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.

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.

Effects of Initial Defects on Effective Elastic Modulus of Concrete with Mesostructure

An exquisite mesostructure model was presented to predict the effective elastic modulus of concrete,in which concrete is realized as a four-phase composite material consisting of coarse aggregates,mortar matrix,interfacial transition zone(ITZ),and initial defects.With the three-dimensional(3D)finite element(FE)simulation,the highly heterogeneous composite elastic behavior of concrete was modeled,and the predicted results were compared with theoretical estimations for validation.Monte Carlo(MC)simulations were performed with the proposed mesostructure model to investigate the various factors of initial defects influencing the elastic modulus of concrete,such as the shape and concentration(pore volume fraction or crack density)of microspores and microcracks.It is found that the effective elastic modulus of concrete decreases with the increase of initial defects concentration,while the distribution and shape characteristics also exert certain influences due to the stress concentration caused by irregular inclusion shape.

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.

Prediction and quantification of effective gas source rocks in a lacustrine basin:Western Depression in the Liaohe Subbasin,China

Due to limited data on the geochemical properties of natural gas,estimations are needed for the effective gas source rock in evaluating gas potential.However,the pronounced heterogeneity of mudstones in lacustrine successions complicates the prediction of the presence and geochemical characteristics of gas source rocks.In this paper,the Liaohe Subbasin of Northeast China is used as an example to construct a practical methodology for locating effective gas source rocks in typical lacustrine basins.Three types of gas source rocks,microbial,oil-type,and coal-type,were distinguished according to the different genetic types of their natural gas.A practical three-dimensional geological model was developed,refined,and applied to determine the spatial distribution of the mudstones in the Western Depression of the Liaohe Subbasin and to describe the geochemical characteristics(the abundance,type,and maturation levels of the organic matter).Application of the model in the subbasin indicates that the sedimentary facies have led to heterogeneity in the mudstones,particularly with respect to organic matter types.The effective gas source rock model constructed for the Western Depression shows that the upper sequence(SQ2)of the Fourth member(Mbr 4)of the Eocene Shahejie Formation(Fm)and the lower and middle sequences(SQ3 and SQ4)of the Third member(Mbr 3)form the principal gas-generating interval.The total volume of effective gas source rocks is estimated to be 586 km^(3).The effective microbial,oil-type,and coal-type gas source rocks are primarily found in the shallow western slope,the central sags,and the eastern slope of the Western Depression,respectively.This study provides a practical approach for more accurately identifying the occurrence and geochemical characteristics of effective natural gas source rocks,enabling a precise quantitative estimation of natural gas reserves.

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.

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.

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.

A Prediction Model of Effective Thermal Conductivity for Metal Powder Bed in Additive Manufacturing

In current research,many researchers propose analytical expressions for calculating the packing structure of spherical particles such as DN Model,Compact Model and NLS criterion et al.However,there is still a question that has not been well explained yet.That is:What is the core factors affecting the thermal conductivity of particles?In this paper,based on the coupled discrete element-finite difference(DE-FD)method and spherical aluminum powder,the relationship between the parameters and the thermal conductivity of the powder(ETC_(p))is studied.It is found that the key factor that can described the change trend of ETC_(p) more accurately is not the materials of the powder but the average contact area between particles(a_(ave))which also have a close nonlinear relationship with the average particle size d_(50).Based on this results,the expression for calculating the ETC_(p) of the sphere metal powder is successfully reduced to only one main parameter d_(50)and an efficient calculation model is proposed which can applicate both in room and high temperature and the corresponding error is less than 20.9%in room temperature.Therefore,in this study,based on the core factors analyzation,a fast calculation model of ETC_(p) is proposed,which has a certain guiding significance in the field of thermal field simulation.

Research on the Evaluation of VBSE Practical Training Teaching Effectiveness Based on CIPP Model at X University

Based on the CIPP(context,input,process,and product)model,this paper constructs an index system suitable for evaluating the teaching effect of VBSE(virtual business social environment)practical training from four aspects:context evaluation,input evaluation,process evaluation,and product evaluation.Taking the students participating in VBSE practical training in X university as the survey population,381 valid sample data were obtained through an online questionnaire survey,and the index weights were determined by factor analysis method.The score value of the VBSE practical training teaching effect was calculated based on the evaluation mean value of three indexes.The results showed that the context evaluation score was 1.56,the input evaluation score was 1.54,the process evaluation score was 1.51,and the product evaluation score was 1.48.Subsequently,this paper put forward some countermeasures from the aspects of optimizing course arrangement,improving hardware facilities,and enhancing team cooperation to provide a guideline for improving the effect of VBSE practical training.

Experimental and theoretical study on the dynamic effective stress of loaded gassy coal during gas release

In the process of mining coalbed methane(CBM),an unsteady state often arises due to the rapid extraction,release and pressure relief of CBM.In this case,the effective stress of coal changes dynamically,affecting the stability of the gassy coal seam.In this paper,gas release tests of gassy coal under conventional triaxial compression were performed,and the dynamic effective stress(DES)during gas release was obtained indirectly based on a constitutive equation and deformation of coal.The results show that the maximum increases in DES caused by the release of free gas and adsorbed gas under the stress of 1.1 MPa were 0.811 and 5.418 MPa,respectively,which seriously affected the stress state of the coal.During the gas release,the free gas pressure and the adsorbed gas volume were the parameters that directly affected the DES and showed a positive linear relationship with the DES with an intercept of zero.The DES of the coal sample increased exponentially with time,which was determined by the contents of free and adsorbed gas.Based on the experimental results and theoretical analysis,an effective stress model was obtained for loaded gassy coal during gas release.The results of verification indicated accuracy greater than 99%.

Improving maize growth and development simulation by integrating temperature compensatory effect under plastic film mulching into the AquaCrop model

Temperature compensatory effect, which quantifies the increase in cumulative air temperature from soil temperature increase caused by mulching, provides an effective method for incorporating soil temperature into crop models. In this study, compensated temperature was integrated into the AquaCrop model to investigate the capability of the compensatory effect to improve assessment of the promotion of maize growth and development by plastic film mulching(PM). A three-year experiment was conducted from2014 to 2016 with two maize varieties(spring and summer) and two mulching conditions(PM and non-mulching(NM)), and the AquaCrop model was employed to reproduce crop growth and yield responses to changes in NM, PM, and compensated PM. A marked difference in soil temperature between NM and PM was observed before 50 days after sowing(DAS) during three growing seasons. During sowing–emergence and emergence–tasseling, the increase in air temperature was proportional to the compensatory coefficient, with spring maize showing a higher compensatory temperature than summer maize. Simulation results for canopy cover(CC) were generally in good agreement with the measurements, whereas predictions of aboveground biomass and grain yield under PM indicated large underestimates from 60 DAS to the end of maturity. Simulations of spring maize biomass and yield showed general increase based on temperature compensation, accompanied by improvement in modeling accuracy, with RMSEs decreasing from 2.5 to 1.6 t ha^(-1)and from 4.1 t to 3.4 t ha^(-1). Improvement in biomass and yield simulation was less pronounced for summer than for spring maize, implying that crops grown during low-temperature periods would benefit more from the compensatory effect. This study demonstrated the effectiveness of the temperature compensatory effect to improve the performance of the AquaCrop model in simulating maize growth under PM practices.

Cardiovascular Cast Model Fabrication and Casting Effectiveness Evaluation in Fetus with Severe Congenital Heart Disease or Normal Heart

To investigate the application and effectiveness of vascular corrosion technique in preparing fetal cardiovascular cast models, 10 normal fetal heart specimens with other congenital disease（control group） and 18 specimens with severe congenital heart disease（case group） from induced abortions were enrolled in this study from March 2013 to June 2015 in our hospital. Cast models were prepared by injecting casting material into vascular lumen to demonstrate real geometries of fetal cardiovascular system. Casting effectiveness was analyzed in terms of local anatomic structures and different anatomical levels（including overall level, atrioventricular and great vascular system, left-sided and right-sided heart）, as well as different trimesters of pregnancy. In our study, all specimens were successfully casted. Casting effectiveness analysis of local anatomic structures showed a mean score from 1.90±1.45 to 3.60±0.52, without significant differences between case and control groups in most local anatomic structures except left ventricle, which had a higher score in control group（P=0.027）. Inter-group comparison of casting effectiveness in different anatomical levels showed no significant differences between the two groups. Intra-group comparison also revealed undifferentiated casting effectiveness between atrioventricular and great vascular system, or left-sided and right-sided heart in corresponding group. Third-trimester group had a significantly higher perfusion score in great vascular system than second-trimester group（P=0.046）, while the other anatomical levels displayed no such difference. Vascular corrosion technique can be successfully used in fabrication of fetal cardiovascular cast model. It is also a reliable method to demonstrate three-dimensional anatomy of severe congenital heart disease and normal heart in fetus.

Modelling seedling development using thermal effectiveness and photosynthetically active radiation

Seedling quality is a prerequisite for successful field performance and therefore influences crop yields. Temperature and illumination are two major factors affecting seedling quality during nursery propagation. Suboptimal temperature or light of nurseries generally result in leggy or weak seedlings and great economic loss. However, production of healthy seedlings is challenging due to the lack of knowledge in systemic management of nursery environments. In this study, we have established simulation models to predict how temperature and illumination coordinately influence the growth of tomato and cabbage seedlings. Specifically, correlation between seedling quality characteristics(root-shoot ratio, G value(growth function: defined as ratio of whole plant dry weight to days of seedling), healthy indexes) and TEP(thermal effectiveness and photosynthetically active radiation) were explored to establish the models, which were validated with independent test data. Our results suggested that the curve of healthy index 1(HI1) and TEP fitted well with high coefficient of determination(R2) in both species, indicating that the model is highly reliable. The HI1 simulation models for tomato and cabbage are HI1=0.0009e0.0308TEP-0.0015 and HI1= 0.0003e0.0671TEP-0.0003, respectively, which can be used for predicting vigors of tomato and cabbage seedlings grown under different temperature and light conditions.

UML-based combat effectiveness simulation system modeling within MDE

To reduce complexity, the combat effectiveness simulation system(CESS) is often decomposed into static structure,physical behavior, and cognitive behavior, and model abstraction is layered onto domain invariant knowledge(DIK) and application variant knowledge(AVK) levels. This study concentrates on the specification of CESS’s physical behaviors at the DIK level of abstraction, and proposes a model driven framework for efficiently developing simulation models within model-driven engineering(MDE). Technically, this framework integrates the four-layer metamodeling architecture and a set of model transformation techniques with the objective of reducing model heterogeneity and enhancing model continuity. As a proof of concept, a torpedo example is illustrated to explain how physical models are developed following the proposed framework. Finally, a combat scenario is constructed to demonstrate the availability, and a further verification is shown by a reasonable agreement between simulation results and field observations.

INTERACTION MODELS FOR EFFECTIVE THERMAL AND ELECTRIC CONDUCTIVITIES OF CARBON NANOTUBE COMPOSITES

The present article provides supplementary information of previous works of analytic models for predicting conductivity enhancements of carbon nanotube composites. The models, though fairly simple, are able to take account of the effects of conductivity anisotropy, nonstraightness, and aspect ratio of the CNT additives on the conductivity enhancement of the composite and to give predictions agreeing well with existing experimental data. The omitted detailed derivation of this model is demonstrated in the present article with a more systematical analysis, which may help with further development in this direction. Furthermore, the effects of various orientation distributions of CNTs are reported here for the first time. The information may be useful in design or fabrication technology of CNT composites for better or specified conductivities.