827 resultados para Feed-forward path


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We propose a new satellite mission to deliver high quality measurements of upper air water vapour. The concept centres around a LiDAR in limb sounding by occultation geometry, designed to operate as a very long path system for differential absorption measurements. We present a preliminary performance analysis with a system sized to send 75 mJ pulses at 25 Hz at four wavelengths close to 935 nm, to up to 5 microsatellites in a counter-rotating orbit, carrying retroreflectors characterized by a reflected beam divergence of roughly twice the emitted laser beam divergence of 15 µrad. This provides water vapour profiles with a vertical sampling of 110 m; preliminary calculations suggest that the system could detect concentrations of less than 5 ppm. A secondary payload of a fairly conventional medium resolution multispectral radiometer allows wide-swath cloud and aerosol imaging. The total weight and power of the system are estimated at 3 tons and 2,700 W respectively. This novel concept presents significant challenges, including the performance of the lasers in space, the tracking between the main spacecraft and the retroreflectors, the refractive effects of turbulence, and the design of the telescopes to achieve a high signal-to-noise ratio for the high precision measurements. The mission concept was conceived at the Alpbach Summer School 2010.

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In this paper we propose an efficient two-level model identification method for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularization parameters in the elastic net are optimized using a particle swarm optimization (PSO) algorithm at the upper level by minimizing the leave one out (LOO) mean square error (LOOMSE). Illustrative examples are included to demonstrate the effectiveness of the new approaches.

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The effect of phase separation and batch duration on the trophic stages of anaerobic digestion was assessed for the first time in leach beds coupled to methanogenic reactors digesting maize (Zea mays). The system was operated for consecutive batches of 7, 14 and 28 days for ~120 days. Hydrolysis rate was higher the shorter the batch, reaching 8.5 gTSdestroyed d-1 in the 7-day system. Phase separation did not affect acidification but methanogenesis was enhanced in the short feed cycle leach beds. Phase separation was inefficient on the 7-day system, where ~89% of methane was produced in the leach bed. Methane production rate increased with shortening the feed cycle, reaching 3.523 l d-1 average in the 7-day system. Low strength leachate from the leach beds decreased methanogenic activity of methanogenic reactors’ sludges. Enumeration of cellulolytic and methanogenic microorganisms indicated a constant inoculation of leach beds and methanogenic reactors through leachate recirculation.

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A two-phase system composed by a leach bed and a methanogenic reactor was modified for the first time to improve volumetric substrate degradation and methane yields from a complex substrate (maize; Zea mays). The system, which was operated for consecutive feed cycles of different durations for 120 days, was highly flexible and its performance improved by altering operational conditions. Daily substrate degradation was higher the shorter the feed cycle, reaching 8.5 g TSdestroyed d�1 (7-day feed cycle) but the overall substrate degradation was higher by up to 55% when longer feed cycles (14 and 28 days) were applied. The same occurred with volumetric methane yields, reaching 0.839 m3 (m3)�1 d�1. The system performed better than others on specific methane yields, reaching 0.434 m3 kg�1 TSadded, in the 14-day and 28-day systems. The UASB and AF designs performed similarly as second stage reactors on methane yields, SCOD and VFA removal efficiencies.

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This paper provides a comparative study of the performance of cross-flow and counter-flow M-cycle heat exchangers for dew point cooling. It is recognised that evaporative cooling systems offer a low energy alternative to conventional air conditioning units. Recently emerged dew point cooling, as the renovated evaporative cooling configuration, is claimed to have much higher cooling output over the conventional evaporative modes owing to use of the M-cycle heat exchangers. Cross-flow and counter-flow heat exchangers, as the available structures for M-cycle dew point cooling processing, were theoretically and experimentally investigated to identify the difference in cooling effectiveness of both under the parallel structural/operational conditions, optimise the geometrical sizes of the exchangers and suggest their favourite operational conditions. Through development of a dedicated computer model and case-by-case experimental testing and validation, a parametric study of the cooling performance of the counter-flow and cross-flow heat exchangers was carried out. The results showed the counter-flow exchanger offered greater (around 20% higher) cooling capacity, as well as greater (15%–23% higher) dew-point and wet-bulb effectiveness when equal in physical size and under the same operating conditions. The cross-flow system, however, had a greater (10% higher) Energy Efficiency (COP). As the increased cooling effectiveness will lead to reduced air volume flow rate, smaller system size and lower cost, whilst the size and cost are the inherent barriers for use of dew point cooling as the alternation of the conventional cooling systems, the counter-flow system is considered to offer practical advantages over the cross-flow system that would aid the uptake of this low energy cooling alternative. In line with increased global demand for energy in cooling of building, largely by economic booming of emerging developing nations and recognised global warming, the research results will be of significant importance in terms of promoting deployment of the low energy dew point cooling system, helping reduction of energy use in cooling of buildings and cut of the associated carbon emission.

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The temporal variability of the atmosphere through which radio waves pass in the technique of differential radar interferometry can seriously limit the accuracy with which the method can measure surface motion. A forward, nested mesoscale model of the atmosphere can be used to simulate the variable water content along the radar path and the resultant phase delays. Using this approach we demonstrate how to correct an interferogram of Mount Etna in Sicily associated with an eruption in 2004-5. The regional mesoscale model (Unified Model) used to simulate the atmosphere at higher resolutions consists of four nested domains increasing in resolution (12, 4, 1, 0.3 km), sitting within the analysis version of a global numerical model that is used to initiate the simulation. Using the high resolution 3D model output we compute the surface pressure, temperature and the water vapour, liquid and solid water contents, enabling the dominant hydrostatic and wet delays to be calculated at specific times corresponding to the acquisition of the radar data. We can also simulate the second-order delay effects due to liquid water and ice.

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The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Net- work (AERONET) routinely monitor clouds using zenith ra- diances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a liquid-water-absorbing wavelength (i.e., 1640 nm) with a non-water-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g m−2 and horizontal resolution of 201 m, the retrieval method underestimates the mean effective radius by 0.8μm, with a root-mean-squared error of 1.7 μm and a relative deviation of 13%. For actual observations with a liquid water path less than 450 g m−2 at the ARM Oklahoma site during 2007– 2008, our 1.5-min-averaged retrievals are generally larger by around 1 μm than those from combined ground-based cloud radar and microwave radiometer at a 5-min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 μm and the relative deviation of 22 % are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11 % with satellite observations and have a negative bias of 1 μm. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

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Climate change is expected to bring warmer temperatures, changes to rainfall patterns, and increased frequency of extreme weather. Projections of climate impacts on feed crops show that there will likely be opportunities for increased productivity as well as considerable threats to crop productivity in different parts of the world over the next 20 to 50 years. On balance, we anticipate substantial risks to the volume, volatility, and quality of animal feed supply chains from climate change. Adaptation strategies and investment informed by high quality research at the interface of crop and animal science will be needed, both to respond to climate change and to meet the increasing demand for animal products expected over the coming decades.

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This work proposes a method to objectively determine the most suitable analogue redesign method for forward type converters under digital voltage mode control. Particular emphasis is placed on determining the method which allows the highest phase margin at the particular switching and crossover frequencies chosen by the designer. It is shown that at high crossover frequencies with respect to switching frequency, controllers designed using backward integration have the largest phase margin; whereas at low crossover frequencies with respect to switching frequency, controllers designed using bilinear integration have the largest phase margins. An accurate model of the power stage is used for simulation, and experimental results from a Buck converter are collected. The performance of the digital controllers is compared to that of the equivalent analogue controller both in simulation and experiment. Excellent correlation between the simulation and experimental results is presented. This work will allow designers to confidently choose the analogue redesign method which yields the greater phase margin for their application.

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Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

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Climate change is putting Colombian agriculture under significant stress and, if no adaptation is made, the latter will be severely impacted during the next decades. Ramirez-Villegas et al. (2012) set out a government-led, top-down, techno-scientific proposal for a way forward by which Colombian agriculture could adapt to climate change. However, this proposal largely overlooks the root causes of vulnerability of Colombian agriculture, and of smallholders in particular. I discuss some of the hidden assumptions underpinning this proposal and of the arguments employed by Ramirez-Villegas et al., based on existing literature on Colombian agriculture and the wider scientific debate on adaptation to climate change. While technical measures may play an important role in the adaptation of Colombian agriculture to climate change, I question whether the actions listed in the proposal alone and specifically for smallholders, truly represent priority issues. I suggest that by i) looking at vulnerability before adaptation, ii) contextualising climate change as one of multiple exposures, and iii) truly putting smallholders at the centre of adaptation, i.e. to learn about and with them, different and perhaps more urgent priorities for action can be identified. Ultimately, I argue that what is at stake is not only a list of adaptation measures but, more importantly, the scientific approach from which priorities for action are identified. In this respect, I propose that transformative rather than technical fix adaptation represents a better approach for Colombian agriculture and smallholders in particular, in the face of climate change.

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In the context of the Ghanaian government’s objective of structural transformation with an emphasis on manufacturing, this paper provides a case study of economic transformation in Ghana, exploring patterns of growth, sectoral transformation, and agglomeration. We document and examine why, despite impressive growth and poverty reduction figures, Ghana’s economy has exhibited less transformation than might be expected for a country that has recently achieved middle-income status. Ghana’s reduced share of agriculture in the economy, unlike many successfully transformed countries in Asia and Latin America, has been filled by services, while manufacturing has stagnated and even declined. Likely causes include weak transformation of the agricultural sector and therefore little development of agroprocessing, the emergence of consumption cities and consumption-driven growth, upward pressure on the exchange rate, weak production linkages, and a poor environment for private-sector-led manufacturing.

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In this paper, dual-hop amplify-and-forward (AF) cooperative systems in the presence of in-phase and quadrature-phase (I/Q) imbalance, which refers to the mismatch between components in I and Q branches, are investigated. First, we analyze the performance of the considered AF cooperative protocol without compensation for I/Q imbalance as the benchmark. Furthermore, a compensation algorithm for I/Q imbalance is proposed, which makes use of the received signals at the destination, from the source and relay nodes, together with their conjugations to detect the transmitted signal. The performance of the AF cooperative system under study is evaluated in terms of average symbol error probability (SEP), which is derived considering transmission over Rayleigh fading channels. Numerical results are provided and show that the proposed compensation algorithm can efficiently mitigate the effect of I/Q imbalance.