Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

Multi-layer quasi-zero-stiffness meta-structure for high-efficiency vibration isolation at low frequency

An easily stackable multi-layer quasi-zero-stiffness(ML-QZS)meta-structure is proposed to achieve highly efficient vibration isolation performance at low frequency.First,the distributed shape optimization method is used to design the unit cel,i.e.,the single-layer QZS(SL-QZS)meta-structure.Second,the stiffness feature of the unit cell is investigated and verified through static experiments.Third,the unit cells are stacked one by one along the direction of vibration isolation,and thus the ML-QZS meta-structure is constructed.Fourth,the dynamic modeling of the ML-QZS vibration isolation metastructure is conducted,and the dynamic responses are obtained from the equations of motion,and verified by finite element(FE)simulations.Finally,a prototype of the ML-QZS vibration isolation meta-structure is fabricated by additive manufacturing,and the vibration isolation performance is evaluated experimentally.The results show that the vibration isolation performance substantially enhances when the number of unit cells increases.More importantly,the ML-QZS meta-structure can be easily extended in the direction of vibration isolation when the unit cells are properly stacked.Hence,the ML-FQZS vibration isolation meta-structure should be a fascinating solution for highly efficient vibration isolation performance at low frequency.

Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Optimum Design for Shrink-fit Multi-layer Vessels under Ultrahigh Pressure Using Different Materials

Multi-layer pressure vessels are widely used in every field of high pressure technology.For the purpose of enhancing a vessels＇ load bearing capacity,a beneficial process like shrink-fit is usually employed.However,few documents on optimum design for multi-layer shrink-fit vessels made of different strength materials can be found,available data are mainly on two-layer vessels.In this paper,an optimum design approach is developed for shrink-fit multi-layer vessels under ultrahigh pressure by using different materials.Maximum shear stress theory is applied as design criteria.The inner and outer radii of a multi-layer vessel,as well as the material of each layer,are assumed to be known.The optimization mathematical model is,thereby,built.Lagrange multipliers method is required to obtain the optimal design formula of wall ratio（ratio of outer to inner radii） of each layer,from which the optimum formulas of shrinkage pressure and radial interference are derived with the superposition principle employed.These formulas are applicable for the optimization design of all multi-layer vessels made of different materials,or same materials.The formulas of the limit working pressure and the contact pressure show that the optimum wall ratio of each layer and limit working pressure are only related to all selected material strength and unrelated to the position of the layer placement in the vessel.However,shrinkage pressure is related to the position of the layer placement in the vessel.Optimization design of an open ended shrink-fit three-layer vessel using different materials and comparisons proved that the optimized multi-layer vessels have outstanding characteristics of small radial interference and are easier for assembly.When the stress of each layer is distributed more evenly and appropriately,the load bearing capability and safety of vessels are enhanced.Therefore,this design is material-saving and cost-effective,and has prospect of engineering application.

A flexible ultra-broadband multi-layered absorber working at 2 GHz-40 GHz printed by resistive ink

A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(FSS),which is printed on PI using conductive ink.To investigate this absorber,both one-dimensional analogous circuit analysis and three-dimensional full-wave simulation based on a physical model are provided.Various crucial electromagnetic properties,such as absorption,effective impedance,complex permittivity and permeability,electric current distribution and magnetic field distribution at resonant peak points,are studied in detail.Analysis shows that the working frequency of this absorber covers entire S,C,X,Ku,K and Ka bands with a minimum thickness of 0.098λ_(max)(λ_(max) is the maximum wavelength in the absorption band),and the fractional bandwidth(FBW)reaches 181.1%.Moreover,the reflection coefficient is less than-10 dB at 1.998 GHz–40.056 GHz at normal incidence,and the absorptivity of the plane wave is greater than 80%when the incident angle is smaller than 50°.Furthermore,the proposed absorber is experimentally validated,and the experimental results show good agreement with the simulation results,which demonstrates the potential applicability of this absorber at 2 GHz–40 GHz.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Multi-layer network embedding on scc-based network with motif

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Multi-layer phenomena in petawatt laser-driven acceleration of heavy ions

Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW laser-accelerated heavy particles using different nanoscale short targets with a thickness of 100 nm Cr, Fe, Ag, Ta, Au, Pb, Th and U, as well as 200 nm thick Al and Ca. An obvious stratification is observed in the simulation. The layering phenomenon is a hybrid acceleration mechanism reflecting target normal sheath acceleration and radiation pressure acceleration, and this phenomenon is understood from the simulated energy spectrum,ionization and spatial electric field distribution. According to the stratification, it is suggested that high-quality heavy-ion beams could be expected for fusion reactions to synthesize superheavy nuclei. Two plasma clusters in the stratification are observed simultaneously, which suggest new techniques for plasma experiments as well as thinner metal targets in the precision machining process.

A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production.

Micrometer-sized ferrosilicon composites wrapped with multi-layered carbon nanosheets as industrialized anodes for high energy lithium-ion batteries

Various nanostructured architectures have been demonstrated to be effective to address the issues of high capacity Si anodes. However, the scale-up of these nano-Si materials is still a critical obstacle for commercialization. Herein, we use industrial ferrosilicon as low-cost Si source and introduce a facile and scalable method to fabricate a micrometer-sized ferrosilicon/C composite anode, in which ferrosilicon microparticles are wrapped with multi-layered carbon nanosheets. The multi-layered carbon nanosheets could effectively buffer the volume variation of Si as well as create an abundant and reliable conductivity framework, ensuring fast transport of electrons. As a result, the micrometer-sized ferrosilicon/C anode achieves a stable cycling with 805.9 m Ah g-1 over 200 cycles at 500 mA g-1 and a good rate capability of455.6 mAh g-1 at 10 A g-1. Therefore, our approach based on ferrosilicon provides a new opportunity in fabricating cost-effective, pollution-free, and large-scale Si electrode materials for high energy lithium-ion batteries.

The role of polyurethane foam compressible layer in the mechanical behaviour of multi-layer yielding supports for deep soft rock tunnels

The polyurethane foam(PU)compressible layer is a viable solution to the problem of damage to the secondary lining in squeezing tunnels.Nevertheless,the mechanical behaviour of the multi-layer yielding supports has not been thoroughly investigated.To fill this gap,large-scale model tests were conducted in this study.The synergistic load-bearing mechanics were analyzed using the convergenceconfinement method.Two types of multi-layer yielding supports with different thicknesses(2.5 cm,3.75 cm and 5 cm)of PU compressible layers were investigated respectively.Digital image correlation(DIC)analysis and acoustic emission(AE)techniques were used for detecting the deformation fields and damage evolution of the multi-layer yielding supports in real-time.Results indicated that the loaddisplacement relationship of the multi-layer yielding supports could be divided into the crack initiation,crack propagation,strain-hardening,and failure stages.Compared with those of the stiff support,the toughness,deformability and ultimate load of the yielding supports were increased by an average of 225%,61%and 32%,respectively.Additionally,the PU compressible layer is positioned between two primary linings to allow the yielding support to have greater mechanical properties.The analysis of the synergistic bearing effect suggested that the thickness of PU compressible layer and its location significantly affect the mechanical properties of the yielding supports.The use of yielding supports with a compressible layer positioned between the primary and secondary linings is recommended to mitigate the effects of high geo-stress in squeezing tunnels.

Deformation and failure of a high-steep slope induced by multi-layer coal mining

During underground mining,accurate revelation on the deformation and failure mechanisms of a high-steep slope under multi-layer mining conditions facilitates the prevention and control of geological disasters in mines.Numerical simulation based on discrete element theory can be used to explore the characteristics and mechanism of action of deformation and failure of a slope under complex geological and multi-layer mining conditions.By utilising PFC2 D(particle flow code) software,the deformation and failure characteristics of a high-steep slope in Faer Coal Mine in Guizhou Province,China were investigated.Additionally,the mechanism of influence of different numbers of mining layers on the deformation and failure of the high and steep slope was elucidated.The result showed that after the goaf passed by the slope toe,multi-layer mining aggravated the subsidence and deformation of the slope toe:the slope toppled forward as it sank.The toppling of the slope changed the slope structures:the strata in the front of the slope were transformed from anti-dip to down-dip features.Extruded by collapsedtoppled rock mass,the slope toe and the rock mass located in the lower part of the slope toe generally exhibited a locking effect on the slope.Multi-layer mining degraded the overall stability of the slope,in that the total displacement of the slope was much greater than the total mining thickness of the coal seams.Based on the aforementioned research,ideas for preventing and controlling geological disasters during mining operations under a high-steep slope were proposed.

Multi-Layer Extension of the High Efficiency Video Coding(HEVC) Standard

Multi?layer extension is based on single?layer design of High Efficiency Video Coding (HEVC) standard and employed as the com?mon structure for scalability and multi?view video coding extensions of HEVC. In this paper, an overview of multi?layer extension is presented. The concepts and advantages of multi?layer extension are briefly described. High level syntax (HLS) for multi?layer extension and several new designs are also detailed.

High mobility group box 1 in the central nervous system:regeneration hidden beneath inflammation

High-mobility group box 1 was first discovered in the calf thymus as a DNA-binding nuclear protein and has been widely studied in diverse fields,including neurology and neuroscience.High-mobility group box 1 in the extracellular space functions as a pro-inflammatory damage-associated molecular pattern,which has been proven to play an important role in a wide variety of central nervous system disorders such as ischemic stroke,Alzheimer’s disease,frontotemporal dementia,Parkinson’s disease,multiple sclerosis,epilepsy,and traumatic brain injury.Several drugs that inhibit high-mobility group box 1 as a damage-associated molecular pattern,such as glycyrrhizin,ethyl pyruvate,and neutralizing anti-high-mobility group box 1 antibodies,are commonly used to target high-mobility group box 1 activity in central nervous system disorders.Although it is commonly known for its detrimental inflammatory effect,high-mobility group box 1 has also been shown to have beneficial pro-regenerative roles in central nervous system disorders.In this narrative review,we provide a brief summary of the history of high-mobility group box 1 research and its characterization as a damage-associated molecular pattern,its downstream receptors,and intracellular signaling pathways,how high-mobility group box 1 exerts the repair-favoring roles in general and in the central nervous system,and clues on how to differentiate the pro-regenerative from the pro-inflammatory role.Research targeting high-mobility group box 1 in the central nervous system may benefit from differentiating between the two functions rather than overall suppression of high-mobility group box 1.

Simulation of thermal field induced by concave spherical transducer in multi-layer media

High intensity focused ultrasound(HIFU)therapy is an effective method in clinical treatment of tumors,in order to explore the bio-heat conduction mechanism of in multi-layer media by concave spherical transducer,temperature field induced by this kind of transducer in multi-layer media will be simulated through solving Pennes equation with finite difference method,and the influence of initial sound pressure,absorption coefficient,and thickness of different layers of biological tissue as well as thermal conductivity parameter on sound focus and temperature distribution will be analyzed,respectively.The results show that the temperature in focus area increases faster while the initial sound pressure and thermal conductivity increase.The absorption coefficient is smaller,the ultrasound intensity in the focus area is bigger,and the size of the focus area is increasing.When the thicknesses of different layers of tissue change,the focus position changes slightly,but the sound intensity of the focus area will change obviously.The temperature in focus area will rise quickly before reaching a threshold,and then the temperature will keep in the threshold range.

Structural Analysis of the Multi-layer Detachment Folding in Eastern Sichuan Province

A serial of＂comb-like and trough-like＂folds developed in eastern Sichuan,controlled by the multi-layer detachment folding,is different from the classical Jura-type structure in their development.The key factor resulting in the development of these structures is the occurrence of detachment layers in different parts of Neoprotozoic to Mesozoic stratigraphy of study area,which, from the bottom to the top,are the lower part of Banxi Group,Lower Cambrian（Niutitang Formation）,Lower Silurian（Longmaxi Formation and Luoreping Formation）,Upper Permian （Wujiaping Formation） and Lower Triassic（Daye Formation）.On the basis of field survey combined with sand-box modeling,this study argued that the detachment layer of the lower part of Banxi Group controlled the development of the＂comb-like＂folds,and the lower part of Cambrian detachment layer controlled the development of＂trough-like＂folds.Because of several detachment layers occurring in the study area,the development of duplex structures different scales is an important deformation mechanism,and the duplexes are the important structures distinguished from the typical detachment folding structures.Due to these duplexes,the surface structures and structural highs may not be the structural highs in the depth.Meanwhile,the detachment layers are good channels for oil/ gas migration benefiting the understanding of accumulation and migration of oil and gas.

Measurement of residual stress in a multi-layer semiconductor heterostructure by micro-Raman spectroscopy

Si-based multilayer structures are widely used in current microelectronics. During their preparation, some inhomogeneous residual stress is induced, resulting in competition between interface mismatching and surface energy and even leading to structure failure. This work presents a methodological study on the measurement of residual stress in a multi-layer semiconductor heterostructure. Scanning electron microscopy（SEM）, micro-Raman spectroscopy（MRS）, and transmission electron microscopy（TEM） were applied to measure the geometric parameters of the multilayer structure. The relationship between the Raman spectrum and the stress/strain on the [100] and [110] crystal orientations was determined to enable surface and crosssection residual stress analyses, respectively. Based on the Raman mapping results, the distribution of residual stress along the depth of the multi-layer heterostructure was successfully obtained.