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The horizontal rotating disc contactor (HRDC) for extraction consists of a mixing chamber and two settling chambers, which enables continuous cycling of the dispersion-mass transfer-separation processes and achieves higher mass transfer efficiency compared to a single equilibrium stage. For O/W emulsion systems, it allowed for continuous separation of the oil phase. In order to further improve the separation performance of the extractor, the structure was optimized by simulating the coalescence and breakup process of O/W emulsions using computer software. A two-dimensional model was established to study the effects of flow rate, droplet size, and wall wettability on coalescence efficiency in kerosene/water systems. The results showed that coalescence efficiency in narrow channels initially increased with flow rate before decreasing, indicating an optimal flow rate exists. When droplet size was smaller than channel dimensions, larger droplets were more prone to coalesce. Additionally, hydrophobic walls exhibited better coalescing effects. These findings provided theoretical support for optimizing HRDC equipment and achieving continuous extraction in different O/W emulsion systems.

Interface molecular passivation is widely utilized to improve the performance and stability of perovskite solar cells (PSCs). However, designing efficient passivation molecules is still challenging. Owing to the fast development of machine learning (ML) methods, screening passivation molecules from molecular libraries with ML models becomes promising. Herein, 3D-MoRSE descriptor sets were introduced to predict the device power conversion efficiency (PCE) by machine learning with automatic relevance determination regression. By fine tuning the scale factor (sL), we found that sL from 0.04 to 0.50 could achieve satisfactory prediction results, and convergence is achieved at s × sL ≈ 1.40. Among all investigated atomic properties, atomic electronegativity and ionization potential revealed a strong correlation with PCE. We identified that molecules with abundant carbon-nitride single or partial-double bonds may achieve good surface passivation and realize high PCE. The highest coefficient of determination (R2) of 0.87 was achieved, demonstrating an improvement of approximately 0.11 compared to existing models. Using our optimal models, we predicted the PCEs of the devices with passivated molecules from the PubChem database, and three molecules in the top 15 candidates show good passivation ability in reported experiments. This work provides a simple and efficient method for molecule description for highly accurate ML predictions, which could accelerate the discovery of new molecules for PSC passivation. [ABSTRACT FROM AUTHOR]

Introduction: The diagnostic accuracy of traditional imaging examination in predicting ypT stage of rectal cancer after neoadjuvant therapy is significantly reduced, which would affect patients' subsequent treatment choices. This study aimed to investigate the use of endorectal shear wave elastography (SWE) for diagnosing ypT0 stage of rectal cancer after neoadjuvant chemoradiotherapy (nCRT)., Methods: Sixty patients with rectal cancer were prospectively recruited in this study. Data on endorectal ultrasound (ERUS) and SWE parameters were collected before nCRT and 6-8 weeks after nCRT. Postoperative pathological results were the gold standard for evaluating the diagnostic accuracy of SWE and ERUS in predicting the ypT0 stage of rectal cancer after nCRT. Receiver operating characteristic (ROC) curve analysis was used to determine the cut-off values of the SWE parameters that best corresponded to the ypT0 stage and analyze the sensitivity, specificity, and accuracy., Results: The diagnostic accuracies of using ERUS to predict the ypT and ypT0 stages of rectal cancer after nCRT were 58.1% (18/31) and 64.3% (9/14), respectively. The ROC curve was constructed with the lesion's Emean, Emean corrected (EC), Emean difference (ED), Emean corrected differencede (ECD), Emean descendding rate (EDR) and Emean corrected descendding rate (ECDR) values after nCRT, the cut-off values of diagnosing the ypT0 stage were 64.40 kPa, 55.45 kPa, 72.55 kPa, 73.75 kPa, 50.15%, and 55.93%, respectively; the area under the curve (AUC) for diagnosing the ypT0 stage was 0.924, 0.933, 0.748, 0.729, 0.857 and 0.861, respectively. The EC value showed the best diagnostic performance., Conclusion: SWE could improve the accuracy of conventional ERUS in diagnosing the ypT0 stage of rectal cancer after nCRT. It is expected to become a new method to help predict pathological complete responses in clinical practice and provide new evidence for the watch-and-wait approach., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liu, Cui, Sun, Gong, Wang, Yang and Wang.)