931 resultados para Large-scale Testing


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Póster presentado en: 21st World Hydrogen Energy Conference 2016. Zaragoza, Spain. 13-16th June, 2016

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We review the use of neural field models for modelling the brain at the large scales necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that is limited to coarse-grained or mean-field activity, neural field models provide a framework for unifying data from different imaging modalities. Starting with a description of neural mass models we build to spatially extended cortical models of layered two-dimensional sheets with long range axonal connections mediating synaptic interactions. Reformulations of the fundamental non-local mathematical model in terms of more familiar local differential (brain wave) equations are described. Techniques for the analysis of such models, including how to determine the onset of spatio-temporal pattern forming instabilities, are reviewed. Extensions of the basic formalism to treat refractoriness, adaptive feedback and inhomogeneous connectivity are described along with open challenges for the development of multi-scale models that can integrate macroscopic models at large spatial scales with models at the microscopic scale.

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Lesson plan published in Critical Pedagogy Handbook, vol. 2

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Understanding the factors that affect seagrass meadows encompassing their entire range of distribution is challenging yet important for their conservation. We model the environmental niche of Cymodocea nodosa using a combination of environmental variables and landscape metrics to examine factors defining its distribution and find suitable habitats for the species. The most relevant environmental variables defining the distribution of C. nodosa were sea surface temperature (SST) and salinity. We found suitable habitats at SST from 5.8 ºC to 26.4 ºC and salinity ranging from 17.5 to 39.3. Optimal values of mean winter wave height ranged between 1.2 m and 1.5 m, while waves higher than 2.5 m seemed to limit the presence of the species. The influence of nutrients and pH, despite having weight on the models, was not so clear in terms of ranges that confine the distribution of the species. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. By contrasting predictive approaches, we defined the variables affecting the distributional areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. These findings are encouraging for its use in future studies on climate-related marine range shifts and meadow restoration projects of these fragile ecosystems.

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O objetivo deste trabalho foi avaliar o cultivo em larga escala de Ankistrodesmus gracilis e Diaphanososma birgei em laboratório através do estudo da biologia das espécies, composição bioquímica e custo operacional de produção. A. gracilis apresentou um crescimento exponencial até o sexto dia, ao redor de 144 x 10(4) células mL-1. Logo em seguida, sofreu um brusco decréscimo apresentando 90 x 10(4) células mL-1 (oitavo dia). A partir do décimo primeiro dia, as células algais tenderam a crescer novamente, apresentando um máximo de 135 x 10(4) células mL-1 no 17º dia. No cultivo de D. birgei, foi observado o primeiro pico de crescimento no nono dia com 140 x 10² indivíduos L-1, aumentando novamente a partir do décimo segundo dia. A alga clorofícea A. gracilis e o zooplâncton D. birgei possuem aproximadamente 50 e 70% de proteína (PS), respectivamente, com teor de carboidrato acima de 5%. A eletricidade e mão de obra foram os itens mais dispendiosos e, de acordo com os dados obtidos, a temperatura, nutrientes, disponibilidade de luz e manejo do cultivo, foram fatores determinantes sobre a produtividade. Os resultados indicam que o meio NPK (20-5-20) pode ser utilizado diretamente como uma alternativa de cultivo em larga escala, considerando o baixo custo de produção, promovendo adequado crescimento e valor nutricional para A. gracilis e D. birgei.

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Performance and economic indicators of a large scale fish farm that produces round fish, located in Mato Grosso State, Brazil, were evaluated. The 130.8 ha-water surface area was distributed in 30 ponds. Average total production costs and the following economic indicators were calculated: gross income (GI), gross margin (GM), gross margin index (GMI), profitability index (PI) and profit (P) for the farm as a whole and for ten ponds individually. Production performance indicators were also obtained, such as: production cycle (PC), apparent feed conversion (FC), average biomass storage (ABS), survival index (SI) and final average weight (FAW). The average costs to produce an average 2.971 kg.ha-1 per year were: R$ 2.43, R$ 0.72 and R$ 3.15 as average variable, fixed and total costs, respectively. Gross margin and profit per year per hectare of water surface were R$ 2,316.91 and R$ 180.98, respectively. The individual evaluation of the ponds showed that the best pond performance was obtained for PI 38%, FC 1.7, ABS 0.980 kg.m-2, TS 56%, FAW 1.873 kg with PC of 12.3 months. The worst PI was obtained for the pond that displayed losses of 138%, FC 2.6, ABS 0.110 kg.m-2, SI 16% and FAW 1.811 kg. However, large scale production of round-fish in farms is economically feasible. The studied farm displays favorable conditions to improve performance and economic indicators, but it is necessary to reproduce the breeding techniques and performance indicators achieved in few ponds to the entire farm.

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This paper proposes a new design method of H∞ filtering for nonlinear large-scale systems with interconnected time-varying delays. The interaction terms with interval time-varying delays are bounded by nonlinear bounding functions including all states of the subsystems. A stable linear filter is designed to ensure that the filtering error system is exponentially stable with a prescribed convergence rate. By constructing a set of improved Lyapunov functions and using generalized Jensen inequality, new delay-dependent conditions for designing H∞ filter are obtained in terms of linear matrix inequalities. Finally, an example is provided to illustrate the effectiveness of the proposed result.

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In this paper, the problem of distributed functional state observer design for a class of large-scale interconnected systems in the presence of heterogeneous time-varying delays in the interconnections and the local state vectors is considered. The resulting observer scheme is suitable for strongly coupled subsystems with multiple time-varying delays, and is shown to give better results for systems with very strong interconnections while only some mild existence conditions are imposed. A set of existence conditions are derived along with a computationally simple observer constructive procedure. Based on the Lyapunov-Krasovskii functional method (LKF) in the framework of linear matrix inequalities (LMIs), delay-dependent conditions are derived to obtain the observer parameters ensuring the exponential convergence of the observer error dynamics. The effectiveness of the obtained results is illustrated and tested through a numerical example of a three-area interconnected system.

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Relying on the absence, presence of level of symptomatology may not provide an adequate indication of the effects of treatment for depression, nor sufficient information for the development of treatment plans that meet patients' needs. Using a prospective, multi-centered, and observational design, the present study surveyed a large sample of outpatients with depression in China (n=9855). The 17-item Hamilton Rating Scale for Depression (HRSD-17) and the Remission Evaluation and Mood Inventory Tool (REMIT) were administered at baseline, two weeks later and 4 weeks, to assess patients' self-reported symptoms and general sense of mental health and wellbeing. Of 9855 outpatients, 91.3% were diagnosed as experiencing moderate to severe depression. The patients reported significant improvement over time on both depressive symptoms and general sense after 4-week treatment. The effect sizes of change in general sense were lower than those in symptoms at both two week and four week follow-up. Treatment effects on both general sense and depressive symptomatology were associated with demographic and clinical factors. The findings indicate that a focus on both general sense of mental health and wellbeing in addition to depressive symptomatology will provide clinicians, researchers and patients themselves with a broader perspective of the status of patients.

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Many algorithms have been introduced to deterministically authenticate Radio Frequency Identification (RFID) tags, while little work has been done to address scalability issue in batch authentications. Deterministic approaches verify tags one by one, and the communication overhead and time cost grow linearly with increasing size of tags. We design a fast and scalable counterfeits estimation scheme, INformative Counting (INC), which achieves sublinear authentication time and communication cost in batch verifications. The key novelty of INC builds on an FM-Sketch variant authentication synopsis that can capture key counting information using only sublinear space. With the help of this well-designed data structure, INC is able to provide authentication results with accurate estimates of the number of counterfeiting tags and genuine tags, while previous batch authentication methods merely provide 0/1 results indicating the existence of counterfeits. We conduct detailed theoretical analysis and extensive experiments to examine this design and the results show that INC significantly outperforms previous work in terms of effectiveness and efficiency.

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OBJECTIVE: To investigate whether cost-related non-collection of prescription medication is associated with a decline in health. SETTINGS: New Zealand Survey of Family, Income and Employment (SoFIE)-Health. PARTICIPANTS: Data from 17 363 participants with at least two observations in three waves (2004-2005, 2006-2007, 2008-2009) of a panel study were analysed using fixed effects regression modelling. PRIMARY OUTCOME MEASURES: Self-rated health (SRH), physical health (PCS) and mental health scores (MCS) were the health measures used in this study. RESULTS: After adjusting for time-varying confounders, non-collection of prescription items was associated with a 0.11 (95% CI 0.07 to 0.15) unit worsening in SRH, a 1.00 (95% CI 0.61 to 1.40) unit decline in PCS and a 1.69 (95% CI 1.19 to 2.18) unit decline in MCS. The interaction of the main exposure with gender was significant for SRH and MCS. Non-collection of prescription items was associated with a decline in SRH of 0.18 (95% CI 0.11 to 0.25) units for males and 0.08 (95% CI 0.03 to 0.13) units for females, and a decrease in MCS of 2.55 (95% CI 1.67 to 3.42) and 1.29 (95% CI 0.70 to 1.89) units for males and females, respectively. The interaction of the main exposure with age was significant for SRH. For respondents aged 15-24 and 25-64 years, non-collection of prescription items was associated with a decline in SRH of 0.12 (95% CI 0.03 to 0.21) and 0.12 (95% CI 0.07 to 0.17) units, respectively, but for respondents aged 65 years and over, non-collection of prescription items had no significant effect on SRH. CONCLUSION: Our results show that those who do not collect prescription medications because of cost have an increased risk of a subsequent decline in health.

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To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.

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This study presents a computational parametric analysis of DME steam reforming in a large scale Circulating Fluidized Bed (CFB) reactor. The Computational Fluid Dynamic (CFD) model used, which is based on Eulerian-Eulerian dispersed flow, has been developed and validated in Part I of this study [1]. The effect of the reactor inlet configuration, gas residence time, inlet temperature and steam to DME ratio on the overall reactor performance and products have all been investigated. The results have shown that the use of double sided solid feeding system remarkable improvement in the flow uniformity, but with limited effect on the reactions and products. The temperature has been found to play a dominant role in increasing the DME conversion and the hydrogen yield. According to the parametric analysis, it is recommended to run the CFB reactor at around 300 °C inlet temperature, 5.5 steam to DME molar ratio, 4 s gas residence time and 37,104 ml gcat -1 h-1 space velocity. At these conditions, the DME conversion and hydrogen molar concentration in the product gas were both found to be around 80%.

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Some color centers in diamond can serve as quantum bits which can be manipulated with microwave pulses and read out with laser, even at room temperature. However, the photon collection efficiency of bulk diamond is greatly reduced by refraction at the diamond/air interface. To address this issue, we fabricated arrays of diamond nanostructures, differing in both diameter and top end shape, with HSQ and Cr as the etching mask materials, aiming toward large scale fabrication of single-photon sources with enhanced collection efficiency made of nitrogen vacancy (NV) embedded diamond. With a mixture of O2 and CHF3 gas plasma, diamond pillars with diameters down to 45 nm were obtained. The top end shape evolution has been represented with a simple model. The tests of size dependent single-photon properties confirmed an improved single-photon collection efficiency enhancement, larger than tenfold, and a mild decrease of decoherence time with decreasing pillar diameter was observed as expected. These results provide useful information for future applications of nanostructured diamond as a single-photon source.