Evaluation of a locally homogeneous flow model of spray combustion

A model of spray combustion which employs a second-order turbulence model was developed. The assumption of locally homogeneous flow is made, implying infinitely fast transport rates between the phase. Measurements to test the model were completed for a gaseous n-propane flame and an air atomized n-pentane spray flame, burning in stagnant air at atmospheric pressure. Profiles of mean velocity and temperature, as well as velocity fluctuations and Reynolds stress, were measured in the flames. The predictions for the gas flame were in excellent agreement with the measurements. The predictions for the spray were qualitatively correct, but effects of finite rate interphase transport were evident, resulting in a overstimation of the rate development of the flow. Predictions of spray penetration length at high pressures, including supercritical combustion conditions, were also completed for comparison with earlier measurements. Test conditions involved a pressure atomized n-pentane spray, burning in stagnant air at pressures of 3, 5, and 9 MPa. The comparison between predictions and measurements was fair. This is not a very sensitive test of the model, however, and further high pressure experimental and theoretical results are needed before a satisfactory assessment of the locally homogeneous flow approximation can be made

Using randomized experiments and structural models for 'scaling up': evidence from the PROGRESA evaluation

The evaluation of welfare programs and more generally government or international organisms interventions is often posed as a one off question, in that evaluators ask whether a specific intervention achieves a specific objective in a specific situation. However,recently, the more general question of whether results from a given studies can be used to predict the effect of different interventions in,possibly,different contexts has received a considerable amount of attention. The usefulness of such an exercise, if successful, is obvious. The ability to extrapolate success stories and avoid failures in different situations would obviously be highly desirable. Unfortunately, a rigorous and successful extrapolation is extremely difficult. Perhaps such difficulties should not be unexpected,given the problems that often one encounters in establishing the effects of social programs in non experimental settings. In this paper we discuss at length the issues involved with the evaluation of social interventions and with the attempts at 'scaling them up'. In particular, we discuss the relative merits of non- parametric evaluation strategies that rely on (possibly experimental) exogenous variation to estimate the impact effects and of more structural approaches. The difference between the two approaches is particularly relevant when one comes to the issue of 'extrapolation' and 'scaling up'. In principle one could consider two types of extrapolation and scaling up. First, one might want to predict the effects of a program that is different from the one that was evaluated or the effect of changing some aspects of the program evaluated. Second, one might want to predict the effect of exporting an existing program from a population where its effects were evaluated (evaluation population) to a different population (implementation population). In what follow we focus on the latter problem and discuss the former only marginally. After considering extensively the conceptual and technical issues involved with this type of exercises, we apply the ideas we discuss to the results from the evaluation of PROGRESA , a large welfare program in Mexico, for which a randomized evaluation sample is available and has been extensively studied. In particular, we divide the seven Mexican states in which the evaluation was carried out in two groups and check to what extent the results in one group can be extrapolated to the other. The advantage of such a strategy is that one can compare the extrapolation results (based on a structural model) with the actual 'ex-post' evaluation that can be carried out either by simple comparison of means or by structural methods

Using randomised experiments and structural models for 'scaling up': evidence from the PROGRESA evaluation

The evaluation of welfare programs and more generally government or international organisma interventions is often posed as a one off question, in that evaluators ask whether a specific intervention achieves a specific objective in a specific situation. However, recently, the more general questions of whether results from a given study can be used to predict the the effect of different interventions in, possibly, different contexts has received a considerable amount of attention. The usefulness of such an exercise, if successful, is obvious. The ability to extrapolate success stories and avoid failures in different situation would obviously be highly desirable. Unfortunately a rigorous and successful extrapolation is extremely difficult. In this paper we discuss the issues involved with the evaluation of social interventions and with the attempts at 'scaling them up'. In particular we discuss the realtive merits of non-parametric evaluation strategies that rely on (possibly experimental) exogenous variation to estimate the impact effects and of more structural approaches. The difference between the two appraoches is particularly relevant when one comes to the issue of 'extrapolation' and 'scaling up'. One could consider two types of extrapolation: (i) Predict the effects of a program that is different from the one that was evaluated; (ii) predict the effect of exporting an existing program from a context where is was evaluated to a different one. In this paper we focus on the latter problem. After discussing the conceptual and technical issues, we apply the ideas we discuss to the results from the evluation of PROGRESA, a large welfare program in Mexico, for which a randomized evaluation sample is available and has been extensively studied. In particular, we divide the seven Mexican states in which the evaluation was carried out into two groups and check to what extent the results in one group can be extrapolated to the others

A Test of Independence in Two-Way Contingency Tables Based on Maximal Correlation

Cataloged from PDF version of article.Maximal correlation has several desirable properties as a measure of dependence, including the fact that it vanishes if and only if the variables are independent. Except for a few special cases, it is hard to evaluate maximal correlation explicitly. We focus on two-dimensional contingency tables and discuss a procedure for estimating maximal correlation, which we use for constructing a test of independence. We compare the maximal correlation test with other tests of independence by Monte Carlo simulations. When the underlying continuous variables are dependent but uncorrelated, we point out some cases for which the new test is more powerful

Parental cooperation in an extreme hot environment: natural behaviour and experimental evidence

One of the most apparent examples of cooperation between unrelated individuals is biparental care whereby the male and the female parent share the rearing of the offspring. Theoretical models of care predict that selection should favour biparental care if it substantially improves the survival of the offspring. Although various ecological factors have been proposed to necessitate biparental care, experimental evidence is scant given the challenges of manipulating ecological factors in the natural habitat of animals. We carried out one such experiment in a small shorebird, the Kentish plover, Charadrius alexandrinus, that breeds in an extreme desert environment. Nest cover and thus exposure to solar radiation vary between nests, and we show that parents at exposed nests spent more time incubating than those at nests shaded by a bush (covered nests). Experimental removal and supplementation of nest cover gave results consistent with the observational data; at experimentally exposed nests both males and females increased incubation effort and relieved each other more frequently whereas at experimentally covered nests we observed the opposite. We conclude that exposure to extreme solar radiation influences biparental care and this necessitates parental cooperation in the Kentish plover. Furthermore, since parental care often coevolves with mating strategies, we conjecture that where the environment puts less pressure on the parents and provides the opportunity for reduced care, both mating systems and parental care can diversify over evolutionary time. (C) 2011 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved

ArCo: the Italian Cultural Heritage Knowledge Graph

ArCo is the Italian Cultural Heritage knowledge graph, consisting of a network of seven vocabularies and 169 million triples about 820 thousand cultural entities. It is distributed jointly with a SPARQL endpoint, a software for converting catalogue records to RDF, and a rich suite of documentation material (testing, evaluation, how-to, examples, etc.). ArCo is based on the official General Catalogue of the Italian Ministry of Cultural Heritage and Activities (MiBAC) - and its associated encoding regulations - which collects and validates the catalogue records of (ideally) all Italian Cultural Heritage properties (excluding libraries and archives), contributed by CH administrators from all over Italy. We present its structure, design methods and tools, its growing community, and delineate its importance, quality, and impact