Offensive Advertisements Influence You More Than Me: An Examination of the Third-Person Effects in the Chinese Cultural Context

This study examined the third-person effect (TPE) hypothesis (Davison, 1983) in offensive advertising in the Chinese cultural context. Based on a survey of 1,539 Chinese Internet users about the third- and firstperson effects among offensive ads, neutral ads, and public service ads, the study inquires into the relationship between the TPE and respondents’ levels of acceptance toward advertising. Besides confirming the TPE existence in an Eastern cultural context, the results suggest that the TPE predict wordof-mouth (WOM) spreading for both offensive and neutral product ads, but not for PSAs. Theoretical contributions and managerial implications of these findings are discussed

Delineating Structural Characteristics of Viral Capsid Proteins Critical for Their Functional Assembly.

Viral capsids exhibit elaborate and symmetrical architectures of defined sizes and remarkable mechanical properties not seen with cellular macromolecular complexes. The limited coding capacity of viral genome necessitates economization upon one or a few identical gene products known as capsid proteins for shell assembly. The functional uniqueness of this class of proteins prompts questions on structural features critically important for their higher order organization. In this thesis, I develop the statistical framework and computational tools to pinpoint the structural characteristics of viral capsid proteins exclusive to the virosphere by testing a series of hypotheses, providing understanding of the physical principles governing molecular self-association that can inform rational design of nanomaterials and therapeutics. In the first chapter, I compare the folds of capsid proteins with those of generic proteins, and establish that capsid proteins are segregated in structural fold space, highlighting the geometric constraints of these building blocks for tiling into a closed shell. Second, I develop a software program, PCalign, for quantifying the physicochemical similarity between protein-protein interfaces. This tool overcomes the major limitation of current methods by using a reduced representation of structural information, greatly expanding the structural interface space that can be investigated through inclusion of large macromolecular assemblies that are often not amenable to high resolution experimental techniques. As an application of this method, I propose a computational framework for template-based protein inhibitor design, leading to the prediction of putative binders for a therapeutic target, the influenza hemagglutinin. In silico evaluations of these candidate drugs parallel those of known protein binders, offering great promise in expanding therapeutic options in the clinic. Lastly, I examine protein-protein interfaces using PCalign, and find strong statistical evidence for the disconnectivity between capsid proteins and cellular proteins in structural interface space. I thus conclude that the basic shape and the sticky edges of these Lego pieces act concertedly to create the sophisticated shell architecture. In summary, the novel tools contributed by this dissertation work lead to delineation of structural features of viral capsid proteins that make them functionally unique, providing an understanding that will serve as the basis for prediction and design.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110375/1/sscheng_1.pd

PCalign: a method to quantify physicochemical similarity of protein-protein interfaces

Abstract Background Structural comparison of protein-protein interfaces provides valuable insights into the functional relationship between proteins, which may not solely arise from shared evolutionary origin. A few methods that exist for such comparative studies have focused on structural models determined at atomic resolution, and may miss out interesting patterns present in large macromolecular complexes that are typically solved by low-resolution techniques. Results We developed a coarse-grained method, PCalign, to quantitatively evaluate physicochemical similarities between a given pair of protein-protein interfaces. This method uses an order-independent algorithm, geometric hashing, to superimpose the backbone atoms of a given pair of interfaces, and provides a normalized scoring function, PC-score, to account for the extent of overlap in terms of both geometric and chemical characteristics. We demonstrate that PCalign outperforms existing methods, and additionally facilitates comparative studies across models of different resolutions, which are not accommodated by existing methods. Furthermore, we illustrate potential application of our method to recognize interesting biological relationships masked by apparent lack of structural similarity. Conclusions PCalign is a useful method in recognizing shared chemical and spatial patterns among protein-protein interfaces. It outperforms existing methods for high-quality data, and additionally facilitates comparison across structural models with different levels of details with proven robustness against noise.http://deepblue.lib.umich.edu/bitstream/2027.42/110905/1/12859_2015_Article_471.pd

Mechanical Behavior of Fiber-to-concrete Interface in Textile Reinforced Concrete: Theoretical Model

This paper presents a theoretical solution of a reinforcement-to-concrete interface model under pull-push loading. Expressions for the interfacial shear stress distribution and load-displacement history are derived for different loading stages. The full debonding propagation process is discussed in detail and the analytical solutions are verified by comparing with existing theoretical models. Results of the analytical solution are presented to illustrate how the bond length and local bond-slip law affect the interfacial bond behavior. While the case study in this paper is on textile reinforced concrete, the analytical solution is equally valid to similar mechanical cases such as rebar reinforced concretes

PCalign: a method to quantify physicochemical similarity of protein-protein interfaces

Abstract Background Structural comparison of protein-protein interfaces provides valuable insights into the functional relationship between proteins, which may not solely arise from shared evolutionary origin. A few methods that exist for such comparative studies have focused on structural models determined at atomic resolution, and may miss out interesting patterns present in large macromolecular complexes that are typically solved by low-resolution techniques. Results We developed a coarse-grained method, PCalign, to quantitatively evaluate physicochemical similarities between a given pair of protein-protein interfaces. This method uses an order-independent algorithm, geometric hashing, to superimpose the backbone atoms of a given pair of interfaces, and provides a normalized scoring function, PC-score, to account for the extent of overlap in terms of both geometric and chemical characteristics. We demonstrate that PCalign outperforms existing methods, and additionally facilitates comparative studies across models of different resolutions, which are not accommodated by existing methods. Furthermore, we illustrate potential application of our method to recognize interesting biological relationships masked by apparent lack of structural similarity. Conclusions PCalign is a useful method in recognizing shared chemical and spatial patterns among protein-protein interfaces. It outperforms existing methods for high-quality data, and additionally facilitates comparison across structural models with different levels of details with proven robustness against noise.http://deepblue.lib.umich.edu/bitstream/2027.42/134734/1/12859_2015_Article_471.pd