Blockchain y conceptos claves para el aprendizaje automático

Hoy en día todos las personas se ven ligadas a lo mecánico. A través del avance, los ingenieros de la tecnología van innovando nuevas ideas para desarrollar diferentes maquinas que conocen por su cuenta a esto se denomina aprendizaje automático, un campo que  investiga diversos modelos predictivos y algoritmos que dan las computadoras, es decir que puedan realizar tareas sin ser programados

Multiclass insect counting through deep learning-based density maps estimation

The use of digital technologies and artificial intelligence techniques for the automation of some visual assessment processes in agriculture is currently a reality. Image-based, and recently deep learning-based systems are being used in several applications. Main challenge of these applications is to achieve a correct performance in real field conditions over images that are usually acquired with mobile devices and thus offer limited quality. Plagues control is a problem to be tackled in the field. Pest management strategies relies on the identification of the level of infestation. This degree of infestation is established through a counting task manually done by the field researcher so far. Current models were not able to appropriately count due to the small size of the insects and on the last year we presented a density map based algorithm that superseded state of the art methods for a single insect type. In this paper, we extend previous work into a multiclass and multi-stadia approach. Concretely, the proposed algorithm has been tested in two use cases: on the one hand, it counts five different types of adult individuals over multiple crop leaves; and on the other hand, it identifies four different stages for immatures over 2-cm leaf disks. In these leaf disks, some of the species are in different stadia being some of them micron size and difficult to be identified even for the non-expert user. The proposed method achieves good results in both cases. The model for counting adult insects in a leaf achieves a RMSE ranging from 0.89 to 4.47, MAE ranging from 0.40 to 2.15, and R2 ranging from 0.86 to 0.91 for 4 different species in its adult phase (BEMITA, FRANOC, MYZUPE and APHIGO) that may appear together in the same leaf. Besides, for FRANOC, two stadia nymphs and adults are considered. The model developed for counting BEMITA immatures in 2-cm disks obtains R2 values up to 0.98 for big nymphs. This solution was embedded in a docker and can be accessed through an app via REST service in mobile devices. It has been tested in the wild under real conditions in different locations worldwide and over 14 different crops.The authors would like to thank all field researchers that generated the dataset, carried out the annotation process, performed the validation in the wild, and in general, supported the work in Tecnalia and BASF specially to Javier Romero, Carlos Javier Jim ́enez, Amaia Ortiz, Aitor Alvarez and Jone Echazarra

"Análisis con Google Trends y Our World in Data sobre la salud mental mundial en el contexto de la pandemia por covid-19"

"Introducción: Durante la pandemia de la covid-19 los servicios de salud mental no pudieron darse abasto debido a la gran demanda, por lo cual, muchas personas optaron por buscar información por Internet que las pudiera ayudar a sobrellevar el proceso psicológico que estaban experimentando en ese momento. Objetivo: Caracterizar la tendencia mundial de búsqueda del término «psiquiatría» en el contexto de covid-19 mediante Google Trends y Our World in Data. Métodos: Estudio descriptivo-transversal sobre las tendencias mundiales de búsquedas de información sobre psiquiatría en el contexto de la covid-19 bajo los términos «psiquiatría», «depresión», «ansiedad», «estrés», «insomnio» y «suicidio» en la categoría de salud en el periodo del 2020-2021. Se generaron gráficos temporales. Resultados: El término «psiquiatría» se mantuvo con un volumen relativo de búsqueda elevado y constante (entre 60 y 90), con una búsqueda importante y paulatina en el mes de abril. El volumen relativo de búsquedas de «depresión», «ansiedad» y «estrés» se mantuvieron constantes con ciertas fluctuaciones no significativas a lo largo del periodo 2020-2021. El término «insomnio» tuvo una predominancia entre enero y junio del 2020, fue decayendo poco a poco desde abril y se mantuvo constante hasta octubre del 2021. Finalmente, el término «suicidio» obtuvo un VRB fluctuante entre 60 y 100 durante este periodo. Conclusiones: Durante el periodo de estudio los temas relacionados con la salud mental y la especialidad de psiquiatría se mantuvieron constantes, con algunas variaciones fluctuantes pero no llamativas.

Analysis of Few-Shot Techniques for Fungal Plant Disease Classification and Evaluation of Clustering Capabilities Over Real Datasets

[EN] Plant fungal diseases are one of the most important causes of crop yield losses. Therefore, plant disease identification algorithms have been seen as a useful tool to detect them at early stages to mitigate their effects. Although deep-learning based algorithms can achieve high detection accuracies, they require large and manually annotated image datasets that is not always accessible, specially for rare and new diseases. This study focuses on the development of a plant disease detection algorithm and strategy requiring few plant images (Few-shot learning algorithm). We extend previous work by using a novel challenging dataset containing more than 100,000 images. This dataset includes images of leaves, panicles and stems of five different crops (barley, corn, rape seed, rice, and wheat) for a total of 17 different diseases, where each disease is shown at different disease stages. In this study, we propose a deep metric learning based method to extract latent space representations from plant diseases with just few images by means of a Siamese network and triplet loss function. This enhances previous methods that require a support dataset containing a high number of annotated images to perform metric learning and few-shot classification. The proposed method was compared over a traditional network that was trained with the cross-entropy loss function. Exhaustive experiments have been performed for validating and measuring the benefits of metric learning techniques over classical methods. Results show that the features extracted by the metric learning based approach present better discriminative and clustering properties. Davis-Bouldin index and Silhouette score values have shown that triplet loss network improves the clustering properties with respect to the categorical-cross entropy loss. Overall, triplet loss approach improves the DB index value by 22.7% and Silhouette score value by 166.7% compared to the categorical cross-entropy loss model. Moreover, the F-score parameter obtained from the Siamese network with the triplet loss performs better than classical approaches when there are few images for training, obtaining a 6% improvement in the F-score mean value. Siamese networks with triplet loss have improved the ability to learn different plant diseases using few images of each class. These networks based on metric learning techniques improve clustering and classification results over traditional categorical cross-entropy loss networks for plant disease identification.This project was partially supported by the Spanish Government through CDTI Centro para el Desarrollo Tecnológico e Industrial project AI4ES (ref CER-20211030), by the University of the Basque Country (UPV/EHU) under grant COLAB20/01 and by the Basque Government through grant IT1229-19

Controlling the polarization and vortex charge of attosecond high-harmonic beams via simultaneous spin–orbit momentum conservation

[EN]Optical interactions are governed by both spin and angular momentum conservation laws, which serve as a tool for controlling light–matter interactions or elucidating electron dynamics and structure of complex systems. Here, we uncover a form of simultaneous spin and orbital angular momentum conservation and show, theoretically and experimentally, that this phenomenon allows for unprecedented control over the divergence and polarization of extreme-ultraviolet vortex beams. High harmonics with spin and orbital angular momenta are produced, opening a novel regime of angular momentum conservation that allows for manipulation of the polarization of attosecond pulses—from linear to circular—and for the generation of circularly polarized vortices with tailored orbital angular momentum, including harmonic vortices with the same topological charge as the driving laser beam. Our work paves the way to ultrafast studies of chiral systems using high-harmonic beams with designer spin and orbital angular momentum.The authors are thankful for useful and productive conversations with E. Pisanty, C. Durfee, D. Hickstein, S. Alperin and M. Siemens. H.C.K. and M.M.M. graciously acknowledge support from the Department of Energy BES Award No. DE-FG02–99ER14982 for the experimental implementation, as well as a MURI grant from the Air Force Office of Scientific Research under Award No. FA9550–16–1–0121 for the theory. J.L.E., N.J.B. and Q.L.N. acknowledge support from National Science Foundation Graduate Research Fellowships (Grant No. DGE-1144083). C.H.-G., J.S.R. and L.P. acknowledge support from Junta de Castilla y León (SA046U16) and Ministerio de Economía y Competitividad (FIS2013–44174-P, FIS2016–75652-P). C.H.-G. acknowledges support from a 2017 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation. L.R. acknowledges support from Ministerio de Educación, Cultura y Deporte (FPU16/02591). A.P. acknowledges support from the Marie Sklodowska-Curie Grant, Agreement No. 702565. We thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2014–2–0085). This research made use of the high-performance computingresources of the Castilla y León Supercomputing Center (SCAYLE, www.scayle.es),financed by the European Regional Development Fund (ERDF). Certain commercial instruments are identified to specify the experimental study adequately. This does not imply endorsement by the National Institute of Standards and Technology (NIST) or that the instruments are the best available for the purpose

Total area of spontaneous portosystemic shunts independently predicts hepatic encephalopathy and mortality in liver cirrhosis

Background & Aims: Spontaneous portosystemic shunts (SPSS) frequently develop in liver cirrhosis. Recent data suggested that the presence of a single large SPSS is associated with complications, especially overt hepatic encephalopathy (oHE). However, the presence of >1 SPSS is common. This study evaluates the impact of total cross-sectional SPSS area (TSA) on outcomes in patients with liver cirrhosis. Methods: In this retrospective international multicentric study, CT scans of 908 cirrhotic patients with SPSS were evaluated for TSA. Clinical and laboratory data were recorded. Each detected SPSS radius was measured and TSA calculated. One-year survival was the primary endpoint and acute decompensation (oHE, variceal bleeding, ascites) was the secondary endpoint. Results: A total of 301 patients (169 male) were included in the training cohort. Thirty percent of all patients presented with >1 SPSS. A TSA cut-off of 83 mm2 was used to classify patients with small or large TSA (S-/L-TSA). Patients with L-TSA presented with higher model for end-stage liver disease score (11 vs. 14) and more commonly had a history of oHE (12% vs. 21%, p <0.05). During follow-up, patients with L-TSA experienced more oHE episodes (33% vs. 47%, p <0.05) and had lower 1-year survival than those with S-TSA (84% vs. 69%, p <0.001). Multivariate analysis identified L-TSA (hazard ratio 1.66; 95% CI 1.02–2.70, p <0.05) as an independent predictor of mortality. An independent multicentric validation cohort of 607 patients confirmed that patients with L-TSA had lower 1-year survival (77% vs. 64%, p <0.001) and more oHE development (35% vs. 49%, p <0.001) than those with S-TSA. Conclusion: This study suggests that TSA >83 mm2 increases the risk for oHE and mortality in patients with cirrhosis. Our results support the clinical use of TSA/SPSS for risk stratification and decision-making in the management of patients with cirrhosis. Lay summary: The prevalence of spontaneous portosystemic shunts (SPSS) is higher in patients with more advanced chronic liver disease. The presence of more than 1 SPSS is common in advanced chronic liver disease and is associated with the development of hepatic encephalopathy. This study shows that total cross-sectional SPSS area (rather than diameter of the single largest SPSS) predicts survival in patients with advanced chronic liver disease. Our results support the clinical use of total cross-sectional SPSS area for risk stratification and decision-making in the management of SPSS.Jonel Trebicka is supported by grants from the Deutsche Forschungsgemeinschaft (SFB TRR57, CRC1382), Cellex Foundation and European Union’s Horizon 2020 research and innovation program GALAXY study (No. 668031), LIVERHOPE (No. 731875) and MICROB-PREDICT (No. 825694) and the Cellex Foundation. Joan Genescà is a recipient of a Research Intensification grant from Instituto de Salud Carlos III, Spain. The study was partially funded by grants PI15/00066, and PI18/00947 from Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, “Investing in your future”). Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivasis supported by Instituto de Salud Carlos III. Macarena Simón-Talero is a recipient of the grant JR 17/00029 from Instituto de Salud Carlos II

Los medios digitales ante la crisis humanitaria. Haití, Honduras, Venezuela, Rusia-Ucrania y Siria

Hoy en día los medios de comunicación deben desempeñar una función social al servicio del público al que se dirigen, especialmente durante los sucesos de gran impacto, como las crisis humanitarias y las catástrofes. Durante este período de desequilibrio social, la propagación de imágenes, videos e información engañosa se intensifica y provoca una falsa ilusión de verdad y realidad, coadyuvando a que la calidad de la información sea sacrificada por la inmediatez y el consumo masivo (Toledano y Ardevól-Abreu, 2013). Bajo esta premisa, estudiantes de la carrera de Comunicación de la Universidad Politécnica Salesiana, Ecuador han realizado el siguiente trabajo titulado “Informe N°1 del Observatorio Internacional sobre los Medios Digitales ante las Crisis Humanitaria”, con el objetivo de analizar y verificar los acontecimientos más relevantes sobre las crisis humanitarias alrededor del mundo y la implicación de los medios en su impacto. Se debe igualmente mencionar que este primer informe forma parte de un proyecto de investigación elaborado por los grupos de investigación Gamelab-UPS y el grupo Comunicación, Educación y Ambiente (GICEA). El objetivo del Primer Observatorio Internacional es verificar y analizar las noticias falsas y bulos que transitan de manera deliberada por la web. Para ello han realizado un análisis minucioso de la información difundida por los medios de comunicación más importantes de Ecuador, Perú y Colombia. En definitiva, el conocimiento de la realidad es lo que le permite a los receptores de contenido formarse una opinión sobre el mundo que los rodea; sin embargo, el desmesurado flujo de información y las noticias falsas (fake news) menoscaban esa credibilidad generando desinformación (Gonzáles, 2019)

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe

Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non‐crop habitats, and species’ dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7‐ and 1.4‐fold respectively. Arable‐dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield‐enhancing ecosystem services