Geometry‐Related Children's Literature Improves the Geometry Achievement and Attitudes of Second‐Grade Students

Use of mathematics‐related literature can engage students' interest and increase their understanding of mathematical concepts. A quasi‐experimental study of two second‐grade classrooms assessed whether daily inclusion of geometry‐related literature in the classroom improved attitudes toward geometry and achievement in geometry. Consistent with the hypothesis, only the students in the classroom with a strong emphasis on geometry‐related children's literature showed a significant improvement in their attitudes about geometry over time. While both classes improved their geometry performance over the 4 weeks of the study, the class with a strong emphasis on geometry‐related literature improved significantly more (51.2%) than the control class (33.47%). Children's literature can provide a useful and interesting context in which students can develop their understanding of geometry.     

ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction via Estimating Equations

Most variable selection techniques for high-dimensional models are designed to be used in settings, where observations are independent and completely observed. At the same time, there is a rich literature on approaches to estimation of low-dimensional parameters in the presence of correlation, missingness, measurement error, selection bias, and other characteristics of real data. In this article, we present ThrEEBoost (Thresholded EEBoost), a general-purpose variable selection technique which can accommodate such problem characteristics by replacing the gradient of the loss by an estimating function. ThrEEBoost generalizes the previously proposed EEBoost algorithm (Wolfson 2011 Wolfson, J. (2011), “EEBoost: A General Method for Prediction and Variable Selection Based on Estimating Equations,” Journal of the American Statistical Association, 106, 296–305.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) by allowing the number of regression coefficients updated at each step to be controlled by a thresholding parameter. Different thresholding parameter values yield different variable selection paths, greatly diversifying the set of models that can be explored; the optimal degree of thresholding can be chosen by cross-validation. ThrEEBoost was evaluated using simulation studies to assess the effects of different threshold values on prediction error, sensitivity, specificity, and the number of iterations to identify minimum prediction error under both sparse and nonsparse true models with correlated continuous outcomes. We show that when the true model is sparse, ThrEEBoost achieves similar prediction error to EEBoost while requiring fewer iterations to locate the set of coefficients yielding the minimum error. When the true model is less sparse, ThrEEBoost has lower prediction error than EEBoost and also finds the point yielding the minimum error more quickly. The technique is illustrated by applying it to the problem of identifying predictors of weight change in a longitudinal nutrition study. Supplementary materials are available online.     

Simplified,interpretable graph convolutional neural networks for small molecule activity prediction

Journal of Computer-Aided Molecular Design - We here present a streamlined, explainable graph convolutional neural network (gCNN) architecture for small molecule activity prediction. We first...     

The educational needs and professional roles of Canadian physicians and nurses regarding genetic testing and adult onset hereditary disease

OBJECTIVE: To investigate the knowledge, professional involvement and confidence of Canadian nurses and physicians in providing genetic services for adult onset hereditary disease. METHODS: 1,425 physicians and 1,425 nurses received a mailed questionnaire with reminders. The response rates were 50% (n = 543) and 79% (n = 975), respectively. RESULTS: Forty-eight percent of physicians and 31% of nurses lacked formal education in genetics. Respondents reported being involved in caring for people at risk for adult onset hereditary disease. Their levels of confidence that they could perform tasks, such as counselling about predictive genetic tests, however, were lower than their levels of expectation that it would be important for them to provide these services. CONCLUSIONS: The expected roles and educational needs of Canadian nurses and physicians have broad areas of overlap suggesting the possibility of combined professional education programs and multiple ways of organizing teams to provide genetic services to people at risk for adult onset hereditary disease.     

High Compression‐Induced Conductivity in a Layered Cu–Br Perovskite

We show that the onset pressure for appreciable conductivity in layered copper‐halide perovskites can decrease by ca. 50 GPa upon replacement of Cl with Br. Layered Cu–Cl perovskites require pressures >50 GPa to show a conductivity of 10^?4 S cm^?1, whereas here a Cu–Br congener, (EA)₂CuBr₄ (EA=ethylammonium), exhibits conductivity as high as 2×10^?3 S cm^?1 at only 2.6 GPa, and 0.17 S cm^?1 at 59 GPa. Substitution of higher‐energy Br 4p for Cl 3p orbitals lowers the charge‐transfer band gap of the perovskite by 0.9 eV. This 1.7 eV band gap decreases to 0.3 eV at 65 GPa. High‐pressure X‐ray diffraction, optical absorption, and transport measurements, and density functional theory calculations allow us to track compression‐induced structural and electronic changes. The notable enhancement of the Br perovskite's electronic response to pressure may be attributed to more diffuse Br valence orbitals relative to Cl orbitals. This work brings the compression‐induced conductivity of Cu‐halide perovskites to more technologically accessible pressures.     

Enzyme Design from the Bottom Up: An Active Nickel Electrocatalyst with a Structured Peptide Outer Coordination Sphere

Catalytic, peptide‐containing metal complexes with a well‐defined peptide structure have the potential to enhance molecular catalysts through an enzyme‐like outer coordination sphere. Here, we report the synthesis and characterization of an active, peptide‐based metal complex built upon the well‐characterized hydrogen production catalyst [Ni(P^Ph₂N^Ph)₂]²⁺ (P^Ph₂N^Ph=1,3,6‐triphenyl‐1‐aza‐3,6‐diphosphacycloheptane). The incorporated peptide maintains its β‐hairpin structure when appended to the metal core, and the electrocatalytic activity of the peptide‐based metal complex (≈100,000 s^?1) is enhanced compared to the parent complex ([Ni(P^Ph₂N^APPA)₂]²⁺; ≈50,500 s^‐1). The combination of an active molecular catalyst with a structured peptide provides a scaffold that permits the incorporation of features of an enzyme‐like outer‐coordination sphere necessary to create molecular electrocatalysts with enhanced functionality.     

Relative acidities and structure analysis of cis and trans isomers of 1,5‐oxazaspiro[5.5] undecane derivatives by multinuclear magnetic resonance

The relative acidities of the cis and trans isomers of a series of 1,5‐oxazaspiro[5.5]undecane derivatives were determined by measuring ΔpK in acid‐base titrations followed by ¹ H NMR. Relative structural stabilities were determined by measuring substituent chemical shift and γ‐gauche effects in ¹³C, ¹⁵N, and ¹⁷O NMR. Crystallographic characterization of a model spiro[5.5]undecane is presented to support the basicity in solid state. Copyright © 2010 John Wiley & Sons, Ltd.