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.

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.

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.

Analysis of the History and Current Situation of the Development of General Practice Teaching Clinics in China

A summary of the exploration of the teaching mode of the general practice teaching clinic, a summary of the deficiencies of the teaching clinic and a summary of the significance of the establishment of the general practice teaching clinic are presented with a view to promoting the development of general practice and cultivating more excellent successors in general practice.

Culturally competent care across borders: Implementing culturally responsive teaching for nurses in diverse workforces

The migration of healthcare professionals,including nurses,is a global phenomenon.It is driven by various factors,including the pursuit of better opportunities,living conditions,and professional development,as well as political instability or conflict in their home countries.The World Health Organization(WHO)has noted that high-income countries often rely on foreign-trained nurses to fill gaps in their healthcare systems[1].For instance,as of 2021,over 40%(52 million)of all nurses in the United States(US)were expatriates[2].In the United Kingdom(UK),the percentage of expatriate nurses was even higher,reaching approximately 18%in 2021[3].Owing to globalization and migration,healthcare providers must possess cultural competence to deliver improved care[4,5].Culturally responsive teaching(CRT)is rooted in the idea that culture plays a vital role in shaping people’s behaviors,beliefs,values,and communication styles[6].Furthermore,these cultural factors influence patients’perspectives on health,illness,healing,and their preferences for care and communication[7].By recognizing and embracing these cultural differences,nurses can provide more effective and compassionate care to their diverse patient population[8].

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.

Exploration on Teaching Reform of Synthetic Biology Course Based on the New Engineering Concept

Synthetic biology is a new frontier of life science,which aims to design,transform and even synthesize organisms with engineering design concept.Doing a good job in the teaching of"synthetic biology"is of great significance to the cultivation and reserve of biotechnology professionals in China,and also has an important impact on students' employment competitiveness.Under the background of"new engineering",the course reform of"synthetic biology"was carried out in terms of the construction of teaching staff,teaching methods,students' participation and the innovation of course content,and specific reform suggestions were put forward,hoping to effectively promote the sustainable development of"synthetic biology"and effectively improve the quality of education.

Practical effect of different teaching modes in teaching gastrointestinal surgery nursing

BACKGROUND With the continuous development and progress of medical technology,the position of surgical nursing in the field of clinical medicine is becoming in-creasingly prominent.As an important branch of the surgical field,the nursing requirements and difficulty of gastrointestinal surgery are also increasing.In order to improve the teaching quality of nursing care in gastrointestinal surgery,many educators and researchers are actively exploring new teaching methods.Among them,the teaching method case-based learning(CBL),scene-simulated learning(SSL),task-based learning(TBL),combining self-evaluation and training mode is considered as an effective method.This method aims to help students to better master knowledge and skills and improve their comprehensive quality by cultivating their self-evaluation ability.AIM To explore the practical effect of CBL-SSL-TBL combined with training mode and student self-assessment in nursing teaching of gastrointestinal surgery.METHODS Seventy-one nursing interns in our hospital from December 2020 to December 2021 were selected.According to different teaching modes,they were divided into observation group CBL-SSL-TBL combined with training mode combined with student self-assessment and control group(conventional teaching mode),of which 36 were in observation group and 35 were in control group.The results of operational skills,theoretical knowledge,nursing students'satisfaction,learning effectiveness questionnaire and teaching effect were compared between the two groups.RESULTS Compared between the two groups,the operational skills and theoretical knowledge scores of the observation group were higher than those of the control group,and the difference was statistically significant(P<0.05).Compared between the two groups,the total satisfaction ratio of the observation group was higher than that of the control group,the difference was statistically significant(P<0.05).Compared between the two groups,the observation group was lower than the control group in the questionnaire results of learning efficacy,and the difference was statistically significant(P<0.05).Compared between the two groups,the proportion of thinking ability,subjective initiative and understanding of theoretical knowledge in the observation group was higher than that in the control group,the difference was statistically significant(P<0.05).CONCLUSION The use of CBL-SSL-TBL combined with training mode and student self-assessment in gastrointestinal surgery nursing teaching can improve the operational skills of nursing interns,theoretical knowledge and satisfaction scores of nursing students,improve the results of learning efficiency questionnaire and teaching effect,which can be popularized in clinical teaching.

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.

Exploration of Teaching Reform of Food Machinery and Equipment Course Based on New Engineering Concept

The new engineering concept aims to train high-quality engineering talents to meet the needs of future science and technology and industrial development through the reform of education and teaching.Under the background of"new engineering",by introducing cutting-edge knowledge of the industry and interdisciplinary integration,adopting innovative teaching methods such as project-driven teaching and flipped classroom,strengthening experimental teaching and school-enterprise cooperation,and establishing comprehensive evaluation and feedback mechanism,Food Machinery and Equipment course is reformed to improve the teaching quality and train high-quality engineering talents to meet the needs of modern food processing industry.

Research on Blended Teaching Mode:A Case Study of Floristry

In order to better carry out research on education and teaching,the author consulted relevant literature on blended teaching mode from 2011-2021 through CNKI,Web of Science and other websites,summarized and analyzed the research status of blended teaching mode,in order to lay a good foundation for studying blended teaching mode in course teaching.

A Structured Method of Teaching Epidural Block reduces the incidence of accidental dural puncture in inexperienced trainees.

Background: The rate of accidental dural puncture is particularly high during the period of training, especially in novices. The structured epidural teaching model (SETM) includes three standardized video lessons, the construction of a 3D epidural module by trainees and practical training by using an epidural simulator with and without the CompuFlo™ Epidural instrument. In this study we report the retrospective analysis of the accidental dural puncture rate of inexperienced trainees during their 6 months clinical practice rotation in obstetrics before and after the introduction of the SETM in our Institution. Method: We evaluated the incidence of accidental dural puncture before the introduction of the SETM methodology and afterwards by analyzing our departmental database from February 2019 to January 2023. All epidural blocks were executed by trainees who had never previously performed an epidural block and were about to begin their obstetrics rotation. Results: We analyzed 7415 epidurals: 3703 were performed before the introduction of the SETM methodology (control group) and 3712 afterwards (study group). The incidence of accidental dural puncture was 0.37% for the control group and 0.13% for the study group (p<.05). The probability of making an accidental dural puncture was 64% (OR: 0.36) lower for trainees who had the training than for those who did not. Conclusions: After the introduction of the structured teaching method, we observed a significant reduction of accidental dural puncture during the training period. We hope that our observation will encourage a constructive discussion among experts about the need to use standardized and validated tools as a valuable aid in teaching epidural anesthesia.

Thinking on Improving Presentation Teaching-Based on the Empirical Analysis of Presentation in College English Classes of Junior Non-English Majors in Universities of Science and Engineering

Based on the empirical investigation of presentation in college English classes for junior non-English majors in science and engineering universities,the author explains her own thinking on how to improve presentation teaching from four aspects:setting teaching objectives,selecting teaching contents,using teaching methods,and evaluating and implementing methods.

Reform of Hospitality English Teaching Based on the Educational Concept of Outcome-Based Education(OBE)

The Outcome-Based Education(OBE)educational concept,proposed by renowned American educator Spady,aims to guide students in mastering learning laws and ultimately achieving expected learning outcomes.The application of OBE educational concept in Hospitality English curriculum not only can effectively enhance the learning effect but also promote the reform of the Hospitality English curriculum,thus improving students’learning enthusiasm.Therefore,taking the Hospitality English curriculum as an example,this paper points out the existing problems in the teaching of this course and suggests the reform measures based on the OBE teaching concept,hoping to provide guidelines for related educational work.

Student-Centered Strategy in Academic English Teaching

Based on the current situation of academic English teaching, this paper discusses “student-centered” teaching strategy in the Academic English Reading and Writing, and explore how to integrate it in classroom activities.