Fractal analysis of the effect of particle aggregation distribution on thermal conductivity of nanofluids

This project was supported by the National Natural Science Foundation of China (No. 41572116), the Fundamental Research Funds for the Central Universities, China University of Geosciences, Wuhan) (No. CUG160602).Peer reviewedPostprin

Ion Competition in Condensed DNA Arrays in the Attractive Regime

AbstractPhysical origin of DNA condensation by multivalent cations remains unsettled. Here, we report quantitative studies of how one DNA-condensing ion (Cobalt3+ Hexammine, or Co3+Hex) and one nonDNA-condensing ion (Mg2+) compete within the interstitial space in spontaneously condensed DNA arrays. As the ion concentrations in the bath solution are systematically varied, the ion contents and DNA-DNA spacings of the DNA arrays are determined by atomic emission spectroscopy and x-ray diffraction, respectively. To gain quantitative insights, we first compare the experimentally determined ion contents with predictions from exact numerical calculations based on nonlinear Poisson-Boltzmann equations. Such calculations are shown to significantly underestimate the number of Co3+Hex ions, consistent with the deficiencies of nonlinear Poisson-Boltzmann approaches in describing multivalent cations. Upon increasing the concentration of Mg2+, the Co3+Hex-condensed DNA array expands and eventually redissolves as a result of ion competition weakening DNA-DNA attraction. Although the DNA-DNA spacing depends on both Mg2+ and Co3+Hex concentrations in the bath solution, it is observed that the spacing is largely determined by a single parameter of the DNA array, the fraction of DNA charges neutralized by Co3+Hex. It is also observed that only ∼20% DNA charge neutralization by Co3+Hex is necessary for spontaneous DNA condensation. We then show that the bath ion conditions can be reduced to one variable with a simplistic ion binding model, which is able to describe the variations of both ion contents and DNA-DNA spacings reasonably well. Finally, we discuss the implications on the nature of interstitial ions and cation-mediated DNA-DNA interactions

Remnant cholesterol is associated with cardiovascular mortality

Background: Genetic, observational, and clinical intervention studies indicate that circulating levels of remnant cholesterol (RC) are associated with cardiovascular diseases. However, the predictive value of RC for cardiovascular mortality in the general population remains unclear. Methods: Our study population comprised 19,650 adults in the United States from the National Health and Nutrition Examination Survey (NHANES) (1999–2014). RC was calculated from non-high-density lipoprotein cholesterol (non-HDL-C) minus low-density lipoprotein cholesterol (LDL-C) determined by the Sampson formula. Multivariate Cox regression, restricted cubic spline analysis, and subgroup analysis were applied to explore the relationship of RC with cardiovascular mortality. Results: The mean age of the study cohort was 46.4 ± 19.2 years, and 48.7% of participants were male. During a median follow-up of 93 months, 382 (1.9%) cardiovascular deaths occurred. In a fully adjusted Cox regression model, log RC was significantly associated with cardiovascular mortality [hazard ratio (HR) 2.82; 95% confidence interval (CI) 1.17–6.81]. The restricted cubic spline curve indicated that log RC had a linear association with cardiovascular mortality (p for non-linearity = 0.899). People with higher LDL-C (≥130 mg/dL), higher RC [≥25.7/23.7 mg/dL in males/females corresponding to the LDL-C clinical cutoff point (130 mg/dL)] and abnormal HDL-C (<40/50 mg/dL in males/females) levels had a higher risk of cardiovascular mortality (HR 2.18; 95% CI 1.13–4.21 in males and HR 2.19; 95% CI 1.24–3.88 in females) than the reference group (lower LDL-C, lower RC and normal HDL-C levels). Conclusions: Elevated RC levels were associated with cardiovascular mortality independent of traditional risk factors

New Insights into Crust and upper Mantle Structure in Guangdong Province, China and Its Geothermal Implications

Southeast Asia contains significant natural geothermal resources. However, the mechanism for generating geothermal anomalies by the crust–mantle structure still needs to define. In this study, we focused on Guangdong Province, China. We conducted three magnetotelluric profiles to interpret the crust and upper mantle structure beneath the Guangdong Province and its geothermal implications. Based on data analysis results, a two-dimension inversion was conducted on the dataset. The inversion model revealed that there is a presence of upwelling channels, and some channels are connected with shallow crustal fault zone; the thickness of crust and lithosphere in Guangdong Province is relatively thin. Such a special crust and upper mantle structure form high surface heat flow. Merged with previous research, our results imply that massive Late Mesozoic granites, which contain high radioactive heat generating elements, are distributed on the surface and underground of Guangdong Province. Based on the correlation between high radioactive Late Mesozoic granites, crust-upper mantle structure, surface heat flow, and locations of natural hot springs, we established a geothermal conceptual model to visualize the origin of a current geophysical and geothermal anomaly in Guangdong Province

Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

Intelligent seamline selection for image mosaicking is an area of active research in the fields of massive data processing, computer vision, photogrammetry and remote sensing. In mosaicking applications for digital orthophoto maps (DOMs), the visual transition in mosaics is mainly caused by differences in positioning accuracy, image tone and relief displacement of high ground objects between overlapping DOMs. Among these three factors, relief displacement, which prevents the seamless mosaicking of images, is relatively more difficult to address. To minimize visual discontinuities, many optimization algorithms have been studied for the automatic selection of seamlines to avoid high ground objects. Thus, a new automatic seamline selection algorithm using a digital surface model (DSM) is proposed. The main idea of this algorithm is to guide a seamline toward a low area on the basis of the elevation information in a DSM. Given that the elevation of a DSM is not completely synchronous with a DOM, a new model, called the orthoimage elevation synchronous model (OESM), is derived and introduced. OESM can accurately reflect the elevation information for each DOM unit. Through the morphological processing of the OESM data in the overlapping area, an initial path network is obtained for seamline selection. Subsequently, a cost function is defined on the basis of several measurements, and Dijkstra’s algorithm is adopted to determine the least-cost path from the initial network. Finally, the proposed algorithm is employed for automatic seamline network construction; the effective mosaic polygon of each image is determined, and a seamless mosaic is generated. The experiments with three different datasets indicate that the proposed method meets the requirements for seamline network construction. In comparative trials, the generated seamlines pass through fewer ground objects with low time consumption

Sedimentary Setting and Ore-Forming Model in the Songtao Manganese Deposit, Southwestern China: Evidence from Audio-Frequency Magnetotelluric and Gravity Data

The break-up of the supercontinent Rodinia in the late Neoproterozoic led to the formation of the Nanhua rift basin within the South China Block. The Datangpo-type manganese deposit, which developed in the Nanhua rift basin, is one of the most important types of manganese deposits in South China. Although it is widely accepted that deep sedimentary structures significantly affect the manganese ore system, the relationship between the manganese deposits in South China and the Nanhua rifting process is still unclear. The origin of the manganese ore layer remains controversial. In this paper, we integrated the audio-frequency magnetotelluric (AMT) data, gravity data, and comprehensive geological and borehole data analysis to characterize the structure of the Datangpo-type manganese deposit in Songtao, Guizhou Province. The resistivity and density models produced an inclined layered structure, which correlated well with the coeval sediment strata of the Nanhua rift basin. A high-resistivity cap was observed from the surface to a depth of 800 m, corresponding to the Cambrian Loushanguan (ϵ3−4ls) and Palang dolomite formation (ϵ2p), which has helped the storage of the manganese ore. The most significant low-resistivity anomaly (25–40 Ω·m) resides at a depth of 1400 m in the Nantuo (Nh3n) gravel sandstone and Datangpo (Nh2d) silty and carbonaceous shale, corresponding to the ore-forming layer. This distinct low-resistivity layer was possibly produced by aqueous fluids and pyrite in the syn-sedimentary fault and alteration zone. The accumulations of sulfide minerals in the rock samples suggest a possible anoxic-euxinic deposition environment during the manganese mineralization and precipitation. The fault revealed in the resistivity models is perhaps a previous fault zone produced by extension in the Nanhua rifting process, which provided migration and upwelling channels for ore-forming minerals. Based on our resistivity models, density models, and geological survey, the manganese ore-forming model was derived, which can help to provide geophysical evidence for the origin of the Datangpo-type manganese deposit

Identifying Network Biomarkers in Early Diagnosis of Hepatocellular Carcinoma via miRNA–Gene Interaction Network Analysis

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer at the histological level. Despite the emergence of new biological technology, advanced-stage HCC remains largely incurable. The prediction of a cancer biomarker is a key problem for targeted therapy in the disease. Methods: We performed a miRNA–gene integrated analysis to identify differentially expressed miRNAs (DEMs) and genes (DEGs) of HCC. The DEM–DEG interaction network was constructed and analyzed. Gene ontology enrichment and survival analyses were also performed in this study. Results: By the analysis of healthy and tumor samples, we found that 94 DEGs and 25 DEMs were significantly differentially expressed in different datasets. Gene ontology enrichment analysis showed that these 94 DEGs were significantly enriched in the term “Liver” with a statistical p-value of 1.71 × 10−26. Function enrichment analysis indicated that these genes were significantly overrepresented in the term “monocarboxylic acid metabolic process” with a p-value = 2.94 × 10−18. Two sets (fourteen genes and five miRNAs) were screened by a miRNA–gene integrated analysis of their interaction network. The statistical analysis of these molecules showed that five genes (CLEC4G, GLS2, H2AFZ, STMN1, TUBA1B) and two miRNAs (hsa-miR-326 and has-miR-331-5p) have significant effects on the survival prognosis of patients. Conclusion: We believe that our study could provide critical clinical biomarkers for the targeted therapy of HCC

Multi-scale and shape constrained localized region-based active contour segmentation of uterine fibroid ultrasound images in HIFU therapy.

To overcome the severe intensity inhomogeneity and blurry boundaries in HIFU (High Intensity Focused Ultrasound) ultrasound images, an accurate and efficient multi-scale and shape constrained localized region-based active contour model (MSLCV), was developed to accurately and efficiently segment the target region in HIFU ultrasound images of uterine fibroids.We incorporated a new shape constraint into the localized region-based active contour, which constrained the active contour to obtain the desired, accurate segmentation, avoiding boundary leakage and excessive contraction. Localized region-based active contour modeling is suitable for ultrasound images, but it still cannot acquire satisfactory segmentation for HIFU ultrasound images of uterine fibroids. We improved the localized region-based active contour model by incorporating a shape constraint into region-based level set framework to increase segmentation accuracy. Some improvement measures were proposed to overcome the sensitivity of initialization, and a multi-scale segmentation method was proposed to improve segmentation efficiency. We also designed an adaptive localizing radius size selection function to acquire better segmentation results.Experimental results demonstrated that the MSLCV model was significantly more accurate and efficient than conventional methods. The MSLCV model has been quantitatively validated via experiments, obtaining an average of 0.94 for the DSC (Dice similarity coefficient) and 25.16 for the MSSD (mean sum of square distance). Moreover, by using the multi-scale segmentation method, the MSLCV model's average segmentation time was decreased to approximately 1/8 that of the localized region-based active contour model (the LCV model).An accurate and efficient multi-scale and shape constrained localized region-based active contour model was designed for the semi-automatic segmentation of uterine fibroid ultrasound (UFUS) images in HIFU therapy. Compared with other methods, it provided more accurate and more efficient segmentation results that are very close to those obtained from manual segmentation by a specialist