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593 result(s) for "sampling framework"
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Reduced phase locking to slow amplitude modulation in adults with dyslexia: An MEG study
Perception of speech at multiple temporal scales is important for the efficient extraction of meaningful phonological elements. Individuals with developmental dyslexia have difficulty in the accurate neural representation of phonological aspects of speech, across languages. Recently, it was proposed that these difficulties might arise in part because of impaired phase locking to the slower modulations in the speech signal (<10Hz), which would affect syllabic parsing and segmentation of the speech stream (the “temporal sampling” hypothesis, Goswami, 2011). Here we measured MEG responses to different rates of amplitude modulated white noise in adults with and without dyslexia. In line with the temporal sampling hypothesis, different patterns of phase locking to amplitude modulation at the delta rate of 2Hz were found when comparing participants with dyslexia to typically-reading participants. Typical readers exhibited better phase locking to slow modulations in right auditory cortex, whereas adults with dyslexia showed more bilateral phase locking. The results suggest that oscillatory phase locking mechanisms for slower temporal modulations are atypical in developmental dyslexia. ► MEG response to amplitude modulation at 2 and 4Hz rates shows two cortical sources. ► MEG response to amplitude modulation at 10 and 20Hz rates has one cortical source. ► Phase locking at 2Hz shows strong right auditory cortex activation in controls. ► Phase locking at 2Hz shows bilateral auditory cortex activation in dyslexics.
High resolution orthomosaics of African coral reefs: a tool for wide-scale benthic monitoring
Coral reefs play a key role in coastal protection and habitat provision. They are also well known for their recreational value. Attempts to protect these ecosystems have not successfully stopped large-scale degradation. Significant efforts have been made by government and research organizations to ensure that coral reefs are monitored systematically to gain a deeper understanding of the causes, the effects and the extent of threats affecting coral reefs. However, further research is needed to fully understand the importance that sampling design has on coral reef characterization and assessment. This study examines the effect that sampling design has on the estimation of seascape metrics when coupling semi-autonomous underwater vehicles, structure-from-motion photogrammetry techniques and high resolution (0.4 cm) underwater imagery. For this purpose, we use FRAGSTATS v4 to estimate key seascape metrics that enable quantification of the area, density, edge, shape, contagion, interspersion and diversity of sessile organisms for a range of sampling scales (0.5 m × 0.5 m, 2 m × 2 m, 5 m × 5 m, 7 m × 7 m), quadrat densities (from 1–100 quadrats) and sampling strategies (nested vs. random) within a 1655 m2 case study area in Ponta do Ouro Partial Marine Reserve (Mozambique). Results show that the benthic community is rather disaggregated within a rocky matrix; the embedded patches frequently have a small size and a regular shape; and the population is highly represented by soft corals. The genus Acropora is the more frequent and shows bigger colonies in the group of hard corals. Each of the seascape metrics has specific requirements of the sampling scale and quadrat density for robust estimation. Overall, the majority of the metrics were accurately identified by sampling scales equal to or coarser than 5 m × 5 m and quadrat densities equal to or larger than 30. The study indicates that special attention needs to be dedicated to the design of coral reef monitoring programmes, with decisions being based on the seascape metrics and statistics being determined. The results presented here are representative of the eastern South Africa coral reefs and are expected to be transferable to coral reefs with similar characteristics. The work presented here is limited to one study site and further research is required to confirm the findings.
Classification with label noise: a Markov chain sampling framework
The effectiveness of classification methods relies largely on the correctness of instance labels. In real applications, however, the labels of instances are often not highly reliable due to the presence of label noise. Training effective classifiers in the presence of label noise is a challenging task that enjoys many real-world applications. In this paper, we propose a Markov chain sampling (MCS) framework that accurately identifies mislabeled instances and robustly learns effective classifiers. MCS builds a Markov chain where each state uniquely represents a set of randomly sampled instances. We show that the Markov chain has a unique stationary distribution, which puts much larger probability weights on the states dominated by correctly labeled instances than the states dominated by mislabeled instances. We propose a Markov Chain Monte Carlo sampling algorithm to approximate the stationary distribution, which is further used to compute the mislabeling probability for each instance, and train noise-resistant classifiers. The MCS framework is highly compatible with a wide spectrum of classifiers that produce probabilistic classification results. Extensive experiments on both real and synthetic data sets demonstrate the superior effectiveness and efficiency of the proposed MCS framework.
Language Acquisition in the Longitudinal Cambridge UK BabyRhythm Cohort
The Cambridge UK BabyRhythm project is a study of 122 infants as they age from 2 – 30 months, investigating cortical tracking and sensorimotor synchronisation to acoustic and visual rhythm in relation to language acquisition. As there are few standardised language tasks appropriate for this age range, the BabyRhythm project adapted a range of parent-report and infant-led experimental measures that could be used within a home testing environment. Here we present a rich description of infant performance on tasks intended to sample 5 linguistic domains: semantics, phonology, grammar, rhythmic timing and gesture. For each task we describe infant performance (mean, median, range), and we also report performance by sex (N female = 57) and by monolingual (N = 91) versus multilingual (N = 31) home environments. We report relations between measures. We share our unique longitudinal database (all data available on OSF), and ‘lessons learned’ on adapting language assessments for very young children. Critically, we identify the language tasks that will be utilised in our longitudinal brain-behaviour analyses, providing the benchmark upon which future neural and behavioural markers will be measured.
Is It About Speech or About Prediction? Testing Between Two Accounts of the Rhythm–Reading Link
Background/Objectives: The mechanisms underlying the positive association between reading and rhythmic skills remain unclear. Our goal was to systematically test between two major explanations: the Temporal Sampling Framework (TSF), which highlights the relation between rhythm and speech encoding, and a competing explanation based on rhythm’s role in enhancing prediction within visual and auditory sequences. Methods: We compared beat versus duration perception for their associations with encoding and sequence learning (prediction-related) tasks, using both visual and auditory sequences. We also compared these associations for Portuguese vs. Greek participants, since Portuguese stress-timed rhythm is more compatible with music-like beats lasting around 500 ms, in contrast to the syllable-timed rhythm of Greek. If rhythm acts via speech encoding, its effects should be more salient in Portuguese. Results: Consistent with the TSF’s predictions, we found a significant association between beat perception and auditory encoding in Portuguese but not in Greek participants. Correlations between time perception and sequence learning in both modalities were either null or insufficiently supported in both groups. Conclusions: Altogether, the evidence supported the TSF-related predictions in detriment of the Rhythm-as-Predictor (RaP) hypothesis.
Survey design for precise fire management conservation targets
Common goals of ecological fire management are to sustain biodiversity and minimize extinction risk. A novel approach to achieving these goals determines the relative proportions of vegetation growth stages (equivalent to successional stages, which are categorical representations of time since fire) that maximize a biodiversity index. The method combines data describing species abundances in each growth stage with numerical optimization to define an optimal growth-stage structure that provides a conservation-based operational target for managers. However, conservation targets derived from growth-stage optimization are likely to depend critically on choices regarding input data. There is growing interest in the use of growth-stage optimization as a basis for fire management, thus understanding of how input data influence the outputs is crucial. Simulated data sets provide a flexible platform for systematically varying aspects of survey design and species inclusions. We used artificial data with known properties, and a case-study data set from southeastern Australia, to examine the influence of (1) survey design (total number of sites and their distribution among growth stages) and (2) species inclusions (total number of species and their level of specialization) on the precision of conservation targets. Based on our findings, we recommend that survey designs for precise estimates would ideally involve at least 80 sites, and include at least 80 species. Greater numbers of sites and species will yield increasingly reliable results, but fewer might be sufficient in some circumstances. An even distribution of sites among growth stages was less important than the total number of sites, and omission of species is unlikely to have a major influence on results as long as several species specialize on each growth stage. We highlight the importance of examining the responses of individual species to growth stage before feeding survey data into the growth-stage optimization black box, and advocate use of a resampling procedure to determine the precision of results. Collectively, our findings form a reproducible guide to designing ecological surveys that yield precise conservation targets through growth-stage optimization, and ultimately help sustain biodiversity in fire-prone systems.
River Radii: A Comparative National Framework for Remote Monitoring of Environmental Change at River Mouths
River mouths are important indicators and mediators of interactions between rivers and the sea that mark the dispersal point for catchment-based stressors and subsidies. Satellite remote sensing data products and algorithms present many new possibilities for monitoring these dynamic and often inaccessible environments. In this study, we describe a national-scale comparative framework based on proximity to river mouths and show its application to the monitoring of coastal ecosystem health in Aotearoa New Zealand. We present results from light attenuation coefficient (Kd) analyses used to develop the framework considering data products of differing resolution and the effects of coastline geometries which might obscure the influence of catchment-derived stressors. Ten-year (2013–2022) Kd values from the highest-resolution product (500 m) showed significant differences (p < 0.01) in successively larger radii (1–20 km) despite the confounding influence of adjacent river mouths. Smaller radii returned a high variability that dropped markedly > 5 km. Tests of a 10 km radius showed that coastline geometry had a significant influence on Kd (p < 0.001), which is also likely for other water quality indicators. An analytical approach stratified by coastline geometry showed significant effects of stream order on open (p < 0.01) but not enclosed coasts, differences between marine bioregions (p < 0.05), and a degradation trend in the 90th percentile of Kd on enclosed coasts, which is indicative of extreme events associated with catchment erosion or sediment resuspension. We highlight applications of the framework to explore trends across many other meaningful scales (e.g., jurisdictions and ecosystem types) in addition to tracking changes at individual river mouths.
Analysis and Evaluation of a Framework for Sampling Database in Recommenders
In this paper the authors proposed a database sampling framework that aims to minimize the time necessary to produce a sample database. They argue that the performance of current relational database sampling techniques that maintain the data integrity of the sample database is low and a faster strategy needs to be devised. The sampling method targets the production environment of a system under development that generally consists of large amounts of data computationally costly to analyze. The results have been improved due to the fact that the authors have selected the users that they had more information about them and they have made the data table denser. Therefore, by increasing the data and making the rating more comprehensive for all the users they can help to produce the more and better association rules. The obtained results were not that much suitable for Jester dataset but with their proposed methods the authors have tried to improve the quantity and quality of the rules. These results indicate that the effectiveness of the system greatly depends on the input data and the applied dataset. In addition, if the user rates more number of the items the system efficiency will be more increased.
Six Steps towards a Spatial Design for Large-Scale Pollinator Surveillance Monitoring
Despite the importance of pollinators to ecosystem functioning and human food production, comprehensive pollinator monitoring data are still lacking across most regions of the world. Policy-makers have recently prioritised the development of large-scale monitoring programmes for pollinators to better understand how populations respond to land use, environmental change and restoration measures in the long term. Designing such a monitoring programme is challenging, partly because it requires both ecological knowledge and advanced knowledge in sampling design. This study aims to develop a conceptual framework to facilitate the spatial sampling design of large-scale surveillance monitoring. The system is designed to detect changes in pollinator species abundances and richness, focusing on temperate agroecosystems. The sampling design needs to be scientifically robust to address questions of agri-environmental policy at the scales of interest. To this end, we followed a six-step procedure as follows: (1) defining the spatial sampling units, (2) defining and delimiting the monitoring area, (3) deciding on the general sampling strategy, (4) determining the sample size, (5) specifying the sampling units per sampling interval, and (6) specifying the pollinator survey plots within each sampling unit. As a case study, we apply this framework to the “Wild bee monitoring in agricultural landscapes of Germany” programme. We suggest this six-step procedure as a conceptual guideline for the spatial sampling design of future large-scale pollinator monitoring initiatives.
Local quantification and characterisation represents a basic tool for integrated residential solid waste management
A sampling and characterisation plan for residential solid waste (SW) produced in the city of Cali in Colombia was developed between January and September 2006; this required designing an undisclosed strategy in the country and the results showed the need for an adjustment to the current SW Colombian classification scheme. The available sampling frame made a two-stage sampling plan necessary, block side (BS) being the first stage and household BS the second. A 0.39 kg/(person-day) solid waste per-capita production (PCP) was found, which increased with socioeconomic status. Food waste was produced most, a large part consisting of cooked food. Waste from personal hygiene items was a third category, although this is not currently a category which is included in Colombian Technical Standard –RAS 2000. Although characterisation techniques are used worldwide, the results showed the relevance of available sampling frame-based local characterisation, using local data for sampling methods and associated sample size selection.