaotic windows.Multiple coexisting attractors also enrich the dynamics of VFSM and prove its sensitivity to initial values.Moreover,the sequence generated by the proposed map passes the statistical test for pseudorandom number and shows strong robustness to parameter estimation,which proves the potential applications in the field of information security.

Extent and Structure of Phenotypic Variability in Solenostemon rotundifolius Germplasm from Ghana and Burkina Faso

Solenostemon rotundifolius is a species belonging to the Lamiaceae family. It is currently one of the minor plants of high socio-economic interest. One of the limitations to promoting this species in Burkina Faso is the lack of varieties that meet consumers’ demands. Implementing a breeding program is an important step toward achieving this goal. Such a program is based on the variability of agronomical traits of interest within evaluated germplasm. This study aimed to assess the level of two germplasms variability of S. rotundifolius from Ghana and Burkina Faso for traits related to vegetative development, cycle, and yield. Agromorphological characterization of 174 accessions, including 116 from Ghana and 58 from Burkina Faso was carried out in Randomised Complete Block Design with three replications. The characterization was made on the basis of fifteen (15) quantitative traits related to the canopy and leaf size, the cycle, and the yield. Analysis of variance revealed significant differences between accessions within each germplasm for all the evaluated traits. The analysis of the structuration of this agromorphological variability allowed organizing the accessions into different groups. These results could lead to the identification of accessions within each germplasm for breeding purposes or future research on genotype-environment interactions.

An approximate analytical model for unconventional reservoir considering variable matrix blocks and simultaneous matrix depletion

In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate production evaluations because of the absence of matrix-macrofracture communication.In addition,most of the existing models are solved analytically based on Laplace transform and numerical inversion.Hence,an approximate analytical solution is derived directly in real-time space considering variable matrix blocks and simultaneous matrix depletion.To simplify the derivation,the simultaneous matrix depletion is divided into two parts:one part feeding the macrofractures and the other part feeding the microfractures.Then,a series of partial differential equations(PDEs)describing the transient flow and boundary conditions are constructed and solved analytically by integration.Finally,a relationship between oil rate and production time in real-time space is obtained.The new model is verified against classical analytical models.When the microfracture system and matrix-macrofracture communication is neglected,the result of the new model agrees with those obtained with the dual-porosity and triple-porosity model,respectively.Certainly,the new model also has an excellent agreement with the numerical model.The model is then applied to two actual tight oil wells completed in western Canada sedimentary basin.After identifying the flow regime,the solution suitably matches the field production data,and the model parameters are determined.Through these output parameters,we can accurately forecast the production and even estimate the petrophysical properties.

Geospatial Variability of Cholera Cases in Malawi Based on Climatic and Socioeconomic Influences

Cholera remains a public health threat in most developing countries in Asia and Africa including Malawi with seasonal recurrent outbreaks. Malawi’s recent Cholera outbreak in 2022 and 2023, exhibited higher morbidity and mortality rates than the past two decades. Lack of spatiotemporal-based technology and variability assessment tools in Malawi’s Cholera monitoring and management, limit our understanding of the disease’s epidemiology. The present work developed a spatiotemporal variability model for Cholera disease at district level and its relationship to socioeconomic and climatic factors based on cumulative confirmed Cholera cases in Malawi from March 2022 to July 2023 using Z-score statistic and multiscale geographically weighted regression (MGWR) in a Geographical Information System (GIS). We found out that socioeconomic factors such as access to safe drinking water, population density and poverty level, and climatic factors including temperature and rainfall strongly influenced Cholera prevalence in a complex and multifaceted manner. The model shows that Lilongwe, Mangochi, Blantyre and Balaka districts were highly vulnerable to Cholera disease followed by lakeshore districts of Salima, Nkhotakota, Nkhata-Bay and Karonga than other districts. We recommend strategic measures such as Water, Sanitation, and Hygiene (WASH) interventions, community awareness on proper water storage, Cholera case management, vaccination campaigns and spatial-based surveillance systems in the most affected districts. This research has shown that MGWR, as a surveillance system, has the potential of providing insights on the disease’s spatial patterns for public health authorities to identify high-risk districts and implement early response interventions to reduce the spread of the disease.

Intraseasonal variability of the Kuroshio observed via mooring at 18°N

Insufficient observations near the origin of the Kuroshio have led to incomplete understanding of the intraseasonal variability(ISV)of the Kuroshio.Direct measurements of the Kuroshio velocity were performed with an array of three profiler moorings(122.7°E,123°E,and 123.3°E)along 18°N from January 2018 to February 2020.The ISV of the Kuroshio at 18°N was investigated based on a combination of mooring observations and global high-resolution HYbrid Coordinate Ocean Model reanalysis data.The estimated time-averaged transport in the upper 350 m across the observation transect was 6.5±2.6 Sv(1.0 Sv=10^(6)m^(3)/s).Two significant ISV peaks at 50-60 and~100 d were recognized in the power spectra of the meridional velocity and transport.Further analysis indicated that the ISV at 50-60 d was caused by westward-propagating eddies at average propagation speed of~13 cm/s and wavelength of~635 km.Another ISV peak at~100 d was mainly caused by northward-propagating eddies generated in the North Equatorial Current region.Further investigation indicated that the ISV of the Kuroshio at 18°N is dominated by meridional transport,rather than by the zonal migration of the Kuroshio main axis.Our findings provide a better understanding of the ISV of the Kuroshio east of Luzon Island.

Sufficient variable selection of high dimensional nonparametric nonlinear systems based on Fourier spectrum of density-weighted derivative

The variable selection of high dimensional nonparametric nonlinear systems aims to select the contributing variables or to eliminate the redundant variables.For a high dimensional nonparametric nonlinear system,however,identifying whether a variable contributes or not is not easy.Therefore,based on the Fourier spectrum of densityweighted derivative,one novel variable selection approach is developed,which does not suffer from the dimensionality curse and improves the identification accuracy.Furthermore,a necessary and sufficient condition for testing a variable whether it contributes or not is provided.The proposed approach does not require strong assumptions on the distribution,such as elliptical distribution.The simulation study verifies the effectiveness of the novel variable selection algorithm.