Accident prediction models with random corridor parameters

Recent research advocates the use of count models with random parameters as an alternative method for analyzing accident frequencies. In this paper a dataset composed of urban arterials in Vancouver, British Columbia, is considered where the 392 segments were clustered into 58 corridors. The main objective is to assess the corridor effects with alternate specifications. The proposed models were estimated in a Full Bayes context via Markov Chain Monte Carlo (MCMC) simulation and were compared in terms of their goodness of fit and inference. A variety of covariates were found to significantly influence accident frequencies. However, these covariates resulted in random parameters and thereby their effects on accident frequency were found to vary significantly across corridors. Further, a Poisson-lognormal (PLN) model with random parameters for each corridor provided the best fit. Apart from the improvement in goodness of fit, such an approach is useful in gaining new insights into how accident frequencies are influenced by the covariates, and in accounting for heterogeneity due to unobserved road geometrics, traffic characteristics, environmental factors and driver behavior. The inclusion of corridor effects in the mean function could also explain enough variation that some of the model covariates would be rendered non-significant and thereby affecting model inference.     

Global stability of infection‐free state and endemic infection state of a modified human immunodeficiency virus infection model

This study proposes a modified human immunodeficiency virus (HIV) infection differential equation model with a saturated infection rate. This model has an infection‐free equilibrium point and an endemic infection equilibrium point. Using Lyapunov functions and LaSalle’s invariance principle shows that if the model’s basic reproductive number R ₀ < 1, the infection‐free equilibrium point is globally asymptotically stable, otherwise the endemic infection equilibrium point is globally asymptotically stable. It is shown that a forward bifurcation will occur when R ₀ = 1. The basic reproductive number R ₀ of the modified model is independent of plasma total CD4⁺ T cell counts and thus the modified model is more reasonable than the original model proposed by Buonomo and Vargas‐De‐León. Based on the clinical data from HIV drug resistance database of Stanford University, using the proposed model simulates the dynamics of two group patients’ anti‐HIV infection treatments. The simulation results have shown that the first 4 weeks’ treatments made the two group patients’ R′ ₀ < 1, respectively. After the period, drug resistance made the two group patients’ R′ ₀ > 1. The results explain why the two group patients’ mean CD4⁺ T cell counts raised and mean HIV RNA levels declined in the first period, but contrary in the following weeks.Inspec keywords: microorganisms, cellular biophysics, differential equations, Lyapunov methods, blood, drugs, patient treatment, RNAOther keywords: global stability, infection‐free state, endemic infection state, modified human immunodeficiency virus infection model, HIV, differential equation model, saturated infection rate, infection‐free equilibrium point, endemic infection equilibrium point, Lyapunov functions, LaSalle invariance principle, forward bifurcation, plasma total CD4⁺ T cell counts, HIV drug resistance database, mean HIV RNA levels     

Investigating different approaches to develop informative priors in hierarchical Bayesian safety performance functions

The Bayesian inference method has been frequently adopted to develop safety performance functions. One advantage of the Bayesian inference is that prior information for the independent variables can be included in the inference procedures. However, there are few studies that discussed how to formulate informative priors for the independent variables and evaluated the effects of incorporating informative priors in developing safety performance functions. This paper addresses this deficiency by introducing four approaches of developing informative priors for the independent variables based on historical data and expert experience. Merits of these informative priors have been tested along with two types of Bayesian hierarchical models (Poisson-gamma and Poisson-lognormal models). Deviance information criterion (DIC), R-square values, and coefficients of variance for the estimations were utilized as evaluation measures to select the best model(s). Comparison across the models indicated that the Poisson-gamma model is superior with a better model fit and it is much more robust with the informative priors. Moreover, the two-stage Bayesian updating informative priors provided the best goodness-of-fit and coefficient estimation accuracies. Furthermore, informative priors for the inverse dispersion parameter have also been introduced and tested. Different types of informative priors’ effects on the model estimations and goodness-of-fit have been compared and concluded. Finally, based on the results, recommendations for future research topics and study applications have been made.     

P-splines quantile regression estimation in varying coefficient models

Quantile regression, as a generalization of median regression, has been widely used in statistical modeling. To allow for analyzing complex data situations, several flexible regression models have been introduced. Among these are the varying coefficient models, that differ from a classical linear regression model by the fact that the regression coefficients are no longer constant but functions that vary with the value taken by another variable, such as for example, time. In this paper, we study quantile regression in varying coefficient models for longitudinal data. The quantile function is modeled as a function of the covariates and the main task is to estimate the unknown regression coefficient functions. We approximate each coefficient function by means of P-splines. Theoretical properties of the estimators, such as rate of convergence and an asymptotic distribution are established. The estimation methodology requests solving an optimization problem that also involves a smoothing parameter. For a special case the optimization problem can be transformed into a linear programming problem for which then a Frisch–Newton interior point method is used, leading to a computationally fast and efficient procedure. Several data-driven choices of the smoothing parameters are briefly discussed, and their performances are illustrated in a simulation study. Some real data analysis demonstrates the use of the developed method.     

Robust control of HIV infection by antiretroviral therapy: a super‐twisting sliding mode control approach

Acquired immune deficiency syndrome is an epidemic infectious disease which is caused by the human immunodeficiency virus (HIV) and that has proliferated across worldwide. It has been a matter of concern for the scientific community to develop an antiretroviral therapy, which will prompt a rapid decline in viral abundance. With this motivation, this study proposes the design of a robust super twisting sliding mode controller based on output information for an uncertain HIV infection model. The control objective is to decrease the concentration of infected CD4+ T cells to a specified level by drug administration using only the output information of the uncertain HIV infection model which is total CD4+ T cell concentration. The robust output‐feedback controller has been developed in combination with a robust exact differentiator, functioning as an observer. The reported analysis demonstrates that the approach proposed here is capable of ensuring robust performance under several operating conditions, measurement and modelling error, parametric uncertainties and external disturbances and the simulation results prove the proficiency of the controller proposed.Inspec keywords: control system synthesis, observers, robust control, drugs, medical control systems, diseases, uncertain systems, variable structure systems, patient treatment, feedback, cellular biophysics, microorganismsOther keywords: robust control, antiretroviral therapy, sliding mode control approach, acquired immune deficiency syndrome, epidemic infectious disease, human immunodeficiency virus, scientific community, robust super, mode controller, output information, uncertain HIV infection model, control objective, infected CD4, total CD4, T cell concentration, robust output‐feedback controller, robust exact differentiator, robust performance     

Discussion: Fuzzy Thinking

This article investigates computation of pointwise and simultaneous tolerance limits under the logistic regression model for binary data. The data consist of n binary responses, where the probability of a positive response depends on covariates via the logistic regression function. Upper tolerance limits are constructed for the number of positive responses in m future trials for fixed as well as varying levels of the covariates. The former provides pointwise upper tolerance limits, and the latter provides simultaneous upper tolerance limits. The upper tolerance limits are obtained from upper confidence limits for the probability of a positive response, modeled using the logistic function. To compute pointwise upper confidence limits for the logistic function, likelihood-based asymptotic methods, small sample asymptotics, as well as bootstrap methods are investigated and numerically compared. To compute simultaneous upper tolerance limits, a bootstrap approach is investigated. The problems have been motivated by an application of interest to the U.S. Army, dealing with the testing of ballistic armor plates for protecting soldiers from projectiles and shrapnel, where the success probability depends on covariates such as the projectile velocity, size of the armor plate, etc. Such an application is used to illustrate the tolerance interval computations in the article. We provide the R codes used for the calculations presented in the examples in the article as supplementary material, available online.     

Modelling the influence of activation-induced apoptosis of CD4+ and CD8+ T-cells on the immune system response of a HIV-infected patient.

On the basis of the human immunodeficiency virus (HIV) infection dynamics model proposed by Adams, the authors propose an extended model that aims at incorporating the influence of activation-induced apoptosis of CD4+ and CD8+ T-cells on the immune system response of HIV-infected patients. Through this model, the authors study the influence of this phenomenon on the time evolution of specific cell populations such as plasma concentrations of HIV copies, or blood concentrations of CD4+ and CD8+ T-cells. In particular, this study shows that depending on its intensity, the apoptosis phenomenon can either favour or mitigate the long-term evolution of the HIV infection.     

Microinflammation in hemodialysis is related to a preactivated subset of monocytes

Increased percentage of monocytes with low CD14 expression and that co-express CD16 (CD14+/CD16+) have been reported in hemodialysis (HD) patients. We sought to determine whether CD14+/CD16+ monocytes in HD therapy are sensibilized cells to a proinflammatory activity. Cells from 32 HD patients, and from 9 Systemic Lupus Erythematosus (SLE), 9 individuals with human immunodeficiency virus (HIV)-1- and 15 healthy controls were studied. Cells were analyzed by means of flow cytometry for CD14/CD16 expression and immune function (cytokine, chemokines, and sialoadhesin expression), and phagocytosis. Increased percentage of CD14+/CD16+ monocytes was observed in HD patients. Compared with CD14++ monocytes, the CD14+/CD16+ monocytes exhibited increased expression of proinflammatory cytokines and markers of differentiated cells. In addition, these monocytes showed an increased phagocytic activity. Similarly, CD14+/CD16+ monocytes from SLE and HIV patients showed increased inflammatory activity as compared with CD14++ cells. These results support that CD14+/CD16+ monocytes from HD patients evidence characteristics of primed prestimulated proinflammatory cells, similar to data observed in SLE and HIV.     

Adaptive neuro-fuzzy inference system multi-objective optimization using the genetic algorithm/singular value decomposition method for modelling the discharge coefficient in rectangular sharp-crested side weirs

In the present article, the adaptive neuro-fuzzy inference system (ANFIS) is employed to model the discharge coefficient in rectangular sharp-crested side weirs. The genetic algorithm (GA) is used for the optimum selection of membership functions, while the singular value decomposition (SVD) method helps in computing the linear parameters of the ANFIS results section (GA/SVD-ANFIS). The effect of each dimensionless parameter on discharge coefficient prediction is examined in five different models to conduct sensitivity analysis by applying the above-mentioned dimensionless parameters. Two different sets of experimental data are utilized to examine the models and obtain the best model. The study results indicate that the model designed through GA/SVD-ANFIS predicts the discharge coefficient with a good level of accuracy (mean absolute percentage error?=?3.362 and root mean square error?=?0.027). Moreover, comparing this method with existing equations and the multi-layer perceptron–artificial neural network (MLP-ANN) indicates that the GA/SVD-ANFIS method has superior performance in simulating the discharge coefficient of side weirs.     

Shape testing in varying coefficient models

We consider varying coefficient models which are an extension of the classical linear regression models in the sense that the regression coefficients are replaced by functions in certain variables (often time). Varying coefficient models have been popular in longitudinal data and panel data studies, and have been applied in fields, such as finance and health sciences. We estimate the coefficient functions by splines. An important question in a varying coefficient model is whether a coefficient function is monotone or convex. We develop consistent testing procedures for monotonicity and convexity. Moreover, we provide procedures to test simultaneously the shapes of certain coefficient functions in a varying coefficient model. The tests use constrained and unconstrained regression splines. The performances of the proposed tests are illustrated on simulated data. We also give a real data application.     

Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection

In spite of widespread use of generalized additive models (GAMs) to remedy the “curse of dimensionality”, there is no well-grounded methodology developed for simultaneous inference and variable selection for GAM in existing literature. However, both are essential in enhancing the capability of statistical models. To this end, we establish simultaneous confidence corridors (SCCs) and a type of Bayesian information criterion (BIC) through the spline-backfitted kernel smoothing techniques proposed in recent articles. To characterize the global features of each non-parametric components, SCCs are constructed for testing their overall trends and entire shapes. By extending the BIC in additive models with identity/trivial link, an asymptotically consistent BIC approach for variable selection is built up in GAM to improve the parsimony of model without loss of prediction accuracy. Simulations and a real example corroborate the above findings.     

Stress analysis and material tailoring in isotropic linear thermoelastic incompressible functionally graded rotating disks of variable thickness

We analyze axisymmetric deformations of a rotating disk with its thickness, mass density, thermal expansion coefficient and shear modulus varying in the radial direction. The disk is made of a rubberlike material that is modeled as isotropic, linear thermoelastic and incompressible. We note that the hydrostatic pressure in the constitutive relation of the material is to be determined as a part of the solution of the problem since it cannot be determined from the strain field. The problem is analyzed by using an Airy stress function φ. The non-homogeneous ordinary differential equation with variable coefficients for φ is solved either analytically or numerically by the differential quadrature method. We have also analyzed the challenging problem of tailoring the variation of either the shear modulus or the thermal expansion coefficient in the radial direction so that a linear combination of the hoop stress and the radial stress is constant in the disk. For a rotating annular disk we present the explicit expression of the thermal expansion coefficient for the hoop stress to be uniform within the disk. For a rotating solid disk we give the exact expressions for the shear modulus and the thermal expansion coefficient as functions of the radial coordinate so as to achieve constant hoop stress. Numerical results for a few typical problems are presented to illuminate effects of material inhomogeneities on deformations of a hollow and a solid rotating disk.     

The electrical properties of resistive and dielectric thin films prepared by reactive sputtering from a tantalum-titanium composite target

Resistive thin films of TaTiN and dielectric thin films of TaTiO prepared by reactive co-sputtering in ArN₂ or ArO₂ mixtures from a TaTi composite target were investigated in an effort to extend the data on the electrical properties of films prepared by reactive sputtering from tantalum targets. The composition of the thin films was controlled by changing the ratio of the tantalum area to the titanium area on the composite target surface.For the TaTiN films the resistivity, the temperature coefficient of resistance and the Hall coefficient were investigated as functions of the nitrogen partial pressure and the composition of the films.The dielectric constant, the temperature coefficient of capacitance and tan δ were studied as functions of composition in films of the TaTiO system.The resistivities of TaTiN films sputtered at a nitrogen partial pressure of 4 × 10^?4 Torr varied linearly from 50 to 270 μω cm as the tantalum weight percentage of the films increased from 10 to 90%. The temperature coefficient of resistance for these films decreased, again linearly, from 1000 to ?50 ppm °C^?1 over the same range of tantalum weight percentage.As the titanium weight percentage of the films increased from 10 to 90%, the dielectric constant and tan δ for the TaTiO films varied linearly from 30 to 70 and from 0.008 to 0.025 respectively.It is believed that these resistive and dielectric thin films will be valuable for producing thin film passive elements in hybrid integrated circuits.     

R.F. reactive sputter deposition of hydrogenated amorphous silicon carbide films

The preparation of hydrogenated amorphous silicon carbide films by r.f. reactive sputtering of a silicon target in Ar-CH₄ gas mixtures with and without an r.f. bias on the substrates was studied. Starting with a pure silicon target and increasing monotonically the CH₄ percentage from 0% to about 10%, films with 1 ⩾ x ⩾ 0 were obtained at decreasing deposition rates. After sputtering for some hours in methane-rich gas mixtures, carbon atoms were incorporated into the silicon target surface, probably as a result of atomic peening, and nearly stoichiometric SiC films were prepared by sputtering of such a target in pure argon. The different mechanisms of film formation, deposition rate, composition, hardness, friction coefficient and stresses in the films as functions of the partial pressure of methane and the value of the r.f. bias were investigated. The IR spectra offilms with different carbon contents were analysed. The greatest hardness was found for nearly stoichiometric SiC films deposited with a bias.     

On modeling the abrasive wear characteristics of in situ Al–12%Si/TiC composites

In this work the abrasive wear characteristics of in situ synthesized Al–12%Si/TiC composites were investigated based on the plan of full factorial design. During the experiment applied load, sliding distance and weight percentage of reinforcement considered as input variables and weight loss and coefficient of friction as responses. The experimental results revealed that the sliding distance and weight percentage of TiC had relatively higher influence on coefficient of friction. On the other hand, the applied load had relatively higher influence on the weight loss. The developed regression equations for predicting the weight loss and coefficient of friction were validated with a number of test cases and it has been observed that the percentage error for both responses is less than ± 10%. It indicates that there is a close agreement between the predicted and measured results. Multi-response optimization technique was also employed to optimize the control factors.     

Switching control strategy for the HIV dynamic system with some unknown parameters

In human immunodeficiency virus (HIV) infection, many factors may influence the counts of healthy cells, immune cells and viruses. Drug treatment design for the HIV dynamic system is a valuable subject to be studied. This study considers an HIV dynamic system model with some unknown parameters and unmeasurable CD8 + T cell count and proposes a switching control strategy to force all states of the system to achieve a healthy status. It is a switching form with two different drug therapies and is designed based on the Lyapunov function theory such that the states of the HIV system approach the health equilibrium asymptotically without the influence of unknown parameters and unmeasurable cell counts. The values of all states and drug concentrations are assured to be positive in the control process so that the control strategy can satisfy the actual treatment requirements. Finally, a numerical example is illustrated to show the effectiveness of the proposed control strategy.Inspec keywords: medical control systems, diseases, microorganisms, cellular biophysics, drugs, patient treatment, Lyapunov methods, switching systems (control)Other keywords: control process, switching control strategy, human immunodeficiency virus infection, healthy cells, immune cells, viruses, drug treatment design, HIV dynamic system model, unmeasurable CD8 + T cell count, switching form, drug therapies, Lyapunov function theory     

Seebeck coefficient and electrical conductivity in the system TiO2VO2

The Seebeck coefficient and the electrical conductivity have been measured as functions of temperature in several compositions within the pseudobinary system TiO₂VO₂. It is found that the Seebeck coefficient is small and varying slowly with temperature while the dependence on temperature of the electrical conductivity is characterized by an activation energy with the value 0.24 eV.     

Construction of upper confidence limit of coefficient of variation for content uniformity

Relative standard deviation (coefficient of variation) plays an important role in meeting the current compendial requirements for content uniformity. Since the sample RSD value would vary from sample to sample in a population (batch), the scientist would need not only the sample estimate of the RSD but also its 95% two-sided upper confidence limit, for making the proper statistical inference as well as for arriving at the appropriate pharmaceutics decisions. The primary purpose of this paper is to depict the five available methods for determining the confidence limit and to discuss their relative merits and similarities in the context of a content uniformity study associated with Product-C. Suitable tables are furnished to facilitate rapid access to the desired RSD confidence limit.     

Prediction of the containment of HIV infection by antiretroviral therapy – a variable structure control approach

It is demonstrated that the reachability paradigm from variable structure control theory is a suitable framework to monitor and predict the progression of the human immunodeficiency virus (HIV) infection following initiation of antiretroviral therapy (ART). A manifold is selected which characterises the infection‐free steady‐state. A model of HIV infection together with an associated reachability analysis is used to formulate a dynamical condition for the containment of HIV infection on the manifold. This condition is tested using data from two different HIV clinical trials which contain measurements of the CD4+ T cell count and HIV load in the peripheral blood collected from HIV infected individuals for the six month period following initiation of ART. The biological rates of the model are estimated using the multi‐point identification method and data points collected in the initial period of the trial. Using the parameter estimates and the numerical solutions of the model, the predictions of the reachability analysis are shown to be consistent with the clinical diagnosis at the conclusion of the trial. The methodology captures the dynamical characteristics of eventual successful, failed and marginal outcomes. The findings evidence that the reachability analysis is an appropriate tool to monitor and develop personalised antiretroviral treatment.Inspec keywords: microorganisms, patient treatment, drugs, parameter estimationOther keywords: HIV infection, antiretroviral therapy, variable structure control theory, human immunodeficiency virus, antiretroviral drugs, multipoint identification method, parameter estimation, reachability analysis     

Distinct Immune Signatures in Peripheral Blood Predict Chemosensitivity in Intrahepatic Cholangiocarcinoma Patients

Intrahepatic cholangiocarcinoma (ICC) is the second most common liver cancer. Chemotherapy remains the main therapeutic strategy for advanced ICC patients, but chemosensitivity varies individually. Here, we applied cytometry by time-of-flight (CyTOF) to establish the immune profile of peripheral blood mononuclear cells (PBMCs) on the single-cell level at indicated time points before, during, and after chemotherapy. Multiplex immunofluorescence staining was applied to examine the spatial distribution of certain immune clusters. Tissue microarrays (TMAs) were used for prognostic evaluation. A total of 20 ICC patients treated with gemcitabine (GEM) were enrolled in our study, including eight cases with good response (R) and 12 cases with non-response (NR). Tremendous changes in PBMC composition, including an increased level of CD4/CD8 double-positive T cells (DPT), were observed after chemotherapy. Patients with higher level of CD4⁺CD45RO⁺CXCR3⁺ T cells before treatment had a favorable response to chemotherapy. Our study identified a positive correlation between the percentage of T cell subpopulations and clinical response after chemotherapy, which suggests that it is practical to predict the potential response before treatment by evaluating the proportions of the cell population in PBMCs.