Improving Polarity Classification for Financial News Using Semantic Similarity Techniques

This article discusses polarity classification for financial news articles. The proposed Semantic Sentiment Analyser makes use of semantic similarity techniques, sentiment composition rules, and the Positivity/Negativity (P/N) ratio in performing polarity classification. An experiment was conducted to compare the performance of three semantic similarity metrics namely HSO, LESK, and LIN to find the semantically similar pair of word as the input word. The best similarity technique (HSO) is incorporated into the sentiment analyser to find the possible polarity carrier from the analysed text before performing polarity classification. The performance of the proposed Semantic Sentiment Analyser was evaluated using a set of manually annotated financial news articles. The results obtained from the experiment showed that the proposed SSA was able to achieve an F-Score of 90.89% for all cases classification

Improving the Accuracy of Stock Price Prediction using Ensemble Neural Network.

This paper describes performance of different classifiers (established/combinations/new prediction methods) that are used in predicting stock price. Artificial Neural Network (ANN) was chosen as the target candidates for the forecasting model in this work because of its ability to solve complex problems such as the stock price prediction. We experimented three types of neural network namely Feed Forward Neural Network (FFNN), Elman Recurrent Neural Network (ERNN), Jordan Recurrent Neural Network (JRNN) and compared their predictions’ accuracy. We then designed an ensemble neural network that combined FFNN, JRNN and ERNN using bagging method to build a more accurate predictive model. Based on the results obtained, our proposed ENN outperformed the other ANNs by achieving the highest prediction’s accuracy

Aim and shoot: molecule-imprinting polymer coated MoO3 for selective SERS detection and photocatalytic destruction of low-level organic contaminants

A sensitive and selective SERS sensor with easy and excellent recyclability is highly demanded because of its great potential application in complex detection environments. Here, using methylene blue (MB) as a model target, a semiconductor-based SERS substrate composed of a MoO3 nanorod core and a uniform molecule-imprinting polymethacrylic acid shell (MIP) with a thickness of 4 nm was designed and fabricated (MoO3@MIP) to achieve selective detection. The key to the successful coating of the ultrathin uniform MIP shell lies in the pretreatment of a MoO3 core with nitric acid, providing sufficient surficial hydroxyls for the anchoring of a polymer precursor. The molecule-imprinted voids for MB were formed simply via light irradiation as a result of photocatalytic degradation by a MoO3 semiconductor. This core–shell MIP composite shows a high SERS selectivity towards low-level MB in a mixed MB/CV solution. The enhanced factor (EF) is high, at 1.6 × 104. More importantly, the selective detection allows the further photocatalytic recycling of MoO3@MIP in an “aim-and-shoot” way, which well preserves the detection selectivity and sensitivity towards MB at least for 4 cycles. Based on decreased sensitivity with the increasing shell thickness (10–24 nm), a MIP-gating charge transfer mechanism is proposed to demonstrate the high EF instead of the molecule-enrichment effect. This “aim-and-shoot” strategy is expected to push forward the prosperous application of selective SERS for trace detection in versatile environments

Cloning and Characterization of a Putative TAC1 Ortholog Associated with Leaf Angle in Maize (Zea mays L.)

BACKGROUND: Modifying plant architecture to increase photosynthesis efficiency and reduce shade avoidance response is very important for further yield improvement when crops are grown in high density. Identification of alleles controlling leaf angle in maize is needed to provide insight into molecular mechanism of leaf development and achieving ideal plant architecture to improve grain yield. METHODOLOGY/PRINCIPAL FINDINGS: The gene cloning was done by using comparative genomics, and then performing real-time polymerase chain reaction (RT-PCR) analysis to assay gene expression. The gene function was validated by sequence dissimilarity analysis and QTL mapping using a functional cleaved amplified polymorphism (CAP). CONCLUSIONS: The leaf angle is controlled by a major quantitative trait locus, ZmTAC1 (Zea mays L. Leaf Angle Control 1). ZmTAC1 has 4 exons encoding a protein with 263 amino acids, and its domains are the same as those of the rice OsTAC1 protein. ZmTAC1 was found to be located in the region of qLA2 by using the CAP marker and the F(2:3) families from the cross between Yu82 and Shen137. Real-time PCR analysis revealed ZmTAC1 expression was the highest in the leaf-sheath pulvinus, less in the leaf and shoot apical meristem, and the lowest in the root. A nucleotide difference in the 5'-untranslated region (UTR) between the compact inbred line Yu82 ("CTCC") and the expanded inbred line Shen137 ("CCCC") influences the expression level of ZmTAC1, further controlling the size of the leaf angle. Sequence verification of the change in the 5'-UTR revealed ZmTAC1 with "CTCC" was present in 13 compact inbred lines and ZmTAC1 with "CCCC" was present in 18 expanded inbred lines, indicating ZmTAC1 had been extensively utilized in breeding with regard to the improvement of the maize plant architecture

In Vitro Study of the Effects of Angiostrongylus cantonensis Larvae Extracts on Apoptosis and Dysfunction in the Blood-Brain Barrier (BBB)

It has been hypothesized that blood-brain barrier (BBB) dysfunction in Angiostrongylus cantonensis infection might be due to the apoptosis of the hosts' BBB cells. Here, we evaluated this hypothesis through several methods, all based on an in vitro mouse BBB model consisting of primary culture brain microvascular endothelial cells (BMECs) and brain astrocytic cells (BACs). In the present study, a four-hour percolation and HRP permeability experiment showed that A. cantonensis larvae extracts can increase the permeability of the BBB. Apoptosis among BMECs and BACs after exposure to larvae extracts was monitored by TUNEL and annexin-V-FITC/PI double staining. A. cantonensis larvae extracts were found to induce apoptosis in both BMECs and BACs. For this reason, we concluded that the induction of apoptosis might participate in the BBB dysfunction observed during angiostrongyliasis. Improved fundamental understanding of how A. cantonensis induces apoptosis may lead to new approaches to the treatment or prevention of this parasitic disease

The relationship between the symptoms of female gonococcal infections and serum progesterone level and the genotypes of Neisseria gonorrhoeae multi-antigen sequence type (NG-MAST) in Wuhan, China

The objective of this investigation was to study the relationship between the symptoms of female gonococcal infections and serum progesterone level and the genotypes of Neisseria gonorrhoeae multi-antigen sequence type (NG-MAST) in Wuhan, China. Eighty-one strains of N. gonorrhoeae were harvested from the vaginal discharge of 975 adult females in Wuhan and were genotyped by using NG-MAST. Serum progesterone (P) and estradiol (E2) levels were measured by radio immunoassay (RIA) in 39 gonorrhea-infected patients with slight symptoms (asymptomatic group) and 42 patients with conspicuous symptoms (symptomatic group). The average levels of serum progesterone in the asymptomatic group were significantly higher than in the symptomatic group (p < 0.05), while no significant difference was found in serum estradiol between the two groups. Of 81 wild-type isolates, 50 NG-MAST sequence types were associated with female infections in Wuhan, and N. gonorrhoeae ST2951, ST735, and ST436 were principally found in asymptomatic patients. ST809 and ST369, however, were mainly detected in asymptomatic female subjects. Gonococcal genetic island (GGI)-positive and GGI-negative strains were found in both the asymptomatic group and the symptomatic group. In females with gonococcal infection, high serum progesterone level is associated with the absence of symptoms, but no association was revealed between genotypes and the presence of symptoms. The GGI bears no relation to the absence of symptoms in the patients

Study on Growth Kinetics of CdSe Nanocrystals with a New Model

A model which involves both bulk diffusion process and surface reaction process has been developed for describing the growth behaviour of nanoparticles. When the model is employed, hypothesising that either of the processes alone dominates the overall growth process is unnecessary. Conversely, the relative magnitude of contributions from both processes could be obtained from the model. Using this model in our system, the growth process of CdSe QDs demonstrated two different growth stages. During the first stage, the growth of CdSe QDs was dominated by bulk diffusion, whereas, neither the bulk diffusion process nor the surface reaction process could be neglected during the later stage. At last, we successfully modelled the Ostwald ripening of CdSe QDs with LSW theories