Indian classical music is entirely based on the “Raga” structures. In Indian classical music, a “Gharana” or school refers to the adherence of a group of musicians to a particular musical style of performing a raga. The objective of this work was to find out if any characteristic acoustic cues exist which discriminates a particular gharana from the other. Another intriguing fact is if the artists of the same gharana keep their singing style unchanged over generations or evolution of music takes place like everything else in nature. In this work, we chose to study the similarities and differences in singing style of some artists from at least four consecutive generations representing four different gharanas using robust non-linear methods. For this, alap parts of a particular raga sung by all the artists were analyzed with the help of non linear multifractal analysis (MFDFA and MFDXA) technique. The spectral width obtained from the MFDFA method gives an estimate of the complexity of the signal whereas the cross correlation coefficient obtained from the MFDXA technique gives the degree of correlation between two nonlinear time series. The observations give a cue in the direction to the scientific recognition of “Guru-Shisya Parampara” (teacher-student tradition)—a hitherto much-heard philosophical term. Moreover the variation in the complexity patterns among various gharanas will give a hint of the characteristic feature of that particular gharana as well as the effect of globalization in the field of classical music happening through past few decades.

In this study the impact of climate change on drought conditions in Serbia is investigated trough the multifractal analysis of standardized precipitation evapotranspiration index (SPEI). The SPEI time series for accumulation time scale of 1, 3, 6 and 12 months were calculated using the high resolution meteorological gridded dataset E-OBS with a resolution of 0.10 in regular latitude/longitude coordinates and time span from 1961 to 2020. The multifractal analysis was performed for two standard climatic periods (1961−1990 and 1991−2020) using multifractal detrended fluctuation analysis method (MFDFA) which is suitable for nonstationary temporal series. In each of 1278 grid cells that cover Serbian territory we analyzed 4 SPEI time series for two 30 years periods (which totals 10224 MFDFA runs) and calculated multifractal spectrum parameters that describe persistence, degree of multifractality and the influence of small/large fluctuations. We found that all the analyzed SPEI series show multifractal properties with the dominance of small fluctuations. The short and medium drought conditions described by SPEI-1, SPEI-3 and SPEI-6 are persistent (the position of maximum of multifractal spectrum is in the range 0.5<α0<1), stronger persistence is found at higher accumulation time scales, while SPEI-12 time series are antipersistent (0<α0-1<0.5). The degree of multifractality (width of multifractal spectrum W) increases from SPEI-1 to SPEI-6 and decreases for SPEI-12. For all series multifractal spectrum is right skewed (skew parameter r>0) indicating that small SPEI temporal fluctuations contribute more to multifractality than large fluctuations. In the second period SPEI-1 SPEI-3 and SPEI-6 series become more persistent with weaker multifractality, indicating that short and medium drought conditions (which are related to soil moisture and crop stress) become easier to predict, while SPEI-12 changed toward random regime and stronger multifractality in eastern and central part of country, indicating that long term drought conditions (related to streamflow, reservoir levels, and groundwater levels) become more difficult for modeling and prediction.

The overall seismicity of Pakistan from 24 B.C to 2020 is analysed in terms of its multifractal behaviour. Seismic events of magnitude ML=3.0 and above are spatially clustered into four distinct groups, each one corresponding to a different region of high seismic activity. The Multifractal Detrended Fluctuation Analysis (MFDA) method applied on each cluster reveals pronounced inter-cluster heterogeneity in terms of the resulting generalised Hurst exponent and fractality spectrum, possibly due to the particular tectonic characteristics of the regions under investigation. Additional results on the variability of the Gutenberg–Richter b‐value across the defined clusters further corroborate the uniqueness of the seismic profile of each region.