电商平台产品共同购买网络的影响因素研究

共同购买网络的推荐系统应用越加广泛，仅基于网络内生结构变量研究其共同购买链接的经济意义已有局限，故加入网络口碑这一外生变量，进行更全面的分析。采用了社会网络方法中指数随机图模型进行建模，主要围绕产品销售量、产品入度、差评率和评论数4个方面因素，探究其对共同购买网络中共同购买链接形成的影响。结果显示，销售量、产品入度和评论数对共同购买链接形成的影响呈正比关系，而差评率则会显著地降低产品共同购买的几率。该指数随机图构建出的共同购买网络为在线电商平台管理网络口碑和推荐系统优化设计提供有益参考。     

Foam-based cleaning of surfaces contaminated with mixtures of oil and soot

Liquid foams of intermediate stability have been shown to be very efficient in the cleaning of sensitive surfaces because of the synergy between imbibition and foam decay. While we quantified these mechanisms for contaminations with liquid oils in our previous work, we show here their extension to oils containing soot particles in an effort to simulate increasingly realistic contaminations. Using foams with a wide range of liquid fractions and with different stabilities, we show that the main cleaning mechanisms remain very similar, with the oil entraining the soot particles. However, we find much less efficient soot removal when the liquid channels of the foams are small enough to hinder efficient transport of the soot particles.     

Chemical Bonding by the Chemical Orthogonal Space of Reactivity

The fashionable Parr–Pearson (PP) atoms-in-molecule/bonding (AIM/AIB) approach for determining the exchanged charge necessary for acquiring an equalized electronegativity within a chemical bond is refined and generalized here by introducing the concepts of chemical power within the chemical orthogonal space (COS) in terms of electronegativity and chemical hardness. Electronegativity and chemical hardness are conceptually orthogonal, since there are opposite tendencies in bonding, i.e., reactivity vs. stability or the HOMO-LUMO middy level vs. the HOMO-LUMO interval (gap). Thus, atoms-in-molecule/bond electronegativity and chemical hardness are provided for in orthogonal space (COS), along with a generalized analytical expression of the exchanged electrons in bonding. Moreover, the present formalism surpasses the earlier Parr–Pearson limitation to the context of hetero-bonding molecules so as to also include the important case of covalent homo-bonding. The connections of the present COS analysis with PP formalism is analytically revealed, while a numerical illustration regarding the patterning and fragmentation of chemical benchmarking bondings is also presented and fundamental open questions are critically discussed.     

Flow state monitoring of gas-water two-phase flow using multi-Gaussian mixture model based on canonical variate analysis

As a highly complex and time-varying process, gas-water two-phase flow is commonly encountered in industries. It has a variety of typical flow states and transition flow states. Accurate identification and monitoring of flow states is not only beneficial to further study of two-phase flow but also helpful for stable operation and economic efficiency of process industry. Combining canonical variate analysis (CVA) and Gaussian mixture model (GMM), a strategy called multi-CVA-GMM is proposed for flow state monitoring in gas-water two-phase flow. CVA is used to extract flow state features from the perspective of correlation between historical data and future data, which solves the cross correlation and temporal correlation of multi-sensor measurement data. GMM calculates the possibility that the current flow state belongs to each typical flow pattern and judges the current flow state by probability indicators. It is conducive to follow-up use of Bayesian inference probability and Mahalanobis distance-based (BID) indicator for flow state monitoring, which avoids repeated traversal of multiple CVA-GMM models and improves the efficiency of the monitoring process. The probability indicators can also be used to analyze transition flow states. The method combining the probabilistic idea of GMM with the deterministic idea of multimodal modeling can accurately identify the current flow state and effectively monitor the evolution of flow state. The multi-CVA-GMM method is validated by using the measured data of the horizontal flow loop of gas-water two-phase flow experimental facility, and its effectiveness is proved.     

Flow modeling of high-viscosity fluids in pipeline infrastructure of oil and gas enterprises

Today, the issues related to solving the problem of finding an effective distribution of oil flows through the system of oil pipelines in order to reduce the total energy consumption are relevant. The solution to this problem is connected with selection of rational pumping modes for various technological sections of oil pipelines using modern methods of mathematical programming or new techniques for improving the energy and transport characteristics of oil.Reducing energy consumption during pumping of crude through oil trunk pipelines can be achieved by various methods. Numerous investigations in this direction are mainly carried out to save energy on separate single-line pipelines. However, due to the development of the network of trunk oil pipelines in the world over the past decades, the issues of energy efficient management of oil flows throughout the entire oil pipeline system of oil and gas enterprises become urgent.This paper analyses parameters for pipeline transport of high-viscosity and heavy oils. The article proposes a method for assessing the rheological properties of oil for further planning of pumping taking into account the preservation of oil quality and an increase in energy and transport characteristics. The proposed solutions and tasks for predicting changes in the viscosity-temperature characteristics of the flow for blends of different oil types are especially relevant in the current conditions of an increase in the share of oil production with complex rheological characteristics. Results of the presented investigations may be used for planning the measures of efficient transportation of high-viscosity and heavy oils.     

Mesenchymal Stromal Cell Therapy in Novel Porcine Model of Diffuse Liver Damage Induced by Repeated Biliary Obstruction

In liver surgery, biliary obstruction can lead to secondary biliary cirrhosis, a life-threatening disease with liver transplantation as the only curative treatment option. Mesenchymal stromal cells (MSC) have been shown to improve liver function in both acute and chronic liver disease models. This study evaluated the effect of allogenic MSC transplantation in a large animal model of repeated biliary obstruction followed by partial hepatectomy. MSC transplantation supported the growth of regenerated liver tissue after 14 days (MSC group, n = 10: from 1087 ± 108 (0 h) to 1243 ± 92 mL (14 days); control group, n = 11: from 1080 ± 95 (0 h) to 1100 ± 105 mL (14 days), p = 0.016), with a lower volume fraction of hepatocytes in regenerated liver tissue compared to resected liver tissue (59.5 ± 10.2% vs. 70.2 ± 5.6%, p < 0.05). Volume fraction of connective tissue, blood vessels and bile vessels in regenerated liver tissue, serum levels of liver enzymes (AST, ALT, ALP and GGT) and liver metabolites (albumin, bilirubin, urea and creatinine), as well as plasma levels of IL-6, IL-8, TNF-α and TGF-β, were not affected by MSC transplantation. In our novel, large animal (pig) model of repeated biliary obstruction followed by partial hepatectomy, MSC transplantation promoted growth of liver tissue without any effect on liver function. This study underscores the importance of translating results between small and large animal models as well as the careful translation of results from animal model into human medicine.     

42CrMo钢加热过程中的奥氏体晶粒尺寸演变

通过金相试验方法测定42CrMo钢在890~930 ℃下保温10~240 min后的晶粒尺寸。结果表明,42CrMo钢在加热到试验温度890~930 ℃时已经完全奥氏体化,保温过程中的晶粒生长属于正常生长;加热温度对晶粒尺寸的影响较大,保温时间对晶粒尺寸的影响较小;随保温时间的延长晶粒生长缓慢,晶粒尺寸与保温时间满足指数小于1的函数关系。基于试验数据,通过线性回归得到晶粒长大的Beck模型参数,通过非线性回归得到Sellars和Anelli模型参数,3个模型的预测精度都较好,而Anelli模型的适用性要高于Beck模型和Sellars模型,故在预测42CrMo钢的奥氏体晶粒长大规律时宜使用Anelli模型。     

Analytical Modeling for Translating Statistical Changes to Circuit Variability by Ultra-Deep Submicron Digital Circuit Design

This paper presents a physics-based compact gate delay model that includes all short-channel phenomena prevalent at the ultra-deep submicron technology node of 32 nm. To simplify calculations, the proposed model is connected to a compact α-power law-based (Sakurai-Newton) model. The model has been tested on a wide range of supply voltages. The model accurately predicts nominal delays and the delays under process variations. It has been shown that at lower technology nodes, the delay is more sensitive to threshold voltage variations, specifically at the sub-threshold operating region as compared with effective channel length variations above the threshold region.     

钻井机器人的连续油管钻压和钻速控制模型

连续油管钻井机器人利用机身内外的钻井液压力差作为动力源，可在牵引连续油管的同时加载钻压。以钻井机器人为基础，建立连续油管钻柱动力学模型，并推导出通过钻井液排量控制钻压和钻速的单参数控制数学模型；对钻井机器人引入调速回路，建立具有调速功能的钻柱动力学模型；在溢流阀调定压力大于机身内外压差时，推导出利用钻井液排量和节流阀流通面积两种参数控制钻压、钻速的数学模型，在溢流阀调定压力小于机身内外压差时，推导出利用钻井液排量、节流阀流通面积和溢流阀调定压力3种参数控制钻压、钻速的数学模型；以11.43 cm（4.5英寸）井眼为例，对上述3种数学模型进行了分析。分析结果表明：钻压、钻速随钻井液排量的增加基本呈线性增加，在钻井液排量大于0.005 m³/s时，钻井机器人能够向前爬行，在钻井液排量大于0.005 7 m³/s时，钻头能够正常钻进；调节节流阀流通面积和溢流阀调定压力，可以在一定范围内无级调钻压和钻速；3种控制方法相结合，可以实现小排量、大钻压，及大排量、小钻压等钻井参数的控制。以控制模型为基础，针对不同井下工况建立钻进工艺的专家数据库，以钻井机器人为"大脑"，结合井下随钻测量数据就能够实现闭环控制，自动钻进。