AN EFFICIENT SEQUENTIAL DESIGN FOR SENSITIVITY EXPERIMENTS

In sensitivity experiments, the response is binary and each experimental unit has a critical stimulus level that cannot be observed directly. It is often of interest to estimate extreme quantiles of the distribution of these critical stimulus levels over the tested products. For this purpose a new sequential scheme is proposed with some commonly used models. By using the bootstrap repeated-sampling principle, reasonable prior distributions based on a historic data set are specified. Then, a Bayesian strategy for the sequential procedure is provided and the estimator is given. Further, a high order approximation for such an estimator is explored and its consistency is proven. A simulation study shows that the proposed method gives superior performances over the existing methods.

Utility of Adaptive Sample Size Designs and A Review Example

Sample size can be a key design feature that not only affects the probability of a trial＇s success but also determines the duration and feasibility of a trial. If an investigational drug is expected to be effective and address unmet medical needs of an orphan disease, where the accrual period may require many years with a large sample size to detect a minimal clinically relevant treatment effect, a minimum sample size may be set to maintain nominal power. In limited situations such as this, there may be a need for flexibility in the initial and final sample sizes; thus, it is useful to consider the utility of adaptive sample size designs that use sample size re-estimation or group sequential design. In this paper, we propose a new adaptive performance measure to consider the utility of an adaptive sample size design in a trial simulation. Considering that previously proposed sample size re-estimation methods do not take into account errors in estimation based on interim results, we propose Bayesian sample size re-estimation criteria that take into account prior information on treatment effect, and then, we assess its operating characteristics in a simulation study. We also present a review example of sample size re-estimation mainly based on published paper and review report in Pharmaceuticals and Medical Devices Agency （PMDA）.

Sequential good lattice point sets for computer experiments

Sequential Latin hypercube designs(SLHDs) have recently received great attention for computer experiments, with much of the research restricted to invariant spaces. The related systematic construction methods are inflexible, and algorithmic methods are ineffective for large designs. For designs in contracting spaces, systematic construction methods have not been investigated yet. This paper proposes a new method for constructing SLHDs via good lattice point sets in various experimental spaces. These designs are called sequential good lattice point(SGLP) sets. Moreover, we provide efficient approaches for identifying the(nearly)optimal SGLP sets under a given criterion. Combining the linear level permutation technique, we obtain a class of asymptotically optimal SLHDs in invariant spaces, where the L1-distance in each stage is either optimal or asymptotically optimal. Numerical results demonstrate that the SGLP set has a better space-filling property than the existing SLHDs in invariant spaces. It is also shown that SGLP sets have less computational complexity and more adaptability.

SEQUENTIAL EMPIRICAL BAYESIAN DESIGN FOR SENSITIVITY EXPERIMENTS

Maximum likelihood recursions were used by Wu （1985） to estimate extreme quantiles of a quantal response curve. For certain choices of initial designs, Wu＇s method performs well. In many fields of application, there often exist some different initial designs which are known as the up-and- down designs. Based on the existing data set from such a design, the authors propose three sequential empirical Bayesian designs by quickly and efficiently exploiting the information in the testing data and known knowledge. The improvement obtained by using the new procedures for the estimation of extreme quantiles is substantial.

Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization

For an expensive to evaluate computer simulator, even the estimate of the overall surface can be a challenging problem. In this paper, we focus on the estimation of the inverse solution, i.e., to find the set(s) of input combinations of the simulator that generates a pre-determined simulator output. Ranjan et al. [1] proposed an expected improvement criterion under a sequential design framework for the inverse problem with a scalar valued simulator. In this paper, we focus on the inverse problem for a time-series valued simulator. We have used a few simulated and two real examples for performance comparison.

An adaptive sequential experiment design method for model validation

Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space.Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model.In this paper,an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed.The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points.To avoid the clustering of samples in the local region,an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation.Besides,the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design.Finally,six benchmark problems and an engineering case are applied to examine the performance of the proposed method.The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.

Diabetic macular edema in proliferative stage treated with anti-vascular endothelial growth factor agent and triamcinolone acetonide by laser-based strategies

AIM： To appraise the effect of treatment for diabetic macular edema（DME） in proliferative stage with sufficient panrentinal photocoagulation（PRP） therapy and intravitreal injections（IV） Conbercept and posterior subtenon＇s triamcinolone acetonide（STTA） sequential therapy.METHODS： This prospective clinical randomized controlled trial of cross-over design was conducted in three phases. The participants included cases of DME in proliferative stage. They were divided into two groups and treated with PRP before enrollment. Group A were treated with IVConbercept 0.5 mg for one month in the 1^st phase. Group B were treated with STTA 40 mg（twice per two weeks）. The interventions were exchanged in the second phase（2mo） between the two groups. In the third phase（3-6mo） no other treatment was given. Best corrected visual acuity（BCVA）, central macular thickness（CMT） measured by OCT and complications were compared.RESULTS： After phase I： in Group A, BCVA improved from 0.201±0.17 to 0.37±0.24（F=5.88, P=0.004）. CMT changed from 449±155.10 to 304.1±84.70 μm（F=14.9, P〈0.01）. In Group B, BCVA changed from 0.195±0.19 to 0.26±0.20（F=0.76, P=0.41） while CMT changed from 463.82±152.92 to 366.00±115.40 μm（F=3.70, P〈0.03）. The improvement of BCVA was better in Group A（P〈0.05）. After phase II： in Group A, BCVA raised to 0.47±0.27（F=0.26, P〈0.01）, CMT reduced to 260.67±62.97 μm（F=-188.3, P〈0.01）; in Group B, BCVA raised to 0.51±0.26（F=0.31, P〈0.01）, CMT reduced to 261.93±50.15 μm（F=-201.9, P〈0.01）. But there were no difference between two groups（P〉0.05）. After phase III： in Group A, BCVA maintained 0.42±0.25（F=0.22, P=0.001）, CMT maintained 267.8±58.34 μm,（F=-0.27, P〈0.01）; in Group B, BCVA was 0.47±0.25（F=-0.27, P〈0.01）, CMT was 272.71±49.16 μm（F=-191.1, P〈0.01）. No serious complications happened in all phases.CONCLUSION： PRP＋Conbercept is better than PRP＋STTA in DME with proliferative stage but PRP＋Conbercept＋STTA sequential therapy may be a wiser choice for persistent effectiveness on anatomical as well as functional status.

Development and psychometric evaluation of the nurse behavior toward confirmed and suspected HIV/AIDS patients (NB-CSHAP) scale

There is a scarcity of literature discussing nurses’ behaviors toward caring for suspected or confirmed human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) patients. The development of a scale specific to measure nurses’ behaviors will allow health institutions to assess the disposition of their nurses in terms of HIV care. This study aims to present the rigors of developing and validating a reliable instrument to contextualize these nurses’ behaviors. This study utilized a sequential exploratory mixed method design to develop the NB-CSHAP scale. Thematic analysis was done on the qualitative data from the interviews with persons living with HIV/AIDS (PLHA) from which items were selected to be included in the scale. Exploratory factor analysis was utilized to extract the factors and Cronbach’s alpha was used to assess the reliability of the instrument. Four factors were extracted and are categorized as either caring or discriminatory behaviors. These include: (1) service-oriented, (2) openhanded, (3) perceptive, and (4) discriminatory. The scale has an internal consistency of 0.73. The scale shows acceptable psychometric properties, hence can be used to assess the nurses’ behaviors in caring for confirmed or suspected HIV clients. The scale may be used by health institutions to determine the quality of the patient care provided by their nurses to clients with confirmed or suspected HIV .

Coordinated Design and Application of Robust Damping Controllers for Shunt FACTS Devices to Enhance Small-signal Stability of Large-scale Power Systems

This paper presents a robust and coordinated supplementary damping controller design of multiple reactive FACTS controllers and their application in a large-scale power system.Reactive FACTS devices,such as static synchronous compensators(STATCOM)and static VAR compensators(SVC),are considered and assessed for their damping controller design.Control objectives,including regional pole placement and norm bounded mix sensitivities,are used to solve the bilinear matrix inequality(BMI)problems in each linearized model via a two-step method.Multiple damping controllers are sequentially designed to avoid coupling effect among the input signals and increase the reliability of the proposed design.A 5-area 16-machine 68-bus power system is used for the implementation of the damping controllers.Numerical linear analysis and real-time simulations in a test platform based on Real-time digital simulators(RTDS)are adopted to test the feasibility and robustness of the coordinated damping controllers.

LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS

In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.

Efficient Robbins–Monro procedure for multivariate binary data

This paper considers the problem of jointly estimating marginal quantiles of a multivariatedistribution.A sufficient condition for an estimator that converges in probability under a multivariate version of Robbins–Monro procedure is provided.We propose an efficient procedurewhich incorporates the correlation structure of the multivariate distribution to improve the estimation especially for cases involving extreme marginal quantiles.Estimation efficiency of theproposed method is demonstrated by simulation in comparison with a general multivariate Robbins–Monro procedure and an efficient Robbins–Monro procedure that estimates the marginalquantiles separately.

Rotorcraft flight endurance estimation based on a new battery discharge model

To avoid the numerical complexities of the battery discharge law of electric-powered rotorcrafts,this study uses the Kriging method to model the discharge characteristics of Li-Po batteries under standard conditions.A linear current compensation term and an ambient temperature compensation term based on radial basis functions are then applied to the trained Kriging model,leading to the complete discharged capacity-terminal voltage model.Using an orthogonal experimental design and a sequential method,the coefficients of the current and ambient temperature compensation terms are determined through robust optimization.An endurance calculation model for electric-powered rotorcrafts is then established,based on the battery discharge model,through numerical integration.Laboratory tests show that the maximum relative error of the proposed discharged capacity-terminal voltage model at detection points is 0.0086,and that of the rotorcraft endurance calculation model is 0.0195,thus verifying their accuracy.A flight test further demonstrates the applicability of the proposed endurance model to general electric-powered rotorcrafts.

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