Thermochemical sulfate reduction in fossil Ordovician deposits of the Majiang area: Evidence from a molecular-marker investigation

The main reservoirs of Majiang fossil deposits consist of the Silurian Wengxiang group, dominantly sandstones, and the Ordovician Honghuayuan formation, dominantly carbonate rocks, and the Lower Cambrian Niutitang Formation mudstones serve as the major source rocks. Thermochemical sulfate reduction (TSR) might have taken place in the Paleozoic marine carbonate oil pools, as indicated by high concentrations of dibenzothiophenes in the extracts (MDBT=0.27-4.32 µg/g extract, and MDBT/MPH= 0.71-1.38). Hydrocarbons in the Pojiaozhai Ordovician carbonate reservoirs have undergone severe TSR and are characterized by higher quantities of diamondoids and MDBT and heavier isotopic values (δ13C=-28.4‰). The very large amounts of dibenzothiophenes might be products of reactions between biphenyls and sulfur species associated with TSR

Comparison of VLBI and GNSS common view for time transfer

With the rapid development of optical clock, the stability and system uncertainty of optical clocks has reached a 1.0e–18 level. Optical clocks will likely constitute the next generation of time-frequency standards for redefining the SI second. Because time and frequency transfer services that rely on satellite systems are not always reliable and currently available technologies are insufficient for comparing the next generation of frequency standards, high-precision time and transfer techniques are strongly desired. Very Long Baseline Interferometry (VLBI) is one of the space geodetic techniques that measure the arrival time delays between multiple stations utilizing radio signals from distant celestial radio sources. Not only can VLBI obtain the angle position measurement of the radio source with sub-millisecond accuracy and the station coordinate measurement with millimeter accuracy, but also, it can provide high-precision information regarding inter-station atomic clock differences. Therefore, it is theoretically feasible to use the VLBI technology to do the remote time transfer. Because of this characteristic of VLBI technology, VLBI has significant application potential in the field of remote time transfer. To confirm the suitability of VLBI to time-frequency transfer for future practical applications, the results of VLBI and GPS common view time transfer were compared using a Kunming-Urumqi baseline. The performance characteristics of time transfer based on VLBI are then analyzed. Experimental results show that VLBI technology can accurately measure the variation of clock differences between stations as same as the GPS common view time comparison technology. It briefly describes the challenges of future VLBI technology for practical applications of time transfer

Spatiotemporal Variation and Driving Analysis of Groundwater in the Tibetan Plateau Based on GRACE Downscaling Data

The special geographical environment of the Tibetan Plateau makes ground observation of Ground Water Storage (GWS) changes difficult, and the data obtained from the GRACE gravity satellites can effectively solve this problem. However, it is difficult to investigate the detailed GWS changes because of the coarser spatial resolution of GRACE data. In this paper, we constructed a 0.1° resolution groundwater storage anomalies (GWSA) dataset on the Tibetan Plateau from 2002 to 2020 based on a phased statistical downscaling model and analyzed the spatiotemporal variation and driving factors of the GWSA in order to better study the changes of GWS on the Qinghai Tibet Plateau. The results show that: (1) In the Tibetan Plateau and 12 sub-basins, the GWSA before and after downscaling show a very high correlation in time series and relatively good performance in spatial consistency, and the downscaled GWSA indicate a consistent trend with the measured groundwater level. (2) The GWSA on the Tibetan Plateau shows a downward trend (−0.45 mm/yr) from 2002 to 2020, and the variation trend of the GWSA in the Tibetan Plateau shows significant spatial heterogeneity. (3) The GWSA changes in the Tibetan Plateau are mainly dominated by natural factors, but the influence of human activities in individual sub-basins can not be ignored. Among the teleconnection factors, El Nino-Southern Oscillation Index (ENSO) has the greatest influence on the GWSA on the Tibetan Plateau

Adjunctive rifampin for the treatment of Staphylococcus aureus bacteremia with deep infections: A meta-analysis.

BACKGROUND:Staphylococcus aureus (S. aureus) bacteremia (SAB) has high morbidity and mortality, with the development of methicillin-resistant S. aureus (MRSA) and the recognized shortcomings of vancomycin, its management is becoming more complicated. Considering the capability to penetrate cells, tissues and biofilms, rifampin has been used as adjunctive agent to against staphylococcal activity. OBJECTIVES:We performed this meta-analysis, aimed to explore the efficacy of adjunctive rifampin for the treatment of SAB. METHODS:Medical literatures were searched in the Pubmed, Medline, Embase and Cochrane databases up to October 2018. Patients with SAB received treatment with or without rifampin were included. The risk ratio (RR) and 95% confidence intervals (CI) of mortality, rate of bacteriological failure and relapse were estimated. RESULTS:Seven articles (five randomized controlled trials and two retrospective cohort studies) enrolling 979 and 636 patients of SAB treated with and without rifampin, respectively, were included. There was no difference of mortality between the adjunctive rifampin therapy and standard therapy on SAB (RR: 0.771, 95% CI: 0.442 to 1.347, I2 = 70.4%). In the subgroup analyses, the decreased mortality was observed in the adjunctive rifampin treatment for patients without MRSA infection (RR: 0.509, 95% CI: 0.372 to 0.697, I2 = 8.8%). In addition, there was no difference of the rate of bacteriologic failure (RR: 0.602, 95% CI: 0.198 to 1.825, I2 = 0.0%) or relapse (RR: 0.574, 95% CI: 0.106 to 3.112, I2 = 77.9%) between the adjunctive rifampin therapy and standard therapy on SAB. CONCLUSIONS:In general, insufficient evidence supported the efficacy of adjunctive use of rifampin for treatment of SAB, adding rifampin to standard therapy didn't decrease the incidence of death, rate of bacteriologic failure and relapse

Polysaccharide from Edible Alga Enteromorpha clathrata Improves Ulcerative Colitis in Association with Increased Abundance of Parabacteroides spp. in the Gut Microbiota of Dextran Sulfate Sodium-Fed Mice

Polysaccharide from the edible alga Enteromorpha clathrata has been demonstrated to exert beneficial effects on human health. However, what effect it has on inflammatory bowel diseases has not been investigated. Here, using a mouse model of dextran sulfate sodium (DSS)-induced ulcerative colitis, we illustrate that Enteromorpha clathrata polysaccharide (ECP) could alleviate body weight loss, reduce incidences of colonic bleeding, improve stool consistency and ameliorate mucosal damage in diseased mice. 16S rRNA high-throughput sequencing and bioinformatic analysis indicated that ECP significantly changed the structure of the gut microbiota and increased the abundance of Parabacteroides spp. in DSS-fed mice. In vitro fermentation studies further confirmed that ECP could promote the growth of Parabacteroides distasonis F1-28, a next-generation probiotic bacterium isolated from the human gut, and increase its production of short-chain fatty acids. Additionally, Parabacteroides distasonis F1-28 was also found to have anti-ulcerative colitis effects in DSS-fed mice. Altogether, our study demonstrates for the first time a beneficial effect of ECP on ulcerative colitis and provides a possible basis for understanding its therapeutic mechanisms from the perspective of symbiotic gut bacteria Parabacteroides distasonis

Deep Learning-Based Object Detection Techniques for Remote Sensing Images: A Survey

Object detection in remote sensing images (RSIs) requires the locating and classifying of objects of interest, which is a hot topic in RSI analysis research. With the development of deep learning (DL) technology, which has accelerated in recent years, numerous intelligent and efficient detection algorithms have been proposed. Meanwhile, the performance of remote sensing imaging hardware has also evolved significantly. The detection technology used with high-resolution RSIs has been pushed to unprecedented heights, making important contributions in practical applications such as urban detection, building planning, and disaster prediction. However, although some scholars have authored reviews on DL-based object detection systems, the leading DL-based object detection improvement strategies have never been summarized in detail. In this paper, we first briefly review the recent history of remote sensing object detection (RSOD) techniques, including traditional methods as well as DL-based methods. Then, we systematically summarize the procedures used in DL-based detection algorithms. Most importantly, starting from the problems of complex object features, complex background information, tedious sample annotation that will be faced by high-resolution RSI object detection, we introduce a taxonomy based on various detection methods, which focuses on summarizing and classifying the existing attention mechanisms, multi-scale feature fusion, super-resolution and other major improvement strategies. We also introduce recognized open-source remote sensing detection benchmarks and evaluation metrics. Finally, based on the current state of the technology, we conclude by discussing the challenges and potential trends in the field of RSOD in order to provide a reference for researchers who have just entered the field

Deep Learning-Based Object Detection Techniques for Remote Sensing Images: A Survey

Object detection in remote sensing images (RSIs) requires the locating and classifying of objects of interest, which is a hot topic in RSI analysis research. With the development of deep learning (DL) technology, which has accelerated in recent years, numerous intelligent and efficient detection algorithms have been proposed. Meanwhile, the performance of remote sensing imaging hardware has also evolved significantly. The detection technology used with high-resolution RSIs has been pushed to unprecedented heights, making important contributions in practical applications such as urban detection, building planning, and disaster prediction. However, although some scholars have authored reviews on DL-based object detection systems, the leading DL-based object detection improvement strategies have never been summarized in detail. In this paper, we first briefly review the recent history of remote sensing object detection (RSOD) techniques, including traditional methods as well as DL-based methods. Then, we systematically summarize the procedures used in DL-based detection algorithms. Most importantly, starting from the problems of complex object features, complex background information, tedious sample annotation that will be faced by high-resolution RSI object detection, we introduce a taxonomy based on various detection methods, which focuses on summarizing and classifying the existing attention mechanisms, multi-scale feature fusion, super-resolution and other major improvement strategies. We also introduce recognized open-source remote sensing detection benchmarks and evaluation metrics. Finally, based on the current state of the technology, we conclude by discussing the challenges and potential trends in the field of RSOD in order to provide a reference for researchers who have just entered the field

Acetylated Chitosan Oligosaccharides Act as Antagonists against Glutamate-Induced PC12 Cell Death via Bcl-2/Bax Signal Pathway

Chitosan oligosaccharides (COSs), depolymerized products of chitosan composed of β-(1→4) d-glucosamine units, have broad range of biological activities such as antitumour, antifungal, and antioxidant activities. In this study, peracetylated chitosan oligosaccharides (PACOs) and N-acetylated chitosan oligosaccharides (NACOs) were prepared from the COSs by chemcal modification. The structures of these monomers were identified using NMR and ESI-MS spectra. Their antagonist effects against glutamate-induced PC12 cell death were investigated. The results showed that pretreatment of PC12 cells with the PACOs markedly inhibited glutamate-induced cell death in a concentration-dependent manner. The PACOs were better glutamate antagonists compared to the COSs and the NACOs, suggesting the peracetylation is essential for the neuroprotective effects of chitosan oligosaccharides. In addition, the PACOs pretreatment significantly reduced lactate dehydrogenase release and reactive oxygen species production. It also attenuated the loss of mitochondrial membrane potential. Further studies indicated that the PACOs inhibited glutamate-induced cell death by preventing apoptosis through depressing the elevation of Bax/Bcl-2 ratio and caspase-3 activation. These results suggest that PACOs might be promising antagonists against glutamate-induced neural cell death

Orientation-First Strategy With Angle Attention Module for Rotated Object Detection in Remote Sensing Images

Recently, object detection in remote sensing images (RSIs) have received extensive attention and made significant progress. Nonetheless, the arbitrary orientations of objects in RSIs make their detection a challenging task. Most of the existing detection methods are difficult to extract the orientation features of objects due to the lack of directionality of conventional convolutions. In addition, the boundary discontinuity in angle regression affects the detection of object orientations. In response to these problems, this article proposes an orientation-first refinement detector (OFRDet), which is based on a strategy that enables the detector to detect the angle of an object ahead of others and presets oriented anchors. In OFRDet, we propose an angle encoding regression module (AERM) and an angle channel attention module (ACAM). AERM transforms angle detection into multiparameter regression, which eliminates boundary discontinuities. ACAM uses convolution kernels with different angles to extract directional features purposefully according to the preset oriented anchors. After these two modules, more accurate bounding boxes are generated and sent to the refined stage to obtain the final detection results. We evaluate our method and demonstrate the effectiveness of it by conducting experiments on two challenging and credible datasets, DOTA, HRSC2016. OFRDet achieves competitive results 79.56%, 96.29% mAP on the two datasets, respectively