Preparation and Application of Sustained-Release Potassium Ferrate(VI)

In this study, a composite system for the sustained release of potassium ferrate(VI) (sustained-release K 2 FeO 4 ) was prepared and applied for water treatment. The objective of this research was to maximize the effectiveness of K 2 FeO 4 for water treatment by enhancing its stability using diatomite. The sustained-release K 2 FeO 4 was characterized using X-ray diffraction, scanning electron microscopy, and Fourier transform infrared spectroscopy. The results indicated that no new crystal phase was formed during the preparation and some K 2 FeO 4 crystals entered the pores of the diatomite. From K 2 FeO 4 release experiments, we found that the decomposition rate of K 2 FeO 4 was obviously decreased, which greatly improved the contact rate between released K 2 FeO 4 and pollutants. Via degradation of methyl orange, which was used as a model pollutant, the influential factor of K 2 FeO 4 content within the complete sustained-release K 2 FeO 4 system was studied. The optimal K 2 FeO 4 content within the sustained-release K 2 FeO 4 system was approximately 70%. In natural water samples, sustained-release K 2 FeO 4 at a dosage of 0.06 g/L and with a reaction time of 20 minutes removed 36.84% of soluble microbial products and 17.03% of simple aromatic proteins, and these removal rates were better than those observed after traditional chlorine disinfection

The Oscillation on Solutions of Some Classes of Linear Differential Equations with Meromorphic Coefficients of Finite [

This paper considers the oscillation on meromorphic solutions of the second-order linear differential equations with the form f′′+A(z)f=0, where A(z) is a meromorphic function with [p,q]-order. We obtain some theorems which are the improvement and generalization of the results given by Bank and Laine, Cao and Li, Kinnunen, and others

Alternative splicing and trans-splicing events revealed by analysis of the Bombyx mori transcriptome

Alternative splicing and trans-splicing events have not been systematically studied in the silkworm Bombyx mori. Here, the silkworm transcriptome was analyzed by RNA-seq. We identified 320 novel genes, modified 1140 gene models, and found thousands of alternative splicing and 58 trans-splicing events. Studies of three SR proteins show that both their alternative splicing patterns and mRNA products are conserved from insect to human, and one isoform of Srsf6 with a retained intron is expressed sex-specifically in silkworm gonads. Trans-splicing of mod(mdg4) in silkworm was experimentally confirmed. We identified integrations from a common 5′-gene with 46 newly identified alternative 3′-exons that are located on both DNA strands over a 500-kb region. Other trans-splicing events in B. mori were predicted by bioinformatic analysis, in which 12 events were confirmed by RT-PCR, six events were further validated by chimeric SNPs, and two events were confirmed by allele-specific RT-PCR in F 1 hybrids from distinct silkworm lines of JS and L10, indicating that trans-splicing is more widespread in insects than previously thought. Analysis of the B. mori transcriptome by RNA-seq provides valuable information of regulatory alternative splicing events. The conservation of splicing events across species and newly identified trans-splicing events suggest that B. mori is a good model for future studies. Published by Cold Spring Harbor Laboratory Press. Copyrigh

GM-TCNet: Gated Multi-scale Temporal Convolutional Network using Emotion Causality for Speech Emotion Recognition

In human-computer interaction, Speech Emotion Recognition (SER) plays an essential role in understanding the user's intent and improving the interactive experience. While similar sentimental speeches own diverse speaker characteristics but share common antecedents and consequences, an essential challenge for SER is how to produce robust and discriminative representations through causality between speech emotions. In this paper, we propose a Gated Multi-scale Temporal Convolutional Network (GM-TCNet) to construct a novel emotional causality representation learning component with a multi-scale receptive field. GM-TCNet deploys a novel emotional causality representation learning component to capture the dynamics of emotion across the time domain, constructed with dilated causal convolution layer and gating mechanism. Besides, it utilizes skip connection fusing high-level features from different gated convolution blocks to capture abundant and subtle emotion changes in human speech. GM-TCNet first uses a single type of feature, mel-frequency cepstral coefficients, as inputs and then passes them through the gated temporal convolutional module to generate the high-level features. Finally, the features are fed to the emotion classifier to accomplish the SER task. The experimental results show that our model maintains the highest performance in most cases compared to state-of-the-art techniques.Comment: The source code is available at: https://github.com/Jiaxin-Ye/GM-TCNe