The Design and Analysis of Partner Studies of HIV Transmission

Common goals in epidemiologic studies of infectious diseases include identification of the infectious agent, description of the modes of transmission and characterization of factors that influence the probability of transmission from infected to uninfected individuals. In the case of AIDS, the agent has been identified as the Human Immunodeficiency Virus (HIV), and transmission is known to occur through a variety of contact mechanisms including unprotected sexual intercourse, transfusion of infected blood products and sharing of needles in intravenous drug use. Relatively little is known about the probability of IV transmission associated with the various modes of contact, or the role that other cofactors play in promoting or suppressing transmission. Here, transmission probability refers to the probability that the virus is transmitted to a susceptible individual following exposure consisting of a series of potentially infectious contacts. The infectivity of HIV for a given route of transmission is defined to be the per contact probability of infection. Knowledge of infectivity and its relationship to other factors is important in understanding the dynamics of the AIDS epidemic and in suggesting appropriate measures to control its spread. The primary source of empirical data about infectivity comes from sexual partners of infected individuals. Partner studies consist of a series of such partnerships, usually heterosexual and monogamous, each composed of an initially infected "index case" and a partner who may or may not be infected by the time of data collection. However, because the infection times of both partners may be unknown and the history of contacts uncertain, any quantitative characterization of infectivity is extremely difficult. Thus, most statistical analyses of partner study data involve the simplifying assumption that infectivity is a constant common to all partnerships. The major objectives of this work are to describe and discuss the design and analysis of partner studies, providing a general statistical framework for investigations of infectivity and risk factors for HIV transmission. The development is largely based on three papers: Jewell and Shiboski (1990), Kim and Lagakos (1990), and Shiboski and Jewell (1992).

The double-stranded RNA-activated protein kinase mediates radiation resistance in mouse embryo fibroblasts through nuclear factor kappaB and Akt activation

PURPOSE: Activation of the double-stranded RNA-activated protein kinase (PKR) leads to the induction of various pathways including the down-regulation of translation through phosphorylation of the eukaryotic translation initiation factor 2alpha (eIF-2alpha). There have been no reports to date about the role of PKR in radiation sensitivity. EXPERIMENTAL DESIGN: A clonogenic survival assay was used to investigate the sensitivity of PKR mouse embryo fibroblasts (MEF) to radiation therapy. 2-Aminopurine (2-AP), a chemical inhibitor of PKR, was used to inhibit PKR activation. Nuclear factor-kappaB (NF-kappaB) activation was assessed by electrophoretic mobility shift assay (EMSA). Expression of PKR and downstream targets was examined by Western blot analysis and immunofluorescence. RESULTS: Ionizing radiation leads to dose- and time-dependent increases in PKR expression and function that contributes to increased cellular radiation resistance as shown by clonogenic survival and terminal nucleotidyl transferase-mediated nick end labeling (TUNEL) apoptosis assays. Specific inhibition of PKR with the chemical inhibitor 2-AP restores radiation sensitivity. Plasmid transfection of the PKR wild-type (wt) gene into PKR(-/-) MEFs leads to increased radiation resistance. The protective effect of PKR to radiation may be mediated in part through NF-kappaB and Akt because both NF-kappaB and Akt are activated after ionizing radiation in PKR+/+ but not PKR-/- cells. CONCLUSIONS: We suggest a novel role for PKR as a mediator of radiation resistance modulated in part through the protective effects of NF-kappaB and Akt activation. The modification of PKR activity may be a novel strategy in the future to overcome radiation resistance.

Vibro-acoustical analysis and design of a multiple-layer constrained viscoelastic damping structure

The goal of this research is to provide a framework for vibro-acoustical analysis and design of a multiple-layer constrained damping structure. The existing research on damping and viscoelastic damping mechanism is limited to the following four mainstream approaches: modeling techniques of damping treatments/materials; control through the electrical-mechanical effect using the piezoelectric layer; optimization by adjusting the parameters of the structure to meet the design requirements; and identification of the damping material’s properties through the response of the structure. This research proposes a systematic design methodology for the multiple-layer constrained damping beam giving consideration to vibro-acoustics. A modeling technique to study the vibro-acoustics of multiple-layered viscoelastic laminated beams using the Biot damping model is presented using a hybrid numerical model. The boundary element method (BEM) is used to model the acoustical cavity whereas the Finite Element Method (FEM) is the basis for vibration analysis of the multiple-layered beam structure. Through the proposed procedure, the analysis can easily be extended to other complex geometry with arbitrary boundary conditions. The nonlinear behavior of viscoelastic damping materials is represented by the Biot damping model taking into account the effects of frequency, temperature and different damping materials for individual layers. A curve-fitting procedure used to obtain the Biot constants for different damping materials for each temperature is explained. The results from structural vibration analysis for selected beams agree with published closed-form results and results for the radiated noise for a sample beam structure obtained using a commercial BEM software is compared with the acoustical results of the same beam with using the Biot damping model. The extension of the Biot damping model is demonstrated to study MDOF (Multiple Degrees of Freedom) dynamics equations of a discrete system in order to introduce different types of viscoelastic damping materials. The mechanical properties of viscoelastic damping materials such as shear modulus and loss factor change with respect to different ambient temperatures and frequencies. The application of multiple-layer treatment increases the damping characteristic of the structure significantly and thus helps to attenuate the vibration and noise for a broad range of frequency and temperature. The main contributions of this dissertation include the following three major tasks: 1) Study of the viscoelastic damping mechanism and the dynamics equation of a multilayer damped system incorporating the Biot damping model. 2) Building the Finite Element Method (FEM) model of the multiple-layer constrained viscoelastic damping beam and conducting the vibration analysis. 3) Extending the vibration problem to the Boundary Element Method (BEM) based acoustical problem and comparing the results with commercial simulation software.

Engineering design motivations : a qualitative and quantitative analysis of university students

What motivates students to perform and pursue engineering design tasks? This study examines this question by way of three Learning Through Service (LTS) programs: 1) an on-going longitudinal study examining the impacts of service on engineering students, 2) an on-going analysis of an international senior design capstone program, and 3) an on-going evaluation of an international graduate-level research program. The evaluation of these programs incorporates both qualitative and quantitative methods, utilizing surveys, questionnaires, and interviews, which help to provide insight on what motivates students to do engineering design work. The quantitative methods were utilized in analyzing various instruments including: a Readiness assessment inventory, Intercultural Development Inventory, Sustainable Engineering through Service Learning survey, the Impacts of Service on Engineering Students’ survey, Motivational narratives, as well as some analysis for interview text. The results of these instruments help to provide some much needed insight on how prepared students are to participate in engineering programs. Additional qualitative methods include: Word clouds, Motivational narratives, as well as interview analysis. This thesis focused on how these instruments help to determine what motivates engineering students to pursue engineering design tasks. These instruments aim to collect some more in-depth information than the quantitative instruments will allow. Preliminary results suggest that of the 120 interviews analyzed Interest/Enjoyment, Application of knowledge and skills, as well as gaining knowledge are key motivating factors regardless of gender or academic level. Together these findings begin to shed light on what motivates students to perform engineering design tasks, which can be applied for better recruitment and retention in university programs.

Design, construction, and testing of a research quality electric machine testbed

With energy demands and costs growing every day, the need for improving energy efficiency in electrical devices has become very important. Research into various methods of improving efficiency for all electrical components will be a key to meet future energy needs. This report documents the design, construction, and testing of a research quality electric machine dynamometer and test bed. This test cell system can be used for research in several areas including: electric drives systems, electric vehicle propulsion systems, power electronic converters, load/source element in an AC Microgrid, as well as many others. The test cell design criteria, and decisions, will be discussed in reference to user functionality and flexibility. The individual power components will be discussed in detail to how they relate to the project, highlighting any feature used in operation of the test cell. A project timeline will be discussed, clearly stating the work done by the different individuals involved in the project. In addition, the system will be parameterized and benchmark data will be used to provide the functional operation of the system. With energy demands and costs growing every day, the need for improving energy efficiency in electrical devices has become very important. Research into various methods of improving efficiency for all electrical components will be a key to meet future energy needs. This report documents the design, construction, and testing of a research quality electric machine dynamometer and test bed. This test cell system can be used for research in several areas including: electric drives systems, electric vehicle propulsion systems, power electronic converters, load/source element in an AC Microgrid, as well as many others. The test cell design criteria, and decisions, will be discussed in reference to user functionality and flexibility. The individual power components will be discussed in detail to how they relate to the project, highlighting any feature used in operation of the test cell. A project timeline will be discussed, clearly stating the work done by the different individuals involved in the project. In addition, the system will be parameterized and benchmark data will be used to provide the functional operation of the system.

Testing Wisconsin asphalt mixtures for the 2002 AASHTO mechanistic design procedure

There has been a continuous evolutionary process in asphalt pavement design. In the beginning it was crude and based on past experience. Through research, empirical methods were developed based on materials response to specific loading at the AASHO Road Test. Today, pavement design has progressed to a mechanistic-empirical method. This methodology takes into account the mechanical properties of the individual layers and uses empirical relationships to relate them to performance. The mechanical tests that are used as part of this methodology include dynamic modulus and flow number, which have been shown to correlate with field pavement performance. This thesis was based on a portion of a research project being conducted at Michigan Technological University (MTU) for the Wisconsin Department of Transportation (WisDOT). The global scope of this project dealt with the development of a library of values as they pertain to the mechanical properties of the asphalt pavement mixtures paved in Wisconsin. Additionally, a comparison with the current associated pavement design to that of the new AASHTO Design Guide was conducted. This thesis describes the development of the current pavement design methodology as well as the associated tests as part of a literature review. This report also details the materials that were sampled from field operations around the state of Wisconsin and their testing preparation and procedures. Testing was conducted on available round robin and three Wisconsin mixtures and the main results of the research were: The test history of the Superpave SPT (fatigue and permanent deformation dynamic modulus) does not affect the mean response for both dynamic modulus and flow number, but does increase the variability in the test results of the flow number. The method of specimen preparation, compacting to test geometry versus sawing/coring to test geometry, does not statistically appear to affect the intermediate and high temperature dynamic modulus and flow number test results. The 2002 AASHTO Design Guide simulations support the findings of the statistical analyses that the method of specimen preparation did not impact the performance of the HMA as a structural layer as predicted by the Design Guide software. The methodologies for determining the temperature-viscosity relationship as stipulated by Witczak are sensitive to the viscosity test temperatures employed. The increase in asphalt binder content by 0.3% was found to actually increase the dynamic modulus at the intermediate and high test temperature as well as flow number. This result was based the testing that was conducted and was contradictory to previous research and the hypothesis that was put forth for this thesis. This result should be used with caution and requires further review. Based on the limited results presented herein, the asphalt binder grade appears to have a greater impact on performance in the Superpave SPT than aggregate angularity. Dynamic modulus and flow number was shown to increase with traffic level (requiring an increase in aggregate angularity) and with a decrease in air voids and confirm the hypotheses regarding these two factors. Accumulated micro-strain at flow number as opposed to the use of flow number appeared to be a promising measure for comparing the quality of specimens within a specific mixture. At the current time the Design Guide and its associate software needs to be further improved prior to implementation by owner/agencies.

MIMO waveform design using continuous phase modulation

Hybrid MIMO Phased-Array Radar (HMPAR) is an emerging technology that combines MIMO (multiple-in, multiple-out) radar technology with phased-array radar technology. The new technology is in its infancy, but much of the theoretical work for this specific project has already been completed and is explored in great depth in [1]. A brief overview of phased-array radar systems, MIMO radar systems, and the HMPAR paradigm are explored in this paper. This report is the culmination of an effort to support research in MIMO and HMPAR utilizing a concept called intrapulse beamscan. Using intrapulse beamscan, arbitrary spatial coverage can be achieved within one MIMO beam pulse. Therefore, this report focuses on designing waveforms for MIMO radar systems with arbitrary spatial coverage using that phenomenon. With intrapulse beamscan, scanning is done through phase-modulated signal design within one pulse rather than phase-shifters in the phased array over multiple pulses. In addition to using this idea, continuous phase modulation (CPM) signals are considered for their desirable peak-to-average ratio property as well as their low spectral leakage. These MIMO waveforms are designed with three goals in mind. The first goal is to achieve flexible spatial coverage while utilizing intrapulse beamscan. As with almost any radar system, we wish to have flexibility in where we send our signal energy. The second goal is to maintain a peak-to-average ratio close to 1 on the envelope of these waveforms, ensuring a signal that is close to constant modulus. It is desired to have a radar system transmit at the highest available power; not doing so would further diminish the already very small return signals. The third goal is to ensure low spectral leakage using various techniques to limit the bandwidth of the designed signals. Spectral containment is important to avoid interference with systems that utilize nearby frequencies in the electromagnetic spectrum. These three goals are realized allowing for limitations of real radar systems. In addition to flexible spatial coverage, the report examines the spectral properties of utilizing various space-filling techniques for desired spatial areas. The space-filling techniques examined include Hilbert/Peano curves and standard raster scans.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

Semantic Methods for Intelligent Distributed Design Environments

Continuous advancements in technology have led to increasingly comprehensive and distributed product development processes while in pursuit of improved products at reduced costs. Information associated with these products is ever changing, and structured frameworks have become integral to managing such fluid information. Ontologies and the Semantic Web have emerged as key alternatives for capturing product knowledge in both a human-readable and computable manner. The primary and conclusive focus of this research is to characterize relationships formed within methodically developed distributed design knowledge frameworks to ultimately provide a pervasive real-time awareness in distributed design processes. Utilizing formal logics in the form of the Semantic Web’s OWL and SWRL, causal relationships are expressed to guide and facilitate knowledge acquisition as well as identify contradictions between knowledge in a knowledge base. To improve the efficiency during both the development and operational phases of these “intelligent” frameworks, a semantic relatedness algorithm is designed specifically to identify and rank underlying relationships within product development processes. After reviewing several semantic relatedness measures, three techniques, including a novel meronomic technique, are combined to create AIERO, the Algorithm for Identifying Engineering Relationships in Ontologies. In determining its applicability and accuracy, AIERO was applied to three separate, independently developed ontologies. The results indicate AIERO is capable of consistently returning relatedness values one would intuitively expect. To assess the effectiveness of AIERO in exposing underlying causal relationships across product development platforms, a case study involving the development of an industry-inspired printed circuit board (PCB) is presented. After instantiating the PCB knowledge base and developing an initial set of rules, FIDOE, the Framework for Intelligent Distributed Ontologies in Engineering, was employed to identify additional causal relationships through extensional relatedness measurements. In a conclusive PCB redesign, the resulting “intelligent” framework demonstrates its ability to pass values between instances, identify inconsistencies amongst instantiated knowledge, and identify conflicting values within product development frameworks. The results highlight how the introduced semantic methods can enhance the current knowledge acquisition, knowledge management, and knowledge validation capabilities of traditional knowledge bases.

Design and Impact of Awareness Functions – A Study about Social Media in Virtual Teams

The usage of social media in leisure time settings has become a prominent research topic. However, less research has been done on the design of social media in collaboration settings. In this study, we investigate how social media can support asynchronous collaboration in virtual teams and specifically how they can increase activity awareness. On the basis of an open source social networking platform, we present two prototype designs: a standard platform with basic support for information processing, communication and process – as suggested by Zigurs and Buckland (1998) – and an advanced platform with additional support for activity awareness via specialfeed functions. We argue that the standard platform already conveys activity awareness to a certain extent, however, that this awareness can be increased even more by the feeds in the advanced platform. Both prototypes are tested in a field experiment and evaluated with respect to their impact on perceived activity awareness, coordination and satisfaction. We show that the advanced design increases coordination and satisfaction through increased perceived activity awareness.

Comparing growth trajectories of risk behaviors from late adolescence through young adulthood: An accelerated design

Risk behaviors such as substance use or deviance are often limited to the early stages of the life course. Whereas the onset of risk behavior is well studied, less is currently known about the decline and timing of cessation of risk behaviors of different domains during young adulthood. Prevalence and longitudinal developmental patterning of alcohol use, drinking to the point of drunkenness, smoking, cannabis use, deviance, and HIV-related sexual risk behavior were compared in a Swiss community sample (N = 2,843). Using a longitudinal cohort-sequential approach to link multiple assessments with 3 waves of data for each individual, the studied period spanned the ages of 16 to 29 years. Although smoking had a higher prevalence, both smoking and drinking up to the point of drunkenness followed an inverted U-shaped curve. Alcohol consumption was also best described by a quadratic model, though largely stable at a high level through the late 20s. Sexual risk behavior increased slowly from age 16 to age 22 and then remained largely stable. In contrast, cannabis use and deviance linearly declined from age 16 to age 29. Young men were at higher risk for all behaviors than were young women, but apart from deviance, patterning over time was similar for both sexes. Results about the timing of increase and decline as well as differences between risk behaviors may inform tailored prevention programs during the transition from late adolescence to adulthood.

DOES THE MESSAGE MATTER? ENHANCING PATIENT ADHERENCE THROUGH PERSUASIVE MESSAGES

To improve health and reduce costs, we need to encourage patients to make better healthcare decisions. Many informatics interventions are aimed at improving health outcomes by influencing patient behavior. However, we know little about how the content of a message in these interventions can influence a health-related decision. In this research we formulate a conceptual model to help explain and guide the design of “persuasive messages”, those which can change and influence patient behavior. We apply the conceptual model to design persuasive appointment reminder messages using humancentered design principles. Finally, we empirically test our hypotheses in a randomized controlled trial in order to determine the effectiveness of persuasive appointment reminders to reduce the number of missed appointments in a sample of 1016 subjects in a community health center. The results of the study confirm that reminder messages are effective in reducing missed appointment compared with no reminders (p=0.028). Further, reminder messages that incorporate heuristic cues such as authority, commitment, liking, and scarcity are more effective than reminder messages without such cues (p=0.006). However, the addition of systematic arguments or reasons for attending appointments have no effect on appointment adherence (p=0.646). The results of this research suggest that the content of reminder messages may be an important factor in helping to reduce missed appointments.