Institutional requirements for market-led development in Latin America

Includes bibliography

Development of sustainable precision farming systems for swine: Estimating realtime individual amino acid requirements in growing-finishing pigs

The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation. Thus, the amino acid requirements estimated by model are animal- and time-dependent and follow, in real time, the individual DFI and BW growth patterns. The proposed model can follow the average feed intake and feed weight trajectory of each individual pig in real time with good accuracy. Based on these trajectories and using classical factorial equations, the model makes it possible to estimate dynamically the AA requirements of each animal, taking into account the intake and growth changes of the animal. © 2012 American Society of Animal Science. All rights reserved.

Latin American and Caribbean development: obstacles, requirements and options

Include bibliography

Challenges in meeting the monitoring requirements of the Millennium Development Goals (MDGs): an examination of selected social statistics for four Caribbean small island developing states

Includes bibliography

Desarrollo de América Latina y el Caribe: escollos, requisitos y opciones = Latin American and Caribbean development: obstacles, requirements and options

Incluye Bibliografía

Daños ocasionados por el huracán Joan en Nicaragua: sus efectos sobre el desarrollo económico y las condiciones de vida, y requerimientos para la rehabilitación y reconstrucción: nota de la Secretaría = Damage caused by hurricane Joan in Nicaragua: its effects on economic development and living conditions, and requirements for rehabilitation and reconstruction: note by the Secretariat

Incluye Bibliografía

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

Emission inventories and modeling requirements for the development of air quality plans. Application to Madrid (Spain)

Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO2. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.

Structural requirements for peptidic antagonists of the corticotropin-releasing factor receptor (CRFR): Development of CRFR2β-selective antisauvagine-30

Different truncated and conformationally constrained analogs of corticotropin-releasing factor (CRF) were synthesized on the basis of the amino acid sequences of human/rat CRF (h/rCRF), ovine CRF (oCRF), rat urocortin (rUcn), or sauvagine (Svg) and tested for their ability to displace [125I-Tyr0]oCRF or [125I-Tyr0]Svg from membrane homogenates of human embryonic kidney (HEK) 293 cells stably transfected with cDNA coding for rat CRF receptor, type 1 (rCRFR1), or mouse CRF receptor, type 2β (mCRFR2β). Furthermore, the potency of CRF antagonists to inhibit oCRF- or Svg-stimulated cAMP production of transfected HEK 293 cells expressing either rCRFR1 (HEK-rCRFR1 cells) or mCRFR2β (HEK-mCRFR2β cells) was determined. In comparison with astressin, which exhibited a similar affinity to rCRFR1 (Kd = 5.7 ± 1.6 nM) and mCRFR2β (Kd = 4.0 ± 2.3 nM), [dPhe11,His12]Svg(11–40), [dLeu11]Svg(11–40), [dPhe11]Svg(11–40), and Svg(11–40) bound, respectively, with a 110-, 80-, 68-, and 54-fold higher affinity to mCRFR2β than to rCRFR1. The truncated analogs of rUcn displayed modest preference (2- to 7-fold) for binding to mCRFR2β. In agreement with the results of these binding experiments, [dPhe11,His12]Svg(11–40), named antisauvagine-30, was the most potent and selective ligand to suppress agonist-induced adenylate cyclase activity in HEK cells expressing mCRFR2β.