Learning a Policy for Opportunistic Active Learning

Active learning identifies data points to label that are expected to be the most useful in improving a supervised model. Opportunistic active learning incorporates active learning into interactive tasks that constrain possible queries during interactions. Prior work has shown that opportunistic active learning can be used to improve grounding of natural language descriptions in an interactive object retrieval task. In this work, we use reinforcement learning for such an object retrieval task, to learn a policy that effectively trades off task completion with model improvement that would benefit future tasks.Comment: EMNLP 2018 Camera Read

Impact of dietary changes on hepatic homocysteine metabolism in young broilers

Information regarding the impact of sulfur amino acids (SAA) on hepatic homocysteine (Hcy) flux through the various metabolic pathways competing for Hcy in young broilers is lacking. An experiment was conducted to evaluate the impact of varying levels of dietary methionine (Met), choline, and betaine on hepatic Hcy flux in young broiler chickens. A standard starter basal diet was fed to chicks until 8 d of age; 12 experimental diets were given from 8-22 d. The experimental basal diet contained deficient levels of Met and cysteine (Cys); supplemental Met (0, 0.08, 0.16, and 0.24%) was added to the basal diet in combination with isomethyl levels of choline (0 or 0.25%) or betaine (0 or 0.28%). The 12 dietary treatments were replicated with three pens containing five chicks each (15 birds per treatment). Weight gain and feed efficiency increased (P \u3c 0.05) with Met addition and were maximized with the addition of 0.16% digestible Met. No significant interactions (P \u3e 0.05) with choline or betaine addition were noted for weight gain, feed intake, or feed efficiency, but numerical improvements for these variables were observed with the addition of choline and betaine to the Met-deficient basal diet. Analysis of liver tissue indicated that folate-dependent remethylation of Hcy predominated over betaine-dependent remethylation. Further, folate-dependent remethylation of Hcy appeared to be impacted by dietary choline and betaine levels, whereas betaine-dependent remethylation appeared to be more impacted by dietary SAA levels

Modeling and Parameter Estimation of Escherichia Coli Bioprocess

Most biopharmaceuticals today are focused on the production of one of three major cell types: the bacterium Escherichia coli, yeasts (Saccharomyces cerevisiae, Pichia pastoris) and mammalian cells (Chinese Hamster Ovary cells). Growth opti-mization is a major focus as this dictates the pace of advancements in drug manu-facturing. The process involved in producing these cells itself is very complex and modeling a system to accurately capture these characteristics can be difficult. The overall process is expensive to run and repeated testing of various control algorithms to optimize growth can prove to be very time consuming as well. In order to develop control strategies and improve the yield of protein, it is beneficial to model a system that captures the responses of the bioprocess. The model can be coupled with different controllers to test the yield output and determine the most effective control strategies without incurring additional costs or time delays. Model parameters are determined by the process of numerical minimization, making use of experimentally obtained data to ensure accurate simulation system behavior. Additionally, a separate system can be developed to switch between the simulation platform and the actual process, with the same control strategy being implemented to compare against results of the simulation and the actual process. This allows for further adjustments to be made to more effectively model the bioprocess. This thesis describes the implementation of the Xu model, found in literature as the simulation counterpart to an experimental hardware setup. A hardware-in-the-loop simulation is developed with the ability to accurately model system parameters against experimentally obtained results in order to carry out control strategy testing on the simulation side before switching to the experimental hardware side. Accurate parameter estimation is achieved by fitting simulation results to experimentally logged data to ensure the simulation replicates the behavior of the physical system, and is subsequently verified against non-training data

Characterisation of Enaptin and Sun1, two novel mammalian nuclear envelope proteins

The nucleus is a highly dynamic organelle showing migratory events during various developmental and cellular processes. These are made possible by its association with the microtubule network and, as shown recently, with the microfilament network. We have characterised Enaptin, a giant protein located at the nuclear membrane, which may provide a link to the actin cytoskeleton. Enaptin has an actin binding domain at the N-terminus with which it binds to the actin cytoskeleton and a transmembrane domain at the C-terminus, which tethers it to the nuclear envelope (NE). Western blotting experiments with antibodies specific to the ABD of Enaptin detect a 400 kDa protein in various cell lines and a 165 kDa protein in mouse brain tissue. We concentrated on the properties of the very C-terminus composed of the last 30 amino acids after the transmembrane domain of Enaptin. A similar stretch of amino acids is found in the related NUANCE and is also highly conserved in proteins of the NE across different species from C. elegans to humans. We show that the conserved amino acids in Enaptin and NUANCE bind to the C-terminus of Sun1 in yeast two hybrid and GST pull down experiments. Sun1 is a novel NE protein with three transmembrane domains in the middle. The C-terminal end of Sun1 is homologous to the SUN domain, which derives its name from its homology between Sad1 (S. pombe protein associated with the spindle pole body) (Iain and Mitsuhiro, 1995) and UNC-84 (C. elegans orthologue of Sun1) (Malone et al., 1999). The SUN domain of Sun1 is however not engaged in the binding of Enaptin. Instead, the interaction site is located in a region neighboring the SUN domain. A dominant negative version of Sun1 (GFP-CT+3TM), which displaces endogenous Sun1 from the NE also displaces NUANCE and emerin, a protein located in the inner nuclear membrane, underlining the fact that NUANCE localisation to the NE is also Sun1 dependent. Further experiments were directed at the identification of the site of location of Sun1 employing expression of GFP-tagged Sun1 as well as antibodies generated against the N- and C-terminus of Sun1. Immunofluorescence studies performed after digitonin permeabilisation finally located the protein at the inner nuclear membrane. In further experiments we analysed the requirements for the nuclear envelope localisation of Sun1. The results point to interactions with different proteins of the NE and also to the importance of the coiled coil domain

High-temperature catalyst supports and ceramic membranes: Metastability and particle packing

Parameters and/or processes responsible for the stability of catalyst supports and ceramic membranes are discussed. Two major parameters/processes were identified which are responsible for the stability of sol-gel derived nanostructured oxides at elevated temperatures. They are metastable-to-stable phase transformation and structure and packing of primary particles within the aggregate. Based on these observations, strategies to develop thermostable nanostructured oxides for high-temperature membrane and catalyst applications are discussed by taking titania and titania-alumina nanocomposites as examples