On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Study on time effect and prediction model of shear strength of root-soil complex under dry-wet cycle

Triaxial compression tests were conducted on the alfalfa root-loess complex at different growthperiods obtained through artificial planting.The research focused on analyzing the time variation law of the shear strength index and deformation index of the alfalfa root-loess complex under dry-wet cycles.Additionally,the time effect of the shear strength index of the alfalfa root-loess complex under dry-wet cycles was analyzed and its prediction model was proposed.The results show that the PG-DWC(dry-wet cycle caused by plant water management during plant growth period)causes the peak strength of plain soil to change in a"V"shape with the increase of growth period,and the peak strength of alfalfa root-loess complex is higher than that of plain soil at the same growth period.The deterioration of the peak strength of alfalfa root-loess complex in the same growth period is aggravated with the increase of drying and wetting cycles.Compared with the 0 days growth period,the effective cohesion of alfalfa root-loess complex under different dry-wet cycles maximum increase rate is at the 180 days,which are 33.88%,46.05%,30.12%and 216.02%,respectively.When the number of dry-wet cycles is constant,the effective cohesion of the alfalfa root-loess complex overall increases with the growth period.However,it gradually decreases comparedwith the previous growth period,and the minimum increase rate are all at the 180 days.For the same growth period,the effective cohesion of the alfalfa root-loess complex decreases with the increase of the number of dry-wet cycles.This indicates that EC-DWC(the dry-wet cycles caused by extreme natural conditions such as continuous rain)have a detrimental effect on the time effect of the shear strength of the alfalfa root-loess complex.Finally,based on the formula of total deterioration,a prediction model for the shear strength of the alfalfa root-loess complex under dry-wet cycles was proposed,which exhibits high prediction accuracy.The research results provide useful guidance for the understanding of mechanical behavior and structural damage evolution of root-soil composite.

Phosphorus limitation on CO_(2)fertilization effect in tropical forests informed by a coupled biogeochemical model

Tropical forests store more than half of the world's terrestrial carbon(C)pool and account for one-third of global net primary productivity(NPP).Many terrestrial biosphere models(TBMs)estimate increased productivity in tropical forests throughout the 21st century due to CO_(2)fertilization.However,phosphorus(P)liaitations on vegetation photosynthesis and productivity could significantly reduce the CO_(2)fertilization effect.Here,we used a carbon-nitrogen-phosphorus coupled model(Dynamic Land Ecosystem Model;DLEM-CNP)with heterogeneous maximum carboxylation rates to examine how P limitation has affected C fluxes in tropical forests during1860-2018.Our model results showed that the inclusion of the P processes enhanced model performance in simulating ecosystem productivity.We further compared the simulations from DLEM-CNP,DLEM-CN,and DLEMC and the results showed that the inclusion of P processes reduced the CO_(2)fertilization effect on gross primary production(GPP)by 25%and 45%,and net ecosystem production(NEP)by 28%and 41%,respectively,relative to CN-only and C-on ly models.From the 1860s to the 2010s,the DLEM-CNP estimated that in tropical forests GPP increased by 17%,plant respiration(Ra)increased by 18%,ecosystem respiration(Rh)increased by 13%,NEP increased by 121%per unit area,respectively.Additionally,factorial experiments with DLEM-CNP showed that the enhanced NPP benefiting from the CO_(2) fertilization effect had been offset by 135%due to deforestation from the 1860s to the 2010s.Our study highlights the importance of P limitation on the C cycle and the weakened CO_(2)fertilization effect resulting from P limitation in tropical forests.

An improved strain-softening constitutive model of granite considering the effect of crack deformation

This paper presents an improved strain-softening constitutive model considering the effect of crack deformation based on the triaxial cyclic loading and unloading test results.The improved model assumes that total strain is a combination of plastic,elastic,and crack strains.The constitutive relationship between the crack strain and the stress was further derived.The evolutions of mechanical parameters,i.e.strength parameters,dilation angle,unloading elastic modulus,and deformation parameters of crack,with the plastic strain and confining pressure were studied.With the increase in plastic strain,the cohesion,friction angle,dilation angle,and crack Poisson's ratio initially increase and subsequently decrease,and the unloading elastic modulus and the crack elastic modulus nonlinearly decrease.The increasing confining pressure enhances the strength and unloading elastic modulus,and decreases the dilation angle and Poisson's ratio of the crack.The theoretical triaxial compressive stress-strain curves were compared with the experimental results,and they present a good agreement with each other.The improved constitutive model can well reflect the nonlinear mechanical behavior of granite.

Similarity Criterion and Scale Effect for Ship Distortion Model Under Combined Loads

For the ultimate strength model test evaluation of large ship structures, the distortion model with non-uniform ratio between the main size and the plate thickness size is usually adopted. It is the key to carry out scale model test to establish a distortion model similar to the real ship structure under combined load. A similarity criterion for ship distortion model under the combined action of bending moment and surface pressure was proposed, and the scale effect for the criterion was verified by a se ries of numerical analysis and model tests. The results show that the similarity criterion for ship distor tion model under combined loads has a certain scale effect. For the model tests of ship cabin struc tures, it is suggested that the scale range between the plate thickness scale and the main dimension scale should be controlled within 2:1, which can be used as a reference for distortion model design and ultimate strength test of large-scale ship structures.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Theoretical study on the effective thermal conductivity of silica aerogels based on a cross-aligned and cubic pore model

Aerogel nanoporous materials possess high porosity, high specific surface area, and extremely low density due to their unique nanoscale network structure. Moreover, their effective thermal conductivity is very low, making them a new type of lightweight and highly efficient nanoscale super-insulating material. However, prediction of their effective thermal conductivity is challenging due to their uneven pore size distribution. To investigate the internal heat transfer mechanism of aerogel nanoporous materials, this study constructed a cross-aligned and cubic pore model(CACPM) based on the actual pore arrangement of SiO_(2) aerogel. Based on the established CACPM, the effective thermal conductivity expression for the aerogel was derived by simultaneously considering gas-phase heat conduction, solid-phase heat conduction, and radiative heat transfer. The derived expression was then compared with available experimental data and the Wei structure model. The results indicate that, according to the model established in this study for the derived thermal conductivity formula of silica aerogel, for powdery silica aerogel under the conditions of T = 298 K, a_(2)= 0.85, D_(1)= 90 μm, ρ = 128 kg/m^(3), within the pressure range of 0–10^(5)Pa, the average deviation between the calculated values and experimental values is 10.51%. In the pressure range of 10^(3)–10^(4)Pa, the deviation between calculated values and experimental values is within 4%. Under these conditions, the model has certain reference value in engineering verification. This study also makes a certain contribution to the research of aerogel thermal conductivity heat transfer models and calculation formulae.

Drivers for Inter-city Innovation Networks Across Chinese Cities:Modelling Physical Versus Intangible Effects

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

Study on the effect of four kinds of raw materials in hypertonic dehydration cell model

It aims to investigate the protective effects of sodium hyaluronate,panthenol,Portulaca oleracea L.and Calendula officinalis L.on hyperosmotic dehydration-induced injury of human immortalized keratinocytes(HaCaT).The safety mass concentrations of four raw materials were screened by detecting cell viability,and the secretion of hyaluronic acid(HA)was determined using the ELISA method.The expression of HaCaT barrier function related genes(OVOL1,EREG,TGM1,TGM2,IVL,IRF6,THBS1,CASP14)was detected at the mRNA level to explore the regulatory effect of four raw materials on these genes.The results demonstrate that pretreatment with the four kinds of raw materials could increase the cell viability after hyperosmotic dehydration,promote the secretion of HA,and improve the expression of barrier function related genes after hyperosmotic dehydration,among which panthenol and Calendula officinalis L.are better.The results show that the four raw materials have a certain protective effect on the hyperosmotic dehydration cell model,which provides data support for its application in cosmetics.

Adaptive Random Effects/Coefficients Modeling

Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.

3D time-domain forward modeling of airborne transient electromagnetism considering superparamagnetic effect

The superparamagnetic effect arises from the superparamagnetism exhibited by a multitude of nano-sized magnetic mineral particles under an external electric field.This phenomenon manifests in transient electromagnetic data primarily as a deceleration in the attenuation rate of late-stage signals,a characteristic difficult to discern directly from airborne transient electromagnetic signals,consequently leading to significant misinterpretations of subterranean electrical structures.This study embarks on 3D forward modeling of airborne electromagnetic responses in the frequency domain,accounting for the superparamagnetic effect,utilizing an unstructured finite element method.Superparamagnetic responses in the time domain were obtained through frequency-time conversion.This investigation explores the influence of various parameters-such as magnetic susceptibility,time constants,and flight altitude-on the superparamagnetic effect by examining the response characteristics of typical targets.Findings indicate that in its late stages,the superparamagnetic effect can induce a relative anomaly of up to 300%.There is a positive correlation between magnetic susceptibility and the strength of the superparamagnetic effect.The influence of the time constant's upper and lower limits on the superparamagnetic effect is minimal;however,the range between these limits significantly affects the effect,showing a negative correlation with its intensity.Higher flight altitudes weaken the superparamagnetic signal.The impact is most pronounced when superparamagnetic minerals are shallowly buried,effectively shielding the underlying geology with the characteristics of a good conductivity anomaly,but this effect diminishes with greater depth.The insights from this study provide a theoretical framework for a deeper understanding of the superparamagnetic effect in transient electromagnetic signals and for more accurate interpretations of subterranean geological and electrical structures.

Sterilization Effect of Cooking Process for Guilin Rice Noodles Based on Heat Conduction Model

Guilin rice noodles, a unique cuisine from Guilin, Guangxi, is renowned both domestically and internationally as one of the top ten “Guilin Classics”. Utilizing a heat conduction model, this study explores the effectiveness of the cooking process in sterilizing Guilin rice noodles before consumption. The model assumes that a large pot is filled with boiling water which is maintained at a constant high temperature heat resource through continuous gentle heating. And the room temperature is set as the initial temperature for the preheating process and the final temperature for the cooling process. The objective is to assess whether the cooking process achieves satisfactory sterilization results. The temperature distribution function of rice noodle with time is analytically obtained using the separation of variables method in the three-dimensional cylindrical coordinate system. Meanwhile, the thermal diffusion coefficient of Guilin rice noodles is obtained in terms of Riedel’ theory. By analyzing the elimination characteristics of Pseudomonas cocovenenans subsp. farinofermentans, this study obtains the optimal time required for effective sterilization at the core of Guilin rice noodles. The results show that the potential Pseudomonas cocovenenans subsp. farinofermentans will be completely eliminated through continuously preheating more than 31 seconds during the cooking process before consumption. This study provides a valuable reference of food safety standards in the cooking process of Guilin rice noodles, particularly in ensuring the complete inactivation of potentially harmful strains such as Pseudomonas cocovenenans subsp. farinofermentans.

Time-Varying Mesh Stiffness Calculation and Dynamic Modeling of Spiral Bevel Gear with Spalling Defects

Time-varying mesh stiffness(TVMS)is a vital internal excitation source for the spiral bevel gear(SBG)transmission system.Spalling defect often causes decrease in gear mesh stiffness and changes the dynamic characteristics of the gear system,which further increases noise and vibration.This paper aims to calculate the TVMS and establish dynamic model of SBG with spalling defect.In this study,a novel analytical model based on slice method is proposed to calculate the TVMS of SBG considering spalling defect.Subsequently,the influence of spalling defect on the TVMS is studied through a numerical simulation,and the proposed analytical model is verified by a finite element model.Besides,an 8-degrees-of-freedom dynamic model is established for SBG transmission system.Incorporating the spalling defect into TVMS,the dynamic responses of spalled SBG are analyzed.The numerical results indicate that spalling defect would cause periodic impact in time domain.Finally,an experiment is designed to verify the proposed dynamic model.The experimental results show that the spalling defect makes the response characterized by periodic impact with the rotating frequency of spalled pinion.

Analysis of the Effectiveness of a General Medicine Management Model in Treating Chronic Coronary Syndrome

Objective:To analyze the effects of a general medicine management model in the treatment of chronic coronary syndrome.Methods:The study included 100 patients with chronic coronary syndrome admitted to the hospital between April 2022 and May 2023.Patients were divided into an observation group and a control group to compare the outcomes of the general medicine-based management model with those of the conventional management model.Results:The incidence of adverse cardiovascular events in the observation group was significantly lower than in the control group(P<0.05).Anxiety and depression scores in the observation group were also significantly lower than those in the control group(P<0.05).Quality-of-life scores and patient satisfaction in the observation group were significantly higher than those in the control group(P<0.05).Conclusion:Implementing a general medicine-based management model for patients with chronic coronary syndrome effectively reduces the incidence of adverse cardiovascular events,significantly improves patients’emotional well-being and quality of life,and has notable clinical significance for wider adoption.

Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

Analysis of the Effect of the Comprehensive Nursing Model on Patients with Moyamoya Disease Undergoing Intracranial and Extracranial Revascularization Surgery

Objective:To explore the effect of a comprehensive nursing model on patients with Moyamoya disease who underwent intracranial and extracranial revascularization surgery.Methods:110 cases were divided into control and observation groups with 55 cases each.The control group received routine perioperative care,and the observation group received perioperative care along with comprehensive nursing care.The two groups’disease cognition levels,anxiety,symptoms,daily living ability scores,and postoperative complication rates were compared.Results:The anxiety score and total postoperative complications of the observation group upon discharge were lower than that of the control group,and the disease cognition level and daily living ability upon discharge were higher than that of the control group(P<0.05).Conclusion:Applying the comprehensive nursing model in conjunction with perioperative care for patients undergoing surgery can effectively improve their anxiety,strengthen activities of daily living,and reduce the risk of postoperative complications.

Model tests and numerical analysis of emergency treatment of cohesionless soil landslide with quick-setting polyurethane

Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.

Numerical modeling of seabed morphological effects from the construction of artificial islands in Danzhou, Hainan

Haihua Islands is a large artificial island in Danzhou, Hainan. The construction of Haihua Islands changes the hYdrodynamic environment of Yangpu waters, and further affects its morphological change. Delft3D is used to set up a two dimensional nested hydrodynamic and sediment model for Yangpu waters in this paper, and this paper focuses on simulating the velocity and morphological change due to the construction of Haihua Islands after the verification of the model. The seabed deposition is small because of low suspended sediment concentration and less sand source near Yangpu waters. The bed level erodes in the south area of Xiaochan Reef and the Yangpu channel due to the velocity increase in the area.

Analysis of Genetic Effects of Nuclear-Cytoplasmic Interaction on Quantitative Traits:Genetic Model for Diploid Plants

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction （NCI） as well as their genotype by environment （GE） interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction （AUP） method. Data on four quantitative traits （boll number, lint percentage, fiber length, and micronaire） in Upland cotton （Gossypium hirsutum L.） were analyzed as a worked example to show the effectiveness of the model.

涉海产业类企业融资效率及影响因素测评研究——基于DEA-Random Effects Models的经验数据

为发展壮大涉海产业类企业并带动海洋产业发展以实现海洋强国战略,有必要对涉海产业类企业融资效率状况进行准确定位并采取相应策略。以企业融资效率理论为基础,运用DEA模型评价涉海产业类企业融资效率及并运用随机效应面板数据模型检验其影响因素。检验结果发现,2008-2013年间涉海产业类企业融资效率整体上处于低效水平,其主要影响因素有宏观经济形势、行业竞争程度、企业规模大小和公司治理机制。企业融资效率与宏观经济形势、行业竞争程度和公司治理机制显著正相关,与企业规模大小显著负相关。这说明涉海产业类企业还有大幅度提高融资效率的空间,政策建议是引导资本市场支持海洋资源开发利用,保持稳定增长的整体经济环境,促进垄断竞争性涉海产业类企业理性投融资,缓解中小型涉海产业类企业融资难困境和深化国有控股涉海产业类企业改革。