Autarkic Indeterminacy and Trade Determinacy

Most existing evidences for indeterminacy are obtained from analyzing models that do not consider trade. This paper considers an extension of Nishimura and Shimomura (Journal of Economic Theory, 2002) Heckscher-Ohlin framework by removing sector-specific externalities in one country while maintaining all other assumptions previously made by the authors. We show that even though indeterminacy arises under autarky, it can be eliminated when trade takes place with another country exhibiting saddle-path stability. Consequently, support for indeterminacy from calibrating an autarkic framework should be treated with some degree of caution.Indeterminacy, Trade, Two-Country, Heckscher-Ohlin

Indeterminacy and market instability

This note shows that indeterminacy arising from an economy exhibiting production with social constant returns to scale may be related to the instability of the consumption goods market equilibrium. Furthermore, trade does not contribute to indeterminacy indeterminacy arises becasue each country's equilibrium path is already indeterminate before trade.

Indeterminacy and Market Instability

This note shows that indeterminacy arising from an economy exhibiting production with social constant returns to scale may be related to the instability of the consumption goods market equilibrium. Furthermore, trade does not contribute to indeterminacy; indeterminacy arises becasue each country’s equilibrium path is already indeterminate before trade.Indeterminacy, Market Instability

Autarkic Indeterminacy and Trade Determinacy

We extend the model of Nishimura and Shimomura (2002) to consider a two-country framework where under autarky indeterminacy arises in one country but determinacy in the other, and show that indeterminacy could be eliminated when trade takes place between the two.Indeterminacy, Trade, Two-Country Framework.

The Evolution of Post-Starburst Galaxies from z∼1z\sim1 to the Present

Post-starburst galaxies are in the transitional stage between blue, star-forming galaxies and red, quiescent galaxies, and therefore hold important clues for our understanding of galaxy evolution. In this paper, we systematically searched for and identified a large sample of post-starburst galaxies from the spectroscopic dataset of the Sloan Digital Sky Survey (SDSS) Data Release 9. In total, we found more than 6000 objects with redshifts between $z\sim0.05$ and $z\sim1.3$, making this the largest sample of post-starburst galaxies in the literature. We calculated the luminosity function of the post-starburst galaxies using two uniformly selected subsamples: the SDSS Main Galaxy Sample and the Baryon Oscillation Spectroscopic Survey CMASS Sample. The luminosity functions are reasonably fit by half-Gaussian functions. The peak magnitudes shift as a function of redshift from $M\sim-23.5$ at $z\sim0.8$ to $M\sim-20.3$ at $z\sim0.1$. This is consistent with the downsizing trend, whereby more massive galaxies form earlier than low-mass galaxies. We compared the mass of the post-starburst stellar population found in our sample to the decline of the global star-formation rate and found that only a small amount ($\sim1\%$) of all star-formation quenching in the redshift range $z=0.2-0.7$ results in post-starburst galaxies in the luminosity range our sample is sensitive to. Therefore, luminous post-starburst galaxies are not the place where most of the decline in star-formation rate of the universe is happening.Comment: 26 pages, 24 figures, 8 tables. Accepted for publication in The Astrophysical Journa

Repositioning a literary magazine to an art group : challenges and strategies

Hong Kong has long been accused of being a “cultural desert”, an image that found resonance largely due to the lack of support and recognition from the government for the cultural industry. In recent years, with the debate on the government’s proposal of setting up a Cultural Bureau, the cultural industry has received unremitting attention and it has pushed the government to invest more in order to support the development of Hong Kong’s arts and culture. Yet, Hong Kong Arts Development Council (HKADC), the statutory funding body, tends to provide funding support to established arts institutions; smaller arts groups received little money and attention, and thus their survival is indeed at risk. With the lion’s share of the government support goes to established groups, the literary groups, like others small arts groups, have faced severe challenges. In this connection, some literary practitioners have taken measures to reinvent themselves conceptually to adapt to the cultural reality. The purpose of this study is to examine the feasibility of repositioning a literary magazine to an art group with sustainable income under the current Hong Kong’s cultural environment. By focusing on the recent transformation of Fleurs des Lettres (字花), a Chinese bi-monthly literary magazine which is supported by HKADC, from a purely literary magazine to an art group; it attempts to explore the crisis it faced and the measures it has taken to respond to the cultural reality of Hong Kong. The paper considers the part played by Fleurs des Lettres in sustaining a healthy future for literature, with particular attention given to audience demands and expectations.published_or_final_versionMedia, Culture and Creative CitiesMasterMaster of Social Sciences in Media, Culture and Creative Citie

Abnormal Infant Movements Classification With Deep Learning on Pose-Based Features

The pursuit of early diagnosis of cerebral palsy has been an active research area with some very promising results using tools such as the General Movements Assessment (GMA). In our previous work, we explored the feasibility of extracting pose-based features from video sequences to automatically classify infant body movement into two categories, normal and abnormal. The classification was based upon the GMA, which was carried out on the video data by an independent expert reviewer. In this paper we extend our previous work by extracting the normalised pose-based feature sets, Histograms of Joint Orientation 2D (HOJO2D) and Histograms of Joint Displacement 2D (HOJD2D), for use in new deep learning architectures. We explore the viability of using these pose-based feature sets for automated classification within a deep learning framework by carrying out extensive experiments on five new deep learning architectures. Experimental results show that the proposed fully connected neural network FCNet performed robustly across different feature sets. Furthermore, the proposed convolutional neural network architectures demonstrated excellent performance in handling features in higher dimensionality. We make the code, extracted features and associated GMA labels publicly available

Numerical simulation of slug flow with high viscosity liquid

Slug flow is one of the most common flow patterns in multiphase oil/gas transport in pipelines. Due to its complexity, it poses numerous challenges to model development. Industrial slug flow models are one-dimensional and can give poor predictions in situations where the associated closures and simplifications are no longer valid. Computational Fluid Dynamics (CFD) facilitates high-resolution studies of slug flow dynamics by implementing multi-dimensional models. Understanding the physics of slug flow would help identify the main flow mechanisms to be modelled and enable the development of mechanistic slug flow models for commercial software. In this thesis, a computational approach is developed. The front tracking method (FTM) (Tryggvason et al. 2001) and the phase field method (PFM) (Ding et al. 2007) are used to model long bubbles in slug flows. Results of the validation study show good agreement with DeBisschop et al. (2002), who performed simulations of long bubbles in two-dimensional channels in the creeping-flow limit. Their work is extended here to moderate Archimedes numbers (10 < Ar < 200). The effects of inertia, surface tension, viscosity and inclination angle on the terminal velocity and the shape of a long bubble in different flow conditions are investigated. Furthermore, the FTM is coupled with a discrete bubble tracking method (DBTM), which has resulted in a robust hybrid method to model small and large bubbles simultaneously in an Eulerian-Lagrangian fashion. The method allows the study of the interaction of the small bubbles with a long bubble. The work is extended further to three dimensions using the PFM. The validation study shows good agreement with the present two-dimensional numerical work. The geometry is converted from a square channel to a pipe to facilitate a more realistic simulation of slug flow in pipelines. This work will provide a rigorous basis for developing simplified models.Open Acces

Application of Genomic Technologies to Study Infertility

An estimated one in eight couples in the United States are diagnosed with infertility. There is a significant genetic contribution to infertility, with estimates of heritability ranging from 0.2 to 0.5. We know surprisingly little about the genetic causes, with only slightly more than a hundred genes known to cause human infertility. I have been translating recent advances in genomics to study infertility in a more efficient manner, in order to improve our knowledge of the genetic causes. By using high throughput genomics and proteomics datasets from other groups, I was able to feed that into a machine learning algorithm to predict novel fertility function genes. While not perfect, this computational model performs comparably to other publish prediction models. In order to test the top predicted fertility genes I also developed an experimental technique to simultaneously screen up to hundreds of genes for spermatogenesis function in vivo in mice. This method is based off of RNAi, and I was able to benchmark its performance to demonstrate that it performed comparably to other benchmarked RNAi screens in flies. I then used this method to test the top 26 predicted spermatogenesis genes and showed that most of them (24/26) have an important role in spermatogenesis. Using this technique, other groups can screen genes for spermatogenesis function in a fraction of the time and cost compared to the traditional approach of generating knockout mouse lines. Finally, I describe the progress I have made in using genetic engineering to rescue spermatogenesis in mice. By analyzing the missteps I have made in delivering constitutively expressed transgenes and CRISPR genes into mouse testes, I describe the probably reasons for my failure and how to implement future experiments to get more success

Herschel Survey of the Palomar-Green QSOs at Low Redshift

We investigate the global cold dust properties of 85 nearby (z < 0.5) QSOs, chosen from the Palomar-Green sample of optically luminous quasars. We determine their infrared spectral energy distributions and estimate their rest-frame luminosities by combining Herschel data from 70 to 500 microns with near-infrared and mid-infrared measurements from the Two Micron All Sky Survey (2MASS) and the Wide-Field Infrared Survey Explorer (WISE). In most sources the far-infrared (FIR) emission can be attributed to thermally heated dust. Single temperature modified black body fits to the FIR photometry give an average dust temperature for the sample of 33~K, with a standard deviation of 8~K, and an average dust mass of 7E6 Solar Masses with a standard deviation of 9E6 Solar Masses. Estimates of star-formation that are based on the FIR continuum emission correlate with those based on the 11.3 microns PAH feature, however, the star-formation rates estimated from the FIR continuum are higher than those estimated from the 11.3 microns PAH emission. We attribute this result to a variety of factors including the possible destruction of the PAHs and that, in some sources, a fraction of the FIR originates from dust heated by the active galactic nucleus and by old stars.Comment: accepted for publication in ApJ