Acoustic impedance inversion in coal strata using the priori constraint-based TCN-BiGRU method

Acoustic impedance inversion is a key technique for the seismic exploration of coalfield, which can determine subsurface lithological changes and coal seam distribution. The traditional method is highly subjective, has poor generalizability, and interpretation can be time and labor consuming. Due to the powerful nonlinear interpretation and feature extraction capabilities of neural networks, deep learning technology has demonstrated potential for geophysical exploration. To predict acoustic impedance accurately and efficiently, this study proposes the use of the initial geological model as the priori constraint for training. The low-frequency feature extraction capability of a bidirectional gated recurrent unit network and the high-frequency feature extraction capability of a temporal convolutional network are used to establish a new acoustic impedance inversion method in coal strata with a priori constraint data. The temporal convolutional network-bidirectional gated recurrent unit method was applied to data from the Xinjing Mining Area in Shanxi province, northern China. The results displayed good precision by accurately predicting the distribution and thickness variation of local coal seams. Compared with the traditional model-based method and the method using temporal convolutional network-bidirectional gated recurrent unit network, the proposed priori constraint-based temporal convolutional network-bidirectional gated recurrent unit network has better feature expression capability and provides more detailed coal seam information. In conclusion, the new method can improve the accuracy of acoustic impedance inversion, which is of great significance for coalfield seismic exploration.Document Type: Original articleCited as: Shi, S., Qi, Y., Chang, W., Li, L., Yao, X., Shi, J. Acoustic impedance inversion in coal strata using the priori constraint-based TCN-BiGRU method. Advances in Geo-Energy Research, 2023, 9(1): 13-24. https://doi.org/10.46690/ager.2023.07.0

The Tianlin Mission: a 6m UV/Opt/IR space telescope to explore the habitable worlds and the universe

[Abridged] It is expected that the ongoing and future space-borne planet survey missions including TESS, PLATO, and Earth 2.0 will detect thousands of small to medium-sized planets via the transit technique, including over a hundred habitable terrestrial rocky planets. To conduct a detailed study of these terrestrial planets, particularly the cool ones with wide orbits, the exoplanet community has proposed various follow-up missions. The currently proposed ESA mission ARIEL is capable of characterization of planets down to warm super-Earths mainly using transmission spectroscopy. The NASA 6m UV/Opt/NIR mission proposed in the Astro2020 Decadal Survey may further tackle down to habitable rocky planets, and is expected to launch around 2045. In the meanwhile, China is funding a concept study of a 6-m class space telescope named Tianlin (A UV/Opt/NIR Large Aperture Space Telescope) that aims to start its operation within the next 10-15 years and last for 5+ years. Tianlin will be primarily aimed to the discovery and characterization of rocky planets in the habitable zones (HZ) around nearby stars and to search for potential biosignatures mainly using the direct imaging method. Transmission and emission spectroscopy at moderate to high resolution will be carried out as well on a population of exoplanets to strengthen the understanding of the formation and evolution of exoplanets. It will also carry out in-depth studies of the cosmic web and early galaxies, and constrain the nature of the dark matter and dark energy. We describe briefly the primary scientific motivations and main technical considerations based on our preliminary simulation results. We find that a monolithic off-axis space telescope with a primary mirror diameter larger than 6m equipped with a high contrast chronograph can identify water in the atmosphere of a habitable-zone Earth-like planet around a Sun-like star.Comment: 15 pages, 5 figures, accepted for publication in RAA and is available onlin

A multiyear assessment of air quality benefits from China’s emerging shale gas revolution: Urumqi as a case study

China is seeking to unlock its shale gas in order to curb its notorious urban air pollution, but robust assessment of the impact on PM2.5 pollution of replacing coal with natural gas for winter heating is lacking. Here, using a whole-city heating energy shift opportunity offered by substantial reductions in coal combustion during the heating periods in Urumqi, northwest China, we conducted a four-year study to reveal the impact of replacing coal with natural gas on the mass concentrations and chemical components of PM2.5. We found a significant decline in PM2.5, major soluble ions and metal elements in PM2.5 in January of 2013 and 2014 compared with the same periods in 2012 and 2011, reflecting the positive effects on air quality of using natural gas as a heating fuel throughout the city. This occurred following complete replacement with natural gas for heating energy in October 2012. The weather conditions during winter did not show any significant variation over the four years of the study. Our results indicate that China and other developing nations will benefit greatly from a change in energy source, that is, increasing the contribution of either natural gas or shale gas to total energy consumption with a concomitant reduction in coal consumption

Rnd3/RhoE Modulates HIF1α/VEGF Signaling by Stabilizing HIF1α and Regulates Responsive Cardiac Angiogenesis

The insufficiency of compensatory angiogenesis in the heart of patients with hypertension contributes to heart failure transition. The hypoxia-inducible factor 1α-vascular endothelial growth factor (HIF1α-VEGF) signaling cascade controls responsive angiogenesis. One of the challenges in reprograming the insufficient angiogenesis is to achieve a sustainable tissue exposure to the proangiogenic factors, such as HIF1α stabilization. In this study, we identified Rnd3, a small Rho GTPase, as a proangiogenic factor participating in the regulation of the HIF1α-VEGF signaling cascade. Rnd3 physically interacted with and stabilized HIF1α, and consequently promoted VEGFA expression and endothelial cell tube formation. To demonstrate this proangiogenic role of Rnd3 in vivo, we generated Rnd3 knockout mice. Rnd3 haploinsufficient (Rnd3(+/-)) mice were viable, yet developed dilated cardiomyopathy with heart failure after transverse aortic constriction stress. The poststress Rnd3(+/-) hearts showed significantly impaired angiogenesis and decreased HIF1α and VEGFA expression. The angiogenesis defect and heart failure phenotype were partially rescued by cobalt chloride treatment, a HIF1α stabilizer, confirming a critical role of Rnd3 in stress-responsive angiogenesis. Furthermore, we generated Rnd3 transgenic mice and demonstrated that Rnd3 overexpression in heart had a cardioprotective effect through reserved cardiac function and preserved responsive angiogenesis after pressure overload. Finally, we assessed the expression levels of Rnd3 in the human heart and detected significant downregulation of Rnd3 in patients with end-stage heart failure. We concluded that Rnd3 acted as a novel proangiogenic factor involved in cardiac responsive angiogenesis through HIF1α-VEGFA signaling promotion. Rnd3 downregulation observed in patients with heart failure may explain the insufficient compensatory angiogenesis involved in the transition to heart failure

Automatic assessment of glioma burden: A deep learning algorithm for fully automated volumetric and bi-dimensional measurement

Background Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO). Methods Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment “baseline” MRIs) from 1 institution. Results The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively. Conclusions Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation

Closely-related taxa influence woody species discrimination via DNA barcoding: evidence from global forest dynamics plots

To determine how well DNA barcodes from the chloroplast region perform in forest dynamics plots (FDPs) from global CTFS-ForestGEO network, we analyzed DNA barcoding sequences of 1277 plant species from a wide phylogenetic range (3 FDPs in tropics, 5 in subtropics and 5 in temperate zone) and compared the rates of species discrimination (RSD). We quantified RSD by two DNA barcode combinations (rbcL + matK and rbcL + matK + trnH-psbA) using a monophyly-based method (GARLI). We defined two indexes of closely-related taxa (G[subscript]m/G[subscript]t and S/G ratios) and correlated these ratios with RSD. The combination of rbcL + matK averagely discriminated 88.65%, 83.84% and 72.51% at the local, regional and global scales, respectively. An additional locus trnH-psbA increased RSD by 2.87%, 1.49% and 3.58% correspondingly. RSD varied along a latitudinal gradient and were negatively correlated with ratios of closely-related taxa. Successes of species discrimination generally depend on scales in global FDPs. We suggested that the combination of rbcL + matK + trnH-psbA is currently applicable for DNA barcoding-based phylogenetic studies on forest communities.Supplementary information accompanies this paper at http://www.nature.com/srep. This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Nature Publishing Group. The published article can be found at: http://www.nature.com/articles/srep1512

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe