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Functional shape memory alloys need to operate reversibly and repeatedly. Quantitative measures of reversibility include the relative volume change of the participating phases and compatibility matrices for twinning. But no similar argument is known for repeatability. This is especially crucial for many future applications, such as artificial heart valves or elastocaloric cooling, in which more than 10 million transformation cycles will be required. We report on the discovery of an ultralow-fatigue shape memory alloy film system based on TiNiCu that allows at least 10 million transformation cycles. We found that these films contain Ti₂Cu precipitates embedded in the base alloy that serve as sentinels to ensure complete and reproducible transformation in the course of each memory cycle.

We describe the design and fabrication of miniaturized origami structures based on thin-film shape memory alloys. These devices are attractive for medical implants, as they overcome the opposing requirements of crimping the implant for insertion into an artery while keeping sensitive parts of the implant nearly stress-free. The designs are based on a group theory approach in which compatibility at a few creases implies the foldability of the whole structure. Importantly, this approach is versatile and thus provides a pathway for patient-specific treatment of brain aneurysms of differing shapes and sizes. The wafer-based monolithic fabrication method demonstrated here, which comprises thin-film deposition, lithography, and etching using sacrificial layers, is a prerequisite for any integrated self-folding mechanism or sensors and will revolutionize the availability of miniaturized implants, allowing for new and safer medical treatments.

The development and growth of Wireless Sensor Networks (WSNs) is significantly propelled by advances in Radio Frequency (RF) and Visible Light Communication (VLC) technologies. This paper endeavors to present a comprehensive review of the state-of-the-art in cognitive hybrid RF-VLC systems for WSNs, emphasizing the critical task of seamlessly integrating Cognitive Radio Sensor Networks (CRSNs) and VLC technologies. The central challenge addressed is the intricate landscape of this integration, characterized by notable trade-offs between performance and complexity, which escalate with the addition of more devices and increased data rates. This scenario necessitates the development of advanced cognitive radio strategies, potentially facilitated by Machine Learning (ML) and Deep Learning (DL) approaches, albeit introducing new complexities such as the necessity for pre-training with extensive datasets. The review scrutinizes the fundamental aspects of CRSNs and VLC, spotlighting key areas like Energy Efficient Resource Allocation, Industrial Scenarios, and Energy Harvesting, and explores the synergistic amalgamation of these technologies as a promising pathway for enhanced spectrum utilization and network performance. By delving into the integration of cognitive radio technology with visible light, this study furnishes valuable insights into the potential for innovative applications in wireless communication, presenting a balanced overview of the current advancements and prospective avenues in the field of cognitive hybrid RF/VLC systems.

While diseases caused by nematodes remains a considerable drawback for the livestock, agriculture and public health, anthelmintics drug resistance has been observed over the past years and is a major concern for parasite control. Ivermectin, initially considered as a highly potent drug, currently presents a reduced anti-helminthic efficacy, which is influenced by expression of several ATP-binding cassette transporters (ABC), among them the P-glycoproteins (Pgps). Here we present some evidences of Pgps dominance during Ivermectin resistance/susceptibility using Pgps double silencing in C. elegans and the phylogenetic relationship of Pgps among nematodes, which strengthen the use of this model for study of drug resistance in nematodes. Firstly, we evaluated the quantitative gene expression of 12 out the 15 known Pgps from resistant and WT strains of C. elegans, we demonstrated the upregulation of Pgps 12 and 13 and downregulation of all remaining Pgps in ivermectin resistant strain. By using an RNAi loss-of-function approach we observed that Pgp 12 gene silencing reverts the resistance phenotype to ivermectin, while Pgp 4 gene silencing does not alter the resistance phenotype but induces a resistance in wild type strain. Interestingly, the dual silencing of Pgp 12 and Pgp 4 expression demonstrates the dominance of phenotype promoted by Pgp 12 silencing. Finally, in silico analysis reveals a close relationship between Pgps from C. elegans and several nematodes parasites. Taken together, our results indicate that Pgp 12 is crucial for the resistance to ivermectin and thus a good candidate for further studies aiming to develop specific inhibitors to this transporter, allowing the continuous use of ivermectin to control the burden on animal and human health inflicted by nematode parasites globally.

Interaction between Equatorial Plasma Bubbles (EPBs) and midnight Brightness wave (MBW) was observed over Bom Jesus da Lapa (13.3° S, 43.5° W; Quasi-Dipole geomagnetic latitude of 14.1° S), using OI 630 nm all-sky images. On the night of December 22nd, 2019, an EPB was seen propagating eastward in its fossil stage until it interacted with an MBW. After the interaction, the west walls of EPBs generated secondary instabilities that can be associated with gradient drift instability (GDI) and/or Kelvin–Helmholtz instabilities (KHI). We suggest that the MBW contributed to generate a shear in the EPBs walls due to changes in the thermospheric dynamics, such as neutral wind in the F layer height. Furthermore, spectral analysis of the all-sky images suggests that GDI and/or KHI generated turbulence and helped to dissipate the EPBs.

Four geographical zones are defined along the trench that is formed due to the subduction of the Nazca plate underneath the South American plate; they are denoted A, B, C and D from north to south; zones A, B and D had a major earthquake after 2010 (magnitude over 8.0), while zone C has not, thus offering a contrast for comparison. For each zone, a sequence of intervals between consecutive seisms with magnitudes greater than or equal to 3.0 is set up and then characterized by Shannon entropy and mutability. These methods show a correlation after a major earthquake in what is known as the aftershock regime but show independence otherwise. Exponential adjustments to these parameters reveal that mutability offers a wider range for the parameters to characterize the recovery compared to the values of the parameters defining the background activity for each zone before a large earthquake. It is found that the background activity is particularly high for zone A, still recovering for zone B, reaching values similar to those of zone A in the case of zone C (without recent major earthquake) and oscillating around moderate values for zone D. It is discussed how this can be an indication of more risk of an important future seism in the cases of zones A and C. The similarities and differences between Shannon entropy and mutability are discussed and explained.

The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

To describe the impact of different doses of corticosteroids on the evolution of patients with COVID-19 pneumonia, based on the potential benefit of the non-genomic mechanism of these drugs at higher doses. Observational study using data collected from the SEMI-COVID-19 Registry. We evaluated the epidemiological, radiological and analytical scenario between patients treated with megadoses therapy of corticosteroids vs low-dose of corticosteroids and the development of complications. The primary endpoint was all-cause in-hospital mortality according to use of corticosteroids megadoses. Of a total of 14,921 patients, corticosteroids were used in 5,262 (35.3%). Of them, 2,216 (46%) specifically received megadoses. Age was a factor that differed between those who received megadoses therapy versus those who did not in a significant manner (69 years [IQR 59-79] vs 73 years [IQR 61-83]; p < .001). Radiological and analytical findings showed a higher use of megadoses therapy among patients with an interstitial infiltrate and elevated inflammatory markers associated with COVID-19. In the univariate study it appears that steroid use is associated with increased mortality (OR 2.07 95% CI 1.91-2.24 p < .001) and megadose use with increased survival (OR 0.84 95% CI 0.75-0.96, p 0.011), but when adjusting for possible confounding factors, it is observed that the use of megadoses is also associated with higher mortality (OR 1.54, 95% CI 1.32-1.80; p < .001). There is no difference between megadoses and low-dose (p .298). Although, there are differences in the use of megadoses versus low-dose in terms of complications, mainly infectious, with fewer pneumonias and sepsis in the megadoses group (OR 0.82 95% CI 0.71-0.95; p < .001 and OR 0.80 95% CI 0.65-0.97; p < .001) respectively. There is no difference in mortality with megadoses versus low-dose, but there is a lower incidence of infectious complications with glucocorticoid megadoses.

Skin fragment with cystic formation which is lined by epithelium epidermoid with a prominent granular layer (arrow) and filled with lamellated keratin material (asterisk) (H&E, 10×). [...]it is necessary to take a multidisciplinary approach in order to find a correct diagnosis. CONFLICT OF INTEREST None of the authors have conflicts of interest to report regarding this manuscript.