Airborne gamma spectrometry is an effective tool for prompt monitoring and mapping of large areas contaminated after NPP accident, radionuclides leakage cases, an impact of uranium ore mining and processing, etc. Airborne spectrometry data analysis using deconvolution technique enables to calculate air kerma rates and/or radionuclides concentrations as well as identification of radionuclides. Application of this technique on the airborne data (from manned as well as an unmanned survey using drones) is rather specific due to the requirements for short time of one scan data acquisition, a relatively long distance from the source and small detector size, due to the limited payload of the usually used drones. Application of deconvolution techniques for analysis of spectra with very poor statistics, methods and possibilities to improve the processing of such spectra are discussed.
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http://dx.doi.org/10.1093/rpd/ncz209 | DOI Listing |
BMC Genomics
January 2025
Department of Virology, Norwegian Institute of Public Health, Oslo, 0456, Norway.
The COVID-19 pandemic has underscored the importance of virus surveillance in public health and wastewater-based epidemiology (WBE) has emerged as a non-invasive, cost-effective method for monitoring SARS-CoV-2 and its variants at the community level. Unfortunately, current variant surveillance methods depend heavily on updated genomic databases with data derived from clinical samples, which can become less sensitive and representative as clinical testing and sequencing efforts decline.In this paper, we introduce HERCULES (High-throughput Epidemiological Reconstruction and Clustering for Uncovering Lineages from Environmental SARS-CoV-2), an unsupervised method that uses long-read sequencing of a single 1 Kb fragment of the Spike gene.
View Article and Find Full Text PDFNowadays, spaceborne LiDAR technology, particularly ICESat-2, has become a transformative tool in marine environmental research. Unlike traditional passive optical remote sensing methods, ICESat-2 offers detailed vertical structure mapping of oceanic optical properties. Despite the potential of ICESat-2 for observing the optical vertical structure, its application in the East China Sea with complex hydrological conditions and dynamic ecosystems remains limited.
View Article and Find Full Text PDFJ Transl Med
January 2025
Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Background: Tumor microenvironment (TME), particularly immune cell infiltration, programmed cell death (PCD) and stress, has increasingly become a focal point in colorectal cancer (CRC) treatment. Uncovering the intricate crosstalk between these factors can enhance our understanding of CRC, guide therapeutic strategies, and improve patient prognosis.
Methods: We constructed an immune-related cell death and stress (ICDS) prognostic model utilizing machine learning methodologies.
Thyroid
January 2025
Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-gu, Republic of Korea.
Although patients with anaplastic thyroid cancer (ATC) generally have a poor prognosis and there are currently no effective treatment options, survival and response to therapy vary between patients. Genomic and transcriptomic profiles of ATC have been reported; however, a comprehensive study of the tumor microenvironment (TME) of ATC is still lacking. This study aimed to elucidate the TME characteristics associated with ATC and their prognostic implications.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, TamilNadu India.
Emotion recognition plays a crucial role in brain-computer interfaces (BCI) which helps to identify and classify human emotions as positive, negative, and neutral. Emotion analysis in BCI maintains a substantial perspective in distinct fields such as healthcare, education, gaming, and human-computer interaction. In healthcare, emotion analysis based on electroencephalography (EEG) signals is deployed to provide personalized support for patients with autism or mood disorders.
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