Second- and third-order bias reduction for one-parameter family models

In this paper we derive second- and third-order bias-corrected maximum likelihood estimates in general uniparametric models. We compare the corrected estimates and the usual maximum likelihood estimate in terms of their mean squared errors. We also obtain closed-form expressions for bias-corrected estimates in one-parameter exponential family models. Our results cover many important and commonly used distributions. Simulation results are also given.     

Electrochemically assisted photocatalysis on self-organized TiO2 nanotubes

In this work we investigate influence of an externally applied bias on the photocatalytic performance of self-organized TiO₂ nanotube layers. These layers were grown by anodization of titanium in fluoride containing electrolytes and have different geometric dimensions. Since the layers are grown directly on the Ti substrate, a very good electrical backside contact is directly provided. Therefore, we use the nanotube layers/Ti structures as photo-anodes for the UV light induced photocatalytic decomposition of acid orange 7. For comparison, we use TiO₂ nanopowder (Degussa P25) compacted also on a Ti sheet. The present results demonstrate that the photocatalytic activity of self-organized TiO₂ nanotube layers can significantly be increased by electrochemical bias.     

Should non-significant bias be included in the uncertainty budget?

The bias of an analytical procedure is calculated in the assessment of trueness. If this experimental bias is not significant, we assume that the procedure is unbiased and, consequently, the results obtained with this procedure are not corrected for this bias. However, when assessing trueness there is always a probability of incorrectly concluding that the experimental bias is not significant. Therefore, non-significant experimental bias should be included as a component of uncertainty. In this paper, we have studied if it is always necessary to include this term and which is the best approach to include this bias in the uncertainty budget. To answer these questions, we have used the Monte-Carlo method to simulate the assessment of trueness of biased procedures and the future results these procedures provide. The results show that non-significant experimental bias should be included as a component of uncertainty when the uncertainty of this bias represents at least a 30% of the overall uncertainty. Received: 29 May 2001 Accepted: 10 December 2001     

Correcting power and p-value calculations for bias in diffusion tensor imaging

Diffusion tensor imaging (DTI) provides quantitative parametric maps sensitive to tissue microarchitecture (e.g., fractional anisotropy, FA). These maps are estimated through computational processes and subject to random distortions including variance and bias. Traditional statistical procedures commonly used for study planning (including power analyses and p-value/alpha-rate thresholds) specifically model variability, but neglect potential impacts of bias. Herein, we quantitatively investigate the impacts of bias in DTI on hypothesis test properties (power and alpha-rate) using a two-sided hypothesis testing framework. We present theoretical evaluation of bias on hypothesis test properties, evaluate the bias estimation technique SIMEX for DTI hypothesis testing using simulated data, and evaluate the impacts of bias on spatially varying power and alpha rates in an empirical study of 21 subjects. Bias is shown to inflame alpha rates, distort the power curve, and cause significant power loss even in empirical settings where the expected difference in bias between groups is zero. These adverse effects can be attenuated by properly accounting for bias in the calculation of power and p-values.     

Influence of deposition parameters on hard Cr-Al-N coatings deposited by multi-arc ion plating

The Cr-Al-N coatings were synthesized at various substrate bias voltages and nitrogen partial pressures by multi-arc ion plating (M-AIP). The relationships between deposition parameters and coating properties were investigated. Morphologies, phase structures, hardness and adhesion strength of the coatings were analyzed by SEM, XRD, XPS, nano-indenter and scratch tester. The results indicated that with the increase of substrate bias voltages, the surface macroparticles and deposition rate reduced mainly for the resputtering phenomenon. The (Cr, Al)N solid-solution phase kept unchanged, but the Cr₂N and AlN phases disappeared gradually. Due to the change of phase structures and residual compressive stress, the hardness values decreased and the adhesion strength decreased initially and then increased. Similarly, with the increase of nitrogen partial pressures, the phase structures of CrAlN coatings varied from Cr + Cr₂N + (Cr,Al)N to Cr₂N + (Cr,Al)N. The surface macroparticles increased due to the decreasing resputtering efficiency, and the deposition rate increased initially and then decreased due to the resputtering phenomenon. With increasing nitrogen partial pressures, adhesion strength decreased initially and then increased. The microhardness increased mainly due to the increase of Cr₂N contents and decrease of metal macroparticles.     

3-T MR-guided brachytherapy for gynecologic malignancies

Gynecologic malignancies are a leading cause of death in women worldwide. Standard treatment for many primary and recurrent gynecologic cancer cases includes external-beam radiation followed by brachytherapy. Magnetic resonance (MR) imaging is beneficial in diagnostic evaluation, in mapping the tumor location to tailor radiation dose and in monitoring the tumor response to treatment. Initial studies of MR guidance in gynecologic brachytherapy demonstrate the ability to optimize tumor coverage and reduce radiation dose to normal tissues, resulting in improved outcomes for patients.     

Characterizations of Overtaking Optimality for Controlled Diffusion Processes

In this paper we give conditions for (the existence and) several characterizations of overtaking optimal policies for a general class of controlled diffusion processes. Our characterization results are of a lexicographical type; namely, first we identify the class of so-called canonical policies, and then within this class we search for policies with some special feature—for instance, canonical policies that in addition maximize the bias. This research was partially supported by CONACyT grant 45693-F. The research of the first author (HJF) was also supported by a CONACyT scholarship.     

The effect of bias voltage and working pressure on S/Mo ratio at MoS2-Ti composite films

S/Mo ratio has a crucial effect on the tribological properties of MoS₂-Ti composite films. The deposition parameters as such bias voltage and working pressure play a dominant role on the change of this ratio value. To determine the effect of working pressure and bias voltage on S/Mo ratio, MoS₂-Ti composite films were deposited on glass wafers by pulsed-dc magnetron sputtering (PMS). The deposition process was performed for nine different test conditions at various levels of target current, working pressure, and substrate voltage using the Taguchi L₉(3⁴) experimental method. It was observed that the chemical composition of MoS₂-Ti composite films was significantly affected by sputtering parameters. It was also observed that S/Mo ratio decreased as the bias voltage increased at a constant working pressure and S/Mo ratio increased with increasing working pressure at a constant bias voltage.     

Kernel-type estimator of the reinsurance premium for heavy-tailed loss distributions

In this paper, we generalize the classical estimator of the reinsurance premium for heavy-tailed loss distributions with a kernel-type estimator. Since this estimator exhibits a bias, we propose its bias-reduced version by using a least-squares method. The asymptotic normality of the proposed estimators is established under suitable assumptions. A small simulation study is carried out to prove the performance of our approach.