我国堆场磷石膏工程特性分析

磷石膏堆场的渗流及稳定性分析结果的可靠度取决于磷石膏物理力学参数的准确性,因此开展磷石膏工程特性研究十分必要。根据我国不同磷石膏堆场的试验数据,分别对磷石膏的物理性质、击实特性、渗透特性、固结特性和强度特性进行了分析。结果表明:磷石膏强度、压缩、渗透特性均与其压实程度密切相关,相同压实程度不同堆场磷石膏的物理力学性质相近;磷石膏渗透特性与其晶体形态有关;磷石膏在荷载作用下具有长期蠕变变形特性,磷石膏堆场封场后仍会发生较大沉降;深部磷石膏破坏时的应变大于浅层磷石膏;磷石膏剪切破坏时产生负孔隙水压力,实际工程中可通过测试孔压的变化了解堆场坝体的安全程度。     

Mechanophysical Cues in Extracellular Matrix Regulation of Cell Behavior

The extracellular matrix (ECM) is a macromolecular network that can provide biochemical and structural support for cell adhesion and formation. It regulates cell behavior by influencing biochemical and physical cues. It is a dynamic structure whose components are modified, degraded, or deposited during connective tissue development, giving tissues strength and structural integrity. The physical properties of the natural ECM environment control the design of naturally or synthetically derived biomaterials to guide cell function in tissue engineering. Tissue engineering is an important field that explores physical cues of the ECM to produce new viable tissue for medical applications, such as in organ transplant and organ recovery. Understanding how the ECM exerts physical effects on cell behavior, when cells are seeded in synthetic ECM scaffolds, is of utmost importance. Herein we review recent findings in this area that report on cell behaviors in a variety of ECMs with different physical properties, i.e., topology, geometry, dimensionality, stiffness, and tension.     

影响煤层气开发效果的地质因素再认识

地质特征认识对煤层气开发效果起着重要作用。在资源特征相差不大的情况下,发现煤层气相邻井的产量差异仍较大。排除工程因素后,通过选取8类地质参数,细致比对了保德区块低产井与邻井的参数特征,筛查出其关键因素为煤层微幅构造与顶板封盖条件,其中以微幅构造为主。据此,重新认识并划分出区块新的次生褶皱背斜单元、向斜单元和斜坡单元,获得了不同次生褶皱构造单元的开发特征。结果表明,高、低产井分布与次生褶皱背斜、向斜相关性高达92%。其中:高产井主要分布在次生褶皱背斜变化较缓、呈隆起状的“平台”,且煤层顶板以泥岩、碳质泥岩为主,封盖性较好;低产井主要分布在次生褶皱向斜,同一井台各井开发效果差异表现为从向斜条带轴部—向斜条带内—向斜条带外的煤层气井平均单井产量不断增加,到向斜轴部的距离大于向斜曲率半径73.5%的范围为主力产气区,小于向斜曲率半径40.0%范围为产水主力区。这对煤层气新井部署、生产管理、开发调整等,具有一定的指导意义。     

An airlight estimation method for image dehazing based on gray projection

Multimedia Tools and Applications - As the key parameter of dehazing algorithms, airlight value directly affect the calculation accuracy of sky region, and any deviation will lead to the chromatic...     

Effects of hydrolysis of precursor on the structures and properties of polymer-derived SiBN ceramic fibers

In this paper, polyborosilazane precursor was synthesied from HMDZ, HSiCl₃, BCl₃ and CH₃NH₂ using a multistep method. By controlling the storage conditions, parts of the polyborosilazane fibers were hydrolyzed. FT-IR, NMR, XRD, TEM and monofilament tensile strength test were employed to study the effects of hydrolysis of precursor on the structures and properties of polymer-derived SiBN ceramic fibers. FT-IR and NMR results indicate that Si-N group in PBSZ reacts with H₂O to form Si-O-Si group. After pyrolysis reaction at 1400℃, Si-O-Si group will finally transformed into highly ordered cristobalite and β-quartz, resulting in formation of the wrinkled surface of the obtained SiBN ceramic fiber. The strip-like defects on fiber surface, according to monofilament tensile strength test, had a significant effect on mechanical property of the obtained SiBN ceramic fiber and caused no increase in fiber tensile strength of hydrolytic polyborosilazane fiber before and after pyrolytic process.     

A dense and compact laser cladding layer with solid metallurgical bonding significantly improved corrosion resistance of Mg alloy for engineering applications

Although Mg alloy attracts great attention for engineering applications because of high specific strength and low density, low corrosion resistance limits its extensive use. In this study, Mg–Al–Zn–Mn alloy was treated via a laser cladding process to generate a dense and compact laser cladding layer with solid metallurgical bonding on the substrate for improving corrosion resistance, effectively hindering the corrosion pervasion into Mg alloy. The corrosion current density declined from 103 μA/cm² for Mg alloy to 13 μA/cm² for the laser cladding layer in NaCl aqueous solution. Moreover, the laser cladding layer was slightly corroded in comparison with Mg alloy in NaCl aqueous solution. Besides, the microhardness of the cladding layer reached a mean value of 170.5 HV, 3.1 times of Mg alloy (56.8 HV) due to the in situ formation of hardening intermetallic phases. Wear resistance of laser cladding layer was also obviously improved. These results demonstrated that the laser cladding layer obviously enhanced anticorrosion property of Mg alloy for engineering applications.     

Improving storability,physiological disorders,and antioxidant properties of ‘Bartlett’ and ‘d’Anjou’ pears (Pyrus communis L.) by pre-harvest 1-methylcyclopropene spraying

Ethylene continues to be a major factor influencing quality of European pears during storage. Although research has been done on the effect of pre-harvest 1-methylcyclopropene (1-MCP) on physiological characteristics in pears, a full understanding of cultivar response and antioxidant metabolism remains elusive. Spraying 1-MCP on ‘Bartlett’ and ‘d’Anjou’ pears was studied with respect to physiology, storage and eating quality, disorders, and antioxidant properties at two harvest date (H1 and H2) during storage and ripening. Treatment with 1-MCP extended the harvest window of ‘Bartlett’ and ‘d’Anjou’ pears 3 and 4 days, respectively, without reducing storage or eating quality. Treatment with 1-MCP reduced ethylene production (EPR) and respiration rates (RR), maintained fruit firmness and green colour during storage and retarded development of desirable melting texture in both cultivars. Additionally, 1-MCP lowered the incidence of disorders by alleviating membrane lipid peroxidation, retaining high total flavonoids (TF) and antioxidant capacity, and enhancing superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activity in both cultivars. Overall, pre-harvest 1-MCP applications could extend storage time of ‘Bartlett’ and ‘d’Anjou’ pears to 5 and 6 months, respectively, at −1.1 ± 0.5 °C, by reducing ethylene synthesis and enhancing antioxidant metabolism.     

基于聚类的数据加权优化在犯罪预测中的应用

近年来，我国传统暴力犯罪与成年人犯罪呈下降态势，但是，犯罪案由层出不穷。为有效提升公安实践工作中犯罪预测能力，打击各类违法犯罪事件,本文针对犯罪数据，提出一种新型犯罪预测模型。利用密度聚类分析方法将犯罪数据分类，然后进行数据降维提取关键属性生成特征数据，继而对特征数据进行加权优化并采用机器学习的方式对特征数据进行学习，从而预测犯罪案由。实验结果表明，与传统方法相比，本文方法具有更好的预测效果，为公安实践工作中类似案件的侦破和预防，提供新的路径支撑。