Fast DGT Based Receivers for GFDM in Broadband Channels

Generalized frequency division multiplexing (GFDM) is a recent multicarrier 5G waveform candidate with flexibility of pulse shaping filters. However, the flexibility of choosing a pulse shaping filter may result in inter carrier interference (ICI) and inter symbol interference (ISI), which becomes more severe in a broadband channel. In order to eliminate the ISI and ICI, based on discrete Gabor transform (DGT), in this paper, a transmit GFDM signal is first treated as an inverse DGT (IDGT), and then a frequency-domain DGT is formulated to recover (as a receiver) the GFDM signal. Furthermore, to reduce the complexity, a suboptimal frequency-domain DGT called local DGT (LDGT) is developed. Some analyses are also given for the proposed DGT based receivers.Comment: 28 pages, 8 figure

Understanding the Joule-Heating Behaviours of Electrically-Heatable Carbon-Nanotube Aerogels

Cylindrical monolithic, electrically-heatable reduced carbon nanotube (rCNT) aerogels were synthesized to exploit their Joule-heating behaviours using two different arrangements (i.e. the top–bottom arrangement and the side–side arrangement) under different compressive strains. The top–bottom arrangement results in faster heating kinetics (up to 286 K min(−1)), higher heating efficiency (up to 80 °C W(−1)), a more uniform temperature distribution profile and higher electro-thermal conversion efficiency than the side–side arrangement. This study provides fundamental perspectives for exploiting the Joule-heating behaviours of geometrically complex nanocarbon aerogels, and thus will have important implications in strain-sensitive materials

Microstructural characterisation of organic matter pores in coal-measure shale

      To gain the insight into the nature of organic matter (OM) micro-nanometer pores and fractal features of coal-measure shale from the OM macromolecular evolution perspective, 28 Taiyuan formation shale samples are collected from Qinshui Basin and characterized with Rock-eval, Field emission scanning electron microscope (FE-SEM), low-pressure N2 gas adsorption (Lp-N2GA) and Fourier transform infrared spectroscopy (FTIR). The results show that OM is in the high-over mature stage. Pore size ranges from 5.7 to 26.7 nm and pores less than 4 nm are dominant. Two pore fractal dimensions D1 and D2 are obtained from Lp-N2GA with the Frenkel-Halsey-Hill method, which are in the range of 2.272-2.617 and 2.561-2.799, respectively. A series of FTIR structure parameters are obtained by peak fitting the FTIR spectra to describe the microstructure of OM molecules, such as length of aliphatic chain, degree of aromatic carbon condensation and hydrocarbon generation potential. Micro-nanometer OM-related pores in FE-SEM images can be classified as OM hydrocarbon-generating pores, OM structure pores, OM intergranular pores and micro- cracks, with the first being most developed. Both hydrocarbon-generation and condensation of aromatic nucleus have positive effects on D1 . Hydrocarbon-generation is more effective for the development of micropores, while the condensation of aromatic nucleus is more conducive for the development of mesopores (<10 nm). The higher the total organic carbon content, and the more the micropores and mesopores (<10 nm) develop, the higher the value of D1 .Cited as: Li, K., Kong, S., Xia, P., Wang, X. Microstructural characterisation of organic matter pores in coal-measure shale. Advances in Geo-Energy Research, 2020, 4(4): 372-391, doi: 10.46690/ager.2020.04.0

Proteomic changes associated with deletion of the Magnaporthe oryzae conidial morphology-regulating gene COM1

<p>Abstract</p> <p>Background</p> <p>The rice blast disease caused by <it>Magnaporthe oryzae </it>is a major constraint on world rice production. The conidia produced by this fungal pathogen are the main source of disease dissemination. The morphology of conidia may be a critical factor in the spore dispersal and virulence of <it>M. oryzae </it>in the field. Deletion of a conidial morphology regulating gene encoding putative transcriptional regulator COM1 in <it>M. oryzae </it>resulted in aberrant conidial shape, reduced conidiation and attenuated virulence.</p> <p>Results</p> <p>In this study, a two-dimensional gel electrophoresis/matrix assisted laser desorption ionization- time of flight mass spectrometry (2-DE/MALDI-TOF MS) based proteomics approach was employed to identify the cellular and molecular components regulated by the COM1 protein (COM1p) that might contribute to the aberrant phenotypes in <it>M. oryzae</it>. By comparing the conidial proteomes of <it>COM1 </it>deletion mutant and its isogenic wild-type strain P131, we identified a potpourri of 31 proteins that exhibited statistically significant alterations in their abundance levels. Of these differentially regulated proteins, the abundance levels of nine proteins were elevated and twelve were reduced in the Δ<it>com1 </it>mutant. Three proteins were detected only in the Δ<it>com1 </it>conidial proteome, whereas seven proteins were apparently undetectable. The data obtained in the study suggest that the COM1p plays a key role in transcriptional reprogramming of genes implicated in melanin biosynthesis, carbon and energy metabolism, structural organization of cell, lipid metabolism, amino acid metabolism, etc. Semi-quantitative RT-PCR analysis revealed the down-regulation of genes encoding enzymes involved in melanin biosynthesis in the <it>COM1 </it>mutant.</p> <p>Conclusions</p> <p>Our results suggest that the COM1p may regulate the transcription of genes involved in various cellular processes indispensable for conidial development and appressorial penetration. These functions are likely to contribute to the effects of COM1p upon the aberrant phenotypes of <it>M. oryzae</it>.</p> <p>Reviewers</p> <p>This article is reviewed by George V. Shpakovski, Karthikeyan Sivaraman (nominated by M. Madan Babu) and Lakshminarayan M. Iyer.</p

Anisotropic Convolutional Networks for 3D Semantic Scene Completion

As a voxel-wise labeling task, semantic scene completion (SSC) tries to simultaneously infer the occupancy and semantic labels for a scene from a single depth and/or RGB image. The key challenge for SSC is how to effectively take advantage of the 3D context to model various objects or stuffs with severe variations in shapes, layouts and visibility. To handle such variations, we propose a novel module called anisotropic convolution, which properties with flexibility and power impossible for the competing methods such as standard 3D convolution and some of its variations. In contrast to the standard 3D convolution that is limited to a fixed 3D receptive field, our module is capable of modeling the dimensional anisotropy voxel-wisely. The basic idea is to enable anisotropic 3D receptive field by decomposing a 3D convolution into three consecutive 1D convolutions, and the kernel size for each such 1D convolution is adaptively determined on the fly. By stacking multiple such anisotropic convolution modules, the voxel-wise modeling capability can be further enhanced while maintaining a controllable amount of model parameters. Extensive experiments on two SSC benchmarks, NYU-Depth-v2 and NYUCAD, show the superior performance of the proposed method. Our code is available at https://waterljwant.github.io/SSC

Arena: A Learning-based Synchronization Scheme for Hierarchical Federated Learning--Technical Report

Federated learning (FL) enables collaborative model training among distributed devices without data sharing, but existing FL suffers from poor scalability because of global model synchronization. To address this issue, hierarchical federated learning (HFL) has been recently proposed to let edge servers aggregate models of devices in proximity, while synchronizing via the cloud periodically. However, a critical open challenge about how to make a good synchronization scheme (when devices and edges should be synchronized) is still unsolved. Devices are heterogeneous in computing and communication capability, and their data could be non-IID. No existing work can well synchronize various roles (\textit{e.g.}, devices and edges) in HFL to guarantee high learning efficiency and accuracy. In this paper, we propose a learning-based synchronization scheme for HFL systems. By collecting data such as edge models, CPU usage, communication time, \textit{etc}., we design a deep reinforcement learning-based approach to decide the frequencies of cloud aggregation and edge aggregation, respectively. The proposed scheme well considers device heterogeneity, non-IID data and device mobility, to maximize the training model accuracy while minimizing the energy overhead. Meanwhile, the convergence bound of the proposed synchronization scheme has been analyzed. And we build an HFL testbed and conduct the experiments with real data obtained from Raspberry Pi and Alibaba Cloud. Extensive experiments under various settings are conducted to confirm the effectiveness of \textit{Arena}

Clinical and pathological analysis of 504 cases of elderly ocular tumors

AIM:To analyze the composition, distribution and characteristics of the elderly primary ocular tumors. <p>METHODS: This was a retrospective study and all 504 cases with primary ocular tumors aged 60 years or older were collected in Shanxi Eye Hospital, during the year 2000-2012. The onset age, location and pathological pattern were analyzed.<p>RESULTS: There were 346 cases of benign ocular tumors(68.7%), and 158 cases of malignancy(31.3%).Papillomas was the most common type of the benign with 83 cases(16.5%), followed by a variety of inflammatory cysts and lesions with 69 cases(13.7%)and 64 cases(12.7%)respectively. Among malignant tumors cases, eyelid basal cell carcinoma originated from epithelial was the most common with 72 cases(14.3%), followed by skin appendages sources malignant tumors with 39 cases(7.7%). Concerning the location of ocular tumors, there were 282 cases of eyelid tumor(56.0%)occupied the first position followed by conjunctival tumor with 157 cases(31.2%). <p>CONCLUSION: The prevalence and type of primary ocular tumor in elderly people are significant differences from the general population and children's, and the proportion of malignant tumors tended to increase along with the increase of age