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This study examined the Muhurat Trading effect on select top five companies of Textiles and Apparel Industries of India from 1st January 2013 to 31st December 2022. In this paper, the differences in mean returns on Muhurat Trading day to pre-Muhurat Trading, post-Muhurat Trading, and regular Trading day have been examined by using the non-parametric Mann-Whitney U test. We found Muhurat Trading days mean returns five to fifteen times higher than regular trading day mean returns for the select companies but It was statistically significant (at 0.01 and 0.05 levels of significance) only for Trident Ltd and Welspun India Ltd. Similarly, we also found superior positive returns on Muhurat Trading in comparison to pre-Muhurat Trading as well as post-Muhurat Trading day returns but statistically insignificant. [ABSTRACT FROM AUTHOR]

Topography evolves under the coupled effect of exogenic and endogenic governing factors, and their scale‐(in)variant dynamics. This results in a self‐affine topography across a finite range, with a characteristic fractal dimension. Fractal analysis has been used to classify geological terrains having distinct litho‐tectonic settings. However, process‐based understanding of the fractal behaviour of a natural landscape is still limited. The current study aims to substantiate and expand upon the present knowledge of topographic response to the complex actions of the governing factors using fractal characteristics. We examined the association between the litho‐tectonic, climatic settings and the fractal characteristics of the topography in the tectonically active Northwest Himalaya. Our analysis was carried out in three separate sectors having diverse litho‐tectonic settings. We used the roughness–length method to calculate the fractal parameters (fractal dimension, D; ordinate intercept, q). The Higher and the Lesser Himalaya were found to be characterized by low D and high q, while the tectonically active Sub Himalaya was found to have moderate D and low q. The southernmost foreland alluvial plains were characterized by high D and low q. Clusters of the fractal parameters were found to be consistent in spatial pattern across the three sectors. Our results showed that the geological–geomorphological settings and the associated processes (e.g. uplift, erosion and diffusion) can be well inferred using the fractal characteristics of the topography. Further, our results implied first‐order control of lithology in sustaining and shaping the topographic geometry (both its amplitude and texture) in the tectonically active Northwest Himalaya. The spatial distribution of the fractal parameters also suggested the secondary control of tectonic uplift and, to a much lesser extent, mean annual rainfall on the topographic geometry. These results collectively point to the role of complex actions of the governing factors in the landscape evolution process. © 2020 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Analyzing engineering colleges in India with Data Envelopment Analysis (DEA) is the focus of this study. Engineering colleges pioneer in teaching and research, creating two sub-processes within engineering education. Thus, our study considers each engineering college to comprise two parallel non-homogenous sub-processes, such as teaching and researching. Unlike the conventional DEA models, where the system is treated as a black box, this work attempts to independently assess the impact of each parallel sub-process so that it is possible to identify specific changes in the respective processes to improve the overall efficiency. In particular, our study analyzed the efficiency of engineering colleges based on the National Institute Ranking Framework (NIRF) data. Further, the comparison of the efficiency scores from teaching and research indicates that, on average, the institutes are more efficient in teaching than researching. The current study helps policymakers set priorities and course corrections for performance improvement programs of engineering colleges in India. • We consider parallel non-homogeneous sub-processes in Data Envelopment Analysis (DEA) model. • We proposed the variable return to scale model for parallel non-homogeneous sub-processes in DEA. • We applied the above methodology to engineering colleges in India, with teaching and research being sub-processes. • We found that engineering colleges are more efficient in teaching than research. • With a ranking system like the NIRF, colleges have improved their efficiency. [ABSTRACT FROM AUTHOR]