Hybrid gain-flattened and reduced power excursion scheme for distributed Raman amplification

We propose and evaluate through extensive numerical modelling a novel distributed hybrid amplification scheme combining first and second-order Raman pumping which gives reduced signal power excursion over a wide spatial-spectral range of 60 km × 80 nm in C + L-bands. © 2013 Optical Society of America.

Resolving ambiguous descriptions through visual information

The project “Reference in Discourse” deals with the selection of a specific object from a visual scene in a natural language situation. The goal of this research is to explain this everyday discourse reference task in terms of a concept generation process based on subconceptual visual and verbal information. The system OINC (Object Identification in Natural Communicators) aims at solving this problem in a psychologically adequate way. The system’s difficulties occurring with incomplete and deviant descriptions correspond to the data from experiments with human subjects. The results of these experiments are reported.

Experimental and theoretical study of longitudinal power distribution in a random DFB fiber laser

We have measured the longitudinal power distribution inside a random distributed feedback Raman fiber laser. The observed distribution has a sharp maximum whose position depends on pump power. The spatial distribution profiles are different for the first and the second Stokes waves. Both analytic solution and results of direct numerical modeling are in excellent agreement with experimental observations. © 2012 Optical Society of America.

Best Constant in the Weighted Hardy Inequality: The Spatial and Spherical Version

Mathematics Subject Classification: 26D10.

Direction Finding Estimators of Cyclostationary Signals in Array Processing for Microwave Power Transmission

A solar power satellite is paid attention to as a clean, inexhaustible large- scale base-load power supply. The following technology related to beam control is used: A pilot signal is sent from the power receiving site and after direction of arrival estimation the beam is directed back to the earth by same direction. A novel direction-finding algorithm based on linear prediction technique for exploiting cyclostationary statistical information (spatial and temporal) is explored. Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or baud rates. The problem was solved by using both cyclic second-order statistics and cyclic higher-order statistics. By evaluating the corresponding cyclic statistics of the received data at certain cycle frequencies, we can extract the cyclic correlations of only signals with the same cycle frequency and null out the cyclic correlations of stationary additive noise and all other co-channel interferences with different cycle frequencies. Thus, the signal detection capability can be significantly improved. The proposed algorithms employ cyclic higher-order statistics of the array output and suppress additive Gaussian noise of unknown spectral content, even when the noise shares common cycle frequencies with the non-Gaussian signals of interest. The proposed method completely exploits temporal information (multiple lag ), and also can correctly estimate direction of arrival of desired signals by suppressing undesired signals. Our approach was generalized over direction of arrival estimation of cyclostationary coherent signals. In this paper, we propose a new approach for exploiting cyclostationarity that seems to be more advanced in comparison with the other existing direction finding algorithms.

Georeferenced standardized apparent wave power along the coastline of Cabrera National Park for analysis of essential habitats of littoral species

Wind- induced exposure is one of the major forces shaping the geomorphology and biota in coastal areas. The effect of wave exposure on littoral biota is well known in marine environments (Ekebon et al., 2003; Burrows et al., 2008). In the Cabrera Archipelago National Park wave exposure has demostrated to have an effect on the spatial distribution of different stages of E.marginatus (Alvarez et al., 2010). Standarized average wave exposures during 2008 along the Cabrera Archipelago National park coast line were calculated to be applied in studies of littoral species distribution within the archipelago. Average wave exposure (or apparent wave power) was calculated for points located 50 m equidistant on the coastline following the EXA methodology (EXposure estimates for fragmented Archipelagos) (Ekebon et al., 2003). The average wave exposures were standardized from 1 to 100 (minimum and maximum in the area), showing coastal areas with different levels of mea wave exposure during the year. Input wind data (direction and intensity) from 2008 was registered at the Cabrera mooring located north of Cabrera Archipelago. Data were provided by IMEDEA (CSIC-UIB, TMMOS http://www.imedea.uib-csic.es/tmoos/boyas/). This cartography has been developed under the framework of the project EPIMHAR, funded by the National Park's Network (Spanish Ministry of Environment, Maritime and Rural Affairs, reference: 012/2007 ). Part of this work has been developed under the research programs funded by "Fons de Garantia Agrària i Pesquera de les Illes Balears (FOGAIBA)".

Investigation of factors driving the costs of operating the 2020 Irish power system with large-scale wind generation

The main goal of this work is to determine the true cost incurred by the Republic of Ireland and Northern Ireland in order to meet their EU renewable electricity targets. The primary all-island of Ireland policy goal is that 40% of electricity will come from renewable sources in 2020. From this it is expected that wind generation on the Irish electricity system will be in the region of 32-37% of total generation. This leads to issues resulting from wind energy being a non-synchronous, unpredictable and variable source of energy use on a scale never seen before for a single synchronous system. If changes are not made to traditional operational practices, the efficient running of the electricity system will be directly affected by these issues in the coming years. Using models of the electricity system for the all-island grid of Ireland, the effects of high wind energy penetration expected to be present in 2020 are examined. These models were developed using a unit commitment, economic dispatch tool called PLEXOS which allows for a detailed representation of the electricity system to be achieved down to individual generator level. These models replicate the true running of the electricity system through use of day-ahead scheduling and semi-relaxed use of these schedules that reflects the Transmission System Operator's of real time decision making on dispatch. In addition, it carefully considers other non-wind priority dispatch generation technologies that have an effect on the overall system. In the models developed, three main issues associated with wind energy integration were selected to be examined in detail to determine the sensitivity of assumptions presented in other studies. These three issues include wind energy's non-synchronous nature, its variability and spatial correlation, and its unpredictability. This leads to an examination of the effects in three areas: the need for system operation constraints required for system security; different onshore to offshore ratios of installed wind energy; and the degrees of accuracy in wind energy forecasting. Each of these areas directly impact the way in which the electricity system is run as they address each of the three issues associated with wind energy stated above, respectively. It is shown that assumptions in these three areas have a large effect on the results in terms of total generation costs, wind curtailment and generator technology type dispatch. In particular accounting for these issues has resulted in wind curtailment being predicted in much larger quantities than had been previously reported. This would have a large effect on wind energy companies because it is already a very low profit margin industry. Results from this work have shown that the relaxation of system operation constraints is crucial to the economic running of the electricity system with large improvements shown in the reduction of wind curtailment and system generation costs. There are clear benefits in having a proportion of the wind installed offshore in Ireland which would help to reduce variability of wind energy generation on the system and therefore reduce wind curtailment. With envisaged future improvements in day-ahead wind forecasting from 8% to 4% mean absolute error, there are potential reductions in wind curtailment system costs and open cycle gas turbine usage. This work illustrates the consequences of assumptions in the areas of system operation constraints, onshore/offshore installed wind capacities and accuracy in wind forecasting to better inform the true costs associated with running Ireland's changing electricity system as it continues to decarbonise into the near future. This work also proposes to illustrate, through the use of Ireland as a case study, the effects that will become ever more prevalent in other synchronous systems as they pursue a path of increasing renewable energy generation.

Dedication and Display of Portrait Statues in Hellenistic Greece: Spatial Practices and Identity Politics

This dissertation models a new approach to the study of ancient portrait statues—one that situates them in their historical, political, and spatial contexts. By bringing into conversation bodies of evidence that have traditionally been studied in discrete categories, I investigate how statue landscapes articulated and reinforced a complex set of political and social identities, how space was utilized and manipulated on a local and a regional level, and how patrons responded to the spatial pressures and visual politics of statue dedication within a constantly changing landscape.

Instead of treating sites independently, I have found it to be more productive—and, indeed, necessary—to examine broader patterns of statue dedication. I demonstrate that a regional perspective, that is, one that takes into account the role of choice and spatial preference in setting up a statue within a regional network of available display locations, can illuminate how space shaped the ancient practice of portrait dedication. This level of analysis is a new approach to the study of portrait statues and it has proved to be a productive way of thinking about how statues and context were used together to articulate identity. Understanding how individual monuments worked within these broader landscapes of portrait dedications, how statue monuments functioned within federal systems, and how monuments set up by individuals and social groups operated along side those set up by political bodies clarifies the important place of honorific statues as an expression of power and identity within the history of the site, the region, and Hellenistic Greece.

Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

Measurement of electromagnetic pulses generated during interactions of high power lasers with solid targets

A target irradiated with a high power laser pulse, blows off a large amount of charge and as a consequence the target itself becomes a generator of electromagnetic pulses (EMP) owing to high return current flowing to the ground through the target holder. The first measurement of the magnetic field induced by the neutralizing current reaching a value of a few kA was performed with the use of an inductive target probe at the PALS Laser Facility (Cikhardt et al. Rev. Sci. Instrum. 85 (2014) 103507). A full description of EMP generation should contain information on the spatial distribution and temporal variation of the electromagnetic field inside and outside of the interaction chamber. For this reason, we consider the interaction chamber as a resonant cavity in which different modes of EMP oscillate for hundreds of nanoseconds, until the EMP is transmitted outside through the glass windows and EM waves are attenuated. Since the experimental determination of the electromagnetic field distribution is limited by the number of employed antennas, a mapping of the electromagnetic field has to be integrated with numerical simulations. Thus, this work reports on a detailed numerical mapping of the electromagnetic field inside the interaction chamber at the PALS Laser Facility (covering a frequency spectrum from 100 MHz to 3 GHz) using the commercial code COMSOL Multiphysics 5.2. Moreover we carried out a comparison of the EMP generated in the parallelepiped-like interaction chamber used in the Vulcan Petawatt Laser Facility at the Rutherford Appleton Laboratory, against that produced in the spherical interaction chamber of PALS.

Time-dependent Suppression of Oscillatory Power in Evolving Solar Magnetic Fields

Oscillation amplitudes are generally smaller within magnetically active regions like sunspots and plage when compared to their surroundings. Such magnetic features, when viewed in spatially resolved power maps, appear as regions of suppressed power due to reductions in the oscillation amplitudes. Employing high spatial- and temporal-resolution observations from the Dunn Solar Telescope (DST) in New Mexico, we study the power suppression in a region of evolving magnetic fields adjacent to a pore. By utilizing wavelet analysis, we study for the first time how the oscillatory properties in this region change as the magnetic field evolves with time. Image sequences taken in the blue continuum, G-band, Ca ii K, and Hα filters were used in this study. It is observed that the suppression found in the chromosphere occupies a relatively larger area, confirming previous findings. Also, the suppression is extended to structures directly connected to the magnetic region, and is found to get enhanced as the magnetic field strength increased with time. The dependence of the suppression on the magnetic field strength is greater at longer periods and higher formation heights. Furthermore, the dominant periodicity in the chromosphere was found to be anti-correlated with increases in the magnetic field strength.

Statistical Analysis of Wind Power Generation in Europe

Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.