Methods for the measurement and characterization of erosion in enamel and dentine

The advantages, limitations and potential applications of available methods for studying erosion of enamel and dentine are reviewed. Special emphasis is placed on the influence of histological differences between the dental hard tissue and the stage of the erosive lesion. No method is suitable for all stages of the lesion. Factors determining the applicability of the methods are: surface condition of the specimen, type of the experimental model, nature of the lesion, need for longitudinal measurements and type of outcome. The most suitable and most widely used methods are: chemical analyses of mineral release and enamel surface hardness for early erosion, and surface profilometry and microradiography for advanced erosion. Morphological changes in eroded dental tissue have usually been characterised by scanning electron microscopy. Novel methods have also been used, but little is known of their potential and limitations. Therefore, there is a need for their further development, evaluation, consolidation and, in particular, validation.

CT based volume measurement and estimation in cases of pericardial effusion

The measurement of fluid volumes in cases of pericardial effusion is a necessary procedure during autopsy. With the increased use of virtual autopsy methods in forensics, the need for a quick volume measurement method on computed tomography (CT) data arises, especially since methods such as CT angiography can potentially alter the fluid content in the pericardium. We retrospectively selected 15 cases with hemopericardium, which underwent post-mortem imaging and autopsy. Based on CT data, the pericardial blood volume was estimated using segmentation techniques and downsampling of CT datasets. Additionally, a variety of measures (distances, areas and 3D approximations of the effusion) were examined to find a quick and easy way of estimating the effusion volume. Segmentation of CT images as shown in the present study is a feasible method to measure the pericardial fluid amount accurately. Downsampling of a dataset significantly increases the speed of segmentation without losing too much accuracy. Some of the other methods examined might be used to quickly estimate the severity of the effusion volumes.

In-situ measurement and characterization of cloud particles using digital in-line holography

Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

Measurement and meaning of head movements in everyday face-to-face communicative interaction

Methodological approaches in which data on nonverbal behavior are collected usually involve interpretive methods in which raters must identify a set of defined categories of behavior. However, present knowledge about the qualitative aspects of head movement behavior calls for recording detailed transcriptions of behavior. These records are a prerequisite for investigating the function and meaning of head movement patterns. A method for directly collecting data on head movement behavior is introduced. Using small ultrasonic transducers, which are attached to various parts of an index person's body (head and shoulders), a microcomputer defines receiver-transducers distances. Three-dimensional positions are calculated by triangulation. These data are used for further calculations concerning the angular orientation of the head and the direction, size, and speed of head movements (in rotational, lateral, and sagittal dimensions).

Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

Cancer, meta-analysis and reporting biases: the case of erythropoiesis-stimulating agents.

Reporting and publication bias is a well-known problem in meta-analysis and healthcare research. In 2002 we conducted a meta-analysis on the effects of erythropoiesis-stimulating agents (ESAs) on overall survival in cancer patients, which suggested some evidence for improved survival in patients receiving ESAs compared with controls. However, a meta-analysis of individual patient data conducted several years later showed the opposite of our first meta-analysis, that is, evidence for increased on-study mortality and reduced overall survival in cancer patients receiving ESAs. We aimed to determine whether the results of our first meta-analysis could have been affected by publication and reporting biases and, if so, whether timely access to clinical study reports and individual patient data could have prevented this. We conducted a hypothetical meta-analysis for overall survival including all studies and study data that could have been available in 2002, at the time when we conducted our first meta-analysis. Compared with our original meta-analysis, which suggested an overall survival benefit for cancer patients receiving ESAs [hazard ratio (HR) 0.81, 95% confidence interval (CI) 0.67‒0.99], our hypothetical meta-analysis based on the results of all studies conducted at the time of the first analysis did not show evidence for a beneficial effect of ESAs on overall survival (HR 0.97, 95% CI 0.83‒1.12). Thus we have to conclude that our first meta-analysis showed misleading overall survival benefits due to publication and reporting biases, which could have been prevented by timely access to clinical study reports and individual patient data. Unrestricted access to clinical study protocols including amendments, clinical study reports and individual patient data is needed to ensure timely detection of both beneficial and harmful effects of healthcare interventions.

3G network traffic sources measurement and analysis

In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright © 2013 John Wiley & Sons, Ltd.

Continuum of depressive and manic mixed states in patients with bipolar disorder: quantitative measurement and clinical features.

Bipolar mixed states combine depressive and manic features, presenting diagnostic and treatment challenges and reflecting a severe form of the illness. DSM-IV criteria for a mixed state require combined depressive and manic syndromes, but a range of mixed states has been described clinically. A unified definition of mixed states would be valuable in understanding their diagnosis, mechanism and treatment implications. We investigated the manner in which depressive and manic features combine to produce a continuum of mixed states. In 88 subjects with bipolar disorder (DSM-IV), we evaluated symptoms and clinical characteristics, and compared depression-based, mania-based, and other published definitions of mixed states. We developed an index of the extent to which symptoms were mixed (Mixed State Index, MSI) and characterized its relationship to clinical state. Predominately manic and depressive mixed states using criteria from recent literature, as well as Kraepelinian mixed states, had similar symptoms and MSI scores. Anxiety correlated significantly with depression scores in manic subjects and with mania scores in depressed subjects. Discriminant function analysis associated mixed states with symptoms of hyperactivity and negative cognitions, but not subjective depressive or elevated mood. High MSI scores were associated with severe course of illness. For depressive or manic episodes, characteristics of mixed states emerged with two symptoms of the opposite polarity. This was a cross-sectional study. Mixed states appear to be a continuum. An index of the degree to which depressive and manic symptoms combine appears useful in identifying and characterizing mixed states. We propose a depressive or manic episode with three or more symptoms of the opposite polarity as a parsimonious definition of a mixed state.

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of root s = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K-s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5 % for central isolated hadrons and 1-3 % for the final calorimeter jet energy scale.