The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects acc...The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.展开更多
α.-Zeins,the major maize endosperm storage proteins,are transcriptionally regulated by Opaque2(O2)and prolamin-box-binding factor 1(PBF1),with Opaque11(O11)functioning upstream of them.However,whether O11 directly bi...α.-Zeins,the major maize endosperm storage proteins,are transcriptionally regulated by Opaque2(O2)and prolamin-box-binding factor 1(PBF1),with Opaque11(O11)functioning upstream of them.However,whether O11 directly binds toα-zein genes and its regulatory interactions with O2 and PBF1 remain unclear.Using the small-kernel mutant sw1,which exhibits decreased 19-kDa and increased 22-kDaα-zein,we positionally clone O11 and find it directly binds to G-box/E-box motifs.O11 activates 19-kDaα-zein transcription,stronger than PBF1 but weaker than O2.Notably,PBF1 competitively binds to an overlapping E-box/P-box motif,and represses O11-mediated transactivation.Although O11 does not physically interact with O2,it participates in the O2-centered hierarchical network to enhanceα-zein expression.sw1 o2 and sw1 pbf1 double mutants exhibit smaller,more opaque kernels with further reduced 19-kDa and 22-kDaα-zeins compared to the single mutants,suggesting distinct regulatory effects of these transcription factors on 19-kDa and 22-kDaα-zein genes.Promoter motif analysis suggests that O11,PBF1,and O2 directly regulate 19-kDaα-zein genes,while O11 indirectly controls 22-kDaα-zein genes via O2 and PBF1 modulation.These findings identify the unique and coordinated roles of O11,O2,and PBF1 in regulatingα.-zein genes and kernel development.展开更多
In this study,Palm kernel shell(PKS)is utilized as a raw material to produce activated biochar as adsorbent for dye removal from wastewater,specifically methylene blue(MB)dye,by utilizing a simplified and costeffectiv...In this study,Palm kernel shell(PKS)is utilized as a raw material to produce activated biochar as adsorbent for dye removal from wastewater,specifically methylene blue(MB)dye,by utilizing a simplified and costeffective approach.Production of activated biocharwas carried out using both a furnace and a domesticmicrowave oven without an inert atmosphere.Three samples of palm kernel shell(PKS)based activated biochar labeled as samples A,B and C were carbonized inside the furnace at 800℃ for 1 h and then activated using the microwave-heating technique with varying heating times(0,5,10,and 15 min).The heating was conducted in the absence of an inert gas.Fourier Transform Infrared Spectroscopy(FTIR)highlighted a significant Si-O stretching vibration between 1040.5 to 692.7 cm−1,indicating the presence of key components(Silica and Alumina)in all PKS-based activated biochar samples.For wastewater treatment,activated biochar samples were tested against a 20 mg/LMethylene Blue(MB)solution,and the MB percentage removal was calculated for each run using a standard curve.Central Composite Design(CCD)experiments were conducted for optimization,with activated biochar Sample C exhibiting the highest adsorption capacity at 88.14%MB removal under specific conditions.ANOVA analysis confirmed the significance of the quadratic model,with a p-value of 0.0222 and R^(2)=0.9438.In conclusion,the results demonstrated the efficiency of PKS-based activated biochar as an adsorbent for MB removal in comparison to other commercial adsorbents.展开更多
Significant advancements have been achieved in the field of Single Image Super-Resolution(SISR)through the utilization of Convolutional Neural Networks(CNNs)to attain state-of-the-art performance.Recent efforts have e...Significant advancements have been achieved in the field of Single Image Super-Resolution(SISR)through the utilization of Convolutional Neural Networks(CNNs)to attain state-of-the-art performance.Recent efforts have explored the incorporation of Transformers to augment network performance in SISR.However,the high computational cost of Transformers makes them less suitable for deployment on lightweight devices.Moreover,the majority of enhancements for CNNs rely predominantly on small spatial convolutions,thereby neglecting the potential advantages of large kernel convolution.In this paper,the authors propose a Multi-Perception Large Kernel convNet(MPLKN)which delves into the exploration of large kernel convolution.Specifically,the authors have architected a Multi-Perception Large Kernel(MPLK)module aimed at extracting multi-scale features and employ a stepwise feature fusion strategy to seamlessly integrate these features.In addition,to enhance the network's capacity for nonlinear spatial information processing,the authors have designed a Spatial-Channel Gated Feed-forward Network(SCGFN)that is capable of adapting to feature interactions across both spatial and channel dimensions.Experimental results demonstrate that MPLKN outperforms other lightweight image super-resolution models while maintaining a minimal number of parameters and FLOPs.展开更多
LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional...LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.展开更多
The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the ...The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the uncertain,complex,and strongly coupled non-Gaussian detection noise.As a result,there are several intractable considerations on the problem of state estimation tasks corrupted by complex non-Gaussian outliers for non-linear dynamics systems in practical application.To address these issues,a new iterated rational quadratic(RQ)kernel high-order unscented Kalman filtering(IRQHUKF)algorithm via capturing the statistics to break through the limitations of the Gaussian assumption is proposed.Firstly,the characteristic analysis of the RQ kernel is investigated in detail,which is the first attempt to carry out an exploration of the heavy-tailed characteristic and the ability on capturing highorder moments of the RQ kernel.Subsequently,the RQ kernel method is first introduced into the UKF algorithm as an error optimization criterion,termed the iterated RQ kernel-UKF(RQ-UKF)algorithm by derived analytically,which not only retains the high-order moments propagation process but also enhances the approximation capacity in the non-Gaussian noise problem for its ability in capturing highorder moments and heavy-tailed characteristics.Meanwhile,to tackle the limitations of the Gaussian distribution assumption in the linearization process of the non-linear systems,the high-order Sigma Points(SP)as a subsidiary role in propagating the state high-order statistics is devised by the moments matching method to improve the RQ-UKF.Finally,to further improve the flexibility of the IRQ-HUKF algorithm in practical application,an adaptive kernel parameter is derived analytically grounded in the Kullback-Leibler divergence(KLD)method and parametric sensitivity analysis of the RQ kernel.The simulation results demonstrate that the novel IRQ-HUKF algorithm is more robust and outperforms the existing advanced UKF with respect to the kernel method in reentry vehicle tracking scenarios under various noise environments.展开更多
Transcription factors play critical roles in the regulation of gene expression during maize kernel development.The maize endosperm,a large storage organ,accounting for nearly 90%of the dry weight of mature kernels,ser...Transcription factors play critical roles in the regulation of gene expression during maize kernel development.The maize endosperm,a large storage organ,accounting for nearly 90%of the dry weight of mature kernels,serves as the primary site for starch storage.In this study,we identify an endosperm-specific EREB gene,ZmEREB167,which encodes a nucleus-localized EREB protein.Knockout of ZmEREB167 significantly increases kernel size and weight,as well as starch and protein content,compared with the wild type.In situ hybridization experiments show that ZmEREB167 is highly expressed in the BETL as well as PED regions of maize kernels.Dual-luciferase assays show that ZmEREB167 exhibits transcriptionally repressor activity in maize protoplasts.Transcriptome analysis reveals that a large number of genes are up-regulated in the Zmereb167-C1 mutant compared with the wild type,including key genetic factors such as ZmMRP-1 and ZmMN1,as well as multiple transporters involved in maize endosperm development.Integration of RNA-seq and ChIP-seq results identify 68 target genes modulated by ZmEREB167.We find that ZmEREB167 directly targets OPAQUE2,ZmNRT1.1,ZmIAA12,ZmIAA19,and ZmbZIP20,repressing their expressions.Our study demonstrates that ZmEREB167 functions as a negative regulator in maize endosperm development and affects starch accumulation and kernel size.展开更多
We present and explore a new shock-capturing particle hydrodynamics approach.Our starting point is a commonly used discretization of smoothed particle hydrodynamics.We enhance this discretization with Roe’s approx-im...We present and explore a new shock-capturing particle hydrodynamics approach.Our starting point is a commonly used discretization of smoothed particle hydrodynamics.We enhance this discretization with Roe’s approx-imate Riemann solver,we identify its dissipative terms,and in these terms,we use slope-limited linear reconstruction.All gradients needed for our method are calculated with linearly reproducing kernels that are constructed to enforce the two lowest-order consistency relations.We scrutinize our reproducing kernel implementation carefully on a“glass-like”particle distribution,and we find that constant and linear functions are recovered to machine precision.We probe our method in a series of challenging 3D benchmark problems ranging from shocks over instabilities to Schulz-Rinne-type vorticity-creating shocks.All of our simulations show excellent agreement with analytic/reference solutions.展开更多
Arogenate dehydratase(ADT)catalyzes the final step in phenylalanine synthesis and is crucial for plant development and metabolism.Previously,we demonstrated that the ADT/prephenate dehydratase ZmADT2 is essential for ...Arogenate dehydratase(ADT)catalyzes the final step in phenylalanine synthesis and is crucial for plant development and metabolism.Previously,we demonstrated that the ADT/prephenate dehydratase ZmADT2 is essential for maize resistance to Ustilago maydis and for overall plant development.In this study,we explored the role of ZmADT2 in maize kernel development.The mmsu mutant,a dysfunctional ZmADT2 variant,exhibits delayed embryo and endosperm development,along with deficiencies in carbohydrate and protein storage.Transcriptome analysis revealed differential expression of many kernel compartment-specific genes between mmsu and wild-type(WT)kernels,with impaired nutrient accumulation and auxin signaling pathway in the mmsu endosperm.Compared to WT,ZmADT2 mutation led to reduced auxin levels and smaller endosperm cell size.Exogenous auxin rescued the small kernel phenotype of mmsu.Additionally,auxin distribution was reduced in the basal endosperm transfer layer(BETL),causing defects in its development and function,including reduced transfer cell elongation,cell wall ingrowth and nutrient uptake.These findings suggest that ZmADT2 mediated mediates an auxin signaling pathway that is essential for maize kernel development.展开更多
In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To addr...In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To address this issue,we integrate Large Kernel Convolution(LKconv)into the U-Net framework,proposing an enhanced network structure named U-LKconv network,which significantly enhances the capability to recover image details even under low sampling conditions.展开更多
Palm kernel cake(PKC),a major by-product of the palm oil industry,is rich in non-starch polysaccharides.In this study,two polysaccharide fractions,precipitated with acetic acid(PPA)and ethanol(PPE),respectively,were e...Palm kernel cake(PKC),a major by-product of the palm oil industry,is rich in non-starch polysaccharides.In this study,two polysaccharide fractions,precipitated with acetic acid(PPA)and ethanol(PPE),respectively,were extracted from PKC using a 2 mol/L NaOH solution.The molecular weight,sugar composition,structural characteristics,morphology,antioxidant activity,as well as in vitro stimulated digestion were investigated in detail.The results revealed that due to its poor solubility of PPA in water,the detected molecular weight of PPA was only 2040 g/mol,which was significantly lower than that of PPE(65,300 g/mol).Although PPA and PPE had a similar sugar composition with varying contents,mannose was the predominant monosaccharide in both,accounting for 87.71%and 60.40%,respectively.Both PPA and PPE were primarily composed of crystalline mannan,consisting of mannopyranosyl units linked by(1→4)-β-glycosidic bonds,along with a small amount of lignin.PPA possibly contained a higher proportion of crystalline mannan,whereas PPE had a larger amount of arabinoxylan and galactomannan.Atomic force microscope revealed a stacked morphology for both PPA and PPE.PPA exhibited a higher scavenging rate against DPPH•and ABTS^(+)•but a weaker HO•scavenging activity and reducing power compared with PPE.Within the polysaccharide concentration range of 0.5-5.0 mg/mL,PPA and PPB demonstrated the strongest scavenging activity against ABTS^(+)•,with the highest scavenging rates exceeding 91%.However,PPA and PPB exhibited the weakest scavenging activity against HO•,with their highest HO•scavenging rates reaching only 44.91%and 55.86%,respectively.The antioxidant activities of both PPA and PPE were weaker than that of ascorbic acid.PPA remained almost stable in the in vitro simulated saliva fluid,while PPE exhibited weaker resistance to it.Both PPA and PPE exhibited weak resistance to the in vitro simulated gastric digestion fluids,but remained relatively stable in the in vitro simulated small-intestinal digestion fluid.The differences in physicochemical properties between PPA and PPE likely played an important role in their distinct biological activities.These findings suggest potential utilization of PKC in exploring dietary polysaccharides with favorable antioxidant activity and unique digestive characteristics.展开更多
Starch serves as a critical storage component,significantly influencing the grain yield and quality of maize(Zea mays L.).Understanding the genetic basis of natural variation in kernel starch content(SC)is essential f...Starch serves as a critical storage component,significantly influencing the grain yield and quality of maize(Zea mays L.).Understanding the genetic basis of natural variation in kernel starch content(SC)is essential for maize breeding to meet future demands.A genome-wide association study(GWAS)identified 84 and 96 loci associated with kernel SC across two years,overlapping with 185 candidate genes.The candidate gene Zm MYB71,encoding a MYB-related transcription factor,demonstrated the highest co-expression frequency with starch synthesis genes.Analysis revealed that Zm MYB71 functions as a nuclear located transcription repressor,and mutants exhibited increased kernel SC by over 2.32%,with minimal impact on amylose content or 100-grain weight.Sh1,Sh2,and GBSSI exhibited up-regulation in mutants by 1.56-,1.45-and 1.32-fold,respectively,aligning with RNA sequencing results;their promoter activities appear directly repressed by Zm MYB71 through the GATATC and TTAGGG motifs.Additionally,the Zm MYB71 elite haplotype Hap1 occurred in over 55%of the high-starch maize sub-populations Iowa Stiff Stalk Synthetic(BSSS)and Partner B(PB),but only in 7.14%of the low-starch sub-population Partner A(PA).Analysis of Hap1 haplotype frequencies across breeding stages revealed a significant increase to 40.28%in inbred groups released after 2010,compared to 28.57 and 27.94%in 1980 and 1990,and 2000,respectively.These findings enhance understanding of natural variation in maize kernel SC and establish Zm MYB71 as a negative regulator with potential applications in SC improvement.展开更多
Mitochondria are semi-autonomous organelles present in eukaryotic cells,containing their own genome and transcriptional machinery.However,their functions are intricately linked to proteins encoded by the nuclear genom...Mitochondria are semi-autonomous organelles present in eukaryotic cells,containing their own genome and transcriptional machinery.However,their functions are intricately linked to proteins encoded by the nuclear genome.Mitochondrial transcription termination factors(mTERFs)are nucleic acid-binding proteins involved in RNA splicing and transcription termination within plant mitochondria and chloroplasts.Despite their recognized importance,the specific roles of mTERF proteins in maize remain largely unexplored.Here,we clone and functionally characterize the maize mTERF18 gene.Our findings reveal that mTERF18 mutations lead to severely undifferentiated embryos,resulting in abortive phenotypes.Early kernel exhibits abnormal basal endosperm transfer layer and a significant reduction in both starch and protein accumulation in mterf18.We identify the mTERF18 gene through mapping-based cloning and validate this gene through allelic tests.mTERF18 is widely expressed across various maize tissues and encodes a highly conserved mitochondrial protein.Transcriptome data reveal that mTERF18 mutations disrupt transcriptional termination of the nad6 gene,leading to undetectable levels of Nad6 protein and reduced complex I assembly and activity.Furthermore,transmission electron microscopy observation of mterf18 endosperm uncover severe mitochondrial defects.Collectively,these findings highlight the critical role of mTERF18 in mitochondrial gene transcription termination and its pivotal impact on maize kernel development.展开更多
This study evaluated corn kernel drying performance and quality changes using hot air drying(HAD)and infrared drying(ID)across temperatures ranging from 55℃ to 80℃.Optimal drying parameters were determined by using ...This study evaluated corn kernel drying performance and quality changes using hot air drying(HAD)and infrared drying(ID)across temperatures ranging from 55℃ to 80℃.Optimal drying parameters were determined by using the entropy weight method,with drying time,specific energy consumption,damage rate,fatty acids,starch,polyphenols,and flavonoids as indicators.Results demonstrated that ID significantly outperformed HAD,achieving drying times up to 20%shorter and reducing specific energy consumption and kernel damage by up to 79.3%and 66.7%,respectively,while also better preserving quality attributes.Both methods exhibited drying profiles characterized by acceleration,constant,and falling rate periods,although the constant rate phase was distinctly observable only at lower temperatures.The effective moisture diffusivity under ID was consistently higher than that under HAD,with a maximum increase of 20.4%.The optimal drying conditions were HAD at 65℃ and ID at 80℃.A BP model was also developed and it showed better predictive performance and adaptability than classical mathematical models.展开更多
Seed maturation is a critical development transition and it largely affects the final yield and quality of crops.Abscisic acid(ABA)-activated sucrose-non-fermentation kinase subfamily 2(SnRK2s)constitute a well-known ...Seed maturation is a critical development transition and it largely affects the final yield and quality of crops.Abscisic acid(ABA)-activated sucrose-non-fermentation kinase subfamily 2(SnRK2s)constitute a well-known regulatory network that modulate seed maturation in Arabidopsis;however,the underlying genetic and regulatory mechanisms in cereal crops remain largely unknown.Here,we found that ABA levels exhibited two distinct peaks during kernel development in maize,corresponding to the lag and maturation phase,respectively.Integrated transcriptome and proteome profiling of kernels treated with exogenous ABA at the pre-maturation stage suggested that the second peak of ABA acts as a trigger for kernel maturation program.Knockout of ZmSnRK2s demonstrated that subclassⅢZmSnRK2s are required for kernel maturation in maize,and the loss-of-function of subclassⅢZmSnRK2s showed a disruption in kernel dehydration and dormancy.We identified a conserved ABA–SnRK2–b ZIP signaling pathway mediating this process in maize.Additionally,ZmSnRK2.10 overexpression accelerates kernel dehydration during maturity,achieving reduced kernel moisture content(KMC)at physiological maturity(PM).Overall,our findings establish ABA-activated SnRK2s as central regulators of kernel maturation in maize and provide valuable genetic resources for breeding maize varieties with low moisture content at harvest.展开更多
As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst ...As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst intensity,the problem of rockburst intensity prediction has not been well solved until now.In this study,we collect 292 sets of rockburst data including eight parameters,such as the maximum tangential stress of the surrounding rock σ_(θ),the uniaxial compressive strength of the rockσc,the uniaxial tensile strength of the rock σ_(t),and the strain energy storage index W_(et),etc.from more than 20 underground projects as training sets and establish two new rockburst prediction models based on the kernel extreme learning machine(KELM)combined with the genetic algorithm(KELM-GA)and cross-entropy method(KELM-CEM).To further verify the effect of the two models,ten sets of rockburst data from Shuangjiangkou Hydropower Station are selected for analysis and the results show that new models are more accurate compared with five traditional empirical criteria,especially the model based on KELM-CEM which has the accuracy rate of 90%.Meanwhile,the results of 10 consecutive runs of the model based on KELM-CEM are almost the same,meaning that the model has good stability and reliability for engineering applications.展开更多
This paper considers the following Marcinkiewicz type integrals■which can be regarded as an extension of the classical Marcinkiewicz integral po introduced by Stein in[Trans Amer Math Soc,88(1958):159-172],where Ω i...This paper considers the following Marcinkiewicz type integrals■which can be regarded as an extension of the classical Marcinkiewicz integral po introduced by Stein in[Trans Amer Math Soc,88(1958):159-172],where Ω is a homogeneous function of degree zero on R^(n)with mean value zero in the unit sphere S^(n-1),Under the assumption that Ω∈L^(∞)(S^(n-1)),the authors establish the L^(q)-estimate and weak(1,1)type estimate as well as the corresponding weighted estimates for po.s with 1<q<∞ and 0<β(q-1)n/q.Moreover,the bounds do not depend on β and the strong(q,q)type and weak(1,1)type estimates for the classical Marcinkiewicz integral po can be recovered from the above estimates of μΩ,β whenβ→0.展开更多
In this paper,a new temporal-spatial fractional order model is proposed to study the dynamic behavior of thermo-viscoelastic nanoplates.Traditional singular kernel in Caputo fractional order differentiation is replace...In this paper,a new temporal-spatial fractional order model is proposed to study the dynamic behavior of thermo-viscoelastic nanoplates.Traditional singular kernel in Caputo fractional order differentiation is replaced by the non-singular kernel and thus leads to a new generalized fractional order differential model with the integer order differential models as a special case.This improved model can more flexibly describe small-scale mechanical behavior and time-dependent heat conduction behavior and provides a clear physical explanation for the fractional order parameters.Spatial nonlocal effects are described in terms of nonlocal strain gradient elasticity and spatial fractional order derivatives,while the time-dependent effects are described in terms of non-Fourier heat conduction,viscoelasticity,and time fractional order derivatives.In addition,it is the first time that the nonlocal characteristic lengths and the memory characteristic times are introduced as two new small-scale parameters in the fractional order derivatives of non-singular kernels to focus on the short-range nonlocal behaviors and the short-term memory behaviors.Numerical examples of the free vibration and the forced vibration under step loading are given,and the effects of the spatial fractional order parameter and the temporal fractional order parameter are both discussed.展开更多
The intensified kernel position effect is a common phenomenon in maize production under higher plant density,which limits crop productivity.Subsoiling is an effective agronomic practice for improving crop productivity...The intensified kernel position effect is a common phenomenon in maize production under higher plant density,which limits crop productivity.Subsoiling is an effective agronomic practice for improving crop productivity.To clarify the effect of subsoiling before winter wheat on the kernel position effect of densely grown summer maize and its regulatory mechanism,field experiments were conducted during the 2020-2021 and 2021-2022 growing seasons using a split-plot design.The main plots included two tillage practices:conventional tillage practice(CT)and subsoiling before the sowing of winter wheat(SS);and the subplots consisted of three plant densities(D1-D3 at 6.0×10~4,7.5×10~4,and 9.0×10~4 plants ha-1).Compared with CT,SS alleviated the kernel position effect by increasing the weight ratio of inferior to superior kernels(WR)in the D2 and D3 treated plants.The higher WR of SS treated plants contributed largely to the improved flling of inferior kernels.Under the same plant density,SS signifcantly improved the root dry matter accumulation(DMA)and antioxidant enzyme activities(superoxide dismutase(SOD)and peroxidase(POD)),and it reduced the malondialdehyde(MDA)content,especially for the plants grown under higher plant densities.These results indicated that SS delayed the root senescence,which is associated with the reduced soil bulk density.In addition,compared with CT,SS increased the leaf chlorophyll content from 20 days after silking to physiological maturity and the post-silking leaf area duration,and it reduced the post-silking leaf chlorophyll reduction rate and leaf area reduction rate,indicating that the post-silking leaf senescence had been alleviated.Under the same plant density,the post-silking DMA of SS was obviously higher than that of CT,which was probably related to the improved leaf area duration and photosynthetic enzyme activities(phosphoenolpyruvate carboxylase(PEPC)and Rubisco).The correlation analysis revealed that the main mechanism of SS in alleviating the kernel position effect of densely grown summer maize is as follows:SS delays the post-silking root-shoot senescence by regulating soil physical properties,and further improves the post-silking DMA and flling of inferior kernels,which ultimately alleviates the kernel position effect and improves grain yield.The results of this study provide new theoretical support for the promotion of summer maize yield by subsoiling before winter wheat.展开更多
The state of health SoH of lithium ion batteries plays a predominant role in ensuring the safe and reliable operation of electric vehicles.In this,a novel SoH estimation approach using support vector regression with a...The state of health SoH of lithium ion batteries plays a predominant role in ensuring the safe and reliable operation of electric vehicles.In this,a novel SoH estimation approach using support vector regression with a Gaussian kernel optimized using the Bayesian optimization technique(BO-SVR with a Gaussian kernel)was proposed.Unlike,traditional approaches that use the internal resistance,and battery capacity as input parameters,this study utilized the equivalent discharging voltage difference interval and equivalent charging voltage difference interval,as they capture the dynamic voltage characteristics associated with the battery degradation.The model was simulated using MATLAB 2023a.The mean absolute error,R^(2),root mean squared error,and mean squared error were considered as performance indicators.The simulation results indicated that the proposed BO-SVR with a Gaussian kernel model had superior performance to other kernel SVR and Gaussian Process Regression models,with a reduced RMSE of 0.0082,thus demonstrating its potential to predict the SoH more accurately.展开更多
基金supported by the China Agriculture Research System of MOF and MARAthe National Natural Science Foundation of China (31872337 and 31501919)the Agricultural Science and Technology Innovation Project,China (ASTIP-IAS02)。
文摘The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.
基金supported by the Natural Science Foundation of Henan Province(242300421028)the National Natural Science Foundation of China(32372091)+3 种基金the Science and Technology Innovation Fund of Henan Agricultural University(202023CXZX002)to ZY.F.the National Key Research and Development Program of China(2021YFF1000304)to Q-W.S.the Natural Science Foundation Youth Fund project of Henan Province(232300421261)to Q-Q.Z.the China Postdoctoral Science Foundation(2024M750812),and Henan Postdoctoral Foundation.
文摘α.-Zeins,the major maize endosperm storage proteins,are transcriptionally regulated by Opaque2(O2)and prolamin-box-binding factor 1(PBF1),with Opaque11(O11)functioning upstream of them.However,whether O11 directly binds toα-zein genes and its regulatory interactions with O2 and PBF1 remain unclear.Using the small-kernel mutant sw1,which exhibits decreased 19-kDa and increased 22-kDaα-zein,we positionally clone O11 and find it directly binds to G-box/E-box motifs.O11 activates 19-kDaα-zein transcription,stronger than PBF1 but weaker than O2.Notably,PBF1 competitively binds to an overlapping E-box/P-box motif,and represses O11-mediated transactivation.Although O11 does not physically interact with O2,it participates in the O2-centered hierarchical network to enhanceα-zein expression.sw1 o2 and sw1 pbf1 double mutants exhibit smaller,more opaque kernels with further reduced 19-kDa and 22-kDaα-zeins compared to the single mutants,suggesting distinct regulatory effects of these transcription factors on 19-kDa and 22-kDaα-zein genes.Promoter motif analysis suggests that O11,PBF1,and O2 directly regulate 19-kDaα-zein genes,while O11 indirectly controls 22-kDaα-zein genes via O2 and PBF1 modulation.These findings identify the unique and coordinated roles of O11,O2,and PBF1 in regulatingα.-zein genes and kernel development.
文摘In this study,Palm kernel shell(PKS)is utilized as a raw material to produce activated biochar as adsorbent for dye removal from wastewater,specifically methylene blue(MB)dye,by utilizing a simplified and costeffective approach.Production of activated biocharwas carried out using both a furnace and a domesticmicrowave oven without an inert atmosphere.Three samples of palm kernel shell(PKS)based activated biochar labeled as samples A,B and C were carbonized inside the furnace at 800℃ for 1 h and then activated using the microwave-heating technique with varying heating times(0,5,10,and 15 min).The heating was conducted in the absence of an inert gas.Fourier Transform Infrared Spectroscopy(FTIR)highlighted a significant Si-O stretching vibration between 1040.5 to 692.7 cm−1,indicating the presence of key components(Silica and Alumina)in all PKS-based activated biochar samples.For wastewater treatment,activated biochar samples were tested against a 20 mg/LMethylene Blue(MB)solution,and the MB percentage removal was calculated for each run using a standard curve.Central Composite Design(CCD)experiments were conducted for optimization,with activated biochar Sample C exhibiting the highest adsorption capacity at 88.14%MB removal under specific conditions.ANOVA analysis confirmed the significance of the quadratic model,with a p-value of 0.0222 and R^(2)=0.9438.In conclusion,the results demonstrated the efficiency of PKS-based activated biochar as an adsorbent for MB removal in comparison to other commercial adsorbents.
文摘Significant advancements have been achieved in the field of Single Image Super-Resolution(SISR)through the utilization of Convolutional Neural Networks(CNNs)to attain state-of-the-art performance.Recent efforts have explored the incorporation of Transformers to augment network performance in SISR.However,the high computational cost of Transformers makes them less suitable for deployment on lightweight devices.Moreover,the majority of enhancements for CNNs rely predominantly on small spatial convolutions,thereby neglecting the potential advantages of large kernel convolution.In this paper,the authors propose a Multi-Perception Large Kernel convNet(MPLKN)which delves into the exploration of large kernel convolution.Specifically,the authors have architected a Multi-Perception Large Kernel(MPLK)module aimed at extracting multi-scale features and employ a stepwise feature fusion strategy to seamlessly integrate these features.In addition,to enhance the network's capacity for nonlinear spatial information processing,the authors have designed a Spatial-Channel Gated Feed-forward Network(SCGFN)that is capable of adapting to feature interactions across both spatial and channel dimensions.Experimental results demonstrate that MPLKN outperforms other lightweight image super-resolution models while maintaining a minimal number of parameters and FLOPs.
文摘LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.
基金supported by the National Natural Science Foundation of China under Grant No.12072090.
文摘The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the uncertain,complex,and strongly coupled non-Gaussian detection noise.As a result,there are several intractable considerations on the problem of state estimation tasks corrupted by complex non-Gaussian outliers for non-linear dynamics systems in practical application.To address these issues,a new iterated rational quadratic(RQ)kernel high-order unscented Kalman filtering(IRQHUKF)algorithm via capturing the statistics to break through the limitations of the Gaussian assumption is proposed.Firstly,the characteristic analysis of the RQ kernel is investigated in detail,which is the first attempt to carry out an exploration of the heavy-tailed characteristic and the ability on capturing highorder moments of the RQ kernel.Subsequently,the RQ kernel method is first introduced into the UKF algorithm as an error optimization criterion,termed the iterated RQ kernel-UKF(RQ-UKF)algorithm by derived analytically,which not only retains the high-order moments propagation process but also enhances the approximation capacity in the non-Gaussian noise problem for its ability in capturing highorder moments and heavy-tailed characteristics.Meanwhile,to tackle the limitations of the Gaussian distribution assumption in the linearization process of the non-linear systems,the high-order Sigma Points(SP)as a subsidiary role in propagating the state high-order statistics is devised by the moments matching method to improve the RQ-UKF.Finally,to further improve the flexibility of the IRQ-HUKF algorithm in practical application,an adaptive kernel parameter is derived analytically grounded in the Kullback-Leibler divergence(KLD)method and parametric sensitivity analysis of the RQ kernel.The simulation results demonstrate that the novel IRQ-HUKF algorithm is more robust and outperforms the existing advanced UKF with respect to the kernel method in reentry vehicle tracking scenarios under various noise environments.
基金supported by STI 2030-Major Project(2023ZD04069)National Key Research and Development Program of China(2023YFD1202900)+3 种基金The National Science Fund for Distinguished Young Scholars(32425041)The“Breakthrough”Science and Technology Project of Tongliao(TL2024TW001)Science and Technology Demonstration Project of Shandong Province(2024SFGC0402)Pinduoduo-China Agricultural University Research Fund(PC2023A01004).
文摘Transcription factors play critical roles in the regulation of gene expression during maize kernel development.The maize endosperm,a large storage organ,accounting for nearly 90%of the dry weight of mature kernels,serves as the primary site for starch storage.In this study,we identify an endosperm-specific EREB gene,ZmEREB167,which encodes a nucleus-localized EREB protein.Knockout of ZmEREB167 significantly increases kernel size and weight,as well as starch and protein content,compared with the wild type.In situ hybridization experiments show that ZmEREB167 is highly expressed in the BETL as well as PED regions of maize kernels.Dual-luciferase assays show that ZmEREB167 exhibits transcriptionally repressor activity in maize protoplasts.Transcriptome analysis reveals that a large number of genes are up-regulated in the Zmereb167-C1 mutant compared with the wild type,including key genetic factors such as ZmMRP-1 and ZmMN1,as well as multiple transporters involved in maize endosperm development.Integration of RNA-seq and ChIP-seq results identify 68 target genes modulated by ZmEREB167.We find that ZmEREB167 directly targets OPAQUE2,ZmNRT1.1,ZmIAA12,ZmIAA19,and ZmbZIP20,repressing their expressions.Our study demonstrates that ZmEREB167 functions as a negative regulator in maize endosperm development and affects starch accumulation and kernel size.
基金supported by the Swedish Research Council(VR)under grant number 2020-05044by the research environment grant"Gravitational Radiation and Electromagnetic Astrophysical Transients"(GREAT)funded by the Swedish Research Council(VR)under Dnr 2016-06012+2 种基金by the Knut and Alice Wallenberg Foundation under grant Dnr.KAW 2019.0112by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)under Germany's Excellence Strategy-EXC 2121"Quantum Universe"-390833306by the European Research Council(ERC)Advanced Grant INSPIRATION under the European Union's Horizon 2020 Research and Innovation Programme(Grant agreement No.101053985).
文摘We present and explore a new shock-capturing particle hydrodynamics approach.Our starting point is a commonly used discretization of smoothed particle hydrodynamics.We enhance this discretization with Roe’s approx-imate Riemann solver,we identify its dissipative terms,and in these terms,we use slope-limited linear reconstruction.All gradients needed for our method are calculated with linearly reproducing kernels that are constructed to enforce the two lowest-order consistency relations.We scrutinize our reproducing kernel implementation carefully on a“glass-like”particle distribution,and we find that constant and linear functions are recovered to machine precision.We probe our method in a series of challenging 3D benchmark problems ranging from shocks over instabilities to Schulz-Rinne-type vorticity-creating shocks.All of our simulations show excellent agreement with analytic/reference solutions.
基金funded by the National Natural Science Foundation of China(32071921)Key R&D Program of Shandong Province,China(2021LZGC022)Taishan Scholars Project(ts201712024).
文摘Arogenate dehydratase(ADT)catalyzes the final step in phenylalanine synthesis and is crucial for plant development and metabolism.Previously,we demonstrated that the ADT/prephenate dehydratase ZmADT2 is essential for maize resistance to Ustilago maydis and for overall plant development.In this study,we explored the role of ZmADT2 in maize kernel development.The mmsu mutant,a dysfunctional ZmADT2 variant,exhibits delayed embryo and endosperm development,along with deficiencies in carbohydrate and protein storage.Transcriptome analysis revealed differential expression of many kernel compartment-specific genes between mmsu and wild-type(WT)kernels,with impaired nutrient accumulation and auxin signaling pathway in the mmsu endosperm.Compared to WT,ZmADT2 mutation led to reduced auxin levels and smaller endosperm cell size.Exogenous auxin rescued the small kernel phenotype of mmsu.Additionally,auxin distribution was reduced in the basal endosperm transfer layer(BETL),causing defects in its development and function,including reduced transfer cell elongation,cell wall ingrowth and nutrient uptake.These findings suggest that ZmADT2 mediated mediates an auxin signaling pathway that is essential for maize kernel development.
文摘In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To address this issue,we integrate Large Kernel Convolution(LKconv)into the U-Net framework,proposing an enhanced network structure named U-LKconv network,which significantly enhances the capability to recover image details even under low sampling conditions.
基金supported by the National Natural Science Foundation of China(No.22068025).
文摘Palm kernel cake(PKC),a major by-product of the palm oil industry,is rich in non-starch polysaccharides.In this study,two polysaccharide fractions,precipitated with acetic acid(PPA)and ethanol(PPE),respectively,were extracted from PKC using a 2 mol/L NaOH solution.The molecular weight,sugar composition,structural characteristics,morphology,antioxidant activity,as well as in vitro stimulated digestion were investigated in detail.The results revealed that due to its poor solubility of PPA in water,the detected molecular weight of PPA was only 2040 g/mol,which was significantly lower than that of PPE(65,300 g/mol).Although PPA and PPE had a similar sugar composition with varying contents,mannose was the predominant monosaccharide in both,accounting for 87.71%and 60.40%,respectively.Both PPA and PPE were primarily composed of crystalline mannan,consisting of mannopyranosyl units linked by(1→4)-β-glycosidic bonds,along with a small amount of lignin.PPA possibly contained a higher proportion of crystalline mannan,whereas PPE had a larger amount of arabinoxylan and galactomannan.Atomic force microscope revealed a stacked morphology for both PPA and PPE.PPA exhibited a higher scavenging rate against DPPH•and ABTS^(+)•but a weaker HO•scavenging activity and reducing power compared with PPE.Within the polysaccharide concentration range of 0.5-5.0 mg/mL,PPA and PPB demonstrated the strongest scavenging activity against ABTS^(+)•,with the highest scavenging rates exceeding 91%.However,PPA and PPB exhibited the weakest scavenging activity against HO•,with their highest HO•scavenging rates reaching only 44.91%and 55.86%,respectively.The antioxidant activities of both PPA and PPE were weaker than that of ascorbic acid.PPA remained almost stable in the in vitro simulated saliva fluid,while PPE exhibited weaker resistance to it.Both PPA and PPE exhibited weak resistance to the in vitro simulated gastric digestion fluids,but remained relatively stable in the in vitro simulated small-intestinal digestion fluid.The differences in physicochemical properties between PPA and PPE likely played an important role in their distinct biological activities.These findings suggest potential utilization of PKC in exploring dietary polysaccharides with favorable antioxidant activity and unique digestive characteristics.
基金the financial support from the National Key Research and Development Program of China(2021YFD1201004)the Science and Technology Innovation Project,Chinese Academy of Agricultural Sciences(CAAS-ZDRW202201)the Shandong Provincial Key R&D Program,China(2023LZGC010)。
文摘Starch serves as a critical storage component,significantly influencing the grain yield and quality of maize(Zea mays L.).Understanding the genetic basis of natural variation in kernel starch content(SC)is essential for maize breeding to meet future demands.A genome-wide association study(GWAS)identified 84 and 96 loci associated with kernel SC across two years,overlapping with 185 candidate genes.The candidate gene Zm MYB71,encoding a MYB-related transcription factor,demonstrated the highest co-expression frequency with starch synthesis genes.Analysis revealed that Zm MYB71 functions as a nuclear located transcription repressor,and mutants exhibited increased kernel SC by over 2.32%,with minimal impact on amylose content or 100-grain weight.Sh1,Sh2,and GBSSI exhibited up-regulation in mutants by 1.56-,1.45-and 1.32-fold,respectively,aligning with RNA sequencing results;their promoter activities appear directly repressed by Zm MYB71 through the GATATC and TTAGGG motifs.Additionally,the Zm MYB71 elite haplotype Hap1 occurred in over 55%of the high-starch maize sub-populations Iowa Stiff Stalk Synthetic(BSSS)and Partner B(PB),but only in 7.14%of the low-starch sub-population Partner A(PA).Analysis of Hap1 haplotype frequencies across breeding stages revealed a significant increase to 40.28%in inbred groups released after 2010,compared to 28.57 and 27.94%in 1980 and 1990,and 2000,respectively.These findings enhance understanding of natural variation in maize kernel SC and establish Zm MYB71 as a negative regulator with potential applications in SC improvement.
基金supported by the National Key Research and Development Program of China(2021YFF1000304)the National Natural Science Foundation of China(32222060)Anhui Agricultural University(RC422404)to J.Y.
文摘Mitochondria are semi-autonomous organelles present in eukaryotic cells,containing their own genome and transcriptional machinery.However,their functions are intricately linked to proteins encoded by the nuclear genome.Mitochondrial transcription termination factors(mTERFs)are nucleic acid-binding proteins involved in RNA splicing and transcription termination within plant mitochondria and chloroplasts.Despite their recognized importance,the specific roles of mTERF proteins in maize remain largely unexplored.Here,we clone and functionally characterize the maize mTERF18 gene.Our findings reveal that mTERF18 mutations lead to severely undifferentiated embryos,resulting in abortive phenotypes.Early kernel exhibits abnormal basal endosperm transfer layer and a significant reduction in both starch and protein accumulation in mterf18.We identify the mTERF18 gene through mapping-based cloning and validate this gene through allelic tests.mTERF18 is widely expressed across various maize tissues and encodes a highly conserved mitochondrial protein.Transcriptome data reveal that mTERF18 mutations disrupt transcriptional termination of the nad6 gene,leading to undetectable levels of Nad6 protein and reduced complex I assembly and activity.Furthermore,transmission electron microscopy observation of mterf18 endosperm uncover severe mitochondrial defects.Collectively,these findings highlight the critical role of mTERF18 in mitochondrial gene transcription termination and its pivotal impact on maize kernel development.
基金financially supported by the Natural Science Foundation of Hunan Province(project No.2024JJ8037:https://kjt.hunan.gov.cn/kjt/xxgk/tzgg/tzgg_1/202403/t20240311_33144606.html,accessed on 27 October 2025)。
文摘This study evaluated corn kernel drying performance and quality changes using hot air drying(HAD)and infrared drying(ID)across temperatures ranging from 55℃ to 80℃.Optimal drying parameters were determined by using the entropy weight method,with drying time,specific energy consumption,damage rate,fatty acids,starch,polyphenols,and flavonoids as indicators.Results demonstrated that ID significantly outperformed HAD,achieving drying times up to 20%shorter and reducing specific energy consumption and kernel damage by up to 79.3%and 66.7%,respectively,while also better preserving quality attributes.Both methods exhibited drying profiles characterized by acceleration,constant,and falling rate periods,although the constant rate phase was distinctly observable only at lower temperatures.The effective moisture diffusivity under ID was consistently higher than that under HAD,with a maximum increase of 20.4%.The optimal drying conditions were HAD at 65℃ and ID at 80℃.A BP model was also developed and it showed better predictive performance and adaptability than classical mathematical models.
基金supported by the National Natural Science Foundation of China(32201696)the Natural Science Foundation of Sichuan Province(23NSFSC4071)。
文摘Seed maturation is a critical development transition and it largely affects the final yield and quality of crops.Abscisic acid(ABA)-activated sucrose-non-fermentation kinase subfamily 2(SnRK2s)constitute a well-known regulatory network that modulate seed maturation in Arabidopsis;however,the underlying genetic and regulatory mechanisms in cereal crops remain largely unknown.Here,we found that ABA levels exhibited two distinct peaks during kernel development in maize,corresponding to the lag and maturation phase,respectively.Integrated transcriptome and proteome profiling of kernels treated with exogenous ABA at the pre-maturation stage suggested that the second peak of ABA acts as a trigger for kernel maturation program.Knockout of ZmSnRK2s demonstrated that subclassⅢZmSnRK2s are required for kernel maturation in maize,and the loss-of-function of subclassⅢZmSnRK2s showed a disruption in kernel dehydration and dormancy.We identified a conserved ABA–SnRK2–b ZIP signaling pathway mediating this process in maize.Additionally,ZmSnRK2.10 overexpression accelerates kernel dehydration during maturity,achieving reduced kernel moisture content(KMC)at physiological maturity(PM).Overall,our findings establish ABA-activated SnRK2s as central regulators of kernel maturation in maize and provide valuable genetic resources for breeding maize varieties with low moisture content at harvest.
基金funded by National Natural Science Foundation of China(Grants Nos.41825018 and 42141009)the Second Tibetan Plateau Scientific Expedition and Research Program(Grants No.2019QZKK0904)。
文摘As one of the most serious geological disasters in deep underground engineering,rockburst has caused a large number of casualties.However,because of the complex relationship between the inducing factors and rockburst intensity,the problem of rockburst intensity prediction has not been well solved until now.In this study,we collect 292 sets of rockburst data including eight parameters,such as the maximum tangential stress of the surrounding rock σ_(θ),the uniaxial compressive strength of the rockσc,the uniaxial tensile strength of the rock σ_(t),and the strain energy storage index W_(et),etc.from more than 20 underground projects as training sets and establish two new rockburst prediction models based on the kernel extreme learning machine(KELM)combined with the genetic algorithm(KELM-GA)and cross-entropy method(KELM-CEM).To further verify the effect of the two models,ten sets of rockburst data from Shuangjiangkou Hydropower Station are selected for analysis and the results show that new models are more accurate compared with five traditional empirical criteria,especially the model based on KELM-CEM which has the accuracy rate of 90%.Meanwhile,the results of 10 consecutive runs of the model based on KELM-CEM are almost the same,meaning that the model has good stability and reliability for engineering applications.
文摘This paper considers the following Marcinkiewicz type integrals■which can be regarded as an extension of the classical Marcinkiewicz integral po introduced by Stein in[Trans Amer Math Soc,88(1958):159-172],where Ω is a homogeneous function of degree zero on R^(n)with mean value zero in the unit sphere S^(n-1),Under the assumption that Ω∈L^(∞)(S^(n-1)),the authors establish the L^(q)-estimate and weak(1,1)type estimate as well as the corresponding weighted estimates for po.s with 1<q<∞ and 0<β(q-1)n/q.Moreover,the bounds do not depend on β and the strong(q,q)type and weak(1,1)type estimates for the classical Marcinkiewicz integral po can be recovered from the above estimates of μΩ,β whenβ→0.
基金supported by the National Natural Science Foundation of China(Grant Nos.12072022 and 11872105)Fundamental Research Funds for the Central Universities(Grant Nos.FRF-TW-2018-005 and FRF-BR-18-008B).
文摘In this paper,a new temporal-spatial fractional order model is proposed to study the dynamic behavior of thermo-viscoelastic nanoplates.Traditional singular kernel in Caputo fractional order differentiation is replaced by the non-singular kernel and thus leads to a new generalized fractional order differential model with the integer order differential models as a special case.This improved model can more flexibly describe small-scale mechanical behavior and time-dependent heat conduction behavior and provides a clear physical explanation for the fractional order parameters.Spatial nonlocal effects are described in terms of nonlocal strain gradient elasticity and spatial fractional order derivatives,while the time-dependent effects are described in terms of non-Fourier heat conduction,viscoelasticity,and time fractional order derivatives.In addition,it is the first time that the nonlocal characteristic lengths and the memory characteristic times are introduced as two new small-scale parameters in the fractional order derivatives of non-singular kernels to focus on the short-range nonlocal behaviors and the short-term memory behaviors.Numerical examples of the free vibration and the forced vibration under step loading are given,and the effects of the spatial fractional order parameter and the temporal fractional order parameter are both discussed.
基金fnancially supported by the Natural Science Foundation of Hebei Province,China(C2021301004)the State Key Laboratory of North China Crop Improvement and Regulation,China(NCCIR2023KF-10)the HAAFS Science and Technology Innovation Special Project,China(2022KJCXZX-LYS-9)。
文摘The intensified kernel position effect is a common phenomenon in maize production under higher plant density,which limits crop productivity.Subsoiling is an effective agronomic practice for improving crop productivity.To clarify the effect of subsoiling before winter wheat on the kernel position effect of densely grown summer maize and its regulatory mechanism,field experiments were conducted during the 2020-2021 and 2021-2022 growing seasons using a split-plot design.The main plots included two tillage practices:conventional tillage practice(CT)and subsoiling before the sowing of winter wheat(SS);and the subplots consisted of three plant densities(D1-D3 at 6.0×10~4,7.5×10~4,and 9.0×10~4 plants ha-1).Compared with CT,SS alleviated the kernel position effect by increasing the weight ratio of inferior to superior kernels(WR)in the D2 and D3 treated plants.The higher WR of SS treated plants contributed largely to the improved flling of inferior kernels.Under the same plant density,SS signifcantly improved the root dry matter accumulation(DMA)and antioxidant enzyme activities(superoxide dismutase(SOD)and peroxidase(POD)),and it reduced the malondialdehyde(MDA)content,especially for the plants grown under higher plant densities.These results indicated that SS delayed the root senescence,which is associated with the reduced soil bulk density.In addition,compared with CT,SS increased the leaf chlorophyll content from 20 days after silking to physiological maturity and the post-silking leaf area duration,and it reduced the post-silking leaf chlorophyll reduction rate and leaf area reduction rate,indicating that the post-silking leaf senescence had been alleviated.Under the same plant density,the post-silking DMA of SS was obviously higher than that of CT,which was probably related to the improved leaf area duration and photosynthetic enzyme activities(phosphoenolpyruvate carboxylase(PEPC)and Rubisco).The correlation analysis revealed that the main mechanism of SS in alleviating the kernel position effect of densely grown summer maize is as follows:SS delays the post-silking root-shoot senescence by regulating soil physical properties,and further improves the post-silking DMA and flling of inferior kernels,which ultimately alleviates the kernel position effect and improves grain yield.The results of this study provide new theoretical support for the promotion of summer maize yield by subsoiling before winter wheat.
基金supported by the Royal Academy of Engineering,UK,under the scheme of Distinguished International Associates(DIA-2424-5-134).
文摘The state of health SoH of lithium ion batteries plays a predominant role in ensuring the safe and reliable operation of electric vehicles.In this,a novel SoH estimation approach using support vector regression with a Gaussian kernel optimized using the Bayesian optimization technique(BO-SVR with a Gaussian kernel)was proposed.Unlike,traditional approaches that use the internal resistance,and battery capacity as input parameters,this study utilized the equivalent discharging voltage difference interval and equivalent charging voltage difference interval,as they capture the dynamic voltage characteristics associated with the battery degradation.The model was simulated using MATLAB 2023a.The mean absolute error,R^(2),root mean squared error,and mean squared error were considered as performance indicators.The simulation results indicated that the proposed BO-SVR with a Gaussian kernel model had superior performance to other kernel SVR and Gaussian Process Regression models,with a reduced RMSE of 0.0082,thus demonstrating its potential to predict the SoH more accurately.
