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See detailEstimating effects of permanent environment, lactation stage, age, and pregnancy on test-day yield.
Bormann, J.; Wiggans, G. R.; Philpot, J. C. et al

in Journal of Dairy Science (2002), 85(1), 2631-26321

Detailed reference viewed: 7 (1 ULg)
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See detailEstimating fatty acid content in cow milk using mid-infrared spectrometry
Soyeurt, Hélène ULg; Dardenne, Pierre; Dehareng, Frédéric et al

in Journal of Dairy Science (2006), 89(9), 3690-3695

Detailed reference viewed: 52 (13 ULg)
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See detailEstimating Glomerular Filtration Rate in 2012 - Does the New Chronic Kidney Disease Epidemiology Equation Fare Better than Older Equations?
DELANAYE, Pierre ULg; Krzesinski, Jean-Marie ULg

in European Nephrology (2012), 6(1), 15-20

Measuring or estimating glomerular filtration rate (GFR) is still considered the best way to apprehend global renal function. In 2009, the Chronic Kidney Disease Epidemiology (CKD-EPI) equation was ... [more ▼]

Measuring or estimating glomerular filtration rate (GFR) is still considered the best way to apprehend global renal function. In 2009, the Chronic Kidney Disease Epidemiology (CKD-EPI) equation was proposed as a better estimator of GFR than the Modification of Diet in Renal Disease (MDRD) study equation. It is supposed to underestimate GFR to a lesser degree in higher GFR levels. In this article, we present and discuss the performances of this new equation. Based on articles published between 2009 and 2012, we underline its advantages, notably better knowledge of chronic kidney disease prevalence, but also its limitations, especially in some specific populations. Our conclusion is that all equations are estimations and that nephrologists should always remain cautions in their interpretation. [less ▲]

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See detailEstimating glomerular filtration rate in Asian subjects: where do we stand?
DELANAYE, Pierre ULg; CAVALIER, Etienne ULg; Mariat, Christophe et al

in Kidney International (2011), 80(5), 439-440

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See detailEstimating Inter-Sensor Sea Surface Temperature Biases using DINEOF analysis
Tomazic, Igor ULg; Alvera Azcarate, Aïda ULg; Troupin, Charles ULg et al

Poster (2013)

Climate studies need long-term data sets of homogeneous quality, in order to discern trends from other physical signals present in the data and to minimise the contamination of these trends by errors in ... [more ▼]

Climate studies need long-term data sets of homogeneous quality, in order to discern trends from other physical signals present in the data and to minimise the contamination of these trends by errors in the source data. Sea surface temperature (SST), defined as one of essential climatology variables, has been increasingly used in both oceanographical and meteorological operational context where there is a constant need for more accurate measurements. Satellite-derived SST provides an indispensable dataset, with both spatially and temporally high resolutions. However, these data have errors of 0.5 K on a global scale and present inter-sensor and inter-regional differences due to their technical characteristics, algorithm limitations and the changing physical properties of the measured environments. These inter-sensor differences should be taken into account in any research involving more than one sensor (SST analysis, long term climate research . . . ). The error correction for each SST sensor is usually calculated as a difference between the SST data derived from referent sensor (e.g. ENVISAT/AATSR) and from the other sensors (SEVIRI, AVHRR, MODIS). However, these empirical difference (bias) fields show gaps due to the satellite characteristics (e.g. narrow swath in case of AATSR) and to the presence of clouds or other atmospheric contaminations. We present a methodology based on DINEOF (Data INterpolation Empirical Orthogonal Functions) to reconstruct and analyse SST biases with the aim of studying temporal and spatial variability of the SST bias fields both at a large scale (European seas) and at a regional scale (Mediterranean Sea) and to perform the necessary corrections to the original SST fields. Two different approaches were taken: by analysing SST biases based on reconstructed SST differences and based on differences of reconstructed SST fields. Corrected SST fields based on both approaches were validated against independent in situ buoy SST data or with ENVISAT/AATSR SST data for areas without in situ data (e.g. eastern Mediterranean). [less ▲]

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See detailEstimating internal pelvic sizes using external body measurements in the double-muscled Belgian Blue beef breed
Coopman, F.; de Smet, S.; Gengler, Nicolas ULg et al

in Animal Science (2003), 76(Part 2), 229-235

In the double-muscled (DM) Belgian Blue beef (BBB) breed, caesarean section (CS) is being applied systematically as a management tool to prevent dystocia. As a matter of fact, CS is the only possible way ... [more ▼]

In the double-muscled (DM) Belgian Blue beef (BBB) breed, caesarean section (CS) is being applied systematically as a management tool to prevent dystocia. As a matter of fact, CS is the only possible way of calving in the breed. High birth weight and a relatively small pelvic area are the main causes of dystocia and, in the DM-BBB breed, the reasons for the systematically applied CS. Selection for lower birth weight and larger pelvic sizes might reduce dystocia and routine CS. Few data on inner pelvic sizes of pedigree animals are available. Using external measurements to estimate the inner pelvic sizes might be an option to resolve this problem. In this study, animals of the DM-BBB breed were measured and weighed on farms and in abattoirs. External and internal pelvic sizes increased with live weight and age of the animals. Gender had a significant influence on inner pelvic traits. Increased muscular conformation was associated with decreased inner pelvic dimensions. Models with weight, gender, age, withers height and outer pelvic width (TcTc) can be used to estimate inner pelvic sizes (R-2 between 0.35 and 0.77). The estimated inner pelvic sizes can then be used to genetically evaluate pelvic traits in the DM-BBB breed. Improving weight, withers height and TcTc width in combination with lowering muscular conformation may help to decrease the high rate of caesarean section in the DM-BBB. [less ▲]

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See detailEstimating marine biogeochemical rates of the carbonate pH system—A Kalman filter tested
Soetaert; Grégoire, Marilaure ULg

in Ecological Modelling (2011), 222

Oxygen (O2), nitrate (NO3), dissolved inorganic carbon (DIC) or pCO2, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying ... [more ▼]

Oxygen (O2), nitrate (NO3), dissolved inorganic carbon (DIC) or pCO2, and pH or total alkalinity (TA), are useful indices of marine chemical, physical and biological processes operating on varying timescales. Although these properties are increasingly being monitored at high frequency, they have not been extensively used for studying ecosystem dynamics. We test whether we can estimate time-evolving biogeochemical rates (e.g. primary production, respiration, calcification and carbonate dissolution, and nitrification) from synthetic high frequency time-series of O2, NO3, DIC, pCO2, TA or pH. More specifically, a Kalman filter has been implemented in a very simplified biogeochemical model describing the dynamics of O2, NO3, DIC and TA and linking the concentration data to biogeochemical fluxes. Different sets of concentration data are assimilated and biogeochemical rates are estimated. The frequency of assimilation required to get acceptable results is investigated and is compared with the frequency of sampling in the field or in controlled experimental settings. Smoothing of the data to remove data noise before assimilation improves the estimation of the biogeochemical rates. The best estimated rates are obtained when assimilating O2, NO3 and TA although the assimilation of DIC instead of TA also gives satisfactory results. In case pH or pCO2 is assimilated rather than DIC or TA, the linearization of the (now nonlinear) observation equation introduces perturbations and the Kalman filter behaves suboptimal. We conclude that, given the resolution of data required, the tool has potential to estimate biogeochemical rates of the carbonate system under controlled settings. [less ▲]

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See detailEstimating myostatin gene effect on milk performance traits using estimated gene content for a large number of non-genotyped cows
Buske, Bernd; Vanrobays, Marie-Laure ULg; Szydlowski, Maciej et al

Conference (2011, August 29)

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See detailEstimating myostatin gene effect on milk performance traits using estimated gene content for a large number of non-genotyped cows
Buske, Bernd ULg; Szydlowski, Maciej; Verkenne, Catherine et al

in Animal (2011), 5(1), 43-47

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See detailEstimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO2
van Gorsel, Eva; Delpierre, Nicolas; Leuning, Ray et al

in Agricultural and Forest Meteorology (2009), 149(11), 1919-1930

Micrometeorological measurements of night time ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and ... [more ▼]

Micrometeorological measurements of night time ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and within plant canopies. The associated horizontal and vertical advective fluxes cannot be measured using instrumentation on the single towers typically used at micrometeorological sites. A common approach to minimize bias is to use a threshold in friction velocity, u*, to exclude periods when advection is assumed to be important, but this is problematic in situations when in-canopy flows are decoupled from the flow above. Using data from 25 flux stations in a wide variety of forest ecosystems globally, we examine the generality of a novel approach to estimating nocturnal respiration developed by van Gorsel et al. (van Gorsel, E., Leuning, R., Cleugh, H.A., Keith, H., Suni, T., 2007. Nocturnal carbon efflux: reconciliation of eddy covariance and chamber measurements using an alternative to the u*-threshold filtering technique. Tellus 59B, 397-403, Tellus, 59B, 307-403). The approach is based on the assumption that advection is small relative to the vertical turbulent flux (F-C) and change in storage (F-S) of CO2 in the few hours after sundown. The sum of F-C and F-S reach a maximum during this period which is used to derive a temperature response function for ecosystem respiration. Measured hourly soil temperatures are then used with this function to estimate respiration R-Rmax. The new approach yielded excellent agreement with (1) independent measurements using respiration chambers, (2) with estimates using ecosystem light-response curves of F-c + F-s extrapolated to zero light, R-LRC, and (3) with a detailed process-based forest ecosystem model, R-cast. At most sites respiration rates estimated using the u*-filter, R-ust, were smaller than R-Rmax, and R-LRC. Agreement of our approach with independent measurements indicates that R-Rmax, provides an excellent estimate of nighttime ecosystem respiration. (C) 2009 Elsevier B.V. All rights reserved. [less ▲]

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See detailEstimating pCO2 from remote sensing in the Belgian Coastal Zone
Borges, Alberto ULg; Ruddick, K.; Harlay, Jérôme ULg

Conference (2012, May 09)

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See detailEstimating pCO2 from remote sensing in the Belgian Coastal Zone
Borges, Alberto ULg; Ruddick, Kevin; Harlay, Jérôme ULg

Poster (2012, April 22)

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See detailEstimating pCO2 from remote sensing in the Belgian coastal zone
Borges, Alberto; Ruddick, Kevin; Lacroix, Geneviève et al

in ESA Special Publication SP-686 (2010)

In coastal waters, a purely field observation based approach will probably be insufficient to better constrain estimates of air-sea CO2 fluxes, to study their inter-annual variability and their long-term ... [more ▼]

In coastal waters, a purely field observation based approach will probably be insufficient to better constrain estimates of air-sea CO2 fluxes, to study their inter-annual variability and their long-term changes. One approach to achieve these goals is to use remotely sensed fields of relevant biogeochemical variables to extrapolate available data, and produce maps of the partial pressure of CO2 (pCO2) and air-sea CO2 fluxes. In the open ocean this approach has to some extent been successfully used based on fields of chlorophyll-a (Chla) and sea surface temperature (SST). This approach remains challenging in coastal waters that have complex optical properties (Case-II waters) and that exhibit highly dynamic pCO2 temporal and spatial variations. In the frame of the Belgian funded BELCOLOUR-II project (Optical remote sensing of marine, coastal and inland waters; http://www.mumm.ac.be/BELCOLOUR/), three field cruises per year (April, July and September) for optical measurements were carried in 2007, 2008, 2009 in the Southern Bight of the North Sea (SBNS). Based on these data-sets, we derived algorithms to compute pCO2 from Chl-a and sea surface salinity (SSS) using multipolynomial regressions (MPR). Here we report the first application of the MPR algorithms to derive pCO2 fields in the Belgian coastal zone based on data gathered in 2007, using remote sensed Chl-a (MERIS) and SSS computed with a 3-D hydrodynamical model of SBNS (COHERENS). [less ▲]

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See detailEstimating pCO2 from remote sensing in the Belgian Coastal Zone
Borges, Alberto ULg; Ruddick, K.; Lacroix, G. et al

in ESA Living Planet Symposium : 28 June - 2 July 2010, Bergen, Norway (2010)

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See detailEstimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data
Kouadio, Amani Louis ULg; Duveiller, Gregory; Djaby, Bakary ULg et al

in International Journal of Applied Earth Observation and Geoinformation (2012), 18

Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation ... [more ▼]

Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence date and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha−1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems. [less ▲]

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See detailEstimating residual fluxes in strong tidal estuaries: discussion of methods and illustration by model results
Regnier, P.; Mouchet, Anne ULg; Wollast, R. et al

in Continental Shelf Research (1998), 18

Detailed reference viewed: 17 (2 ULg)
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See detailEstimating stellar mean density through seismic inversions
Reese, Daniel ULg; Marques, J. P.; Goupil, M. J. et al

in Astronomy and Astrophysics (2012), 539(A63), 18

Determining the mass of stars is crucial both for improving stellar evolution theory and for characterising exoplanetary systems. Asteroseismology offers a promising way for estimating the stellar mean ... [more ▼]

Determining the mass of stars is crucial both for improving stellar evolution theory and for characterising exoplanetary systems. Asteroseismology offers a promising way for estimating the stellar mean density. When combined with accurate radii determinations, such as are expected from GAIA, this yields accurate stellar masses. The main difficulty is finding the best way to extract the mean density of a star from a set of observed frequencies. We seek to establish a new method for estimating the stellar mean density, which combines the simplicity of a scaling law while providing the accuracy of an inversion technique. We provide a framework in which to construct and evaluate kernel-based linear inversions that directly yield the mean density of a star. We then describe three different inversion techniques (SOLA and two scaling laws) and apply them to the Sun, several test cases and three stars, alpha Cen B, HD 49933 and HD 49385, two of which are observed by CoRoT. The SOLA (subtractive optimally localised averages) approach and the scaling law based on the surface correcting technique described by Kjeldsen et al. (2008, ApJ, 683, L175) yield comparable results that can reach an accuracy of 0.5 % and are better than scaling the large frequency separation. The reason for this is that the averaging kernels from the two first methods are comparable in quality and are better than what is obtained with the large frequency separation. It is also shown that scaling the large frequency separation is more sensitive to near-surface effects, but is much less affected by an incorrect mode identification. As a result, one can identify pulsation modes by looking for an l and n assignment which provides the best agreement between the results from the large frequency separation and those from one of the two other methods. Non-linear effects are also discussed, as is the effects of mixed modes. In particular, we show that mixed modes bring little improvement to the mean density estimates because of their poorly adapted kernels. [less ▲]

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See detailEstimating survival rates in ecological studies with small unbalanced sample sizes: an alternative Bayesian point estimator
Damgaard, Christian; Fayolle, Adeline ULg

in Computational Ecology and Software (2011), 1(4), 243-248

Increasingly, the survival rates in experimental ecology are presented using odds ratios or log response ratios, but the use of ratio metrics has a problem when all the individuals have either died or ... [more ▼]

Increasingly, the survival rates in experimental ecology are presented using odds ratios or log response ratios, but the use of ratio metrics has a problem when all the individuals have either died or survived in only one replicate. In the empirical ecological literature, the problem often has been ignored or circumvented by different, more or less ad hoc approaches. Here, it is argued that the best summary statistic for communicating ecological results of frequency data in studies with small unbalanced samples may be the mean of the posterior distribution of the survival rate. The developed approach may be particularly useful when effect size indexes, such as odds ratios, are needed to compare frequency data between treatments, sites or studies. [less ▲]

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See detailEstimating Systematic Risk in the Presence of Thin Trading and Conditional Heteroscedasticity
Corhay, Albert ULg; Tourani Rad, Alireza; Urbain, Jean-Pierre

in In The Money (1997), 2

Detailed reference viewed: 5 (4 ULg)