RESUMO
A composite material composed of anodized aluminum oxide (AAO), carbon (C), and magnesium oxide (MgO) was developed for CO2 capture applications. Inspired by the bryophyte organism, the AAO/C/MgO composite mirrors two primary features of these species-(1) morphological characteristics and (2) elemental composition-specifically carbon, oxygen, and magnesium. The synthesis process involved two sequential steps: electroanodization of aluminum foil followed by a hydrothermal method using a mixture of glucose and magnesium chloride (MgCl2). The concentration of MgCl2 was systematically varied as the sole experimental variable across five levels-1 mM, 2 mM, 3 mM, 4 mM, and 5 mM-to investigate the impact of MgO formation on the samples' chemical and physical properties, and consequently, their CO2 capture efficiency. Thus, scanning electron microscopy analysis revealed the AAO substrate's porous structure, with pore diameters measuring 250 ± 30 nm. The growth of MgO on the AAO substrate resulted in spherical structures, whose diameter expanded from 15 nm ± 3 nm to 1000 nm ± 250 nm with increasing MgCl2 concentration from the minor to major concentrations explored, respectively. X-ray photoelectron spectroscopy (XPS) analysis indicated that carbon serves as a linking agent between AAO and MgO within the composite. Notably, the composite synthesized with a 4 mM MgCl2 concentration exhibited the highest CO2 capture efficiency, as determined by UV-Vis absorbance studies using a sodium carbonate solution as the CO2 source. This efficiency was quantified with a 'k' constant of 0.10531, significantly higher than those of other studied samples. The superior performance of the 4 mM MgCl2 sample in CO2 capture is likely due to the optimal density of MgO structures formed on the sample's surface, enhancing its adsorptive capabilities as suggested by the XPS results.
RESUMO
Breast cancer is a significant health concern for women, emphasizing the need for early detection. This research focuses on developing a computer system for asymmetry detection in mammographic images, employing two critical approaches: Dynamic Time Warping (DTW) for shape analysis and the Growing Seed Region (GSR) method for breast skin segmentation. The methodology involves processing mammograms in DICOM format. In the morphological study, a centroid-based mask is computed using extracted images from DICOM files. Distances between the centroid and the breast perimeter are then calculated to assess similarity through Dynamic Time Warping analysis. For skin thickness asymmetry identification, a seed is initially set on skin pixels and expanded based on intensity and depth similarities. The DTW analysis achieves an accuracy of 83%, correctly identifying 23 possible asymmetry cases out of 20 ground truth cases. The GRS method is validated using Average Symmetric Surface Distance and Relative Volumetric metrics, yielding similarities of 90.47% and 66.66%, respectively, for asymmetry cases compared to 182 ground truth segmented images, successfully identifying 35 patients with potential skin asymmetry. Additionally, a Graphical User Interface is designed to facilitate the insertion of DICOM files and provide visual representations of asymmetrical findings for validation and accessibility by physicians.
