Maritime antarctic lakes as sentinels of climate change

Remote lakes, such as lakes from the Maritime Antarctica, can be used as sentinels of climate change, because they are mostly free of direct anthropogenic pressures, and they experience climate change as a main stressor capable of modifying the ecosystem structure and function. In this paper, the content of a lecture that has been presented at the First Conference of Lake Sustainability, which has been centred in our studies on lakes from Byers Peninsula (Maritime Antarctica), are summarized. These included physical, chemical and biological studies of these lakes and other freshwater ecosystems, which highlighted the relevance of biotic interactions for these ecosystems and its sensibility to temperature variations and to biological invasions, which is of rel- evance given the acute regional warming occurring during the last decades in the area, concomitant with the enhancement of dispersion of alien species linked to the increased presence of humans

Can compact optimisation algorithms be structurally biased?

In the field of stochastic optimisation, the so-called structural bias constitutes an undesired behaviour of an algorithm that is unable to explore the search space to a uniform extent. In this paper, we investigate whether algorithms from a subclass of estimation of distribution algorithms, the compact algorithms, exhibit structural bias. Our approach, justified in our earlier publications, is based on conducting experiments on a test function whose values are uniformly distributed in its domain. For the experiment, 81 combinations of compact algorithms and strategies of dealing with infeasible solutions have been selected as test cases. We have applied two approaches for determining the presence and severity of structural bias, namely an (existing) visual and an (updated) statistical (Anderson-Darling) test. Our results suggest that compact algorithms are more immune to structural bias than their counterparts maintaining explicit populations. Both tests indicate that strong structural bias is found only in the cBFO algorithm, regardless of the choice of strategy of dealing with infeasible solutions, and cPSO with mirror strategy. For other test cases, statistical and visual tests disagree on some cases classified as having mild or strong structural bias: the former one tends to make harsher decisions, thus needing further investigation

Riesgo de mortalidad total y cardiovascular según la clasificación propuesta por las guías KDIGO en pacientes con diabetes tipo 2

Antecedentes y objetivo: El objetivo del estudio fue comprobar la validez de la clasificación de riesgo KDIGO 2012 para predecir mortalidad total (MT) y cardiovascular (MCV) en diabetes mellitus tipo 2 (DM2). Materiales y métodos: Estudio de cohortes prospectivo incluyendo pacientes con DM2. Los puntos finales clínicos fueron MT y MCV. La principal variable predictora fue la clasificación KDIGO, una variable que recoge 4 niveles de riesgo en dependencia de una combinación de la tasa de filtración glomerular y la excreción de albúmina urinaria. La evaluación del poder predictivo se realizó con el índice de mejora de discriminación integrada (IDI). Resultados: Se incluyeron 453 pacientes (39, 3% varones, edad 64, 9 [DE 9, 3] años y evolución de DM2 de 10, 4 [DE 7, 5] años). Durante una mediana de 13 años de seguimiento, hubo incremento significativo de la tasa/1000 pacientes-año de MT (26, 5 vs. 45, 1 vs. 79, 2 vs. 109, 8; p< 0, 001) y de MCV (8, 1 vs. 17, 4 vs. 24, 7 vs. 57, 5; p< 0, 001) en las sucesivas categorías de riesgo KDIGO. En análisis multivariante también hubo incremento de riesgo de MT (HR[riesgo moderado] = 1, 29; HR[riesgo alto] = 1, 83; HR[riesgo muy alto] = 2, 15; p = 0, 016) y MCV (HR[riesgo moderado] = 1, 73; HR[riesgo alto] = 2, 27; HR[riesgo muy alto] = 4, 22; p = 0, 007) en las sucesivas categorías. La clasificación KDIGO mejoró la predicción de MT (IDI = 0, 00888; p = 0, 047) y MCV (IDI = 0, 01813; p = 0, 035). Conclusiones: La clasificación de riesgo según guías KDIGO 2012 puede estratificar eficazmente el riesgo de MT y MCV en pacientes con DM2. Background and aims: Our aim was to assess the usefulness of KDIGO 2012 risk classification to predict total and cardiovascular mortality in type 2 diabetes mellitus (DM2). Material and methods: Prospective cohort study that included DM2 patients. Clinical end-points were total and cardiovascular mortality. The main predictive variable was KDIGO risk classification, which is a combination of urinary albumin excretion and glomerular filtration rate. The predictive value was evaluated by the integrated discrimination improvement (IDI) index. Results: 453 patients (39.3% males, aged 64.9 [SD 9.3] and with a mean diabetes duration of 10.4 [SD 7.5] years) were included. During a median follow-up of 13 years, mortality rates per 1000 patients/year (26.5 vs. 45.1 vs. 79, 2 vs. 109, 8; p< 0, 001) and cardiovascular mortality (8.1 vs. 17.4 vs. 24.7 vs. 57.5; p< 0, 001) were progressively increased in successive KDIGO categories. In the multivariate analysis, there was also a progressive increase of mortality risk (HR[moderate risk] = 1.29; HR[high risk]) = 1.83; HR[very high risk] = 2.15; p =.016) and cardiovascular mortality risk (HR[moderate risk] = 1.73; HR[high risk] = 2.27; HR[very high risk] = 4.22; p =.007) in the successive categories. KDIGO classification was able to improve the mortality risk prediction (IDI = 0.00888; p =.047) and cardiovascular mortality risk prediction (IDI = 0.01813; p =.035). Conclusions: KDIGO risk classification can effectively stratify total and cardiovascular mortality risk in DM2 patients

Facile Synthesis of Amine-Functionalized Eu3+-Doped La(OH)3 Nanophosphors for Bioimaging

Here, we report a straightforward synthesis process to produce colloidal Eu3+-activated nanophosphors (NPs) for use as bioimaging probes. In this procedure, poly(ethylene glycol) serves as a high-boiling point solvent allowing for nanoscale particle formation as well as a convenient medium for solvent exchange and subsequent surface modification. The La(OH)3:Eu3+ NPs produced by this process were ~3.5 nm in diameter as determined by transmission electron microscopy. The NP surface was coated with aminopropyltriethoxysilane to provide chemical functionality for attachment of biological ligands, improve chemical stability and prevent surface quenching of luminescent centers. Photoluminescence spectroscopy of the NPs displayed emission peaks at 597 and 615 nm (λex = 280 nm). The red emission, due to 5D0 → 7F1 and 5D0 → 7F2 transitions, was linear with concentration as observed by imaging with a conventional bioimaging system. To demonstrate the feasibility of these NPs to serve as optical probes in biological applications, an in vitro experiment was performed with HeLa cells. NP emission was observed in the cells by fluorescence microscopy. In addition, the NPs displayed no cytotoxicity over the course of a 48-h MTT cell viability assay. These results suggest that La(OH)3:Eu3+ NPs possess the potential to serve as a luminescent bioimaging probe

Geometric Variability in Parametric 3D Models: Implications for Engineering Design

[EN] Modern manufacturing companies operate in environments characterized by increasingly shorter development cycles and the need to develop highly customizable products at competitive prices. In this paper, we examine the role of parametric 3D modeling in the product development process, and highlight the importance of robustness, flexibility, and responsiveness to geometric variations, which are particularly relevant in the context of the Model-Based Enterprise (MBE). We discuss the often-inefficient parametric 3D modeling practices used in industry, their root causes and implications, and identify the detrimental effects of low-quality models on engineering design activities, specifically design changes during development, generative design algorithms, design optimization, simulation, product/part family configuration, AI-based parametric modeling, Model-Based System Engineering (MBSE), and parametric and adaptive encryption. Finally, we present future lines of research aimed at increasing the quality of parametric models.Aranburu, A.; Justel, D.; Contero, M.; Camba, JD. (2022). Geometric Variability in Parametric 3D Models: Implications for Engineering Design. Procedia CIRP. 109:383-388. https://doi.org/10.1016/j.procir.2022.05.26638338810

VUV spectroscopy of luminescent materials for plasma display panels and Xe discharge lamps

In plasma display panels and Xe discharge lamps, phosphors with a high quantum efficiency under vacuum ultraviolet (VUV) excitation are required. Absolute quantum efficiencies of such phosphors are usually be determined by using synchrotron radiation since the excitation wavelength can be freely tuned over a wide energy range. A serious drawback of the use of synchrotron radiation for this purpose is the accessibility towards research facilities and the time-consuming measurement procedure which is not in line with the fast pace of industrial phosphor development. We have built up a VUV spectrophotometer which allows the measurement of absolute excitation and reflection spectra in the wavelength range of 115-350 nm. Additionally, a procedure was developed to derive spectrally resolved quantum efficiencies from these excitation spectra. In this work, the set-up of the VUV spectrometer is described and its performance is documented by comparing the obtained light output data of several phosphors with results recorded by using synchrotron radiation. It is shown that also a relatively simple VUV spectrometer can be used to determine absolute light output and quantum efficiency data in the excitation range between 115 and 350 nm with an experimental error lower than 10%

VUV spectroscopy of luminescent materials for plasma display panels and Xe discharge lamps

In plasma display panels and Xe discharge lamps, phosphors with a high quantum efficiency under vacuum ultraviolet (VUV) excitation are required. Absolute quantum efficiencies of such phosphors are usually be determined by using synchrotron radiation since the excitation wavelength can be freely tuned over a wide energy range. A serious drawback of the use of synchrotron radiation for this purpose is the accessibility towards research facilities and the time-consuming measurement procedure which is not in line with the fast pace of industrial phosphor development. We have built up a VUV spectrophotometer which allows the measurement of absolute excitation and reflection spectra in the wavelength range of 115-350 nm. Additionally, a procedure was developed to derive spectrally resolved quantum efficiencies from these excitation spectra. In this work, the set-up of the VUV spectrometer is described and its performance is documented by comparing the obtained light output data of several phosphors with results recorded by using synchrotron radiation. It is shown that also a relatively simple VUV spectrometer can be used to determine absolute light output and quantum efficiency data in the excitation range between 115 and 350 nm with an experimental error lower than 10%

Regional weather survey on Byers Peninsula, Livingston Island, South Shetland Islands, Antarctica

Título del pre-print: Regional weather survey as tool for landscape studies of maritime AntarcticaIn 2001 the LIMNOPOLAR Project was launched with the aim of addressing the suitability of freshwater ecosystems as useful sentinels of climate change. In this project, an automatic weather station was deployed on Byers Peninsula (Livingston Island, South Shetland Islands) near several freshwater ecosystems under research. Here the multi-year data recorded are presented and compared with meteorological time series from the observatories at the Spanish Juan Carlos I Station, Deception Island and Bellingshausen Station. Lake freezing and thawing periods and snow cover are also investigated. The main results indicate that Byers Peninsula is affected by the very cloudy and wet Antarctic maritime climate. Mean annual temperature is -2.8°C and summer mean temperatures are above freezing. The region shows moderate winds over the year and with moderate, mostly liquid precipitation during the summer. There is a significant linear relationship with meteorological records obtained from Juan Carlos I Station located on the east of Livingston Island. Correlations between meteorological data from both sites are high but with colder and much windier conditions on Byers Peninsula. Therefore, the usefulness and accuracy of meteorological records in the interpretation of ecosystem dynamics are presented.This work was funded by the Ministerio de Ciencia e Innovación (Spain) through the grants REN2000-0435, CGL2005-06549, POL2006-06635

How Does the Modeling Strategy Influence Design Optimization and the Automatic Generation of Parametric Geometry Variations?

[EN] The robustness and flexibility of a feature-based parametric CAD model determines the extent to which the geometry can be modified and reused in other design scenarios. The ability of a model to successfully adapt to changes depends on the type and sequence of the modeling operations selected to build the geometry, the parent-child dependencies defined during the modeling process, and the type and scope of the desired geometric change. Several formal modeling methodologies have been proposed to maximize model reusability, which have been shown to outperform unstructured approaches when designers need to manually modify the geometry. However, the effect of these parametric model strategies on the generation of valid solutions in heavily automated tasks has not yet been investigated. In this paper, we compare and analyze the performance of three wellestablished parametric modeling methodologies in various design optimization scenarios that involve the automatic generation of a large number of geometric variations. We discuss the results of a study with four parametric models of varying complexity and identify the limitations of each strategy in relation to the internal structure of the model. Our results show that explicit references and resilient modeling strategies are relatively robust for simple parts, but their effectiveness decreases significantly as the complexity of the model increases. In addition, we introduce the concept of intrinsic variability, which impacts the effectiveness of the methodology, and thus the quality of the parametric model, based on how the methodology is interpreted and executed.Aranburu, A.; Cotillas, J.; Justel, D.; Contero, M.; Camba, JD. (2022). How Does the Modeling Strategy Influence Design Optimization and the Automatic Generation of Parametric Geometry Variations?. Computer-Aided Design. 151:1-13. https://doi.org/10.1016/j.cad.2022.10336411315