Resultados de investigación

Water scarcity presents an increasingly urgent challenge with global implications for the production of irrigated vegetables. Among these crops, tomatoes stand out as one of the most widely cultivated. Given their vulnerability to water stress, it is crucial to ensure efficient and sustainable water management for tomato irrigation. This study aims to explore the varying capacities for drought avoidance, drought acclimation, and drought tolerance among three local and three commercial resilient tomato varieties in response to water stress and re-watering. We subjected tomato plants to either two brief periods of water stress (WE1) or one extended period of water stress (WE2), followed by rehydration, as evidenced by the measured stem water potential (Ψstem ≈ -1.6 MPa). Physiological and biochemical parameters were analyzed to understand how different tomato varieties respond to water stress. Our results did not reveal significant differences in the response to water stress among the varieties that could be attributed to their origin. Once the plants were rehydrated, they quickly regained their original values, with no statistically significant differences compared to untreated plants. An assessment of lipid peroxidation, antioxidant capacity, phenols, and flavonoids revealed that only during the second episode of water stress in WE1 plants or at the end of the prolonged water stress in WE2 plants did water stress trigger an overproduction of reactive oxygen species (ROS), which attacked membrane lipids and resulted in oxidative damage. However, after rehydration, tomato plants returned to normal values of oxidative parameters, indicating the absence of irreversible damage. Although the severe water stress did not compromise the viability of the plants, all treatments and varieties exhibited a predictable and substantial growth inhibition. In conclusion, the different tomato varieties studied displayed similar responses to water stress, primarily characterized by inhibition of gas exchange processes and heightened oxidative stress. Nonetheless, none of the plants suffered irreversible damage from this stress, as they fully recovered their normal physiological and biochemical values following re-watering. The whole work can be download at: https://doi.org/10.1016/j.agwat.2023.108529

Descripción del dataset

Original data for the paper, in a excel file with several sheets.

1. Metolodogía (empleada para la recogida o generación de los datos)

Data were obtained in an assay of tomato in a greenhouse.

Códigos Deep Learning (entrenamiento y predicción) de un clasificador de la gravedad de lesiones orales - TFM Alejandro Redondo García. En los ficheros encontramos dos carpetas (si seleccionamos la visualización del árbol en la web). 1. Codigo_InvestigacionPosteriorTFM. Esta carpeta contiene lo siguiente: archivo ClasificadorLesionesOrales_CrossValidation.py - es el código en python del clasificador de Deep Learning con cross validation, archivo GenerarCSV.py - es el código en python para generar el .csv, archivo Manual.pdf - son las instrucciones para ejecutar el código ClasificadorLesionesOrales_CrossValidation.py, archivo modelosTimm.csv - son los modelos disponibles de clasificación, archivo PrediccionClasificadorLesionesOrales.py - es el código para realizar la inferencia del modelo entrenado, carpeta DatasetCross - contiene un ejemplo del formato del dataset que necesita el código ClasificadorLesionesOrales_CrossValidation.py y carpeta Resultados - es un ejemplo de resultado que arroja del modelo entrenado, concretamente se guardan las métricas, la configuración y los pesos del modelo. 2. Codigo_TFM. Esta carpeta contiene lo siguiente: archivo ClasificadorLesionesOrales.py - es el código en python del clasificador de Deep Learning sin cross validation, archivo Manual.pdf - son las instrucciones para ejecutar el código ClasificadorLesionesOrales.py, archivo modelosTimm.csv - son los modelos disponibles de clasificación, archivo PrediccionClasificadorLesionesOrales.py - es el código para realizar la inferencia del modelo entrenado, carpeta Dataset - contiene un ejemplo del formato del dataset que necesita el código ClasificadorLesionesOrales.py, carpeta Predicciones - contiene un ejemplo de la inferencia del modelo y carpeta Resultados - es un ejemplo de resultado que arroja del modelo entrenado, concretamente se guardan las métricas, la configuración y los pesos del modelo. Nota.: Es recomendable leer los manuales antes de utilizar los códigos.

This is a subsection of the Spanish data collected for an international Project (https://doi.org/10.17605/OSF.IO/5NKQ9) focused on studying the impact and response to the COVID-19 lockdown across the world for families of individuals with special needs. In this particular Spanish subproject we studied the emotional impact of the strict lockdown during COVID-19 on Spanish caregivers of individuals with Autism Spectrum Disorder, Williams Syndrome and Down syndrome. Data were collected through an online survey. All caregivers reported concerns directly related to the pandemic and lockdown situation. Anxiety was predicted by previous anxiety disorder and the child’s diagnosis. The confinement in Spain was especially demanding for families of individuals with ASD.

Despite continuous efforts by the petroleum industry to address societal needs, the effective management of potentially hazardous wastes, such as refinery sludge, remains a significant challenge. Refinery sludge is a stable emulsion comprising water, petroleum hydrocarbons (e.g., oils, fats, organic compounds), solids, and metals. Hydrothermal carbonization (HTC) is a promising and environmentally friendly approach for valorizing oily sludge from refineries, given its adaptability and high efficiency in processing wet or high-moisture-content organic wastes. This study aims to systematically evaluate the effects of three key factors—initial sludge composition (through the mixing of three distinct real oily sludge streams from refinery), HTC temperature, and reaction time—on the properties of the resulting hydrochar, aqueous phase and oily phase. This scope was reached through a full factorial design of experiments and a deepened characterization of the as-received petrochemical samples and the separated HTC products. The study resulted in predictive models for 32 response variables associated with the HTC process using real refinery sludge mixtures. These variables include the HTC product distribution, hydrochar yield, higher heating value (HHV) of produced hydrochar, and the characteristics of the process water, among others. The developed models provide a reliable framework for optimizing HTC outputs and forecasting quality variations in response to changes in the operating conditions studied.

Following the implementation of the new European legislation on opium alkaloids (OAs) in food in 2023, scientific research has focused on developing analytical methodologies to determine the presence of these compounds in different foods. However, health authorities continue to suggest further studies to evaluate the occurrence of main OAs and the impact of culinary processing. Concerns remain regarding the potential health risks associated with consuming foods containing OAs. This review provides an updated overview of OAs on food, addressing their occurrence, toxicity, and the risks and benefits associated with poppy seed consumption. It compiles data from recent studies and official reports, including notifications from the Rapid Alert System for Food and Feed (RASFF). Additionally, the influence of culinary processing on OAs concentration is analyzed, highlighting the main findings and research gaps. The review also discusses advancements in analytical methodologies, with emphasis on improvements in green sample preparation to purify extracts and validation of methodologies to improve detection reliability. Elevated concentrations of OAs above legislated limits have been reported. However, various culinary processing methods allow for significant reduction of these levels. Proper control of the initial concentration, together with appropriate processing practices, can mitigate the risks associated with ingestion of contaminated foods. Despite methodological advances in detection, further refinement of analytical methods for different food matrices is needed. Future research should focus on the optimization of these methods for the determination of all OAs, besides morphine and codeine, as well as on the effects of processing and the possible formation of degradation compounds.

Currently, the development of environmentally friendly analytical methodologies is a challenge for analytical chemistry. Therefore, the search for solvents to extract analytes of interest from complex matrices has progressed considerably in recent years. In the present work, 15 hydrophobic natural deep eutectic solvents (HNADES) consisting of a mixture of different donors and acceptors in different ratios have been prepared and compared to evaluate the most efficient extraction of opium alkaloids (OA) from fortified water samples. After selecting the most effective one consisting in a mixture of thymol and camphor in the ratio 1:1 ([Thy]:[Cam] 1:1), a rapid analytical methodology to determine OA in poppy seed beverages was optimised and validated for the first time. It was based on a miniaturised liquid–liquid extraction (m-LLE) with 0.5 mL of sample and 0.5 mL of HNADES by vortexing for 1 min, followed by 1 min centrifugation and subsequent analysis by high-performance liquid chromatography with diode array detector (HPLC-DAD). The validation was successful, showing extraction efficiencies between 91 and 107 % for all analytes, low limits of quantification (0.1 µg/mL for all analytes, except for morphine, 0.4 µg/mL) and precision values below 15 %. In addition, the greenness of the method was evaluated, obtaining a 0.79 on the AGREEprep metric scale. Therefore, it was demonstrated that the methodology developed to analyse OAs in poppy seed beverage was efficient, fast, simple and environmentally friendly.

Description of the project

This dataset is the result of the research carried out in the project "A Benchmark for Rey-Osterrieth Complex Figure (ROCF) Test Automatic Scoring", whose main goal was to establish a baseline for the scoring task consisting of: a dataset with 528 ROCF and results obtained by several deep learning models, as well as, by a group of psychology experts.,

Description of the dataset

This dataset contains a single folder with 528 grayscale images of Rey-Osterrieth Complex Figures.,

Methodology

The methodology used to collect the data consists of 3 steps:

• Step 1. Pencil drawing of 528 Rey-Osterrieth Complex Figures by 241 participants.
• Step 2. Drawings are scanned, cropped and cleaned of annotations.
• Step 3. The resulting images are rescaled to 384x384 pixels.

,

Descripción del proyecto

El contenido de este dataset es resultado de la investigación llevada a cabo en el proyecto "Banco de Pruebas para la Puntuación Automática del Test de la Figura Compleja de Rey-Osterrieth (FCRO)", cuyo objetivo principal era el de establecer una línea base para dicha tarea que incluye: un dataset con 528 FCRO y resultados obtenidos por varios modelos de aprendizaje profundo, así como, por varios profesionales de la psicología.,

Descripción del dataset

Este dataset contiene una única carpeta con 528 imágenes en escala de grises de figuras complejas de Rey-Osterrieth.,

Metodología

La metodología empleada para la obtención de los datos incluye 3 etapas:

• Etapa 1. Dibujado a lápiz de 528 figuras complejas de Rey-Osterrieth por parte de 241 participantes.
• Etapa 2. Los dibujos son escaneados, recortados y limpiados de anotaciones.
• Etapa 3. Las imágenes resultantes son re-escaladas a tamaño 384x384 píxeles.

This dataset is a companion reproducibility package of the related paper submitted for publication, whose aim is to allow the exact replication of a very large experimental survey on word similarity between the families of ontology-based semantic similarity measures and word embedding models as detailed in ‘appendix-reproducible-experiments.pdf’ file. Our experiments are based on the evaluation of all methods with the HESML V1R4 semantic measures library and the recording of these experiments with Reprozip. HESML is a self-contained Java software library of semantic measures based on WordNet whose latest version, called HESML V1R4, also supports the evaluation of pre-trained word embedding files. HESML is a self-contained experimentation platform on word similarity which is especially well suited to run large experimental surveys by supporting the execution of automatic reproducible experiment files on word similarity based on a XML-based file format called (*.exp). On the other hand, ReproZip is a virtualisation tool whose aim is to warrant the exact replication of experimental results onto a different system from that originally used in their creation. Reprozip captures all the program dependencies and is able to reproduce the packaged experiments on any host platform, regardless of the hardware and software configuration used in their creation. Thus, ReproZip warrants the reproduction of the experiments introduced herein in the long-term. Finally, other very valuable feature of Reprozip is that it allows to modify the input files of any Reprozip package with the aim of evaluating a set of experiments using originally unconsidered methods, configuration parameters or datasets. This dataset contains a Reprozip package to reproduce our experiments in any supported platform, as well as all pre-trained word embedding models and word similarity datasets used in our experiments. In addition, this dataset also contains all raw output files generated by our experiments, and a R script file to generate all output processed files corresponding to the data tables in our related paper. Finally, we provide a very detailed experimental setup in the aforementioned PDF file to allow all our experiments to be reproduced exactly.

The database comprises the examination of the censors' reports on Graham Greene's play The Living Room (1953) submitted to the Spanish censorship board in the 1950s, 1960s and 1970s.

Datos cualitativos anonimizados obtenidos a través de entrevistas semiestructuradas en el marco de la técnica de historias de vida, sobre cuatro casos de personas emprendedoras con discapacidad. Los datos son fruto de la selección y análisis cualitativo de las narraciones obtenidas. Están referidos a las características de sus trayectorias, los motivos y necesidades para desarrollar su actividad emprendedora, las claves del éxito emprendedor, las competencias puestas en juego, las barreras percibidas, las estrategias de afrontamiento y los condicionantes del emprendimiento.