As social networks become more prevalent, there is significant interest in studying these network data, the focus often being on detecting anomalous events. This area of research is referred to as social network surveillance or social network change detection. While there are a variety of proposed methods suitable for different monitoring situations, two important issues have yet to be completely addressed in network surveillance literature. First, performance assessments using simulated data to evaluate the statistical performance of a particular method. Second, the study of aggregated data in social network surveillance. The research presented tackle these issues in two parts, evaluation of a popular anomaly detection method and investigation of the effects of different aggregation levels on network anomaly detection. / Ph. D. / Social networks are increasingly becoming a part of our normal lives. These networks contain a wealth of information that can be immensely useful in a variety of areas, from targeting a specific audience for advertisement, to apprehending criminals, to detecting terrorist activities. The research presented focus evaluating popular methods on monitoring these social networks, and the potential information loss one might encounter when only limited information can be collected over a specific time period, we present our commendations on social network monitoring that are applicable to a wide range of scenarios as well.

<p dir="ltr">Alpha-synuclein protein aggregation, involving the recruitment of native monomeric protein by fibrillar seeds, has been proposed as the event that precipitates Parkinson’s disease pathology. However, the specific molecular processes underlying this aggregation are not fully understood, mirroring the limitations seen in understanding the etiology of other prion-like neurodegenerative diseases. There are proposed mechanisms connecting alpha-synuclein aggregation to endocytic processes involving the escape and retention of fibrillar seeds. Additionally, intracellular protein-membrane interactions may also play a role. However, effective methods to probe the evolution of aggregation states with sufficient sensitivity in the context of these cellular processes are lacking.</p><p dir="ltr">A time-gated fluorescence lifetime imaging microscope system was developed to monitor the evolution of seeded aggregation in primary neurons in the context of endocytic processes that have yet to be well explored. This aggregation monitoring was enabled by measuring self-quenching-induced fluorescence lifetime changes of alpha-synuclein-fluorophore fusion proteins, providing a sensitive aggregate detection method. Results from this work demonstrate that both escape and retention of fibrillar seeds from endocytic compartments are seeding pathways for aggregation. In addition, a novel imaging scheme was developed using fluorescence lifetime measurements of tethered Förster resonance energy transfer (FRET) reporters to probe membrane-induced alpha-synuclein aggregation. Using this method in neurons enabled deciphering of which intracellular membrane surfaces likely play a role in alpha-synuclein aggregation.</p><p dir="ltr">This work used fluorescence lifetime imaging to enable insights into the underlying mechanisms of alpha-synuclein aggregation in neurons. This has broader applications to other prion-like neurodegenerative diseases. These insights further our understanding of neurodegenerative disease etiology and can inform more effective treatments. Additionally, an approach to noise estimation that enables accurate extraction of fluorescence lifetime information in the presence of substantial detector noise is presented. This will enable longer-term multi-time-point fluorescence lifetime imaging of aggregation in neurons.</p>

Recently, there has been a massive growth in the number of mobile users and their traffic. The data traffic volume almost doubles every year. Mobile users are currently running multiple applications that require higher bandwidth which makes users so limited to the service providers' resources. Increasing the utilization of the existing spectrum can significantly improve network capacity, data rates and user experience. Spectrum sharing enables wireless systems to harvest under-utilized swathes of spectrum, which would vastly increase the efficiency of spectrum usage. Making more spectrum available can provide significant gain in mobile broadband capacity only if those resources can be aggregated efficiently with the existing commercial mobile system resources. Carrier aggregation (CA) is one of the most distinct features of 4G systems including Long Term Evolution Advanced (LTE-Advanced). In this dissertation, a resource allocation with carrier aggregation framework is proposed to allocate multiple carriers resources optimally among users with elastic and inelastic traffic in cellular networks. We use utility proportional fairness allocation policy, where the fairness among users is in utility percentage of the application running on the user equipment (UE). A resource allocation (RA) with CA is proposed to allocate single or multiple carriers resources optimally among users subscribing for mobile services. Each user is guaranteed a minimum quality of service (QoS) that varies based on the user's application type. In addition, a resource allocation with user discrimination framework is proposed to allocate single or multiple carriers resources among users running multiple applications. Furthermore, an application-aware resource block (RB) scheduling with CA is proposed to assign RBs of multiple component carriers to users' applications based on a utility proportional fairness scheduling policy. We believe that secure spectrum auctions can revolutionize the spectrum utilization of cellular networks and satisfy the ever increasing demand for resources. Therefore, a framework for multi-tier dynamic spectrum sharing system is proposed to provide an efficient sharing of spectrum with commercial wireless system providers (WSPs) with an emphasis on federal spectrum sharing. The proposed spectrum sharing system (SSS) provides an efficient usage of spectrum resources, manages intra-WSP and inter-WSP interference and provides essential level of security, privacy, and obfuscation to enable the most efficient and reliable usage of the shared spectrum. It features an intermediate spectrum auctioneer responsible for allocating resources to commercial WSPs' base stations (BS)s by running secure spectrum auctions. In order to insure truthfulness in the proposed spectrum auction, an optimal bidding mechanism is proposed to enable BSs (bidders) to determine their true bidding values. We also present a resource allocation based on CA approach to determine the BS's optimal aggregated rate allocated to each UE from both the BS's permanent resources and winning auctioned spectrum resources. / Ph. D.

Cardinality estimation is a fundamental task in database query processing and optimization. As shown in recent papers, machine learning (ML)-based approaches may deliver more accurate cardinality estimations than traditional approaches. However, a lot of training queries have to be executed during the model training phase to learn a data-dependent ML model making it very time-consuming. Many of those training or example queries use the same base data, have the same query structure, and only differ in their selective predicates. To speed up the model training phase, our core idea is to determine a predicate-independent pre-aggregation of the base data and to execute the example queries over this pre-aggregated data. Based on this idea, we present a specific aggregate-based training phase for ML-based cardinality estimation approaches in this paper. As we are going to show with different workloads in our evaluation, we are able to achieve an average speedup of 90 with our aggregate-based training phase and thus outperform indexes.

Over the past several decades conservation easements have seen immense growth in their popularity. There are now over 40 million acres of easement land in the United States, up from only 1.4 million in 1998. A significant body of research exists on easements, factors that lead to their adoption, their consequences and effectiveness, and problems that arise from their use, among other topics. Our study contributes to this literature by exploring community and system-level effects on easement adoption, using Virginia as a case study, and applying a novel approach that incorporates spatial analysis and the insights of conservation professionals. The purpose of our research was to explore whether community-level factors affect easement adoption decisions, and what those factors are. Previously established variables were investigated to gauge their relationship to easement occurrence when scaled up to the community level, as well as to test our ability to make predictions about where easements should be most likely to occur. Spatial market segmentation data was also incorporated into this analysis to determine whether it could augment our understanding of community-level factors and predictive ability. Statistical models produced were reasonably predictive. However, we suspect that this was the case for different reasons at our community scale of analysis than at the individual landowner level examined in previous research. We used surveys and interviews with easement professionals to further explore additional variables that might explain adoption patterns. Results indicate the importance of system-level factors including change agents, opinion leaders, and local government and land-use planning. / Master of Science / Conservation easements are an increasingly common form of land protection. Unlike traditional conservation methods that involve directly purchasing and protecting land, such as national parks and forests, conservation easements allow private individuals to maintain ownership of their property while also ensuring that that land is conserved, remaining both undeveloped and unsubdivided. Our research was aimed at investigating whether communitylevel social factors might affect the ability and interest of landowners to adopt easements, and we focused our efforts on the state of Virginia. A combination of information collected through surveys and interviews with conservation professionals from across the state and publically available data were used to address the topic. Our results contained important lessons for conservationists and researchers alike. One such lesson was the apparent propensity for landowners who are more likely to adopt easements to have characteristics different, and sometimes even opposite, the general characteristics of people living in their surrounding community. Other lessons included the identification of community-level factors that affect the likelihood of easement adoption, including the presence of influential community members, and the support or opposition of local governments and land-use planning to easements.

No / This paper reports on the growth of benzamide crystals in the presence of 2'-aminoacetophenone. The resulting self-replicating intergrowth of benzamide crystals gives rise to ordered crystal aggregates in which individuals share a common c*. This behavior is interpreted using the concept of a motif capper additive which is able to halt the extension of structural motifs at the surface of a growing crystal. In this case the additive was selected to terminate the hydrogen-bonding ribbons, which extend along the b axis of the benzamide structure.

No / Biosimilar pharmaceuticals are complex biological molecules that have similar physicochemical properties to the originator therapeutic protein. They are produced by complex multi-stage processes and are not truly equivalent. Therefore, for a biosimilar to be approved for market it is important to demonstrate that the biological product is highly similar to a reference product. This includes its primary and higher order structures and its aggregation behaviour. Representative lots of both the proposed biosimilar and the reference product are analysed to understand the lot-to-lot variability of both drug substances in the manufacturing processes. Whilst it is not easy to characterise every variation of a protein structure at present additional analytical technologies need to be utilised to ensure the safety and efficacy of any potential biosimilar product. We have explored the use of Taylor dispersion analysis (TDA) to analyse such batch to batch variations in the model protein, bovine serum albumin (BSA) and compared the results to that obtained by conventional dynamic light scattering analysis (DLS). Inter and intra batch differences were evident in all grades of BSA analysed. However, the reproducibility of the TDA measurements, enabled the stability and reversibility of BSA aggregates to be more readily monitored. This demonstrates that Taylor dispersion analysis is a very sensitive technique to study higher order protein states and aggregation. The results, here, also indicate a correlation between protein purity and the physical behaviour of the samples after heat shocking. Here, the protein with the highest quoted purity resulted in a reduced increase in the measured hydrodynamic radius after heat stressing, indicating that less unfolding/aggregation had occurred. Whilst DLS was also able to observe the presence of aggregates, its bias towards larger aggregates indicated a much larger increase in hydrodynamic radii and is less sensitive to small changes in hydrodynamic radii. TDA was also able to identify low levels of larger aggregates that were not observed by DLS. Therefore, given the potential for immunogenicity effects that may result from such aggregates it is suggested that TDA may be suitable in the evaluating detailed batch to batch variability and process induced physical changes of biopharmaceuticals and biosimilars.

Yes / The recent advancements in wireless sensor hardware ensures sensing multiple sensor data such as temperature, pressure, humidity, etc. using a single hardware unit, thus defining it as multi-sensor data communication in wireless sensor networks (WSNs). The in-processing technique of data aggregation is crucial in energy-efficient WSNs; however, with the requirement of end-to-end data confidentiality it may prove to be a challenge. End-to-end data confidentiality along with data aggregation is possible with the implementation of a special type of encryption scheme called privacy homomorphic (PH) encryption schemes. This paper proposes an optimized PH encryption scheme for WSN integrated networks handling multi-sensor data. The proposed scheme ensures light-weight payloads, significant energy and bandwidth consumption along with lower latencies. The performance analysis of the proposed scheme is presented in this paper with respect to the existing scheme. The working principle of the multi-sensor data framework is also presented in this paper along with the appropriate packet structures and process. It can be concluded that the scheme proves to decrease the payload size by 56.86% and spend an average energy of 8-18 mJ at the aggregator node for sensor nodes varying from 10-50 thereby ensuring scalability of the WSN unlike the existing scheme.

Parkinson's Disease (PD) is a neurodegenerative disorder characterized by motor and nonmotor symptoms, including gastrointestinal (GI) dysfunction. Symptoms such as constipation, bloating, and nausea often show early signs before the onset of motor symptoms. Recent research has suggested an essential role of the human gut microbiome and gut dysbiosis, an imbalance in gut microbiota composition, in the pathogenesis of PD. This thesis aims to assess the potential relationship between gut dysbiosis and PD by conducting a meta-analysis, focusing on differences in gut microbiota between PD patients and healthy controls and evaluating their implications for GI dysfunction and PD progression. The primary objectives of this meta-analysis are to (1) compare gut microbiota composition between PD patients and healthy controls via quantitative statistical metrics; (2) identify bacterial taxa differences and their functional roles; (3) assess whether these changes support the hypothesis that gut dysbiosis contributes to α-synuclein (α-SYN) aggregation and PD progression; and (4) evaluate the impact of study methodology and heterogeneity on the reported outcomes. The results revealed no statistically significant differences in alpha diversity between PD patients and controls, likely influenced by substantial heterogeneity across studies. However, specific bacterial taxa were consistently altered, with increased levels of pro-inflammatory bacteria and decreased levels of SCFA-producing bacteria in PD patients. This meta-analysis provides insights into the potential role of gut dysbiosis in PD, suggesting that changes in specific bacterial taxa may contribute to gut inflammation, increased gut permeability, and α-SYN aggregation. The findings highlight the complexity of the gut-brain axis in PD and the need for further longitudinal studies to understand the underlying mechanisms and explore targeted therapeutic intervention.

Ischemia followed by reperfusion, as happens in myocardial infarction, or the development of acute respiratory distress syndrome, are associated with a exaggerated extravasation of leukocytes into the surrounding tissue , which may cause severe bystander damage. In animal models of these diseases, pharmacological blockage of the leukocyte adhesion molecule, L-selectin (CD62L), has been shown to be partially protective by reduction or inhibition of leukocyte-mediated secondary tissue damage. The aim of this project was the development of an in vitro assay to investigate the relative effectiveness of potential L-selectin antagonists. Ideally, the assay should require low sample volumes and allow for measurements of larger series of reagents. The assay system investigated was based on the homotypic granulocyte aggregation under shear stress, which mimicks the L-selectin-dependent adhesion of leukocytes to previously arrested neutrophils on vascular endothelium. After optimizing numerous variables of the aggregation assay, the requirement of L-selectin for the homotypic granulocyte aggregation induced was demonstrated by inhibition experiments using soluble L-selectin or monoclonal antibodies directed against the lectin domain of L-selectin. Several carbohydrate polymers with L-selectin binding properties, such as the seaweed-derived fucose polymer fucoidin, high-molecular-weight dextran sulfate or heparin, also inhibited neutrophil aggregation in a dose-dependent fashion. However, despite employing a flow cytometry-based read-out technique, the assay remained extremely labor intensive, precluding investigations of extended series. Therefore, the homotypic aggregation experiments with freshly isolated human granulocytes remains a useful tool to further evaluate specific questions of L-selectin dependent adhesion processes, but it is not apt for transfer into routine laboratories.