柠条的纤维特性及其双螺杆CMP制浆性能研究

以柠条为原料，分析了其化学组分和纤维形态，并探讨了柠条双螺杆CMP法的制浆工艺以及浆料的纤维形态和成纸的物理性能。研究结果表明：与针、阔叶木相比，柠条原料中纤维素和综纤维素质量分数较低，苯醇抽出物和热水抽出物质量分数较高，柠条纤维长度总体偏短，木质部和皮部的纤维质量平均长度分别为0.621和0.819 mm，还存在部分杂细胞。采用3.5% Na₂SO₃和1.5% NaOH常温预浸12 h、90℃汽蒸1 h后再用双螺杆挤浆机在质量分数35%下进行搓丝，并结合高浓盘磨机磨浆，所得CMP浆得率可达73%。柠条CMP浆基本保持了纤维原有的长度，质量平均长度达0.650 mm，长宽比为32.7，纤维解离较好，但分丝帚化情况不理想，含有部分纤维束和杂细胞。当加拿大游离度为300 mL时，柠条CMP浆成纸的环压强度指数和松厚度较高，分别为8.67（N·m）/g和2.56 cm³/g，抗张指数为19.6（N·m）/g，本色浆白度较高，达50%（ISO）。柠条CMP浆适合配抄瓦楞原纸等包装用纸，漂白后可配抄新闻纸和白板纸。     

Augmented context-based recommendation service framework using knowledge over the Linked Open Data cloud

This research proposes ACARDS (Augmented-Context bAsed RecommenDation Service) framework that is able to utilize knowledge over the Linked Open Data (LOD) cloud to recommend context-based services to users. To improve the level of user satisfaction with the result of the recommendation, the ACARDS framework implements a novel recommendation algorithm that can utilize the knowledge over the LOD cloud. In addition, the noble algorithm is able to use new concepts like the enriched tags and the augmented tags that originate from the hashtags on the SNSs materials. These tags are utilized to recommend the most appropriate services in the user’s context, which can change dynamically. Last but not least, the ACARDS framework implements the context-based reshaping algorithm on the augmented tag cloud. In the reshaping process, the ACARDS framework can recommend the highly receptive services in the users’ context and their preferences. To evaluate the performance of the ACARDS framework, we conduct four kinds of experiments using the Instagram materials and the LOD cloud. As a result, we proved that the ACARDS framework contributes to increasing the query efficiency by reducing the search space and improving the user satisfaction on the recommended services.     

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.     

30Cr13不锈钢冶炼过程夹杂物控制技术

  针对30Cr13生产过程中存在的轧材非金属夹杂物合格率偏低仅85%左右的问题，通过对30Cr13不锈钢精炼过程钢中非金属夹杂物存在形态进行分析，并结合现有精炼工艺制度，在实验室研究的基础上制定了不锈钢精炼过程非金属夹杂物控制方案。工业应用后，精炼结束钢中大于5 μm的非金属夹杂物总数、形状以及尺寸等参数均得到了有效改善，钢水洁净度大大提高。     

基于多元神经网络融合的分布式资源空间文本分类研究

针对实体产业对科技资源的服务需求,以服务效应作为资源文本分类标准,提出一种基于多元神经网络融合的分布式资源空间文本分类模型。设计了包含词嵌入层、卷积层、双向门控循环单元层、注意力机制层和softmax层的多元神经网络通路;在此基础上采用基于需求—效应—资源分类策略,完成了从定性科技资源需求到定量资源服务效应求解,再到定性科技资源输出的映射变换,重点解决了分布式科技资源局部和全局语义特征形式多样、文本长距离依赖特征显著、重要资源信息难以准确识别的问题,进而从分布式科技资源空间中快速准确地获取效应知识,提升实体产业产品研发效率和创新能力;通过万方专利科技资源数据集验证了所提方法的可行性和有效性,为更加全面地挖掘资源文本特征和按需服务实体产业提供了一种新的思路和手段。     

Modelling,simulation and identification of an engine air path electromechanical actuator

This paper deals with the modelling and the identification of an electromechanical Diesel engine actuator. The studied Bosch GPA-S actuator is designed for swirl/tumble flaps to control the air amount entering into the cylinder. This study aims to design a complete simulator that reproduces, with sufficient accuracy, the actuator dynamics taking into account the effects of the friction phenomenon. Hence, an overview of the actuator structure and its operation principle is first given. Then, its mathematical model as well as the nonlinearity, related to its behaviour, is discussed. Next, three identification procedures, which allow estimating both the system parameters and the friction model coefficients, are introduced. Finally, simulation results, using MATLAB, and experimental results, using LabVIEW, are presented demonstrating the effectiveness of the proposed techniques.     

A self‐scalable load injection service

Load testing of applications is an important and costly activity for software provider companies. Classical solutions are very difficult to set up statically, and their cost is prohibitive in terms of both human and hardware resources. Virtualized cloud computing platforms provide new opportunities for stressing an application's scalability, by providing a large range of flexible and less expensive (pay‐per‐use model) computation units. On the basis of these advantages, load testing solutions could be provided on demand in the cloud. This paper describes a Benchmark‐as‐a‐Service solution that automatically scales the load injection platform and facilitates its setup according to load profiles. Our approach is based on: (i) virtualization of the benchmarking platform to create self‐scaling injectors; (ii) online calibration to characterize the injector's capacity and impact on the benched application; and (iii) a provisioning solution to appropriately scale the load injection platform ahead of time. We also report experiments on a benchmark illustrating the benefits of this system in terms of cost and resource reductions. Copyright © 2013 John Wiley & Sons, Ltd.     

Intelligent Information‐Centric Networking routing scheme under imprecise information

Information‐Centric Networking (ICN) has been accepted to overcome some weaknesses of the current Internet architecture, showing that “what is being exchanged” is more important than “who are exchanging information.” Given the inadequate considerations on Quality of Service (QoS) and energy saving in ICN routing, we propose in this paper a routing algorithm to enhance the two aspects. At first, on one hand, Cauchy distribution is used as a fuzzy model to evaluate users' QoS requirements, such as bandwidth, delay, and error rate; on the other hand, we formulate energy saving problem to evaluate the green quality of routing algorithm. Then, we design a link selection approach by considering QoS and energy saving, which belongs to a multi‐objective decision problem resolved by intelligent drops algorithm. Finally, we implement the proposed algorithm and compare it with the famous adaptive forwarding mechanism in terms of some significant metrics, and the experimental results reveal that the proposed algorithm is more efficient.     

Correlation between instrumental texture and colour quality attributes with sensory analysis of selected cheeses as affected by fat contents

This study evaluated several physical and sensory parameters of different types of cheese available in the Polish market. The measurements of textural properties were conducted in an Instron universal testing machine, while the colour properties of cheeses were measured using a Minolta chromameter. The chemical composition was determined by means of the near‐infrared spectroscopy (NIRs). Moreover, a trained sensory panel was invited to assess the cheese texture‐related properties. Generally, cheeses with reduced fat content were characterised by higher hardness, adhesiveness, cohesiveness and elasticity. Texture‐related parameters of cheese with canola oil were comparable to that of most of full‐fat cheeses. The correlation analysis between physical and sensory attributes related to cheese textural properties indicated the potential applications of TPA, shear and penetration tests (r = 0.766, r = 0.75 and r = 0.765, respectively) for the evaluation of sensory properties related to the hardness. Meanwhile, the elasticity of cheese obtained from sensory evaluation was strongly correlated with the elasticity determined from the shear test (r = 0.722) and moderately correlated with the elasticity from penetration test (r = 0.588), indicating a need to refine the method of penetration test. In addition, cheeses exhibited higher meltability during convection heating at 230 °C than microwave heating. The values of meltability for cheese with reduced fat content were lower than those of full‐fat cheese.