Reconstruction of Pacific Ocean Bottom Water Salinity During the Last Glacial Maximum

Knowledge of salinity in the deep ocean is important for understanding past ocean circulation and climate. Based on sedimentary pore fluid chloride measurements of a single Pacific site, Adkins et al. (2002) suggested that, during the Last Glacial Maximum (LGM), the Pacific deep bottom water was saltier than expected based on lower sea level alone. Here we present high-resolution salinity profiles from five sites in the South, Equatorial, and North Pacific Ocean. Our study greatly constrains understanding of LGM salinity in the Pacific Ocean. Our results show that LGM chloride concentrations of deep Pacific bottom water were 4.09 ± 0.4% greater than today\u27s values. Pacific Ocean bottom water salinity was also indistinguishable from being homogeneous across the wide range of latitudes studied here. These LGM salinity reconstructions are on average slightly higher (~1.4 to 1% higher) than expected from sea level of the time, which is generally inferred to have been ~120 to ~135 m lower than today

Validation of Immunoassay-Based Tools for the Comprehensive Quantification of Aß40 and Aß42 Peptides in Plasma

Recent advances in neuroimaging and cerebrospinal fluid (CSF) biomarker assays have provided evidence of a long preclinical stage of Alzheimer''s disease (AD). This period is being increasingly targeted for secondary prevention trials of new therapies. In this context, the interest of a noninvasive, cost-effective amyloid-ß (Aß) blood-based test does not need to be overstated. Nevertheless, a thorough validation of these bioanalytical methods should be performed as a prerequisite for confident interpretation of clinical results. The aim of this study was to validate ELISA sandwich colorimetric ABtest40 and ABtest42 for the quantification of Aß40 and Aß42 in human plasma. The validation parameters assessed included precision, accuracy, sensitivity, specificity, recovery, and dilution linearity. ABtest40 and ABtest42 proved to be specific for their target peptide using Aß peptides with sequence similar to the target. Mean relative error in the quantification was found to be below 7.5 for both assays, with high intra-assay, inter-assay, and inter-batch precision (CV <9.0 on average). Sensitivity was assessed by determination of the limit of quantification fulfilling precision and accuracy criteria; it was established at 7.60 pg/ml and 3.60 pg/ml for ABtest40 and ABtest42, respectively. Plasma dilution linearity was demonstrated in PBS; however, dilution in a proprietary formulated buffer significantly increased the recovery of both Aß40 and Aß42 masked by matrix interactions, allowing a more comprehensive assessment of the free and total peptide levels in the plasma. In conclusion, both assays were successfully validated as tools for the quantification Aß40 and Aß42 in plasma

Downscaling CMIP6 climate projections to classify the future offshore wind energy resource in the Spanish territorial waters

The Spanish government has established a Maritime Spatial Planning including areas for wind farms, with the aim of contributing up to 40% of European floating offshore wind power by 2030. Thus, it is crucial to assess the current and future offshore wind energy resource in these areas, and classify the near future resource by considering wind power density and other relevant factors like resource stability, environmental risks, and installation costs. To attain the necessary high spatial resolution, a dynamic downscaling of a multi-model ensemble from the 6th phase of the Coupled Model Intercomparison Project was conducted using the Weather Research and Forecasting model in Spanish territorial waters, including the Iberian Peninsula, Balearic Islands, and Canary Islands. Future projections were considered under the Shared Socioeconomic Pathways 2–4.5 and 5–8.5 scenarios. According to the results, Spain’s offshore wind energy potential is projected to grow in the upcoming years, particularly in the Atlantic Ocean and surrounding the Canary Islands. Wind resource classification in the potential offshore wind farm areas reveals noteworthy diversity, with ratings ranging from “fair” (3/7) to “outstanding” (6/7). The most promising areas for offshore wind farm development in the near future are located in the northwest of the Iberian Peninsula and the Canary Islands.Xunta de Galicia | Ref. ED431C 2021/44Agencia Estatal de Investigación | Ref. TED2021-129479A-I00Agencia Estatal de Investigación | Ref. PID2021-128510OB-I00Agencia Estatal de Investigación | Ref. IJC2020-043745-

Detección de indicadores de seguridad de pacientes (PSI-Patient Safety Indicators) en un estudio multi-céntrico de carga de enfermedad y resultados de la atención

La calidad/ seguridad de la atención médica se puede estimar analizando los registros de egresos de hospitales generales de agudos (HGA). Se obtuvieron indicadores de seguridad de los pacientes (PSI), que detectan eventos adversos en la atención médica (EAs). En un estudio multi-céntrico se adecuó un método para obtener los PSI en la Argentina basado en codificaciones diagnosticas primarias (Dx1) y secundarias (Dx2) y codificaciones de procedimientos (Px1 y Px 2). La estandarización de los diagnósticos y de los procedimientos permitió realizar la plataforma del estudio Utilización de Servicios, Costos y Resultados en Argentina (USCR-A). Se obtienen los EAs definidos por los PSI #3, #7 y #13. El objetivo de este trabajo es presentar los resultados cuali y cuantitativos de una aplicación de los PSI en el contexto del trabajo y registro del estudio multi-céntrico en Utilización de Servicios, Costos y Resultados en Argentina (USCR-A).Sociedad Argentina de Informática e Investigación Operativ

Experiences with stochastic algorithms for a class of constrained global optimisation problems

The solution of a variety of classes of global optimisation problems is required in the implementation of a framework for sensitivity analysis in multicriteria decision analysis. These problems have linear constraints, some of which have a particular structure, and a variety of objective functions, which may be smooth or non-smooth. The context in which they arise implies a need for a single, robust solution method. The literature contains few experimental results relevant to such a need. We report on our experience with the implementation of three stochastic algorithms for global optimisation: the multi-level single linkage algorithm, the topographical algorithm and the simulated annealing algorithm. Issues relating to their implementation and use to solve practical problems are discussed. Computational results suggest that, for the class of problems considered, simulated annealing performs well

Characterization of the shallow subsurface structure across the Carrascoy Fault System (SE Iberian Peninsula) using P-wave tomography and Multichannel Analysis of Surface Waves

The seismicity in the SE Iberian Peninsula is distributed parallel to the coast in a well-developed strike-slip fracture system known as the Eastern Betic Shear Zone (EBSZ). This work focuses on the characterization of the shallow subsurface structure of the Algezares-Casas Nuevas Fault, within the Carrascoy Fault System of the EBSZ. The Carrascoy Fault borders the Guadalentín Depression to the south, which is a densely populated area with extensive agricultural activity. Therefore, this faults system represents a seismic hazard with significant social and economic implications. We have constructed two velocity-depth models based on P-wave tomography and Multichannel Analysis of Surface Waves (MASW) acquired from seismic reflection data. The resulting velocity models have allowed us to interpret the first ~250m depth and have revealed: i) the thickness of the critical zone; ii) the geometry of the Algezares-Casas Nuevas Fault; iii) the depth of the Messinian/Tortonian contact and iv) the presence of blind thrusts and damage zones under the Guadalentín Depression. Our results have also helped us to estimate an apparent vertical slip rate of 0.66±0.06m/ky for the Algezares-Casas Nuevas Fault since 209.1±6.2ka. Our results provide a methodological and backflow protocol to study the shallow subsurface of active faults, complementing previous geological models based on paleoseismological trenches, and can be used to improve the seismic hazard assessment of tectonically active regions around the world

Joint analysis of species and genetic variation to quantify the role of dispersal and environmental constraints in community turnover

Spatial turnover of biological communities is determined by both dispersal and environmental constraints. However, we lack quantitative predictions about how these factors interact and influence turnover across genealogical scales. In this study, we have implemented a predictive framework based on approximate Bayesian computation (ABC) to quantify the signature of dispersal and environmental constraints in community turnover. First, we simulated the distribution of haplotypes, intra-specific lineages and species in biological communities under different strengths of dispersal and environmental constraints. Our simulations show that spatial turnover rate is invariant across genealogical scales when dispersal limitation determines the species ranges. However, when environmental constraint limits species ranges, spatial turnover rates vary across genealogical scales. These simulations were used in an ABC framework to quantify the role of dispersal and environmental constraints in 16 empirical biological communities sampled from local to continental scales, including several groups of insects (both aquatic and terrestrial), molluscs and bats. In seven datasets, the observed genealogical invariance of spatial turnover, assessed with distance–decay curves, suggests a dispersal-limited scenario. In the remaining datasets, the variance in distance–decay curves across genealogical scales was best explained by various combinations of dispersal and environmental constraints. Our study illustrates how modelling spatial turnover at multiple genealogical scales (species and intraspecific lineages) provides relevant insights into the relative role of dispersal and environmental constraints in community turnover

Towards Inverse Uncertainty Quantification in&#160;Software Development (Short Paper)

With the purpose of delivering more robust systems, this paper revisits the problem of Inverse Uncertainty Quantification that is related to the discrepancy between the measured data at runtime (while the system executes) and the formal specification (i.e., a mathematical model) of the system under consideration, and the value calibration of unknown parameters in the model. We foster an approach to quantify and mitigate system uncertainty during the development cycle by combining Bayesian reasoning and online Model-based testing

Gradient Methods for Solving Stackelberg Games

Stackelberg Games are gaining importance in the last years due to the raise of Adversarial Machine Learning (AML). Within this context, a new paradigm must be faced: in classical game theory, intervening agents were humans whose decisions are generally discrete and low dimensional. In AML, decisions are made by algorithms and are usually continuous and high dimensional, e.g. choosing the weights of a neural network. As closed form solutions for Stackelberg games generally do not exist, it is mandatory to have efficient algorithms to search for numerical solutions. We study two different procedures for solving this type of games using gradient methods. We study time and space scalability of both approaches and discuss in which situation it is more appropriate to use each of them. Finally, we illustrate their use in an adversarial prediction problem.Comment: Accepted in ADT Conference 201