Government of Andhra Pradesh

The growing demand for high-speed wireless communication has driven significant advancements in millimeter-wave (mmWave) technologies, particularly in next-generation systems like 5G and beyond. Millimeter-wave Multiple-Input Multiple-Output (MIMO) systems have emerged as a promising solution to address the need for increased data rates, capacity, and spectral efficiency. This manuscript proposes a novel approach named Mitigating Channel Power Leakage in Millimeter-Wave MIMO Systems Using an Optimized Physically Consistent Neural Network (MCPL-MW-MIMO-PCNN). Here, transmitting as well as receiving beamformers are chosen via offline training of an analog beamforming (ABF) network, which takes the channel as input. To mitigate channel power leakage, the Physically Consistent Neural Network (PCNN) is employed, aligning the channel gains of selected beams in the same direction to maximize the received signal-to-noise ratio (SNR). Finally, the Multi Objective Fitness Dependent Optimizer (MOFDO) is considered to optimize the weight parameter of the PCNN classifier, which accurately mitigates channel power leakage. The proposed MCPL-MW-MIMO-PCNN is implemented in Python. The performance of the MCPL-MW-MIMO-PCNN approach attains 18.36%, 22.58%, and 29.99% lower bit error rate and 23.58%, 24.36%, and 30.72% higher spectral efficiency when compared to the existing techniques: DL dependent analog beam forming design for mmWave massive MIMO scheme (ABD-MWMMS-TNN), DL driven hybrid beam forming technique for mmWave MIMO system (HBM-MWMS-ANN), and DL framework for beam selection and power control in M-MIMO-mmWave communications (BSPC-MIMO-LSTM) methods.

Natural farming (NF) has emerged as a promising agro-ecological tactic to enhance resource use and reduce dependence on synthetic agricultural inputs. However, comprehensive field-based evidence across diverse agro-climatic regions remains limited. This study assessed the effects of NF on water use, water and crop productivity, economic returns, energy consumption, and soil fertility across four agro-climatic zones of Andhra Pradesh, India, using a paired-field approach during 2023–2025. Compared with conventional farming (CF), NF reduced total water utilization by 16.1–39.0%, resulting in a 15.0–55.5% improvement in water productivity. Although rice yield declined marginally by 4.40–8.40% in the Southern, Krishna, and High-Altitude zones during some seasons, yields remained comparable in the Godavari zone. The cost of cultivation decreased substantially by 20.6–35.1%, while gross returns remained largely comparable between production systems, varying from −7.0% to +5.05%. Consequently, NF increased net returns by 8.8–29.0% and improved the benefit-cost ratio by 23.7–47.8% relative to CF. Irrigation-related energy consumption was reduced by 21.8–57.7%, indicating greater resource-use efficiency under NF. The sustainable yield index values remained high (0.68–0.91), demonstrating stable crop productivity despite reduced external inputs. Natural farming practices also improved soil health by buffering soil pH towards neutrality; soil organic carbon (SOC) enhanced from 0.38–0.73% under CF to 0.57–1.01% under NF. Similarly, available nitrogen, phosphorus, and potassium increased under NF. Overall, these findings demonstrate that natural farming improves water and energy productivity, reduces production costs, and increases farm profitability while maintaining stable rice productivity across diverse agro-climatic conditions. The results highlight the potential of natural farming as a climate-resilient and resource-efficient strategy for sustainable rice production in India.

Calcium Oxide nanoparticles (CaO NPs) were synthesised using Lemon Peel Powder Extract (LPE) (LPE-CaO NPs) through ultrasonic-assisted coprecipitation. The XRD pattern reveals the formation of crystalline LPE-CaO NPs with an FCC crystal structure, space group is F m-3 m, and the average crystallite size is 67.9977 nm. UV-Visible spectroscopy showed the maximum absorbance peaks at 264 nm for LPE, while the characteristic absorption at 300 nm in biosynthesised LPE-CaO NPs, indicates the CaO NPs formation. The photoluminescence (PL) study shows an intense emission peak centred at ~ 380 nm, which is consistent with the direct band gap (~ 3.181 eV) obtained from Tauc plot analysis. The FTIR peak at 522 cm − 1 , attributed to the Ca-O stretching vibrations, supports the formation of CaO NPs, while FTIR peaks of LPE at 1224 cm − 1 and 1026 cm − 1 were attributed to the C-O and C-O-C stretching vibrations, acting as reducing and capping agents in the synthesis of CaO NPs. FESEM images show nearly spherical morphology, and the average particle size of LPE-CaO NPs is 87.88 ± 19.47 nm. Electrical impedance, electric modulus, and electrical conductivity have been examined at the frequency (f) (100 Hz-1 MHz) in the temperature range (303 K-383 K). The impedance decreases with increasing temperature, indicating a negative temperature coefficient of resistance (NTCR) in LPE-CaO NPs. The relaxation peaks in electric modulus analysis shift to higher frequencies with increasing temperature, indicating a decrease in relaxation time and confirming a thermally activated relaxation process. The activation energies obtained from electrical impedance (E aZ = 0.0741 eV) and electric modulus (E aM = 0.073 eV) are closely in agreement, supporting thermally activated relaxation behaviour in LPE-CaO NPs. Therefore, these findings establish LPE-CaO NPs as a promising material for applications involving thermally activated electrical responses.

Assuming the presence of magnetic fields, heat transfer, mass transfer, and variable diffusion coefficients, this work seeks numerical solutions to the problem of two-dimensional, non-Newtonian, viscous, incompressible, electrically conducting nanofluid flow across an inclined stretched sheet. By applying the appropriate similarity adjustments, the flow’s partial differential equations are transformed into standard differential equations. The partial differential equations are also controlled by the nanofluid model and the Navier-Stokes equations. The resulting ordinary differential equations are quantitatively resolved by using the Runge-Kutta technique. Furthermore, the numbers related to the flow factors previously discussed are expressed using the Skin-friction coefficient, the Rate of Heat Transfer Coefficient (also known as the Nusselt number), and the Rate of Mass Transfer Coefficient (also known as the Sherwood number). Graphs depict how concentration, temperature, and motion patterns are affected by various physical parameters. To sum up, the current study confirms the findings of previously published studies. The research reveals that when the magnetic fluid and unsteadiness parameters increase, the velocity profiles decrease. On the other hand, when the Grashof number changes for heat and mass transfer and the suction/injection parameters change, the velocity profiles rise. The temperature curves, Prandtl number, and unsteadiness characteristics all undergo changes when the thermal conductivity parameter increases. A lower concentration curve is seen with an increase in the variable diffusion coefficient number.

This study investigates the use of coconut shells as a sustainable reinforcement material to enhance the bearing capacity of sandy soil. Laboratory model tests were conducted to assess the performance of coconut shell-reinforced sand as a foundation medium. Different shell arrangement patterns were analyzed and compared with the performance of HDPE geocells. The results indicate that coconut shell reinforcement substantially increases soil bearing capacity, from 218 kPa in unreinforced sand beds to 414.5 kPa with coconut shell mat reinforcement. Coconut shell mats present a cost-effective and environmentally friendly alternative to commercial geocells. However, their limited durability in untreated form confines their application to short-term uses, emphasizing the necessity for proper treatment to support long-term applications.