Enhancement of Flotation Selectivity of Sphalerite Using Mineral-Stressed Paenibacillus polymyxa and Its Cellular Components

The selective flotation of sphalerite from a sphalerite-galena mineral mixture was achieved using cellular components of Paenibacillus polymyxa after adaptation to the above minerals. The soluble and insoluble fractions of the thermolysed bacterial cells adapted to sphalerite yielded higher flotation recoveries of sphalerite with selectivity indices ranging between 22 and 29. The protein profile for the unadapted and mineral-stressed cells was found to differ distinctly, attesting to variation in the yield and nature of extra-cellular polymeric substances. The changes induced in the bacterial cell wall components after adaptation to sphalerite or galena with respect to the contents of phosphate, uronic acid and acetylated sugars of P. polymyxa were quantified. In keeping with these changes, a marginal morphological transition of P. polymyxa from rods to spheres was observed. The role of the dissolved metal ions from the minerals as well as that of the constituents of extracellular secretions in modulating the surface potential of the mineral-stressed cells were demonstrated. These studies highlighted that, mineral stress led to qualitative and quantitative changes in the cellular components, which facilitated the enhancement of flotation selectivity of sphalerite.

Enhancement Mechanism of Fluorescence Intensity in Presence of Plasmonic Nanoparticles

The emission intensity of fluorophore molecule may change in presence of strong plasmon field induced by nanoparticles. The enhancement intensity is optimized through selective clustering or functionalization of nanoparticles in closed vicinity of fluorophore. Our study is aimed at understanding the enhancement mechanism of fluorescence intensity in presence of gold nanoparticles to utilize it in molecular sensing and in situ imaging in the microfluidic lab-on-chip device. Related phenomena are studied in situ in a microfluidic channel via fluorescence imaging. Detailed analysis is carried out to understand the possible mechanism of enhancement of fluorescence due to nanoparticles. In the present experimental study we show that SYTO9 fluorescence intensity increased in presence of Au nanoparticles of similar to 20 nm diameter. The fluorescence intensity is 20 time more compared to that in absence of Au nanoparticles. The enhancement of fluorescence intensity is attributed to the plasmonic resonance of Au nanoparticle at around the fluorescence emission wavelength. Underlying fundamental mechanism via dipole interaction model is explored for quantitative correlation of plasmonic enhancement properties.

Small-Signal Stability Analysis of an Open-Loop Induction Motor Drive Including the Effect of Inverter Deadtime

This paper demonstrates light-load instability in a 100-kW open-loop induction motor drive on account of inverter deadtime. An improved small-signal model of an inverter-fed induction motor is proposed. This improved model is derived by linearizing the nonlinear dynamic equations of the motor, which include the inverter deadtime effect. Stability analysis is carried out on the 100-kW415-V three-phase induction motor considering no load. The analysis brings out the region of instability of this motor drive on the voltage versus frequency (V-f) plane. This region of light-load instability is found to expand with increase in inverter deadtime. Subharmonic oscillations of significant amplitude are observed in the steady-state simulated and measured current waveforms, at numerous operating points in the unstable region predicted, confirming the validity of the stability analysis. Furthermore, simulation and experimental results demonstrate that the proposed model is more accurate than an existing small-signal model in predicting the region of instability.

Simultaneous enhancement of electrical conductivity and thermopower in Bi2S3 under hydrostatic pressure

The inverse coupled dependence of electrical conductivity and thermopower on carrier concentration presents a big challenge in achieving a high figure of merit. However, the simultaneous enhancement of electrical conductivity and thermopower can be realized in practice by carefully engineering the electronic band structure. Here by taking the example of Bi2S3, we report a simultaneous increase in both electrical conductivity and thermopower under hydrostatic pressure. Application of hydrostatic pressure enables tuning of electronic structure in such a way that the conductivity effective mass decreases and the density of states effective mass increases. This dependence of effective masses leads to simultaneous enhancement in electrical conductivity and thermopower under n-type doping leading to a huge improvement in the power factor. Also lattice thermal conductivity exhibits very weak pressure dependence in the low pressure range. The large power factor together with low lattice thermal conductivity results in a high ZT value of 1.1 under n-type doping, which is nearly two times higher than the previously reported value. Hence, this pressure-tuned behaviour can enable the development of efficient thermoelectric devices in the moderate to high temperature range. We further demonstrate that similar enhancement can be observed by generating chemical pressure by doping Bi2S3 with smaller iso-electronic elements such as Sb at Bi sites, which can be achieved experimentally.

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.