Plegar el pliegue. Una aproximación al desafío transhumanista en clave de Neobarroco

El presente artículo parte de una incursión historiográfica en las filosofías barrocas de G. W. Leibniz y Baltasar Gracián, mediada por los estudios de Gilles Deleuze sobre el Barroco y el concepto de «pliegue». A partir de ahí, se tratará de ofrecer una evaluación crítica del controvertido fenómeno cultural que es el transhumanismo contemporáneo, guiada por la tesis según la cual los rasgos idiosincrásicos del pensamiento y la vida en el siglo XVII («ethos barroco») perviven en nuestros días bajo la forma de un Neobarroco. Concretamente, mostraremos que: i) nuestra época está fuertemente condicionada por un contexto de crisis cultural en el que un movimiento —el transhumanismo— trata de salvar un ideal, que no es ya teológico como en el Barroco clásico, sino antropológico; ii) la función operatoria propia de este Neobarroco contemporáneo es el «sobrepliegue», que permite hacerse cargo de la insoslayable componente tecnológica que presenta actualmente la antropología

AQUACOAST: A Simulation Tool to Explore Coastal Groundwater and Irrigation Farming Interactions

In the framework of coastal groundwater-dependent irrigation agriculture, modelling becomes indispensable to know how this renewable resource responds to complex (usually not conceptualized nor monitored) biophysical, social, and economic interactions. Friendly user interfaces are essential to involve nonmodeling experts in exploiting and improving models. Decision support systems (DSS) are software systems that integrate models, databases, or other decision aids and package them in a way that decision makers can use. This paper addresses these two issues: firstly with the implementation of a System Dynamics (SD) model in Vensim software that considers the integration of hydrological, agronomic, and economic drivers and secondly with the design of a Venapp, push-button interfaces that allow users access to a Vensim model without going through the Vensim modelling environment. The prototype designed, the AQUACOAST tool, gives an idea of the possibilities of this type of models to identify and analyze the impact of apparently unrelated factors such as the prices of cultivated products, subsidies or exploitation costs on the advance of saltwater intrusion, and the great threat to coastal groundwater-dependent irrigation agriculture systems.This study was funded by the European Research Council grant agreement no. 647038 (BIODESERT)

Source areas evolution in the Neogene Agost Basin (Betic Cordillera): implications for regional reconstructions

Sedimentary and mineralogical analyses were performed in the Neogene Agost Basin (External Domain, Betic Cordillera) to reconstruct relationships between tectonics and sedimentation, and source areas evolution over time. The sedimentary analysis allowed defining two sedimentary sequences: (1) Lower Stratigraphic Unit, Serravallian p.p. and (2) Upper Stratigraphic Unit, post Lower Tortonian (Upper Miocene p.p.) separated by an angular unconformity. They consist of marine (lithofacies L-1 to L-3) and continental (lithofacies L-4 to L-8) deposits, respectively. The analysis of mineralogical assemblages and some XRD parameters of the sedimentary sequences and older formations allowed recognizing a sedimentary evolution controlled by the activation of different source areasover time. In particular, the Ill+Kln±Sme+Chl claymineral association characterizes the supply from Triassic formations; the Ill+Kln+Sme association from Albian formations; the Sme+Ill±Kln+(I-S) and Sme+Ill±Kln associations from Upper Cretaceous p.p. formations; and the Sme+Ill±Kln+(I-S) association from Paleogene formations, testifying a tectonic mobility of the basin margins differentiated over time. This reconstruction leads to propose detailed relationships between types of deposits and provenance and not a classic ?unroofing?, as follows: (i) the lithofacies L-1 (lithofacies L-2 and L-3 were not analysed) is characterized by the Ill+Kln+Sme mineralogical association indicating an origin from the Albian formations; (ii) the lithofacies L-4 shows a mixture of Ill+Kln+Sme and Sme+Ill+Kln associations sourced from the Albian and Upper Cretaceous formations; (iii) the lithofacies L-5 is characterized by the Sme+Ill±Kln+(I-S) association indicating a provenance from the Upper Cretaceous and Paleogene formations, and (iv) the lithofacies L-6 to L-8 are characterized by the Ill+Kln±Sme+Chl association indicating a supply mainly from Triassic deposits. The evolutionary sedimentary model reconstructed for the Agost Basin, which improves a previous contribution about the same area, has been correlated with those reported in other intramontane Neogene basins in the Betic-Rifian Arc studied with similar resolution, this obtaining useful information for regional reconstructions.Research supported by: Research Project CGL2016-75679-P, Spanish Ministry of Education and Science; Research Groups and Projects of the Generalitat Valenciana, Alicante University (CTMAIGA); Research Group RNM 146, Junta de Andalucía; Grants from University of Urbino Carlo Bo, responsible M. Tramontana

SAT: A Software for Assessing the Risk of Desertification in Spain

Desertification is a major global environmental issue exacerbated by climate change. Strategies to combat desertification include prevention which seeks to reverse the process before the system reaches the stable desertified state. One of these initiatives is to implement early warning tools. This paper presents SAT (the Spanish acronym for Early Warning System), a decision support system (DSS), for assessing the risk of desertification in Spain, where 20% of the land has already been desertified and 1% is in active degradation. SAT relies on three versions of a Generic Desertification Model (GDM) that integrates economics and ecology under the predator-prey paradigm. The models have been programmed using Vensim, a type of software used to build and simulate System Dynamics (SD) models. Through Visual Basic programming, these models are operated from the Excel environment. In addition to the basic simulation exercises, specially designed tools have been coupled to assess the risk of desertification and determine the ranking of the most influential factors of the process. The users targeted by SAT are government land-use planners as well as desertification experts. SAT tool is implemented for five case studies, each one of them representing a desertification syndrome identified in Spain. Given the general nature of the tool and the fact that all United Nations Convention to Combat Desertification (UNCCD) signatory countries are committed to developing their National Plans to Combat Desertification (NPCD), SAT could be exported to regions threatened by desertification and expanded to cover more case studies.This work was funded by TRAGSATEC Public Enterprise on behalf of the Spanish Ministry of Agriculture, Food, and Environment under Contract 23.674. The generic desertification model was developed under the umbrella of DeSurvey IP (European Commission FP6 Contract no. 003950). The paper was written within the framework of the project BIODESERT, funded by the European Research Council (ERC Grant agreement no. 647038)

The Importance of Prevention in Tackling Desertification: An Approach to Anticipate Risks of Degradation in Coastal Aquifers

Groundwater degradation is a major issue on an increasingly hot and thirsty planet. The problem is critical in drylands, where recharge rates are low and groundwater is the only reliable resource in a context of water scarcity and stress. Aquifer depletion and contamination is a process of desertification. Land Degradation Neutrality is regarded as the main initiative to tackle land degradation and desertification. It is embedded in target 15.3 of the Sustainable Development Goals and focused on preventing these dynamics. Within this framework, we present an approach to assess risks of degradation and desertification in coastal basins with aquifers threatened by seawater intrusion. The approach utilizes an integrated system dynamics model representing the main relationships between the aquifer and an intensively irrigated area (greenhouses) driven by short- and medium-term profitability. The study area is located in a semi-arid region in Southern Spain, the Gualchos stream basin, which contains the Castell de Ferro aquifer. We found that the risk of salinization of the aquifer is 73%, while there is a 70% risk that the system would increases its demand for surface water in the future, and the chance of doubling the current demand is almost 50%. If the current system of reservoirs in the area were not able to satisfy such an increase in demand because of climate change, the basin would be at a serious risk of desertification.This research was funded by the European Research Council (ERC grant agreement 647038 (BIODESERT)) and by the project 101086497 funded by European Union’s Horizon-CL6-2022-Governance-01-07 research and innovation program

A Python Application for Visualizing the 3D Stratigraphic Architecture of the Onshore Llobregat River Delta in NE Spain

This paper introduces a Python application for visualizing the 3D stratigraphic architecture of porous sedimentary media. The application uses the parameter granulometry deduced from borehole lithological records to create interactive 3D HTML models of essential stratigraphic elements. On the basis of the high density of boreholes and the subsequent geological knowledge gained during the last six decades, the Quaternary onshore Llobregat River Delta (LRD) in northeastern Spain was selected to show the application. The public granulometry dataset produced by the Water Authority of Catalonia from 433 boreholes in this strategic coastal groundwater body was clustered into the clay–silt, coarse sand, and gravel classes. Three interactive 3D HTML models were created. The first shows the location of the boreholes granulometry. The second includes the main gravel and coarse sand sedimentary bodies (lithosomes) associated with the identified three stratigraphic intervals, called lower (>50 m b.s.l.) in the distal LRD sector, middle (20–50 m b.s.l.) in the central LRD, and upper (<20 m b.s.l.) spread over the entire LRD. The third deals with the basement (Pliocene and older rocks) top surface, which shows an overall steeped shape deepening toward the marine platform and local horsts, probably due to faulting. The modeled stratigraphic elements match well with the sedimentary structures reported in recent scientific publications. This proves the good performance of this incipient Python application for visualizing the 3D stratigraphic architecture, which is a crucial stage for groundwater management and governance.Research Project PID2020-114381GB-100 of the Spanish Ministry of Science and Innovation, Research Groups and Projects of the Generalitat Valenciana from the University of Alicante (CTMA-IGA), and Research Groups FQM-343 and RNM-188 of the Junta de Andalucía

Confidence of a k-Nearest Neighbors Python Algorithm for the 3D Visualization of Sedimentary Porous Media

In a previous paper, the authors implemented a machine learning k-nearest neighbors (KNN) algorithm and Python libraries to create two 3D interactive models of the stratigraphic architecture of the Quaternary onshore Llobregat River Delta (NE Spain) for groundwater exploration purposes. The main limitation of this previous paper was its lack of routines for evaluating the confidence of the 3D models. Building from the previous paper, this paper refines the programming code and introduces an additional algorithm to evaluate the confidence of the KNN predictions. A variant of the Similarity Ratio method was used to quantify the KNN prediction confidence. This variant used weights that were inversely proportional to the distance between each grain-size class and the inferred point to work out a value that played the role of similarity. While the KNN algorithm and Python libraries demonstrated their efficacy for obtaining 3D models of the stratigraphic arrangement of sedimentary porous media, the KNN prediction confidence verified the certainty of the 3D models. In the Llobregat River Delta, the KNN prediction confidence at each prospecting depth was a function of the available data density at that depth. As expected, the KNN prediction confidence decreased according to the decreasing data density at lower depths. The obtained average-weighted confidence was in the 0.44−0.53 range for gravel bodies at prospecting depths in the 12.7−72.4 m b.s.l. range and was in the 0.42−0.55 range for coarse sand bodies at prospecting depths in the 4.6−83.9 m b.s.l. range. In a couple of cases, spurious average-weighted confidences of 0.29 in one gravel body and 0.30 in one coarse sand body were obtained. These figures were interpreted as the result of the quite different weights of neighbors from different grain-size classes at short distances. The KNN algorithm confidence has proven its suitability for identifying these anomalous results in the supposedly well-depurated grain-size database used in this study. The introduced KNN algorithm confidence quantifies the reliability of the 3D interactive models, which is a necessary stage to make decisions in economic and environmental geology. In the Llobregat River Delta, this quantification clearly improves groundwater exploration predictability.Research Project PID2020-114381GB-100 of the Spanish Ministry of Science and Innovation, Research Project 101086497 of the Horizon Europe Framework Programme HORIZON-CL6-2022-GOVERNANCE-01-07, Research Groups and Projects of the Generalitat Valenciana from the University of Alicante (CTMA-IGA), and Research Groups FQM-343 and RNM-188 of the Junta de Andalucía

A K-Nearest Neighbors Algorithm in Python for Visualizing the 3D Stratigraphic Architecture of the Llobregat River Delta in NE Spain

The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning classifier; which uses proximity and similarity to make classifications or predictions about the grouping of an individual data point. This ability makes the KNN algorithm ideal for classifying datasets of geological variables and parameters prior to 3D visualization. This paper introduces a machine learning KNN algorithm and Python libraries for visualizing the 3D stratigraphic architecture of sedimentary porous media in the Quaternary onshore Llobregat River Delta (LRD) in northeastern Spain. A first HTML model showed a consecutive 5 m-equispaced set of horizontal sections of the granulometry classes created with the KNN algorithm from 0 to 120 m below sea level in the onshore LRD. A second HTML model showed the 3D mapping of the main Quaternary gravel and coarse sand sedimentary bodies (lithosomes) and the basement (Pliocene and older rocks) top surface created with Python libraries. These results reproduce well the complex sedimentary structure of the LRD reported in recent scientific publications and proves the suitability of the KNN algorithm and Python libraries for visualizing the 3D stratigraphic structure of sedimentary porous media, which is a crucial stage in making decisions in different environmental and economic geology disciplines.Research Project PID2020-114381GB-100 of the Spanish Ministry of Science and Innovation, Research Groups and Projects of the Generalitat Valenciana from the University of Alicante (CTMA-IGA), and Research Groups FQM-343 and RNM-188 of the Junta de Andalucía

Scientific Programming Tools for Water Management

This special issue delivers a platform in which researchers expose intersections between algorithm design, software platforms, and hardware architectures to deal with emerging challenges in the scientific field of management of water and water-dependent resources. Since the call for papers was announced in June 2019, this special issue has received 10 manuscripts. After a rigorous review process, 6 papers have been finally accepted for publication. Published papers deal with groundwater quality monitoring, coastal groundwater-dependent irrigation agriculture, desertification risk, water recovery from tailings, future scenarios of water resources, and vulnerability of coastal aquifers

Optimization Design of RC Elevated Water Tanks under Seismic Loads

[EN] This paper deals with the seismic column design of 35 elevated RC water storage tanks. Tanks comprise a top conic trunk reservoir, a column with variable hollow square cross-sections, and a shallow foundation on a sand layer. The five-column heights considered are 20, 25, 30, 35, and 40 m. The five tanks are subjected to seven degrees of seismic loading characterized by the reference peak ground acceleration in Eurocode 8. The elevated tanks are designed against the full prescriptions of Eurocode 2, Eurocode 8, and the Spaniard Structural Code of Practice. This includes variable loads for seismicity, wind, snow, etc., together with the action of self-weight and dead loads. The optimization design method considered is a variant of the old bachelor algorithm, an adaptive threshold acceptance method with a neighborhood move based on the mutation operator from genetic algorithms. Column results show the high nonlinearity of the problem since the horizontal seismic forces depend on the rigidity and height of the columns. The main features of the optimized tanks give guidance for the practical design of this kind of elevated RC water tank.Grant PID2020-117056RB-I00 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe".Martínez-Martín, FJ.; Yepes, V.; Gonzalez Vidosa, F.; Hospitaler Pérez, A.; Alcalá-González, J. (2022). Optimization Design of RC Elevated Water Tanks under Seismic Loads. Applied Sciences. 12(11):1-19. https://doi.org/10.3390/app12115635119121