Development of a Sorption Technique for the Selective Separation of Plutonium and Americium from Nitric Acid Intermediate-Level Wastes of Chemical and Metallurgical Production

Radiochemistry - The sorption extraction of Pu and Am from nitric acid simulation solutions were studied on a solid extractant (TVEX) AXIONIT MND 40T in a static mode. It is shown that the...     

智能建造技术协同创新主体互动关系研究

文章分析智能建造技术创新主体的特点，界定并划分智能建造技术协同创新主体互动关系的范畴和类别，建立智能建造协同创新的多方演化博弈模型，揭示智能建造技术协同创新主体互动关系。主要结论为：①智能建造技术协同创新呈现级联性、函数性、动态平衡性、不确定性和指数性特征；②智能建造技术协同创新主体互动关系分为同质性的内部主体互动和异质性的内部主体与外部主体互动，表现出利益共生、成长进化和共享协同的特征；③创新主体之间的互动行为有利于对创新资源进行有效配置，推动智能建造技术的应用。     

Universal Information Software Technology for Non-Oriented Mixed Forests

Cybernetics and Systems Analysis - A new information software technology has been created, which is implemented in a software package and is destined to perform a wide, easily supplemented set of...     

Optimized decomposition and two-step nonlinear integration model with error correction strategy coupled interval prediction for digital currency price forecast

Digital currency price prediction is vital to both sellers and purchasers. Over these years, decomposition and integration models have been applied more and more to realize the goal of precise prediction, however, many of them tend to neglect the reconstruction of features or the residual series. Altogether, one of the biggest drawbacks of the decomposition and integration framework is the method applied requires manual parameter setting whether it is for decomposition or integration. Still, for the results, they are merely satisfied with the point prediction which brings high uncertainty. In this paper, an optimized feature reconstruction decomposition and two-step nonlinear integration method is proposed which gives consideration to feature reconstruction, nonlinear integration, optimization and interval prediction. The original data series is decomposed through improved variational mode decomposition based approximate entropy feature reconstruction system. Then, improved particle swarm optimization-gated recurrent unit (iPSO-GRU) is utilized in the first and second nonlinear integration part separately. Meanwhile, the residual series is given attention, if it is not a white noise series, the residual will be the input of iPSO-GRU whose result will be added back to the second integration result to form the point prediction result. Based on the point prediction result, interval prediction estimate will be generated as well via maximum likelihood function. This study chooses three kinds of digital currency as cases and the results show that the MAPE values of point prediction are all below 3.5%, and CP values of interval prediction are all 1 with suitable MWP. In addition, compared with other benchmark models, the proposed model shows better performance.

     

Gelling behavior of MgAl2O4 slurries with a common dispersant

MgAl₂O₄ transparent ceramics were shaped by a commonly used polyacrylic acid (PAA), which acted as both dispersant and gelling agent. The spinel slurries were prepared by ball-milling MgAl₂O₄ powder, PAA, and water in an attrition mill. The gelling of slurries happened at room temperature in air atmosphere without any other organic additive. The gelling mechanism was the formation of chelates between Mg²⁺ and carboxyl groups (-COO⁻) of PAA. The frequency-based testing method was applied to investigate the gelling process of the as-prepared slurry. In addition, a novel in situ characterization method based on a modified indentation testing was invented to better understand the strengthening of the wet green body with time and to guide when demolding could be carried out. After sintering, transparent MgAl₂O₄ ceramics with high in-line transmittance were resulted.     

Polysorbate identity and quantity dictate the extensional flow properties of protein-excipient solutions

While protein medications are promising for treatment of cancer and autoimmune diseases, challenges persist in terms of development and injection stability of high-concentration formulations. Here, the extensional flow properties of protein-excipient solutions are examined via dripping-onto-substrate extensional rheology, using a model ovalbumin (OVA) protein and biocompatible excipients polysorbate 20 (PS20) and 80 (PS80). Despite similar PS structures, differences in extensional flow are observed based on PS identity in two regimes: at moderate total concentrations where surface tension differences drive changes in extensional flow behavior, and at small PS:OVA ratios, which impact the onset of weakly elastic flow behavior. Undesirable elasticity is observed in ultra-concentrated formulations, independent of PS identity; higher PS contents are required to observe these effects than in analogous polymeric excipient solutions. These studies reveal novel extensional flow behaviors in protein-excipient solutions, and provide a straightforward methodology for assessing the extensional flow stability of new protein-excipient formulations.     

Hydrogenation of CO2 to Hydrocarbons over Zirconia-Supported Cobalt Catalyst Promoted with Potassium

Catalysis Letters - The purpose of this study was to investigate the promotive effect of potassium on the catalytic performance and properties of Co/ZrO2 catalysts during hydrogenation of CO2 to...