Magnetism of small V clusters embedded in a Cu fcc matrix: an ab initio study

We present extensive first principles density functional theory (DFT) calculations dedicated to analyze the magnetic and electronic properties of small V$_{n}$ clusters (n=1,2,3,4,5,6) embedded in a Cu fcc matrix. We consider different cluster structures such as: i) a single V impurity, ii) several V$_{2}$ dimers having different interatomic distance and varying local atomic environment, iii) V$_{3}$ and iv) V$_{4}$ clusters for which we assume compact as well as 2- and 1-dimensional atomic configurations and finally, in the case of the v) V$_{5}$ and vi) V$_{6}$ structures we consider a square pyramid and a square bipyramid together with linear arrays, respectively. In all cases, the V atoms are embedded as substitutional impurities in the Cu network. In general, and as in the free standing case, we have found that the V clusters tend to form compact atomic arrays within the cooper matrix. Our calculated non spin-polarized density of states at the V sites shows a complex peaked structure around the Fermi level that strongly changes as a function of both the interatomic distance and local atomic environment, a result that anticipates a non trivial magnetic behavior. In fact, our DFT calculations reveal, in each one of our clusters systems, the existence of different magnetic solutions (ferromagnetic, ferrimagnetic, and antiferromagnetic) with very small energy differences among them, a result that could lead to the existence of complex finite-temperature magnetic properties. Finally, we compare our results with recent experimental measurements.Comment: 7 pages and 4 figure

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

MiRNAs in early brain development and pediatric cancer

The size and organization of the brain are determined by the activity of progenitor cells early in development. Key mechanisms regulating progenitor cell biology involve miRNAs. These small noncoding RNA molecules bind mRNAs with high specificity, controlling their abundance and expression. The role of miRNAs in brain development has been studied extensively, but their involvement at early stages remained unknown until recently. Here, recent findings showing the important role of miRNAs in the earliest phases of brain development are reviewed, and it is discussed how loss of specific miRNAs leads to pathological conditions, particularly adult and pediatric brain tumors. Let-7 miRNA downregulation and the initiation of embryonal tumors with multilayered rosettes (ETMR), a novel link recently discovered by the laboratory, are focused upon. Finally, it is discussed how miRNAs may be used for the diagnosis and therapeutic treatment of pediatric brain tumors, with the hope of improving the prognosis of these devastating diseases.A.P. was funded by a predoctoral fellowship from Fundación Tatiana Pérez de Guzmán el Bueno. Work in the lab was supported by grants from the European Research Council (309633) and the Spanish State Research Agency (PGC2018-102172-B-I00, as well as through the “Severo Ochoa” Programme for Centers of Excellence in R&D, ref. SEV-2017-0723).Peer reviewe

Emotional processing in Parkinson's disease and anxiety: an EEG study of visual affective word processing

A general problem in the design of an EEG-BCI system is the poor quality and low robustness of the extracted features, affecting overall performance. However, BCI systems that are applicable in real-time and outside clinical settings require high performance. Therefore, we have to improve the current methods for feature extraction. In this work, we investigated EEG source reconstruction techniques to enhance the extracted features based on a linearly constrained minimum variance (LCMV) beamformer. Beamformers allow for easy incorporation of anatomical data and are applicable in real-time. A 32-channel EEG-BCI system was designed for a two-class motor imagery (MI) paradigm. We optimized a synchronous system for two untrained subjects and investigated two aspects. First, we investigated the effect of using beamformers calculated on the basis of three different head models: a template 3-layered boundary element method (BEM) head model, a 3-layered personalized BEM head model and a personalized 5-layered finite difference method (FDM) head model including white and gray matter, CSF, scalp and skull tissue. Second, we investigated the influence of how the regions of interest, areas of expected MI activity, were constructed. On the one hand, they were chosen around electrodes C3 and C4, as hand MI activity theoretically is expected here. On the other hand, they were constructed based on the actual activated regions identified by an fMRI scan. Subsequently, an asynchronous system was derived for one of the subjects and an optimal balance between speed and accuracy was found. Lastly, a real-time application was made. These systems were evaluated by their accuracy, defined as the percentage of correct left and right classifications. From the real-time application, the information transfer rate (ITR) was also determined. An accuracy of 86.60 ± 4.40% was achieved for subject 1 and 78.71 ± 0.73% for subject 2. This gives an average accuracy of 82.66 ± 2.57%. We found that the use of a personalized FDM model improved the accuracy of the system, on average 24.22% with respect to the template BEM model and on average 5.15% with respect to the personalized BEM model. Including fMRI spatial priors did not improve accuracy. Personal fine- tuning largely resolved the robustness problems arising due to the differences in head geometry and neurophysiology between subjects. A real-time average accuracy of 64.26% was reached and the maximum ITR was 6.71 bits/min. We conclude that beamformers calculated with a personalized FDM model have great potential to ameliorate feature extraction and, as a consequence, to improve the performance of real-time BCI systems