Background: Diabetes is a risk factor for the progression and prognosis of coronavirus disease (COVID-19), but the relationship between glycosylated hemoglobin (HbA1c) level, inflammation, and prognosis of COVID-19 patients has not been explored. Methods: This was a retrospective study of COVID-19 patients who underwent an HbA1c test. Their demographic data, medical history, signs and symptoms of COVID-19, laboratory test results, and final outcomes of COVID-19 treatment were collected and analyzed. Results: A total of 132 patients were included and divided into three groups based on their blood glucose status. There were significant differences in SaO 2 , serum ferritin level, Creactive protein (CRP), erythrocyte sedimentation rate (ESR), fibrinogen (Fbg) level, and IL6 level among the three groups. A pairwise comparison of the groups showed that groups B and C were significantly different from group A in terms of CRP, ESR, and Fbg, IL6, and serum ferritin levels (P < 0.05). Correlation analysis showed that there was a linear negative correlation between SaO 2 and HbA1c (r = À0.22, P = 0.01), while there was a linear positive correlation between serum ferritin, CRP, Fbg, and ESR levels and HbA1c (P < 0.05). Conclusions: High HbA1c level is associated with inflammation, hypercoagulability, and low SaO 2 in COVID-19 patients, and the mortality rate (27.7%) is higher in patients with diabetes. Determining HbA1c level after hospital admission is thus helpful assessing inflammation, hypercoagulability, and prognosis of COVID-19 patients.

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Abstract-Controlling the welding process by monitoring the weld pool surface becomes more and more popular in robotic arc welding. In this paper, we propose a monitoring system to infer the P-gas metal arc welding (GMAW) weld pool geometry from the reflected laser lines, which are projected onto the specular weld pool and reflected onto a diffusive plane. The parallel straight lines are distorted according to the shape of the weld pool and thus contain the weld pool's shape information. Accurately computing the equations of the imaged laser lines in the world coordinate system is critical for the subsequent weld pool shape estimation. This paper focuses on accurately segmenting and identifying the reflected laser lines and novel image processing algorithms are proposed to fulfill this specific task. Experimental results verified the effectiveness of the proposed algorithms.Index Terms-Clustering, gas metal arc welding (GMAW), gas tungsten arc welding (GTAW), image processing, machine vision, monitoring, segmentation.

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Robust measurement of the specular weld pool surface can help better understand the complex welding processes and provide feedback for robotic welding. The strong arc light and the specular surface of the weld pool make it difficult for the direct sensing measurement. In this paper, a novel imaging and measurement system is proposed, and it makes use of the strong penetrability of the laser to avoid the interference of arc light and obtain the surface information of the weld pool. By intercepting the reflection of a projected laser pattern twice, the proposed system gives a closed-form solution for each reflected ray and a closed-form solution for the corresponding point on the weld pool surface. The weld pool surface can be thus reconstructed by one-shot structured light projection. To increase the robustness of the measurement system, the least deformation principle is proposed to rectify the coefficient errors of the computed plane equation. Finally, a sequence of 3-D weld pools is reconstructed and compared with state-of-art literature. The comparison verifies that our method is significantly better than all the other methods in measuring the 3-D weld pool shapes.

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Platycodonis radix is extensively used for treating cough, excessive phlegm, sore throat, bronchitis and asthma in the clinic. Meanwhile, the stems, leaves and seeds of Platycodon grandiflorum (PG) have some pharmaceutical activities such as anti-inflammation and anti-oxidation effects, etc. These effects must be caused by the different metabolites in various parts of herb. In order to profile the different parts of PG, the ultra-high performance liquid chromatography combined with quadrupole time-of- flight mass spectrometry (UPLC-QTOF-MSE) coupled with UNIFI platform and multivariate statistical analyses was used in this study. Consequently, for the constituent screening, 73, 42, 35, 44 compounds were characterized from the root, stem, leaf and seed, respectively. The stem, leaf and seed contain more flavonoids but few saponins that can be easily discriminated in the root. For the metabolomic analysis, 15, 5, 7, 11 robust biomarkers enabling the differentiation among root, stem, leaf and seed, were discovered. These biomarkers can be used for rapid identification of four different parts of PG grown in northeast China.

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