Weed mapping in early-season sunflower fields using images from an unmanned aerial vehicle (UAV)

Revista oficial de la Asociación Española de Teledetección[EN] Weed mapping in early season requires of very high spatial resolution images (pixels <5 cm). Currently only Unmanned Aerial Vehicles (UAV) can take such images. The aim of this work was to evaluate the optimal flight altitude for mapping weeds in an early season sunflower field using a low-cost camera that took images in the visible spectrum at several flight altitudes (40, 60, 80 and 100 m). The object based image analysis procedure used for weed mapping was divided in two main phases: 1) crop-row identification, and 2) crop, weed and bare soil classification. The algorithm identified the crop rows with 100% accuracy at every flight altitude (phase 1) and it detected weed-free zones with 100% accuracy in the images captured at 40 and 60 m flight altitude. In weed-infested zones, the classification algorithm obtained the best results in the images captured at low altitude (40 m), reporting 71% of correctly classified sampling frames (phase 2). Most of errors committed (incorrectly classified frames) were produced by non-detection of weeds (negative false). Subsequent studies would consist in a multi-temporal study aiming to detect weeds are at a more advance growth stage. It could reduce the percentage of negative false in the classification.[ES] La discriminación de malas hierbas en fase temprana con técnicas de teledetección requiere imágenes re-motas de muy elevada resolución espacial (píxeles <5 cm). Actualmente, sólo los vehículos aéreos no tripulados (UAV) pueden generar este tipo de imágenes. El objetivo de este trabajo fue evaluar imágenes UAV tomadas con una cámara visible a diferentes alturas de vuelo (40, 60, 80 y 100 m) y cuantificar la influencia de la resolución espacial en la discrimi-nación de malas hierbas en fase temprana en un cultivo de girasol. Se aplicó un algoritmo de clasificación de imágenes basado en objetos, el cual se divide en dos fases principales: 1) detección de líneas de cultivo y 2) clasificación de cultivo, malas hierbas y suelo desnudo. El algoritmo resultó 100% eficaz en la detección de las líneas de cultivo en todos los ca-sos (fase 1), así como en la detección de zonas libres de mala hierba en las imágenes tomadas a 40 y 60 m de altura. En las zonas con presencia de malas hierbas, los mejores resultados se obtuvieron en las imágenes tomadas a baja altura (40 m), con un 71% de marcos de muestreo clasificados correctamente (fase 2). La mayoría de los fallos de clasificación cometidos en todas las imágenes fueron falsos negativos, es decir, malas hierbas no detectadas debido a su pequeño tamaño en el momento de la captura de las imágenes. Por tanto, el siguiente paso sería desarrollar un estudio multi-temporal para estudiar la detección de las malas hierbas en estados fenológicos más avanzados. Esto podría facilitar su discriminación en las imágenes y, por tanto, disminuir el porcentaje de falsos negativos en las clasificacionesEste trabajo fue financiado por el proyecto Recupera 2020 (Ministerio de Economía y Competitividad y Fondos FEDER de la Unión Europea). La investigación de Jorge Torres Sánchez fue financiada por el programa FPI (CSIC y fondos FEDER).Peña, J.; Torres-Sánchez, J.; Serrano-Pérez, A.; López-Granados, F. (2014). Detección de malas hierbas en girasol en fase temprana mediante imágenes tomadas con un vehículo aéreo no tripulado (UAV). Revista de Teledetección. (42):39-48. doi:10.4995/raet.2014.3148SWORD39484

Hexaferrite-based permanent magnets with upper magnetic properties by cold sintering process via a non-aqueous solvent

The incessant technological pursuit towards a more sustainable and green future depends strongly on permanent magnets. At present, their use is widespread, making it imperative to develop new processing methods that generate highly competitive magnetic properties reducing the fabrication temperatures and costs. Herein, a novel strategy for developing dense sintered magnets based on Sr-hexaferrites with upper functional characteristics is presented. An innovative cold sintering approach using glacial acetic acid as novelty, followed by a post-annealing at 1100 {\deg}C, achieves a densification of the ceramic magnets of 92% with respect to the theoretical density and allows controlling the particle growth. After the cold sintering process, a fraction of amorphous SrO is identified, in addition to a partial transformation to {\alpha}-Fe2O3 as secondary crystalline phase. 46 wt% of SrFe12O19 remains, which is mostly recuperated after the post-thermal treatment. These findings do not significantly modify the final structure of ferrite magnets, neither at short- nor long-range order. The innovative process has a positive impact on the magnetic properties, yielding competitive ferrite magnets at lower sintering temperatures with an energy efficiency of at least 25%, which opens up a new horizon in the field of rare-earth free permanent magnets and new possibilities in other applications

Dos posibles recintos campamentales romanos en la provincia de Lugo: crítica y elogio de la noticia arqueológica

Here we present the evidences of two possible Roman camps located in the province of Lugo and their morphology is analysed with remote sensing and field survey. From a critical point of view, we reflect on the limitations and possibilities of archaeological news as part of the process of generating historical knowledge.Se presentan las evidencias de dos posibles recintos campamentales romanos situados en la provincia de Lugo y se analiza su morfología con medios de teledetección y prospección. Desde un punto de vista crítico, se reflexiona sobre las limitaciones y posibilidades de la noticia arqueológica como parte del proceso de generación de conocimiento histórico

Topologically protected superconducting ratchet effect generated by spin-ice nanomagnets

We have designed, fabricated and tested a robust superconducting ratchet device based on topologically frustrated spin ice nanomagnets. The device is made of a magnetic Co honeycomb array embedded in a superconducting Nb film. This device is based on three simple mechanisms: (i) the topology of the Co honeycomb array frustrates in-plane magnetic configurations in the array yielding a distribution of magnetic charges which can be ordered or disordered with in-plane magnetic fields, following spin ice rules; (ii) the local vertex magnetization, which consists of a magnetic half vortex with two charged magnetic Neel walls; (iii) the interaction between superconducting vortices and the asymmetric potentials provided by the Neel walls. The combination of these elements leads to a superconducting ratchet effect. Thus, superconducting vortices driven by alternating forces and moving on magnetic half vortices generate a unidirectional net vortex flow. This ratchet effect is independent of the distribution of magnetic charges in the array

Robust Crop and Weed Segmentation under Uncontrolled Outdoor Illumination

An image processing algorithm for detecting individual weeds was developed and evaluated. Weed detection processes included were normalized excessive green conversion, statistical threshold value estimation, adaptive image segmentation, median filter, morphological feature calculation and Artificial Neural Network (ANN). The developed algorithm was validated for its ability to identify and detect weeds and crop plants under uncontrolled outdoor illuminations. A machine vision implementing field robot captured field images under outdoor illuminations and the image processing algorithm automatically processed them without manual adjustment. The errors of the algorithm, when processing 666 field images, ranged from 2.1 to 2.9%. The ANN correctly detected 72.6% of crop plants from the identified plants, and considered the rest as weeds. However, the ANN identification rates for crop plants were improved up to 95.1% by addressing the error sources in the algorithm. The developed weed detection and image processing algorithm provides a novel method to identify plants against soil background under the uncontrolled outdoor illuminations, and to differentiate weeds from crop plants. Thus, the proposed new machine vision and processing algorithm may be useful for outdoor applications including plant specific direct applications (PSDA)

La medida de la empatía en el alumnado de la Facultad de Ciencias de la Educación de Granada

El objetivo principal de este trabajo de investigación ha sido analizar la capacidad empática de 100 universitarios de la Facultad de Ciencias de la Educación de Granada. Para ello hemos utilizado el “Interpersonal Reactivity Index” (IRI), que es uno de los cuestionarios más utilizados para evaluar esta capacidad. Este instrumento incluye dos subescalas dedicadas a factores cognitivos, la toma de perspectiva (PT) y la fantasía (FS) y otras dos a factores emocionales, la preocupación empática (EC) y el malestar personal (PD).The main aim of this research was to analyse the capacity for empathy in 100 university students from the Faculty of Education in Granada. We used the “Interpersonal Reactivity Index” (IRI), which is one of the most common instruments used to evaluate this capacity. It contains two subscales to measure cognitive factors, perspective taking (PT) and Fantasy and two subscales to measures emotional factors, empathic concern (EC) and personal distress (PD).Departamento de Psicología Socia