Scampering in the City: Examining the Ecological and Social Viability of Black-Tailed Prairie Dogs (Cynomys ludovicianus) in Denver, Colorado

The conservation of prairie dogs is highly contested due to the embedded view that they are pests. This research addressed the ecological and social viability of prairie dog colonies in Denver, Colorado. Remote sensing analysis was applied to identify potentially viable areas for urban prairie dog colonies. In order to assess the social viability of urban colonies, knowledge and attitudinal surveys were distributed to residents near existing colonies and residents near potential colonies. Statistical analysis of responses provided insight into relationships between proximity to colonies, ecological knowledge, attitudes towards prairie dogs, demographics, and the presence of educational literature. Results indicated that women are consistently more favorable towards prairie dogs; knowledge was strongly associated with favorability towards prairie dogs; and residents living near colonies were more favorable towards local prairie dogs than residents living near potential colonies. While additional education and outreach is necessary in order to improve residents\u27 attitudes towards prairie dogs, this species has the potential to be viable in Denver

Culturing Adult Stem Cells for Cell-Based Therapeutics: Neuroimmune Applications

Pluripotent stem cells can be successfully isolated from a variety of tissues from adult organisms. This fact opens the exciting possibility of cell-based therapies for a large number of clinical treatments. However, the development of optimized protocols to obtain, grow, and cryopreserve cells, as well as that of effective clinical treatment procedures, is no easy task. The therapeutic potential of cells expanded in vitro depends on a multitude of factors including isolation procedures, donor and tissue types, expansion and preservation methods, etc. Researchers are investing great efforts to determine which of these many variables significantly impact downstream performance of in vitro expanded stem cells by studying associated changes in molecular profiles and their effect on the host immune system. This chapter reviews the current status of stem cell production and its derivatives, which are paving the way to different treatments in the clinic. Due to the research interests of our labs, particular emphasis is placed on the potential benefits of stem cell-based therapeutics for the treatment of spinal cord injuries and the neuroimmune disease myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) not only derived from differentiation and cell engraftment mechanisms but also due to the anti-inflammatory and immunoregulatory capacities of these cells

OPTIMIZATION MODELS AND METHODOLOGIES TO SUPPORT EMERGENCY PREPAREDNESS AND POST-DISASTER RESPONSE

This dissertation addresses three important optimization problems arising during the phases of pre-disaster emergency preparedness and post-disaster response in time-dependent, stochastic and dynamic environments. The first problem studied is the building evacuation problem with shared information (BEPSI), which seeks a set of evacuation routes and the assignment of evacuees to these routes with the minimum total evacuation time. The BEPSI incorporates the constraints of shared information in providing on-line instructions to evacuees and ensures that evacuees departing from an intermediate or source location at a mutual point in time receive common instructions. A mixed-integer linear program is formulated for the BEPSI and an exact technique based on Benders decomposition is proposed for its solution. Numerical experiments conducted on a mid-sized real-world example demonstrate the effectiveness of the proposed algorithm. The second problem addressed is the network resilience problem (NRP), involving an indicator of network resilience proposed to quantify the ability of a network to recover from randomly arising disruptions resulting from a disaster event. A stochastic, mixed integer program is proposed for quantifying network resilience and identifying the optimal post-event course of action to take. A solution technique based on concepts of Benders decomposition, column generation and Monte Carlo simulation is proposed. Experiments were conducted to illustrate the resilience concept and procedure for its measurement, and to assess the role of network topology in its magnitude. The last problem addressed is the urban search and rescue team deployment problem (USAR-TDP). The USAR-TDP seeks an optimal deployment of USAR teams to disaster sites, including the order of site visits, with the ultimate goal of maximizing the expected number of saved lives over the search and rescue period. A multistage stochastic program is proposed to capture problem uncertainty and dynamics. The solution technique involves the solution of a sequence of interrelated two-stage stochastic programs with recourse. A column generation-based technique is proposed for the solution of each problem instance arising as the start of each decision epoch over a time horizon. Numerical experiments conducted on an example of the 2010 Haiti earthquake are presented to illustrate the effectiveness of the proposed approach

The Validation of Novel Ecological Survey Methods for Use in Describing Harvest Mouse Micromys minutus Autecology

According to much of the literature relating to Micromys minutus (harvest mouse) the species has historically presented many challenges to researchers, particularly when attempting to collect sufficient data to describe their ecology, life history and responses to the ever-increasing threat of habitat loss and fragmentation. Methodological improvements are needed which provide sufficient species-specific data to underpin conservation and which are of sufficient quality to allow their movement ecology to be quantified. Here two novel methods were developed and tested, which included remote scent surveys using a detection dog and Radio Frequency Identification (RFID) trapping. After validation, RFID trapping was then used to quantify M. minutus movement in fragmented habitats. A preliminary study was carried out which assessed the ability of a dog to be trained to indicate the scent of M. minutus. Here positive reinforcement training methods were used and the dog’s effectiveness was evaluated in a training environment using scent samples collected from controlled and uncontrolled situations. Secondly, RFID trap effectiveness was compared to the results of live trapping. Data were maximised by releasing individually tagged M. minutus into a suitable semi-natural enclosure on the Moulton College estate. After validation a further release was undertaken to investigate M. minutus movement ecology. Here gaps of differing widths were incorporated into the release enclosures and movements between the habitat patches were measured. Individuals included in each release cohort were exposed to an Open Field Test prior to release, and thus, their behaviour in relation to trapping and movement was also assessed. There is strong evidence that a dog can be trained to detect M. minutus and discriminate their scent from other sympatric nontarget species in a controlled training environment. When applied to uncontrolled field situations, the remote scent survey proved more effective than nest search surveys by volunteers during the autumn months, providing preliminary evidence that olfactory indicators could be more efficient than visual clues when establishing presence of M. minutus. Additional validation in uncontrolled settings is still required. Encouraging results were also seen during validation of the use of RFID trapping with better results in terms of raw trapping rates over live trapping being observed. Furthermore, findings indicate that M. minutus have sufficient navigational and motion capacity to successfully move over gaps ≤2m, but gaps greater than 2m could limit their movement with possible implications for population persistence. The findings also suggest that individuals that explore more slowly may have an advantage when inhabiting a fragmented habitat. Thus, movement propensity is likely to be an individual behavioural trait and may vary across situations; this provides a novel perspective on their conservation and may support conservation decisions being based on behaviour rather than density. The data collected for this thesis demonstrates that progress has been made in terms of monitoring M. minutus and the findings presented are entirely novel for this species. Nevertheless, they remain a challenging species and more questions have been asked than can be answered within the thesis. However, the sum of this work has provided a clear direction for future research on M. minutus

Evolutionary Robot Swarms Under Real-World Constraints

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, na especialidade de Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraNas últimas décadas, vários cientistas e engenheiros têm vindo a estudar as estratégias provenientes da natureza. Dentro das arquiteturas biológicas, as sociedades que vivem em enxames revelam que agentes simplistas, tais como formigas ou pássaros, são capazes de realizar tarefas complexas usufruindo de mecanismos de cooperação. Estes sistemas abrangem todas as condições necessárias para a sobrevivência, incorporando comportamentos de cooperação, competição e adaptação. Na “batalha” sem fim em prol do progresso dos mecanismos artificiais desenvolvidos pelo homem, a ciência conseguiu simular o primeiro comportamento em enxame no final dos anos oitenta. Desde então, muitas outras áreas, entre as quais a robótica, beneficiaram de mecanismos de tolerância a falhas inerentes da inteligência coletiva de enxames. A área de investigação deste estudo incide na robótica de enxame, consistindo num domínio particular dos sistemas robóticos cooperativos que incorpora os mecanismos de inteligência coletiva de enxames na robótica. Mais especificamente, propõe-se uma solução completa de robótica de enxames a ser aplicada em contexto real. Nesta ótica, as operações de busca e salvamento foram consideradas como o caso de estudo principal devido ao nível de complexidade associado às mesmas. Tais operações ocorrem tipicamente em cenários dinâmicos de elevadas dimensões, com condições adversas que colocam em causa a aplicabilidade dos sistemas robóticos cooperativos. Este estudo centra-se nestes problemas, procurando novos desafios que não podem ser ultrapassados através da simples adaptação da literatura da especialidade em algoritmos de enxame, planeamento, controlo e técnicas de tomada de decisão. As contribuições deste trabalho sustentam-se em torno da extensão do método Particle Swarm Optimization (PSO) aplicado a sistemas robóticos cooperativos, denominado de Robotic Darwinian Particle Swarm Optimization (RDPSO). O RDPSO consiste numa arquitetura robótica de enxame distribuída que beneficia do particionamento dinâmico da população de robôs utilizando mecanismos evolucionários de exclusão social baseados na sobrevivência do mais forte de Darwin. No entanto, apesar de estar assente no caso de estudo do RDPSO, a aplicabilidade dos conceitos aqui propostos não se encontra restrita ao mesmo, visto que todos os algoritmos parametrizáveis de enxame de robôs podem beneficiar de uma abordagem idêntica. Os fundamentos em torno do RDPSO são introduzidos, focando-se na dinâmica dos robôs, nos constrangimentos introduzidos pelos obstáculos e pela comunicação, e nas suas propriedades evolucionárias. Considerando a colocação inicial dos robôs no ambiente como algo fundamental para aplicar sistemas de enxames em aplicações reais, é assim introduzida uma estratégia de colocação de robôs realista. Para tal, a população de robôs é dividida de forma hierárquica, em que são utilizadas plataformas mais robustas para colocar as plataformas de enxame no cenário de forma autónoma. Após a colocação dos robôs no cenário, é apresentada uma estratégia para permitir a criação e manutenção de uma rede de comunicação móvel ad hoc com tolerância a falhas. Esta estratégia não considera somente a distância entre robôs, mas também a qualidade do nível de sinal rádio frequência, redefinindo assim a sua aplicabilidade em cenários reais. Os aspetos anteriormente mencionados estão sujeitos a uma análise detalhada do sistema de comunicação inerente ao algoritmo, para atingir uma implementação mais escalável do RDPSO a cenários de elevada complexidade. Esta elevada complexidade inerente à dinâmica dos cenários motivaram a ultimar o desenvolvimento do RDPSO, integrando para o efeito um mecanismo adaptativo baseado em informação contextual (e.g., nível de atividade do grupo). Face a estas considerações, o presente estudo pode contribuir para expandir o estado-da-arte em robótica de enxame com algoritmos inovadores aplicados em contexto real. Neste sentido, todos os métodos propostos foram extensivamente validados e comparados com alternativas, tanto em simulação como com robôs reais. Para além disso, e dadas as limitações destes (e.g., número limitado de robôs, cenários de dimensões limitadas, constrangimentos reais limitados), este trabalho contribui ainda para um maior aprofundamento do estado-da-arte, onde se propõe um modelo macroscópico capaz de capturar a dinâmica inerente ao RDPSO e, até certo ponto, estimar analiticamente o desempenho coletivo dos robôs perante determinada tarefa. Em suma, esta investigação pode ter aplicabilidade prática ao colmatar a lacuna que se faz sentir no âmbito das estratégias de enxames de robôs em contexto real e, em particular, em cenários de busca e salvamento.Over the past decades, many scientists and engineers have been studying nature’s best and time-tested patterns and strategies. Within the existing biological architectures, swarm societies revealed that relatively unsophisticated agents with limited capabilities, such as ants or birds, were able to cooperatively accomplish complex tasks necessary for their survival. Those simplistic systems embrace all the conditions necessary to survive, thus embodying cooperative, competitive and adaptive behaviours. In the never-ending battle to advance artificial manmade mechanisms, computer scientists simulated the first swarm behaviour designed to mimic the flocking behaviour of birds in the late eighties. Ever since, many other fields, such as robotics, have benefited from the fault-tolerant mechanism inherent to swarm intelligence. The area of research presented in this Ph.D. Thesis focuses on swarm robotics, which is a particular domain of multi-robot systems (MRS) that embodies the mechanisms of swarm intelligence into robotics. More specifically, this Thesis proposes a complete swarm robotic solution that can be applied to real-world missions. Although the proposed methods do not depend on any particular application, search and rescue (SaR) operations were considered as the main case study due to their inherent level of complexity. Such operations often occur in highly dynamic and large scenarios, with harsh and faulty conditions, that pose several problems to MRS applicability. This Thesis focuses on these problems raising new challenges that cannot be handled appropriately by simple adaptation of state-of-the-art swarm algorithms, planning, control and decision-making techniques. The contributions of this Thesis revolve around an extension of the Particle Swarm Optimization (PSO) to MRS, denoted as Robotic Darwinian Particle Swarm Optimization (RDPSO). The RDPSO is a distributed swarm robotic architecture that benefits from the dynamical partitioning of the whole swarm of robots by means of an evolutionary social exclusion mechanism based on Darwin’s survival-of-the-fittest. Nevertheless, although currently applied solely to the RDPSO case study, the applicability of all concepts herein proposed is not restricted to it, since all parameterized swarm robotic algorithms may benefit from a similar approach The RDPSO is then proposed and used to devise the applicability of novel approaches. The fundamentals around the RDPSO are introduced by focusing on robots’ dynamics, obstacle avoidance, communication constraints and its evolutionary properties. Afterwards, taking the initial deployment of robots within the environment as a basis for applying swarm robotics systems into real-world applications, the development of a realistic deployment strategy is proposed. For that end, the population of robots is hierarchically divided, wherein larger support platforms autonomously deploy smaller exploring platforms in the scenario, while considering communication constraints and obstacles. After the deployment, a way of ensuring a fault-tolerant multi-hop mobile ad hoc communication network (MANET) is introduced to explicitly exchange information needed in a collaborative realworld task execution. Such strategy not only considers the maximum communication range between robots, but also the minimum signal quality, thus refining the applicability to real-world context. This is naturally followed by a deep analysis of the RDPSO communication system, describing the dynamics of the communication data packet structure shared between teammates. Such procedure is a first step to achieving a more scalable implementation by optimizing the communication procedure between robots. The highly dynamic characteristics of real-world applications motivated us to ultimate the RDPSO development with an adaptive strategy based on a set of context-based evaluation metrics. This thesis contributes to the state-of-the-art in swarm robotics with novel algorithms for realworld applications. All of the proposed approaches have been extensively validated in benchmarking tasks, in simulation, and with real robots. On top of that, and due to the limitations inherent to those (e.g., number of robots, scenario dimensions, real-world constraints), this Thesis further contributes to the state-of-the-art by proposing a macroscopic model able to capture the RDPSO dynamics and, to some extent, analytically estimate the collective performance of robots under a certain task. It is the author’s expectation that this Ph.D. Thesis may shed some light into bridging the reality gap inherent to the applicability of swarm strategies to real-world scenarios, and in particular to SaR operations.FCT - SFRH/BD /73382/201

Forests for a Better Future Sustainability, Innovation and Interdisciplinarity

This book highlights the role of research in innovation and sustainability in the forest sector. The contributions included fall within the broad thematic areas of forest science and cover crucial topics such as biocontrol, forest fire risk, harvesting and logging practices, quantitative and qualitative assessments of forest products, urban forests, and wood treatments—topics that have also been addressed from an interdisciplinary perspective. The contributions also have practical applications, as they deal with the ecological and economic importance of forests and new technologies for the conservation, monitoring, and improvement of services and forest value

Multiagent autonomous energy management

The objective of this thesis is to design distributed software agents for reliable operation of integrated electric power systems of modern electric warships. The automatic reconfiguration of electric shipboard power systems is an important step toward improved fight-through and self-healing capabilities of naval warships. The improvements are conceptualized by redesigning the electric power system and its controls. This research focuses on a new scheme for an energy management system in the form of distributed control/software agents. Multiagent systems provide an ideal level of abstraction for modeling complex applications where distributed and heterogeneous entities need to cooperate to achieve a common goal. The agents\u27 task is to ensure supply of the various load demands while taking into consideration system constraints and load and supply path priorities. A self-stabilizing maximum flow algorithm is investigated to allow implementation of the agents\u27 strategies and find a global solution by only considering local information and a minimum amount of communication. (Abstract shortened by UMI.)