Genetic and Agronomic Parameter Estimates of Growth, Yield and Related Traits of Maize (Zea mays L.) under Different Rates of Nitrogen Fertilization

This study evaluated the genetic and agronomic parameter estimates of maize under different nitrogen rates. The trial was established at the Njala Agricultural Research Centre experimental site during 2021 and 2022 in a split block design with three maize varieties (IWCD2, 2009EVDT, and DMR-ESR-Yellow) and seven nitrogen (0, 30, 60, 90, 120, 150 and 180 kg∙N∙ha−1) rates. Findings showed that cob diameter and anthesis silking time (ASI) had intermediate heritability, ASI had high genetic advance, ASI and grain yield had high genotypic coefficient of variation (GCV), while traits with high phenotypic coefficient of variation (PCV) were plant height, ASI, grain yield, number of kernel per cob, number of kernel rows, ear length, and ear height. The PCV values were higher than GCV, indicating the influence of the environment in the studied traits. Nitrogen rates and variety significantly (p < 0.05) influenced grain yield production. Mean grain yields and economic parameter estimates increased with increasing nitrogen rates, with the 30 and 180 kg∙N∙ha−1 plots exhibiting the lowest and highest grain yields of 1238 kg∙ha−1 and 2098 kg∙ha−1, respectively. Variety and nitrogen effects on partial factor productivity (PFPN), agronomic efficiency (AEN), net returns (NR), value cost ratio (VCR) and marginal return (MR) indicated that these parameters were significantly affected (p < 0.05) by these factors. The highest PFPN (41.3 kg grain kg−1∙N) and AEN (29.4 kg grain kg−1∙N) were obtained in the 30 kg∙N∙ha−1 plots, while the highest VCR (2.8) and MR (SLL 1.8 SLL−1 spent on N) were obtained in the 180 kg∙N∙ha−1. The significant influence of variety and nitrogen on traits suggests that increasing yields and maximizing profits require use of appropriate nitrogen fertilization and improved farming practices that could be exploited for increased productivity of maize.

Machine learning-based comparison of factors influencing estimated glomerular filtration rate in Chinese women with or without nonalcoholic fatty liver

BACKGROUND The prevalence of non-alcoholic fatty liver(NAFLD)has increased recently.Subjects with NAFLD are known to have higher chance for renal function impairment.Many past studies used traditional multiple linear regression(MLR)to identify risk factors for decreased estimated glomerular filtration rate(eGFR).However,medical research is increasingly relying on emerging machine learning(Mach-L)methods.The present study enrolled healthy women to identify factors affecting eGFR in subjects with and without NAFLD(NAFLD+,NAFLD-)and to rank their importance.AIM To uses three different Mach-L methods to identify key impact factors for eGFR in healthy women with and without NAFLD.METHODS A total of 65535 healthy female study participants were enrolled from the Taiwan MJ cohort,accounting for 32 independent variables including demographic,biochemistry and lifestyle parameters(independent variables),while eGFR was used as the dependent variable.Aside from MLR,three Mach-L methods were applied,including stochastic gradient boosting,eXtreme gradient boosting and elastic net.Errors of estimation were used to define method accuracy,where smaller degree of error indicated better model performance.RESULTS Income,albumin,eGFR,High density lipoprotein-Cholesterol,phosphorus,forced expiratory volume in one second(FEV1),and sleep time were all lower in the NAFLD+group,while other factors were all significantly higher except for smoking area.Mach-L had lower estimation errors,thus outperforming MLR.In Model 1,age,uric acid(UA),FEV1,plasma calcium level(Ca),plasma albumin level(Alb)and T-bilirubin were the most important factors in the NAFLD+group,as opposed to age,UA,FEV1,Alb,lactic dehydrogenase(LDH)and Ca for the NAFLD-group.Given the importance percentage was much higher than the 2nd important factor,we built Model 2 by removing age.CONCLUSION The eGFR were lower in the NAFLD+group compared to the NAFLD-group,with age being was the most important impact factor in both groups of healthy Chinese women,followed by LDH,UA,FEV1 and Alb.However,for the NAFLD-group,TSH and SBP were the 5th and 6th most important factors,as opposed to Ca and BF in the NAFLD+group.

SUFFICIENT AND NECESSARY CONDITIONS ON THE EXISTENCE AND ESTIMATES OF BOUNDARY BLOW-UP SOLUTIONS FOR SINGULAR p-LAPLACIAN EQUATIONS

Let?denote a smooth,bounded domain in R^(N)(N≥2).Suppose that g is a nondecreasing C^(1)positive function and assume that b(x)is continuous and nonnegative inΩ,and that it may be singular on■Ω.In this paper,we provide sufficient and necessary conditions on the existence of boundary blow-up solutions to the p-Laplacian problem△_(p)u=b(x)g(u)for x∈Ω,u(x)→+∞as dist(x,■Ω)→0.The estimates of such solutions are also investigated.Moreover,when b has strong singularity,the nonexistence of boundary blow-up(radial)solutions and infinitely many radial solutions are also considered.

Estimates on Blow-up Rate of Nonlinear Parabolic Systems with Nonlinear Boundary Conditions

In this paper, the estimate on blow-up rate of the following nonlinear parabolic system is considered：{ut=uxx＋u^l 11v^l 12,vt=vxx＋u^l21v^l22,（x,t）∈（0,1）×（0,T）,ux（0,t）=0,vx（0,t）=0,t∈（0,T）,ux（1,t）=（u^p11v^p12）（1,t）,vx（1,t）=（u^p21v^p22）（1,t）,t∈（0,T）,u（x,0）=u0（x）,v（x,0）=v0（x）,x∈（0,1）We will prove that there exist two positive constants such that：c≤max x∈[0,1]u（x,t）（T-t）^r（l1-1）≤C,0〈t〈T,c≤max x∈[0,1] v（x,t）（T-t）^1/（t1-1）≤C,0〈t〈T.where l1=l21α/α2＋l22,r=α1/α2〉1,α1≤α2〈0.

Physics-informed neural network approach for heat generation rate estimation of lithium-ion battery under various driving conditions

Accurate insight into the heat generation rate(HGR) of lithium-ion batteries(LIBs) is one of key issues for battery management systems to formulate thermal safety warning strategies in advance.For this reason,this paper proposes a novel physics-informed neural network(PINN) approach for HGR estimation of LIBs under various driving conditions.Specifically,a single particle model with thermodynamics(SPMT) is first constructed for extracting the critical physical knowledge related with battery HGR.Subsequently,the surface concentrations of positive and negative electrodes in battery SPMT model are integrated into the bidirectional long short-term memory(BiLSTM) networks as physical information.And combined with other feature variables,a novel PINN approach to achieve HGR estimation of LIBs with higher accuracy is constituted.Additionally,some critical hyperparameters of BiLSTM used in PINN approach are determined through Bayesian optimization algorithm(BOA) and the results of BOA-based BiLSTM are compared with other traditional BiLSTM/LSTM networks.Eventually,combined with the HGR data generated from the validated virtual battery,it is proved that the proposed approach can well predict the battery HGR under the dynamic stress test(DST) and worldwide light vehicles test procedure(WLTP),the mean absolute error under DST is 0.542 kW/m^(3),and the root mean square error under WLTP is1.428 kW/m^(3)at 25℃.Lastly,the investigation results of this paper also show a new perspective in the application of the PINN approach in battery HGR estimation.

BLOW-UP ESTIMATES FOR A NON-NEWTONIAN FILTRATION SYSTEM

The prior estimate and decay property of positive solutions are derived for a system of quasi- linear elliptic differential equations first. Hence, the result of non-existence for differential equation system of radially nonincreasing positive solutions is implied. By using this nonexistence result, blowup estimates for a class quasi-linear reaction-diffusion systems ( non-Newtonian filtration systems) are established, which extends the result of semi-linear reaction diffusion( Fujita type) systems.

Estimates of Convergence Rate of Parallel Multisplitting Itertive Methods

This paper givers an estimated formula of convergence rate for parallel multisplitting iterative method.Using the formula,we can simplify and unify the proof of convergence of PMI_method.

Strong Convergence Rates of Double Kernel Estimates of Conditional Desity Under Stationary Sequences

In the paper,we study the strong convergence rates of double kernel estimates of conditional density under stationary sequences.

Probability estimation method for fatigue crack growth rate based on a∼t data from service

Purpose–The study aims to provide a basis for the effective use of safety-related information data and a quantitative assessment way for the occurrence probability of the safety risk such as the fatigue fracture of the key components.Design/methodology/approach–The fatigue crack growth rate is of dispersion,which is often used to accurately describe with probability density.In view of the external dispersion caused by the load,a simple and applicable probability expression of fatigue crack growth rate is adopted based on the fatigue growth theory.Considering the isolation among the pairs of crack length a and crack formation time t(a∼t data)obtained from same kind of structural parts,a statistical analysis approach of t distribution is proposed,which divides the crack length in several segments.Furthermore,according to the compatibility criterion of crack growth,that is,there is statistical development correspondence among a∼t data,the probability model of crack growth rate is established.Findings–The results show that the crack growth rate in the stable growth stage can be approximately expressed by the crack growth control curve da/dt=5 Q•a,and the probability density of the crack growth parameter Q represents the external dispersion;t follows two-parameter Weibull distribution in certain a values.Originality/value–The probability density f(Q)can be estimated by using the probability model of crack growth rate,and a calculation example shows that the estimation method is effective and practical.

SEIHCRD Model for COVID-19 Spread Scenarios,Disease Predictions and Estimates the Basic Reproduction Number,Case Fatality Rate,Hospital,and ICU Beds Requirement

We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.

BLOW-UP CONDITIONS FOR A SEMILINEAR PARABOLIC SYSTEM ON LOCALLY FINITE GRAPHS

In this paper, we investigate a blow-up phenomenon for a semilinear parabolic system on locally finite graphs. Under some appropriate assumptions on the curvature condition CDE’(n,0), the polynomial volume growth of degree m, the initial values, and the exponents in absorption terms, we prove that every non-negative solution of the semilinear parabolic system blows up in a finite time. Our current work extends the results achieved by Lin and Wu (Calc Var Partial Differ Equ, 2017, 56: Art 102) and Wu (Rev R Acad Cien Serie A Mat, 2021, 115: Art 133).

GLOBAL BLOWUP AND BLOWUP RATE ESTIMATES OF SOLUTIONS FOR A CLASS OF NONLINEAR NON-LOCAL REACTION-DIFFUSION PROBLEMS

In this paper, the global blowup properties of solutions for a class of nonlinear non-local reaction-diffusion problems are investigated by the methods of the prior estimates. Moreover, the blowup rate estimate of the solution is given.

Blow-up Time Estimates of Parabolic Equations with General Coupled Nonlinearities

This paper deals with some parabolic equations,where the reaction and the boundary flux are taken of some general forms.We study the explicit blow-up time estimates according to the different coupled relationship,including the lower and upper bounds of blow-up time for every dimension of space domains.As examples,the results could be used to so many completely coupled models.

On the L_p Convergence Rate of Kernel Estimates for the Nonparametric Regression Function

Let (X,Y) be an R^d×R^1 valued random vector (X_1,Y_1),…, (X_n,Y_n) be a random sample drawn from (X,Y), and let E|Y|<∞. The regression function m(x)=E(Y|X=x) for x∈R^d is estimated by where, and h_n is a positive number depending upon n only, nad K is a given nonnegative function on R^d. In the paper, we study the L_p convergence rate of kernel estimate m_n(x) of m(x) in suitable condition, and improve and extend the results of Wei Lansheng.

Pension replacement rate related to the scope and specific estimates

Pension replacement rate in respect of almost everyone＇s retirement, about the sustainability of the whole pension system, stable relations of society as a whole. For the pension replacement rate study, researchers conducted a more in-depth exploration, according to their different research needs to develop a different pension replacement rate concept. Based on previous studies scholars, for the relevant category of pension replacement rate to sort out, and for different categories of calculation method of the sort, in order to provide a reference for further study of the pension replacement rate.

APPROXIMATION RATES OF ERROR DISTRIBUTION OF DOUBLE KERNEL ESTIMATES OF CONDITIONAL DENSITY

In this paper, the normal approximation rate and the random weighting approximation rate of error distribution of the kernel estimator of conditional density function f(y|x) are studied. The results may be used to construct the confidence interval of f(y|x) .

Approach to estimating non-point pollutant load removal rates based on water environmental capacity: a case study in Shenzhen

An innovative approach based on water environmental capacity for non-point source NPS pollution removal rate estimation was discussed by using both univariate and multivariate data analysis.Taking Shenzhen city as the study case a 67% to 74% NPS pollutant load removal rate can lead to meeting the chemical oxygen demand COD pollution control target for most watersheds.In contrast it is hardly to achieve the ammonia nitrogen NH4-N total phosphorus TP and biological oxygen demand BOD5 pollution control target by simply removing NPS pollutants. This highlights that the pollution control strategies should be taken according to different pollutant species and sources in different watersheds rather than one-size-fits-all .

Loss Rate Estimation of Yield and Output Value of Tobacco Leaf Infected by Tobacco Blown Spot (Alternaria alternata)

[Objective] The paper was to study the effect of tobacco blown spot on the yield and output value of tobacco leaf.[Method]The upper,middle and lower leaves in tobacco plant were selected during the harvest period of tobacco to carry out loss rate estimation of yield and output value of tobacco leaf caused by different disease levels of brown spot.Regression correlation analysis was also conducted.[Result]The disease levels of brown spot had extremely significant strong negative correlation with single leaf weight of tobacco leaf,and it had extremely significant strong positive correlation with the loss rate of single leaf weight.The increase speed of loss rate of single leaf weight of middle and upper leaves was obviously faster than that of lower leaves.The loss rates of single leaf weight of upper,middle and lower leaves were 3.18%-28.95%,3.43%-28.88% and 10.07%-26.90%,respectively.The higher the disease level of blown spot was,the lower the yield and output value of tobacco leaf was,and the corresponding loss rate was also higher.Correlation analysis showed that the disease level of blown spot had extremely significant strong negative correlation with the yield and output value of tobacco leaf,and it had extremely significant strong positive correlation with the loss rate of yield and output value.The negative impact of blown spot on the output value of tobacco leaf was far greater than that on the yield.The highest loss rate of the yield of tobacco leaf was 28.56%,while the highest loss rate of output value reached 89.67%.[Conclusion] The study provided theoretical basis for accurately holding the critical period for the control of blown spot,thus reducing the damage on tobacco leaf and improving the output value of tobacco leaf.

Blow-Up Rate for a Semilinear Parabolic System

This paper deals with the blow-up rate of positive solution for a semilinearparabolic system coupled in the equations and boundary condition. The upper and lower bounds ofblow-up rates are obtained.

BLIND SYMBOL RATE ESTIMATION OF SATELLITE COMMUNICATION SIGNAL BY HAAR WAVELET TRANSFORM

As the raised cosine shaping filter is often employed in practical satellite communication system,the envelope fluctuation at the symbol transition point is decreased which leads to the failure of the common wavelet algorithm under low SNR.Accordingly,a method of blind symbol rate estimation using signal preprocessing and Haar wavelet is proposed in this paper.Firstly,the effect of filter shaping can be reduced by the signal preprocessing.Then,the optimal scale factor is searched and the signal is processed and analyzed by the Haar wavelet transform.Finally,the symbol rate line is extracted and a nonlinear filter method is inducted for improving the estimation performance.Theoretical analysis and computer simulation show the efficiency of the proposed algorithm under low SNR and small roll-off factor.