A Woman’s Perspective on Leadership in K-12 Education

This qualitative research is the outcome of an interview with a woman on her experiences as a K-12 leader and her perspective of cultural differences and women leadership. The overall viewpoint of leadership was on a leader’s ability to be transformative. Transformational leadership in this context referred to a leaders’ ability to capitalize on the differences within a multicultural society, societal changes, and social justice. Northouse (2010) in the opening chapter of his book on leadership, Leadership; Theory and Practice; 5th Edition, speaks of how leadership has become conceptualized. One such concept is that transformational leadership is a process that motivates followers to accomplish more than what is usually expected. However, for leadership to be transformational it must reflect cultural intelligence. Cultural intelligence is defined as an individual’s capability to function effectively across cultures, nationalities, ethnicities, and organizations, as well as other types of culture (Van Dyne, Ang, and Livermore, 2010)

A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain useful insights for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of the structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are nontrivial to catch. Here, we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Position (SOAP). We compare and classify a set of 13 FFs, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernel-based metrics allows us to compare, discriminate, and correlate different FFs at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling nonaverage events (originating from local transitions), for example, the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows us to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit versus explicit solvent FFs

Automatic Middle-Out Optimisation of Coarse-Grained Lipid Force Fields

Automatic data-driven approaches are increasingly used to develop accurate molecular models. But the parameters of such automatically-optimised models are typically untransferable. Using a multi-reference approach in combination with an automatic optimisation engine (SwarmCGM), here we show that it is possible to optimise coarse-grained (CG) lipid models that are also transferable, generating optimised lipid force fields. The parameters of the CG lipid models are iteratively and simultaneously optimised against higher-resolution simulations (bottom-up) and experimental data (top-down references). Including different types of lipid bilayers in the training set guarantees the transferability of the optimised force field parameters. Tested against state-of-the-art CG lipid force fields, we demonstrate that SwarmCGM can systematically improve their parameters, enhancing the agreement with the experiments even for lipid types not included in the training set. The approach is general and can be used to improve existing CG lipid force fields, as well as to develop new custom ones.Comment: Paper (Pages 1-16) + Supporting Information (Pages 17-40

Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy

<p>Abstract</p> <p>Background</p> <p>We conducted an ecological study in four French administrative departments and highlighted an excess risk in cancer morbidity for residents around municipal solid waste incinerators. The aim of this paper is to show how important are advanced tools and statistical techniques to better assess weak associations between the risk of cancer and past environmental exposures.</p> <p>Methods</p> <p>The steps to evaluate the association between the risk of cancer and the exposure to incinerators, from the assessment of exposure to the definition of the confounding variables and the statistical analysis carried out are detailed and discussed. Dispersion modelling was used to assess exposure to sixteen incinerators. A geographical information system was developed to define an index of exposure at the IRIS level that is the geographical unit we considered.</p> <p>Population density, rural/urban status, socio-economic deprivation, exposure to air pollution from traffic and from other industries were considered as potential confounding factors and defined at the IRIS level. Generalized additive models and Bayesian hierarchical models were used to estimate the association between the risk of cancer and the index of exposure to incinerators accounting for the confounding factors.</p> <p>Results</p> <p>Modelling to assess the exposure to municipal solid waste incinerators allowed accounting for factors known to influence the exposure (meteorological data, point source characteristics, topography). The statistical models defined allowed modelling extra-Poisson variability and also non-linear relationships between the risk of cancer and the exposure to incinerators and the confounders.</p> <p>Conclusion</p> <p>In most epidemiological studies distance is still used as a proxy for exposure. This can lead to significant exposure misclassification. Additionally, in geographical correlation studies the non-linear relationships are usually not accounted for in the statistical analysis. In studies of weak associations it is important to use advanced methods to better assess dose-response relationships with disease risk.</p

Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning Particle Swarm Optimization

We present Swarm-CG, a versatile software for the automatic iterative parametrization of bonded parameters in coarse-grained (CG) models, ideal in combination with popular CG force fields such as MARTINI. By coupling fuzzy self-tuning particle swarm optimization to Boltzmann inversion, Swarm-CG performs accurate bottom-up parametrization of bonded terms in CG models composed of up to 200 pseudo atoms within 4-24 h on standard desktop machines, using default settings. The software benefits from a user-friendly interface and two different usage modes (default and advanced). We particularly expect Swarm-CG to support and facilitate the development of new CG models for the study of complex molecular systems interesting for bio- and nanotechnology. Excellent performances are demonstrated using a benchmark of 9 molecules of diverse nature, structural complexity, and size. Swarm-CG is available with all its dependencies via the Python Package Index (PIP package: swarm-cg). Demonstration data are available at: www.github.com/GMPavanLab/SwarmCG

Cooperative Supramolecular Block Copolymerization for the Synthesis of Functional Axial Organic Heterostructures

Supramolecular block copolymerzation with optically or electronically complementary monomers provides an attractive bottom-up approach for the non-covalent synthesis of nascent axial organic heterostructures, which promises to deliver useful applications in energy conversion, optoelectronics, and catalysis. However, the synthesis of supramolecular block copolymers (BCPs) constitutes a significant challenge due to the exchange dynamics of non-covalently bound monomers and hence requires fine microstructure control. Furthermore, temporal stability of the segmented microstructure is a prerequisite to explore the applications of functional supramolecular BCPs. Herein, we report the cooperative supramolecular block copolymerization of fluorescent monomers in solution under thermodynamic control for the synthesis of axial organic heterostructures with light-harvesting properties. The fluorescent nature of the core-substituted naphthalene diimide (cNDI) monomers enables a detailed spectroscopic probing during the supramolecular block copolymerization process to unravel a nucleation-growth mechanism, similar to that of chain copolymerization for covalent block copolymers. Structured illumination microscopy (SIM) imaging of BCP chains characterizes the segmented microstructure and also allows size distribution analysis to reveal the narrow polydispersity (polydispersity index (PDI) ≈ 1.1) for the individual block segments. Spectrally resolved fluorescence microscopy on single block copolymerized organic heterostructures shows energy migration and light-harvesting across the interfaces of linearly connected segments. Molecular dynamics and metadynamics simulations provide useful mechanistic insights into the free energy of interaction between the monomers as well as into monomer exchange mechanisms and dynamics, which have a crucial impact on determining the copolymer microstructure. Our comprehensive spectroscopic, microscopic, and computational analyses provide an unambiguous structural, dynamic, and functional characterization of the supramolecular BCPs. The strategy presented here is expected to pave the way for the synthesis of multi-component organic heterostructures for various functions

Risk for non Hodgkin’s lymphoma in the vicinity of French municipal solid waste incinerators

<p>Abstract</p> <p>Background</p> <p>Dioxin emissions from municipal solid waste incinerators are one of the major sources of dioxins and therefore are an exposure source of public concern. There is growing epidemiologic evidence of an increased risk for non-Hodgkin's lymphoma (NHL) in the vicinity of some municipal solid waste incinerators with high dioxin emission levels. The purpose of this study was to examine this association on a larger population scale.</p> <p>Methods</p> <p>The study area consisted of four French administrative departments, comprising a total of 2270 block groups. NHL cases that had been diagnosed during the period 1990–1999, and were aged 15 years and over, were considered. Each case was assigned a block group by residential address geocoding. Atmospheric Dispersion Model System software was used to estimate immissions in the surroundings of 13 incinerators which operated in the study area. Then, cumulative ground-level dioxin concentrations were calculated for each block group. Poisson multiple regression models, incorporating penalized regression splines to control for covariates and dealing with Poisson overdispersion, were used. Five confounding factors were considered: population density, urbanisation, socio-economic level, airborne traffic pollution, and industrial pollution.</p> <p>Results</p> <p>A total of 3974 NHL incident cases was observed (2147 among males, and 1827 among females) during the 1990–1999 time period. A statistically significant relationship was found at the block group level between risk for NHL and dioxin exposure, with a relative risk (RR) of 1.120 (95% confidence interval [CI] 1.002 – 1.251) for persons living in highly exposed census blocks compared to those living in slightly exposed block groups. Population density appeared positively linked both to risk for NHL and dioxin exposure. Subgroup multivariate analyses per gender yielded a significant RR for females only (RR = 1.178, 95% CI 1.013 – 1.369).</p> <p>Conclusion</p> <p>This study, in line with previous results obtained in the vicinity of the incinerator located in Besançon (France), adds further evidence to the link between NHL incidence and exposure to dioxins emitted by municipal solid waste incinerators. However, the findings of this study cannot be extrapolated to current incinerators, which emit lower amounts of pollutants.</p