Integrating Pro-Environmental Behavior with Transportation Network Modeling: User and System Level Strategies, Implementation, and Evaluation

Personal transport is a leading contributor to fossil fuel consumption and greenhouse (GHG) emissions in the U.S. The U.S. Energy Information Administration (EIA) reports that light-duty vehicles (LDV) are responsible for 61\% of all transportation related energy consumption in 2012, which is equivalent to 8.4 million barrels of oil (fossil fuel) per day. The carbon content in fossil fuels is the primary source of GHG emissions that links to the challenge associated with climate change. Evidently, it is high time to develop actionable and innovative strategies to reduce fuel consumption and GHG emissions from the road transportation networks. This dissertation integrates the broader goal of minimizing energy and emissions into the transportation planning process using novel systems modeling approaches. This research aims to find, investigate, and evaluate strategies that minimize carbon-based fuel consumption and emissions for a transportation network. We propose user and system level strategies that can influence travel decisions and can reinforce pro-environmental attitudes of road users. Further, we develop strategies that system operators can implement to optimize traffic operations with emissions minimization goal. To complete the framework we develop an integrated traffic-emissions (EPA-MOVES) simulation framework that can assess the effectiveness of the strategies with computational efficiency and reasonable accuracy. ^ The dissertation begins with exploring the trade-off between emissions and travel time in context of daily travel decisions and its heterogeneous nature. Data are collected from a web-based survey and the trade-off values indicating the average additional travel minutes a person is willing to consider for reducing a lb. of GHG emissions are estimated from random parameter models. Results indicate that different trade-off values for male and female groups. Further, participants from high-income households are found to have higher trade-off values compared with other groups. Next, we propose personal mobility carbon allowance (PMCA) scheme to reduce emissions from personal travel. PMCA is a market-based scheme that allocates carbon credits to users at no cost based on the emissions reduction goal of the system. Users can spend carbon credits for travel and a market place exists where users can buy or sell credits. This dissertation addresses two primary dimensions: the change in travel behavior of the users and the impact at network level in terms of travel time and emissions when PMCA is implemented. To understand this process, a real-time experimental game tool is developed where players are asked to make travel decisions within the carbon budget set by PMCA and they are allowed to trade carbon credits in a market modeled as a double auction game. Random parameter models are estimated to examine the impact of PMCA on short-term travel decisions. Further, to assess the impact at system level, a multi-class dynamic user equilibrium model is formulated that captures the travel behavior under PMCA scheme. The equivalent variational inequality problem is solved using projection method. Results indicate that PMCA scheme is able to reduce GHG emissions from transportation networks. Individuals with high value of travel time (VOTT) are less sensitive to PMCA scheme in context of work trips. High and medium income users are more likely to have non-work trips with lower carbon cost (higher travel time) to save carbon credits for work trips. ^ Next, we focus on the strategies from the perspectives of system operators in transportation networks. Learning based signal control schemes are developed that can reduce emissions from signalized urban networks. The algorithms are implemented and tested in VISSIM micro simulator. Finally, an integrated emissions-traffic simulator framework is outlined that can be used to evaluate the effectiveness of the strategies. The integrated framework uses MOVES2010b as the emissions simulator. To estimate the emissions efficiently we propose a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the link driving schedules for MOVES2010b. Test results using the data from a five-intersection corridor show that HC-DTW technique can significantly reduce emissions estimation time without compromising the accuracy. The benefits are found to be most significant when the level of congestion variation is high. ^ In addition to finding novel strategies for reducing emissions from transportation networks, this dissertation has broader impacts on behavior based energy policy design and transportation network modeling research. The trade-off values can be a useful indicator to identify which policies are most effective to reinforce pro-environmental travel choices. For instance, the model can estimate the distribution of trade-off between emissions and travel time, and provide insights on the effectiveness of policies for New York City if we are able to collect data to construct a representative sample. The probability of route choice decisions vary across population groups and trip contexts. The probability as a function of travel and demographic attributes can be used as behavior rules for agents in an agent-based traffic simulation. Finally, the dynamic user equilibrium based network model provides a general framework for energy policies such carbon tax, tradable permit, and emissions credits system

Statistical Mechanics of the Hyper Vertex Cover Problem

We introduce and study a new optimization problem called Hyper Vertex Cover. This problem is a generalization of the standard vertex cover to hypergraphs: one seeks a configuration of particles with minimal density such that every hyperedge of the hypergraph contains at least one particle. It can also be used in important practical tasks, such as the Group Testing procedures where one wants to detect defective items in a large group by pool testing. Using a Statistical Mechanics approach based on the cavity method, we study the phase diagram of the HVC problem, in the case of random regualr hypergraphs. Depending on the values of the variables and tests degrees different situations can occur: The HVC problem can be either in a replica symmetric phase, or in a one-step replica symmetry breaking one. In these two cases, we give explicit results on the minimal density of particles, and the structure of the phase space. These problems are thus in some sense simpler than the original vertex cover problem, where the need for a full replica symmetry breaking has prevented the derivation of exact results so far. Finally, we show that decimation procedures based on the belief propagation and the survey propagation algorithms provide very efficient strategies to solve large individual instances of the hyper vertex cover problem.Comment: Submitted to PR

Design, synthesis and testing of novel anti-cancer agents targeting secretory pathway calcium ATPase

Secretory pathway calcium ATPase (SPCA) 1 was found to be associated with basal-like breast cancers, which had the poorest prognosis with minimal therapeutic agents available. Increased expression of insulin-like growth factor receptor was identified in a study to possess a strong involvement in cancer initiation, proliferation and resistance to anti-cancer therapy. This finding had provided a window of opportunity to place SPCA1 as a new therapeutic target for basal-like breast cancer. The main aims were to fully understand the role of SPCA1 in basal-like breast cancer and to design, synthesise and test chemical compounds that would inhibit the growth of basal-like breast cancer cells in vitro. Additional focus was also placed on discovering sarcoplasmic-endoplasmic reticulum calcium ATPase (SERCA) inhibitors to streamline the drug discovery process. The use of molecular modelling, virtual screening, chemical synthesis and biological assays had assisted with the decision of selecting potential compounds. At least three out of seven tested compounds had an effect on the intracellular calcium signals. However, the potency and selectivity of these compounds would need to be improved to become better SERCA inhibitors. Therefore more future work is warranted to further refine the potency and selectivity of these compounds on the target receptors

Identification of Contractile Vacuole Proteins in Trypanosoma cruzi

Contractile vacuole complexes are critical components of cell volume regulation and have been shown to have other functional roles in several free-living protists. However, very little is known about the functions of the contractile vacuole complex of the parasite Trypanosoma cruzi, the etiologic agent of Chagas disease, other than a role in osmoregulation. Identification of the protein composition of these organelles is important for understanding their physiological roles. We applied a combined proteomic and bioinfomatic approach to identify proteins localized to the contractile vacuole. Proteomic analysis of a T. cruzi fraction enriched for contractile vacuoles and analyzed by one-dimensional gel electrophoresis and LC-MS/MS resulted in the addition of 109 newly detected proteins to the group of expressed proteins of epimastigotes. We also identified different peptides that map to at least 39 members of the dispersed gene family 1 (DGF-1) providing evidence that many members of this family are simultaneously expressed in epimastigotes. Of the proteins present in the fraction we selected several homologues with known localizations in contractile vacuoles of other organisms and others that we expected to be present in these vacuoles on the basis of their potential roles. We determined the localization of each by expression as GFP-fusion proteins or with specific antibodies. Six of these putative proteins (Rab11, Rab32, AP180, ATPase subunit B, VAMP1, and phosphate transporter) predominantly localized to the vacuole bladder. TcSNARE2.1, TcSNARE2.2, and calmodulin localized to the spongiome. Calmodulin was also cytosolic. Our results demonstrate the utility of combining subcellular fractionation, proteomic analysis, and bioinformatic approaches for localization of organellar proteins that are difficult to detect with whole cell methodologies. The CV localization of the proteins investigated revealed potential novel roles of these organelles in phosphate metabolism and provided information on the potential participation of adaptor protein complexes in their biogenesis

Spatiotemporal calcium-dynamics in presynaptic terminals

This thesis deals with a newly-developed model for the spatiotemporal calcium dynamics within presynaptic terminals. The model is based on single-protein kinetics and has been used to successfully describe different neuron types such as pyramidal neurons in the rat neocortex and the Calyx of Held of neurons from the rat brainstem. A limited number of parameters had to be adjusted to fluorescence measurements of the calcium concentration. These values can be interpreted as a prediction of the model, and in particular the protein densities can be compared to independent experiments. The contribution of single proteins to the total calcium dynamics has been analysed in detail for voltage-dependent calcium channel, plasma-membrane calcium ATPase, sodium-calcium exchanger, and endogenous as well as exogenous buffer proteins. The model can be used to reconstruct the unperturbed calcium dynamics from measurements using fluorescence indicators. The calcium response to different stimuli has been investigated in view of its relevance for synaptic plasticity. This work provides a first step towards a description of the complete synaptic transmission using single-protein data

Deciphering Regulatory Networks in the Mouse Genome

Regardless of all the major achievements in the field of genomics and in depth studies of the protein-coding genes, our knowledge about non-coding regions and their contribution in diseases remains incomplete. Large scale projects such as the ENCODE have produced a wealth of sequencing data which can be utilised to study epigenetic features associated with gene regulation. These studies have comprehensively identified regulatory elements such as enhancers in the human genome, but numerous questions still remain on their effect on gene function and disease causation. The aim of this thesis is to identify enhancer regulatory networks in the mouse genome and investigate their effect on mouse models of human diseases. In order to study enhancer regulation, I have taken two approaches. First, I have produced a catalogue of well-defined multiple enhancer types in a diverse range of mouse tissues and cell-types. By systematically comparing different enhancer types, I found that super- and typical-enhancers have different effect on gene expression, but both are preferentially associated with relevant tissue-type phenotypes. Also genes associated with super- and typical-enhancers exhibit no difference in phenotype effect size or pleiotropy. Second, by utilising publicly available regulatory annotations, my enhancer catalogue and omics data, I have investigated regulatory mechanisms associated with metabolic and circadian mouse models. Here I identified novel regulatory networks or enhancers or transcription factor binding sites pertaining to the mutant mice. In conclusion, my research has shown the usefulness of integrating enhancer annotations with an array of molecular data and has for the first time shown how different enhancer architectures influence gene function in the mouse genome. This study provides a valuable dataset to further characterise the mechanisms of gene regulation by enhancers in the mouse genome

Assessing the Benefits of Extra-pair Mating for Female Purple Martins (Progne subis)

Approximately 75% of socially monogamous passerines pursue extra-pair mating with the frequency of extra-pair paternity varying among and within taxonomic groups. Despite the ubiquity of extra-pair mating systems, substantial research into the subject has produced mixed results and the benefits to females remain elusive. Two genetic benefits hypotheses, the good genes hypothesis and heterozygosity theory, predict that extra-pair offspring (EPO) should generally be more fit than within-pair offspring (WPO). This study aims to test for genetic-based benefits to extra-pair mating in purple martins (Progne subis) by comparing EPO and WPO. Specifically, I compare the first year survival estimates of EPO and WPO and of those offspring that are recruited into the breeding population, I compare the reproductive success of EPO and WPO. I found no differences in first-year survival probability nor did I find any differences in reproductive success between EPO and WPO. I conclude that female purple martins are not benefiting from extra-pair mating through the improved survival or reproductive success of their offspring. Such benefits may be context-dependent or historical contexts in which the benefits of extra-pair mating for females may no longer exist for this semi-domesticated species

A Mighty Small Heart: The Cardiac Proteome of Adult Drosophila melanogaster

Drosophila melanogaster is emerging as a powerful model system for the study of cardiac disease. Establishing peptide and protein maps of the Drosophila heart is central to implementation of protein network studies that will allow us to assess the hallmarks of Drosophila heart pathogenesis and gauge the degree of conservation with human disease mechanisms on a systems level. Using a gel-LC-MS/MS approach, we identified 1228 protein clusters from 145 dissected adult fly hearts. Contractile, cytostructural and mitochondrial proteins were most abundant consistent with electron micrographs of the Drosophila cardiac tube. Functional/Ontological enrichment analysis further showed that proteins involved in glycolysis, Ca2+-binding, redox, and G-protein signaling, among other processes, are also over-represented. Comparison with a mouse heart proteome revealed conservation at the level of molecular function, biological processes and cellular components. The subsisting peptidome encompassed 5169 distinct heart-associated peptides, of which 1293 (25%) had not been identified in a recent Drosophila peptide compendium. PeptideClassifier analysis was further used to map peptides to specific gene-models. 1872 peptides provide valuable information about protein isoform groups whereas a further 3112 uniquely identify specific protein isoforms and may be used as a heart-associated peptide resource for quantitative proteomic approaches based on multiple-reaction monitoring. In summary, identification of excitation-contraction protein landmarks, orthologues of proteins associated with cardiovascular defects, and conservation of protein ontologies, provides testimony to the heart-like character of the Drosophila cardiac tube and to the utility of proteomics as a complement to the power of genetics in this growing model of human heart disease