Liposome Crosslinked Polyacrylamide/DNA Hydrogel: a Smart Controlled‐Release System for Small Molecular Payloads

A novel stimuli‐responsive hydrogel system with liposomes serving as both noncovalent crosslinkers and functional small molecules carriers for controlled‐release is developed. Liposomes can crosslink polyacrylamide copolymers functionalized with cholesterol‐modified DNA motifs to yield a DNA hydrogel system, due to the hydrophobic interaction between cholesteryl groups and the lipid bilayer of liposomes. Functional information encoded DNA motifs on the polymer backbones endow the hydrogel with programmable smart responsive properties. In a model system, the hydrogel exhibits stimuli‐responsive gel‐to‐sol transformation triggered by the opening of DNA motifs upon the presence of a restriction endonuclease enzyme, EcoR I, or temperature change, realizing the controlled‐release of liposomes which are highly efficient carriers of active small molecules payloads. Two active molecules, 1,1‐dioctadecyl‐3,3,3,3‐tetramethylindodicarbocyanine perchlorate (DiIC18(5)) and calcein, are chosen as the hydrophobic and hydrophilic model payloads, respectively, to address the feasibility of the releasing strategy. Moreover, the hydrogel exhibits injectable property as well as self‐recovery behaviors.     

High‐Performance As‐Cast Nonfullerene Polymer Solar Cells with Thicker Active Layer and Large Area Exceeding 11% Power Conversion Efficiency

In this work, a nonfullerene polymer solar cell (PSC) based on a wide bandgap polymer donor PM6 containing fluorinated thienyl benzodithiophene (BDT‐2F) unit and a narrow bandgap small molecule acceptor 2,2′‐((2Z,2′Z)‐((4,4,9,9‐tetrahexyl‐4,9‐dihydro‐s‐indaceno[1,2‐b:5,6‐b′]dithiophene‐2,7‐diyl)bis(methanylylidene))bis(3‐oxo‐2,3‐dihydro‐1H‐indene‐2,1‐diylidene))dimalononitrile (IDIC) is developed. In addition to matched energy levels and complementary absorption spectrum with IDIC, PM6 possesses high crystallinity and strong π–π stacking alignment, which are favorable to charge carrier transport and hence suppress recombination in devices. As a result, the PM6:IDIC‐based PSCs without extra treatments show an outstanding power conversion efficiency (PCE) of 11.9%, which is the record value for the as‐cast PSC devices reported in the literature to date. Moreover, the device performances are insensitive to the active layer thickness (≈95–255 nm) and device area (0.20–0.81 cm²) with PCEs of over 11%. Besides, the PM6:IDIC‐based flexible PSCs with a large device area of 1.25 cm² exhibit a high PCE of 6.54%. These results indicate that the PM6:IDIC blend is a promising candidate for future roll‐to‐roll mass manufacturing and practical application of highly efficient PSCs.     

Lamellarly Stacking Porous N,P Co‐Doped Mo2C/C Nanosheets as High Performance Anode for Lithium‐Ion Batteries

Layered stacking and highly porous N, P co‐doped Mo₂C/C nanosheets are prepared from a stable Mo‐enhanced hydrogel. The hydrogel is formed through the ultrafast cross‐linking of phosphomolybdic acid and chitosan. During the reduction of the composite hydrogel framework under inert gas protection, highly porous N and P co‐doped carbon nanosheets are produced with the in situ formation of ultrafine Mo₂C nanoparticles highly distributed throughout the nanosheets which are entangled via a hierarchical lamellar infrastructure. This unique architecture of the N, P co‐doped Mo₂C/C nanosheets tremendously promote the electrochemical activity and operate stability with high specific capacity and extremely stable cycling. In particular, this versatile synthetic strategy can also be extended to other polyoxometalate (such as phosphotungstic acid) to provide greater opportunities for the controlled fabrication of novel hierarchical nanostructures for next‐generation high performance energy storage applications.     

模糊聚类网中多对一映射的实现

分析了模糊聚类网实现多对一映射的两种方式：有监督和无监督,给出了实现这两种方式的网络模型：自适应模糊信要成聚类网和二次模糊聚类网。     

Interference coordination in full-duplex HetNet with large-scale antenna arrays

Massive multiple-input multiple-output (MIMO), small cell, and full-duplex are promising techniques for future 5G communication systems, where interference has become the most challenging issue to be addressed. In this paper, we provide an interference coordination framework for a two-tier heterogeneous network (HetNet) that consists of a massive-MIMO enabled macro-cell base station (MBS) and a number of full-duplex small-cell base stations (SBSs). To suppress the interferences and maximize the throughput, the full-duplex mode of each SBS at the wireless backhaul link (i.e., in-band or out-of-band), which has a different impact on the interference pattern, should be carefully selected. To address this problem, we propose two centralized algorithms, a genetic algorithm (GEA) and a greedy algorithm (GRA). To sufficiently reduce the computational overhead of the MBS, a distributed graph coloring algorithm (DGCA) based on price is further proposed. Numerical results demonstrate that the proposed algorithms significantly improve the system throughput.     

基于自适应外点剔除与解耦算法的视觉里程计

针对视觉里程计内点确定的问题,提出了一种基于自适应外点剔除与解耦算法的视觉里程计方法.采用ORB（Oriented FAST and Rotated BRIEF）算子检测特征点.采用经光流归一化的重投影误差作为内点评判标准,归一化的重投影误差与特征点的深度及位置无关.自运动估计分为两步：先使用改进的5-point RANSAC方法结合球形线性插值求解优化的旋转参数;然后采用两帧间光束法平差,结合归一化的重投影误差去除外点,迭代循环到最大次数或内点集合不变,得到最优的平移参数.采用公共数据集KITTI对算法进行测试,实验表明本文算法较之传统的采用固定阈值重投影误差评估内点并同时估计6自由度的方法,在外点剔除方面有显著提升,与同类视觉里程计方法相比在精度上也有提升.     

Internet of Vehicles in Big Data Era

As the rapid development of automotive telematics, modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks (VANETs) are evolving to the Internet of Vehicles (IoV), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between IoV and big data in vehicular environment, mainly on how IoV supports the transmission, storage, computing of the big data, and how IoV benefits from big data in terms of IoV characterization, performance evaluation and big data assisted communication protocol design. We then investigate the application of IoV big data in autonomous vehicles. Finally, the emerging issues of the big data enabled IoV are discussed.      

Aggregated Temporal Tensor Factorization Model for Point-of-Interest Recommendation

Point-of-interest (POI) recommendation is an important application in location-based social networks (LBSNs), which mines user check-in sequences to suggest interesting locations for users. Because user check-in behavior exhibits strong temporal patterns—for instance, users would like to check-in at restaurants at noon and visit bars at night. Hence, capturing the temporal influence is necessary to ensure the high performance in a POI recommendation system. Previous studies observe that the temporal characteristics of user mobility in LBSNs can be summarized in three aspects: periodicity, consecutiveness, and non-uniformness. However, previous work does not model the three characteristics together. More importantly, we observe that the temporal characteristics exist at different time scales, which cannot be modeled in prior work. In this paper, we propose an Aggregated Temporal Tensor Factorization (ATTF) model for POI recommendation to capture the three temporal features together, as well as at different time scales. Specifically, we employ a temporal tensor factorization method to model the check-in activity, subsuming the three temporal features together. Next, we exploit a linear combination operator to aggregate temporal latent features’ contributions at different time scales. Experiments on two real-world data sets show that the ATTF model achieves better performance than the state-of-the-art temporal models for POI recommendation.     

A Fast 2D Shape Recovery Approach by Fusing Features and Appearance

In this paper, we present a fusion approach to solve the nonrigid shape recovery problem, which takes advantage of both the appearance information and the local features. We have two major contributions. First, we propose a novel progressive finite Newton optimization scheme for the feature-based nonrigid surface detection problem, which is reduced to only solving a set of linear equations. The key is to formulate the nonrigid surface detection as an unconstrained quadratic optimization problem that has a closed-form solution for a given set of observations. Second, we propose a deformable Lucas-Kanade algorithm that triangulates the template image into small patches and constrains the deformation through the second-order derivatives of the mesh vertices. We formulate it into a sparse regularized least squares problem, which is able to reduce the computational cost and the memory requirement. The inverse compositional algorithm is applied to efficiently solve the optimization problem. We have conducted extensive experiments for performance evaluation on various environments, whose promising results show that the proposed algorithm is both efficient and effective.     

基于拟态架构的内生安全云数据中心关键技术和实现方法

云数据中心是新一代信息基础设施的代表,其安全问题也成为近年来备受关注的焦点,具有重要的意义。首先,在对现有云安全形势分析的基础上,通过新兴的内生安全概念探索云数据中心的安全架构、关键技术和实现方法,期望利用拟态构造设计解决现有防护手段难以处理的漏洞、后门等内生安全问题。其次,提出了一种云数据中心内生安全架构与相关关键技术实现构想,同时给出了现有云平台系统拟态化改造的模式与技术趋势。未来,基于拟态架构的内生安全云数据中心或将为新一代信息基础设施建设提供有效的安全解决方案,进而加速云化服务模式的应用与推广。