The Towne-Heuer reading passage—A reliable aid to the evaluation of voice

The science of voice evaluation and assessment has profited from technological advancement and objective measurement of voice parameters has become an integral part of the voice examination, however, subjective voice evaluation remains a vital component of any voice examination. The Towne-Heuer Reading Passage was developed in 1970 to provide a reading sample that would facilitate subjective voice evaluation. The reliability of the passage was established using three judges listening to 15 normal Philadelphia speakers and 15 vocal abuse-misuse clients with verified vocal nodules. The frequency of hard glottal attack (HGA) was determined for the two groups and high interjudge and intrajudge correlation was found. A difference in the frequency of HGA was found between the two groups.     

Nanostructured lipid carriers for triamcinolone acetonide delivery to the posterior segment of the eye

Triamcinolone acetonide (TA) is a corticosteroid drug currently administered by intravitreal injection for a broad spectrum of inflammatory, edematous and angiogenic ocular diseases. To increase the drug's bioavailability by ocular instillation, TA was encapsulated in nanostructured lipid carriers (NLC), previously optimized by our group using a factorial design approach. In the present paper, nanometric (∼200 nm), unimodal and negatively charged NLC loaded with the fluorescent lipid marker Nile red (NR-NLC) and drug (TA-NLC) were produced by high pressure homogenization. Based on the selected formulations, in vivo tests were carried out by eye-drop instillation of NR-NLC in mice, revealing the systems’ ability of delivering lipophilic actives to the posterior segment of the eye via the corneal and non-corneal pathways. Short and long-term stability of TA-NLC was assessed by high performance stability analysis using the Turbiscan^®. The results showed a backscattering of less than 1.5% and during a period of 6 months, anticipated the low tendency of these particles for aggregation during shelf life when stored at room temperature.     

Consistency of spike and slab regression

Spike and slab models are a popular and attractive variable selection approach in regression settings. Applications for these models have blossomed over the last decade and they are increasingly being used in challenging problems. At the same time, theory for spike and slab models has not kept pace with the applications. There are many gaps in what we know about their theoretical properties. An important property known to hold in these models is selective shrinkage: a unique property whereby the posterior mean is shrunk toward zero for non-informative variables only. This property has been shown to hold under orthogonality for continuous priors under the modified class of rescaled spike and slab models. In this paper, we extend this result to the general case and prove an oracle property for the posterior mean under a discrete two-component prior. An immediate consequence is that a strong selective shrinkage property holds. Interestingly, the conditions needed for our result to hold in the non-orthogonal setting are more stringent than in the orthogonal case and amount to a type of enforced sparsity condition that must be met by the prior.     

A posterior preference articulation approach to multiresponse surface optimization

In multiresponse surface optimization (MRSO), responses are often in conflict. To obtain a satisfactory compromise, the preference information of a decision maker (DM) on the tradeoffs among the responses should be incorporated into the problem. In most existing work, the DM expresses a subjective judgment on the responses through a preference parameter before the problem-solving process, after which a single solution is obtained. In this study, we propose a posterior preference articulation approach to MRSO. The approach initially finds a set of nondominated solutions without the DM’s preference information, and then allows the DM to select the best solution from among the nondominated solutions. An interactive selection method based on pairwise comparisons made by the DM is adopted in our method to facilitate the DM’s selection process. The proposed method does not require that the preference information be specified in advance. It is easy and effective in that a satisfactory compromise can be obtained through a series of pairwise comparisons, regardless of the type of the DM’s utility function.     

Skew normal measurement error models

In this paper we define a class of skew normal measurement error models, extending usual symmetric normal models in order to avoid data transformation. The likelihood function of the observed data is obtained, which can be maximized by using existing statistical software. Inference on the parameters of interest can be approached by using the observed information matrix, which can also be computed by using existing statistical software, such as the Ox program. Bayesian inference is also discussed for the family of asymmetric models in terms of invariance with respect to the symmetric normal distribution showing that early results obtained for the normal distribution also holds for the asymmetric family. Results of a simulation study and an analysis of a real data set analysis are provided.     

重力坝坝基沿软弱结构面滑动失稳的非线性机制

对于存在单组软弱结构面的坝基深层抗滑问题,考虑了坝基软弱结构面介质在不同环境因素条件下的复杂弹脆性(应变硬化)和应变软化属性,用突变论建立了坝基沿单软弱结构面滑动的尖点突变模型。通过建立的模型分析,发现坝基滑动失稳主要取决于软弱面上复杂弹脆性介质和应变软化介质在应变软化拐点处的刚度比k、材料的均匀性指标m及几何—力学参数ξ;并给出了发生突变失稳的充分力学判据,指出传统的刚体极限平衡分析法存在一定的缺陷。指出库水水位上升还存在一种降低介质材料刚度比k的新机制,从理论上阐明,坝基滑动突变失稳的发生相应于水位峰值,在时间上可能具有滞后性;而工程处理措施的实施除提高坝基软弱结构面抗滑能力外,还具有一种增大材料刚度比k的新效应,使得滑动失稳更不易发生。     

Numerical Aspects in Estimating the Parameters of a Mixture of Normal Distributions

Abstract

Mixtures of normal distributions arise naturally in robustness analyses when distributional assumptions are not met and with the analysis of contaminated data. Typically these analyses involve substantial computational problems. We present some simulation procedures that address these difficulties.     

Changing statistical significance with the amount of information: The adaptive α significance level

We put forward an adaptive alpha which changes with the amount of sample information. This calibration may be interpreted as a Bayes–non-Bayes compromise, and leads to statistical consistency. The calibration can also be used to produce confidence intervals whose size takes in consideration the amount of observed information.