Modelling High-Dimensional Data by Mixtures of Factor Analyzers

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix with complexity lying between that of the isotropic and full covariance structure models. We shall illustrate the use of mixtures of factor analyzers in a practical example that considers the clustering of cell lines on the basis of gene expressions from microarray experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

Evaluation of two HbA1c point-of-care analyzers.

BACKGROUND Measurement of HbA1c is the most important parameter to assess glycemic control in diabetic patients. Different point-of-care devices for HbA1c are available. The aim of this study was to evaluate two point-of-care testing (POCT) analyzers (DCA Vantage from Siemens and Afinion from Axis-Shield). We studied the bias and precision as well as interference from carbamylated hemoglobin. METHODS Bias of the POCT analyzers was obtained by measuring 53 blood samples from diabetic patients with a wide range of HbA1c, 4%-14% (20-130 mmol/mol), and comparing the results with those obtained by the laboratory method: HPLC HA 8160 Menarini. Precision was performed by 20 successive determinations of two samples with low 4.2% (22 mmol/mol) and high 9.5% (80 mmol/mol) HbA1c values. The possible interference from carbamylated hemoglobin was studied using 25 samples from patients with chronic renal failure. RESULTS The means of the differences between measurements performed by each POCT analyzer and the laboratory method (95% confidence interval) were: 0.28% (p<0.005) (0.10-0.44) for DCA and 0.27% (p<0.001) (0.19-0.35) for Afinion. Correlation coefficients were: r=0.973 for DCA, and r=0.991 for Afinion. The mean bias observed by using samples from chronic renal failure patients were 0.2 (range -0.4, 0.4) for DCA and 0.2 (-0.2, 0.5) for Afinion. Imprecision results were: CV=3.1% (high HbA1c) and 2.97% (low HbA1c) for DCA, CV=1.95% (high HbA1c) and 2.66% (low HbA1c) for Afinion. CONCLUSIONS Both POCT analyzers for HbA1c show good correlation with the laboratory method and acceptable precision.

Aerosols monitoring in Rio Claro, Brazil: Using lidar and air pollution analyzers

Brazil has an important role in the biomass burning aerosol activity. During the Dry Season (June-September) of 2009 an aerosol profiling campaign was carried out using a backscattering and Raman lidar system in Rio Claro-SP, Brazil (22°23'S and 47°32'W). The main goal of this campaign was to observe the biomass burning aerosol load due to sugarcane crops and also study the air dispersion conditions, planetary boundary and mixed layer daily evolution. In this paper we aim to present the preliminary results of the influence of this type of aerosol over the city of Rio Claro-SP, Brazil and one case study to evaluate the aerosol profile in a biomass burning episode that occurred in July, 2009. On July 15 an intense burning was observed about 300 m away from the lidar location. Throughout the measurements it was observed that the plumes reached up to 900 m, and that there was a time gap between the plumes. The gas analyzers showed a strong influence of this burning as it was noticed in the measurements of CO, NO x and nephelometer, whereas the PM10 did not have due to this burning, possibly because the particulate was deposited further from the emission source, not being detected by the equipment. © Sociedad Española de Óptica.

Optimized design of substrate-integrated hollow waveguides for mid-infrared gas analyzers

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A new basic effect in retarding potential analyzers

The Retarding Potential Analyzer (RPA) is the standard instrument for in situ measurement of ion temperature and other ionospheric parameters. The fraction of incoming ions rejected by a RPA produces perturbations that reach well ahead of a thin Debye sheath, a feature common to all collisionless, hypersonic flows past ion-rejecting bodies. This phenomenon is here found to result in a correction to Whipple’s classical law for the current characteristic of an ideal RPA sheath thin; inverse ram ion Mach number M-1, and ram angle of RPA aperture u, small or moderately small.

The automatic generation of Floyd production syntactic analyzers /

"September 9, 1969."

Direct support and general support maintenance repair parts and special tools list for spectrum analyzers TS-723/U, TS-723A/U, TS-723B/U, TS-723C/U, and TS-723D/U (NSN 6625-00-668-9418).

"June 1976."

Operator's, organizational, direct support, and general support maintenance manual : spectrum analyzers TS-723A/U, TS-723B/U, TS-723C/U, and TS-723D/U (NSN 6625-00-668-9418).

"January 1976."

Wavefront analyzers induce instrument myopia

PURPOSE: To assess the accuracy of three wavefront analyzers versus a validated binocular open-view autorefractor in determining refractive error in non-cycloplegic eyes. METHODS: Eighty eyes were examined using the SRW-5000 open-view infrared autorefractor and, in randomized sequence, three wavefront analyzers: 1) OPD-Scan (NIDEK, Gamagori, Japan), 2) WASCA (Zeiss/Meditec, Jena, Germany), and 3) Allegretto (WaveLight Laser Technologies AG, Erlangen, Germany). Subjects were healthy adults (19 men and 21 women; mean age: 20.8 +/- 2.5 years). Refractive errors ranged from +1.5 to -9.75 diopters (D) (mean: +1.83 +/- 2.74 D) with up to 1.75 D cylinder (mean: 0.58 +/- 0.53 D). Three readings were collected per instrument by one examiner without anticholinergic agents. Refraction values were decomposed into vector components for analysis, resulting in mean spherical equivalent refraction (M) and J0 and J45 being vectors of cylindrical power at 0 degrees and 45 degrees, respectively. RESULTS: Positive correlation was observed between wavefront analyzers and the SRW-5000 for spherical equivalent refraction (OPD-Scan, r=0.959, P<.001; WASCA, r=0.981, P<.001; Allegretto, r=0.942, P<.001). Mean differences and limits of agreement showed more negative spherical equivalent refraction with wavefront analyzers (OPD-Scan, 0.406 +/- 0.768 D [range: 0.235 to 0.580 D] [P<.001]; WASCA, 0.511 +/- 0.550 D [range: 0.390 to 0.634 D] [P<.001]; and Allegretto, 0.434 +/- 0.904 D [range: 0.233 to 0.635 D] [P<.001]). A second analysis eliminating outliers showed the same trend but lower differences: OPD-Scan (n=75), 0.24 +/- 0.41 D (range: 0.15 to 0.34 D) (P<.001); WASCA (n=78), 0.46 +/- 0.47 D (range: 0.36 to 0.57 D) (P<.001); and Allegretto (n=77), 0.30 +/- 0.62 D (range: 0.16 to 0.44 D) (P<.001). No statistically significant differences were noted for J0 and J45. CONCLUSIONS: Wavefront analyzer refraction resulted in 0.30 D more myopia compared to SRW-5000 refraction in eyes without cycloplegia. This is the result of the accommodation excess attributable to instrument myopia. For the relatively low degrees of astigmatism in this study (<2.0 D), good agreement was noted between wavefront analyzers and the SRW-5000. Copyright (C) 2006 SLACK Incorporated

Assessment of Two Diabetes Point-of-Care Analyzers Measuring Hemoglobin A1c in the Peruvian Amazon

Aims: Measurement of glycated hemoglobin (HbA1c) is an important indicator of glucose control over time. Point-of-care (POC) devices allow for rapid and convenient measurement of HbA1c, greatly facilitating diabetes care. We assessed two POC analyzers in the Peruvian Amazon where laboratory-based HbA1c testing is not available.

Methods: Venous blood samples were collected from 203 individuals from six different Amazonian communities with a wide range of HbA1c, 4.4-9.0% (25-75 mmol/mol). The results of the Afinion AS100 and the DCA Vantage POC analyzers were compared to a central laboratory using the Premier Hb9210 high-performance liquid chromatography (HPLC) method. Imprecision was assessed by performing 14 successive tests of a single blood sample.

Results: The correlation coefficient r for POC and HPLC results was 0.92 for the Afinion and 0.93 for the DCA Vantage. The Afinion generated higher HbA1c results than the HPLC (mean difference = +0.56% [+6 mmol/mol]; p < 0.001), as did the DCA Vantage (mean difference = +0.32% [4 mmol/mol]). The bias observed between POC and HPLC did not vary by HbA1c level for the DCA Vantage (p = 0.190), but it did for the Afinion (p < 0.001). Imprecision results were: CV = 1.75% for the Afinion, CV = 4.01% for the DCA Vantage. Sensitivity was 100% for both devices, specificity was 48.3% for the Afinion and 85.1% for the DCA Vantage, positive predictive value (PPV) was 14.4% for the Afinion and 34.9% for the DCA Vantage, and negative predictive value (NPV) for both devices was 100%. The area under the receiver operating characteristic (ROC) curve was 0.966 for the Afinion and 0.982 for the DCA Vantage. Agreement between HPLC and POC in classifying diabetes and prediabetes status was slight for the Afinion (Kappa = 0.12) and significantly different (McNemar’s statistic = 89; p < 0.001), and moderate for the DCA Vantage (Kappa = 0.45) and significantly different (McNemar’s statistic = 28; p < 0.001).

Conclusions: Despite significant variation of HbA1c results between the Afinion and DCA Vantage analyzers compared to HPLC, we conclude that both analyzers should be considered in health clinics in the Peruvian Amazon for therapeutic adjustments if healthcare workers are aware of the differences relative to testing in a clinical laboratory. However, imprecision and bias were not low enough to recommend either device for screening purposes, and the local prevalence of anemia and malaria may interfere with diagnostic determinations for a substantial portion of the population.

Bipolar Disorder: Recent Advances And Future Trends In Bioanalytical Developments For Biomarker Discovery.

In this manuscript we briefly describe bipolar disorder (a depressive and manic mental disease), its classification, its effects on the patient, which sometimes include suicidal tendencies, and the drugs used for treatment. We also address the status quo with regard to diagnosis of bipolar disorder and recent advances in bioanalytical approaches for biomarker discovery. These approaches focus on blood samples (serum and plasma) and proteins as the main biomarker targets, and use various strategies for protein depletion. Strategies include use of commercially available kits or other homemade strategies and use of classical proteomics methods for protein identification based on bottom-up or top-down approaches, which used SELDI, ESI, or MALDI as sources for mass spectrometry, and up-to-date mass analyzers, for example Orbitrap. We also discuss some future objectives for treatment of this disorder and possible directions for the correct diagnosis of this still-unclear mental illness.

Eletroforese capilar acoplada à espectrometria de massas (CE-MS): vinte anos de desenvolvimento

CE-MS has been increasingly used for analysis of a vast array of compounds. This article reviews the different electrophoretic modes, interfaces and mass analyzers that are commonly used in the CE-MS coupling, as well as the technique advantages and performance characteristics. A large compilation of CE-MS applications is also presented. Therefore, this review is both a guide for beginners and a collection of key references for people who are familiar to the technique. Furthermore, this is the first CE-MS review published in a Brazilian journal and marks the installation of the first two commercial CE-MS units in Sao Paulo State.

Influence of a light meal on routine haematological tests

Introduction Patient-related variables such as physical exercise stress and fasting status are Important sources of variability in laboratory testing However no clear indications about tasting requirements exist for routine haematological tests nor has the influence of meals been assessed Methods We studied 17 healthy volunteers who consumed a light meal containing a standardized amount of carbohydrates, protein and lipids Blood was taken for routine haematological tests before the meal and 1 2 and 4 hours thereafter Results One hour after the meal neutrophil count and mean corpuscular haemoglobin (MHC) increased significantly whereas lymphocyte and monocyte counts red blood cell distribution width, haematocrit, and mean corpuscular volume decreased significantly A clinically significant variation was only observed for lymphocytes Two hours after the meal a significant increase was observed for neutrophils and MCH whereas lymphocytes eosinophils, haemoglobin and haematocrit decreased significantly Clinically significant variations were recorded for lymphocytes red blood cells (RBC), haemoglobin haematocrit and MCH Four hours after the meal MCH was significantly increased while lymphocytes eosinophils, RBC, haemoglobin and haematocrit were significantly decreased Clinically significant variations were recorded for neutrophils eosinophils RBC hematocrit and MCH Conclusion The significant variation of several haematological parameters after a light meal demonstrates that the fasting time needs to be carefully considered in order to interpret the results of haematological tests correctly

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.