We demonstrate how to process comprehensive two-dimensional gas chromatograms (GC × GC chromatograms) to remove nonsample information (artifacts), including background and retention time shifts. We also demonstrate how this, combined with further reduction of the influence of irrelevant information, allows for data analysis without integration or peak deconvolution (pixel-based analysis).
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http://dx.doi.org/10.1021/ac403650d | DOI Listing |
Int J Remote Sens
November 2024
Department of Physical Geography, Utrecht University, Utrecht, The Netherlands.
Tidal flat ecosystems, are under steady decline due to anthropogenic pressures including sea level rise and climate change. Monitoring and managing these coastal systems requires accurate and up-to-date mapping. Sediment characteristics and macrozoobenthos are major indicators of the environmental status of tidal flats.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Departamento de Geografía, Facultad de Ciencias, Universidad de la República, Montevideo 4225, Uruguay.
Recent advancements in Earth Observation sensors, improved accessibility to imagery and the development of corresponding processing tools have significantly empowered researchers to extract insights from Multisource Remote Sensing. This study aims to use these technologies for mapping summer and winter Land Use/Land Cover features in Cuenca de la Laguna Merín, Uruguay, while comparing the performance of Random Forests, Support Vector Machines, and Gradient-Boosting Tree classifiers. The materials include Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission imagery, Google Earth Engine, training and validation datasets and quoted classifiers.
View Article and Find Full Text PDFJ Chromatogr A
January 2025
School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. Electronic address:
The evolution of precursors to form secondary organic aerosol (SOA) is still a challenge in atmospheric chemistry. Chamber experiments were conducted to simulate the ambient OH oxidation of naphthalene and α-pinene, which are typical markers of anthropogenic and biogenic emissions. Particulate matters were sampled by quartz filters and were analyzed by comprehensive two-dimensional gas chromatography (GC×GC) coupled with a thermal desorption system (TD) and a mass spectrometer (MS).
View Article and Find Full Text PDFSci Rep
December 2024
Department of Neurology, Mayo Clinic, Jacksonville, MN, USA.
We developed a simple quantifiable scoring system that predicts aneurysmal subarachnoid hemorrhage (aSAH) mortality, delayed cerebral ischemia (DCI), and modified Rankin scale (mRS) outcomes using readily available SAH admission data with SAH volume (SAHV) measured on computed tomography (CT). We retrospectively analyzed a cohort of 277 patients with aSAH admitted at our Comprehensive Stroke Center at Mayo Clinic in Jacksonville, Florida, between January 5, 2012, and February 24, 2022. We developed a mathematical radiographic model SAHV that measures basal cisternal SAH blood volume using a derivation of the ABC/2 ellipsoid formula (A = width/thickness, B = length, C = vertical extension) on noncontrast CT, which we previously demonstrated is comparable to pixel-based manual segmentation on noncontrast CT.
View Article and Find Full Text PDFTrends Mol Med
December 2024
Tianjin Cancer Institute, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China. Electronic address:
Deep learning has revolutionized cancer diagnostics, shifting from pixel-based image analysis to more comprehensive, patient-centric care. This opinion article explores recent advancements in neural network architectures, highlighting their evolution in biomedical research and their impact on medical imaging interpretation and multimodal data integration. We emphasize the need for domain-specific artificial intelligence (AI) systems capable of handling complex clinical tasks, advocating for the development of multimodal large language models that can integrate diverse data sources.
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