Literatura académica sobre el tema "Imprecision zone"

ABSTRACT New gamma interferon (IFN-γ) release assays (IGRAs) to detect an exposure to Mycobacterium tuberculosis have recently been launched. The majority of the studies in temperate-climate countries agree that these methods have superior specificity and equal or even superior sensitivity over tuberculin skin tests (TSTs) in the diagnosis of latent tuberculosis (TB) infection (LTBI). However, reproducibility data of IGRAs are virtually missing. We assessed within-run, between-run, and total imprecision of two commercial IGRAs by testing samples from subjects with a stable state of TB infection or treated pulmonary TB, a sample from a healthy volunteer, and internal quality control samples. We calculated coefficients of variance (CV%s) to describe assays variability and compared the obtained results to the reported CV%s for other commercial immunodiagnostic methods. We illustrate an example of assay variability near the cutoff zone to demonstrate the necessity of a gray zone. Due to the strict adherence to the standard operation procedures (SOP) adopted in our laboratory, the total imprecision of enzyme-linked immunospot (ELISPOT)- and enzyme immunoassay (EIA)-based IGRAs was at a maximum CV% of 37.8% for the samples with moderate and high reactivities. Imprecision of testing samples with very low reactivity levels or nonreactive samples may, however, exceed 100%. In conclusion, despite multiple steps of the method performance, the analytical imprecision of IGRAs, which in our study design included also between-lot variability and had a component of normal biological variation, was well in accordance with the reported imprecisions of other manual immunodiagnostic tests. The recognition of the variability around the cutoff point advocates the use of a gray zone to avoid ambiguous result interpretations.

A methodology based on fuzzy set theory is presented to express imprecision of input data in a non-probabilitic sense. Imprecision may originate from indirect measurements, estimation routines, subjective interpretation, and expert judgement of available information. A numerical finite difference solution scheme was chosen to solve one-dimensional steady-state water flow in the unsaturated zone of a layered soil profile. To extend the solution algorithm to operate with fuzzy soil-hydraulic properties and boundary conditions, it is necessary to incorporate the scheme into a nonlinear optimisation routine from where resulting membership functions of soil water pressures with depths can be calculated. By subsequently considering the different imprecise parameters in the calculations and analysing their impact, it is concluded that resulting imprecision not only depends on the degree of imprecision and the number of uncertain parameters but also very much on the system context (e.g. boundary conditions and spatial distribution). The comparison with a closed form solution to solve the fuzzy water flow problem show the potential of that method to be extended towards transient, two- and three-dimensional process descriptions.

Abstract Background: Most processes for fabricating biosensors applied to screen-printed carbon electrodes (SPCEs) are complex. This study presents a novel one-step process for manufacturing electrodes for injection-molding biosensors. Methods: During the sensor-fabrication process, barrel-plated gold electrodes were inserted into an injection-molded base. The electrode directly touched the electrical contact of a meter. We analyzed technical measurements for this biosensor, including tests of the measurement range, within-run imprecision, and between-meter imprecision. In clinical trials, experienced technicians tested 3 alternative sites (fingertip, palm, and arm). The results were simultaneously compared with plasma values obtained with the hexokinase method on the Olympus AU640 instrument. Analytical results were evaluated according to International Standards Organization 15197 (ISO 15197:2003) criteria and by Clarke error grid analysis (EGA), and CVs were calculated to evaluate within-run imprecision. Results: The glucose measurement range was 0.6– 33.3 mmol/L (y = 0.96x + 0.07 mmol/L; r2 = 0.9977). The CVs in the within-run imprecision test were 1.7%–3.5%, and the overall CV was 2.1%, indicating good reproducibility of results. The Student t-tests of mean values from 5 meters revealed statistically insignificant differences (P > 0.05). In clinical trials, the agreement of the Rightest GM310 meter results with those of a laboratory method complied with ISO 15197:2003 criteria. In the EGA, 100% of the values were within the acceptable zones (A + B), and the proportion of values within zone A exceeded 95%. Conclusions: The Bionime Rightest GM310 meter applied a simplified process for biosensor fabrication and displayed acceptable performance for monitoring glucose concentrations at alternative test sites.

This paper presents a framework for evaluation of nitrate control strategies that use spatially variable nitrogen input in the presence of imprecise information. The research stems from the fact that diffuse pollution has caused water consumers to be concerned with reducing the risk posed by contaminated water supplies. An important element in quantifying risk reduction is the use of simulation modeling to predict the transport and fate of contaminants under variable rate application as employed in a wellhead protection area strategy. Specifically, a groundwater model is linked with an unsaturated zone transport (and crop production) model which provides the nutrient and recharge loading rates to the saturated zone. To consider uncertainty stemming from the unsaturated zone model output, in addition to aquifer parameters, a new groundwater modeling technique is developed in which fuzzy set theory is combined with finite-difference modeling methods. The groundwater model incorporates imprecise parameters (i.e., transmissivity) into the modelling process through the use of fuzzy set theory. Imprecision has been encoded directly into the finite-difference equations using fuzzy numbers as input, and level-set operations combined with non-linear optimization are used to solve the system of equations. The resulting fuzzy output can be interpreted as the level of imprecision associated with the model. A case study is presented to illustrate the methodology.

Indoor localization has several applications ranging from people tracking and indoor navigation, to autonomous robot navigation and asset tracking. We tackle the problem as a zoning localization where the objective is to determine the zone where the mobile sensor resides at any instant. The decision-making process in localization systems relies on data coming from multiple sensors. The data retrieved from these sensors require robust fusion approaches to be processed. One of these approaches is the belief functions theory (BFT), also called the Dempster–Shafer theory. This theory deals with uncertainty and imprecision with a theoretically attractive evidential reasoning framework. This paper investigates the usage of the BFT to define an evidence framework for estimating the most probable sensor’s zone. Real experiments demonstrate the effectiveness of this approach and its competence compared to state-of-the-art methods.

Abstract Hemoglobin A2 (Hb A2) and hemoglobin F (Hb F) are important analytes in the diagnosis and follow up of Hb diseases. We evaluated a new capillary zone electrophoresis (CZE) kit for Hb A2 and Hb F measurements. The imprecision ranged from 3% to 6% for Hb A2 and Hb F at physiological and pathological concentrations. The method compared well with cation-exchange HPLC for Hb A2 and Hb F and with anion-exchange chromatography in microcolumns (MAEC), for Hb A2. Nevertheless, higher results were obtained [Hb A2 CZE (%) = 1.233 Hb A2 HPLC − 0.2; Hb A2 CZE (%) = 1.190 Hb A2 MAEC + 0.1; Hb FCZE (%) = 1.118 Hb FHPLC + 0.4], and new reference values had to be determined (Hb A2 2.7–3.8%; Hb F <1.2%). Quantification of Hb A2 was not influenced by Hb S. Measurement of Hb F was accurate and precise except at low concentrations in Hb AS patients. This new CZE kit is rapid, precise, and reliable, and seems appropriate for use in clinical laboratories.

Monitoring the tool state during the cutting process becomes very important since the introduction of CAM in manufacturing process. The tool life based only on economic data is not enough especially in the case precision cutting due to the scattering of tool wear which depends on much more mechanical and physical properties of the workpiece and tool materials. Attempts to assess the state of wear of the tool by direct measurement of the wear indicators have been unsuccessful due to difficult access in the cutting zone and measurement imprecision. We have so wear patterns appreciation by measuring indirect indicators of wear, the main models are based on measuring vibration, acoustic emission or cutting forces and power consumption separately or together. These models have the disadvantage that should be followed at least two indicators simultaneously for a minimum precision of the results. Considering the wear models developed over time it can be seen that there is a clear relationship between wear and stabilized temperature. The paper aims to study the introduction temperature as indirect indicator of tool state in addition to the existing indicators, this leads to increased reliability of results of monitoring of wear.

Abstract During a trapping study interval, each target insect is either caught or not caught. Therefore, the current analysis treats trapping as a binomial process. Data from a binomial calculator, along with computer simulations of random walkers, documented that the inherent variance associated with estimates of absolute population density generated by a single catch number in a pheromone-baited monitoring trap becomes very high when catch probability averaged across the trap’s sampling area falls below 0.02, as is the case for most insect trapping systems operating in the open field. The imprecision associated with interpretations of single catch numbers renders many current pest management decisions risky and unsatisfactory. Here we reinforce how single-trap, multiple-release experiments can and should be used to measure catch probability, plume reach, and trap sampling area. When catch probability lies in the danger zone below 0.02, steps are suggested for how multiple traps might be deployed to raise composite catch probability to a level where estimates of absolute pest density become reliable. Heat transfer is offered as an appropriate conceptual model for the mechanics of trapping. A call is made for a radical rethinking in the designs of insect monitoring traps in light of their significant current deficits highlighted by this study.

The Brabant Lake area mostly comprises Early Proterozoic clastic metasediments of the MacLean Lake belt, eastern La Ronge Domain, Reindeer Zone. The belt underwent upper amphibolite facies metamorphism, with sillimanite occurring in both psammitic and pelitic gneisses. Biotite + garnet + sillimanite + cordierite + quartz + K-feldspar + plagioclase parageneses suggest peak metamorphic pressure–temperature (P–T) conditions of 650–750 °C at 4–6 kbar (1 bar = 100 kPa) and [Formula: see text]. Both psammitic and pelitic gneisses underwent anatexis, which may have caused a reduction in water pressure. P–T conditions were also calculated by applying thermometry on the basis of garnet–biotite Fe–Mg exchange and barometry on the basis of garnet + plagioclase + sillimanite + quartz assemblages. The most precise garnet–biotite thermometer yielded temperatures of 608–758 °C (mean 690 °C). A more recent version, which incorporates the effects of minor components and nonideal mixing in both garnet and biotite, yielded a wider range of temperatures (565–826 °C), suggesting that imprecision in garnet–biotite thermometry may be due to disparate closing temperatures or disequilibrium. Application of several recent calibrations of the grossular + anorthite + sillimanite + quartz barometer produced a range of pressure estimates: three of these calibrations gave results compatible with documented mineral parageneses and experimental data, yielding 6.1 ± 0.5,6.1 ± 0.8, and 6.8 ± 0.9 kbar, respectively. Estimated mean pressures from another calibration are about 1–2 kbar higher. Peak metamorphic conditions at Brabant Lake are comparable with those experienced by metasediments of the Kisseynew Domain in Saskatchewan and Manitoba and other portions of the Reindeer Zone. Of 19 analyzed garnets from metapelites, 4 showed distinct chemical zonation. Garnet core growth appears coeval with syn-D2 peak metamorphic conditions; such cores yield the highest temperature estimates. Lower temperature estimates from garnet rims (range 610–660 °C, mean 630 °C) reflect retrogression under postpeak metamorphic conditions.

Abstract Because of increased interest in the assay of albumin in urine and the sensitivity required to quantify concentrations associated with (a) increased risk of developing end-stage renal disease and cardiovascular disease among people with diabetes and (b) renal damage caused by exposure to nephrotoxic substances, we conducted a pilot study of the variation of these measurements within and among five laboratories that use various immunoassays. These assays included two different enzyme immunoassays, two different immunoturbidimetric assays, a fluorescent immunoassay, and a zone immunoelectrophoresis assay. The results indicate considerable variation both within and among laboratories for measurements at or near the normal range. Variability is equally attributable to the precision of individual immunoassays and to the variation of the mean values obtained by each laboratory. Individual laboratory CVs ranged from 5.8% to 18.2% for mid- and high-concentration samples treated with preservative and from 8.4% to 23.6% for mid- and high-concentration samples containing no preservative. The relative bias of individual laboratory means ranged from -56.4% to 20.5% for the two preserved materials and from -32.6% to 0.8% for the two materials containing no preservative. To reduce the chance of misdiagnosing the risk associated with above-normal albumin concentrations in urine, we need to address the problems contributing to imprecision and inaccuracy, particularly laboratory-to-laboratory variability.

En partitionnement de données, l'objectif consiste à regrouper des objets en fonction de leur similarité. K-means est un des modèles les plus utilisés, chaque classe est représentée par son centroïde. Les objets sont assignés à la classe la plus proche selon une distance. Le choix de cette distance revêt une grande importance pour prendre en compte la similarité entre les données. En optant pour la distance de Mahalanobis au lieu de la distance euclidienne, le modèle est capable de détecter des classes de forme ellipsoïdale et non plus seulement sphérique. L'utilisation de cette distance offre de nombreuses opportunités, mais elle soulève également de nouveaux défis explorés dansma thèse.L'objectif central concerne l'optimisation des modèles, en particulier FCM-GK (variante floue de k-means) qui est un problème non convexe. L'idée est d'obtenir un partitionnement de meilleure qualité, sans créer un nouveau modèle en appliquant des méthodes d'optimisation plus robustes. À cet égard, nous proposons deux approches :ADMM (Alternating Direction Method of Multipliers) et la méthode du gradient accéléré de Nesterov. Les expériences numériques soulignent l'intérêt particulier de l'optimisation par ADMM, surtout lorsque le nombre d'attributs dans le jeu de données est significativement plus élevé que le nombre de clusters. L'incorporation de la distance de Mahalanobis dans le modèle requiert l'introduction d'une mesure d'évaluation dédiée aux partitions basées sur cette distance. Une extension de la mesure d'évaluation de Xie et Beni est proposée. Cet index apparaît comme un outil pour déterminer la distance optimale à utiliser.Enfin, la gestion des sous-ensembles dans ECM (variante évidentielle) est traitée en abordant la détermination optimale de la zone d'imprécision. Une nouvelle formulation des centroides et des distances des sous-ensembles à partir des clusters est introduite. Les analyses théoriques et les expérimentations numériques mettent en évidence la pertinence de cette nouvelle formulation
In data partitioning, the goal is to group objects based on their similarity. K-means is one of the most commonly used models, where each cluster is represented by its centroid. Objects are assigned to the nearest cluster based on a distance metric. The choice of this distance is crucial to account for the similarity between the data points. Opting for the Mahalanobis distance instead of the Euclidean distance enables the model to detect classes of ellipsoidal shape rather than just spherical ones. The use of this distance metric presents numerous opportunities but also raises new challenges explored in my thesis.The central objective is the optimization of models, particularly FCM-GK (a fuzzy variant of k-means), which is a non-convex problem. The idea is to achieve a higher-quality partitioning without creating a new model by applying more robust optimization methods. In this regard, we propose two approaches: ADMM (Alternating Direction Method of Multipliers) and Nesterov's accelerated gradient method. Numerical experiments highlight the particular effectiveness of ADMM optimization, especially when the number of attributes in the dataset is significantly higher than the number of clusters.Incorporating the Mahalanobis distance into the model requires the introduction of an evaluation measure dedicated to partitions based on this distance. An extension of the Xie and Beni evaluation measure is proposed. This index serves as a tool to determine the optimal distance to use.Finally, the management of subsets in ECM (evidential variant) is addressed by determining the optimal imprecision zone. A new formulation of centroids and distances for subsets from clusters is introduced. Theoretical analyses and numerical experiments underscore the relevance of this new formulation