475 resultados para Complements


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Purpose: SCN1A is the most clinically relevant epilepsy gene, most mutations lead to severe myoclonic epilepsy of infancy (SMEI) and generalized epilepsy with febrile seizures plus (GEFS+). We studied 132 patients with epilepsy syndromes with seizures precipitated by fever, and performed phenotype-genotype correlations with SCN1A alterations. Methods: We included patients with SMEI including borderline SMEI (SMEB), GEFS+, febrile seizures (FS), or other seizure types precipitated by fever. We performed a clinical and genetic study focusing on SCN1A, using dHPLC, gene sequencing, and MLPA to detect genomic deletions/duplications on SMEI/SMEB patients. Results: We classified patients as: SMEI/SMEB = 55; GEFS+ = 26; and other phenotypes = 51. SCN1A analysis by dHPLC/sequencing revealed 40 mutations in 37 SMEI/SMEB (67%) and 3 GEFS+ (11.5%) probands. MLPA showed genomic deletions in 2 of 18 SMEI/SMEB. Most mutations were de novo (82%). SMEB patients carrying mutations (8) were more likely to have missense mutations (62.5%), conversely SMEI patients (31) had more truncating, splice site or genomic alterations (64.5%). SMEI/SMEB with truncating, splice site or genomic alterations had a significantly earlier age of onset of FS compared to those with missense mutations and without mutations (p = 0.00007, ANOVA test). None of the remaining patients with seizures precipitated by fever carried SCN1A mutations. Conclusion: We obtained a frequency of 71% SCN1A abnormalities in SMEI/SMEB and of 11.5% in GEFS+ probands. MLPA complements DNA sequencing of SCN1A increasing the mutation detection rate. SMEI/SMEB with truncating, splice site or genomic alterations had a significantly earlier age of onset of FS. This study confirms the high sensitivity of SCN1A for SMEI/SMEB phenotypes. © 2007 International League Against Epilepsy.

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This article places the changing policy profile of the CDU into the context of the gradual transformation of German society since the 1970s and especially since unification in 1990. It argues that in order to understand key areas where the CDU has reformed its programme, we must first understand the broader, meta-level trends in society. In its main section, the article sketches out the long-term changes that have occurred in three principal areas (demographics, labour market outcomes and the economic status and the role of women), and relates these to debates that have taken place in the CDU's programmatic profile. The article therefore concludes that consideration of the societal context complements agency-based explanations for programmatic change. © 2013 Association for the Study of German Politics.

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This study explores the challenges of implementing International Financial Reporting Standards (IFRS) at the organisational level. Based on interviews with experts with aggregated experience relating to the transition projects of over 170 reporting entities, this paper highlights the main challenges in delivering a successful implementation of IFRS. The findings show that the problems faced in implementation include lack of education and training, securing executive-level support, identifying and responding to the wider business-related implications of the transition, and issues with capturing the necessary information for reporting under IFRS.This paper complements the existing literature and offers a qualitative alternative to considering the transition to IFRS, offering insight into the organisational context of IFRS implementation. These insights are useful not only from a historic perspective, but also for organisations and regulators in the many jurisdictions where IFRS is permitted but not required, where more reporting entities will voluntarily move to IFRS-based reporting in the future. More broadly, they are also applicable to the challenges faced in implementing new and significantly revised IFRSs.

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Heuristics, simulation, artificial intelligence techniques and combinations thereof have all been employed in the attempt to make computer systems adaptive, context-aware, reconfigurable and self-managing. This paper complements such efforts by exploring the possibility to achieve runtime adaptiveness using mathematically-based techniques from the area of formal methods. It is argued that formal methods @ runtime represents a feasible approach, and promising preliminary results are summarised to support this viewpoint. The survey of existing approaches to employing formal methods at runtime is accompanied by a discussion of their challenges and of the future research required to overcome them. © 2011 Springer-Verlag.

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Fueled by increasing human appetite for high computing performance, semiconductor technology has now marched into the deep sub-micron era. As transistor size keeps shrinking, more and more transistors are integrated into a single chip. This has increased tremendously the power consumption and heat generation of IC chips. The rapidly growing heat dissipation greatly increases the packaging/cooling costs, and adversely affects the performance and reliability of a computing system. In addition, it also reduces the processor's life span and may even crash the entire computing system. Therefore, dynamic thermal management (DTM) is becoming a critical problem in modern computer system design. Extensive theoretical research has been conducted to study the DTM problem. However, most of them are based on theoretically idealized assumptions or simplified models. While these models and assumptions help to greatly simplify a complex problem and make it theoretically manageable, practical computer systems and applications must deal with many practical factors and details beyond these models or assumptions. The goal of our research was to develop a test platform that can be used to validate theoretical results on DTM under well-controlled conditions, to identify the limitations of existing theoretical results, and also to develop new and practical DTM techniques. This dissertation details the background and our research efforts in this endeavor. Specifically, in our research, we first developed a customized test platform based on an Intel desktop. We then tested a number of related theoretical works and examined their limitations under the practical hardware environment. With these limitations in mind, we developed a new reactive thermal management algorithm for single-core computing systems to optimize the throughput under a peak temperature constraint. We further extended our research to a multicore platform and developed an effective proactive DTM technique for throughput maximization on multicore processor based on task migration and dynamic voltage frequency scaling technique. The significance of our research lies in the fact that our research complements the current extensive theoretical research in dealing with increasingly critical thermal problems and enabling the continuous evolution of high performance computing systems.

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The National System for the Integral Development of the Family (DIF) in Mexico assists children in orphanages. This paper provides an overview of its current practices, and advocates a holistic educational/social model for “alternative orphanages,” integrating Maslow’s Hierarchy of Needs and the rights-based approach. The model complements DIF’s social efforts.

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My dissertation is the first project on the Haitian Platform for Advocacy for an Alternative Development- PAPDA, a nation-building coalition founded by activists from varying sectors to coordinate one comprehensive nationalist movement against what they are calling an Occupation. My work not only provides information on this under-theorized popular movement but also situates it within the broader literature on the postcolonial nation-state as well as Latin American and Caribbean social movements. The dissertation analyzes the contentious relationship between local and global discourses and practices of citizenship. Furthermore, the research draws on transnational feminist theory to underline the scattered hegemonies that intersect to produce varied spaces and practices of sovereignty within the Haitian postcolonial nation-state. The dissertation highlights how race and class, gender and sexuality, education and language, and religion have been imagined and co-constituted by Haitian social movements in constructing ‘new’ collective identities that collapse the private and the public, the rural and the urban, the traditional and the modern. My project complements the scholarship on social movements and the postcolonial nation-state and pushes it forward by emphasizing its spatial dimensions. Moreover, the dissertation de-centers the state to underline the movement of capital, goods, resources, and populations that shape the postcolonial experience. I re-define the postcolonial nation-state as a network of local, regional, international, and transnational arrangements between different political agents, including social movement actors. To conduct this interdisciplinary research project, I employed ethnographic methods, discourse and textual analysis, as well as basic mapping and statistical descriptions in order to present a historically-rooted interpretation of individual and organizational negotiations for community-based autonomy and regional development.

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Event-B is a formal method for modeling and verification of discrete transition systems. Event-B development yields proof obligations that must be verified (i.e. proved valid) in order to keep the produced models consistent. Satisfiability Modulo Theory solvers are automated theorem provers used to verify the satisfiability of logic formulas considering a background theory (or combination of theories). SMT solvers not only handle large firstorder formulas, but can also generate models and proofs, as well as identify unsatisfiable subsets of hypotheses (unsat-cores). Tool support for Event-B is provided by the Rodin platform: an extensible Eclipse based IDE that combines modeling and proving features. A SMT plug-in for Rodin has been developed intending to integrate alternative, efficient verification techniques to the platform. We implemented a series of complements to the SMT solver plug-in for Rodin, namely improvements to the user interface for when proof obligations are reported as invalid by the plug-in. Additionally, we modified some of the plug-in features, such as support for proof generation and unsat-core extraction, to comply with the SMT-LIB standard for SMT solvers. We undertook tests using applicable proof obligations to demonstrate the new features. The contributions described can potentially affect productivity in a positive manner.

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The main focus of this thesis is to address the relative localization problem of a heterogenous team which comprises of both ground and micro aerial vehicle robots. This team configuration allows to combine the advantages of increased accessibility and better perspective provided by aerial robots with the higher computational and sensory resources provided by the ground agents, to realize a cooperative multi robotic system suitable for hostile autonomous missions. However, in such a scenario, the strict constraints in flight time, sensor pay load, and computational capability of micro aerial vehicles limits the practical applicability of popular map-based localization schemes for GPS denied navigation. Therefore, the resource limited aerial platforms of this team demand simpler localization means for autonomous navigation. Relative localization is the process of estimating the formation of a robot team using the acquired inter-robot relative measurements. This allows the team members to know their relative formation even without a global localization reference, such as GPS or a map. Thus a typical robot team would benefit from a relative localization service since it would allow the team to implement formation control, collision avoidance, and supervisory control tasks, independent of a global localization service. More importantly, a heterogenous team such as ground robots and computationally constrained aerial vehicles would benefit from a relative localization service since it provides the crucial localization information required for autonomous operation of the weaker agents. This enables less capable robots to assume supportive roles and contribute to the more powerful robots executing the mission. Hence this study proposes a relative localization-based approach for ground and micro aerial vehicle cooperation, and develops inter-robot measurement, filtering, and distributed computing modules, necessary to realize the system. The research study results in three significant contributions. First, the work designs and validates a novel inter-robot relative measurement hardware solution which has accuracy, range, and scalability characteristics, necessary for relative localization. Second, the research work performs an analysis and design of a novel nonlinear filtering method, which allows the implementation of relative localization modules and attitude reference filters on low cost devices with optimal tuning parameters. Third, this work designs and validates a novel distributed relative localization approach, which harnesses the distributed computing capability of the team to minimize communication requirements, achieve consistent estimation, and enable efficient data correspondence within the network. The work validates the complete relative localization-based system through multiple indoor experiments and numerical simulations. The relative localization based navigation concept with its sensing, filtering, and distributed computing methods introduced in this thesis complements system limitations of a ground and micro aerial vehicle team, and also targets hostile environmental conditions. Thus the work constitutes an essential step towards realizing autonomous navigation of heterogenous teams in real world applications.

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Topological quantum error correction codes are currently among the most promising candidates for efficiently dealing with the decoherence effects inherently present in quantum devices. Numerically, their theoretical error threshold can be calculated by mapping the underlying quantum problem to a related classical statistical-mechanical spin system with quenched disorder. Here, we present results for the general fault-tolerant regime, where we consider both qubit and measurement errors. However, unlike in previous studies, here we vary the strength of the different error sources independently. Our results highlight peculiar differences between toric and color codes. This study complements previous results published in New J. Phys. 13, 083006 (2011).

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The ultimate goal of wildlife recovery is abundance growth of a species, though it must also involve the reestablishment of the species’ ecological role within ecosystems frequently modified by humans. Reestablishment and subsequent recovery may depend on the species’ degree of adaptive behavior as well as the duration of their functional absence and the extent of ecosystem alteration. In cases of long extirpations or extensive alteration, successful reestablishment may entail adjusting foraging behavior, targeting new prey species, and encountering unfamiliar predatory or competitive regimes. Recovering species must also increasingly tolerate heightened anthropogenic presence, particularly within densely inhabited coastal zones. In recent decades, gray seals (Halichoerus grypus) recovered from exploitation, depletion, and partial extirpation in the Northwest Atlantic. On Cape Cod, MA, USA, gray seals have reestablished growing breeding colonies and seasonally interact with migratory white sharks (Carcarodon carcharias). Though well-studied in portions of their range due to concerns over piscivorous impacts on valuable groundfish, there are broad knowledge gaps regarding their ecological role to US marine ecosystems. Furthermore, there are few studies that explicitly analyze gray seal behavior under direct risk of documented shark predation.

In this dissertation, I apply a behavioral and movement ecology approach to telemetry data to understand gray seal abundance and activity patterns along the coast of Cape Cod. This coastal focus complements extensive research documenting and describing offshore movement and foraging behavior and allows me to address questions about movement decisions and risk allocation. Using beach counts of seals visible in satellite imagery, I estimate the total regional abundance of gray seals using correction factors from haul out behavior and demonstrate a sizeable prey base of gray seals locally. Analyzing intra-annual space use patterns, I document small, concentrated home ranges utilizing nearshore habitats that rapidly expand with shifting activity budgets to target disperse offshore habitats following seasonal declines in white sharks. During the season of dense shark presence, seals conducted abbreviated nocturnal foraging trips structured temporally around divergent use of crepuscular periods. The timing of coastal behavior with different levels of twilight indicate risk allocation patterns with diel cycles of empirical white shark activity. The emergence of risk allocation to explain unique behavioral and spatial patterns observed in these gray seals points to the importance of the restored predator-prey dynamic in gray seal behavior along Cape Cod.

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Purpose: Eco-innovation is any form of product, process or organisational innovation that contributes towards sustainable development. Firms can eco-innovate in a variety of ways. The purpose of this paper is to identify nine different eco-innovation activities – including such items as reducing material use per unit of output, reducing energy use per unit of output, reducing carbon dioxide (CO2) “footprint” – and the authors ask whether these act as substitutes or complements to one another. Design/methodology/approach: Eco-innovation is any form of product, process or organisational innovation that contributes towards sustainable development. Firms can eco-innovate in a variety of ways. In this paper the authors identify nine different eco-innovation activities – including such items as reducing material use per unit of output, reducing energy use per unit of output, reducing CO2 “footprint” – and the authors ask whether these act as substitutes or complements to one another. Findings: Introducing only one eco-innovation activity has little payoff (in terms of turnover per worker) with only those firms who reduce their CO2 “footprint” having higher levels of turnover per worker. When introducing more than one eco-innovation activity the authors find that certain eco-innovation activities complement one another (e.g. reducing material use within the firm at the same time as improving the ability to recycle the product after use) others act as substitutes (e.g. reducing material use within the firm at the same time as recycling waste, water or materials within the firm). Practical implications: The results suggest that firms can maximise their productive capacity by considering specific combinations of eco-innovation. This suggests that firms should plan to introduce eco-innovation which act as complements, thereby, boosting productivity. It also suggests that eco-innovation stimuli, introduced by policy makers, should be targeted at complementary eco-innovations. Originality/value: The paper analyses whether eco-innovations act as complements or substitutes. While a number of studies have analysed the importance of eco-innovation for firm performance, few have assessed the extent to which diverse types of eco-innovation interact with each other to complement or substitute for one another.

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This dissertation studies capacity investments in energy sources, with a focus on renewable technologies, such as solar and wind energy. We develop analytical models to provide insights for policymakers and use real data from the state of Texas to corroborate our findings.

We first take a strategic perspective and focus on electricity pricing policies. Specifically, we investigate the capacity investments of a utility firm in renewable and conventional energy sources under flat and peak pricing policies. We consider generation patterns and intermittency of solar and wind energy in relation to the electricity demand throughout a day. We find that flat pricing leads to a higher investment level for solar energy and it can still lead to more investments in wind energy if considerable amount of wind energy is generated throughout the day.

In the second essay, we complement the first one by focusing on the problem of matching supply with demand in every operating period (e.g., every five minutes) from the perspective of a utility firm. We study the interaction between renewable and conventional sources with different levels of operational flexibility, i.e., the possibility

of quickly ramping energy output up or down. We show that operational flexibility determines these interactions: renewable and inflexible sources (e.g., nuclear energy) are substitutes, whereas renewable and flexible sources (e.g., natural gas) are complements.

In the final essay, rather than the capacity investments of the utility firms, we focus on the capacity investments of households in rooftop solar panels. We investigate whether or not these investments may cause a utility death spiral effect, which is a vicious circle of increased solar adoption and higher electricity prices. We observe that the current rate-of-return regulation may lead to a death spiral for utility firms. We show that one way to reverse the spiral effect is to allow the utility firms to maximize their profits by determining electricity prices.

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The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

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This thesis proposes to trace and explore an emotional geography and cartography of the republican withdrawal at the end of the Spanish Civil War in Catalonia during the months of January and February 1939. Thus, it complements existing historiographical scholarship on the Spanish Civil War and Spanish Republican Exile, especially with regard to what was experienced in Catalan territory. However, its main purpose is not that of the historian, to reveal and explain unexplored stories, but to locate existing narratives, memoirs, journals and testimonies carefully in the landscape in which they took place, exposing their emotional bonds with the places and spaces of the withdrawal of the protagonists of the Republican exodus of 1939. Whilst there has been significant work in recent years to “recover” spaces associated with violent of traumatic memories of conflict and displacement, including the creation of a network of “Democratic Memory” places in Catalonia, the spaces explored in this thesis have not so far been construed as places of memory. In part, this is because of the diversity of emotions and affective responses they provoked and continue to evoke, but also because the geography of the Retirada is characterized by mobility and multiplicity. So instead of an historical approach, despite being influenced by Walter Benjamin's concept of history, this thesis draws on existing methods and approaches related to cultural geography, in particular, the emerging interdisciplinary field known as emotional geographies. In order to create a vision of La Retirada that is sensitive to its mobility and multiplicity, the primary methodology used has been that of interdisciplinary assemblage, juxtaposing images, documents and stories of past and present, in a process redolent of that which Marianne Hirsch calls "post-memory".