A Note on the Prior Distributions of Weibull Parameters for the Reliability Function

In Bayesian Inference it is often desirable to have a posterior density reflecting mainly the information from sample data. To achieve this purpose it is important to employ prior densities which add little information to the sample. We have in the literature many such prior densities, for example, Jeffreys (1967), Lindley (1956); (1961), Hartigan (1964), Bernardo (1979), Zellner (1984), Tibshirani (1989), etc. In the present article, we compare the posterior densities of the reliability function by using Jeffreys, the maximal data information (Zellner, 1984), Tibshirani's, and reference priors for the reliability function R(t) in a Weibull distribution.

The Neuropsychiatric Inventory-Clinician rating scale (NPI-C): Reliability and validity of a revised assessment of neuropsychiatric symptoms in dementia

Background: Neuropsychiatric symptoms (NPS) affect almost all patients with dementia and are a major focus of study and treatment. Accurate assessment of NPS through valid, sensitive and reliable measures is crucial. Although current NPS measures have many strengths, they also have some limitations (e.g. acquisition of data is limited to informants or caregivers as respondents, limited depth of items specific to moderate dementia). Therefore, we developed a revised version of the NPI, known as the NPI-C. The NPI-C includes expanded domains and items, and a clinician-rating methodology. This study evaluated the reliability and convergent validity of the NPI-C at ten international sites (seven languages). Methods: Face validity for 78 new items was obtained through a Delphi panel. A total of 128 dyads (caregivers/patients) from three severity categories of dementia (mild = 58, moderate = 49, severe = 21) were interviewed separately by two trained raters using two rating methods: the original NPI interview and a clinician-rated method. Rater 1 also administered four additional, established measures: the Apathy Evaluation Scale, the Brief Psychiatric Rating Scale, the Cohen-Mansfield Agitation Index, and the Cornell Scale for Depression in Dementia. Intraclass correlations were used to determine inter-rater reliability. Pearson correlations between the four relevant NPI-C domains and their corresponding outside measures were used for convergent validity. Results: Inter-rater reliability was strong for most items. Convergent validity was moderate (apathy and agitation) to strong (hallucinations and delusions; agitation and aberrant vocalization; and depression) for clinician ratings in NPI-C domains. Conclusion: Overall, the NPI-C shows promise as a versatile tool which can accurately measure NPS and which uses a uniform scale system to facilitate data comparisons across studies. Copyright © 2010 International Psychogeriatric Association.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Determination of disease biomarkers in Eucalyptus by comprehensive two-dimensional gas chromatography and multivariate data analysis

In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC. ×. GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte. © 2013 Elsevier B.V..

The Brazilian version of the Neuropsychiatric Inventory-Clinician rating scale (NPI-C): Reliability and validity in dementia

ABSTRACT Background: Patients with dementia may be unable to describe their symptoms, and caregivers frequently suffer emotional burden that can interfere with judgment of the patient's behavior. The Neuropsychiatric Inventory-Clinician rating scale (NPI-C) was therefore developed as a comprehensive and versatile instrument to assess and accurately measure neuropsychiatric symptoms (NPS) in dementia, thereby using information from caregiver and patient interviews, and any other relevant available data. The present study is a follow-up to the original, cross-national NPI-C validation, evaluating the reliability and concurrent validity of the NPI-C in quantifying psychopathological symptoms in dementia in a large Brazilian cohort. Methods: Two blinded raters evaluated 312 participants (156 patient-knowledgeable informant dyads) using the NPI-C for a total of 624 observations in five Brazilian centers. Inter-rater reliability was determined through intraclass correlation coefficients for the NPI-C domains and the traditional NPI. Convergent validity included correlations of specific domains of the NPI-C with the Brief Psychiatric Rating Scale (BPRS), the Cohen-Mansfield Agitation Index (CMAI), the Cornell Scale for Depression in Dementia (CSDD), and the Apathy Inventory (AI). Results: Inter-rater reliability was strong for all NPI-C domains. There were high correlations between NPI-C/delusions and BPRS, NPI-C/apathy-indifference with the AI, NPI-C/depression-dysphoria with the CSDD, NPI-C/agitation with the CMAI, and NPI-C/aggression with the CMAI. There was moderate correlation between the NPI-C/aberrant vocalizations and CMAI and the NPI-C/hallucinations with the BPRS. Conclusion: The NPI-C is a comprehensive tool that provides accurate measurement of NPS in dementia with high concurrent validity and inter-rater reliability in the Brazilian setting. In addition to universal assessment, the NPI-C can be completed by individual domains. © International Psychogeriatric Association 2013.

Test-retest reliability of a 3-min isokinetic all-out test using two different cadences

Objectives: To investigate the test-retest reliability of mechanical parameters derived from a 3-min isokinetic all-out test, performed at 60 and 100 rpm. Reliability and validity of the peak oxygen uptake derived from 3-min isokinetic all-out test were also tested. Design: 14 healthy male subjects completed an incremental ramp testing and four randomized 3-min isokinetic all-out test (two at 60 rpm and two at 100 rpm). Methods: The absolute and relative reliability of the following parameters were analyzed: peak power, mean power, end power, fatigue index, work performed above end power and peak oxygen uptake. Results: No difference was found between each two sets of data, although there were between-cadence differences for peak power, mean power, end power, and fatigue index. Higher intra-class correlation (ICC) and lower coefficient of variation (CV) were found for end power (ICC = 0.91 and 0.95; CV = 5.6 and 5.7%) and mean power (ICC = 0.97 and 0.98; CV = 2.4 and 3.1%), than for peak power (ICC = 0.81 and 0.84; CV = 8.7 and 10%) and work performed above end power (ICC = 0.79 and 0.84; CV = 7.9 and 10.6%; values reported for 60 rpm and 100 rpm, respectively). High reliability scores were also observed for peak oxygen uptake at both cadences (60 rpm, CV = 3.2%; 100 rpm, CV = 2.3%,) with no difference with the incremental ramp testing peak oxygen uptake. Conclusions: The power profile and peak oxygen uptake of a 3-min isokinetic all-out test are both highly reliable, whether the test is performed at 60 or 100 rpm. Besides, peak oxygen uptake and work performed above end power were not affected by the change in cadence while peak power, mean power, end power, and fatigue index were. © 2013.

Influence of abutment-to-fixture design on reliability and failure mode of all-ceramic crown systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Test-retest reliability of electromyographic variables of masseter and temporal muscles in patients with cerebral palsy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Providing Reliable Data Transport for Dynamic Event Sensing in Wireless Sensor Networks

In this paper, we propose a Loss Tolerant Reliable (LTR) data transport mechanism for dynamic Event Sensing (LTRES) in WSNs. In LTRES, a reliable event sensing requirement at the transport layer is dynamically determined by the sink. A distributed source rate adaptation mechanism is designed, incorporating a loss rate based lightweight congestion control mechanism, to regulate the data traffic injected into the network so that the reliability requirement can be satisfied. An equation based fair rate control algorithm is used to improve the fairness among the LTRES flows sharing the congestion path. The performance evaluations show that LTRES can provide LTR data transport service for multiple events with short convergence time, low lost rate and high overall bandwidth utilization.

Sulcus anatomy and diameter in pseudophakic eyes and correlation with biometric data: Evaluation with a 50 MHz ultrasound biomicroscope

PURPOSE: To evaluate the sulcus anatomy and possible correlations between sulcus diameter and white-to-white (WTW) diameter in pseudophakic eyes, data that may be important in the stability of add-on intraocular lenses (IOLs). SETTING: University Eye Hospital, Tuebingen, Germany. DESIGN: Case series. METHODS: In pseudophakic eyes, the axial length (AL) and horizontal WTW were measured by the IOLMaster device. Cross-sectional images were obtained with a 50 MHz ultrasound biomicroscope on the 4 meridians: vertical, horizontal (180 degrees), temporal oblique, and nasal oblique. Sulcus-to-sulcus (STS), angle-to-angle (ATA), and sclera-to-sclera (ScTSc) diameters were measured. The IOL optic diameter (6.0 mm) served as a control. To test reliability, optic measurements were repeated 5 times in a subset of eyes. RESULTS: The vertical ATA and STS diameters were statistically significantly larger than the horizontal diameter (P=.0328 and P=.0216, respectively). There was no statistically significant difference in ScTSc diameters. A weak correlation was found between WTW and horizontal ATA (r = 0.5766, P<.0001) and between WTW and horizontal STS (r = 0.5040, P=.0002). No correlation was found between WTW and horizontal ScTSc (r = 0.2217, P=.1217). CONCLUSIONS: The sulcus anatomy had a vertical oval shape with the vertical meridian being the largest, but it also had variation in the direction of the largest meridian. The WTW measurements showed a weak correlation with STS. In pseudophakic eyes, Soemmerring ring or a bulky haptic may affect the ciliary sulcus anatomy.

A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

Bootstrap confidence intervals for industrial recurrent event data

Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.

Reliability and consistency affect the integration of visual depth cues

Abstract Originalsprache (englisch) Visual perception relies on a two-dimensional projection of the viewed scene on the retinas of both eyes. Thus, visual depth has to be reconstructed from a number of different cues that are subsequently integrated to obtain robust depth percepts. Existing models of sensory integration are mainly based on the reliabilities of individual cues and disregard potential cue interactions. In the current study, an extended Bayesian model is proposed that takes into account both cue reliability and consistency. Four experiments were carried out to test this model's predictions. Observers had to judge visual displays of hemi-cylinders with an elliptical cross section, which were constructed to allow for an orthogonal variation of several competing depth cues. In Experiment 1 and 2, observers estimated the cylinder's depth as defined by shading, texture, and motion gradients. The degree of consistency among these cues was systematically varied. It turned out that the extended Bayesian model provided a better fit to the empirical data compared to the traditional model which disregards covariations among cues. To circumvent the potentially problematic assessment of single-cue reliabilities, Experiment 3 used a multiple-observation task, which allowed for estimating perceptual weights from multiple-cue stimuli. Using the same multiple-observation task, the integration of stereoscopic disparity, shading, and texture gradients was examined in Experiment 4. It turned out that less reliable cues were downweighted in the combined percept. Moreover, a specific influence of cue consistency was revealed. Shading and disparity seemed to be processed interactively while other cue combinations could be well described by additive integration rules. These results suggest that cue combination in visual depth perception is highly flexible and depends on single-cue properties as well as on interrelations among cues. The extension of the traditional cue combination model is defended in terms of the necessity for robust perception in ecologically valid environments and the current findings are discussed in the light of emerging computational theories and neuroscientific approaches.

Boundary condition identification of a bridge pier using experimental data and FEM modal updating

Over the past twenty years, new technologies have required an increasing use of mathematical models in order to understand better the structural behavior: finite element method is the one mostly used. However, the reliability of this method applied to different situations has to be tried each time. Since it is not possible to completely model the reality, different hypothesis must be done: these are the main problems of FE modeling. The following work deals with this problem and tries to figure out a way to identify some of the unknown main parameters of a structure. This main research focuses on a particular path of study and development, but the same concepts can be applied to other objects of research. The main purpose of this work is the identification of unknown boundary conditions of a bridge pier using the data acquired experimentally with field tests and a FEM modal updating process. This work doesn’t want to be new, neither innovative. A lot of work has been done during the past years on this main problem and many solutions have been shown and published. This thesis just want to rework some of the main aspects of the structural optimization process, using a real structure as fitting model.

German validation of the Conners Adult ADHD Rating Scales (CAARS) II: reliability, validity, diagnostic sensitivity and specificity

The German version of the Conners Adult ADHD Rating Scales (CAARS) has proven to show very high model fit in confirmative factor analyses with the established factors inattention/memory problems, hyperactivity/restlessness, impulsivity/emotional lability, and problems with self-concept in both large healthy control and ADHD patient samples. This study now presents data on the psychometric properties of the German CAARS-self-report (CAARS-S) and observer-report (CAARS-O) questionnaires.