Preparation and characterization of calcium phosphate cement with enhanced tissue adhesion for bone defect repair

Anti-washout and tissue adhesion properties are essential for the clinical application of injectable bone materials. In this study, we prepared calcium phosphate cement (CPC) with anti-washout and tissue adhesion properties and attempted to build covalent bonds between CPC and the amino groups in bone tissue under a self-regulating pH system in the CPC (acidic to basic). The results of push-out tests demonstrated that a significant enhancement (from 6.42 ± 0.76 N to 61.5 ± 4.09 N) in tissue adhesion was obtained with the addition of 6% (w/w) oxidized sodium alginate (OSA) in CPC. The FTIR, XRD, anti-washout test, XPS, pH test, and SEM results suggested that the synergistic effect of OSA-citric acid (CA) led to the formation of a three-dimensional gel network structure in the CPC, and the Schiff base reaction between aldehyde and amino groups induced adhesion between CPC and the bone tissue. Further, the addition of less OSA had no significant negative effect on the hydration properties of CPC. Our work aims to promote the development of injectable bone material in clinical applications.     

高光谱激光雷达谱位合一的角度效应分析

高光谱激光雷达以其谱位合一的技术优势为实现超三维精准遥感观测提供了可行途径,因此成为当前激光雷达与高光谱遥感领域共同大力推进的前沿发展方向。目前已有多型原型系统研发出来并得到了原理性验证,然而针对其数据处理核心环节问题的基础技术仍较为欠缺。典型问题之一是不同波段回波信号受激光入射角度的影响,该角度效应限制了高光谱激光雷达实现高性能遥感。以芬兰空间信息研究所高光谱激光雷达原型系统扫描桦树树干为例探讨了该角度效应,发现了不同激光波段对不同入射角度的回波强度响应模式,推导出了角度效应的基本规律及其精细尺度的统计规律,为后续该方向的系统研发、数据处理及信息提取等提供了可借鉴的底层机理与技术基础。     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Fluoride-mediately solvothermal synthesis and tunable photocatalytic selectivity of urchin-like ZrO2 hollow microspheres

Photocatalysts often show excellent performances on the basis of their surface state of exposed faces with high reactivity, but unfortunately surfaces of this type are usually concealed into the interior of crystals for their high surface energy. We report here a possibility that for fluorine-terminated surfaces of monoclinic ZrO₂, these higher-energy surfaces could be retained and exposed. Urchin-like ZrO₂ hollow microspheres (UZHS) composed of nanoribbons with exposed (010) facets are obtained through a fluoride mediately solvothermal method. We prove the stabilization effect of fluorine adsorption on (010) facets by density functional theory calculations. More interestingly, UZHS exhibit tunable photocatalytic selectivity in dye degradation. The fluorinated UZHS exhibit good performances both on decomposing Congo red (CR) and methylene blue, while the surface-modified UZHS by calcination only favor decomposition of CR.     

Screening of frozen-thawed conditions for keeping nutritive compositions and physicochemical characteristics of goat milk

Frozen milk can help producers overcome the seasonality of goat milk production, low goat production and short lactation periods, and avoid discarding milk during some special periods. We investigated effects of combination between freezing (cryogenic refrigerator of ?16 to ?20°C or ultra-cryogenic refrigerator of ?76 to ?80°C) and thawing (homeothermy of 20 to 25°C or refrigeration of 2 to 4°C) on nutritive compositions and physicochemical characteristics of raw goat milk during storage period (80 d). Compared with fresh goat milk, the frozen-thawed milk decreased contents of fat, protein, and lactose, as well as surface tension and stability coefficient, whereas increased effective diameter and polydispersity index. The average values of color values (L*, a*, and b*) in 4 group samples changed from 83.01 to 82.25, ?1.40 to ?1.54, 3.51 to 3.81, respectively, and the ΔE of most samples did not exceed 2. In contrast to the other 3 frozen-thawed treatments, goat milk treated with ultra-cryogenic freezing-homeothermic thawing (UFHT) possessed higher fat (5.20 g/100 g), smaller effective particle diameter (0.32 µm), and the lowest polydispersity index value (0.26). The color and confocal laser scanning microscopy images of UFHT were similar to those of fresh goat milk, illustrating UFHT was the optimal approach to maintain the natural quality of goat milk. Our finding provides a theoretical basis for producers to freeze surplus milk.     

DNAN及TNT基熔铸炸药综合性能比较

为了对比载体炸药2,4,6-三硝基甲苯(TNT)和2,4-二硝基苯甲醚(DNAN)、以及以它们为基的熔铸炸药的综合性能,系统研究了DNAN和TNT、以及DNAN/HMX(20/80)和TNT/HMX(25/75)熔铸炸药的流变、能量、安全、以及力学等性能。结果表明:载体炸药DNAN(6.87 m Pa·s)的粘度低于TNT(9.05 mPa·s),DNAN/HMX熔铸体系的极限固含量(约80%)高于TNT/HMX熔铸体系(约75%);DNAN/HMX(20/80)和TNT/HMX(25/75)熔铸炸药的爆速分别为8336 m·s~(-1)和8452 m·s~(-1),爆压分别为31.03 GPa和31.44 GPa;在1 K·min~(-1)的慢速烤燃条件下,DNAN/HMX(20/80)和TNT/HMX(25/75)熔铸炸药的响应等级分别为燃烧反应和爆炸反应;在4.51GPa的冲击波入射压力条件下,TNT/HMX(25/75)在8～12 mm内达到完全爆轰,而DNAN/HMX(20/80)在12 mm内未能达到完全爆轰;DNAN/HMX(20/80)的抗拉和抗压强度均大于TNT/HMX(25/75)。因此可以得出结论,在能量性能基本持平的情况下,DNAN/HMX(20/80)熔铸炸药的安全及力学性能优于TNT/HMX(25/75)熔铸炸药。     

Numerical Investigation of the Capture of Polydisperse Particles by Charged Droplets

The capture of particles by charged droplets was simulated by considering the electrostatic interactions of droplet-droplet and droplet-particle. The results indicate that the electrostatic repulsion between droplets leads to a dynamic accumulation mode of particles. However, the droplet spacing has an insignificant effect on the capture efficiency when the electrostatic deposition predominates. The increase of droplet charge remarkably improves the capture efficiency, in which the capture of fine particles accounts for the largest proportion. Compared to the droplet charge, the droplet size shows a limited improvement in the capture efficiency. Reducing the droplet velocity prolongs the capture time instead of enhancing the capture capacity per unit time, thereby improving capture efficiency.     

Combining molybdenum carbide with ceria overlayers to boost Mo/CeO2 catalyzed ammonia synthesis

The design of an efficient non-noble metal catalyst is of burgeoning interest for ammonia synthesis. Herein, we report a Mo₂C/CeO₂ catalyst that is superior in ammonia synthesis activity. In this catalyst, molybdenum carbide coexisted with the ceria overlayers which is from the ceria support as the strong metal–support interaction. There is a high proportion of low-valent Mo species, as well as high concentration of Ce³⁺ and surface oxygen species. The presence of Mo₂C and CeO₂ overlayers not only leads to enhancement of hydrogen and nitrogen adsorption, but also facilitates the desorption and exchange of adsorbed species with the gaseous reagents. Compared with the Mo/CeO₂ catalyst prepared without carbonization, the Mo₂C/CeO₂ catalyst is more than sevenfold higher in ammonia synthesis rate. This work not only presents an explicit example of designing Mo-based catalyst that is highly efficient for ammonia synthesis by tuning the adsorption and desorption properties of the reactant gases, but opens a perspective for other elements in ammonia synthesis.     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。