An analytic solution for propagation of blast waves in stellar interiors

B, V observations of the eclipsing binary RS CVn have been presented. A dip around 0 ^p . I appears to be a wave minimum which fits well in the Wave minimum phase-time relation, but deviates from the Wave aplitude-time relation, derived for the RS CVn. Either, the Wave amplitude-time relation requires a modification or the amplitude of the wave minmum appears masked by the intrinsic variability of one of the components or by the Sun-spot activity of the system. The colour exhibits variation. The secondary component appears active.     

Period variation of BZ Eridani

We find that the Chandrasekhar-Kendall functions (A) do not satisfy the identity (A·)A=(×A)×A+1.2A² and, therefore, the results, in magnetohydrodynamics and other fields, obtained by two independent authors may differ from one another.     

Light variability in ɛ UMA

FirstU, B, andV observations of UMa are presented. Light curves show light variations of varying amplitude. Colour indices also show small colour variations.     

Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data

ABSTRACT

We study the problem of landuse characterization at the urban-object level using deep learning algorithms. Traditionally, this task is performed by surveys or manual photo interpretation, which are expensive and difficult to update regularly. We seek to characterize usages at the single object level and to differentiate classes such as educational institutes, hospitals and religious places by visual cues contained in side-view pictures from Google Street View (GSV). These pictures provide geo-referenced information not only about the material composition of the objects but also about their actual usage, which otherwise is difficult to capture using other classical sources of data such as aerial imagery. Since the GSV database is regularly updated, this allows to consequently update the landuse maps, at lower costs than those of authoritative surveys. Because every urban-object is imaged from a number of viewpoints with street-level pictures, we propose a deep-learning based architecture that accepts arbitrary number of GSV pictures to predict the fine-grained landuse classes at the object level. These classes are taken from OpenStreetMap. A quantitative evaluation of the area of Île-de-France, France shows that our model outperforms other deep learning-based methods, making it a suitable alternative to manual landuse characterization.     

Risk,perception and adaptation to climate change: evidence from arid region,India

The paper contributes to the growing literature highlighting the significance of assessing risk and vulnerability, micro-level perceptions and adaptation decision-making in building resilience of farm communities to climate change in dryland region of India. To select a region for grassroots enquiry, spatial differential in risk to climate change was assessed in Rajasthan, using IPCC AR5 framework. Among the highly vulnerable and risky districts, Bikaner district was selected for elicitation of micro-level imperatives. Rising atmospheric temperature, inter-seasonal displacements of rainfall and recurrence of extreme events were perceived by the farmers resulting in resource degradation, production risks and erosion of households’ socio-economic dynamics. As risk preventive measures, suitable adjustment in agricultural practices, natural resource management, shift to off-farm activities and other relief measures were adopted by the farmers. Farmer’s choice of adaptation was influenced by several climatic, socio-economic and infrastructural & institutional factors in varying degree. Moreover, several financial, economic, infrastructural and informational bottlenecks to adaptations were reported during household survey and FGDs. The results suggest that capturing grassroots evidence is crucial for directing locally tailored adaptation strategies, along with the improving deficiencies in the developmental pathways for climate-resilient agriculture.

     

Petrology, geochemistry and genesis of newly discovered Mesoproterozoic highly magnesian, calcite-rich kimberlites from Siddanpalli, Eastern Dharwar Craton, Southern India: products of subduction-related magmatic sources?

The Siddanpalli kimberlites constitute a newly discovered cluster (SKC) of Mesoproterozoic (1090 Ma) dykes occurring in the granite-greenstone terrain of the Gadwal area in the Eastern Dharwar Craton (EDC), Southern India. They belong to coherent facies and contain serpentinized olivines (two generations), phlogopite, spinel, perovskite, ilmenite, apatite, carbonate and garnet xenocrysts. A peculiar feature of these kimberlites is the abundance of carbonate and limestone xenoliths of the eroded platformal Proterozoic (Purana) sedimentary cover of Kurnool/Bhima age. Chemically, the Siddanpalli dykes are the most magnesium-rich (up to 35 wt.% MgO) and silica-undersaturated (SiO₂?<?35 wt.%) of all kimberlites described so far from the Eastern Dharwar Craton. The La/Yb ratio in the Siddanpalli kimberlites (64–105) is considerably lower than that in the other EDC kimberlites (108–145), primarily owing to their much higher HREE abundances. Since there is no evidence of any crustal contamination by granitic rocks we infer this to be a specific character of the magmatic source. A comparison of the REE geochemistry of the Siddanpalli kimberlites with petrogenetic models for southern African kimberlites suggests that they display involvement of a wide range in the degree of melting in their genesis. The different geochemical signatures of the SKC compared to the other known kimberlites in the EDC can be explained by a combination of factors involving: (i) higher degrees of partial melting; (ii) relatively shallower depths of derivation; (iii) possible involvement of subducted component in their mantle source region; and (iv) previous extraction of boninitic magmas from their geological domain.     

New legume fruits from the oligocene sediments of Assam

For the first time a rich assemblage of legume fruits is described from the Late Oligocene sediments of the Makum as well as Dilli-Jeypore coalfields of Assam. A new genus Buteocarpon has been instituted for the fossil fruits resembling Butea Roxb. of the family Fabaceae. In addition, six new species of the genus Leguminocarpon Goeppert are also described. Their presence indicates a warm and humid climate in the region during the deposition of the sediments.