Rethinking Local Government Support for Youth Arts:The Case of NOISE South Dublin

Within Ireland, interest in strategically supporting young people’s participation in the arts has increased. Additionally, awareness of the Internet’s potential for promot- ing engagement with the arts has grown. Addressing national directives and local needs assessments, South Dublin County Council’s Arts Office initiated NOISE South Dublin (http://www.noisesouthdublin.com), an interactive Web site based on Australia Council’s NOISE project (http://www.noise.net), to promote the creative development of young people in the county. This article presents the practical chal- lenges and potential of youth arts Web-based programs for harnessing the creative engagement of youth. It concludes that the Internet is only useful if it expands online engagement offline.

Integrated Earth Resistivity Tomography (ERT) and Multilevel Gas Sampling: A Tool to Map Geogenic and Anthropogenic Methane Accumulation on Brownfield Sites

Soil gas emissions of methane and carbon dioxide on brownfield sites are usually attributed to anthropogenic activities; however geogenic sources of soil gas are often not considered during site investigation and risk management strategies. This paper presents a field study at a redeveloped brownfield site on a flood plain to identify accumulations of methane biogas trapped in underlying sediments. The investigation is based on a multidisciplinary approach using direct multi-level sampling measurements and Earth resistivity tomography . Resistivity imaging was applied to evaluate the feasibility of identifying the size and spatial continuity of soil gas accumulations in anthropogenic and naturally occurring deposits. As a result, biogas accumulations are described within both anthropogenic deposits and pristine organic sediments. This result is important to identify the correct approaches to identify and manage risks associated with soil gas emissions on brownfield and pristine sites. The organic-rich sediments in Quaternary fluvial environments of São Paulo Basin in particular the Tietê River, biogas reservoirs can be generated and trapped beneath geogenic and anthropogenic layers, potentially requiring the management of brownfield developments across this region.

Understanding Astrophysical Noise from Stellar Surface Magneto-Convection

To obtain cm/s precision, stellar surface magneto-convection must be disentangled from observed radial velocities (RVs). In order to understand and remove the convective signature, we create Sun-as-a-star model observations based on a 3D magnetohydrodynamic solar simulation. From these Sun-as-a-star model observations, we find several line characteristics are correlated with the induced RV shifts. The aim of this campaign is to feed directly into future high precision RV studies, such as the search for habitable, rocky worlds, with forthcoming spectrographs such as ESPRESSO.

Low Noise Amplifier With Integrated Balanced Antenna for 60 GHz Wireless Communications

The implementation of a dipole antenna co-designed and monolithically integrated with a low noise amplifier (LNA) on low resistivity Si substrate (20 Omega . cm) manufactured in 0.35 mu m commercial SiGe HBT process with f(T)/f(max) of 170 GHz and 250 GHz is investigated theoretically and experimentally. An air gap is introduced between the chip and a reflective ground plane, leading to substantial improvements in efficiency and gain. Moreover, conjugate matching conditions between the antenna and the LNA are exploited, enhancing power transfer between without any additional matching circuit. A prototype is fabricated and tested to validate the performance. The measured 10-dB gain of the standalone LNA is centered at 58 GHz with a die size of 0.7 mm x 0.6 mm including all pads. The simulated results showed antenna directivity of 5.1 dBi with efficiency higher than 70%. After optimization, the co-designed LNA-Antenna chip with a die size of 3 mm x 2.8 mm was characterized in anechoic chamber environment. A maximum gain of higher than 12 dB was obtained.

An iterative longest matching segment approach to speech enhancement with additive noise and channel distortion

This paper presents a new approach to speech enhancement from single-channel measurements involving both noise and channel distortion (i.e., convolutional noise), and demonstrates its applications for robust speech recognition and for improving noisy speech quality. The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise for speech estimation. Third, we present an iterative algorithm which updates the noise and channel estimates of the corpus data model. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.

Speech Enhancement from Additive Noise and Channel Distortion - a Corpus-Based Approach

This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement. Index Terms: corpus-based speech model, longest matching segment, speech enhancement, speech recognition

Wide Matching - An Approach to Improving Noise Robustness for Speech Enhancement

It is shown that under certain conditions it is possible to obtain a good speech estimate from noise without requiring noise estimation. We study an implementation of the theory, namely wide matching, for speech enhancement. The new approach performs sentence-wide joint speech segment estimation subject to maximum recognizability to gain noise robustness. Experiments have been conducted to evaluate the new approach with variable noises and SNRs from -5 dB to noise free. It is shown that the new approach, without any estimation of the noise, significantly outperformed conventional methods in the low SNR conditions while retaining comparable performance in the high SNR conditions. It is further suggested that the wide matching and deep learning approaches can be combined towards a highly robust and accurate speech estimator.

Perceptual learning of acoustic noise generates memory-evoked potentials

Experience continuously imprints on the brain at all stages of life. The traces it leaves behind can produce perceptual learning [1], which drives adaptive behavior to previously encountered stimuli. Recently, it has been shown that even random noise, a type of sound devoid of acoustic structure, can trigger fast and robust perceptual learning after repeated exposure [2]. Here, by combining psychophysics, electroencephalography (EEG), and modeling, we show that the perceptual learning of noise is associated with evoked potentials, without any salient physical discontinuity or obvious acoustic landmark in the sound. Rather, the potentials appeared whenever a memory trace was observed behaviorally. Such memory-evoked potentials were characterized by early latencies and auditory topographies, consistent with a sensory origin. Furthermore, they were generated even on conditions of diverted attention. The EEG waveforms could be modeled as standard evoked responses to auditory events (N1-P2) [3], triggered by idiosyncratic perceptual features acquired through learning. Thus, we argue that the learning of noise is accompanied by the rapid formation of sharp neural selectivity to arbitrary and complex acoustic patterns, within sensory regions. Such a mechanism bridges the gap between the short-term and longer-term plasticity observed in the learning of noise [2, 4-6]. It could also be key to the processing of natural sounds within auditory cortices [7], suggesting that the neural code for sound source identification will be shaped by experience as well as by acoustics.

Effects of the climatic factors and anthropogenic actions in the Ria de Aveiro

A compreensão dos impactes das alterações climáticas é fundamental para a gestão a longo do prazo dos ecossistemas estuarinos. Esta compreensão só poderá ser efectiva considerando a variabilidade climática natural e o papel relativo das intervenções antropogénicas nestes ecossistemas. Assim, a presente dissertação analisa a influência das alterações climáticas e pressões antropogénicas na qualidade da água e dinâmica ecológica da Ria de Aveiro com base numa abordagem integrada, que combinou a análise de séries temporais dos últimos 25 anos e a modelação numérica de elevada resolução de cenários futuros de alterações climáticas e intervenções antropogénicas. A componente de modelação de qualidade da água e ecológica foi melhorada a vários níveis. A análise de sensibilidade do modelo 3D hidrodinâmicoecológico ECO-SELFE aplicado à Ria de Aveiro e a revisão das constantes de semi-saturação para absorção de nutrientes pelo fitoplâncton contribuíram para a precisão e robustez das aplicações. A concentração do fitoplâncton foi significativamente influenciada pelas taxas de crescimento do fitoplâncton e de mortalidade e excreção do zooplâncton, e apresentou uma sensibilidade reduzida à variação das constantes de semi-saturação na gama identificada para as diatomáceas. O acoplamento do ECO-SELFE a um modelo de campo próximo e a integração do ciclo do oxigénio aumentaram a sua capacidade de representação dos processos e das escalas espaciais relevantes. A validação do ECO-SELFE foi realizada com base num conjunto de campanhas específicas realizadas no canal de Mira. Os padrões espaciais e temporais observados para as várias variáveis (clorofila a, nutrientes, oxigénio dissolvido, salinidade, temperatura da água, correntes e níveis) foram simulados com erros menores ou semelhantes aos obtidos neste tipo de aplicações. A análise dos padrões de variabilidade espacial e temporal da qualidade da água e ecológica na Ria de Aveiro a diferentes escalas, efectuada com base nos dados históricos de 1985 a 2010 complementados pelas campanhas realizadas, sugeriu uma influência combinada da variabilidade climática e das acções antropogénicas. Os cenários futuros de alterações climáticas e intervenções antropogénicas simulados evidenciaram uma influência mais significativa das alterações climáticas quando comparadas com os efeitos das acções antropogénicas analisadas. As variações mais significativas são previstas para os cenários de subida do nível do mar, seguidos dos cenários de alterações dos regimes hidrológicos, evidenciando o papel da circulação (maré e caudal fluvial) no estabelecimento da qualidade da água e dinâmica ecológica na laguna. Para os cenários de subida do nível do mar são previstos decréscimos significativos da clorofila a e dos nutrientes a jusante e nas zonas intermédias do canal, e um aumento significativo da salinidade a montante. Estas alterações poderão favorecer modificações da composição e distribuição das comunidades, afectando a cadeia alimentar e causando uma progressão para montante de espécies marinhas. Os resultados sugerem ainda que os efeitos poderão ser mais significativos em estuários pouco profundos.

Toxicogenomics of natural and anthropogenic effectors in eleutheroembryos

The introduction of chemicals into the environment by human activities may represent a serious risk to environmental and human health. Environmental risk assessment requires the use of efficient and sensitive tools to determine the impact of contaminants on the ecosystems. The use of zebrafish for the toxicity assessment of pharmaceuticals, drugs, and pollutants, is becoming well accepted due to zebrafish unique advantages for the screening of compounds for hazard identification. The aim of the present work is to apply toxicogenomic approaches to identify novel biomarkers and uncovered potential modes of action of classic and emergent contaminants able to disrupt endocrine systems, such as the Retinoic Acid Receptor, Retinoid X Receptor and the Aryl Hydrocarbon Receptor. This study relies on different nuclear and cytosolic protein receptors and other conditional (ligand- or stress- activated) transcriptional factors that are intimately involved in the regulation of defensome genes and in mechanisms of chemical toxicity. The transcriptomic effects of organic compounds, endogenous compounds, and nanoparticles were analysed during the early stages of zebrafish development. Studying the gene expression profiles of exposed and unexposed organisms to pollutants using microarrays allowed the identification of specific gene markers and to establish a "genetic code" for the tested compounds. Changes in gene expression were observed at toxicant concentrations that did not cause morphological effects. Even at low toxicant concentrations, the observed changes in transcript levels were robust for some target genes. Microarray responses of selected genes were further complemented by the real time quantitative polymerase chain reaction (qRT-PCR) methodology. The combination of bio-informatic, toxicological analyses of differential gene expression profiles, and biochemical and phenotypic responses across the treatments allowed the identification of uncovered potential mechanisms of action. In addition, this work provides an integrated set of tools that can be used to aid management-decision making by improving the predictive capability to measure environmental stress of contaminants in freshwater ecosystems. This study also illustrates the potential of zebrafish embryos for the systematic, large-scale analysis of chemical effects on developing vertebrates.

Wind energy resource modelling in Portugal and its future large-scale alteration due to anthropogenic induced climate changes

The high dependence of Portugal from foreign energy sources (mainly fossil fuels), together with the international commitments assumed by Portugal and the national strategy in terms of energy policy, as well as resources sustainability and climate change issues, inevitably force Portugal to invest in its energetic self-sufficiency. The 20/20/20 Strategy defined by the European Union defines that in 2020 60% of the total electricity consumption must come from renewable energy sources. Wind energy is currently a major source of electricity generation in Portugal, producing about 23% of the national total electricity consumption in 2013. The National Energy Strategy 2020 (ENE2020), which aims to ensure the national compliance of the European Strategy 20/20/20, states that about half of this 60% target will be provided by wind energy. This work aims to implement and optimise a numerical weather prediction model in the simulation and modelling of the wind energy resource in Portugal, both in offshore and onshore areas. The numerical model optimisation consisted in the determination of which initial and boundary conditions and planetary boundary layer physical parameterizations options provide wind power flux (or energy density), wind speed and direction simulations closest to in situ measured wind data. Specifically for offshore areas, it is also intended to evaluate if the numerical model, once optimised, is able to produce power flux, wind speed and direction simulations more consistent with in situ measured data than wind measurements collected by satellites. This work also aims to study and analyse possible impacts that anthropogenic climate changes may have on the future wind energetic resource in Europe. The results show that the ECMWF reanalysis ERA-Interim are those that, among all the forcing databases currently available to drive numerical weather prediction models, allow wind power flux, wind speed and direction simulations more consistent with in situ wind measurements. It was also found that the Pleim-Xiu and ACM2 planetary boundary layer parameterizations are the ones that showed the best performance in terms of wind power flux, wind speed and direction simulations. This model optimisation allowed a significant reduction of the wind power flux, wind speed and direction simulations errors and, specifically for offshore areas, wind power flux, wind speed and direction simulations more consistent with in situ wind measurements than data obtained from satellites, which is a very valuable and interesting achievement. This work also revealed that future anthropogenic climate changes can negatively impact future European wind energy resource, due to tendencies towards a reduction in future wind speeds especially by the end of the current century and under stronger radiative forcing conditions.

Primary production in systems subject to natural and anthropogenic eutrophication

Tese dout., Química, Universidade do Algarve, 2005