Maharaja Agrasen University

The Indian monsoon is a distinct meteorological phenomenon of vital socio-economic importance in the Indian subcontinent. Analysis of available Indian and regional datasets spanning over a century provides critical insights into rainfall variability. Two major characteristicsA-long-term trend and breakApointsA-have been analysed for Indian summer monsoon rainfallA(ISMR) and Kerala summer monsoon rainfall (KSMR). AKerala is selected as it marks the onset of monsoon in India. Trend analysis was performed using the non-parametric Mann-Kendall test, suited for detecting monotonic trends in non-normal data, under the null hypothesis of no trend at the 95% confidence level for both ISMR and KSMR. Break points, indicating shifts in rainfall regimes, were identified using a Bayesian change point detection method. Prediction of seasonal rain is vital for planning and governance, and machine learning models are proven tools for accurate meteorological prediction. However, whether such predictions can sustain long-term statistical characteristics remains underexplored. In this study, we developed ML models to assess if predictions preserve the observed trends and parameters across break point intervals. The best-performing LSTM model (lag = 12) achieved RMSE of 147 (train) and 167 (test) with correlations >= 0.85, reproducing 4 of 5 observed break points and matching Mann-Kendall trend results. The findings demonstrate that ML-based long-term seasonal monsoon modelling can retain trends, break points, and statistical parameters over multi-decadal horizons.

This study investigates the enhancement of mechanical performance in polylactic acid (PLA) components fabricated using fused deposition modeling (FDM) through the application of a zinc coating via the electric arc thermal spray process. Three major parameters of FDM processing such as infill density (60, 80 and 100 percent), printing speed (20, 40 and 60 mm/s) and the infill pattern (linear, triangular and hexagonal) were systematically studied on tensile and flexural strengths of the coated PLA specimens. Moreover, the experimental design was optimized by means of Taguchi L9 orthogonal array and mechanical properties (tensile and flexural strength) were determined with the help of a universal testing machine (UTM). The findings indicate that tensile and flexural behaviors are controlled by unique optimum combinations of the parameters. The highest tensile strength of 53.44 MPa was achieved at 100 percent infill density, a print speed of 40 mm/s and triangular infill pattern. However, the highest flexural strength of 146.6 MPa was achieved at 100 percent infill density, a print speed of 20 mm/s and hexagonal infill pattern. These results reveal that incorporating FDM with electric arc thermal spray coating could provide a promising path to boosting dramatically the mechanical performance of 3D-printed PLA components to expand their scope of use in high-end engineering disciplines.

Potentilla argyrophylla Wall. ex Lehm., a significant medicinal plant employed in Ayurveda, Siddha, Sowa-Rigpa, and Chinese medicine, was collected from Kunzum Pass (altitude similar to 4590 m), Spiti Valley, a UNESCO-recognized Cold-Desert Biosphere, Himachal Pradesh, India. The aerial parts were analyzed for phytochemical content, antioxidant, antimicrobial, and alpha-amylase inhibitory activities, and employed phytofabrication of silver nanoparticles. Synthesized silver nanoparticles (PoSNPs) were characterized using UV spectroscopy, x-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, high-resolution transmission electron microscopy, energy-dispersive x-ray spectroscopy, and selected area electron diffraction analyses. Antimicrobial potential was examined against Candida albicans MTCC 227, Bacillus cereus BCS1, Streptococcus mutans MTCC 890, and Escherichia coli MTCC 443. Total phenol content was higher in methanol extract, while acetone extract was richer in flavonoids and tannins. Both extracts possessed antimicrobial (highest MIC 625 & micro;g/ml against S. mutans), antioxidant (IC50 76.14 and 58.69 & micro;g/ml for acetone and methanol extracts, respectively), and alpha amylase inhibition (IC50 2.08 and 5.41 mg/ml for acetone and methanol extracts, respectively) potentials. Notably, crystalline and almost spherical PoSNPs outperformed their parent extract in antimicrobial (MIC 3.91 & micro;g/ml against S. mutans) and antioxidant (IC50 12.94 & micro;g/ml) activities, highlighting their potential for biomedical applications.

The current study demonstrates a green synthesis of MoO₃-CeO₂ doped CuO nanocomposites supported on Pinus roxburghii biochar (PRB/MCCu), using Syzygium cumini leaf extract. The physicochemical properties of synthesized PRB/MCCu nanocomposites were examined using XRD, FTIR, XPS, FESEM–EDX, HRTEM, BET, TGA and ESR analyses. The synthesized PRB/MCCu nanocomposites exhibits a uniform metal oxide distribution, higher surface area (137.76 m² g⁻¹), an average pore diameter of 4.23 nm, and reduced band gap of 2.42 eV. The efficiency of PRB/MCCu nanocomposites has been assessed using adsorption and degradation (photocatalysis + sono-photocatalysis) experiment. The cefixime (CFX) adsorption followed the Langmuir isotherm (R² = 0.99), indicating monolayer adsorption, while kinetic data best fitted the pseudo-second-order model (R² > 0.98), confirming chemisorption as the dominant mechanism. The adsorption of cefixime (CFX) was strongly pH-dependent, showing maximum removal at pH 5.0 and mainly due to enhanced electrostatic attraction, hydrogen bonding, and π–π interactions between CFX and functionalized PRB/MCCu surface. While maximum degradation of 94.98

In this work, we examine the cosmological viability of an accelerating Brans-Dicke universe in the presence of Tsallis holographic dark energy, extending earlier study that employed a logarithmic form of the Brans-Dicke scalar field in a spatially flat Friedmann-Robertson-Walker space-time. While previous analysis has primarily focused on late-time acceleration, we investigate both early and late-time cosmic evolution within this framework. The dynamical behavior of the deceleration and equation-of-state parameters is analyzed to assess whether the model can qualitatively reproduce the known expansion history of the universe, including an inflationary phase and the subsequent decelerated era. We further examine the evolution of the matter to dark energy density ratio and find that it varies sufficiently slowly at late times, indicating a soft alleviation of the cosmic coincidence problem. In addition, the generalized second law of thermodynamics is employed as a consistency test to assess the thermodynamic viability of the model during different evolutionary epochs. The standard energy conditions are also investigated as consistency checks rather than as sources of novel phenomenology. Our results indicate that the considered Tsallis holographic dark energy scenario within Brans-Dicke theory provides a self-consistent and analytically tractable framework for describing the qualitative features of cosmic evolution.