Social Fingerprinting: Identifying Users of Social Networks by their Data Footprint

This research defines, models, and quantifies a new metric for social networks: the social fingerprint. Just as one\u27s fingers leave behind a unique trace in a print, this dissertation introduces and demonstrates that the manner in which people interact with other accounts on social networks creates a unique data trail. Accurate identification of a user\u27s social fingerprint can address the growing demand for improved techniques in unique user account analysis, computational forensics and social network analysis. In this dissertation, we theorize, construct and test novel software and methodologies which quantify features of social network data. All approaches and methodologies are framed to test the accuracy of social fingerprint identification. Further, we demonstrate and verify that features of anonymous data trails observed on social networks are unique identifiers of social network users. Lastly, this research delivers scalable technology for future research in social network analysis, business analytics and social fingerprinting

Social-Ecological Change, Resilience, and Adaptive Capacity in the McKenzie River Valley, Oregon

This study explores perceptions of long-term residents regarding links between governance, landscape, and community change in the McKenzie River Valley (MRV) in western Oregon and provides a general assessment of factors affecting resilience and adaptive capacity. Residents interviewed indicated that dramatic changes driven by market competition, timber industry changes, increased regulation, and rural restructuring have occurred in both the landscape and community. The changes that have transpired have redefined the relationship between the community and the landscape, moving away from local dependence on timber harvests to an economy focused on tourism and other ecosystem services. In doing so the community has transitioned from one with a logging community identity to one that has begrudgingly become a retirement and vacation community. We found that the social-ecological system (SES) in the MRV is still in the midst of reorganization in the wake of the 1990s Timber Wars. As a result of low institutional capacity, the system is vulnerable to exogenous drivers of change. Using a modified version of Ostrom’s (2009) framework for SES analysis, this study recommends policymakers and policy entrepreneurs take three key steps to facilitate enhanced resilience and adaptive capacity: 1) support transboundary management strategies that transcend landownership classifications; 2) tighten system feedbacks to include more local influence; and 3) develop local multilayered institutions organized vertically and horizontally. Future research should explore the potential for collaborative forestry and stewardship contracting to enhance social-ecological resilience in this valley

Computational Ranking of Yerba Mate Small Molecules Based on Their Predicted Contribution to Antibacterial Activity against Methicillin-Resistant Staphylococcus aureus

The aqueous extract of yerba mate, a South American tea beverage made from Ilex paraguariensis leaves, has demonstrated bactericidal and inhibitory activity against bacterial pathogens, including methicillin-resistant Staphylococcus aureus (MRSA). The gas chromatography-mass spectrometry (GC-MS) analysis of two unique fractions of yerba mate aqueous extract revealed 8 identifiable small molecules in those fractions with antimicrobial activity. For a more comprehensive analysis, a data analysis pipeline was assembled to prioritize compounds for antimicrobial testing against both MRSA and methicillin-sensitive S.aureus using forty-two unique fractions of the tea extract that were generated in duplicate, assayed for activity, and analyzed with GC-MS. As validation of our automated analysis, we checked our predicted active compounds for activity in literature references and used authentic standards to test for antimicrobial activity. 3,4-dihydroxybenzaldehyde showed the most antibacterial activity against MRSA at low concentrations in our bioassays. In addition, quinic acid and quercetin were identified using random forests analysis and 5-hydroxy pipecolic acid was identified using linear discriminant analysis. We also generated a ranked list of unidentified compounds that may contribute to the antimicrobial activity of yerba mate against MRSA. Here we utilized GC-MS data to implement an automated analysis that resulted in a ranked list of compounds that likely contribute to the antimicrobial activity of aqueous yerba mate extract against MRSA

The Linked Data Benchmark Council (LDBC): Driving competition and collaboration in the graph data management space

Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements, including the need for a concise query language and graph-aware query optimization techniques. The goal of the Linked Data Benchmark Council (LDBC) is to design a set of standard benchmarks that capture representative categories of graph data management problems, making the performance of systems comparable and facilitating competition among vendors. LDBC also conducts research on graph schemas and graph query languages. This paper introduces the LDBC organization and its work over the last decade

The Linked Data Benchmark Council (LDBC): Driving competition and collaboration in the graph data management space

Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements, including the need for a concise query language and graph-aware query optimization techniques. The goal of the Linked Data Benchmark Council (LDBC) is to design a set of standard benchmarks that capture representative categories of graph data management problems, making the performance of systems comparable and facilitating competition among vendors. LDBC also conducts research on graph schemas and graph query languages. This paper introduces the LDBC organization and its work over the last decade

Top 20 unique retention times ranked by antimicrobial significance against MRSA using random forests.

<p>Top 20 unique retention times ranked by antimicrobial significance against MRSA using random forests.</p

Overlay of initial yerba mate extract fraction chromatograms.

<p>A) The black chromatogram corresponds to a yerba mate extract fraction that demonstrated antibacterial activity against methicillin-resistant <i>Staphylococcus aureus</i> (MRSA); the red chromatogram corresponds to a yerba mate fraction that had no antibacterial activity against MRSA. B) Retention times of identified compounds and quantification in sorbitol equivalents were reported.</p