End-to-End Intelligent Framework for Rockfall Detection

Rockfall detection is a crucial procedure in the field of geology, which helps to reduce the associated risks. Currently, geologists identify rockfall events almost manually utilizing point cloud and imagery data obtained from different caption devices such as Terrestrial Laser Scanner or digital cameras. Multi-temporal comparison of the point clouds obtained with these techniques requires a tedious visual inspection to identify rockfall events which implies inaccuracies that depend on several factors such as human expertise and the sensibility of the sensors. This paper addresses this issue and provides an intelligent framework for rockfall event detection for any individual working in the intersection of the geology domain and decision support systems. The development of such an analysis framework poses significant research challenges and justifies intensive experimental analysis. In particular, we propose an intelligent system that utilizes multiple machine learning algorithms to detect rockfall clusters of point cloud data. Due to the extremely imbalanced nature of the problem, a plethora of state-of-the-art resampling techniques accompanied by multiple models and feature selection procedures are being investigated. Various machine learning pipeline combinations have been benchmarked and compared applying well-known metrics to be incorporated into our system. Specifically, we developed statistical and machine learning techniques and applied them to analyze point cloud data extracted from Terrestrial Laser Scanner in two distinct case studies, involving different geological contexts: the basaltic cliff of Castellfollit de la Roca and the conglomerate Montserrat Massif, both located in Spain. Our experimental data suggest that some of the above-mentioned machine learning pipelines can be utilized to detect rockfall incidents on mountain walls, with experimentally proven accuracy

Dinámica, Factores condicionantes y posibles causas de la formación de la tartera de Cambrils (Solsonès, Lleida)

Landslides and rockfalls are a common hazard in mountain areas like the Pyrenees. However, due to the difficulty of access and therefore of data acquisition, and the low density of population they are poorly studied. The Tartera de Cambrils, is located in a small town in the Solsonès region, Catalonia, and is the product of ancient landslides and succeeding rockfalls. These processes can endanger different infrastructures in the village of Cambrils such as the road, the sports centre, the salt flats called 'El Salí' (currently also being used for tourist activity), two inns and several houses. This study aims to determine the processes that caused the initial landslides, those that occur at the rock slope nowadays and their causative factors. For this, we compiled information from the literature, conducted a field study building a geologic and geomorphologic cartography and acquired LiDAR data, with a Terrestrial Laser Scan, and photographs in order to produce three-dimensional point clouds. We also analyse the rock-cliff stability using photogrammetry and LiDAR data and direct measures of rock mass discontinuities. The bedding dips smoothly and contrary to the slope, making planar sliding an unprovable mechanism, favouring wedge sliding and toppling. The rock discontinuities are the main causative factor of rockfalls. Rockfall originates from rock fronts of decametric volume along the main scarp and on the scree. These rock fronts rotated respect to the rock in situ. The farther away from the main scarp, the larger the rotation of the blocks. The analysis of the fractures allows estimating an important possibility of rockfall directly affecting the inns and the road and provides fundamental data for the development of protection measures

Geological characterization of the Llano del Águila fault in Campo de Dalías (Almería): possible seismogenic source of the 1804 earthquake

El 25 de agosto de 1804 un fuerte terremoto sacudió la región del Campo de Dalías (Almería) llegando a sentirse con una intensidad EMS de IX (Mw ~6,4). En este estudio se muestran evidencias que sugieren una relación entre este episodio sísmico y la falla de Llano del Águila. Se trata de una falla normal sub vertical de dirección NW-SE y paralela a la falla de Loma del Viento, situada a unos 3 km al sur. Para la caracterización de la falla de Llano del Águila se ha llevado a cabo una nueva interpretación geomorfológica de los depósitos aluviales cuaternarios que se ven atravesados por la traza de la falla a lo largo del área de estudio. Se han identificado cuatro generaciones de abanicos aluviales provenientes de la Sierra de Gádor, y dos secciones de falla a escala cartográfica (Cantera Este y Rambla de la Maleza). La interpretación geomorfológica se basa en el análisis de fotografías aéreas históricas. Debido a la intensa antropización de la zona, los modelos digitales del terreno actuales no son útiles. Para solventar esta limitación se procesó un modelo digital de elevaciones mediante fotogrametría usando las fotos aéreas del vuelo interministerial (1977). El análisis de escarpes de falla mediante perfiles topográficos medidos en el nuevo modelo de elevaciones proporciona un salto vertical de 6,3 ± 1,9 m para la sección de la Cantera Este y de 12,1 ± 1,9 m para la sección de la Rambla de la Maleza. Estas interpretaciones han sido verificadas en el campo donde además se adquirieron nuevos datos sobre la cinemática de la falla. Todo ello ha permitido estimar la tasa de deslizamiento neta de cada sección: 0,016 ± 0,002 y 0,10 ± 0,02 mm/año para la sección de la Cantera Este y 0,031 ± 0,002 – 0,19 ± 0,.02 mm/año para la Rambla de la Maleza, respectivamente para los últimos 126 y 781 ka (Pleistoceno Medio). A partir de la longitud total de la traza de la falla se puede estimar mediante relaciones empíricas una magnitud máxima potencial de 6,59 ± 0,19.On August 25, 1804, an earthquake with a Mw ~6.4 and a maximum intensity of IX, caused serious damage in several locations of Campo de Dalías region (Almeria) This study provides new evidence of the relationship between this episode and the Llano del Águila fault. A NW-SE subvertical fault, with a normal-dextral slip, that runs parallel to the Loma del Viento fault, located at about 3 km to the south. For the characterization of the Llano del Águila fault, a new geomorphologic interpretation of the Quaternary alluvial deposits and their relationship with the trace of the structure has been carried out. Four generations of alluvial fans draining the Sierra de Gádor and two fault sections have been identified at a cartographic scale (Cantera Est and Rambla de la Maleza). All the geomorphologic interpretation is made by the analysis of historical aerial photos. Due the high anthropization of the area, modern elevation models are not sufficiently useful. To overcome this limitation, a digital elevation model was obtained through photogrammetry with the aerial photos of the interministerial flight (1977). Fault scarp analysis from topographic profiles measured on the new elevation model provides a 6.3 ± 1.9 m vertical slip for the Cantera East section and a 12.1 ± 1.9 m vertical slip for the Rambla de la Maleza section. All these interpretations have been verified in the field and new data on the kinematics have been acquired to estimate the net slip rate of each section. A 0.016 ± 0.002 – 0.10 ± 0.02 mm/yr slip rate has been estimated for the Cantera Est section and a 0.031 ± 0.002 – 0.19 ± 0.02 mm/yr for the Rambla de la Maleza one, for the last 126 – 781 ky (middle Pleistocene). A maximum magnitude of 6.59 ± 0.19 is estimated through empirical relationships from the total length of the fault trace.Depto. de Geodinámica, Estratigrafía y PaleontologíaFac. de Ciencias GeológicasTRUEpu

Rockfall Magnitude-Frequency Relationship Based on Multi-Source Data from Monitoring and Inventory

Quantitative hazard analysis of rockfalls is a fundamental tool for sustainable risk management, even more so in places where the preservation of natural heritage and people's safety must find the right balance. The first step consists in determining the magnitude-frequency relationship, which corresponds to the apparently simple question: how big and how often will a rockfall be detached from anywhere in the cliff? However, there is usually only scarce data on past activity from which to derive a quantitative answer. Methods are proposed to optimize the exploitation of multi-source inventories, introducing sampling extent as a main attribute for the analysis. This work explores the maximum possible synergy between data sources as different as traditional inventories of observed events and current remote sensing techniques. Both information sources may converge, providing complementary results in the magnitude-frequency relationship, taking advantage of each strength that overcomes the correspondent weakness. Results allow characterizing rockfall detachment hazardous conditions and reveal many of the underlying conditioning factors, which are analyzed in this paper. High variability of the hazard over time and space has been found, with strong dependencies on influential external factors. Therefore, it will be necessary to give the appropriate reading to the magnitude-frequency scenarios, depending on the application of risk management tools (e.g., hazard zoning, quantitative risk analysis, or actions that bring us closer to its forecast). In this sense, some criteria and proxies for hazard assessment are proposed in the paper

Machine Learning-Based Rockfalls Detection with 3D Point Clouds, Example in the Montserrat Massif (Spain)

Rock slope monitoring using 3D point cloud data allows the creation of rockfall inventories, provided that an efficient methodology is available to quantify the activity. However, monitoring with high temporal and spatial resolution entails the processing of a great volume of data, which can become a problem for the processing system. The standard methodology for monitoring includes the steps of data capture, point cloud alignment, the measure of differences, clustering differences, and identification of rockfalls. In this article, we propose a new methodology adapted from existing algorithms (multiscale model to model cloud comparison and density-based spatial clustering of applications with noise algorithm) and machine learning techniques to facilitate the identification of rockfalls from compared temporary 3D point clouds, possibly the step with most user interpretation. Point clouds are processed to generate 33 new features related to the rock cliff differences, predominant differences, or orientation for classification with 11 machine learning models, combined with 2 undersampling and 13 oversampling methods. The proposed methodology is divided into two software packages: point cloud monitoring and cluster classification. The prediction model applied in two study cases in the Montserrat conglomeratic massif (Barcelona, Spain) reveal that a reduction of 98% in the initial number of clusters is sufficient to identify the totality of rockfalls in the first case study. The second case study requires a 96% reduction to identify 90% of the rockfalls, suggesting that the homogeneity of the rockfall characteristics is a key factor for the correct prediction of the machine learning models

La protección medioambiental como criterio en la selección de inversiones socialmente responsables: una aproximación multicriterio

[EN] A greater environmental and ethical awareness of companies and organizations is also ap-plied to portfolio selection. This note aims to put forward a multicriteria model of Goal Programming (GP) to design efficient portfolios considering classic financial criteria and environmental criteria[ES] La mayor concienciación medioambiental y ética de empresas y organizaciones se traslada también a la selección de carteras. En esta nota se propone un modelo multicriterio de programación por me-tas para la selección de carteras incorporando a los criterios clásicos financieros, criterios mediambientalesGarcía-Bernabeu, A.; Pla-Santamaria, D.; Bravo, M.; Pérez-Gladish, B. (2015). The Environmental Protection as a selection criterion in Socially Responsible Investments: A multicriteria approach. Economía Agraria y Recursos Naturales - Agricultural and Resource Economics. 15(1):101-112. doi:10.7201/earn.2015.01.06SWORD10111215

Early stress exposure on zebrafish development: effects on survival, malformations and molecular alterations

[EN] The effects of stress during early vertebrate development can be especially harmful. Avoiding stressors in fish larvae is essential to ensure the health of adult fish and their reproductive performance and overall production. We examined the consequences of direct exposure to successive acute stressors during early development, including their effects on miR-29a and its targets, survival, hatching and malformation rates, larval behaviour and cartilage and eye development. Our aim was to shed light on the pleiotropic effects of early-induced stress in this vertebrate model species. Our results showed that direct exposure to successive acute stressors during early development significantly upregulated miR-29a and downregulated essential collagen transcripts col2a1a, col6a2 and col11a1a, decreased survival and increased malformation rates (swim bladder, otoliths, cardiac oedema and ocular malformations), promoting higher rates of immobility in larvae. Our results revealed that stress in early stages can induce different eye tissular architecture and cranioencephalic cartilage development alterations. Our research contributes to the understanding of the impact of stressful conditions during the early stages of zebrafish development, serving as a valuable model for vertebrate research. This holds paramount significance in the fields of developmental biology and aquaculture and also highlights miR-29a as a potential molecular marker for assessing novel larval rearing programmes in teleost species.MCIN/AEIEuropean Union NextGenerationEU/PRT

Acute Coronary Syndrome in the Older Patient

Coronary artery disease is one of the leading causes of morbidity and mortality, and its prevalence increases with age. The growing number of older patients and their differential characteristics make its management a challenge in clinical practice. The aim of this review is to summarize the state-of-the-art in diagnosis and treatment of acute coronary syndromes in this subgroup of patients. This comprises peculiarities of ST-segment elevation myocardial infarction (STEMI) management, updated evidence of non-STEMI therapeutic strategies, individualization of antiplatelet treatment (weighting ischemic and hemorrhagic risks), as well as assessment of geriatric conditions and ethical issues in decision making

Serum Potassium Dynamics During Acute Heart Failure Hospitalization

[Abstract] Background. Available information about prognostic implications of potassium levels alteration in the setting of acute heart failure (AHF) is scarce. Objectives. We aim to describe the prevalence of dyskalemia (hypo or hyperkalemia), its dynamic changes during AHF-hospitalization, and its long-term clinical impact after hospitalization. Methods. We analyzed 1779 patients hospitalized with AHF who were included in the REDINSCOR II registry. Patients were classified in three groups, according to potassium levels both on admission and discharge: hypokalemia (potassium  5 mEq/L). Results. The prevalence of hypokalemia and hyperkalemia on admission was 8.2 and 4.6%, respectively, and 6.4 and 2.7% at discharge. Hyperkalemia on admission was associated with higher in-hospital mortality (OR = 2.32 [95% CI: 1.04–5.21] p = 0.045). Among patients with hypokalemia on admission, 79% had normalized potassium levels at discharge. In the case of patients with hyperkalemia on admission, 89% normalized kalemia before discharge. In multivariate Cox regression, dyskalemia was associated with higher 12-month mortality, (HR = 1.48 [95% CI, 1.12–1.96], p = 0.005). Among all patterns of dyskalemia persistent hypokalemia (HR = 3.17 [95% CI: 1.71–5.88]; p < 0.001), and transient hyperkalemia (HR = 1.75 [95% CI: 1.07–2.86]; p = 0.023) were related to reduced 12-month survival. Conclusions. Potassium levels alterations are frequent and show a dynamic behavior during AHF admission. Hyperkalemia on admission is an independent predictor of higher in-hospital mortality. Furthermore, persistent hypokalemia and transient hyperkalemia on admission are independent predictors of 12-month mortality.This work is funded by the Instituto de Salud Carlos III (Ministry of Economy, Industry, and Competitiveness) and co-funded by the European Regional Development Fund, through the CIBER in cardiovascular diseases (CB16/11/00502)