This article introduces a compact four-port MIMO antenna specifically developed for use in 5G midband and ultra-wideband communication systems. The proposed antenna features a compact structure with four symmetrical monopole radiating elements arranged in a closely spaced configuration (less than λmax/2), enabling efficient space utilization without using any decoupling structures in between the radiating elements. Machine learning (ML) algorithms namely random forest, decision tree and K-nearest neighbour (KNN) were employed to predict S-parameters from antenna design features, with KNN achieving the best accuracy and lowest mean squared error. Unlike traditional HFSS-based parametric sweeps, this work integrates ML regression with grid search to optimize element spacing, minimizing total S-parameter error across the frequency range. This approach significantly reduces simulation effort while ensuring optimal performance for compact, high-isolation MIMO antennas. The antenna is fabricated using FR4 substrate (εr = 4.4) and measures only 60 × 60 × 1.6 mm3. An operational bandwidth of 9.9 GHz (2.1–12 GHz) and strong isolation of 15 dB are offered. The MIMO characteristics are validated using diversity parameters such as envelope correlation coefficient (ECC), diversity gain (DG), mean effective gain (MEG) and total active reflection coefficient (TARC). The designed antenna demonstrates excellent MIMO performance exhibiting an average ECC of 0.0304, DG close to 9.99 and MEGij difference below 0.94 dB. It offers TARC under − 10 dB and exhibits a signal group delay below 0.25 ns confirming strong diversity and MIMO performance across the intended wide frequency band.
Masonry walls continue to play a vital role in modern construction due to their functional benefits in partitioning, privacy, and acoustic insulation. However, their inherent brittleness and limited tensile capacity restrict structural performance, particularly under in-plane and out-of-plane loading. This study investigates the efficacy of Engineered Cementitious Composites (ECC) as a plastering material for enhancing masonry walls. Eight wallette specimens were fabricated, including one pair of conventional specimens plastered with 1:5 cement–sand mortar and three pairs of ECC-strengthened specimens incorporating different fibre types. Static loading tests were conducted under both in-plane (axial compression) and out-of-plane (flexural) conditions, with height-to-length ratios ranging from 1.0 to 1.5 to capture failure modes such as rocking, toe crushing, and diagonal splitting. Results indicate that ECC-strengthened masonry significantly enhances structural performance by reducing crack propagation and increasing load-carrying capacity compared to conventional masonry. Under in-plane loading, polyvinyl alcohol (PVA) fibre-reinforced ECC improved load resistance by 44
The phenomenon of cash-for-vote is a significant threat to the integrity of electoral processes. This paper presents a maximum flow network interdiction model tailored for the Election Commission of India (ECI) to prevent the flow of illicit cash during elections. We formulate the problem mathematically and propose implementation strategies. We model the cash-for-vote scenario as a directed graph G=(V,E) , where V is the set of nodes representing entities such as political party offices, agents, intermediaries, local distributors, and voters etc., and E is the set of directed edges representing the cash flow routes with its capacities. The political party’s goal is to maximize the flow within the network to influence voters, while the Election Commission of India (ECI) seeks to reduce the maximum cash flow in the distribution network using the least amount of available resources. This work proposes a bilevel optimization problem where one optimization problem serves as a constraint to another. At the upper level, the ECI’s objective is to minimize cash flow, whereas at the lower level, the political party aims to maximize it. The two-stage problem is transformed into a single minimization problem by taking the dual of the inner problem. The resulting problem is then linearized into a mixed integer programming (MIP) problem and solved by standard commercial solvers. The model is tested on the generated realistic data sets that reflects political party’s cash flow at each level of the network. Computational analysis of these test cases offers guidance on the interdiction decisions that the commission should adopt for their efforts to prevent cash flow. We also address the different variants of the model, its mathematical approach to solve and future research directions to pursue.
Paracetamol based benzoxazines (PA-Bz) were synthesized using structurally different amines namely 4-aminoacetanilide (AAC), aniline (AN), adamantylamine (AM) and 1,12-diaminododecane (DAD) through Mannich condensation (PA-AAC, PA-AN, PA-AM, PA-DAD). The molecular structure of the synthesized benzoxazines was confirmed through spectroscopic techniques. DSC studies showed that curing temperature of the synthesized benzoxazines are ranged between 205 and 232 degrees C. TGA results showed that poly(PA-DAD) showed the highest maximum degradation temperature of 452 degrees C. Contact angle measurement revealed that poly(PA-AM) exhibited the maximum water contact angle value of 142 degrees. The contact angle studies clearly showed that the resulting polymer can be used for the coating purpose as a hydrophobic sealant. Both PA-AM and its corresponding polymer demonstrated the higher antimicrobial activity. All the synthesized compounds showed 99% corrosion inhibition efficiency. The swelling ratio and high gel content of poly(PA-AN) and poly(PA-DAD) proved its higher crosslinking density. The results obtained on different analysis indicated that the synthesized benzoxazines can be used effectively in coating application, oil-water separation process and also to inhibit the microbial growth on the surface.
The precise and simultaneous determination of nucleobases plays a key role in disease diagnostics, genetic research, and food safety monitoring. In this endeavour, we demonstrate for the first time the application of nickel cobalt oxide (NiCo2O4) nanostructures, synthesized via a sustainable Aloe vera-mediated method, for the electrochemical detection of nucleobases. This first report of Aloe vera-mediated NiCo2O4 enables ultralow limit of detection (LoD) values for guanine (G), adenine (A), thymine (T), and uracil (U), ranging from 0.0040 to 0.0151 mu M, with wide linear ranges and exceptional sensitivities (12.07-83.81 mu A cm- 2 mu M- 1) using differential pulse voltammetry (DPV). The engineered morphology, defect-rich surfaces, and reduced crystallite size of NiCo2O4, authenticated by X-ray diffraction (XRD), Raman, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM), enhance charge-transfer properties, governed by the harmonious Ni2+/Ni3+ and Co2+/Co3+ redox couples. Integrated into a glassy carbon electrode (GCE), this green-synthesized nanocatalyst exhibits high selectivity against common interferents and superior stability, proposing a sustainable, highperformance platform for nucleic acid analysis.
