Fracture processes of self compacting Concrete using image analysis

The mode I fracture toughness of concrete can be experimentally determined using three point bend beam in conjunction with digital image correlation (DIC). Three different geometrically similar sizes of beams are cast for this study. To study the influence of fly ash and silica fume on fracture toughness of SCC, three SCC mixes are prepared with and without mineral additions. The scanning electron microscope (SEM) images are taken on the fractured surface to add information on fracture process in SCC. From this study, it is concluded that the fracture toughness of SCC with mineral addition is higher when compared to those without mineral addition.

Discrimination of alpha-Amino Acids Using Green Tea Flavonoid (-)-Epigallocatechin Gallate as a Chiral Solvating Agent

We report a special, hitherto-unexplored property of (-)-epigallocatechin gallate (EGCG) as a chiral solvating agent for enantiodiscrimination of alpha-amino acids in the polar solvent DMSO. This phenomenon has been investigated by H-1 NMR spectroscopy. The mechanism of the interaction property of EGCG with alpha-amino acids has been understood as arising out of hydrogen-bonded noncovalent interactions, where the -OH groups of two phenyl rings of EGCG play dominant roles. The conversion of the enantiomeric mixture into diastereomers yielded well-resolved peaks for D and L amino acids permitting the precise measurement of enantiomeric composition. Often one encounters complex situations when the spectra are severely overlapped or partially resolved hampering the testing of enantiopurity and the precise measurement of enantiomeric excess (ee). Though higher concentration of EGCG yielded better discrimination, the use of lower concentration being economical, we have exploited an appropriate 2D NMR experiment in overcoming such problems. Thus, in the present study we have successfully demonstrated the utility of the bioflavonoid (-)-EGCG, a natural product as a chiral solvating agent for the discrimination of large number of alpha-amino acids in a polar solvent DMSO. Another significant advantage of this new chiral sensing agent is that it is a natural product and does not require tedious multistep synthesis unlike many other chiral auxiliaries.

Green synthesis of polysaccharide/gold nanoparticle nanocomposite: An efficient ammonia sensor

A low cost eco-friendly method for the synthesis of gold nanoparticles (AuNPs) using guar gum (GG) as a reducing agent is reported. The nanoparticles obtained are characterized by UV-vis spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD). Based on these results, a potential mechanism for this method of AuNPs synthesis is discussed. GG/AuNPs nanocomposite (GG/AuNPs NC) was exploited for optical sensor for detection of aqueous ammonia based on surface plasmon resonance (SPR). It was found to have good reproducibility, response times of similar to 10 s and excellent sensitivity with a detection limit of 1 ppb (parts-per-billion). This system allows the rapid production of an ultra-low-cost GG/AuNPs NC-based aqueous ammonia sensor.

A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.

Some implications of lepton flavor violating processes in a supersymmetric Type II seesaw model at TeV scale

We have conceived a supersymmetric Type II seesaw model at TeV scale, which has some additional particles consisting of scalar and fermionic triplet Higgs states, whose masses are around a few hundred GeV. In this particular model, we have studied constraints on the masses of triplet states arising from the lepton flavor violating (LFV) processes, such as mu -> 3e and mu -> e gamma. We have analyzed the implications of these constraints on other observable quantities such as the muon anomalous magnetic moment and the decay patterns of scalar triplet Higgses. Scalar triplet Higgs states can decay into leptons and into supersymmetric fields. We have found that the constraints from LFV can affect these various decay modes.

Power-optimal scheduling for a green base station with delay constraints

We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.

Flow cytometry analysis of human fetal osteoblast fate processes on spark plasma sintered hydroxyapatite-titanium biocomposites

Hydroxyapatite (HA)-based biocomposites have been widely investigated for a multitude of applications and these studies have been largely driven to improve mechanical properties (toughness and strength) without compromising cytocompatibility properties. Apart from routine cell viability/proliferation analysis, limited efforts have been made to quantify the fate processes (cell proliferation, cell cycle, and cell apoptosis) of human fetal osteoblast (hFOB) cells on HA-based composites, in vitro. In this work, the osteoblast cell fate process has been studied on a model hydroxyapatite-titanium (HA-Ti) system using the flow cytometry. In order to retain both HA and Ti, the novel processing technique, that is, spark plasma sintering, was suitably adopted. The cell fate processes of hFOBs, as evaluated using a flow cytometry, revealed statistically insignificant differences among HA-10 wt % Ti and HA and control (tissue culture polystyrene surface) in terms of osteoblast apoptosis, proliferation index as well as division index. For the first time, we provide quantified flow cytometry results to demonstrate that 10 wt % Ti additions to HA do not have any significant influence on the fate processes of human osteoblast-like cells, in vitro.

Does lean imply green?: a study of the power performance implications of Java runtime bloat

The presence of software bloat in large flexible software systems can hurt energy efficiency. However, identifying and mitigating bloat is fairly effort intensive. To enable such efforts to be directed where there is a substantial potential for energy savings, we investigate the impact of bloat on power consumption under different situations. We conduct the first systematic experimental study of the joint power-performance implications of bloat across a range of hardware and software configurations on modern server platforms. The study employs controlled experiments to expose different effects of a common type of Java runtime bloat, excess temporary objects, in the context of the SPECPower_ssj2008 workload. We introduce the notion of equi-performance power reduction to characterize the impact, in addition to peak power comparisons. The results show a wide variation in energy savings from bloat reduction across these configurations. Energy efficiency benefits at peak performance tend to be most pronounced when bloat affects a performance bottleneck and non-bloated resources have low energy-proportionality. Equi-performance power savings are highest when bloated resources have a high degree of energy proportionality. We develop an analytical model that establishes a general relation between resource pressure caused by bloat and its energy efficiency impact under different conditions of resource bottlenecks and energy proportionality. Applying the model to different "what-if" scenarios, we predict the impact of bloat reduction and corroborate these predictions with empirical observations. Our work shows that the prevalent software-only view of bloat is inadequate for assessing its power-performance impact and instead provides a full systems approach for reasoning about its implications.

Mechanism design for green, truthful procurement auctions

Auction based mechanisms have become popular in industrial procurement settings. These mechanisms minimize the cost of procurement and at the same time achieve desirable properties such as truthful bidding by the suppliers. In this paper, we investigate the design of truthful procurement auctions taking into account an additional important issue namely carbon emissions. In particular, we focus on the following procurement problem: A buyer wishes to source multiple units of a homogeneous item from several competing suppliers who offer volume discount bids and who also provide emission curves that specify the cost of emissions as a function of volume of supply. We assume that emission curves are reported truthfully since that information is easily verifiable through standard sources. First we formulate the volume discount procurement auction problem with emission constraints under the assumption that the suppliers are honest (that is they report production costs truthfully). Next we describe a mechanism design formulation for green procurement with strategic suppliers. Our numerical experimentation shows that emission constraints can significantly alter sourcing decisions and affect the procurement costs dramatically. To the best of our knowledge, this is the first effort in explicitly taking into account carbon emissions in planning procurement auctions.

Validation based sparse Gaussian processes for ordinal regression

This paper proposes a sparse modeling approach to solve ordinal regression problems using Gaussian processes (GP). Designing a sparse GP model is important from training time and inference time viewpoints. We first propose a variant of the Gaussian process ordinal regression (GPOR) approach, leave-one-out GPOR (LOO-GPOR). It performs model selection using the leave-one-out cross-validation (LOO-CV) technique. We then provide an approach to design a sparse model for GPOR. The sparse GPOR model reduces computational time and storage requirements. Further, it provides faster inference. We compare the proposed approaches with the state-of-the-art GPOR approach on some benchmark data sets. Experimental results show that the proposed approaches are competitive.

Combining ``chimie douce'' and green principles for the developing world: Improving industrial viability of photocatalytic water remediation

We highlight the need for a comprehensive, multi-disciplinary approach for the development of cost-effective water remediation methods. Combining ``chimie douce'' and green chemical principles seems essential for making these technologies economically viable and socially relevant (especially in the developing world). A comprehensive approach to water remediation will take into account issues such as nanotoxicity, chemical yield, cost, and ease of deployment in reactors. By considering technological challenges that lie ahead, we will attempt to identify directions that are likely to make photocatalytic water remediation a more global technology than it currently is. (C) 2013 Elsevier Ltd. All rights reserved

Plant latex mediated green synthesis of ZnAl2O4:Dy3+ (1-9 mol%) nanophosphor for white light generation

ZnAl2O4:Dy3+ (1-9 mol%) nanophosphors were synthesized by a simple, cost effective and environmental friendly route using Euphorbia tirucalli plant latex. The structural properties and morphological features of the phosphors were well studied by PXRD, FTIR, SEM and TEM measurements. The luminescent properties of ZnAl2O4:Dy3+ (1-9 mol%) nanophosphors were investigated from the excitation and emission spectra. The phosphor performance was evaluated by color co-ordinates. The values were well located in the near white region as a result it was highly useful for the fabrication of green component in WLEDs. The average particle size was found to be similar to 9-18 nm and same was confirmed by TEM and Scherrer's method. The highest photoluminescence (PL) and thermoluminescence (TL) intensity was obtained to be similar to 7 mol% Dy3+ concentration. A single TL glow peak was recorded at 172 degrees C at a warming rate of 2.5 degrees Cs (1). The intensity at 172 degrees C peak increases linearly up to 1 kGy and after that it diminishes. PL intensity was studied with different plant latex concentration (2-8 ml) and highest PL intensity was recorded for similar to 8 ml. The optimized phosphor showed good reusability, low fading and wide range of linearity with gamma-dose hence the phosphor was quite useful in radiation dosimetry. (C) 2013 Elsevier B.V. All rights reserved.

Particle size, morphology and color tunable ZnO:Eu3+ nanophosphors via plant latex mediated green combustion synthesis

Efficient ZnO:Eu3+ (1-11 mol%) nanophosphors were prepared for the first time by green synthesis route using Euphorbia tirucalli plant latex. The final products were well characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), etc. The average particle size of ZnO:Eu3+ (7 mol%) was found to be in the range 27-47 nm. With increase of plant latex, the particle size was reduced and porous structure was converted to spherical shaped particles. Photoluminescence (PL) spectra indicated that the peaks situated at similar to 590, 615, 648 and 702 nm were attributed to the D-5(0) -> F-7(j(j=1,2,3,4)) transitions of Eu3+ ions. The highest PL intensity was recorded for 7 mol% with Eu3+ ions and 26 ml plant latex concentration. The PL intensity increases with increase of plant latex concentration up to 30 ml and there after it decreases. The phosphor prepared by this method show spherical shaped particles, excellent chromaticity co-ordinates in the white light region which was highly useful for WLED's. Further, present method was reliable, environmentally friendly and alternative to economical routes. (c) 2013 Elsevier B.V. All rights reserved.

Purifying water containing both anionic and cationic species using a (Zn, Cu)O, ZnO, and Cobalt Ferrite based multiphase adsorbent system

For the purpose of water purification, novel and low-cost adsorbents which are promising replacements for activated carbon are being actively pursued. However, a single-phase material that adsorbs both cationic and anionic species remains elusive. Hence, a low-cost, multiphase adsorbent bed that purifies water containing both anionic and cationic pollutants is a desirable alternative. We choose anionic (Congo red, Orange G) and cationic (methylene blue, malachite green) dyes as model pollutants. These dyes are chosen since they are widely found in effluents from textile, leather, fishery, and pharmaceutical industries, and their carcinogenic, mutagenic, genotoxic, and cytotoxic impact on mammalian cells is well-established. We show that ZnO, (Zn0.24Cu0.76)O and cobalt ferrite based multiphase fixed adsorbent bed efficiently adsorbs model anionic (Congo red, Orange G) and cationic (methylene blue and malachite green) pollutants, and their complex mixtures. All adsorbent phases are synthesized using room-temperature, high-yield (similar to 96-100%), green chemical processes. The nanoadsorbents are characterized by using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area analysis, and zeta potential measurements. The constituent nanophases are deliberately chosen to be beyond 50 nm, in order to avoid the nanotoxic size regime of oxides. Adsorption characteristics of each of the phases are examined. Isotherm based analysis shows that adsorption is both spontaneous and highly favorable. zeta potential measurements indicate that electrostatic interactions are the primary driving force for the observed adsorption behavior. The isotherms obtained are best described using a composite Langmuir-Freundlich model. Pseudo-first-order, rapid kinetics is observed (with adsorption rate constants as high as 0.1-0.2 min(-1) in some cases). Film diffusion is shown to be the primary mechanism of adsorption.

AIPE-active green phosphorescent iridium(III) complex impregnated test strips for the vapor-phase detection of 2,4,6-trinitrotoluene (TNT)

Detection of explosives, especially trinitrotoluene (TNT), is of utmost importance due to its highly explosive nature and environmental hazard. Therefore, detection of TNT has been a matter of great concern to the scientific community worldwide. Herein, a new aggregation-induced phosphorescent emission (AIPE)-active iridium(III) bis(2-(2,4-difluorophenyl)pyridinato-NC2') (2-(2-pyridyl)benzimidazolato-N,N') complex FIrPyBiz] has been developed and serves as a molecular probe for the detection of TNT in the vapor phase, solid phase, and aqueous media. In addition, phosphorescent test strips have been constructed by impregnating Whatman filter paper with aggregates of FIrPyBiz for trace detection of TNT in contact mode, with detection limits in nanograms, by taking advantage of the excited state interaction of AIPE-active phosphorescent iridium(III) complex with that of TNT and the associated photophysical properties.