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.

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.

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.

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.

The Influence Mechanism of an Inclusive Organizational Climate on Innovation Input of Sci-Tech Talents

With the implementation of China’s innovation-driven development strategy,the competition among sci-tech talents has become increasingly fierce.Stimulating the innovative vigor of sci-tech talents has become a hot topic in theoretical research and policy practice.Based on the data from 246 questionnaires collected from sci-tech talents in Hebei province,this study explored the influence mechanism of an inclusive organizational climate on innovation input from technological talents and verified the mediating effects of innovation self-efficacy and intrinsic motivation.The results indicate that an inclusive organizational climate has a significant positive impact on innovation input,innovation self-efficacy,and intrinsic motivation of sci-tech talents.Both innovation self-efficacy and intrinsic motivation play a partial mediating role between an inclusive climate and innovation input.This study verified the important role of an inclusive climate in an organization’s human resource management practices and encouraged managers to emphasize enhancing the innovation self-efficacy and intrinsic motivation of sci-tech talents,thereby continuously improving the level of innovation.

Blast wave characteristics of multi-layer composite charge:Theoretical analysis,numerical simulation,and experimental validation

This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the charge,a peak overpressure prediction model for the composite charge under singlepoint detonation and simultaneous detonation was established.The effects of the charge structure and initiation method on the overpressure field characteristics were investigated in AUTODYN simulation.The accuracy of the prediction model and the reliability of the numerical simulation method were subsequently verified in a series of static explosion experiments.The results reveal that the mass of the inner charge was the key factor determining the peak overpressure of the composite charge under single-point detonation.The peak overpressure in the radial direction improved apparently with an increase in the aspect ratio of the charge.The overpressure curves in the axial direction exhibited a multi-peak phenomenon,and the secondary peak overpressure even exceeded the primary peak at distances of 30D and 40D(where D is the charge diameter).The difference in peak overpressure among azimuth angles of 0-90°gradually decreased with an increase in the propagation distance of the shock wave.The coupled effect of the detonation energy of the inner and outer charge under simultaneous detonation improved the overpressure in both radial and axial directions.The difference in peak overpressure obtained from model prediction and experimental measurements was less than 16.4%.

Optimizing slope safety factor prediction via stacking using sparrow search algorithm for multi-layer machine learning regression models

The safety factor is a crucial quantitative index for evaluating slope stability.However,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration of the influencing factors,leading to large errors in their calculations.Therefore,a stacking ensemble learning model(stacking-SSAOP)based on multi-layer regression algorithm fusion and optimized by the sparrow search algorithm is proposed for predicting the slope safety factor.In this method,the density,cohesion,friction angle,slope angle,slope height,and pore pressure ratio are selected as characteristic parameters from the 210 sets of established slope sample data.Random Forest,Extra Trees,AdaBoost,Bagging,and Support Vector regression are used as the base model(inner loop)to construct the first-level regression algorithm layer,and XGBoost is used as the meta-model(outer loop)to construct the second-level regression algorithm layer and complete the construction of the stacked learning model for improving the model prediction accuracy.The sparrow search algorithm is used to optimize the hyperparameters of the above six regression models and correct the over-and underfitting problems of the single regression model to further improve the prediction accuracy.The mean square error(MSE)of the predicted and true values and the fitting of the data are compared and analyzed.The MSE of the stacking-SSAOP model was found to be smaller than that of the single regression model(MSE=0.03917).Therefore,the former has a higher prediction accuracy and better data fitting.This study innovatively applies the sparrow search algorithm to predict the slope safety factor,showcasing its advantages over traditional methods.Additionally,our proposed stacking-SSAOP model integrates multiple regression algorithms to enhance prediction accuracy.This model not only refines the prediction accuracy of the slope safety factor but also offers a fresh approach to handling the intricate soil composition and other influencing factors,making it a precise and reliable method for slope stability evaluation.This research holds importance for the modernization and digitalization of slope safety assessments.

Explosive synchronization of multi-layer complex networks based on star connection between layers with delay

Explosive synchronization(ES)is a kind of first-order jump phenomenon that exists in physical and biological systems.In recent years,researchers have focused on ES between single-layer and multi-layer networks.Most research on complex networks with delay has focused on single-layer or double-layer networks,multi-layer networks are seldom explored.In this paper,we propose a Kuramoto model of frequency weights in multi-layer complex networks with delay and star connections between layers.Through theoretical analysis and numerical verification,the factors affecting the backward critical coupling strength are analyzed.The results show that the interaction between layers and the average node degree has a direct effect on the backward critical coupling strength of each layer network.The location of the delay,the size of the delay,the number of network layers,the number of nodes,and the network topology are revealed to have no direct impact on the backward critical coupling strength of the network.Delay is introduced to explore the influence of delay and other related parameters on ES.

Thoughts on Cultivation of Top-notch Innovative Talents of Food Subject in Local Universities

The cultivation of top-notch innovative talents is one of the most prominent tasks in China s universities in the new era,and also an opportunity and challenge for local universities.Taking the food subject of local universities as an example,some suggestions were put forward from the aspects of security measures,teacher team construction,talent selection and management,and talent cultivation,in order to provide reference for the exploration and practice of cultivating top-notch innovative talents in the food subject of local universities.

Exploration of the Training Mode of School-enterprise Collaborative AI Innovative Talents Based on PaddlePaddle

This paper takes the school-enterprise cooperation between the University of Electronic Science and Technology of China(UESTC)and Baidu(China)Co.,Ltd.as an example to build the Paddle Paddle(Sichuan)AI Education Innovation Center by enjoying the best of both UESTC and Baidu(China),and cooperating with 16 universities in Sichuan Province.With the support of this center,both the school and the enterprise successfully built a school-enterprise collaborative AI innovative talent training model,which mainly serves the universities,industries,and districts.Furthermore,this training model is able to facilitate the update of the industrial intelligence and the regional economic development in southwest China,and also provide a reference for deep integration of school-enterprise collaboration and the cultivation of innovative talents in electronic information fields.

Exploration and Practice of the Cultivation Model for Top Undergraduate Talents Based on Subject Contests in the AI Era

With the rise of artificial intelligence and the rapid development of industrial applications based on deep learning,the demand for innovative and practical talents is rapidly increased.The cultivation of talents in computer discipline has attracted a lot of attention from universities,research institutions,and Internet giants.Subject contests play a crucial role in cultivating top undergraduate talents.This paper proposes a cultivation model that takes the industry application of deep learning as the background,and guides students to learn,practice,and innovate incrementally from machine learning application to deep learning application by participating in subject contests.It aims to help undergraduates to master the cutting-edge technologies and applications,and ultimately cultivate top,innovative,and practical undergraduate talents in the computer field in the era of artificial intelligence.

Teaching of Organic Chemistry of Cultivating Applied Pharmaceutical Talents

In order to effectively cultivate applied pharmaceutical talents,aiming at the current teaching situation of organic chemistry,the basic course of pharmaceutical specialty,including the problems of curriculum setting,experimental teaching,and the integration of classroom and professional knowledge,it is proposed to overcome the problem of curriculum setting by combining"online+offline"in teaching.It should overcome the problems in experimental teaching with the help of virtual simulation platform.By cultivating students organic chemistry thinking and paying attention to the integration of subject and professional knowledge,students recognition of organic chemistry course can be improved,and the quality of training can be improved.

Research on the Cultivation of Innovative Talents in Software Engineering Based on the OBE Concept

Under the background of New Engineering,focusing on talent cultivation,this article explores the teaching reform and innovation of software engineering majors.Starting from the goal of cultivating software engineering talents in the context of New Engineering,the concept of outcome-based education is introduced to study and explore the construction of innovative talent training models for software engineering majors in universities.Through recent years’application practice,initial results have been achieved,which can provide feasible methods and ideas for the cultivation of innovative talents in other majors.

Detecting Phishing Using a Multi-Layered Social Engineering Framework

As businesses develop and expand with a significant volume of data,data protection and privacy become increasingly important.Research has shown a tremendous increase in phishing activities during and after COVID-19.This research aimed to improve the existing approaches to detecting phishing activities on the internet.We designed a multi-layered phish detection algorithm to detect and prevent phishing applications on the internet using URLs.In the algorithm,we considered technical dimensions of phishing attack prevention and mitigation on the internet.In our approach,we merge,Phishtank,Blacklist,Blocklist,and Whitelist to form our framework.A web application system and browser extension were developed to implement the algorithm.The multi-layer phish detector evaluated ten thousandURLs gathered randomly from the internet(five thousand phishing and five thousand legitimate URLs).The system was estimated to detect levels of accuracy,true-positive and false-positive values.The system level accuracy was recorded to be 98.16%.Approximately 49.6%of the websites were detected as illegitimate,whilst 49.8%were seen as legitimate.

Study on Influencing Factors and Mechanism of Scientific and Technological Innovation Talents Gathering in Zhejiang Province

This paper systematically studies the influencing factors and mechanism of the agglomeration of scientific and technological innovation talents in Zhejiang Province. The findings are as follows: Firstly, environmental factors such as marketization level, financial development, opening to the outside world, infrastructure construction, medical resources, educational resources, cultural resources and policy support have a positive impact on the agglomeration of scientific and technological talents in Zhejiang Province;Secondly, in the transmission mechanism of the influence of various environmental factors on the concentration of scientific and technological talents in Zhejiang, economic development plays an intermediary role, and the effect is obvious. Various environmental factors indirectly affect the concentration of scientific and technological talents in Zhejiang through economic development. Finally, although both the level and quality of economic development have significant effect on the total concentration of scientific and technological talents in Zhejiang, the mediating effect of economic development level is more significant. These studies are for Zhejiang Province. It provides a theoretical basis for cultivating high-end talents and realizing the agglomeration of scientific and technological innovation talents.

Research on the Integrated Training Path of Secondary Vocational,Vocational,and Undergraduate Talents Based on Modern Vocational Education Group

Accelerating the construction of modern vocational education groups and promoting the integrated training of secondary vocational,vocational,and undergraduate talents,providing talent support for regional economic development,are inevitable choices to enhance the adaptability of vocational education.Based on the new development and requirements in the new situation,vocational colleges actively explore the path of connecting and cultivating secondary vocational,vocational,and undergraduate talents in accordance with the talent needs of local economic development and industrial system development.The linkage between government,school,and enterprise is established to build a modern vocational education group,aiming to build a professional chain in the industrial chain and promote innovative development of the new industrial system.Relying on the development needs of professional clusters,a multi-level system of connecting and cultivating secondary vocational,vocational,and undergraduate talents is constructed,which is in line with industry and enterprise standards.It is also necessary to build a“post-course competition certification”talent training model for connecting secondary vocational,vocational,and undergraduate students,rely on the advantages of multiple schools and enterprises,establish a platform for integrating industry and education,and innovate the evaluation system for connecting secondary vocational,vocational,and undergraduate students.

Coupling coordinated development among digital economy,regional innovation,and talent employment:A case study in the Hangzhou Metropolitan Circle,China

Coordinative development across various systems,particularly the economic,social,cultural,and human resources subsystems,is a key aspect of urban sustainability and has a direct impact on the quality of urbanization.The Hangzhou Metropolitan Circle,comprising Hangzhou City,Huzhou City,Jiaxing City,and Shaoxing City,was the first metropolitan circle approved by the National Development and Reform Commission(NDRC)as a demonstration of economic transformation in China.To evaluate the coupling coordination degree of the four cities and analyze the coordinative development in three systems(including digital economy,regional innovation,and talent employment),we collected panel data during 2015–2022 from these four cities.The development level of the three systems was evaluated by the standard deviation method and comprehensive development index.The results are as follows:(1)the level of coupling coordinated development of the three systems in the Hangzhou Metropolitan Circle was relatively low;(2)the coupling coordination degree of the four cities in the Hangzhou Metropolitan Circle showed significant regional differences,among which Hangzhou City was in the leading position,and Huzhou,Jiaxing,and Shaoxing cities made steady but slow progress in the coupling development of the three systems;and(3)the development of digital economy and talent employment needs to be strengthened.This study contributes to the coordinative development of Hangzhou Metropolitan Circle by innovatively focusing on the coupling coordination relationship among digital economy,regional innovation,and talent employment,which also meets the industrial layout of Hangzhou Metropolitan Circle.In this way,the optimal allocation and sustainable development of digital economy,regional innovation,and talent employment in the Hangzhou Metropolitan Circle can be achieved.

Analysis of Professional Quality Cultivation Strategies for Infant and Child Care Service Talents from the Perspective of Collaboration of Medical Care,Parenting,and Education,and Integration of Industry and Education

The collaboration of medical care,parenting,and education aims to integrate nursing,midwifery,infant and child care services,and management with speech and hearing rehabilitation technology,among other elements related to the infant care industry chain.This integration targets pediatrics talent training in nine infant care positions,including nursing,infant health care and management,and child rehabilitation,to ensure that the capabilities and quality of professional talents can meet the health care needs of infants and young children.This article briefly explains the background of the“collaboration of medical care,parenting,and education,and integration of industry and education.”It analyzes the necessity of cultivating infant and child care service talents based on the perspective of“collaboration of medical care,parenting,and education,and integration of industry and education.”Based on this perspective,we conducted an in-depth study of the cultivation of professional qualities of infant and child care service talents.

Research on the Construction Status of the Beijing-Tianjin-Hebei Medical Talent Community and the Countermeasures for Its Realization

In April 2015,the Political Bureau of the CPC Central Committee adopted the“Outline of the Plan for the Coordinated Development of Beijing,Tianjin,and Hebei.”In July 2017,the“Plan for the Integrated Development of Beijing,Tianjin,and Hebei Talents(2017–2030),”jointly prepared by the leading groups of the three regions,was officially released.The core of the coordinated development of these three regions is the orderly removal of non-capital functions from Beijing.Talents,especially medical talents,are integral to this transition.The construction of a medical talent community across these three regions promotes the further development of a healthier China,meets the growing needs of the people for a better life,and embodies the concept of putting people first.This paper begins by examining the current situation of the construction of the Beijing-Tianjin-Hebei medical talent community,reviewing the progress made,analyzing existing problems,and proposing targeted countermeasures and suggestions.