HCN channels enhance spike phase coherence and regulate the phase of spikes and LFPs in the theta-frequency range

What are the implications for the existence of subthreshold ion channels, their localization profiles, and plasticity on local field potentials (LFPs)? Here, we assessed the role of hyperpolarization-activated cyclic-nucleotide-gated (HCN) channels in altering hippocampal theta-frequency LFPs and the associated spike phase. We presented spatiotemporally randomized, balanced theta-modulated excitatory and inhibitory inputs to somatically aligned, morphologically realistic pyramidal neuron models spread across a cylindrical neuropil. We computed LFPs from seven electrode sites and found that the insertion of an experimentally constrained HCN-conductance gradient into these neurons introduced a location- dependent lead in the LFP phase without significantly altering its amplitude. Further, neurons fired action potentials at a specific theta phase of the LFP, and the insertion of HCN channels introduced large lags in this spike phase and a striking enhancement in neuronal spike-phase coherence. Importantly, graded changes in either HCN conductance or its half-maximal activation voltage resulted in graded changes in LFP and spike phases. Our conclusions on the impact of HCN channels on LFPs and spike phase were invariant to changes in neuropil size, to morphological heterogeneity, to excitatory or inhibitory synaptic scaling, and to shifts in the onset phase of inhibitory inputs. Finally, we selectively abolished the inductive lead in the impedance phase introduced by HCN channels without altering neuronal excitability and found that this inductive phase lead contributed significantly to changes in LFP and spike phase. Our results uncover specific roles for HCN channels and their plasticity in phase-coding schemas and in the formation and dynamic reconfiguration of neuronal cell assemblies.

Analytical approach to quantile estimation in regional frequency analysis based on fuzzy framework

Regional frequency analysis is widely used for estimating quantiles of hydrological extreme events at sparsely gauged/ungauged target sites in river basins. It involves identification of a region (group of watersheds) resembling watershed of the target site, and use of information pooled from the region to estimate quantile for the target site. In the analysis, watershed of the target site is assumed to completely resemble watersheds in the identified region in terms of mechanism underlying generation of extreme event. In reality, it is rare to find watersheds that completely resemble each other. Fuzzy clustering approach can account for partial resemblance of watersheds and yield region(s) for the target site. Formation of regions and quantile estimation requires discerning information from fuzzy-membership matrix obtained based on the approach. Practitioners often defuzzify the matrix to form disjoint clusters (regions) and use them as the basis for quantile estimation. The defuzzification approach (DFA) results in loss of information discerned on partial resemblance of watersheds. The lost information cannot be utilized in quantile estimation, owing to which the estimates could have significant error. To avert the loss of information, a threshold strategy (TS) was considered in some prior studies. In this study, it is analytically shown that the strategy results in under-prediction of quantiles. To address this, a mathematical approach is proposed in this study and its effectiveness in estimating flood quantiles relative to DFA and TS is demonstrated through Monte-Carlo simulation experiments and case study on Mid-Atlantic water resources region, USA. (C) 2015 Elsevier B.V. All rights reserved.

Oriented nanometric aggregates of partially inverted zinc ferrite: One-step processing and tunable high-frequency magnetic properties

In this work, it is demonstrated that the in situ growth of oriented nanometric aggregates of partially inverted zinc ferrite can potentially pave a way to alter and tune magnetocrystalline anisotropy that, in turn, dictates ferromagnetic resonance frequency (f(FMR)) by inducing strain due to aggregation. Furthermore, the influence of interparticle interaction on magnetic properties of the aggregates is investigated. Mono-dispersed zinc ferrite nanoparticles (<5 nm) with various degrees of aggregation were prepared through decomposition of metal-organic compounds of zinc (II) and iron (III) in an alcoholic solution under controlled microwave irradiation, below 200 degrees C. The nanocrystallites were found to possess high degree of inversion (>0.5). With increasing order of aggregation in the samples, saturation magnetization (at 5 K) is found to decrease from 38 emu/g to 24 emu/g, while coercivity is found to increase gradually by up to 100% (525 Oe to 1040 Oe). Anisotropy-mediated shift of f(FMR) has also been measured and discussed. In essence, the result exhibits an easy way to control the magnetic characteristics of nanocrystalline zinc ferrite, boosted with significant degree of inversion, at GHz frequencies. (C) 2015 AIP Publishing LLC.

Decreasing intensity of monsoon low-frequency intraseasonal variability over India

Understanding the changing nature of the intraseasonal oscillatory (ISO) modes of Indian summer monsoon manifested by active and break phase, and their association with extreme rainfall events are necessary for probabilistic estimation of flood-related risks in a warming climate. Here, using ground-based observed rainfall, we define an index to measure the strength of monsoon ISOs and show that the relative strength of the northward-propagating low-frequency ISO (20-60 days) modes have had a significant decreasing trend during the past six decades, possibly attributed to the weakening of large-scale circulation in the region during monsoon season. This reduction is compensated by a gain in synoptic-scale (3-9 days) variability. The decrease in low-frequency ISO variability is associated with a significant decreasing trend in the percentage of extreme events during the active phase of the monsoon. However, this decrease is balanced by significant increasing trends in the percentage of extreme events in the break and transition phases. We also find a significant rise in the occurrence of extremes during early and late monsoon months, mainly over eastern coastal regions. Our study highlights the redistribution of rainfall intensity among periodic (low-frequency) and non-periodic (extreme) modes in a changing climate scenario.

Soft Real Time Implementation of a Cognitive Radio Testbed for Frequency Hopping Primary Satisfying QoS Requirements

The Cognitive Radio (CR) is a promising technology which provides a novel way to subjugate the issue of spectrum underutilization caused due to the fixed spectrum assignment policies. In this paper we report the design and implementation of a soft-real time CR MAC, consisting of multiple secondary users, in a frequency hopping (Fit) primary scenario. This MAC is capable of sensing the spectrum and dynamically allocating the available frequency bands to multiple CR users based on their QoS requirements. As the primary is continuously hopping, a method has also been implemented to detect the hop instant of the primary network. Synchronization usually requires real time support, however we have been able to achieve this with a soft-real time technique which enables a fully software implementation of CR MAC layer. We demonstrate the wireless transmission and reception of video over this CR testbed through opportunistic spectrum access. The experiments carried out use an open source software defined radio package called GNU Radio and a basic radio hardware component USRP.

Microwave absorbers designed from PVDF/SAN blends containing multiwall carbon nanotubes anchored cobalt ferrite via a pyrene derivative

Lightweight and flexible electromagnetic shielding materials were designed by selectively localizing multiwall carbon nanotubes (MWNTs) anchored magnetic nanoparticles in melt mixed co-continuous blends of polyvinylidene fluoride (PVDF) and poly(styrene-co-acrylonitrile) (SAN). In order to facilitate better dispersion, the MWNTs were modified using pyrenebutyric acid (PBA) via pi-pi stacking. While one of the two-targeted properties, i.e., high electrical conductivity, was achieved by PBA modified MWNTs, high magnetic loss was accomplished by introducing nickel (NF) or cobalt ferrites (CF). Moreover, the attenuation by absorption can be tuned either by using NF (58% absorption) or CF (64% absorption) in combination with PBA-MWNTs. More interestingly, when CF was anchored on to MWNTs via the pyrene derivative, the minimum reflection loss attained was -55 dB in the Ku band (12-18 GHz) frequency and with a large bandwidth. In addition, the EM waves were blocked mostly by absorption (70%). This study opens new avenues in designing flexible and lightweight microwave absorbers.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Engineering nanostructured polymer blends with controlled nanoparticle location for excellent microwave absorption: a compartmentalized approach

In order to obtain better materials, control over the precise location of nanoparticles is indispensable. It is shown here that ordered arrangements of nanoparticles, possessing different characteristics (electrical/ magnetic dipoles), in the blend structure can result in excellent microwave absorption. This is manifested from a high reflection loss of ca. -67 dB for the best blend structure designed here. To attenuate electromagnetic radiation, the key parameters of high electrical conductivity and large dielectric/magnetic loss are targeted here by including a conductive material multiwall carbon nanotubes, MWNTs], ferroelectric nanostructured material with associated relaxations in the GHz frequency barium titanate, BT] and lossy ferromagnetic nanoparticles nickel ferrite, NF]. In this study, bi-continuous structures were designed using 50/50 (by wt) blends of polycarbonate (PC) and polyvinylidene fluoride (PVDF). The MWNTs were modified using an electron acceptor molecule, a derivative of perylenediimide, which facilitates p-p stacking with the nanotubes and stimulates efficient charge transport in the blends. The nanoscopic materials have specific affinity towards the PVDF phase. Hence, by introducing surface-active groups, an ordered arrangement can be tailored. To accomplish this, both BT and NF were first hydroxylated followed by the introduction of amine-terminal groups on the surface. The latter facilitated nucleophilic substitution reactions with PC and resulted in their precise location. In this study, we have shown for the first time that by a compartmentalized approach, superior EM attenuation can be achieved. For instance, when the nanoparticles were localized exclusively in the PVDF phase or in both the phases, the minimum reflection losses were ca. -18 dB (for the MWNT/BT mixture) and -29 dB (for the MWNT/NF mixture), and the shielding occurred primarily through reflection. Interestingly, by adopting the compartmentalized approach wherein the lossy materials were in the PC phase and the conductive materials (MWNT) were in the PVDF phase, outstanding reflection losses of ca. -57 dB (for the BT and MWNT combination) and -67 dB (for the NF and MWNT combination) were noted and the shielding occurred primarily through absorption. Thus, the approach demonstrates that nanoscopic structuring in the blends can be achieved under macroscopic processing conditions and this strategy can further be explored to design microwave absorbers.

Engineering Nanostructures by Decorating Magnetic Nanoparticles onto Graphene Oxide Sheets to Shield Electromagnetic Radiations

In this study, a minimum, reflection loss of 70 a was achieved, for a 6 mm thick shield (at 17.1 GHz frequency) employing a unique approach. This was accomplished by engineering nanostructures through decoration of magnetic nanopartides (nickel, Ni) onto graphene oxide (GO) sheets. Enhanced electromagnetic (EM) shielding was derived by selectively, localizing the nanoscopic particles in a specific phase of polyethylene (PE)/poly(ethylene oxide) (PEO) blends. By introduction of a conducting inclusion (like multiwall carbon nanotubes, MWNTs) together with the engineered nanostructures (nickel-decorated GO, (GO-Ni), the shielding efficiency can be enhanced significantly in contrast to physically mixing the particles in the blends. For instance, the composites showed a shielding efficiency >25 dB for a combination of MWNTS (3 wt %) and Ni nanoparticles (52 wt %) in PE/PEO blends. However, similar shielding effectiveness could be achieved for a combination of MWNTs (3 wt %) and 10 vol % of GO-Ni where in the effective concentration of Ni was only 19 wt %. The GO-Ni sheets facilitated in an efficient charge transfer as manifested from high electrical conductivity in the blends besides enhancing the permeability in the blends. It is envisioned that GO is simultaneously reduced in the process of synthesizing GO-Ni, and this facilitated in efficient charge transfer between the neighboring CNTs. More interestingly, the blends With MWNTs/GO-Ni attenuated the incoming EM radiation mostly by absorption. This study opens new avenues in designing polyolefin-based lightweight shielding materials by engineering nanostructures for numerous applications.

Cultivation of Pleurotus spp. on a combination of anaerobically digested plant material and various agro-residues

Two species of Pleurotus, Pleurotus florida and Pleurotus flabellatus were cultivated on two agro-residues (paddy straw; PS and coir pith; CP) singly as well as in combination with biogas digester residue (BDR, main feed leaf biomass). The biological efficiency, nutritional value, composition and nutrient balance (C, N and P) achieved with these substrates were studied. The most suitable substrate that produced higher yields and biological efficiency was PS mixed with BDR followed by coir pith with BDR. Addition of BDR with agro-residues could increase mushroom yield by 20-30%. The biological efficiency achieved was high for PS + BDR (231.93% for P. florida and 209.92% for P. flabellatus) and for CP + BDR (14831% for P. florida and 188.46% for P. flabellatus). The OC (organic carbon), TKN (nitrogen) and TP (phosphate) removal of the Pleurotus spp. under investigation suggests that PS with BDR is the best substrate for growing mushroom. (C) 2015 Published by Elsevier Inc. on behalf of International Energy Initiative.

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Biodiesel Exhaust Treatment with HFAC Plasma supported by Red Mud: Study on DeNOx and power consumption

The concentration of Nitrogen Oxides (NOx) in engines which use biodiesel as fuel is higher compared to conventional diesel engine exhaust. In this paper, an attempt has been made to treat this exhaust using a combination of High frequency AC (HFAC) plasma and an industrial waste, Red Mud which shows proclivity towards Nitrogen dioxide (NO2) adsorption. The high frequency AC source in combination with the proposed compact double dielectric plasma reactors is relatively more efficient in converting Nitric Oxide (NO) to NO2. It has been shown that the plasma treated gas enhances the activity of red mud as an adsorbent/catalyst and about 60-72% NOx removal efficiency was observed at a specific energy of 250 J/L. The advantage in this method is the cost effectiveness and abundant availability of the waste red mud in the industry. Further, power estimation studies were carried out using Manley's equation for the two reactors employed in the experiment and a close agreement between experimental and predicted powers was observed. (C) 2015 The Authors. Published by Elsevier Ltd.

Combination of Cyanine Behaviour and Giant Hyperpolarisability in Novel Merocyanine Dyes: Beyond the Bond Length Alternation (BLA) Paradigm

Merocyanine dyes that exhibit antithetic cyaninelike behaviour and giant first-order hyperpolarisability (beta) values have been designed. These cyanine-type dyes open up an intriguing route towards molecular-based electrooptic materials as well as new second-harmonic generation dyes for imaging.

Chronic lung infection by Pseudomonas aeruginosa biofilm is cured by L-Methionine in combination with antibiotic therapy

Bacterial biofilms are associated with 80-90% of infections. Within the biofilm, bacteria are refractile to antibiotics, requiring concentrations >1,000 times the minimum inhibitory concentration. Proteins, carbohydrates and DNA are the major components of biofilm matrix. Pseudomonas aeruginosa (PA) biofilms, which are majorly associated with chronic lung infection, contain extracellular DNA (eDNA) as a major component. Herein, we report for the first time that L-Methionine (L-Met) at 0.5 mu M inhibits Pseudomonas aeruginosa (PA) biofilm formation and disassembles established PA biofilm by inducing DNase expression. Four DNase genes (sbcB, endA, eddB and recJ) were highly up-regulated upon L-Met treatment along with increased DNase activity in the culture supernatant. Since eDNA plays a major role in establishing and maintaining the PA biofilm, DNase activity is effective in disrupting the biofilm. Upon treatment with L-Met, the otherwise recalcitrant PA biofilm now shows susceptibility to ciprofloxacin. This was reflected in vivo, in the murine chronic PA lung infection model. Mice treated with L-Met responded better to antibiotic treatment, leading to enhanced survival as compared to mice treated with ciprofloxacin alone. These results clearly demonstrate that L-Met can be used along with antibiotic as an effective therapeutic against chronic PA biofilm infection.