Estimation of the effect of long-range transport on seasonal variation of aerosols over northeastern India

Spectral aerosol optical depth (AOD) at ten discrete channels in the visible and near IR regions were estimated over Dibrugarh, located in the northeastern part of India, using a ground-based multi-wavelength solar radiometer (MWR) from October 2001 to February 2006. The observations reveal seasonal variations with low values of AODs in retreating monsoon and high values in the pre-monsoon season. Generally the AODs are high at shorter wavelengths and low at longer wavelengths. AOD spectra are relatively steep in winter compared to that in the monsoon period. The average value of AOD lies between 0.44±0.07 and 0.56±0.07 at 500 nm during the pre-monsoon season and between 0.19±0.02 and 0.22±0.02 during re-treating monsoon at the same wavelength. Comparison of MWR observation on Dibrugarh with satellite (MODIS) observation indicates a good correspondence between ground-based and satellite derived AODs. The synoptic wind pattern obtained from National Centre for Medium Range Weather Forecasting (NCMRWF), India and back trajectory analysis using the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT4) Model indicates that maximum contribution to aerosol extinction could be due to transport of pollutants from the industrialized and urban regions of India and large amounts of desert and mineral aerosols from the west Asian and Indian desert. Equal contributions from Bay-of- Bengal (BoB), in addition to that from the Indian landmass and west Asian desert leads to a further increase of AOD over the region of interest in the pre-monsoon seasons

Possible impact of a major oil-well fire on aerosol optical depth at Dibrugarh

This article does not have an abstract

A New Om(z)Om(z) Diagnostic of Dark Energy in General Relativity Theory

In this paper, we propose a new parametrization of dark energy based on the $Om(z)$ diagnostic tool behavior. For this purpose, we investigate a functional form of the $Om(z)$ that predicts the popular dark energy dynamical models, namely phantom and quintessence. We also found the famous cosmological constant for specified values of the model's parameters. We employed the Markov Chain Monte Carlo approach to constrain the cosmological model using Hubble, Pantheon samples, and BAO datasets. Finally, we used observational constraints to investigate the characteristics of dark energy evolution and compare our findings to cosmological predictions.Comment: The European Physical Journal C accepted versio

A new f(Q)f(Q) cosmological model with H(z)H(z) quadratic expansion

We present a new $f(Q)$ cosmological model capable of reproducing late-time acceleration, i.e. $f\left( Q\right) = \lambda_{0}\left( \lambda +Q\right) ^{n}$ by supporting certain parametrization of the Hubble parameter. By using observational data from Hubble, Pantheon, and Baryonic Acoustic Oscillations (BAO) dataset, we investigate the constraints on the proposed quadratic Hubble parameter $H(z)$. This proposal caused the Universe to transition from its decelerated phase to its accelerated phase. Further, the current constrained value of the deceleration parameter from the combined Hubble+Pantheon+BAO dataset is $q_{0}=-0.285\pm 0.021$, which indicates that the Universe is accelerating. We also analyze the evolution of energy density, pressure, and EoS parameters to infer the Universe's accelerating behavior. Finally, we use a stability analysis with linear perturbations to assure the model's stability.Comment: Physics of the Dark Universe published versio

Quasinormal Modes of Black holes in f(Q)f(Q) gravity

In this work, we have studied the quasinormal modes of a black hole in a model of the type $f(Q)=\underset{n}{\sum}a_{n}\left(Q-Q_{0}\right)^{n}$ in $f(Q)$ gravity by using a recently introduced method known as Bernstein spectral method and confirmed the validity of the method with the help of well known Pad\'e averaged higher order WKB approximation method. Here we have considered scalar perturbation and electromagnetic perturbation in the black hole spacetime and obtained the corresponding quasinormal modes. We see that for a non-vanishing nonmetricity scalar $Q_0$, quasinormal frequencies in scalar perturbation are greater than those in electromagnetic perturbation scenarios. On the other hand, the damping rate of gravitational waves is higher for electromagnetic perturbation. To confirm the quasinormal mode behaviour, we have also investigated the time domain profiles for both types of perturbations.Comment: 15 pages, 6 figures. Published versio

Micellar-polymer for enhanced oil recovery for Upper Assam Basin

One of the major enhanced oil recovery (EOR) processes is chemical flooding especially for the depleted reservoirs. Chemical flooding involves injection of various chemicals like surfactant, alkali, polymer etc. to the aqueous media. Bhogpara and Nahorkatiya are two depleted reservoirs of upper Assam basin where chemical flooding can be done to recover the trapped oil that cannot be recovered by conventional flooding process. Micellar-polymer (MP) flooding involves injection of micelle and polymer to the aqueous phase to reduce interfacial tension and polymer is added to control the mobility of the solution, which helps in increasing both displacement and volumetric sweep efficiency and thereby leads to enhanced oil recovery. This work represents the use of black liquor as micelle or surfactant that is a waste product of Nowgong Paper Mills, Jagiroad, Assam, which is more efficient than the synthetic surfactants. The present study examines the effect of MP flooding through the porous media of two depleted oil fields of upper Assam basin i.e. Bhogpara and Nahorkatiya for MP EOR. This work also compares the present MP flood with the earlier work done on surfactant (S) flooding. It was experimentally determined that the MP flood is more efficient EOR process for Bhogpara and Nahorkatiya reservoirs. The study will pertain to the comprehensive interfacial tension (IFT) study and the displacement mechanism in conventional core samples

Quasinormal Modes and Optical Properties of 4-D black holes in Einstein Power-Yang-Mills Gravity

This paper explores the impact of the Yang-Mills charge parameter and the exponent term on a $4$D black hole solution in the Einstein Power-Yang-Mills theory. Through an investigation of the massless scalar quasinormal mode spectrum, black hole shadow, and emission rate, we have determined that the effects of these two parameters are opposite. Specifically, the Yang-Mills charge parameter causes an increase in the real quasinormal frequencies with a correspondingly smaller damping rate. It also results in a smaller black hole shadow and a lower evaporation rate.Comment: 13 pages, 9 figure

MAC: A Meta-Learning Approach for Feature Learning and Recombination

Optimization-based meta-learning aims to learn an initialization so that a new unseen task can be learned within a few gradient updates. Model Agnostic Meta-Learning (MAML) is a benchmark algorithm comprising two optimization loops. The inner loop is dedicated to learning a new task and the outer loop leads to meta-initialization. However, ANIL (almost no inner loop) algorithm shows that feature reuse is an alternative to rapid learning in MAML. Thus, the meta-initialization phase makes MAML primed for feature reuse and obviates the need for rapid learning. Contrary to ANIL, we hypothesize that there may be a need to learn new features during meta-testing. A new unseen task from non-similar distribution would necessitate rapid learning in addition reuse and recombination of existing features. In this paper, we invoke the width-depth duality of neural networks, wherein, we increase the width of the network by adding extra computational units (ACU). The ACUs enable the learning of new atomic features in the meta-testing task, and the associated increased width facilitates information propagation in the forwarding pass. The newly learnt features combine with existing features in the last layer for meta-learning. Experimental results show that our proposed MAC method outperformed existing ANIL algorithm for non-similar task distribution by approximately 13% (5-shot task setting)Comment: 20 pages, 3 figures, 2 graph