Osmania University is a collegiate public state university located in Hyderabad, Telangana, India. The university was founded by and named after Mir Osman Ali Khan, the 7th Nizam of Hyderabad in 1918. It is the third oldest university in southern India, and the first to be established in the erstwhile Kingdom of Hyderabad. It was the first Indian university to have Urdu as a medium of instruction — but with English as a compulsory subject. As of 2012, the university hosts 3,700 international students from more than 80 nations.The O.U. is one of the largest university systems in the world with over 300,000 students on its campuses and affiliated colleges. The Osmania Medical College was once a part of the O.U. System. However, it is now under the supervision of Kaloji Narayana Rao University of Health Sciences.U.
Studying the cross-correlation function between the soft and hard X-ray emission in Neutron Star Low Mass X-ray Binaries provides crucial insight into the structure and dynamics of the innermost accretion regions. In this work, we investigate the CCF of the Z-source GX 349+2 using an XMM-Newton observation. We noted that asymmetric CCFs with lags of a few hundred seconds between soft and hard band light curves in the horizontal branch, whereas CCFs remained symmetric in normal and flaring branches. We also performed a CCF study during the flux transition duration and observed lags of the order of a few tens to hundreds of seconds. Monte Carlo simulations were performed to assess the robustness of these CCFs, confirming their significance at a 95% confidence level. We propose that the observed hard lags arise from the readjustment of the boundary layer/coronal region located near the inner edge of the accretion disk. From the measured lags, we estimate the characteristic size of the boundary layer. We show that the observed lags could also be associated with the depletion timescale of the boundary layer with low viscosity.
This literature review examines the transformative role of machine learning (ML) and deep learning (DL) in enhancing optical spectroscopy for breast cancer diagnosis. By synthesizing advancements from peer-reviewed studies (2015–2025), we evaluate how ML/DL integration improves the detection of malignancy-associated biochemical changes, enabling noninvasive, rapid, and accurate differentiation between healthy and cancerous tissues. This review highlights key spectroscopic modalities, such as Raman, fluorescence, diffusive optical spectroscopy (DOS), and photoacoustic spectroscopy (PAS), and their integration with AI-driven models, such as convolutional neural networks (CNNs), support vector machines (SVMs), and logistic regression. These techniques achieve diagnostic accuracies of up to 94
As antimicrobial resistance (AMR) continues to rise globally, there is an increasing need for antibacterial agents, and polymer nanostructures are emerging as promising candidates. In this work, we report conjugated polymer-based nanohybrids that exhibit broad-spectrum efficacy against pathogenic Gram-positive and Gram-negative microorganisms, inhibiting both microbial growth and biofilm formation. Specifically, antimicrobial nanohybrids composed of CuS nanoparticles and polyaniline (PANI) nanosheets demonstrate pronounced activity under 365 nm UV irradiation, achieving up to 70% bacterial removal at concentrations in the microgram-per-milliliter range. The CuS/PANI nanohybrids (NHs) displayed photoinduced antimicrobial activity both in suspension and as thin films deposited on glass substrates. The CuS/PANI exhibited significant zones of 13 +/- 2.01 mm and 10.5 +/- 0.70 mm against Staphylococcus aureus and Escherichia coli, respectively, as observed by agar well assay. At an MIC50 of 500 mu g/mL, a reduction in biofilm biomass by 58.72% against S. aureus and 51.03% against E. coli was observed, indicating effective prevention of bacterial adherence and significant DNA and protein leakage (12.3-7.25 mu g/mL) (12.6-8 mu g/mL), respectively. The antimicrobial effect is attributed to membrane damage, ultimately leading to bacterial death and suppression of biofilm formation. The combination of biological safety at effective antimicrobial concentrations, broad-spectrum antibacterial performance, and strong inhibition of biofilm formation highlights the potential of the polymer-based NHs reported herein as promising candidates for therapeutic applications. The photoactivated CuS/PANI nanohybrid demonstrated potent antimicrobial activity, positioning them as a promising approach for combating bacterial infections.
This study investigates the reflection of plane waves in a thermoelastic diffusion medium governed by the Moore–Gibson–Thompson (MGT) heat conduction model, incorporating both impedance boundary conditions and temperature-dependent material properties. The governing field equations are formulated by coupling mechanical, thermal, and diffusive effects, and Helmholtz decomposition is employed to identify distinct longitudinal (P), transverse shear (SV), thermal (T), and diffusive (P₀) wave modes. Analytical expressions for reflection coefficients are derived, enabling a detailed examination of wave–boundary interactions under varying physical parameters. The results reveal that impedance parameters and temperature-dependent properties significantly influence reflection amplitudes and mode conversion, while thermal diffusion enhances the contribution of diffusive wave modes. Furthermore, the interplay between thermal relaxation and diffusion is shown to alter wave propagation characteristics in a non-trivial manner. These findings provide new insights into thermo-diffusive wave behavior and establish a more comprehensive framework for modeling wave propagation in advanced engineering and geophysical materials.
This study examines the reflection behaviour of plane waves both longitudinal and transverse at an impedance boundary within a bio-thermoelastic diffusion half-space governed by the Moore-Gibson-Thompson (MGT) heat conduction model. The formulation is carried out in two dimensions using dimensionless parameters and potential functions for simplification. Analytical treatment reveals the existence of four types of longitudinal waves and one transverse wave, each propagating at distinct velocities. Amplitude ratios for longitudinal (P), thermal (T), chemical potential (Po), and shear vertical (SV) waves are derived and analyzed as functions of incident angle, frequency, and various medium parameters. The influence of impedance conditions and blood perfusion rate on reflection coefficients is illustrated graphically. Several special cases are also discussed. The findings have significant implications in biomedical engineering, geophysical exploration, and seismic wave analysis.
