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Large enrollment, introductory science and engineering classes at research universities are frequently the subject of Discipline-Based Education Research projects and are commonly taught by non-tenure track faculty. However, tenure-track and nontenure-track faculty may encounter different institutional structures that impact their implementation of, or intention to use, evidence-based instructional practices. We used a multiple nested case study framed by the Teacher-Centered Systemic Reform model to identify structural, cultural, and personal components of reform that differed by faculty position and home academic department in the context of a discipline based education research project. Structural, cultural, and personal drivers and barriers to reform differed between position types and among departments but there were interactions between these two effects, suggesting both need to be considered in reform efforts and research projects. Overall, involvement in the discipline-based education research project served as a positive experience, addressed barriers and enhanced drivers for adopting EBIP. Our study highlights factors that promote and prevent the integration of evidence-based practices, and we suggest that involvement in discipline-based education research can encourage the adoption of student-centered pedagogy in science and engineering classes. 

The scalable and facile preparation of single-atom catalysts remains a critical challenge. Here, we introduce Diluted Atomic Layer Deposition (DALD), a unique approach for synthesizing supported metal catalysts with precisely tunable loadings. Unlike conventional metal deposition by ALD which uses pure metal precursors, DALD employs a diluted precursor mixture, combining organometallic precursors with the corresponding free ligand in controlled ratios. The method enables precise control over metal loadings, allowing the synthesis of structures ranging from nanoparticles to isolated single atoms, as exemplified by Ir, Rh, and Pt on high-surface-area γ-Al2O3. With its inherent simplicity and exceptional efficiency in metal precursor utilization, DALD represents a highly scalable strategy, unlocking opportunities for integrating single-atom catalysts into industrial processes. 

The structure of the title compound, [CdCl₂(C₁₅H₁₆N₄S)], at 100 K has monoclinic (P2₁/c) symmetry. The compound has a layer structure and is a 1:1 complex of the organic ligand and cadmium chloride. The ligand, 3,3-dimethyl-1-[(E)-[phenyl(pyridine-2-yl)methylidene]amino]thiourea (L, Bp44mT), is of interest with respect to anticancer activity, antiviral properties and potential use in conditions of iron overload, from hemochromatosis or from multiple transfusions in hematological disorders such as sickle cell disease or beta thalassemia. This study is aimed at uncovering the basis of selectivity of the ligand as a chelator and for lead optimization. We also examine the ligand's potential use in treating heavy metal poisoning from cadmium, arsenic, lead or mercury, and for environmental remediation. The crystal structure exhibits no intermolecular or intramolecular hydrogen bonding with the supramolecular features being driven by hydrophobic, π–π and long-range dispersion forces. 

Structural characteristics are reported for two thioether–ketones,DtdpeandMtdp[2-({2-[(2-oxo-2-phenylethyl)sulfanyl]ethyl}sulfanyl)-1-phenylethan-1-one, C₁₈H₁₈O₂S₂, and 2-[(2-oxo-2-phenylethyl)sulfanyl]-1-phenylethan-1-one, C₁₆H₁₄O₂S], and for related derivatives, the bis(pyridylhydrazones)DhpkandPrpsb[2-((2E)-2-{(2Z)-2-phenyl-2-[2-(pyridin-2-yl)hydrazin-1-ylidene]ethylidene}hydrazin-1-yl)pyridine, C₁₈H₁₆N₆, and 2-[(2Z,12Z)-3,12-diphenyl-14-(pyridin-2-yl)-5,10-dithia-1,2,13,14-tetraazatetradeca-2,12-dien-1-yl]pyridine, C₃₀H₃₂N₆S₂], as well as for the macrocyclic thiocarbohydrazide derivativeCtrsp[(3E,8Z)-3,9-dimethyl-1,11-dithia-4,5,7,8-tetraazacyclotetradeca-3,8-diene-6-thione, C₁₀H₁₈N₄S₃]. Three of the five compounds exhibit conformational enantiomerism in the solid state. The occurrence of intra- and intermolecular hydrogen bonding is commented upon through quantum mechanical (DFT) calculations. Weak C—H...S interactions are noted, while stronger N—H...N and N—H...S hydrogen bridges are delineated. 

In the centrosymmetric title complexes, di-μ-acetato-bis({N,N-dimethyl-2-[phenyl(pyridin-2-yl)methylidene]hydrazine-1-carbothioamidato}zinc(II)), [Zn₂(C₁₅H₁₅N₄S)₂(C₂H₃O₂)₂] (I), and di-μ-acetato-bis({N-ethyl-2-[phenyl(pyridin-2-yl)methylidene]hydrazine-1-carbothioamidato}zinc(II)), [Zn₂(C₁₆H₁₇N₄S)₂(C₂H₃O₂)₂] (II), the zinc ions are chelated by theN,N,S-tridentate ligands and bridged by pairs of acetate ions. The acetate ion in (I) is disordered over two orientations in a 0.756 (6):0.244 (6) ratio, leading to different zinc coordination modes for the major (5-coordinate) and minor (6-coordinate) disorder components. Geometrical indices [τ₅= 0.32 and 0.30 for (I) (major component) and (II), respectively] suggest the zinc coordination in these phases to be distorted square pyramidal. This study forms part of our aim to discern the mechanism of metal binding in these chelators, their specificity and selectivity, and to gain insight into the role of cellular zinc in physiological processes such as infection, immunity and cancer. 

Disrupted iron balance causes anemia and iron overload leading to hypoxia and systemic oxidative stress. Iron overload may arise from red blood cell disorders such as sickle cell disease, thalassemia major and primary hemochromatosis, or from treatment with multiple transfusions. These hematological disorders are characterized by constant red blood cell hemolysis and the release of iron. Hemolysis is a continuous source of reactive oxygen species whose accumulation changes the redox potential in the erythrocyte, the endothelium and other tissue causing damage to organ systems. Iron overload and its consequences can be treated with iron chelating therapy. We have carried out structural studies of small molecule ligands that were previously reported for their iron chelating ability. The chelators were analyzed using mass spectrometry, proton nuclear magnetic resonance and infrared spectroscopy. The iron chelators, 2-benzoylpyridine-4,4-dimethyl-3-thiosemicarbazone, 3-ethyl-1-{[2-phenyl-1-(pyridin-2-yl)ethylidene]amino}thiourea and 1-{[2-phenyl-1-(pyridin-2-yl)ethylidene]amino}-3-(prop‑2-en-1-yl)thiourea in their unbound conformation were crystallized and their structures were determined. This work addresses the evolution of a thiosemicarbazone class of iron chelators by analyzing and comparing the structure and properties of a series of closely related molecules, relating these to their in vitro activity thus providing valuable update to the search for newer, better and more effective iron chelators and metal-based therapeutics. 

Adaptive behavior in complex environments critically relies on the ability to appropriately link specific choices or actions to their outcomes. However, the neural mechanisms that support the ability to credit only those past choices believed to have caused the observed outcomes remain unclear. Here, we leverage multivariate pattern analyses of functional magnetic resonance imaging (fMRI) data and an adaptive learning task to shed light on the underlying neural mechanisms of such specific credit assignment. We find that the lateral orbitofrontal cortex (lOFC) and hippocampus (HC) code for the causal choice identity when credit needs to be assigned for choices that are separated from outcomes by a long delay, even when this delayed transition is punctuated by interim decisions. Further, we show when interim decisions must be made, learning is additionally supported by lateral frontopolar cortex (lFPC). Our results indicate that lFPC holds previous causal choices in a ‘pending’ state until a relevant outcome is observed, and the fidelity of these representations predicts the fidelity of subsequent causal choice representations in lOFC and HC during credit assignment. Together, these results highlight the importance of the timely reinstatement of specific causes in lOFC and HC in learning choice-outcome relationships when delays and choices intervene, a critical component of real-world learning and decision making. 

Abstract Scholars disagree as to whether Americans’ attitudes toward local issues are structured ideologically and whether these are related to national policy ideology. We use two surveys of American adults to assess whether and to what extent Americans' local policy attitudes exhibit a similar structure as do national policy attitudes. We find that items asking about local policy are just as likely to reflect a latent dimension of policy preferences as those asking about national policy. Additionally, when local and national items are scaled separately, those scales are highly correlated. Our findings indicate that attitudes toward many local issues are aligned with national ideology. A smaller subset of attitudes about local issues appears distinctively local and possibly structured by non-ideological cleavages. 

This study explores the application of Atomic Layer Deposition (ALD) to functionalize high-surface-area carbon supports with metal and metal oxide films and particles for applications in catalysis and electrocatalysis. The work reported here demonstrates that, through careful choice of precursors and absorption and reaction conditions, self-limited ALD growth on a high-surface-area carbon support can be achieved. Specific examples presented include the growth of conformal films of ZrO2 and SnO2 and the deposition of Ga2O3 and Pt particles on a carbon black support with a surface area of 250 m2·g−1. A novel strategy for controlling the Pt weight loading and producing sub-nanometer Pt particles on a carbon support using a single ALD cycle is also presented. 

We consider quantile estimation in a semi-supervised setting, characterized by two available data sets: (i) a small or moderate sized labeled data set containing observations for a response and a set of possibly high dimensional covariates, and (ii) a much larger unlabeled data set where only the covariates are observed. We propose a family of semi-supervised estimators for the response quantile(s) based on the two data sets, to improve the estimation accuracy compared to the supervised estimator, i.e., the sample quantile from the labeled data. These estimators use a flexible imputation strategy applied to the estimating equation along with a debiasing step that allows for full robustness against misspecification of the imputation model. Further, a one-step update strategy is adopted to enable easy implementation of our method and handle the complexity from the non-linear nature of the quantile estimating equation. Under mild assumptions, our estimators are fully robust to the choice of the nuisance imputation model, in the sense of always maintaining root-n consistency and asymptotic normality, while having improved efficiency relative to the supervised estimator. They also attain semi-parametric optimality if the relation between the response and the covariates is correctly specified via the imputation model. As an illustration of estimating the nuisance imputation function, we consider kernel smoothing type estimators on lower dimensional and possibly estimated transformations of the high dimensional covariates, and we establish novel results on their uniform convergence rates in high dimensions, involving responses indexed by a function class and usage of dimension reduction techniques. These results may be of independent interest. Numerical results on both simulated and real data confirm our semi-supervised approach's improved performance, in terms of both estimation and inference.