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.

Plasma nitrogen fixation system with dual-loop enhancement for improved energy efficiency and its efficacy for lettuce cultivation

Plasma nitrogen fixation(PNF)has been emerging as a promising technology for greenhouse gasfree and renewable energy-based agriculture.Yet,most PNF studies seldom address practical application-specific issues.In this work,we present the development of a compact and automatic PNF system for on-site agricultural applications.The system utilized a gliding-arc discharge as the plasma source and employed a dual-loop design to generate NO_(x)from air and water under atmospheric conditions.Experimental results showed that the system with a dualloop design performs well in terms of energy costs and production rates.Optimal operational parameters for the system were determined through experimentation,resulting in an energy cost of 13.9 MJ mol^(-1)and an energy efficiency of 16 g kWh^(-1)for NO_(3)^(-)production,respectively.Moreover,the concentration of exhausted NO_(x)was below the emission standards.Soilless lettuce cultivation experiments demonstrated that NO_(x)^(-)produced by the PNF system could serve as liquid nitrate nitrogen fertilizer.Overall,our work demonstrates the potential of the developed PNF system for on-site application in the production of green-leaf vegetables.

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.

Strawberry (Fragaria spp.): Cultivation, Production, Consumption, and Marketing in Cameroon

Strawberry (Fragaria spp.) is one of the most important fruits classified as exotic fruits imported into Cameroon. To have an inventory of its cultivation in Cameroon, a survey study was carried out among eight farms of Fragaria spp. from January 2021 to February 2022. The plant was introduced in Cameroon in 2018. There are 13 varieties of Fragaria spp. currently cultivated. Among these 13 varieties, eleven are hybrids of Fragaria x ananassa (“Amiga”, “Amine”, “Camarosa”, “Chandler”, “Charlotte”, “Elsanta”, “Gariguette”, “Madame Moutot”, “Ostara”, “Ruby gem” and “San Andreas”), and two of the hybrids of Fragaria vesca (“Maestro” and “Mara des bois”). The cropping system, irrigation system, and type of fertilizers applied differ from one strawberry farm to another. Biofertilizers (such as mycorrhizal), inorganic and organic fertilizers are actually used to improve production. The potential annual production of strawberries from January 2021 to February 2022, estimated based on the survey data, was 21.216 tons for all growers. Among these eight production farms, the Lolodorf BIO Farm presents 6000 kg (six tons) of strawberries and 100,000 stolons (seedlings) produced, from seven varieties of Fragaria spp. cultivated, with 6 varieties which are hybrids variety Fragaria x ananassa (“Amiga”, “Amine”, “Chandler”, “Gariguette”, “Madame Moutot”, and “Ruby gem”), and one which is a hybrid of Fragaria vesca (“Mara des bois”). Certain diseases were also observed and recorded depending on the growing areas.

Cultivation Path of Nursing Undergraduates’Scientific Research and Innovation Ability

Objective: The cultivation of the innovation ability and scientific research is one of the nursing learning objectives for undergraduate students. To explore the method and effect of training system of scientific research innovation ability of nursing undergraduates based on “3332”. Methods: Three course learning modules are constructed: stage-based course learning module, systematic project practice training module and comprehensive practice training module. A practical training platform for scientific research innovation projects is built, and undergraduate scientific research innovation ability training is carried out from both in-class and out-of-class lines. Results: Since 2017, the students have obtained 7 national innovation and entrepreneurship training programs, 52 university-level undergraduate scientific research projects, published more than 10 academic papers, and obtained 2 patent authorization. Conclusions: The training system of scientific research innovation ability of nursing undergraduates based on “3332” is conducive to the development of scientific research innovation ability of nursing students, and to cultivate nursing talents who can adapt to the development of the new era and have better post competence.

The response of roots and the rhizosphere environment to integrative cultivation practices in paddy rice

Integrative cultivation practices(ICPs)are essential for enhancing cereal yield and resource use efficiency.However,the effects of ICP on the rhizosphere environment and roots of paddy rice are still poorly understood.In this study,four rice varieties were produced in the field.Each variety was treated with six different cultivation techniques,including zero nitrogen application(0 N),local farmers’practice(LFP),nitrogen reduction(NR),and three progressive ICP techniques comprised of enhanced fertilizer N practice and increased plant density(ICP1),a treatment similar to ICP1 but with alternate wetting and moderate drying instead of continuous flooding(ICP2),and the same practices as ICP2 with the application of organic fertilizer(ICP3).The ICPs had greater grain production and nitrogen use efficiency than the other three methods.Root length,dry weight,root diameter,activity of root oxidation,root bleeding rate,zeatin and zeatin riboside compositions,and total organic acids in root exudates were elevated with the introduction of the successive cultivation practices.ICPs enhanced nitrate nitrogen,the activities of urease and invertase,and the diversity of microbes(bacteria)in rhizosphere and non-rhizosphere soil,while reducing the ammonium nitrogen content.The nutrient contents(ammonium nitrogen,total nitrogen,total potassium,total phosphorus,nitrate,and available phosphorus)and urease activity in rhizosphere soil were reduced in all treatments in comparison with the non-rhizosphere soil,but the invertase activity and bacterial diversity were greater.The main root morphology and physiology,and the ammonium nitrogen contents in rhizosphere soil at the primary stages were closely correlated with grain yield and internal nitrogen use efficiency.These findings suggest that the coordinated enhancement of the root system and the environment of the rhizosphere under integrative cultivation approaches may lead to higher rice production.

Determinants of Tobacco Cultivation and the Associated Impacts of Adoption in Hurungwe District, Zimbabwe

Tobacco is an essential cash crop in Zimbabwe and a strategic livelihood option for hundreds of thousands of rural households. However, the crop is linked to negative environmental, economic, and social impacts. The existing studies on tobacco cultivation in Zimbabwe present contradictory findings on the determinants and impacts of adoption, leaving unanswered questions about the crop’s sustainability impact in the country. This article investigates the determinants of smallholder farmers’ decisions to grow tobacco and the associated impacts of adoption. Random and purposive sampling were used to select 273 household surveys, including tobacco and non-tobacco smallholder farmers, and 56 expert interviews to answer the research questions. We employed regression models alongside expert interviews and document analysis to identify the determinants influencing the decision-making process of smallholder farmers in Zimbabwe regarding tobacco cultivation. Additionally, our investigation aimed to elucidate the perceived impacts associated with the adoption of this agricultural practice. The regression analysis indicated that the farmer’s age, education level, farming experience, family size, household income, and perceived high farm profitability are significant drivers of tobacco adoption. We also discovered divergent and convergent perceptions of the critical impacts of tobacco cultivation. The study highlights the need for proactive multi-stakeholder collaboration and sustainable financial arrangements to address the negative impacts of tobacco production. As the primary stakeholder responsible for regulating and promoting agricultural activities, the Zimbabwean government should provide meaningful financial support, increase access to credit, and ensure better market facilities for alternative crops to reduce the over-dependence on tobacco.

Detection of Bisphenol A (BPA) in Plastic Bottles Using Vertical Cultivation at Various Temperatures

Polycarbonate plastics containing bisphenol A (BPA) used to manufacture drinking water bottles. Kurdistan region in northern Iraq is a developed area with increased pollution from plastic bottles. Trace amounts of BPA have been detected in bottled water samples. The absorption of BPA was measured with HPLC using a vertical cultivation system with Bulbs of the Allium Cepa plant planted in these plastic bottles with monitored growth. Vertical cultivation was found to have a low level of BPA in the plant cells, making it a safe cultivation method under specific climate conditions. The mean concentration of BPA in vertical cultivation is 0.19 ug/ml (3.8 ng for a 20 uL injection), and the Limit of Quantification (LOQ) is 0.63 ug/ml (12.7 ng for 20 uL injection). While Scanning Electron Microscope (SEM) shows that the concentrations are relatively low in water samples stored at room temperature compared to those exposed to direct sunlight (40°C) and water bottle samples stored at (-4°C), The correlation coefficients were found to be good (0.9992). SEM is used for plastic bottle samples stored at different temperatures. The images identify compound decay and explore the morphology of BPA in manufactured plastic materials.

Technique of Earthworms Restoring Soil in Greenhouse Cultivation

The production environment of greenhouse cultivation is relatively closed,the multiple cropping index is high,the management of fertilizationwatering and pesticideapplication isblindtosomeextent,andthe phenomenonofcontinuous cropping isalsocommonSoilquali-ty affects the sustainable development of greenhouse cultivation.Earthworm is a ubiquitous invertebrate organism in soil,an important part of soil system,a link between terrestrial organisms and soil organisms,an important link in the small cycle of soil material organisms,and plays an important role in maintaining the structure and function of soil ecosystem.Different ecotypes of earthworms are closely related to their habi-tats(soil layers)and food resource preferences,and then affect their ecological functions.The principle of earthworm regulating soil function is essentially the close connection and interaction between earthworm and soil microorganism.Using different ecotypes of earthworms and bio-logical agents to carry out combined remediation of greenhouse cultivation soil is a technical model to realize sustainable development of green-house cultivation.

Strategic insights into the cultivation of pancreatic cancer organoids from endoscopic ultrasonography-guided biopsy tissue

BACKGROUND The frequent suboptimal efficacy of endoscopic ultrasound-guided fine-needle biopsy(EUS-FNB)to culture pancreatic cancer(PC)organoids(PCOs)poses a major challenge in the advancement of personalized medicine for advanced PC.AIM To explore how to obtain appropriate puncture tissues from EUS-FNB and optimize the strategy for efficiently constructing PCOs,providing an efficient tool for the advancement of personalized medicine.METHODS Patients who underwent EUS-FNB for the diagnosis of PC tissue were prospectively enrolled.We refined the endoscopic biopsy procedures and organoid cultivation techniques.All tissue specimens verified by on-site pathological assessment were cultured in a semi-suspended medium in a microfluidic environment.We assessed differences in PCOs cultured beyond and below five generations examining patient demographics,specimen and organoid attributes,and the sensitivity of organoids to a panel of clinical drugs through cell viability assays.RESULTS In this study,16 patients with PC were recruited,one sample was excluded because onsite cytopathology showed no tumor cells.Successful organoid generation occurred in 93.3%(14 of 15)of the EUS-FNB specimens,with 60%(9 of 15)sustaining over five generations.Among these patients,those with a history of diabetes,familial cancer,or larger tumors exhibited enhanced PCO expandability.The key factors influencing longterm PCOs expansion included initial needle sample quality(P=0.005),rapid initiation of organoid culture postisolation(P≤0.001),and high organoid activity(P=0.031).Drug sensitivity analysis revealed a partial response in two patients following therapeutic intervention and surgery and stable disease in four patients,indicating a moderate correlation between organoid response and clinical outcomes.CONCLUSION Optimal initial needle sampling,rapid and precise biopsy sample processing,process isolated samples as soon as possible,and sufficient cellular material are crucial for successful cultivating PCOs.High organoid activity is an important factor in maintaining their long-term expansion,which is essential for shortening the time of drug sensitivity analysis and is the basis of PC research.

High Yield Cultivation and Pest Control Technology of Cashew

In order to enhance the yield and quality of cashew,it is essential to implement high-yield cultivation techniques effectively throughout the production process.Additionally,pest control measures should be employed to provide technical support for the industrialized development of cashew.

Rice Cultivation under Film Mulching Can Improve Soil Environment and Be Beneficial for Rice Production in China

Rice cultivation under film mulching is an integrated management technology that can conserve water, increase soil temperature, improve yield, and enhance water and nitrogen use efficiencies. Despite these advantages, the system does have its drawbacks, such as soil organic matter reduction and microplastic pollution, which impede the widespread adoption of film mulching cultivation in China. Nonetheless, the advent of degradable film, controlled-release fertilizer, organic fertilizer, and film mulching machinery is promoting the development of rice film mulching cultivation. This review outlines the impact of rice cultivation under film mulching on soil moisture, soil temperature, soil fertility, greenhouse gas emissions, weed control, and disease and pest management. It also elucidates the mechanism of changes in rice growth, yield and quality, water use efficiency, and nitrogen use efficiency. This paper incorporates a review of published research articles and discusses some uncertainties and shortcomings associated with rice cultivation under film mulching. Consequently, prospective research directions for the technology of rice film mulching cultivation are outlined, and recommendations for future research into rice cultivation under film mulching are proposed.