Drones, Volume 6; https://doi.org/10.3390/drones6100276
The advancement in computing and telecommunication has broadened the applications of drones beyond military surveillance to other fields, such as agriculture. Livestock farming using unmanned aerial vehicle (UAV) systems requires surveillance and monitoring of animals on relatively large farmland. A reliable communication system between UAVs and the ground control station (GCS) is necessary to achieve this. This paper describes learning-based communication strategies and techniques that enable interaction and data exchange between UAVs and a GCS. We propose a deep auto-encoder UAV design framework for end-to-end communications. Simulation results show that the auto-encoder learns joint transmitter (UAV) and receiver (GCS) mapping functions for various communication strategies, such as QPSK, 8PSK, 16PSK and 16QAM, without prior knowledge.
Brain Sciences, Volume 12; https://doi.org/10.3390/brainsci12101293
To study the biodistribution of new chemical and biological entities, an in vitro model of the blood–brain barrier (BBB) may become an essential tool during early phases of drug discovery. Here, we present a proof-of-concept of an in-house designed three-dimensional BBB biochip designed by us. This three-dimensional dynamic BBB model consists of endothelial cells and astrocytes, co-cultured on opposing sides of a polymer-coated membrane under flow mimicking blood flow. Our results demonstrate a highly effective BBB as evidenced by (i) a 30-fold increase in transendothelial electrical resistance (TEER), (ii) a significantly higher expression of tight junction proteins, and (iii) the low FITC–dextran permeability of our technical solution as compared to a static in vitro BBB model. Importantly, our three-dimensional BBB model effectively expresses P-glycoprotein (Pg-p), a hallmark characteristic for brain-derived endothelial cells. In conclusion, we provide here a complete holistic approach and insight to the whole BBB system, potentially delivering translational significance in the clinical and pharmaceutical arenas.
Metals, Volume 12; https://doi.org/10.3390/met12101601
The energy used to melt the material at each layer during laser-directed energy deposition (L-DED) accumulates in the solidified layers upon layer deposition and leads to an increase in the temperature of the part with an increasing number of layers. This heat accumulation can lead to inhomogeneous solidification conditions, increasing residual stresses and potentially anisotropic mechanical properties due to columnar grain structures. In this work, infrared imaging is applied during the directed energy deposition process to capture the evolution of the temperature field in high spatial and temporal evolutions. Image processing algorithms determined the solidification rate and the temperature gradient in the spatial and temporal evolutions and evidenced their change with the proceeding deposition process. Metallographic analysis proves that these changes significantly affect the local grain structure of the L-DED fabricated parts. The study provides comprehensive quantitative measurements of the change in the solidification variables in local and temporal resolutions. The comprehensive comparison of different parameter combinations reveals that applied power, and especially the frequency of the consecutive deposition of the individual layers, are the key parameters to adjusting heat accumulation. These findings provide a methodology for optimising L-DED manufacturing processes and tailoring the local microstructure development by controlling heat accumulation.
Remote Sensing, Volume 14; https://doi.org/10.3390/rs14194792
Remote sensing is a method used for monitoring and measuring agricultural crop fields. Unmanned aerial vehicles (UAV) are used to effectively monitor crops via different camera technologies. Even though aerial imaging can be considered a rather straightforward process, more focus should be given to data quality and processing. This research focuses on evaluating the influences of field conditions on raw data quality and commonly used vegetation indices. The aerial images were taken with a custom-built UAV by using a multispectral camera at four different times of the day and during multiple times of the season. Measurements were carried out in the summer seasons of 2019 and 2020. The imaging data were processed with different software to calculate vegetation indices for 10 reference areas inside the fields. The results clearly show that NDVI (normalized difference vegetation index) was the least affected vegetation index by the field conditions. The coefficient of variation (CV) was determined to evaluate the variations in vegetation index values within a day. Vegetation index TVI (transformed vegetation index) and NDVI had coefficient of variation values under 5%, whereas with GNDVI (green normalized difference vegetation index), the value was under 10%. Overall, the vegetation indices that include near-infrared (NIR) bands are less affected by field condition changes.
Diversity, Volume 14; https://doi.org/10.3390/d14100798
Based on the critical review of the literature published in the last 22 years, an attempt was made to evaluate the current knowledge gap on the distribution and status of the native Testudines taxa occurring in Sicily (namely Caretta caretta, Emys trinacris, and Testudo hermanni hermanni), as well as the available knowledge of the only non-native species with putative viable populations occurring on the island, i.e., Trachemys scripta. Summarizing the current information, all of the Testudines species occurring in Sicily showed a fragmented and incompletely-known distribution, and only scarce data are available about their phenology. Moreover, despite their inclusion of international and national laws (Bern Convention, CITES, Habitat directive), all three native species are facing several threats (e.g., habitat alteration, the occurrence of invasive species, parasite spillover) leading to a reduction of their populations on the island. Future monitoring programs on the island should be enhanced, with an emphasis on those taxa in decline. Moreover, involve Citizen Science programs should also be implemented in order to increase the awareness of non-experts and facilitate the monitoring task.
Applied Sciences, Volume 12; https://doi.org/10.3390/app12199633
The carbon/TiO2 hybrid dots (C/TiO2-Dots) are structurally TiO2 nanoparticles (in the order of 25 nm in diameter from commercially available colloidal TiO2 samples) surface-attached by nanoscale carbon domains with organic moieties, thus equivalent to hybrids of individual TiO2 nanoparticles each decorated with many carbon dots. These hybrid dots with exposure to visible light exhibit potent antibacterial properties, similar to those found in neat carbon dots with the same light activation. The results from the use of established scavengers for reactive oxygen species (ROS) to “quench” the antibacterial activities, an indication for shared mechanistic origins, are also similar. The findings in experiments on probing biological consequences of the antibacterial action suggest that the visible light-activated C/TiO2-Dots cause significant damage to the bacterial cell membrane, resulting in higher permeability, with the associated oxidative stress leading to lipid peroxidation, inhibiting bacterial growth. The induced bacterial cell damage could be observed more directly in the transmission electron microscopy (TEM) imaging. Opportunities for the further development of the hybrid dots platform for a variety of antibacterial applications are discussed.
Cancers, Volume 14; https://doi.org/10.3390/cancers14194671
The formation of stress granules (SG) is regarded as a cellular mechanism to temporarily limit protein synthesis and prevent the unfolding of proteins in stressed cells. It has been noted that SG formation can promote the survival of stressed cells. Paradoxically, however, persistent SGs could cause cell death. The underlying molecular mechanism that affects the relationship between SG dynamics and cellular states is not fully understood. Here we found that SG dynamics in cancer cells differ significantly from those in normal cells. Specifically, prolonged stress caused the formation of persistent SGs and consequently resulted in apoptosis in the normal cells. By contrast, cancer cells resolved SGs and survived the prolonged stress. Regarding the mechanism, the knockdown of HSP70 or the inhibition of the HSP70s’ ATPase activity caused defective SG clearance, leading to apoptosis in otherwise healthy cancer cells. On the other hand, the knockout of G3BPs to block the formation of SGs allowed cancer cells to escape from the HSP70 inhibition-induced apoptosis. Given the observation that SG dynamics were barely affected by the inhibition of autophagy or proteasome, we propose that SG dynamics are regulated mainly by HSP70-mediated refolding of the unfolded proteins or their removal from SGs. As a result, cancer cells evade stress-induced apoptosis by promoting the HSP70-dependent SG clearance.
Marine drugs, Volume 20; https://doi.org/10.3390/md20100602
The first investigation of the South China Sea soft coral Sarcophyton boettgeri afforded five new capnosane diterpenes, sarboettgerins A–E (1–5), together with one known related compound, pavidolide D (6). Their structures, including absolute configurations, were elucidated by the extensive spectroscopic analysis, 13C NMR calculations, and X-ray diffraction. Among them, new compounds 1–5 were featured by the rarely encountered Z-geometry double bond Δ1 within the 5/11-fused bicyclic capnosane carbon framework. Plausible biogenetic relationships of all isolates were proposed, and they might give an insight into future biomimetic synthesis of these novel compounds. In an in vitrobioassay, compound 5 displayed potent anti-neuroinflammatory activity against LPS-induced NO release in BV-2 microglial cells, which might be developed as a new type of potential neuroprotective agent in future.
Microorganisms, Volume 10; https://doi.org/10.3390/microorganisms10101903
The prompt presumptive identification of methicillin-resistant Staphylococcus aureus (MRSA) using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) can aid in early clinical management and infection control during routine bacterial identification procedures. This study applied a machine learning approach to MALDI-TOF peaks for the presumptive identification of MRSA and compared the accuracy according to staphylococcal cassette chromosome mec (SCCmec) types. We analyzed 194 S. aureus clinical isolates to evaluate the machine learning-based identification system (AMRQuest software, v.2.1, ASTA: Suwon, Korea), which was constructed with 359 S. aureus clinical isolates for the learning dataset. This system showed a sensitivity of 91.8%, specificity of 83.3%, and accuracy of 87.6% in distinguishing MRSA. For SCCmec II and IVA types, common MRSA types in a hospital context, the accuracy was 95.4% and 96.1%, respectively, while for the SCCmec IV type, it was 21.4%. The accuracy was 90.9% for methicillin-susceptible S. aureus. This presumptive MRSA identification system may be helpful for the management of patients before the performance of routine antimicrobial resistance testing. Further optimization of the machine learning model with more datasets could help achieve rapid identification of MRSA with less effort in routine clinical procedures using MALDI-TOF MS as an identification method.
Land, Volume 11; https://doi.org/10.3390/land11101657
In the context of territorial development, the construction of specific and competitive local resources is based on the identification of their intangible and material elements but also their links to the region. The connection between these links and local heritage, along with their spatial dimension, makes the active participation of residents in the entire process necessary. This paper presents the application of an integrated methodology that fosters the involvement of residents in a process of collecting relevant implicit information, with the assistance of experts, in order to identify cultural resources from different historical periods. This methodology is based on the synergy of three components: interdisciplinarity, local community participation, and the use of non-destructive cutting-edge technologies (remote sensing, UAV mapping, ground-penetrating radar, and 3D GIS interactive representations). The use of various methods and tools is organized in successive phases, the objective being the substantial participation of residents through 3D interactive visualisations of their area. 3D representations enable the activation of local memory in conjunction with the collection of information regarding location, type, and traces of cultural resources. The entire process validates the implicit information that guides the competent authorities and experts in the further search for more precise information, both from satellite data (high-resolution images) and images from subsurface mapping (ground-penetrating radar). The proposed methodology significantly accelerates the process of identifying cultural resources and provides a comprehensive picture to local government and cultural institutions about the area’s cultural resources and planning possibilities while reducing the failures and costs of the research process.