Assessment of immune responses and intestinal flora in BALB/c mice model of wheat food allergy via different sensitization methods

Increasing incidences showed that food allergies have attracted more and more attention from researchers.BALB/c mice were sensitized with wheat gluten combined with aluminum hydroxide adjuvant via intraperitoneal injection,transdermal sensitization,and oral gavage sensitization route.Results showed that all the three sensitization methods could induce allergic symptoms;increase the serum antibody(total immunoglobulin E(IgE),specific IgE,IgG,IgA)and histamine content;promote the secretion of Th2 cytokines(interleukin(IL)-4,IL-5,IL-13)and inflammatory factors(IL-6,IL-17 A,IL-10);and inhibit the production of Th1 cytokines(IFN-γ,IL-2).However,the allergic symptoms of mice sensitized by intraperitoneal injection were the most obvious among the three models.The level of serum antibodies in intraperitoneal injection group was significantly higher than control.Subsequently,16 S rRNA sequencing technology was used to analyze the intestinal flora of mice.The results showed that the abundance of Firmicutes in the wheat protein sensitized group was lower than that in the normal group,while the abundance of Bacteroidetes was higher,and Lactobacillus was the difference marker in normal group.Bacterial species diversity analysis showed that the species richness and diversity of intestinal flora in mice were decreased,the difference between mice induced by intraperitoneal injection and normal control group mice was the most significant.Taken together,these results show that among three sensitization methods used to build a mouse model with aluminum hydroxide as adjuvant,intraperitoneal injection is the comparably best way to build a mouse sensitization mode.

Border Sensitive Knowledge Distillation for Rice Panicle Detection in UAV Images

Research on panicle detection is one of the most important aspects of paddy phenotypic analysis.A phenotyping method that uses unmanned aerial vehicles can be an excellent alternative to field-based methods.Nevertheless,it entails many other challenges,including different illuminations,panicle sizes,shape distortions,partial occlusions,and complex backgrounds.Object detection algorithms are directly affected by these factors.This work proposes a model for detecting panicles called Border Sensitive Knowledge Distillation(BSKD).It is designed to prioritize the preservation of knowledge in border areas through the use of feature distillation.Our feature-based knowledge distillation method allows us to compress the model without sacrificing its effectiveness.An imitation mask is used to distinguish panicle-related foreground features from irrelevant background features.A significant improvement in Unmanned Aerial Vehicle(UAV)images is achieved when students imitate the teacher’s features.On the UAV rice imagery dataset,the proposed BSKD model shows superior performance with 76.3%mAP,88.3%precision,90.1%recall and 92.6%F1 score.

Application of the extended Fourier amplitude sensitivity testing(FAST)method to inflated,axial stretched,and residually stressed cylinders

This paper is dedicated to applying the Fourier amplitude sensitivity test(FAST)method to the problem of mixed extension and inflation of a circular cylindrical tube in the presence of residual stresses.The metafunctions and the Ishigami function are considered in the sensitivity analysis(SA).The effects of the input variables on the output variables are investigated,and the most important parameters of the system under the applied pressure and axial force such as the axial stretch and the azimuthal stretch are determined.

Reliability Sensitivity-based Correlation Coefficient Calculation in Structural Reliability Analysis

The correlation coefficients of random variables of mechanical structures are generally chosen with experience or even ignored,which cannot actually reflect the effects of parameter uncertainties on reliability.To discuss the selection problem of the correlation coefficients from the reliability-based sensitivity point of view,the theory principle of the problem is established based on the results of the reliability sensitivity,and the criterion of correlation among random variables is shown.The values of the correlation coefficients are obtained according to the proposed principle and the reliability sensitivity problem is discussed.Numerical studies have shown the following results：（1） If the sensitivity value of correlation coefficient ρ is less than（at what magnitude 0.000 01）,then the correlation could be ignored,which could simplify the procedure without introducing additional error.（2） However,as the difference between ρs,that is the most sensitive to the reliability,and ρR,that is with the smallest reliability,is less than 0.001,ρs is suggested to model the dependency of random variables.This could ensure the robust quality of system without the loss of safety requirement.（3） In the case of ｜Eabs｜ρ0.001 and also ｜Erel｜ρ0.001,ρR should be employed to quantify the correlation among random variables in order to ensure the accuracy of reliability analysis.Application of the proposed approach could provide a practical routine for mechanical design and manufactory to study the reliability and reliability-based sensitivity of basic design variables in mechanical reliability analysis and design.

Sensitivity analysis of influencing parameters in cavern stability

In order to analyze the stability of the underground rock structures,knowing the sensitivity of geomechanical parameters is important.To investigate the priority of these geomechanical properties in the stability of cavern,a sensitivity analysis has been performed on a single cavern in various rock mass qualities according to RMR using Phase 2.The stability of cavern has been studied by investigating the side wall deformation.Results showed that most sensitive properties are coefficient of lateral stress and modulus of deformation.Also parameters of Hoek-Brown criterion and r c have no sensitivity when cavern is in a perfect elastic state.But in an elasto-plastic state,parameters of Hoek-Brown criterion and r c affect the deformability;such effect becomes more remarkable with increasing plastic area.Other parameters have different sensitivities concerning rock mass quality(RMR).Results have been used to propose the best set of parameters for study on prediction of sidewall displacement.

Reliability and sensitivity analyses of HPT blade-tip radial running clearance using multiply response surface model

To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysis of BTRRC was accomplished from a probabilistic prospective by considering nonlinear material attributes and dynamic loads. Firstly, multiply response surface model(MRSM) was proposed and the mathematical model of this method was established based on quadratic function. Secondly, the BTRRC was decomposed into three sub-components(turbine disk, blade and casing), and then the single response surface functions(SRSFs) of three structures were built in line with the basic idea of MRSM. Thirdly, the response surface function(MRSM) of BTRRC was reshaped by coordinating SRSFs. From the analysis, it is acquired to probabilistic distribution characteristics of input-output variables, failure probabilities of blade-tip clearance under different static blade-tip clearances δ and major factors impacting BTRRC. Considering the reliability and efficiency of gas turbine, δ=1.87 mm is an optimally acceptable option for rational BTRRC. Through the comparison of three analysis methods(Monte Carlo method, traditional response surface method and MRSM), the results show that MRSM has higher accuracy and higher efficiency in reliability sensitivity analysis of BTRRC. These strengths are likely to become more prominent with the increasing times of simulations. The present study offers an effective and promising approach for reliability sensitivity analysis and optimal design of complex dynamic assembly relationship.

Ergodic sensitivity analysis of one-dimensional chaotic maps

Sensitivity analysis in chaotic dynamical systems is a challenging task from a computational point of view.In this work,we present a numerical investigation of a novel approach,known as the space-split sensitivity or S3 algorithm.The S3 algorithm is an ergodic-averaging method to differentiate statistics in ergodic,chaotic systems,rigorously based on the theory of hyperbolic dynamics.We illustrate S3 on one-dimensional chaotic maps,revealing its computational advantage over na?ve finite difference computations of the same statistical response.In addition,we provide an intuitive explanation of the key components of the S3 algorithm,including the density gradient function.

Optimal control of natural resources in mining industry

The paper focuses on the optimal control of natural resources in mining industry. The purpose is to pro- pose an optimal extraction series of these resources during the lifetime of the Mine＇s maintenance. Fol- lowing the proposed optimal control model, a sensitivity analysis has been performed that includes the interest rate impact on the optimal solution. This study shows that the increasing of the interest rate sti- mulates faster extraction of the resources. The discounting factor induces that the resource has to be extracted faster hut this effect is counterbalanced by the diminishing returns of the annual cash flow. At higher parameters of ＂alpha＂ close to one of the power function about 80% from the whole resource will be extracted during the first 4 years of object/mine maintenance. An existence of unique positive root with respect to return of investment has been proposed and proved by two ways： by the ＂method of chords＂ and by using specialized software.

An inverse problem to estimate an unknown order of a Riemann-Liouville fractional derivative for a fractional Stokes' first problem for a heated generalized second grade fluid

In this paper,we propose a numerical method to estimate the unknown order of a Riemann-Liouville fractional derivative for a fractional Stokes＇ first problem for a heated generalized second grade fluid.The implicit numerical method is employed to solve the direct problem.For the inverse problem,we first obtain the fractional sensitivity equation by means of the digamma function,and then we propose an efficient numerical method,that is,the Levenberg-Marquardt algorithm based on a fractional derivative,to estimate the unknown order of a Riemann-Liouville fractional derivative.In order to demonstrate the effectiveness of the proposed numerical method,two cases in which the measurement values contain random measurement error or not are considered.The computational results demonstrate that the proposed numerical method could efficiently obtain the optimal estimation of the unknown order of a RiemannLiouville fractional derivative for a fractional Stokes＇ first problem for a heated generalized second grade fluid.

Shape optimization of axisymmetric solids with the finite cell method using a fixed grid

In this work, a design procedure extending the B-spline based finite cell method into shape optimization is developed for axisymmetric solids involving the centrifugal force effect. We first replace the traditional conforming mesh in the finite element method with structured cells that are fixed during the whole design process with a view to avoid the sophisticated re-meshing and eventual mesh distortion.Then, B-spline shape functions are further implemented to yield a high-order continuity field along the cell boundary in stress analysis. By means of the implicit description of the shape boundary, stress sensitivity is analytically derived with respect to shape design variables. Finally, we illustrate the efficiency and accuracy of the proposed protocol by several numerical test cases as well as a whole design procedure carried out on an aeronautic turbine disk.

Second-order sensitivity of eigenpairs in multiple parameter structures

This paper presents methods for computing a second-order sensitivity matrix and the Hessian matrix of eigenvalues and eigenvectors of multiple parameter structures. Second-order perturbations of eigenvalues and eigenvectors are transformed into multiple parameter forms,and the second-order perturbation sensitivity matrices of eigenvalues and eigenvectors are developed.With these formulations,the efficient methods based on the second-order Taylor expansion and second-order perturbation are obtained to estimate changes of eigenvalues and eigenvectors when the design parameters are changed. The presented method avoids direct differential operation,and thus reduces difficulty for computing the second-order sensitivity matrices of eigenpairs.A numerical example is given to demonstrate application and accuracy of the proposed method.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

A network-based virtual slack bus model for energy conversion units in dynamic energy flow analysis

Integrated energy system(IES) is a viable route to “carbon peak and carbon neutral”. As the basis and cornerstone of economic operation and security of IES, energy flow calculation(EFC) has been widely studied. Traditional EFC focuses on the single or distributed slack bus models, which results in the lack of unlimited power to maintain system operation, especially for electric power grid working in islanded or coupled mode. To deal with this problem, this paper proposes a network-based virtual-slack bus(VSB) model in EFC. Firstly, considering the anticipated growth of energy conversion units(ECUs) with power adjustment capacity, the generators and ECUs are together modeled as a virtual slack bus model to reduce the concentrated power burden of IES. Based on this model, a power sensitivity method is designed to achieve the power sharing among the ECUs, where the power can be allocated adaptively based on the network conditions. Moreover, the method is helpful to maintain the voltage and pressure profile of IES. With these changes, a dynamic energy flow analysis including virtual slack bus types is extended for IES.It can realize the assessment of the system state. Finally, simulation studies illustrate the beneficial roles of the VSB model.

Impact of Renewable Energy Sources on Steady-state Stability of Weak AC/DC Systems

In recent years,the penetration of renewable resources into AC power systems has increased tremendously,creating a significantly impact on the latter’s operations and stability.In this respect,it is also important to gain a basic analytical understanding of such impact on the steady-state stability of power systems with electrically weak AC/DC interconnections,but such works are not very evident in the literature.Therefore,a classical analytic model of the single and multi-infeed HVDC system which now incorporates renewable resources is proposed.Then the well-established concept of voltage sensitivity of the AC/DC interconnection is applied to analyze the impact of the renewable resources on the steady-state stability of these composite system models,as well as on the influence of system conditions and parameters.This impact is also compared with that arising from other types of shunt devices alternatively connected at the same AC/DC interconnection,therefore their relative beneficial or negative impacts will also be benchmarked.

Characterization of the Rice Canopy Infested with Brown Spot Disease Using Field Hyperspectral Data

Based on the field hyperspectral data from the analytical spectral devices （ASD） spectrometer, we characterized the spectral properties of rice canopies infested with brown spot disease and selected spectral regions and bands sensitive to four severity degrees （severe, moderate, light, and healthy）. The results show that the curves＇ variation on the original and the first- and second-order de- rivative curves are greatly different, but the spectral difference in the near-infrared region is the most obvious for each level. Specifically, the peaks are located at 822, 738, and 793 nm, while the valleys are located at 402, 570, and 753 run, respectively. The sensitive regions are between 430-520, 530-550, and 650-710 nm, and the bands are 498, 539, and 673 nm in the sensitivity analysis, while they are in the ranges of 401-530, 550-730 as well as at 498 nm and 678 nm in the continuum removal.

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Identifying source information after river chemical spill occurrences is critical for emergency responses.However,the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated.To fill this gap,stochastic analysis approaches,including a regional sensitivity analysis method,identifiability plot and perturbation methods,were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework.Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules.For example,the release load can be most easily inverted,and the source location is responsible for the largest uncertainty among the source parameters.The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty.The differences among the different objective functions are smaller for instantaneous release than for continuous release cases.Small monitoring errors affect the inversion results only slightly,which can be ignored in practice.Interestingly,the estimated values of the release location and time negatively deviate from the real values,and the extent is positively correlated with the relative size of the mixing zone to the objective river reach.These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

Impact of Climate Change on Maize Potential Productivity and the Potential Productivity Gap in Southwest China

The impact of climate change on maize potential productivity and the potential productivity gap in Southwest China（SWC） are investigated in this paper.We analyze the impact of climate change on the photosynthetic,light-temperature,and climatic potential productivity of maize and their gaps in SWC,by using a crop growth dynamics statistical method.During the maize growing season from 1961 to 2010,minimum temperature increased by 0.20℃ per decade（p 〈 0.01） across SWC.The largest increases in average and minimum temperatures were observed mostly in areas of Yunnan Province.Growing season average sunshine hours decreased by 0.2 h day^（-1） per decade（p 〈 0.01） and total precipitation showed an insignificant decreasing trend across SWC.Photosynthetic potential productivity decreased by 298 kg ha^（-1）per decade（p 〈 0.05）.Both light-temperature and climatic potential productivity decreased（p 〈 0.05） in the northeast of SWC,whereas they increased（p 〈 0.05） in the southwest of SWC.The gap between lighttemperature and climatic potential productivity varied from 12 to 2729 kg ha^（-1）,with the high value areas centered in northern and southwestern SWC.Climatic productivity of these areas reached only 10%-24%of the light-temperature potential productivity,suggesting that there is great potential to increase the maize potential yield by improving water management in these areas.In particular,the gap has become larger in the most recent 10 years.Sensitivity analysis shows that the climatic potential productivity of maize is most sensitive to changes in temperature in SWC.The findings of this study are helpful for quantification of irrigation water requirements so as to achieve maximum yield potentials in SWC.

Sensitivity Analysis of the Hydrodynamic Coefficients in 4 Degrees of Freedom Ship Manoeuvring Mathematical Model

The S-type test is simulated based on a ship manoeuvring mathematical model of 4 degrees of freedom(4-DOF);simultaneously,sensitivity analysis of the hydrodynamic coefficients in the mathematical model is implemented by using an indirect method.The mathematical model is simplified by omitting the coefficients of smaller sensitivity according to the results of sensitivity analysis.The 10°/10° zigzag test and 35° turning circle manoeuvre are simulated with the original and the simplified mathematical models.The comparison of the simulation results shows the effectiveness of the sensitivity analysis and the validity of the simplified model.

An improved method of angle measurement with a position sensitive detector

An improved method of angle measurement is proposed based on a parallel plate interferometer. A position detection system is incorporated into a parallel plate interferometer in order to realize large deflection angle measurement. A reflecting mirror is introduced for increasing the measurement resolution. In experiments, a deflection angle of a measured target was measured within ～3° with high accuracy. And as a phase modulating interferometer, it was used to measure a small angular displacement with a repeatability of 5.5 × 10^-8 rad.

A sensitive and convenient enzyme-linked immunosorbent assay method in serum MG7 antigen detection in gastric cancer

Objective To explore a highly sensitive and highly specific method to detect the serum MG7 antigen(Ag)level for early gastric cancer diagnosis.Methods The serum MG7-Ag level was detected by enzyme-linked immunosorbent assay(ELISA)method in 116 preoperative gastric cancer patients,63 postoperative gastric cancer patients,41 patients with precancerous lesion,37 pa-