Optical measurement of the temporal delay between two ultra-short and focussed laser pluses

Temporal overlapping of ultra-short and focussed laser pulses is a particularly challenging task, as this timescale lies orders of magnitude below the typical range of fast electronic devices. Here we present an optical technique that allows for the measurement of the temporal delay between two focussed and ultra-short laser pulses. This method is virtually applicable to any focussing geometry and relative intensity of the two lasers. Experimental implementation of this technique provides excellent quantitative agreement with theoretical expectations. The proposed technique will prove highly beneficial for high-power multiple-beam laser experiments.

Temporal structure of attosecond pulses from laser-driven coherent synchrotron emission

The microscopic dynamics of laser-driven coherent synchrotron emission transmitted through thin foils are investigated using particle-in-cell simulations. For normal incidence interactions, we identify the formation of two distinct electron nanobunches from which emission takes place each half-cycle of the driving laser pulse. These emissions are separated temporally by 130 attoseconds and are dominant in different frequency ranges, which is a direct consequence of the distinct characteristics of each electron nanobunch. This may be exploited through spectral filtering to isolate these emissions, generating electromagnetic pulses of duration ~70 as.

Climate drives temporal replacement and nested‐resultant richness patterns of Scottish coastal vegetation

Beta diversity quantifies spatial and/or temporal variation in species composition. It is comprised of two distinct components, species replacement and nestedness, which derive from opposing ecological processes. Using Scotland as a case study and a β-diversity partitioning framework, we investigate temporal replacement and nestedness patterns of coastal grassland species over a 34-yr time period. We aim to 1) understand the influence of two potentially pivotal processes (climate and land-use changes) on landscape-scale (5 × 5 km) temporal replacement and nestedness patterns, and 2) investigate whether patterns from one β-diversity component can mask observable patterns in the other.

We summarised key aspects of climate driven macro-ecological variation as measures of variance, long-term trends, between-year similarity and extremes, for three important climatic predictors (minimum temperature, water-balance and growing degree-days). Shifts in landscape-scale heterogeneity, a proxy of land-use change, was summarised as a spatial multiple-site dissimilarity measure. Together, these climatic and spatial predictors were used in a multi-model inference framework to gauge the relative contribution of each on temporal replacement and nestedness patterns.

Temporal β-diversity patterns were reasonably well explained by climate change but weakly explained by changes in landscape-scale heterogeneity. Climate was shown to have a greater influence on temporal nestedness than replacement patterns over our study period, linking nestedness patterns, as a result of imbalanced gains and losses, to climatic warming and extremes respectively. Important climatic predictors (i.e. growing degree-days) of temporal β-diversity were also identified, and contrasting patterns between the two β-diversity components revealed.

Results suggest climate influences plant species recruitment and establishment processes of Scotland's coastal grasslands, and while species extinctions take time, they are likely to be facilitated by climatic perturbations. Our findings also highlight the importance of distinguishing between different components of β-diversity, disentangling contrasting patterns than can mask one another.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

Evaluación temporal del uso actual del suelo del Bosque Protector Aguarongo y sus áreas colindantes. Área de estudio : Parroquias Santa Ana, San Bartolomé y Zhidmad

Se evaluó el uso actual del suelo, mediante la creación de mapas de uso/cobertura y capacidad de acogida; la problemática consiste en el crecimiento agropecuario; se validó esta información obteniendo que la expansión agropecuaria y las actividades antrópicas, aportan a la fragmentación del hábitat del bosque en detrimento de la biodiversidad existente.

Phylogenetic and functional diversity of estuarine bacterioneuston

A micro-camada superficial da água (SML) é caracterizada pela ocorrência de grandes quantidades de compostos orgânicos, pela acumulação de contaminantes antropogênicos e é submetida a uma intensa radiação solar, extrema mudança de temperatura e, no caso dos estuários, flutuação de salinidade. Estas propriedades físico-químicas estão, provavelmente, a modular a comunidade bacteriana (bacterioneuston) com propriedades filogenéticas e funcionais específicas. Neste estudo, as abordagens dependentes e independentes do cultivo foram aplicadas para avaliar a estrutura e dinâmica das comunidades bacterioneuston e bacterioplâncton em três localizações geográficas ao longo do estuário da Ria de Aveiro. Além disso, comparámos a diversidade filogenética de grupos específicos (Aeromonas, Pseudomonas e Psychrobacter) presentes em bacterioneuston e bacterioplâncton. Finalmente, as duas comunidades foram comparadas em termos de prevalência e diversidade de bactérias resistentes aos antibióticos e respetivos genes de resistência. Bactérias heterotróficas cultiváveis foram enriquecidas em SML. Eletroforese em gel de gradiente desnaturante (DGGE) permitiu a identificação de filotipos específicos em SML. Além disso, a análise de agrupamento dos perfis de DGGE de ambas as comunidades revelou uma ligeira tendência de agrupamento de acordo com a camada amostrada. As diferenças entre as duas comunidades variaram de acordo com factores espaciais e temporais. Em termos de diversidade filogenética de grupos específicos, não foram identificadas diferenças consistentes entre SML e UW com relação às comunidades de Aeromonas. Com relação ao género Pseudomonas, uma unidade operacional taxonómica cultivável foi consistentemente hiper-representada nas amostras de SML. Metodologias dependentes e independentes do cultivo revelaram a presença de populações de Psychrobacter complexas e muito estáveis em todos os sítios e datas de amostragens, com diferenças significativas entre as comunidades de Psychrobacter presentes em SML e UW. Estirpes representativas de prováveis novas espécies também foram cultivadas. Em termos de resistência aos antibióticos, a prevalência de bactérias resistentes em SML foi alta sugerindo selecção pelas condições presentes em SML. É preciso enfatizar que a resistência aos antibióticos foi incomum entre as bactérias estuarinas e os mecanismos de resistência foram, predominantemente, intrínsecos. Pela combinação de abordagens inovadoras dependentes e independentes do cultivo, este estudo forneceu novas e consistentes informações com relação às diferenças em ambas as comunidades bacterianas e em relação a alguns dos fatores que contribuem para a sua formação.

Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well-understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modeling of neural circuits found in the brain.

Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain’s neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

Spatial and temporal assessment of sediment contamination in Sado estuary: a methodological approach

For better management of estuarine ecosystems their contamination assessment should be easily communicated to local managers and decision makers. The problem is the lack of available data and the search of methodologies to enable that assessment using only few data. The Sado estuary in Portugal is as good example of a site where human pressures and ecological values collide with each other and where the degree of metal and organic contamination has not been subject to an overall assessment, either in terms of spatial or temporal variability, in a way that managers can understand.

Composition, temporal and spatial patterns of very-nearshore larval fish assemblages at the Arrábida marine park

Tese dout., Ciências do Mar, Universidade do Algarve, 2006

Small area estimation for the price of habitation transaction: comparison of different uncertainty measures of temporal EBLUP

Local level planning requires statistics for small areas, but normally due to cost or logistic constraints, sample surveys are often planned to provide reliable estimates only for large geographical regions and large subgroups of a population.

Estimação jackknife ponderada do erro quadrático médio de predição do EBLUP temporal

A metodologia baseada na melhor predição linear empírica não enviesada (Empirical Best Linear Unbiased Prediction), consagrada com o acrónimo EBLUP, é muito utilizada na estimação de parâmetros para pequenos domínios. Apesar da relativa facilidade de dedução dos EBLUPs, mesmo num contexto de um modelo longitudinal, a medição da sua qualidade é um problema complexo devido à di culdade de estimação do erro quadrático médio de predição (EQMP) de tais preditores. Neste trabalho utiliza-se um estimador de parâmetros de interesse em pequenos domínios assistido pelo modelo temporal de Rao-Yu (Rao e Yu, 1994). O EBLUP temporal é apresentado e é revisitada a aproximação analítica assimptótica do EQMP do EBLUP temporal proposta por Rao e Yu (1994). Sob o modelo de Rao-Yu, é proposta uma metodologia jackknife ponderada para estimar o EQMP do EBLUP, desenvolvida a partir dos trabalhos de Chen e Lahiri (2008). Foi realizado um estudo por simulação com o objectivo de comparar o desempenho do estimador proposto com o obtido por via da aproximação analítica do EQMP.

Modelação morfodinâmica a longa escala temporal: aplicabilidade de um modelo baseado em processos

Disssertação de mest., Estudos Marinhos e Costeiros, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2010