News-Driven Stock Prediction With Attention-Based Noisy Recurrent State Transition

We consider direct modeling of underlying stock value movement sequences over time in the news-driven stock movement prediction. A recurrent state transition model is constructed, which better captures a gradual process of stock movement continuously by modeling the correlation between past and future price movements. By separating the effects of news and noise, a noisy random factor is also explicitly fitted based on the recurrent states. Results show that the proposed model outperforms strong baselines. Thanks to the use of attention over news events, our model is also more explainable. To our knowledge, we are the first to explicitly model both events and noise over a fundamental stock value state for news-driven stock movement prediction.Comment: 12 page

Deep neural network-based image enhancement algorithm for low-illumination images underground coal mines

Due to the complexity of the spatial environment and poor lighting conditions in underground coal mines, the images obtained by vision devices are prone to problems such as insufficient contrast and poor texture details, which seriously affect the reliability of the work of vision devices and limit further image-based intelligent applications. To improve the contrast of low-illumination images in underground mines while enhancing their texture details, a deep neural network-based low-illumination image enhancement model is proposed, which contains three sub-networks, namely, decomposition network, illumination adjustment network and reflection reconstruction network. The decomposition network decomposes the underground coal mine image into light and reflection components; the light adjustment network effectively reduces the parameters of the model using depth-separable convolutional structure and strengthens the feature extraction ability of the network; in addition, the MobileNet network structure is introduced to further lighten the light adjustment network while maintaining its feature extraction accuracy and effectively realizing the contrast adjustment of light components; the reflection reconstruction network introduces a residual network structure to improve the contrast adjustment of light components. Finally, the processed illumination and reflection components are fused based on Retinex theory to obtain enhanced images, which achieve contrast enhancement and detail enhancement of underground mine images, overcoming the problems of detail loss, blurred edges, and lack of contrast and clarity of the enhanced image that exist in existing enhancement algorithms. Numerical experiments show that the proposed model can effectively enhance the texture details of the image while improving the contrast of underground mine images, and has good stability and robustness, which can well meet the needs of low-light image enhancement in coal mines

I/Q Imbalance and Imperfect SIC on Two-way Relay NOMA Systems

Abstract: Non-orthogonal multiple access (NOMA) system can meet the demands of ultra-high data rate, ultra-low latency, ultra-high reliability and massive connectivity of user devices (UE). However, the performance of the NOMA system may be deteriorated by the hardware impairments. In this paper, the joint effects of in-phase and quadrature-phase imbalance (IQI) and imperfect successive interference cancellation (ipSIC) on the performance of two-way relay cooperative NOMA (TWR C-NOMA) networks over the Rician fading channels are studied, where two users exchange information via a decode-and-forward (DF) relay. In order to evaluate the performance of the considered network, analytical expressions for the outage probability of the two users, as well as the overall system throughput are derived. To obtain more insights, the asymptotic outage performance in the high signal-to-noise ratio (SNR) region and the diversity order are analysed and discussed. Throughout the paper, Monte Carlo simulations are provided to verify the accuracy of our analysis. The results show that IQI and ipSIC have significant deleterious effects on the outage performance. It is also demonstrated that the outage behaviours of the conventional OMA approach are worse than those of NOMA. In addition, it is found that residual interference signals (IS) can result in error floors for the outage probability and zero diversity orders. Finally, the system throughput can be limited by IQI and ipSIC, and the system throughput converges to a fixed constant in the high SNR region

Tunable photochemical deposition of silver nanostructures on layered ferroelectric CuInP2_2S6

2D layered ferroelectric materials such as CuInP$_2$S6 (CIPS) are promising candidates for novel and high-performance photocatalysts, owning to their ultrathin layer thickness, strong interlayer coupling, and intrinsic spontaneous polarization, while how to control the photocatalytic activity in layered CIPS remains unexplored. In this work, we report for the first time the photocatalytic activity of ferroelectric CIPS for the chemical deposition of silver nanostructures (AgNSs). The results show that the shape and spatial distribution of AgNSs on CIPS are tunable by controlling layer thickness, environmental temperature, and light wavelength. The ferroelectric polarization in CIPS plays a critical role in tunable AgNS photodeposition, as evidenced by layer thickness and temperature dependence experiments. We further reveal that AgNS photodeposition process starts from the active site creation, selective nanoparticle nucleation/aggregation, to the continuous film formation. Moreover, AgNS/CIPS heterostructures prepared by photodeposition exhibit excellent resistance switching behavior and good surface enhancement Raman Scattering activity. Our findings provide new insight into the photocatalytic activity of layered ferroelectrics and offer a new material platform for advanced functional device applications in smart memristors and enhanced chemical sensors.Comment: 18 pages, 5 figure

Pirfenidone Inhibits Cell Proliferation and Collagen I Production of Primary Human Intestinal Fibroblasts

Intestinal fibrosis is a common complication of inflammatory bowel disease. So far, there is no safe and effective drug for intestinal fibrosis. Pirfenidone is an anti-fibrotic compound available for the treatment of idiopathic pulmonary fibrosis. Here, we explored the anti-proliferative and anti-fibrotic properties of pirfenidone on primary human intestinal fibroblasts (p-hIFs). p-hIFs were cultured in the absence and presence of pirfenidone. Cell proliferation was measured by a real-time cell analyzer (xCELLigence) and BrdU incorporation. Cell motility was monitored by live cell imaging. Cytotoxicity and cell viability were analyzed by Sytox green, Caspase-3 and Water Soluble Tetrazolium Salt-1 (WST-1) assays. Gene expression of fibrosis markers was determined by quantitative reverse transcription PCR (RT-qPCR). The mammalian target of rapamycin (mTOR) signaling was analyzed by Western blotting and type I collagen protein expression additionally by immunofluorescence microscopy. Pirfenidone dose-dependently inhibited p-hIF proliferation and motility, without inducing cell death. Pirfenidone suppressed mRNA levels of genes that contribute to extracellular matrix production, as well as basal and TGF-beta 1-induced collagen I protein production, which was associated with inhibition of the rapamycin-sensitive mTOR/p70S6K pathway in p-hIFs. Thus, pirfenidone inhibits the proliferation of intestinal fibroblasts and suppresses collagen I production through the TGF-beta 1/mTOR/p70S6K signaling pathway, which might be a novel and safe anti-fibrotic strategy to treat intestinal fibrosis

Decentralized Energy Management of Networked Microgrid Based on Alternating-Direction Multiplier Method

With the ever-intensive utilization of distributed generators (DGs) and smart devices, distribution networks are evolving from a hierarchal structure to a distributed structure, which imposes significant challenges to network operators in system dispatch. A distributed energy-management method for a networked microgrid (NM) is proposed to coordinate a large number of DGs for maintaining secure and economic operations in the electricity-market environment. A second-order conic programming model is used to formulate the energy-management problem of an NM. Network decomposition was first carried out, and then a distributed solution for the established optimization model through invoking alternating-direction method of multipliers (ADMM). A modified IEEE 33-bus power system was finally utilized to demonstrate the performance of distributed energy management in an NM

Joint Impact of Hardware Impairments and Imperfect Channel State Information on Multi-Relay Networks

In this paper, we investigate the performance of dual-hop (DH) decode-and-forward (DF) multi-relay networks, for which two practical deleterious factors are taken into account, namely hardware impairments (HIs) and imperfect channel state information (ICSI). The communication between the source and the destination is realized with the aid of DF multi-relays, where both hops are assumed to be independent but non-identically distributed α-μ fading. Aiming at improving the system performance, three representative relay selection strategies are considered, in which the best relay is selected according to the link quality of source-to-relay and/or relay-to-destination. To characterize the performance of the proposed strategies, two key performance metrics, namely outage probability (OP) and ergodic capacity (EC), are analyzed insightfully. We first derive closed-form expressions for both exact and asymptotic OPs. Utilizing the derived results, diversity orders achieved at the destinations are obtained. We demonstrate that the OPs of considered networks are limited by HIs and ICSI, and the diversity orders are zeros due to the presence of ICSI. Then, we study the ECs of the proposed relay selection schemes, and upper bounds for the EC and asymptotic expressions for the EC in the high signal-to-noise ratio (SNR) regime are derived. To obtain more insights, the affine expansions for the EC are involved by two metrics of high-SNR slope and highSNR power offset. It is shown that there are rate ceilings for the EC due to HIs and ICSI, which result in zero high-SNR slopes and finite high-SNR power offsets

Secure Analysis of Multi-Antenna NOMA Networks Under I/Q Imbalance

This paper investigates the reliability and security performance of the downlink non-orthogonal multiple access (NOMA) networks over Nakagami-m fading channels, where the base station (BS) aims to communicate with multi-antenna NOMA users in the presence of a multi-antenna eavesdropper. To be more practical, a detrimental factor at both transmitter and receiver is considered, namely in-phase and quadrature-phase imbalance (IQI). To further improve the reliability and security of the considered networks, the selection combining (SC) algorithm at the receiver is taken into account. More specifically, the exact analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived in closed-form. To obtain a better understanding of the influence for the IQI parameters on the system performance, the asymptotic behaviors for the outage probabilities (OPs) in the high signal-to-noise ratio (SNR) region are analyzed. Based on the asymptotic results, the diversity order of the considered system are obtained and discussed. The numerical results are presented to verify the validity of the theoretical analysis