The novel coronavirus SARS-CoV-2 is the cause of an ongoing pandemic. The highest mortality rate is observed among the older adult population. During the first wave of the pandemic (March-June 2020), following a national health decree demanding that no visitors or family members be allowed in health institutions, our geriatric rehabilitation center closed gates to all visitors from the outside. We aimed to assess the rehabilitation outcomes of older patients with hip fractures in the first pandemic wave, who underwent rehabilitation under complete social isolation from primary care givers and family members. This was a retrospective cohort study. It took place at a university-affiliated, major postacute geriatric rehabilitation center. Rehabilitation outcomes measured were discharge functional independence measure (FIM) score and motor FIM score, FIM score change, motor FIM score change, favorable motor FIM effectiveness, length of stay, discharge destination, and home aid at discharge. The study group did not have a detrimental effect on the rehabilitation outcomes of these patients. More evidence must be gathered and presented on the matter.In this study, we perform ab initio calculations, using density functional theory, to provide more insights about the role of alkane chain in primary amine capped (CdSe)33 and (CdS)33 quantum dots (QDs). We passivate the QDs surfaces with seven primary amines of different carbon chain lengths starting from NH3 to hexylamine. The primary amine ligands induce a blue shift in the band gap of the ligated QDs, in agreement with experimental studies, but the alkane chain itself show negligible changes in the band gap. By increasing the chain length the binding energy between ligands and the QDs increases but its rate decreases due to the increase of steric hindrance between the ligands. The role of van der Waals forces in such behavior is found to be notable which is done by performing geometry optimization through adding and neglecting the dispersion correction effects for each system. The results of this study can provide helpful information for ligand selectivity in controlling the size and properties of the QDs using primary amines.Although many schemes have been proposed to obtain full half-metallicity in zigzag silicene nanoribbons with edge monohydrogenation (H-H ZSiNRs) by chemical modification, the resulted negligible energy difference between the antiferromagnetic (AFM) and ferromagnetic (FM) configurations makes the half-metallicity hardly observable practically. In this work, based on density functional calculations, we find that the ZSiNRs with edge dihydrogenation (H2-H2 ZSiNRs) can be tuned to be half-metallic by replacing the central two zigzag Si chains with two zigzag Al-P chains, and more importantly, the FM-AFM energy difference is significantly increased compared with the H-H cases. The obtained half-metallicity originates from the different potential between two edges of the ribbon after doping, which results in the edge states of two spin channels shifting oppositely in energy. VVD-214 This mechanism is so robust that the half-metallicity can always be achieved, irrespective of the ribbon width. Our finding provides a fantastic way for achieving stable half-metallicity in ZSiNRs.Classification of EEG-based motor imagery (MI) is a crucial non-invasive application in brain-computer interface (BCI) research. This paper proposes a novel convolutional neural network (CNN) architecture for accurate and robust EEG-based MI classification that outperforms the state-of-the-art methods. The proposed CNN model, namely EEG-Inception, is built on the backbone of the Inception-Time network, which has showed to be highly efficient and accurate for time-series classification. Also, the proposed network is an end-to-end classification, as it takes the raw EEG signals as the input and does not require complex EEG signal-preprocessing. Furthermore, this paper proposes a novel data augmentation method for EEG signals to enhance the accuracy, at least by 3%, and reduce overfitting with limited BCI datasets. The proposed model outperforms all state-of-the-art methods by achieving the average accuracy of 88.4% and 88.6% on the 2008 BCI Competition IV 2a (four-classes) and 2b datasets (binary-classes), respectively. Furthermore, it takes less than 0.025 seconds to test a sample suitable for real-time processing. Moreover, the classification standard deviation for nine different subjects achieves the lowest value of 5.5 for the 2b dataset and 7.1 for the 2a dataset, which validates that the proposed method is highly robust. From the experiment results, it can be inferred that the EEG-Inception network exhibits a strong potential as a subject-independent classifier for EEG-based MI tasks.The aim of this study was to obtain hierarchical scaffolds combining 3D printing and two electrofluidodynamic methods. The multi-layered scaffold is composed by 3D printed struts, electrospun fibers obtained from poly(ε-caprolactone) (PCL) and electrosprayed spheres produced from hydrophobically modified chitosan, namely chitosan grafted with linoleic acid (CHLA). Since CHLA has been used for the first time in the electrospraying (EDS) process, the formation of spheres needed an optimization process. The EDS process was strongly affected by the solvent mixture composition, concentration of acid used for CHLA dissolution and solution flow rate. By using the optimized electrospraying conditions, uniformly distributed spheres have been obtained, decorating struts and nanofibers. Preliminary biological tests with mouse preosteoblasts (MC3T3-E1) were performed to investigate the effect of the hierarchical scaffold on cell seeding efficacy. Results showed that the hierarchical structure enhances cell seeding efficacy, respect to the 3D printed struts alone, preventing that the cells passed through the struts during the seeding. Moreover, the addition of the electrosprayed nanoparticles does not affect the cell seeding efficiency. The versatility of the proposed structure, with the added value of CHLA nanoparticles decoration could be suitable for several applications in tissue engineering, mainly related to drug delivery systems.