The epiphytic transcriptome of Podoshaera fusca, the causal agent of cucurbit powdery mildew

3rd International Powdery Mildew Workshop, Copenhagen, Denmar

Locomotor activating effects and addiction-like features of MDPV as assessed in preclinical studies: a review.

Introducción: La 3,4-Methylenedioxypyrovalerone (mdpv) es un componente de las denominadas sales de baño, aparecidas en el mercado a final de la década del 2000 debido a la falta de precursores de síntesis de mdma, y su uso va en aumento. El ob- jetivo de este trabajo es clarificar sus características farmacológicas y potencialidades adictivas. Método: Mediante búsquedas en PubMed, 21 estudios relacionados con la química, farmacología o potencial adictivo del mdpv fueron seleccionados. Resulta- dos: El mdpv muestra ser capaz de inducir una potente hiperlocomoción, preferencias condicionadas, sensibilización conductual, autoadministración y altos puntos de corte en pruebas de razón progresiva. Conclusión: Los estudios revisados apuntan a que el mdpv es un potente psicoestimulante con un potencial adictivo similar al de la cocaí- na o la metanfetamina. Su abuso continuado podría llevar a una epidemia de adictos al mdpv.Introduction: 3,4-Methylenedioxypyrovalerone (mdpv) is a major component of the new psychoactive substances termed “bath salts”. These substances appeared on the drug market at the end of the last century given the lack of mdma precursors, caused by its worldwide prosecution by governments and police agencies, and its growing use. The goal of this work was to clarify its pharmacological features and addiction-like potentiali- ties. Methods: By PubMed searches, 21 studies related to mdpv chemistry, pharmaco logy or addictive features were selected. Results: mdpv is seen to be able to induce potent hyperlocomotion, conditioned place preference, behavioural sensitisation, self- administration and high breakpoints in progressive ratio schedules. Conclusion: The reviewed studies indicate that mdpv is a powerful psychostimulant with a similar addictive potential to that of cocaine or methamphetamine. Its abuse can lead to an epidemic of mdpv addicts

Evaluación de la capacidad nematicida de los agentes de biocontrol UMAF6614 y UMAF6639

Los nematodos fitoparásitos son uno de los grupos de patógenos de cultivos más destructivos causando graves pérdidas anuales a nivel mundial. La mayoría de los nematodos fitoparásitos se localizan en el suelo siendo patógenos de la raíz, lo que implica una gran dificultad en cuanto a su control y erradicación. Hoy en día, la aplicación de agentes químicos sigue siendo el método más común para la gestión y control de estos patógenos. Sin embargo, debido a la crecientes preocupaciones sobre los problemas de seguridad del medio ambiente y salud pública, muchos nematicidas químicos con alto grado de toxicidad se han retirado o se ha restringido su uso. Por tanto, urge desarrollar alternativas ecológicas para el control de estos patógenos. El empleo de bacterias beneficiosas para combatir plagas o enfermedades de plantas ha cobrado gran importancia en las últimas décadas. Entre las diferentes especies microbianas estudiadas, los miembros del género Bacillus se han demostrado eficaces para su uso como agentes de control biológico. En un estudios previos, se demostró que las cepas de Bacillus amyloliquefaciens, UMAF6614 y UMAF6639, son excelentes candidatas como agentes de biocontrol contra enfermedades fúngicas y bacterianas de las cucurbitáceas. Tras realizar los ensayos de mortalidad se ha visto que estas cepas tienen actividad nematicida pero se desconoce cuáles son los factores que median esta actividad y el modo de acción de dichos factores. Por tanto, en este trabajo se integran técnicas de química analítica y aproximaciones genómicas para identificar los compuestos responsables de dicha actividad y regiones en el genoma que codifiquen compuestos con actividad nematicida

A Deep Learning-Based Multimodal Architecture to predict Signs of Dementia

This paper proposes a multimodal deep learning architecture combining text and audio information to predict dementia, a disease which affects around 55 million people all over the world and makes them in some cases dependent people. The system was evaluated on the DementiaBank Pitt Corpus dataset, which includes audio recordings as well as their transcriptions for healthy people and people with dementia. Different models have been used and tested, including Convolutional Neural Networks (CNN) for audio classification, Transformers for text classification, and a combination of both in a multimodal ensemble. These models have been evaluated on a test set, obtaining the best results by using the text modality, achieving 90.36% accuracy on the task of detecting dementia. Additionally, an analysis of the corpus has been conducted for the sake of explainability, aiming to obtain more information about how the models generate their predictions and identify patterns in the data.We would like to thank “A way of making Europe” European Regional Development Fund (ERDF) and MCIN/AEI/10.13039/501100011033 for supporting this work under the MoDeaAS project (grant PID2019-104818RB-I00) and AICARE project (grant SPID202200X139779IV0). Furthermore, we would like to thank Nvidia for their generous hardware donation that made these experiments possible

Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques

This study presents a pioneering approach that leverages advanced sensing technologies and data processing techniques to enhance the process of clinical documentation generation during medical consultations. By employing sophisticated sensors to capture and interpret various cues such as speech patterns, intonations, or pauses, the system aims to accurately perceive and understand patient–doctor interactions in real time. This sensing capability allows for the automation of transcription and summarization tasks, facilitating the creation of concise and informative clinical documents. Through the integration of automatic speech recognition sensors, spoken dialogue is seamlessly converted into text, enabling efficient data capture. Additionally, deep models such as Transformer models are utilized to extract and analyze crucial information from the dialogue, ensuring that the generated summaries encapsulate the essence of the consultations accurately. Despite encountering challenges during development, experimentation with these sensing technologies has yielded promising results. The system achieved a maximum ROUGE-1 metric score of 0.57, demonstrating its effectiveness in summarizing complex medical discussions. This sensor-based approach aims to alleviate the administrative burden on healthcare professionals by automating documentation tasks and safeguarding important patient information. Ultimately, by enhancing the efficiency and reliability of clinical documentation, this innovative method contributes to improving overall healthcare outcomes.We would like to thank “A way of making Europe” European Regional Development Fund (ERDF) and MCIN/AEI/10.13039/501100011033 for supporting this work under the “CHAN-TWIN” project (grant TED2021-130890B-C21. HORIZON-MSCA-2021-SE-0 action number: 101086387, REMARKABLE, Rural Environmental Monitoring via ultra wide-ARea networKs And distriButed federated Learning; CIAICO/2022/132 Consolidated group project “AI4Health” funded by the Valencian government and International Center for Aging Research ICAR funded project “IASISTEM.” This work has also been supported by a Valencian government grant for PhD studies, CIACIF/2022/175 and a research initiation grant from the University of Alicante, AII23-12

A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols.

Maze navigation is a recurring challenge in robotics competitions, where the aim is to design a strategy for one or several entities to traverse the optimal path in a fast and efficient way. To do so, numerous alternatives exist, relying on different sensing systems. Recently, camera-based approaches are becoming increasingly popular to address this scenario due to their reliability and given the possibility of migrating the resulting technologies to other application areas, mostly related to human-robot interaction. The aim of this paper is to present a pipeline methodology towards enabling a robot solving maze autonomously, by means of computer vision and path planning. Afterwards, the robot is capable of communicating the learned experience to a second robot, which then will solve the same challenge considering its own mechanical characteristics which may differ from the first robot. The pipeline is divided into four steps: (1) camera calibration (2) maze mapping (3) path planning and (4) communication. Experimental validation shows the efficiency of each step towards building this pipeline

Metal content determination in biodiesel samples by microwave mineralization and ICP-AES

El trabajo comprende la puesta a punto de un método de digestión, mediante calentamiento de microondas, de muestras de biodiesel obtenidas mediante catálisis homogénea de aceites vegetales, para la determinación de 20 elementos mediante ICP-AES

SENTIMENT CASCADES IN THE 15M MOVEMENT Sentiment cascades in the 15M movement

Abstract Recent grassroots movements have suggested that online social networks might play a key role in their organization, as adherents have a fast, many-to-many, communication channel to help coordinate their mobilization. The structure and dynamics of the networks constructed from the digital traces of protesters have been analyzed to some extent recently. However, less effort has been devoted to the analysis of the semantic content of messages exchanged during the protest. Using the data obtained from a microblogging service during the brewing and active phases of the 15M movement in Spain, we perform the first large scale test of theories on collective emotions and social interaction in collective actions. Our findings show that activity and information cascades in the movement are larger in the presence of negative collective emotions and when users express themselves in terms related to social content. At the level of individual participants, our results show that their social integration in the movement, as measured through social network metrics, increases with their level of engagement and of expression of negativity. Our findings show that non-rational factors play a role in the formation and activity of social movements through online media, having important consequences for viral spreading

Pediatric Parapneumonic Empyema, Spain

Increased incidence is principally due to highly invasive nonvaccine serotypes of pneumococci, especially serotype 1