Estudio experimental de sistemas poliméricos para recubrimiento de metal en prótesis

Introducción: Ante el las imperfecto comportamiento de las porcelanas dentales en implanto-prótesis, optamos por un composite reforzado: "Cristobal+". Desglosamos el presente estudio en dos partes: in vivo, e in vitro. Objetivos: Registrar y comparar el desgaste de las cúspides activas de las restauraciones (implanto-soportadas atornilladas) confeccionadas con Cristobal+, con el de dientes naturales adyacentes; así como valorar la estabilidad estética, y comportamiento frente a la adhesión bacteriana, en el momento de la ubicación de las rehabilitaciones, transcurrido un mes, tres, seis, y doces meses. Respecto a la fase in vitro, comparar los datos de dureza superficial, dureza Vickers, con los aportados por estudios previos; y confrontar los resultados de resistencia al cizallamiento ofrecidos por dos patrones en interfase: macrorretención+adhesión química versus adhesión química. Material y Método: Cuantificamos los valores del radio descrito por la porción más convexa del perfil de cada una de las cinco réplicas (una por cada fase temporal anteriormente descrita) de cada serie (diente natural o restauración), empleando para tal fin, el microscopio sin oculares, microscopia metalográfica, y el software "Autocad Architectural Desktop" versión 3.3. Para la valoración de la estabilidad estética se empleó un luxómetro, y la retención de placa: el "Índice de Quigley-Hein modificado por Turesky". Fase in vitro: durómetro, y máquina de ensayos para cizallamiento. Resultados: Las cúspides de las restauraciones confeccionadas con Cristobal+ muestran un desgaste estadísticamente significativo a lo largo de doce meses (p<0.05), así como una inestabilidad estética para p<0.01, y un excelente comportamiento frente a la adhesión bacteriana (p<0.01). Tanto los valores de dureza superficial, como Vickers se equiparan a estudios precedentes (p<0.01). Respecto al patrón adhesión+macrorretención, revelan mejores resultados (p<0.01). Discusión: Estos métodos fueron seleccionados por su fiabilidad y objetividad, ante parámetros tan complejos. Según los resultados aún quedan vías abiertas para la mejora del comportamiento de los composites

Lente intraocular multifocal refractiva con calidad óptica optimizada en un rango de foco y procedimiento para obtenerla

La presente invención describe una lente intraocular multifocal refractiva con geometría asférica en ambas superficies de tal forma que el mapa de potencia óptica local de la lente, en combinación con la cornea, tiene una zona central de potencia óptica intermedia rodeada en transición suave por un anillo de potencia óptica máxima, tras el cual se alternan de forma suave anillos de potencia oscilante. La lente proporciona un comportamiento estable en términos de calidad de imagen, tanto a través de foco como frente a cambios de pupila. El procedimiento para obtenerla se basa en la optimización de una función de mérito multiconfiguración que integra de manera simultánea el comportamiento óptico de un ojo modelo que incorpora la lente, frente a diferentes distancias al plano objeto.Peer reviewedConsejo Superior de Investigaciones CientíficasB1 Patente sin examen previ

Automatic Generation of Urban Road 3D Models for Pedestrian Studies From LiDAR Data

[Abstract] The point clouds acquired with a mobile LiDAR scanner (MLS) have high density and accuracy, which allows one to identify different elements of the road in them, as can be found in many scientific references, especially in the last decade. This study presents a methodology to characterize the urban space available for walking, by segmenting point clouds from data acquired with MLS and automatically generating impedance surfaces to be used in pedestrian accessibility studies. Common problems in the automatic segmentation of the LiDAR point cloud were corrected, achieving a very accurate segmentation of the points belonging to the ground. In addition, problems caused by occlusions caused mainly by parked vehicles and that prevent the availability of LiDAR points in spaces normally intended for pedestrian circulation, such as sidewalks, were solved in the proposed methodology. The innovation of this method lies, therefore, in the high definition of the generated 3D model of the pedestrian space to model pedestrian mobility, which allowed us to apply it in the search for shorter and safer pedestrian paths between the homes and schools of students in urban areas within the Big-Geomove project. Both the developed algorithms and the LiDAR data used are freely licensed for their use in further research.This research study was funded by the Directorate-General for Traffic of Spain, grant number SPIP2017-0234

Spatial analysis of habitat quality in a fragmented population of little bustard (Tetrax tetrax): Implications for conservation

P. 45-56Little bustard populations have suffered reduction and isolation as a consequence of landscape transformations resulting from changes in traditional agricultural systems. Consequently, the species survives within reduced and fragmentary habitats, like islands isolated in a modified matrix. In this paper, we analyze the spatial variations in male density and habitat quality in a fragmented population located at the limit of the species’ Iberian range, which is affected by agricultural intensification, using a regional modelling approach. Habitat quality (quantified according to the species perception) and bird density decreased along the intensification gradient. However, in the most intensive agricultural zone, the quality of habitats selected by little bustard males increased, while density decreased, against the expected. In possible explanation, we suggest: (1) density is not necessarily a good indicator of habitat quality, (2) population could be under-saturated in this zone, (3) interannual variations in species distribution, or (4) other relevant variables related to the agricultural intensification process not included in this analysis, such as small-scale disturbances. Analysis of population distribution pattern showed a spatial configuration in which the most densely populated squares were located at the core of the biggest population patches, in contact with mid-density squares, and all surrounded by low-density squares. Fragmentation negatively affected habitat quality and male density. Largest population patches, containing higher density values, were located at the beginning of the intensification gradient. Preservation of little bustard densities is related to an adequate management of the farming system. Habitat fragmentation requires an urgent conservation strategy to prevent local and regional scale habitat deterioration, by reducing patch isolation to maintain genetic diversification and functional connectivity

Relevance of UAV and sentinel-2 data fusion for estimating topsoil organic carbon after forest fire

[EN] The evaluation at detailed spatial scale of soil status after severe fires may provide useful information on the recovery of burned forest ecosystems. Here, we aimed to assess the potential of combining multispectral imagery at different spectral and spatial resolutions to estimate soil indicators of burn severity. The study was conducted in a burned area located at the northwest of the Iberian Peninsula (Spain). One month after fire, we measured soil burn severity in the field using an adapted protocol of the Composite Burn Index (CBI). Then, we performed soil sampling to analyze three soil properties potentially indicatives of fire-induced changes: mean weight diameter (MWD), soil moisture content (SMC) and soil organic carbon (SOC). Additionally, we collected post-fire imagery from the Sentinel-2A MSI satellite sensor (10–20 m of spatial resolution), as well as from a Parrot Sequoia camera on board an unmanned aerial vehicle (UAV; 0.50 m of spatial resolution). A Gram-Schmidt (GS) image sharpening technique was used to increase the spatial resolution of Sentinel-2 bands and to fuse these data with UAV information. The performance of soil parameters as indicators of soil burn severity was determined trough a machine learning decision tree, and the relationship between soil indicators and reflectance values (UAV, Sentinel-2 and fused UAV-Sentinel-2 images) was analyzed by means of support vector machine (SVM) regression models. All the considered soil parameters decreased their value with burn severity, but soil moisture content, and, to a lesser extent, soil organic carbon discriminated at best among soil burn severity classes (accuracy = 91.18 %; Kappa = 0.82). The performance of reflectance values derived from the fused UAV-Sentinel-2 image to monitor the effects of wildfire on soil characteristics was outstanding, particularly for the case of soil organic carbon content (R2 = 0.52; RPD = 1.47). This study highlights the advantages of combining satellite and UAV images to produce spatially and spectrally enhanced images, which may be relevant for estimating main impacts on soil properties in burned forest areas where emergency actions need to be applied.S

Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles

ArtículoThe evaluation of the effect of burn severity on forest soils is essential to determine the impact of wildfires on a range of key ecological processes, such as nutrient cycling and vegetation recovery. The main objective of this study was to assess the potentiality of different spectral products derived from RGB and multispectral imagery collected by unmanned aerial vehicles (UAVs) at very high spatial resolution for discriminating spatial variations in soil burn severity after a heterogeneous wildfire. In the case study, we chose a mixed-severity fire that occurred in the northwest (NW) of the Iberian Peninsula (Spain) in 2019 that affected 82.74 ha covered by three different types of forests, each dominated by Pinus pinaster, Pinus sylvestris, and Quercus pyrenaica. We evaluated soil burn severity in the field 1 month after the fire using the Composite Burn Soil Index (CBSI), as well as a pool of five individual indicators (ash depth, ash cover, fine debris cover, coarse debris cover, and unstructured soil depth) of easy interpretation. Simultaneously, we operated an unmanned aerial vehicle to obtain RGB and multispectral postfire images, allowing for deriving six spectral indices. Then, we explored the relationship between spectral indices and field soil burn severity metrics by means of univariate proportional odds regression models. These models were used to predict CBSI categories, and classifications were validated through confusion matrices. Results indicated that multispectral indices outperformed RGB indices when assessing soil burn severity, being more strongly related to CBSI than to individual indicators. The Normalized Difference Water Index (NDWI) was the best-performing spectral index for modelling CBSI (R2cv = 0.69), showing the best ability to predict CBSI categories (overall accuracy = 0.83). Among the individual indicators of soil burn severity, ash depth was the one that achieved the best results, specifically when it was modelled from NDWI (R2cv = 0.53). This work provides a useful background to design quick and accurate assessments of soil burn severity to be implemented immediately after the fire, which is a key factor to identify priority areas for emergency actions after forest fires.S

Fire regime attributes shape pre-fire vegetation characteristics controlling extreme fire behavior under different bioregions in Spain

[EN] Background Designing effective land management actions addressed to increase ecosystem resilience requires us to understand how shifting fire regimes are shaping landscapes. In this study, we aim to assess the link between fire regime and pre-fire vegetation biophysical characteristics (type, amount, and structure) in controlling extreme fire behavior across Atlantic-Transition-Mediterranean bioregions in Spain marked by different summer drought conditions and dominant plant regenerative traits. We used remote sensing metrics to estimate fire severity and pre-fire vegetation characteristics in eight study areas recently affected by large and highly severe wildfires under different environmental contexts. Furthermore, to account for fire regime attributes, we retrieved, for each target wildfire, the perimeter of the past wildfires that occurred between 1985 and 2022 and calculated fire recurrence, the time the since last fire (TSLF), and fire severity of previous wildfires (FSPW). The effect of fire regime attributes on pre-fire vegetation was examined using generalized linear mixed models (GLMMs). Results During the study period, fire recurrence decreased significantly in all bioregions analyzed. Fire severity increased under Atlantic conditions and decreased under Mediterranean environmental context, where the time since the last fire was the highest. Pre-fire fuel type and amount were identified as primary drivers of fire severity, being both strongly modulated by fire regime but following distinct mechanisms depending on the environmental context of each bioregion. In Atlantic sites, more frequent past wildfires of low to moderate fire severity were associated with a greater dominance of fire-prone shrublands with moderate fuel amounts, which increases the risk of severe wildfires. Similar trends occurred in Transition and Mediterranean sites but under the previous occurrence of highly severe wildfires. Specifically, long times after highly severe wildfires (> 30 years) increased fuel amount in conifer-dominated ecosystems in all bioregions analyzed, heightening susceptibility to extreme fire behavior. Conclusions Our findings highlight that fire-prone ecosystems need adaptative management strategies to mitigate the effects of fire regime changes, but these actions should be specific to the climatic and ecological context[ES] Antecedentes. El diseño de acciones efectivas de manejo de tierras para incrementar la resiliencia de los ecosistemas, requiere que entendamos cómo el cambio en los regímenes de fuego está modelando los paisajes. En este estudio, buscamos determinar la relación entre el régimen de fuego y las características biofísicas de la vegetación pre-fuego (tipo, cantidad, estructura) en el control de fuegos de comportamiento extremo a través de las biorregiones Atlántica-Transicional-Mediterránea de España, marcadas por diferentes condiciones de sequía durante el verano y las características vegetativas de las especies de plantas dominantes. Usamos las mediciones de sensores remotos para estimar la severidad del fuego y las características de la vegetación en el pre-fuego, en ocho áreas afectadas por incendios grades y severos ocurridos bajo diferentes contextos ambientales. Además, para tener en cuenta los atributos del régimen de fuegos, recuperamos, para cada fuego seleccionado, el perímetro de los fuegos pasados que ocurrieron entre 1985 y 2022 y calculamos la recurrencia del fuego, el tiempo desde el último incendio (TSLF), y la severidad de los fuegos previos (FSPW). El efecto de los atributos del régimen de fuegos sobre la vegetación pre-fuego fue examinada usando modelos lineales generalizados (GLMMs). Resultados. Durante el período de estudio, la recurrencia del fuego decreció significativamente en todas las biorregiones analizadas. La severidad del fuego creció bajo condiciones Atlánticas y decreció bajo contextos ambientales Mediterráneos, donde el tiempo desde el último fuego fue el más alto. Los tipos de combustibles en el pre-fuego y su cantidad fueron identificados como los principales conductores de la severidad del fuego, siendo ambos fuertemente modulados por el régimen de fuego aunque siguiendo distintos mecanismos dependiendo del contexto ambiental de cada biorregión. En sitios Atlánticos, los fuegos pasados más frecuentes de moderada a baja severidad fueron asociados con una dominancia mayor de arbustales propensos al fuego con cantidades moderadas de combustible, lo cual incrementa el riesgo de incendios severos. Tendencias similares ocurren en sitios de Transición y Mediterráneos, aunque bajo la ocurrencia de fuegos altamente severos. Específicamente, tiempos largos luego de fuegos altamente severos (> 30 años) incrementaron la cantidad de combustible en ecosistemas dominados por coníferas en todas las biorregiones analizadas, elevando la susceptibilidad a fuegos de comportamiento extremo. Conclusiones. Nuestros resultados enfatizan que los ecosistemas propensos al fuego necesitan de estrategias de manejo adaptativo para mitigar los efectos de los cambios en los regímenes de fuegos, aunque esas acciones debieran ser específicas dentro de los contextos climáticos y ecológicosSIThis study was financially supported by the Spanish Ministry of Science and Innovation in the framework of LANDSUSFIRE project (PID2022-139156OB-C21, PID2022-139156OB-C22) within the National Program for the Promotion of Scientific-Technical Research (2021–2023); by the Spanish Ministry of Science and Innovation and the Next-Generation Funds of the European Union (EU) in the framework of the FIREMAP project (TED2021-130925B-I00); by the Regional Government of the Principality of Asturias, the Foundation for the Promotion of Applied Scientific Research and Technology in Asturias (FICYT) and the European Regional Development Fund (ERDF) in the framework of the REWILDING project (AYUD/2021/51261); by the Regional Government of Castile and León in the framework of the IA-FIREXTCyL project (LE081P23); and by Portuguese funds through FCT-Portuguese Foundation for Science and Technology, project UIDB/04033/2020 (DOI:https://doi.org/10.54499/UIDB/04033/2020). David Beltrán-Marcos was supported by a pre-doctoral contract from the Regional Government of Castile and León co-financed by the European Social Fund (EDU/556/2019

Factors associated with obstetric violence implicated in the development of postpartum depression and post-traumatic stress disorder: a systematic review

Postpartum depression (PPD) and post-traumatic stress disorder (PTSD) continue to be prevalent, and disabling women with mental disorders and obstetric violence (OV) may be a trigger for them, particularly during maternity. We aimed to analyze the association between manifestations of OV with the development of PPD and PTSD during pregnancy, childbirth, and postpartum. This systematic review was based on the PRISMA 2020 statement and explored original articles published between 2012 and 2022. A total of 21 articles were included in the analysis, and bias was assessed by the Effective Public Health Practice Project’s Quality Assessment Tool. The highest rate of PPD symptoms appeared in women under 20 years old, multiparous, and with low education levels. The higher PTSD ratio was present in women under 35 years, primiparous, and with secondary studies. The mode of labor (instrumental or C-section) was identified as a major risk factor of PPD, being mediator variables of the informal coercion of health professionals and dissatisfaction with newborn healthcare. Instead, partner support during labor and high satisfaction with healthcare during birth were protective factors. Regarding PTSD, the mode of labor, several perineal tears, and the Kristeller technique were risk factors, and loss of autonomy and coercion modulated PTSD symptomatology. The protective factors for PTSD were respect for the labor plan, adequate communication with health professionals, social support during labor, and the skin-to-skin procedure. This systematic review provides evidence that OV contributes to PPD and PTSD, being important in developing standardized tools to prevent it. This study recommends changes in maternal healthcare policies, such as individualized healthcare assistance, humanized pregnancy protocols, and women’s mental health follow-up, and improvements in the methodological quality of future researchThis research was funded by Instituto de las Mujeres, Ministerio de Igualdad (Spain), grant number PAC22-20/2ACT/2

Climatic stability, not average habitat temperature, determines thermal tolerance of subterranean beetles

The climatic variability hypothesis predicts the evolution of species with wide thermal tolerance ranges in environments with variable temperatures, and the evolution of thermal specialists in thermally stable environments. In caves, the extent of spatial and temporal thermal variability experienced by taxa decreases with their degree of specialization to deep subterranean habitats. We use phylogenetic generalized least squares to model the relationship among thermal tolerance (upper lethal limits), subterranean specialization (estimated using ecomorphological traits), and habitat temperature in 16 beetle species of the tribe Leptodirini (Leiodidae). We found a significant, negative relationship between thermal tolerance and the degree of subterranean specialization. Conversely, habitat temperature had only a marginal effect on lethal limits. In agreement with the climatic variability hypothesis and under a climate change context, we show that the specialization process to live in deep subterranean habitats involves a reduction of upper lethal limits, but not an adjustment to habitat temperature. Thermal variability seems to exert a higher evolutionary pressure than mean habitat temperature to configure the thermal niche of subterranean species. Our results provide novel insights on thermal physiology of species with poor dispersal capabilities and on the evolutionary process of adaptation to subterranean environments. We further emphasize that the pathways determining vulnerability of subterranean species to climate change greatly depend on the degree of specialization to deep subterranean environments.Peer reviewe