Highly active hybrid mesoporous silica-supported base organocatalysts for C-C bond formation

[EN] New base hybrid catalysts, based on silyl-derivatives of molecules carrying amino, diamino, pyrrolidine, pyrazolium and imidazolium functionalities have been successfully achieved through post synthetic grafting onto M41S-type support. Different characterization techniques were implemented to study the characteristics of the materials, such as elemental analysis, solid state MAS NMR and FTIR spectroscopies, X-ray diffraction (XRD), thermogravimetric and differential thermal analyses (TGA-DTA) and textural properties through N-2 physisorption analysis. The catalytic activity and recyclability of these compounds as base catalysts was demonstrated for C-C bond forming reactions such as Knoevenagel condensations and Michael additions rationalizing the differences observed as function of the reaction mechanisms. An enamine mechanism was proposed for Knoevenagel condensations and an enolate mechanism for Michael additions.The authors are grateful for financial support from the Spanish Government by MAT2017-82288-C2-1-P and Severo Ochoa Excellence ProgramSEV-2016-0683. The authors thank the MULTY2HYCAT (EUHorizon 2020 funded project under grant agreement no. 720783). A. E. acknowledges "La Caixa" foundation for PhD scholarship.Erigoni, A.; Hernández Soto, MC.; Rey Garcia, F.; Segarra-Almela, MDLC.; Díaz Morales, UM. (2020). Highly active hybrid mesoporous silica-supported base organocatalysts for C-C bond formation. Catalysis Today. 345:227-236. https://doi.org/10.1016/j.cattod.2019.09.041S227236345Díaz, U., Brunel, D., & Corma, A. (2013). Catalysis using multifunctional organosiliceous hybrid materials. Chemical Society Reviews, 42(9), 4083. doi:10.1039/c2cs35385gFérey, G. (2008). Hybrid porous solids: past, present, future. Chem. Soc. Rev., 37(1), 191-214. doi:10.1039/b618320bLoy, D. 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Resumen de FinancES 2023: Análisis de Sentimiento Dirigido en Español sobre Finanzas

This paper presents the FinancES 2023 shared task, organized in the IberLEF 2023 workshop, within the framework of the 39th International Conference of the Spanish Society for Natural Language Processing (SEPLN 2023). The aim of this task is to extend the challenge of sentiment analysis in Spanish to the financial domain, in order to extract the sentiment that a piece of financial information can have for several actors, including the main economic target (i.e., the specific company or asset where the economic fact applies), other companies (i.e., the entities producing the goods and services that others consume) and consumers (i.e., households/individuals). Specifically, two tasks are proposed and evaluated separately. One to identify the main target and to determine the sentiment polarity towards such target, and a second task to assess the sentiment towards both other companies and consumers. The ranking includes results for 10 different teams proposing novel approaches, mostly based on Transformers and generative language models.Este artículo resume la tarea FinancES 2023, organizada en el taller IberLEF 2023, dentro del marco de la 39ª Conferencia Internacional de la Sociedad Española de Procesamiento del Lenguaje Natural (SEPLN 2023). El objetivo de esta tarea es mejorar la materia de la minería de opiniones en español dentro del ámbito financiero realizando el análisis de sentimientos desde distintos puntos de vista. En concreto, se proponen y estudian dos tareas que son evaluadas de forma independiente. La primera tarea consiste en (i) identificar el actor principal asociado a una noticia financiera, y (ii) el sentimiento expresado hacia dicho actor. La segunda tarea consiste en determinar el sentimiento de la noticia (i) hacia otras empresas (i.e., otros agentes económicos), y (ii) hacia los consumidores (i.e., la sociedad). El ranking incluye los resultados de 10 equipos diferentes que proponen enfoques novedosos, en su mayoría basados en Transformers y modelos generativos del lenguaje.This work is part of the research project AIInFunds (PDC2021-121112-I00) funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. This work is also part of the research project LaTe4PSP (PID2019-107652RB-I00) funded by MCIN/AEI/10.13039/501100011033 and the research project LaTe4PoliticES (PID2022-138099OB-I00) funded by MCIN/AEI/10.13039/501100011033 and the European Fund for Regional Development (FEDER)-a way to make Europe

Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography

[EN] Electrohysterography (EHG) has emerged as an alternative technique to predict preterm labor, which still remains a challenge for the scientific-technical community. Based on EHG parameters, complex classification algorithms involving non-linear transformation of the input features, which clinicians found difficult to interpret, were generally used to predict preterm labor. We proposed to use genetic algorithm to identify the optimum feature subset to predict preterm labor using simple classification algorithms. A total of 203 parameters from 326 multichannel EHG recordings and obstetric data were used as input features. We designed and validated 3 base classifiers based on k-nearest neighbors, linear discriminant analysis and logistic regression, achieving F1-score of 84.63 ± 2.76%, 89.34 ± 3.5% and 86.87 ± 4.53%, respectively, for incoming new data. The results reveal that temporal, spectral and non-linear EHG parameters computed in different bandwidths from multichannel recordings provide complementary information on preterm labor prediction. We also developed an ensemble classifier that not only outperformed base classifiers but also reduced their variability, achieving an F1-score of 92.04 ± 2.97%, which is comparable with those obtained using complex classifiers. Our results suggest the feasibility of developing a preterm labor prediction system with high generalization capacity using simple easy-to-interpret classification algorithms to assist in transferring the EHG technique to clinical practice.This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR) and by the Generalitat Valenciana (AICO/2019/220).Nieto-Del-Amor, F.; Prats-Boluda, G.; Martínez-De-Juan, JL.; Díaz-Martínez, MDA.; Monfort-Ortiz, R.; Diago-Almela, VJ.; Ye Lin, Y. (2021). Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography. Sensors. 21(10):1-15. https://doi.org/10.3390/s21103350S115211

Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals

[EN] One of the remaining challenges for the scientific-technical community is predicting preterm births, for which electrohysterography (EHG) has emerged as a highly sensitive prediction technique. Sample and fuzzy entropy have been used to characterize EHG signals, although they require optimizing many internal parameters. Both bubble entropy, which only requires one internal parameter, and dispersion entropy, which can detect any changes in frequency and amplitude, have been proposed to characterize biomedical signals. In this work, we attempted to determine the clinical value of these entropy measures for predicting preterm birth by analyzing their discriminatory capacity as an individual feature and their complementarity to other EHG characteristics by developing six prediction models using obstetrical data, linear and non-linear EHG features, and linear discriminant analysis using a genetic algorithm to select the features. Both dispersion and bubble entropy better discriminated between the preterm and term groups than sample, spectral, and fuzzy entropy. Entropy metrics provided complementary information to linear features, and indeed, the improvement in model performance by including other non-linear features was negligible. The best model performance obtained an F1-score of 90.1 ± 2% for testing the dataset. This model can easily be adapted to real-time applications, thereby contributing to the transferability of the EHG technique to clinical practice.This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR), and by the Generalitat Valenciana (AICO/2019/220)Nieto Del-Amor, F.; Beskhani, R.; Ye Lin, Y.; Garcia-Casado, J.; Díaz-Martínez, MDA.; Monfort-Ortiz, R.; Diago-Almela, VJ.... (2021). Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals. Sensors. 21(18):1-17. https://doi.org/10.3390/s21186071S117211

Seagrass of Vasiliko Bay, Eastern Mediterranean: Lost Cause or Priority Conservation Habitat?

Mediterranean coasts are affected by multiple mounting pressures. In Cyprus, marine fish farming has grown rapidly in the past decade and is concentrated in the west side of Vasiliko Bay. The east coast of this bay has ports, a power station, a desalination unit, a cement factory, a major new oil terminal, and gas storage facilities. The bay is earmarked to create the largest hydrocarbon processing, storing, and transport facility in the region. Here, we assess the status of Posidonia oceanica habitat in an understudied region at the upper thermal, and eastern limit, of this Mediterranean endemic seagrass. An extensive ancient seagrass meadow was revealed, covering about 200 ha across 10 km of coastline, over soft substrata at ca 10–30 m depth, and over hard substrata at ca 0–6 m depth. Seagrass shoot density and leaf surface area decreased, both with increasing depth and with proximity to industrial developments; part of the meadow had been destroyed by dredging to build a jetty. Close to fish farms the seagrass had higher epiphytic biomass as well as lower leaf number, mass, and surface area, all of which indicate adverse effects of eutrophication and increased turbidity. Despite these multiple stressors, most of the meadow was in good ecological status, with some of the highest shoot densities ever reported. Furthermore, iconic species like sea turtles, monk seals, and dolphins were seen during sampling. Posidonia oceanica meadows off Cyprus are among the most valuable in the Mediterranean due to their tolerance of high seawater temperatures. Managers of future coastal developments in the region will need to adhere to European legislation and international conventions designed to secure the socioeconomic benefits of seagrass beds.</jats:p

Illness perception and treatment adherence in polypharmacy chronic patients of primary care

OBJETIVOS: - Conocer la percepción de enfermedad en los pacientes crónicos polimedicados desde Atención Primaria. - Determinar si existe una mayor percepción de enfermedad en el grupo que recibe la intervención enfermera. - Determinar si existe una mayor adhesión al tratamiento en el grupo que recibe la intervención enfermera

Transcription, indexing and automatic analysis of judicial declarations from phonetic representations and techniques of forensic linguistics

Recientes avances tecnológicos han permitido mejorar los procesos judiciales para la búsqueda de información en los expedientes judiciales asociados a un caso. Sin embargo, cuando técnicos y peritos deben revisar pruebas almacenadas en vídeos y fragmentos de audio, se ven obligados a realizar una búsqueda manual en el documento multimedia para localizar la parte que desean revisar, lo cual es una tarea tediosa y que consume bastante tiempo. Para poder facilitar el desempeño de los técnicos, el presente proyecto consiste en un sistema que permite la transcripción e indexación automática de contenido multimedia basado en tecnologías de deep-learning en entornos de ruido y con múltiples interlocutores, así como la posibilidad de realizar análisis de lingüística forense sobre los datos para ayudar a los peritos a analizar los testimonios de modo que se aporten evidencias sobre la veracidad del mismo.Recent technological advances have made it possible to improve the search for information in the judicial files of the Ministry of Justice associated with a trial. However, when judicial experts examine evidence in multimedia files, such as videos or audio fragments, they must manually search the document to locate the fragment at issue, which is a tedious and time-consuming task. In order to ease this task, we propose a system that allows automatic transcription and indexing of multimedia content based on deep-learning technologies in noise environments and with multiple speakers, as well as the possibility of applying forensic linguistics techniques to enable the analysis of witness statements so that evidence on its veracity is provided.Este proyecto ha sido financiado por el Instituto de Fomento de la Región de Murcia con fondos FEDER dentro del proyecto con referencia 2018.08.ID+I.0025

Validation of UVEDAI: An Index for Evaluating the Level of Inflammatory Activity in Uveitis

Introduction Uveitis is the inflammation of the middle layer of the eye, the uvea, and is a major cause of blindness. None of the instruments used in clinical practice are, in themselves, sufficient to evaluate the course of uveitis. Therefore, it is necessary to develop instruments enabling standardized measurement of inflammatory activity. We developed a composite disease activity index for patients with uveitis known as UVEDAI, which considers the overall activity of the eye. The objective of this study was to validate the composite index of ocular inflammation, UVEDAI. Methods A multicenter cross-sectional study involving eight Spanish tertiary hospitals. Sixty-two patients aged ≥ 18 years with acute uveitis were recruited. Participants gave informed consent before participating in the study. A full ophthalmological examination was performed by two ophthalmologists to determine inflammatory activity: one used the UVEDAI score and the other used clinical judgment. The ophthalmologists did not share their findings with each other to avoid introducing bias into the analysis. Construct validity was established by means of factor analysis. The criterion validity of the index was determined using an ordinal multivariate regression model, in which the dependent variable was the degree of uveal inflammation (mild, moderate, or high/severe). Cut-off points were determined for the UVEDAI and for the receiver operating characteristic (ROC) curves. Results Sixty-two patients were included. Total variance with the three components accounted for 80.32% of the construct validity. Each of the three components identified one type of eye involvement. The discriminatory capacity of UVEDAI was 0.867 (95% CI 0.778; 0.955 p < 0.001) for mild versus moderate–high and 0.946 (95% CI 0.879; 1.000 p < 0.001) for high versus mild–moderate. Conclusions The variables included in UVEDAI enable ocular inflammatory activity to be described with a high degree of accuracy. The index may be used to evaluate and classify this activity with considerable discriminatory power.We would like to acknowledge the support of Abbvie: this study was conducted with an unrestricted grant from Abbvie. The Spanish Society of Rheumatology is the sponser and funder of this study and the journal's Rapid Service Fee, and has participated in the study design; in the analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. The corresponding author had full access to all study data and had final responsibility for the decision to submit the manuscript for publication