Ab initio lattice dynamics and electron-phonon coupling of Bi(111)

We present a comprehensive ab initio study of structural, electronic, lattice dynamical and electron-phonon coupling properties of the Bi(111) surface within density functional perturbation theory. Relativistic corrections due to spin-orbit coupling are consistently taken into account. As calculations are carried out in a periodic slab geometry, special attention is given to the convergence with respect to the slab thickness. Although the electronic structure of Bi(111) thin films varies significantly with thickness, we found that the lattice dynamics of Bi(111) is quite robust and appears converged already for slabs as thin as 6 bilayers. Changes of interatomic couplings are confined mostly to the first two bilayers, resulting in super-bulk modes with frequencies higher than the optic bulk spectrum, and in an enhanced density of states at lower frequencies for atoms in the first bilayer. Electronic states of the surface band related to the outer part of the hole Fermi surfaces exhibit a moderate electron-phonon coupling of about 0.45, which is larger than the coupling constant of bulk Bi. States at the inner part of the hole surface as well as those forming the electron pocket close to the zone center show much increased couplings due to transitions into bulk projected states near Gamma_bar. For these cases, the state dependent Eliashberg functions exhibit pronounced peaks at low energy and strongly deviate in shape from a Debye-like spectrum, indicating that an extraction of the coupling strength from measured electronic self-energies based on this simple model is likely to fail.Comment: 30 pages, 11 figure

Transnational, Social, and Neighborhood Ties and Smoking Among Latino Immigrants: Does Gender Matter?

Objectives. We examined whether transnational ties, social ties, and neighborhood ties were independently associated with current smoking status among Latino immigrants. We also tested interactions to determine whether these associations were moderated by gender. Methods. We conducted a series of weighted logistic regression analyses (i.e., economic remittances, number of return visits, friend support, family support, and neighborhood cohesion) using the Latino immigrant subsample (n = 1629) of the National Latino and Asian American Study in 2002 and 2003. Results. The number of past-year return visits to the country-of-origin was positively associated with current smoker status. Gender moderated the association between economic remittances, friend support, and smoking. Remittance behavior had a protective association with smoking, and this association was particularly pronounced for Latino immigrant women. Friendship support lowered the odds of smoking among men, but not women. Conclusions. Our results underscore the growing importance of transnational networks for understanding Latino immigrant health and the gendered patterns of the associations between social ties, transnational ties, and health risk behaviors

Deep neural networks for the quantile estimation of regional renewable energy production

Wind and solar energy forecasting have become crucial for the inclusion of renewable energy in electrical power systems. Although most works have focused on point prediction, it is currently becoming important to also estimate the forecast uncertainty. With regard to forecasting methods, deep neural networks have shown good performance in many fields. However, the use of these networks for comparative studies of probabilistic forecasts of renewable energies, especially for regional forecasts, has not yet received much attention. The aim of this article is to study the performance of deep networks for estimating multiple conditional quantiles on regional renewable electricity production and compare them with widely used quantile regression methods such as the linear, support vector quantile regression, gradient boosting quantile regression, natural gradient boosting and quantile regression forest methods. A grid of numerical weather prediction variables covers the region of interest. These variables act as the predictors of the regional model. In addition to quantiles, prediction intervals are also constructed, and the models are evaluated using different metrics. These prediction intervals are further improved through an adapted conformalized quantile regression methodology. Overall, the results show that deep networks are the best performing method for both solar and wind energy regions, producing narrow prediction intervals with good coverage

Pareto optimal prediction intervals with hypernetworks

As the relevance of probabilistic forecasting grows, the need of estimating multiple high-quality prediction intervals (PI) also increases. In the current state of the art, most deep neural network gradient descent-based methods take into account interval width and coverage into a single loss function, focusing on a unique nominal coverage target, and adding additional parameters to control the coverage-width trade-off. The Pareto Optimal Prediction Interval Hypernetwork (POPI-HN) approach developed in this work has been derived to treat this coverage-width trade-off as a multi-objective problem, obtaining a complete set of Pareto Optimal solutions (Pareto front). POPI-HN are able to be trained through gradient descent with no need to add extra parameters to control the width-coverage trade-off of PIs. Once the Pareto set has been obtained, users can extract the PI with the required coverage. Comparative results with recently introduced Quality-Driven loss show similar behavior in coverage while improving interval width for the majority of the studied domains, making POPI-HN a competing alternative for estimating uncertainty in regression tasks where PIs with multiple coverages are needed.This publication is part of the I+D+i project PID2019-107455RB-C22, funded by MCIN /AEI/10.13039/501100011033. This work was also supported by the Comunidad de Madrid Excellence Program. Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2022

Biocatalyzed synthesis of antidiabetic drugs: A review

The biocatalyzed production of building blocks for synthesizing drugs is a very attractive research field, because of the sustainability introduced in a synthetic schedule when chemical steps are substituted by biocatalyzed protocols. In this article, we will show how different antidiabetic drugs, for treating diabetes mellitus Type 1 and Type 2, can be more efficiently and effectively synthetized with the help of different types of biocatalysts. The huge overall drug market for these drugs, as well as the great number of people suffering from diabetes (the prevalence of all types of diabetes is growing), makes this topic attractive enough to focus on more efficient synthetic protocols for preparing antidiabetic drugs. Examples covering biocatalyzed synthesis of insulin analogues, sensitizers (PPAR agonists), secretagogues (GLP-1 analogues, GPR119 agonists) and enzyme inhibitors (α-glucosidase inhibitors, DPP4-inhibitors, SGLT-2 inhibitors and 11β-HSD1 inhibitors) will be presented

Counteracting effects of soil biota on emergence and growth of herbaceous plants

https://doi.org/10.5281/zenodo.7972878Background Plants condition the biotic composition of their rhizosphere. In turn, this plant legacy on the soil biota may affect the performance of plants recruiting in their vicinity. Unravelling how plant-soil legacies drive plant recruitment is key to understand vegetation dynamics and plant community assembly. Studies on the topic usually focus on the effects of soil microbiota as a whole, while the relative role of different guilds of soil organisms in the plant recruitment processes is not usually dissected. Aims Here, we used soils of Mediterranean woody plant species to test whether arbuscular mycorrhizal fungi (AMF) and small-size microbiota (< 50 µm) (MB) affect the germination success and growth of eight herbaceous plants. Results We documented a significant increase in seedling emergence probability when small-sized MB was present and no effect of AMF. In contrast, the aboveground plant biomass decreased with the presence of MB and increased with that of AMF. Interestingly, those plants growing in the absence of MB and in soils from woody plants associated with higher AMF richness developed higher aboveground biomass. Conclusion This study brings new evidence on how soil microbial communities can determine the performance of their associated herb community, and also, how the effects of different microbial guilds may change across the plant ontogeny. Given these results, the differential effect of soil microbial functional guilds should be considered to better understand plant soil legacies and feedbacks, potentially driving plant recruitment and community assembly.Universidad de Jaén/CBUAThe Spanish Ministerio de Economía y Competitividad (MEC) throughout COEXMED II project (CGL2015-69118-C2-1-P)University of Jaén through Acción 9 programme.Project LifeWatch-SUMHAL-WP5 (LWE2103014) (5.1.7

Screening of herbicides in grain legumes: pre-emergence herbicides in faba beans

Ante la escasez de herbicidas autorizados en leguminosas, se realizaron dos ensayos en habas con 10 herbicidas elegidos por estar autorizados en otras leguminosas o en otros países. Ninguno de los productos resultó totalmente eficaz y selectivo. Algunos de los herbicidas de preemergencia autorizados en España en habas para grano resultaron menos eficaces contra las malas hierbas y produjeron mayor fitotoxicidad que otros no autorizados. Así mismo, productos autorizados en Francia resultaron fitotóxicos en nuestras condiciones. Los mejores resultados seguido de ixosaben y aclonifen. Sin embargo será necesario ajustar dosis y buscar otras alternativas, como combinaciones de productos o estrategias de control para mejorar las eficacias y la selectividad, y sobre todo elegir los productos en función de las especies de malas hierbas dominantes en cada finca.Faced with a shortage of herbicides in legumes, two trials were conducted in faba beans to evaluate 10 herbicides elected by being authorized in other legumes or in other countries. None of the product was completely effective and selective. Some of the pre-emergence herbicides authorized in Spain for grain faba beans were less effective against weeds and produced more phytotoxicity than others not authorized. Likewise, products authorized in France turned out quite phytotoxic in our conditions. The best results were obtained with metribuzin by its effective weed control and low phytotoxicity, followed by ixosaben and aclonifen. However it will be necessary to adjust dose, to look for other alternatives, such as combinations of products or control strategies to improve effectiveness and selectivity, and above all choose the products depending on the species of dominant weeds in each farm