COMPARATIVE EVALUATION OF THERMAL CONDUCTIVITY OF ZIRCONIA SOLID AND HONEYCOMB STRUCTURES

Porous zirconia ceramic monoliths have been extensively used in thermo-structural applications due to their inherent low thermal conductivity in combination with their adaptability to form complicated shapes through advanced ceramic processing techniques. However, extruded cellular honeycomb structures made from these materials have been less explored for thermal management applications. There exist large potential applications due to their unique configurations, resulting in better heat-management mechanisms. Some of the studies carried out on zirconia honeycombs are safeguarded through patents due to its technical importance, or the information is not in the public domain. In the present study, for the sake of comparison, honeycomb specimens with varying wall thicknesses and unit cell lengths maintaining almost same bulk density of around 90% theoretical and relative density of 0.34-0.37 were prepared and subjected to thermal conductivity evaluation along with the solid samples with relative density of 1.0 using monotonic heating regime methodology. In addition, the effect of channel shape was also evaluated using square and triangular channeled honeycombs with the same relative densities. The results obtained from these specimens were correlated with their configurations to bring out the advantages accrued by using the honeycomb with these configurations. It was observed that a significant decrease in thermal conductivity was achieved in honeycombs, which can be attributed to the behavior of various heat transfer mechanisms that are operative at high temperatures in combination with the considerable reduction in thermal mass and the consequent conduction through the solids.

Heat Shock Protein 90 Inhibitors as Broad Spectrum Anti-Infectives

Combating stress is one of the prime requirements for any organism. For parasitic microbes, stress levels are highest during the growth inside the host. Their survival depends on their ability to acclimatize and adapt to new environmental conditions. Robust cellular machinery for stress response is, therefore, both critical and essential especially for pathogenic microorganisms. Microbes have cleverly exploited stress proteins as virulence factors for pathogenesis in their hosts. Owing to its ability to sense and respond to the stress conditions, Heat shock protein 90 (Hsp90) is one of the key stress proteins utilized by parasitic microbes. There are growing evidences for the critical role played by Hsp90 in the growth of pathogenic organisms like Candida, Giardia, Plasmodium, Trypanosoma, and others. This review, therefore, explores potential of exploiting Hsp90 as a target for the treatment of infectious diseases. This molecular chaperone has already gained attention as an effective anti-cancer drug target. As a result, a lot of research has been done at laboratory, preclinical and clinical levels for several Hsp90 inhibitors as potential anti-cancer drugs. In addition, lot of data pertaining to toxicity studies, pharmacokinetics and pharmacodynamics studies, dosage regime, drug related toxicities, dose limiting toxicities as well as adverse drug reactions are available for Hsp90 inhibitors. Therefore, repurposing/repositioning strategies are also being explored for these compounds which have gone through advanced stage clinical trials. This review presents a comprehensive summary of current status of development of Hsp90 as a drug target and its inhibitors as candidate anti-infectives. A particular emphasis is laid on the possibility of repositioning strategies coupled with pharmaceutical solutions required for fulfilling needs for ever growing pharmaceutical infectious disease market.

Design and synthesis of positional isomers of 5 and 6-bromo-1-(phenyl)sulfonyl]-2-(4-nitrophenoxy)methyl]-1H-benzimida zoles as possible antimicrobial and antitubercular agents

In this Letter, we report the structure activity relationship (SAR) studies on series of positional isomers of 5(6)-bromo-1-(phenyl)sulfonyl]-2-(4-nitrophenoxy)methyl]-1H-benzim idazoles derivatives 7(a-j) and 8(a j) synthesized in good yields and characterized by H-1 NMR, C-13 NMR and mass spectral analyses. The crystal structure of 7a was evidenced by X-ray diffraction study. The newly synthesized compounds were evaluated for their in vitro antibacterial activity against Staphylococcus aureus, (Gram-positive), Escherichia coil and Klebsiella pneumoniae (Gram-negative), antifungal activity against Candida albicans, Aspergillus flavus and Rhizopus sp. and antitubercular activity against Mycobacterium tuberculosis H37Rv, Mycobacterium smegmatis, Mycobacterium fortuitum and MDR-TB strains. The synthesized compounds displayed interesting antimicrobial activity. The compounds 7b, 7e and 7h displayed significant activity against Mycobacterium tuberculosis H37Rv strain.

Average Modelling of a Voltage Source Inverter with Dead-Time in a Synchronous Reference Frame

Voltage source inverters are an integral part of renewable power sources and smart grid systems. Computationally efficient and fairly accurate models for the voltage source inverter are required to carry out extensive simulation studies on complex power networks. Accuracy requires that the effect of dead-time be incorporated in the inverter model. The dead-time is essentially a short delay introduced between the gating pulses to the complementary switches in an inverter leg for the safety of power devices. As the modern voltage source inverters switch at fairly high frequencies, the dead-time significantly influences the output fundamental voltage. Dead-time also causes low-frequency harmonic distortion and is hence important from a power quality perspective. This paper studies the dead-time effect in a synchronous dq reference frame, since dynamic studies and controller design are typically carried out in this frame of reference. For the sake of computational efficiency, average models are derived, incorporating the dead-time effect, in both RYB and dq reference frames. The average models are shown to consume less computation time than their corresponding switching models, the accuracies of the models being comparable. The proposed average synchronous reference frame model, including effect of dead-time, is validated through experimental results.

Biogenic nanosilver incorporated reverse osmosis membrane for antibacterial and antifungal activities against selected pathogenic strains: An enhanced eco-friendly water disinfection approach

Reverse osmosis (RO) membranes have been used extensively in water desalination plants, waste water treatment in industries, agricultural farms and drinking water production applications. The objective of this work is to impart antibacterial and antifungal activities to commercially available RO membrane used in water purification systems by incorporating biogenic silver nanoparticles (AgNPs) synthesized using Rosa indica wichuriana hybrid leaf extract. The morphology and surface topography of uncoated and AgNPs-coated RO membrane were studied using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Elemental composition of the AgNPs-coated RO membrane was analyzed by energy-dispersive X-ray spectroscopy (EDAX). The functional groups were identified by Fourier Transform Infrared spectroscopy (FT-IR). Hydrophilicity of the uncoated and AgNPs-coated RO membrane was analyzed using water contact angle measurements. The thermal properties were studied by thermogravimetric analysis (TGA). The AgNPs incorporated RO membrane exhibited good antibacterial and antifungal activities against pathogenic bacterial strains such as E. coli, S. aureus, M. luteus, K. pneumoniae, and P. aeruginosa and fungal strains such as Candida tropicalis, C. krusei, C. glabrata, and C. albicans.

Trm1p, a Zn(II)(2)Cys(6)-type transcription factor, is essential for the transcriptional activation of genes of methanol utilization pathway, in Pichia pastoris

The zinc finger transcription factors Mxr1p and Rop are key regulators of methanol metabolism in the methylotrophic yeast, Pichia pastoris, while Trm1p and Trm2p regulate methanol metabolism in Candida boidinii. Here, we demonstrate that Trm1p is essential for the expression of genes of methanol utilization (mut) pathway in P. pastoris as well. Expression of AOXI and other genes of mut pathway is severely compromised in P. pastoris Delta Trm1 strain resulting in impaired growth on media containing methanol as the sole source of carbon. Trm1p localizes to the nucleus of cells cultured on glucose or methanol. The zinc finger domain of Mxr1p but not Trm1p binds to AOXI promoter sequences in vitro, indicating that these two positive regulators act by different mechanisms. We conclude that both Trm1p and Mxr1p are essential for the expression of genes of mut pathway in P. pastoris and the mechanism of transcriptional regulation of mut pathway may be similar in P. pastoris and C. boidinii. (C) 2014 Elsevier Inc. All rights reserved.

Two timescale convergent Q-learning for sleep-scheduling in wireless sensor networks

In this paper, we consider an intrusion detection application for Wireless Sensor Networks. We study the problem of scheduling the sleep times of the individual sensors, where the objective is to maximize the network lifetime while keeping the tracking error to a minimum. We formulate this problem as a partially-observable Markov decision process (POMDP) with continuous stateaction spaces, in a manner similar to Fuemmeler and Veeravalli (IEEE Trans Signal Process 56(5), 2091-2101, 2008). However, unlike their formulation, we consider infinite horizon discounted and average cost objectives as performance criteria. For each criterion, we propose a convergent on-policy Q-learning algorithm that operates on two timescales, while employing function approximation. Feature-based representations and function approximation is necessary to handle the curse of dimensionality associated with the underlying POMDP. Our proposed algorithm incorporates a policy gradient update using a one-simulation simultaneous perturbation stochastic approximation estimate on the faster timescale, while the Q-value parameter (arising from a linear function approximation architecture for the Q-values) is updated in an on-policy temporal difference algorithm-like fashion on the slower timescale. The feature selection scheme employed in each of our algorithms manages the energy and tracking components in a manner that assists the search for the optimal sleep-scheduling policy. For the sake of comparison, in both discounted and average settings, we also develop a function approximation analogue of the Q-learning algorithm. This algorithm, unlike the two-timescale variant, does not possess theoretical convergence guarantees. Finally, we also adapt our algorithms to include a stochastic iterative estimation scheme for the intruder's mobility model and this is useful in settings where the latter is not known. Our simulation results on a synthetic 2-dimensional network setting suggest that our algorithms result in better tracking accuracy at the cost of only a few additional sensors, in comparison to a recent prior work.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Lower Bound Axisymmetric Limit Analysis Using Drucker-Prager Yield Cone and Simulation with Mohr-Coulomb Pyramid

This paper presents a lower bound limit analysis approach for solving an axisymmetric stability problem by using the Drucker-Prager (D-P) yield cone in conjunction with finite elements and nonlinear optimization. In principal stress space, the tip of the yield cone has been smoothened by applying the hyperbolic approximation. The nonlinear optimization has been performed by employing an interior point method based on the logarithmic barrier function. A new proposal has also been given to simulate the D-P yield cone with the Mohr-Coulomb hexagonal yield pyramid. For the sake of illustration, bearing capacity factors N-c, N-q and N-gamma have been computed, as a function of phi, both for smooth and rough circular foundations. The results obtained from the analysis compare quite well with the solutions reported from literature.

Sonic hedgehog-responsive lipoxygenases and cyclooxygenase-2 modulate Dectin-1-induced inflammatory cytokines

Immune responses during fungal infections are predominately mediated by 5/15-lipoxygenases (LO)-or cyclooxygenase (COX)-2-catalysed bioactive eicosanoid metabolites like leukotrienes, lipoxins and prostaglandins. Although few host mediators of fungi-triggered eicosanoid production have been established, the molecular mechanism of expression and regulation of 5-LO, 15-LO and COX-2 are not well-defined. Here, we demonstrate that, macrophages infected with representative fungi Candida albicans, Aspergillus flavus or Aspergillus fumigatus or those treated with Curdlan, a selective agonist of pattern recognition receptor for fungi Dectin-1, displays increased expression of 5-LO, 15-LO and COX-2. Interestingly, Dectin-1-responsive Syk pathway activates mTOR-sonic hedgehog (SHH) signaling cascade to stimulate the expression of these lipid metabolizing enzymes. Loss-of-function analysis of the identified intermediaries indicates that while Syk-mTOR-SHH pathway-induced 5-LO and 15-LO suppressed the Dectin-l-responsive pro-inflammatory signature cytokines like TNE-alpha, IL-1 beta and IL-12, Syk-mTOR-SHH-induced COX-2 positively regulated these cytokines. Dectin-1-stimulated IL-6, however, is dependent on 5-LO, 15-LO and COX-2 activity. Together, the current study establishes Dectin-1-arbitrated host mediators that direct the differential regulation of immune responses during fungal infections and thus are potential candidates of therapeutic intervention. (C) 2015 Elsevier Ltd. All rights reserved.