Differential Cocrystallization Behavior of Isomeric Pyridine Carboxamides toward Antitubercular Drug Pyrazinoic Acid

Pyrazinoic acid, the active form of the antitubercular pro-drug Pyrazinamide, is an amphiprotic molecule containing carboxylic acid and pyridine groups and therefore can form both salts and cocrystals with relevant partner molecules. Cocrystallization of pyrazinoic acid with isomeric pyridine carboxamide series resulted in a dimorphic mixed-ionic complex with isonicotinamide and in eutectics with nicotinamide and picolinamide, respectively. It is observed that with alteration of the carboxamide position, steric and electrostatic compatibility issues between molecules of the combination emerge and affect intermolecular interactions and supramolecular growth, thus leading to either cocrystal or eutectic for different pyrazinoic acid-pyridine carboxamide combinations. Intermolecular interaction energy calculations have been performed to understand the role of underlying energetics on the formation of cocrystal/eutectic in different combinations. On the other hand, two molecular salts with piperazine and cytosine and a gallic acid cocrystal of the drug were obtained, and their X-ray crystal structures were also determined in this work.

Low-Wear High-Friction Behavior of Copper Matrix Composites Dispersed With an In Situ Polymer Derived Ceramic

We show that copper-matrix composites that contain 20 vol. % of an in situ processed, polymer-derived, ceramic phase constituted from Si-C-N have unusual friction-and-wear properties. They show negligible wear despite a coefficient of friction (COF) that approaches 0.7. This behavior is ascribed to the lamellar structure of the composite such that the interlamellar regions are infused with nanoscale dispersion of ceramic particles. There is significant hardening of the composite just adjacent to the wear surface by severe plastic deformation.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

Compressive flow behavior of Al-Si based alloy: Role of heat treatment

The flow characteristics of a near eutectic Al-Si based cast alloy have been examined in compression at strain rates varying from 3 x 10(-4) to 10(2) s(-1) and at three different temperatures, i.e., room temperature (RT), 100 degrees C and 200 degrees C. The dependence of the flow behavior on heat treatment is studied by testing the alloy in non-heat treated (NHT) and heat treated (HT) conditions. The heat treatment has strong influence on strain rate sensitivity (SRS), strength and work hardening behavior of the alloy. It is observed that the strength of the alloy increases with increase in strain rate and it increases more rapidly above the strain rate of 10(-1) s(-1) in HT condition at all the temperatures, and at 100 degrees C and 200 degrees C in NHT condition. The thermally dependent process taking place in the HT matrix is responsible for the observed greater SRS in HT condition. The alloy in HT condition exhibits a larger work hardening rate than in NHT condition during initial stages of straining. However, the hardening rate decreases more sharply at higher strains in HT condition due to precipitate shearing and higher rate of Si particle fracture. Thermal hardening is observed at 200 degrees C in NHT condition due to precipitate formation, which results in increased SRS at higher temperatures. Thermal softening is observed in HT condition at 200 C due to precipitate coarsening, which leads to a decrease in SRS at higher temperatures. Stress simulations by a finite element method support the experimentally observed particle and matrix fracture behavior. A negative SRS and serrated flow are observed in the lower strain rate regime (3 x 10(-4)-10(-2) s(-1)) at RT and 100 degrees C, in both NHT and HT conditions. The observations show that both dynamic strain aging (DSA) and precipitate shearing play a role in serrated flow. (C) 2015 Elsevier B.V. All rights reserved.

Adaptive Mesh Refinement for Fast Convergence of EFIE-Based 3-D Extraction

3-D full-wave method of moments (MoM) based electromagnetic analysis is a popular means toward accurate solution of Maxwell's equations. The time and memory bottlenecks associated with such a solution have been addressed over the last two decades by linear complexity fast solver algorithms. However, the accurate solution of 3-D full-wave MoM on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretization may not be fine enough to capture spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates a large number of solution variables and therefore requires an unnecessarily large matrix solution. In this paper, different refinement criteria are studied in an adaptive mesh refinement platform. Consequently, the most suitable conductor mesh refinement criterion for MoM-based electromagnetic package-board extraction is identified and the advantages of this adaptive strategy are demonstrated from both accuracy and speed perspectives. The results are also compared with those of the recently reported integral equation-based h-refinement strategy. Finally, a new methodology to expedite each adaptive refinement pass is proposed.

Electrochemical behavior of Zn-graphene composite coatings

A Zn-graphene composite coating was electrodeposited on mild steel. The graphene was synthesized by electrochemical exfoliation of graphite. Electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction techniques were used to characterize the coatings. Compared to a pure Zn coating, the Zn-graphene coating exhibited reduced grain size, reduced surface defects, hillock structures over the coating surface and an altered texture. The corrosion behavior of the coatings was examined by Tafel polarization and electrochemical impedance spectroscopic methods. A significant improvement in the corrosion resistance in terms of reduction in corrosion current and corrosion rate and increase in polarization resistance was noted in the case of the Zn coating containing graphene.

Orotic acid as a useful supramolecular synthon for the fabrication of an OPV based hydrogel: stoichiometry dependent injectable behavior

A facile hydrogelation of a p-pyridylenevinylene derivative (PV) bearing oxyethylene chains in the presence of orotic acid (OA) occurs via various non-covalent interactions. Depending on the PV: OA molar ratio, the hydrogel shows vesicle to either cluster-type aggregate or fiber transformation. Visual color tuning, stimuli-responsiveness and injectable properties of the hydrogel are also observed.

Adaptive executions of hyperbolic block-structured AMR applications on GPU systems

A block-structured adaptive mesh refinement (AMR) technique has been used to obtain numerical solutions for many scientific applications. Some block-structured AMR approaches have focused on forming patches of non-uniform sizes where the size of a patch can be tuned to the geometry of a region of interest. In this paper, we develop strategies for adaptive execution of block-structured AMR applications on GPUs, for hyperbolic directionally split solvers. While effective hybrid execution strategies exist for applications with uniform patches, our work considers efficient execution of non-uniform patches with different workloads. Our techniques include bin-packing work units to load balance GPU computations, adaptive asynchronism between CPU and GPU executions using a knapsack formulation, and scheduling communications for multi-GPU executions. Our experiments with synthetic and real data, for single-GPU and multi-GPU executions, on Tesla S1070 and Fermi C2070 clusters, show that our strategies result in up to a 3.23 speedup in performance over existing strategies.

Adaptive Pulse Width Control and Sampling for Low Power Pulse Oximetry

Remote sensing of physiological parameters could be a cost effective approach to improving health care, and low-power sensors are essential for remote sensing because these sensors are often energy constrained. This paper presents a power optimized photoplethysmographic sensor interface to sense arterial oxygen saturation, a technique to dynamically trade off SNR for power during sensor operation, and a simple algorithm to choose when to acquire samples in photoplethysmography. A prototype of the proposed pulse oximeter built using commercial-off-the-shelf (COTS) components is tested on 10 adults. The dynamic adaptation techniques described reduce power consumption considerably compared to our reference implementation, and our approach is competitive to state-of-the-art implementations. The techniques presented in this paper may be applied to low-power sensor interface designs where acquiring samples is expensive in terms of power as epitomized by pulse oximetry.

Rheological Behavior of Al-7Si-0.3Mg Alloy at Mushy State

In recent years, semisolid manufacturing has emerged as an attractive option for near net shape forming of components with aluminum alloys. In this class of processes, the key to success lies mainly in the understanding of rheological behavior of the semi-solid slurry in the temperature range between liquidus and solidus. The present study focuses on the non-Newtonian flow behavior of the pseudo plastic slurry of Al-7Si-0.3Mg alloy for a wide shear range using a high-temperature Searle-type rheometer. The rheological behavior of the slurry is studied with respect to relevant process variables and microstructural features such as shear rate, shear duration, temperature history, primary particle size, shape, and their distribution. The experiments performed are isothermal tests, continuous cooling tests, shear jump tests, and shear time tests. The continuous cooling experiments are aimed toward studying the viscosity and shear stress evolution within the slurry matrix with increasing solid fraction at a constant shear rate. Three different cooling rates are considered and their effect on flow behavior of the slurry was studied under iso-shear condition. Descending shear jump experiments are performed to understand the viscous instability of the slurry.

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.

Conceptualization of a Behavior Modification Tool for University Systems and Doctoral Students

This paper describes a university based system relevant to doctoral students who have problems with themselves, their peers and research supervisors. Doctoral students have various challenges to solve and these challenges contribute to delays in their thesis submission. This tool aims at helping them think through their problem in a pre-counseling stage. The tool uses narratives and hypothetical stories to walk a doctoral student through options of responses he or she can make given the situation in the narrative. Narratives were developed after a preliminary survey (n=57) of doctoral students. The survey indicated that problems they experienced were: busy supervisors, negative competition from peers and laziness with self. The narrative scenarios in the tool prompt self-reflection and provide for options to chose from leading to the next scenario that will ensue. The different stages of the stimulus-response cycles are designed based on Thomas-Kilmann conflict resolution techniques (collaboration and avoidance). Each stimulus-response cycle has a score attached that reflects the student's ability to judge a collaborative approach. At the end of all the stages a scorecard is generated indicating either a progressive or regressive outcome of thesis submission.

Effects of Interface Treatment on the Fatigue Behavior of Shape Memory Alloy Reinforced Polymer Composites

Interfacial properties of Shape Memory Alloy (SMA) reinforced polymer matrix composites can be enhanced by improving the interfacial bonding. This paper focuses on studying the interfacial stresses developed in the SMA-epoxy interface due to various laser shot penning conditions. Fiber-pull test-setup is designed to understand the role of mechanical bias stress cycling and thermal actuation cycling. Phase transformation is tracked over mechanical and thermal fatigue cycles. A micromechanics based model developed earlier based on shear lag in SMA and energy based consistent homogenization is extended here to incorporate the stress-temperature phase diagram parameters for modeling fatigue.

Mapping the intriguing transient morphologies and the demixing behavior in PS/PVME blends in the presence of rod-like nanoparticles

The demixing behavior, transient morphologies and mechanism of phase separation in PS/PVME blends were greatly altered in the presence of a very low concentration of rod-like particles (multiwall carbon nanotubes, MWNTs). This phenomenon is due to the specific interaction of one of the phases (PVME) with the anisotropic MWNTs, which creates a heterogeneous environment in the blend. This specific interaction alters the chain dynamics in the interfacial region as against the bulk. A comprehensive analysis using isochronal temperature sweep was performed to understand the demixing temperature in the blends. The evolution of phase morphology as a function of time and temperature was assessed by polarizing optical microscopy (POM), atomic force microscopy (AFM) and scanning electron microscopy (SEM). The addition of MWNTs increased the rheological demixing temperature and the spinodal temperature in almost all the compositions. The intriguing transient morphologies were mapped, which varied from nucleation and growth to coalescence-induced viscoelastic phase separation (C-VPS) in PVME-rich blends, to spinodal decomposition in the near-critical compositions, to transient gel-induced VPS (T-VPS) in the PS-rich compositions. Mapping of the morphology development displayed two types of fracture mechanisms: ductile fracture for near-critical compositions and brittle fracture for off-critical composition. The change in the phase separation mechanism in the presence of MWNTs was due to the variation in dynamic asymmetry brought about by these anisotropic particles. All these observations were correlated by POM, SEM and AFM studies. The length of the cooperatively rearranging region (CRR), as evaluated using modulated differential scanning calorimetry (MDSC) measurements, was found to be composition-independent. The observed variation of effective glass transition of PVME (low T-g component) on blending with PS (high Tg component) and by the addition of MWNTs accounts for the dynamic heterogeneity introduced by MWNTs in the system.

Dynamic compression behavior of reactive spark plasma sintered ultrafine grained (Hf, Zr)B-2-SiC composites

This paper reports the dynamic compression behavior of ultrafine grained (Hf, Zr)B-2-SiC composites, sintered using reactive spark plasma sintering at 1600 degrees C for 10 min. Dynamic strength of similar to 2.3 GPa has been measured using Split Hopkinson Pressure Bar (SHPB) tests in a reproducible manner at strain rates of 800-1300 s(-1). A comparison with competing boride based armor ceramics, in reference to the spectrum of properties evaluated, establishes the potential of (Hf, Zr)B-2-SiC composites for armor applications. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved.