Qualifying Chinese Medical Licensing Examination with Knowledge Enhanced Generative Pre-training Model

Generative Pre-Training (GPT) models like ChatGPT have demonstrated exceptional performance in various Natural Language Processing (NLP) tasks. Although ChatGPT has been integrated into the overall workflow to boost efficiency in many domains, the lack of flexibility in the finetuning process hinders its applications in areas that demand extensive domain expertise and semantic knowledge, such as healthcare. In this paper, we evaluate ChatGPT on the China National Medical Licensing Examination (CNMLE) and propose a novel approach to improve ChatGPT from two perspectives: integrating medical domain knowledge and enabling few-shot learning. By using a simple but effective retrieval method, medical background knowledge is extracted as semantic instructions to guide the inference of ChatGPT. Similarly, relevant medical questions are identified and fed as demonstrations to ChatGPT. Experimental results show that directly applying ChatGPT fails to qualify the CNMLE at a score of 51 (i.e., only 51\% of questions are answered correctly). While our knowledge-enhanced model achieves a high score of 70 on CNMLE-2022 which not only passes the qualification but also surpasses the average score of humans (61). This research demonstrates the potential of knowledge-enhanced ChatGPT to serve as versatile medical assistants, capable of analyzing real-world medical problems in a more accessible, user-friendly, and adaptable manner

Research on the Supervision of vehicle 4G Video Surveillance platform in Freight Company

In order to solve the difficult problem of dynamic driving detection in vehicle transportation for a long time, Jiaozuo Transportation Bureau took the lead in using 4G platform for dynamic supervision of driver behavior, so as to reduce driving accidents. According to the data provided by Jiaozuo freight company, this paper analyzes the internal relationship among vehicle qualified rate, 4G video vehicle monitoring and evaluation project score and alarm record. And according to the relationship between the three, we use SPSS software to analyze the correlation and cluster of freight companies, and study the closed-loop disposal and company policy of companies with good operation

Effect of the Strength of Initial Aluminium on the Bonding Properties and Deformation Coordination of Ti/Al Composite Sheets by the Cold Roll Bonding Process

Ti/Al composite sheets were prepared using the cold rolling process, and different initial aluminium strengths were considered. The results showed that the peel strength of the Ti/Al composite sheet increased with the increasing initial strength of aluminium under the same reduction. A higher strength of the initial aluminium corresponds to better deformation coordination between titanium and aluminium, where the strain hardening of titanium and aluminium plays an important role. The change degree of the components of twins on the titanium side for the Ti/Al composite sheet with a low aluminium strength is stronger than that for the Ti/Al composite sheet with a high aluminium strength. The strong change in the components of twins may result in the low uniformity of the microstructure on the titanium side. The analysis of the peeling surface shows aluminium residue on the titanium side, while there was almost no titanium residue on the aluminium side. At the same reduction, a higher strength of aluminium corresponds to less aluminium residue on the titanium side. The bonding properties of Ti/Al cold-rolled composite sheets were determined by four strong bonding areas. The strength of the initial aluminium was the main factor, and the residual amount of aluminium on the titanium side of the peeling surfaces was a secondary factor

Evaluation of recurrence risk for patients with stage I invasive lung adenocarcinoma manifesting as solid nodules based on 18F-FDG PET/CT, imaging signs, and clinicopathological features

Abstract Background Stage I lung adenocarcinoma is a heterogeneous group. Previous studies have shown the prognostic evaluation value of PET/CT in this cohort; however, few studies focused on stage I invasive adenocarcinoma manifesting as solid nodules. This study aimed to evaluate the recurrence risk for patients with stage I invasive lung adenocarcinoma manifesting as solid nodules based on 18F-FDG PET/CT, CT imaging signs, and clinicopathological parameters. Methods We retrospectively enrolled 230 patients who underwent 18F-FDG PET/CT examination between January 2013 and July 2019. Metabolic parameters: maximum standard uptake value (SUVmax), mean standard uptake value, tumor metabolic volume (MTV), and total tumor glucose digestion were collected. Kaplan–Meier method was used to evaluate recurrence-free survival (RFS), and the multivariate Cox proportional hazards model was used to determine the independent risk factors associated with RFS. The time-dependent receiver operating characteristic curve (ROC) method was used to calculate the optimal cutoff value of metabolic parameters. Results The 5-year RFS rate for all patients was 71.7%. Multivariate Cox analysis revealed that the International Association for the Study of Lung Cancer Pathology Committee (IASLC) pathologic grade 3 [Hazard ratio (HR), 3.96; 95% Confidence interval (CI), 1.11–14.09], the presence of cavity sign (HR 5.38; 95% CI 2.23–12.96), SUVmax (HR 1.23; 95% CI 1.13–1.33), and MTV (HR 1.05; 95% CI 1.01–1.08) were potential independent prognostic factors for RFS. Patients with IASLC grade 3, the presence of cavity sign, SUVmax > 3.9, or MTV > 5.4 cm3 were classified as high risk, while others were classified as low risk. There was a significant difference in RFS between the high-risk and low-risk groups (HR 6.04; 95% CI 2.17–16.82, P < 0.001), and the 5-year RFS rate was 94.1% for the low-risk group and 61.3% for the high-risk group. Conclusions We successfully evaluate the recurrence risk of patients with stage I invasive adenocarcinoma manifesting as solid nodules for the first time. The 5-year RFS rate in the high-risk group was significantly lower than in the low-risk group (61.3% vs. 94.1%). Our study may aid in optimizing therapeutic strategies and improving survival benefits for those patients

Analysis of Cold Composite Sheet Rolling Considering Anisotropic Effect and Position-Dependent Friction Model

The large difference in mechanical properties and plastic deformation ability of each layer will have a great impact on the overall performance of a composite sheet prepared by cold-roll bonding. The effect of rolling and material variables on the stress distribution and bonding state in the rolling deformation zone should be studied. In this work, an accurate cold-rolling deformation model considering the anisotropic effect and position-dependent friction model is established using the slab method. Effects of different process and material variables are analyzed. Related experiments were performed on Ti-Al clads and calculation results from the deformation model were compared with the experimental results. This model can well predict the Ti/Al thickness ratio after rolling, and the smaller the initial aluminum strength, the more accurate the predicted value; the minimum error is within 1%. The deformation coordination between the titanium and aluminum layers becomes better with the increase in rolling reduction and initial aluminum strength. At 50% reduction, the deformation ratio of titanium and aluminum increases from 93.8% to 98.1%, which is consistent with the trend of the results calculated using this model

Enhanced NH₃ Synthesis from Air in a Plasma Tandem-Electrocatalysis System Using Plasma-Engraved N‑Doped Defective MoS₂

We have developed a sustainable method to produce NH3 directly from air using a plasma tandem-electrocatalysis system that operates via the N2–NOx–NH3 pathway. To efficiently reduce NO2– to NH3, we propose a novel electrocatalyst consisting of defective N-doped molybdenum sulfide nanosheets on vertical graphene arrays (N-MoS2/VGs). We used a plasma engraving process to form the metallic 1T phase, N doping, and S vacancies in the electrocatalyst simultaneously. Our system exhibited a remarkable NH3 production rate of 7.3 mg h–1 cm–2 at −0.53 V vs RHE, which is almost 100 times higher than the state-of-the-art electrochemical nitrogen reduction reaction and more than double that of other hybrid systems. Moreover, a low energy consumption of only 2.4 MJ molNH3–1 was achieved in this study. Density functional theory calculations revealed that S vacancies and doped N atoms play a dominant role in the selective reduction of NO2– to NH3. This study opens up new avenues for efficient NH3 production using cascade systems