880 resultados para Macronutrient requirements


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The present study was conducted to assess the interrelation between teat anatomy and machine milking in dairy buffaloes raised in Switzerland. A 3-min pre-stimulation induced milk ejection before cluster attachment in most cases and caused an optimal milk removal during machine milking. In an additional experiment, longitudinal cross-section ultrasound was obtained before and after a 3-min pre-stimulation. Teat wall thickness, teat diameter, cisternal diameter and teat canal length were evaluated. It was observed that 3-min pre-stimulation dramatically reduced teat canal length whereas all the other anatomical parameters remained unchanged. The vacuum needed to open the teat canal was also measured before and after a 3-min pre-stimulation by using a special teat cup with only the mouthpiece of the liner remaining on the top of the teat cup (no liner, no pulsation). Without pre-stimulation but after wetting the teat canal by stripping one squirt of milk out of the teat, no milk could be withdrawn with a vacuum up to 39 kPa. However, after pre-stimulation, milk flow occurred in all buffaloes at a vacuum between 16 and 38 kPa. In the last experiment, the teat tissue was examined in slaughtered buffaloes and compared with teat tissue of cows. No difference was noted in histological sections and teat canal length was similar in cows and buffaloes. Proximal to the teat canal, the teat did not pass into an open cistern but the lumen was collapsed. In conclusion, buffaloes need to be well pre-stimulated because the tissue above the teat canal provides additional teat closure before milk ejection. Therefore, milk can only be obtained after pre-stimulation.

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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.

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We appreciate the thorough discussion provided by Professor Yuan Ding. His comments raise legitimate issues. In this response, we offer clarifications and suggest avenues for future research. Our response follows the structure of the discussant’s paper and elaborates on each point separately.

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We test for differences in financial reporting quality between companies that are required to file periodically with the SEC and those that are exempted from filing reports with the SEC under Rule 12g3-2(b). We examine three earnings quality measures: conservatism, abnormal accruals, and the predictability of earnings. Our results, for all three measures, show different financial reporting quality for companies that file with the SEC than for companies exempt from filing requirements. This paper provides empirical evidence of a link between filing with the SEC and financial reporting quality for foreign firms.

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Fas (CD95/Apo-1) ligand is a potent inducer of apoptosis and one of the major killing effector mechanisms of cytotoxic T cells. Thus, Fas ligand activity has to be tightly regulated, involving various transcriptional and post-transcriptional processes. For example, preformed Fas ligand is stored in secretory lysosomes of activated T cells, and rapidly released by degranulation upon reactivation. In this study, we analyzed the minimal requirements for activation-induced degranulation of Fas ligand. T cell receptor activation can be mimicked by calcium ionophore and phorbol ester. Unexpectedly, we found that stimulation with phorbol ester alone is sufficient to trigger Fas ligand release, whereas calcium ionophore is neither sufficient nor necessary. The relevance of this process was confirmed in primary CD4(+) and CD8(+) T cells and NK cells. Although the activation of protein kinase(s) was absolutely required for Fas ligand degranulation, protein kinase C or A were not involved. Previous reports have shown that preformed Fas ligand co-localizes with other markers of cytolytic granules. We found, however, that the activation-induced degranulation of Fas ligand has distinct requirements and involves different mechanisms than those of the granule markers CD63 and CD107a/Lamp-1. We conclude that activation-induced degranulation of Fas ligand in cytotoxic lymphocytes is differently regulated than other classical cytotoxic granule proteins.