Chromatic and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems

Adaptive mate choice has been accepted as the leading theory to explain the colorful plumage of birds.This theory hypothesizes that conspicuous colors act as signals to advertise the qualities of the owners.However,a dilemma arises in that conspicuous colors may not only attract mates,but also alert predators.The"private channels of communication"hypothesis proposes that some intraspecific signals may not be visible to heterospecific animals because of different visual systems.To better understand the evolution of plumage colors and sexual selection in birds,here we studied the chromatic difference and achromatic differences of melanin-and carotenoid-based plumage coloration in five minivet species(Pericrocotus spp.)under conspecific and predator visual systems.We found that either the chromatic or achromatic difference among male or female minivets’plumage was consistently higher under conspecific vision than under predator vision for all five studied species of minivets.This result indicated that individual differences in plumage colors of minivets were visible to the conspecific receivers and hidden from potential predators as a result of evolution under predation risk and conspecific communication.However,males were under a higher risk of predation because they were more conspicuous than females to the vision of a nocturnal predator.

Finite-difference modeling of Maxwell viscoelastic media developed from perfectly matched layer

In numerical simulation of wave propagation,both viscoelastic materials and perfectly matched layers(PMLs)attenuate waves.The wave equations for both the viscoelastic model and the PML contain convolution operators.However,convolution operator is intractable in finite-difference time-domain(FDTD)method.A great deal of progress has been made in using time stepping instead of convolution in FDTD.To incorporate PML into viscoelastic media,more memory variables need to be introduced,which increases the code complexity and computation costs.By modifying the nonsplitting PML formulation,I propose a viscoelastic model,which can be used as a viscoelastic material and/or a PML just by adjusting the parameters.The proposed viscoelastic model is essentially equivalent to a Maxwell model.Compared with existing PML methods,the proposed method requires less memory and its implementation in existing finite-difference codes is much easier.The attenuation and phase velocity of P-and S-waves are frequency independent in the viscoelastic model if the related quality factors(Q)are greater than 10.The numerical examples show that the method is stable for materials with high absorption(Q=1),and for heterogeneous media with large contrast of acoustic impedance and large contrast of viscosity.

Well-Posedness and a Finite Difference Approximation for a Mathematical Model of HPV-Induced Cervical Cancer

We present a first-order finite difference scheme for approximating solutions of a mathematical model of cervical cancer induced by the human papillomavirus (HPV), which consists of four nonlinear partial differential equations and a nonlinear first-order ordinary differential equation. The scheme is analyzed and used to provide an existence-uniqueness result. Numerical simulations are performed in order to demonstrate the first-order rate of convergence. A sensitivity analysis was done in order to compare the effects of two drug types, those that increase the death rate of HPV-infected cells, and those that increase the death rate of the precancerous cell population. The model predicts that treatments that affect the precancerous cell population by directly increasing the corresponding death rate are far more effective than those that increase the death rate of HPV-infected cells.

Animal Models of Obsessive-Compulsive Disorder: Strain Differences

Obsessive-compulsive disorder (OCD) is characterized by obsessions (intrusive thoughts, images etc.) and compulsions (repetitive, stereotyped and perseverant acts). Animal models of OCD are specifically devoted to simulating compulsive features of the disorder. In OCD, compulsive behaviors are recognized as repetitive and maladaptive and symptoms relief can be experienced due to treatment with selective serotonin reuptake inhibitors. Many animal models of OCD are provided with some degree of validity. Genetically based differences in behavior in animal models of OCD are of great value, given that human OCD is reported to involve genetic factors. Some animal models of OCD were already used in studies for the evaluation of strain differences. These works were explored in the present review.

Numerical Modelling of Coupled Heat and Mass Transfer in Porous Materials: Application to Cinder Block Bricks

In this work, we present numerical modelling of coupled heat and mass transfer within porous materials. Our study focuses on cinder block bricks generally used in building construction. The material is assumed to be placed in air. Moisture content and temperature have been chosen as the main transfer drivers and the equations governing these transfer drivers are based on the Luikov model. These equations are solved by an implicit finite difference scheme. A Fortran code associated with the Thomas algorithm was used to solve the equations. The results show that heat and mass transfer depend on the temperature of the air in contact with the material. As this air temperature rises, the temperature within the material increases, and more rapidly at the material surface. Also, thermal conductivity plays a very important role in the thermal conduction of building materials and influences heat and mass transfer in these materials. Materials with higher thermal conductivity diffuse more heat.

Analysis of Regional Differences of Energy Footprint in China Based on STIRPAT Model

On the basis of the previous researches and the ecological footprint theory,we use the cross-sectional data of Chinese energy consumption in 2007 to calculate the regional differences of energy consumption footprint of 30 provinces in China;by using the method of EEF calculation method,we calculate the regional distribution of EFI and analyze its law;through the construction of STIRPAT model,we reveal the relationship between EEF and factors of population and economy.The results show that provinces with higher EEF mainly concentrate in the Middle Eastern China,which have a developed industry,such as Shandong,Hebei,Liaoning Province and so on.However,provinces with lower EEF mainly concentrate in the Western China,which have a relatively poor economy,such as Ningxia,Qinghai Province and so on.These results are in accordance with the area distribution of China's economic development level.The EFI decreases gradually from west to east.As the level of regional economy is improved,the EFI has the downward trend.The quantity of population shows notable impact on EFI.The per capita GDP does not show the nagative relationship with EFI,which can not prove the existence of Environmental Kuznets Curve.

Application of Conjugate Gradient Approach for Nonlinear Optimal Control Problem with Model-Reality Differences

In this paper, an efficient computational algorithm is proposed to solve the nonlinear optimal control problem. In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. The aim of applying this model is to take into account the differences between the real plant and the model used during the calculation procedure. In doing so, an expanded optimal control problem is introduced such that system optimization and parameter estimation are mutually interactive. Accordingly, the optimality conditions are derived after the Hamiltonian function is defined. Specifically, the modified model-based optimal control problem is resulted. Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. When the convergence is achieved, the iterative solution approaches to the correct solution of the original optimal control problem, in spite of model-reality differences. For illustration, an economic growth problem is solved by using the algorithm proposed. The results obtained demonstrate the efficiency of the algorithm proposed. In conclusion, the applicability of the algorithm proposed is highly recommended.

A Gauss-Newton Approach for Nonlinear Optimal Control Problem with Model-Reality Differences

Output measurement for nonlinear optimal control problems is an interesting issue. Because the structure of the real plant is complex, the output channel could give a significant response corresponding to the real plant. In this paper, a least squares scheme, which is based on the Gauss-Newton algorithm, is proposed. The aim is to approximate the output that is measured from the real plant. In doing so, an appropriate output measurement from the model used is suggested. During the computation procedure, the control trajectory is updated iteratively by using the Gauss-Newton recursion scheme. Consequently, the output residual between the original output and the suggested output is minimized. Here, the linear model-based optimal control model is considered, so as the optimal control law is constructed. By feed backing the updated control trajectory into the dynamic system, the iterative solution of the model used could approximate to the correct optimal solution of the original optimal control problem, in spite of model-reality differences. For illustration, current converted and isothermal reaction rector problems are studied and the results are demonstrated. In conclusion, the efficiency of the approach proposed is highly presented.

The Precise Finite Difference Method for Seismic Modeling

D seismic modeling can be used to study the propagation of seismic wave exactly and it is also a tool of 3-D seismic data processing and interpretation. In this paper the arbitrary difference and precise integration are used to solve seismic wave equation, which means difference scheme for space domain and analytic integration for time domain. Both the principle and algorithm of this method are introduced in the paper. Based on the theory, the numerical examples prove that this hybrid method can lead to higher accuracy than the traditional finite difference method and the solution is very close to the exact one. Also the seismic modeling examples show the good performance of this method even in the case of complex surface conditions and complicated structures.

Irregular surface seismic forward modeling by a body-fitted rotated–staggered-grid finite-difference method

Finite-difference(FD) methods are widely used in seismic forward modeling owing to their computational efficiency but are not readily applicable to irregular topographies. Thus, several FD methods based on the transformation to curvilinear coordinates using body-fitted grids have been proposed, e.g., stand staggered grid(SSG) with interpolation, nonstaggered grid, rotated staggered grid(RSG), and fully staggered. The FD based on the RSG is somewhat superior to others because it satisfies the spatial distribution of the wave equation without additional memory and computational requirements; furthermore, it is simpler to implement. We use the RSG FD method to transform the firstorder stress–velocity equation in the curvilinear coordinates system and introduce the highprecision adaptive, unilateral mimetic finite-difference(UMFD) method to process the freeboundary conditions of an irregular surface. The numerical results suggest that the precision of the solution is higher than that of the vacuum formalism. When the minimum wavelength is low, UMFD avoids the surface wave dispersion. We compare FD methods based on RSG, SEM, and nonstaggered grid and infer that all simulation results are consistent but the computational efficiency of the RSG FD method is higher than the rest.

Differences of Hydrocarbon Enrichment between the Upper and the Lower Structural Layers in the Tazhong Paleouplift

The Tazhong paleouplift is divided into the upper and the lower structural layers, bounded by the unconformity surface at the top of the Ordovician carbonate rock. The reservoirs in the two layers from different parts vary in number, type and reserves, but the mechanism was rarely researched before. Therefore, an explanation of the mechanism will promote petroleum exploration in Tazhong paleouplift. After studying the evolution and reservoir distribution of the Tazhong paleouplift, it is concluded that the evolution in late Caledonian, late Hercynian and Himalayan periods resulted in the upper and the lower structural layers. It is also defined that in the upper structural layer, structural and stratigraphic overlap reservoirs are developed at the top and the upper part of the paleouplift, which are dominated by oil reservoirs, while for the lower structural layer, lithological reservoirs are developed in the lower part of the paleouplift, which are dominated by gas reservoirs, and more reserves are discovered in the lower structural layer than the upper. Through a comparative analysis of accumulation conditions of the upper and the lower structural layers, the mechanism of enrichment differences is clearly explained. The reservoir and seal conditions of the lower structural layer are better than those of the upper layer, which is the reason why more reservoirs have been found in the former. The differences in the carrier system types, trap types and charging periods between the upper and the lower structural layers lead to differences in the reservoir types and distribution. An accumulation model is established for the Tazhong paleouplift. For the upper structural layer, the structural reservoirs and the stratigraphic overlap reservoirs are formed at the upper part of the paleouplift, while for the lower structural layer, the weathering crust reservoirs are formed at the top, the reef-flat reservoirs are formed on the lateral margin, the karst and inside reservoirs are formed in the lower part of the paleouplift.

Numerical modeling of wave equation by a truncated high-order finite-difference method

Finite-difference methods with high-order accuracy have been utilized to improve the precision of numerical solution for partial differential equations. However, the computation cost generally increases linearly with increased order of accuracy. Upon examination of the finite-difference formulas for the first-order and second-order derivatives, and the staggered finite-difference formulas for the first-order derivative, we examine the variation of finite-difference coefficients with accuracy order and note that there exist some very small coefficients. With the order increasing, the number of these small coefficients increases, however, the values decrease sharply. An error analysis demonstrates that omitting these small coefficients not only maintain approximately the same level of accuracy of finite difference but also reduce computational cost significantly. Moreover, it is easier to truncate for the high-order finite-difference formulas than for the pseudospectral for- mulas. Thus this study proposes a truncated high-order finite-difference method, and then demonstrates the efficiency and applicability of the method with some numerical examples.

EFFICIENT ESTIMATION OF FUNCTIONAL-COEFFICIENT REGRESSION MODELS WITH DIFFERENT SMOOTHING VARIABLES

In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective.

Flow difference effect in the lattice hydrodynamic model

In this paper, a new lattice hydrodynamic model based on Nagatani＇s model INagatani T 1998 Physica A 261 5991 is presented by introducing the flow difference effect. The stability condition for the new model is obtained by using the linear stability theory. The result shows that considering the flow difference effect leads to stabilization of the system compared with the original lattice hydrodynamic model. The jamming transitions among the freely moving phase, the coexisting phase, and the uniform congested phase are studied by nonlinear analysis. The modified KdV equation near the critical point is derived to describe the traffic jam, and kink -antikink soliton solutions related to the traffic density waves are obtained. The simulation results are consistent with the theoretical analysis for the new model.

Three-dimensional forward modeling and inversion of borehole-to-surface electrical imaging with different power sources

Borehole-to-surface electrical imaging （BSEI） uses a line source and a point source to generate a stable electric field in the ground. In order to study the surface potential of anomalies, three-dimensional forward modeling of point and line sources was conducted by using the finite-difference method and the incomplete Cholesky conjugate gradient （ICCG） method. Then, the damping least square method was used in the 3D inversion of the formation resistivity data. Several geological models were considered in the forward modeling and inversion. The forward modeling results suggest that the potentials generated by the two sources have different surface signatures. The inversion data suggest that the low- resistivity anomaly is outlined better than the high-resistivity anomaly. Moreover, when the point source is under the anomaly, the resistivity anomaly boundaries are better outlined than when using a line source.

Second-order difference scheme for a nonlinear model of wood drying process

A numerical simulation for a model of wood drying process is considered. The model is given by a couple of nonlinear differential equations. One is a nonlinear parabolic equation and the other one is a nonlinear ordinary equation. A difference scheme is derived by the method of reduction of order. First, a new variable is introduced and the original problem is rewritten into a system of the first-order differential equations. Secondly, a difference scheme is constructed for the later problem. The solvability, stability and convergence of the difference scheme are proved by the energy method. The convergence order of the difference scheme is secondorder both in time and in space. A prior error estimate is put forward. The new variable is put aside to reduce the computational cost. A numerical example testifies the theoretical result.

Effect of strain rate difference between inside and outside groove in M-K model on prediction of forming limit curve of Ti6Al4V at elevated temperatures

The influence of initial groove angle on strain rate inside and outside groove of Ti6Al4V alloy was investigated.Based on the evolution of strain rate inside and outside groove,the effect of strain rate difference on the evolution of normal stress and effective stress inside and outside groove was also analyzed.The results show that when linear loading path changes from uniaxial tension to equi-biaxial tension,the initial groove angle plays a weaker role in the evolution of strain rate in the M-K model.Due to the constraint of force equilibrium between inside and outside groove,the strain rate difference makes the normal stress inside groove firstly decrease and then increase during calculation,which makes the prediction algorithm of forming limit convergent at elevated temperature.The decrease of normal stress inside groove is mainly caused by high temperature softening effect and the rotation of groove,while the increase of normal stress inside groove is mainly due to strain rate hardening effect.

Modeling Tracer Flow Characteristics in Different Types of Pores: Visualization and Mathematical Modeling

Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tracer transport,this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport.The visualization results show a faster tracer movement into movable water than it into bound water,and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity.Moreover,the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression.The new model also distinguishes flowing and storage pores,accounting for different tracer transport mechanisms(dispersion,diffusion and adsorption)in different types of pores.The resulting analytical solution better matches with tracer production data than the standard model.The residual sum of squares(RSS)from the new model is 0.0005,which is 100 times smaller than the RSS from the standard model.The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope,whereas the superficial velocity and bound water saturation show a positive correlation.

A geometrically and locally adaptive remeshing method for finite difference modeling of mining-induced surface subsidence

Surface subsidence induced by underground mining is a typical serious geohazard.Numerical approaches such as the discrete element method(DEM)and finite difference method(FDM)have been widely used to model and analyze mining-induced surface subsidence.However,the DEM is typically computationally expensive,and is not capable of analyzing large-scale problems,while the mesh distortion may occur in the FDM modeling of largely deformed surface subsidence.To address the above problems,this paper presents a geometrically and locally adaptive remeshing method for the FDM modeling of largely deformed surface subsidence induced by underground mining.The essential ideas behind the proposed method are as follows:(i)Geometrical features of elements(i.e.the mesh quality),rather than the calculation errors,are employed as the indicator for determining whether to conduct the remeshing;and(ii)Distorted meshes with multiple attributes,rather than those with only a single attribute,are locally regenerated.In the proposed method,the distorted meshes are first adaptively determined based on the mesh quality,and then removed from the original mesh model.The tetrahedral mesh in the distorted area is first regenerated,and then the physical field variables of old mesh are transferred to the new mesh.The numerical calculation process recovers when finishing the regeneration and transformation.To verify the effectiveness of the proposed method,the surface deformation of the Yanqianshan iron mine,Liaoning Province,China,is numerically investigated by utilizing the proposed method,and compared with the numerical results of the DEM modeling.Moreover,the proposed method is applied to predicting the surface subsidence in Anjialing No.1 Underground Mine,Shanxi Province,China.

Susceptibility-weighted imaging is suitable for evaluating signal strength in different brain regions of a rabbit model of acute hemorrhagic anemia

Acute hemorrhagic anemia can decrease blood flow and oxygen supply to brain, and affect its physiological function. While detecting changes in brain function in patients with acute hemorrhagic anemia is helpful for preventing neurological complications and evaluating therapeutic effects, clinical changes in the nervous systems of these patients have not received much attention. In part, this is because current techniques can only indirectly detect changes in brain function following onset of anemia, which leads to lags between real changes in brain function and their detection.