Upper gastrointestinal bleeding (UGIB) is common in liver cirrhosis. Although esophageal and gastric varices (EGV) is the main bleeding source, there were still a proportion of patients with peptic ulcer bleeding. Thus, this study aimed to analyze the characteristic of variceal bleeding and peptic ulcer bleeding in liver cirrhosis. Cirrhotic patients with confirmed UGIB by urgent endoscopy from July 2012 to June 2018 were enrolled, and classified into peptic ulcer bleeding group (n = 248) and variceal bleeding group (n = 402). Clinical and endoscopic characteristics, therapeutic efficacy and prognosis were evaluated, and independent risk factors for 42-day morality were determined. The mean age and gender ratio of peptic ulcer bleeding group were higher than those in variceal bleeding group (55.58 ± 11.37 vs. 52.87 ± 11.57, P < 0.01; 4.51:1 vs. 2.87:1, P = 0.023). Variceal bleeding group most commonly presented as red blood emesis and coffee grounds (67.16%), while peptic ulcer group primarily manifested as melena (62.10%). Hepatocellular carcinoma was more prevalent in peptic ulcer group (141 vs. 119, P < 0.01). Albumin level in variceal bleeding group was lower higher (P < 0.01), but serum bilirubin, creatinine and prothrombin time were significantly higher (all P < 0.01). Success rate of endoscopic hemostasis for variceal bleeding and peptic ulcer bleeding was 89.05% and 94.35% (P = 0.021). Univariate and multivariate analysis identified prothrombin time (P = 0.041, OR [95% CI] 0.884 [0.786–0.995]), MELD score (P = 0.000, OR [95% CI] 1.153 [1.073–1.240]), emergency intervention (P = 0.002, OR [95% CI] 8.656 [2.219–33.764]), hepatic encephalopathy before bleeding (P = 0.003, OR [95% CI] 8.119 [2.084–31.637]) and hepatic renal syndrome before bleeding (P = 0.029, OR [95% CI] 3.877 [1.152–13.045]) as the independent predictors for 42-day mortality. Peptic ulcer bleeding should be distinguished from variceal bleeding by clinical and endoscopic characteristics.

Objective: To compare the efficacy, advantages and disadvantages of endoscopic CO2 laser cauterization (ECLC) and open neck surgery in the treatment of congenital pyriform sinus fistula (CPSF). Methods: From September 2014 to March 2017, 80 cases with confirmed diagnosis of CPSF received initial treatment at Guangdong Provincial People's Hospital were prospectively analyzed, including 34 males and 46 females, aged 18 to 672 (194.17±141.18) months. They were consecutively divided into endoscopic group and open-surgery group, with 40 cases in each group. Both groups of patients received surgical treatment under general anesthesia. The endoscopic group was treated by endoscopic CO2 laser cauterization, and the open-surgery group underwent the following surgery: first, we performed suspension laryngoscopy examination to confirm the presence of fistula in the bottom of the piriform fossa, then open-neck resection of congenital piriform sinus fistula with recurrent laryngeal nerve and/or lateral branch of superior laryngeal nerve anatomy plus partial thyroidectomy were performed. The data between the two groups were compared, including the operative time, intraoperative blood loss, postoperative pain, average length of stay, neck cosmetic scores, complications and cure rates. All patients were followed up in outpatient clinics. Statistical analysis was performed using SPSS 20.0 software. P<0.05 indicates that the difference is statistically significant. Results: All patients were successfully completed the operation. The operative time, intraoperative blood loss, postoperative pain and average length of hospital stay in the endoscopic group were significantly less than those in the open group [(27.4±5.5) min to (105.8±52.5) min, (0.6±0.5) ml to (33.6±41.5) ml, (1.7±0.9) points to (4.6±0.7) points, (5.9±2.9)d to(8.9±3.3)d, t values were-9.400, -5.031, -16.199, -4.293, P values were all<0.01]; The neck cosmetic score in the endoscopy group was significantly greater than that of the open group [(9.9±0.4) against (5.8±0.9) points, t=25.847, P0.05). Three months after the first treatment, the cure rate in the endoscopic group (82.5%, 33/40) was significantly lower than that in the open-neck group (100.0%, 40/40), χ²=5.64, P<0.05. The follow-up time was 12 months after the last treatment. Eighty cases were followed up and none was lost to follow-up. During the follow-up period, the cure rate of the endoscopy group (97.5%, 39/40) was compared with that of the open group (100.0%, 40/40), and the difference was not statistically significant. Conclusions: In the treatment of CPSF, the two-surgical method each has their advantages. Compared with open-neck surgery, ECLC is simpler, repeatable. ECLC has shorter time in operation and hospital stay, less complications, and less postoperative pain and more precise cosmetic results. It could be preferred for the initial treatment of CPSF and relapsed cases after cauterization. But subject to relatively low cure rate of one-time cauterization and uncertain long-term efficacy, it cannot completely replace the open-neck surgery at present.

Vehicle failure prediction technology is an important part of PHM (Prognostic and Health Management) technology, which is of great significance to the safety of vehicles and to improve driving safety. Based on the vehicle operating data collected by the on-board terminal (T-box) of the telematics system, the research on the state of vehicle failure is conducted. First, this paper conducts statistical analysis on vehicle historical fault data. Preprocessing procedures such as cleaning, integration, and protocol are performed to group the data set. Then, three indexes including recency (R) frequency (F), and days (D) are selected to construct a vehicle security status subdivision system, and K -Means algorithm is utilized to divide different vehicle categories from the perspective of vehicle value. Labeled information of vehicles in different security status are further established. Moreover, taking engine faults as an example, this paper uses gray correlation analysis method to extract key fault characteristic parameters. Based on self-organizing mapping network theory (SOM), the fault prediction model is built. And, by learning the fault data of the vehicles and obtaining the characteristic differences between different states, the prediction of fault and evaluation of vehicle condition is completed. Finally, test data is selected to verify the prediction accuracy of the model.