Partial least squares regression has been an alternative to ordinary least squares for handling multicollinearity in several areas of scientific research since the 1960s. It has recently gained much attention in the analysis of high dimensional genomic data. We show that known asymptotic consistency of the partial least squares estimator for a univariate response does not hold with the very large p and small n paradigm. We derive a similar result for a multivariate response regression with partial least squares. We then propose a sparse partial least squares formulation which aims simultaneously to achieve good predictive performance and variable selection by producing sparse linear combinations of the original predictors. We provide an efficient implementation of sparse partial least squares regression and compare it with well-known variable selection and dimension reduction approaches via simulation experiments. We illustrate the practical utility of sparse partial least squares regression in a joint analysis of gene expression and genomewide binding data.

Electrocatalytic denitrification is a promising technology for the removal of NO x species in groundwater.However, a lack of understanding of the molecular pathways that control the overpotential and product distribution have limited the development of practical electrocatalysts, and additional atomic-level insights are needed to advance this field. Adsorbed NO has been identified as a key intermediate in the NO x electroreduction network, and the elementary steps by which it decomposes to NH 4 + , N 2 , NH 2 OH, or N 2 O remain a subject of debate. Herein, we report a combined Density Functional Theory (DFT) and kinetic Monte Carlo (kMC) study of this reaction on Pt(100), a catalytic surface that is known to be active for the activation of strong covalent bonds, in acidic electrolytes. This approach describes the effects of coverage-dependent adsorbate-adsorbate interactions, water-mediated protonation kinetics and thermodynamics, and transient potential sweeps, on reaction rates and selectivities. The results predict NO stripping curves in excellent agreement with experiments while, at the same time, providing a mechanistic interpretation of observed current peaks. Further, production of NH 4 + products is traced to the rapid kinetics of N-O bond breaking in reactive intermediates, while rapid hydrogenation of surface N* species prevent competing pathways from forming either N 2 or N 2 O. The combined DFT-kMC methodology thus provides a unique tool to describe the mechanism and energetics of platinum-catalyzed electroreduction in the nitrogen cycle, and this approach should also find application to related electrocatalytic processes that are of technological and environmental interest.

The mechanism of nitric oxide electroreduction on Pt(111) is investigated using a combination of first principles calculations and electrokinetic rate theories. Barriers for chemical cleavage of N-O bonds on Pt(111) are found to be inaccessibly high at room temperature, implying that explicit electrochemical steps, along with the aqueous environment, play important roles in the experimentally observed formation of ammonia. Use of explicit water models, and associated determination of potential-dependent barriers based on Bulter-Volmer kinetics, demonstrate that ammonia is produced through a series of water-assisted protonation and bond dissociation steps at modest voltages (<0.3 V). In addition, the analysis sheds light on the poorly understood formation mechanism of nitrous oxide (N2 O) at higher potentials, which suggests that N2 O is not produced through a Langmuir-Hinshelwood mechanism; rather, its formation is facilitated through an Eley-Rideal-type process.

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Novel biodegradable poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [PHBV]/graphene nanocomposites were prepared by solution casting. The thermal properties, crystallization behavior, microstructure, and fracture morphology of the composites were investigated. Scanning electron microscope (SEM) results show that graphene layers are homogeneously dispersed in the polymer matrix. X-ray diffraction (XRD) and dynamic scanning calorimetry (DSC) studies show that the well dispersed graphene sheets act as nucleating agent for crystallization. Consequently, the mechanical properties of the composites have been substantially improved as evident from dynamic mechanical and static tensile tests. Differential thermal analysis (DTA) showed an increase in temperature of maximum degradation. Soil degradation tests of PHBV/graphene nanocomposites showed that presence of graphene doesn’t interfere in its biodegradability