El saber y los valores en la filosofía de Max Scheler

Ningun

Karl Otto Apel y el problema de la fundamentación de la ética en la época de la ciencia : (un aporte para la superación de la dicotomía entre la objetividad de la ciencia y la subjetividad de la ética o entre lo público y lo privado)

Ningun

Crystal structure of Li_2B_(12)H_(12): a possible intermediate species in the decomposition of LiBH_4

The crystal structure of solvent-free Li_2B_(12)H_(12) has been determined by powder X-ray diffraction and confirmed by a combination of neutron vibrational spectroscopy and first-principles calculations. This compound is a possible intermediate in the dehydrogenation of LiBH_4, and its structural characterization is crucial for understanding the decomposition and regeneration of LiBH_4. Our results reveal that the structure of Li_2B_(12)H_(12) differs from other known alkali-metal (K, Rb, and Cs) derivatives

Using agronomic biofortification to boost zinc, selenium, and iodine concentrations of food crops grown on the loess plateau in China

Micronutrient malnutrition among humans is typically caused by micronutrient deficiency in soils and then staple food crops grown on these soils. In this study, field trials were conducted to investigate the biofortification of micronutrients in the edible parts of winter wheat, maize, soybean, potato, canola, and cabbage. Fertilizers of Se, Zn and I were applied to soil independently or together, while Se and Zn were sprayed as solution on winter wheat in another part of the trials. Selenium, when applied to the soil in the form of sodium selenate, whether alone or combined with Zn and⁄or I, was effective in increasing Se to around target levels in all of the tested crops. Selenium as sodium selenite was effective as a foliar application to winter wheat, increasing it from 25 to 312 µg kg⁻¹ in wheat grain with 60 g Se ha⁻¹ . For Zn, soil-applied zinc sulphate was only found to be effective for increasing the Zn concentration in cabbage leaf and canola seed, with 35 and 61 mg kg ⁻¹, respectively, while foliar zinc sulphate application was effective in biofortifying winter wheat, increasing grain Zn from 20 to 30 mg kg⁻¹ . While for I, soil-applied potassium iodate was only effective in increasing I concentration in cabbage leaf, and biofortification of the other crops was not possible. The enhancements of Se, Zn, and I concentration resulting from either the single or combined application of microelement fertilizers were similar. Therefore, agronomic biofortification of edible parts of various food crops with Zn, Se, and I can be an effective way to increase micronutrient concentrations, and the effectiveness depends on crop species, fertilizer forms and application methods.H. Mao, J. Wang, Z. Wang, Y. Zan, G. Lyons, C. Zo

CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations

We propose CaSPR, a method to learn object-centric Canonical Spatiotemporal Point Cloud Representations of dynamically moving or evolving objects. Our goal is to enable information aggregation over time and the interrogation of object state at any spatiotemporal neighborhood in the past, observed or not. Different from previous work, CaSPR learns representations that support spacetime continuity, are robust to variable and irregularly spacetime-sampled point clouds, and generalize to unseen object instances. Our approach divides the problem into two subtasks. First, we explicitly encode time by mapping an input point cloud sequence to a spatiotemporally-canonicalized object space. We then leverage this canonicalization to learn a spatiotemporal latent representation using neural ordinary differential equations and a generative model of dynamically evolving shapes using continuous normalizing flows. We demonstrate the effectiveness of our method on several applications including shape reconstruction, camera pose estimation, continuous spatiotemporal sequence reconstruction, and correspondence estimation from irregularly or intermittently sampled observations.Comment: NeurIPS 202

Assessment of the Contribution of Polarimetric Persistent Scatterer Interferometry on Sentinel-1 Data

Time series of Sentinel-1 data are widely used for monitoring displacements of the Earth surface using persistent scatterer interferometry. By default over land, Sentinel-1 images include two polarimetric channels: VV and VH. However, most works in this application exploit only the VV channel, whereas the VH channel is discarded for its lower amplitude. Thanks to the development of polarimetric persistent scatterer interferometry methods, one can integrate multi-polarisation channels into a single optimal one. Previous studies proved that the number and spatial density of measurement points is increased. In this work, we explore the reason why the VH channel increases the number of measurement points when using the amplitude dispersion ( DA ) as selection criterion. Results obtained over three geographical locations show that the VH channel helps in two ways. In first place, the mean amplitude is increased for targets which have higher amplitude in VH channel, usually associated with rotated elements in the scene. In second place, and more importantly, the amplitude dispersion is decreased over many areas for which the VV channel exhibits fluctuations and peaks. Thanks to the insensitivity of the VH channel to these scene changes, it provides additional measurement points which are reliable despite their low amplitude. The increment of measurement points not only extends the spatial density and enables the detection of active deformation areas not found in the VV results, but also provides more accurate results than only using the VV channel, thanks to the increased density of points, which helps the deformation estimation.This work was supported by the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development (EFRD) under Projects PID2020-117303GB-C21 and PID2020-117303GB-C22. The research was carried out partially in the framework of the ESA-MOST China DRAGON-5 project with ref. 59339

An optimal rewiring strategy for cooperative multiagent social learning

Multiagent coordination is a key problem in cooperative multiagent systems (MASs). It has been widely studied in both fixed-agent repeated interaction setting and static social learning framework. However, two aspects of dynamics in real-world MASs are currently neglected. First, the network topologies can change during the course of interaction dynamically. Second, the interaction utilities can be different among each pair of agents and usually unknown before interaction. Both issues mentioned above increase the difficulty of coordination. In this paper, we consider the multiagent social learning in a dynamic environment in which agents can alter their connections and interact with randomly chosen neighbors with unknown utilities beforehand. We propose an optimal rewiring strategy to select most beneficial peers to maximize the accumulated payoffs in long-run interactions. We empirically demonstrate the effects of our approach in a variety of large-scale MASs