Using heat treatment effects and EBSD analysis to tailor microstructure of hybrid Mg nanocomposite for enhanced overall mechanical response

In this study, a detailed investigation on the effect of heat treatment on the microstructural characteristics, texture evolution and mechanical properties of Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite is presented. Optimised heat treatment parameters, namely, heat treatment temperature and heat treatment time, were first identified through grain size and microhardness measurements. Initially, heat treatment of composites was conducted at temperature range between 100 and 300 degrees C for 1 h. Based on optical microscopic analysis and microhardness measurements, it was evident that significant grain growth and reduction in microhardness occurred for temperatures > 200 degrees C. The cutoff temperature that caused significant grain growth/matrix softening was thus identified. Second, at constant temperature (200 degrees C), the effect of variation of heat treatment time was carried out (ranging between 1 and 5 h) so as to identify the range wherein increase in average grain size and reduction in microhardness occurred. Furthering the study, the effect of optimised heat treatment parameters (200 degrees C, 5 h) on the microstructural texture evolution and hence, on the tensile and compressive properties of the Mg-(5.6Ti+2.5B(4)C)(BM) hybrid nanocomposite was carried out. From electron backscattered diffraction (EBSD) analysis, it was identified that the optimised heat treatment resulted in recrystallisation and residual stress relaxation, as evident from the presence of similar to 87% strain free grains, when compared to that observed in the non-heat treated/as extruded condition (i.e. 2.2 times greater than in the as extruded condition). For the heat treated composite, under both tensile and compressive loads, a significant improvement in fracture strain values (similar to 60% increase) was observed when compared to that of the non-heat treated counterpart, with similar to 20% reduction in yield strength. Based on structure-property correlation, the change in mechanical characteristics is identified to be due to: (1) the presence of less stressed matrix/reinforcement interface due to the relief of residual stresses and (2) texture weakening due to matrix recrystallisation effects, both arising due to heat treatment.

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.

Lipid coated mesoporous silica nanoparticles as an oral delivery system for targeting and treatment of intravacuolar Salmonella infections

Lipid coated mesoporous silica nanoparticle (L-MSN) were synthesized for oral delivery of ciprofloxacin for intracellular elimination of Salmonella pathogen. The particle size was found to be between 50-100 nm with a lipid coat of approximately 5 nm thickness. The lipid coating was achieved by sonication of liposomes with the MSN particles and evaluated by CLSMand FTIR studies. The L-MSN particles exhibited lower cytotoxicity compared to bare MSN particles. Ciprofloxacin, a fluoroquinolone antibiotic, loaded into the L-MSN particles showed enhanced antibacterial activity against free drug in in vitro assays. The lipid coat was found to aid in intravacuolar targeting of the drug cargo as observed by confocal microscopy studies. We also observed that a lower dose of antibiotic was sufficient to clear the pathogen from mice and increase their survivability using the L-MSN oral delivery system.

Development, in vitro and in vivo characterization of zoledronic acid functionalized hydroxyapatite nanoparticle based formulation for treatment of osteoporosis in animal model

We investigated the potential of using novel zoledronic acid (ZOL)-hydroxyapatite (HA) nanoparticle based drug formulation in a rat model of postmenopausal osteoporosis. By a classical adsorption method, nanoparticles of HA loaded with ZOL (HNLZ) drug formulation with a size range of 100-130 nm were prepared. 56 female Wistar rats were ovariectomized (OVX) or sham-operated at 3 months of age. Twelve weeks post surgery, rats were randomized into seven groups and treated with various doses of HNLZ (100, 50 and 25 mu g/kg, intravenous single dose), ZOL (100 mu g/kg, intravenous single dose) and HA nanoparticle (100 mu g/kg, intravenous single dose). Untreated OVX and sham OVX served as controls. After three months treatment period, we evaluated the mechanical properties of the lumbar vertebra and femoral mid-shaft. Femurs were also tested for trabecular microarchitecture. Sensitive biochemical markers of bone formation and bone resorption in serum were also determined. With respect to improvement in the mechanical strength of the lumbar spine and the femoral mid-shaft, the therapy with HNLZ drug formulation was more effective than ZOL therapy in OVX rats. Moreover, HNLZ drug therapy preserved the trabecular microarchitecture better than ZOL therapy in OVX rats. Furthermore, the HNLZ drug formulation corrected increase in serum levels of bone-specific alkaline phosphatase, procollagen type I N-terminal propeptide, osteocalcin, tartrate-resistant acid phosphatase 5b and C-telopeptide of type 1 collagen better than ZOL therapy in OVX rats. The results strongly suggest that HNLZ novel drug formulation appears to be more effective approach for treating severe osteoporosis in humans. (C) 2014 Elsevier B.V. All rights reserved.

Novel multimeric IL-1 receptor antagonist for the treatment of rheumatoid arthritis

Protein therapeutics targeting inflammatory mediators have shown great promise for the treatment of autoimmunities such as rheumatoid arthritis (RA). However, a significant challenge in this area has been their low in vivo stability and consequently their severely compromised therapeutic efficacy. One such therapeutic molecule IL-1 receptor antagonist (IL-1ra), used in the treatment of rheumatoid arthritis, has displayed only modest efficacy in human clinical trials owing to its short biological half-life. Herein, we report a novel approach to conglomerate individual protein entities into a drug depot by incorporation of an amyloidogenic motif Lys-Phe-Phe-Glu (KFFE) thereby dramatically improving their systemic persistence and in turn their therapeutic efficacy in a mice model of autoimmune arthritis. (C) 2014 Elsevier Ltd. All rights reserved.

Absence of systemic toxicity in mouse model towards BaTiO3 nanoparticulate based eluate treatment

One of the existing issues in implant failure of orthopedic biomaterials is the toxicity induced by the fine particles released during long term use in vivo, leading to acute inflammatory response. In developing a new class of piezobiocomposite to mimic the integrated electrical and mechanical properties of bone, bone-mimicking physical properties as well as in vitro cytocompatibility properties have been achieved with spark plasma sintered hydroxyapatite (HA)-barium titanate (BaTiO3) composites. However, the presence of BaTiO3 remains a concern towards the potential toxicity effect. To address this issue, present work reports the first result to conclusively confirm the non-toxic effect of HA-BaTiO3 piezobiocomposite nanoparticulates, in vivo. Twenty BALB/c mice were intraarticularly injected at their right knee joints with different concentrations of HA-BaTiO3 composite of up to 25 mg/ml. The histopathological examination confirmed the absence of any trace of injected particles or any sign of inflammatory reaction in the vital organs, such as heart, spleen, kidney and liver at 7 days post-exposure period. Rather, the injected nanoparticulates were found to be agglomerated in the vicinity of the knee joint, surrounded by macrophages. Importantly, the absence of any systemic toxicity response in any of the vital organs in the treated mouse model, other than a mild local response at the site of delivery, was recorded. The serum biochemical analyses using proinflammatory cytokines (TNF-alpha and IL-1 beta) also complimented to the non-immunogenic response to injected particulates. Altogether, the absence of any inflammatory/ adverse reaction will open up myriad of opportunities for BaTiO3 based piezoelectric implantable devices in biomedical applications.

A Distributed TDMA Slot Scheduling Algorithm for Spatially Correlated Contention in WSNs

In WSNs the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting simultaneously. Such a situation is known as spatially correlated contention. The random access method to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration, and therefore generating an optimal or suboptimal schedule is not very useful. Additionally, if an algorithm takes very long time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. In this paper, we present a distributed TDMA slot scheduling (DTSS) algorithm, which considerably reduces the time required to perform scheduling, while restricting the schedule length to the maximum degree of interference graph. The DTSS algorithm supports unicast, multicast, and broadcast scheduling, simultaneously without any modification in the protocol. We have analyzed the protocol for average case performance and also simulated it using Castalia simulator to evaluate its runtime performance. Both analytical and simulation results show that our protocol is able to considerably reduce the time required for scheduling.

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.

Low Complexity Power and Scheduling Policies for Wireless Networks to Provide Quality of Service

We consider optimal power allocation policies for a single server, multiuser system. The power is consumed in transmission of data only. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity.

Performance of OFDM Systems With Best-m Feedback, Scheduling, and Delays for Uniformly Correlated Subchannels

Contemporary cellular standards, such as Long Term Evolution (LTE) and LTE-Advanced, employ orthogonal frequency-division multiplexing (OFDM) and use frequency-domain scheduling and rate adaptation. In conjunction with feedback reduction schemes, high downlink spectral efficiencies are achieved while limiting the uplink feedback overhead. One such important scheme that has been adopted by these standards is best-m feedback, in which every user feeds back its m largest subchannel (SC) power gains and their corresponding indices. We analyze the single cell average throughput of an OFDM system with uniformly correlated SC gains that employs best-m feedback and discrete rate adaptation. Our model incorporates three schedulers that cover a wide range of the throughput versus fairness tradeoff and feedback delay. We show that, for small m, correlation significantly reduces average throughput with best-m feedback. This result is pertinent as even in typical dispersive channels, correlation is high. We observe that the schedulers exhibit varied sensitivities to correlation and feedback delay. The analysis also leads to insightful expressions for the average throughput in the asymptotic regime of a large number of users.

An Implementation of Partitioned Scheduling Scheme for Hard Real-Time Tasks in Multicore Linux with Fair Share for Linux Tasks

The correctness of a hard real-time system depends its ability to meet all its deadlines. Existing real-time systems use either a pure real-time scheduler or a real-time scheduler embedded as a real-time scheduling class in the scheduler of an operating system (OS). Existing implementations of schedulers in multicore systems that support real-time and non-real-time tasks, permit the execution of non-real-time tasks in all the cores with priorities lower than those of real-time tasks, but interrupts and softirqs associated with these non-real-time tasks can execute in any core with priorities higher than those of real-time tasks. As a result, the execution overhead of real-time tasks is quite large in these systems, which, in turn, affects their runtime. In order that the hard real-time tasks can be executed in such systems with minimal interference from other Linux tasks, we propose, in this paper, an integrated scheduler architecture, called SchedISA, which aims to considerably reduce the execution overhead of real-time tasks in these systems. In order to test the efficacy of the proposed scheduler, we implemented partitioned earliest deadline first (P-EDF) scheduling algorithm in SchedISA on Linux kernel, version 3.8, and conducted experiments on Intel core i7 processor with eight logical cores. We compared the execution overhead of real-time tasks in the above implementation of SchedISA with that in SCHED_DEADLINE's P-EDF implementation, which concurrently executes real-time and non-real-time tasks in Linux OS in all the cores. The experimental results show that the execution overhead of real-time tasks in the above implementation of SchedISA is considerably less than that in SCHED_DEADLINE. We believe that, with further refinement of SchedISA, the execution overhead of real-time tasks in SchedISA can be reduced to a predictable maximum, making it suitable for scheduling hard real-time tasks without affecting the CPU share of Linux tasks.

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.

Additive effect of zoledronic acid and alfacalcidol in the treatment of disuse osteoporosis in rats

Objectives: Disuse by bed rest, limb immobilization or space flight causes rapid bone loss. We conducted the present study to investigate the therapeutic effects of zoledronic acid (ZOL), alone and in combination with alfacalcidol (ALP) in a rat model of disuse osteoporosis. Methods: In the present study, 3-month-old male Wistar rats had their right hind-limb immobilized (RHLI) for 10 weeks to induce osteopenia, then were divided into four groups: 1 - RHLI positive control; 2 - RHLI plus ZOL (50 mu g/kg, i.v. single dose); 3 - RHLI plus ALP (0.5 mu g/kg, oral gauge daily); 4- RHLI plus ALP (0.5 mu g/kg, oral gauge daily) plus ZOL (50 mu g/kg, i.v. single dose) for another 10 weeks. One group of non-immobilized rats was used as negative control. At the end of the treatment, the femurs were removed and tested for bone porosity, bone mechanical properties, and bone dry and ash weight. Results: Combination therapy with ZOL plus ALP was more effective in decreasing bone porosity than each drug administered as monotherapy in RHLI rats. With respect to improvement in the mechanical strength of the femoral mid-shaft, the combination treatment of ZOL plus ALP was more effective than each drug administered as a monotherapy. Moreover, combination therapy using ZOL plus ALF was more effective in improving dry bone and ash weight, than single-drug therapy using ZOL or ALP in RHLI rats. Conclusions: These data suggest that combination therapy with ZOL plus ALP represents a potentially useful therapeutic option for the treatment of disuse osteoporosis. (C) 2014 Elsevier Editora Ltda. All rights reserved.

Wireless scheduling with partial channel state information: large deviations and optimality

We consider a server serving a time-slotted queued system of multiple packet-based flows, where not more than one flow can be serviced in a single time slot. The flows have exogenous packet arrivals and time-varying service rates. At each time, the server can observe instantaneous service rates for only a subset of flows ( selected from a fixed collection of observable subsets) before scheduling a flow in the subset for service. We are interested in queue length aware scheduling to keep the queues short. The limited availability of instantaneous service rate information requires the scheduler to make a careful choice of which subset of service rates to sample. We develop scheduling algorithms that use only partial service rate information from subsets of channels, and that minimize the likelihood of queue overflow in the system. Specifically, we present a new joint subset-sampling and scheduling algorithm called Max-Exp that uses only the current queue lengths to pick a subset of flows, and subsequently schedules a flow using the Exponential rule. When the collection of observable subsets is disjoint, we show that Max-Exp achieves the best exponential decay rate, among all scheduling algorithms that base their decision on the current ( or any finite past history of) system state, of the tail of the longest queue. To accomplish this, we employ novel analytical techniques for studying the performance of scheduling algorithms using partial state, which may be of independent interest. These include new sample-path large deviations results for processes obtained by non-random, predictable sampling of sequences of independent and identically distributed random variables. A consequence of these results is that scheduling with partial state information yields a rate function significantly different from scheduling with full channel information. In the special case when the observable subsets are singleton flows, i.e., when there is effectively no a priori channel state information, Max-Exp reduces to simply serving the flow with the longest queue; thus, our results show that to always serve the longest queue in the absence of any channel state information is large deviations optimal.