Phase lagging model of brain response to external stimuli - modeling of single action potential

In this paper we detail a phase lagging model of brain response to external stimuli. The model is derived using the basic laws of physics like conservation of energy law. This model eliminates the paradox of instantaneous propagation of the action potential in the brain. The solution of this model is then presented. The model is further applied in the case of a single neuron and is verified by simulating a single action potential. The results of this modeling are useful not only for the fundamental understanding of single action potential generation, but also they can be applied in case of neuronal interactions where the results can be verified against the real EEG signal.Comment: 19 page

All tree level scattering amplitudes in Chern-Simons theories with fundamental matter

We show that Britto-Cachazo-Feng-Witten (BCFW) recursion relations can be used to compute all tree level scattering amplitudes in terms of $2\rightarrow2$ scattering amplitude in $U(N)$ ${\mathcal N}=2$ Chern-Simons (CS) theory coupled to matter in fundamental representation. As a byproduct, we also obtain a recursion relation for the CS theory coupled to regular fermions, even though in this case standard BCFW deformations do not have a good asymptotic behaviour. Moreover at large $N$, $2\rightarrow 2$ scattering can be computed exactly to all orders in 't Hooft coupling as was done in earlier works by some of the authors. In particular, for ${\mathcal N}=2$ theory, it was shown that $2\rightarrow 2$ scattering is tree level exact to all orders except in the anyonic channel arXiv:1505.06571, where it gets renormalized by a simple function of 't Hooft coupling. This suggests that it may be possible to compute the all loop exact result for arbitrary higher point scattering amplitudes at large $N$.Comment: RevTEX 4.1, 5 pages+6 Appendices, 7 figures; V2 Published versio

White Mirror: Leaking Sensitive Information from Interactive Netflix Movies using Encrypted Traffic Analysis

Privacy leaks from Netflix videos/movies is well researched. Current state-of-the-art works have been able to obtain coarse-grained information such as the genre and the title of videos by passive observation of encrypted traffic. However, leakage of fine-grained information from encrypted traffic has not been studied so far. Such information can be used to build behavioural profiles of viewers. On 28th December 2018, Netflix released the first mainstream interactive movie called 'Black Mirror: Bandersnatch'. In this work, we use this movie as a case-study to show for the first time that fine-grained information (i.e., choices made by users) can be revealed from encrypted traffic. We use the state information exchanged between the viewer's browser and Netflix as the side-channel. To evaluate our proposed technique, we built the first interactive video traffic dataset of 100 viewers; which we will be releasing. Preliminary results indicate that the choices made by a user can be revealed 96% of the time in the worst case.Comment: 2 pages, 2 figures, 1 tabl

Preparation and Characterization of Activated Carbon from Jackfruit Peel

Activated carbon in powdered form was prepared from jackfruit peel, a domestic waste. Jackfruit peel having limited economic value has been used as a precursor material to prepare activated carbon. Activated carbon was prepared by the chemical activation of the raw material (Jackfruit peel) which was initially processed and subsequently subjected to activation using varying activating agents such as Potassium Hydroxide (KOH), Zinc Chloride (ZnCl2) and Phosphoric Acid (H3PO4). Surface characteristics such as porosity, iodine number, moisture content, pH, ash content and specific gravity of the prepared activated carbon were estimated. The surface properties from different characterization like FTIR, SEM, TGA analysis indicated that the activated carbon prepared can be utilized as a suitable adsorbent

Convolutional restricted Boltzmann machine (CRBM) correlated variational wave function for the Hubbard model on a square lattice: Mott metal-insulator transition

We use a convolutional restricted Boltzmann machine (CRBM) neural network to construct a variational wave function (WF) for the Hubbard model on a square lattice and study it using the variational Monte Carlo (VMC) method. In the wave function, the CRBM acts as a correlation factor to a mean-field BCS state. The number of variational parameters in the WF does not grow automatically with the lattice size and it is computationally much more efficient compared to other neural network based WFs. We find that in the intermediate to strong coupling regime of the model at half-filling, the wave function outperforms even the highly accurate long range backflow-Jastrow correlated wave function. Using the WF, we study the ground state of the half-filled model as a function of onsite Coulomb repulsion $U$. We consider two cases for the next-nearest-neighbor hopping parameter, e.g., $t'=0$ as well as a frustrated model case with $t'\neq 0$. By examining several quantities, e.g., double occupancy, charge gap, momentum distribution, and spin-spin correlations, we find that the weekly correlated phase in both cases is paramagnetic metallic (PM). As $U$ is increased, the system undergoes a first-order Mott transition to an insulating state at a critical $U_c$, the value of which depends upon $t'$. The Mott state in both cases is spin gapped with long range antiferromagnetic (AF) order. Remarkably, the AF order emerges spontaneously from the wave function which does not have any explicitly broken symmetry in it. Apart from some quantitative differences in the results for the two values of $t'$, we find some interesting qualitative differences in the way the Mott transition takes place in the two cases.Comment: 8 pages, 10 figure

Effective Utilization and Conversion of Spent Distillery Liquid to Valuable Products Using an Intensified Technology of Two-stage Biological Sequestration

The potential of Cladosporium cladosporioides and Phormidium valdernium in treating spent distillery liquid in a two-stage sequential step was investigated. During the batch experiment, a maximum decolourisation of 68.5 % and 81.37 % COD reduction was achieved in the first-stage bioreactor. Further, the spent wash from bioreactor was treated with cyanobacteria in the second stage and resulted in COD reduction (3,652 mg L–1) of 89.5 % and 92.7 % decolorization, respectively. Biodegradation was confirmed using HPLC analysis, and the products released during the degradation in the two stages were identified using GC-MS analysis, and found to be 2-octenyl acetate, 1,6-heptadiene from the fungi and oxotetrahydrofuran, hexadecane from cyanobacteria which in turn reveals the fact that the sequential treatment was through the mechanism of biodegradation and not by adsorption. The results imply that sequential treatment using the combination of fungi and cyanobacteria resulted in better degradation and decolourisation for the distillery spent wash