A vector space model approach to social relation extraction from text corpus

Social network analysis (SNA) is significantly about research of social relations as well as structure in social environment. All the dependencies between people, organizations and environment constitute one or several networks. The author presented a vector space model (VSM) approach to extract and represent relations from text corpus. The approach employed VSM to represent the weight value of every social object's frequency in every text. It reflected the relationships between social objects and text corpus. Then the vector space is decomposed into a new vector space reflecting the relationships between social objects. It is concluded that the application of VSM can obtain deeper social relations hid in text and text corpus and increase the effect and efficiency of social network analysis of text corpus. © 2011 IEEE

A homogenisation pre-treatment for adherent and corrosion-resistant Ni electroplated coatings on Mg-alloy AZ91D

Multi-step Ni electroplatings were applied to AZ91D following the development of a homogenisation pre-treatment. The Ni coating was well adhered, as verified by thermal shock testing, and provided corrosion protection in 3.5. wt.% NaCl for 74. h at a coating thickness of ~15. μm. Being a cathodic coating, further protection in the presence of defects was not demonstrated herein, however realisation of quality Ni coatings on Mg is technologically important. To this end, achieving microstructural homogeneity on AZ91D is critical prior to plating or coating (such as electroless plating and chemical conversion coating) multi phase Mg-alloys. © 2013 Elsevier Ltd

Exact recovery of sparse signals with side information

AbstractCompressed sensing has captured considerable attention of researchers in the past decades. In this paper, with the aid of the powerful null space property, some deterministic recovery conditions are established for the previous $$ell _{1}$$ ℓ 1 –$$ell _{1}$$ ℓ 1 method and the $$ell _{1}$$ ℓ 1 –$$ell _{2}$$ ℓ 2 method to guarantee the exact sparse recovery when the side information of the desired signal is available. These obtained results provide a useful and necessary complement to the previous investigation of the $$ell _{1}$$ ℓ 1 –$$ell _{1}$$ ℓ 1 and $$ell _{1}$$ ℓ 1 –$$ell _{2}$$ ℓ 2 methods that are based on the statistical analysis. Moreover, one of our theoretical findings also shows that the sharp conditions previously established for the classical $$ell _{1}$$ ℓ 1 method

Evaluating quality of Chinese product reviews based on fuzzy logic

The prevalence of web2.0 makes e-Commerce an increasingly popular trend. Consumers can post their product reviews about product after buying products on the web. These product reviews can help online user make sensible decisions and enable business enterprises to improve their business strategies. To cope with the information overload problem, opinion mining is needed to extract useful expression and summarize important opinion for users. But the quality of product reviews at websites varies greatly. In this paper, we propose a method based fuzzy logic to evaluate the quality of Chinese product reviews. We define three fuzzy sets to represent the different types of product reviews. We determine the quality of product reviews under the proximity membership principle based the three fuzzy sets. Experiments based on an expert-composed product reviews corpus show that our method can achieve promising performance. © 2011 Springer-Verlag

Hypergraph regularized sparse feature learning

As an important pre-processing stage in many machine learning and pattern recognition domains, feature selection deems to identify the most discriminate features for a compact data representation. As typical feature selection methods, Lasso and its variants using the l1-norm based regularization have received much attention in recent years. However, most of existing l1-norm based sparse feature selection methods ignore the structure information of data or only consider the pairwise relationships among samples. In this paper, we propose a hypergraph regularized sparse feature learning method, where the high-order relationships among samples are modeled and incorporated into the learning process. Specifically, we first construct a hypergraph with multiple hyperedges to capture the high-order relationships among samples, followed by the computation of a hypergraph Laplacian matrix. Then, we propose a hypergraph regularization term, and a hypergraph regularized Lasso model. We conduct a series of experiments on a number of data sets from UCI machine learning repository, and two real-world neuroimaging based classification tasks. Experimental results demonstrate that the proposed method achieves promising classification results, compared with several well known feature selection approaches

Predictive information in corporate bond yields

We document strong evidence of the cross-sectional predictability of corporate bond returns based on a set of yield predictors that capture the information in the yields of past 1, 3, 6, 12, 24, 36, and 48 months. Return predictability is economically and statistically significant, and is robust to various controls. The uncovered predictability presents the most pronounced anomaly in the corporate bond literature that challenges rational pricing models

Population-based comparative analysis of differentially expressed genes between Kashin–Beck disease grades I and II

<p><b>Objectives</b>: To identify the differences and similarities of differentially expressed genes in peripheral blood mononuclear cells (PBMCs) between Kashin–Beck disease (KBD) grades I and II.</p> <p><b>Method</b>: In total, 100 patients with KBD and 100 healthy controls were selected from a KBD endemic area and divided into 100 pairs of KBD vs. controls (50 pairs of patients with KBD grade I and healthy controls, 50 pairs of patients with KBD grade II and healthy controls). RNA was isolated from KBD PBMCs and healthy control PBMCs. Microarray analysis was conducted to identify differentially expressed genes in the different stages of KBD. The microarray data obtained were further confirmed using quantitative real-time polymerase chain reaction (qRT-PCR).</p> <p><b>Results</b>: In total, eight differentially expressed genes in KBD grade I and 69 differentially expressed genes in KBD grade II were identified. Among these genes, six common genes were differentially expressed in both stages of the disease. The expression ratios of four common genes differed significantly between KBD grades I and II. Based on the expression ratios of the four genes, linear discriminant analysis (LDA) correctly classified the KBD grade (I or II) with 81% accuracy.</p> <p><b>Conclusions</b>: The similarities and differences of differentially expressed genes in PBMCs of patients with different stages of KBD may play an important role in the pathogenesis of the early phase of KBD. Additionally, six common genes may be considered blood-based genetic biomarkers for the detection and treatment of KBD.</p

Tailoring nickel coatings via electrodeposition from a eutectic-based ionic liquid doped with nicotinic acid

Pure nickel (Ni) was electrodeposited onto a copper (Cu) substrate from choline chloride-urea (1:2 molar ratio) eutectic-based ionic liquid (1:2 ChCl-urea IL) with 0-1200 mg/L additions of nicotinic acid (NA). The effect of NA on the voltammetric behavior of Ni (II) was investigated by cyclic voltammetry, whilst the nucleation/growth of Ni deposits was studied by chronoamperometry. The resultant surface morphologies and microstructures of the Ni coatings were revealed by SEM/EDXS, XRD and TEM, demonstrating that NA can inhibit, hence tailor, the Ni deposition and serve as a very effective brightener producing highly uniform and smooth Ni deposits. The nucleation/growth process of Ni was not affected by the presence of NA, proceeding via three-dimensional instantaneous nucleation. NA has a profound grain refining effect with a grain size of ∼4.2 nm achievable. © 2011 Elsevier B.V. All rights reserved

Peptides derived from lupin proteins confer potent protection against oxidative stress

BACKGROUND: Lupin seeds are rich in proteins, which are utilized in the food industry. There is an increased interest in lupin research due to its association with health-related benefits, such as reduction of hypertension and hyperglycemia. However, studies on the peptides derived from lupin proteins are rare. RESULTS: Lupin protein hydrolysates (LPHs) were prepared by proteolysis using alcalase, trypsin and pepsin, respectively. All the hydrolysates demonstrated higher antioxidant and angiotensin I-converting enzyme (ACE) inhibitory activities compared to lupin proteins. The hydrolysates were fractionated into three fractions based on molecular weight (MW), and the peptides with MW < 3 kDa (LPH3) had the highest antioxidant and ACE inhibitory activities compared to other fractions. Cell model study revealed that LPH3 fraction had the highest protection against the generation of reactive oxygen species in HepG2 cells, which was associated with increased activities of superoxide dismutase and glutathione peroxidase through upregulation of SOD1, GPX1, GCLM, SLC7A11 and SRXN1 expression. CONCLUSIONS: The analysis of amino acid composition indicated that the peptides were characterized with high content of hydrophobic amino acids, which may be responsible for the greatest antioxidant activity. This study highlights the promising potential of lupin peptides as a functional ingredient in healthy foods. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industr

Electrodeposition of chemically and mechanically protective Al-coatings on AZ91D Mg alloy

Electrodeposition of aluminium coatings upon AZ91D in aluminum chloride/1-ethyl-3-methylimidazolium chloride ionic liquid was achieved. Post-plating heat treatment processes compatible with AZ91D solution treatment (420°C) and aging treatment (200°C) were explored to improve coatings adhesion and hardness, and to maintain corrosion resistance. 420°C treatment produced a β-phase (Mg17Al12) enriched two-phase coating; whilst treatment at 200°C leads to a tri-layer structure, rich in γ-phase (Mg2Al3). The 200°C treatment was shown to be most effective for corrosion resistance, eradicating water reduction as the principal cathodic reaction and increasing surface hardness. © 2010 Elsevier Ltd