Classification of red grapes according to their state of ripeness using a low-cost multispectral device

[ES] El objetivo del presente trabajo fue evaluar la idoneidad de un sensor multiespectral de bajo costo para la determinación del estado de maduración de uvas tintas. El dispositivo propuesto se basa en un sensor multiespectral, con 18 bandas de detección en el rango entre los 410 y los 940 nm. La recogida de muestras se llevó a cabo en un viñedo comercial situado en Rociana del Condado, Huelva. El dispositivo propuesto se utilizó para adquirir la respuesta espectral de 80 racimos de uva en condiciones de laboratorio. Tras esto, cada una de las muestras fue analizada mediante métodos estándar de laboratorio para obtener indicadores objetivos de su estado de maduración (sólidos solubles totales y acidez). Los 18 valores de reflectancia ofrecidos por el sensor fueron usados como datos de entrada para entrenar redes neuronales artificiales para la clasificación de las muestras de uva en función de los parámetros objetivo. Los resultados obtenidos fueron prometedores, lo cual allana el camino hacia la implementación de un sistema para la monitorización del estado de maduración de uvas asequible para los vinicultores.[EN] The present work aims to evaluate a low-cost multispectral device for non-destructive grape ripening status assessment. The proposed device is based on a multispectral sensor, with a spectral response of 18 channels in a range from 410 to 940 nm. The experimental validation was carried out in a commercial vineyard in Rociana del Condado, Huelva. The proposed device was used to analyze 80 grape samples under laboratory conditions. After being processed with the proposed device the grape samples were analyzed with standard chemical methods to generate ground truth values of ripening status indicators (solid soluble content, and acidity). The 18-reflectance data corresponding to the spectral channels of the employed sensor, were used as input variables for developing artificial neural network models to classify the berries samples based on the mentioned ripeness indicators. The obtained results were promising, which paves the way for the implementation of a portable grape ripening appraisal system affordable for grape growers

Electrical conductivity of oxidized-graphenic nanoplatelets obtained from bamboo: Effect of the oxygen content

The large-scale production of graphene and reduced-graphene oxide (rGO) requires low-cost and eco-friendly synthesis methods. We employed a new, simple, cost-effective pyrolytic method to synthetize oxidized-graphenic nanoplatelets (OGNP) using bamboo pyroligneous acid (BPA) as a source. Thorough analyses via high-resolution transmission electron microscopy and electron energy-loss spectroscopy provides a complete structural and chemical description at the local scale of these samples. In particular, we found that at the highest carbonization temperature the OGNP-BPA are mainly in a sp2 bonding configuration (sp2 fraction of 87%). To determine the electrical properties of single nanoplatelets, these were contacted by Pt nanowires deposited through focused-ion-beam-induced deposition techniques. Increased conductivity by two orders of magnitude is observed as oxygen content decreases from 17% to 5%, reaching a value of 2.3 103 S m-1 at the lowest oxygen content. Temperature-dependent conductivity reveals a semiconductor transport behavior, described by the Mott three-dimensional variable range hopping mechanism. From the localization length, we estimate a band-gap value of 0.22(2) eV for an oxygen content of 5%. This investigation demonstrates the great potential of the OGNP-BPA for technological applications, given that their structural and electrical behavior is similar to the highly reduced rGO sheets obtained by more sophisticated conventional synthesis methods

Garvicins AG1 and AG2 : two novel class IId bacteriocins of lactococcus garvieae Lg-Granada

Funding: This research was funded by the Spanish Ministry of Science, Innovation, and Universities, grant number RTI2018-098530-B-I00. The APC was funded by the Spanish Ministry of Science, Innovation, and Universities, grant number RTI2018-098530-B-I00.Lactococcus garvieae causes infectious diseases in animals and is considered an emerging zoonotic pathogen involved in human clinical conditions. In silico analysis of plasmid pLG50 of L. garvieae Lg-Granada, an isolate from a patient with endocarditis, revealed the presence of two gene clusters (orf 46–47 and orf 48–49), each one encoding a novel putative bacteriocin, i.e., garvicin AG1 (GarAG1; orf 46) and garvicin AG2 (GarAG2; orf 48), and their corresponding immunity proteins (orf 47 and orf 49). The chemically synthesised bacteriocins GarAG1 and GarAG2 presented inhibitory activity against pathogenic L. garvieae strains, with AG2 also being active against Listeria monocytogenes, Listeria ivanovii and Enterococcus faecalis. Genetic organisation, amino acid sequences and antimicrobial activities of GarAG1 and GarAG2 indicate that they belong to linear non-pediocin-like one-peptide class IId bacteriocins. Gram-positive bacteria that were sensitive to GarAG2 were also able to ferment mannose, suggesting that this bacteriocin could use the mannose phosphotransferase transport system (Man-PTS) involved in mannose uptake as a receptor in sensitive strains. Intriguingly, GarAG1 and GarAG2 were highly active against their own host, L. garvieae Lg-Granada, which could be envisaged as a new strategy to combat pathogens via their own weapons.Publisher PDFPeer reviewe

A multiscale material model for metallic powder compaction during hot isostatic pressing

The prediction of the distortions during Near-Net-Shape Hot Isostatic Pressing (NNS-HIP) is an intrinsic multiscale problem where the local interactions among particles determine the macroscopic distortions taking place during the sintering and densification of a component. In this work, a multiscale approach is proposed to solve this problem. In particular, a viscoplastic constitutive model capable of predicting macroscopic contractions during a HIP process with high accuracy has been developed, implemented and validated. The macroscopic model incorporates the mechanical behaviour predicted at the meso-scale by means of multiple-particle finite element models (MP-FEM) of an agglomerate of powder particles. The model is validated through the prediction of distortions during HIP of a full scale industrial case. It is concluded that adding the microscopic information of the HIP process to simulate the contractions at the macroscopic level results in a considerable improvement of the accuracy of the predictions

Clasificación de cultivos y de sus medidas agroambientales mediante segmentación de imágenes QuickBird

En la últimas décadas han ido creciendo considerablemente los conocimientos y la sensibilización sobre la protección al medioambiente en muy diversas áreas, entre las que se encuentra la Agricultura. El uso intensivo del laboreo ocasiona graves daños medioambientales como la erosión del suelo, la contaminación de las aguas superficiales (escorrentía y colmatación de embalses), el descenso del contenido de la materia orgánica y de la biodiversidad de los suelos labrados, y el aumento de la emisión de CO2 del suelo a la atmósfera. Actualmente, la Unión Europea sólo subvenciona a los agricultores que cumplen lo que se conoce como “Medidas Agroambientales o de Condicionalidad” cuyo diseño ha estado dentro de las competencias de las Políticas Agrarias Autonómicas, Nacionales y Europeas. Estas medidas consisten en alterar el perfil y la estructura del suelo lo menos posible, dejando éste sin labrar y permanentemente protegido por cubiertas vegetales (rastrojo) en el caso de cultivos herbáceos (ej. trigo, maíz, girasol), o por cubiertas vegetales vivas o inertes (restos de poda) en el caso de cultivos leñosos (principalmente cítricos y olivar). El seguimiento del cumplimiento de estas medidas se realiza a través de visitas presenciales a un 1% de los campos susceptibles de recibir ayudas. Este método es ineficiente y provoca muchos errores con la consiguiente presentación de un ingente número de reclamaciones. Para subsanar esta problemática, en este artículo presentamos los resultados obtenidos en la clasificación de los cultivos y las medidas agroambientales asociadas a éstos en una imagen multiespectral QuickBird tomada a principios de Julio de una zona típica de cultivos en régimen de secano de Andalucía. Se aplicaron 5 métodos de clasificación (Paralelepípedos, P; Mínima Distancia, MD; Distancia de Mahalanobis, MC; Mapeo del Ángulo Espectral, SAM; y Máxima Probabilidad, ML) para la discriminación de rastrojo de trigo quemado y sin quemar, arbolado, carreteras, olivar, cultivos herbáceos de siembra primaveral y suelo desnudo. Además, la imagen es segmentada en objetos para comparar la fiabilidad obtenida aplicando los métodos anteriores partiendo tanto de píxeles como de objetos como Unidades Mínimas de Información (MIU). El análisis de los resultados permite concluir que las clasificaciones de todos los usos de suelo basadas en objetos claramente mejoraron las basadas en píxeles, obteniéndose precisiones (overall accuracy) mayores al 85%. La elección de un método de clasificación u otro influye en gran medida en la precisión de los mapas obtenidos. Debido a que la precisión del mapa temático que necesitamos obtener ha de ser muy elevada para tomar decisiones sobre Conceder / No conceder las ayudas, sería interesante estudiar si el incremento de la resolución espacial que se obtenga gracias a la fusión de imágenes multiespectral y pancromática de QuickBird para obtener una imagen fusionada con resolución espacial de la pancromática (0.7 m) y espectral de la multiespectral (4 bandas) mejora la precisión de cualquiera de los métodos de clasificación estudiadosSoil management in crops is mainly based on intensive tillage operations, which have a great relevancy in terms of increase of atmospheric CO2, desertification, erosion and land degradation. Due to these negative environmental impacts, the European Union only subsidizes cropping systems which require the implementation of certain no-tillage systems and agro-environmental measures, such as keeping the winter cereal residues and non-burning of stubble to reduce erosion, and to increase the organic matter, the fertility of soils and the crop production. Nowadays, the follow-up of these agrarian policy actions is achieved by ground visits to sample targeted farms; however, this procedure is time-consuming and very expensive. To improve this control procedure, a study of the accuracy performance of several classification methods has been examined to verify if remote sensing can offer the ability to efficiently identify crops and their agro-environmental measures in a typical agricultural Mediterranean area of dry conditions. Five supervised classification methods based on different decision rule routines, Parallelepiped (P), Minimum Distance (MD), Mahalanobis Classifier Distance (MC), Spectral Angle Mapper (SAM), and Maximum Likelihood (ML), were examined to determine the most suitable classification algorithm for the identification of agro-environmental measures such as winter cereal stubble and burnt stubble areas and other land uses such as river side trees, vineyard, olive orchards, spring sown crops, roads and bare soil. An object segmentation of the satellite information was also added to compare the accuracy of the classification results of pixel and object as Minimum Information Unit (MIU). A multispectral QuickBird image taken in early summer was used to test these MIU and classification methods. The resulting classified images indicated that object-based analyses clearly outperformed pixel ones, yielding overall accuracies higher than 85% in most of the classifications. The choice of a classification method can markedly influence the accuracy of classification maps

Application of the Kalman filter in the processing of very noisy measurements, a case study: motorcycle dyno with aerodynamic analysis capability

[ES] En este trabajo se presenta una aplicación del filtro de Kalman para tratar medidas altamente ruidosas de cara a su empleo en un sistema de control. En concreto, el sistema con el que se ha trabajado es un banco de potencia para motocicletas al que se ha añadido un ventilador de gran potencia capaz de generar una corriente de aire a una velocidad igual a la que está desarrollando la motocicleta sobre el rodillo, permitiendo así la realización de estudios aerodinámicos. Las variables a medir se ven fuertemente afectadas por ruido generado por el inversor que alimenta el ventilador, por las interferencias provocadas por los pulsos de la bobina de alta tensión de la motocicleta o por las turbulencias de la corriente de aire en el caso del sensor de velocidad del aire. Además, teniendo en cuenta que varias de las señales a medir son pulsos que deben computarse en cada intervalo de control, también van a producirse errores que pueden considerarse ruidos del proceso. El filtro de Kalman, empleado para tratar las medidas y algunas de las variables calculadas en el algoritmo consiguen reducir el ruido de todas las variables a valores aceptables que permiten la realización de las acciones de control y trazado de curvas de potencia y par de la motocicleta

Digital image correlation after focused ion beam micro-slit drilling: A new technique for measuring residual stresses in hardmetal components at local scale

A new method has been developed for measuring residual stresses at the surface of hardmetal components with higher spatial resolution than standard X-ray diffraction methods. It is based on measuring the surface displacements produced when stresses are partially released by machining a thin slit perpendicularly to the tested surface. Slit machining is carried out by focused ion beam (FIB). Measurement of the displacement fields around the FIB slit are performed by applying an advanced digital image correlation algorithm based on Fourier analysis with sub-pixel resolution. This method compares SEM images of the same area of the hardmetal surface before and after slitting. The method has been successfully applied to as-ground and femto-laser textured surfaces showing good correlation with the standard sin2 ψ XRD technique. It is concluded that texturing induced by laser pulses in the femtoseconds regime is not perfectly adiabatic, since residual stresses are reduced by 15

Digital image correlation after focused ion beam micro-slit drilling: A new technique for measuring residual stresses in hardmetal components at local scale

A new method has been developed for measuring residual stresses at the surface of hardmetal components with higher spatial resolution than standard X-ray diffraction methods. It is based on measuring the surface dis-placements produced when stresses are partially released by machining a thin slit perpendicularly to the tested surface. Slit machining is carried out by focused ion beam (FIB). Measurement of the displacement fields around the FIB slit are performed by applying an advanced digital image correlation algorithm based on Fourier analysis with sub-pixel resolution. This method compares SEM images of the same area of the hardmetal surface before and after slitting. The method has been successfully applied to as-ground and femto-laser textured surfaces showing good correlation with the standard sin2 psi XRD technique. It is concluded that texturing induced by laser pulses in the femtoseconds regime is not perfectly adiabatic, since residual stresses are reduced by 15%

Detection of kinase domain mutations in BCR::ABL1 leukemia by ultra-deep sequencing of genomic DNA

The screening of the BCR::ABL1 kinase domain (KD) mutation has become a routine analysis in case of warning/failure for chronic myeloid leukemia (CML) and B-cell precursor acute lymphoblastic leukemia (ALL) Philadelphia (Ph)-positive patients. In this study, we present a novel DNA-based next-generation sequencing (NGS) methodology for KD ABL1 mutation detection and monitoring with a 1.0E−4 sensitivity. This approach was validated with a well-stablished RNA-based nested NGS method. The correlation of both techniques for the quantification of ABL1 mutations was high (Pearson r = 0.858, p < 0.001), offering DNA-DeepNGS a sensitivity of 92% and specificity of 82%. The clinical impact was studied in a cohort of 129 patients (n = 67 for CML and n = 62 for B-ALL patients). A total of 162 samples (n = 86 CML and n = 76 B-ALL) were studied. Of them, 27 out of 86 harbored mutations (6 in warning and 21 in failure) for CML, and 13 out of 76 (2 diagnostic and 11 relapse samples) did in B-ALL patients. In addition, in four cases were detected mutation despite BCR::ABL1 < 1%. In conclusion, we were able to detect KD ABL1 mutations with a 1.0E−4 sensitivity by NGS using DNA as starting material even in patients with low levels of disease.Tis project was funded in part by CRIS CANCER FOUNDATION