A weed monitoring system using UAV-imagery and the Hough transform

Usually, crops require the use of herbicides as a useful manner of controlling the quality and quantity of crop production. Although there are weed-free areas, the most common approach is to broadcast herbicides entirely over crop fields, resulting in a reduction of profits and increase in environmental risks. Recently, patch spraying has allowed the use of site-specific weed management, allowing precise and timely weed maps at very early phenological stage, either by ground sampling or remote analysis. Remote imagery from piloted planes and satellites are not suitable for this purpose given their low spatial and temporal resolutions, however, unmanned aerial vehicles (UAV) represent an excellent alternative. This paper presents a new classification framework for weed monitoring via UAV showing promising results and accurate generalisation in different scenariosLos cultivos precisan del uso de herbicidas para controlar la calidad y cantidad de producción. A pesar de que las malas hierbas se distribuyen en rodales, la práctica más extendida es la fumigación de herbicidas en todo el cultivo, resultando en un aumento del coste y de riesgos mediambientales. La pulvericación por parches ha dado lugar al auge de otras técnicas de manejo de malas hierbas, permitiendo su tratamiento en un estado fenológico temprano. Las imágenes remotas de aviones pilotados o satélites no son útiles en este caso debido a su baja resolución espacial y temporal. Sin embargo, este no es el caso de los vehículos aéreos no tripulados. Este artículo presenta un nuevo método para monitorización de malas hierbas usando este tipo de vehículos, mostrando resultados prometedore

Neck circumference is associated with nutritional status in elderly nursing home residents

Objectives: Anthropometry is an easy and noninvasive method to evaluate nutritional status in institutionalized elderly people who are often bedridden. The aim of this study was to investigate the relationship between the neck circumference (NC) and nutritional status of elderly nursing home residents and to find cutoff points for NC size to identify individuals at risk of malnutrition. Methods: A cross-sectional study was developed with data collected from 352 elderly people living in five public nursing homes. Different anthropometric measures and the Mini Nutritional Assessment (MNA) were used to determine nutritional status. Receiver operating characteristic (ROC) curves were built for each anthropometric variable to determine their sensitivity and specificity for predicting the risk of malnutrition according to the MNA. Results: The mean age of the participants (59% females) was 83 years old. In total, 48.3% of women and 45.5% of men were at risk of malnutrition according to their MNA scores. All anthropometric measurements were highly intercorrelated in both men and women, indicating a high degree of collinearity. Bootstrapped linear regression was used to assess the strength of the association between an individuals’ nutritional status and their anthropometric parameters. Calf circumference and NC presented the best predictive value with the highest sensitivity for diagnosing the risk of malnutrition in both institutionalized elderly men and women. The best cutoff points of NC to identify elderly nursing home residents at risk of malnutrition were 35.2 cm for females and 37.8 cm for males. Conclusions: NC is associated with other classical anthropometric parameters and malnutrition status in elderly people living in nursing homes

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

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

Agreement between a simple dyspnea-guided treatment algorithm for stable COPD and the GOLD guidelines: A pilot study

Introduction: Guidelines recommendations for the treatment of COPD are poorly followed. This could be related to the complexity of classification and treatment algorithms. The purpose of this study was to validate a simpler dyspnea-based treatment algorithm for inhaled pharmacotherapy in stable COPD, comparing its concordance with the current Global Initiative for Obstructive Lung Disease (GOLD) guideline. Methods: We enrolled patients who had been diagnosed with COPD in three primary care facilities and two tertiary hospitals in Spain. We determined anthropometric data, forced expiratory volume in the 1st second (percent), exacerbations, and dyspnea based on the modified Medical Research Council scale. We evaluated the new algorithm based on dyspnea and exacerbations and calculated the concordance with the current GOLD recommendations. Results: We enrolled 100 patients in primary care and 150 attending specialized care in a respiratory clinic. There were differences in the sample distribution between cohorts with 41% vs 26% in grade A, 16% vs 12% in grade B, 16% vs 22% in grade C, and 27% vs 40% in grade D for primary and respiratory care, respectively (P=0.005). The coincidence of the algorithm with the GOLD recommendations in primary care was 93% and 91.8% in the respiratory care cohort. Conclusion: A simple dyspnea-based treatment algorithm for inhaled pharmacotherapy of COPD could be useful in the management of COPD patients and concurs very well with the recommended schema suggested by the GOLD initiative

Monolithic crystals for PET devices: optical coupling optimization

NOTICE: this is the author’s version of a work that was accepted for publication in Nuclear Instruments and Methods in Physics Research Section A. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Nuclear Instruments and Methods in Physics Research Section A [Volume 731, 11 December 2013, Pages 288–294] DOI 10.1016/j.nima.2013.05.049[EN] In this work we present a method to efficiently collect scintillation light when using monolithic scintillator crystals. The acceptance angle of the scintillation light has been reduced by means of optical devices reducing the border effect which typically affects continuous crystals. We have applied this procedure on gamma detectors for PET systems using both position sensitive PMTs and arrays of SiPMs. In the case of using SiPMs, this approach also helps to reduce the photosensor active area. We evaluated the method using PMTs with a variety of different crystals with thicknesses ranging from 10 to 24 mm. We found that our design allows the use of crystal blocks with a thickness of up to 18 mm without degrading the spatial resolution caused by edge effects and without a significant detriment to the energy resolution. These results were compared with simulated data. The first results of monolithic LYSO crystals coupled to an array of 256 SiPMs by means of individual optical light guides are also presented.This work was supported by the Centre for Industrial Technological Development co-funded by FEDER through the Technology Fund (DREAM Project, IDI-20110718), the Spanish Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica (I+D +I) under Grant no. FIS2010-21216-CO2-01 and the Valencian Local Government under Grant PROMETEO 2008/114.González Martínez, AJ.; Peiró, A.; Conde, P.; Hernández Hernández, L.; Moliner Martínez, L.; Orero Palomares, A.; Rodríguez-Álvarez, M.... (2013). Monolithic crystals for PET devices: optical coupling optimization. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 731:288-294. https://doi.org/10.1016/j.nima.2013.05.049S28829473

BNCT research activities at the Granada group and the project NeMeSis: Neutrons for medicine and sciences, towards an accelerator-based facility for new BNCT therapies, medical isotope production and other scientific neutron applications

The Granada group in BNCT research is currently performing studies on: nuclear and radiobiological data for BNCT, new boron compounds and a new design for a neutron source for BNCT and other applications, including the production of medical radioisotopes. All these activities are described in this report.Asociación Española Contra el Cáncer (AECC) PS16163811PORRSpanish MINECO FIS2015-69941-C2-1-PJunta de Andalucía P11-FQM-8229Campus of International Excellence BioTic P-BS-64Spanish Fundacion ACSAsociación Capitán AntonioLa Kuadrilla de IznallozSonriendo se Puede Gana

Determinants and Differences in Satisfaction with the Inhaler Among Patients with Asthma or COPD

Satisfaction with the inhaler is an important determinant of treatment adherence in patients with asthma and chronic obstructive pulmonary disease (COPD). However, few studies have compared these 2 groups to identify the factors associated with satisfaction with the inhaler. To assess and compare satisfaction with the inhaler in patients with asthma or COPD and to determine the variables associated with high inhaler satisfaction. A multicenter, cross-sectional study of 816 patients (406 with asthma and 410 with COPD) was conducted. Satisfaction was assessed with the Feeling of Satisfaction with Inhaler (FSI-10) questionnaire. All participants completed the Test of Adherence to Inhalers and either the Asthma Control Test (ACT) or the COPD Assessment Test (CAT). Overall, the asthma group was significantly more satisfied with the inhaler (mean [standard deviation] FSI-10 scores: 44.1 [6.5] vs 42.0 [7.7]; P <.001) and more satisfied on most (7 of 10; 70%) items. Patients with asthma were significantly more satisfied with the inhaler regardless of the adherence level or the type of nonadherence pattern. Younger age, good disease control (ACT ≥20 or CAT ≤10), previous inhaler training, and absence of unwitting nonadherence were all independently and significantly associated with high inhaler satisfaction. Age, disease control, and training in inhalation technique all play a more significant role than the specific diagnosis in explaining satisfaction with the device in patients with asthma and COPD. These findings underscore the need to provide better training and more active monitoring of the inhalation technique to improve patient satisfaction, treatment adherence, and clinical outcomes

Activation of pro- and anti-inflammatory responses in lung tissue injury during the acute phase of PRRSV-1 infection with the virulent strain Lena

Porcine reproductive and respiratory syndrome virus (PRRSV) plays a key role in porcine respiratory disease complex modulating the host immune response and favouring secondary bacterial infections. Pulmonary alveolar macrophages (PAMs) are the main cells supporting PRRSV replication, with CD163 as the essential receptor for viral infection. Although interstitial pneumonia is by far the representative lung lesion, suppurative bronchopneumonia is described for PRRSV virulent strains. This research explores the role of several immune markers potentially involved in the regulation of the inflammatory response and sensitisation of lung to secondary bacterial infections by PRRSV-1 strains of different virulence. Conventional pigs were intranasally inoculated with the virulent subtype 3 Lena strain or the low virulent subtype 1 3249 strain and euthanised at 1, 3, 6 and 8 dpi. Lena-infected pigs exhibited more severe clinical signs, macroscopic lung score and viraemia associated with an increase of IL-6 and IFN-γ in sera compared to 3249-infected pigs. Extensive areas of lung consolidation corresponding with suppurative bronchopneumonia were observed in Lena-infected pigs. Lung viral load and PRRSV-N-protein+ cells were always higher in Lena-infected animals. PRRSV-N-protein+ cells were linked to a marked drop of CD163+ macrophages. The number of CD14+ and iNOS+ cells gradually increased along PRRSV-1 infection, being more evident in Lena-infected pigs. The frequency of CD200R1+ and FoxP3+ cells peaked late in both PRRSV-1 strains, with a strong correlation between CD200R1+ cells and lung injury in Lena-infected pigs. These results highlight the role of molecules involved in the earlier and higher extent of lung lesions in piglets infected with the virulent Lena strain, pointing out the activation of routes potentially involved in the restraint of the local inflammatory response.info:eu-repo/semantics/acceptedVersio