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Now showing 1 - 5 of 11

Recent Submissions

Fabrication of iridium-gold nanocomposite for the detection of selective serotonin reuptake inhibitors
(International Association of Physical Chemists, 2026) Barry, Simone; Cupido, Candice; Pokpas, Keagan; Mulaudzi, Takalani; Ngece-Ajayi, Rachel Fanelwa
A comprehensive study of the development of a novel electrochemical sensor based on iridium-gold nanocomposite (IrAuNPs) modified electrodes for the detection of antidepressants, paroxetine (PRX) and citalopram (CIT) was conducted. The sensing platform, based on a glassy carbon electrode, was modified by drop-casting IrAuNPs, which allowed for enhanced conductivity. IrAuNPs, along with their counterparts iridium nanoparticles (IrNPs) and gold nanoparticles (AuNPs), were synthesized from coffee waste extract (CWE) via complete green chemistry. The physicochemical properties of synthesized nanomaterials were characterized using ultraviolet-visible spectroscopy, dynamic light scattering, highresolution transmission electron microscopy, Fourier-transform infrared spectroscopy, cyclic voltammetry and square wave voltammetry. Results showed that the CWE could reduce the respective metallic salts to form mostly near-spherical to spherical IrAuNPs, IrNPs and AuNPs with core sizes ranging from 2.02 nm to 13.27 nm. The electrochemical sensor could determine PRX and CIT in the concentration ranges of 20 to 200 nM and 1 to 10 µM, with detection limits of 0.072 nM and 0.085 µM, respectively. The sensor showed a recovery of 86 to 115.1 %. The proposed sensor demonstrated good precision and accuracy, with excellent sensitivity and selectivity for drug identification in a rapid analysis time, which is crucial for applications in biological matrices.
Understanding the spatiotemporal variation of water quality and phytoplankton biomass in subtropical reservoir using the blue–sky multispectral data
(John Wiley and Sons Ltd, 2025) Dube, Timothy; Dalu, Tatenda; Muthivhi, Faith F.
Chlorophyll-a (chl-a) is an optically active compound used as a proxy for phytoplankton biomass to determine the trophic states of aquatic ecosystems. Blue–sky remote sensing technologies present low-cost and effective monitoring techniques for water quality on a large scale. This study was aimed at using readily available Landsat multispectral images to assess the spatial and temporal variation of phytoplankton biomass in Nandoni reservoir, Limpopo Province, and at examining the relationships that exist between the physicochemical variables and chl-a concentration. Landsat 7 ETM+ and Landsat 8 OLI images for June (dry) and December (wet), for the years 2008–2020, were used to derive the distribution of chl-a concentration. Using regression techniques, in situ measured chl-a showed a strong and perfectly linear relationship to the predicted Landsat chl-a in the Nandoni reservoir. There was a negative significant correlation between land use and land cover and water quality variables. Using permutational multivariate analysis of variance (PERMANOVA) analysis, we uncovered significant differences for chl-a concentration in sites, seasons and zones. A significant positive correlation was observed between water temperature and chl-a concentration. In contrast, a strong negative significant correlation was observed for chl-a with salinity and total dissolved solids. chl-a concentration in the Nandoni reservoir was derived using Landsat remote sensing images, suggesting that the Landsat data is suitable for monitoring small reservoirs in a short timescale. The results of this study suggest that remote sensing techniques can be used to control the development of an early warning system for this study and other reservoirs. Furthermore, the results highlight the role of using analysis ready Landsat series data in monitoring phytoplankton biomass and chl-a abundance in freshwater systems.
Crafts for H i cosmology. I. Data processing pipeline and validation tests
(American Astronomical Society, 2025) Hu, Wenkai; Yang, Wenxiu; Wolz, Laura
We present the calibration procedures and validation of source measurement with the data of the Commensal Radio Astronomy FAST Survey for H i intensity mapping by the Five-hundred-meter Aperture Spherical Radio Telescope. Using a 70 hr drift-scan observation with the L-band (1.05-1.45 GHz) 19 beam receiver, we obtain the data covering a 270 deg2 sky area. We employ both the pulsar backend and the spectrum backend to calibrate the spectral time-ordered data (TOD) before projecting them onto HEALPix maps. We produce calibrated TOD with a frequency resolution of 30 kHz and time resolution of 1 s and the map data cube with a frequency resolution of 30 kHz and spatial resolution of 2.95 arcmin2. We examine the pointing errors, noise overflow, radio-frequency interference (RFI) contamination, and their effect on the data quality. The resulting noise level is ∼5.7 mJy for the calibrated TOD and 1.6 mJy for the map, consistent with the theoretical predictions within 5% at RFI-free channels. We also validate the data by principal component analysis and find that the residual map looks thermal noise dominated after removing 30 modes. We identify 447 isolated bright continuum sources in our data matching the NRAO VLA Sky Survey catalog, with relative flux error of 8.3% for TOD and 6.6% for the map level. We also measure the H i emission of 90 galaxies with redshift z < 0.07 and compare them with H i-MaNGA spectra, yielding an overall relative H i integral flux error of 16.7%. These results provide an important first step in assessing the feasibility of conducting cosmological H i detection with CRAFTS.
Climate and groundwater depth relationships in selected Breede Gouritz water management area subregions between 2009 and 2020
(MDPI, 2025) Correia, Monica M.; Kanyerere, Thokozani; Jovanovic, Nebo; Goldin, Jacqueline; John, Moyin
Groundwater resources are changing under the current climate change trajectory. Mitigation and adaptation measures include understanding the inter-working relationships among all climate variables and water resources, specifically groundwater, since it has less direct impacts than surface waters due to its nature. The Breede Gouritz Water Management Area provides an interesting platform to assess these interdependencies, since they have not been assessed before. To assess any underlying dependencies, a multivariate analysis of independent variables including monthly average temperature, summative precipitation, and average evapotranspiration, and a dependent monthly variable, i.e., average groundwater depth, from 14 boreholes was conducted. Moreover, a groundwater depth near-future prediction for each relevant borehole was made. The Multiple Linear Regression model was chosen as the appropriate one since it is cost- and time-effective, entry-level, easy to interpret, and provides a simple and basic understanding of the relationship dependencies. The Kruskal-Wallis test was also performed to elaborate on findings from the Multiple Linear Regression models. Simple linear models incorporating independent and dependent variables can only account for up to 41.7% of the variation in groundwater depth. Groundwater depth is mainly influenced by temperature and evapotranspiration and is expected to be lower for ten dependent variables. The more arid regions in the study area can expect groundwater depth to lower soon and need to use alternative water resources. The temperate west of the study area could expect more favorable outcomes regarding groundwater depth in the near future. Incorporating more variables and using a multi-modal approach to combat non-linear relationships is recommended in future.
Emission-line stacking of 21 cm intensity maps with MeerKLASS: inference pipeline and application to the L-band deep-field data
(American Astronomical Society, 2025) Spinelli, Marta; Wang, Jingying; Fonseca, José; Camera, Stefano; Wang, Jingying
We present a novel analysis of observational systematics through the emission-line stacking of the MeerKLASS L-band deep-field intensity maps, following the detection in MeerKLASS Collaboration et al. A stacking signal is obtained by stacking the 21 cm intensity map cubelets around the galaxy positions from the GAMA survey at 0.39 ≲ z ≲ 0.46. An extensive simulation framework is built to study the viability of the stacking detection, the covariance estimation, and the model inference, which are then applied to the data. The statistical significance of the detection is 8.66σ when averaged into an angular map, and 7.45σ when averaged into a spectrum. The stacked spectrum exhibits an oscillating component of systematics, and we provide evidence that these systematics are a convolutional effect on the map data. The oscillation frequency matches the diffraction from the secondary reflector into the primary beam of the MeerKAT telescope. Bayesian inference can be used to constrain the systematics and the average H i emission of the galaxies. The fitting of the parameters gives a constraint on the systematics frequency ν sys [ MHz ] = 17.9 0 − 4.27 + 6.53 . The posterior of the systematics amplitude reaches the wide prior and gives A sys = 0.5 0 − 0.33 + 0.33 . A tentative measurement of the average H i mass of the sources is achieved at log 10 [ 〈 M H I 〉 / M ⊙ ] = 9.8 4 − 0.59 + 0.48 , which is an underestimation limited by the narrow redshift bin, the strong degeneracy with the systematics, and the low-density galaxy sample. These shortfalls will be resolved for future MeerKLASS data to enable accurate measurements of the H i density through stacking of intensity maps.