The impact of cultural diversity and economic growth on the equalization of public cultural services——Empirical test based on spatial econometric model

The 13th Five Year Plan of the National Basic Public Service System plays an important role in promoting the equalization of basic public services in urban and rural areas. Based on the panel data of 242 prefecture level cities in 30 provinces of China from 2008 to 2018, this paper uses the spatial econometric model for empirical analysis. The study finds that the direct effect of cultural diversity on the equalization of public cultural services is negative and significant, that is, cultural diversity hinders the equalization of public cultural services in the region; the overall effect of economic growth on the equalization of public cultural services is positive and significant, and economic growth is indeed conducive to the promotion of public cultural services equal development in the region. Based on this, it is proposed that local governments should establish a differentiated supply system of public cultural products to effectively integrate local cultural resources, talents, volunteers and social organizations. We will increase financial investment in public cultural services and use government purchases to promote the gradual equalization of public cultural services in rural areas, border ethnic areas and urban rural fringe areas

Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings

In neural machine translation, a source sequence of words is encoded into a vector from which a target sequence is generated in the decoding phase. Differently from statistical machine translation, the associations between source words and their possible target counterparts are not explicitly stored. Source and target words are at the two ends of a long information processing procedure, mediated by hidden states at both the source encoding and the target decoding phases. This makes it possible that a source word is incorrectly translated into a target word that is not any of its admissible equivalent counterparts in the target language. In this paper, we seek to somewhat shorten the distance between source and target words in that procedure, and thus strengthen their association, by means of a method we term bridging source and target word embeddings. We experiment with three strategies: (1) a source-side bridging model, where source word embeddings are moved one step closer to the output target sequence; (2) a target-side bridging model, which explores the more relevant source word embeddings for the prediction of the target sequence; and (3) a direct bridging model, which directly connects source and target word embeddings seeking to minimize errors in the translation of ones by the others. Experiments and analysis presented in this paper demonstrate that the proposed bridging models are able to significantly improve quality of both sentence translation, in general, and alignment and translation of individual source words with target words, in particular.Comment: 9 pages, 6 figures. Accepted by ACL201

Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery

At present, countless approaches to fault diagnosis in reciprocating machines have been proposed, all considering that the available machinery dataset is in equal proportions for all conditions. However, when the application is closer to reality, the problem of data imbalance is increasingly evident. In this paper, we propose a method for the creation of diagnoses that consider an extreme imbalance in the available data. Our approach first processes the vibration signals of the machine using a wavelet packet transform-based feature-extraction stage. Then, improved generative models are obtained with a dissimilarity-based model selection to artificially balance the dataset. Finally, a Random Forest classifier is created to address the diagnostic task. This methodology provides a considerable improvement with 99% of data imbalance over other approaches reported in the literature, showing performance similar to that obtained with a balanced set of data.National Natural Science Foundation of China, under Grant 51605406National Natural Science Foundation of China under Grant 7180104

Frequency-Aware Transformer for Learned Image Compression

Learned image compression (LIC) has gained traction as an effective solution for image storage and transmission in recent years. However, existing LIC methods are redundant in latent representation due to limitations in capturing anisotropic frequency components and preserving directional details. To overcome these challenges, we propose a novel frequency-aware transformer (FAT) block that for the first time achieves multiscale directional ananlysis for LIC. The FAT block comprises frequency-decomposition window attention (FDWA) modules to capture multiscale and directional frequency components of natural images. Additionally, we introduce frequency-modulation feed-forward network (FMFFN) to adaptively modulate different frequency components, improving rate-distortion performance. Furthermore, we present a transformer-based channel-wise autoregressive (T-CA) model that effectively exploits channel dependencies. Experiments show that our method achieves state-of-the-art rate-distortion performance compared to existing LIC methods, and evidently outperforms latest standardized codec VTM-12.1 by 14.5%, 15.1%, 13.0% in BD-rate on the Kodak, Tecnick, and CLIC datasets

What Is a Better Marketing Strategy for Live Streaming Broadcasters? A Topic Model of Social Interactions

Live streaming has spawned a new business model called live-streaming commerce (LSC). Interactive LSC features affect viewer purchasing behavior. This study empirically examines two types of social interactions in danmaku: transaction-oriented and relationship-oriented. Viewers in the first category focus on products and transactions and tend to talk non-emotionally. While relationship-oriented viewers might treat broadcasters as friends, using emotional language in their interactions. Our econometric model shows a curvilinear association of relationship-oriented social interaction and viewer purchase behaviors in LSC, but social interactions have varying effects on viewer purchase behaviors.We discuss implications of heterogeneous social-interaction strategies across different broadcasters

Direct sequencing and expression analysis of a large number of miRNAs in Aedes aegypti and a multi-species survey of novel mosquito miRNAs

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a novel class of gene regulators whose biogenesis involves hairpin structures called precursor miRNAs, or pre-miRNAs. A pre-miRNA is processed to make a miRNA:miRNA* duplex, which is then separated to generate a mature miRNA and a miRNA*. The mature miRNAs play key regulatory roles during embryonic development as well as other cellular processes. They are also implicated in control of viral infection as well as innate immunity. Direct experimental evidence for mosquito miRNAs has been recently reported in anopheline mosquitoes based on small-scale cloning efforts.</p> <p>Results</p> <p>We obtained approximately 130, 000 small RNA sequences from the yellow fever mosquito, <it>Aedes aegypti</it>, by 454 sequencing of samples that were isolated from mixed-age embryos and midguts from sugar-fed and blood-fed females, respectively. We also performed bioinformatics analysis on the <it>Ae. aegypti </it>genome assembly to identify evidence for additional miRNAs. The combination of these approaches uncovered 98 different pre-miRNAs in <it>Ae. aegypti </it>which could produce 86 distinct miRNAs. Thirteen miRNAs, including eight novel miRNAs identified in this study, are currently only found in mosquitoes. We also identified five potential revisions to previously annotated miRNAs at the miRNA termini, two cases of highly abundant miRNA* sequences, 14 miRNA clusters, and 17 cases where more than one pre-miRNA hairpin produces the same or highly similar mature miRNAs. A number of miRNAs showed higher levels in midgut from blood-fed female than that from sugar-fed female, which was confirmed by northern blots on two of these miRNAs. Northern blots also revealed several miRNAs that showed stage-specific expression. Detailed expression analysis of eight of the 13 mosquito-specific miRNAs in four divergent mosquito genera identified cases of clearly conserved expression patterns and obvious differences. Four of the 13 miRNAs are specific to certain lineage(s) within mosquitoes.</p> <p>Conclusion</p> <p>This study provides the first systematic analysis of miRNAs in <it>Ae. aegypti </it>and offers a substantially expanded list of miRNAs for all mosquitoes. New insights were gained on the evolution of conserved and lineage-specific miRNAs in mosquitoes. The expression profiles of a few miRNAs suggest stage-specific functions and functions related to embryonic development or blood feeding. A better understanding of the functions of these miRNAs will offer new insights in mosquito biology and may lead to novel approaches to combat mosquito-borne infectious diseases.</p

Learning spatial and spectral features via 2D-1D generative adversarial network for hyperspectral image super-resolution

Three-dimensional (3D) convolutional networks have been proven to be able to explore spatial context and spectral information simultaneously for super-resolution (SR). However, such kind of network can’t be practically designed very ‘deep’ due to the long training time and GPU memory limitations involved in 3D convolution. Instead, in this paper, spatial context and spectral information in hyperspectral images (HSIs) are explored using Two-dimensional (2D) and Onedimenional (1D) convolution, separately. Therefore, a novel 2D-1D generative adversarial network architecture (2D-1DHSRGAN) is proposed for SR of HSIs. Specifically, the generator network consists of a spatial network and a spectral network, in which spatial network is trained with the least absolute deviations loss function to explore spatial context by 2D convolution and spectral network is trained with the spectral angle mapper (SAM) loss function to extract spectral information by 1D convolution. Experimental results over two real HSIs demonstrate that the proposed 2D-1D-HSRGAN clearly outperforms several state-of-the-art algorithms

Anti-nociceptive effect of total alkaloids isolated from the seeds of Areca catechu L (Arecaceae) in mice

Purpose: To investigate the antinociceptive effect of the total alkaloids (TA) isolated from the seeds of Areca catechu L. (SAC) and to elucidate the probable mechanism of action.Methods: TA extraction conditions including concentration of ethanol, extraction  temperature, liquid–solid ratio and designed pH were optimized by an orthogonal  experiment {L9(3)4} test. The antinociceptive effect of the extract in mice was  evaluated by acetic acid writhing reflex test, hot plate test, capsaicin-induced  nociception test, tail-flick test and formalin-induced pain test in mice. Furthermore, pretreatment of the animals with naloxone (2 mg/kg) was performed to investigate whether the antinociceptive effect involved the opioid route or not. The locomotor activity of TA in mice were also assessed.Results: The optimum extraction conditions of TA were as follows: solid-liquid ratio of 1: 15 (w/v), ethanol concentration of 80 %, pH of 9.0 and extraction temperature of 70°C. Oral administration of TA produced a marked anti-nociceptive activity in mice, and pretreatment with naloxone did not reverse the anti-nociceptive activity of TA in mice. Also, the locomotor activity of mice was not affected by TA. In addition, TA significantly down-regulated the expression levels of COX-2 in the dorsal root of mice spinal cord at 100, 200 and 400 mg/kg doses.Conclusion: The results demonstrate that TA possesses significant anti-nociceptive effects, and the mechanisms are closely related to suppression of COX-2 expression. Overall, the results provided scientific support for the use of TA in treatment of pain.Keywords: Areca catechu, Total alkaloids, Anti-nociceptive, Formalin-induced pain, Naloxon