Generalized Anticipation Effect Models for Traffic Flow

Taking into account the startup behaviour of following vehicles in the waiting area of urban traffic signal, we propose an extended Nagel-Schreckenberg model for single-lane traffic flow, in which the dynamic behavior of each vehicle depends on not only its own headway but also the headway of the immediately preceding one. The numerical simulation of the present model reproduces some complicated nonlinear phenomena observed in real traffic such as free flow, ghostly blockage, synchronized flow and so on. For specific parameter combinations the flow-density relation of this model shows two meta-stable branches near the transition density from free flow to wide moving traffic jam. Finally, the analytical results of the model under some specific parameters are given by using the mean field theory.

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.

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.

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.

Establishment and Evaluation of a Mouse Model of Allergic Rhinitis

[Objectives]To explore a new method for induction of allergic rhinitis in mice,and compare and evaluate it with common modeling methods.[Methods]36 mice were randomly divided into the control group,blank group and experimental group,and there were 12 mice in each group.The mice in the control group were conventionally induced.That is,the mice were first injected intraperitoneally with the mixture composed of OVA 50μg,[Al(OH)3]5 mg and 1ml of normal saline once every other day,and then since the 15 th d,20μL of 5%OVA solution was dropped into each nasal cavity once a day,which lasted for 7 d.The blank group was treated with the same amount of normal saline according to the control group,and received intraperitoneal injection and bilateral nasal drip respectively.In the experimental group,mice were first given intraperitoneal injection of the mixture composed of ovalbumin(OVA)75μg,aluminum hydroxide gel[Al(OH)3]8 mg and normal saline 1.5 mL for basic sensitization.On the 26 th d,20μL of 3%OVA solution was dropped into each nasal cavity once a day,which lasted for 10 d.The number of sneezes,the number of nose scratching,the amount of nasal discharge,and the activity of mice in each group were observed,and the behavior of allergic reaction was scored.Meanwhile,the number of eosinophils in the nasal discharge of mice and the IgE content in serum were measured.[Results]The score of nasal stimulation symptoms,the number of eosinophils and serum IgE level of mice in the control group and the experimental group were higher than those in the blank group(P<0.05),and there was no statistical significance between the two groups in the three indicators(P>0.05).[Conclusions]The modeling method was more suitable for the development of allergic rhinitis patients condition,and reduced the probability of death of mice due to modeling,and simplified the experimental operation.

Integrating Downstream Ecological, Social and Economic Effects of Hydropower to Hydraulic Modeling: A Review

Hydropower gains increasing importance as a steerable and controllable power source in a renewable energy mix and deregulated markets. Although hydropower produces fossil-free energy, it has a significant impact on the local environment. This review investigates the effects of flow alterations by hydropower on the downstream river system and the possibilities to integrate these effects into hydraulic modeling. The results show that various effects of flow regulation on the ecosystem, but also social and economic effects on related communities were observed in the last decades. The application of hydraulic models for investigations of ecological effects is common. Especially hydraulic effects and effects on fish were extensively modeled with the help of hydraulic 1D- and 2D-simulations. Current applications to investigate social and economic effects integrated into hydraulic modeling are meanwhile limited. Approaches to realizing this integration are presented. Further research on the economic valuation of ecosystems and integration of social and economic effects to hydraulic models is necessary to develop holistic tools to support decision-making on sustainable hydropower.

Dynamic Analysis of an Algae-Fish Harvested Model with Allee Effect

In this paper, an algae-fish harvested model with Allee effect was established to further explore the dynamic evolution mechanism under the influence of key factors. Mathematical theoretical work not only investigated the existence and stability of all possible equilibrium points, but also probed into the occurrence of transcritical and Hopf bifurcation. The numerical simulation works verified the effectiveness of the theoretical derivation results and displayed rich bifurcation dynamical behaviors, which showed that Allee effect and harvest have played a vital role in the dynamic relationship between algae and fish. In summary, it was expected that these research results would be beneficial for promoting the study of bifurcation dynamics in aquatic ecosystems.

The Use of Models to Evaluate Corrosion Effects on Mild Steel Heat Exchanger in Water and Mono Ethanol Amine (MEA)

Heat exchanger is an important equipment used in process industries for cooling and heating purposes. Its design configuration which involves the flow of cold and hot fluids within the exchanger subjects it to corrosion attack. The article utilized the principle of mass and energy conservation in the development of weight and temperature models to study the effect of corrosion on mild steel coupon inside the exchanger containing water and Mono ethanol amine (MEA). The models developed were resolved analytically using Laplace Transform and simulated using Excel as simulation tool and data obtained from experiment in the laboratory to obtain profiles of weight loss and temperature as a function of time. The weight loss and performance of mild steel under various corrosive conditions were examined which indicates the effect of corrosion on the mild steel heat exchanger in water and MEA media. The result shows that water is more corrosive than MEA at higher temperatures and at lower temperatures of 35°C and 1 atm, MEA has inhibitive properties than water as indicated by the weight loss result with time. The comparative analysis between the results obtained from the model simulation and experimental results shows that the result obtained from the model is more reliable and demonstrated better performance characteristics as it clearly shows mild steel heat exchanger experiences more corrosive effect in water medium than MEA at higher temperatures. And at lower temperatures, MEA becomes more inhibitive and less corrosive than water. The model simulation results correlate with various literatures and hence, it is valid for future referencing.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Existence of Forced Waves and Their Asymptotic for Leslie-Gower Prey-Predator Model with Nonlocal Effects under Shifting Environment

In this paper, we prove the existence of forced waves for Leslie-Gower prey-predator model with nonlocal effects under shifting environment. By constructing a pair of upper and lower solutions with the method of monotone iteration, we can obtain the existence of forced waves for any positive constant shifting speed. Finally, we show the asymptotical behavior of traveling wave fronts in two tails.

Study of the Magnetocaloric Effect in La0.5Sm0.2Sr0.3Mn1-xFexO3 (x = 0 and 0.05) Manganites with the Mean-Field Theory

In this paper, the magnetocaloric in La0.5Sm0.2Sr0.3Mn1-xFexO3 compounds with x = 0 (LSSMO) and x = 0.05 (LSSMFO) were simulated using mean field model theory. A strong consistency was observed between the theoretical and experimental curves of magnetizations and magnetic entropy changes, −ΔSM(T). Based on the mean-field generated −ΔSM(T), the substantial Temperature-averaged Entropy Change (TEC) values reinforce the appropriateness of these materials for use in magnetic refrigeration technology within TEC (10) values of 1 and 0.57 J∙kg−1∙K−1under 1 T applied magnetic field.

Modeling the Infection Disease (Covid-19) and the Effect of Vaccination

In this paper we provide different types of approach in mathematical biology about infection disease and understanding the dynamic of epidemic mathematical models specially in COVID-19 disease which first outbroke in China and fast spread around the world. We work in the connection between the mathematical models and the solution analytically and numerically. At first, we emphasize the Susceptible-Infectious-Recovered (SIR) models’ extension for policy significance. Then, we found the improved SIER model done by research. In third section, we examine the improved model when an appropriate vaccine has been found, we introduce the model of SIR with vaccine term which ends up with discussion and conclusion about the effect of vaccinate. The comprehension of COVID-19 transmission methods, structures, and characteristics is greatly aided by these mathematical models analytically and numerically.

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。

Growth Ring-dependent Fracture Toughness of Sea Urchin Spines Estimated by Boundary Effect Model

Although the fracture behavior of sea urchin spines has been extensively investigated,there is as yet a lack of quantitative estimation on the effect of growth rings on the fracture properties of sea urchin spines.In sea urchin spines,much denser pores present in growth rings rather than porous layers.The tensile strength and fracture toughness of sea urchin spine samples with different numbers of growth rings are measured by the Boundary Effect Model(BEM).The experimental results of single-edge notched three-point bending tests indicate that the BEM is an appropriate method to estimate the fracture toughness of the present porous sea urchin spines,and the number of growth rings plays an important role in the fracture properties of spines.Specifically,the tensile strength and fracture toughness of sea urchin spines can be significantly improved with the increase in the number of growth rings,and their fracture toughness can even reach a relatively high value compared with some other porous materials with an identical porosity.The present research findings are expected to provide a fundamental insight into the design of high-performance bionic materials with a highly porous structure.

Generalized Height-Diameter Models for Pinus montezumae Lamb. and Pinus pseudostrobus Lindl. Plantations in Michoacan, Mexico

Tree height (H) in a natural stand or forest plantation is a fundamental variable in management, and the use of mathematical expressions that estimate H as a function of diameter at breast height (d) or variables at the stand level is a valuable support tool in forest inventories. The objective was to fit and propose a generalized H-d model for Pinus montezumae and Pinus pseudostrobus established in forest plantations of Nuevo San Juan Parangaricutiro, Michoacan, Mexico. Using nonlinear least squares (NLS), 10 generalized H-d models were fitted to 883 and 1226 pairs of H-d data from Pinus montezumae and Pinus pseudostrobus, respectively. The best model was refitted with the maximum likelihood mixed effects model (MEM) approach by including the site as a classification variable and a known variance structure. The Wang and Tang equation was selected as the best model with NLS;the MEM with an additive effect on two of its parameters and an exponential variance function improved the fit statistics for Pinus montezumae and Pinus pseudostrobus, respectively. The model validation showed equality of means among the estimates for both species and an independent subsample. The calibration of the MEM at the plot level was efficient and might increase the applicability of these results. The inclusion of dominant height in the MEM approach helped to reduce bias in the estimates and also to better explain the variability among plots.

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.

EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL

Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.

A Macroscopic Model for the Portevin-Le Chatelier Effect

The Portevin-Le Chatelier (PLC) effect means serrated yielding or jerky flow phenomenon in some alloys. In this paper a macroscopic model is developed to investigate the PLC effect with the emphasis on mechanical response of the structure evolution on microscopic scale. In addition to the normal work hardening effect, the model takes account of the thermal activation of dislocation moving with the aid of stress and the collective interactions between mobile dislocations and solute atoms due to dynamic strain ageing (DSA). It can satisfy the negative strain rate sensitivity of flow stress, which is believed to be one of the most special features associated with the PLC effect. The heterogeneous nature of the deformed material is also considered by introducing a nonuniform spatial distribution of some model parameters. The serrated yielding and localized deformation behavior can be successfully reproduced via numerical simulation based on this model.

Nonlinear mixed-effects height to crown base and crown length dynamic models using the branch mortality technique for a Korean larch( Larix olgensis ) plantations in northeast China

Korean larch(Larix olgensis)is one of the main tree species for aff orestation and timber production in northeast China.However,its timber quality and growth ability are largely infl uenced by crown size,structure and shape.The majority of crown models are static models based on tree size and stand characteristics from temporary sample plots,but crown dynamic models has seldom been constructed.Therefore,this study aimed to develop height to crown base(HCB)and crown length(CL)dynamic models using the branch mortality technique for a Korean larch plantation.The nonlinear mixed-eff ects model with random eff ects,variance functions and correlation structures,was used to build HCB and CL dynamic models.The data were obtained from 95 sample trees of 19 plots in Meng JiaGang forest farm in Northeast China.The results showed that HCB progressively increases as tree age,tree height growth(HT growth)and diameter at breast height growth(DBH growth).The CL was increased with tree age in 20 years ago,and subsequently stabilized.HT growth,DBH growth stand basal area(BAS)and crown competition factor(CCF)signifi cantly infl uenced HCB and CL.The HCB was positively correlated with BAS,HT growth and DBH growth,but negatively correlated with CCF.The CL was positively correlated with BAS and CCF,but negatively correlated with DBH growth.Model fi tting and validation confi rmed that the mixed-eff ects model considering the stand and tree level random eff ects was accurate and reliable for predicting the HCB and CL dynamics.However,the models involving adding variance functions and time series correlation structure could not completely remove heterogeneity and autocorrelation,and the fi tting precision of the models was reduced.Therefore,from the point of view of application,we should take care to avoid setting up over-complex models.The HCB and CL dynamic models in our study may also be incorporated into stand growth and yield model systems in China.

THEORETICAL MODEL OF EFFECTIVE STRESS COEFFICIENT FOR ROCK/SOIL-LIKE POROUS MATERIALS

Physical mechanisms and influencing factors on the effective stress coefficient for rock/soil-like porous materials are investigated, based on which equivalent connectivity index is proposed. The equivalent connectivity index, relying on the meso-scale structure of porous material and the property of liquid, denotes the connectivity of pores in Representative Element Area （REA）. If the conductivity of the porous material is anisotropic, the equivalent connectivity index is a second order tensor. Based on the basic theories of continuous mechanics and tensor analysis, relationship between area porosity and volumetric porosity of porous materials is deduced. Then a generalized expression, describing the relation between effective stress coefficient tensor and equivalent connectivity tensor of pores, is proposed, and the expression can be applied to isotropic media and also to anisotropic materials. Furthermore, evolution of porosity and equivalent connectivity index of the pore are studied in the strain space, and the method to determine the corresponding functions in expressions above is proposed using genetic algorithm and genetic programming. Two applications show that the results obtained by the method in this paper perfectly agree with the test data. This paper provides an important theoretical support to the coupled hydro-mechanical research.