Hierarchical Approach for Survivable Network Design

A central design challenge facing network planners is how to select a cost-effective network configuration that can provide uninterrupted service despite edge failures. In this paper, we study the Survivable Network Design (SND) problem, a core model underlying the design of such resilient networks that incorporates complex cost and connectivity trade-offs. Given an undirected graph with specified edge costs and (integer) connectivity requirements between pairs of nodes, the SND problem seeks the minimum cost set of edges that interconnects each node pair with at least as many edge-disjoint paths as the connectivity requirement of the nodes. We develop a hierarchical approach for solving the problem that integrates ideas from decomposition, tabu search, randomization, and optimization. The approach decomposes the SND problem into two subproblems, Backbone design and Access design, and uses an iterative multi-stage method for solving the SND problem in a hierarchical fashion. Since both subproblems are NP-hard, we develop effective optimization-based tabu search strategies that balance intensification and diversification to identify near-optimal solutions. To initiate this method, we develop two heuristic procedures that can yield good starting points. We test the combined approach on large-scale SND instances, and empirically assess the quality of the solutions vis-à-vis optimal values or lower bounds. On average, our hierarchical solution approach generates solutions within 2.7% of optimality even for very large problems (that cannot be solved using exact methods), and our results demonstrate that the performance of the method is robust for a variety of problems with different size and connectivity characteristics.

Design and construction of a new Drosophila species, D.synthetica, by synthetic regulatory evolution

Here, I merge the principles of synthetic biology1,2 and regulatory evolution3-11 to create a new species12-15 with a minimal set of known elements. Using preexisting transgenes and recessive mutations of Drosophila melanogaster, a transgenic population arises with small eyes and a different venation pattern that fulfills the criteria of a new species according to Mayr's "Biological Species Concept"7,10. The genetic circuit entails the loss of a non-essential transcription factor and the introduction of cryptic enhancers. Subsequent activation of those enhancers causes hybrid lethality. The transition from "transgenic organisms" towards "synthetic species", such as Drosophila synthetica, constitutes a safety mechanism to avoid hybridization with wild type populations and preserve natural biodiversity16-18. Drosophila synthetica is the first transgenic organism that cannot hybridize with the original wild type population but remains fertile when crossed with other transgenic animals.

Population-Based Design of Mandibular Plates Based on Bone Quality and Morphology

In this paper we present a new population-based implant design methodology, which advances the state-of-the-art approaches by combining shape and bone quality information into the design strategy. The method enhances the mechanical stability of the fixation and reduces the intra-operative in-plane bending which might impede the functionality of the locking mechanism. The method is presented for the case of mandibular locking fixation plates, where the mandibular angle and the bone quality at screw locations are taken into account. Using computational anatomy techniques, the method automatically derives, from a set of computed tomography images, the mandibular angle and the bone thickness and intensity values at the path of every screw. An optimisation strategy is then used to optimise the two parameters of plate angle and screw position. Results for the new design are presented along with a comparison with a commercially available mandibular locking fixation plate. A statistically highly significant improvement was observed. Our experiments allowed us to conclude that an angle of 126° and a screw separation of 8mm is a more suitable design than the standard 120° and 9mm.

Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials

Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as "mortality," "other objective," "or subjective," and Bayesian hierarchical models were used to estimate associations of trial characteristics with average bias and between-trial heterogeneity. Intervention effect estimates seemed to be exaggerated in trials with inadequate or unclear (vs. adequate) random-sequence generation (ratio of odds ratios, 0.89 [95% credible interval {CrI}, 0.82 to 0.96]) and with inadequate or unclear (vs. adequate) allocation concealment (ratio of odds ratios, 0.93 [CrI, 0.87 to 0.99]). Lack of or unclear double-blinding (vs. double-blinding) was associated with an average of 13% exaggeration of intervention effects (ratio of odds ratios, 0.87 [CrI, 0.79 to 0.96]), and between-trial heterogeneity was increased for such studies (SD increase in heterogeneity, 0.14 [CrI, 0.02 to 0.30]). For each characteristic, average bias and increases in between-trial heterogeneity were driven primarily by trials with subjective outcomes, with little evidence of bias in trials with objective and mortality outcomes. This study is limited by incomplete trial reporting, and findings may be confounded by other study design characteristics. Bias associated with study design characteristics may lead to exaggeration of intervention effect estimates and increases in between-trial heterogeneity in trials reporting subjectively assessed outcomes.

Population-based design of mandibular fixation plates with bone quality and morphology considerations

In this paper we present a new population-based implant design methodology, which advances the state-of-the-art approaches by combining shape and bone quality information into the design strategy. The method may enhance the mechanical stability of the fixation and reduces the intra-operative in-plane bending which might impede the functionality of the locking mechanism. The computational method is presented for the case of mandibular locking fixation plates, where the mandibular angle and the bone quality at screw locations are taken into account. The method automatically derives the mandibular angle and the bone thickness and intensity values at the path of every screw from a set of computed tomography images. An optimization strategy is then used to optimize the two parameters of plate angle and screw position. The method was applied to two populations of different genders. Results for the new design are presented along with a comparison with a commercially available mandibular locking fixation plate (MODUS(®) TriLock(®) 2.0/2.3/2.5, Medartis AG, Basel, Switzerland). The proposed designs resulted in a statistically significant improvement in the available bone thickness when compared to the standard plate. There is a higher probability that the proposed implants cover areas of thicker cortical bone without compromising the bone mineral density around the screws. The obtained results allowed us to conclude that an angle and screw separation of 129° and 9 mm for females and 121° and 10 mm for males are more suitable designs than the commercially available 120° and 9 mm.

Anatomical study of the human middle ear for the design of implantable hearing aids

OBJECTIVE: To generate anatomical data on the human middle ear and adjacent structures to serve as a base for the development and optimization of new implantable hearing aid transducers. Implantable middle ear hearing aid transducers, i.e. the equivalent to the loudspeaker in conventional hearing aids, should ideally fit into the majority of adult middle ears and should utilize the limited space optimally to achieve sufficiently high maximal output levels. For several designs, more anatomical data are needed. METHODS: Twenty temporal bones of 10 formalin-fixed adult human heads were scanned by a computed tomography system (CT) using a slide thickness of 0.63 mm. Twelve landmarks were defined and 24 different distances were calculated for each temporal bone. RESULTS: A statistical description of 24 distances in the adult human middle ear which may limit or influence the design of middle ear transducers is presented. Significant inter-individual differences but no significant differences for gender, side, age or degree of pneumatization of the mastoid were found. Distances, which were not analyzed for the first time in this study, were found to be in good agreement with the results of earlier studies. CONCLUSION: A data set describing the adult human middle ear anatomy quantitatively from the point of view of designers of new implantable hearing aid transducers has been generated. In principle, the method employed in this study using standard CT scans could also be used preoperatively to rule out exclusion criteria.

Bayesian Geostatistical Design

This paper describes the use of model-based geostatistics for choosing the optimal set of sampling locations, collectively called the design, for a geostatistical analysis. Two types of design situations are considered. These are retrospective design, which concerns the addition of sampling locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing optimal positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model parameter values are unknown. The results show that in this situation a wide range of inter-point distances should be included in the design, and the widely used regular design is therefore not the optimal choice.

Drug-eluting or bare-metal stents for large coronary vessel stenting? The BASKET-PROVE (PROspective Validation Examination) trial: study protocol and design

BACKGROUND: Based on a subgroup analysis of 18-month BAsel Stent Kosten Effektivitäts Trial (BASKET) outcome data, we hypothesized that very late (> 12 months) stent thrombosis occurs predominantly after drug-eluting stent implantation in large native coronary vessel stenting. METHODS: To prove or refute this hypothesis, we set up an 11-center 4-country prospective trial of 2260 consecutive patients treated with > or = 3.0-mm stents only, randomized to receive Cypher (Johnson ; Johnson, Miami Lakes, FL), Vision (Abbott Vascular, Abbott Laboratories, IL), or Xience stents (Abbott Vascular). Only patients with left main or bypass graft disease, in-stent restenosis or stent thrombosis, in need of nonheart surgery, at increased bleeding risk, without compliance/consent are excluded. All patients are treated with dual antiplatelet therapy for 12 months. The primary end point will be cardiac death/nonfatal myocardial infarction after 24 months with further follow-up up to 5 years. RESULTS: By June 12, 229 patients (10% of the planned total) were included with a baseline risk similar to that of the same subgroup of BASKET (n = 588). CONCLUSIONS: This study will answer several important questions of contemporary stent use in patients with large native vessel stenting. The 2-year death/myocardial infarction-as well as target vessel revascularization-and bleeding rates in these patients with a first- versus second-generation drug-eluting stent should demonstrate the benefit or harm of these stents compared to cobalt-chromium bare-metal stents in this relevant, low-risk group of everyday patients. In addition, a comparison with similar BASKET patients will allow to estimate the impact of 12- versus 6-month dual antiplatelet therapy on these outcomes.

Automated design of self-stabilization

Self-stabilization is a property of a distributed system such that, regardless of the legitimacy of its current state, the system behavior shall eventually reach a legitimate state and shall remain legitimate thereafter. The elegance of self-stabilization stems from the fact that it distinguishes distributed systems by a strong fault tolerance property against arbitrary state perturbations. The difficulty of designing and reasoning about self-stabilization has been witnessed by many researchers; most of the existing techniques for the verification and design of self-stabilization are either brute-force, or adopt manual approaches non-amenable to automation. In this dissertation, we first investigate the possibility of automatically designing self-stabilization through global state space exploration. In particular, we develop a set of heuristics for automating the addition of recovery actions to distributed protocols on various network topologies. Our heuristics equally exploit the computational power of a single workstation and the available parallelism on computer clusters. We obtain existing and new stabilizing solutions for classical protocols like maximal matching, ring coloring, mutual exclusion, leader election and agreement. Second, we consider a foundation for local reasoning about self-stabilization; i.e., study the global behavior of the distributed system by exploring the state space of just one of its components. It turns out that local reasoning about deadlocks and livelocks is possible for an interesting class of protocols whose proof of stabilization is otherwise complex. In particular, we provide necessary and sufficient conditions – verifiable in the local state space of every process – for global deadlock- and livelock-freedom of protocols on ring topologies. Local reasoning potentially circumvents two fundamental problems that complicate the automated design and verification of distributed protocols: (1) state explosion and (2) partial state information. Moreover, local proofs of convergence are independent of the number of processes in the network, thereby enabling our assertions about deadlocks and livelocks to apply on rings of arbitrary sizes without worrying about state explosion.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

Orbits design for Leo space based solar power satellite system

Space Based Solar Power satellites use solar arrays to generate clean, green, and renewable electricity in space and transmit it to earth via microwave, radiowave or laser beams to corresponding receivers (ground stations). These traditionally are large structures orbiting around earth at the geo-synchronous altitude. This thesis introduces a new architecture for a Space Based Solar Power satellite constellation. The proposed concept reduces the high cost involved in the construction of the space satellite and in the multiple launches to the geo-synchronous altitude. The proposed concept is a constellation of Low Earth Orbit satellites that are smaller in size than the conventional system. For this application a Repeated Sun-Synchronous Track Circular Orbit is considered (RSSTO). In these orbits, the spacecraft re-visits the same locations on earth periodically every given desired number of days with the line of nodes of the spacecraft’s orbit fixed relative to the Sun. A wide range of solutions are studied, and, in this thesis, a two-orbit constellation design is chosen and simulated. The number of satellites is chosen based on the electric power demands in a given set of global cities. The orbits of the satellites are designed such that their ground tracks visit a maximum number of ground stations during the revisit period. In the simulation, the locations of the ground stations are chosen close to big cities, in USA and worldwide, so that the space power constellation beams down power directly to locations of high electric power demands. The j2 perturbations are included in the mathematical model used in orbit design. The Coverage time of each spacecraft over a ground site and the gap time between two consecutive spacecrafts visiting a ground site are simulated in order to evaluate the coverage continuity of the proposed solar power constellation. It has been observed from simulations that there always periods in which s spacecraft does not communicate with any ground station. For this reason, it is suggested that each satellite in the constellation be equipped with power storage components so that it can store power for later transmission. This thesis presents a method for designing the solar power constellation orbits such that the number of ground stations visited during the given revisit period is maximized. This leads to maximizing the power transmission to ground stations.

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.

CRITERIA FOR SUSTAINABLE PRODUCT DESIGN WITH 3D PRINTING IN THE DEVELOPING WORLD

The demand for consumer goods in the developing world continues to rise as populations and economies grow. As designers, manufacturers, and consumers look for ways to address this growing demand, many are considering the possibilities of 3D printing. Due to 3D printing’s flexibility and relative mobility, it is speculated that 3D printing could help to meet the growing demands of the developing world. While the merits and challenges of distributed manufacturing with 3D printing have been presented, little work has been done to determine the types of products that would be appropriate for such manufacturing. Inspired by the author’s two years of Peace Corps service in the Tanzania and the need for specialty equipment for various projects during that time, an in-depth literature search is undertaken to better understand and summarize the process and capabilities of 3D printing. Human-centered design considerations are developed to focus on the product desirability, the technical feasibility, and the financial viability of using 3D printing within Tanzania. Beginning with concerns of what Tanzanian consumers desire, many concerns later arise in regards to the feasibility of creating products that would be sufficient in strength and quality for the demands of developing world consumers. It is only after these concerns are addressed that the viability of products can be evaluated from an economic perspective. The larger impacts of a product beyond its use are vital in determining how it will affect the social, economic, and environmental well-being of a developing nation such as Tanzania. Thus technology specific criteria are necessary for assessing and quantifying the broader impacts that a 3D-printed product can have within its ecosystem, and appropriate criteria are developed for this purpose. Both sets of criteria are then demonstrated and tested while evaluating the desirability, feasibility, viability, and sustainability of printing a piece of equipment required for the author’s Peace Corps service: a set of Vernier calipers. Required for science educators throughout the country, specialty equipment such as calipers initially appear to be an ideal candidate for 3D printing, though ultimately the printing of calipers is not recommended due to current restrictions in the technology. By examining more specific challenges and opportunities of the products 3D printing can produce, it can be better determined what place 3D printing will have in manufacturing for the developing world. Furthermore, the considerations outlined in this paper could be adapted for other manufacturing technologies and regions of the world, as human centered design and sustainability will be critical in determining how to supply the developing world with the consumer goods it demands.

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 establishment of a biobank in a multicenter prospective cohort study of elderly patients with venous thromboembolism (SWITCO65+)

In the field of thrombosis and haemostasis, many preanalytical variables influence the results of coagulation assays and measures to limit potential results variations should be taken. To our knowledge, no paper describing the development and maintenance of a haemostasis biobank has been previously published. Our description of the biobank of the Swiss cohort of elderly patients with venous thromboembolism (SWITCO65+) is intended to facilitate the set-up of other biobanks in the field of thrombosis and haemostasis. SWITCO65+ is a multicentre cohort that prospectively enrolled consecutive patients aged ≥65 years with venous thromboembolism at nine Swiss hospitals from 09/2009 to 03/2012. Patients will be followed up until December 2013. The cohort includes a biobank with biological material from each participant taken at baseline and after 12 months of follow-up. Whole blood from all participants is assayed with a standard haematology panel, for which fresh samples are required. Two buffy coat vials, one PAXgene Blood RNA System tube and one EDTA-whole blood sample are also collected at baseline for RNA/DNA extraction. Blood samples are processed and vialed within 1 h of collection and transported in batches to a central laboratory where they are stored in ultra-low temperature archives. All analyses of the same type are performed in the same laboratory in batches. Using multiple core laboratories increased the speed of sample analyses and reduced storage time. After recruiting, processing and analyzing the blood of more than 1,000 patients, we determined that the adopted methods and technologies were fit-for-purpose and robust.