The Relationship Between Investor Sentiment and Stock Market Volatility: Based on the VAR Model

Using web crawling technology crawls investors’ comments of SANY stock(Stock Code: 600031) and Fujian Expressway stock(Stock Code: 600033) from February 11, 2015 to August 16, 2017. Then using semi-supervised machine learning method construct investor sentiment index. Moreover, collecting the daily closing stock price and trading volume data from Qianlong software explore the relationship between investor sentiment and stock market volatility based on VAR model and Granger Test Method. The results show that the rate of return and trading volume have a two-way Granger causality, while negative emotion and the rate of return have a one-way Granger causality. Furthermore, with the impulse response function and variance decomposition, the results show that trading volume has significant effects on rate of return and negative emotions of investors have significant negative effects on rate of return and trading volume

A Robust Integrated Multi-Strategy Bus Control System via Deep Reinforcement Learning

An efficient urban bus control system has the potential to significantly reduce travel delays and streamline the allocation of transportation resources, thereby offering enhanced and user-friendly transit services to passengers. However, bus operation efficiency can be impacted by bus bunching. This problem is notably exacerbated when the bus system operates along a signalized corridor with unpredictable travel demand. To mitigate this challenge, we introduce a multi-strategy fusion approach for the longitudinal control of connected and automated buses. The approach is driven by a physics-informed deep reinforcement learning (DRL) algorithm and takes into account a variety of traffic conditions along urban signalized corridors. Taking advantage of connected and autonomous vehicle (CAV) technology, the proposed approach can leverage real-time information regarding bus operating conditions and road traffic environment. By integrating the aforementioned information into the DRL-based bus control framework, our designed physics-informed DRL state fusion approach and reward function efficiently embed prior physics and leverage the merits of equilibrium and consensus concepts from control theory. This integration enables the framework to learn and adapt multiple control strategies to effectively manage complex traffic conditions and fluctuating passenger demands. Three control variables, i.e., dwell time at stops, speed between stations, and signal priority, are formulated to minimize travel duration and ensure bus stability with the aim of avoiding bus bunching. We present simulation results to validate the effectiveness of the proposed approach, underlining its superior performance when subjected to sensitivity analysis, specifically considering factors such as traffic volume, desired speed, and traffic signal conditions

With Brexit, inward investment will fall in the UK

Supply chains cross borders many times before components go into a final product in any EU country, write David Bailey, Nigel Driffield and Michail Karoglo

Identification and characterization of mRNAs and lncRNAs in the uterus of polytocous and monotocous Small Tail Han sheep (Ovis aries)

Background Long non-coding RNAs (lncRNAs) regulate endometrial secretion and uterine volume. However, there is little research on the role of lncRNAs in the uterus of Small Tail Han sheep (FecB++). Herein, RNA-seq was used to comparatively analyze gene expression profiles of uterine tissue between polytocous and monotocous sheep (FecB++) in follicular and luteal phases. Methods To identify lncRNA and mRNA expressed in the uterus, the expression of lncRNA and mRNA in the uterus of Small Tail Han sheep (FecB++) from the polytocous group (n = 6) and the monotocous group (n = 6) using RNA-sequencing and real-time polymerase chain reaction (RT-PCR). Identification of differentially expressed lncRNAs and mRNAs were performed between the two groups and two phases . Gene ontology (GO) and pathway enrichment analyses were performed to analyze the biological functions and pathways for the differentially expressed mRNAs. LncRNA-mRNA co-expression network was constructed to further analyses the function of related genes. Results In the follicular phase, 473 lncRNAs and 166 mRNAs were differentially expressed in polytocous and monotocous sheep; in the luteal phase, 967 lncRNAs and 505 mRNAs were differentially expressed in polytocous and monotocous sheep. GO and KEGG enrichment analysis showed that the differentially expressed lncRNAs and their target genes are mainly involved in ovarian steroidogenesis, retinol metabolism, the oxytocin signaling pathway, steroid hormone biosynthesis, and the Foxo signaling pathway. Key lncRNAs may regulate reproduction by regulating genes involved in these signaling pathways and biological processes. Specifically, UGT1A1, LHB, TGFB1, TAB1, and RHOA, which are targeted by MSTRG.134747, MSTRG.82376, MSTRG.134749, MSTRG.134751, and MSTRG.134746, may play key regulatory roles. These results offer insight into molecular mechanisms underlying sheep prolificacy

The small molecule luteolin inhibits N-acetyl-α-galactosaminyltransferases and reduces mucin-type O-glycosylation of amyloid precursor protein

Mucin-type O-glycosylation is the most abundant type of O-glycosylation. It is initiated by the members of the polypeptide N-acetyl-α-galactosaminyltransferase (ppGalNAc-T) family and closely associated with both physiological and pathological conditions, such as coronary artery disease or Alzheimer's disease. The lack of direct and selective inhibitors of ppGalNAc-Ts has largely impeded research progress in understanding the molecular events in mucin-type O-glycosylation. Here, we report that a small molecule, the plant flavonoid luteolin, selectively inhibits ppGalNAc-Ts in vitro and in cells. We found that luteolin inhibits ppGalNAc-T2 in a peptide/protein-competitive manner but not promiscuously (e.g. via aggregation-based activity). X-ray structural analysis revealed that luteolin binds to the PXP motif-binding site found in most protein substrates, which was further validated by comparing the interactions of luteolin with wild-type enzyme and with mutants using 1H NMR-based binding experiments. Functional studies disclosed that luteolin at least partially reduced production of β-amyloid protein by selectively inhibiting the activity of ppGalNAc-T isoforms. In conclusion, our study provides key structural and functional details on luteolin inhibiting ppGalNAc-T activity, opening up the way for further optimization of more potent and specific ppGalNAc-T inhibitors. Moreover, our findings may inform future investigations into site-specific O-GalNAc glycosylation and into the molecular mechanism of luteolin-mediated ppGalNAc-T inhibition.This work was supported by the National Basic Research Program of China Grants 2012CB822103 and 2011CB910603 (to Y. Z.); National High Technology Research and Development Program of China Grant 2012AA020203 (to Y. Z.); National Natural Science Foundation Grants 31170771 (to Y. Z.), 31370806 (to Y. Z.), and 31570796 (to Y. Z.); National Basic Research Program of China Grant 2012CB822103 (to F. W.); National Natural Science Foundation Grants 31270853 and 81102377 (to F. W.); Agencia Aragonesa para la Investigación y Desarrollo (ARAID), Ministerio de Economía y Competitividad, Grants CTQ2013-44367-C2-2-P and BFU2016-75633-P (to R. H.-G.); Diputación General de Aragón (DGA) Grant B89 (to R. H.-G.); and the EU Seventh Framework Programme (2007–2013) under BioStruct-X (Grant Agreement 283570 and BIOSTRUCTX 5186) (to R. H.-G.).Peer Reviewe

Genome-Wide Association Studies for Dynamic Plant Height and Number of Nodes on the Main Stem in Summer Sowing Soybeans

Plant height (PH) and the number of nodes on the main stem (NN) serve as major plant architecture traits affecting soybean seed yield. Although many quantitative trait loci for the two traits have been reported, their genetic controls at different developmental stages in soybeans remain unclear. Here, 368 soybean breeding lines were genotyped using 62,423 single nucleotide polymorphism (SNP) markers and phenotyped for the two traits at three different developmental stages over two locations in order to identify their quantitative trait nucleotides (QTNs) using compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) approaches. As a result, 11 and 13 QTNs were found by CMLM to be associated with PH and NN, respectively. Among these QTNs, 8, 3, and 4 for PH and 6, 6, and 8 for NN were found at the three stages, and 3 and 6 were repeatedly detected for PH and NN. In addition, 34 and 30 QTNs were found by mrMLM to be associated with PH and NN, respectively. Among these QTNs, 11, 13, and 16 for PH and 11, 15, and 8 for NN were found at the three stages. A majority of these QTNs overlapped with the previously reported loci. Moreover, one QTN within the known E2 locus for flowering time was detected for the two traits at all three stages, and another that overlapped with the Dt1 locus for stem growth habit was also identified for the two traits at the mature stage. This may explain the highly significant correlation between the two traits. Our findings provide evidence for mixed major plus polygenes inheritance for dynamic traits and an extended understanding of their genetic architecture for molecular dissection and breeding utilization in soybeans