Evidence-based management of bullous pemphigoid

Bullous pemphigoid (BP) is the most common autoimmune subepidermal bullous disease typically affecting the elderly. Although different therapeutic regimens have been proposed, a review of the evidence is needed to aid clinicians in their decision making and management. Systemic therapies such as corticosteroids and adjuvants are effective in BP but are plagued with adverse effects, and potent topical steroids are an alternative treatment. This article reviews the evidence supporting different therapeutic options in the management of BP.

Fidelity of Implementation of Research-Based Instructional Strategies (RBIS) in Engineering Science Courses

Background Increasing attention is being paid to improvement in undergraduate science, technology, engineering, and mathematics (STEM) education through increased adoption of research-based instructional strategies (RBIS), but high-quality measures of faculty instructional practice do not exist to monitor progress. Purpose/Hypothesis The measure of how well an implemented intervention follows the original is called fidelity of implementation. This theory was used to address the research questions: What is the fidelity of implementation of selected RBIS in engineering science courses? That is, how closely does engineering science classroom practice reflect the intentions of the original developers? Do the critical components that characterize an RBIS discriminate between engineering science faculty members who claimed use of the RBIS and those who did not? Design/Method A survey of 387 U.S. faculty teaching engineering science courses (e.g., statics, circuits, thermodynamics) included questions about class time spent on 16 critical components and use of 11 corresponding RBIS. Fidelity was quantified as the percentage of RBIS users who also spent time on corresponding critical components. Discrimination between users and nonusers was tested using chi square. Results Overall fidelity of the 11 RBIS ranged from 11% to 80% of users spending time on all required components. Fidelity was highest for RBIS with one required component: case-based teaching, just-in-time teaching, and inquiry learning. Thirteen of 16 critical components discriminated between users and nonusers for all RBIS to which they were mapped. Conclusions Results were consistent with initial mapping of critical components to RBIS. Fidelity of implementation is a potentially useful framework for future work in STEM undergraduate education.

Multi-node TOA-DOA cooperative LOS-NLOS localization : enabling high accuracy and reliability

This dissertation investigates high performance cooperative localization in wireless environments based on multi-node time-of-arrival (TOA) and direction-of-arrival (DOA) estimations in line-of-sight (LOS) and non-LOS (NLOS) scenarios. Here, two categories of nodes are assumed: base nodes (BNs) and target nodes (TNs). BNs are equipped with antenna arrays and capable of estimating TOA (range) and DOA (angle). TNs are equipped with Omni-directional antennas and communicate with BNs to allow BNs to localize TNs; thus, the proposed localization is maintained by BNs and TNs cooperation. First, a LOS localization method is proposed, which is based on semi-distributed multi-node TOA-DOA fusion. The proposed technique is applicable to mobile ad-hoc networks (MANETs). We assume LOS is available between BNs and TNs. One BN is selected as the reference BN, and other nodes are localized in the coordinates of the reference BN. Each BN can localize TNs located in its coverage area independently. In addition, a TN might be localized by multiple BNs. High performance localization is attainable via multi-node TOA-DOA fusion. The complexity of the semi-distributed multi-node TOA-DOA fusion is low because the total computational load is distributed across all BNs. To evaluate the localization accuracy of the proposed method, we compare the proposed method with global positioning system (GPS) aided TOA (DOA) fusion, which are applicable to MANETs. The comparison criterion is the localization circular error probability (CEP). The results confirm that the proposed method is suitable for moderate scale MANETs, while GPS-aided TOA fusion is suitable for large scale MANETs. Usually, TOA and DOA of TNs are periodically estimated by BNs. Thus, Kalman filter (KF) is integrated with multi-node TOA-DOA fusion to further improve its performance. The integration of KF and multi-node TOA-DOA fusion is compared with extended-KF (EKF) when it is applied to multiple TOA-DOA estimations made by multiple BNs. The comparison depicts that it is stable (no divergence takes place) and its accuracy is slightly lower than that of the EKF, if the EKF converges. However, the EKF may diverge while the integration of KF and multi-node TOA-DOA fusion does not; thus, the reliability of the proposed method is higher. In addition, the computational complexity of the integration of KF and multi-node TOA-DOA fusion is much lower than that of EKF. In wireless environments, LOS might be obstructed. This degrades the localization reliability. Antenna arrays installed at each BN is incorporated to allow each BN to identify NLOS scenarios independently. Here, a single BN measures the phase difference across two antenna elements using a synchronized bi-receiver system, and maps it into wireless channel’s K-factor. The larger K is, the more likely the channel would be a LOS one. Next, the K-factor is incorporated to identify NLOS scenarios. The performance of this system is characterized in terms of probability of LOS and NLOS identification. The latency of the method is small. Finally, a multi-node NLOS identification and localization method is proposed to improve localization reliability. In this case, multiple BNs engage in the process of NLOS identification, shared reflectors determination and localization, and NLOS TN localization. In NLOS scenarios, when there are three or more shared reflectors, those reflectors are localized via DOA fusion, and then a TN is localized via TOA fusion based on the localization of shared reflectors.

Resource management in location aware cognitive radio networks

Dynamic spectrum access (DSA) aims at utilizing spectral opportunities both in time and frequency domains at any given location, which arise due to variations in spectrum usage. Recently, Cognitive radios (CRs) have been proposed as a means of implementing DSA. In this work we focus on the aspect of resource management in overlaid CRNs. We formulate resource allocation strategies for cognitive radio networks (CRNs) as mathematical optimization problems. Specifically, we focus on two key problems in resource management: Sum Rate Maximization and Maximization of Number of Admitted Users. Since both the above mentioned problems are NP hard due to presence of binary assignment variables, we propose novel graph based algorithms to optimally solve these problems. Further, we analyze the impact of location awareness on network performance of CRNs by considering three cases: Full location Aware, Partial location Aware and Non location Aware. Our results clearly show that location awareness has significant impact on performance of overlaid CRNs and leads to increase in spectrum utilization effciency.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.

Desertification mitigation and water harvesting based on sustainable land management

Traditionally, desertification research has focused on degradation assessments, whereas prevention and mitigation strategies have not sufficiently been emphasised, although the concept of sustainable land management (SLM) is increasingly being acknowledged. SLM strategies are interventions at the local to regional scale aiming at increasing productivity, protecting the natural resource base, and improving livelihoods. The global WOCAT initiative and its partners have developed harmonized frameworks to compile, evaluate and analyse the impact of SLM practices around the globe. Recent studies within the EU research project DESIRE developed a methodological framework that combines a collective learning and decision-making approach with use of best practices from the WOCAT database. In-depth assessment of 30 technologies and 8 approaches from 17 desertification sites enabled an evaluation of how SLM addresses prevalent dryland threats such as water scarcity, soil and vegetation degradation, low production, climate change, resource use conflicts and migration. Among the impacts attributed to the documented technologies, those mentioned most were diversified and enhanced production and better management of water and soil degradation, whether through water harvesting, improving soil moisture, or reducing runoff. Water harvesting offers under-exploited opportunities for the drylands and the predominantly rainfed farming systems of the developing world. Recently compiled guidelines introduce the concepts behind water harvesting and propose a harmonised classification system, followed by an assessment of suitability, adoption and up-scaling of practices. Case studies go from large-scale floodwater spreading that make alluvial plains cultivable, to systems that boost cereal production in small farms, as well as practices that collect and store water from household compounds. Once contextualized and set in appropriate institutional frameworks, they can form part of an overall adaptation strategy for land users. More field research is needed to reinforce expert assessments of SLM impacts and provide the necessary evidence-based rationale for investing in SLM. This includes developing methods to quantify and value ecosystem services, both on-site and off-site, and assess the resilience of SLM practices, as currently aimed at within the new EU CASCADE project.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.