Optimal electricity distribution framework for public space: Assessing renewable energy proposals for Freshkills Park, New York City

Integrating renewable energy into public space is becoming more common as a climate change solution. However, this approach is often guided by the environmental pillar of sustainability, with less focus on the economic and social pillars. The purpose of this paper is to examine this issue in the speculative renewable energy propositions for Freshkills Park in New York City submitted for the 2012 Land Art Generator Initiative (LAGI) competition. This paper first proposes an optimal electricity distribution (OED) framework in and around public spaces based on relevant ecology and energy theory (Odum’s fourth and fifth law of thermodynamics). This framework addresses social engagement related to public interaction, and economic engagement related to the estimated quantity of electricity produced, in conjunction with environmental engagement related to the embodied energy required to construct the renewable energy infrastructure. Next, the study uses the OED framework to analyse the top twenty-five projects submitted for the LAGI 2012 competition. The findings reveal an electricity distribution imbalance and suggest a lack of in-depth understanding about sustainable electricity distribution within public space design. The paper concludes with suggestions for future research.

Impact of coverage-dependent marginal costs on optimal HPV vaccination strategies.

The effectiveness of vaccinating males against the human papillomavirus (HPV) remains a controversial subject. Many existing studies conclude that increasing female coverage is more effective than diverting resources into male vaccination. Recently, several empirical studies on HPV immunization have been published, providing evidence of the fact that marginal vaccination costs increase with coverage. In this study, we use a stochastic agent-based modeling framework to revisit the male vaccination debate in light of these new findings. Within this framework, we assess the impact of coverage-dependent marginal costs of vaccine distribution on optimal immunization strategies against HPV. Focusing on the two scenarios of ongoing and new vaccination programs, we analyze different resource allocation policies and their effects on overall disease burden. Our results suggest that if the costs associated with vaccinating males are relatively close to those associated with vaccinating females, then coverage-dependent, increasing marginal costs may favor vaccination strategies that entail immunization of both genders. In particular, this study emphasizes the necessity for further empirical research on the nature of coverage-dependent vaccination costs.

Method for computing the optimal signal distribution and channel capacity

An iterative method for computing the channel capacity of both discrete and continuous input, continuous output channels is proposed. The efficiency of new method is demonstrated in comparison with the classical Blahut - Arimoto algorithm for several known channels. Moreover, we also present a hybrid method combining advantages of both the Blahut - Arimoto algorithm and our iterative approach. The new method is especially efficient for the channels with a priory unknown discrete input alphabet.

Reformulation of a thermostable broadly protective recombinant vaccine against human papilloma virus

The causal relationship between Human Papilloma Virus (HPV) infection and cervical cancer has motivated the development, and further improvement, of prophylactic vaccines against this virus. 70% of cervical cancers, 80% of which in low-resources countries, are associated to HPV16 and HPV18 infection, with 13 additional HPV types, classified as high-risk, responsible for the remaining 30% of tumors. Current vaccines, Cervarix® (GlaxoSmithKline) and Gardasil®(Merk), are based on virus-like particles (VLP) obtained by self-assembly of the major capsid protein L1. Despite their undisputable immunogenicity and safety, the fact that protection afforded by these vaccines is largely limited to the cognate serotypes included in the vaccine (HPV 16 and 18, plus five additional viral types incorporated into a newly licensed nonavalent vaccine) along with high production costs and reduced thermal stability, are pushing the development of 2nd generation HPV vaccines based on minor capsid protein L2. The increase in protection broadness afforded by the use of L2 cross-neutralizing epitopes, plus a marked reduction of production costs due to bacterial expression of the antigens and a considerable increase in thermal stability could strongly enhance vaccine distribution and usage in low-resource countries. Previous studies from our group identified three tandem repeats of the L2 aa. 20-38 peptide as a strongly immunogenic epitope if exposed on the scaffold protein thioredoxin (Trx). The aim of this thesis work is the improvement of the Trx-L2 vaccine formulation with regard to cross-protection and thermostability, in order to identify an antigen suitable for a phase I clinical trial. By testing Trx from different microorganisms, we selected P. furiosus thioredoxin (PfTrx) as the optimal scaffold because of its sustained peptide epitope constraining capacity and striking thermal stability (24 hours at 100°C). Alternative production systems, such as secretory Trx-L2 expression in the yeast P. pastoris, have also been set-up and evaluated as possible means to further increase production yields, with a concomitant reduction of production costs. Limitations in immune-responsiveness caused by MHC class II polymorphisms –as observed, for example, in different mouse strains- have been overcome by introducing promiscuous T-helper (Th) epitopes, e.g., PADRE (Pan DR Epitope), at both ends of PfTrx. This allowed us to obtain fairly strong immune responses even in mice (C57BL/6) normally unresponsive to the basic Trx-L2 vaccine. Cross-protection was not increased, however. I thus designed, produced and tested a novel multi-epitope formulation consisting of 8 and 11 L2(20-38) epitopes derived from different HPV types, tandemly joined into a single thioredoxin molecule (“concatemers”). To try to further increase immunogenicity, I also fused our 8X and 11X PfTrx-L2 concatemers to the N-terminus of an engineered complement-binding protein (C4bp), capable to spontaneously assemble into ordered hepatmeric structures, previously validated as a molecular adjuvant. Fusion to C4bp indeed improved antigen presentation, with a fairly significant increase in both immunogenicity and cross-protection. Another important issue I addressed, is the reduction of vaccine doses/treatment, which can be achieved by increasing immunogenicity, while also allowing for a delayed release of the antigen. I obtained preliminary, yet quite encouraging results in this direction with the use of a novel, solid-phase vaccine formulation, consisting of the basic PfTrx-L2 vaccine and its C4bp fusion derivative adsorbed to mesoporus silica-rods (MSR).

Optimal Data Distributions in Machine Learning

In the first part of the thesis we explore three fundamental questions that arise naturally when we conceive a machine learning scenario where the training and test distributions can differ. Contrary to conventional wisdom, we show that in fact mismatched training and test distribution can yield better out-of-sample performance. This optimal performance can be obtained by training with the dual distribution. This optimal training distribution depends on the test distribution set by the problem, but not on the target function that we want to learn. We show how to obtain this distribution in both discrete and continuous input spaces, as well as how to approximate it in a practical scenario. Benefits of using this distribution are exemplified in both synthetic and real data sets.

In order to apply the dual distribution in the supervised learning scenario where the training data set is fixed, it is necessary to use weights to make the sample appear as if it came from the dual distribution. We explore the negative effect that weighting a sample can have. The theoretical decomposition of the use of weights regarding its effect on the out-of-sample error is easy to understand but not actionable in practice, as the quantities involved cannot be computed. Hence, we propose the Targeted Weighting algorithm that determines if, for a given set of weights, the out-of-sample performance will improve or not in a practical setting. This is necessary as the setting assumes there are no labeled points distributed according to the test distribution, only unlabeled samples.

Finally, we propose a new class of matching algorithms that can be used to match the training set to a desired distribution, such as the dual distribution (or the test distribution). These algorithms can be applied to very large datasets, and we show how they lead to improved performance in a large real dataset such as the Netflix dataset. Their computational complexity is the main reason for their advantage over previous algorithms proposed in the covariate shift literature.

In the second part of the thesis we apply Machine Learning to the problem of behavior recognition. We develop a specific behavior classifier to study fly aggression, and we develop a system that allows analyzing behavior in videos of animals, with minimal supervision. The system, which we call CUBA (Caltech Unsupervised Behavior Analysis), allows detecting movemes, actions, and stories from time series describing the position of animals in videos. The method summarizes the data, as well as it provides biologists with a mathematical tool to test new hypotheses. Other benefits of CUBA include finding classifiers for specific behaviors without the need for annotation, as well as providing means to discriminate groups of animals, for example, according to their genetic line.

Content Delivery System for Optimal VoD Streaming

The demand of video contents has rapidly increased in the past years as a result of the wide deployment of IPTV and the variety of services offered by the network operators. One of the services that has especially become attractive to the customers is real-time video on demand (VoD) because it offers an immediate streaming of a large variety of video contents. The price that the operators have to pay for this convenience is the increased traffic in the networks, which are becoming more congested due to the higher demand for VoD contents and the increased quality of the videos. As a solution, in this paper we propose a hierarchical network system for VoD content delivery in managed networks, which implements redistribution algorithm and a redirection strategy for optimal content distribution within the network core and optimal streaming to the clients. The system monitors the state of the network and the behavior of the users to estimate the demand for the content items and to take the right decision on the appropriate number of replicas and their best positions in the network. The system's objectives are to distribute replicas of the content items in the network in a way that the most demanded contents will have replicas closer to the clients so that it will optimize the network utilization and will improve the users' experience. It also balances the load between the servers concentrating the traffic to the edges of the network.

Architectures for Video-on-Demand content distribution in managed networks

La demanda de contenidos de vídeo ha aumentado rápidamente en los últimos años como resultado del gran despliegue de la TV sobre IP (IPTV) y la variedad de servicios ofrecidos por los operadores de red. Uno de los servicios que se ha vuelto especialmente atractivo para los clientes es el vídeo bajo demanda (VoD) en tiempo real, ya que ofrece una transmisión (streaming) inmediata de gran variedad de contenidos de vídeo. El precio que los operadores tienen que pagar por este servicio es el aumento del tráfico en las redes, que están cada vez más congestionadas debido a la mayor demanda de contenidos de VoD y al aumento de la calidad de los propios contenidos de vídeo. Así, uno de los principales objetivos de esta tesis es encontrar soluciones que reduzcan el tráfico en el núcleo de la red, manteniendo la calidad del servicio en el nivel adecuado y reduciendo el coste del tráfico. La tesis propone un sistema jerárquico de servidores de streaming en el que se ejecuta un algoritmo para la ubicación óptima de los contenidos de acuerdo con el comportamiento de los usuarios y el estado de la red. Debido a que cualquier algoritmo óptimo de distribución de contenidos alcanza un límite en el que no se puede llegar a nuevas mejoras, la inclusión de los propios clientes del servicio (los peers) en el proceso de streaming puede reducir aún más el tráfico de red. Este proceso se logra aprovechando el control que el operador tiene en las redes de gestión privada sobre los equipos receptores (Set-Top Box) ubicados en las instalaciones de los clientes. El operador se reserva cierta capacidad de almacenamiento y streaming de los peers para almacenar los contenidos de vídeo y para transmitirlos a otros clientes con el fin de aliviar a los servidores de streaming. Debido a la incapacidad de los peers para sustituir completamente a los servidores de streaming, la tesis propone un sistema de streaming asistido por peers. Algunas de las cuestiones importantes que se abordan en la tesis son saber cómo los parámetros del sistema y las distintas distribuciones de los contenidos de vídeo en los peers afectan al rendimiento general del sistema. Para dar respuesta a estas preguntas, la tesis propone un modelo estocástico preciso y flexible que tiene en cuenta parámetros como las capacidades de enlace de subida y de almacenamiento de los peers, el número de peers, el tamaño de la biblioteca de contenidos de vídeo, el tamaño de los contenidos y el esquema de distribución de contenidos para estimar los beneficios del streaming asistido por los peers. El trabajo también propone una versión extendida del modelo matemático mediante la inclusión de la probabilidad de fallo de los peers y su tiempo de recuperación en el conjunto de parámetros del modelo. Estos modelos se utilizan como una herramienta para la realización de exhaustivos análisis del sistema de streaming de VoD asistido por los peers para la amplia gama de parámetros definidos en los modelos. Abstract The demand of video contents has rapidly increased in the past years as a result of the wide deployment of IPTV and the variety of services offered by the network operators. One of the services that has especially become attractive to the customers is real-time Video on Demand (VoD) because it offers an immediate streaming of a large variety of video contents. The price that the operators have to pay for this convenience is the increased traffic in the networks, which are becoming more congested due to the higher demand for VoD contents and the increased quality of the videos. Therefore, one of the main objectives of this thesis is finding solutions that would reduce the traffic in the core of the network, keeping the quality of service on satisfactory level and reducing the traffic cost. The thesis proposes a system of hierarchical structure of streaming servers that runs an algorithm for optimal placement of the contents according to the users’ behavior and the state of the network. Since any algorithm for optimal content distribution reaches a limit upon which no further improvements can be made, including service customers themselves (the peers) in the streaming process can further reduce the network traffic. This process is achieved by taking advantage of the control that the operator has in the privately managed networks over the Set-Top Boxes placed at the clients’ premises. The operator reserves certain storage and streaming capacity on the peers to store the video contents and to stream them to the other clients in order to alleviate the streaming servers. Because of the inability of the peers to completely substitute the streaming servers, the thesis proposes a system for peer-assisted streaming. Some of the important questions addressed in the thesis are how the system parameters and the various distributions of the video contents on the peers would impact the overall system performance. In order to give answers to these questions, the thesis proposes a precise and flexible stochastic model that takes into consideration parameters like uplink and storage capacity of the peers, number of peers, size of the video content library, size of contents and content distribution scheme to estimate the benefits of the peer-assisted streaming. The work also proposes an extended version of the mathematical model by including the failure probability of the peers and their recovery time in the set of parameters. These models are used as tools for conducting thorough analyses of the peer-assisted system for VoD streaming for the wide range of defined parameters.

Multiple criteria optimization of contemporary logistics distribution network problems

In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistics distribution network. The proposed approach outperforms traditional cost-based optimization techniques because it considers both quantitative and qualitative factors and also aims at maximizing the benefits of deliverer and customers. In the approach, the AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to some critical customer-oriented criteria. The results of AHP prioritization are utilized as the input of the ILP model, the objective of which is to select the best warehouses at the lowest possible cost. In this article, two commercial packages are used: including Expert Choice and LINDO.

Design of conjugate, conjoined shapes and tilings using topology optimization

We present a method for obtaining conjugate, conjoined shapes and tilings in the context of the design of structures using topology optimization. Optimal material distribution is achieved in topology optimization by setting up a selection field in the design domain to determine the presence/absence of material there. We generalize this approach in this paper by presenting a paradigm in which the material left out by the selection field is also utilised. We obtain conjugate shapes when the region chosen and the region left-out are solutions for two problems, each with a different functionality. On the other hand, if the left-out region is connected to the selected region in some pre-determined fashion for achieving a single functionality, then we get conjoined shapes. The utilization of the left-out material, gives the notion of material economy in both cases. Thus, material wastage is avoided in the practical realization of these designs using many manufacturing techniques. This is in contrast to the wastage of left-out material during manufacture of traditional topology-optimized designs. We illustrate such shapes in the case of stiff structures and compliant mechanisms. When such designs are suitably made on domains of the unit cell of a tiling, this leads to the formation of new tilings which are functionally useful. Such shapes are not only useful for their functionality and economy of material and manufacturing, but also for their aesthetic value.

Boundary-layer suction system design for laminar-flying-wing aircraft

The present study aims to provide insight into the parameters affecting practical laminar-flow-control suction power requirements for a commercial laminar-flying-wing transport aircraft. It is shown that there is a minimum power requirement independent of the suction system design, associated with the stagnation pressure loss in the boundary layer. This requirement increases with aerofoil section thickness, but depends only weakly on Mach number and (for a thick, lightly loaded laminar flying wing) lift coefficient. Deviation from the optimal suction distribution, due to a practical chamber-based architecture, is found to have very little effect on the overall suction coefficient; hence, to a good approximation, the power penalty is given by the product of the optimal suction flow rate coefficient and the average skin pressure drop. In the spanwise direction, through suitable choice of chamber depth, the pressure drop due to frictional and inertial effects may be rendered negligible. Finally, if there are fewer pumps than chambers, the average pressure drop from the aerofoil surface to the pump collector ducts, rather than to the chambers, determines the power penalty. For the representative laminar-flying-wing aircraft parameters considered here, the minimum power associated with boundary-layer losses alone contributes some 80-90% of the total power requirement. © 2011 by the American Institute of Aeronautics and Astronautics, Inc.

Improving cold chain technologies through the use of phase change material

Gemstone Team FRESH

Metodologias de optimização topológica em cálculo estrutural

A optimização estrutural é uma temática antiga em engenharia. No entanto, com o crescimento do método dos elementos finitos em décadas recentes, dá origem a um crescente número de aplicações. A optimização topológica, especificamente, surge associada a uma fase de definição de domínio efectivo de um processo global de optimização estrutural. Com base neste tipo de optimização, é possível obter a distribuição óptima de material para diversas aplicações e solicitações. Os materiais compósitos e alguns materiais celulares, em particular, encontram-se entre os materiais mais proeminentes dos nossos dias, em termos das suas aplicações e de investigação e desenvolvimento. No entanto, a sua estrutura potencialmente complexa e natureza heterogénea acarretam grandes complexidades, tanto ao nível da previsão das suas propriedades constitutivas quanto na obtenção das distribuições óptimas de constituintes. Procedimentos de homogeneização podem fornecer algumas respostas em ambos os casos. Em particular, a homogeneização por expansão assimptótica pode ser utilizada para determinar propriedades termomecânicas efectivas e globais a partir de volumes representativos, de forma flexível e independente da distribuição de constituintes. Além disso, integra processos de localização e fornece informação detalhada acerca de sensibilidades locais em metodologias de optimização multiescala. A conjugação destas áreas pode conduzir a metodologias de optimização topológica multiescala, nas quais de procede à obtenção não só de estruturas óptimas mas também das distribuições ideais de materiais constituintes. Os problemas associados a estas abordagens tendem, no entanto, a exigir recursos computacionais assinaláveis, criando muitas vezes sérias limitações à exequibilidade da sua resolução. Neste sentido, técnicas de cálculo paralelo e distribuído apresentam-se como uma potencial solução. Ao dividir os problemas por diferentes unidades memória e de processamento, é possível abordar problemas que, de outra forma, seriam proibitivos. O principal foco deste trabalho centra-se na importância do desenvolvimento de procedimentos computacionais para as aplicações referidas. Adicionalmente, estas conduzem a diversas abordagens alternativas na procura simultânea de estruturas e materiais para responder a aplicações termomecânicas. Face ao exposto, tudo isto é integrado numa plataforma computacional de optimização multiobjectivo multiescala em termoelasticidade, desenvolvida e implementada ao longo deste trabalho. Adicionalmente, o trabalho é complementado com a montagem e configuração de um cluster do tipo Beowulf, assim como com o desenvolvimento do código com vista ao cálculo paralelo e distribuído.

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.