Behavioral Assessment of Core ADHD Symptoms Using the QbTest

Objective: Hyperactivity, one of the core symptoms of ADHD, has been mostly neglected in neuropsychological assessment of childhood ADHD. The neuropsychological Quantified behavior Test (QbTest) separately assesses all three core symptoms of ADHD on a behavioral level. Factor structure of the QbTest and its concurrent and discriminant validity are presented. Method: An exploratory factor analysis (n = 828 children) was performed. In a second sample (n = 102 children) a Multi-Trait-Multi-Method (MTMM) approach was used for validity analyses. Results: A three factorial model explained 76 % of the total variance, with the resulting QbTest factors significantly influenced by age and gender. The MTMM approach yielded promising results for discriminant, yet inconsistent findings for concurrent validity between the QbTest and another attention test as well as for Conners' Parent and Teacher Rating Scales. Conclusion: Results indicate that the QbTest may be helpful for the behavioral assessment of childhood ADHD, yet further studies on its psychometric quality and clinical utility are needed. (J. of Att. Dis. 2012; XX(X) 1-XX).

A multi-model comparison of Atlantic multidecadal variability

A multi-model analysis of Atlantic multidecadal variability is performed with the following aims: to investigate the similarities to observations; to assess the strength and relative importance of the different elements of the mechanism proposed by Delworth et al. (J Clim 6:1993–2011, 1993) (hereafter D93) among coupled general circulation models (CGCMs); and to relate model differences to mean systematic error. The analysis is performed with long control simulations from ten CGCMs, with lengths ranging between 500 and 3600 years. In most models the variations of sea surface temperature (SST) averaged over North Atlantic show considerable power on multidecadal time scales, but with different periodicity. The SST variations are largest in the mid-latitude region, consistent with the short instrumental record. Despite large differences in model configurations, we find quite some consistency among the models in terms of processes. In eight of the ten models the mid-latitude SST variations are significantly correlated with fluctuations in the Atlantic meridional overturning circulation (AMOC), suggesting a link to northward heat transport changes. Consistent with this link, the three models with the weakest AMOC have the largest cold SST bias in the North Atlantic. There is no linear relationship on decadal timescales between AMOC and North Atlantic Oscillation in the models. Analysis of the key elements of the D93 mechanisms revealed the following: Most models present strong evidence that high-latitude winter mixing precede AMOC changes. However, the regions of wintertime convection differ among models. In most models salinity-induced density anomalies in the convective region tend to lead AMOC, while temperature-induced density anomalies lead AMOC only in one model. However, analysis shows that salinity may play an overly important role in most models, because of cold temperature biases in their relevant convective regions. In most models subpolar gyre variations tend to lead AMOC changes, and this relation is strong in more than half of the models.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Acurácia da seleção simultânea para caracteres de interesse em milho tropical de segunda safra

O milho de segunda safra, também conhecido como milho safrinha, é definido como aquele semeado entre os meses de janeiro e março. Esta modalidade de cultivo atingiu no ano agrícola de 2013/2014 uma área plantada de 9,18 milhões de hectares, superior a área cultivada com milho primeira safra, que no mesmo período foi de 6,61 milhões de hectares. Na segunda safra, há alto risco de instabilidades climáticas, principalmente em decorrência de baixas temperaturas, geadas, má distribuição de chuvas e redução do fotoperíodo. Todos estes fatores prejudicam a atividade fotossintética do milho, reduzindo sua produtividade. No entanto, dada a importância deste cultivo, empresas públicas, privadas e universidades vêm buscando incrementar a produtividade e a estabilidade. Para isso, alguns caracteres são especialmente preconizados. Devido ao alto risco de perda por adversidades ambientais, muitos produtores investem pouco em adubação, principalmente adubação nitrogenada. Neste contexto, o desenvolvimento de plantas mais eficientes no uso e, ou, tolerantes ao estresse por nitrogênio, resultaria em maior segurança para o produtor. Não obstante, a precocidade tem elevada importância, já que materiais precoces reduzem o risco de perdas neste período. No entanto, a mesma deve estar sempre associada a alta produtividade. Assim, para a seleção simultânea destes caracteres, pode-se lançar mão de índices per se de resposta das plantas ao estresse, análises gráficas e, ou, índices de seleção simultânea. Adicionalmente, os valores genotípicos das linhagens para essas características, além de serem preditos via REML/BLUP single-trait (análise univariada), também podem ser preditos via REML/BLUP multi-trait (análise multivariada). Dessa forma, os valores genotípicos são corrigidos pela covariância existente entre os caracteres. Assim, o objetivo deste trabalho foi verificar a possibilidade de seleção simultânea para eficiência no uso e tolerância ao estresse por nitrogênio, além de plantas precoces e produtivas. Para isto, linhagens de milho tropical foram cultivadas e avaliadas para estes caracteres. Foram então simulados diversos cenários de seleção simultânea. A partir destes resultados, observou-se que o índice per se de resposta das plantas ao estresse Média Harmônica da Performance Relativa (MHPR) foi o mais eficiente na seleção de plantas eficientes no uso e tolerantes ao estresse por nitrogênio. Isto ocorreu devido a forte correlação desfavorável entre os índices que estimam a eficiência e a tolerância, além da superioridade e em acurácia, herdabilidade e ganhos com a seleção deste índice per se. Já para a seleção simultânea da produtividade e precocidade, o índice Aditivo de seleção simultânea, utilizando os valores genotípicos preditos via REML/BLUP single-trait se mostrou o mais eficiente, já que obteve ganhos satisfatórios em todos os caracteres e há a possibilidade de modular, de forma mais satisfatória, os ganhos em cada caractere. Conclui-se que a seleção simultânea tanto para eficiência no uso e tolerância ao estresse por nitrogênio, quanto para produtividade e precocidade são possíveis. Além disso, a escolha do melhor método de seleção simultânea depende da magnitude e do sentido da correlação entre os caracteres.

On-line microwave-based preconcentration device for inductively coupled plasma atomic emission spectrometry: Application to the elemental analysis of spirit samples

A microwave-based thermal nebulizer (MWTN) has been employed for the first time as on-line preconcentration device in inductively coupled plasma atomic emission spectrometry (ICP-AES). By the appropriate selection of the experimental conditions, the MWTN could be either operated as a conventional thermal nebulizer or as on-line analyte preconcentration and nebulization device. Thus, when operating at microwave power values above 100 W and highly concentrated alcohol solutions, the amount of energy per solvent mass liquid unit (EMR) is high enough to completely evaporate the solvent inside the system and, as a consequence, the analyte is deposited (and then preconcentrated) on the inner walls of the MWTN capillary. When reducing the EMR to the appropriate value (e.g., by reducing the microwave power at a constant sample uptake rate) the retained analyte is swept along by the liquid-gas stream and an analyte-enriched aerosol is generated and next introduced into the plasma cell. Emission signals obtained with the MWTN operating in preconcentration-nebulization mode improved when increasing preconcentration time and sample uptake rate as well as when decreasing the nozzle inner diameter. When running with pure ethanol solution at its optimum experimental conditions, the MWTN in preconcentration-nebulization mode afforded limits of detection up to one order of magnitude lowers than those obtained operating the MWTN exclusively as a nebulizer. To validate the method, the multi-element analysis (i.e. Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Pb and Zn) of different commercial spirit samples in ICP-AES has been performed. Analyte recoveries for all the elements studied ranged between 93% and 107% and the dynamic linear range covered up to 4 orders of magnitude (i.e. from 0.1 to 1000 μg L−1). In these analysis, both MWTN operating modes afforded similar results. Nevertheless, the preconcentration-nebulization mode permits to determine a higher number of analytes due to its higher detection capabilities.

Chemical analysis of powdered metallurgical slags by X-ray fluorescence spectrometry

Slag composition determines the physical and chemical properties as well as the application performance of molten oxide mixtures. Therefore, it is necessary to establish a routine instrumental technique to produce accurate and precise analytical results for better process and production control. In the present paper, a multi-component analysis technique of powdered metallurgical slag samples by X-ray Fluorescence Spectrometer (XRFS) has been demonstrated. This technique provides rapid and accurate results, with minimum sample preparation. It eliminates the requirement for a fused disc, using briquetted samples protected by a layer of Borax(R). While the use of theoretical alpha coefficients has allowed accurate calibrations to be made using fewer standard samples, the application of pseudo-Voight function to curve fitting makes it possible to resolve overlapped peaks in X-ray spectra that cannot be physically separated. The analytical results of both certified reference materials and industrial slag samples measured using the present technique are comparable to those of the same samples obtained by conventional fused disc measurements.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

Development and evaluation of an ion induced x-ray emission system for the analysis of light and medium weight elements

The present work describes the development of a proton induced X-ray emission (PIXE) analysis system, especially designed and builtfor routine quantitative multi-elemental analysis of a large number of samples. The historical and general developments of the analytical technique and the physical processes involved are discussed. The philosophy, design, constructional details and evaluation of a versatile vacuum chamber, an automatic multi-sample changer, an on-demand beam pulsing system and ion beam current monitoring facility are described.The system calibration using thin standard foils of Si, P, S,Cl, K, Ca, Ti, V, Fe, Cu, Ga, Ge, Rb, Y and Mo was undertaken at proton beam energies of 1 to 3 MeV in steps of 0.5 MeV energy and compared with theoretical calculations. An independent calibration check using bovine liver Standard Reference Material was performed.  The minimum detectable limits have been experimentally determined at detector positions of 90° and 135° with respect to the incident beam for the above range of proton energies as a function of atomic number Z. The system has detection limits of typically 10- 7 to 10- 9 g for elements 14analysis and calculations of areal density of thin foils using Rutherford backscattering data.  Amniotic fluid samples supplied by South Sefton Health Authority were successfully analysed for their low base line elemental concentrations. In conclusion the findings of this work are discussed with suggestions for further work .

Elemental analysis and forensic comparison of soils by laser-induced breakdown spectroscopy (LIBS) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS)

The elemental analysis of soil is useful in forensic and environmental sciences. Methods were developed and optimized for two laser-based multi-element analysis techniques: laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS). This work represents the first use of a 266 nm laser for forensic soil analysis by LIBS. Sample preparation methods were developed and optimized for a variety of sample types, including pellets for large bulk soil specimens (470 mg) and sediment-laden filters (47 mg), and tape-mounting for small transfer evidence specimens (10 mg). Analytical performance for sediment filter pellets and tape-mounted soils was similar to that achieved with bulk pellets. An inter-laboratory comparison exercise was designed to evaluate the performance of the LA-ICP-MS and LIBS methods, as well as for micro X-ray fluorescence (μXRF), across multiple laboratories. Limits of detection (LODs) were 0.01-23 ppm for LA-ICP-MS, 0.25-574 ppm for LIBS, 16-4400 ppm for μXRF, and well below the levels normally seen in soils. Good intra-laboratory precision (≤ 6 % relative standard deviation (RSD) for LA-ICP-MS; ≤ 8 % for μXRF; ≤ 17 % for LIBS) and inter-laboratory precision (≤ 19 % for LA-ICP-MS; ≤ 25 % for μXRF) were achieved for most elements, which is encouraging for a first inter-laboratory exercise. While LIBS generally has higher LODs and RSDs than LA-ICP-MS, both were capable of generating good quality multi-element data sufficient for discrimination purposes. Multivariate methods using principal components analysis (PCA) and linear discriminant analysis (LDA) were developed for discriminations of soils from different sources. Specimens from different sites that were indistinguishable by color alone were discriminated by elemental analysis. Correct classification rates of 94.5 % or better were achieved in a simulated forensic discrimination of three similar sites for both LIBS and LA-ICP-MS. Results for tape-mounted specimens were nearly identical to those achieved with pellets. Methods were tested on soils from USA, Canada and Tanzania. Within-site heterogeneity was site-specific. Elemental differences were greatest for specimens separated by large distances, even within the same lithology. Elemental profiles can be used to discriminate soils from different locations and narrow down locations even when mineralogy is similar.