Study on Failure Length of Cementing Interface in Horizontal Wells During Fracturing

The cementing interface of oil and gas wells is often the weak link between oil and gas turbulence. Due to the low cementation strength at the fracturing interface, the two interfaces have been crushed to form turbulence channels before the target layer is opened during fracturing. If the closure is not good, there will be inter-layer channeling. Therefore, the pressure bearing capacity of the fracturing interface is an important indicator for designing the fracturing construction parameters. The pressure capacity of the two interfaces during the fracturing process is the key to evaluating the success of the fracturing construction. This paper establishes the calculation model for the stress distribution of horizontal wells in horizontal wells under the effect of non-uniform stress. At the same time, the influence of the pressure change in the wellbore during the fracturing process on the stress distribution in the borehole wall was analyzed. The calculation model of the interfacial stress distribution in the horizontal well during the fracturing process was established, and the debonding pressure and debonding length of the two interfaces under different cementing strengths were calculated. After the establishment of the horizontal well fracturing two interface crack propagation mechanics model, calculate the pressure required for cracks along the two interfaces to expand at different failure lengths

Climate change impact on China food security in 2050

Climate change is now affecting global agriculture and food production worldwide. Nonetheless the direct link between climate change and food security at the national scale is poorly understood. Here we simulated the effect of climate change on food security in China using the CERES crop models and the IPCC SRES A2 and B2 scenarios including CO2 fertilization effect. Models took into account population size, urbanization rate, cropland area, cropping intensity and technology development. Our results predict that food crop yield will increase +3-11 % under A2 scenario and +4 % under B2 scenario during 2030-2050, despite disparities among individual crops. As a consequence China will be able to achieve a production of 572 and 615 MT in 2030, then 635 and 646 MT in 2050 under A2 and B2 scenarios, respectively. In 2030 the food security index (FSI) will drop from +24 % in 2009 to -4.5 % and +10.2 % under A2 and B2 scenarios, respectively. In 2050, however, the FSI is predicted to increase to +7.1 % and +20.0 % under A2 and B2 scenarios, respectively, but this increase will be achieved only with the projected decrease of Chinese population. We conclude that 1) the proposed food security index is a simple yet powerful tool for food security analysis; (2) yield growth rate is a much better indicator of food security than yield per se; and (3) climate change only has a moderate positive effect on food security as compared to other factors such as cropland area, population growth, socio-economic pathway and technology development. Relevant policy options and research topics are suggested accordingly

Graph Sampling-based Meta-Learning for Molecular Property Prediction

Molecular property is usually observed with a limited number of samples, and researchers have considered property prediction as a few-shot problem. One important fact that has been ignored by prior works is that each molecule can be recorded with several different properties simultaneously. To effectively utilize many-to-many correlations of molecules and properties, we propose a Graph Sampling-based Meta-learning (GS-Meta) framework for few-shot molecular property prediction. First, we construct a Molecule-Property relation Graph (MPG): molecule and properties are nodes, while property labels decide edges. Then, to utilize the topological information of MPG, we reformulate an episode in meta-learning as a subgraph of the MPG, containing a target property node, molecule nodes, and auxiliary property nodes. Third, as episodes in the form of subgraphs are no longer independent of each other, we propose to schedule the subgraph sampling process with a contrastive loss function, which considers the consistency and discrimination of subgraphs. Extensive experiments on 5 commonly-used benchmarks show GS-Meta consistently outperforms state-of-the-art methods by 5.71%-6.93% in ROC-AUC and verify the effectiveness of each proposed module. Our code is available at https://github.com/HICAI-ZJU/GS-Meta.Comment: Accepted by IJCAI 202

IMJENSE: Scan-specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI

Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging (MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an inverse problem relating the sparsely sampled k-space measurements to the desired MRI image. Despite the success of many existing reconstruction algorithms, it remains a challenge to reliably reconstruct a high-quality image from highly reduced k-space measurements. Recently, implicit neural representation has emerged as a powerful paradigm to exploit the internal information and the physics of partially acquired data to generate the desired object. In this study, we introduced IMJENSE, a scan-specific implicit neural representation-based method for improving parallel MRI reconstruction. Specifically, the underlying MRI image and coil sensitivities were modeled as continuous functions of spatial coordinates, parameterized by neural networks and polynomials, respectively. The weights in the networks and coefficients in the polynomials were simultaneously learned directly from sparsely acquired k-space measurements, without fully sampled ground truth data for training. Benefiting from the powerful continuous representation and joint estimation of the MRI image and coil sensitivities, IMJENSE outperforms conventional image or k-space domain reconstruction algorithms. With extremely limited calibration data, IMJENSE is more stable than supervised calibrationless and calibration-based deep-learning methods. Results show that IMJENSE robustly reconstructs the images acquired at 5$\mathbf{\times}$ and 6$\mathbf{\times}$ accelerations with only 4 or 8 calibration lines in 2D Cartesian acquisitions, corresponding to 22.0% and 19.5% undersampling rates. The high-quality results and scanning specificity make the proposed method hold the potential for further accelerating the data acquisition of parallel MRI

Association between Non-High-Density-Lipoprotein-Cholesterol Levels and the Prevalence of Asymptomatic Intracranial Arterial Stenosis

Objective: The aim of this study was to assess the association between non-high-density-lipoprotein-cholesterol (non-HDL-C) and the prevalence of asymptomatic intracranial arterial stenosis (ICAS). Methods and Results: The Asymptomatic Polyvascular Abnormalities Community (APAC) study is a prospective cohort study based on the Kailuan district (China) population. A total of 5351 eligible subjects, aged ≥40, and without history of stroke or myocardial infarction, were enrolled in this study. Transcranial Doppler Ultrasonography (TCD) was performed on all enrolled subjects for the evaluation of ICAS presence. Out of 5351 patients, 698 subjects showed evidence of ICAS (prevalence of 13.04%). Multivariate analysis showed that non-HDL-C is an independent indicator for the presence of ICAS (OR = 1.15, 95%CI: 1.08 – 1.23), but with a gender difference (P for interaction<0.01): in men, non-HDL-C is an independent indicator for ICAS (multivariate-adjusted OR = 1.28, 95%CI: 1.18–1.39), but not in women (multivariate-adjusted OR = 1.03, 95%CI: 0.93–1.14). Subjects were divided into five subgroups based non-HDL-C levels and these levels correlated linearly with the prevalence of ICAS (P for trend <0.01). Compared with the first quintile, multivariate-adjusted OR (95%CI) of the second, third, fourth and fifth quintiles were: 1.05 (0.71–1.56), 1.33 (0.91–1.95), 1.83 (1.27–2.63), 2.48 (1.72–3.57), respectively. Conclusion: Non-HDL-C is an independent predictor of ICAS prevalence in men but not in women, suggesting that non-HDL-C levels could be used as a surveillance factor in the primary prevention of ischemic stroke, especially in men

Direct Determination of Electron-Phonon Coupling Matrix Element in a Correlated System

High-resolution electron energy loss spectroscopy measurements have been carried out on an optimally doped cuprate Bi2Sr2CaCu2O8+{\delta}. The momentum-dependent linewidth and the dispersion of an A1 optical phonon are obtained. Based on these data as well as the detailed knowledge of the electronic structure from angle-resolved photoemission spectroscopy, we develop a scheme to determine the full structure of electron-phonon coupling for a specific phonon mode, thus providing a general method for directly resolving the EPC matrix element in systems with anisotropic electronic structures

Negative Propagation Effects in Two-Dimensional Silicon Photonic Crystals

We demonstrated negative refraction effects of light propagating in two-dimensional square and hexagonal-lattice silicon photonic crystals (PhCs). The plane wave expansion method was used to solve the complex eigenvalue problems, as well as to find dispersion curves and equal-frequency contour (EFC). The finite-difference time-domain (FDTD) method was used to simulate and visualize electromagnetic wave propagation and scattering in the PhCs. Theoretical analyses and numerical simulations are presented. Two different kinds of negative refractions, namely, all-angle negative refraction (AANR) without a negative index and negative refraction with effective negative index, have been verified and compared

Simultaneous extraction and purification of alkaloids from Sophora flavescens Ait. by microwave-assisted aqueous two-phase extraction with ethanol/ammonia sulfate system

A rapid and effective method of integrating extraction and purification for alkaloids from Sophora flavescens Ait. was developed by microwave-assisted aqueous two-phase extraction (MAATPE) based on the high efficiency of microwave-assisted extraction (MAE) and the demixing effect of aqueous two-phase extraction (ATPE). The aqueous two-phase system (ATPS), ethanol/ammonia sulfate was chosen from seven combinations of ethanol/salt systems, and its extraction properties were investigated in detail. Key factors, namely, the compositions of ATPS, solvent-to-materials ratio, and the extraction temperature were selected for optimization of the experimental conditions using response surface methodology (RSM) on the basis of the results of the single-factor experiment. The final optimized conditions were, the compositions of ATPS: ethanol 28% (w/w) and (NH4)2SO4 18% (w/w), solvent-to-material ratio 60:1, temperature 90 C, extraction time 5 min, and microwave power 780 W. MAATPE was superior to MAE, the latter using a single solvent, not only in extraction yield but also in impurity content. Moreover, compared with the combination of MAE and ATPE in the two-step mode, MAATP demonstrated fewer impurities, a better yield (63.78 ± 0.45 mg/g) and a higher recovery (92.09 ± 0.14%) in the extraction and purification of alkaloids. A continuous multiphase-extraction model of MAATPE was proposed to explicate the extraction mechanism. MAATPE revealed that the interaction between microwave and ATPS cannot only cause plant cell rupture but also accelerate demixing, improving mass-transfer from solid–liquid extraction to liquid– liquid purification. MAATPE simplified procedures also contributed to the lower loss occurrence, better extraction efficiency, and reduced impurity to target constituents.The Science and Technology Project of Guangzhou (No. 2008Z1-E301) and Faculty Development fund Project of Guangdong Pharmaceutical University (No. 52104109