IIS University, officially IIS (Deemed to be University), is a private higher education institute deemed to be university, located in Jaipur, Rajasthan, India. Formerly International College for Girls (ICG), it was conferred the deemed university status in 2009.
Withania coagulans (Stocks) Dunal is a “Near-Threatened” medicinal herb valued for its bioactive withanolides, yet its natural regeneration remains poor. This study evaluated the responses of in vitro cultured shoot tip and nodal explants to graded supplementation of Mn, Zn, and Fe in the culture medium (1x, 5x, 10x, 20x, 30x, and 50x Murashige and Skoog levels) to assess their effects on morphogenesis, antioxidant activity, and micronutrient accumulation. It was hypothesised that moderate micronutrient enrichment would enhance growth and antioxidant activity, whereas higher levels would inhibit development. Moderate supplementation, particularly at 10x–20x levels, significantly improved regeneration efficiency (up to 95
Air pollution poses a significant public health risk, as pollutants, emitted from both natural and anthropogenic sources, can penetrate deep into the respiratory system, leading to a wide range of respiratory diseases. While numerous studies have examined the role of meteorological factors in modulating air quality, limited research has focussed specifically on their effectiveness in regions characterized by intensive mineral extraction activities, particularly coal mining zones where emission loads remain persistently high. In this context, the concentration levels of PM10, PM2.5, SO2, and NO2 were continuously monitored for one year using an automated ambient air quality monitoring system to investigate their seasonal behaviour and meteorological interactions. The recorded concentration ranged from 17.49 to 393.40 µg/m3 for PM10, 5.45 to 231.53 µg/m3 for PM2.5, 12.3 to 62.05 µg/m3 for NO2, and 11.59 to 182 µg/m3 for SO2. The pollutant concentrations peaked during winter and declined during summer and monsoon seasons. The trend analysis using Theil–Sen estimator revealed significant negative trends for all four pollutants PM10 (− 181.79 units), PM2.5 (− 106.11 units), SO2 (− 22.76 units), and NO2 (− 29.89 units). The linear regression analysis demonstrated a strong correlation between PM10 and PM2.5 (R2 = 0.89), whereas a weak association (R2 = 0.01) was observed between NO2 and SO2. Nonlinear regression further indicated temperature as a key influencing factor, showing a strong inverse relationship with NO2 (− 13.218) and a moderate negative impact on PM2.5 (− 1.517). Overall, the findings of this study underscore highlight the seasonal vulnerability of coal mining regions to pollutant accumulation and highlights the limitations of mechanisms under elevated emission scenarios. Furthermore, this study establishes temperature as a boundary-layer control variable and emphasizes that effective air-quality management in coal-mining regions must integrate real-time meteorological forecasting with emission scheduling for sustainable air-quality compliance.
The boom in urbanization has exerted heavy stress on energy requirements and infrastructural sustainability and buildings occupy approximately a quarter of the world energy consumption and a third of the greenhouse gas emission. This is the main issue that is addressed in the United Nations Sustainable Development Goal 11 (SDG 11), the goal that promotes sustainable cities and communities. The concept of Artificial Intelligence (AI) has already become a strong tool to enable real-time predictions of building energy, optimization, and control, though a thematic synthesis of this accumulation of research has stayed scarce. In this paper, the bibliometric and thematic analysis is performed on 947 articles that are indexed by Scopus and published in the period of 2020-2026 on the topic of using AI in the context of energy-efficient buildings. The findings indicate that there has been a sudden rise in the number of publications since 2020 with the greatest contributors being China, the United States, the United Kingdom, and India and prominent journals being Applied Energy and Sustainable Cities and Sustainability. It identifies five major research clusters, namely: HVAC optimization, occupancy detection, smart energy management systems, renewable energy integration and digital twins. In addition to deep learning and machine learning, which are the focus of modern studies, reinforcement learning and computer vision demonstrate good prospects of adaptive, occupantcentric control. Such issues as scalability, interoperability, data privacy, and deployment cost are still present, which reveals some directions on the way in which future research can be focused on the development of SDG 11.
Stroke is a leading cause of long-term disability, with spasticity being one of the most common complications affecting functional mobility and quality of life in hemiparetic patients. Although therapeutic exercises remain the cornerstone of post-stroke rehabilitation, complementary therapies such as herbal massage oils have gained attention for their potential to enhance recovery. This comparative study aims to investigate the synergistic effects of Dr. JAF (Paralysis Oil) combined with therapeutic exercises on spasticity management in post-stroke hemiparetic patients. The study compares the outcomes of patients receiving therapeutic exercises alone with those receiving a combination of Dr. JAF (Paralysis Oil) and therapeutic exercises. Clinical parameters such as muscle tone, range of motion, motor function, pain, and functional independence are evaluated using standardized assessment scales. It is anticipated that the combined intervention will produce greater reductions in spasticity and improved functional outcomes compared with exercise alone. The findings may provide evidence for integrating complementary herbal therapy with conventional physiotherapy to optimize post-stroke rehabilitation
The electronic structure, lattice dynamics, bonding, elastic response, and anisotropic thermoelectric transport properties of tetragonal GeS_2 and GeSe_2 were investigated using density functional theory, density functional perturbation theory, Wannier interpolation, and scattering-aware Boltzmann transport. The relaxed structures are mechanically and dynamically stable within the calculated harmonic description. The HSE03/Wannier band gaps are 2.48 eV for GeS_2 and 1.23 eV for GeSe_2, while substitution of S by Se lowers the upper phonon frequency from approximately 13.6 to 10.3 THz. The phonon Boltzmann transport calculations reveal pronounced lattice-transport anisotropy. Within the relaxation-time approximation, the 300 K in-plane and cross-plane lattice thermal conductivities are 26.86 and 1.19 W m^-1 K^-1 for GeS_2, and 18.74 and 1.52 W m^-1 K^-1 for GeSe_2, respectively. At 800 K, these values decrease to 10.22 and 0.46 W m^-1 K^-1 for GeS_2, and 7.25 and 0.58 W m^-1 K^-1 for GeSe_2. Frequency-resolved analysis shows that low-frequency phonons carry most of the heat, whereas the small cross-plane values reflect restricted out-of-plane phonon transport. Combining the ShengBTE RTA lattice tensors with AMSET electronic coefficients gives zT=0.257 for n-type cross-plane GeS_2 at 800 K and 10^19 cm^-3. The corresponding PBE-AMSET estimate for GeSe_2 is zT=0.066 for p-type cross-plane transport at 800 K and 3×10^20 cm^-3. LOBSTER analysis identifies mixed covalent–ionic Ge–X bonding, with Ge–S bonds having a larger stabilizing ICOHP magnitude than Ge–Se bonds (-5.27 versus -4.74 eV per bond). These results identify tetragonal GeX_2 compounds as strongly anisotropic thermoelectrics with moderate calculated zT values whose cross-plane response benefits from suppressed lattice heat transport.
