This study evaluated the predictive and concurrent validity of the Tiered Fidelity Inventory (TFI). Structural equation modeling was applied to test the associations between the TFI and student outcomes. First, a total of 1,691 schools with TFI Tier 1 in 2016-17 and school-wide discipline outcomes in 2015-16 and 2016-17 were targeted, finding a negative association between TFI Tier 1 and differences between African American and non-African American students in major office discipline referrals (ODR) per 100 students per day in elementary schools. A sensitivity test with schools with TFI Tier 1, 2, and 3 was conducted, showing a negative association between TFI Tier 1 and the square root of major ODR rates in elementary schools. Second, TFI Tier 1 was positively related to the proportions of students meeting or exceeding state-wide standards in reading from 1,361 schools with TFI Tier 1 and academic outcomes in 2014-15 and 2015-16. Also, the association between TFI Tier 1 and academic outcomes was found to be stronger when schools implemented SWPBIS for 6 or more years. A sensitivity test with schools with TFI Tier 1, 2, and 3 indicated positive associations between TFI Tier 1 and the proportions of students meeting or exceeding state-wide standards in both subjects. Third, TFI Tier2 was positively associated with the logit of proportions of students with CICO daily points from 570 schools with TFI Tier 2 in 2016-17 and CICO outcomes in 2015-16 and 2016-17. Fourth, correlations between the Evaluation subscale of TFI Tier 1 or 2 and relevant measures in 2016-17 were tested from 2,379 schools. TFI Tier 1 Evaluation was positively correlated with counts of TFI administrations, number of fidelity measures, and counts of viewing SWIS Reports. These correlations were significant except for ODRs by staff. Also, TFI Tier 2 Evaluation was significantly positively correlated with years of SWPBIS implementation, years of CICO-SWIS implementation, and counts of viewing CICO Reports except student period, and negatively with counts of viewing student single period. These findings were discussed by comparing them with previous research findings, suggesting implications for future research and practice, and addressing research limitations.

Nuclear receptors (NRs) are important transcription factors involved in the regulation of a variety of physiological processes such as embryonic development, cell differentiation and homeostasis (for review, see Mangelsdorf et al., 1995 TenBaum and Baniahrned, 1997). In contrast to membrane bound receptors, they bind small lipophilic ligands and function in the nucleus as ligand-modulated transcription factors. The ligands for nuclear receptors include steroids (glucocorticoids, progestins, mineralocorticoids, androgens and estrogens), vitamin D3, retinoids, thyroid hormone, prostaglandins, farnesoids etc. Several other nuclear receptors are classified as orphan receptors for which no ligand has yet been identified. More than 300 nuclear receptors have now been identified and together these proteins comprise the single largest family of metazoan transcription factors, the nuclear receptor superfamily. Recently, a unified nomenclature has been evolved (nuclear receptor nomenclature committee, 1999), a summary of which is presented in Table 1.

L'analyse de défaillances joue un rôle important dans l'amélioration des performances et de la fabrication des circuits intégrés. Des défaillances peuvent intervenir à tout moment dans la chaîne d'un produit, que ce soit au niveau conception, durant la qualification du produit, lors de la production, ou encore lors de son utilisation. Il est donc important d'étudier ces défauts dans le but d'améliorer la fiabilité des produits. De plus, avec l'augmentation de la densité et de la complexité des puces, il est de plus en plus difficile de localiser les défauts, et ce malgré l'amélioration des techniques d'analyses. Ce travail de thèse s'inscrit dans ce contexte et vise à étudier et développer une nouvelle technique d'analyse de défaillance basée sur l'étude de l'onde laser réfléchie le "Laser Voltage Imaging" (LVI) pour l'analyse de défaillance des technologies ultimes (inférieur à 45nm).