Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Hybrid game strategies for MO problems in aerospace design

Game strategies have been developed in past decades and used in the field of economics, engineering, computer science and biology due to their efficiency in solving design optimisation problems. In addition, research on Multi-Objective (MO) and Multidisciplinary Design Optimisation (MDO) has focused on developing robust and efficient optimisation method to produce quality solutions with less computational time. In this paper, a new optimisation method Hybrid Game Strategy for MO problems is introduced and compared to CMA-ES based optimisation approach. Numerical results obtained from both optimisation methods are compared in terms of computational expense and model quality. The benefits of using Game-strategies are demonstrated.

Fusion of worlds?: Consumers' self-narrative in a hybrid digital/physical world

As the Internet becomes deeply embedded in consumers' life and continuously accessed through mobile devices, the boundary between the digital and the physical becomes less defined. This thesis investigates how this blurring boundary impacts on consumers' construction of their self-narrative and found that consumers' narrative is paradoxically coherent and fragmented and depicts a heroic story of the self. Prior studies show consumers achieve their desired life story through meaningful consumption, however, the notion of fragmented lives are challenged. Further, extensive digital leisure consumption is often viewed in a less positive light. Nevertheless, consumers, who significantly consume digital leisure, do not disregard their physical world or favour one space over the other. Rather, they negotiate key aspects from their digital and physical lives and fluidly move between these two worlds, creating a hybrid narrative that saves their self and others.

Samoa’s education policy: Negotiating a hybrid space for values

This paper analyses the education policy of Samoa to examine the values that are presented within as relevant to the education system. Drawing on the theory of postcolonialism and globalization, we illustrate how the global and local interact within the education policy to create a hybrid, heterogeneous mix of values and, while the policy acknowledges the significance of Samoan values, it is principally directed towards universal values being incorporated into the education system. We undertake a critical policy analysis to illustrate how the hybrid set of values are indicative of a neo-colonial discourse and argue that universal values are required, however, these need to be equally matched with local Samoan values for the education policy to be highly relevant, authentic and applicable to the Samoan education context.

Uncanny nature: Hybrid stop motion using Blender

This talk gives an overview of the project "Uncanny Nature", which incoporates a style of animation called Hybrid Stop Motion, that combines physical object armatures with virtual copies. The development of the production pipeline (using a mix of Blender, Dragonframe, Photoscan and Arduino) is discussed, as well as the way that Blender was used throughout the production to visualise, model, animate and composite the elements together.

Alloying gold with copper makes for a highly selective visible-light photocatalyst for the reduction of nitroaromatics to anilines

Finely control of product selectivity is an essential issue in organic chemical production. In the synthesis of functionalized anilines via reduction of the corresponding nitroarenes, the challenge is to selectively reduce only the nitro group in the presence of other reducible functional groups in nitroarene molecules at a high reaction rate. Normally, the nitroarene is reduced stepwise through a series of intermediates that remain as byproducts, increasing the aniline synthesis cost. Here we report that alloying small amounts of copper into gold nanoparticles can alter the reaction pathway of the catalytic reduction under visible-light irradiation at ambient temperature, allowing nitroaromatics to be transformed directly to anilines in a highly selective manner. The reasons for the high efficiency of the photocatalytic reduction under these comparatively benign conditions as well as the light-excited reaction mechanisms are discussed. This photocatalytic process avoids byproducts, exhibits a high reaction rate and excellent substituent tolerance, and can be used for the synthesis of many useful functionalized anilines under environmentally benign conditions. Switching of the reaction pathway simply by tailoring the bimetallic alloy NPs of the photocatalysts is effective for engineering of product chemoselectivity.

A hybrid agent architecture for modeling autonomous agents in SAGE

This paper highlights the Hybrid agent construction model being developed that allows the description and development of autonomous agents in SAGE (Scalable, fault Tolerant Agent Grooming Environment) - a second generation FIPA-Compliant Multi-Agent system. We aim to provide the programmer with a generic and well defined agent architecture enabling the development of sophisticated agents on SAGE, possessing the desired properties of autonomous agents - reactivity, pro-activity, social ability and knowledge based reasoning. © Springer-Verlag Berlin Heidelberg 2005.

A dye-sensitized visible light photocatalyst-Bi24 O31 Cl10

The p-block semiconductors are regarded as a new family of visible-light photocatalysts because of their dispersive and anisotropic band structures as well as high chemical stability. The bismuth oxide halides belong to this family and have band structures and dispersion relations that can be engineered by modulating the stoichiometry of the halogen elements. Herein, we have developed a new visible-light photocatalyst Bi 24 O 31 Cl 10 by band engineering, which shows high dye-sensitized photocatalytic activity. Density functional theory calculations reveal that the p-block elements determine the nature of the dispersive electronic structures and narrow band gap in Bi 24 O 31 Cl 10. Bi 24 O 31 Cl 10 exhibits excellent visible-light photocatalytic activity towards the degradation of Rhodamine B, which is promoted by dye sensitization due to compatible energy levels and high electronic mobility. In addition, Bi 24 O 31 Cl 10 is also a suitable photoanode material for dye-sensitized solar cells and shows power conversion efficiency of 1.5%.

Predicting single-layer technetium dichalcogenides (TcX2, X = S, Se) with promising applications in photovoltaics and photocatalysis

One of the least known compounds among transition metal dichalcogenides (TMDCs) is the layered triclinic technetium dichalcogenides (TcX2, X = S, Se). In this work, we systematically study the structural, mechanical, electronic, and optical properties of TcS2 and TcSe2 monolayers based on density functional theory (DFT). We find that TcS2 and TcSe2 can be easily exfoliated in a monolayer form because their formation and cleavage energy are analogous to those of other experimentally realized TMDCs monolayer. By using a hybrid DFT functional, the TcS2 and TcSe2 monolayers are calculated to be indirect semiconductors with band gaps of 1.91 and 1.69 eV, respectively. However, bilayer TcS2 exhibits direct-bandgap character, and both TcS2 and TcSe2 monolayers can be tuned from semiconductor to metal under effective tensile/compressive strains. Calculations of visible light absorption indicate that 2D TcS2 and TcSe2 generally possess better capability of harvesting sunlight compared to single-layer MoS2 and ReSe2, implying their potential as excellent light-absorbers. Most interestingly, we have discovered that the TcSe2 monolayer is an excellent photocatalyst for splitting water into hydrogen due to the perfect fit of band edge positions with respect to the water reduction and oxidation potentials. Our predictions expand the two-dimensional (2D) family of TMDCs, and the remarkable electronic/optical properties of monolayer TcS2 and TcSe2 will place them among the most promising 2D TMDCs for renewable energy application in the future.

The pedagogic prosthetic: Augmented learning as content-in-motion in hybrid educational spheres

This article draws on the design and implementation of three mobile learning projects introduced by Flanagan in 2011, 2012 and 2014 engaging a total of 206 participants. The latest of these projects is highlighted in this article. Two other projects provide additional examples of innovative strategies to engage mobile and cloud systems describing how electronic and mobile technology can help facilitate teaching and learning, assessment for learning and assessment as learning, and support communities of practice. The second section explains the theoretical premise supporting the implementation of technology and promulgates a hermeneutic phenomenological approach. The third section discusses mobility, both in terms of the exploration of wearable technology in the prototypes developed as a result of the projects, and the affordances of mobility within pedagogy. Finally the quantitative and qualitative methods in place to evaluate m-learning are explained.

Single atom (Pd/Pt) supported on graphitic carbon nitride as efficient photocatalyst for visible-light reduction of carbon dioxide

Reducing carbon dioxide (CO2) to hydrocarbon fuel with solar energy is significant for high-density solar energy storage and carbon balance. In this work, single palladium/platinum (Pd/Pt) atoms supported on graphitic carbon nitride (g-C3N4), i.e. Pd/g-C3N4 and Pt/g-C3N4, acting as photocatalysts for CO2 reduction were investigated by density function theory (DFT) calcu-lations for the first time. During CO2 reduction, the individual metal atoms function as the active sites, while g-C3N4 provides the source of hydrogen (H*) from hydrogen evolution reaction. The complete, as-designed photocatalysts exhibit excellent activity in CO2 reduction. HCOOH is the preferred product of CO2 reduction on the Pd/g-C3N4 catalyst with a rate-determining barrier of 0.66 eV, while the Pt/g-C3N4 catalyst prefers to reduce CO2 to CH4 with a rate-determining barrier of 1.16 eV. In addition, depositing atom catalysts on g-C3N4 significantly enhances the visible light absorption, rendering them ideal for visible light reduction of CO2. Our findings open a new avenue of CO2 reduction for renewable energy supply.