Research on Multi-Wave Pore Pressure Prediction Method Based on Three Field Velocity Fusion

The optimization of velocity field is the core issue in reservoir seismic pressure prediction. For a long time, the seismic processing velocity analysis method has been used in the establishment of pressure prediction velocity field, which has a long research period and low resolution and restricts the accuracy of seismic pressure prediction;This paper proposed for the first time the use of machine learning algorithms, based on the feasibility analysis of wellbore logging pressure prediction, to integrate the CVI velocity inversion field, velocity sensitive post stack attribute field, and AVO P-wave and S-wave velocity reflectivity to obtain high-precision seismic P and S wave velocities. On this basis, high-resolution formation pore pressure and other parameters prediction based on multi waves is carried out. The pressure prediction accuracy is improved by more than 50% compared to the P-wave resolution of pore pressure prediction using only root mean square velocity. Practice has proven that the research method has certain reference significance for reservoir pore pressure prediction.

Research on Fracture Prediction Method Based on Multi-Source Information Fusion

Machine learning is a good method for predicting fracture by integrating multi-source information. Post-stack seismic attributes are commonly used to predict medium to large fractures, while pre-stack seismic attributes are proven to be more sensitive to small and micro sized fractures through forward modeling. Using machine learning algorithm to fuse information from different scales to predict fracture can greatly improve the accuracy of fracture prediction. On the basis of In-Situ stress prediction, the paper conducted post-stack seismic attribute analysis and pre-stack seismic attribute analysis, further studied on the sensitivity of seismic attributes to fracture and selected sensitive attributes, used the sensitivity log of well-bore fractures as the target log for learning, ultimately obtained a comprehensive body of fracture. Through blind well verification, the prediction results match well with the we1l data and the prediction results is highly consistent with the production data. The results of fracture prediction are reliable, and the research method has certain reference significance for fracture prediction.

A Review of the Status and Development Strategies of Computer Science and Technology Under the Background of Big Data

This article discusses the current status and development strategies of computer science and technology in the context of big data.Firstly,it explains the relationship between big data and computer science and technology,focusing on analyzing the current application status of computer science and technology in big data,including data storage,data processing,and data analysis.Then,it proposes development strategies for big data processing.Computer science and technology play a vital role in big data processing by providing strong technical support.

舌癌组织缺氧微环境中脂联素的表达与调控

目的:脂联素(adiponectin,APN)是一种内源性细胞因子,与多种肿瘤的发生发展密切相关。本研究旨在检测舌癌APN及其受体(AdipoR1和AdipoR2)的组织学表达分布特征,探讨APN在局部组织中的表达是否受到缺氧诱导因子HIF-1α的调控。方法:采用免疫组织化学检测舌癌组织中APN及其受体的表达分布特征;慢病毒包装HIF-1αshRNA载体并转染舌癌细胞构建稳定沉默HIF-1α的细胞系;应用RT-PCR和蛋白质印迹法(Western blot)检测APN及其受体mRNA和蛋白在缺氧条件下的表达变化。结果:在肿瘤发生早期,即当肿瘤体积较小(T1和T2期)或未发生淋巴结转移(N0期)时,肿瘤组织APN及AdipoR1的表达与癌旁正常上皮相比上调(P<0.05,<0.01),AdipoR2的表达无显著改变。将舌癌细胞缺氧后APN及AdipoR1的表达分别上调,但AdipoR2的表达不变。敲低HIF-1α表达后缺氧处理可同时下调APN及AdipoR1表达。结论:舌癌局部缺氧微环境下,APN-Adi poR1信号通路被激活,该过程受到HIF-1α的调控。

A high-quality Actinidia chinensis(kiwifruit)genome

Actinidia chinensis(kiwifruit)is a perennial horticultural crop species of the Actinidiaceae family with high nutritional and economic value.Two versions of the A.chinensis genomes have been previously assembled,based mainly on relatively short reads.Here,we report an improved chromosome-level reference genome of A.chinensis(v3.0),based mainly on PacBio long reads and Hi-C data.The high-quality assembled genome is 653 Mb long,with 0.76%heterozygosity.At least 43%of the genome consists of repetitive sequences,and the most abundant long terminal repeats were further identified and account for 23.38%of our novel genome.It has clear improvements in contiguity,accuracy,and gene annotation over the two previous versions and contains 40,464 annotated protein-coding genes,of which 94.41%are functionally annotated.Moreover,further analyses of genetic collinearity revealed that the kiwifruit genome has undergone two whole-genome duplications:one affecting all Ericales families near the K-T extinction event and a recent genus-specific duplication.The reference genome presented here will be highly useful for further molecular elucidation of diverse traits and for the breeding of this horticultural crop,as well as evolutionary studies with related taxa.

Single Nucleotide Polymorphisms (SNPs) of URAT1 (rs7932775) and ABCG2 (rs3825016) on Chronic Kidney Disease Patients with Hyperuricemia

Background: More and more chronic kidney disease (CKD) patients are accompanied with hyperuricaemia. As is known, hyperuricaemia is an independent hazard of both cardiovascular diseases (CVD) and chronic kidney diseases. We aim at identifying Single Nucleotide Polymorphism (SNP) difference of hURAT1 (rs7932775) and ABCG2 (rs3825016) on CKD patient with hyperuricemia and/or gout. Methods: All forty-two CKD patients were divided into two groups: hyperuricemia, and control group. 24 hours urine sample and serum were prepared for testing biochemistry parameters. The polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method is used to analyze hURAT1 and ABCG2 single nucleotide polymorphisms in different groups. Results: 17 patients have CT SNP of hURAT1 (rs7932775) and 13 patients have CT SNP of ABCG2 (rs3825016) in hyperuricemia group, while only 5 persons and 6 persons have the same mutations in control group respectively. 7 patients have CT SNP of both hURAT1 (rs7932775) and ABCG2 (rs3825016) in hyperuricemia group, while only 2 persons have the same mutations in control group. CT mutation rates of hURAT1 (rs7932775) and ABCG2 (rs3825016) in hyperuricemia group were 60.7% (17/28) and 50% (13/28) respectively, higher than that of control group (35.7% (5/14) and 42.8% (6/14)). What is more, Double SNP mutations in both hURAT1 (rs7932775) and ABCG2 (rs3825016) in hyperuricemia group were 25% (7/28), higher than that of control group (14.2%, 2/14). Conclusion: There are higher mutation rates of CT SNP in hURAT1 (rs7932775) and/or ABCG2 (rs3825016) in hyperuricemia group. We can conclude that hyperuricemia is a high risk factor in progress of CKD, which is necessary to take measures of decreasing serum uric acid to delay CKD progress.

Spectrum and energy efficient multi-antenna spectrum sensing for green UAV communication

Unmanned Aerial Vehicle(UAV)communication is a promising technology that provides swift and flexible ondemand wireless connectivity for devices without infrastructure support.With recent developments in UAVs,spectrum and energy efficient green UAV communication has become crucial.To deal with this issue,Spectrum Sharing Policy(SSP)is introduced to support green UAV communication.Spectrum sensing in SSP must be carefully formulated to control interference to the primary users and ground communications.In this paper,we propose spectrum sensing for opportunistic spectrum access in green UAV communication to improve the spectrum utilization efficiency.Different from most existing works,we focus on the problem of spectrum sensing of randomly arriving primary signals in the presence of non-Gaussian noise/interference.We propose a novel and improved p-norm-based spectrum sensing scheme to improve the spectrum utilization efficiency in green UAV communication.Firstly,we construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson process.Then,we analyze and derive the approximate analytical expressions of the false-alarm and detection probabilities by utilizing the central limit theorem.Simulation results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and arrive randomly during spectrum sensing in the green UAV communication.

New Blind Recognition Method of SCLD and OFDM in Alpha-Stable Noise

This paper deals with modulation classification under the alpha-stable noise condition. Our goal is to discriminate orthogonal frequency division multiplexing (OFDM) modulation type from single carrier linear digital (SCLD) modulations in this scenario. Based on the new results concerning the generalized cyclostationarity of these signals in alpha-stable noise which are presented in this paper, we construct new modulation classification features without any priori information of carrier frequency and timing offset of the received signals, and use support vector machine (SVM) as classifier to discriminate OFDM from SCLD. Simulation results show that the recognition accuracy of the proposed algorithm can be up to 95% when the mix signal to noise ratio (MSNR) is up to ?1 dB.

A New Method to Identify the Maximum Time Interval between Individual Events in Compound Rainstorm and Heatwave Events

Growing evidence indicates that extreme heat and rain may occur in succession within short time periods and cause greater impacts than individual events separated in time and space.Therefore,many studies have examined the impacts of compound hazard events on the social-ecological system at various scales.The definition of compound events is fundamental for such research.However,there are no existing studies that support the determination of time interval between individual events of a compound rainstorm and heatwave(CRH)event,which consists of two or more potentially qualifying component heatwave and rainstorm events.To address the deficiency in defining what individual events can constitute a CRH event,this study proposed a novel method to determine the maximum time interval for CRH events through the change in CRH event frequency with increasing time interval between individual events,using southern China as a case study.The results show that the threshold identified by the proposed method is reasonable.For more than 90%of the meteorological stations,the frequency of CRH events has reached a maximum when the time interval is less than or equal to the threshold.This study can aid in time interval selection,which is an important step for subsequent study of CRH events.

Relationships Between Evacuation Population Size, Earthquake Emergency Shelter Capacity, and Evacuation Time

Determining the location of earthquake emergency shelters and the allocation of affected population to them are key issues that face shelter planning and emergency management. To solve this emergency shelter location–allocation problem, evacuation time and the construction cost of shelters—both influenced by the evacuation population size and its spatial distribution—are two important considerations. In this article, a mathematical model with two objectives—to minimize total weighted evacuation time(TWET) and total shelter area(TSA)—is allied with a modified particle swarm optimization algorithm to address the problem. The relationships between evacuation population size, evacuation time, and total shelter area are examined using Jinzhan Town in Chaoyang District of Beijing, China, as a case study. The results show that TWET has a power function relationship with TSA under different population size scenarios, and a linear function applies between evacuation population and TWET under different TSAs. The joint relationships of TSA, TWET, and population size show that TWET increases with population increase and TSA decrease, and compared with TSA, population influences TWET more strongly. Given a reliable projection of population change and spatial planning of a study area, this method can be useful for government decision making on the location of earthquake emergency shelters and on the allocation of evacuees to those shelters.

Energetic materials based on poly furazan and furoxan structures

Furazan and furoxan represent fascinating explosophoric units with intriguing structures and unique properties.Compared with other nitrogen-rich heterocycles,most poly furazan and furoxan-based heterocycles demonstrate superior energetic performances due to the higher enthalpy of formation and density levels.A large variety of advanced energetic materials have been achieved based on the combination of furazan and furoxan moieties with different kinds of linkers and this review provides an overview of the development of energetic poly furazan and furoxan structures during the past decades,with their physical properties and detonation characteristics summarized and compa red with traditional energetic materials.Various synthetic strategies towards these compact energetic structures are highlighted by covering the most important cyclization methods for construction of the hetercyclic scaffolds and the following modifications such as nitrations and oxidations.Given the synthetic availabilities and outstanding properties,energetic materials based on poly furazan and furoxan structures are undoubtedly listed as a promising candidate for the development of new-generation explosives,propellants and pyrotechnics.

Thermal studies of novel molecular perovskite energetic material(C_(6)H_(14)N_(2))[NH_(4)(ClO_(4))_(3)]

(C6H(14)N2)[NH4(ClO4)3] is a newly developed porous hybrid inorganic-organic framework material with easy access and excellent detonation performances,however,its thermal properties is still unclear and severely hampered further applications.In this study,thermal behaviors and non-isothermal decomposition reaction kinetics of(C6H(14)N2)[NH4(ClO4)3] were investigated systematically by the combination of differential scanning calorimetry(DSC) and simultaneous thermal analysis methods.In-situ FTIR spectroscopy technology was applied for investigation of the structure changes of(C6H(14)N2) NH4(ClO4)3]and some selected referents for better understanding of interactions between different components during the heating process.Experiment results indicated that the novel molecular perovskite structure renders(C6H(14)N2)[NH4(ClO4)3] better thermal stability than most of currently used energetic materials.Underhigh temperature s,the stability of the cage skeleton constructed by NH4^+and ClO4^-ions determined the decomposition process rather than organic moiety confined in the skeleton.The simple synthetic method,good detonation performances and excellent thermal properties make(C6H(14)N2)[NH4(ClO4)3] an ideal candidate for the preparation of advanced explosives and propellants.