The Origin of Helicity in Solar Active Regions

We present calculations of helicity based on our solar dynamo model and show that the results are consistent with observational data.Comment: To appear in the Proceedings of IAU Symposium 22

Dimension Driven Accelerating Universe

The current acceleration of the universe leads us to investigate higher dimensional gravity theory, which is able to explain acceleration from a theoretical view point without the need of introducing dark energy by hand. We argue that the terms containing higher dimensional metric coefficients produce an extra negative pressure that apparently drives an acceleration of the 3D space, tempting us to suggest that the accelerating universe seems to act as a window to the existence of extra spatial dimensions. Interesting to point out that in this case our cosmology apparently mimics the well known quintessence scenario fuelled by a generalised Chaplygin-type of fluid where a smooth transition from a dust dominated model to a de Sitter like one takes place. Correspondence to models generated by a tachyonic form of matter is also briefly discussed

Helicity of solar active regions from a Dynamo Model

We calculate helicities of solar active regions based on the idea that poloidal flux lines get wrapped around a toroidal flux tube rising through the convection zone, thereby giving rise to the helicity. Rough estimates based on this idea compare favorably with the observed magnitude of helicity. We use our solar dynamo model based on the Babcock-Leighton a-effect to study how helicity varies with latitude and time. At the time of solar maximum, our theoretical model gives negative helicity in the northern hemisphere and positive helicity in the south, in accordance with observed hemispheric trends. However, we find that during a short interval at the beginning of a cycle, helicities tend to be opposite of the preferred hemispheric trends

Prospects of five-dimensional Lμ−LτL_\mu-L_\tau gauge interactions in the light of elastic neutrino-electron scatterings: the scope of the DUNE near detector

We discuss the future prospects of a minimally five-dimensional version of the well-motivated scenario for addressing the discrepancy in the muon anomalous magnetic moment, the $U(1)_{L_\mu - L_\tau}$ extension of the standard model (SM) gauge symmetry. Here, multiple associated massive gauge bosons appear thanks to the five-dimensional $U(1)_{L_\mu - L_\tau}$ gauge symmetry, and they contribute to the muon $(g-2)$ and also other processes. We focus on the powerful probe of elastic neutrino-electron scatterings since the upcoming DUNE experiment will explore MeV-scale uncharted regions by previous experiments (e.g., CHARM-II and Borexino) in the near future. We found that even with small kinetic mixing parameters, much of the parameter space, including those satisfying muon $(g-2)$, can be probed using several years of data from the DUNE experiment, focusing on the near detector. In our scenario, interference effects between intermediate-state gauge bosons play an important role. Our results include comparisons between flat and warped extra dimensions.Comment: 40 pages, 7 figure

Plasma spraying of an indigenous yttria stabilized zirconia powder prepared by the sol-gel technique

An indigenous sol-gel derived yttria-partially stabilized zirconia (Y-PSZ) powder has been characterized and its suitability for plasma spraying applications evaluated. The powder, determined to have about 5.1% yttria content, predominantly consisted of spherical particles with an average equivalent particle diameter close to 25 mum. Furthermore, it was found that the powder did not contain any particles > 50 mum, which is considered the ideal upper size limit for spray-grade ceramic powders in order to ensure complete melting during spraying. The sol-gel produced powder exhibited good flow characteristics and the plasma sprayed coatings developed using this powder were also found to have excellent thermal shock resistance. The corresponding results obtained using an imported Y-PSZ powder are also presented for the purpose of comparison

Is the energy balance in a tropical lowland rice paddy perfectly closed?

A two-year (2015 and 2016) field experiment was carried out to study the surface energy budget and energy balance closure (EBC) in a tropical lowland rice paddy in Cuttack, India. Maintenance of a standing water layer in lowland irrigated rice ecosystem makes it unique and this strongly influences the surface energy balance which may alter the surface runoff, ground water storage, water cycle, surface energy budget, and possibly microclimate of the region. To study this, an experiment was conducted using eddy covariance system to measure the surface energy balance components during two cropping seasons (dry season, DS and wet season, WS) and two consecutive fallow periods (dry fallow, DF and wet fallow, WF). The rice was grown in puddled wet lands in DS and WS and the ground was left fallow (DF and WF) during the rest of the year. Results displayed that daily average latent heat flux at surface (LE) and at canopy height (LEc) dominated over sensible heat flux at surface (H) and canopy height (Hc), respectively due to the presence of water source coming from the standing water in the rice field. The EBC was evaluated by ordinary least square (OLS), energy balance ratio (EBR) and residual heat flux (RHF). In OLS, the slope ranged 0.38-0.89 (2015) and 0.28-0.99 (2016) during the study period. Average RHF was 10.3-12.0% higher in WS as compared to DS. It was concluded that the EBC estimated using RHF is the most suitable way to calculate closure for lowland rice paddy since it can distinguish different seasons distinctively, followed by OLS. Much variation was not observed in EBR after inclusion of storage terms (water, soil, photosynthesis, canopy) to the classical EBR

A Comparative Analysis of Machine-learning Models for Solar Flare Forecasting : Identifying High-performing Active Region Flare Indicators

Solar flares create adverse space weather impacting space- and Earth-based technologies. However, the difficulty of forecasting flares, and by extension severe space weather, is accentuated by the lack of any unique flare trigger or a single physical pathway. Studies indicate that multiple physical properties contribute to active region flare potential, compounding the challenge. Recent developments in machine learning (ML) have enabled analysis of higher-dimensional data leading to increasingly better flare forecasting techniques. However, consensus on high-performing flare predictors remains elusive. In the most comprehensive study to date, we conduct a comparative analysis of four popular ML techniques (k nearest neighbors, logistic regression, random forest classifier, and support vector machine) by training these on magnetic parameters obtained from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory for the entirety of solar cycle 24. We demonstrate that the logistic regression and support vector machine algorithms perform extremely well in forecasting active region flaring potential. The logistic regression algorithm returns the highest true skill score of 0.967 +/- 0.018, possibly the highest classification performance achieved with any strictly parametric study. From a comparative assessment, we establish that magnetic properties like total current helicity, total vertical current density, total unsigned flux, R_VALUE, and total absolute twist are the top-performing flare indicators. We also introduce and analyze two new performance metrics, namely, severe and clear space weather indicators. Our analysis constrains the most successful ML algorithms and identifies physical parameters that contribute most to active region flare productivity.Peer reviewe

Review of nano-clay polymer composites for controlled nitrogen release: prospects and limitations

This review paper discusses the potential and limitations of polymer composites for smart nitrogen (N) supply to meet the needs of agricultural crops. Unlike most conventional fertilizers, nano-clay polymer composites (NCPCs) offer a slow-release mechanism that enhances nitrogen use efficiency and reduces its loss to the environment. NCPCs are normally synthesized using solution blending, melt blending and in situ polymerization. Solution blending offers a better clay dispersion in the polymer matrix than melt blending owing to its low viscosity and strong stirring force. NCPCs have been characterized by several techniques, including equilibrium water absorbency, Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction and nutrient release kinetics. The potential benefits of using these composites are highlighted, including improved nitrogen use efficiency and reduced environmental impacts, as are their prospects for widespread use in agriculture and mitigation of the adverse environmental effects from conventional fertilizers. In addition, the limitations of NCPC technology, such as cost, scalability and potential negative environmental effects, are also investigated. The paper provides a wide perspective on the NCPC technology, including the regulatory environment and policy, industry trends and commercialization potential. NCPCs offer many benefits to increase nitrogen use efficiency and reduce pollution affecting water quality, air quality and climate. The main current barrier to overcome is to reduce production costs, so that farmers may also benefit financially from the higher nitrogen use efficiency and associated reduced amounts of nitrogen wasted to the environment