The use of Raman microspectroscopy to depth profile multi-layered polymer laminates is becoming increasingly popular. However, the results are generally degraded by aberrations introduced by the change in refractive index at the air/sample interface. Recent research has suggested that the use of an immersion oil and suitable objective can reduce this effect. This study evaluates this proposal by comparing depth profiling results on a multi-layer poly(styrene)/poly(methylmethacrylate) (PS/PMMA) laminate polymer from both dry metallurgical objectives and immersion objectives (used in combination with an oil of suitable refractive index). The immersion technique enabled successful depth profiling to the full working distance of the objective (100 microm), showing clear and distinct variations in 11 different layers within the laminate; a dry metallurgical objective used for comparison achieved poor resolution of only two layers. This is the first demonstration of depth profiling within a polymer laminate to this depth. The depth profiling results are compared to results obtained by sectioning the PS/PMMA sample after setting it in resin.
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Anal Chim Acta
February 2025
Department of Chemistry, University of Waterloo, Waterloo, ON, Canada. Electronic address:
Background: Normothermic ex situ heart perfusion (ESHP) has emerged as a valid modality for advanced cardiac allograft preservation and conditioning prior to transplantation though myocardial function declines gradually during ESHP thus limiting its potential for expanding the donor pool. Recently, the utilization of dialysis has been shown to preserve myocardial and coronary vasomotor function. Herein, we sought to determine the changes in myocardial metabolism that could support this improvement.
View Article and Find Full Text PDFSci Total Environ
January 2025
Center for Marine Sensors, Institute for Chemistry and Biology of the Marine Environment (ICBM), Carl von Ossietzky University of Oldenburg, 26382 Wilhelmshaven, Germany.
Microplastics (MP) are known to be ubiquitous. The pathways and fate of these contaminants in the marine environment are receiving increasing attention, but still knowledge gaps exist. In particular, the link between mass-based MP quantification and oceanographic parameters is often lacking.
View Article and Find Full Text PDFNutrients
January 2025
Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy.
Non-celiac gluten/wheat sensitivity (NCGWS) is a syndrome for which pathogenesis and management remain debated. It is described as a condition characterized by gastrointestinal and extra-intestinal symptoms rapidly occurring after gluten ingestion in subjects who have had celiac disease or wheat allergy excluded. To date, the diagnosis of NCGWS is challenging as no universally recognized biomarkers have been yet identified, nor has a predisposing genetic profile been described.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Laboratory of Geophysical EM Probing Technologies, Ministry of Natural Resources, Dongli, Tianjin 300300, China.
The strong multi-stage tectonic movement caused the northwest of the North China Plain to rise and the southeast to fall. The covering layer in the plain area was several kilometers thick. In addition to expensive drilling, it is difficult to obtain deep geological information through traditional geological exploration.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100811, China.
While deep learning techniques have been extensively employed in malware detection, there is a notable challenge in effectively embedding malware features. Current neural network methods primarily capture superficial characteristics, lacking in-depth semantic exploration of functions and failing to preserve structural information at the file level. Motivated by the aforementioned challenges, this paper introduces MalHAPGNN, a novel framework for malware detection that leverages a hierarchical attention pooling graph neural network based on enhanced call graphs.
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