基于并行跟踪检测框架与深度学习的目标跟踪算法

在空地协同背景下，地面目标的移动导致其在无人机视角下外观会发生较大变化，传统算法很难满足此类场景的应用要求。针对这一问题，提出基于并行跟踪和检测（PTAD）框架与深度学习的目标检测与跟踪算法。首先，将基于卷积神经网络（CNN）的目标检测算法SSD作为PTAD的检测子处理关键帧获取目标信息并提供给跟踪子；其次，检测子与跟踪子并行处理图像帧并计算检测与跟踪结果框的重叠度及跟踪结果的置信度；最后，根据跟踪子与检测子的跟踪或检测状态来判断是否对跟踪子或检测子进行更新，并对图像帧中的目标进行实时跟踪。在无人机视角下的视频序列上开展实验研究和对比分析，结果表明所提算法的性能高于PTAD框架下最优算法，而且实时性提高了13%，验证了此算法的有效性。     

Transverse heat transfer coefficient in the dual channel ITER TF CICCs. Part III: Direct method of assessment

The data resulting from the thermal-hydraulic test of the ITER TF CICC are used to determine the flow partition and the overall effective heat transfer coefficient (h_BC) between bundle and central channel in a direct way, i.e. by analysis of the heat transfer between both flow channels, based on the mass and energy balance equations and the readings of thermometers located inside the cable. In cases without a local heat source in the considered cable segment the obtained h_BC values were consistent with those obtained in earlier studies by analysis of experimental data using indirect methods. It was also observed that the transverse heat transfer was strongly enhanced in a cable segment heated from outside. This phenomenon results from the mass transfer from the bundle region to the central channel. The experimental h_BC data obtained for the case without a heat source in the considered segment were also compared with those calculated using various heat transfer correlations.     

Coastal trapped waves in the southern Caspian Sea

Previous studies reported coastal trapped waves (CTWs) in the Caspian Sea (CS). This study deals with the generation mechanisms, the temporal and spatial variability of CTWs in this area, and their transformations during propagation from the origin to the destination using recent measurements and high-resolution numerical simulations. CTWs are observed at all stations with periods of 2–6 days after northerly storms. The Absheron Peninsula, old Sefidrud delta, and Nur coasts were identified as the CTWs prone regions. The generation of CTWs in these locations was confirmed using numerical experiments. The propagation away from the generating location of CTWs was analyzed using a representative real wind storm. In the west part of the CS, the generation mechanism of CTWs is mainly similar to the barotropic Kelvin waves; in contrast, it is similar to the continental shelf waves in the southern shelves. The results can be used to study the contribution of generated CTWs to the transport of sediment and biological materials in all large lakes.     

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.     

基于广义二次互相关的低信噪比信号时延估计

针对时延估计精度受噪声影响,导致时延估计不准确的问题,在现有广义二次相关算法的基础上,提出了一种改进的广义二次相关算法,通过将二次相关函数先做指数运算,降低噪声干扰,再将傅里叶逆变换得到的相关函数做高次方运算,达到锐化峰值提高时延正确率的目的。仿真结果表明,信噪比(SNR)在0~10 dB时,改进算法的均方根误差明显优于广义二次相关算法,正确率相比于广义二次相关算法也显著提高,且在更低SNR的情况下仍然具有一定优势。     

Advances and perspectives on one-dimensional nanostructure electrode materials for potassium-ion batteries

Potassium-ion batteries (PIBs) have aroused considerable interest as a promising next-generation advanced large-scale energy storage system due to the abundant potassium resources and high safety. However, the K⁺ with large ionic radius brings restricted diffusion kinetics and severe volume expansion in electrode materials, resulting in inferior actual rate characteristics and rapid capacity fading. Designing electrode materials with one-dimensional (1D) nanostructure can effectively enhance various electrochemical properties due to the well-guided electron transfer pathways, short ionic diffusion channels and high specific surface areas. In this review, we summarize the recent research progress and achievements of 1D nanostructure electrode materials in PIBs, especially focusing on the development and application of cathode and anode materials. The nanostructure, synthetic methods, electrochemical performances and structure-performance correlation are discussed in detail. The advanced characterizations on the reaction mechanisms of 1D nanostructure electrode materials in PIBs are briefly summarized. Furthermore, the main future research directions of 1D nanostructure electrode materials are also predicted, hoping to accelerate their development into the practical PIBs market.     

LaMgAl11O19 synthesis using non-hydrolytic sol-gel methods

Polycrystalline LaMgAl₁₁O₁₉ (LMA) was prepared by four different non-hydrolytic sol-gel methods. From stable solutions, four powder precursors containing an amorphous and nanocrystalline phase with specific reactivity were obtained. The particle size, morphology, thermal behaviour, and phase composition of the powder precursors were studied using DLS, TEM, DSC/TG and XRD. Bulk ceramic samples containing LMA were prepared at 1200?°C for 16?h and examined in terms of phase purity and microstructure using XRD, SEM, and TEM. Raman spectroscopy of pure LMA was used to study the structure in detail. A mechanism of LMA formation and a relation between powder precursor properties and final phase composition is proposed. These findings may be useful for designing modern technologies for fabrication of LMA for optical or protective coating applications.     

A generation method of artificial fluctuation data of wind power output considering smoothing effect

To use realistic wind power fluctuation data is important in simulating frequency change of power systems. It is well known that the smoothing effect must be taken into account when generating the artificial wind power output. Therefore, this paper proposed a new method to generate fluctuation waveform considering smoothing effect based on random number to fulfill the correlation among multiple sites and autoregression model. The effectiveness of the proposed method was tested by using practical wind speed data measured in Tohoku district.