Dealing With Many Species: Improving Methodology For Forming And Assessing Species Complexes

In the United States, the Magnuson-Stevens Reauthorization Act mandates that all federally fished species must have catch limits, which can be challenging for data-limited species. One approach is to assess and manage a group of species with similar life history characteristics, vulnerability to the fishery, and overlapping geographic distributions in a single management unit, or a complex (i.e., stock or species complex). Using the Gulf of Alaska (GOA) Other Rockfish complex as a case study, the main goals of this dissertation are five-fold: 1) review species complexes in the United States; 2) compare multivariate techniques for assigning species to complexes; 3) group species based on spatial and temporal patterns using a new application of a species distribution model (i.e., Vector Autoregressive Spatio-Temporal model, VAST, model); 4) compare catch advice between existing assessment models used for species complexes with that from the new spatio-temporal modelling (i.e., VAST) application; 5) refine management advice on appropriate species groupings and associated catch limits for this complex. In Chapter 1 a review was undertaken of all managed and assessed complexes in the United States, thereby identifying regional differences in management strategies and assessment models used to set catch limits for established complexes. The remaining chapters focused on the GOA Other Rockfish, a group of 27 Sebastes species. In Chapter 2, a suite of multivariate methods (e.g., cluster analyses and ordination techniques) was developed and applied on an array of datasets (e.g., life history values, fishery-dependent catch, and fishery-independent surveys), to examine how species groupings can vary depending on the methods or data utilized. Results indicated that the species composition for the two main gear types, trawl and longline gear, were different. Chapter 3 addressed the complex membership using a spatio-temporal species distribution model, which was used to investigate the temporal and spatial relationships among species and compared with groupings based on harvest fractions and life history values. Main results for species groupings were consistent across methods from Chapter 2 and 3, suggesting that rockfish belonging to a sub-group of the GOA Other Rockfish (i.e., members of the Demersal Shelf Rockfish) should be removed and managed separately from the Other Rockfish complex throughout the GOA management area. Using the resultant complexes, Chapter 4 compared two assessment models for the GOA Other Rockfish: the currently used random effects model and a newly, developed spatio-temporal model (VAST). While the results of this research are specific to the GOA Other Rockfish, the lessons and recommendations are applicable to other complexes with similar data availability. Multiple data sources and a variety of methods should be used to identify or verify complex membership, where the best species groupings are those that are consistent across all analyses. Variation in groupings across analytical methods and data inputs can provide further insight into data needs or species that warrant careful monitoring. Additionally, new assessment models for species complexes should be explored and tested to ensure results adequately reflect the status of the complex and provide reasonable harvest limits

Prediction intervals for fractionally integrated time series and volatility models

The two of the main formulations for modeling long range dependence in volatilities associated with financial time series are fractionally integrated generalized autoregressive conditional heteroscedastic (FIGARCH) and hyperbolic generalized autoregressive conditional heteroscedastic (HYGARCH) models. The traditional methods of constructing prediction intervals for volatility models, either employ a Gaussian error assumption or are based on asymptotic theory. However, many empirical studies show that the distribution of errors exhibit leptokurtic behavior. Therefore, the traditional prediction intervals developed for conditional volatility models yield poor coverage. An alternative is to employ residual bootstrap-based prediction intervals. One goal of this dissertation research is to develop methods for constructing such prediction intervals for both returns and volatilities under FIGARCH and HYGARCH model formulations. In addition, this methodology is extended to obtain prediction intervals for autoregressive moving average (ARMA) and fractionally integrated autoregressive moving average (FARIMA) models with a FIGARCH error structure. The residual resampling is done via a sieve bootstrap approach, which approximates the ARMA and FARIMA portions of the models with an AR component. AIC criteria is used to find order of the finite AR approximation on the conditional mean process. The advantage of the sieve bootstrap method is that it does not require any knowledge of the order of the conditional mean process. However, we assume that the order of the FIGARCH part is known. Monte- Carlo simulation studies show that the proposed methods provide coverages closed to the nominal values --Abstract, page iv

Data Transmission Scheduling For Distributed Simulation Using Packet A

Communication bandwidth and latency reduction techniques are developed for Distributed Interactive Simulation (DIS) protocols. Using logs from vignettes simulated by the OneSAF Testbed Baseline (OTB), a discrete event simulator based on the OMNeT++ modeling environment is developed to analyze the Protocol Data Unit (PDU) traffic over a wireless flying Local Area Network (LAN). Alternative PDU bundling and compression techniques are studied under various metrics including slack time, travel time, queue length, and collision rate. Based on these results, Packet Alloying, a technique for the optimized bundling of packets, is proposed and evaluated. Packet Alloying becomes more active when it is needed most: during negative spikes of transmission slack time. It produces aggregations that preserve the internal PDU format, allowing the resulting packets to be subjectable to further bundling and/or compression by conventional techniques. To optimize the selection of bundle delimitation, three online predictive strategies were developed: Neural-Network based, Always-Wait, and Always-Send. These were compared with three offline strategies defined as Type, Type-Length and Type-Length-Size. Applying Always-Wait to the studied vignette using the wireless links set to 64 Kbps, a reduction in the magnitude of negative slack time from -75 to -9 seconds for the worst spike was achieved, which represents a reduction of 88 %. Similarly, at 64 Kbps, Always-Wait reduced the average satellite queue length from 2,963 to 327 messages for a 89% reduction. From the analysis of negative slack-time spikes it was determined which PDU types are of highest priority. The router and satellite queues in the case study were modified accordingly using a priority-based transmission scheduler. The analysis of total travel times based of PDU types numerically shows the benefit obtained. The contributions of this dissertation include the formalization of a selective PDU bundling scheme, the proposal and study of different predictive algorithms for the next PDU, and priority-based optimization using Head-of-Line (HoL) service. These results demonstrate the validity of packet optimizations for distributed simulation environments and other possible applications such as TCP/IP transmissions

Doctor of Philosophy

dissertationAn introduction to Scanning Probe Microscopy is given along with some basic principles in the detection of electron tunneling by Atomic Force Microscopy (AFM) using electrostatic force. Dynamic Tunneling Force Microscopy (DTFM), a new scanned probe force-detected tunneling technique, is presented and described, in which shuttling of electrons between electron trap states and a conductive AFM probe provides a means to image these trap states with subnanometer spatial resolution. The further development of Single Electron Tunneling Force Spectroscopy (SETFS) is described, providing a method to measure the energy of electronic trap states. It is used to find the energy spectrum of individual monolayer-protected gold clusters. A novel technique is presented whereby the electron trap states' depth and energy are independently determined using SETFS. Finally, a new technique is described and explored, by which "single spin" electron spin resonance measurements can in principle be performed. The method employs the detection of magnetic resonance through spin dependent tunneling, providing a means to identify individual paramagnetic electron states in dielectric films with atomic spatial resolution

A Computational Fluid Dynamics Investigation of Hemolysis Potential in a Microfluidic Hemoperfusion Device Designed for Use in Sepsis Treatment

The potential of red blood cell (RBC) and platelet damage was studied for a novel microfluidic hemoperfusion device currently in development at Oregon State University for use in treating sepsis. COMSOL 4.4's computational fluid dynamics (CFD) module was used to examine shear rate profiles in laminar, Newtonian blood flow throughout pre-specified lamina dimensions. The shear rates observed were converted into blood damage statistics using the average residence time and equations that estimates (1) total fraction of hemolysis and (2) critical shear stress at which hemolysis begins to take place. The resulting hemolysis values for the current flow rate (0.3mL/min) and a hematocrit of 45% were 0.0148% of RBCs and 0.00122% of platelets. For 65% hematocrit, hemolysis values increased to 0.0511% for RBCs and 0.00591% for platelets. In terms of the critical threshold for hemolysis to start occurring, in 45% hematocrit flow, shear stresses applied to RBCs reached only 6.65% of the critical threshold for hemolysis; platelets reached 11.4% of that threshold. At 65% hematocrit, RBCs and platelets reached 11.1% and 18.9% of the critical threshold respectively. Thus, it can be initially concluded that the mechanical stresses in the current lamina design do not produce significant levels of blood hemolysis

The protective gene dose effect of the APOE ε2 allele on gray matter volume in cognitively unimpaired individuals

INTRODUCTION: Harboring two copies of the apolipoprotein E (APOE) ε2 allele strongly protects against Alzheimer's disease (AD). However, the effect of this genotype on gray matter (GM) volume in cognitively unimpaired individuals has not yet been described. METHODS: Multicenter brain magnetic resonance images (MRIs) from cognitively unimpaired ε2 homozygotes were matched (1:1) against all other APOE genotypes for relevant confounders (n = 223). GM volumes of ε2 genotypic groups were compared to each other and to the reference group (APOE ε3/ε3). RESULTS: Carrying at least one ε2 allele was associated with larger GM volumes in brain areas typically affected by AD and also in areas associated with cognitive resilience. APOE ε2 homozygotes, but not APOE ε2 heterozygotes, showed larger GM volumes in areas related to successful aging. DISCUSSION: In addition to the known resistance against amyloid-β deposition, the larger GM volumes in key brain regions may confer APOE ε2 homozygotes additional protection against AD-related cognitive decline

Deposition of amyloid β in the walls of human leptomeningeal arteries in relation to perivascular drainage pathways in cerebral amyloid angiopathy

Deposition of amyloid beta (AB) in the walls of cerebral arteries as cerebral amyloid angiopathy (CAA) suggests an age-related failure of perivascular drainage of soluble A? from the brain. As CAA is associated with Alzheimer's disease and with intracerebral haemorrhage, the present study determines the unique sequence of changes that occur as A? accumulates in artery walls. Paraffin sections of post-mortem human occipital cortex were immunostained for collagen IV, fibronectin, nidogen 2, AB and smooth muscle actin and the immunostaining was analysed using Image J and confocal microscopy. Results showed that nidogen 2 (entactin) increases with age and decreases in CAA. Confocal microscopy revealed stages in the progression of CAA: AB initially deposits in basement membranes in the tunica media, replaces first the smooth muscle cells and then the connective tissue elements to leave artery walls completely or focally replaced by AB. The pattern of development of CAA in the human brain suggests expansion of AB from the basement membranes to progressively replace all tissue elements in the artery wall. Establishing this full picture of the development of CAA is pivotal in understanding the clinical presentation of CAA and for developing therapies to prevent accumulation of AB in artery walls. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock

Factors influencing loyalty intention behaviours of online social buying consumers in South Africa

Social buying is a recent marketing innovation in which provides Pareto-improving welfare gains to merchants, consumers, and brokers. Consumers benefit from access to significant discounts on advertised products and services, the broker benefits from taking a significant cut in each transaction with very low fixed costs, and merchants are able to reduce their advertising costs, gain access to new markets and drive traffic to their stores. The phenomenal growth of social buying carries commensurate risks for brokers, including increased competition due to a lack of service differentiation and low entry barriers. The complete social buying transaction is completed over two stages: the initial online e-commerce transaction and the subsequent fulfilment transaction where the voucher is redeemed with the merchant. In order to explore the sustainability of the social buying business model, it is necessary to identify the factors which drive loyalty behaviours in social buying, as well as the interrelationships between the factors. This research proposes from the marketing literature Oliver’s (1980) expectancy-disconfirmation theory (EDT) as the main theoretical framework on which to model these relationships. EDT is then successfully synthesised with DeLone and McLean’s (2003) information systems success model to create a framework which can appropriately model both the online and traditional stages of the social buying transaction. This study contributes to the marketing literature by establishing EDT as a suitable framework for investigating social buying. It is believed that this study is the first to do so. Furthermore, it is believed this is the first study examining the social buying innovation in the South African context.Graduate School of Business LeadershipM.B.A