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The optical conductivity in a Kondo lattice system is presented in terms of the memory function formalism. I use Kondo-lattice Hamiltonian for explicit calculations. I compute the frequency dependent imaginary part of the memory function ($M^{\p\p}(\om)$), and the real part of the memory function $M^{\p}(\om)$ by using the Kramers-Kronig transformation. Optical conductivity is computed using the generalized Drude formula. I find that high frequency tail of the optical conductivity scales as $\sigma(\om) \sim \frac{1}{\om}$ instead of the Drude $\frac{1}{\om^2}$ law. Such a behaviour is seen in strange metals. My work points out that it may be the magnetic scattering mechanisms that are important for the anomalous behaviour of strange metals., Comment: 9

We calculate resistivity in the paramagnetic phase just above the curie temperature in a $2d$ ferromagnetic metal. The required dynamical susceptibility in the formalism of resistivity is calculated within the Random Phase Approximation(RPA). The mechanism of resistivity is magnetic scattering in which $s$-band electrons are scattered off the magnetic spin fluctuations of d-band electrons. We use the $s$-$d$ Hamiltonian formalism. We find that near the quantum critical point the resistivity in $2d$ scales as $T^{\frac{4}{3}}$, whereas in $3d$ it scales as $T^{\frac{5}{3}}$. In contrast to it, resistivity due to phonon scattering is given by $T^5$ in low temperature limit as is well known. Our RPA result agrees with the Self-Consistence Renormalisation(SCR) theory result., 11 pages

Since the development of first lipid-based nanocarrier system, about 15% of the present pharmaceutical market uses nanomedicines to achieve medical benefits. Nanotechnology is an advanced area to meliorate the delivery of compounds for improved medical diagnosis and curing disease. Nanomedicines are gaining significant interest due to the ultra small size and large surface area to mass ratio. In this review, we discuss the potential of nanotechnology in delivering of active moieties for the disease therapy including their toxicity evidences. This communication will help the formulation scientists in understanding and exploring the new aspects of nanotechnology in the field of nanomedicine.

Generally, hydrophobic amino acids provide hydrophobic interactions during peptide aggregation. However, besides the hydrophobic amino acids, some hydrophilic amino acids, such as glutamine, are also considered to be essential elements in many self-aggregating peptides. For example, huntingtin contains polyglutamine at its N-terminus and the yeast prion Sup35 protein has the GNNQQNY sequence, a peptide well-known for its ability for amyloid fibril formation. However, despite the frequent emergence of glutamine in self-assembling systems, the molecular mechanism of amyloid formation involving this unique amino acid has not been well documented. It is still not clear how this hydrophilic amino acid is responsible for the hydrophobic interaction in the self-association process. Therefore, in this study, we have carried out classical molecular dynamics simulations of the GNNQQNY peptide and its derivatives in pure water. We quantify the propensity for the formation of β-sheet conformation with an increasing glutamine number in the peptide sequence. In addition, we assess the importance of the hydrophobicity of the dimethanediyl group present in glutamine (as well as in glutamic acid) for the self-association of the peptides through nonpolar solvent medium simulations.

In addition to maternal mortality, information on maternal near miss and severe maternal morbidity are important in maternal healthcare. We aimed to determine the incidence, causes and outcome of severe maternal morbidity and near miss, and the sociodemographic and obstetric factors associated with these at a tertiary care teaching hospital in Delhi.Women admitted with severe maternal morbidity and near miss, as defined by the WHO study group, were included in the study. The incidence ratio of near miss and severe morbidity in the hospital was determined, and a case-control study was conducted to study the factors associated with the occurrence of near miss. Information was obtained from hospital records and interviews, using a semi-structured open-ended questionnaire.The incidence ratio of near miss was 6.85/ 1000, and severe morbidity was 11.38/1000 live births. Hypertensive disorders and haemorrhage were the common causes of cases of near miss and severe morbidity. Coagulation dysfunction (62%) was the most common organ dysfunction, followed by uterine dysfunction (22%). Older age (odds ratio [OR] 2.01, confidence interval [CI] 1.02-3.93), the absence of formal education (OR 2.05, CI 1.11-3.75),18 years of age at marriage (OR 2.01, CI 1.21-3.32), lower income (OR 3.8, CI 1.88-7.64), gravida of four or more (OR 2.25, CI 1.21-4.17) and residence outside Delhi (OR 9.31, CI 4.36-19.90) were significant predictors of near miss. Sepsis, hypertensive disorders and haemorrhage were the most common underlying conditions in women who died. The foetal outcome was a live birth in 64% of near-miss cases and 62% among severe morbidity.The burden of severe maternal morbidity and near miss is high. These need to be identified and managed at the earliest.

The implementation of Memristor will have a wider range of applications in various fields. Digital switching systems depend on reliable and high-quality synchronization from timing circuits and they are the fundamental units of ICs. So we designed timing circuits using hybrid integration of Memristor using the TEAM model, which is simplified yet captures all main characteristics and CMOS (90 nm technology). Timing circuits like astable multivibrator, voltage-controlled oscillators (VCO) are designed and we analyzed all the important parameters like frequency stability, delay, power, phase noise, noise factor, no of devices used and compare them with the timing circuits designed by conventional CMOS. All the circuits are designed and simulated in Virtuoso Cadence.

In this proposed work, room temperature fast response and recovery Pt-modified WO3/p–Si and WO3 device sensors were fabricated using sol–gel method for the influence of methanol gas concentrations. Two different types of sensors have been fabricated for sensing of methanol concentration in the temperature range of 25–45 ℃. TEM, XRD, and FESEM are useful for exploring the structural property and the surface property of Pt–WO3 and WO3 thin film. Gas-sensing response is observed at the room temperature range. It was observed that Pt-modified WO3/p–Si thin film with Al presents higher response as compared to unmodified WO3/p–Si thin film.

Earth’s atmosphere supports a variety of internal wave motion which are responsible for spatio-temporal changes in temperature, winds, density, and chemical constituents. One of the most striking dynamical features of the upper atmosphere (i.e. mesosphere and lower thermosphere [MLT], 50-120 km) are atmospheric tides. In particular, the eastward-propagating nonmigrating diurnal tide with zonal wave number 3 (DE3), originating from tropical deep convection, introduces a large longitudinal and local time variability in temperature, wind and density in the MLT region. The DE3 is thus key to understanding how tropospheric weather influences space weather. However, DE3 short-term tidal variability is not well understood and part of the motivation for constellation missions. Single satellites such as TIMED nevertheless provide a pathway to identify multi-timescale tidal variability from days to years. We utilize 16 years of SABER (an instrument onboard the TIMED satellite) DE3 “tidal deconvolution” diagnostic that provides a unique opportunity to investigate interannual changes in short-term (days to weeks) tidal variability on various planetary wave time scales. The approach is based on information-theoretic techniques using Bayesian statistics, time dependent probability density functions and Kullback-Leibler divergence followed by multiple linear regression analysis. In this presentation, we focus on interannual changes in short-term DE3 variability on a 10-day planetary wave timescale and how it changes as a function of the quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO) and the solar cycle.

Observations from the recently launched Global-Scale Observations of the Limb and Disk (GOLD) instrument on the geostationary SES-14 communications satellite provide the first observational proof for the impact of stratospheric weather, that is, polar vortex dynamics during a Sudden Stratospheric Warming (SSW), on the composition of the thermosphere. During the early January 2019 SSW, GOLD observes a >10% O/N2 column density ratio depletion in both hemispheres unrelated to geomagnetic activity. The data and supporting TIE-GCM and WACCM-X simulations show that enhanced global-scale wave activity during the SSW causes an enhanced wave driving of the lower thermosphere zonal mean circulation that leads to a reduction in lower thermosphere atomic oxygen, which then propagates through molecular diffusion into the upper thermosphere. The observed composition changes will likely impact Earth's ionospheric plasma environment as well and imply another pathway for SSW impacts on space weather, in addition to dynamo processes.

A condition for spin wave generation in an itinerant electron magnetic system is worked out using Random Phase Approximation. We show that exchange coupling parameterIImust be greater than a cut-off parameter ∏0≥6h2kF25Nm for the spin wave generation.

The groundwater management problems are broadly solved using the coupled simulation-optimization model. In the coupled simulation-optimization model, Analytic element method (AEM) based simulation model and particle swarm optimization (PSO) based optimization model is adopted to find out the best groundwater management strategy. Moreover, the coupled model is applied to a illustrative example to check its efficiency in solving the groundwater management problems involving large number of decision variables. Two-dimensional isotropic, homogeneous and confined aquifer is considered for the groundwater flow simulation. AEM is used to simulate the groundwater flow and to penalize the constraints, whereas PSO is used to evaluate the objective function (time varying operating cost) of the management problem. The optimization model calls the simulation model repeatedly until the stopping criterion is achieved. To evaluate the performance of the developed methodology optimization model using Nelder-Meade method is also considered. The obtained results are compared with PSO based optimization model. Obtained results demonstrate the potential applicability of the model to solve groundwater management problems.

The efficiency of silicon based solar cell has increased only by 1% in past 15 years where as in 6 years the efficiency of Perovskite solar cell has got the pace and increased up to ∼22%. Photovoltaic performance of lead free PerovskiteBiFeO3 with graphene electrode and Ti/Ni/Cd doped BiFeO3 with graphene electrode has been compared in this work. The open circuit voltages of pure BFO, Ti doped BFO, Ni doped BFO, and Cd doped BFO are 0.49 V, 0.77 V, 0.56 V, 0.49 V respectively, and short circuit current densities are 273.44 μA/cm2, 7519 μA/cm2, 4217 μA/cm2, 285.61 μA/cm2 respectively. Comparative study of thin film formation through different methodologies like dipping, spray and spin are also analysed and observed, that ‘Ti’ doped BFO along with formation of layer by spinning process exerts significant improved performance of 3.043% of efficiency, however the model of this solar cell is observed 9.06% of efficiency by simulation.

Evolution of TFET has revolutionized semiconductor physics and these has been a tremendous and steady in development of VLSI technology incorporating TFET. An innovative TFET called Double Symmetrical Source Tunnel FET (DSS-TFET) is put forward in this paper, which foster higher ON Current (I ON ) with smaller driving voltage as compared to conventional TFETs. The tunnelling area is considerably reduced which in turn increases the I ON , for a smaller turn on voltage. The influence of variation parameters like channel length, oxide thickness, gate work function and Source-length on the efficiency of the device have been studied and compared with conventional TFET devices. Silvaco-Atlas 2-D simulation has been used in the work to achieve excellent SS of 23mV/decade and high I ON /I OFF of 1013 at $\mathrm{V}_{\text{DS}}=0.1\mathrm{V}$ . 1-D Quantum confinement effect has been studied for the proposed DSS-TFET using the Schrodinger-Poisson model in the simulations. The DSS-TFET has excellent performance characteristics and is viable for low power applications.

We theoretically analyse D.C. resistivity($\rho$) in the Kondo-lattice model using the powerful memory function approach. The complete temperature evolution of $\rho$ is investigated using the W\"{o}lfle-G\"{o}tze expansion of the memory function. The resistivity in this model originates due to spin-flip magnetic scattering of conduction $s$-electron off the quasi-localized $d$ or $f$ electron spins. We find the famous resistivity upturn at lower temperature regime ($k_B T<, Comment: 16 pages, and 4 figures

The potential impact of thin film perovskite solar cell is metamorphic as it can reduce the cost associated with manufacturing of solar cells. Perovskite materials have impressive optoelectronic properties such as high mobility, high absorption and long diffusion length of charge carriers. The power conversion efficiency of lead contained metal halide perovskite has reached up to 23%, but lead is a highly toxic element thereby harmful for environment. In this work Sn based perovskite (CH3NH3SnI3) has been proposed and investigated using hole transport layer. Along with absorption of light by active layer, charge separation and extraction also plays a crucial role in controlling the device performance. The potential of ZnTe as hole collector has been explored. Here we report modeling, simulation and fabrication of lead-free CH3NH3SnI3 perovskite solar cell processed on ZnTe as hole transport layer. Remarkably, we achieve efficiency of 22.96% in simulation and 8.41% in fabrication.

Forecasting of space–time groundwater level is important for sparsely monitored regions. Time series analysis using soft computing tools is powerful in temporal data analysis. Classical geostatistical methods provide the best estimates of spatial data. In the present work a hybrid framework for space–time groundwater level forecasting is proposed by combining a soft computing tool and a geostatistical model. Three time series forecasting models: artificial neural network, least square support vector machine and genetic programming (GP), are individually combined with the geostatistical ordinary kriging model. The experimental variogram thus obtained fits a linear combination of a nugget effect model and a power model. The efficacy of the space–time models was decided on both visual interpretation (spatial maps) and calculated error statistics. It was found that the GP–kriging space–time model gave the most satisfactory results in terms of average absolute relative error, root mean square error, no...

In the present work, uncertainty-based dynamic sampling frameworks were tested for a sampling horizon with multiple time steps. Future concentration values were assumed as fuzzy numbers. Multiple realization–based simulations were used for generation of fuzzy numbers. The first framework considers fuzzy variance reduction. The second framework considers mass estimation error reduction with maximization of spatial coverage of the dynamic sampling network. It is a multi-objective optimization problem with a large number of objectives. In Dhar and Patil (2012), uncertainty-based optimal sampling design model was suggested using Nondominated Sorting Genetic Algorithm-II (NSGA-II) as its optimization algorithm. However, NSGA-II becomes computationally expensive while handling more than three objectives. We extend the previously suggested algorithm for multi-objective sampling network design problems based on NSGA-III framework. Two design frameworks were proposed: one incorporating a simulation model and a fuzzy covariance for minimizing the total contaminant-concentration variance and the other incorporating a simulation model and a fuzzy kriging model in conjunction with an optimization model to minimize the fuzzy mass estimation error and spatial coverage of spatiotemporal sampling locations. NSGA-III was used for solving the sampling network design model. Performances of the proposed frameworks were evaluated for two hypothetical illustrative examples. The results indicate that the proposed design frameworks perform satisfactorily under uncertain system conditions.

Technological advancements in the field of machine learning have attempted classification of the images of gigantic datasets. Classification with content-based image feature extraction categorizes the images based on the image content in contrast to conventional text-based annotation. The chapter has presented a feature extraction technique based on application of image transform. The method has extracted meaningful features and facilitated feature dimension reduction. A technique, known as fractional coefficient of transforms, is adopted to facilitate feature dimension reduction. Two different color spaces, namely RGB and YUV, are considered to compare the classification metrics to figure out the best possible reduced feature dimension. Further, the results are compared to state-of-the-art techniques which have revealed improved performance for the proposed feature extraction technique.

In recent times, there has been an increased demand for cost-effective, robust and highly reliable humidity sensors. 2D material MoS2 (n-type) have demonstrated their potential application in chemical and humidity sensing. In this work, an organic-inorganic p-n heterojunction based sensor has been fabricated using the inorganic MoS2 and the organic CuPc, and its viability towards humidity sensing has been experimentally demonstrated. The thin film sensor was characterized by SEM and the results revealed the formation of CuPc nanoflowers on MoS2 surface. The XRD results also indicate excellent crystallization. The sensor shows reduced resistance with increasing RH% and the variation has been observed to be almost linear. The sensing range is from 20% RH to 98% RH. The measured sensitivity is 0.615 MΩ/%RH. The demonstrated results are of great interest in terms of sensitivity, linear response, range of humidity monitoring and stability.

++ ,TDS, TSS and fluoride are positively correlated with pH but Conductivity, Total Alkalinity and Cl - are negatively correlated with pH. Calcium and Iron showed no relation with pH. The Iron value of ground water is also above the permissible limit.

Electronic Procurement Systems (EPS) are being acknowledged by researchers as promising technological enablers for achieving a responsive supply chain, and thereby, for gaining a competitive advantage in today’s global marketplace. A number of empirical studies have focused on the adoption of EPS in different countries. There is, however, a scarcity of work related to EPS adoption in India, even though information technology and the Internet play a significant role in that country. To fill this gap, we first discuss the potential supply chain benefits of EPS, especially as they relate to large multinational companies. Then, we specifically consider the Indian context. We highlight several firms whose innovative logistics operations permit the respective supply chains to function, uniquely blending Indian customs with modern business practices. We report on an empirical survey, as well as three case-studies relating to the importance and impact of EPS adoption in India.