Frequent consumption of aflatoxins-contaminated spices has been linked to serious adverse health effects among consumers. The likelihood of exposure to these toxins is influenced by the level of public awareness. Controlling aflatoxins contamination throughout the food chain is critical for public health. This study aimed to assess the handling practices and awareness of aflatoxin contamination among micro- and small-scale spice processors. A total of 60 processors from 4 districts of two regions of Tanzania were interviewed. The results showed that while 56.7% of interviewed processors were aware of aflatoxin contamination in spices primarily through training (38.3%) and mass media (30%). However, there were still misconceptions regarding the causes and effects of aflatoxins to human health. It was observed that, poor drying and storage practices, inadequate monitoring of processors aggravated the situation. Nonetheless, all interviewed processors expressed willingness to participate in training programs to ensure quality and safety along the chain. The study findings underscore the necessity for targeted interventions to reduce aflatoxin risks in the spice value chain. These should include strengthened food safety inspections and enforcement, as well as tailored training and support for micro and small-scale spice processors. Enhancing their knowledge and ability to adopt proper handling, drying and storage practices is critical for enhancing food safety and safeguarding public health.

Silver nanoparticles (Ag⁺NPs) contamination in the environment is a serious concern. This study investigated selected heavy metal (Ag⁺, Cd^2+, Cr²⁺ and Pb²⁺) concentrations at different sampling points to assess the risk to human health (infants, children, and adults). To do this, an enclosed area (laboratory) of 12.6 m X 8.5 m (107.1 m²) was clearly marked at different coded distances of S1, S2, S3, and S4 representing 2, 4, 6, and 8 m, while unpolluted atmosphere at 50 m away without Ag⁺NPs served as the control (S5). The silver fireworks were allowed to burn for an approximate 00h03m30s at each sampling points using a high-volume air sampler mounted at the Environmental Engineering Departmental Laboratory, Rivers State University, with windows and doors closed to simulate indoor conditions. Samples were digested using a mixture of analytical-grade nitric acid, analytical-grade hydrochloric acid and analyzed to evaluate the levels of heavy metals by atomic absorption spectrophotometry. The Ag⁺ result at S1 shows 30,000 µg/cm³, S2 was 29,000 µg/cm³, while S3 was 28000 µg/cm³ and then S4 was 13,000 µg/cm³. These results exceeded the permissible values of the United States National Ambient Air Concentration for rural, urban and industrial areas (0.0005, 0.004 and 0.6 µg/cm³, respectively). The result for the control (S5) (0.037 µg/cm³) was within the maximum allowable value. Results from other heavy metals such as Cd were 1000, 743, 401, 153, 0.001 µg/cm³, Cr was 5000, 4000, 3729, 2960, 0.002 µg/cm³, Pb was 0.048, 0.041, 0.035, 0.034 and 0.01, µg/cm³, respectively. However, higher values of Ag⁺, Cd, and Cr indicated a higher propensity for the metals to be toxic (bioavailable). In addition, the assessment of the potential health risk posed by these metals proved contaminated and harmful. Visitors recorded high values in exposure concentration (EC) and low values in average daily dose (ADD).

This work evaluated the bioremediation potential of Jatropha tanjorensis leaf extract at different masses (250g, 500g and 750g) over a 40-day period. To achieve this, crude oil contamination of sandy loam soil was stimulated in twelve plastic reactors containing fixed masses of soil (4kg each) of topsoil homogenized with 500g of Bonny light crude oil. The Jatropha tanjorensis leaves were cultivated, rinsed with distilled water, blended, and purified by filtration. The leaf extract was applied at the stated concentrations including a control reactor (without leaf extract). The plastics reactors were kept in an open air shielded away from rainfall. The physicochemical characteristics determined were particle size distribution (PSD), potential of hydrogen (pH), electrical conductivity (EC), organic matter (OM), organic carbon (OC), selected heavy metals (Cr, Cd, Zn, Pb) and sample management were all in line with standard procedure. After 40 days of treatment, results obtained showed that plastic reactor with 750g of leaf extract produced the highest amount of cadmium reduction of 97% (from an initial of and there was significant difference among treatment (P < 0.05). The sequence of reduction among treatment was 750g > 500g > 250g of the leaf extract. Chromium, Lead and zinc followed similar trend. Thus, the Jatropha tanjorensis leaf extract has the potential to ameliorate crude oil-contaminated soil.

The accurate estimation of Individual Wave Components (IWC) is crucial for automated diagnosis of the human digestive system in a clinical setting. However, this process can be challenging due to signal contamination by other signal sources in the body, such as the lungs and heart, as well as environmental noise. To address this issue, various denoising techniques are commonly employed in bowel sound signal processing. While denoising is important, it can increase computational complexity, making it challenging for portable devices. Therefore, signal processing algorithms often require a trade-off between fidelity and computational complexity. This study aims to evaluate an IWC parameter extraction algorithm that was previously developed and reconstruct the IWC without denoising using synthetic and clinical data. To that end, the role of a reliable model in creating synthetic data is paramount. The rigorous testing of the algorithm is limited by the availability of quality and quantity recorded data. To overcome this challenge, a mathematical model has been proposed to generate synthetic bowel sound data that can be used to test new algorithms. The proposed algorithm’s robust performance is evaluated using both synthetic and clinically recorded data. We perform time-frequency analysis of original and reconstructed bowel sound signals in various digestive system states and characterize the performance using Monte Carlo simulation when denoising is not applied. Overall, our study presents a promising algorithm for accurate IWC estimation that can be useful for predicting anomalies in the digestive system.