Search

War, natural disasters, and other emergencies regularly disrupt children's education in developing countries. The digital divide has long since affected low-resource and rural schools' responses to crises that necessitate distance learning, often excluding children in remote and rural parts of countries from internet-dependent online learning programmes. In no place is this truer than in Haiti where, prior to August 2020, political unrest combined with the COVID-19 pandemic caused learners to miss 60% of their scheduled days in the 2019-2020 school year with only 45% of Haitian households having access to a power source, let alone internet or a smart device, that would enable them to participate in online learning. This study presents findings from exploratory research on the readiness of the Haitian education system to withstand crises and the impact of COVID-19 on the system and its learners. Through analyses of secondary data and semi-structured interviews with a variety of education stakeholders, the research reveals gaps in the system's readiness; identifies key challenges prompted by school closures in Haiti and shares a handful of innovative responses developed to respond to these challenges. Findings indicate that the COVID-19 health crisis has not created the need for educational reform in Haiti, but rather, by exacerbating pre-existing gaps and frailties within the system, the pandemic has heightened the urgency with which educational reform must be pursued. Salient gaps include a significant digital divide, financial instability and inattention to learning adjacent needs such as nutrition and psychosocial health for parents and children alike. While this initial research has exposed a series of significant gaps and inequalities in the Haitian education system, moving forward, more comprehensive research is needed to determine how such inequalities can be most effectively addressed. Although the Haitian government has a key role to play in addressing these inequalities, findings from this study reveal that governmental responses to COVID-19 school closures and broader digital learning inequalities, were ineffective in their reach and did not reflect the majority of Haitian learners and their families' realities. Findings also identify numerous innovations and assets on the part of non-governmental actors striving to address these gaps. However, these mechanisms were limited in scope and lacked the coordination among one another and the government that would be required to have scalable or measurable impact. Therefore, more research is needed to determine what the most successful mechanisms for addressing inequalities in the Haitian education system are and how they can be most effectively leveraged and scaled to create a more resilient education system moving forward.

War, natural disasters, and other emergencies regularly disrupt children's education in developing countries. The digital divide has long since affected low-resource and rural schools' responses to crises that necessitate distance learning, often excluding children in remote and rural parts of countries from internet-dependent online learning programmes. In no place is this truer than in Haiti where, prior to August 2020, political unrest combined with the COVID-19 pandemic caused learners to miss 60% of their scheduled days in the 2019--2020 school year with only 45% of Haitian households having access to a power source, let alone internet or a smart device, that would enable them to participate in online learning. This study presents findings from exploratory research on the readiness of the Haitian education system to withstand crises and the impact of COVID-19 on the system and its learners. Through analyses of secondary data and semi-structured interviews with a variety of education stakeholders, the research reveals gaps in the system's readiness; identifies key challenges prompted by school closures in Haiti and shares a handful of innovative responses developed to respond to these challenges. Findings indicate that the COVID-19 health crisis has not created the need for educational reform in Haiti, but rather, by exacerbating pre-existing gaps and frailties within the system, the pandemic has heightened the urgency with which educational reform must be pursued. Salient gaps include a significant digital divide, financial instability and inattention to learning adjacent needs such as nutrition and psychosocial health for parents and children alike. While this initial research has exposed a series of significant gaps and inequalities in the Haitian education system, moving forward, more comprehensive research is needed to determine how such inequalities can be most effectively addressed. Although the Haitian government has a key role to play in addressing these inequalities, findings from this study reveal that governmental responses to COVID-19 school closures and broader digital learning inequalities, were ineffective in their reach and did not reflect the majority of Haitian learners and their families' realities. Findings also identify numerous innovations and assets on the part of non-governmental actors striving to address these gaps. However, these mechanisms were limited in scope and lacked the coordination among one another and the government that would be required to have scalable or measurable impact. Therefore, more research is needed to determine what the most successful mechanisms for addressing inequalities in the Haitian education system are and how they can be most effectively leveraged and scaled to create a more resilient education system moving forward. [ABSTRACT FROM AUTHOR]

High-pressure turbine blades are subject to large thermomechanical loads that may threaten their mechanical integrity. The prediction of the heat transfer on the blade surface, crucial to ensure its durability, thus requires an accurate description of the flow physics around the blade to be reliable. In an effort to better qualify the use of computational fluid dynamics in this design context as well as the need for an improved understanding of the flow physics, this paper investigates a transonic highly loaded linear turbine blade cascade that has been found difficult to predict in the literature using large-eddy simulations. Indeed, the configuration results in shocks and acoustic waves on the suction side of the blade, features that are commonly encountered in high-pressure turbines. Turbulent spots are observed on the suction-side boundary layer with an inlet turbulence intensity of 6%. The turbulent spots are shown to have a complex and highly unsteady effect on the shock/boundary-layer interaction, disrupting flow detachment and creating laminar spots downstream of the shock. To address these transient flow phenomena, conditional averages based on the intermittency level are introduced to show that accurate heat transfer predictions require an accurate prediction of the rate of turbulent-spot production. The analysis then focuses on the effect of intermittency on the turbulent kinetic energy exchanges in the near-wall region as the turbulent kinetic energy balance must be addressed in Reynolds-averaged Navier–Stokes models. [ABSTRACT FROM AUTHOR]

This paper studies the large-eddy simulation of anisothermal low Mach number turbulent channel flows. We consider the large-eddy simulations of the low Mach number equations in two formulations, the velocity formulation and the Favre formulation. In both formulations, we investigate the subgrid-scale modeling of the two most significant subgrid terms of the filtered low Mach number equations: the momentum convection subgrid term and the density-velocity correlation subgrid term. To this end, the predictions of large-eddy simulations implementing the models are compared to filtered direct numerical simulations. We address several types of subgrid-scale models: functional eddy-viscosity or eddy-diffusivity models, structural models, tensorial models, and dynamic versions of these models. For the momentum convection subgrid term, we recommend the use of the scale-similarity model and the constant-parameter or dynamic tensorial anisotropic minimum-dissipation (AMD) model. For the density-velocity correlation subgrid term, several models are able to improve temperature-related statistics, for instance, the AMD model and the scale-similarity model. More accurate results are obtained with the Favre formulation than with the velocity formulation. [ABSTRACT FROM AUTHOR]

This paper studies the large-eddy simulation (LES) of isothermal turbulent channel flows. We investigate zero-equation algebraic models without wall function or wall model: functional models, structural models, and mixed models. In addition to models from the literature, new models are proposed and their relevance is examined. Dynamic versions of each type of model are also analyzed. The performance of the subgrid-scale models is assessed using the same finite difference numerical method and physical configuration. The friction Reynolds number of the simulations is 180. Three different mesh resolutions are used. The predictions of large-eddy simulations are compared to those of a direct numerical simulation filtered at the resolution of the LES meshes. The results are more accurate than those of a simulation without model. The predictions of functional eddy-viscosity models can be improved using constant-parameter or dynamic tensorial methods. [ABSTRACT FROM AUTHOR]

Spatial and spectral energy exchanges associated with the turbulence kinetic energy per unit mass, or the half-trace of the velocity covariance tensor, are studied in an anisothermal low Mach number turbulent channel flow. The temperatures of the two channel walls are 293 K and 586 K. This generates a strong temperature gradient in the wall-normal direction. The effect of the temperature gradient on the energy exchanges is investigated using two direct numerical simulations of the channel, at the mean friction Reynolds numbers 180 and 395. The temperature gradient creates an asymmetry between the energy exchanges at the hot and cold sides due to the variations of the local fluid properties and low Reynolds number effects. The low Reynolds number effects are smaller at higher Reynolds numbers, reducing the asymmetry between the hot and cold sides. We also decomposed the energy exchanges in order to study separately the mean-property terms, as found in the constant-property isothermal case, and the thermal terms, specific to flows with variable fluid properties. The significant thermal terms have a similar effect on the flow. Besides, low Reynolds number effects have a negligible impact on thermal terms and only affect mean-property terms. [ABSTRACT FROM AUTHOR]

ABSTRACT The present study aims at investigating the influence of Ar sputtering gas pressure on the properties of molybdenum back contact (deposited on soda-lime glass) and consequences on co-evaporated Cu(In,Ga)Se2 (CIGSe) absorber layer and related solar cell. Films 300 nm thick have been grown with argon pressure between 0·75 and 11·25 mTorr; these films have been characterized by several techniques showing that the increase of the sputtering pressure yields wider amorphous areas, containing oxygen and sodium, between the molybdenum grains, thus higher sheet resistance. The volume ratio of these amorphous areas is referenced to as 'porosity'. The structural and morphological properties of co-evaporated CIGSe have not been reliably observed influenced by the molybdenum porosity; the only noticeable change is the sodium content of the absorber, which increases with the porosity of the back contact. The impact of the amount of sodium on the device performance has been observed to be very important. On the one hand, as already reported, sodium is beneficial for the open-circuit voltage. On the other hand, a too high amount of sodium is detrimental for the fill factor (hindered shunt resistance), thus the cell efficiency; this latter observation is interpreted as a change in the grain boundary electrical properties. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Kriging was first introduced in the field of geostatistics. Nowadays, it is widely used to model computer experiments. Since the results of deterministic computer experiments have no experimental variability, Kriging is appropriate in that it interpolates observations at data points. Moreover, Kriging quantifies prediction uncertainty, which plays a major role in many applications. Among practitioners we can distinguish those who use Universal Kriging where the parameters of the model are estimated and those who use Bayesian Kriging where model parameters are random variables. The aim of this article is to show that the prediction uncertainty has a correct interpretation only in the case of Bayesian Kriging. Different cases of prior distributions have been studied and it is shown that in one specific case, Bayesian Kriging supplies an interpretation as a conditional variance for the prediction variance provided by Universal Kriging. Finally, a simple petroleum engineering case study presents the importance of prior information in the Bayesian approach. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper is concerned with an asymptotic approach for a micropolar flow through a thin curvilinear channel. A priori estimates (which we obtain together with the existence and the uniqueness of the solution) are used to establish the error between the exact solution and the asymptotic one and to justify the asymptotic analysis. We obtain the expression of an expansion of order K and we study the general problems for the boundary layer functions. Under some additional assumptions on the data we obtain satisfactory error estimates. [ABSTRACT FROM AUTHOR]

The asymptotic analysis of a micropolar flow through a wavy tube structure is studied. We suppose that the domain depends on a small parameter that represents the width and the order of the periodicty of the domain. The Stokes and Navier-Stokes problems in the union of tubes (with a constant section) were earlier studied. The generalization of the Method of Asymptotic Partial Decomposition of Domain in a structure with some periodic tubes is described and justified in order to propose a simplified modeling for the bloodstream. [ABSTRACT FROM AUTHOR]

The steady motion of a micropolar fluid through a wavy tube with the dimensions depending on a small parameter is studied. An asymptotic expansion is proposed and error estimates are proved by using a boundary layer method. We apply the method of partial asymptotic decomposition of domain and we prove that the solution of the partially decomposed problem represents a good approximation for the solution of the considered problem. [ABSTRACT FROM AUTHOR]

Abstract Background The C. elegans Promoterome is a powerful resource for revealing the regulatory mechanisms by which transcription is controlled pan-genomically. Transcription factors will form the core of any systems biology model of genome control and therefore the promoter activity of Promoterome inserts for C. elegans transcription factor genes was examined, in vivo, with a reporter gene approach. Results Transgenic C. elegans strains were generated for 366 transcription factor promoter/gfp reporter gene fusions. GFP distributions were determined, and then summarized with reference to developmental stage and cell type. Reliability of these data was demonstrated by comparison to previously described gene product distributions. A detailed consideration of the results for one C. elegans transcription factor gene family, the Six family, comprising ceh-32, ceh-33, ceh-34 and unc-39 illustrates the value of these analyses. The high proportion of Promoterome reporter fusions that drove GFP expression, compared to previous studies, led to the hypothesis that transcription factor genes might be involved in local gene duplication events less frequently than other genes. Comparison of transcription factor genes of C. elegans and Caenorhabditis briggsae was therefore carried out and revealed very few examples of functional gene duplication since the divergence of these species for most, but not all, transcription factor gene families. Conclusion Examining reporter expression patterns for hundreds of promoters informs, and thereby improves, interpretation of this data type. Genes encoding transcription factors involved in intrinsic developmental control processes appear acutely sensitive to changes in gene dosage through local gene duplication, on an evolutionary time scale.

Abstract Background Differential gene expression specifies the highly diverse cell types that constitute the nervous system. With its sequenced genome and simple, well-defined neuroanatomy, the nematode C. elegans is a useful model system in which to correlate gene expression with neuron identity. The UNC-4 transcription factor is expressed in thirteen embryonic motor neurons where it specifies axonal morphology and synaptic function. These cells can be marked with an unc-4::GFP reporter transgene. Here we describe a powerful strategy, Micro-Array Profiling of C. elegans cells (MAPCeL), and confirm that this approach provides a comprehensive gene expression profile of unc-4::GFP motor neurons in vivo. Results Fluorescence Activated Cell Sorting (FACS) was used to isolate unc-4::GFP neurons from primary cultures of C. elegans embryonic cells. Microarray experiments detected 6,217 unique transcripts of which ~1,000 are enriched in unc-4::GFP neurons relative to the average nematode embryonic cell. The reliability of these data was validated by the detection of known cell-specific transcripts and by expression in UNC-4 motor neurons of GFP reporters derived from the enriched data set. In addition to genes involved in neurotransmitter packaging and release, the microarray data include transcripts for receptors to a remarkably wide variety of signaling molecules. The added presence of a robust array of G-protein pathway components is indicative of complex and highly integrated mechanisms for modulating motor neuron activity. Over half of the enriched genes (537) have human homologs, a finding that could reflect substantial overlap with the gene expression repertoire of mammalian motor neurons. Conclusion We have described a microarray-based method, MAPCeL, for profiling gene expression in specific C. elegans motor neurons and provide evidence that this approach can reveal candidate genes for key roles in the differentiation and function of these cells. These methods can now be applied to generate a gene expression map of the C. elegans nervous system.