Mathematical theory for the interface mode in a waveguide bifurcated from a Dirac point

In this paper, we prove the existence of a bound state in a waveguide that consists of two semi-infinite periodic structures separated by an interface. The two periodic structures are perturbed from the same periodic medium with a Dirac point and they possess a common band gap enclosing the Dirac point. The bound state, which is called interface mode here, decays exponentially away from the interface with a frequency located in the common band gap and can be viewed as a bifurcation from the Dirac point. Using the layer potential technique and asymptotic analysis, we first characterize the band gap opening for the two perturbed periodic media and derive the asymptotics of the Bloch modes near the band gap edges. By formulating the eigenvalue problem for the waveguide with two semi-infinite structures using a boundary integral equation over the interface and analyzing the characteristic values of the associated boundary integral operator, we prove the existence of the interface mode for the waveguide when the perturbation of the periodic medium is small

Efficiency of Commercial Banks in Developing Countries: A Case Study of China Mainland, India and Indonesia

This study investigates the influence of the risk factor (equity) and environmental conditions have on the cost efficiency of three developing Asian countries, China mainland, India and Indonesia for cross-country comparisons of efficiency using a parametric approach, covering period of year 2006 to 2012. The goal of this analysis is to identify the impacts brought by equity and environmental variables on commercial banking efficiency in China mainland, India and Indonesia, especially the 2008 global financial crisis. To conduct this analysis, stochastic frontier analysis is utilized. Results show that the environmental conditions of each country play important roles in the definition and specification of the common frontier of different countries. Results suggest that the banking efficiency in China mainland, India and Indonesia has a gradually declined tendency before and after incorporating the environmental variables. Without the environmental variables, the average cost-efficiency scores of three countries line in the range of 83.6% to 83.9% from year 1999 to year 2006 and in the range of 77.6% to 78.6% for the period of 2007 to 2012. When environmental variables are included in the model, the differences between two periods are increased substantially, ranging from 80% to 45%. After incorporating the risk factor (equity), cost efficiency scores for commercial banking sector in China mainland, India and Indonesia have become slightly lowered, but show a same tendency as the ones when the risk factor is removed. Overall, the results demonstrate that environmental variables contribute significantly to the difference in efficiency scores between the three counties. In other words, failure to incorporate the environmental factors may not be able to adequately describe the banking efficiency tendency of China mainland, India and Indonesia in the period of 1999 to 2012. However, the results also indicate that the impact of equity makes slightly difference on the level of efficiency in these three developing Asian countries in the sample period

Prompt Tuning based Adapter for Vision-Language Model Adaption

Large pre-trained vision-language (VL) models have shown significant promise in adapting to various downstream tasks. However, fine-tuning the entire network is challenging due to the massive number of model parameters. To address this issue, efficient adaptation methods such as prompt tuning have been proposed. We explore the idea of prompt tuning with multi-task pre-trained initialization and find it can significantly improve model performance. Based on our findings, we introduce a new model, termed Prompt-Adapter, that combines pre-trained prompt tunning with an efficient adaptation network. Our approach beat the state-of-the-art methods in few-shot image classification on the public 11 datasets, especially in settings with limited data instances such as 1 shot, 2 shots, 4 shots, and 8 shots images. Our proposed method demonstrates the promise of combining prompt tuning and parameter-efficient networks for efficient vision-language model adaptation. The code is publicly available at: https://github.com/Jingchensun/prompt_adapter

Personality predicts words in favorite songs

Psychologists have long theorized that people actively create, select, or modify situations in order to fulfill their psychological needs. However, little is known about how people use forms of art and entertainment such as music to enhance the potential for need satisfaction in their environment. In this research, we propose that people like certain songs because the linguistic cues in their lyrics are congruent with personality and hence can satisfy personal needs. To test this hypothesis, we measured participants’ personality and the linguistic styles of their favorite songs, and identified associations between personality and word use in lyrics, while controlling for preferences for melodic attributes and uses of music. We observed significant associations between personality traits predict linguistic cues in favorite songs, such as extraverts tending to like songs expressing positive emotions and conscientious individuals tending to like songs with lyrics that display cognitive complexity. These associations between personality and lyrics were stronger for participants who generally liked a song because of its lyrics rather than melody. These results improve our understanding of how people use linguistic cues in language products to satisfy their needs, and provide a new framework for understanding the mechanisms of musical preferences. They also have important practical implications