Discrete-Rate Adaptation and Selection in Energy Harvesting Wireless Systems

In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.

A delocalizable cationic headgroup together with an oligo-oxyethylene spacer in gemini cationic lipids improves their biological activity as vectors of plasmid DNA

Lipoplex nano-aggregates constituted of plasmid DNA (pDNA) pEGFP-C3 and mixed cationic liposomes, consisting of several percentages of a gemini cationic lipid (GCL) of the 1,2-bis(hexadecyl imidazolium) oxyethylene series, referred to as (C(16)Im)(2)(C2O)(n), with oxyethylene spacers (n = 1, 2 or 3) between the imidazolium cationic groups and the DOPE zwitterionic helper lipid, have been characterized by various biophysical and biological approaches carried out at several GCL compositions (alpha), and either the mass or the effective charge ratio of the lipoplex. The electrochemical study by zeta-potential confirms that the three GCLs yield a 10% lower effective charge than the nominal one, while compacted pDNA yields only a 25% effective negative charge. The SAXS study reveals, irrespective of the spacer length (n) and effective charge ratio (rho(eff)), the presence of two lamellar structures, i.e., one (L-alpha,L-main) in the whole GCL composition and another (L-alpha,L-DOPE,L-rich) with higher periodicity values that coexists with the previous one at low GCL composition (alpha = 0.2). The cryo-TEM analysis shows two types of multilamellar structures consisting of cationic lipidic bilayers with pDNA sandwiched between them: a cluster-type (C-type) at low alpha = 0.2 and a fingerprint-type (FP-type) at alpha >= 0.5, both with similar interlamellar spacing (d) in agreement with the L-alpha,L-main structure determined by SAXS. Transfection efficacies (TEs) of each lipid mixture were determined in four different cell lines (HEK293T, HeLa, Caco-2 and A549) at several alpha and rho(eff) values in the absence and presence of serum (FBS). The optimized formulations (alpha = 0.2 and rho(eff) = 2.0) substantially transfect cells much better than a commercial transfection reagent, Lipofectamine 2000 and previously studied efficient lipoplexes containing other cationic head groups or spacers both in the absence and presence of serum. The activity of optimized formulations may be attributed to the combination of several factors, such as: (a) the fusogenic character of DOPE which results in higher fluidity of the lipoplexes at alpha = 0.2, (b) the coexistence of two lamellar structures at alpha = 0.2 that synergizes the TE of these lipid vectors, and mainly (c) the higher biocompatibility of the GCLs reported in this work due to the presence of two imidazolium cationic groups together with an oligo-oxyethylene spacer. The length of the spacer in the GCL seems to have less impact, although (C(16)Im)(2)(C2O)(n)/DOPEpDNA lipoplexes with n = 1 and 3 show higher gene transfection than n = 2. All the optimum formulations reported herein are all highly efficient with negligible levels of toxicity, and thus, may be considered as very promising gene vectors for in vivo applications.

Active Viscoelastic Matter: From Bacterial Drag Reduction to Turbulent Solids

A paradigm for internally driven matter is the active nematic liquid crystal, whereby the equations of a conventional nematic are supplemented by a minimal active stress that violates time-reversal symmetry. In practice, active fluids may have not only liquid-crystalline but also viscoelastic polymer degrees of freedom. Here we explore the resulting interplay by coupling an active nematic to a minimal model of polymer rheology. We find that adding a polymer can greatly increase the complexity of spontaneous flow, but can also have calming effects, thereby increasing the net throughput of spontaneous flow along a pipe (a ``drag-reduction'' effect). Remarkably, active turbulence can also arise after switching on activity in a sufficiently soft elastomeric solid.

Calcium Permeable AMPA Receptor-Dependent Long Lasting Plasticity of Intrinsic Excitability in Fast Spiking Interneurons of the Dentate Gyrus Decreases Inhibition in the Granule Cell Layer

The local fast-spiking interneurons (FSINs) are considered to be crucial for the generation, maintenance, and modulation of neuronal network oscillations especially in the gamma frequency band. Gamma frequency oscillations have been associated with different aspects of behavior. But the prolonged effects of gamma frequency synaptic activity on the FSINs remain elusive. Using whole cell current clamp patch recordings, we observed a sustained decrease of intrinsic excitability in the FSINs of the dentate gyrus (DG) following repetitive stimulations of the mossy fibers at 30 Hz (gamma bursts). Surprisingly, the granule cells (GCs) did not express intrinsic plastic changes upon similar synaptic excitation of their apical dendritic inputs. Interestingly, pairing the gamma bursts with membrane hyperpolarization accentuated the plasticity in FSINs following the induction protocol, while the plasticity attenuated following gamma bursts paired with membrane depolarization. Paired pulse ratio measurement of the synaptic responses did not show significant changes during the experiments. However, the induction protocols were accompanied with postsynaptic calcium rise in FSINs. Interestingly, the maximum and the minimum increase occurred during gamma bursts with membrane hyperpolarization and depolarization respectively. Including a selective blocker of calcium-permeable AMPA receptors (CP-AMPARs) in the bath; significantly attenuated the calcium rise and blocked the membrane potential dependence of the calcium rise in the FSINs, suggesting their involvement in the observed phenomenon. Chelation of intracellular calcium, blocking HCN channel conductance or blocking CP-AMPARs during the experiment forbade the long lasting expression of the plasticity. Simultaneous dual patch recordings from FSINs and synaptically connected putative GCs confirmed the decreased inhibition in the GCs accompanying the decreased intrinsic excitability in the FSINs. Experimentally constrained network simulations using NEURON predicted increased spiking in the GC owing to decreased input resistance in the FSIN. We hypothesize that the selective plasticity in the FSINs induced by local network activity may serve to increase information throughput into the downstream hippocampal subfields besides providing neuroprotection to the FSINs. (c) 2014 Wiley Periodicals, Inc.

Efficient QR Decomposition Using Low Complexity Column-wise Givens Rotation (CGR)

QR decomposition (QRD) is a widely used Numerical Linear Algebra (NLA) kernel with applications ranging from SONAR beamforming to wireless MIMO receivers. In this paper, we propose a novel Givens Rotation (GR) based QRD (GR QRD) where we reduce the computational complexity of GR and exploit higher degree of parallelism. This low complexity Column-wise GR (CGR) can annihilate multiple elements of a column of a matrix simultaneously. The algorithm is first realized on a Two-Dimensional (2 D) systolic array and then implemented on REDEFINE which is a Coarse Grained run-time Reconfigurable Architecture (CGRA). We benchmark the proposed implementation against state-of-the-art implementations to report better throughput, convergence and scalability.

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.

PriDyn: Enabling Differentiated I/O Services in Cloud Using Dynamic Priorities

Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.

Optimal power allocation for protective jamming in wireless networks: A flow based model

We address the problem of passive eavesdroppers in multi-hop wireless networks using the technique of friendly jamming. The network is assumed to employ Decode and Forward (DF) relaying. Assuming the availability of perfect channel state information (CSI) of legitimate nodes and eavesdroppers, we consider a scheduling and power allocation (PA) problem for a multiple-source multiple-sink scenario so that eavesdroppers are jammed, and source-destination throughput targets are met while minimizing the overall transmitted power. We propose activation sets (AS-es) for scheduling, and formulate an optimization problem for PA. Several methods for finding AS-es are discussed and compared. We present an approximate linear program for the original nonlinear, non-convex PA optimization problem, and argue that under certain conditions, both the formulations produce identical results. In the absence of eavesdroppers' CSI, we utilize the notion of Vulnerability Region (VR), and formulate an optimization problem with the objective of minimizing the VR. Our results show that the proposed solution can achieve power-efficient operation while defeating eavesdroppers and achieving desired source-destination throughputs simultaneously. (C) 2015 Elsevier B.V. All rights reserved.

Automated cell viability assessment using a microfluidics based portable imaging flow analyzer

In this work, we report a system-level integration of portable microscopy and microfluidics for the realization of optofluidic imaging flow analyzer with a throughput of 450 cells/s. With the use of a cellphone augmented with off-the-shelf optical components and custom designed microfluidics, we demonstrate a portable optofluidic imaging flow analyzer. A multiple microfluidic channel geometry was employed to demonstrate the enhancement of throughput in the context of low frame-rate imaging systems. Using the cell-phone based digital imaging flow analyzer, we have imaged yeast cells present in a suspension. By digitally processing the recorded videos of the flow stream on the cellphone, we demonstrated an automated cell viability assessment of the yeast cell population. In addition, we also demonstrate the suitability of the system for blood cell counting. (C) 2015 AIP Publishing LLC.

Calcium binding properties of calcium dependent protein kinase 1 (CaCDPK1) from Cicer arietinum

Calcium plays a crucial role as a secondary messenger in all aspects of plant growth, development and survival. Calcium dependent protein kinases (CDPKs) are the major calcium decoders, which couple the changes in calcium level to an appropriate physiological response. The mechanism by which calcium regulates CDPK protein is not well understood. In this study, we investigated the interactions of Ca2+ ions with the CDPK1 isoform of Cicer arietinum (CaCDPK1) using a combination of biophysical tools. CaCDPK1 has four different EF hands as predicted by protein sequence analysis. The fluorescence emission spectrum of CaCDPK1 showed quenching with a 5 nm red shift upon addition of calcium, indicating conformational changes in the tertiary structure. The plot of changes in intensity against calcium concentrations showed a biphasic curve with binding constants of 1.29 mu M and 120 mu M indicating two kinds of binding sites. Isothermal calorimetric (ITC) titration with CaCl2 also showed a biphasic curve with two binding constants of 0.027 mu M and 1.7 mu M. Circular dichroism (CD) spectra showed two prominent peaks at 208 and 222 nm indicating that CaCDPK1 is a alpha-helical rich protein. Calcium binding further increased the alpha-helical content of CaCDPK1 from 75 to 81%. Addition of calcium to CaCDPK1 also increased fluorescence of 8-anilinonaphthalene-1-sulfonic acid (ANS) indicating exposure of hydrophobic surfaces. Thus, on the whole this study provides evidence for calcium induced conformational changes, exposure of hydrophobic surfaces and heterogeneity of EF hands in CaCDPK1. (C) 2015 Elsevier GmbH. All rights reserved.

Status of the crystallography beamlines at Elettra

Elettra is one of the first 3rd-generation storage rings, recently upgraded to routinely operate in top-up mode at both 2.0 and 2.4 GeV. The facility hosts four dedicated beamlines for crystallography, two open to the users and two under construction, and expected to be ready for public use in 2015. In service since 1994, XRD1 is a general-purpose diffraction beamline. The light source for this wide (4-21 keV) energy range beamline is a permanent magnet wiggler. XRD1 covers experiments ranging from grazing incidence X-ray diffraction to macromolecular crystallography, from industrial applications of powder diffraction to X-ray phasing with long wavelengths. The bending magnet powder diffraction beamline MCX has been open to users since 2009, with a focus on microstructural investigations and studies under non-ambient conditions. A superconducting wiggler delivers a high photon flux to a new fully automated beamline dedicated to macromolecular crystallography and to a branch beamline hosting a high-pressure powder X-ray diffraction station (both currently under construction). Users of the latter experimental station will have access to a specialized sample preparation laboratory, shared with the SISSI infrared beamline. A high throughput crystallization platform equipped with an imaging system for the remote viewing, evaluation and scoring of the macromolecular crystallization experiments has also been established and is open to the user community.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

Curcumin Pyrazole and its derivative (N-(3-Nitrophenylpyrazole) Curcumin inhibit aggregation, disrupt fibrils and modulate toxicity of Wild type and Mutant alpha-Synuclein

Accumulating evidence suggests that deposition of neurotoxic a-synuclein aggregates in the brain during the development of neurodegenerative diseases like Parkinson's disease can be curbed by anti-aggregation strategies that either disrupt or eliminate toxic aggregates. Curcumin, a dietary polyphenol exhibits anti-amyloid activity but the use of this polyphenol is limited owing to its instability. As chemical modifications in curcumin confiscate this limitation, such efforts are intensively performed to discover molecules with similar but enhanced stability and superior properties. This study focuses on the inhibitory effect of two stable analogs of curcumin viz. curcumin pyrazole and curcumin isoxazole and their derivatives against a-synuclein aggregation, fibrillization and toxicity. Employing biochemical, biophysical and cell based assays we discovered that curcumin pyrazole (3) and its derivative N-(3-Nitrophenylpyrazole) curcumin (15) exhibit remarkable potency in not only arresting fibrillization and disrupting preformed fibrils but also preventing formation of A11 conformation in the protein that imparts toxic effects. Compounds 3 and 15 also decreased neurotoxicity associated with fast aggregating A53T mutant form of a-synuclein. These two analogues of curcumin described here may therefore be useful therapeutic inhibitors for the treatment of a-synuclein amyloidosis and toxicity in Parkinson's disease and other synucleinopathies.

Molecular dynamics insight to phase transition in n-alkanes with carbon nanofillers

The present work aims to investigate the phase transition, dispersion and diffusion behavior of nanocomposites of carbon nanotube (CNT) and straight chain alkanes. These materials are potential candidates for organic phase change materials(PCMs) and have attracted flurry of research recently. Accurate experimental evaluation of the mass, thermal and transport properties of such composites is both difficult as well as economically taxing. Additionally it is crucial to understand the factors that results in modification or enhancement of their characteristic at atomic or molecular level. Classical molecular dynamics approach has been extended to elucidate the same. Bulk atomistic models have been generated and subjected to rigorous multistage equilibration. To reaffirm the approach, both canonical and constant-temperature, constant-pressure ensembles were employed to simulate the models under consideration. Explicit determination of kinetic, potential, non-bond and total energy assisted in understanding the enhanced thermal and transport property of the nanocomposites from molecular point of view. Crucial parameters including mean square displacement and simulated self diffusion coefficient precisely define the balance of the thermodynamic and hydrodynamic interactions. Radial distribution function also reflected the density variation, strength and mobility of the nanocomposites. It is expected that CNT functionalization could improve the dispersion within n-alkane matrix. This would further ameliorate the mass and thermal properties of the composite. Additionally, the determined density was in good agreement with experimental data. Thus, molecular dynamics can be utilized as a high throughput technique for theoretical investigation of nanocomposites PCMs. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Hemagglutinin sequence conservation guided stem immunogen design from influenza A H3 subtype

Seasonal epidemics caused by influenza A (H1 and H3 subtypes) and B viruses are a major global health threat. The traditional, trivalent influenza vaccines have limited efficacy because of rapid antigenic evolution of the circulating viruses. This antigenic variability mediates viral escape from the host immune responses, necessitating annual vaccine updates. Influenza vaccines elicit a protective antibody response, primarily targeting the viral surface glycoprotein hemagglutinin (HA). However, the predominant humoral response is against the hypervariable head domain of HA, thereby restricting the breadth of protection. In contrast, the conserved, subdominant stem domain of HA is a potential ``universal'' vaccine candidate. We designed an HA stem-fragment immunogen from the 1968 pandemic H3N2 strain (A/Hong Kong/1/68) guided by a comprehensive H3 HA sequence conservation analysis. The biophysical properties of the designed immunogen were further improved by C-terminal fusion of a trimerization motif, ``isoleucine-zipper'', or ``foldon''. These immunogens elicited cross-reactive, antiviral antibodies and conferred partial protection against a lethal, homologous HK68 virus challenge in vivo. Furthermore, bacterial expression of these immunogens is economical and facilitates rapid scale-up.