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Abstract In this paper, a robot system for hanging and removing grounding rods is designed by integrating 3D recognition technology, hand-eye self-calibration technology, and automatic operation technology. Specifically, a novel hand-eye self-calibration algorithm is proposed that only uses common objects in the actual scene, which differs from traditional robot hand-eye calibration in that it requires a dedicated calibration board to assist with offline completion. Addressing the problem that existing self-calibration methods cannot be optimized as a whole, resulting in low accuracy and instability of the solution, a multi-stage objective function optimization self-calibration algorithm is proposed. An optimization method based on the minimization of re-projection error is designed to compensate for the results, which uses an efficient Oriented fast and rotated brief (ORB) feature extraction algorithm and introduces a scoring mechanism to retain more correct matching points in the feature matching stage. Experimental verifications are conducted using both public dataset and practical robot system. In the dataset experiment, our method demonstrates superior accuracy and robustness compared to existing self-calibration methods. Furthermore, the practical robot platform experiment confirms the feasibility and efficacy of our approach across various wind speeds and lighting conditions.

Glass fiber-reinforced polymer (GFRP) composites were prepared with ortho-phthalic unsaturated polyester resin as the matrix. Mass productions were carried out on a production line using infrared laser radiation and tunnel-kiln heating. Infrared laser radiation heating can realize internal and external collaborative curing by utilizing the deep penetration of the infrared laser, whereas, the curing of tunnel kilns mainly depends on heat conduction and heat convection. The tensile strength of the bar cured by laser radiation was approximately 25% higher than that of the bar cured by the tunnel kiln. The temperature field of the GFRP bars under the two curing modes was simulated using the finite element method, and The fiber at the fracture of reinforcement was analyzed using scanning electron microscopy and FTIR spectrum. The results showed that there was more fiber adhesion resin in the GFRP bars heated by infrared laser radiation, whereas the adhesion resin on the fibers was less scattered in the tunnel–kiln-heated GFRP bars.

Objectives: Non-invasive prenatal testing (NIPT) has been widely used in recent years. According to clinical experience from all hospitals providing prenatal screening services in Beijing, we explored the feasibility of using NIPT for the analysis of common foetal aneuploidies among pregnancies.Methods: In total, 68,763 maternal blood samples were collected from January 2020 to December 2020 at the Beijing prenatal diagnosis agency. Cases with positive screening results by NIPT detection were validated using prenatal diagnosis.Results: In total, 920 cases had a high-risk NIPT result, and 755 cases were shown to be truly positive by a chromosome karyotyping analysis; the prenatal diagnosis rate was 82.07% (755/920). Of the920 cases, there were 164 cases of T21, 70 cases of T18, 38 cases of T13, 360 cases of SCAs and 288 cases of other chromosomal abnormalities. The positive rates of T21, T18, T13, and SCAs were 0.24% (164/68,763), 0.10% (70/68,763), 0.06% (38/68,763) and 0.52% (360/68,763), respectively. The sensitivity and specificity were 98.17% and 99.92% for T21, 96.15% and 99.93% for T18, and 100% and 99.95% for T13, respectively. The PPVs of T21,T18,T13 and SCAs were65.24% (107/164), 35.71% (25/70), 18.42% (7/38) and 31.39% (113/360), respectively. For all indications, there were more higher T21/18/13 in the high-risk group than in the low-risk group (comprising only cases of voluntary request), with a positive rate of 0.46% vs. 0.27% (p < 0.001), sensitivity of 99.16% vs. 91.30% (p = 0.02) and PPV of 56.73%vs.32.81% (p = 0.001), but there was no significant difference in specificity between the groups (p = 0.71). The detection indication with the highest PPV (100%) by NIPT was ultrasound structural abnormalities and ultrasound soft marker abnormalities for T21 and ultrasound structural abnormalities and NT thickening for T18 and T13. The PPVs of different clinical indications of T21 (p = 0.002), T13 (p = 0.04) and SACs (p = 0.02) were statistically significant.Conclusion: The high specificity, efficiency and safety (non-invasiveness) of NIPT can effectively improve the detection rate of common chromosomal aneuploidy, thereby reducing the occurrence of birth defects. We should encourage pregnant women with NIPT-high-risk results to undergo a prenatal diagnosis to determine whether the foetus has chromosomal abnormalities. More importantly, the screening efficiency of NIPT in the low-risk group was significantly lower than that in the high-risk group. Therefore, the use of NIPT in low-risk groups should be fully promoted, and socioeconomic benefits should be considered.

Background: In China, congenital heart disease (CHD) is the most common birth defect type, with approximately 13,000 new cases annually. This study aimed to investigate high-risk factors, prenatal screening and prenatal diagnosis as a basis for clinical decisions.Methods: All CHD cases identified from 2018 to 2020 were obtained from the Beijing city birth defect surveillance system and prenatal diagnosis institutions. The prenatal CHD diagnosis was confirmed by fetal echocardiography and amniotic fluid or cord blood genetic examination. Chi-square, odds ratio (OR), 95% confidence interval (CI), and univariate and multivariate logistic analyses were used to explore the high-risk factors, prenatal screening and prenatal diagnosis of CHD. Results: In total, 6,786/594,860 fetuses with CHD were diagnosed by prenatal echocardiography. The average incidence of CHD was 11.4 per 1,000 births, with an increase of 30.7 per 1,000 births from 2018 to 2020 (P < 0.05); the average incidence of complex CHD (CCHD) was 2.02 per 1,000 births, with no significant change from 2018 to 2020 (P > 0.05). Women age ≥35 years (OR 1.06, 95% CI 0.77–1.46) was at higher risk of having babies with CHD than women aged 21–34 years. Overall, CHD incidence increased with maternal age (OR1.03, 95% CI 1.02–1.03). Additionally, women who had a non-local household registration (OR 1.16, 95% CI 1.10–1.22) or had diabetes mellitus (DM) (OR 1.16, 95% CI 0.96–1.25) were at higher risk of CHD. As an independent factor, CCHD was related to maternal age, DM, fetal gender, and maternal education level (all P < 0.05). The prenatal ultrasound screening detection rate of CCHD was 97.59%, which was far higher than that of total CHD (51.67%) (P < 0.001). The prenatal ultrasound diagnosis rate of CCHD was higher than that of simple CHD (P < 0.001), but the coincidence rate in the ultrasound diagnosis of CCHD was lower than that of simple CHD (P < 0.001). Prenatal genetic testing revealed chromosomal abnormalities in 25.62% (279/1089) of CHD cases with indications for a prenatal diagnosis.Conclusions: Maternal age, household registration and DM were related to CHD occurrence. Prenatal ultrasound screening is a highly effective method for CCHD diagnosis, and CHD fetuses should be closely evaluated to exclude chromosomal abnormalities.

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and alignmultiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (~30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect longrange interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurboFold's purely in silico prediction not only is close to experimentally guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5' and 3' untranslated regions (UTRs) (~29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient andmutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and fulllength genome studies and will be a useful tool in fighting the current and future pandemics. [ABSTRACT FROM AUTHOR]