Feature Grouping and Sparse Principal Component Analysis

Sparse Principal Component Analysis (SPCA) is widely used in data processing and dimension reduction; it uses the lasso to produce modified principal components with sparse loadings for better interpretability. However, sparse PCA never considers an additional grouping structure where the loadings share similar coefficients (i.e., feature grouping), besides a special group with all coefficients being zero (i.e., feature selection). In this paper, we propose a novel method called Feature Grouping and Sparse Principal Component Analysis (FGSPCA) which allows the loadings to belong to disjoint homogeneous groups, with sparsity as a special case. The proposed FGSPCA is a subspace learning method designed to simultaneously perform grouping pursuit and feature selection, by imposing a non-convex regularization with naturally adjustable sparsity and grouping effect. To solve the resulting non-convex optimization problem, we propose an alternating algorithm that incorporates the difference-of-convex programming, augmented Lagrange and coordinate descent methods. Additionally, the experimental results on real data sets show that the proposed FGSPCA benefits from the grouping effect compared with methods without grouping effect.Comment: 21 pages, 5 figures, 2 table

Establishment of a Numerical Model for Sulfate Attacked Concrete Considering Multi-factors

Sulfate attack is one of the major durability problems of concrete structures, which is manifested by expansive cracks and deterioration of cement paste. In this study, a numerical model is proposed to predict the process of ionic diffusion into concrete under external sulfate attack. The chemical reaction and diffusion processes are considered in this model. Furthermore, the influence of calcium leaching, chemical activity of multi-ions, temperature and changes in porosity are also taken into account. The initial porosity and tortuosity are assumed to be homogeneous in concrete, and the chemical potential gradient is regarded as the driving force for ions migrating in pore solution. The modified Davies equation is employed to quantize interaction effect among different ions in solution. A temperature dependent parameter is introduced in the diffusion process of sulfate ion. The dissolution of solid calcium is divided into two stages referring to solid-liquid equilibrium curve of calcium ion. One is the dissolution of the calcium hydroxide, and the other is the decalcification of the calcium silicate hydrate. The influence of calcium leaching on porosity is further considered in diffusion coefficient. Moreover, changes in porosity due to formation of expansive ettringite are also reflected in the diffusion coefficient. Finally, a new numerical model is established and a comparison of the model prediction with the experimental results has been conducted. It is demonstrated that the established diffusion-reaction model can provide a better deterioration assessment of concrete structures exposed to sulfate attack

Blockchain and Sustainability: A Tertiary Study

Blockchain is an emerging technology with potential to address issues related to sustainability. Literature reviews on blockchain and sustainability exist, but there is a need to consolidate existing results, in particular, in terms of Sustainable Development Goals (SDG). This extended abstract presents an ongoing tertiary study based on existing literature reviews to investigate the relationship between blockchain and sustainability in terms of SDGs. Results from a pilot analysis of 18 reviews using thematic analysis are presented.Comment: Accepted by BoKSS 2021, to be published by IEE

A Contrastive Study on Dynamic Evolution of Users\u27 Relationship Network in Online Health Community based on Stochastic Actor-oriented Model

Online health community can break the limitations of time and space to provide medical and health information for users, meanwhile can promote the formation and evolution of friendships between users. This paper takes the largest diabetes community in China - Sweet Home as the research, and uses the dynamic social network analysis, which is based on stochastic actor-oriented models, to study the impact of individual attributes and network structure on the evolution of users\u27 friendships. It is found that in sub-forums that highly relate to diabetes, basic user attributes such as gender, age, and disease type have significant impacts on the formation of relationships, while in sub-forum of sharing and accompanying, the detailed attributes such as the number of friends, online time, bonus points have a significant impact on the formation of relationships. However, transitive triads have no significant influences on the formation of friends

Enhanced physicochemical and functional properties of pea (Pisum sativum) protein by pH-shifting and ultrasonication combined process

In recent years, pea protein as a novel food ingredient has drawn increasing attention due to its high nutritional value, hypoallergenic, and low price. As an amphiphilic molecule, protein is known as a natural and bio-safe emulsifier. However, similar to other legume proteins, the low water solubility and poor functional properties of pea protein limit its applications in the food industry. This study was undertaken to investigate the effects of pH-shifting in combination with ultrasonication on the structural and physicochemical properties of pea protein isolate (PPI). PPI dispersions (30 mg/ml each) were treated with ultrasonication, pH-shifting, and pH-shifting in combination with ultrasound and compared to control (no treatment). Water solubility, particle size, solution turbidity, surface hydrophobicity, free sulfhydryl group content, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) of the soluble pea protein obtained by the above treatments were determined. The PPI samples (10 mg/ml) treated with pH-shifting at pH 12 in combination with ultrasound (pH12+U5), which had highest solubility, were used to prepare nanoemulsions (0.25% oil) and nanocomplexes loaded with vitamin D3 (VD3). Storage stability, photooxidation protective ability, and morphological structure of the PPI-stabilized nano-systems were examined. The pH12+U5 treatment increased the solubility of PPI from 8.17% (Control) to 60.83%, and reduced the volume-weighted mean diameters D [4, 3] of the soluble protein aggregates from 206.9 (Control) to 45.2 nm. The surface hydrophobicity of the pH12+U5-treated PPI was significantly higher than that of the native protein, while its free sulfhydryl group content was slightly decreased. Structural rearrangement of the treated PPI was observed in the SDS-PAGE, showing that the alkaline pH-shifting and ultrasonic treatment can disrupt covalent and non-covalent bonds. Even though there was no significant improvement in the antioxidant activity of the pH12+U5-processed protein compared to the native PPI, it exhibited good radical scavenging ability. After exposure to UV-light (312 nm, 15 W) for 180 minutes, the VD3 retained in the PPI-based nanoemulsion and nanocomplex was 74.22% and 65.37%, respectively, in contrast to 8.71% in the Control, demonstrating a good photooxidation protection ability of the nano-structures. Besides, the D [4, 3] of the droplets in the nanoemulsion and nanocomplex stabilized by the pH12+U5-treated PPI were 113.93 and 88.90 nm, respectively, and both nano-systems exhibited good stability during storage for 30 days. In summary, the combination of pH-shifting and ultrasonication effectively improved the structural and physicochemical properties of pea protein isolate. The pea protein isolate processed with this new method would be a promising carrier to deliver and protect lipophilic bioactive components in food products, which could lead to foods with improved flavor, nutritional value, and shelf life