Characteristic tryptic peptides and gelling properties of porcine skin gelatin affected by thermal action

Thermal action in extraction process had effects on characteristic tryptic peptides identification and gelling properties of porcine gelatin. SDS-PAGE, HPLC-LTQ/Orbitrap high-resolution mass spectrometry, texture analyser and rheometer were used to evaluate collagen depolymerisation degree, characteristic tryptic peptides and gelling properties of gelatins prepared in various thermal actions. Results showed that with increasing temperature and time, depolymerisation degree enlarged, while gel strength, gelling and melting temperature decreased. Mass spectra showed that 47 and 49 common characteristic tryptic peptides were identified in gelatins extracted at 50 °C and 100 °C with various times, respectively. Moreover, 34 common characteristic tryptic peptides were identified in all gelatin samples. Further comparison between this work and our previous investigations yielded 20 common characteristic tryptic peptides, which stably exist in various thermal actions. These common characteristic tryptic peptides may be very helpful for the accurate authentication of porcine gelatin.     

Flash Lamps as Ignition and Initiation Sources of the VS-2 Pyrotechnic Composition

In the present work it is found that the pyrotechnic composition VS-2 can be initiated with flash lamps IFC-500 and EVIS. VS-2 pyrotechnic composition contains 90% of mercury（Ⅱ） 5-hydrazinotetrazolate perchlorate and 10% of optically transparent copolymer of 2-methyl-5-vinyltetrazole and methacrylic acid （PVMT）. We have found that the flash lamps make it possible to initiate combustion of VS-2 composition with its transition to detonation both in cylindrical charges placed in brass caps of 5 mm diameter and 2 mm high， and film charges with 10 mm×80 mm in size and surface weights of 60 mg·cm^-2 and 90 mg·cm^-2， showing ignition delay times 10 μs and 3 μs， respectively. We also measured detonation velocities for VS-2 composition film charges， which were 4375-4505 m·s^-1 （of the charge being surface mass 60 mg·cm^-2） and 4221-4281 m·s^-1 （of the charge being surface mass 90 mg·cm^-2） and their blasting action on the aluminum plate. The depths of the normal shock wave imprints at the charge-barrier interface were 0.6-0.7 mm （for surface mass of the film charges 60 mg·cm^-2） and 1.2-1.3 mm （for surface mass of the film charges 90 mg·cm^-2）.     

碳酸性侵蚀与AAR作用下纳米混凝土的耐久性

地铁混凝土处于地下空间,容易受到地下水的碳酸性侵蚀；碱集料反应 (AAR)是一种严重的混凝土耐久性问题,既难以发现又难以修补,由两者共同作用引起的混凝土耐久性降低严重影响地铁隧道的正常使用.为研究纳米材料对地铁混凝土在碳酸性侵蚀和AAR共同作用下耐久性的影响,在普通混凝土中掺入适量纳米SiO₂和纳米Fe₂O₃,利用自行研制的碳酸性侵蚀试验箱进行试验,采用碳酸性侵蚀深度、膨胀率和声速作为测试指标来评价纳米混凝土在碳酸性侵蚀和AAR共同作用下的耐久性.试验结果表明:掺入纳米颗粒后,混凝土的膨胀率和侵蚀深度有了明显降低,而声速有了明显提升,说明纳米混凝土的耐久性优于普通混凝土；在182 d龄期时,掺量为2%的纳米SiO₂混凝土耐久性改善最明显,侵蚀深度和膨胀率最小,声速最大且声速下降幅度最小；其次是掺量为1%的纳米Fe₂O₃混凝土.由于纳米颗粒特殊的物理化学性质,改善了混凝土内部的微观结构和孔溶液的化学组成,使碳酸性侵蚀和碱集料反应共同作用下混凝土的耐久性得到了提高.     

Selection of risk response actions with consideration of secondary risks

Secondary risk in project risk management refers to the risk that arises as a direct result of implementing a risk response action (RRA). It is important for project managers (PMs) to consider the effects caused by the secondary risks in the process of RRA selection. The purpose of this paper is to propose an optimization method to address the problem of selecting risk response actions (RRAs) with consideration of secondary risk which is seldom considered in the existing studies. The optimization model aims to minimize the total risk costs with time constraint being placed on the project makespan. By solving the model, an optimal set of RRAs along with the earliest start time for each activity can both be obtained. The results show that secondary risk plays an important role in the process of RRA selection. Project managers should allocate more budget for responding the project risk when the secondary risk is considered, and consider all factors relating to both time and cost so as to select appropriate RRAs to mitigate primary risk and secondary risk.     

Convolutional neural network with adaptive inferential framework for skeleton-based action recognition

In the task of skeleton-based action recognition, CNN-based methods represent the skeleton data as a pseudo image for processing. However, it still remains as a critical issue of how to construct the pseudo image to model the spatial dependencies of the skeletal data. To address this issue, we propose a novel convolutional neural network with adaptive inferential framework (AIF-CNN) to exploit the dependencies among the skeleton joints. We particularly investigate several initialization strategies to make the AIF effective with each strategy introducing the different prior knowledge. Extensive experiments on the dataset of NTU RGB+D and Kinetics-Skeleton demonstrate that the performance is improved significantly by integrating the different prior information. The source code is available at: https://github.com/hhe-distance/AIF-CNN.     

Human action recognition toward massive-scale sport sceneries based on deep multi-model feature fusion

In sport sceneries, automatically recognizing human actions is a useful technique that can be popularly applied in may domains, such as human body tracking and athlete behavior analysis Most state-of-the-art deep architectures have achieved competitive performance in recognizing human action. However, it is still a challenging task due to the unavoidable occlusion, camera angle changes, and varied human posture. In this paper, we propose a novel deep multimodal feature fusion algorithm for human action recognition. The key technique is a multi-model feature fusion scheme. More specifically, we fuse visual feature, skeleton posture, probability maps and audio signal into a hybrid feature, which is utilized to represent human action. Then these feature channels are optimally combined using a deep model, wherein the weights of multiple feature channels can be predicted intelligently. Finally, the optimally fused feature are fed into a multi-class SVM for conducting human action recognition. Extensive comparative results and parameter analysis have shown the effectiveness of our proposed method.     

海藻多酚功能性作用机制及其应用初探

海藻多酚是海藻次级代谢产物,具有多种生物学活性,能够为人体所吸收和利用,所以海藻多酚成为了现阶段海洋活性物质研究的一个重点。就海藻多酚功能性作用机制以及其应用做分析,旨在为实践提供指导和帮助。     

Effects of ethylenediamine on the physico-chemical properties of heavy oil

As a type of organic base, ethylenediamine has a significant influence on the properties of the heavy oil, which can be used to emulsify the heavy oil under shear conditions. After 12?hours of shearing at the rate of 20r/min at the temperature of 60?°C, a volume heavy oil can be completely emulsified in 9 volume ethylenediamine solution with mass concentration of 5000?mg/L to form an O/W emulsion. Under the action of ethylenediamine, the interfacial tension is decreased, the Zeta potential is increased, the interfacial shear viscosity has a little change, and the stabilization of O/W emulsion is increased. The results can provide a reference for the study the mechanism of emulsification of heavy oil by using organic alkali.     

基于IMCT理论的CaO-SiO2-MgO-Al2O3-Na2O渣系的脱硫热力学模型

 为了精确表征含Na2O渣系的脱硫能力，改善脱硫效果，基于熔渣离子与分子共存理论（IMCT）建立了CaO-SiO2-MgO-Al2O3-Na2O渣系结构单元的作用浓度计算模型和1 753 K时该渣系的脱硫热力学模型。并对渣系的总硫分配比及各自硫分配比的影响因素进行了讨论分析。理论结果表明，除LS， MgS外，随着Al2O3质量分数的增加，该渣系的脱硫能力明显下降，而MgO和Na2O质量分数的增加，对提高渣系的脱硫能力具有明显的促进作用。此外，少量的Na2O即可表现出很强的脱硫效果，这为含有Na2O的冶金二次资源在铁水脱硫过程中的应用以及铁水脱硫渣系的优化提供了必要的理论依据。