In-situ marine gas hydrate production methane leaks electrical monitoring system

In the process of gas hydrate exploitation, methane leakage needs to be monitored in real time, so an in-situ electrical monitoring system for methane leakage is designed. The monitoring system is mainly composed of monitoring cable, acquisition station, power module and general control platform. According to the electrical principle, the system carries out regional monitoring on the seabed formation, forms the resistivity map, and realizes methane leakage monitoring. The cost of the monitoring system is low, and it can be remotely controlled or automatically collected data according to the preset program, so the system has good application and research value

In-Situ Metrology of Large Segmented Detector Based on Modified Optical Truss

To precisely map cosmic structures and capture time-domain events, future large survey telescopes will be equipped with segmented detectors that greatly expand their field of view. Segment flatness and assembly accuracy will be essential for them to make accurate observations. Instead of physically measuring distances between adjacent mirror surfaces, our modified optical truss enables the angle (slope) between them to be calculated. Furthermore, we calculated the relative tilt and piston between the segmented detectors. The modified optical truss can measure the flatness of a mosaicked detector before and after it is assembled into a telescope. We reduced the volume, weight, and power of our device compared with earlier versions. Its angular accuracy is now better than 0.1 arcsecs, and, at a maximum scope of 500 µm, the linear accuracy of the new truss is better than 25 µm. In fact, accuracy and testing ranges are comparable to instruments found in optics labs

Mining of long non-coding RNAs with target genes in response to rust based on full-length transcriptome in Kentucky bluegrass

Kentucky bluegrass (Poa pratensis L.) is an eminent turfgrass species with a complex genome, but it is sensitive to rust (Puccinia striiformis). The molecular mechanisms of Kentucky bluegrass in response to rust still remain unclear. This study aimed to elucidate differentially expressed lncRNAs (DELs) and genes (DEGs) for rust resistance based on the full-length transcriptome. First, we used single-molecule real-time sequencing technology to generate the full-length transcriptome of Kentucky bluegrass. A total of 33,541 unigenes with an average read length of 2,233 bp were obtained, which contained 220 lncRNAs and 1,604 transcription factors. Then, the comparative transcriptome between the mock-inoculated leaves and rust-infected leaves was analyzed using the full-length transcriptome as a reference genome. A total of 105 DELs were identified in response to rust infection. A total of 15,711 DEGs were detected (8,278 upregulated genes, 7,433 downregulated genes) and were enriched in plant hormone signal transduction and plant–pathogen interaction pathways. Additionally, through co-location and expression analysis, it was found that lncRNA56517, lncRNA53468, and lncRNA40596 were highly expressed in infected plants and upregulated the expression of target genes AUX/IAA, RPM1, and RPS2, respectively; meanwhile, lncRNA25980 decreased the expression level of target gene EIN3 after infection. The results suggest that these DEGs and DELs are important candidates for potentially breeding the rust-resistant Kentucky bluegrass

Congenital cataract: prevalence and surgery age at Zhongshan Ophthalmic Center (ZOC).

Congenital cataract (CC) is the primary cause of treatable childhood blindness. Population-based assessments of prevalence and surgery age of CC, which are critical for improving management strategies, have been unavailable in China until now. We conducted a hospital-based, cross-sectional study of the hospital charts of CC patients younger than 18 years old from January 2005 to December 2010 at Zhongshan Ophthalmic Center (ZOC) in Guangzhou, China. Residence, gender, age at surgery, hospitalization time, and the presence of other ocular abnormalities were extracted and statistically analyzed in different subgroups. The search identified 1314 patients diagnosed with CC from a total of 136154 hospitalizations, which accounted for 2.39% of all the cataract in-patients and 1.06% of the total in-patients over the six-year study period. Of the identified CC patients, 9.2% had ≥ 2 hospitalizations due to the necessity of additional surgeries, with a total ratio of boys to girls of 1.75 ∶ 1. Based on a subgroup analysis according to age, patients 2-6 years old constituted the highest proportion (29.22%) of all hospitalized CC patients, and those 13-18 years old constituted the lowest proportion (13.47%) of the total number. The average age at surgery was 27.62 ± 23.36 months, but CC patients ≤ 6 years old (especially ≤ 6 months old) became increasingly prevalent throughout the 6-year study period. A total of 276 cases (20.93%) of CC were associated with one or more other ocular abnormalities, the highest incidence rates were observed for exotropia (6.24%), nystagmus (6.16%), and refractive error (3.65%). In conclusion, CC patients accounted for 2.39% of all cataract in-patients in a review of 6 years of hospitalization charts from ZOC. The age at the time of surgery decreased over the 6-year study period, which probably reflects the continuing improvement of public awareness of children's eye care in China

Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study

Objective To develop and validate a real-world screening, guideline-based deep learning (DL) system for referable diabetic retinopathy (DR) detection.Design This is a multicentre platform development study based on retrospective, cross-sectional data sets. Images were labelled by two-level certificated graders as the ground truth. According to the UK DR screening guideline, a DL model based on colour retinal images with five-dimensional classifiers, namely image quality, retinopathy, maculopathy gradability, maculopathy and photocoagulation, was developed. Referable decisions were generated by integrating the output of all classifiers and reported at the image, eye and patient level. The performance of the DL was compared with DR experts.Setting DR screening programmes from three hospitals and the Lifeline Express Diabetic Retinopathy Screening Program in China.Participants 83 465 images of 39 836 eyes from 21 716 patients were annotated, of which 53 211 images were used as the development set and 30 254 images were used as the external validation set, split based on centre and period.Main outcomes Accuracy, F1 score, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), Cohen’s unweighted κ and Gwet’s AC1 were calculated to evaluate the performance of the DL algorithm.Results In the external validation set, the five classifiers achieved an accuracy of 0.915–0.980, F1 score of 0.682–0.966, sensitivity of 0.917–0.978, specificity of 0.907–0.981, AUROC of 0.9639–0.9944 and AUPRC of 0.7504–0.9949. Referable DR at three levels was detected with an accuracy of 0.918–0.967, F1 score of 0.822–0.918, sensitivity of 0.970–0.971, specificity of 0.905–0.967, AUROC of 0.9848–0.9931 and AUPRC of 0.9527–0.9760. With reference to the ground truth, the DL system showed comparable performance (Cohen’s κ: 0.86–0.93; Gwet’s AC1: 0.89–0.94) with three DR experts (Cohen’s κ: 0.89–0.96; Gwet’s AC1: 0.91–0.97) in detecting referable lesions.Conclusions The automatic DL system for detection of referable DR based on the UK guideline could achieve high accuracy in multidimensional classifications. It is suitable for large-scale, real-world DR screening

Total numbers of hospitalized patients ≤6 months old in different years (P<0.05).

<p>Total numbers of hospitalized patients ≤6 months old in different years (P<0.05).</p

Associated ocular abnormalities and their incidences.

<p>*PHPV = Persistent hyperplastic primary vitreous.</p>#<p>CPPM = Congenital persistent pupillary membrane.</p

Analysis of the number of patients in and gender ratio of each age subgroup.

<p>M = months, Y = years.</p