This paper proposes a Kretschmann configuration surface plasmon resonance (SPR) sensor setup incorporating gold and graphene quantum dot (GQD) bilayers for the detection of uric acid (UA) solution. The confirmation of the deposition of gold and GQD films onto the sensor substrate was accomplished through the utilization of a field emission scanning electron microscope (FESEM) and energy-dispersive X-ray spectroscopy (EDX). Analysis revealed an average film thickness of 55.4 nm for the gold film and 5.8 nm for the GQD film. Different concentrations of UA solution were tested with the proposed setup and the performance was evaluated in terms of sensitivity, linearity, limit of detection (LOD), binding affinity, full width at half maximum (FWHM), detection accuracy (DA), signal-to-noise ratio (SNR), and figure of merit (FOM). The sensitivities achieved for the SpR sensors were 0.23%/(mg/dL) and 3.77%/(mg/dL) with correlation coefficients of 0.0318 and 0.825 for gold and gold-GQD, respectively. The corresponding LODs were 32.85 mg/dL and 4.74 mg/dL, with binding affinity constants of 91.87 μM ^-1 and 89.18 μM ^-1 , respectively. Adding GQD to the gold film increased the sensitivity of the SPR sensor substantially while demonstrating excellent reproducibility, repeatability, and reusability, exalted DA and SNR, constricted FWHM, and superlative FOM. These outcomes harbor the potential to spark a proficient and modest technique that enables the detection of UA in saliva, thus expediting near-patient testing.

Energy audit and reliability assessment of distribution systems are important to keep track of power system's performance. This will in turn help to minimize power interruptions to customers, boost industrialization, research, and economic development in any nation. In this paper, we present the reliability assessment of power distribution in Afe Babalola University, Ado-Ekiti, Nigeria which is a private University with an estimated population of about 10,500 and having a peak power demand of 2MW. A critical assessment of the power distribution system was carried out with data obtained from the campus's central Substation, taking into account various reliability indices. Furthermore, the load consumption of each substation was obtained from the period of January, 2017 to December, 2017. The results obtained show that the University attained a power availability (ASAI) of 0.99984 because of the presence of strategically placed distributed generators (DGs). The reliability assessment revealed SAIDI as 1.4347 hours /customer year, CAIDI as 0.6620 hours/customer interruption, ASUI as 0.00016, and SAIFI as 2.16712 failures/ customer year. Furthermore, the study revealed that the university spends more on diesel generators than on the electricity supplied from Benin Electricity Distribution Company (BEDC). The aforementioned reliability results reveal that power distribution in Afe Babalola University is very reliable, efficient and stable.

Power system components are susceptible to failures which causes undesirable interruptions to consumer's power supply thus affecting the overall power system availability. Reliability evaluation is therefore important in power system studies to ensure continuity of power supply in line with the country's increasing population and the need to foster industrialization. This study is centered on reliability assessment of Mofor Injection Substation. This assessment evaluates the performance of the Mofor Injection substation considering various system parameters which contribute to the seamless operation of the station. Historical data obtained from the power substations from January, 2017 to December, 2017 were used to analyze the Injection Substation power reliability. The results obtained revealed a power availability index (ASAI) of 0.7683796 and 0.768968 for Ekete and Orhuwhorun substations respectively. Also, other reliability indices evaluated were SAIDI, CAIDI and SAIFI. The aforementioned reliability results reveals that power distribution at Mofor injection substation can be said to be unreliable, inefficient, undesirable and unstable.

This study presented a surface-functionalized sensor probe using 3-aminopropyltriethoxysilane (APTES) self-assembled monolayers on a Kretschmann-configured plasmonic platform. The probe featured stacked nanocomposites of gold (via sputtering) and graphene quantum dots (GQD, via spin-coating) for highly sensitive and accurate uric acid (UA) detection within the physiological ranges. Characterization encompassed the field emission scanning electron microscopy for detailed imaging, energy-dispersive X-ray spectroscopy for elemental analysis, and Fourier transform infrared spectroscopy for molecular identification. Surface functionalization increased sensor sensitivity by 60.64%, achieving 0.0221 °/(mg/dL) for the gold-GQD probe and 0.035 5 °/(mg/dL) for the gold-APTES-GQD probe, with linear correlation coefficients of 0.8249 and 0.8509, respectively. The highest sensitivity was 0.070 6 °/(mg/dL), with a linear correlation coefficient of 0.993 and a low limit of detection of 0.2 mg/dL. Furthermore, binding affinity increased dramatically, with the Langmuir constants of 14.29 µM ⁻¹ for the gold-GQD probe and 0.000 1 µM ⁻¹ for the gold-APTES-GQD probe, representing a 142 900-fold increase. The probe demonstrated notable reproducibility and repeatability with relative standard deviations of 0.166% and 0.013%, respectively, and exceptional temporal stability of 99.66%. These findings represented a transformative leap in plasmonic UA sensors, characterized by enhanced precision, reliability, sensitivity, and increased surface binding capacity, synergistically fostering unprecedented practicality.

Accurate and sensitive biomarker detection is vital for modern diagnostics, especially in point-of-care testing (POCT), where real-time analysis is essential. Uric acid (UA), a key indicator of metabolic disorders including gout, nephropathy, and cardiovascular disease, requires precise quantification across physiologically relevant ranges in complex matrices. Conventional UA detection methods suffer from instability, poor selectivity, and susceptibility to interference. This letter presents an innovative nonenzymatic hybrid surface plasmon resonance–localized surface plasmon resonance (SPR-LSPR) sensor that combines the long-range sensitivity of SPR with the near-field enhancement of LSPR. The platform incorporates a nanostructured gold-3-aminopropyltriethoxysiane-gold nanoparticle-graphene quantum dots (Au-APTES-AuNP-GQD) matrix, leveraging gold thin films, amine-functionalized AuNP, and GQD to enhance plasmonic confinement and molecular recognition. Structural and optical characterizations confirmed its nanoscale integrity. The sensor achieved a sensitivity of 0.1828°/(mg/dL), a low detection limit of 0.1658mg/dL, and linearity (R² = 0.8655) across a 1–9mg/dL UA physiological range. It demonstrated high selectivity, with a 1.1757° shift and 90.1% relative response to UA in the presence of common interferents. This label-free, real-time, and scalable sensor is highly suited for POCT and continuous UA monitoring, with modular adaptability for broader clinical biomarker detection.