Stable Transition of Quadruped Rhythmic Motion Using the Tracking Differentiator

Since the quadruped robot possesses predominant environmental adaptability,it is expected to be employed in nature environments. In some situations,such as ice surface and tight space,the quadruped robot is required to lower the height of center of gravity( COG) to enhance the stability and maneuverability. To properly handle these situations,a quadruped controller based on the central pattern generator( CPG) model,the discrete tracking differentiator( TD) and proportional-derivative( PD) sub-controllers is presented. The CPG is used to generate basic rhythmic motion for the quadruped robot. The discrete TD is not only creatively employed to implement the transition between two different rhythmic medium values of the CPG which results in the adjustment of the height of COG of the quadruped robot,but also modified to control the transition duration which enables the quadruped robot to achieve the stable transition. Additionally,two specific PD sub-controllers are constructed to adjust the oscillation amplitude of the CPG,so as to avoid the severe deviation in the transverse direction during transition locomotion. Finally,the controller is validated on a quadruped model. A tunnel with variable height is built for the quadruped model to travel through. The simulation demonstrates the severe deviation without the PD sub-controllers,and the reduced deviation with the PD sub-controllers.

A Grounded Capacitor Differentiator Using Current Feedback Amplifier

A new non-inverting RC active differentiator network base on a current feedback amplifier and using a grounded capacitor is described. Small time constant can be achieved by adjusting a single grounded resistor. Because the output impedance of the CFA is very low, the output terminal of the proposed circuit can be directly connected to the next stage. Experimental results that confirm theoretical analysis are presented.

DIFFERENTIATOR SERIES SOLUTION OF LINEAR DIFFERENTIAL ORDINARY EQUATION

In this paper, the principle techinique of the differentiator method, and some examples using the method to obtain the general solution and special solution of the differential equation are introduced. The essential difference between this method and the others is that by this method special and general solutions can be obtained directly with the operations of the differentor in the differential equation and without the enlightenment of other scientific knowledge.

Diversity of photonic differentiators based on flexible demodulation of phase signals

We theoretically propose a multifunctional photonic differentiation （DIFF） scheme based on phase demodulation using two cascaded linear filters. The photonic D1FF has a diversity of output forms, such as the 1 st order intensity DIFF, the 1 st order field DIFF and its inversion, and the 2nd-order field DIFF, depending on the relative shift between the optical carrier and the filter＇s resonant notches. As a proof, we also experimentally demonstrate the DIFF diversity using a phase modulator and two delay interferometers （Dis）. The calculated average deviation is less than 7% for all DIFF waveforms. Our schemes show the advantages of flexible DIFF functions and forms, which may have different optical applications. For example, high order field differentiators can be used to generate complex temporal waveforms, and intensity differentiators are useful for the ultra-wideband pulse generation.

Wave field in two-phase media by the convolutional differentiator method

This paper applies the convolutional differentiator method, based on generalized Forsyte orthogonal polynomial （CFPD）, to simulate the seismic wave propagation in two-phase media. From the numerical results we can see that three types of waves, fast P-waves, S-waves and slow P-waves, can be observed in the seismic wave field. The experiments on anisotropic models demonstrate that the wavefront is elliptic instead of circular and S-wave splitting occurs in anisotropic two-phase media. The research has confirmed that the rules of elastic wave propagation in fluid-saturated porous media are controlled by Biot＇s theory. Experiment on a layered fault model shows the wavefield generated by the interface and the fault very well, indicating the effectiveness of CFPD method on the wavefield modeling for real layered media in the Earth. This research has potential applications to the investigation of Earth＇s deep structure and oil/gas exploration.

Adaptive Differentiators via Second Order Sliding Mode for a Fixed Wing Aircraft

Safety automation of complex mobile systems is a current topic issue in industry and research laboratories,especially in aeronautics.The dynamic models of these systems are nonlinear,Multi-Input Multi-Output(MIMO)and tightly coupled.The nonlinearity resides in the dynamic equations and also in the aerodynamic coefficients’variability.This paper is devoted to developing the piloting law based on the combination of the robust differentiator with a dynamic adaptation of the gains and the robust controller via second order sliding mode,by using an aircraft in virtual simulated environments.To deal with the design of an autopilot controller,we propose an environment framework based on a Software In the Loop(SIL)methodology and we use Microsoft Flight Simulator(FS-2004)as the environment for plane simulation.The first order sliding mode control may be an appropriate solution to this piloting problem.However,its implementation generates a chattering phenomenon and a singularity problem.To overcome these problems,a new version of the adaptive differentiators for second order sliding modes is proposed and used for piloting.For the sliding mode algorithm,higher gains values may be used to improve accuracy;however this leads to an amplification of noise in the estimated signals.A good tradeoff between these two criteria(accuracy,robustness to noise ratio)is difficult to achieve.On the one hand,these values must increase the gains in order to derive a signal sweeping of some frequency ranges.On the other hand,low gains values have to be imposed to reduce noise amplification.So,our goal is to develop a differentiation algorithm in order to have a good compromise between error and robustness to noise ratio.To fit this requirement,a new version of differentiators with a higher order sliding modes and a dynamic adaptation of the gains,is proposed:the first order differentiator for the control of longitudinal speed and the second order differentiator for the control of the Euler angles.

Design of a Modified Tracking Differentiator

A modified tracking differentiator is proposed. Firstly, a nonlinear odd exponent continuous function is adopted which is only stable at one equilibrium point and proved the global asymptotic stability of the modified tracking differentiator by select a Lyapunov function. Through combining of the nonlinear and linear function properly, it can be sure that the state converges to the equilibrium point with high speed automatically no matter that the state was far away from the equilibrium point or near to it, and it can prevent the chattering.?Simulation results show that the modified tracking differentiator tracking results?are?superior to the classical nonlinear tracking differentiator, and the response?of state variables tracking differentiator estimated?is?almost coincide with the real state of the variables of the given system.

A Single Resistor Tunable Grounded Capacitor Dual-Input Differentiator

A new current feedback amplifier (CFA) based dual-input differentiator (DID) design with grounded capacitor is presented;its time constant (τo) is independently tunable by a single resistor. The proposed circuit yields a true DID function with ideal CFA devices. Analysis with nonideal devices having parasitic capacitance (Cp) shows extremely low but finite phase error (θe);suitable design θe could be minimized significantly. The design is practically active-insensitive relative to port mismatch errors (ε) of the active element. An allpass phase shifter circuit implementation is derived with slight modification of the differentiator. Satisfactory experimental results had been verified on typical wave processing and phase-selective filter design applications.

On a novel tracking differentiator design based on iterative learning in a moving window

Differential signals are key in control engineering as they anticipate future behavior of process variables and therefore are critical in formulating control laws such as proportional-integral-derivative(PID).The practical challenge,however,is to extract such signals from noisy measurements and this difficulty is addressed first by J.Han in the form of linear and nonlinear tracking differentiator(TD).While improvements were made,TD did not completely resolve the conflict between the noise sensitivity and the accuracy and timeliness of the differentiation.The two approaches proposed in this paper start with the basic linear TD,but apply iterative learning mechanism to the historical data in a moving window(MW),to form two new iterative learning tracking differentiators(IL-TD):one is a parallel IL-TD using an iterative ladder network structure which is implementable in analog circuits;the other a serial IL-TD which is implementable digitally on any computer platform.Both algorithms are validated in simulations which show that the proposed two IL-TDs have better tracking differentiation and de-noise performance compared to the existing linear TD.

Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

Transcriptional regulation in the development and dysfunction of neocortical projection neurons

Glutamatergic projection neurons generate sophisticated excitatory circuits to integrate and transmit information among different cortical areas,and between the neocortex and other regions of the brain and spinal cord.Appropriate development of cortical projection neurons is regulated by certain essential events such as neural fate determination,proliferation,specification,differentiation,migration,survival,axonogenesis,and synaptogenesis.These processes are precisely regulated in a tempo-spatial manner by intrinsic factors,extrinsic signals,and neural activities.The generation of correct subtypes and precise connections of projection neurons is imperative not only to support the basic cortical functions(such as sensory information integration,motor coordination,and cognition)but also to prevent the onset and progression of neurodevelopmental disorders(such as intellectual disability,autism spectrum disorders,anxiety,and depression).This review mainly focuses on the recent progress of transcriptional regulations on the development and diversity of neocortical projection neurons and the clinical relevance of the failure of transcriptional modulations.

An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

Cell replacement with stem cell-derived retinal ganglion cells from different protocols

Glaucoma,characterized by a degenerative loss of retinal ganglion cells,is the second leading cause of blindness worldwide.There is currently no cure for vision loss in glaucoma because retinal ganglion cells do not regenerate and are not replaced after injury.Human stem cell-derived retinal ganglion cell transplant is a potential therapeutic strategy for retinal ganglion cell degenerative diseases.In this review,we first discuss a 2D protocol for retinal ganglion cell differentiation from human stem cell culture,including a rapid protocol that can generate retinal ganglion cells in less than two weeks and focus on their transplantation outcomes.Next,we discuss using 3D retinal organoids for retinal ganglion cell transplantation,comparing cell suspensions and clusters.This review provides insight into current knowledge on human stem cell-derived retinal ganglion cell differentiation and transplantation,with an impact on the field of regenerative medicine and especially retinal ganglion cell degenerative diseases such as glaucoma and other optic neuropathies.

Metabolic and proteostatic differences in quiescent and active neural stem cells

Adult neural stem cells are neurogenesis progenitor cells that play an important role in neurogenesis.Therefore,neural regeneration may be a promising target for treatment of many neurological illnesses.The regenerative capacity of adult neural stem cells can be chara cterized by two states:quiescent and active.Quiescent adult neural stem cells are more stable and guarantee the quantity and quality of the adult neural stem cell pool.Active adult neural stem cells are chara cterized by rapid proliferation and differentiation into neurons which allow for integration into neural circuits.This review focuses on diffe rences between quiescent and active adult neural stem cells in nutrition metabolism and protein homeostasis.Furthermore,we discuss the physiological significance and underlying advantages of these diffe rences.Due to the limited number of adult neural stem cells studies,we refe rred to studies of embryonic adult neural stem cells or non-mammalian adult neural stem cells to evaluate specific mechanisms.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

Novel adaptive neural control of flexible air-breathing hypersonic vehicles based on sliding mode differentiator

A novel adaptive neural control strategy is exploited for the longitudinal dynamics of a generic flexible air-breathing hypersonic vehicle（FAHV）.By utilizing functional decomposition method, the dynamics of FAHV is decomposed into the velocity subsystem and the altitude subsystem.For each subsystem, only one neural network is employed for the unknown function approximation.To further reduce the computational burden, minimal-learning parameter（MLP）technology is used to estimate the norm of ideal weight vectors rather than their elements.By introducing sliding mode differentiator（SMD） to estimate the newly defined variables, there is no need for the strict-feedback form and virtual controller.Hence the developed control law is considerably simpler than the ones derived from back-stepping scheme.Finally, simulation studies are made to illustrate the effectiveness of the proposed control approach in spite of the flexible effects, system uncertainties and varying disturbances.

Large-range tunable fractional-order differentiator based on cascaded microring resonators

In this paper, we experimentally demonstrate an all-optical continuously tunable fractional-order differentiator using on-chip cascaded electrically tuned microring resonators （MRRs）. By changing the voltage applied on a MRR, the phase shift at the resonance frequency of the MRR varies, which can be used to implement tunable fractional-order differentiator. Hence fractional-order differentiator with a larger ttmable range can be obtained by cascading more MRR units on a single chip. In the experiment, we applied two direct current voltage sources on two cascaded MRRs respectively, and a tunable order range of 0.57 to 2 have been demonstrated with Gaussian pulse injection, which is the largest tuning range to our knowledge.

PML Absorbing Boundary Condition for Seismic Numerical Modeling by Convolutional Differentiator in Fluid-Saturated Porous Media

The perfectly matched layer（PML） was first introduced by Berenger as an absorbing boundary condition for electromagnetic wave propagation.In this article,a method is developed to ex-tend the PML to simulating seismic wave propagation in fluid-saturated porous medium.This non-physical boundary is used at the computational edge of a Forsyte polynomial convolutional differenti-ator（FPCD） algorithm as an absorbing boundary condition to truncate unbounded media.The incor-poration of PML in Biot＇s equations is given.Numerical results show that the PML absorbing bound-ary condition attenuates the outgoing waves effectively and eliminates the reflections adequately.

DNA methylation in poultry:a review

As an important epigenetic modification,DNA methylation is involved in many biological processes such as animal cell differentiation,embryonic development,genomic imprinting and sex chromosome inactivation.As DNA methylation sequencing becomes more sophisticated,it becomes possible to use it to solve more zoological problems.This paper reviews the characteristics of DNA methylation,with emphasis on the research and application of DNA methylation in poultry.