End-to-End Insulator String Defect Detection in a Complex Background Based on a Deep Learning Model

Normal power line insulators ensure the safe transmission of electricity. The defects of the insulator reduce the insulation, which may lead to the failure of power transmission systems. As unmanned aerial vehicles (UAVs) have developed rapidly, it is possible for workers to take and upload aerial images of insulators. Proposing a technology to detect insulator defects with high accuracy in a short time can be of great value. The existing methods suffer from complex backgrounds so that they have to locate and extract the insulators at first. Some of them make detection relative to some specific conditions such as angle, brightness, and object scale. This study aims to make end-to-end detections using aerial images of insulators, giving the locations of insulators and defects at the same time while overcoming the disadvantages mentioned above. A DEtection TRansformer (DETR) having an encoder–decoder architecture adopts convolutional neural network (CNN) as the backbone network, applies a self-attention mechanism for computing, and utilizes object queries instead of a hand-crafted process to give the direct predictions. We modified this for insulator detection in complex aerial images. Based on the dataset we constructed, our model can get 97.97 in mean average precision when setting the threshold of intersection over union at 0.5, which is better than Cascade R-CNN and YOLOv5. The inference speed of our model can reach 25 frames per second, which is qualified for actual use. Experimental results demonstrate that our model meets the robustness and accuracy requirements for insulator defect detection

Sustained activity within the default mode network during an implicit memory task

Recent neuroimaging studies have shown that several brain regions - namely, the posterior cingulate cortex (PCC), ventral medial prefrontal cortex (vmPFC), and the bilateral angular gyrus - are more active during resting states than during cognitive tasks (i.e., default mode network). Although there is evidence showing that the default mode network is associated with unconscious state, it is unclear whether this network is associated with unconscious processing when normal human subjects perform tasks without awareness. We manipulated the level of conscious processing in normal subjects by asking them to perform an implicit and an explicit memory task, and analyzed signal changes in the default mode network for the stimuli versus baseline in both tasks. The functional magnetic resonance imaging (fMRI) analysis showed that the level of activation in regions within this network during the implicit task was not significantly different from that during the baseline, except in the left angular gyrus and the insula. There was strong deactivation for the explicit task when compared with the implicit task in the default mode regions, except in the left angular gyrus and the left middle temporal gyrus. These data suggest that the activity in the default network is sustained and less disrupted when an implicit memory task is performed, but is suspended when explicit retrieval is required. These results provide evidence that the default mode network is associated with unconscious processing when human subjects perform an implicit memory task. (c) 2009 Elsevier Srl. All rights reserved

Oxidative dehydrogenation of ethane to ethylene over LiCl/SO42--ZrO2 catalyst

Sulfated zirconia (SO42--ZrO2) samples were prepared by a modified two-step method (refluxing ZrO(OH)(2) precursor in basic solution followed by drying and (NH4)(2)SO4 impregnation) and then impregnated with a LiCl solution to give the SO42--ZrO2-supported LICI catalysts with Li mass content of 0.5% similar to 15%. The catalysts were characterized by X-ray diffraction, scanning electron microscopy, N-2 adsorption, temperature-programmed desorption-mass spectrometry, and X-ray photoelectron spectroscopy. The results show that with increasing LiCl loading, the specific surface area and acidity of the catalysts as well as the volume fraction of tetragonal zirconia in the catalysts decrease, while the catalytic performance of the catalysts for oxidative dehydrogenation of ethane (ODHE) to ethylene increases. Over the LiCl/SO42--ZrO2 catalyst with a Li content of 15% ethylene yield of 77.8% with an ethane conversion of 90.6% is achieved at 650 degrees C, and the yield higher than 71% is maintained over a period of 24 h. The textural structure of ZrO? has little effect on the catalytic behavior of the LiCl/SO42--ZrO2 catalysts. The specific surface area of SO42--ZrO2 samples prepared by the fled two-step method is much bigger than that of the SO42--ZrO2 samples made by the method reported in literature, and therefore more LiCl call be loaded on unit mass of support. This is favorable to improve the catalyst stability and slow down catalyst deactivation during the ODHE reaction due to the loss of LiCl

Integrated Profiling of MicroRNAs and mRNAs: MicroRNAs Located on Xq27.3 Associate with Clear Cell Renal Cell Carcinoma

Background: With the advent of second-generation sequencing, the expression of gene transcripts can be digitally measured with high accuracy. The purpose of this study was to systematically profile the expression of both mRNA and miRNA genes in clear cell renal cell carcinoma (ccRCC) using massively parallel sequencing technology. Methodology: The expression of mRNAs and miRNAs were analyzed in tumor tissues and matched normal adjacent tissues obtained from 10 ccRCC patients without distant metastases. In a prevalence screen, some of the most interesting results were validated in a large cohort of ccRCC patients. Principal Findings: A total of 404 miRNAs and 9,799 mRNAs were detected to be differentially expressed in the 10 ccRCC patients. We also identified 56 novel miRNA candidates in at least two samples. In addition to confirming that canonical cancer genes and miRNAs (including VEGFA, DUSP9 and ERBB4; miR-210, miR-184 and miR-206) play pivotal roles in ccRCC development, promising novel candidates (such as PNCK and miR-122) without previous annotation in ccRCC carcinogenesis were also discovered in this study. Pathways controlling cell fates (e. g., cell cycle and apoptosis pathways) and cell communication (e. g., focal adhesion and ECM-receptor interaction) were found to be significantly more likely to be disrupted in ccRCC. Additionally, the results of the prevalence screen revealed that the expression of a miRNA gene cluster located on Xq27.3 was consistently downregulated in at least 76.7% of similar to 50 ccRCC patients. Conclusions: Our study provided a two-dimensional map of the mRNA and miRNA expression profiles of ccRCC using deep sequencing technology. Our results indicate that the phenotypic status of ccRCC is characterized by a loss of normal renal function, downregulation of metabolic genes, and upregulation of many signal transduction genes in key pathways. Furthermore, it can be concluded that downregulation of miRNA genes clustered on Xq27.3 is associated with ccRCC

Global modeling of aerosol dynamics: Model description, evaluation, and interactions between sulfate and nonsulfate aerosols

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95258/1/jgrd12001.pd

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

The Diversity and Composition of Soil Microbial Community Differ in Three Typical Wetland Types of the Sanjiang Plain, Northeastern China

The wetlands in China’s Sanjiang Plain have experienced intensive anthropogenic disturbance recently, and this has obviously changed their environmental characteristics. Soil microorganisms play an important role in wetland ecosystems. However, the effects of different wetland types on soil microbial diversity and community composition remain largely unclear. Therefore, we assessed the effects of three typical wetland types—permanently flooded wetlands, seasonally flooded wetlands and non-flooded wetlands—on soil microbial communities in the Sanjiang Plain, using phospholipid fatty acid analysis (PLFA) technology. A total of 56 different PLFA compounds were identified, of which 10 are typically produced by uncharacterized bacteria, 15 by Gram-positive bacteria, and 11 by Gram-negative bacteria. In addition, 2 fungal groups were identified, based on four PLFAs, and four PLFAs typical for protozoa were detected. High levels were detected for 16:0 (attributed to bacteria) and i17:1ω9c (produced by Gram-positive bacteria). The latter (i17:1ω9c) was exceptionally high in non-flooded soil (8407.15 ± 2675.84 ng/g). High levels of 18:1ω7c (1939.15 ± 666.13 ng/g) and 18:1ω9c (1713.26 ± 360.65 ng/g) were detected in permanently flooded wetlands and about the same in seasonally flooded wetlands, but lower ranks were present in the drier non-flooded wetlands. The Shannon-Wiener diversity index decreased with permanently flooded wetlands (3.05) > seasonally flooded wetlands (3.02) > non-flooded wetlands (2.12). Redundancy analysis showed that the two axes could explain a total of 94.48% of soil microbial communities. Soil water content, total and available phosphorus, and total and available nitrogen correlated significantly with soil microbial communities of three wetland types. Cluster analysis of correlations between individual PLFA biomarkers and soil physiochemical properties demonstrated the complexity of the community responses to the three different habitats. This study demonstrates that microbial diversity and composition changed sensitivity among the three wetland types, and soil moisture content was the key environmental factor to affect the soil microbial communities

The Diversity and Composition of Soil Microbial Community Differ in Three Typical Wetland Types of the Sanjiang Plain, Northeastern China

The wetlands in China’s Sanjiang Plain have experienced intensive anthropogenic disturbance recently, and this has obviously changed their environmental characteristics. Soil microorganisms play an important role in wetland ecosystems. However, the effects of different wetland types on soil microbial diversity and community composition remain largely unclear. Therefore, we assessed the effects of three typical wetland types—permanently flooded wetlands, seasonally flooded wetlands and non-flooded wetlands—on soil microbial communities in the Sanjiang Plain, using phospholipid fatty acid analysis (PLFA) technology. A total of 56 different PLFA compounds were identified, of which 10 are typically produced by uncharacterized bacteria, 15 by Gram-positive bacteria, and 11 by Gram-negative bacteria. In addition, 2 fungal groups were identified, based on four PLFAs, and four PLFAs typical for protozoa were detected. High levels were detected for 16:0 (attributed to bacteria) and i17:1ω9c (produced by Gram-positive bacteria). The latter (i17:1ω9c) was exceptionally high in non-flooded soil (8407.15 ± 2675.84 ng/g). High levels of 18:1ω7c (1939.15 ± 666.13 ng/g) and 18:1ω9c (1713.26 ± 360.65 ng/g) were detected in permanently flooded wetlands and about the same in seasonally flooded wetlands, but lower ranks were present in the drier non-flooded wetlands. The Shannon-Wiener diversity index decreased with permanently flooded wetlands (3.05) > seasonally flooded wetlands (3.02) > non-flooded wetlands (2.12). Redundancy analysis showed that the two axes could explain a total of 94.48% of soil microbial communities. Soil water content, total and available phosphorus, and total and available nitrogen correlated significantly with soil microbial communities of three wetland types. Cluster analysis of correlations between individual PLFA biomarkers and soil physiochemical properties demonstrated the complexity of the community responses to the three different habitats. This study demonstrates that microbial diversity and composition changed sensitivity among the three wetland types, and soil moisture content was the key environmental factor to affect the soil microbial communities