Effect of gate voltage on spin transport along α\alpha-helical protein

Recently, the chiral-induced spin selectivity in molecular systems has attracted extensive interest among the scientific communities. Here, we investigate the effect of the gate voltage on spin-selective electron transport through the $\alpha$-helical peptide/protein molecule contacted by two nonmagnetic electrodes. Based on an effective model Hamiltonian and the Landauer-B\"uttiker formula, we calculate the conductance and the spin polarization under an external electric field which is perpendicular to the helix axis of the $\alpha$-helical peptide/protein molecule. Our results indicate that both the magnitude and the direction of the gate field have a significant effect on the conductance and the spin polarization. The spin filtration efficiency can be improved by properly tuning the gate voltage, especially in the case of strong dephasing regime. And the spin polarization increases monotonically with the molecular length without the gate voltage, which is consistent with the recent experiment, and presents oscillating behavior in the presence of the gate voltage. In addition, the spin selectivity is robust against the dephasing, the on-site energy disorder, and the space angle disorder under the gate voltage. Our results could motivate further experimental and theoretical works on the chiral-based spin selectivity in molecular systems.Comment: 8 pages, 7 figure

The impact of mandatory savings on life cycle consumption and portfolio choice

University of Technology Sydney. Faculty of Business.Retirement income systems have increasingly attracted academic research and policy discussion in the light of population aging in developed countries. Management of retirement wealth is of first order importance if sustainable pension systems are to be maintained while providing desirable retirement living standards. In Australia, employers have been compelled by the Superannuation Guarantee to make minimum contributions to retirement accounts on behalf of their employees. Nevertheless, the structure of superannuation is still being discussed and reformed with the aim of making it a better, fairer and more cost-effective system. While there are many empirical studies and policy reviews, research addressing the impact and efficiency of superannuation from a theoretical perspective is lacking. To fill this gap, and to contribute to the wealth management literature, this thesis examines the impact of mandated contributions into superannuation accounts on individuals’ lifetime consumption, risky asset allocation and wealth using a continuous time dynamic life cycle model. First, in Chapter 2, we provide a dynamic model incorporating the compulsory savings constraint for a representative agent. The agent is endowed with deterministic labour income, and assumed to rationally make decisions that maximise his lifetime utility of consumption. Consistent with the primary aim of superannuation, we clearly identify and conclude that compulsory contributions alter the agent’s consumption behaviour and risky investment to be more conservative, which in turn may increase the agent’s total wealth over the life cycle. Building on the model in Chapter 2, we further introduce a life insurance purchase to hedge the mortality risk of the representative agent in Chapter 3. The dynamic model in Chapter 3 is an extension of the work of Pliska and Ye (2007), in which we further consider the forced savings constraint. In addition to the foundational results derived in Chapter 2, we demonstrate a lower bequest value and lower life insurance demand under the compulsory savings constraint. In Chapter 4 we calibrate the theoretical model to the Household, Income and Labour Dynamics in Australia (HILDA) survey data and conduct a range of policy analyses. In particular, we can investigate the welfare loss arising from the one-rate-for-all compulsory contribution rules. Simulations of optimal paths show that the consumption of low-wealth individuals is severely constrained under current settings, resulting in a sizeable welfare loss. In response, we propose a time-varying contribution rate for individuals, which can mitigate the welfare loss while enhancing retirement wealth to achieve a desired retirement living standard

Jointly Modeling Embedding and Translation to Bridge Video and Language

Automatically describing video content with natural language is a fundamental challenge of multimedia. Recurrent Neural Networks (RNN), which models sequence dynamics, has attracted increasing attention on visual interpretation. However, most existing approaches generate a word locally with given previous words and the visual content, while the relationship between sentence semantics and visual content is not holistically exploited. As a result, the generated sentences may be contextually correct but the semantics (e.g., subjects, verbs or objects) are not true. This paper presents a novel unified framework, named Long Short-Term Memory with visual-semantic Embedding (LSTM-E), which can simultaneously explore the learning of LSTM and visual-semantic embedding. The former aims to locally maximize the probability of generating the next word given previous words and visual content, while the latter is to create a visual-semantic embedding space for enforcing the relationship between the semantics of the entire sentence and visual content. Our proposed LSTM-E consists of three components: a 2-D and/or 3-D deep convolutional neural networks for learning powerful video representation, a deep RNN for generating sentences, and a joint embedding model for exploring the relationships between visual content and sentence semantics. The experiments on YouTube2Text dataset show that our proposed LSTM-E achieves to-date the best reported performance in generating natural sentences: 45.3% and 31.0% in terms of BLEU@4 and METEOR, respectively. We also demonstrate that LSTM-E is superior in predicting Subject-Verb-Object (SVO) triplets to several state-of-the-art techniques