The impact of the Florida state -mandated Basic Skills Exit Tests at Miami -Dade Community College

The purpose of this study was to explore the impact of the Florida State-mandated Basic Skills Exit Tests (BSET) on the effectiveness of remedial instruction programs to adequately serve the academically underprepared student population. The primary research question concerned whether the introduction of the BSET has resulted in remedial completers who are better prepared for college-level coursework. ^ This study consisted of an ex post facto research design to examine the impact of the BSET on student readiness for subsequent college-level coursework at Miami-Dade Community College. Two way analysis of variance was used to compare the performance of remedial and college-ready students before and after the introduction of the BSET requirement. Chi-square analysis was used to explore changes in the proportion of students completing and passing remedial courses. Finally, correlation analysis was used to explore the utility of the BSET in predicting subsequent college-level course performance. Differences based on subject area and race/ethnicity were explored. ^ The introduction of the BSET did not improve the performance of remedial completers in subsequent college-level courses in any of the subject areas. The BSET did have a negative impact on the success rate of students in remedial reading and mathematics courses. There was a significant decrease in minority students' likelihood of passing remedial reading and mathematics courses after the BSET was introduced. The reliability of the BSET is unacceptably low for all subject areas, based on estimates derived from administrations at M-DCC. Nevertheless, there was a significant positive relationship between BSET score and grade point average in subsequent college-level courses. This relationship varied by subject area and ethnicity, with the BSET reading score having no relationship with subsequent course performance for Black non-Hispanic students. ^ The BSET had no discernable positive effect on remedial student performance in subsequent college-level courses. In other words, the BSET has not enhanced the effectiveness of the remedial programs to prepare students for later coursework at M-DCC. The BSET had a negative impact on the progress and success of students in remedial reading and mathematics. ^

Assessing Methods for Assigning SNPs to Genes in Gene-Based Tests of Association Using Common Variants

Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to single-marker tests. In this analysis we conduct a variety of simulation studies applied to five popular gene-based tests investigating general trends related to their performance in realistic situations. In particular, we focus on the impact of non-causal SNPs and a variety of LD structures on the behavior of these tests. Ultimately, we find that non-causal SNPs can significantly impact the power of all gene-based tests. On average, we find that the “noise” from 6–12 non-causal SNPs will cancel out the “signal” of one causal SNP across five popular gene-based tests. Furthermore, we find complex and differing behavior of the methods in the presence of LD within and between non-causal and causal SNPs. Ultimately, better approaches for a priori prioritization of potentially causal SNPs (e.g., predicting functionality of non-synonymous SNPs), application of these methods to sequenced or fully imputed datasets, and limited use of window-based methods for assigning inter-genic SNPs to genes will improve power. However, significant power loss from non-causal SNPs may remain unless alternative statistical approaches robust to the inclusion of non-causal SNPs are developed.

A study of gas holdup properties of selected non-Newtonian simulants

The U.S. Department of Energy (DOE) needs a design basis to properly design a PJM and ventilation systems for the Waste Treatment Plant vessels. In order to meet DOE's needs for proper ventilation and PJM design technologies, Florida International University's Hemispheric Center for Environmental Technology (FIU-HCET) has studied the properties for gas holdup in selected non Newtonian fluids with physicochemical properties comparable to nuclear waste. The primary purpose of this research was to study the holdup properties of selected non - Newtonian simulants and quantify the level of gas holdup in selected simulants using continuous argon injection in five gallons vessel. Gas holdup tests involved the injection of gas bubbles in simulant waste in scaled prototypic vessels. The holdup was measured as a function of injection rate in the vessel. Tests were performed with both Laponite, Clay 12%, Clay 27% and Qard 13.5. This work showed that the percentage of holdup was about 3% for all simulants despite the significant differences in rheology.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Molecular docking and geographical information systems as tools to assess the potential impact of veterinary medicines on non-target organisms and the environment

Veterinary medicines (VMs) from agricultural industry can enter the environment in a number of ways. This includes direct exposure through aquaculture, accidental spillage and disposal, and indirect entry by leaching from manure or runoff after treatment. Many compounds used in animal treatments have ecotoxic properties that may have chronic or sometimes lethal effects when they come into contact with non-target organisms. VMs enter the environment in mixtures, potentially having additive effects. Traditional ecotoxicology tests are used to determine the lethal and sometimes reproductive effects on freshwater and terrestrial organisms. However, organisms used in ecotoxicology tests can be unrepresentative of the populations that are likely to be exposed to the compound in the environment. Most often the tests are on single compound toxicity but mixture effects may be significant and should be included in ecotoxicology testing. This work investigates the use, measured environmental concentrations (MECs) and potential impact of sea lice treatments on salmon farms in Scotland. Alternative methods for ecotoxicology testing including mixture toxicity, and the use of in silico techniques to predict the chronic impact of VMs on different species of aquatic organisms were also investigated. The Scottish Environmental Protection Agency (SEPA) provided information on the use of five sea lice treatments from 2008-2011 on Scottish salmon farms. This information was combined with the recently available data on sediment MECs for the years 2009-2012 provided by SEPA using ArcGIS 10.1. In depth analysis of this data showed that from a total of 55 sites, 30 sites had a MEC higher than the maximum allowable concentration (MAC) as set out by SEPA for emamectin benzoate and 7 sites had a higher MEC than MAC for teflubenzuron. A number of sites that were up to 16 km away from the nearest salmon farm reported as using either emamectin benzoate or teflubenzuron measured positive for the two treatments. There was no relationship between current direction and the distribution of the sea lice treatments, nor was there any evidence for alternative sources of the compounds e.g. land treatments. The sites that had MECs higher than the MAC could pose a risk to non-target organisms and disrupt the species dynamics of the area. There was evidence that some marine protected sites might be at risk of exposure to these compounds. To complement this work, effects on acute mixture toxicity of the 5 sea lice treatments, plus one major metabolite 3-phenoxybenzoic acid (3PBA), were measured using an assay using the bioluminescent bacteria Aliivibrio fischeri. When exposed to the 5 sea lice treatments and 3PBA A. fischeri showed a response to 3PBA, emamectin benzoate and azamethiphos as well as combinations of the three. In order to establish any additive effect of the sea lice treatments, the efficacy of two mixture prediction equations, concentration addition (CA) and independent action ii(IA) were tested using the results from single compound dose response curves. In this instance IA was the more effective prediction method with a linear regression confidence interval of 82.6% compared with 22.6% of CA. In silico molecular docking was carried out to predict the chronic effects of 15 VMs (including the five used as sea lice control). Molecular docking has been proposed as an alternative screening method for the chronic effects of large animal treatments on non-target organisms. Oestrogen receptor alpha (ERα) of 7 non-target bony fish and the African clawed frog Xenopus laevis were modelled using SwissModel. These models were then ‘docked’ to oestradiol, the synthetic oestrogen ethinylestradiol, two known xenoestrogens dichlorodiphenyltrichloroethane (DDT) and bisphenol A (BPA), the antioestrogen breast cancer treatment tamoxifen and 15 VMs using Auto Dock 4. Based on the results of this work, four VMs were identified as being possible xenoestrogens or anti-oestrogens; these were cypermethrin, deltamethrin, fenbendazole and teflubenzuron. Further investigation, using in vitro assays, into these four VMs has been suggested as future work. A modified recombinant yeast oestrogen screen (YES) was attempted using the cDNA of the ERα of the zebrafish Danio rerio and the rainbow trout Oncorhynchus mykiss. Due to time and difficulties in cloning protocols this work was unable to be completed. Use of such in vitro assays would allow for further investigation of the highlighted VMs into their oestrogenic potential. In conclusion, VMs used as sea lice treatments, such as teflubenzuron and emamectin benzoate may be more persistent and have a wider range in the environment than previously thought. Mixtures of sea lice treatments have been found to persist together in the environment, and effects of these mixtures on the bacteria A. fischeri can be predicted using the IA equation. Finally, molecular docking may be a suitable tool to predict chronic endocrine disrupting effects and identify varying degrees of impact on the ERα of nine species of aquatic organisms.

Receptive Vocabulary of CLIL and Non-CLIL Primary and Secondary School Learners

CLIL instruction has been reported to be beneficial for foreign language vocabulary learning since CLIL students show higher vocabulary profiles than students of their same age in traditional EFL contexts. However, to our knowledge, the receptive vocabulary knowledge of CLIL and non-CLIL learners at the end of primary and secondary education has not been examined yet. Hence, this study aims at comparing the receptive vocabulary size 79 CLIL primary learners with the receptive vocabulary knowledge of 331 non-CLIL learners at the end of primary and secondary school. Sex-based differences were also analysed. The 2k Vocabulary Levels Test (VLT) was used for the purposes of the study. Results revealed that learners’ receptive vocabulary sizes lie within the most frequent 1000 words, non-CLIL secondary school students throw better results than primary students but the differences between the secondary group and the CLIL group are not statistically significant. As for sex-based differences, we found no significant differences among the groups. These findings led us to believe that the CLIL approach offers a benefit for vocabulary acquisition since CLIL learners have been exposed to the foreign language for a shorter period of time and the results are quite similar to their non-CLIL secondary school partners.

A new generation of companion diagnostics: cobas BRAF, KRAS and EGFR mutation detection tests

The cobas® (Roche) portfolio of companion diagnostics in oncology currently has three assays CE-marked for in vitro diagnostics. Two of these (EGFR and BRAF) are also US FDA-approved. These assays detect clinically relevant mutations that are correlated with response (BRAF, EGFR) or lack of response (KRAS) to targeted therapies such as selective mutant BRAF inhibitors in malignant melanoma, tyrosine kinases inhibitor in non-small cell lung cancer and anti-EGFR monoclonal antibodies in colorectal cancer, respectively. All these assays are run on a single platform using DNA extracted from a single 5 µm section of a formalin-fixed paraffin-embedded tissue block. The assays provide an ‘end-to-end’ solution from extraction of DNA to automated analysis and report on the cobas z 480. The cobas tests have shown robust and reproducible performance, with high sensitivity and specificity and low limit of detection, making them suitable as companion diagnostics for clinical use.

Design and implementation of a non-destructive defect detection technique based on UWB-SAR imaging

In the last twenty years aerospace and automotive industries started working widely with composite materials, which are not easy to test using classic Non-Destructive Inspection (NDI) techniques. Pairwise, the development of safety regulations sets higher and higher standards for the qualification and certification of those materials. In this thesis a new concept of a Non-Destructive defect detection technique is proposed, based on Ultrawide-Band (UWB) Synthetic Aperture Radar (SAR) imaging. Similar SAR methods are yet applied either in minefield [22] and head stroke [14] detection. Moreover feasibility studies have already demonstrated the validity of defect detection by means of UWB radars [12, 13]. The system was designed using a cheap commercial off-the-shelf radar device by Novelda and several tests of the developed system have been performed both on metallic specimen (aluminum plate) and on composite coupon (carbon fiber). The obtained results confirm the feasibility of the method and highlight the good performance of the developed system considered the radar resolution. In particular, the system is capable of discerning healthy coupons from damaged ones, and correctly reconstruct the reflectivity image of the tested defects, namely a 8 x 8 mm square bulge and a 5 mm drilled holes on metal specimen and a 5 mm drilled hole on composite coupon.

Conception mécaniste-empirique des chaussées non revêtues

Dans le contexte où les routes non revêtues sont susceptibles de subir des charges importantes, une méthode rigoureuse pour la conception de ces chaussées basée sur des principes mécanistes-empiriques et sur le comportement mécanique des sols support est souhaitable. La conception mécaniste combinée à des lois d’endommagement permet l’optimisation des structures de chaussées non revêtues ainsi que la réduction des coûts de construction et d’entretien. Le but de ce projet est donc la mise au point d’une méthode de conception mécaniste-empirique adaptée aux chaussées non revêtues. Il a été question tout d’abord de mettre au point un code de calcul pour la détermination des contraintes et des déformations dans la chaussée. Ensuite, des lois d’endommagement empiriques pour les chaussées non revêtues ont été développées. Enfin, les méthodes de calcul ont permis la création d’abaques de conception. Le développement du code de calcul a consisté en une modélisation de la chaussée par un système élastique multi-couches. La modélisation a été faite en utilisant la transformation d’Odemark et les équations de Boussinesq pour le calcul des déformations sous la charge. L’élaboration des fonctions de transfert empiriques adaptées aux chaussées non revêtues a également été effectuée. Le développement des fonctions de transfert s’est fait en deux étapes. Tout d’abord, l’établissement de valeurs seuil d’orniérage considérant des niveaux jugés raisonnables de conditions fonctionnelle et structurale de la chaussée. Ensuite, le développement de critères de déformation admissible en associant les déformations théoriques calculées à l’aide du code de calcul à l’endommagement observé sur plusieurs routes en service. Les essais ont eu lieu sur des chaussées typiques reconstituées en laboratoire et soumises à un chargement répété par simulateur de charge. Les chaussées ont été instrumentées pour mesurer la déformation au sommet du sol d’infrastructure et les taux d’endommagements ont été mesurés au cours des essais.

Une analyse de corrélation entre des modèles éducationnels et des activités d'apprentissage tels que perçus par les étudiants de l'Université de Sherbrooke

[…] Le but de la présente étude consiste à rechercher des manifestations empiriques qui rendent compte d'une relation entre des modèles éducationnels différents et des séries d'activités d'apprentissage. Pour réaliser cet objectif, il importe dans une première étape, d'expliciter les différents modèles éducationnels retenus et qui peuvent être des facteurs d'orientations ou d'influences des activités d'apprentissage au niveau universitaire. Ensuite, on précisera comment s'effectue la sélection des activités d'apprentissage qui sont supposées être engendrées par ces modèles éducationnels. Une troisième étape servira à expliciter la méthode utilisée pour recueillir de l’information sur les modèles éducationnels et les activités d'apprentissage. La fin de ce chapitre annoncera les hypothèses de la recherche. [...]

Non-acute Transient Reversible Adrenal Insufficiency in a Survivor of Critical Illness: A Lesser-known Cause of Primary Adrenal Insufficiency

Objectives: Primary adrenal insufficiency AI is regarded as a progressive disease needing lifelong replacement therapy, but this may not always be the case. Material and methods: A non-acute presentation of AI following a hypotensive episode caused by blood loss was investigated. Results: Adrenal function fully recovered without treatment. Conclusions: There should be a high index of suspicion and a low threshold for performing tests of adrenal function in survivors of critical illness and severe hypotensive episodes.

In situ characterization of sediment oxygen demand across the spectrum of non-resuspension to full resuspension with varying bed shear stress

Sediment oxygen demand (SOD) can be a significant oxygen sink in various types of water bodies, particularly slow-moving waters with substantial organic sediment accumulation. In most settings where SOD is a concern, the prevailing hydraulic conditions are such that the impact of sediment resuspension on SOD is not considered. However, in the case of Bubbly Creek in Chicago, Illinois, the prevailing slack water conditions are interrupted by infrequent intervals of very high flow rates associated with pumped combined sewer overflow (CSO) during intense hydrologic events. These events can cause resuspension of the highly organic, nutrient-rich bottom sediments, resulting in precipitous drawdown of dissolved oxygen (DO) in the water column. While many past studies have addressed the dependence of SOD on near-bed velocity and bed shear stress prior to the point of sediment resuspension, there has been limited research that has attempted to characterize the complex and dynamic phenomenon of resuspended-sediment oxygen demand. To address this issue, a new in situ experimental apparatus referred to as the U of I Hydrodynamic SOD Sampler was designed to achieve a broad range of velocities and associated bed shear stresses. This allowed SOD to be analyzed across the spectrum of no sediment resuspension associated with low velocity/ bed shear stress through full sediment resuspension associated with high velocity / bed shear stress. The current study split SOD into two separate components: (1) SODNR is the sediment oxygen demand associated with non-resuspension conditions and is a surface sink calculated using traditional methods to yield a value with units (g/m2/day); and (2) SODR is the oxygen demand associated with resuspension conditions, which is a volumetric sink most accurately characterized using non-traditional methods and units that reflect suspension in the water column (mg/L/day). In the case of resuspension, the suspended sediment concentration was analyzed as a function of bed shear stress, and a formulation was developed to characterize SODR as a function of suspended sediment concentration in a form similar to first-order biochemical oxygen demand (BOD) kinetics with Monod DO term. The results obtained are intended to be implemented into a numerical model containing hydrodynamic, sediment transport, and water quality components to yield oxygen demand varying in both space and time for specific flow events. Such implementation will allow evaluation of proposed Bubbly Creek water quality improvement alternatives which take into account the impact of SOD under various flow conditions. Although the findings were based on experiments specific to the conditions in Bubbly Creek, the techniques and formulations developed in this study should be applicable to similar sites.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

The big four skills: Teachers’ assumptions on measurement of non-native students cognition

The four-skills on tests for young native speakers commonly do not generate correlation incongruency concerning the cognitive strategies frequently reported. Considering the non-native speakers there are parse evidence to determine which tasks are important to assess properly the cognitive and academic language proficiency (Cummins, 1980; 2012). Research questions: It is of high probability that young students with origin in immigration significantly differ on their communication strategies and skills in a second language processing context (1); attached to this first assumption, it is supposed that teachers significantly differ depending on their scientific area and previous training (2). Purpose: This study intends to examine whether school teachers (K-12) as having different origin in scientific domain of teaching and training perceive differently an adapted four-skills scale, in European Portuguese. Research methods: 77 teachers of five areas scientific areas, mean of teaching year service = 32 (SD= 2,7), 57 males and 46 females (from basic and high school levels). Main findings: ANOVA (Effect size and Post-hoc Tukey tests) and linear regression analysis (stepwise method) revealed statistically significant differences among teachers of different areas, mainly between language teachers and science teachers. Language teachers perceive more accurately tasks in a multiple manner to the broad skills that require to be measured in non-native students. Conclusion: If teachers perceive differently the importance of the big-four tasks, there would be incongruence on skills measurement that teachers select for immigrant puppils. Non-balanced tasks and the teachers’ perceptions on evaluation and toward competence of students would likely determine limitations for academic and cognitive development of non-native students. Furthermore, results showed sufficient evidence to conclude that tasks are perceived differently by teachers toward importance of specific skills subareas. Reading skills are best considered compared to oral comphreension skills in non-native students.

An extension of STARD statements for reporting diagnostic accuracy studies on liver fibrosis tests: the Liver-FibroSTARD standards

International audience