Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders

While recent neural encoder-decoder models have shown great promise in modeling open-domain conversations, they often generate dull and generic responses. Unlike past work that has focused on diversifying the output of the decoder at word-level to alleviate this problem, we present a novel framework based on conditional variational autoencoders that captures the discourse-level diversity in the encoder. Our model uses latent variables to learn a distribution over potential conversational intents and generates diverse responses using only greedy decoders. We have further developed a novel variant that is integrated with linguistic prior knowledge for better performance. Finally, the training procedure is improved by introducing a bag-of-word loss. Our proposed models have been validated to generate significantly more diverse responses than baseline approaches and exhibit competence in discourse-level decision-making.Comment: Appeared in ACL2017 proceedings as a long paper. Correct a calculation mistake in Table 1 E-bow & A-bow and results into higher score

Superradiant instability of the charged scalar field in stringy black hole mirror system

It has been shown that the mass of the scalar field in the charged stringy black hole is never able to generate a potential well outside the event horizon to trap the superradiant modes. This is to say that the charged stringy black hole is stable against the massive charged scalar perturbation. In this paper we will study the superradiant instability of the massless scalar field in the background of charged stringy black hole due to a mirror-like boundary condition. The analytical expression of the unstable superradiant modes is derived by using the asymptotic matching method. It is also pointed out that the black hole mirror system becomes extremely unstable for a large charge $q$ of scalar field and the small mirror radius $r_m$.Comment: 5 pages, no figure, published versio

Time evolutions of scalar field perturbations in DD-dimensional Reissner-Nordstr\"om Anti-de Sitter black holes

Reissner-Nordstr\"om Anti-de Sitter (RNAdS) black holes are unstable against the charged scalar field perturbations due to the well-known superradiance phenomenon. We present the time domain analysis of charged scalar field perturbations in the RNAdS black hole background in general dimensions. We show that the instabilities of charged scalar field can be explicitly illustrated from the time profiles of evolving scalar field. By using the Prony method to fit the time evolution data, we confirm the mode that dominates the long time behavior of scalar field is in accordance with the quasinormal mode from the frequency domain analysis. The superradiance origin of the instability can also be demonstrated by comparing the real part of the dominant mode with the superradiant condition of charged scalar field. It is shown that all the unstable modes are superradiant, which is consistent with the analytical result in the frequency domain analysis. Furthermore, we also confirm there exists the rapid exponential growing modes in the RNAdS case, which makes the RNAdS black hole a good test ground to investigate the nonlinear evolution of superradiant instability.Comment: 15 pages, 7 figure

ORIGINS AND SEASONAL VARIATION OF DISINFECTION BYPRODUCT PRECURSORS

Disinfection byproducts (DBPs) are formed from the disinfectant (e.g., chlorine) reacting with components of natural organic matter (NOM) in water drawn from surface water supplies, and are considered as the cause of potential serious human health problems. DBP precursors originate in large reservoirs from at least three types of sources: (1) watershed or allochthonous, (2) algal or autochthonous, and (3) bottom sediments or benthic. The properties of the NOM and the DBP precursor content of that NOM are unique to each source. The first objective of this dissertation was to use temporal and spatial water quality data from a drinking water reservoir to shed light on autochthonous and benthic sources of NOM and DBP precursors. The second objective of this dissertation was to identify the seasonal variation and spatial fate of DBP precursors in a drinking water system located in a temperate environment where seasonal variations of surface water quality and water temperature are considerable. Organic matter released from plants is quite likely the most important fraction as potential DBP precursors, especially in heavily forested catchments. However, very few studies have been conducted on plant leachate as DBP precursors. The third objective of this dissertation was to characterize the organic matter that is released by plants, and examine their potentials to form DBPs under light, dark, and dark-with-biocide conditions. The final objective of this dissertation was to determine the comparative significance of DBP (i.e., trihalomethanes, dihaloacetic acids, and trihaloacetic acids) precursors released from profundal sediments of a water supply impoundment under aerobic, hypoxic, and anaerobic conditions

Analysis of turbidity progress curves from protein aggregation reactions

To investigate the individual and combined effects of protein molecular chaperone abilities on the aggregation of proteins a vital first step is the development of a robust and simple assay for examining the aggregation of proteins. By far the most common in vitro method to monitor protein aggregation is the turbidity assay. All protein aggregates scatter light in the visible wavelength region since their size ranges from nanometer to micrometers. This characteristic combined with a lack of absorption in the visible wavelength region makes the low-cost turbidity assay a particularly attractive method for monitoring protein aggregation. Colloidal solution turbidity is generally considered to exhibit a linear relationship with the aggregation reaction. However, this assumption is usually not based on convincing supporting experiments or theory. The turbidity of a colloidal solution is not only determined by the size, but also the shape of the particles. As a result, analyzing the relationship between solution turbidity and protein aggregation can be quite challenging. In my postgraduate research I examined and developed improved methods for simulating and analyzing turbidity profiles of mixed protein aggregation reactions, which will greatly facilitate the understanding of protein aggregation and the effect of molecular chaperone reactions. In my first paper I contributed to developing a hybrid method for simulating turbidity of protein aggregates of different sizes in the low concentration limit. This simulation utilises a combination of the Rayleigh, the Rayleigh-Gans-Debye (RGD) and approximate forms of the Mie scattering equations. This hybrid approach was used to generate empirical interpolating functions, which may be used for both simulation and analysis of turbidity profiles. In my second paper, I helped to develop a method for quantifying the variability in the amyloid aggregation assay. We investigated the variability in the amyloid aggregation kinetics, and developed methods for its simulation, identification and analysis. Rather unexpectedly, such an analysis had not been previously developed despite it being the fundamental cornerstone of all differential analyses of drug and condition effects upon the protein aggregation reaction. In my third paper, I reviewed the physical chemistry of the turbidimetric assay methodology, investigating the reviewed information with a series of pedagogical kinetic simulations. We particularly focused upon recent literature relating to ultra-microscope image analysis light scattering and turbidity development by protein aggregates and computer simulation of the kinetics of amyloid and other aggregate types