Trace doping of multiple elements enables stable battery cycling of LiCoO2 at 4.6 V

LiCoO2 is a dominant cathode material for lithium-ion (Li-ion) batteries due to its high volumetric energy density, which could potentially be further improved by charging to high voltages. However, practical adoption of high-voltage charging is hindered by LiCoO2’s structural instability at the deeply delithiated state and the associated safety concerns. Here, we achieve stable cycling of LiCoO2 at 4.6 V (versus Li/Li+) through trace Ti–Mg–Al co-doping. Using state-of-the-art synchrotron X-ray imaging and spectroscopic techniques, we report the incorporation of Mg and Al into the LiCoO2 lattice, which inhibits the undesired phase transition at voltages above 4.5 V. We also show that, even in trace amounts, Ti segregates significantly at grain boundaries and on the surface, modifying the microstructure of the particles while stabilizing the surface oxygen at high voltages. These dopants contribute through different mechanisms and synergistically promote the cycle stability of LiCoO2 at 4.6 V

On-line 3D active pose-graph SLAM based on key poses using graph topology and sub-maps

© 2019 IEEE. In this paper, we present an on-line active pose-graph simultaneous localization and mapping (SLAM) frame-work for robots in three-dimensional (3D) environments using graph topology and sub-maps. This framework aims to find the best trajectory for loop-closure by re-visiting old poses based on the T-optimality and D-optimality metrics of the Fisher information matrix (FIM) in pose-graph SLAM. In order to reduce computational complexity, graph topologies are introduced, including weighted node degree (T-optimality metric) and weighted tree-connectivity (D-optimality metric), to choose a candidate trajectory and several key poses. With the help of the key poses, a sampling-based path planning method and a continuous-time trajectory optimization method are combined hierarchically and applied in the whole framework. So as to further improve the real-time capability of the method, the sub-map joining method is used in the estimation and planning process for large-scale active SLAM problems. In simulations and experiments, we validate our approach by comparing against existing methods, and we demonstrate the on-line planning part using a quad-rotor unmanned aerial vehicle (UAV)

Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet

Catheter segmentation in 3D ultrasound is important for computer-assisted cardiac intervention. However, a large amount of labeled images are required to train a successful deep convolutional neural network (CNN) to segment the catheter, which is expensive and time-consuming. In this paper, we propose a novel catheter segmentation approach, which requests fewer annotations than the supervised learning method, but nevertheless achieves better performance. Our scheme considers a deep Q learning as the pre-localization step, which avoids voxel-level annotation and which can efficiently localize the target catheter. With the detected catheter, patch-based Dual-UNet is applied to segment the catheter in 3D volumetric data. To train the Dual-UNet with limited labeled images and leverage information of unlabeled images, we propose a novel semi-supervised scheme, which exploits unlabeled images based on hybrid constraints from predictions. Experiments show the proposed scheme achieves a higher performance than state-of-the-art semi-supervised methods, while it demonstrates that our method is able to learn from large-scale unlabeled images.Comment: Accepted by MICCAI 202

Duration of untreated bipolar disorder: A multicenter study

Little is known about the demographic and clinical differences between short and long duration of untreated bipolar disorder (DUB) in Chinese patients. This study examined the demographic and clinical features of short (≤2 years) and long DUB (\u3e2 years) in China. A consecutively recruited sample of 555 patients with bipolar disorder (BD) was examined in 7 psychiatric hospitals and general hospital psychiatric units across China. Patients’ demographic and clinical characteristics were collected using a standardized protocol and data collection procedure. The mean DUB was 3.2 ± 6.0 years; long DUB accounted for 31.0% of the sample. Multivariate analyses revealed that longer duration of illness, diagnosis of BD type II, and earlier misdiagnosis of BD for major depressive disorder or schizophrenia were independently associated with long DUB. The mean DUB in Chinese BD patients was shorter than the reported figures from Western countries. The long-term impact of DUB on the outcome of BD is warranted

Pressure responses and phase transitions during the release of high pressure CO2 from a large-scale pipeline

As part of the carbon capture and storage (CCS) process, pipeline transportation is the safest and most economic option for delivering captured CO2 to a storage site. However, in the event of pipeline rupture an enormous mass of CO2 may be released very rapidly, presenting several risks to the pipeline and surrounding population including the significantly increased risk of brittle fracture in the pipe wall. The study of pressure variation and phase change in CO2 during pipeline blowdown can contribute to the understanding of fracture initiation and propagation, as well as downstream CO2 diffusion behavior. As part of the CO2QUEST project, a reusable, industrial scale pipeline experimental apparatus with a total length of 258 m and the inner diameter of 233 mm was fabricated to study pure CO2 pipeline blowdown. A dual-disc blasting device was used to remotely control the opening of the pipeline. The instantaneous pressure response following release was measured with high frequency pressure transducers. Variation in fluid temperature at the top and bottom of pipeline was also recorded. Six groups of pure CO2 pipeline release experiments were conducted with initially gaseous and dense phase inventories with three orifice diameters (15 mm, 50 mm and Full Bore Rupture). The typical waveform characteristics of pressure responses accompanying by the process of phase transitions in gaseous and dense CO2 leakage were observed during the release as results of the propagation of a series of expansion waves. The complicated phase transitions were obtained during depressurization of gaseous and dense CO2 releases. The gas-solid phase or gas-liquid-solid phase appeared when the pressure was below the triple point during the dense CO2 release. Keyword

Early growth response protein-1 promoter-mediated synergistic antitumor effect of hTERTC27 gene therapy and 5-flurorouracil on nasopharyngeal carcinoma

hTERTC27 is a newly constructed polypeptide that can induce telomere dysfunction. To study the synergistic antitumor effects of the hTERTC27 polypeptide driven by the early growth response protein-1 (Egr-1) promoter and chemotherapeutic 5-flurorouracil (5-FU) on nasopharyngeal carcinoma, a series of in vitro and in vivo experiments were performed. The results showed that hTERTC27 expression was significantly increased up to 7.21-folds by the 5-FU-activated Egr-1 promoter in C666-1 cells. Overexpressed hTERTC27 made the cells more sensitive to 5-FU, and additionally, inhibited cell proliferation about 20.41%. Combinational therapy of overexpressed hTERTC27 driven by the 5-FU-activated Egr-1 promoter and 5-FU synergistically inhibited cell proliferation and promoted apoptosis of C666-1 cells for about 4.75-fold and 1.76-fold in comparison with a sole therapy of hTERTC27 or 5-FU in vitro. In vivo experiments showed that overexpressed hTERTC27 driven by 5-FU-activated Egr-1 promoter and 5-FU synergistically reduced tumor volume, tumor weight, and local infiltration, which may be relative to tumor cell apoptosis. These results suggest that combinational therapy of overexpressed hTERTC27, which is driven by the 5-FU-activated Egr-1 promoter, and 5-FU may provide a novel approach to treat nasopharyngeal cancer. © 2012 Mary Ann Liebert, Inc.published_or_final_versio

Research progress on fracture control of accidental leakage and decompression in CO2 pipeline transportation

Pipeline is the optimal way in transporting large amounts of carbon dioxide (CO2) in CCUS (carbon capture, utilization and storage) technology industrial chain. In this paper, the research progress on decompression and fracture propagation of CO2 pipeline leakage was reviewed from aspects of experiment and computer simulation. The influence of phase state, pipe material and buried condition on crack propagation was analyzed. The influence of equation of state (EOS), impurity factor and theoretical model on experimental and simulation calculation were discussed. The EOS suitable for the establishment of decompression wave prediction model was summarized and the theoretical method and simulation software of fluid-structure coupling research, as well as the technical documentations for the design of CO2 transport pipelines, were mentioned. The scientific problems that need to be studied further in CO2 pipeline leakage decompression and fracture propagation control were summarized. Prospecting the research contents that need to be carried out include: ①establishing the EOS calculation model of multivariate mixture at three phase point and phase line, ②seting up the coupling relationship between the thermal properties of CO2 and crack propagation furtherly, ③establishing the stop criterion of pipeline fracture, and ④developing and optimizing the special crack stop devices to avoid fracture propagation for CO2 transportation pipelines

Region-based and pathway-based QTL mapping using a p-value combination method

Quantitative trait locus (QTL) mapping using deep DNA sequencing data is a challenging task. In this study we performed region-based and pathway-based QTL mappings using a p-value combination method to analyze the simulated quantitative traits Q1 and Q4 and the exome sequencing data. The aims were to evaluate the performance of the QTL mapping approaches that were used and to suggest plausible strategies for QTL mapping of DNA sequencing data. We conducted single-locus QTL mappings using a linear regression model with adjustments for age and smoking status, and we also conducted region-based and pathway-based QTL mappings using a truncated product method for combining p-values from the single-locus QTL mapping. To account for the features of rare variants and common single-nucleotide polymorphisms (SNPs), we considered independently rare-variant-only, common-SNP-only, and combined analyses. An analysis of 200 simulated replications showed that the three region-based methods reasonably controlled type I error, whereas the combined analysis yielded the greatest statistical power. Rare-variant-only, common-SNP-only, and combined analyses were also applied to pathway-based QTL mappings. We found that pathway-based QTL mappings had a power of approximately 100% when the significance of the vascular endothelial growth factor pathway was evaluated, but type I errors were slightly inflated. Our approach complements single-locus QTL mapping. An integrated approach using single-locus, combined region-based, and combined pathway-based analyses should yield promising results for QTL mapping of DNA sequencing data

Dual Space Graph Contrastive Learning

Unsupervised graph representation learning has emerged as a powerful tool to address real-world problems and achieves huge success in the graph learning domain. Graph contrastive learning is one of the unsupervised graph representation learning methods, which recently attracts attention from researchers and has achieved state-of-the-art performances on various tasks. The key to the success of graph contrastive learning is to construct proper contrasting pairs to acquire the underlying structural semantics of the graph. However, this key part is not fully explored currently, most of the ways generating contrasting pairs focus on augmenting or perturbating graph structures to obtain different views of the input graph. But such strategies could degrade the performances via adding noise into the graph, which may narrow down the field of the applications of graph contrastive learning. In this paper, we propose a novel graph contrastive learning method, namely Dual Space Graph Contrastive (DSGC) Learning, to conduct graph contrastive learning among views generated in different spaces including the hyperbolic space and the Euclidean space. Since both spaces have their own advantages to represent graph data in the embedding spaces, we hope to utilize graph contrastive learning to bridge the spaces and leverage advantages from both sides. The comparison experiment results show that DSGC achieves competitive or better performances among all the datasets. In addition, we conduct extensive experiments to analyze the impact of different graph encoders on DSGC, giving insights about how to better leverage the advantages of contrastive learning between different spaces

H-Dihyperon in Quark Cluster Model

The H dihyperon (DH) is studied in the framework of the SU(3) chiral quark model. It is shown that except the $\sigma$ chiral field, the overall effect of the other SU(3) chiral fields is destructive in forming a stable DH. The resultant mass of DH in a three coupled channel calculation is ranged from 2225 $MeV$ to 2234 $MeV$.Comment: 9 pages, emte