Transplanted coral (Order: Scleractinia) colony condition was surveyed at five injury event sites, two coral nurseries, and one impact minimization location off the coast of Broward County, Florida, USA in 2012. Because stony corals are long-lived and slow growing, generally growing less than one centimeter in diameter per year, determining transplantation success requires long-term (greater than two years) monitoring. Long-term monitoring efforts, however, are rarely completed. This study is unique in that it examined stony coral transplantation success of several projects over a time period of 6-17 years. Control colonies were also surveyed in order to compare naturally growing coral colonies to the experimental (transplanted) colonies. Because the transplantation activities at the projects examined in this study occurred over a long time period (oldest population occurred 17 years prior to this study and the youngest occurred six years), colony percent partial mortality was used as a measure of success (colony condition). A successful effort should result in transplanted colonies experiencing partial morality similar to that of control colonies over extended periods of time. The control colonies used came from Broward County Annual Monitoring sites, and the M/V Firat and the C/V Hind ship grounding sites. The experimental colonies used came from five injury events (C/V Hind, Clipper Lasco, M/V Firat, and M/V Spar Orion ship grounding sites and Hillsboro Cable Drag location), two stony coral nurseries (DERM Modules and Warren Modules), and one impact minimization location (Broward County Mitigation Boulders). With all control colonies pooled and experimental colonies pooled, no significant differences in colony partial mortality were found between the experimental and control colonies. Once each experimental coral colony was reattached to the substrate, it generally appeared similar to the control colonies; the mean percent mortality for control colonies was 50% (2.95 ±SE) and the mean percent mortality for experimental colonies was 56% (1.24 ±SE). However, differences were found between stony coral species within each treatment (control and experimental). Colony mortality for identified control corals was greatest for Porites astreoides, Siderastrea siderea, and Montastrea annularis complex. For experimental colonies, S. siderea and P. astreoides had the most mortality. The least mortality of the control corals were found in Montastrea cavernosa, Solenastrea bournoni, and Meandrina meandrites. Of the experimental colonies, S. bournoni, M. meandrites, and Montastrea annularis complex had the least mortality. Resource managers need to consider colony transplantation location, coral species, and percent initial colony mortality when allocating efforts for injury and impact minimization events. Also, project initial restoration and final reports documenting transplantation locations and colony species, size and/or mortality should to be more detailed; this would be beneficial for future monitoring efforts.

L’atelier de Sinope (Turquie), cité située sur les rivages du Pont-Euxin, a émis des monnaies de bronze depuis la fondation coloniale, en 46 av. J.-C. jusqu’à l’arrêt des productions sous Gallien (260-268). Le présent ouvrage, qui s’accompagne d’un catalogue et de planches illustratives, en reconstitue l’histoire, en le replacant dans son contexte. La production est analysée selon deux grilles de lecture : l’objet-monnaie en tant que tel (sa diffusion, ses caractéristiques métrologiques, la répartition chronologique des émissions) et la monnaie comme support d’images et de textes, témoin privilégié de l’évolution de ses allégeances et de ses croyances, au premier chef desquels figure le dieu Sérapis. / The mint of Sinope (Turkey), a roman city on the Pontus Euxinus, has produced bronze coins since the colonial foundation in 46 a.C. up to Gallienus (260-268). This thesis, accompanied by a catalogue and illustrative plates, is devoted to explain its history. The coinage, contextualized, is studied within two approaches: the coin as an object (chronological and geographical distribution, intrinsic characteristics) and as a means to convey images and text. Those testify mainly of its allegiance and its beliefs, in first place the god Sarapis, and how they evolved.

Disruptions in the response of endothelial progenitor cells to changes in oxygen environment may present a possible mechanism behind multiple pediatric pulmonary disease models, such as bronchopulmonary dysplasia. Using high-throughput fixed single-cell protein and RNA imaging, we have created "stop-motion" movies of Thymosin. 4 (T beta 4) and Hypoxia Inducible Factor 1 alpha (HIF-1 alpha) protein expression and vascular endothelial growth factor (vegf) and endothelial nitric oxide synthase (eNOS) mRNA in human umbilical cord-derived endothelial colony-forming cells (ECFC). ECFC were grown in vitro under both room air and hyperoxia (50% O-2). We find elevated basal T beta 4 protein expression in ECFC derived from prematurely born infants versus full term infants. T beta 4 is a potent growth hormone that additionally acts as an actin sequestration protein and regulates the stability of HIF-1 alpha. This basal level increase of T beta 4 is associated with lower HIF1 alpha nuclear localization in preterm versus term ECFC upon exposure to hyperoxia. We find altered expression in the pro-angiogenic genes vegf and eNOS, two genes that HIF-1 alpha acts as a transcription factor for. This provides a potential link between a developmentally regulated protein and previously observed impaired function of preterm ECFC in response to hyperoxia.

Supply chain optimization is one of the key components for the effective management of a company with a complex manufacturing process and distribution network. Companies with a global presence in particular are motivated to optimize their distribution plans in order to keep their operating costs low and competitive. Changing condition in the global market and volatile energy prices increase the need for an automatic decision and optimization tool. In recent years, many techniques and applications have been proposed to address the problem of supply chain optimization. However, such techniques are often too problemspecific or too knowledge-intensive to be implemented as in-expensive, and easy-to-use computer system. The effort required to implement an optimization system for a new instance of the problem appears to be quite significant. The development process necessitates the involvement of expert personnel and the level of automation is low. The aim of this project is to develop a set of strategies capable of increasing the level of automation when developing a new optimization system. An increased level of automation is achieved by focusing on three areas: multi-objective optimization, optimization algorithm usability, and optimization model design. A literature review highlighted the great level of interest for the problem of multiobjective optimization in the research community. However, the review emphasized a lack of standardization in the area and insufficient understanding of the relationship between multi-objective strategies and problems. Experts in the area of optimization and artificial intelligence are interested in improving the usability of the most recent optimization algorithms. They stated the concern that the large number of variants and parameters, which characterizes such algorithms, affect their potential applicability in real-world environments. Such characteristics are seen as the root cause for the low success of the most recent optimization algorithms in industrial applications. Crucial task for the development of an optimization system is the design of the optimization model. Such task is one of the most complex in the development process, however, it is still performed mostly manually. The importance and the complexity of the task strongly suggest the development of tools to aid the design of optimization models. In order to address such challenges, first the problem of multi-objective optimization is considered and the most widely adopted techniques to solve it are identified. Such techniques are analyzed and described in details to increase the level of standardization in the area. Empirical evidences are highlighted to suggest what type of relationship exists between strategies and problem instances. Regarding the optimization algorithm, a classification method is proposed to improve its usability and computational requirement by automatically tuning one of its key parameters, the termination condition. The algorithm understands the problem complexity and automatically assigns the best termination condition to minimize runtime. The runtime of the optimization system has been reduced by more than 60%. Arguably, the usability of the algorithm has been improved as well, as one of the key configuration tasks can now be completed automatically. Finally, a system is presented to aid the definition of the optimization model through regression analysis. The purpose of the method is to gather as much knowledge about the problem as possible so that the task of the optimization model definition requires a lower user involvement. The application of the proposed algorithm is estimated that could have saved almost 1000 man-weeks to complete the project. The developed strategies have been applied to the problem of Caterpillar’s global supply chain optimization. This thesis describes also the process of developing an optimization system for Caterpillar and highlights the challenges and research opportunities identified while undertaking this work. This thesis describes the optimization model designed for Caterpillar’s supply chain and the implementation details of the Ant Colony System, the algorithm selected to optimize the supply chain. The system is now used to design the distribution plans of more than 7,000 products. The system improved Caterpillar’s marginal profit on such products by a factor of 4.6% on average.

Numerous organizations collect and distribute non-aggregate personal data for a variety of different purposes, including demographic and public health research. In these situations, the data distributor is responsible with the protection of the anonymity and personal information of individuals. Microaggregation is one of the most commonly used statistical disclosure control methods. In microaggregation, the set of original records is first partitioned into several groups. The records in the same group are similar to each other. The minimum number of records in each group is k. Each record is replaced by the mean value of the group (centroid). The confidentiality of records is protected by ensuring that each group has at least a minimum of k records and each record is indistinguishable from at least k-1 other records in the microaggregated dataset. The goal of this process is to keep the within-group homogeneity higher and the information loss lower, where information loss is the sum squared deviation between the actual records and the group centroids. Several heuristics have been proposed for the NP-hard minimum information loss microaggregation problem. Among the most promising methods is the multivariate Hansen-Mukherjee (MHM) algorithm that uses a shortest path algorithm to identify the best partition consistent with a specified ordering of records. Developing improved heuristics for ordering multivariate points for microaggregation remains an open research challenge. This dissertation adapts a version of the population-based ant colony optimization algorithm (PACO) to order records within which MHM algorithm is used iteratively to improve the quality of grouping. Results of computational experiments using benchmark test problems indicate that P-ACO/MHM based microaggregation algorithm yields comparable or improved information loss than those obtained by extant methods.

This work demonstrates the connections that exist in rhetoric and planning between the Irish plantation projects in the Ards, Munster , Ulster and the Jamestown colony in Virginia . The planners of these projects focused on the creation of internal stability rather than the mission to 'civilize' the natives. The continuity between these projects is examined on several points: the rhetoric the English used to describe the native peoples and the lands to be colonized, who initiated each project, funding and financial terms, the manner of establishing title, the manner of granting the lands to settlers, and the status the natives were expected to hold in the plantation. Comparison of these points highlights the early English colonial idea and the variance between rhetoric and planning.

As estratégias de mapeamento utilizando múltiplos robôs móveis possuem uma série de vantagens quando comparadas àquelas estratégias baseadas em um único robô. As principais vantagens que podem ser elucidadas são: flexibilidade, ganho de informação e redução do tempo de construção do mapa do ambiente. No presente trabalho, um método de integração de mapas locais é proposto baseado em observações inter-robôs, considerando uma nova abordagem para a exploração do ambiente. Tal abordagem é conhecida como Sistema de Vigilância baseado na Modificação do Sistema Colônias de Formigas, ou IAS-SS. A estratégia IAS-SS é inspirada em mecanismos biológicos que definem a organização social de sistemas de enxames. Especificamente, esta estratégia é baseada em uma modificação do tradicional algoritmo de otimização por colônias de formiga. A principal contribuição do presente trabalho é a adaptação de um modelo de compartilhamento de informações utilizado em redes de sensores móveis, adaptando o mesmo para tarefas de mapeamento. Outra importante contribuição é a colaboração entre o método proposto de integração de mapas e a estratégia de coordenação de múltiplos robôs baseada na teoria de colônias de formigas. Tal colaboração permite o desenvolvimento de uma abordagem de exploração que emprega um mecanismo não físico para depósito e detecção de feromônios em ambientes reais por meio da elaboração do conceito de feromônios virtuais integrados. Resultados obtidos em simulação demonstram que o método de integração de mapas é eficiente, de modo que os ensaios experimentais foram realizados considerando-se um número variável de robôs móveis durante o processo de exploração de ambientes internos com diferentes formas e estruturas. Os resultados obtidos com os diversos experimentos realizados confirmam que o processo de integração é efetivo e adequado para executar o mapeamento do ambiente durante tarefas de exploração e vigilância do mesmo / The multiple robot map building strategies have several advantages when compared to strategies based on a single robot, in terms of flexibility, gain of information and reduction of map building time. In this work, a local map integration method is proposed based on the inter-robot observations, considering a recent approach for the environment exploration. This approach is based on the Inverse Ant System-Based Surveillance System strategy, called IASSS. The IAS-SS strategy is inspired on biological mechanisms that define the social organization of swarm systems. Specifically, it is based on a modified version of the known ant colony algorithm. The main contribution of this work is the fit of an information sharing model used in an mobile sensor network, adapting the method for mapping tasks. Another important contribution is the collaboration between the local map integration method and the multiple robot coordination strategy based on ant colony theory. Through this collaboration it is possible to develop an approach that uses a mechanism for controlling the access to pheromones in real environments. Such mechanism is based on the integrated virtual pheromones concept. Simulation results show that the map integration method is efficient, the trials are performed considering a variable number of robots and environments with different structures. Results obtained from several experiments confirm that the integration process is effective and suitable to execute mapping during the exploration task

Clustering is actively used in several research fields, such as pattern recognition, machine learning and data mining. This dissertation focuses on clustering algorithms in the data mining area. Clustering algorithms can be applied to solve the unsupervised learning problem, which deals with finding clusters in unlabeled data. Most clustering algorithms require the number of cluster centers be known in advance. However, this is often not suitable for real world applications, since we do not know this information in most cases. Another question becomes, once clusters are found by the algorithms, do we believe the clusters are exactly the right ones or do there exist better ones? In this dissertation, we present two new Swarm Intelligence based approaches for data clustering to solve the above issues. Swarm based approaches to clustering have been shown to be able to skip local extrema by doing a form of global search, our two newly proposed ant clustering algorithms take advantage of this. The first algorithm is a kernel-based fuzzy ant clustering algorithm using the Xie-Beni partition validity metric, it is a two stage algorithm, in the first stage of the algorithm ants move the cluster centers in feature space, the cluster centers found by the ants are evaluated using a reformulated kernel-based Xie-Beni cluster validity metric. We found when provided with more clusters than exist in the data our new ant-based approach produces a partition with empty clusters and/or very lightly populated clusters. Then the second stage of this algorithm was applied to automatically detect the number of clusters for a data set by using threshold solutions. The second ant clustering algorithm, using chemical recognition of nestmates is a combination of an ant based algorithm and a consensus clustering algorithm. It is a two-stage algorithm without initial knowledge of the number of clusters. The main contributions of this work are to use the ability of an ant based clustering algorithm to determine the number of cluster centers and refine the cluster centers, then apply a consensus clustering algorithm to get a better quality final solution. We also introduced an ensemble ant clustering algorithm which is able to find a consistent number of clusters with appropriate parameters. We proposed a modified online ant clustering algorithm to handle clustering large data sets. To our knowledge, we are the first to use consensus to combine multiple ant partitions to obtain robust clustering solutions. Experiments were done with twelve data sets, some of which were benchmark data sets, two artificially generated data sets and two magnetic resonance image brain volumes. The results show how the ant clustering algorithms play an important role in finding the number of clusters and providing useful information for consensus clustering to locate the optimal clustering solutions. We conducted a wide range of comparative experiments that demonstrate the effectiveness of the new approaches.

A mobile ad hoc network is a collection of wireless mobile devices which dynamically form a temporary network, without using any existing network infrastructure or centralised administration. Each node in the network effectively becomes a router, and forwards packets towards the packet’s destination node. Ad hoc networks are characterized by frequently changing network topology, multi-hop wireless connections and the need for dynamic, efficient routing protocols. <p.This work considers the routing problem in a network of uniquely addressable sensors. These networks are encountered in many industrial applications, where the aim is to relay information from a collection of data gathering devices deployed over an area to central points. The routing problem in such networks are characterised by: <ul> <li>The overarching requirement for low power consumption, as battery powered sensors may be required to operate for years without battery replacement;</li> <li>An emphasis on reliable communication as opposed to real-time communication, it is more important for packets to arrive reliably than to arrive quickly; and</li> <li>Very scarce processing and memory resources, as these sensors are often implemented on small low-power microprocessors.</li> </ul> This work provides overviews of routing protocols in ad hoc networks, swarm intelligence, and swarm intelligence applied to ad hoc routing. Various mechanisms that are commonly encountered in ad hoc routing are experimentally evaluated under situations as close to real-life as possible. Where possible, enhancements to the mechanisms are suggested and evaluated. Finally, a routing protocol suitable for such low-power sensor networks is defined and benchmarked in various scenarios against the Ad hoc On-Demand Distance Vector (AODV) algorithm. / Dissertation (MSc)--University of Pretoria, 2005. / Computer Science / Unrestricted

Due to tuberculosis (TB) being one of the top ten diseases in Africa with the highest mortality rate, a crucial objective is to find the appropriate medication to cure patients and prevent people from contracting the disease. Since this statistic is not improving sufficiently, it is evident that there is a need for new anti-TB drugs. One of the main challenges in developing new and effective drugs for the treatment of TB is to identify the combinations of effective drugs when subsequent testing of patients in pivotal clinical trials are performed. During the early weeks of the treatment of TB, trials of the early bactericidal activity assess the decline in colony-forming unit (CFU) count of Mycobacterium TB in the sputum of patients containing smear-microscopy-positive pulmonary TB. A previously published dataset containing CFU counts of treated patients over 56 days is used to perform joint modeling of the nonlinear data over time and the patients’ sputum culture conversion (i.e., the time-to-event outcome). It is clear from the results obtained that there is an association between the longitudinal and time-to-event outcomes. / Mini Dissertation ( MSc (Advanced Data Analytics))--University of Pretoria, 2021. / South African Medical Research Council (SAMRC) / Statistics / MSc (Advanced Data Analytics) / Restricted