16,130 research outputs found
Social inclusion of Chinese immigrants in Portugal: The roles of length of residence and social networks
Focusing on Chinese immigrants, this study investigated the role of length of residence and social networks on social inclusion, which we operationalized as psychological adaptation, socio-cultural adaptation, economic adaptation and political participation in the Portuguese society. The study found that:(a) Chinese immigrants’ overall social networks was positively correlated with psychological adaptation and socio-cultural adaptation; (b)Chinese immigrants’ length of residence in the host society was positively related to psychological adaptation and socio-cultural adaptation; (c) The overall social networks but not differentiated networks mediated the relationship between immigrants’ length of residence and their socio-cultural adaptation and the relationship between length of residence and psychological adaptation. Limitations of the study and implications for further research were discussed
Elastic Constants and Homogenized Moduli of Monoclinic Structures Based on Density Functional Theory
Elastic constants and homogenized properties of two monoclinic structures (gypsum and tobermorite) were investigated by first-principles method. The gypsum (chemical formula of CaSO4•2H2O) is an evaporite mineral and a kind of hydration product of anhydrite. Besides, the 11 Å tobermorite model (chemical formula: Ca4Si6O14(OH)4·2H2O) as an initial configuration of C-S-H structure is commonly used. Elastic constants are calculated based on density functional theory (DFT), which can also contribute to provide information for investigating the stability, stiffness, brittleness, ductility, and anisotropy of gypsum and tobermorite polycrystals. In addition, based on elastic constants (13 independent constants) of the monoclinic gypsum crystal, the elastic properties of polycrystals are obtained. The bulk modulus B, shear modulus G, Young’s modulus E, and Poisson’s ration ν are derived. Therefore, it is fairly meaningful to study the elastic constants to understand the physical, chemical, and mechanical properties of two monoclinic structures. Elastic constants can be used as the measure criterion of the resistance of a crystal to an externally applied stress. The calculated parameters are all in excellent agreement with reference
Atomistic Simulation of Anistropic Crystal Structures at Nanoscale
Multiscale simulations of atomistic/continuum coupling in computational materials science, where the scale expands from macro-/micro- to nanoscale, has become a hot research topic. These small units, usually nanostructures, are commonly anisotropic. The development of molecular modeling tools to describe and predict the mechanical properties of structures reveals an undeniable practical importance. Typical anisotropic structures (e.g. cubic, hexagonal, monoclinic) using DFT, MD, and atomic finite element methods are especially interesting, according to the modeling requirement of upscaling structures. It therefore connects nanoscale modeling and continuous patterns of deformation behavior by identifying relevant parameters from smaller to larger scales. These methodologies have the prospect of significant applications. I would like to recommend this book to both beginners and experienced researchers
Image Aesthetics Assessment Using Composite Features from off-the-Shelf Deep Models
Deep convolutional neural networks have recently achieved great success on
image aesthetics assessment task. In this paper, we propose an efficient method
which takes the global, local and scene-aware information of images into
consideration and exploits the composite features extracted from corresponding
pretrained deep learning models to classify the derived features with support
vector machine. Contrary to popular methods that require fine-tuning or
training a new model from scratch, our training-free method directly takes the
deep features generated by off-the-shelf models for image classification and
scene recognition. Also, we analyzed the factors that could influence the
performance from two aspects: the architecture of the deep neural network and
the contribution of local and scene-aware information. It turns out that deep
residual network could produce more aesthetics-aware image representation and
composite features lead to the improvement of overall performance. Experiments
on common large-scale aesthetics assessment benchmarks demonstrate that our
method outperforms the state-of-the-art results in photo aesthetics assessment.Comment: Accepted by ICIP 201
Exploring Network Effects of Point-to-Point Networks: An Investigation of the Spatial Entry Patterns of Southwest Airlines
This paper explores network effects in Point-to-Point airline networks by examining the spatial entry patterns of Southwest airlines during the 1990-2006 period. Estimation results from a spatial probit model reveal clear spatial dependence in profitability across different routes served by the carrier. Detailed investigation suggests two main sources of network effects, namely: (1) airport and regional presence, and (2) substitutability of markets. Findings of the paper suggest also that the network effects embedded in Southwest’s Point-to-Point network have many distinguishing features as compared to those identified in a typical Hub-and-Spoke network. This study brings some fresh insights on airline network effects in general, as well as explaining the pattern of aggressive network expansions of LCCs in particular.Point-to-Point Networks, spatial entry patterns, Southwest airlines, spatial probit model
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