Coordinate-Parametric Matrix Model Inspired Square-Conjoint Pattern in Cross Woven for Conventional Bamboo Mat

In the study,it is proposed that a coordinate-parametric matrix model is performed to a square-conjoint pattern of cross woven(SCPCW)in the bamboo mat.The patterns of SCPCW are firstly detected according to the perspective of configuration,which is divided into the basic-monomer shape and the basic combination shape.Secondly,the compositions of design patterns in SCPCW are analyzed to attain the trend of curve shape.Based on the coordinate-parametric matrix model,the specimens of SCPCW are subsequently accomplished to elaborate the woven logic of bamboo mats.The digital innovation of SCPCW,defined by a mathematical resolution,is implemented by the software of Grasshopper(GH),which plays a crucial role in capturing image information by the Image Sampler component.Successively,the weaving logic of coordinated matrix is referred to apply in the computing component of Grasshopper software.Finally,the computer simulation could demonstrate that the coordinate-parametric matrix model of SCPCWwould be realized to analyze the micro-weaving structure and overall weaving effect in the bamboo mat.

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.

Monitoring models for base flow effect and daily variation of dam seepage elements considering time lag effect

Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine(SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam.Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution.

Level crossing in a two-photon Jaynes-Cummings model

In this paper,the energy spectrum of the two-photon Jaynes-Cummings model（TPJCM） is calculated exactly in the non-rotating wave approximation（non-RWA）,and we study the level-crossing problem by means of fidelity.A narrow peak of the fidelity is observed at the level-crossing point,which does not appear at the avoided-crossing point.Therefore fidelity is perfectly suited for detecting the level-crossing point in the energy spectrum.

Analysis of Factors Influencing Insomnia and Construction of a Prediction Model:A Cross-sectional Survey on Rescuers

Objective To determine the factors influencing insomnia and construct early insomnia warning tools for rescuers to informbest practices for early screening and intervention.Methods Cluster sampling was used to conduct a cross-sectional survey of 1,133 rescuers from one unit in Beijing,China.Logistic regression modeling and R software were used to analyze insomniarelated factors and construct a PRISM model,respectively.Results The positive rate of insomnia among rescuers was 2.74%.Accounting for participants’age,education,systolic pressure,smoking,per capita family monthly income,psychological resilience,and cognitive emotion regulation,logistic regression analysis revealed that,compared with families with an average monthly income less than 3,000 yuan,the odds ratio(OR)values and the[95%confidence interval(CI)]for participants of the following categories were as follows:average monthly family income greater than 5,000 yuan:2.998(1.307–6.879),smoking:4.124(1.954–8.706),and psychological resilience:0.960(0.933–0.988).The ROC curve area of the PRISM model(AUC)=0.7650,specificity=0.7169,and sensitivity=0.7419.Conclusion Insomnia was related to the participants’per capita family monthly income,smoking habits,and psychological resilience on rescue workers.The PRISM model’s good diagnostic value advises its use to screen rescuer early sleep quality.Further,advisable interventions to optimize sleep quality and battle effectiveness include psychological resilience training and smoking cessation.

Cellular automata modeling of pedestrian＇s crossing dynamics

Cellular automata modeling techniques and the characteristics of mixed traffic flow were used to derive the 2-dimensional model presented here for simulation of pedestrian’s crossing dynamics. A conception of “stop point” is introduced to deal with traffic obstacles and resolve conflicts among pedestrians or between pedestrians and the other vehicles on the crosswalk. The model can be easily extended, is very efficient for simulation of pedestrian’s crossing dy- namics, can be integrated into traffic simulation software, and has been proved feasible by simulation experiments.

Time lag characteristics of sap flow in seed-maize and their implications for modeling transpiration in an arid region of Northwest China

Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation（R_s） and vapor pressure deficit of the air（VPD_（air））. Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in R_s and preceded the changes in VPD_（air） both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize＇s sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and R_s in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPD_（air） in comparison with wet soil and also increase the speed by which sap flow adjusts to R_s. However, sap flow lags that were associated with R_s before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.

Assessing the host genetic background effects on type 2 diabetes and obesity development in response to mixed–oral bacteria and high-fat diet using the collaborative cross mouse model

Background: Host genetic background and sex, play central roles in defining the pathogenesis of type 2 diabetes(T2 D), obesity and infectious diseases. Our previous studies demonstrated the utilization of genetically highly diverse inbred mouse lines, namely collaborative cross(CC), for dissecting host susceptibility for the development of T2 D and obesity, showing significant variations following high-fat(42% fat) diet(HFD). Here, we aimed to assessing the host genetic background and sex effects on T2 D and obesity development in response to oral-mixed bacterial infection and HFD using the CC lines.Materials and Methods: Study cohort consists of 97 mice from 2 CC lines(both sexes), maintained on either HFD or Standard diet(CHD) for 12 weeks. At week 5 a group of mice from each diet were infected with Porphyromonas gingivalis(Pg) and Fusobacterium nucleatum(Fn) bacteria(control groups without infection). Body weight(BW) and glucose tolerance ability were assessed at the end time point of the experiment.Results: The CC lines varied(P <.05) at their BW gain and glucose tolerance ability(with sex effect) in response to diets and/or infection, showing opposite responses despite sharing the same environmental conditions. The combination of diet and infection enhances BW accumulation for IL1912, while restraints it for IL72. As for glucose tolerance ability, only females(both lines) were deteriorated in response to infection.Conclusions: This study emphasizes the power of the CC mouse population for the characterization of host genetic makeup for defining the susceptibility of the individual to development of obesity and/or impaired glucose tolerance.

An Application of the Modified Shear Lag Model to Study the Influence of Thermal Residual Stresses on the Stiffness and Yield Strength of Short Fiber Reinforced Metal Matrix Composites

The modified shear lag model proposed recently was applied to calculate thermal residual stresses and subsequent stress distributions under tensile and compressive loadings. The expressions for the elastic moduli and the yield strengths under tensile and compressive loadings were derived which take account of thermal residual stresses. The asymmetries in the elastic modulus and the yield strength were interpreted using the derived expressions and the obtained results of the stress calculations. The model predictions have exhibited good agreements with the experimental results and also with the other theoretical predictions

A Problem of a Semi-Infinite Medium Subjected to Exponential Heating Using a Dual-Phase-Lag Thermoelastic Model

The problem of a semi-infinite medium subjected to thermal shock on its plane boundary is solved in the context of the dual-phase-lag thermoelastic model. The expressions for temperature, displacement and stress are presented. The governing equations are expressed in Laplace transform domain and solved in that domain. The solution of the problem in the physical domain is obtained by using a numerical method for the inversion of the Laplace transforms based on Fourier series expansions. The numerical estimates of the displacement, temperature, stress and strain are obtained for a hypothetical material. The results obtained are presented graphically to show the effect phase-lag of the heat flux and a phase-lag of temperature gradient on displacement, temperature, stress.

Model-based cross section calculations on production of 43,34Sc,45Ti, 51Cr, 54Mn, and 55Fe radioisotopes

A cross section database on excitation functions of reactions produced by charged particles is essential for many areas of nuclear research. Particularly, accurate knowledge on nuclear cross sections for the cyclotron production of radioisotopes is very important for nuclear medicine. In the present paper, the cross section calculations for the production of^(43),^(34)Sc,^(45)Ti,^(51)Cr,^(54)Mn, and^(55) Fe radioisotopes were carried out by the use of ALICE/ASH code using the Fermi gas model, Kataria Ramamurthy Fermi gas model, and superfluid nuclear model for nuclear level density. Thereby, these model calculations were compared with the available measured data.

Validation method for simulation models with cross iteration

Cross iteration often exists in the computational process of the simulation models, especially for control models. There is a credibility defect tracing problem in the validation of models with cross iteration. In order to resolve this problem, after the problem formulation, a validation theorem on the cross iteration is proposed, and the proof of the theorem is given under the cross iteration circumstance. Meanwhile, applying the proposed theorem, the credibility calculation algorithm is provided, and the solvent of the defect tracing is explained. Further, based on the validation theorem on the cross iteration, a validation method for simulation models with the cross iteration is proposed, which is illustrated by a flowchart step by step. Finally, a validation example of a sixdegree of freedom (DOF) flight vehicle model is provided, and the validation process is performed by using the validation method. The result analysis shows that the method is effective to obtain the credibility of the model and accomplish the defect tracing of the validation.

Effects of rotation and gravity on an electro-magneto-thermoelastic medium with diffusion and voids by using the Lord-Shulman and dual-phase-lag models

The effects of rotation and gravity on an electro-magneto-thermoelastic medium with diffusion and voids in a generalized thermoplastic half-space are studied by using the Lord-Shulman (L-S) model and the dual-phase-lag (DPL) model. The analytical solutions for the displacements, stresses, temperature, diffusion concentration, and volume fraction field with different values of the magnetic field, the rotation, the gravity, and the initial stress are obtained and portrayed graphically. The results indicate that the effects of gravity, rotation, voids, diffusion, initial stress, and electromagnetic field are very pronounced on the physical properties of the material.

A New Smoothing Approach with Diverse Fixed-lags Based on Target Motion Model

Recently, lots of smoothing techniques have been presented for maneuvering target tracking. Interacting multiple model-probabilistic data association （IMM-PDA） fixed-lag smoothing algorithm provides an efficient solution to track a maneuvering target in a cluttered environment. Whereas, the smoothing lag of each model in a model set is a fixed constant in traditional algorithms. A new approach is developed in this paper. Although this method is still based on IMM-PDA approach to a state augmented system, it adopts different smoothing lag according to diverse degrees of complexity of each model. As a result, the application is more flexible and the computational load is reduced greatly. Some simulations were conducted to track a highly maneuvering target in a cluttered environment using two sensors. The results illustrate the superiority of the proposed algorithm over comparative schemes, both in accuracy of track estimation and the computational load.

Eigenvalue Modeling and Cross-Correlation Analysis for 6. 0- 6. 4 GHz MIMO Channel

In Multiple-Input Multiple-Output( MIMO) system, the number of positive channel matrix eigenvalues is directly related to system performance. In order to characterize and model channel matrix eigenvalues,channel measurements at 6. 0- 6. 4GHz by using 4 × 4 MIMO structure were conducted in a typical classroom environment. Based on measured data, the eigenvalues were modeled as Log-Normal distributed random variables and parameterized. Furthermore, Cross-Correlation( CC) coefficients of eigenvalues were estimated. The measurement results show that,under both Light-Of-Sight( LOS) and NonLight-Of-Sight( NLOS) scenarios,eigenvalues are highly de-correlated so that CC can be ignored for eigenvalue model.

A Dynamic Cross Contagion Model of Currency Crisis between Two Countries

The contagion aspect of the currency crisis is an important research issue today.In this paper, we set up a dynamic differential model of currency crisis cross contagions between two countries by expanding generalized logistics model, and analyze all kinds of possible equilibrium conditions. It is probably a new idea of studying currency crisis contagion mechanism.

Modeling Crash Risk at Rail-Highway Grade Crossings by Track Class

The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.

Modeling the Surface Cross-Contamination of <i>Salmonella</i>spp. on Ready-to-Eat Meat via Slicing Operation

Salmonella spp. surface transfer patterns/models between ready-to-eat (RTE) deli meat and a typical meat slicer are presented. A five-strain cocktail of Salmonella spp. was inoculated directly onto the rim of a round slicer blade at an initial level of ca. 4, 5, 6, 7 or 8 log CFU/blade (ca. 3, 4, 5, 6 or 7 log CFU/cm2 of the blade edge area). Thereafter, a RTE deli meat (ham) was sliced to a thickness of 1.5 - 2.0 mm. In another cross-contamination scenario, a clean blade was initially used to slice ham, which was pre-surface-inoculated with the Salmonella cocktail (ca. 2, 3, 4, 5, 6 or 7 log CFU/cm2 with a total area of 100 cm2), followed by slicing of an un-inoculated ham. The log CFU of Salmonella per ham slice was determined and empirical models were developed. The models, follow the decreasing Power law, predict the surface cross-contamination of Salmonella spp. (at any initial level) for sliced deli meat (ham) and will provide a useful tool in developing RTE meat risk assessments. Surface transfer patterns of three foodborne pathogens, i.e. Listeria monocytogenes, E. coli O157:H7 and Salmonella predicted by models are also presented.

Modeling of Continuous Cross-flow Microfiltration Process in an Airlift External-loop Slurry Reactor

New modified combination mathematical models including the pores blocking models and the cake layer models were developed to describe the continuous cross-flow microfiltration in an airlift external loop slurry reactor. The pores blocking models were created based on the standard blocking law and the intermediate blocking law, and then the cake layer models were developed based on the hydrodynamic theory in which the calculation method of porosity of cake layer was newly corrected. The Air-Water-FCC equilibrium catalysts cold model experiment was used to verify the relevant models.Results showed that the calculated values fitted well with experimental data with a relative error of less than 10%.

Spatial Pattern Induced by Cross-Diffusion in a Chemostat Model with Maintenance Energy

A chemostat model with maintenance energy and crossdiffusion is considered,and the formation of patterns is caused by the cross-diffusion. First, through linear stability analysis, the necessary conditions for the formation of the spatial patterns are given. Then numerical simulations by changing the values of crossdiffusions in the unstable domain are performed. The results showthat the cross-diffusion coefficient plays an important role in the formation of the pattern, and the different values of the crossdiffusion coefficients may lead to different types of pattern formation.