Objectives/Hypothesis: To develop a deep-learning-based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design: Retrospective study. Methods: A total of 24,667 laryngoscopy images (normal, vocal nodule, polyps, leukoplakia and malignancy) were collected to develop and test a convolutional neural network (CNN)-based classifier. A comparison between the proposed CNNbased classifier and the clinical visual assessments (CVAs) by 12 otolaryngologists was conducted. Results: In the independent testing dataset, an overall accuracy of 96.24% was achieved; for leukoplakia, benign, malignancy, normal, and vocal nodule, the sensitivity and specificity were 92.8% vs. 98.9%, 97% vs. 99.7%, 89% vs. 99.3%, 99.0% vs. 99.4%, and 97.2% vs. 99.1%, respectively. Furthermore, when compared with CVAs on the randomly selected test dataset, the CNN-based classifier outperformed physicians for most laryngeal conditions, with striking improvements in the ability to distinguish nodules (98% vs. 45%, P < .001), polyps (91% vs. 86%, P < .001), leukoplakia (91% vs. 65%, P < .001), and malignancy (90% vs. 54%, P < .001). Conclusions: The CNN-based classifier can provide a valuable reference for the diagnosis of laryngeal neoplasms during laryngoscopy, especially for distinguishing benign, precancerous, and cancer lesions.

When surfactant is used as emulsifier, the stability of emulsion is often greatly reduced with the influence of reservoir conditions (temperature, pressure, salinity, etc.), which shortens the validity period of emulsion. Pickering emulsion has a wide range of applications in the oil and gas field due to its advantages of good stability and easy regulation. In this article, the formation, stabilization mechanism, and influencing factors of Pickering emulsions were introduced, and the application status and prospects of Pickering emulsions in oil and gas field were summarized. It was pointed out that Pickering emulsion has many advantages and important research value when applied in deep strata and complicated reservoirs. It is expected that this article can effectively reflect the application value of Pickering emulsion in oil and gas field and promote the application of Pickering emulsion in petroleum industry.

Welan gum is one of the most promising polymers used in polymer flooding for enhancing oil recovery, due to its excellent temperature resistance and salt-tolerance performance. However, welan gum, as a polymer with higher molecular weight, can be adsorbed and detained in the pore throat of the reservoir, which is characterized by a smaller size. Montmorillonite, a kind of clay mineral with high content in reservoir rocks, has strong adsorption capacity. Therefore, the adsorption behavior of welan gum on montmorillonite, as well as its influencing factors, are studied in this paper. The results show that the adsorption capacity is 2.07 mg/g. The adsorption capacity decreased with the increase in temperature. Both acidic and alkaline conditions reduced the adsorption capacity. The existence of inorganic salt affected the adsorption capacity. In addition, the higher the cation value, the lower the adsorption capacity. The characterization tests showed that the adsorption of welan gum on montmorillonite was characterized by physical adsorption and surface adsorption, indicating that there were no changes in the internal structure of montmorillonite. This study provides feasible methods to reduce the amount of welan gum adsorbed on montmorillonite, which is of great significance for reducing the permeability damage caused by welan gum adsorption and promoting the application of welan gum in polymer flooding for enhancing oil recovery.

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Graphene oxide is an excellent additive in anti-corrosion coatings because of its chemical inertness, permeation resistance, and high mechanical strength. In addition, the presence of oxygen-containing functional groups on the surface of graphene oxide gives it hydrophilic properties while efficiently promoting chemical functionalization, thus enhancing its dispersibility and corrosion inhibition properties. Modified graphene oxide corrosion inhibitors are a new field of interest for corrosion scientists. This paper presents the primary research on graphene oxide as a novel corrosion protection material, including the synthesis of modified graphene oxide and its remarkable performance in corrosion protection coatings and corrosion inhibitors. Different kinds of modified graphene oxide coatings are outlined, including the research progress on modified graphene oxide innovative coatings with pH response in recent years. The synthesis of modified graphene oxide corrosion inhibitors and their corrosion inhibition mechanisms are reviewed. Finally, the typical role of modified graphene oxide in coatings and the prospect of its research are discussed.