Negative hyperconjugation and red-, blue- or zero-shift in X-Z center dot center dot center dot Y complexes

A generalized explanation is provided for the existence of the red-and blue-shifting nature of X-Z bonds (Z = H, halogens, chalcogens, pnicogens, etc.) in X-Z center dot center dot center dot Y complexes based on computational studies on a selected set of weakly bonded complexes and analysis of existing literature data. The additional electrons and orbitals available on Z in comparison to H make for dramatic differences between the H-bond and the rest of the Z-bonds. The nature of the X-group and its influence on the X-Z bond length in the parent X-Z molecule largely controls the change in the X-Z bond length on X-Z center dot center dot center dot Y bond formation; the Y-group usually influences only the magnitude of the effects controlled by X. The major factors which control the X-Z bond length change are: (a) negative hyperconjugative donation of electron density from X-group to X-Z sigma* antibonding molecular orbital (ABMO) in the parent X-Z, (b) induced negative hyperconjugation from the lone pair of electrons on Z to the antibonding orbitals of the X-group, and (c) charge transfer (CT) from the Y-group to the X-Z sigma* orbital. The exchange repulsion from the Y-group that shifts partial electron density at the X-Z sigma* ABMO back to X leads to blue-shifting and the CT from the Y-group to the sigma* ABMO of X-Z leads to red-shifting. The balance between these two opposing forces decides red-, zero- or blue-shifting. A continuum of behaviour of X-Z bond length variation is inevitable in X-Z center dot center dot center dot Y complexes.

Conformational Stability and Intramolecular Hydrogen Bonding in 1,2-Ethanediol and 1,4-Butanediol

The gas-phase infrared spectra of 1,2-ED and 1,4-BD have been, recorded at three different temperatures using a multipass gas cell of 6 m optical path length. DFT calculation has also been carried out using 6-311++G** and aug-cc-pVDZ basis sets to look for the existence of intramolecular hydrogen bonding, in them from the red shift and infrared absorption intensity enhancement of the bonded O-H band compared to that of the free O-H hand. Equilibrium population analysis With 10 conformers of 1,2-ED and 1,4-BD at experimental temperatures were-carried out for the reconstruction of the Observed vibrational spectra at that temperature,using standard statistical relationships. The most abundant conformer at experimental temperatures, was identified. In 1,2-ED a red shift of 45 cm(-1) in the intramolecularly interacting O-H stretching vibrational band position and no significant intensity enhancement compared to that of-the free O-H have been observed. On the contrary, in one of the hydrogen bonded conformers of 1,4-BD, a 124 cm(-1) red shift in the O-H stretching frequency and 8.5 times-intensity enhancement for the ``bonded'' O-H compared to that of the ``free'' O-H is seen. On the basis of this comparative study, we have concluded that strong intramolecular hydrogen bonding exists in 1,4-BD. But there appears, to be weak intramolecular hydrogen bonding in 1,2-ED at temperatures of 303, 313, and 323 Km the gas phase We have found that most stable hydrogen-bonded conformers of 1,4-BD are less populated than some of the non-hydrogen-bonded conformers. Even for the 1,4-BD, the relative population of the g'GG'Gt conformer, which has a strong intramolecular,hydrogen bond, is less than what is predicted. Perhaps the intramolecular hydrogen bond plays a less Significant role in the relative stability,of the various Conformers than what has been predicted from calculations and prevails in the literature.

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.

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.

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.

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.

High Performance Modulation of High-Frequency AC Link Inverter

Inverters with high voltage conversion ratio are used in systems with sources such as batteries, photovoltaic (PV) modules or fuel cells. Transformers are often used in such inverters to provide the required voltage conversion ratio and isolation. In this paper, a compact high-frequency (HF) transformer interfaced AC link inverter with lossless snubber is discussed. A high performance synchronized modulation scheme is proposed for this inverter. This modulation addresses the issue of over-voltage spikes due to transformer leakage inductance and it is shown that the circuit can operate safely even when the turn-on delay, such as dead-time, is not used in the HF rectifier section. The problem of spurious turn-on in the HF inverter switches is also mitigated by the proposed modulation method. The circuit performance is validated experimentally with a $900W$ prototype inverter.

A recursive multi-scaling approach to regional flood frequency analysis

Scaling approaches are widely used by hydrologists for Regional Frequency Analysis (RFA) of floods at ungauged/sparsely gauged site(s) in river basins. This paper proposes a Recursive Multi-scaling (RMS) approach to RFA that overcomes limitations of conventional simple- and multi-scaling approaches. The approach involves identification of a separate set of attributes corresponding to each of the sites (being considered in the study area/region) in a recursive manner according to their importance, and utilizing those attributes to construct effective regional regression relationships to estimate statistical raw moments (SMs) of peak flows. The SMs are then utilized to arrive at parameters of flood frequency distribution and quantile estimate(s) corresponding to target return period(s). Effectiveness of the RMS approach in arriving at flood quantile estimates for ungauged sites is demonstrated through leave-one-out cross-validation experiment on watersheds in Indiana State, USA. Results indicate that the approach outperforms index-flood based Region-of-Influence approach, simple- and multi-scaling approaches and a multiple linear regression method. (C) 2015 Elsevier B.V. All rights reserved.

Evaluation of the Index-Flood Approach Related Regional Frequency Analysis Procedures

Index-flood related regional frequency analysis (RFA) procedures are in use by hydrologists to estimate design quantiles of hydrological extreme events at data sparse/ungauged locations in river basins. There is a dearth of attempts to establish which among those procedures is better for RFA in the L-moment framework. This paper evaluates the performance of the conventional index flood (CIF), the logarithmic index flood (LIF), and two variants of the population index flood (PIF) procedures in estimating flood quantiles for ungauged locations by Monte Carlo simulation experiments and a case study on watersheds in Indiana in the U.S. To evaluate the PIF procedure, L-moment formulations are developed for implementing the procedure in situations where the regional frequency distribution (RFD) is the generalized logistic (GLO), generalized Pareto (GPA), generalized normal (GNO) or Pearson type III (PE3), as those formulations are unavailable. Results indicate that one of the variants of the PIF procedure, which utilizes the regional information on the first two L-moments is more effective than the CIF and LIF procedures. The improvement in quantile estimation using the variant of PIF procedure as compared with the CIF procedure is significant when the RFD is a generalized extreme value, GLO, GNO, or PE3, and marginal when it is GPA. (C) 2015 American Society of Civil Engineers.

Design and implementation of spectrum sensing for cognitive radios with a frequency-hopping primary system

In this work, spectrum sensing for cognitive radios is considered in the presence of multiple Primary Users (PU) using frequency-hopping communication over a set of frequency bands. The detection performance of the Fast Fourier Transform (FFT) Average Ratio (FAR) algorithm is obtained in closed-form, for a given FFT size and number of PUs. The effective throughput of the Secondary Users (SU) is formulated as an optimization problem with a constraint on the maximum allowable interference on the primary network. Given the hopping period of the PUs, the sensing duration that maximizes the SU throughput is derived. The results are validated using Monte Carlo simulations. Further, an implementation of the FAR algorithm on the Lyrtech (now, Nutaq) small form factor software defined radio development platform is presented, and the performance recorded through the hardware is observed to corroborate well with that obtained through simulations, allowing for implementation losses. (C) 2015 Elsevier B.V. All rights reserved.

High frequency millimetre wave absorbers derived from polymeric nanocomposites

The world has dominated by automation, wireless communication and various electronic equipments, which has led to the most undesirable offshoots like electromagnetic (EM) pollution. The rationale is environmental concern and the necessity to develop EM absorbing materials. This paper reviews the state of the art of designing polymer based nanocomposites containing nanoscopic particles with high electrical conductivity and complex microwave properties for enhanced EM attenuation. Given the brevity of this review article, herein we have summarized the high frequency millimetre wave absorbing properties of polymer nanocomposites consisting of various nanoparticles that either reflect or absorb microwave radiation like electrically conducting carbon nanotubes (CNTs) and graphene nanosheets (GNs), high dielectric constant ceramic nanoparticles that show relaxation loss in the microwave frequency and magnetic metal and ferrite nanoparticles that absorb microwave radiation through natural resonance, eddy current and hysteresis losses. Furthermore, we have stressed the necessity and impact of hybrid nanoparticles consisting of magnetic and dielectric nanoparticles along with conducting inclusions like CNT and GNs in this review. Electromagnetic interference (EMI) theory and necessary criterion for attenuation has been briefly discussed. The emphasis is made on various mechanisms towards EM attenuation controlled by these nanoparticles. Various structures developed using polymer nanocomposites like bulk, foam and layered structures and their effect on EM attenuation has been elaborately discussed. In addition, various covalent/non-covalent modifications on nanoparticles have been juxtaposed in context to EM attenuation. In addition, we have highlighted important facets and direction for enhancing the microwave attenuation. (C) 2016 Elsevier Ltd. All rights reserved.

Molecular dynamics and simulations study on the vibrational and electronic solvatochromism of benzophenone

Solvent plays a key role in diverse physico-chemical and biological processes. Therefore, understanding solute-solvent interactions at the molecular level of detail is of utmost importance. A comprehensive solvatochromic analysis of benzophenone (Bzp) was carried out in various solvents using Raman and electronic spectroscopy, in conjunction with Density Functional Theory (DFT) calculations of supramolecular solute-solvent clusters generated using classical Molecular Dynamics Simulations (c-MDSs). The >C=O stretching frequency undergoes a bathochromic shift with solvent polarity. Interestingly, in protic solvents this peak appears as a doublet: c-MDS and ad hoc explicit solvent ab initio calculations suggest that the lower and higher frequency peaks are associated with the hydrogen bonded and dangling carbonyl group of Bzp, respectively. Additionally, the dangling carbonyl in methanol (MeOH) solvent is 4 cm(-1) blue-shifted relative to acetonitrile solvent, despite their similar dipolarity/polarizability. This suggests that the cybotactic region of the dangling carbonyl group in MeOH is very different from its bulk solvent structure. Therefore, we propose that this blue-shift of the dangling carbonyl originates in the hydrophobic solvation shell around it resulting from extended hydrogen bonding network of the protic solvents. Furthermore, the 1(1)n pi* (band I) and 1(1)pi pi* (band II) electronic transitions show a hypsochromic and bathochromic shift, respectively. In particular, these shifts in protic solvents are due to differences in their excited state-hydrogen bonding mechanisms. Additionally, a linear relationship is obtained for band I and the >C=O stretching frequency (cm(-1)), which suggests that the different excitation wavelengths in band I correspond to different solvation states. Therefore, we hypothesize that the variation in excitation wavelengths in band I could arise from different solvation states leading to varying solvation dynamics. This will have implications for ultrafast processes associated with electron-transfer, charge transfer, and also the photophysical aspects of excited states. (C) 2016 AIP Publishing LLC.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

Evaluation and Minimization of Low-Order Harmonic Torque in Low-Switching-Frequency Inverter-Fed Induction Motor Drives

A low-order harmonic pulsating torque is a major concern in high-power drives, high-speed drives, and motor drives operating in an overmodulation region. This paper attempts to minimize the low-order harmonic torques in induction motor drives, operated at a low pulse number (i.e., a low ratio of switching frequency to fundamental frequency), through a frequency domain (FD) approach as well as a synchronous reference frame (SRF) based approach. This paper first investigates FD-based approximate elimination of harmonic torque as suggested by classical works. This is then extended into a procedure for minimization of low-order pulsating torque components in the FD, which is independent of machine parameters and mechanical load. Furthermore, an SRF-based optimal pulse width modulation (PWM) method is proposed to minimize the low-order harmonic torques, considering the motor parameters and load torque. The two optimal methods are evaluated and compared with sine-triangle (ST) PWM and selective harmonic elimination (SHE) PWM through simulations and experimental studies on a 3.7-kW induction motor drive. The SRF-based optimal PWM results in marginally better performance than the FD-based one. However, the selection of optimal switching angle for any modulation index (M) takes much longer in case of SRF than in case of the FD-based approach. The FD-based optimal solutions can be used as good starting solutions and/or to reasonably restrict the search space for optimal solutions in the SRF-based approach. Both of the FD-based and SRF-based optimal PWM methods reduce the low-order pulsating torque significantly, compared to ST PWM and SHE PWM, as shown by the simulation and experimental results.