Taming the killer in the kitchen: mitigating household air pollution from solid-fuel cookstoves through building design

In this study, we attempt to mitigate household air pollution (HAP) through improved kitchen design. Field surveys were conducted in ten kitchens of rural western India, which were then modelled and simulated for dynamic indoor airflow network analysis. The simulated results were statistically clustered using principal component analysis and hierarchical agglomerative clustering, to construct a cumulative built environment parameter called ‘Built Factor’ for each kitchen, and subsequently a derivative matrix was developed. Categorization of better performing kitchens from this derivative matrix enabled in deriving the built parameter thresholds for a ‘better’ kitchen design. This derived kitchen showed 60 % reduction in PM2.5 peak concentration during cooking hours. The evaluation described here is essentially a “proof of concept”, that effective building design can be an alternative way to reduce HAP without the introduction of chimneys, improved cookstoves or shifting to cleaner fuel.     

Competitiveness and an Emerging Sector: The Russian Software Industry and its Global Linkages

This paper analyzes the Russian software industry in the context of trade in information technology services. We assess Russia's underlying sources of competitive edge in software, such as its scientific establishments, education system, diaspora and low costs, and identify the institutional impediments to growth. A survey reveals that foreign outsourcing contracts, a high value-added niche and high education levels characterize Russia's small, privately held software firms. A comparison with the Indian software industry underscores the structural differences in outsourcing relationships developed by the two countries and emphasizes that national advantages are complex amalgamations of many factors and need to be overtly marketed. Beyond the resources that give comparative and competitive advantage to a transitioning economy, a critical role is played by powerful industry organizations and by non-market state institutions that can level the economic field and inject credibility into market structures.     

Preprecipitation in Al/Zn/Mg alloys studied by hardness and small-angle X-ray scattering measurements

Small-angle X-ray scattering techniques and hardness measurements have been used to study preprecipitation in two Al/Zn/Mg alloys containing the same Zn content (2.46 at. %) but different Mg contents. Changes in Guinier-Preston (G-P) zone size are observed to follow the same pattern as changes in hardness. It is also observed that a critical zone size is required for the nucleation of the intermediate precipitate,'; the size being dependent on the Mg content. The role of Mg as a reversible-vacancy trap is also established.     

On allocation of resources during testing phase of a modular software

To provide reliable software, it is tested over a wide range of testing environment. In the process, testing resources such as time, testing personnel etc. are used. These resources are not infinitely large and therefore need to be used judiciously. In this article, we discuss the testing resource allocation problem among modules to maximize the total fault removal from software consisting of several independent components (modules). For the resulting optimization problem, we define marginal testing effort function (MTEF), where the testing resource consumption is represented in terms of fault removal. The three MTEFs proposed in this article account for both exponential and S-shaped growth curves, which are commonly used in software reliability analysis. Results are illustrated numerically using different data sets.     

Nanoshells with Targeted Simultaneous Enhancement of Magnetic and Optical Imaging and Photothermal Therapeutic Response

Integrating multiple functionalities into individual nanoscale complexes is of tremendous importance in biomedicine, expanding the capabilities of nanoscale structures to perform multiple parallel tasks. Here, the ability to enhance two different imaging technologies simultaneously—fluorescence optical imaging and magnetic resonance imaging—with antibody targeting and photothermal therapeutic actuation is combined all within the same nanoshell‐based complex. The nanocomplexes are constructed by coating a gold nanoshell with a silica epilayer doped with Fe₃O₄ and the fluorophore ICG, which results in a high T₂ relaxivity (390 mM ^?1 s^?1) and 45× fluorescence enhancement of ICG. Bioconjugate nanocomplexes target HER2+ cells and induce photothermal cell death upon near‐IR illumination.     

Dirichlet Priors for MAP Inference of Protein Conformation Abundances from SAXS

Estimation of mixture coefficients of protein conformations in solution find applications in understanding protein behavior. We describe a method for maximum a posteriori (MAP) estimation of the mixture coefficients of ensemble of conformations in a protein mixture solution using measured small angle X-ray scattering (SAXS) intensities. The proposed method builds upon a model for the measurements of crystallographically determined conformations. Assuming that a priori information on the protein mixture is available, and that priori information follows a Dirichlet distribution, we develop a method to estimate the relative abundances with MAP estimator. The Dirichlet distribution depends on concentration parameters which may not be known in practice and thus need to be estimated. To estimate these unknown concentration parameters we developed an expectation-maximization (EM) method. Adenylate kinase (ADK) protein was selected as the test bed due to its known conformations Beckstein et al. (Journal of Molecular Biology, 394(1), 160 1). Known conformations are assumed to form the full vector bases that span the measurement space. In Monte Carlo simulations, mixture coefficient estimation performances of MAP and maximum likelihood (ML) (which assumes a uniform prior on the mixture coefficients) estimators are compared. MAP estimators using known and unknown concentration parameters are also compared in terms of estimation performances. The results show that prior knowledge improves estimation accuracy, but performance is sensitive to perturbations in the Dirichlet distribution’s concentration parameters. Moreover, the estimation method based on EM algorithm shows comparable results to approximately known prior parameters.     

Six sigma-based approach to optimize deep drawing operation variables

The six sigma approach has been increasingly adopted worldwide in the manufacturing sector in order to enhance the productivity and quality performance and to make the process robust to quality variations. This paper deals with one such application of six sigma methodology to improve the yield of deep drawing operations. The deep drawing operation has found extensive application in producing automotive components and many household items. The main issue of concern of the deep drawn products involves different critical process parameters and governing responses, which influences the yield of the operation. The effects of these parameters are analysed by the DMAIC (Define, Measurement, Analyse, Improve, Control)-based six sigma approach. A multiple response optimization model is formulated using the fuzzy-rule-based system. The functional relationship between the process variables and the responses is established, and thereafter their optimum setting is explored with the aid of response surface methodology (RSM). Rigorous experimentations have been carried out, and it is observed that the process capability of processes is enhanced significantly, after the successful deployment of the six sigma methodology.     

Optically- and thermally-responsive programmable materials based on carbon nanotube-hydrogel polymer composites

A simple approach is described to fabricate reversible, thermally- and optically responsive actuators utilizing composites of poly(N-isopropylacrylamide) (pNIPAM) loaded with single-walled carbon nanotubes. With nanotube loading at concentrations of 0.75 mg/mL, we demonstrate up to 5 times enhancement to the thermal response time of the nanotube-pNIPAM hydrogel actuators caused by the enhanced mass transport of water molecules. Additionally, we demonstrate the ability to obtain ultrafast near-infrared optical response in nanotube-pNIPAM hydrogels under laser excitation enabled by the strong absorption properties of nanotubes. The work opens the framework to design complex and programmable self-folding materials, such as cubes and flowers, with advanced built-in features, including tunable response time as determined by the nanotube loading.     

Theranostic nanoshells: from probe design to imaging and treatment of cancer

Recent advances in nanoscience and biomedicine have expanded our ability to design and construct multifunctional nanoparticles that combine targeting, therapeutic, and diagnostic functions within a single nanoscale complex. The theranostic capabilities of gold nanoshells, spherical nanoparticles with silica cores and gold shells, have attracted tremendous attention over the past decade as nanoshells have emerged as a promising tool for cancer therapy and bioimaging enhancement. This Account examines the design and synthesis of nanoshell-based theranostic agents, their plasmon-derived optical properties, and their corresponding applications. We discuss the design and preparation of nanoshell complexes and their ability to enhance the photoluminescence of fluorophores while maintaining their properties as MR contrast agents. In this Account, we discuss the underlying physical principles that contribute to the photothermal response of nanoshells. We then elucidate the photophysical processes that induce nanoshells to enhance the fluorescence of weak near-infrared fluorophores. Nanoshells illuminated with resonant light are either strong optical absorbers or scatterers, properties that give rise to their unique capabilities. These physical processes have been harnessed to visualize and eliminate cancer cells. We describe the application of nanoshells as a contrast agent for optical coherence tomography of breast carcinoma cells in vivo. Our recent studies examine nanoshells as a multimodal theranostic probe, using these nanoparticles for near-infrared fluorescence and magnetic resonance imaging (MRI) and for the photothermal ablation of cancer cells. Multimodal nanoshells show theranostic potential for imaging subcutaneous breast cancer tumors in animal models and the distribution of tumors in various tissues. Nanoshells also show promise as light-triggered gene therapy vectors, adding temporal control to the spatial control characteristic of nanoparticle-based gene therapy approaches. We describe the fabrication of DNA-conjugated nanoshell complexes and compare the efficiency of light-induced and thermally-induced release of DNA. Double-stranded DNA nanoshells also provide a way to deliver small molecules into cells: we describe the delivery and light-triggered release of DAPI (4',6-diamidino-2-phenylindole), a dye molecule used to stain DNA in the nuclei of cells.