The ART of performance: engaging young people with assisted reproductive technologies

More children than ever before are conceived with the use of assisted reproductive technologies and many are raised in families that are structurally different from most. Research on the experiences of children growing up in diverse families has shown that children may face disapproval, a lack of understanding, and in some cases, bullying by those outside of their home environment, including from their peers at school This study evaluated the use of theatrical performance and post-performance discussions as a method of informing young people about different families. Findings indicated that performance was an effective and engaging learning tool, as it presented first-hand experiences of family diversity. Post-performance discussions were important in enabling young people to improve their understanding of different methods of Assisted Reproductive Technologies and diverse family forms. Young people were found to value engagement activities that are unbiased, interactive, and do not make them feel awkward or uncomfortable

Sagittal Abdominal Diameter As A Surrogate Marker Of Insulin Resistance In An Admixtured Population-brazilian Metabolic Syndrome Study (brams)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Background Sagittal abdominal diameter (SAD) has been proposed as a surrogate marker of insulin resistance (IR). However, the utilization of SAD requires specific validation for each ethnicity. We aimed to investigate the potential use of SAD, compared with classical anthropometrical parameters, as a surrogate marker of IR and to establish the cutoff values of SAD for screening for IR. Methods A multicenter population survey on metabolic disorders was conducted. A race-admixtured sample of 824 adult women was assessed. The anthropometric parameters included: BMI, waist circumference (WC), waist-to-hip ratio and SAD. IR was determined by a hyperglycemic clamp and the HOMA-IR index. Results After adjustments for age and total body fat mass, SAD (r = 0.23 and r = -0.70) and BMI (r = 0.20 and r = -0.71) were strongly correlated with the IR measured by the HOMA-IR index and the clamp, respectively (p < 0.001). In the ROC analysis, the optimal cutoff for SAD in women was 21.0 cm. The women with an increased SAD presented 3.2 (CI 95%: 2.1-5.0) more likelihood of having IR, assessed by the HOMA-IR index compared with those with normal SAD (p < 0.001); whereas women with elevated BMI and WC were 2.1 (95% CI: 1.4-3.3) and 2.8 (95% CI: 1.7-4.5) more likely to have IR (p < 0.001), respectively. No statistically significant results were found for waist-to-hip ratio. Conclusions SAD can be a suitable surrogate marker of IR. Understanding and applying routine and simplified methods is essential because IR is associated with an increased risk of obesity-related diseases even in the presence of normal weight, slight overweight, as well as in obesity. Further prospective analysis will need to verify SAD as a determinant of clinical outcomes, such as type 2 diabetes and cardiovascular events, in the Brazilian population.105Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)CNPq [563664/2010-0

Soil classification from visible/near-infrared diffuse reflectance spectra at multiple depths.

Abstract : Visible/near-infrared diffuse reflectance spectroscopy (VNIRS) offers an alternative to conventional analytical methods to estimate various soil attributes. However, the use of VNIRS in soil survey and taxonomic classification is still underexplored. We investigated the potential use of VNIRS to classify soils in a region with variable soils, geology, and topography in southeastern Brazil. We combined principal component (PC) analysis, and multinomial logistic regression to classify 291 soils at the levels of suborder (second highest), and suborder with textural classification (STC), described in the field according to the Brazilian Soil Classification System. Soil visible/near-infrared (400-2500 nm) spectra were collected from three depth intervals (0-20, 40-60, and 80-100 cm), and combined in sequence to compose a pseudo multi-depth spectral curve, which was used to derive the classification models. The percent of correctly classified soils at the suborder level was 79% using 20 PCs, and 96% using 30 PCs. At the STC level, soils were correctly classified in 100%, and 78% of the cases using 20, and 30 PCs, respectively. Given the inherent complexity and variability within soil taxonomic groups, and in contrast the similarity among different groups, combining spectral data from different depths in multivariate classification offered a simple and inexpensive solution to adequately distinguish soils. This novel approach could improve soil classification and survey in a cost-efficient manner, supporting sustainable use, and management of tropical soils

Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the Central Amazon.

Visible and near-infrared diffuse reflectance spectroscopy (VIS-NIR) has shown levels of accuracy comparable to conventional laboratory methods for estimating soil properties. Soil chemical and physical properties have been predicted by reflectance spectroscopy successfully on subtropical and temperate soils, whereas soils from tropical agro-forest regions have received less attention, especially those from tropical rainforests. A spectral characterization provides a proficient pathway for soil characterization. The first step in this process is to develop a comprehensive VIS-NIR soil library of multiple key soil properties to be used in future soil surveys. This paper presents the first VIS-NIR soil library for a remote region in the Central Amazon. We evaluated the performance of VIS-NIR for the prediction of soil properties in the Central Amazon, Brazil. Soil properties measured and predicted were: pH, Ca, Mg, Al, H, H+Al, P, organic C (SOC), sum of bases, cation exchange capacity (CEC), percentage of base saturation (V), Al saturation (m), clay, sand, silt, silt/clay (S/C), and degree of flocculation. Soil samples were scanned in the laboratory in the VIS-NIR range (350-2500 nm), and forty-one pre-processing methods were tested to improve predictions. Clay content was predicted with the highest accuracy, followed by SOC. Sand, S/C, H, Al, H+Al, CEC, m and V predictions were reasonably good. The other soil properties were poorly predicted. Among the soil properties predicted well, SOC is one of the critical soil indicators in the global carbon cycle. Besides the soil property of interest, the landscape position, soil order and depth influenced in the model performance. For silt content, pH and S/C, the model performed better in well-drained soils, whereas for SOC best predictions were obtained in poorly drained soils. The association of VIS-NIR spectral data to landforms, vegetation classes, and soil types demonstrate potential for soil characterization

Treinamento em mapeamento digital de solos: carbono no Rio de Janeiro, Brasil.

No período de 24 a 28 de setembro de 2012 foi realizado na Embrapa Solos, Rio de Janeiro, RJ, o Curso de Capacitación en Cartografía Digital de Suelos, que contou com a presença de 17 pedólogos de 17 países da América Latina e Caribe. O objetivo do curso foi capacitar os pedólogos em mapeamento digital de solos utilizando os softwares livres SAGA, R e RStudio. No curso realizou-se, como estudo de caso, o mapeamento do carbono orgânico do solo na camada 0-10 cm no município de Campos dos Goytacazes, RJ, Brasil. Apresentamos as etapas de treinamento realizadas durante o curso, incluindo a preparação de dados de solos e covariáveis ambientais, análise exploratória de dados, modelagem espacial, produção de mapas e validação dos resultados obtidos. A combinação dos softwares livres SAGA, R e RStudio mostrou-se bastante flexível para a realização do curso e mapeamento digital de carbono orgânico do solo, sendo recomendada para outros cursos e projetos de mapeamento digital de solos. A estrutura do curso mostrou-se adequada também para implementação através de ensino à distância (resultados apresentados em outro trabalho nestes anais). Para êxito de cursos e projetos similares, salientamos a importância da experiência prévia dos participantes com conceitos e técnicas de pedologia, estatística, geoprocessamento e linguagem de programação, bem como da existência de um banco de dados de solos organizado e disponível

Treinamento presencial e à distância em mapeamento digital de solos para latinoamericanos.

A produção de informação de solos é demorada e custosa, sendo essa informação essencial para a agricultura, gerenciamento dos recursos naturais, simulações dos efeitos das mudanças climáticas, entre outros. O mapeamento digital de solos (MDS) tem avançado como metodologia complementar ao levantamento clássico de solos buscando soluções rápidas e eficazes para o mapeamento de solos, utilizando dados auxiliares (covariáveis) e métodos estatísticos e matemáticos. Nesse contexto, a Embrapa Solos realizou, através de um acordo firmado com a Organização das Nações Unidas para a Alimentação e a Agricultura (FAO), cursos de capacitação em MDS para técnicos de 18 países da América Latina e Caribe (LAC). Foram oferecidos dois cursos presenciais nas instalações da Embrapa Solos, no Rio de Janeiro, RJ, Brasil, e um curso à distância, onde foram empregados softwares livres para preparação e análise de dados (SAGA, R e RStudio), criação de vídeo (CamStudio e iSpring) e ensino à distância (Moodle). Os cursos tiveram conteúdo teórico-prático, tendo sido realizado como estudo de caso no primeiro curso presencial o mapeamento digital de carbono do solo (cujos resultados são apresentados em outro trabalho nestes anais). Este trabalho apresenta a experiência desenvolvida pela Embrapa Solos e os principais resultados do esforço para capacitar, presencialmente e à distância, técnicos de diferentes países da LAC em MDS

Enhancing digital soil mapping in southeastern Brazil: incorporating stream density and soil reflectance from multiple depths.

This study proposes a novel and simple method to incorporate laboratory soil spectral data in the production of digital soil maps

Identifying and correcting oblique striping in the topodata digital elevation model.

The Topodata digital elevation model (DEM) is the best DEM available for digital soil mapping (DSM) in Brazil. However, it is not ready to use. We show that the kriging interpolator used to downscale the SRTM DEM from 3 arc-seconds to 1 arc-second spatial resolution increased the double oblique striping (15º and 60º) so common to SRTM DEMs. This is because kriging is quite sensitive to outliers. Besides, the Gaussian model of spatial covariance used in the downscaling enhanced the sensitivity of kriging to outliers, thus enhancing the striping. 2D Fast Fourier Transform can be used to identify whether a destriping procedure need to be employed. The bilinear or cubic resampling methods should be used to warp Topodata DEMs because they are insensitive to the double oblique striping

Influence of the spatial extent and resolution of input data on soil carbon models in Florida, USA.

Understanding the causes of spatial variation of soil carbon (C) has important implications for regional and global C dynamics studies. Soil C predictive models can identify sources of C variation, but may be influenced by scale parameters, including the spatial extent and resolution of input data. Our objective was to investigate the influence of these scale parameters on soil C spatial predictive models in Florida, USA. We used data from three nested spatial extents (Florida, 150,000 km2; Santa Fe River watershed, 3,585 km2; and University of Florida Beef Cattle Station, 5.58 km2) to derive stepwise linear models of soil C as a function of 24 environmental properties. Models were derived within the three extents and for seven resolutions (30?1920 m) of input environmental data in Florida and in the watershed, then cross-evaluated among extents and resolutions, respectively. The quality of soil C models increased with an increase in the spatial extent (R2 from 0.10 in the cattle station to 0.61 in Florida) and with a decrease in the resolution of input data (R2 from 0.33 at 1920-m resolution to 0.61 at 30-m resolution in Florida). Soil and hydrologic variables were the most important across the seven resolutions both in Florida and in the watershed. The spatial extent and resolution of environmental covariates modulate soil C variation and soil-landscape correlations influencing soil C predictive models. Our results provide scale boundaries to observe environmental data and assess soil C spatial patterns, supporting C sequestration, budgeting and monitoring programs