Simulation of immiscible water-alternating-CO2 flooding in the Liuhua Oilfield Offshore Guangdong, China

In this paper, the immiscible water-alternating-CO2 flooding process at the LH11-1 oilfield, offshore Guangdong Province, was firstly evaluated using full-field reservoir simulation models. Based on a 3D geological model and oil production history, 16 scenarios of water-alternating-CO2 injection operations with different water alternating gas (WAG) ratios and slug sizes, as well as continuous CO2 injection (Con-CO2) and primary depletion production (No-CO2) scenarios, have been simulated spanning 20 years. The results represent a significant improvement in oil recovery by CO2 WAG over both Con-CO2 and No-CO2 scenarios. The WAG ratio and slug size of water affect the efficiency of oil recovery and CO2 injection. The optimum operations are those with WAG ratios lower than 1:2, which have the higher ultimate oil recovery factor of 24%. Although WAG reduced the CO2 injection volume, the CO2 storage efficiency is still high, more than 84% of the injected CO2 was sequestered in the reservoir. Results indicate that the immiscible water-alternating-CO2 processes can be optimized to improve significantly the performance of pressure maintenance and oil recovery in offshore reef heavy-oil reservoirs significantly. The simulation results suggest that the LH11-1 field is a good candidate site for immiscible CO2 enhanced oil recovery and storage for the Guangdong carbon capture, utilization and storage (GDCCUS) project

The role of 245 phase in alkaline iron selenide superconductors revealed by high pressure studies

Here we show that a pressure of about 8 GPa suppresses both the vacancy order and the insulating phase, and a further increase of the pressure to about 18 GPa induces a second transition or crossover. No superconductivity has been found in compressed insulating 245 phase. The metallic phase in the intermediate pressure range has a distinct behavior in the transport property, which is also observed in the superconducting sample. We interpret this intermediate metal as an orbital selective Mott phase (OSMP). Our results suggest that the OSMP provides the physical pathway connecting the insulating and superconducting phases of these iron selenide materials.Comment: 32 pages, 4 figure

3D seismic simulation analysis of the Longtoushan Town Basin during the 2014 Ludian earthquake, Yunnan province

On 3 August 2014, a magnitude Ms 6.5 earthquake struck Ludian County, Zhaotong City, Yunnan Province, causing grave losses of life and property in the Longtoushan Town Basin near the fault. In this study, a three-dimensional model of the Longtoushan Town Basin and the velocity structure of the surrounding area, and the Spectral Elements in Elastic Dynamics code, which combines the discontinuous Galerkin technique and the spectral element method (SEM) are used to simulate and study the entire seismic wave propagation process. The results show that due to the variations in the basin geometry and the impedance ratio of the media inside and outside the basin, the seismic waves incident on the basin edge are refracted and diffracted, further prolonging the ground motion holding time within the basin. In the bedrock outside the basin, the velocity peaks are higher at higher elevations; viceversa within the basin, the locally depressed basement produces an obvious amplification effect. The amplitude of the ground motion is not the greatest in the thickest sedimentary layers in the basin, and it is closely related to the degree of undulation at the base of the sedimentary layers, the overburden thickness, and the basin geometry. The peak ground accelerations (PGAs) of approximately 8 m/s2 in the east–west (E–W) direction and 3 m/s2 in the north–south (N–S) direction are influenced by the rupture directivity effect (the ruptured surface is the Baogunao–Xiaohe fault that is oriented in the N–W direction). The peak ground velocity with a sedimentary model is 2.6 and 1.6 times that of the non-sedimentary model in the E–W and N–S directions, respectively. The maximum amplification factor for PGA in the E–W direction is 2.8 and that in the N–S direction is approximately 2.3. The results are in agreement with the actual observed seismic station data in terms of the waveforms and peaks, and the intensity distribution map matches the actual damage distribution. This proves the accuracy and rationality of the method used in this study. The results are useful for the seismic zoning of cities, and they can help engineers predict ground motions for future large earthquakes

Genomic data for 78 chickens from 14 populations

Background: Since the domestication of the red jungle fowls (Gallus gallus; dating back to~10 000 B.P.) in Asia, domestic chickens (Gallus gallus domesticus) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production, and skin color. Population genomic variations through diversifying selection have not been fully investigated. Findings: The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of five wild red jungle fowls and eight Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ~21.30 gigabases (Gb) of high-quality data from each individual to the reference chicken genome, we identified ~6.44 million (M) single nucleotide polymorphisms (SNPs) for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. Conclusions: The current data is important for population genetics and further studies in chickens and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chickens.Peer reviewedAnimal Scienc

Study on the influence of grinding disc motion on the forming of silicon nitride ceramic balls

In order to improve the processing accuracy of silicon nitride ceramic balls and to investigate the mechanism of forming ceramic balls by flexible support grinding method, a new cone-type flexible support grinding method with controlled deflection motion of grinding disc is proposed. Based on the new grinding method, a simulation model is established to deeply analyze the influence of the deflection motion of the grinding disc on the grinding trajectory and force state of the silicon nitride ceramic balls. Orthogonal experiments were conducted on a new cone-type flexible support grinding platform built to further analyze the effect of grinding disc motion characteristics on ball formation. Simulation and experimental results show that under the flexible support grinding method, As the increases of grinding disc deflection angle, the standard deviation of ball trajectory uniformity decreased from 43.58 to 35.49, the maximum contact force increased to 4 times the initial value, the average ball diameter variation increased from 1.466 μm to 2.382 μm, and the batch diameter variation increased from 4.98 μm to 10.27 μm. The lower grinding disc deflection motion is beneficial to optimize the grinding trajectory, but increases the unevenness of the ball force, which is not conducive to improving the average ball diameter variation and batch diameter variation of silicon nitride ceramic balls. In the actual process, the angle of deflection of the grinding disc must be controlled to within 0.02°

A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model

National Basic Research Program of China [2010CB945004]; National Natural Science Foundation of China [30772546]Identification of novel cancer genes for molecular therapy and diagnosis is a current focus of breast cancer research. Although a few small gene sets were identified as prognosis classifiers, more powerful models are still needed for the definition of effective gene sets for the diagnosis and treatment guidance in breast cancer. In the present study, we have developed a novel statistical approach for systematic analysis of intrinsic correlations of gene expression between development and tumorigenesis in mammary gland. Based on this analysis, we constructed a predictive model for prognosis in breast cancer that may be useful for therapy decisions. We first defined developmentally associated genes from a mouse mammary gland epithelial gene expression database. Then, we found that the cancer modulated genes were enriched in this developmentally associated genes list. Furthermore, the developmentally associated genes had a specific expression profile, which associated with the molecular characteristics and histological grade of the tumor. These result suggested that the processes of mammary gland development and tumorigenesis share gene regulatory mechanisms. Then, the list of regulatory genes both on the developmental and tumorigenesis process was defined an 835-member prognosis classifier, which showed an exciting ability to predict clinical outcome of three groups of breast cancer patients (the predictive accuracy 64 similar to 72%) with a robust prognosis prediction (hazard ratio 3.3 similar to 3.8, higher than that of other clinical risk factors (around 2.0-2.8)). In conclusion, our results identified the conserved molecular mechanisms between mammary gland development and neoplasia, and provided a unique potential model for mining unknown cancer genes and predicting the clinical status of breast tumors. These findings also suggested that developmental roles of genes may be important criteria for selecting genes for prognosis prediction in breast cancer

Polyethylene Microplastic Particles Alter the Nature, Bacterial Community and Metabolite Profile of Reed Rhizosphere Soils

With the wide use of polyethylene film, the influence of polyethylene microplastic particles produced by its weathering on the rhizosphere soil microenvironment has attracted more and more attention from scientific research circles. In this study, the effects of low (0.2% w/w), medium (1% w/w), and high (2% w/w) doses of polyethylene particles and the combined reed biomass (2% w/w) on soil environmental factors and bacterial communities and metabolites in the reed rhizosphere were evaluated by a 90-day pot microscopic simulation system. The shape and surface microstructure of polyethylene particles in each treatment group changed obviously. A high (2% w/w) dose of microplastics significantly increased the TKN, TOC, and TP in reed root soil. The addition of the biomass significantly improved the activities of urease and sucrase in the soil. The α diversity of bacteria was not significantly affected by the addition of LDPE microplastics and biomass, but the β diversity of the bacterial community and the relative abundance of the Candidatus_Roku Bacteria, Chloroflexi, Unclassified_Blastocatella_Genus were significantly changed by the addition of middle (1% w/w) and high (2% w/w) doses of microplastics. In addition, the spectrum analysis of the soil metabolites showed that the abundance of soil metabolites was changed in each treatment group, and the differential metabolites were significantly up-regulated or down-regulated. Our findings provide a scientific reference to elucidate the impact of LDPE microplastic particles on the inter-rooted soil microenvironment and improve our understanding of the potential risks of microplastics in soil ecosystems

A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model

<div><p>Identification of novel cancer genes for molecular therapy and diagnosis is a current focus of breast cancer research. Although a few small gene sets were identified as prognosis classifiers, more powerful models are still needed for the definition of effective gene sets for the diagnosis and treatment guidance in breast cancer. In the present study, we have developed a novel statistical approach for systematic analysis of intrinsic correlations of gene expression between development and tumorigenesis in mammary gland. Based on this analysis, we constructed a predictive model for prognosis in breast cancer that may be useful for therapy decisions. We first defined developmentally associated genes from a mouse mammary gland epithelial gene expression database. Then, we found that the cancer modulated genes were enriched in this developmentally associated genes list. Furthermore, the developmentally associated genes had a specific expression profile, which associated with the molecular characteristics and histological grade of the tumor. These result suggested that the processes of mammary gland development and tumorigenesis share gene regulatory mechanisms. Then, the list of regulatory genes both on the developmental and tumorigenesis process was defined an 835-member prognosis classifier, which showed an exciting ability to predict clinical outcome of three groups of breast cancer patients (the predictive accuracy 64∼72%) with a robust prognosis prediction (hazard ratio 3.3∼3.8, higher than that of other clinical risk factors (around 2.0–2.8)). In conclusion, our results identified the conserved molecular mechanisms between mammary gland development and neoplasia, and provided a unique potential model for mining unknown cancer genes and predicting the clinical status of breast tumors. These findings also suggested that developmental roles of genes may be important criteria for selecting genes for prognosis prediction in breast cancer.</p> </div