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Endoscopic capacity in West Africa
摘要： Background: Levels of endoscopic demand and capacity in West Africa are unclear. Objectives: This paper aims to: 1. describe the current labor and endoscopic capacity, 2. quantify the impact of a mixed-methods endoscopy course on healthcare professionals in West Africa, and 3. quantify the types of diagnoses encountered. Methods: In a three-day course, healthcare professionals were surveyed on endoscopic resources and capacity and were taught through active observation of live cases, case discussion, simulator experience and didactics. Before and after didactics, multiple-choice exams as well as questionnaires were administered to assess for course efficacy. Also, a case series of 23 patients needing upper GI endoscopy was done. Results: In surveying physicians, less than half had resources to perform an EGD and none could perform an ERCP, while waiting time for emergency endoscopy in urban populations was at least one day. In assessing improvement in medical knowledge among participants after didactics, objective data paired with subjective responses was more useful than either alone. Of 23 patients who received endoscopy, 7 required endoscopic intervention with 6 having gastric or esophageal varices. Currently the endoscopic capacity in West Africa is not sufficient. A formal GI course with simulation and didactics improves gastrointestinal knowledge amongst participants.
关键词： endoscopic demand,training course,West Africa,Endoscopic capacity
更新于2025-09-23 15:23:52
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Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
摘要： Accurate global solar radiation prediction is highly essential for related research on renewable energy sources. The cost implication and measurement expertise of global solar radiation emphasize that intelligence prediction models need to be applied. On the basis of long-term measured daily solar radiation data, this study uses a novel regularized online sequential extreme learning machine, integrated with variable forgetting factor (FOS-ELM), to predict global solar radiation at Bur Dedougou, in the Burkina Faso region. Bayesian Information Criterion (BIC) is applied to build the seven input combinations based on speed (Wspeed), maximum and minimum temperature (Tmax and Tmin), maximum and minimum humidity (Hmax and Hmin), evaporation (Eo) and vapor pressure deficiency (VPD). For the difference input parameters magnitudes, seven models were developed and evaluated for the optimal input combination. Various statistical indicators were computed for the prediction accuracy examination. The experimental results of the applied FOS-ELM model demonstrated a reliable prediction accuracy against the classical extreme learning machine (ELM) model for daily global solar radiation simulation. In fact, compared to classical ELM, the FOS-ELM model reported an enhancement in the root mean square error (RMSE) and mean absolute error (MAE) by (68.8–79.8%). In summary, the results clearly confirm the effectiveness of the FOS-ELM model, owing to the fixed internal tuning parameters.
关键词： global solar radiation,West Africa region,energy harvesting,FOS-ELM model,input optimization
更新于2025-09-23 15:22:29
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Impact of global warming on photovoltaic power generation over West Africa
摘要： Many West African countries are plagued with poor electricity. The abundance of solar irradiance over the region makes solar energy an attractive solution to the problem, but there is a dearth of information on how the ongoing solar dimming and global warming may alter the solar energy over the region in the future at various global warming levels. This study investigates the impact of climate change on photovoltaic power generation potential (PVP) over West Africa under four global warming levels (1.5°C; 2.0°C; 2.5°C and 3.0°C) and under the representative concentration pathway 8.5 (RCP 8.5) climate change scenario. Fourteen regional climate model simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) were analysed for the study. The capability of the simulations to reproduce the PVP and climate variables over West Africa is quantified. The results show that the CORDEX simulation ensemble captures the spatial distribution and the annual cycle of climate variables and PVP over West Africa, though with few biases. The simulation and observation indicate that PVP over West Africa ranges from 8% to 25% and the annual cycle is influenced by the seasonal variation of the monsoon system. The simulation ensemble projects a decrease of PVP over West Africa in the future and indicates that the magnitude of the decrease grows with warming levels. The maximum decrease in PVP projected over any country or zone in the region is less than 3.8% even for a warming level of 3.0°C. Hence, the study suggests that ongoing global warming may have an influence on PVP over West Africa.
关键词： West Africa,Global warming,Global dimming,Solar energy,Paris agreement
更新于2025-09-12 10:27:22
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Mapping the Leaf Economic Spectrum across West African Tropical Forests Using UAV-Acquired Hyperspectral Imagery
摘要： The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p < 0.01) correlations with LMA and leaf chemical traits: r2 = 0.42 (LMA), r2 = 0.43 (N), r2 = 0.21 (P), r2 = 0.20 (leaf potassium (K)), r2 = 0.23 (leaf calcium (Ca)) and r2 = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p < 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r2 = 0.25 (LMA), r2 = 0.22 (N), r2 = 0.22 (P), and r2 = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.
关键词： hyperspectral,spectroscopy,West Africa,tropical forest,UAV,Ghana,leaf traits,PLSR,leaf economic spectrum
更新于2025-09-10 09:29:36