VictorJuiz/thesis huggingface dataset:
Communities in Social Networks: Modelling, Analysis, and Detection

The main subject of this thesis is to study the structure of communities in social networks and to develop community detection algorithms that are highly efficient for real-world graphs. In particular, we are interested in understanding the formation process of a community and its emerging structural patterns. With the knowledge of such structures, it becomes possible to devise efficient community detection algorithms that are faster than the conventional clustering algorithms for generic graphs. We propose a mathematical model for information communities where members interact via the production and consumption of content. Each member allocates their time between production and consumption with the objective of maximizing their individual utilization. We define the community as "stable and efficient" when a Nash equilibrium is reached while the social welfare is maximized. We analyze the conditions for forming a stable and efficient community and the results show that the structure with a "small core of celebrity producers" is optimal among all structures considered. Based on the insights from the analysis, we devise a community detection algorithm for user-item graphs, taking advantage of the structure that assumes the existence of cores. Our algorithm exhibits a sub-quadratic time complexity which is significantly lower than the cubic-time complexity of state-of-the-art quasi-clique based algorithms. The algorithm dramatically reduces the amount of time needed to process the entire graph, making it practical for large-scale inputs. The performance of the algorithm is experimentally evaluated with various real-world datasets. As another attempt to study community structures via mathematical modelling, we model the dynamics of the gender ratio in a workforce as a recursive process characterized by two factors: how strongly a potential candidate is influenced by the observed gender ratio (Factor #1) and how strongly an employer prefers one gender over the other (Factor #2). Our analysis results show that, to avoid the gender ratio converging to single-gender dominance, there are specific requirements on the values of Factor #1 and Factor #2. While not attempting to be comprehensive, this analysis provides some fine-grained insights for future studies on related subjects.

Advisor: Marbach, Peter
Sequence-function Relationships in Intrinsically Disordered Regions through the Lens of Evolution

Intrinsically disordered regions (IDRs) are regions of proteins that do not autonomously fold into stable secondary or tertiary structures. Though they defy the classical view of proteins as rigidly structured macromolecules, IDRs are widespread in living organisms, and are involved in a diverse array of functions. The majority of IDRs appear to be rapidly evolving at the level of the primary amino acid sequence, which makes it difficult to quantify evolutionary conservation and associate these regions with biological function using standard sequence analysis. The aim of my thesis research has thus been to understand evolutionary constraint and sequence-function relationships in IDRs. Using a functionally characterized IDR in the yeast protein Ste50, I first found that highly diverged amino acid sequences can encode conserved phenotypes in IDRs, showing that sequence divergence does not necessarily imply functional divergence in these regions. Using a phylogenetic comparative framework, I found that the net charge of the Ste50 IDR, rather than the precise amino acids, is a functional molecular feature that is preserved over evolution. I next expanded my evolutionary analysis of IDRs to the yeast proteome, and found that most highly diverged IDRs contain many molecular features that are preserved over evolution. I summarized the evolution of these molecular features with an "evolutionary signature" for each IDR, and found that groups of IDRs with similar evolutionary signatures are enriched for specific biological functions. I also found that IDRs with similar evolutionary signatures can rescue function in vivo despite negligible sequence similarity. Finally, I used these evolutionary signatures to train a statistical model, and found that they can be used to classify IDRs for a diverse set of biological functions. I identified the molecular features contributing to these functional predictions, and attributed distinct functions to specific IDRs in proteins with multiple IDRs. Overall, this work shows that there is rich functional information in IDR sequences, and that this information can be revealed through evolutionary analysis.

Keywords: disordered
evolution
protein
signalling
yeast
Advisor: Moses, Alan M
On the Space Complexity of Colourless Tasks

In this thesis, we prove lower bounds on the number of registers needed to solve colourless tasks in asynchronous shared memory systems. Many fundamental synchronization tasks, such as consensus, k-set agreement, and epsilon-approximate agreement, are colourless. We show that it is possible to transform any nondeterministic solo-terminating algorithm (including any randomized wait-free algorithm) into an obstruction-free algorithm that uses the same number of registers. This result extends to algorithms using any finite number of deterministic objects that support read operations. Hence, we can focus on proving lower bounds for obstruction-free algorithms. We prove a tight lower bound on the number of registers needed to solve obstruction-free consensus. We also prove the first non-constant lower bounds on the number of registers needed to solve obstruction-free k-set agreement and obstruction-free epsilon-approximate agreement. The bound for k-set agreement is asymptotically tight when k is a constant and the bound for epsilon-approximate agreement is asymptotically tight when epsilon is sufficiently small. To prove these bounds, we introduce a new technique, revisionist simulations. This technique allows us to prove a general theorem that yields lower bounds on the number of registers needed to solve any colourless task in an obstruction-free manner. Finally, we define the class of extension-based proofs and show that no extension-based proof can establish the impossibility of deterministically solving k-set agreement among n > k > 1 processes in a wait-free manner using registers.

Keywords: colourless tasks
consensus
distributed computing
set agreement
space complexity
Advisor: Ellen, Faith
Mechanisms of Post-transcriptional Control in Mammalian Neural Stem Cells

The diverse types of neurons that populate the mammalian forebrain are the fundamental requirement for the assembly of complex circuitry. However, the mechanisms regulating the genesis of these distinct neuronal populations from neural precursor cells (NPCs) are still not well understood. In this thesis, I address the question of whether post-transcriptional mechanisms regulate neuronal differentiation and fate specification within the developing forebrain. First, I show that embryonic NPCs are transcriptionally primed to make diverse neuronal subtypes, and that a Pum2-4E-T complex represses the translation of neuronal specifier mRNAs to ensure the appropriate temporal specification of daughter neurons. Second, I show that 4E-T mediated translational repression continues to act as a critical regulator of NPC maintenance and differentiation at postnatal stages. Based on the work presented in this thesis, I propose that translational repression mechanisms act to ensure the appropriate differentiation of transcriptionally primed NPCs in response to rapidly changing environmental cues.

Keywords: cell fate specification
immunohistochemistry
neocortex
neural stem cells
post-transcriptional control
single-cell RNA sequencing
Advisor: Miller, Freda
Start-ups as Buyers in Technology Markets: Evidence from the Bio-pharmaceutical Industry

My dissertation studies start-ups’ strategies in the market for technologies, with a focus on their role as technology buyers, in the context of the bio-pharmaceutical industry. The ﬁrst chapter clariﬁes when and what start-ups are likely to buy. Building on the classic assumption that start-ups are most advantaged in developing early-stage technologies and drawing on research examining M resource reconﬁgurations, I argue that start-ups will have opportunities to buy from sellers that experienced recent M events because M resource reconﬁgurations release early-stage technologies that would otherwise be further developed and sold to incumbents when late-staged. To test the predictions, I exploit a novel data set involving 97,202 U.S. bio-pharmaceutical patents, and adopt a quasi-experimental approach, using M that unexpectedly failed to go through. The results show that sellers’ M events increase the probability that a patent will be bought by a start-up by around 50%, a ﬁnding that is driven primarily by an increase in start-ups’ acquisitions of early-stage technologies. The second chapter studies the possible impact of venture capital (VC) backing for start-ups’ probability of buying external technologies. An analysis of nearly 3,137 U.S. bio-pharmaceutical start-ups founded between 1996 and 2012 suggests that start-ups are about 2% more likely to acquire external technologies after they receive VC funding. To address the concern that a ﬁrm’s VC backing status might not be random, I construct an instrumental variable, capturing exogenous variation in VC funding at the MSA level. IV regression results reveal that VC backing status causes over 30% increase in start-ups’ probability of acquiring external technologies. The third chapter examines a puzzle in the literature explaining technology transaction timing: why some quality signals that reduce information asymmetries promote early licensing (e.g., licensors’ alliance experiences), whereas others do not (e.g., patents). By building a formal model and exploiting a novel data set comprising 124 U.S. exclusive licensing agreements announced between 2009 and 2015, I show that patents, in addition to reducing information asymmetry, induce licensors’ over-optimism regarding buyer competition, which delays licensing timing. Overall, my dissertation contributes to a more comprehensive and nuanced understanding of the market for technologies.

Keywords: Entrepreneurial Growth Strategy
Market for Technologies
Start-ups
Technology Acquisition
Advisor: Gans, Joshua
Between Chinese and Western Norms: Local Policy Deliberation and Cross-issue-area Variations in China’s Global Governance Strategies

As a rising power, China sometimes plays an ideational leadership role in global governance by constructing homegrown norms and policy ideas, but at other times it embraces Western global governance norms and rules and even imports them for domestic reforms. When will China provide alternative global governance ideas, and when will it learn from the West? This study argues that varied Chinese global governance strategies are produced by varied trajectories of the local policy deliberation mechanism. Local policy deliberation is a pragmatic mechanism of ideational change taking place within local policy communities (i.e., communities of ministry-level bureaucrats and their advisors). Its trajectories are shaped by two conditions. First, uncertainty build-up and problematization of local orthodoxy trigger local ideational change and determine the scope of change. Second, local policy communities’ evaluations of local-idea-informed policy experiments determine the outcome of policy selection. While local policy communities facing uncertainty tend to prioritize local-centric policy innovation, idea importation incentives emerge when the governance performance of such local-centric innovations are perceived as negative. The two conditions can be influenced by multiple factors but are profoundly shaped by policy communities’ interpretations and interests. I illustrate the theory using a comparative case study and process tracing. In the international development cooperation (IDC) case, two rounds of local policy deliberations have focused on absorbing novel local ideas for policy innovation, and local-centric policy experiments were politically endorsed by a passive local policy community. The products were homegrown IDC norms and practices. In the climate case, although local policy deliberation initially brought in local ideas (i.e., the command and control measure), the governance performance of local-centric policy experiments was seen as negative. This generated strong incentives for importing foreign ideas (e.g., ET). In the finance case, a lack of local financial governance knowledge gave Western actors more influence over Chinese financial policy community’s beliefs from the very beginning. The local commitment to norm integration has been robust since the 1990s.

Keywords: China
climate governance
financial governance
global governance
international development cooperation
norm
Advisor: Hoffmann, Matthew J.
Polyurethane Biomaterial-based Strategies toward Anti-infective Gingival Tissue Constructs

Gingival recession is found in 58% of adults over 30 years old regardless of oral hygiene. Tissue engineering strategies have the potential to overcome the limitations of the current standard of treatment, autologous grafts, among which include tissue shortage and co-morbidity. It is proposed that the gingival connective tissues may be tissue engineered using polyurethane-based scaffold platforms. Polyurethane biomaterials have adaptable chemistry, diverse mechanical properties and suitable biocompatibility and biodegradation characteristics for tissue engineering applications. However, the use of a synthetic material in the infectious oral environment has the potential to lead to biomaterial-associated infections. As such, two different anti-infective scaffold systems will be evaluated in this thesis. In the first system, a degradable polycarbonate urethane (PCNU) was co-electrospun with an antimicrobial oligomer (AO) containing the antibiotic ciprofloxacin (CF) to generate antimicrobial nanofibres. Scaffolds with a higher loading of AO were found to have CF localized on the fibre surfaces which led to a fast release of AO (~100% released within 7 days). Loaded drug was found to slow hydrolysis kinetics of the PCNU scaffolds, and the form of CF loaded was found to significantly affect fibroblast cell attachment, wherein CF incorporated in free form increased cell attachment and spreading on the scaffolds relative to scaffolds with AO. In the second system, a polyurethane-based random pore hydrogel sponge, D-PHI, was used as a scaffold for generating prevascularized gingival constructs via perfusion co-culture of gingival fibroblasts and human vascular endothelial cells (HUVECs) in D-PHI. These constructs are potentially anti-infective in that they will be readily perfused upon implantation so that host defense mechanisms can fight colonization of the scaffold material by plaque bacteria. In an in vivo subcutaneous model, a portion of engineered microvessels in D-PHI were found to be functional (i.e. perfused with host blood and non-leaky) at 14 days after implantation. The investigation of this system demonstrated the critical importance of perfusion flow toward generating engineered microvessels in vitro. The two strategies find similarities in that they both apply synthetic polyurethane materials with unique surface chemistries, geometries, and mechanical properties that allowed for control over their performance as anti-infective gingival constructs in terms of degradation, drug release, cell attachment, and tissue morphogenesis in in vitro models. The peer-reviewed work from this thesis furthers the field’s understanding of polymer-drug and polymer-cell interactions toward optimizing soft tissue constructs for regenerative medicine.

Keywords: antimicrobials
biomaterials
drug delivery
electrospinning
in vivo
tissue engineering
Advisor: Santerre, Paul
Security Entrenchment and the Dynamics of Politicide: Evidence from Indonesia

This dissertation examines variations in violence during politicide. Why do some areas have greater levels of killings and long term detentions than others, controlling for the size of the victim group? Moreover, why do some areas have greater rates of killing relative to detentions? Using process tracing to compare three Indonesian provinces that experienced politicide in 1965-66, I argue these dynamics are shaped by two factors: the degree to which security forces are entrenched at the local level, and the strength of civilian networks willing to collaborate with security forces. The first two chapters develop my theoretical framework, situate it in current debates of mass violence, and outline the methodology used. Chapter three overviews the origins of the Indonesian politicide, in which the Indonesian army killed an estimated 500,000 civilian communist supporters. The following three chapters trace the dynamics of this politicide in Central Java, East Java, and West Java. Through these cases, I demonstrate that low security entrenchment leads to higher levels of violence and higher rates of killing, as security forces lacked the ability to use violence more selectively. The strain of caring for these detainees then poses a logistical problem and incentivizes mass executions. Collaborator networks can further increase killings when security forces are weak by pressuring them to use additional lethal violence or engage in lethal violence unilaterally. I conclude by demonstrating how these findings are likely to apply across cases of politicide more broadly, and reflect on the relationship between security capacity, mass violence, and repression.

Keywords: Genocide
Indonesia
Killing
Mass Violence
PKI
Politicide
Advisor: Bertrand, Jacques
Bayes Factor Approaches for Region-Based Analysis of Rare Variants from Next Generation Sequencing Studies

The emergence of new high-throughput genotyping technologies, such as Next Generation Sequencing (NGS), allows the study of the human genome at an unprecedented depth and scale. The discovery of germline rare variants (RVs) through NGS is a very challenging issue in the field of human genetics. Since RVs have extremely low frequencies, traditional strategies that analyze one variant at a time are underpowered for detecting associations with RVs. Gene-level or region-based statistics can provide a first step in the analysis of RVs that can lead to further experimental validation. Bayesian analysis is not well developed for RV analysis. Our goal in this thesis is to develop such approaches and show their interests for germline RV analyses in the context of case-control studies. Chapter 1 gives a general overview about NGS data analysis and methods for association tests with RV data. In Chapter 2, we propose a novel region-based statistical approach based on the Bayes Factor (BF) to assess evidence of association between a set of RVs located on the same genomic region and a disease outcome in the context of case-control design. We derive the theoretical null distribution of the BF under our prior setting. Informative priors are introduced using prior evidence of association from a Kolmogorov-Smirnov test statistic. In Chapter 3, we introduce a Bayesian procedure to control the False Discovery Rate (BFDR) in the context of genome-wide inference. We develop a simulation program, sim1000G, to generate RV data similar to the 1,000 genomes sequencing project and assess our BFDR procedure. Our simulation studies show that the new BF statistic outperforms standard methods (SKAT, SKAT-O, Burden test) in case-control studies with moderate sample sizes and is equivalent to them under large sample size scenarios. Chapter 4 concludes this thesis with an extension of the BF approach that integrates individual-level and variant-level covariates by using a Bayesian regression approach and inference based on the Integrated Nested Laplace Approximation (INLA). Finally, the interests of our methodological developments are illustrated throughout the thesis by real data applications to a lung cancer case-control study seeking RV association with known and novel cancer genes.

Keywords: Bayesian Analysis
Biostatistical method
False discovery rate
Genome wide association study
Rare genetic variants
Sequencing data
Advisor: Briollais, Laurent
Xu, Wei
MKRN2 Interacts with GLE1 and Negatively Regulates mRNA Nuclear Export and Retinal Development

Canonical mammalian mRNA export is terminated at the cytoplasmic face of the nuclear pore complex. A key factor implicated in mRNA export termination is GLE1, a highly conserved, DEAD-box helicase activator protein. I conducted an affinity-purification mass-spectrometry screen of human RNA-binding E3 ubiquitin ligases from tissue cell cultures, and discovered a novel physical interaction between MKRN2 and a GLE1-containing complex of mRNA export factors. We next assessed GLE1 epistasis with MKRN2 in a genetically tractable zebrafish model. Consistent with an antagonistic relationship between GLE1 and MKRN2, injection of GLE1 morpholinos into zebrafish embryos deficient in MKRN2 rescued or altered the pronounced retinal defects associated with GLE1 depletion. My data therefore implicate MKRN2 as both a novel macromolecular binding partner and putative new negative regulator of GLE1, and by extension mRNA export. To further explore this hypothesis, I subsequently investigated the function of MKRN2 in mRNA processing in human cell lines. Analysis of the RNA-binding activity of MKRN2 by individual-nucleotide resolution crosslinking and immunoprecipitation (iCLIP) established that MKRN2 binds to specific mRNAs directly and predominantly in their 3' untranslated region (3'UTR) in regions enriched for C-rich sequences. Biochemical fractionation and sequencing of transcripts from MKRN2 knockdown cells also revealed that nuclear export of mRNAs bound by MKRN2 was enhanced upon MKRN2 knockdown. Taken together, these results indicate that MKRN2 interacts physically and functionally with GLE1, and other associated widely conserved mRNA export factors, to negatively regulate mRNA export of select target transcripts.

Keywords: GLE1
MKRN2
mRNA export
Retinal development
RNA binding protein
Advisor: Emili, Andrew