Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.     

Prompting structure stability of O3–NaNi0.5Mn0.5O2 via effective surface regulation based on atomic layer deposition

Layered O3 type oxides exhibit promising prospects as high-performance cathodes for sodium-ion batteries (SIBs) due to their low cost and high theoretical capacities. Nevertheless, the intrinsic surface composition and bulk structure degradation upon cycling presents a huge obstacle to stable sodium-ion storage/transportation. Besides, the effective surface decoration on layered O3 oxides is still challenging through conventional wet chemical route owing to their extraordinarily high surface sensitivities. Herein, a typical O3 type layered oxide of NaNi_0.5Mn_0.5O₂ (NNMO) was selected and successfully encapsulated by precisely controlled Al₂O₃ layers via atomic layer deposition (ALD) technology. With the optimally controlled Al₂O₃ thickness of 3 nm, the surface regulated NNMO delivers a highly reversible capacity of 73.6 mA h g^-1, with a significantly improved capacity retention of 68.0% after 300 cycles at 0.5 C, and a superior rate capability of 65.8 mA h g^-1 at 10 C. Further air sensitivity tests demonstrate that the protective layer could effectively mitigate the generation of sodium-based impurities on NNMO, and reduce the surface sensitivities. Both chemical and electrochemical aging tests confirm the contribution of Al₂O₃ coating layer in alleviating ion dissolution as well as stabilizing the structure and morphology of NNMO. Based on regulating the surface of O3 type layered oxides utilizing ALD technique, this work supplies an effective and facile strategy to overcome the challenges from fast structure degradation and electrochemical property decay, which not only highlights the significance and effectiveness of surface engineering in secondary batteries, but also sheds light on accurate interface construction and regulation for active electrode materials, particularly for those sensitive to ambient atmosphere.     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

microRNA在亨廷顿病中的研究进展

亨廷顿病(Huntington's disease, HD)是神经退行性疾病(neurodegenerative disorders)中一种单基因遗传病,由亨廷顿基因(the huntingtin gene, HTT)第一个外显子中的CAG三核苷酸序列重复扩增引起,尚无法治愈。HTT编码的蛋白产物被称为亨廷顿蛋白(Huntingtin protein, Htt)。突变亨廷顿蛋白(mutated huntingtin protein, mHtt)容易形成聚集体,具有毒性,导致一系列细胞学异常和神经元功能障碍。microRNA(miRNA)在基因转录后水平调控中起重要作用,其表达的改变与HD病理过程有关,成为治疗HD的潜在生物标志物。近年来,对一些特定miRNA在HD中调控机制及靶基因预测方面的研究可为HD提供潜在的治疗方法。本文就miRNA在HD中的相关研究进展进行综述。