Vocational Training Council

This study presents an integrated framework combining computational simulations and machine learning (ML) to design and optimize supercritical carbon dioxide (CO₂) pipeline networks for large-scale carbon capture and storage (CCS) applications. Using ANSYS fluent, the fluid dynamics of supercritical CO₂ transport were analyzed under various operational conditions to generate synthetic insights and complement real-world datasets collected from CO₂ sequestration activities and industrial sources. Key variables such as pressure, temperature, and pipeline diameter were extracted, engineered into time-lagged and rolling features, and used to train a random forest regressor model. Feature importance analysis revealed that short-term flow trends, volatility, and geographic segmentation are dominant predictors of CO₂ flow behavior. The ML model achieved high performance, with an R² score of 0.9897 and a low RMSE of 0.0335, indicating strong predictive reliability. Hyperparameter tuning further optimized model accuracy, while visual analyses including actual vs. predicted comparisons, residual distributions, and feature interaction heatmaps validated the model’s robustness. The results demonstrate that data-driven approaches can complement simulation-based methods to improve the design, monitoring, and operational efficiency of CO₂ transport systems. This work provides a scalable, intelligent solution for CCS pipeline optimization, supporting the global transition toward low-carbon infrastructure.

The present study aims to investigate the putative protective role of curcumin (CUR) against oxidative stress and lung damage caused by a heavy metal mixture (Cd+As) with cadmium (Cd) + arsenic (As). Wistar albino rats were randomly divided into five experimental groups: Control, 0.44 + 5.55 mg/kg Cd+As, 100 mg/kg CUR, 100 CUR + Cd+As, and 200 CUR + Cd+As groups. The Cd+As increased malondialdehyde levels and oxidative stress. However, it also led to a decrease in levels of glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) in lung tissue homogenates. Different doses of CUR effectively prevented Cd+As-induced lipid peroxidation and suppression of antioxidant capacity in lung tissue. Also, lung tissue administered Cd+As showed elevated levels of congestion, inflammation, alveolar damage, and apoptosis, as evidenced by decreased Bcl-2 and increased expression levels of Bax and caspase-3. The high dose remarkably improved lung injury in Cd+As-injected rats, better than the low dose. The results show that CUR treatment is effective in protecting against Cd+As-induced lipid peroxidation and reducing the negative effects of metal mixture on antioxidant status. This study suggests that CUR may be a potential new approach for the prevention/treatment of Cd+As-induced pulmonary toxicity and possibly other lung diseases associated with oxidative stress and inflammation. Furthermore, in silico studies on how CUR and Cd+As treatments affect the activities of the enzymes CAT and GPx1 showed that ROS induced by Cd+As treatment caused changes in the enzymes CAT and GPx1, while CAT was modulated by CUR treatment, whereas GPx1 was not modulated.

This study presents a comprehensive analysis of global methane (CH<sub>4</sub>) emissions using advanced data exploration and machine learning techniques, with an emphasis on identifying key sectoral contributors, geographic emission hotspots, and the performance of mitigation technologies. Employing methods such as random forest regression, geospatial mapping, and multi-dimensional visual analytics, the research highlights the energy sector’s dominant role in methane output and reveals detailed emission patterns across U.S. states. The analytical framework includes time-series feature engineering, synthetic data augmentation for localized insights, and 3D surface modeling to examine the relationships between energy production levels, temporal trends, and emission intensities. The results provide actionable insights for policymakers by identifying critical points of intervention and advocating for the integration of artificial intelligence-driven exhaust after-treatment systems to reduce methane emissions. This work offers a scalable, reproducible approach for environmental monitoring and supports global decarbonization efforts in line with U.S. clean energy objectives. The random forest model used in this study achieved a mean absolute error of 2.71 and an R² score of 0.81, demonstrating strong predictive accuracy for methane emissions trends based on regional and sectoral data.

Background: Strengthening digital and pedagogical competence among allied health educators is critical, especially in low-resource settings where digital literacy gaps persist. While faculty development initiatives increasingly explore ICT-enabled teaching, limited research has examined educators’ immediate reflections using video-based methods. Such video-based approaches can capture authentic and spontaneous insights following training. Method: A qualitative descriptive design was used. Reflections from nine educators were captured through a single video-recorded testimonial session after a three-day ICT-focused pedagogical training. These reflections were transcribed and analysed thematically using Braun and Clarke’s reflexive approach. Result: Four themes emerged: 1) enhanced digital competence, 2) first-time exposure and professional growth, 3) application of ICT skills to teaching and supervision, and 4) the need for continued training and adaptation of the use of ICT in teaching and learning. Participants highlighted transferable practical skills and recognised gaps requiring ongoing support. Conclusion: Short-term, contextually relevant training demonstrated transformative potential in building educators’ digital and pedagogical capacity. Video-based evaluation proved effective in capturing authentic reflections, scalability, and informing tailored programme design. Findings are context-specific and not statistically generalizable, but they provide transferable insights for similar low-resource educational settings. However, confidentiality presents a significant challenge in video-based data collection, and appropriate ethical safeguards are necessary to protect participant identity. Recommendation: Institutions should prioritise ongoing ICT-focused faculty development, and future studies should examine sustained impacts on teaching practices and learning outcomes.

In this study, a simple and efficient analytical formula is presented to calculate the generalized Bloch-Gruneisen function. The proposed analytical formula for the generalized Bloch-Gruneisen function is corrected for non-integer and integer values of parameter 𝑚. Note that the Bloch-Gruneisen function is preferred to calculate thermal conductivity and electrical resistivity of solid materials. It has been demonstrated that the offered analytical formula gives very correct results of semiconductor and superconductivity for a wide range of temperatures. As an example, the Bloch-Gruneisen function of MgB2 material, which is envisioned as an alternative superconducting wire for advanced fusion reactors, has been calculated and compared with theoretical calculations and experimental data. The results obtained for m=3.5 were found to be in excellent agreement with the experimental data, with a maximum deviation of approximately 1.26%. The results demonstrated that the analytical formula can be satisfactorily used for solid materials.

This article explores the possibility of diagnosing unwanted pressure drops in pneumatic systems. The proposed algorithm aims to distinguish the causes and location of their occurrence. The diagnostics clearly distinguish pressure drops caused by supply lines from those caused in the main or branch lines of an industrial pneumatic system. Pressure drops in pneumatic systems are one of the main causes of increased energy consumption. For the energy and resource optimization of pneumatic systems, it is essential to detect and locate the causes of pressure drops. This article proposes an approach for using the time diagrams of two measurable variables—flow rate and pressure—at the inlet of the end consumer (machine). Based on constant monitoring and a correlation relationship between the two time series, we determined indicators for detecting and locating unwanted pressure drops. In order to verify the proposed approach and the performed analysis, in general, we made observations of 16 real production machines and lines.

The urban developmental process depicts transformation of the landscape through spatial changes in zones closer to towns and cities across the world. This is evident in the spatio-temporal and sectorial changes in demographic, social, economic, technological and environmental aspects. Bamenda City is experiencing rapid growth in population and continues expansion of built-up land use, resulting in the reduction of agricultural and forest lands. There is continuous haphazard densification of buildings and uncontrolled urban sprawl. The aim of this article is to examine the dynamic trends and drivers of urban development anchored on the premise that urban development trends are directly related to population growth in Bamenda City. The methodology uses historical survey and correlational designs of field investigations to administer 300 questionnaires to the target population with a spatial picture reflected on the three municipalities (Bamenda I. Bamenda II and Bamenda III) for comparative analysis. Landsat Images were processed to show the spatio-temporal changes in land uses from 2000-2024. This was complemented by field observations and secondary data sources from institutions. Findings revealed that urban development is manifested in significant increase in infrastructures (22.7%) and peri-urban growth (18.2%). The trend is increasing in spatial rates seen in Bamenda I (47%), Bamenda II (42%) and Bamenda III (45%). Farmland use has reduced from 124.36 km<sup>2 </sup>(44.6%) in 2000 to 119.17 km<sup>2</sup> (42.7%) in 2024 while built-up land has increased from 28.16 km<sup>2 </sup>(10.1%) 62.99 km<sup>2</sup> (22.6%) in 2024. Population increase has been most dominant driver of urban development (Bamenda II (31%), Bamenda I (30%) and Bamenda III (28.8%). This replicates an inseparable nexus between population growth and urban. The study recommends the need for controlled land use planning to mitigate the increasing duplication of land uses and planned urban development.

IntroductionSexually transmitted infections are of great public health importance. The screening of these infections not being part of the routine healthcare package for PLWHIV means most of the infected individuals who are asymptomatic end up being undetected. This study aims to determine the seroprevalence of syphilis, chlamydia, and HBV among PLWHIV in Meme division. Additionally, it aimed to assess the factors associated with STI transmission.MethodsA hospital-based cross-sectional design was adopted that recruited a total of 364 PLWHIV from the urban and rural communities in Meme division from December 2024 to April 2025. About 4 mL of blood was collected and placed in a sodium citrated tube. The sample was used for ABO blood grouping, syphilis, hepatitis B, and chlamydia screening using serological assays. The data was analysed using SPSS version 25. Fisher’s exact test was used to determine the difference in proportions and logistic regression model was used to determine risk factors associated with STI transmission. p-values <0.05 were considered as statistically significant.ResultsThe overall seroprevalence of syphilis, HBV and chlamydia infection among PLWHIV from rural areas was 30/150 (20%) [95% CI 0.139–0.273], 13/150 (8.7%) [95% CI 0.047–0.143] and 6/150 (4.0%) [95% CI 0.014–0.085] while in urban area the seroprevalence was 41/214 (19.2%) [95% CI 0.141–0.250], 33/214 (15.4%) [95% CI 0.108–0.209] and 5/214 (2.3%) [95% CI 0.007–0.053] respectively. A couple of the individuals were infected with at least more than one STI. Multivariate analysis shows that females had a lower odd to STI infection (AOR = 0.468, 95% CI 0.252–0.867, p < 0.016), having multiple sexual partners had a lower odd to STI (AOR = 0.346, 95% CI 0.160–0.748, p < 0.007), bathing before and after sexual intercourse recorded a lower odd to STI (AOR = 0.458, 95% CI 0.272–0.772, p < 0.003) as well as those who reported having sex 1–3 times a week also had a lesser odd to STI (AOR = 0.526, 95% CI 0.296–0.935, p < 0.029).ConclusionSexually transmitted infection was high among PLWHIV in Meme division with individuals from rural communities having the highest prevalence of infections. The most dominant of these infections was syphilis followed by HBV and lastly Chlamydia.

This paper presents a solar tree prototype for implementing agrivoltaics in small suburban farms. Agrivoltaics integrates photovoltaic power generation and agricultural activities, minimizing competition between energy and food production. While technical aspects of agrivoltaics are well-studied, its implementation remains challenging, especially for small farms. The prototype uses IoT, 3D printing, and commercial components. Design principles, structure, solar-to-electricity conversion, and solar tracking mechanisms are discussed. Experiments had been conducted to enhance light-dependent resistor (LDR) accuracy for tracking, exploring shielding and tradeoffs.