The Hα\alpha broadband photometric reverberation mapping of four Seyfert 1 galaxies

Broadband photometric reverberation mapping (PRM) have been investigated for AGNs in recent years, but mostly on accretion disk continuum RM. Due to the small fraction of broad emission lines in the broadband, PRM for emission lines is very challenging. Here we present an ICCF-Cut method for broadband PRM to obtain the H$\alpha$ broad line lag and apply it to four Seyfert 1 galaxies, MCG+08-11-011, NGC 2617, 3C 120 and NGC 5548. All of them have high quality broadband lightcurves with daily/sub-daily cadence, which enables us to extract H$\alpha$ lightcurves from the line band by subtracting the contributions from the continuum and host galaxy. Their extracted H$\alpha$ lightcurves are compared with the lagged continuum band lightcurves, as well as the lagged H$\beta$ lightcurves obtained by spectroscopic RM (SRM) at the same epochs. The consistency of these lightcurves and the comparison with the SRM H$\beta$ lags provide supports to the H$\alpha$ lags of these AGNs, in a range from 9 to 19 days, obtained by the ICCF-Cut, JAVELIN and $\chi^2$ methods. The simulations to evaluate the reliability of H$\alpha$ lags and the comparisons between SRM H$\beta$ and PRM H$\alpha$ lags indicate that the consistency of the ICCF-Cut, JAVELIN and $\chi^2$ results can ensure the reliability of the derived H$\alpha$ lags. These methods may be used to estimate the broad line region sizes and black hole masses of a large sample of AGNs in the large multi-epoch high cadence photometric surveys such as LSST in the future.Comment: 22 pages, 19 figures, accepted for publication in Ap

Wind Speed Inversion in High Frequency Radar Based on Neural Network

Wind speed is an important sea surface dynamic parameter which influences a wide variety of oceanic applications. Wave height and wind direction can be extracted from high frequency radar echo spectra with a relatively high accuracy, while the estimation of wind speed is still a challenge. This paper describes an artificial neural network based method to estimate the wind speed in HF radar which can be trained to store the specific but unknown wind-wave relationship by the historical buoy data sets. The method is validated by one-month-long data of SeaSonde radar, the correlation coefficient between the radar estimates and the buoy records is 0.68, and the root mean square error is 1.7 m/s. This method also performs well in a rather wide range of time and space (2 years around and 360 km away). This result shows that the ANN is an efficient tool to help make the wind speed an operational product of the HF radar

Data Acquisition and Control System for Broad-band Microwave Reflectometry on EAST

Microwave reflectometry is a non-intrusive plasma diagnostic tool which is widely applied in many fusion devices. In 2014, the microwave reflectometry on Experimental Advanced Superconducting Tokamak (EAST) had been upgraded to measure plasma density profile and fluctuation, which covered the frequency range of Q-band (32-56 GHz), V-band (47-76 GHz) and W-band (71-110 GHz). This paper presented a dedicated data acquisition and control system (DAQC) to meet the measurement requirements of high accuracy and temporal resolution. The DAQC consisted of two control modules, which integrated arbitrary waveform generation block (AWG) and trigger processing block (TP), and two data acquisition modules (DAQ) that was implemented base on the PXIe platform from National Instruments (NI). All the performance parameters had satisfied the requirements of reflectometry. The actual performance will be further examined in the experiments of EAST in 2014.Comment: 2 pages, 2 figures, 19th IEEE-NPSS Real-Time conferenc

Homocysteine and Carotid Plaque Stability: A Cross-Sectional Study in Chinese Adults

Background and Purpose This study aimed to explore the possible association of plasma total homocysteine with carotid plaque stability. Methods: A cross-sectional study was conducted from 2010 to 2011. A stratified random sample of 2,919 Chinese participants aged 40 years or older was enrolled. Plasma total homocysteine levels were measured and carotid plaques were evaluated by ultrasonography. Logistic regression model was used to analyze the association of homocysteine levels to the progression of carotid plaque development, while adjusting for demographics and vascular risk factors. Results: The mean level of plasma homocysteine in the subjects was 14.9 µmol/l. Along with increase in homocysteine level, the risk of advanced carotid plaque elevated (odds ratio = 1.28; 95% confidence interval = 1.09–1.51) after adjusting for age, sex, and other potential confounders. Stratified by sex, higher homocysteine level was strongly associated with advanced carotid plaque in men (OR = 1.41; 95% confidence interval = 1.17–1.70), but not in women. Conclusion: The findings suggest that plasma level of homocysteine may be associated with advanced carotid plaque, which constitutes high risks of stroke, in male Chinese adults

Segmentation of kidney lesions with attention model based on Deeplab

We participate this challenge by developing a hierarchical framework. We build the model from two fully convolutional networks: (1) a simple Unet model to normalize the input iamges, (2) a segmentaion network which is an attention model based on Deeplab model. Two models are connected in tandem and trained end-to-end. To ensure a better results, we use the preprocess method proposed by nnUnet in our experiments

Atlas of human dental pulp cells at multiple spatial and temporal levels based on single-cell sequencing analysis

The dental pulp plays a crucial role in the long-term maintenance of tooth function. The progress of endodontic treatment and pulp tissue regeneration engineering has made pulp-regeneration therapy promising in clinical practice. However, the mechanisms of pulp regeneration and the role of dental stem cells in development and regeneration have not been fully elucidated. Bridging the gaps between clinical operation and basic research is urgently needed. With the application of single-cell sequencing technology in dental research, the landscapes of human dental pulp cells have begun being outlined. However, the specific cellular heterogeneity of dental pulp cells, especially that of dental stem cells, at different spatial and temporal levels, is still unclear. In this study, we used single-cell RNA sequencing analysis of pulp samples at four different developmental stages and combined the findings with immunohistochemical staining to explore the development of dental pulp and stem cells. The results revealed temporal changes in the proportion of pulp cells during development. For example, mononuclear phagocytes accounted for a higher proportion in early samples. Odontoblasts identified by DMP1 had a higher expression of ion channel-related and neurodevelopment-related genes. Subpopulations were identified in fibroblasts, odontoblasts, and mesenchymal stem cells. We identified a subclass of odontoblasts that expresses DGKI and RRBP1 present in early developmental samples. A population of earlier mesenchymal stem cells expressed the SEPTIN gene, which may have greater proliferative and differentiation potential. Furthermore, dental pulp stem cells can differentiate into two directions: mineralization and myogenesis. In summary, the specific cellular heterogeneity of dental pulp cells was revealed at different spatial and temporal levels. These findings may shed light on the mechanism of tooth development. The gene expression profile of developing pulp cells may help to select cells for regenerative engineering and improve the success of dental pulp regeneration

Comprehensive analysis of Cuproplasia and immune microenvironment in lung adenocarcinoma

Background: Trace elements such as copper are essential for human health. Recently the journal Nat Rev Cancer has put forward the concept of Cuproplasia, a way of promoting tumor growth through reliance on copper. We attempted to conduct a comprehensive analysis of Cuproplasia-related genes in lung adenocarcinoma (LUAD) to explore the mechanism of action of Cuproplasia-related genes in LUAD.Method: Transcriptome data and clinical information of LUAD were obtained from TCGA-LUAD and GSE31210, and prognostic models of Cuproplasia-related genes were constructed and verified by regression analysis of GSVA, WGCNA, univariate COX and lasso. The signal pathways affected by Cuproplasia-related genes were analyzed by GO, KEGG and hallmarK pathway enrichment methods. Five immunocell infiltration algorithms and IMVIGOR210 data were used to analyze immune cell content and immunotherapy outcomes in the high-low risk group.Results: In the results of WGCNA, BROWN and TURQUOISE were identified as modules closely related to Cuproplasia score. In the end, lasso regression analysis established a Cuproplasia-related signature (CRS) based on 24 genes, and the prognosis of high-risk populations was worse in TCGA-LUAD and GSE31210 datasets. The enrichment analysis showed that copper proliferation was mainly through chromosome, cell cycle, dna replication, g2m checkpoint and other pathways. Immunoinfiltration analysis showed that there were differences in the content of macrophages among the four algorithms. And IMVIGOR210 found that the lower the score, the more effective the immunotherapy was.Conclusion: The Cuproplasia related gene can be used to predict the prognosis and immunotherapy outcome of LUAD patients, and may exert its effect by affecting chromosome-related pathways and macrophages