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Glucose-derived porous activated carbon materials (AGC-600-4 and AGC-180-x) are prepared using ZnCl2 as the etching agent via impregnation treatment and hydrothermal method followed by the calcination process. The analytic results indicate that the obtained materials exhibit higher specific surface area and superior double-layer capacitive behavior than the corresponding pristine carbon (GC-600 and GC-180) when used as electrode materials for supercapacitors. Moreover, compared with the AGC-600-4 nanosheets, the optimal AGC-180-4 microspheres have a high specific surface area of 1713 m2 g−1 and a maximum specific capacitance of 235.9 F g−1 at a current density of 1.0 A g−1 in the three-electrode system. Meanwhile, AGC-180-4 also exhibits better capacitive properties than AGC-600-4 in the two-electrode system, showing an excellent cyclic stability with a high energy density of 24.63 Wh kg−1 at the power density of 949.5 W kg−1. It is thus demonstrated that AGC-180-4 could be ideal electrode materials for supercapacitor due to its unique etched spherical structure and excellent electrochemical properties.

Liver vessels provide lots of important information for liver-disease diagnosis and liver surgery. This paper presents an effective liver vessel segmentation method from abdominal computer tomography angiography (CTA) images. The proposed method applies two techniques including centerline constraint and intensity model for effective detection of liver vessels, in which the former aims at generating the position and distance restraints for the detection of thin vessels by the offset medialness filter and height ridge traversal algorithm, while the latter is mainly used to extract intensity feature for the detection of thick vessels based on Kernel Fuzzy C-Means (KFCM). And then, the centerline constraint and intensity model are integrated into graph cuts for ultimate liver vessel segmentation. The proposed method does not require any manual selection of the initial vessel regions, and is capable of dealing with complex liver vessel systems. The experimental results on clinical CTA data sets give an average accuracy, sensitivity, and specificity of 97.4%, 83.0%, and 98.1%, respectively, which show the efficiency of the proposed method on liver vessel segmentation.

Segmenting liver tumors from computed tomography (CT) images plays a very important role in computer-aided diagnosis, surgical planning, and treatment monitoring. However, accurate and robust segmentation of the tumors remains a challenging issue, due to low contrast and vague boundaries between the tumors and surrounding tissues as well as the wide variations of the tumors in intensity, shape, and location across patients. In this paper, we developed an effective method for liver tumor segmentation with adaptive region growing and graph cuts. First, initial segmentation results for liver tumors and the regions of interest (ROIs) that contain the tumors are extracted by adaptive region growing with a manual selected seed specified for each tumor region. Then, the ROIs are enhanced by Gaussian fitting based nonlinear mapping according to the intensity distributions of the initially segmented tumor regions. Finally, the enhanced information combined with gradient information is integrated into graph cuts to extract the tumors from the ROIs effectively and accurately. The method is non-sensitive to noise and does not involve a pre-segmentation of liver or a complicated and tedious procedure of training. Results on 3Dircadb dataset demonstrate that the method achieves much better comprehensive performance on liver tumor segmentation compared with many art-of-state methods and has a huge advantage in segmenting the tumors with low contrast, small size, and weak boundaries.

In computer vision, superpixel segmentation has been widely used as a very important preprocessing to reduce the number of image primitives for subsequent image processing tasks. To improve the segmentation accuracy and the robustness to noise, a hierarchical multi-level segmentation framework is developed in this paper. First, original image is initially segmented by a local information based simple liner iterative clustering (LI-SLIC) method. Then, the initial generated superpixels are further segmented hierarchically by LI-SLIC to ensure that all pixels contained within each superpixel belong to a same object. Finally, to eliminate over-segmentation and reduce the number of superpixels, adjacent superpixels belonging to a same object are merged based on the probability distribution similarity. The proposed method does not require setting the seeds or number of the superpixels to be generated in advance, which can segment image into an appropriate number of superpixels without under- or over- segmentation automatically according to its content. Experiments are conducted on two public datasets Berkeley and 3Dircadb, and the results demonstrate that our method is more effective and accurate than many existing superpixel methods and shows a great advantage in dealing with images corrupted by various noises.

Density-peak clustering is used to segment initial slice automatically.The pixel-, patch-based and inter-slice based features are used for segmentation.A novel automatic vessel compensation method is proposed based on border marching.Our method can segment livers with low contrast, varying shapes and intensities.Our method outperforms many existing methods on liver segmentation. Background and ObjectiveIdentifying liver regions from abdominal computed tomography (CT) volumes is an important task for computer-aided liver disease diagnosis and surgical planning. This paper presents a fully automatic method for liver segmentation from CT volumes based on graph cuts and border marching. MethodsAn initial slice is segmented by density peak clustering. Based on pixel- and patch-wise features, an intensity model and a PCA-based regional appearance model are developed to enhance the contrast between liver and background. Then, these models as well as the location constraint estimated iteratively are integrated into graph cuts in order to segment the liver in each slice automatically. Finally, a vessel compensation method based on the border marching is used to increase the segmentation accuracy. ResultsExperiments are conducted on a clinical data set we created and also on the MICCAI2007 Grand Challenge liver data. The results show that the proposed intensity, appearance models, and the location constraint are significantly effective for liver recognition, and the undersegmented vessels can be compensated by the border marching based method. The segmentation performances in terms of VOE, RVD, ASD, RMSD, and MSD as well as the average running time achieved by our method on the SLIVER07 public database are 5.83.2%, -0.14.1%, 1.00.5mm, 2.01.2mm, 21.29.3mm, and 4.7 minutes, respectively, which are superior to those of existing methods. ConclusionsThe proposed method does not require time-consuming training process and statistical model construction, and is capable of dealing with complicated shapes and intensity variations successfully.

Mammalian interphase chromosomes interact with the nuclear lamina (NL) through hundreds of large lamina-associated domains (LADs). We report a method to map NL contacts genome-wide in single human cells. Analysis of nearly 400 maps reveals a core architecture consisting of gene-poor LADs that contact the NL with high cell-to-cell consistency, interspersed by LADs with more variable NL interactions. The variable contacts tend to be cell-type specific and are more sensitive to changes in genome ploidy than the consistent contacts. Single-cell maps indicate that NL contacts involve multivalent interactions over hundreds of kilobases. Moreover, we observe extensive intra-chromosomal coordination of NL contacts, even over tens of megabases. Such coordinated loci exhibit preferential interactions as detected by Hi-C. Finally, the consistency of NL contacts is inversely linked to gene activity in single cells and correlates positively with the heterochromatic histone modification H3K9me3. These results highlight fundamental principles of single-cell chromatin organization., National Institutes of Health (U.S.) (Grant R01 GM114190), National Human Genome Research Institute (U.S.) (Grant R01 HG003143)

CoS-Co(OH)2 heterostructure with conductive polypyrrole (PPy) as charger transfer mediator were rationally designed and embedded onto the g-C3N4 photocatalyst as the dual noble-metal-free cocatalyst for the first time, for improving the transport, separation and utilization efficiency of the photo-generated charge carriers. Notably, CoS, acting as photocatalytic hydrogen production cocatalyst, not only facilitated the utilization of charge carriers, but also accelerated the charge separation owing to its lower flat band potential. Furthermore, Co(OH)2 photocatalytic oxygen production cocatalyst exhibited a synergistic effect with CoS for further improving the charge carriers utilization efficiency. Consequently, g-C3N4-PPy, ternary g-C3N4-PPy-CoS and quaternary g-C3N4-PPy-CoS-Co(OH)2 heterostructures exhibited the photocatalytic hydrogen production activities of 2.49, 23.27 and 46.67 μmol/h, which were 17, 155 and 311-fold in comparison with that of pristine g-C3N4, respectively. This work provided a hopeful insight for the design of high performance cocatalyst for improving the transport, separation and utilization of photo-exited charge carriers.

A major challenge in biology is to understand how complex gene expression patterns are encoded in the genome. While transcriptional enhancers have been studied extensively, few transcriptional silencers have been identified and they remain poorly understood. Here we used a novel strategy to screen hundreds of sequences for tissue-specific silencer activity in whole Drosophila embryos. Strikingly, almost all transcriptional silencers we identified were also active enhancers in other cellular contexts. These elements are bound by more transcription factors than non-silencers. A subset of these silencers form long-range contacts with promoters. Deletion of a silencer caused derepression of its target gene. Our results challenge the common practice of treating enhancers and silencers as separate classes of regulatory elements and suggest the possibility that thousands or more bifunctional CRMs remain to be discovered in Drosophila and 10(4)-10(5) in human.