Color-Transfer-Enhanced Data Construction and Validation for Deep Learning-Based Upper Gastrointestinal Landmark Classification in Wireless Capsule Endoscopy.

While the adoption of wireless capsule endoscopy (WCE) has been steadily increasing, its primary application remains limited to observing the small intestine, with relatively less application in the upper gastrointestinal tract. However, there is a growing anticipation that advancements in capsule endoscopy technology will lead to a significant increase in its application in upper gastrointestinal examinations. This study addresses the underexplored domain of landmark identification within the upper gastrointestinal tract using WCE, acknowledging the limited research and public datasets available in this emerging field. To contribute to the future development of WCE for gastroscopy, a novel approach is proposed. Utilizing color transfer techniques, a simulated WCE dataset tailored for the upper gastrointestinal tract is created. Using Euclidean distance measurements, the similarity between this color-transferred dataset and authentic WCE images is verified. Pioneering the exploration of anatomical landmark classification with WCE data, this study integrates similarity evaluation with image preprocessing and deep learning techniques, specifically employing the DenseNet169 model. As a result, utilizing the color-transferred dataset achieves an anatomical landmark classification accuracy exceeding 90% in the upper gastrointestinal tract. Furthermore, the application of sharpen and detail filters demonstrates an increase in classification accuracy from 91.32% to 94.06%.

Rational Design of a Necklace-like ZIF-67/Poly(vinylidene fluoride) Electrospun Nanofiber Hybrid Membrane for Simultaneous Removal of PM0.3 and SO2.

Growing concerns over poor air quality, especially in urban and industrial regions, have led to increased global demands for advanced air-purification technologies. However, the stability and airborne pollutant control abilities of the available air-purification materials under diverse environmental conditions are limited. Thus, the advanced development of filtration materials that can effectively control different types of pollutants, such as particulate matter (PM) and gaseous pollutants, simultaneously has attracted attention. The zeolitic imidazolate framework (ZIF), a type of porous metal-organic framework (MOF), is a promising material for capturing weakly acidic toxic gases such as SO2 owing to its excellent adsorption performance and high thermal and chemical stability. In this study, we successfully developed an ultrastable necklace-like multifunctional hybrid membrane via the cetyltrimethylammonium bromide-assisted in situ growth of zeolitic imidazolate framework (ZIF)-67 crystals on electrospun Co2+-doped poly(vinylidene fluoride) nanofibers (70 nm) that can be used in different moisture environments to achieve sustainable air-filtration performance. The hybrid nanocomposite membrane demonstrated excellent performance for the simultaneous control of intractable fine PM0.3 (filtration efficiency, 99.461%) and SO2 (adsorption capacity, 1476.5 mg g-1) under different humidity conditions. This study contributes to the optimal synergistic integration of the advanced metal-organic framework (MOF)-nanofiber nanocomposite membranes and can guide the rational design and conceptualization of a facile and novel membrane for various applications in the environmental science and energy fields.