Exploring the Impact of Social Influence Mechanisms and Network Density on Societal Polarization

I present an agent-based model, inspired by the opinion dynamics(OD) literature, to explore the underlying behaviors that may inducesocietal polarization. My agents interact on a social network, in whichadjacent nodes can influence each other, and each agent holds an arrayof continuous opinion values (on a 0-1 scale) on a number of separateissues. I use three measures as a proxy for the virtual society’s “po-larization:” the average assortativity of the graph with respect to theagents’ opinions, the number of non-uniform issues, and the numberof distinct opinion buckets in which agents have the same opinionsafter the model reaches an equilibrium.I look at multiple model parameters that affect polarization. Thefirst is the density of edges in the network: this corresponds to theaverage number of meaningful social connections that agents in a so-ciety have. First, I find that lower edge density results in higher levelsof assortativity for Erd ̈os-R ́enyi graphs. The second is the level of“openness” and “disgust” of agents to differing opinions; i.e., howclose or distant a neighboring node’s opinion on an issue must be toan agent’s own before the agent will adjust its opinion on a different is-sue. I refer to this novel mechanism as cross-issue influence. Throughthis mechanism, I find that when agents in the model are less opento new opinions, there will be less consensus on any given issue forall agents in the model. Additionally, I find that there will be fewerdistinct opinion buckets and therefore higher polarization in modelswhere agents follow a cross-issue influence mechanism compared tosame-issue influence

The Greenhouse Effect: What is the Relationship between Media Attention and Supreme Court Law Clerk Diversity?

This study will explore the power of media attention in relation to diversity of the clerk cohort to understand the factors that impact Supreme Court law clerk diversity

Blood coagulation factor X exerts differential effects on adenovirus entry into human lymphocytes

It has been proposed that blood coagulation factors, principally factor X (FX), enhance the uptake of human adenovirus type 5 (Ad5) into cultured epithelial cells by bridging the viral hexon capsid protein and cell-surface heparan sulphate proteoglycans (HSPGs). We studied the effects of FX on Ad transduction of lymphoid cell lines (NK92MI, a natural killer cell line; Daudi, a B-cell line and Jurkat, a T-cell line) as well as primary peripheral blood lymphocytes (PBL) and HeLa epithelial cells using either replication-deficient Ad5, or a derivative in which the Ad5 fiber was replaced with that of another Ad type, Ad35, termed Ad5F35. PBL and NK92MI were resistant to Ad5 transduction. Transduction of Jurkat and Daudi cells by Ad5 was reduced by FX but without discernible effects on cell-surface Ad5 binding. FX reduced virus binding and transduction of all lymphoid cell lines by Ad5F35, as well as transduction of the T- and Natural Killer (NK)-cell populations of PBL. Flow cytometry analysis showed that all lymphoid cell lines were negative for HSPG components, in contrast to HeLa cells. FX reduced transduction of an HSPG-negative mutant Chinese hamster ovary cell line (CHOpgsA745) by Ad5 and Ad5F35, with Ad5F35 binding also being reduced by FX. These results point to fiber-dependent differences (Ad5 versus Ad35 fiber) in Ad binding to and transduction of human lymphoid and epithelial cells in the presence of FX

Predicting and Preventing Breakoff in Web Surveys

Due to recent general shifts from mail to the web in survey data collection modes, respondents who break off prior to completing web surveys have become a more prevalent problem in data collection. Given the already lower response rates in web surveys as compared to more traditional modes, such as face-to-face interviewing, it is crucial to keep as many diverse respondents in a web survey as possible. This action will help prevent breakoff bias, and thus maintain high data quality and produce more accurate survey estimates. To prevent and reduce web survey breakoffs, Chapter 4 of this dissertation aimed to understand the breakoff process and its associated variables. The typical breakoff respondent: tended to be female; was non-white; was a student; waited for email reminders to start the questionnaire; and answered on a mobile device. Respondents who had broken off the questionnaire in previous waves were more likely to quit the questionnaire again very early on. Based on the findings from Chapter 4, predictions were then made about breakoff timing at the page-level in the second paper. In addition to well-known factors associated with breakoff, such as using a mobile device, Chapter 5 examined the relationships of previous response behaviors like speeding and item nonresponse with breakoff timing. This allowed for predictions about the risk of quitting for each respondent at the page-level using Cox survival models. Male respondents tended to quit at the beginning of the questionnaire, while female respondents had a higher risk of quitting toward the end of the questionnaire. There was no significant difference in breakoff risks between mobile respondents and non-mobile respondents at the beginning of the questionnaire. This quickly changed with every page completed by mobile respondents. Item nonresponse and extensive scrolling behavior were both positively associated with the risk of breaking off. Short response times and response time changes (speeding up and slowing down) both increased the risk of quitting the questionnaire. Finally, in a real-time experiment implemented for Chapter 6, interventions were conducted with respondents who had a high predicted probability of breaking off from a web survey. For this approach, a prediction model was implemented in the next wave of a panel study, and this model evaluated the risk of breaking off on every page for each respondent in addition to comparing the estimated risk with an established threshold. If the estimated risk exceeded the threshold, then the respondents saw a motivational pop-up message reminding them of their commitment to completing the questionnaire. Females, students, Blacks, and respondents on mobile devices reacted positively when assigned to the treatment group and showed less undesirable response behavior than respondents in the control group. The dissertation concludes with recommendations for practice and suggested directions for future work in this area.PHDSurvey MethodologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149963/1/fmitter_1.pd

Can conversational interviewing improve survey response quality without increasing interviewer effects?

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141370/1/rssa12255_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141370/2/rssa12255.pd

Ground Source Heat Pump Sub-Slab Heat Exchange Loop Performance in a Cold Climate

This report presents a cold-climate project that examines an alternative approach to ground source heat pump (GSHP) ground loop design. The innovative ground loop design is an attempt to reduce the installed cost of the ground loop heat exchange portion of the system by containing the entire ground loop within the excavated location beneath the basement slab. Prior to the installation and operation of the sub-slab heat exchanger, energy modeling using TRNSYS software and concurrent design efforts were performed to determine the size and orientation of the system. One key parameter in the design is the installation of the GSHP in a low-load home, which considerably reduces the needed capacity of the ground loop heat exchanger. This report analyzes data from two cooling seasons and one heating season. Upon completion of the monitoring phase, measurements revealed that the initial TRNSYS simulated horizontal sub-slab ground loop heat exchanger fluid temperatures and heat transfer rates differed from the measured values. To determine the cause of this discrepancy, an updated model was developed utilizing a new TRNSYS subroutine for simulating sub-slab heat exchangers. Measurements of fluid temperature, soil temperature, and heat transfer were used to validate the updated model

Modelling Energy Consumption based on Resource Utilization

Power management is an expensive and important issue for large computational infrastructures such as datacenters, large clusters, and computational grids. However, measuring energy consumption of scalable systems may be impractical due to both cost and complexity for deploying power metering devices on a large number of machines. In this paper, we propose the use of information about resource utilization (e.g. processor, memory, disk operations, and network traffic) as proxies for estimating power consumption. We employ machine learning techniques to estimate power consumption using such information which are provided by common operating systems. Experiments with linear regression, regression tree, and multilayer perceptron on data from different hardware resulted into a model with 99.94\% of accuracy and 6.32 watts of error in the best case.Comment: Submitted to Journal of Supercomputing on 14th June, 201

Cross-species genomic and functional analyses identify a combination therapy using a CHK1 inhibitor and a ribonucleotide reductase inhibitor to treat triple-negative breast cancer

INTRODUCTION: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that is diagnosed in approximately 15% of all human breast cancer (BrCa) patients. Currently, no targeted therapies exist for this subtype of BrCa and prognosis remains poor. Our laboratory has previously identified a proliferation/DNA repair/cell cycle gene signature (Tag signature) that is characteristic of human TNBC. We hypothesize that targeting the dysregulated biological networks in the Tag gene signature will lead to the identification of improved combination therapies for TNBC. METHODS: Cross-species genomic analysis was used to identify human breast cancer cell lines that express the Tag signature. Knock-down of the up-regulated genes in the Tag signature by siRNA identified several genes that are critical for TNBC cell growth. Small molecule inhibitors to two of these genes were analyzed, alone and in combination, for their effects on cell proliferation, cell cycle, and apoptosis in vitro and tumor growth in vivo. Synergy between the two drugs was analyzed by the Chou-Talalay method. RESULTS: A custom siRNA screen was used to identify targets within the Tag signature that are critical for growth of TNBC cells. Ribonucleotide reductase 1 and 2 (RRM1 and 2) and checkpoint kinase 1 (CHK1) were found to be critical targets for TNBC cell survival. Combination therapy, to simultaneously attenuate cell cycle checkpoint control through inhibition of CHK1 while inducing DNA damage with gemcitabine, improved therapeutic efficacy in vitro and in xenograft models of TNBC. CONCLUSIONS: This combination therapy may have translational value for patients with TNBC and improve therapeutic response for this aggressive form of breast cancer

Retargeted adenoviruses for radiation-guided gene delivery

The combination of radiation with radiosensitizing gene delivery or oncolytic viruses promises to provide an advantage that could improve the therapeutic results for glioblastoma. X-rays can induce significant molecular changes in cancer cells. We isolated the GIRLRG peptide that binds to radiation-inducible 78 kDa glucose-regulated protein (GRP78), which is overexpressed on the plasma membranes of irradiated cancer cells and tumor-associated microvascular endothelial cells. The goal of our study was to improve tumor-specific adenovirus-mediated gene delivery by selectively targeting the adenovirus binding to this radiation-inducible protein. We employed an adenoviral fiber replacement approach to conduct a study of the targeting utility of GRP78-binding peptide. We have developed fiber-modified adenoviruses encoding the GRP78-binding peptide inserted into the fiber-fibritin. We have evaluated the reporter gene expression of fiber-modified adenoviruses in vitro using a panel of glioma cells and a human D54MG tumor xenograft model. The obtained results demonstrated that employment of the GRP78-binding peptide resulted in increased gene expression in irradiated tumors following infection with fiber-modified adenoviruses, compared with untreated tumor cells. These studies demonstrate the feasibility of adenoviral retargeting using the GRP78-binding peptide that selectively recognizes tumor cells responding to radiation treatment

Enhancement of CD4+ T Cell Function as a Strategy for Improving Antibiotic Therapy Efficacy in Tuberculosis: Does It Work?

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) remains a major public health problem worldwide due in part to the lack of an effective vaccine and to the lengthy course of antibiotic treatment required for successful cure. Combined immuno/chemotherapeutic intervention represents a major strategy for developing more effective therapies against this important pathogen. Because of the major role of CD4+ T cells in containing Mtb infection, augmentation of bacterial specific CD4+ T cell responses has been considered as an approach in achieving this aim. Here we present new data from our own research aimed at determining whether boosting CD4+ T cell responses can promote antibiotic clearance. In these studies, we first characterized the impact of antibiotic treatment of infected mice on Th1 responses to major Mtb antigens and then performed experiments aimed at sustaining CD4+ T cell responsiveness during antibiotic treatment. These included IL-12 infusion, immunization with ESAT-6 and Ag85B immunodominant peptides and adoptive transfer of Th1-polarized CD4+ T cells specific for ESAT-6 or Ag85B during the initial month of chemotherapy. These approaches failed to enhance antibiotic clearance of Mtb, indicating that boosting Th1 responses to immunogenic Mtb antigens highly expressed by actively dividing bacteria is not an effective strategy to be used in the initial phase of antibiotic treatment, perhaps because replicating organisms are the first to be eliminated by the drugs. These results are discussed in the context of previously published findings addressing this concept along with possible alternate approaches for harnessing Th1 immunity as an adjunct to chemotherapy