小微数据包高效无线传输技术的发展和趋势

5G-NR和B5G系统都需能高效地支持小微数据包(块)的传输,且在不同的无线传输技术(如宽带或超低时延)之间快速灵活地切换。系统梳理和比较和小微数据包(块)相关的多种无线传输技术,如两步RACH、预配置授权和公共资源竞争等,分析它们对3GPP各个系统和各个RAN协议的影响和复杂度优劣等,并进一步展望其未来发展和应用趋势。     

湿法氧化锌种类和用量对天然橡胶性能的影响

研究湿法氧化锌种类和用量对天然橡胶(NR)性能的影响。结果表明:与添加普通氧化锌的胶料相比,对于未填充炭黑NR体系,减半用量的湿法氧化锌混炼胶的焦烧时间和t90较短,Fmax较大;硫化胶的定伸应力、拉伸强度和剪切模量(G′)较大,拉断伸长率、损耗模量(G″)和损耗因子(tanδ)较小。对于填充炭黑NR体系,减半用量的湿法氧化锌混炼胶的门尼粘度、G′和G″较大,tanδ较小,焦烧时间和t90较短,Fmax较大;硫化胶的密度稍低,硬度和定伸应力较大,耐老化性能较好,玻璃化温度较低,tanδ较小,其他物理性能变化不大。湿法氧化锌FF的性能优于湿法氧化锌HR。     

新型防老剂RT-1对天然橡胶性能的影响

研究新型防老剂RT-1对天然橡胶(NR)性能的影响。结果表明:加入防老剂RT-1,NR胶料的ML增大,MH减小,t90和ts1延长,老化后NR硫化胶的拉伸性能较好,热氧化活化能增大;防老剂RT-1对NR硫化胶热氧老化的防护效果优于防老剂BHT和4010NA。     

NR/CIIR/TPI共混物相容性及力学性能的分子动力学模拟

采用分子动力学(MD)方法计算了不同聚合度的天然橡胶(NR)、氯化丁基橡胶(CIIR)和杜仲胶(TPI)的溶解度参数,分析了体系的相容性;模拟研究了NR/CIIR/TPI共混物的力学性能。结果表明,添加30份以内的TPI可以降低模量,改善共混物的力学性能。     

NR/SiO_2复合体系结合胶及动态力学性能研究

研究了白炭黑用量和Si69原位改性对NR/SiO2复合体系结合胶含量及其与动态力学性能之间关系的影响。结果表明,随着白炭黑用量的增大,2种复合体系(NR/SiO2/Si69和NR/SiO2)结合胶含量均呈现先增大后减小的趋势。当白炭黑用量达到临界值时,复合体系结合胶含量最大,此时Payne效应开始显现。当白炭黑用量超过临界值时,复合体系结合胶含量减小,形成完善的填料网络结构,出现明显的Payne效应。与NR/SiO2复合体系相比,NR/SiO2/Si69复合体系结合胶含量大大提高,白炭黑用量的临界值也相应提高,Payne效应减弱。     

除臭菌株对NR动态力学性能的影响

采用RPA2000橡胶加工分析仪,分析了不同凝固方式获得的NR的动态力学性能。结果发现,除臭菌株C5对生物凝固胶的动态力学性能无不良影响,且加有除臭菌株C5的生物凝固胶块具有比生物凝固和酸凝固更好的加工性能和回弹性。     

Blind quality assessment for screen content images via convolutional neural network

With the wide propagation of cloud and mobile computing, screen content images (SCIs) have become more indispensable in our daily lives. Compared to natural scene images (NSIs), SCIs possess many particular characteristics, like mixed contents, extremely sharp edges, and text graphics. Consequently, more challenges occur in the feature extraction, which is used to reflect the distortion, during the quality assessment of SCIs. Recently, some convolutional neural network (CNN) models have been designed by automatically learning feature to evaluate the quality. In this paper, we develop a novel blind quality assessment method for SCIs via the CNN. First, compared with existing CNN-based methods, the proposed method avoids the disadvantage of training with image patches, and it is the pioneering attempt that takes the entire image as inputs. Second, instead of the image gray value, the original image is decomposed into two portions, i.e., the predicted and unpredicted portions, according to the internal generative mechanism (IGM) theory as the input of CNN. Through the CNN, all features of the image are learned automatically from beginning to end, and the network finally outputs the predicted score. Since existing SCI database is too small, to fully train the network, we collected 30000 SCIs and employed a high-accuracy full-reference quality assessment metric of SCI to compute scores as the training labels. Experimental results on SIQAD database demonstrate that the proposed method is comparable to reference-based SCI quality assessment metrics and is superior to the state-of-the-art NSI quality assessment metrics.     

Blind image quality assessment with improved natural scene statistics model

No-reference (NR)/blind image quality assessment (IQA) metrics play an important role in the area of image processing. Natural scene statistics (NSS) model assumes that natural images possess certain regular statistical properties and is widely used in NR IQA metrics. Most existing NSS-based NR algorithms are achieved by measuring the variation of image statistics, which are characterized by the fitting parameters of NSS model, across different distortions. However, distortions not only change the image statistics, but also disturb the statistical regularity held by natural images. As a result, the distribution of distorted images can not well follow the NSS model. There exists fitting error between the real distribution of the distorted image and the fitted one under certain NSS model. In this paper, the statistical distributions of the distorted images are discussed in detail. We suggest to take the fitting errors into account as well as the fitting parameters for feature extraction, and propose a novel NR IQA algorithm. Experimental results on several image databases demonstrate that the proposed metric performs highly consistent with human visual perception.     

No reference image blurriness assessment with local binary patterns

In this paper, we put forward an effective and efficient no reference image blurriness assessment metric on the basis of local binary pattern (LBP) features. In this proposal, we reveal that part of the LBP histogram bins present monotonously with the degree of blurriness. The proposed method contains the following steps. Firstly, the LBP maps of an input image are extracted with multiple radiuses. And then, the frequency of pattern histogram is analyzed before part of bins are chosen as the features. In addition, we also take the entropy of these bins as another feature. Finally, we learn the extracted features to predict the image blurriness score. Validation of the proposed method is conducted on the blurred images of LIVE-II, CSIQ, TID2008, TID2013, LIVE3D IQA Phase I and LIVE3D IQA Phase II. Experimental results demonstrate that compared with the state-of-the-art image quality assessment (IQA) methods, the proposed algorithm has notable advantage in correlation with subjective perception and computational complexity.     

Effect of surface-mannose modification on aerosolized liposomal delivery to alveolar macrophages

Purpose: The effect of surface-mannose modification on aerosolized liposomal delivery to alveolar macrophages (AMs) was evaluated in vitro and in vivo. Method: 4-Aminophenyl-α-D-mannopyranoside (Man) was used for surface-mannose modification, and mannosylated liposomes with various mannosylation rates (particle size: 1000 nm) were prepared. Results: In the in vitro uptake experiments, the uptake of mannosylated liposomes by AMs was increased with the increase in the mannosylation rate over the range 2.4–9.1 mol% Man and became constant at over 9.1%. Thus, the most efficient mannosylation rate was 9.1 mol% Man. Furthermore, free mannose inhibited the uptake of mannosylated liposomes by AMs. This indicates that the uptake mechanism of mannosylated liposomes by AMs is mannose receptor-mediated endocytosis. In the in vivo animal experiments, the mannosylated liposomes (mannosylation rate, 9.1 mol% Man) were more efficiently delivered to AMs after pulmonary aerosolization to rats than nonmodified liposomes and did not harm lung tissues. Conclusion: These results indicate that surface-mannose modification is useful for efficient aerosolized liposomal delivery to AMs.