Infrared-Improved Soft-wall AdS/QCD Model for Mesons

We construct and investigate an infrared-improved soft-wall AdS/QCD model for mesons. Both linear confinement and chiral symmetry breaking of low energy QCD are well characterized in such an infrared-improved soft-wall AdS/QCD model. The model enables us to obtain a more consistent numerical prediction for the mass spectra of resonance scalar, pseudoscalar, vector and axial-vector mesons. In particular, the predicted mass for the lightest ground state scalar meson shows a good agreement with the experimental data. The model also provides a remarkable check for the Gell-Mann-Oakes-Renner relation and a sensible result for the space-like pion form factor.Comment: 15 pages, 4 figures, 7 tables, published versio

The Role of Self-congruity in Consumer Preferences: Perspectives from Transaction Records

Personalised marketing is more persuasive than traditional techniques aimed at the masses, however marketers do not always have access to consumers’ private attributes in order to apply these insights. The effect of personalisation is based on an established theory in consumer psychology – self-congruity theory – which posits that individuals prefer products, brands and advertisements that embody characteristics that match with their self-concepts. Self-congruence not only enhances marketing effectiveness, it can also be used to improve consumer well-being. While it has been established that consumers who spend in a way that is more congruent with their personality are happier, clarifications around the types of individuals who are more or less likely to engage in self-congruent spending, as well as the moderating effects on the benefit in happiness from such consumption could inform policy for improving happiness at a collective level. This thesis contributes to a growing body of research which attempts to understand how consumption patterns are related to consumers’ characteristics, its applications in advertising, as well as consumer well-being. By using a dataset containing more than 1 million transactions recorded over a period of 12-months, the thesis demonstrates the value of the digital footprint in the form of bank transactions for enriching our understanding of key questions in consumer research, underpinned by the theory of self-congruity. This thesis combines methods from computational social science with personality psychology to test research questions on consumer preferences. Two components of the thesis focused on the predictive utility of transaction records in inferring consumer attributes with which to personalise advertising, as well as the use of transaction records in examining self-congruence in overall consumption patterns and its relationship with happiness. Through five empirical studies, this work suggests that consumer attributes such as age and financial distress can be reliably inferred from consumption patterns reflected in transaction records (Chapter 3 and 5). The inferred age can be used to personalise advertisements in order to increase their appeal (Chapter 4). Using an objective measure of self-congruence in overall consumption pattern computed from transaction records and panel ratings, the thesis shows that individuals differ in their tendency to spend in a way that is congruent with their personality based on their levels of materialism and financial distress (Chapter 6). As the most important predictor of self-congruent spending, financial distress moderates the relationship between self-congruent spending and happiness (Chapter 7). These findings contribute insights into how consumption patterns are related to consumer attributes and usefulness for personalisation in marketing, as well as policy recommendations for improving well-being by targeting consumption patterns in financially distressed individuals. In addition, this thesis also showcases the value of machine learning and large-scale behavioural field data in the study of consumer psychology. Privacy and ethical concerns surrounding automated profiling and microtargeting are also cautioned

A closer look at interacting dark energy with statefinder hierarchy and growth rate of structure

We investigate the interacting dark energy models by using the diagnostics of statefinder hierarchy and growth rate of structure. We wish to explore the deviations from $\Lambda$CDM and to differentiate possible degeneracies in the interacting dark energy models with the geometrical and structure growth diagnostics. We consider two interacting forms for the models, i.e., $Q_1=\beta H\rho_c$ and $Q_2=\beta H\rho_{de}$, with $\beta$ being the dimensionless coupling parameter. Our focus is the I$\Lambda$CDM model that is a one-parameter extension to $\Lambda$CDM by considering a direct coupling between the vacuum energy ($\Lambda$) and cold dark matter (CDM), with the only additional parameter $\beta$. But we begin with a more general case by considering the I$w$CDM model in which dark energy has a constant $w$ (equation-of-state parameter). For calculating the growth rate of structure, we employ the "parametrized post-Friedmann" theoretical framework for interacting dark energy to numerically obtain the $\epsilon(z)$ values for the models. We show that in both geometrical and structural diagnostics the impact of $w$ is much stronger than that of $\beta$ in the I$w$CDM model. We thus wish to have a closer look at the I$\Lambda$CDM model by combining the geometrical and structural diagnostics. We find that the evolutionary trajectories in the $S^{(1)}_3$--$\epsilon$ plane exhibit distinctive features and the departures from $\Lambda$CDM could be well evaluated, theoretically, indicating that the composite null diagnostic $\{S^{(1)}_3, \epsilon\}$ is a promising tool for investigating the interacting dark energy models.Comment: 17 pages, 4 figures; accepted for publication in JCA

Advances in Electrochemical Nitric Oxide Exhaust Gas Sensors

The role of porosity on impedancemetric NOx sensing is discussed for sensors composed of a porous yttria-stabilized zirconia (YSZ) electrolyte and dense Au electrodes. NOx sensors considered here were fabricated at firing temperatures of 950–1200°C, which established a range of electrolyte microstructures where the porosity ranged from approximately 50% to 44%. Analysis of the electrical response of the NOx sensors indicated that sensors fired at 1050°C resulting in an electrolyte porosity of 46% demonstrated higher NOx sensitivity based on the operating conditions studied. The impedance of the sensors demonstrated a strong dependence on the electrolyte porosity. The activation energy of the sensors, which ranged from 109.2 to 81.1 kJ/mol, decreased with decreasing electrolyte porosity. Sensors with an electrolyte porosity ≥46% were limited by dissociated adsorption, whereas gas diffusion was rate limiting for sensors with an electrolyte porosity <46%. The impedancemetric response of the porous sensors to NO concentrations ≤10 ppm was distinguishable at operating frequencies as high as 40 Hz, thereby suggesting rapid sensing capabilities. Overall, the microstructure of the sensors composed of a YSZ electrolyte with 46% porosity promoted a strong, rapid, and highly sensitive response to NOx

Surgical treatment of neuropathic pain

Neuropathic pain (NP) is a transient dysfunction caused by the damage of peripheral nerve and central nervous system, characterized with hyperalgesia, allodynia and spontaneous pain. Surgical treatment of neuropathic pain has experienced a long process, and plays an important role. This paper reviews recent documents of surgical techniques in the treatment of neuropathic pain. There are three kinds of surgical techniques: neuromodulation, microsurgical lesions and nerve decompression