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Abstract Enhancing the supercapacitors’ performance relies on the increased capacitance and voltage window, which are the current key challenges for developing new materials. In this study, the mononuclear NiII‐bis(oxamato) complex ([nBu4N]2[Ni(opba)], 1) has been synthesized and used as a template in polypyrrole (PPy) based conductive polymer as a novel electrode material for supercapacitor applications. The surface and structural properties of PPy and PPy/1 electrodes were studied using SEM and TEM to elucidate their interactions. The results of characterization techniques revealed that complex 1 altered the morphology, creating a prominent three‐dimensional globular structure in the PPy/1 hybrid material without significant chemical modification. The electrochemical properties of PPy and PPy/1 were investigated by CV, EIS, and GCD analyses. The PPy/1 electrode demonstrated intense pseudocapacitive behavior, showing a significantly widened potential window and increased current compared to the PPy electrode, resulting in enhanced energy storage capacity within the material. This improvement was evaluated by testing a symmetric supercapacitor in a coin cell architecture with an alginate‐based gel acting as both electrolyte and separator. The maximum specific cell capacitance reached 41.6 F g−1 at a current density of 0.2 A g−1, with a remarkable capacity retention of 97 % after 1000 galvanostatic charge/discharge cycles.

# Background Patients with chronic lung disease (CLD), such as asthma or chronic obstructive pulmonary disease, were expected to have an increased risk of clinical manifestations and severity of COVID-19. However, these comorbidities have been reported less frequently than expected. Chronic treatment with inhaled corticosteroids (ICS) may impact the clinical course of COVID-19. The main objective of this study is to know the influence of chronic treatment with ICS on the prognosis of COVID-19 hospitalized patients with CLD. # Methods A multicenter retrospective cohort study was designed, including patients hospitalized with COVID-19. Epidemiological and clinical data were collected at admission and at seven days, and clinical outcomes were collected. Patients with CLD with and without chronic treatment with ICS were compared. # Results Two thousand five hundred ninety-eight patients were included, of which 1,171 patients had a diagnosis of asthma and 1,427 of COPD (53.37% and 41.41% with ICS, respectively). No differences were found in mortality, transfer to ICU, or development of moderate-severe ARDS. Patients with chronic ICS had a longer hospital stay in both asthma and COPD patients (9 vs. 8 days, *p =* 0.031 in asthma patients), (11 vs. 9 days, *p =* 0.018 in COPD patients); although they also had more comorbidity burden. # Conclusions Patients with chronic inhaled corticosteroids had longer hospital stays and more chronic comorbidities, measured by the Charlson comorbidity index, but they did not have more severe disease at admission, evaluated with qSOFA and PSI scores. Chronic treatment with inhaled corticosteroids had no influence on the prognosis of patients with chronic lung disease and COVID-19.

Computer vision has advanced much in recent years. Several tasks, such as image recognition, classification, or image restoration, are regularly solved with applications using artificial intelligence techniques. Image restoration comprises different use cases such as style transferring, improvement of quality resolution, or completing missing parts. The latter is also known as image inpainting, virtual image inpainting in this case, which consists of reconstructing missing regions or elements. This paper explores how to evaluate the performance of a deep learning method to do virtual image inpainting to reconstruct missing architectonical elements in images of ruined Greek temples to measure the performance of different activation functions. Unlike a previous study related to this work, a direct reconstruction process without segmented images was used. Then, two evaluation methods are presented: the objective one (mathematical metrics) and an expert (visual perception) evaluation to measure the performance of the different approaches. Results conclude that ReLU outperforms other activation functions, while Mish and Leaky ReLU perform poorly, and Swish’s professional evaluations highlight a gap between mathematical metrics and human visual perception.

Background: This study aimed to validate the role of the D-dimer to lymphocyte ratio (DLR) for mortality prediction in a large national cohort of hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: A retrospective, multicenter, observational study that included hospitalized patients due to SARS-CoV-2 infection in Spain was conducted from March 2020 to March 2022. All biomarkers and laboratory indices analyzed were measured once at admission. Results: A total of 10,575 COVID-19 patients were included in this study. The mean age of participants was 66.9 (±16) years, and 58.6% (6202 patients) of them were male. The overall mortality rate was 16.3% (n = 1726 patients). Intensive care unit admission was needed in 10.5% (n = 1106 patients), non-invasive mechanical ventilation was required in 8.8% (n = 923 patients), and orotracheal intubation was required in 7.5% (789 patients). DLR presented a c-statistic of 0.69 (95% CI, 0.68–0.71) for in-hospital mortality with an optimal cut-off above 1. Multivariate analysis showed an independent association for in-hospital mortality for DLR > 1 (adjusted OR 2.09, 95% CI 1.09–4.04; p = 0.03); in the same way, survival analysis showed a higher mortality risk for DLR > 1 (HR 2.24; 95% CI 2.03–2.47; p < 0.01). Further, no other laboratory indices showed an independent association for mortality in multivariate analysis. Conclusions: This study confirmed the usefulness of DLR as a prognostic biomarker for mortality associated with SARS-CoV-2 infection, being an accessible, cost-effective, and easy-to-use biomarker in daily clinical practice.

Enhancing the supercapacitors' performance relies on the increased capacitance and voltage window, which are the current key challenges for developing new materials. In this study, the mononuclear NiII‐bis(oxamato) complex ([nBu4N]2[Ni(opba)], 1) has been synthesized and used as a template in polypyrrole (PPy) based conductive polymer as a novel electrode material for supercapacitor applications. The surface and structural properties of PPy and PPy/1 electrodes were studied using SEM and TEM to elucidate their interactions. The results of characterization techniques revealed that complex 1 altered the morphology, creating a prominent three‐dimensional globular structure in the PPy/1 hybrid material without significant chemical modification. The electrochemical properties of PPy and PPy/1 were investigated by CV, EIS, and GCD analyses. The PPy/1 electrode demonstrated intense pseudocapacitive behavior, showing a significantly widened potential window and increased current compared to the PPy electrode, resulting in enhanced energy storage capacity within the material. This improvement was evaluated by testing a symmetric supercapacitor in a coin cell architecture with an alginate‐based gel acting as both electrolyte and separator. The maximum specific cell capacitance reached 41.6 F g−1 at a current density of 0.2 A g−1, with a remarkable capacity retention of 97 % after 1000 galvanostatic charge/discharge cycles. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to assess the influence of translucent monolithic versus bilayered crowns and whether the use of a CoCr base abutments affects the fatigue and fracture resistance of screwed implant‐supported single crowns with external connections under mechanical cycling. Materials and Methods: Fifty specimens were divided into groups: (1) metal–ceramic (MC) crown, (2) veneered zirconia crown (Zr), (3) veneered zirconia crown with a CoCr base abutment (ZrB), (4) monolithic translucent zirconia crown (MZr), and (5) monolithic translucent zirconia crown with a CoCr base abutment (MZrB). Specimens underwent mechanical cycling (5 × 106 cycles; 150 N) evaluating fatigue resistance (number of failures) and those that failed were subsequently subjected to fractographic analyses (stereomicroscope and scanning electron microscope) to evaluate failure location and area, and maximum fracture load was also measured. Results: The failure‐related survival rate (100%) and maximum fracture resistance of the MZrB were significantly higher than those of MC and Zr (50%; p < 0.05). There were no significant differences in the failure rate and fracture resistance when a CoCr base abutment was used or not in the translucent monolithic Zr groups (p > 0.05;MZrB vs. MZr). Failure location, with MC crowns' fractures, noted at the screw area (p = 0.043), while all‐ceramic crowns were mostly in the cuspid and to failure area, the Zr group had the largest mean (15.55 ± 9.17 mm2) among the groups, significant difference only when compared with MC (1.62 ± 0.81 mm2) (p = 0.025). Conclusions: Translucent monolithic zirconia crowns exhibited significantly higher fatigue and fracture resistance compared with conventional MC and bilayered crowns. Clinical Significance: The appropriate choice of material and manufacturing technique is crucial for predicting the higher clinical performance of single crowns. Enhanced mechanical resistance in terms of fatigue and fracture resistance can be achieved by replacing MC and bilayered restorations with computer‐aided design and computer‐aided manufacturing monolithic zirconia. [ABSTRACT FROM AUTHOR]

Computer vision has advanced much in recent years. Several tasks, such as image recognition, classification, or image restoration, are regularly solved with applications using artificial intelligence techniques. Image restoration comprises different use cases such as style transferring, improvement of quality resolution, or completing missing parts. The latter is also known as image inpainting, virtual image inpainting in this case, which consists of reconstructing missing regions or elements. This paper explores how to evaluate the performance of a deep learning method to do virtual image inpainting to reconstruct missing architectonical elements in images of ruined Greek temples to measure the performance of different activation functions. Unlike a previous study related to this work, a direct reconstruction process without segmented images was used. Then, two evaluation methods are presented: the objective one (mathematical metrics) and an expert (visual perception) evaluation to measure the performance of the different approaches. Results conclude that ReLU outperforms other activation functions, while Mish and Leaky ReLU perform poorly, and Swish's professional evaluations highlight a gap between mathematical metrics and human visual perception. [ABSTRACT FROM AUTHOR]

Background: This study aimed to validate the role of the D-dimer to lymphocyte ratio (DLR) for mortality prediction in a large national cohort of hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: A retrospective, multicenter, observational study that included hospitalized patients due to SARS-CoV-2 infection in Spain was conducted from March 2020 to March 2022. All biomarkers and laboratory indices analyzed were measured once at admission. Results: A total of 10,575 COVID-19 patients were included in this study. The mean age of participants was 66.9 (±16) years, and 58.6% (6202 patients) of them were male. The overall mortality rate was 16.3% (n = 1726 patients). Intensive care unit admission was needed in 10.5% (n = 1106 patients), non-invasive mechanical ventilation was required in 8.8% (n = 923 patients), and orotracheal intubation was required in 7.5% (789 patients). DLR presented a c-statistic of 0.69 (95% CI, 0.68–0.71) for in-hospital mortality with an optimal cut-off above 1. Multivariate analysis showed an independent association for in-hospital mortality for DLR > 1 (adjusted OR 2.09, 95% CI 1.09–4.04; p = 0.03); in the same way, survival analysis showed a higher mortality risk for DLR > 1 (HR 2.24; 95% CI 2.03–2.47; p < 0.01). Further, no other laboratory indices showed an independent association for mortality in multivariate analysis. Conclusions: This study confirmed the usefulness of DLR as a prognostic biomarker for mortality associated with SARS-CoV-2 infection, being an accessible, cost-effective, and easy-to-use biomarker in daily clinical practice. [ABSTRACT FROM AUTHOR]