Engineering directed excitonic energy transfer

We provide an intuitive platform for engineering exciton transfer dynamics. We show that careful consideration of the spectral density, which describes the system-bath interaction, leads to opportunities to engineer the transfer of an exciton. Since excitons in nanostructures are proposed for use in quantum information processing and artificial photosynthetic designs, our approach paves the way for engineering a wide range of desired exciton dynamics. We carefully describe the validity of the model and use experimentally relevant material parameters to show counter-intuitive examples of a directed exciton transfer in a linear chain of quantum dots

By-passing the Kohn-Sham equations with machine learning

Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields, ranging from materials science to biochemistry to astrophysics. Machine learning holds the promise of learning the kinetic energy functional via examples, by-passing the need to solve the Kohn-Sham equations. This should yield substantial savings in computer time, allowing either larger systems or longer time-scales to be tackled, but attempts to machine-learn this functional have been limited by the need to find its derivative. The present work overcomes this difficulty by directly learning the density-potential and energy-density maps for test systems and various molecules. Both improved accuracy and lower computational cost with this method are demonstrated by reproducing DFT energies for a range of molecular geometries generated during molecular dynamics simulations. Moreover, the methodology could be applied directly to quantum chemical calculations, allowing construction of density functionals of quantum-chemical accuracy

Evaluating the impact of a resident research program in general surgery

Background: Programs of resident research have been found to improve research productivity. However, evidence of the success of these programs is lacking in a Canadian context. The objective of this study was to evaluate the impact of the introduction of a formal program of resident research at a single Canadian academic centre.Methods: Resident research activities were tracked over a 10-year period (Resident Research Day (RRD) presentations, abstract presentations, published articles). Activities were divided into pre (2002-2007) and post (2007-2012) resident research program implementation time frames. Differences in research productivity were compared between time frames. Surveys of resident attitudes towards research were administered prior to the program’s implementation in 2007, and following introduction of the resident research program in 2009 and 2015.Results: Overall, research productivity (abstracts, publications, and RRD presentations) increased between pre and post resident research program time periods, with a statistically significant increase in mean number of published abstracts. Resident attitudes towards research changed somewhat over time, with fewer residents supporting mandatory research in recent years.Conclusion: Implementation of a resident program of research resulted in a significant increase in research productivity. The setting of clear, modifiable, and achievable goals, as well as providing tools for research success, have contributed to the success of this program

Accelerating Resolution-of-the-Identity Second Order Møller-Plesset Quantum Chemistry Calculations with Graphical Processing Units

The modification of a general purpose code for quantum mechanical calculations of molecular properties (Q-Chem) to use a graphical processing unit (GPU) is reported. A 4.3x speedup of the resolution-of-the-identity second-order Møller−Plesset perturbation theory (RI-MP2) execution time is observed in single point energy calculations of linear alkanes. The code modification is accomplished using the compute unified basic linear algebra subprograms (CUBLAS) library for an NVIDIA Quadro FX 5600 graphics card. Furthermore, speedups of other matrix algebra based electronic structure calculations are anticipated as a result of using a similar approach.Chemistry and Chemical Biolog

Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units and a Mixed Precision Matrix Multiplication Library

Two new tools for the acceleration of computational chemistry codes using graphical processing units (GPUs) are presented. First, we propose a general black-box approach for the efficient GPU acceleration of matrix−matrix multiplications where the matrix size is too large for the whole computation to be held in the GPU’s onboard memory. Second, we show how to improve the accuracy of matrix multiplications when using only single-precision GPU devices by proposing a heterogeneous computing model, whereby single- and double-precision operations are evaluated in a mixed fashion on the GPU and central processing unit, respectively. The utility of the library is illustrated for quantum chemistry with application to the acceleration of resolution-of-the-identity second-order Møller−Plesset perturbation theory calculations for molecules, which we were previously unable to treat. In particular, for the 168-atom valinomycin molecule in a cc-pVDZ basis set, we observed speedups of 13.8, 7.8, and 10.1 times for single-, double- and mixed-precision general matrix multiply (SGEMM, DGEMM, and MGEMM), respectively. The corresponding errors in the correlation energy were reduced from −10.0 to −1.2 kcal mol$^{-1}$ for SGEMM and MGEMM, respectively, while higher accuracy can be easily achieved with a different choice of cutoff parameter.Chemistry and Chemical Biolog

Effects of a culturally responsive speech and language intervention for students of Indigenous and non-Indigenous ancestry

This study explored the effectiveness of a speech and language intervention that was designed to be culturally responsive and adapted to provide explicit language instruction. Participants included all 774 kindergarten students from a mid-sized rural school district in British Columbia. Seventy-seven students screened as at risk received the intervention, and the remaining students participated in the regular kindergarten curriculum. Results indicated statistically significant effects of the intervention on language and vocabulary skills. No differential effects were observed between students of Indigenous and non-Indigenous heritage. Results are discussed in terms of culturally responsive and explicit instruction for early language development.Key words: early intervention, language intervention, cultural responsiveness, Aboriginal educationCette étude a examiné l'efficacité d'une intervention orthophonique et linguistique conçue pour être culturellement adaptée et permettre un enseignement explicite des langues. 774 élèves de maternelle d'un district scolaire rural de taille moyenne en Colombie-Britannique ont participé à cette étude. Parmi eux, 77 étudiants, sélectionnés comme étant à risque, ont participé à l'intervention, tandis que les autres étudiants ont participé au programme de maternelle habituel. Les résultats ont montré des effets statistiquement significatifs de l'intervention sur le langage et le vocabulaire. Aucune différence n'a été observée entre les étudiants ayant un patrimoine culturel autochtone ou non autochtone. Ces résultats sont débatus en termes d'enseignement explicite et culturellement adapté pour le développement précoce du langage.Mots clés: intervention précoce, intervention linguistique, sensibilisation à la culturel, éducation des Autochtone

Accelerated Computational Discovery of High-Performance Materials for Organic Photovoltaics by Means of Cheminformatics

In this perspective we explore the use of strategies from drug discovery, pattern recognition, and machine learning in the context of computational materials science. We focus our discussion on the development of donor materials for organic photovoltaics by means of a cheminformatics approach. These methods enable the development of models based on molecular descriptors that can be correlated to the important characteristics of the materials. Particularly, we formulate empirical models, parametrized using a training set of donor polymers with available experimental data, for the important current–voltage and efficiency characteristics of candidate molecules. The descriptors are readily computed which allows us to rapidly assess key quantities related to the performance of organic photovoltaics for many candidate molecules. As part of the Harvard Clean Energy Project, we use this approach to quickly obtain an initial ranking of its molecular library with 2.6 million candidate compounds. Our method reveals molecular motifs of particular interest, such as the benzothiadiazole and thienopyrrole moieties, which are present in the most promising set of molecules.Chemistry and Chemical Biolog

Fracture Incidence and Risk of Osteoporosis in Female Type 2 Diabetic Patients in Korea

BackgroundThere are no published data regarding fracture risk in type 2 diabetic patients in Korea. In this study, we compared the fracture incidence and risk of osteoporosis of type 2 diabetic female patients with those in a non-diabetic hypertensive cohort.MethodsThe incidence of fracture in a type 2 diabetic cohort was compared with that in a non-diabetic hypertensive cohort over the course of 7 years. Female type 2 diabetic and non-diabetic hypertensive patients who visited Eulji General Hospital outpatient clinic from January 2004 to April 2004 were assigned to the diabetic cohort and the non-diabetic hypertensive cohort, respectively. Surveys on fracture event, use of anti-osteoporosis medications, and bone mineral density were performed.ResultsThe number of fractures was 88 in the female diabetic cohort (n=1,268, 60.6±11.5 years) and 57 in the female non-diabetic hypertensive cohort (n=1,014, 61.4±11.7 years). The RR in the diabetic cohort was 1.38 (P=0.064; 95% confidence interval [CI], 0.98 to 1.94) when adjusted for age. Diabetic patients with microvascular complications (61.0%) showed a higher RR of 1.81 (P=0.014; 95% CI, 1.13 to 2.92) compared with those without these complications. The prevalence of osteoporosis was comparable between the groups, while use of anti-osteoporosis medication was more common in the diabetic cohort (12.8%) than in the hypertensive cohort (4.5%) (P<0.001).ConclusionIn our study, a higher fracture risk was observed in female type 2 diabetics with microvascular complications. Special concern for this risk group is warranted

Probabilistic Clustering of Time-Evolving Distance Data

We present a novel probabilistic clustering model for objects that are represented via pairwise distances and observed at different time points. The proposed method utilizes the information given by adjacent time points to find the underlying cluster structure and obtain a smooth cluster evolution. This approach allows the number of objects and clusters to differ at every time point, and no identification on the identities of the objects is needed. Further, the model does not require the number of clusters being specified in advance -- they are instead determined automatically using a Dirichlet process prior. We validate our model on synthetic data showing that the proposed method is more accurate than state-of-the-art clustering methods. Finally, we use our dynamic clustering model to analyze and illustrate the evolution of brain cancer patients over time