ABSTRACT
Background: Prognosis is crucial for personalized treatment and surveillance suggestion of the resected non-small-cell lung cancer (NSCLC) patients in stage I-III. Although the tumor-node-metastasis (TNM) staging system is a powerful predictor, it is not perfect enough to accurately distinguish all the patients, especially within the same TNM stage. In this study, we developed an intelligent prognosis evaluation system (IPES) using pre-therapy CT images to assist the traditional TNM staging system for more accurate prognosis prediction of resected NSCLC patients. Methods: 20,333 CT images of 6371 patients from June 12, 2009 to March 24, 2022 in West China Hospital of Sichuan University, Mianzhu People's Hospital, Peking University People's Hospital, Chengdu Shangjin Nanfu Hospital and Guangan Peoples' Hospital were included in this retrospective study. We developed the IPES based on self-supervised pre-training and multi-task learning, which aimed to predict an overall survival (OS) risk for each patient. We further evaluated the prognostic accuracy of the IPES and its ability to stratify NSCLC patients with the same TNM stage and with the same EGFR genotype. Findings: The IPES was able to predict OS risk for stage I-III resected NSCLC patients in the training set (C-index 0.806; 95% CI: 0.744-0.846), internal validation set (0.783; 95% CI: 0.744-0.825) and external validation set (0.817; 95% CI: 0.786-0.849). In addition, IPES performed well in early-stage (stage I) and EGFR genotype prediction. Furthermore, by adopting IPES-based survival score (IPES-score), resected NSCLC patients in the same stage or with the same EGFR genotype could be divided into low- and high-risk subgroups with good and poor prognosis, respectively (p < 0.05 for all). Interpretation: The IPES provided a non-invasive way to obtain prognosis-related information from patients. The identification of IPES for resected NSCLC patients with low and high prognostic risk in the same TNM stage or with the same EGFR genotype suggests that IPES have potential to offer more personalized treatment and surveillance suggestion for NSCLC patients. Funding: This study was funded by the National Natural Science Foundation of China (grant 62272055, 92259303, 92059203), New Cornerstone Science Foundation through the XPLORER PRIZE, Young Elite Scientists Sponsorship Program by CAST (2021QNRC001), Clinical Medicine Plus X - Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities (K.C.), Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Chinese Academy of Medical Sciences (2021RU002), BUPT Excellent Ph.D. Students Foundation (CX2022104).
ABSTRACT
Inhibiting hydrate decomposition due to the friction heat generated by the drilling tools is one of the key factors for drilling hydrate formation. Since the existing method based on chemical inhibition technology can only delay the hydrate decomposition rate, a phase-change microcapsule was introduced in this paper to inhibit, by the intelligent control of the drilling fluid temperature, the decomposition of the formation hydrate, which was microencapsulated by modified n-alkane as the core material, and nano-silica was taken as the shell material. Scanning electron microscope (SEM), size distribution, X-ray diffraction (XRD), and Fourier transform infrared spectrometer (FT-IR) were utilized to characterize the structural properties of microcapsules. Differential scanning calorimetry (DSC) spectra displayed that the latent heat was 136.8 J/g in the case of melting enthalpy and 136.4 J/g in the case of solidification enthalpy, with an encapsulation efficiency of 62.6%. In addition, the prepared microcapsules also showed good thermal conductivity and reliability. By comparison, it was also proved that the microcapsules had good compatibility with drilling fluid, which can effectively control the temperature of drilling fluid for the inhibition of hydrate decomposition.
ABSTRACT
A ranging method based on the differential time domain method (DTDM) is proposed in order to improve ranging accuracy and the range of active measurement based on peak discriminator (PD). We develop mathematical models and deduce that zero-crossing sensitivity is an important factor, which affects the ranging error of DTDM. Additionally, zero-crossing sensitivity is determined by delayed time. We carried out relative experiments and obtained the smallest ranging error when delayed time is receiving pulse width. We also compare ranging, three-dimensional (3D) point clouds and depth images based on two methods under same testing conditions. The results show that DTDM is beneficial in improving performance of pulse laser ranging and 3D imaging.
