Hybrid deep learning models with multi-classification investor sentiment to forecast the prices of China's leading stocks.

The prediction of stock prices has long been a captivating subject in academic research. This study aims to forecast the prices of prominent stocks in five key industries of the Chinese A-share market by leveraging the synergistic power of deep learning techniques and investor sentiment analysis. To achieve this, a sentiment multi-classification dataset is for the first time constructed for China's stock market, based on four types of sentiments in modern psychology. The significant heterogeneity of sentiment changes in the sectors' leading stock markets is trained and mined using the Bi-LSTM-ATT model. The impact of multi-classification investor sentiment on stock price prediction was analyzed using the CNN-Bi-LSTM-ATT model. It finds that integrating sentiment indicators into the prediction of industry leading stock prices can enhance the accuracy of the model. Drawing upon four fundamental sentiment types derived from modern psychology, our dataset provides a comprehensive framework for analyzing investor sentiment and its impact on forecasting the stock prices of China's A-share market.

The Risk Contagion between Chinese and Mature Stock Markets: Evidence from a Markov-Switching Mixed-Clayton Copula Model.

Exploring the risk spillover between Chinese and mature stock markets is a promising topic. In this study, we propose a Markov-switching mixed-Clayton (Ms-M-Clayton) copula model that combines a state transition mechanism with a weighted mixed-Clayton copula. It is applied to investigate the dynamic risk dependence between Chinese and mature stock markets in the Americas, Europe, and Asia-Oceania regions. Additionally, the conditional value at risk (CoVaR) is applied to analyze the risk spillovers between these markets. The empirical results demonstrate that there is mainly a time-varying but stable positive risk dependence structure between Chinese and mature stock markets, where the upside and downside risk correlations are asymmetric. Moreover, the risk contagion primarily spills over from mature stock markets to the Chinese stock market, and the downside effect is stronger. Finally, the risk contagion from Asia-Oceania to China is weaker than that from Europe and the Americas. The study provides insights into the risk association between emerging markets, represented by China, and mature stock markets in major regions. It is significant for investors and risk managers, enabling them to avoid investment risks and prevent risk contagion.

Market Efficiency and Cross-Correlations of Chinese New Energy Market with Other Assets: Evidence from Multifractality Analysis.

Despite the upgrading of the attention and investment of new energy in Chinese public, its market efficiency and associations with other assets are relatively rarely explored. This paper, firstly, explores the multifractal feature and market efficiency of Chinese new energy market (NEI) by the multifractal detrended fluctuation analysis. Secondly, the multifractal cross-correlation analysis is performed to discuss the multifractality of cross-correlations between NEI and crude oil, external new energy indices (Global (SPGCE), United States (ECO) and Europe (ERIX)) and safe-haven asset (GOLD) respectively. The results show that Chinese new energy market has obvious multifractality with low market efficiency, which is mainly sourced from long-range correlation. It has the strongest linkages with external new energy markets and most insignificant association with gold. The heterogeneous sources contribute to their multifractal cross-correlations. It provides useful enlightenment for decision-makers to implement energy policy and reform, and for investors to make investment decisions.

Mining the Roles of Wheat (Triticum aestivum) SnRK Genes in Biotic and Abiotic Responses.

Sucrose non-fermenting-1-related protein kinases (SnRKs) play vital roles in plant growth and stress responses. However, little is known about the SnRK functions in wheat. In this study, 149 TaSnRKs (wheat SnRKs) were identified and were divided into three subfamilies. A combination of public transcriptome data and real-time reverse transcription-polymerase chain reaction (qRT-PCR) analysis revealed the distinct expression patterns of TaSnRKs under various abiotic and biotic stresses. TaSnRK2.4-B, a member of SnRK2s, has different expression patterns under polyethylene glycol (PEG), sodium chloride (NaCl) treatment, and high concentrations of abscisic acid (ABA) application. Yeast two-hybrid assay indicated that TaSnRK2.4-B could interact with the SnRK2-interacting calcium sensor (SCS) in wheat and play a role in the ABA-dependent pathway. Moreover, TaSnRK2.4-B might be a negative regulator in wheat against pathogen infection. The present study provides valuable information for understanding the functions of the TaSnRK family and provides recommendations for future genetic improvement in wheat stress resistance.

Investigation and Genome-Wide Association Analysis of Fusarium Seedling Blight Resistance in Chinese Elite Wheat Lines.

Fusarium seedling blight (FSB) is an important disease of wheat occurring as part of the Fusarium disease complex consisting also of Fusarium head blight (FHB). 240 Chinese elite cultivars and lines were evaluated in greenhouse experiments for FSB resistance and genotyped using the wheat 90 K single nucleotide polymorphism arrays. Among them, 23 accessions had an average lesion length of less than 0.6 cm, exhibiting potential for breeding for FSB resistance in wheat. Jingfumai 1 and Yangmai 11 had a relatively high resistance to both FSB and FHB simultaneously. Six relatively stable quantitative trait loci (QTLs) were detected on chromosome arms 1DL, 3AS, 3BL, 6BL, 7AL, and Un using the mixed linear model approach, interpreting 4.83-7.53% of phenotypic variation. There was a negative correlation between the average FSB lesion length and the BLUE FHB index with a low coefficient, and resistance to both diseases appeared to be conferred by different QTLs across the same population. Four KASP markers were detected on 1DL, 3AS, 3BL, and 6BL in QTLs to facilitate marker-assisted selection. Combined with transcriptome data analysis, eight defense-related genes were considered as candidates for mapping QTLs. The resistant elite germplasm, mapped QTLs, and KASP markers developed in this study are useful resources for enhancing Fusarium seedling blight in wheat breeding.

Crude oil prices and volatility prediction by a hybrid model based on kernel extreme learning machine.

In view of the important position of crude oil in the national economy and its contribution to various economic sectors, crude oil price and volatility prediction have become an increasingly hot issue that is concerned by practitioners and researchers. In this paper, a new hybrid forecasting model based on variational mode decomposition (VMD) and kernel extreme learning machine (KELM) is proposed to forecast the daily prices and 7-day volatility of Brent and WTI crude oil. The KELM has the advantage of less time consuming and lower parameter-sensitivity, thus showing fine prediction ability. The effectiveness of VMD-KELM model is verified by a comparative study with other hybrid models and their single models. Except various commonly used evaluation criteria, a recently-developed multi-scale composite complexity synchronization (MCCS) statistic is also utilized to evaluate the synchrony degree between the predictive and the actual values. The empirical results verify that 1) KELM model holds better performance than ELM and BP in crude oil and volatility forecasting; 2) VMD-based model outperforms the EEMD-based model; 3) The developed VMD-KELM model exhibits great superiority compared with other popular models not only for crude oil price, but also for volatility prediction.

Function and Characterization Analysis of BodoOBP8 from Bradysia odoriphaga (Diptera: Sciaridae) in the Recognition of Plant Volatiles and Sex Pheromones.

The belowground pest Bradysia odoriphaga (Diptera: Sciaridae) has a sophisticated and sensitive olfactory system to detect semiochemical signals from the surrounding environment. In particular, odorant-binding proteins (OBPs) are crucial in capturing and transporting these semiochemical signals across the sensilla lymph to the corresponding odorant receptors. In this study, we cloned a full-length cDNA sequence of BodoOBP8 from B. odoriphaga. Real-time PCR (qRT-PCR) analysis revealed that BodoOBP8 has the highest expression levels in males, with more pronounced expression in the male antennae than in other tissues. In this study, the recombinant protein BodoOBP8 was successfully expressed by a bacterial system to explore its function. Competitive binding assays with 33 host plant volatiles and one putative sex pheromone (n-heptadecane) revealed that purified BodoOBP8 strongly bound to two sulfur compounds (methyl allyl disulfide and diallyl disulfide) and to n-heptadecane; the corresponding dissolution constants (Ki) were 4.04, 6.73, and 4.04 µM, respectively. Molecular docking indicated that Ile96, Ile103, Ala107, and Leu111, located in the hydrophobic cavity of BodoOBP8, are the key residues mediating the interaction of BodoOBP8 with two sulfur compounds (methyl allyl disulfide and diallyl disulfide) and n-heptadecane. These results show that BodoOBP8 plays a role in the recognition of plant volatiles and sex pheromones, suggesting its application as a molecular target for the screening of B. odoriphaga attractants and repellents and facilitating a new mechanism of B. odoriphaga control.

Genome-wide identification of ZF-HD gene family in Triticum aestivum: Molecular evolution mechanism and function analysis.

ZF-HD family genes play important roles in plant growth and development. Studies about the whole genome analysis of ZF-HD gene family have been reported in some plant species. In this study, the whole genome identification and expression profile of the ZF-HD gene family were analyzed for the first time in wheat. A total of 37 TaZF-HD genes were identified and divided into TaMIF and TaZHD subfamilies according to the conserved domain. The phylogeny tree of the TaZF-HD proteins was further divided into six groups based on the phylogenetic relationship. The 37 TaZF-HDs were distributed on 18 of 21 chromosomes, and almost all the genes had no introns. Gene duplication and Ka/Ks analysis showed that the gene family may have experienced powerful purification selection pressure during wheat evolution. The qRT-PCR analysis showed that TaZF-HD genes had significant expression patterns in different biotic stress and abiotic stress. Through subcellular localization experiments, we found that TaZHD6-3B was located in the nucleus, while TaMIF4-5D was located in the cell membrane and nucleus. Our research contributes to a comprehensive understanding of the TaZF-HD family, provides a new perspective for further research on the biological functions of TaZF-HD genes in wheat.

A hybrid model combining variational mode decomposition and an attention-GRU network for stock price index forecasting.

In this paper we introduce a new hybrid model based on variational mode decomposition (VMD) and Gated Recurrent Units (GRU) network improved by attention mechanism to enhance the accuracy of stock price indices forecasting. In the process of establishing the model, VMD is made a use to decompose the primary series into some almost orthogonal subsequences. The attention mechanism is introduced into GRU to assign different weights to the input elements in advance so that better predictive results can be achieved for each component. In empirical experiment, London FTSE Index (FTSE) and Nasdaq Index (IXIC) are adopted to examine the performance of VMD-AttGRU model. Empirical results report that the developed hybrid model outperforms the single models and indeed raises the accuracy of stock price indices forecasting. In addition, the introduction of attention mechanism can increase the level predictive accuracy but decrease the correctness of direction forecasting.

Nonlinear Multiscale Entropy and Recurrence Quantification Analysis of Foreign Exchange Markets Efficiency.

The regularity of price fluctuations in exchange rates plays a crucial role in foreign exchange (FX) market dynamics. In this paper, we quantify the multiply irregular fluctuation behaviors of exchange rates in the last 10 years (November 2006-November 2016) of eight world economies with two nonlinear approaches. One is a recently proposed multiscale weighted permutation entropy (MWPE) and another is the typical quantification recurrence analysis (RQA) technique. Furthermore, we utilize the RQA technique to study the different intrinsic mode functions (IMFs) that represents different frequencies and scales of the raw time series via the empirical mode decomposition algorithm. Complexity characteristics of abundance and distinction are obtained in the foreign exchange markets. The empirical results show that JPY/USD (followed by EUR/USD) implies a a higher complexity and indicates relatively higher efficiency of the Japanese FX market, while some economies like South Korea, Hong Kong and China show lower and weaker efficiency of their FX markets. Meanwhile, it is suggested that the financial crisis enhances the market efficiency in the FX markets.

Financial Time Series Prediction Using Elman Recurrent Random Neural Networks.

In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices.

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system.

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

Differences and determinants in access to essential public health services in China: a case study with hypertension people and under-sixes as target population.

BACKGROUND: Since 2009, health reform had launched in China and essential public health services were provided for all residents to ensure service equity and accessibility, and to achieve sustained population-wide health improvement. This study aimed to investigate the differences and determinants among populations with different characteristics access to essential public health services in China, especially hypertension people and children aged 0-6 years. METHODS: A cross-sectional study with socio-demographic data analysis was undertaken to estimate distribution characteristics of receiving essential public health services of hypertension patients and children. Regular follow-ups and effective blood pressure control reflected the effective management for hypertension patients, and for children, public services provided were vaccination on schedule and regular physical check-up. Logistic regression was used to determine the predictors for effective management. RESULTS: A total of 1 505 hypertension patients and 749 children were involved; 39.14% of hypertension participants could control their blood pressure in the normal range, and the rate in urban areas (43.61%) was higher than that in rural (31.88%). And 34.68% of them could receive more than 4 times follow-ups by the medical technician. Of 754 children, 79.84% could receive the periodic physical examination and 98.40% had vaccinated regularly. Children living in rural areas were more likely to have regular check-ups (83.96%) and regular vaccination (nearly 99%). Overall, geographic location and education level were the determinants of people access to essential public health services. CONCLUSIONS: Implementation of the health reform since 2009 has headed China's public health system in the right direction and promoted the improvement of public health system development. Our study highlights the growing needs for more public health services in China, and China's public health system needs to be greatly improved in terms of its quality and accessibility.

[Expression of cyclooxygenase-2 and relationship with mismatch repair gene and microsatellite instability in hereditary non-polyposis colorectal cancer].

OBJECTIVE: To investigate the expression of Cyclooxygenase (COX)-2 and the relationship between cox-2, mismatch repair gene (MMR) proteins and microsatellite instability (MSI) in HNPCC. METHODS: Twenty-eight cases of adenomas and 14 cases of carcinomas were collected from 33 HNPCC families patients by colonoscopy. Sporadic adenomas (n = 32) and carcinomas (n = 24) were used as a control group. The expressions of COX-2 and mismatch repair gene hMLH1, hMSH2, hMSH6 proteins were examined by immunohistochemistry. MS1 were analyzed by using PCR with BAT25, BAT26, D2S123, D5S346 and D17S250 loci. RESULTS: The COX-2 high-expression rates were 53.6% (15/28) and 42.9% (6/14) in HNPCC adenomas and carcinomas, and were 62.5% (20/32) and 91.7% (22/24) in sporadic adenomas and carcinomas. COX-2 expression was lower in HNPCC carcinomas than that of sporadic carcinomas (P < 0.05). MMR deficiency rate and positive rate of MSI-H were both 71.4% (10/14) respectively in HNPCC carcinomas. It was higher than that in sporadic colorectal carcinomas [both 12.5% (3/24)]. Eight (80.0%) COX-2 low-expression were observed in 10 HNPCC carcinomas with MMR-deficient system while 4 cox-2 high-expression cases were observed in 4 HNPCC carcinomas with MMR-proficient system. COX-2 expression was lower in HNPCC carcinomas and adenomas, sporadic carcinomas with MMR-deficient system than that of MMR-proficient (P < 0.05). The COX-2 low-expression rates were 80.0% (8/10), 66.7% (12/18) and 66.7% (2/3) in HNPCC adenomas, HNPCC carcinomas and sporadic carcinomas with MSI-H. Cox-2 expression was lower in HNPCC and sporadic carcinomas (adenocarcinomas) with MSI-H than that of MSS (P < 0.05). CONCLUSION: Compared with sporadic carcinomas, the COX-2 expression was lower in HNPCC carcinomas. There was negative correlation between COX-2 expression and MMR-deficient (MSI-H). The detection of COX-2, MMR protein and MSI is of important significance in further studying the pathogenesis and interventional therapy of colorectal neoplasms.

[Mutation of hMLH1 and hMSH2 genes in hereditary nonpolyposis colorectal cancer: analysis of 76 probands].

OBJECTIVE: To investigate the mutations of the mismatch repair genes hMLH1 and hMSH2 in hereditary nonpolyposis colorectal cancer (HNPCC). METHODS: The DNA samples of 76 probands of HNPCC families underwent PCR amplification and sequencing on 35 exons in hMLH1 and hMSH2 genes. RESULTS: (1) The overall mutation rate of the hMLH1 and hMSH2 genes was 33% (25/76). (2) 22 mutations were found, 16 in the hMLH1 gene and 6 in the hMSH2 gene. (3) The spectrum of mutation type included frame shift, nonsense, splice site, and missense mutations. Missense mutation was the most common mutation type. CONCLUSION: The hMLH1 and hMSH2 mutations in Chinese HNPCC families show a wide spectrum. It seems that hMLH1 gene is involved more frequently than hMSH2 gene. A certain number of HNPCC families can be benefited from the genetic screening for mutation of the mismatch repair genes.