Linear-in-Parameter Models Based on Parsimonious Genetic Programming Algorithm and Its Application to Aero-Engine Start Modeling

A novel Parsimonious Genetic Programming （PGP） algorithm together with a novel aero-engine optimum data-driven dynamic start process model based on PGP is proposed. In application of this method, first, the traditional Genetic Programming（GP） is used to generate the nonlinear input-output models that are represented in a binary tree structure; then, the Orthogonal Least Squares algorithm （OLS） is used to estimate the contribution of the branches of the tree （refer to basic function term that cannot be decomposed anymore according to special rule） to the accuracy of the model, which contributes to eliminate complex redundant subtrees and enhance GP＇s convergence speed; and finally, a simple, reliable and exact linear-in-parameter nonlinear model via GP evolution is obtained. The real aero-engine start process test data simulation and the comparisons with Support Vector Machines （SVM） validate that the proposed method can generate more applicable, interpretable models and achieve comparable, even superior results to SVM.

Roll System and Stock's Multi-parameter Coupling Dynamic Modeling Based on the Shape Control of Steel Strip

The existence of rolling deformation area in the rolling mill system is the main characteristic which dis- tinguishes the other machinery. In order to analyze the dynamic property of roll system＇s flexural deformation, it is necessary to consider the transverse periodic movement of stock in the rolling deformation area which is caused by the flexural deformation movement of roll system simul- taneously. Therefore, the displacement field of roll system and flow of metal in the deformation area is described by kinematic analysis in the dynamic system. Through intro- ducing the lateral displacement function of metal in the deformation area, the dynamic variation of per unit width rolling force can be determined at the same time. Then the coupling law caused by the co-effect of rigid movement and flexural deformation of the system structural elements is determined. Furthermore, a multi-parameter coupling dynamic model of the roll system and stock is established by the principle of virtual work. More explicitly, the cou- pled motion modal analysis was made for the roll system. Meanwhile, the analytical solutions for the flexural defor- mation movement＇s mode shape functions of rolls are discussed. In addition, the dynamic characteristic of the lateral flow of metal in the rolling deformation area has been analyzed at the same time. The establishment ofdynamic lateral displacement function of metal in the deformation area makes the foundation for analyzing the coupling law between roll system and rolling deformation area, and provides a theoretical basis for the realization of the dynamic shape control of steel strip.

Highly maneuvering target tracking using multi-parameter fusion Singer model

An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.

Multi-parameter quantitative assessment of 3D geological models for complex fault-block oil reservoirs

In the field of 3 D geologic modeling, researchers often pay more attention to modeling methods and workflows, but neglect the quantitative evaluation of models. If the evaluation is narrowed to the same reservoir type, the comparability and practicality of quantitative assessment will be emerging. The evaluation system should include three parts: data verification, geological understanding and process check. Data verification mainly involves testing the accuracy of local prediction with actual data, and geological understanding is to examine whether the global estimation honors geological principles and prior insights. Process check is also indispensable to avoid occasionality. To this end, we produced a set of assessment criteria, taking complex fault-block sandstone oil reservoir as an example. To be specific, thirteen characteristic parameters were totally selected, setting weights according to their rated importance, formulating three-level evaluation standards in a centesimal system for each characteristic parameter, and obtaining the final assessment based on the cumulative score. The results indicate that such evaluation can not only access the quality of the model objectively and comprehensively, but also identify the aspects in need of improvement through the deduction items.

A five-parameter constitutive model for hysteresis shearing and energy dissipation of rock joints

Rock joints exhibit hysteresis shearing behavior and produce energy dissipation under shear cyclic loads,which however cannot be accurately depicted by existing constitutive models. This paper establishes a constitutive model for hysteresis shearing and associated energy dissipation of rock joints. Analytical expressions of the model during cyclic shearing processes are derived. Derivation of the model indicates no energy dissipation in the elastic stage. When the shear load exceeds elastic boundary, nonlinear energy dissipation takes place. Validations with experiments show that the proposed model provides good conformities with direct shear curves and hysteresis loops, and can predict the energy dissipation characteristics of rock joints under different working conditions. Compared to the constitutive models using Weibull's distribution, the proposed one is smooth at the elastic boundary and can accurately capture the maximum shear stress. Unlike the existing incremental-type models, the proposed one provides clear and direct analytical expressions for both shear stress and energy dissipation during the whole displacement domain, which is more convenient in application.

Auto-parametric resonance of a continuous-beam-bridge model under two-point periodic excitation:an experimental investigation and stability analysis

The auto-parametric resonance of a continuous-beam bridge model subjected to a two-point periodic excitation is experimentally and numerically investigated in this study.An auto-parametric resonance experiment of the test model is conducted to observe and measure the auto-parametric resonance of a continuous beam under a two-point excitation on columns.The parametric vibration equation is established for the test model using the finite-element method.The auto-parametric resonance stability of the structure is analyzed by using Newmark's method and the energy-growth exponent method.The effects of the phase difference of the two-point excitation on the stability boundaries of auto-parametric resonance are studied for the test model.Compared with the experiment,the numerical instability predictions of auto-parametric resonance are consistent with the test phenomena,and the numerical stability boundaries of auto-parametric resonance agree with the experimental ones.For a continuous beam bridge,when the ratio of multipoint excitation frequency(applied to the columns)to natural frequency of the continuous girder is approximately equal to 2,the continuous beam may undergo a strong auto-parametric resonance.Combined with the present experiment and analysis,a hypothesis of Volgograd Bridge's serpentine vibration is discussed.

GIS-Based Hydrogeological-Parameter Modeling

A regression model is proposed to relate the variation of water well depth with topographic properties (area and slope), the variation of hydraulic conductivity and vertical decay factor. The implementation of this model in GIS environment (ARC/TNFO) based on known water data and DEM is used to estimate the variation of hydraulic conductivity and decay factor of different lithology units in watershed context.

LUMPED-PARAMETER MODEL OF MASS TRANSFER IN HEMODIALYZER WITH ULTRAFILTRATION

1 INTRODUCTIONHemodialysis with ultrafiltration,also called hemodiafiltration(HDF),is a main methodof treatment for patients with chronic renal failure.The HDF procedure providesadequate removals of both small and middle molecular weight toxic substamces fromuremic blood,which is not possible by dialysis or ultrafiltration alone.According toclinical experience[1],the HDF procedure is well accepied by the patients,and thetreatment time is reduced by using it.

A TWO-PARAMETER MODEL FOR THREE TYPES OF NUCLEPORE FILTRATION OF LEUKOCYTES

Micropore filtration of leukocytes is one of the main methods for evaluating leukocytes' deformability. Here a biofluid mechanical model was proposed for three cases: (i) filtration under gravity; (ii) constant pressure filtration; (iii) constant flow rate filtration. In previous models, constant blood cell resistance was assumed. In this paper, when evaluating the filter resistance to leukocytes, not only the effect of the change in the driving pressure but also the difference in the deformability of individual leukocytes are taken into consideration. Moreover, based on Moessmer's experimental results, a probability distribution function for the transit time of polymorphonuclear cells (PMNs) through the filter is assumed. Finally, numerical curves are obtained for the above three types of filtration and the comparison between the theoretical and experimental results of PMNs for case (i) turns out to be satisfactory. The two parameters in the model, A and B represent leukocytes' deformability under low and high pressure respectively.

Feasibility study on the binary-parameter retrieval model of ocean suspended sediment concentration based on MODIS data

This paper brought out a new idea on the retrieval of suspended sediment concentration, which uses both the water-leaving radiance from remote sensing data and the grain size of the suspended sediment. A principal component model and a neural network model based on those two parameters were constructed. The analyzing results indicate that testing errors of the models using the two parameters are 0.256 and 0.244, while the errors using only water-leaving radiance are 0,384 and 0.390. The stability of the models with grain size parameter is also better than the one without grain size. This research proved that it is necessary to introduce the grain size parameter into suspended sediment concentration retrieval models in order to improve the retrieval precision of these models.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Critical Finite Size Scaling Relation of the Order-Parameter Probability Distribution for the Three-Dimensional Ising Model on the Creutz Cellular Automaton

We study the order parameter probability distribution at the critical point for the three-dimensional spin-1/2 and spin-1 Ising models on the simple cubic lattice under periodic boundary conditions. The finite size scaling relation for the order parameter probability distribution is tested and verified numerically by microcanonical Creutz cellular automata simulations. The state critical exponent δ, which characterizes the far tail regime of the scaling order parameter probability distribution, is estimated for three-dimensional Ising models using the cellular automaton simulations at the critical temperature. The results are in good agreement with the Monte Carlo calculations.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

A two-parameter mathematical model for immobilizedenzymes and Homotopy analysis method

A two parameter mathematical model was developed to find the concentration for immobilized enzyme systems in porous spherical particles. This model contains a non-linear term related to reversible Michaelies-Menten kinetics. Analytical expression pertaining to the substrate concentration was reported for all possible values of Thiele module φ and α . In this work, we report the theoretically evaluated steady-state effectiveness factor for immobilized enzyme systems in porous spherical particles. These analytical results were found to be in good agreement with numerical results. Moreover, herein we employ new “Homotopy analysis method” (HAM) to solve non-linear reaction/diffusion equation.

Re-Parameterization the Logistic Model in Assessing Changes in the Baroreceptor Reflex

The logistic model is frequently used to describe the nonlinear relationship between systemic arterial pressure (SAP) and carotid sinus pressure (CSP). In this paper, we propose using maximum gain and saturation as parameters in the logistic model. By this method, the estimates and standard errors together with confidence intervals for maximum gain and saturation are direct outputs from the curve fitting, which also makes it easy to perform various hypotheses testing on these quantities. The method is illustrated by real life data from a study on the carotid baroreflex function during infusion of sodium nitroprusside, in which seven healthy, young men who were clinically proved to be free from any disease were studied. Their heart rate, arterial blood pressure and central venous pressure were measured. Neck pressure and neck suction protocol was carried out to selectively elicit changes in CSP and the responsiveness of SAP. Data were analyzed and compare before and after nitroprusside infusion. Our results showed that nitroprusside significantly decreased arterial blood pressure and central venous pressure, and significantly increased heart rate, and significantly augmented maximum gain of the carotid baroreflex function.

GC-MCSPT-A MODIFIED HARD-SPHERE THREE-PARAMETER EQUATION OF STATE WITH GROUP MODEL FOR VLE PREDICTION

The mixing rule for a new group-contribution equation of state was proposed by combining the excess Gibbs energy model with the modified Hard-Sphere Three-Parameter Equation of State designated as the MCSPT equation. Low-and high-pressure vapor-liquid equilibria of 28 binary and 9 ternary systems containing strongly polar substances were predicted by using the interaction parameters of the original and modified UNIFAC model. Predicted results have shown that the proposed GO-MCSPT equation has an extensive applicability with satisfactory accuracy.

Adsorption of Naphthol Green B on unburned carbon：2-and3-parameter linear and non-linear equilibrium modelling

The study deals with adsorption of Naphthol Green B on two unburned carbons and the parent coal,from which the UCs have been created in a fluidised-bed power station.Particular attention has been paid to the adsorption equilibrium modelling:experimental data has been analysed using 2-parameter(Langmuir,Freundlich) and3-parameter(Redlich-Peterson) isotherms — both linear and non-linear regressions have been used for the estimation of the isotherm parameters.In the case of both UCs,the Langmuir isotherm model provides the worst fit,whereas 2-parameter Freundlich and 3-parameter Redlich-Peterson models are both good,from which 3-parameter Redlich-Peterson isotherm provides slightly better results(despite the penalty used for the higher number of parameters).In the case of both UCs,the linear regression of Freundlich and Redlich-Peterson models provides good results(comparable with non-linear regressions).Unlike both UCs,the best fit of the experimental data from the adsorption on the coal has been achieved by the Langmuir isotherm model.The results based on the Freundlich or Redlich-Peterson model were(in this case) somewhat worse.

A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control

Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parametermodel-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.

Capacitive Model and S-Parameters of Double-Pole Four-Throw Double-Gate RF CMOS Switch

In this paper, we have analyzed the Double-Pole Four-Throw Double-Gate Radio-Frequency Complementary Metal-Oxide-Semiconductor (DP4T DG RF CMOS) switch using S-parameters for 1 GHz to 60 GHz of frequency range. DP4T DG RF CMOS switch for operation at high frequency is also analyzed with its capacitive model. The re-sults for the development of this proposed switch include the basics of the circuit elements in terms of capacitance, re-sistance, impedance, admittance, series equivalent and parallel equivalent of this network at different frequencies which are present in this switch whatever they are ON or OFF.