Characterization of functional single jersey knitted fabrics using non-conventional yarns for sportswear

Eight functional single jersey plain knitted fabrics have been developed in order to assess a quantitative analysis of various comfort-related properties in terms of thermal control, air and water vapor permeability, wickability, coefficient of kinetic friction and antimicrobial efficiency, using eight different commercially available functional yarns: Polyester Craque and viscose Craque conventional yarns as controls; Finecool and Coolmax polyester yarns for moisture management and quick drying; Holofiber polyester yarns containing an optical responsive material that the producer claims to improve body oxygenation; Airclo polyester hollow yarns for efficient control of body temperature; and, finally, polyester Trevira and viscose Seacell for antimicrobial activity. According to the results, Coolmax for moisture management, Airclo for thermal control and Seacell for antimicrobial activity present the best performances as technical textiles for sportswear for the respective specific functional property.The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Jefferson M Souza acknowledges CAPES Foundation, Ministry of Education of Brazil (Proc. n 8976/13-9). Andrea Zille acknowledges FCT funding from Programa Compromisso para a Ciência 2008, Portugal, FEDER funding from the Programa Operacional Factores de Competitividade-COMPETE and national funds through FCT – Foundation for Science and Technology within the scope of the projects POCI-01-0145-FEDER-007136 and UID/CTM/00264

Imaging in population science: cardiovascular magnetic resonance in 100,000 participants of UK Biobank - rationale, challenges and approaches

PMCID: PMC3668194SEP was directly funded by the National Institute for Health Research Cardiovascular Biomedical Research Unit at Barts. SN acknowledges support from the Oxford NIHR Biomedical Research Centre and from the Oxford British Heart Foundation Centre of Research Excellence. SP and PL are funded by a BHF Senior Clinical Research fellowship. RC is supported by a BHF Research Chair and acknowledges the support of the Oxford BHF Centre for Research Excellence and the MRC and Wellcome Trust. PMM gratefully acknowledges training fellowships supporting his laboratory from the Wellcome Trust, GlaxoSmithKline and the Medical Research Council

Acute Toxicity and Determination of the Active Constituents of Aqueous Extract of Uncaria tomentosa

Uncaria tomentosa is a medicinal plant used in folk medicine by Amazon tribes. In this study the constituents of aqueous extract of U. tomentosa bark were quantified by chromatographic technique and its lethal concentration 50 (48 h) in Hyphessobrycon eques was determined. The chromatography showed high levels of oxindole alkaloids, quinovic acid glycosides, and low molecular weight polyphenols. The CL50 48 h was 1816 mg/L. Fish showed behavior changes at concentrations above 2000 mg/L, accompanied by a significant decrease of dissolved oxygen. At the highest concentration 100% mortality was observed attributed to oxygen reduction by the amount of oxindole alkaloids, polyphenols accumulation of the extract in the gills, and the interaction of these compounds with dopamine. In conclusion, the aqueous extract of U. tomentosa did not alter the chemical components and it was shown that U. tomentosa has low toxicity to H. eques; therefore, it can be used safely in this species

Segmentação Semântica de Medidores de Energia Elétrica e Componentes de Identificação / Semantic Segmentation of Electricity Meters and Identification Components

A Agência Nacional de Energia Elétrica (ANEEL) classifica erros de medição de consumo e processamento de fatura como perdas não-técnicas.  Quando essas irregularidades são identificadas, ´e solicitada a aquisição da imagem do medidor e a captura da localização geográfica do leiturista para registrar a sua presença no local. Essas imagens são enviadas para o setor de auditoria. Este recebe um grande volume de imagens, cuja análise completa é muito lenta. Como alternativa, tem-se a autoleitura, que é a leitura feita pelo próprio cliente através de plataformas digitais. E para garantir a segurança no processo de autoleitura, é necessária uma etapa automática de validação (autoauditoria).  Este trabalho propõe um método baseado em aprendizado profundo para a segmentação semântica de medidores de energia e componentes de identificação, almejando contribuir com mais eficiência ao processo de validação de leitura.  O método apresenta mean average precision (mAP) de 73,10% para os casos em que intersection over union (IoU) ? a 0,50; 42,17% para IoU ? 0,75 e 41,28% quando IoU ? 0,99