ROV's Video Recordings as a Tool to Estimate Variation in Megabenthic Epifauna Diversity and Community Composition in the Guaymas Basin

Patterns in benthic megafauna diversity in littoral and intertidal zones in the Gulf of California have been associated with both habitat heterogeneity and substrate type. Current knowledge of invertebrate communities in hard bottom habitats at depths > 200 m in the Gulf is poor due to the methodological limitations inherent in sampling deep habitats. Using video imagery of benthic habitats coupled with environmental data from the Remotely Operated Vehicle Doc Ricketts, we documented variation in the diversity and community composition of the benthos from 849 to 990 m depth in the NW limit of the Guaymas Basin, in relation to dissolved oxygen and substrate characteristics. This depth range overlaps an oxygen minimum zone where oxygen drops to levels < 0.5 ml L-1 and strong gradients in a narrow depth range occur. Dissolved oxygen varied along our benthic survey from 0.200 to 0.135 ml L-1. We observed high taxonomic richness across an area of rocky outcrops through the lower transition zone. This megafaunal pattern differs from reports from other oxygen minimum zones characterized by a great abundance of a few species. Taxonomic richness diminished at depths with reduced dissolved oxygen in the lower boundary of the oxygen minimum zone with increasing soft sediment cover. We found that rocky outcrops and structure-forming organisms such as corals, sponges, and oyster aggregations supported a higher diversity (H' = 0.8) than soft sediment (H' = 0.7) as have been observed in other habitats such as seamounts. Environmental variables that explained most of the megafaunal variation were substrate type (18.4%), depth (1.14%) and temperature (0.9%). Salinity (0.45%) and dissolved oxygen (0.3%) were less important factors to explain the megafaunal composition variance. Substrate type played a key role in the diversity and composition of benthic megafauna. These results broaden our understanding concerning the potential roles of substrate characteristics in the community composition of the deep-sea benthic megafaunal assemblages in the Gulf of California and oxygen minimum zones in general

Introducción al estudio de la capacidad civil

Es necesario efectuar un estudio, exhaustivo de las disposiciones sobre la capacidad civil que se encuentran diseninadas en nuestra legislación y principalmente en nuestro Código Civil, a efecto de que dichas disposiciones se armonicen con los adolantes de la ciencia del derecho y de la era científica del mundo cambiante en que vivimos. Y haciendo un fervoroso llamado a las personas estudiosas de la ciencia del derecho, a fin de interesarles a un estudio científico, del tema que en esta humilde tesis desarrollamos

Applying the theory of constraints to the logistics service of medical records of a hospital

Management of patient records in a hospital is of major importance, for its impact both on the quality of care and on the associated costs. Since this process is circular, the prevention of the building up of bottlenecks is especially important. Thus, the objective of this paper was to analyze whether the Theory of Constraints (TOC) can be useful to the logistics of medical records in hospitals. The paper is based on a case study conducted about the 2007-2011 period in the Medical Records Logistics Service at the Hospital Universitario Virgen Macarena in Seville (Spain). From April 2008, a set of actions in the clinical record logistics system were implemented based on the application of TOC principles. The results obtained show a significant increase in the level of service and employee productivity, as well as a reduction of cost and the number of patients’ complaints

Evaluation of the Physical and Oxidative Stabilities of Fish Oil-in-Water-in-Olive Oil Double Emulsions (O1/W/O2) Stabilized with Whey Protein Hydrolysate

This work studied the physical and oxidative stabilities of fish oil-in-water-in-olive oil double emulsions (O1/W/O2), where whey protein hydrolysate was used as a hydrophilic emulsifier. A 20 wt.% fish oil-in-water emulsion, stabilized with whey protein hydrolysate (oil: protein ratio of 5:2 w/w) and with a zeta potential of ~�����40 mV, only slightly increased its D4,3 value during storage at 8 C for seven days (from 0.725 to 0.897 m), although it showed severe physical destabilization when stored at 25 C for seven days (D4,3 value increased from 0.706 to 9.035 m). The oxidative stability of the 20 wt.% fish oil-in-water emulsion decreased when the storage temperature increased (25 vs. 8 C) as indicated by peroxide and p-anisidine values, both in the presence or not of prooxidants (Fe2+). Confocal microscopy images confirmed the formation of 20 wt.% fish oil-in-water-in-olive oil (ratio 25:75 w/w) using Polyglycerol polyricinoleate (PGPR, 4 wt.%). Double emulsions were fairly physically stable for 7 days (both at 25 and 8 C) (Turbiscan stability index, TSI < 4). Moreover, double emulsions had low peroxide (<7 meq O2/kg oil) and p-anisidine (<7) values that did not increase during storage independently of the storage temperature (8 or 25 C) and the presence or not of prooxidants (Fe2+), which denotes oxidative stability.the I+D+i projects CTQ2017-87076-R and PID2020-114137RBI00 funded by MCIN/AEI/10.13039/50110001103

Length of the artificial incubation in red-legged partridge (Alectoris rufa)

La incubación artificial de los huevos es una fase del manejo clave para la viabilidad de las granjas cinegéticas de perdiz roja (Alectoris rufa). Sin embargo, la duración de la incubación artificial y la dispersión de las eclosiones no han sido previamente cuantificadas en esta especie. Con este objetivo se analizaron cuatro ensayos de incubación artificial de huevos de perdiz roja procedentes de tres granjas cinegéticas del sur de España realizados incluyendo variabilidad de factores de manejo de los reproductores y de la incubación. La duración media de la incubación fue de 23,4 días, difiriendo entre ensayos (P = 0,004), con un valor modal de 23 días y finalizando la mayoría de las eclosiones (percentil 95) el día 24,5 de incubación. La eclosión mostró una distribución asimétrica positiva y leptocúrtica, como corresponde al patrón de eclosión de las especies precociales. Las eclosiones, que pueden comenzar el día 21,5 y finalizar el día 26 de incubación, se extendieron en promedio durante cuatro días, periodo mayor que el descrito en la literatura divulgativa probablemente porque en el presente estudio los huevos no estuvieron en contacto entre sí, lo que pudo limitar la sincronía en la eclosión. Los resultados de este estudio son útiles para conocer la distribución de la eclosión en las granjas cinegéticas de perdiz roja, posibilitando la mejora del manejo de los lotes de huevos en la nacedoraThe artificial incubation of the eggs is a key management phase for the feasibility of the red-legged partridge (Alectoris rufa) game farms. However, the length of the artificial incubation and the spreading pattern of the hatching have not been previously quantified in this species. To this end, four trials of artificial incubation of eggs from three red-legged partridge game farms located in southern Spain were analised. The trials included a wide range of variability with regard to management of breeders and incubation process. The average length of the incubation period was 23.4 days, with differences among trials (P = 0,004), showing a modal value of 23 days. Most of the chicks (percentile 95) hatched before 24.5 days of incubation. The distribution of the hatch was leptokurtic and showed positive asymmetry, fitting with the hatching pattern of the precocial species. The hatching, that can start on day 21.5 and finish on day 26 of incubation, were spread over four days on average. This period was longer than that described in the informative literature, probably because in the present study the eggs were not in contact with each other, which could have limited the hatching synchrony. The results of the present study are useful to understand the distribution of hatching in the red-legged game farms, enabling improved management of the batches of eggs in the hatchery

Modificación de la base imponible del IVA en quiebras, suspensiones de pagos, concursos y créditos incobrables

Este trabajo contiene una explicación detallada, apoyada con la legislación correspondiente, de un tema tan actual y de tanta trascendencia en estos momentos de crisis como es la modificación de la base imponible del IVA en el caso de suspensión de pagos, concurso y créditos incobrables. Analizamos la evolución que ha tenido la normativa en lo referente a rectificación de las bases imponibles desde que está en vigor el IVA. Consideramos el procedimiento de recuperación del IVA en el caso de insolvencia del deudor, así como la comunicación por parte del acreedor a la Administración de la modificación de la base imponible. Estudiamos detalladamente tres casos: antes del 1 de enero de 1998, después de esta fecha y, por último, la más reciente modificación tras la reforma de 26 de diciembre de 2008

Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off

Electroencephalography (EEG) datasets are often small and high dimensional, owing to cumbersome recording processes. In these conditions, powerful machine learning techniques are essential to deal with the large amount of information and overcome the curse of dimensionality. Artificial Neural Networks (ANNs) have achieved promising performance in EEG-based Brain-Computer Interface (BCI) applications, but they involve computationally intensive training algorithms and hyperparameter optimization methods. Thus, an awareness of the quality-cost trade-off, although usually overlooked, is highly beneficial. In this paper, we apply a hyperparameter optimization procedure based on Genetic Algorithms to Convolutional Neural Networks (CNNs), Feed-Forward Neural Networks (FFNNs), and Recurrent Neural Networks (RNNs), all of them purposely shallow. We compare their relative quality and energy-time cost, but we also analyze the variability in the structural complexity of networks of the same type with similar accuracies. The experimental results show that the optimization procedure improves accuracy in all models, and that CNN models with only one hidden convolutional layer can equal or slightly outperform a 6-layer Deep Belief Network. FFNN and RNN were not able to reach the same quality, although the cost was significantly lower. The results also highlight the fact that size within the same type of network is not necessarily correlated with accuracy, as smaller models can and do match, or even surpass, bigger ones in performance. In this regard, overfitting is likely a contributing factor since deep learning approaches struggle with limited training examples.Spanish Ministerio de Ciencia, Innovacion y Universidades PGC2018-098813-B-C31 PGC2018-098813-B-C32 PSI201565848-

Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off

Electroencephalography (EEG) datasets are often small and high dimensional, owing to cumbersome recording processes. In these conditions, powerful machine learning techniques are essential to deal with the large amount of information and overcome the curse of dimensionality. Artificial Neural Networks (ANNs) have achieved promising performance in EEG-based Brain-Computer Interface (BCI) applications, but they involve computationally intensive training algorithms and hyperparameter optimization methods. Thus, an awareness of the quality-cost trade-off, although usually overlooked, is highly beneficial. In this paper, we apply a hyperparameter optimization procedure based on Genetic Algorithms to Convolutional Neural Networks (CNNs), Feed-Forward Neural Networks (FFNNs), and Recurrent Neural Networks (RNNs), all of them purposely shallow. We compare their relative quality and energy-time cost, but we also analyze the variability in the structural complexity of networks of the same type with similar accuracies. The experimental results show that the optimization procedure improves accuracy in all models, and that CNN models with only one hidden convolutional layer can equal or slightly outperform a 6-layer Deep Belief Network. FFNN and RNN were not able to reach the same quality, although the cost was significantly lower. The results also highlight the fact that size within the same type of network is not necessarily correlated with accuracy, as smaller models can and do match, or even surpass, bigger ones in performance. In this regard, overfitting is likely a contributing factor since deep learning approaches struggle with limited training examples

Entrevista: “¿Qué opinan los expertos? Formatos y palabras: crear, leer, transmitir”

Ilustración: "Blá, blá, blá"En esta primera sección de entrevistas hemos contado con la colaboración invitada de diversos expertos en materias literarias ofreciendo su opinión acerca de cuestiones relacionadas con el tema monográfico propuesto en la convocatoria, Formatos y palabras: crear, leer, transmitir. De este modo, personalidades pertenecientes al área universitaria como Pedro Ruiz Pérez, Domingo Sánchez-Mesa, Ignacio García y Manuel I. Capel Tuñón, junto con los editores Igor Pagani (Mondadori) y Luis Escobar (María Muratore Ediciones), el crítico literario Vicente Luis Mora y el empresario Juan González (Grammata-Papyre) reflexionan sobre la relación existente entre el soporte (físico o digital) y su influencia en la creación literaria. Al mismo tiempo, se presta atención a factores económicos y de distribución, preguntándonos si la llegada del libro digital supondrá una democratización de la literatura, al ser capaz de alcanzar una mayor difusión; por último, creemos necesario reflexionar acerca del concepto “libro”, en términos de si es posible su aplicación independientemente del soporte en que se presente el contenido o si, por el contrario, se ciñe estrictamente al texto presentado en papel