Pub Date : 2026-01-02DOI: 10.1016/j.sciaf.2025.e03172
Taher Ammar , Mohamed Abdel-Monem , Karim El-Dash
Road construction projects in Egypt, as in many other developing African countries, frequently experience significant cost overruns. This study systematically analyzes the causes of such overruns to enhance understanding and improve risk management practices in the field. The research identifies key factors contributing to cost overruns and examines their relationships. A prediction model was developed to help estimate appropriate contingency costs by evaluating the impact of these factors on the overall project cost. Using Factor Analysis (FA), Regression Analysis (RA), and Regression Model (RM), the study assessed the significance of various cost overrun factors. The findings indicate that poor material quality, scope-of-work changes, and quantity variations are the primary causes of cost overruns in road construction projects. This study benefits both local and international researchers and practitioners by providing actionable insights. It highlights the practical implications of the findings and emphasizes key features that decision-makers should consider to improve the performance of the road network construction sector. As a critical driver of urban development and modern community establishment, enhancing the efficiency of road construction is essential for sustainable growth and infrastructure development. The study also helps the government address the risks associated with road network projects during the pre-tendering phase, enabling it to better manage its financial resources.
{"title":"Using factor analysis and regression technique to predict cost overrun in road network construction projects","authors":"Taher Ammar , Mohamed Abdel-Monem , Karim El-Dash","doi":"10.1016/j.sciaf.2025.e03172","DOIUrl":"10.1016/j.sciaf.2025.e03172","url":null,"abstract":"<div><div>Road construction projects in Egypt, as in many other developing African countries, frequently experience significant cost overruns. This study systematically analyzes the causes of such overruns to enhance understanding and improve risk management practices in the field. The research identifies key factors contributing to cost overruns and examines their relationships. A prediction model was developed to help estimate appropriate contingency costs by evaluating the impact of these factors on the overall project cost. Using Factor Analysis (FA), Regression Analysis (RA), and Regression Model (RM), the study assessed the significance of various cost overrun factors. The findings indicate that poor material quality, scope-of-work changes, and quantity variations are the primary causes of cost overruns in road construction projects. This study benefits both local and international researchers and practitioners by providing actionable insights. It highlights the practical implications of the findings and emphasizes key features that decision-makers should consider to improve the performance of the road network construction sector. As a critical driver of urban development and modern community establishment, enhancing the efficiency of road construction is essential for sustainable growth and infrastructure development. The study also helps the government address the risks associated with road network projects during the pre-tendering phase, enabling it to better manage its financial resources.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03172"},"PeriodicalIF":3.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.sciaf.2025.e03161
Jeremiah January , Gasper Mwanga , Isack E. Kibona , Nyimvua Shaban Mbare
<div><div>An optimal control model for rotavirus transmission was formulated to minimize both the cost of implementing interventions and the burden of infection among children and caregivers. The model integrates five time-dependent control functions: vaccination of children (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>), public health education (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>), treatment of infected children (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>3</mn></mrow></msub></math></span>), water treatment and sanitation (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>4</mn></mrow></msub></math></span>), and hygiene promotion (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>5</mn></mrow></msub></math></span>). Pontryagin’s Maximum Principle was applied to derive the necessary conditions for optimality, and numerical simulations were conducted using the Runge–Kutta method to determine the optimal time-dependent control profiles and corresponding epidemiological outcomes. Simulation results at <span><math><mrow><mi>t</mi><mo>=</mo><mn>220</mn></mrow></math></span> days indicate a substantial reduction in rotavirus infections among children and caregivers when integrated controls are applied. The number of infected and hospitalized children (<span><math><msub><mrow><mi>I</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>) approach zero, while the vaccinated population (<span><math><msub><mrow><mi>V</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>) reaches approximately <span><math><mrow><mn>2</mn><mo>.</mo><mn>58</mn><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>7</mn></mrow></msup></mrow></math></span>, confirming the central role of vaccination in suppressing new infections. The concentration of environmental rotavirus particles (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>r</mi></mrow></msub></math></span>) also tends to zero, highlighting the combined efficacy of hygiene and sanitation interventions in reducing environmental transmission. Among the evaluated control strategies, the combination of vaccination, treatment, and hygiene (<span><math><msub><mrow><mi>S</mi></mrow><mrow><mn>13</mn></mrow></msub></math></span>) emerges as both the most cost-effective and epidemiologically impactful strategy. This approach achieves near-complete elimination of child infections at a moderate total cost of approximately $6.17<span><math><mrow><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>11</mn></mrow></msup></mrow></math></span>, yielding the best balance between health outcomes and economic feasibility. In contrast, the single-control strategies (<span><math><msub><mrow><mi>S</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>–<span><math><msub><mrow><mi>S</mi></mrow><mrow><mn>5</mn></mrow></msub></math></span>)
{"title":"Modeling and optimal control of rotavirus transmission dynamics with cost effectiveness","authors":"Jeremiah January , Gasper Mwanga , Isack E. Kibona , Nyimvua Shaban Mbare","doi":"10.1016/j.sciaf.2025.e03161","DOIUrl":"10.1016/j.sciaf.2025.e03161","url":null,"abstract":"<div><div>An optimal control model for rotavirus transmission was formulated to minimize both the cost of implementing interventions and the burden of infection among children and caregivers. The model integrates five time-dependent control functions: vaccination of children (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>), public health education (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>), treatment of infected children (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>3</mn></mrow></msub></math></span>), water treatment and sanitation (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>4</mn></mrow></msub></math></span>), and hygiene promotion (<span><math><msub><mrow><mi>u</mi></mrow><mrow><mn>5</mn></mrow></msub></math></span>). Pontryagin’s Maximum Principle was applied to derive the necessary conditions for optimality, and numerical simulations were conducted using the Runge–Kutta method to determine the optimal time-dependent control profiles and corresponding epidemiological outcomes. Simulation results at <span><math><mrow><mi>t</mi><mo>=</mo><mn>220</mn></mrow></math></span> days indicate a substantial reduction in rotavirus infections among children and caregivers when integrated controls are applied. The number of infected and hospitalized children (<span><math><msub><mrow><mi>I</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>) approach zero, while the vaccinated population (<span><math><msub><mrow><mi>V</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>) reaches approximately <span><math><mrow><mn>2</mn><mo>.</mo><mn>58</mn><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>7</mn></mrow></msup></mrow></math></span>, confirming the central role of vaccination in suppressing new infections. The concentration of environmental rotavirus particles (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>r</mi></mrow></msub></math></span>) also tends to zero, highlighting the combined efficacy of hygiene and sanitation interventions in reducing environmental transmission. Among the evaluated control strategies, the combination of vaccination, treatment, and hygiene (<span><math><msub><mrow><mi>S</mi></mrow><mrow><mn>13</mn></mrow></msub></math></span>) emerges as both the most cost-effective and epidemiologically impactful strategy. This approach achieves near-complete elimination of child infections at a moderate total cost of approximately $6.17<span><math><mrow><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>11</mn></mrow></msup></mrow></math></span>, yielding the best balance between health outcomes and economic feasibility. In contrast, the single-control strategies (<span><math><msub><mrow><mi>S</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>–<span><math><msub><mrow><mi>S</mi></mrow><mrow><mn>5</mn></mrow></msub></math></span>)","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03161"},"PeriodicalIF":3.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.sciaf.2025.e03168
Mohammed Ahmed Ebrahim , Zebene Asfaw , Shewakena Teklegiorgis , Ewunetu Tazebew
On-farm tree resources sustain biodiversity, provide multiple products, and improve resilience of farming systems. Understanding the diversity and composition of on-farm tree resources is essential for designing tree-growing interventions, yet remains unexplored in many socio-ecological contexts. This study assessed the species composition and diversity of woody plants across agroforestry practices in Kalu district, Northeastern Ethiopia. A multistage random sampling was employed to select a total of 54 sample farms across two study sites (Lowland and Midland) to inventory woody plants in four agroforestry practices: agroforestry parklands, home-gardens, boundary live fences, and woodlot plantations. A total of 56 woody species were recorded across farmlands, of which 66 % were native and 34 % were exotic. Species richness and diversity differed significantly among agroforestry practices (p < 0.05), with home-gardens and live fences showing high average richness (5.85 and 4.33 species, respectively). Parklands supported lower diversity, while woodlots consistently showed the lowest richness and diversity. Home-gardens exhibited a significant trade-off between species richness and evenness (J = 0.61), driven by the dominance of Catha edulis and Eucalyptus spp. The results also highlight the overlooked role of boundary live fences in sustaining woody species diversity within farming systems. Multivariate analysis (ANOSIM, Global R = 0.39) indicated moderate compositional differences, driven by practice-specific dominance of woody species rather than complete species turnover. Overall, the study underscores the importance of integrating higher tree diversity across agroforestry practices and implementing targeted diversification strategies to enhance agrobiodiversity and livelihood outcomes in dryland agroecosystems.
农场树木资源维持生物多样性，提供多种产品，并提高农业系统的复原力。了解农场树木资源的多样性和组成对于设计树木种植干预措施至关重要，但在许多社会生态背景下仍未得到探索。本研究评估了埃塞俄比亚东北部Kalu地区不同农林业方式下木本植物的物种组成和多样性。采用多阶段随机抽样的方法，在两个研究地点（低地和中部）共选择54个样本农场，对四种农林业实践（农林业公园、家庭花园、边界活围栏和林地种植园）中的木本植物进行调查。共记录到56种木本植物，其中66%为本地植物，34%为外来植物。不同农林业方式的物种丰富度和多样性差异显著（p < 0.05），家庭花园和围栏的平均丰富度较高（分别为5.85种和4.33种）。公园地的多样性较低，林地的丰富度和多样性均最低。在Catha edulis和Eucalyptus的主导下，家庭花园的物种丰富度和均匀度之间存在显著的权衡关系（J = 0.61）。研究结果还强调了边界围栏在维持农业系统内木本物种多样性方面被忽视的作用。多变量分析（ANOSIM, Global R = 0.39）表明，不同树种间存在适度的成分差异，这主要是由木本树种的特定优势驱动，而非完全的物种更替。总体而言，该研究强调了在农林业实践中整合高等树木多样性和实施有针对性的多样化战略的重要性，以提高旱地农业生态系统的农业生物多样性和生计成果。
{"title":"Species composition and diversity of on-farm tree resources in Kalu district, Northeastern Ethiopia","authors":"Mohammed Ahmed Ebrahim , Zebene Asfaw , Shewakena Teklegiorgis , Ewunetu Tazebew","doi":"10.1016/j.sciaf.2025.e03168","DOIUrl":"10.1016/j.sciaf.2025.e03168","url":null,"abstract":"<div><div>On-farm tree resources sustain biodiversity, provide multiple products, and improve resilience of farming systems. Understanding the diversity and composition of on-farm tree resources is essential for designing tree-growing interventions, yet remains unexplored in many socio-ecological contexts. This study assessed the species composition and diversity of woody plants across agroforestry practices in Kalu district, Northeastern Ethiopia. A multistage random sampling was employed to select a total of 54 sample farms across two study sites (Lowland and Midland) to inventory woody plants in four agroforestry practices: agroforestry parklands, home-gardens, boundary live fences, and woodlot plantations. A total of 56 woody species were recorded across farmlands, of which 66 % were native and 34 % were exotic. Species richness and diversity differed significantly among agroforestry practices (<em>p</em> < 0.05), with home-gardens and live fences showing high average richness (5.85 and 4.33 species, respectively). Parklands supported lower diversity, while woodlots consistently showed the lowest richness and diversity. Home-gardens exhibited a significant trade-off between species richness and evenness (<em>J</em> = 0.61), driven by the dominance of <em>Catha edulis</em> and <em>Eucalyptus</em> spp. The results also highlight the overlooked role of boundary live fences in sustaining woody species diversity within farming systems. Multivariate analysis (ANOSIM, Global <em>R</em> = 0.39) indicated moderate compositional differences, driven by practice-specific dominance of woody species rather than complete species turnover. Overall, the study underscores the importance of integrating higher tree diversity across agroforestry practices and implementing targeted diversification strategies to enhance agrobiodiversity and livelihood outcomes in dryland agroecosystems.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03168"},"PeriodicalIF":3.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite national strategies to digitize education, the gap between administrative policy and classroom reality remains significant, particularly regarding the impact of digital tools on equity in underserved settings. This study addresses the urgent need to evaluate how technology integration affects student outcomes in resource-constrained environments. Guided by Viau’s motivational framework and Rabardel’s instrumental approach, we employed a mixed-methods design to investigate the integration of multimedia tools, specifically Scratch and GeoGebra, among fourth-grade students in rural Morocco. Data were collected through surveys with teachers (n = 132) and students (n = 148), followed by a comparative intervention involving control and experimental groups. The results demonstrate that utilizing technology as a pedagogical instrument, rather than a mere delivery mechanism, significantly enhances student engagement, cognitive autonomy, and perseverance compared to traditional instruction. Specifically, the intervention group showed statistically significant gains in perceived choice and performance. Distinct from prior studies that focus solely on infrastructure access, this research provides rare empirical evidence from North Africa demonstrating that well-designed interactive learning environments function as equity levers. Crucially, we show that digital tools reduce the performance gap between high- and low-achieving students in resource-constrained rural settings.
{"title":"Pedagogical integration of information communication and technologies in rural mathematics education: Enhancing motivation and equity in low-resource contexts","authors":"Hajar Zoubir , Abderrahmane Ben Rherbal , Youssef Sefri , Abdelhak Chakli","doi":"10.1016/j.sciaf.2025.e03171","DOIUrl":"10.1016/j.sciaf.2025.e03171","url":null,"abstract":"<div><div>Despite national strategies to digitize education, the gap between administrative policy and classroom reality remains significant, particularly regarding the impact of digital tools on equity in underserved settings. This study addresses the urgent need to evaluate how technology integration affects student outcomes in resource-constrained environments. Guided by Viau’s motivational framework and Rabardel’s instrumental approach, we employed a mixed-methods design to investigate the integration of multimedia tools, specifically Scratch and GeoGebra, among fourth-grade students in rural Morocco. Data were collected through surveys with teachers (<em>n</em> = 132) and students (<em>n</em> = 148), followed by a comparative intervention involving control and experimental groups. The results demonstrate that utilizing technology as a pedagogical instrument, rather than a mere delivery mechanism, significantly enhances student engagement, cognitive autonomy, and perseverance compared to traditional instruction. Specifically, the intervention group showed statistically significant gains in perceived choice and performance. Distinct from prior studies that focus solely on infrastructure access, this research provides rare empirical evidence from North Africa demonstrating that well-designed interactive learning environments function as equity levers. Crucially, we show that digital tools reduce the performance gap between high- and low-achieving students in resource-constrained rural settings.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03171"},"PeriodicalIF":3.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-31DOI: 10.1016/j.sciaf.2025.e03174
Samphelix O. Obende , Charles O. Ochieng , Emmanuel A. Shikanga , Wilberforce Ndarawit , Njogu M. Kimani
The search for new anticancer agents has led to the exploration of various botanical resources, with the genus Croton emerging as a promising source of bioactive compounds. CDK4/6 are key cell cycle regulators linked to cancer pathogenesis, and their inhibition has been shown to be effective in treating various cancer cases. Although inhibitors like ribociclib and abemaciclib have demonstrated therapeutic effectiveness, resistance to these drugs invariably arises, requiring the investigation of alternative therapeutic options. In this study, computational screening techniques were used to identify potential dual inhibitors of CDK4/6, aiming to expedite the discovery of alternative anticancer therapeutics from Croton phytochemical data. Prior to structure-based virtual screening, phytochemicals from Croton Spp were identified by an in-depth review of the literature. The chemical space of these phytochemicals was analyzed in comparison with FDA cancer compounds. The resultant druglike molecules were docked into CDK4 (7SJ3) and 6 (5L2T) receptors. The high-ranking ligands were subjected to molecular simulations and HOMO-LUMO energy gap assessments. In chemical space analysis, 56 out of 900 Croton compounds were found to have similar properties to FDA anticancer agents. Molecular docking studies of these 56 compounds revealed that 26 compounds showed high docking scores with CDK6, similar to ribociclib, and six compounds with CDK4, similar to abemaciclib. Cracroson F (1), Crotocascarin K (2), Cajucarinolide (3), and Isocajucarinolide (4) were predicted as the dual inhibitors showing docking scores for CDK4 (-11, -11, -10.7, and -10.6 kcalmol-1, respectively) and CDK6 (-9.1, -9.4, -8.4, and -9.6 kcalmol-1, respectively). Compounds 1 and 3 showed stability in 200 ns MD simulations, generating hydrophobic, ionic, and hydrogen interactions with an ideal radius of gyration and root mean square deviations and fluctuations (RMSD and RMSF). DFT calculation revealed that 3 (ΔE = 3.522 eV) was more reactive than 1 (ΔE = 3.648 eV) due to its HOMO-LUMO gap, though both were inferior to the standards. These two compounds were predicted to have acceptable pharmacokinetics, off-target, and toxicity profiles, indicating their potential as drug candidates. The in silico study thus identified promising Croton-lead compounds with potential anticancer properties, requiring further experimental (in vitro and in vivo) evaluation.
{"title":"Computational insights into Croton species as sources of CDK4/6 inhibitors for cancer therapy","authors":"Samphelix O. Obende , Charles O. Ochieng , Emmanuel A. Shikanga , Wilberforce Ndarawit , Njogu M. Kimani","doi":"10.1016/j.sciaf.2025.e03174","DOIUrl":"10.1016/j.sciaf.2025.e03174","url":null,"abstract":"<div><div>The search for new anticancer agents has led to the exploration of various botanical resources, with the genus Croton emerging as a promising source of bioactive compounds. CDK4/6 are key cell cycle regulators linked to cancer pathogenesis, and their inhibition has been shown to be effective in treating various cancer cases. Although inhibitors like ribociclib and abemaciclib have demonstrated therapeutic effectiveness, resistance to these drugs invariably arises, requiring the investigation of alternative therapeutic options. In this study, computational screening techniques were used to identify potential dual inhibitors of CDK4/6, aiming to expedite the discovery of alternative anticancer therapeutics from Croton phytochemical data. Prior to structure-based virtual screening, phytochemicals from Croton Spp were identified by an in-depth review of the literature. The chemical space of these phytochemicals was analyzed in comparison with FDA cancer compounds. The resultant druglike molecules were docked into CDK4 (7SJ3) and 6 (5L2T) receptors. The high-ranking ligands were subjected to molecular simulations and HOMO-LUMO energy gap assessments. In chemical space analysis, 56 out of 900 Croton compounds were found to have similar properties to FDA anticancer agents. Molecular docking studies of these 56 compounds revealed that 26 compounds showed high docking scores with CDK6, similar to ribociclib, and six compounds with CDK4, similar to abemaciclib. Cracroson F (<strong>1</strong>), Crotocascarin K (<strong>2</strong>), Cajucarinolide (<strong>3</strong>), and Isocajucarinolide (<strong>4</strong>) were predicted as the dual inhibitors showing docking scores for CDK4 (-11, -11, -10.7, and -10.6 kcalmol<sup>-1</sup>, respectively) and CDK6 (-9.1, -9.4, -8.4, and -9.6 kcalmol<sup>-1</sup>, respectively). Compounds <strong>1</strong> and <strong>3</strong> showed stability in 200 ns MD simulations, generating hydrophobic, ionic, and hydrogen interactions with an ideal radius of gyration and root mean square deviations and fluctuations (RMSD and RMSF). DFT calculation revealed that <strong>3</strong> (ΔE = 3.522 eV) was more reactive than <strong>1</strong> (ΔE = 3.648 eV) due to its HOMO-LUMO gap, though both were inferior to the standards. These two compounds were predicted to have acceptable pharmacokinetics, off-target, and toxicity profiles, indicating their potential as drug candidates. The in silico study thus identified promising Croton-lead compounds with potential anticancer properties, requiring further experimental (in vitro and in vivo) evaluation.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03174"},"PeriodicalIF":3.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CYP11B1 inhibitors play a critical role in controlling cortisol biosynthesis and represent promising therapeutic candidates for disorders such as Cushing’s syndrome and hypertension. In this study, a series of novel analogues were designed and evaluated using an integrated approach combining quantitative structure–activity relationship (QSAR) modeling, molecular docking, and ADME predictions. Multiple linear regression (MLR), partial least squares (PLS), and principal component regression (PCR) models were constructed to establish robust predictive relationships between molecular descriptors and inhibitory activity against CYP11B1. The models were rigorously validated through external test-set prediction, Y-randomization, and applicability-domain (AD) analysis, all satisfying OECD criteria (R² = 0.725–0.772, Q² = 0.701–0.752, RMSE = 0.242–0.310).
Docking simulations revealed that compound D3 exhibited the most favorable binding affinity (−7.45 kcal/mol) and formed stable π–H and π–cation interactions with key residues Arg404 and Leu113, suggesting selective inhibition of CYP11B1. ADME and drug-likeness evaluation indicated predicted favorable pharmacokinetic properties, including high gastrointestinal absorption, absence of blood–brain barrier penetration, and good solubility, with D3 also demonstrating the lowest synthetic-accessibility score (SA = 3.09).
Overall, this integrated computational approach successfully identified D3 as a potent and synthetically feasible CYP11B1 inhibitor candidate. These findings provide a validated framework for the rational design and optimization of new inhibitors with improved pharmacological and metabolic profiles.
{"title":"An integrated computational approach combining QSAR modeling, molecular docking, and ADME profiling for the discovery of selective CYP11B1 inhibitors","authors":"Mohamed El Yaqoubi , Mouad Lahyaoui , Ahmed Mazzah , Hafsa El-idrissi , Yousra Seqqat , Amal Haoudi , Riham Sghyar , Taoufiq Saffaj , Bouchaib Ihssane , Fouad Ouazzani Chahdi , Youssef Kandri Rodi","doi":"10.1016/j.sciaf.2025.e03176","DOIUrl":"10.1016/j.sciaf.2025.e03176","url":null,"abstract":"<div><div>CYP11B1 inhibitors play a critical role in controlling cortisol biosynthesis and represent promising therapeutic candidates for disorders such as Cushing’s syndrome and hypertension. In this study, a series of novel analogues were designed and evaluated using an integrated approach combining quantitative structure–activity relationship (QSAR) modeling, molecular docking, and ADME predictions. Multiple linear regression (MLR), partial least squares (PLS), and principal component regression (PCR) models were constructed to establish robust predictive relationships between molecular descriptors and inhibitory activity against CYP11B1. The models were rigorously validated through external test-set prediction, Y-randomization, and applicability-domain (AD) analysis, all satisfying OECD criteria (R² = 0.725–0.772, Q² = 0.701–0.752, RMSE = 0.242–0.310).</div><div>Docking simulations revealed that compound D3 exhibited the most favorable binding affinity (−7.45 kcal/mol) and formed stable π–H and π–cation interactions with key residues Arg404 and Leu113, suggesting selective inhibition of CYP11B1. ADME and drug-likeness evaluation indicated predicted favorable pharmacokinetic properties, including high gastrointestinal absorption, absence of blood–brain barrier penetration, and good solubility, with D3 also demonstrating the lowest synthetic-accessibility score (SA = 3.09).</div><div>Overall, this integrated computational approach successfully identified D3 as a potent and synthetically feasible CYP11B1 inhibitor candidate. These findings provide a validated framework for the rational design and optimization of new inhibitors with improved pharmacological and metabolic profiles.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03176"},"PeriodicalIF":3.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study proposes and applies a machine-learning-driven optimization framework to predict and enhance the thermomechanical performance of carbon-free adobe bricks reinforced with straw and sawdust. To move beyond trial-and-error mix design under a strength–insulation trade-off, the study establishes reproducible mix-selection rules that reduce experimental iterations. Experimental tests show that adding small amounts of straw (1% and 2%) significantly improves compressive strength, increasing it from 5.41 MPa to 9.62 MPa (+78%) and 7.93 MPa (+46.5%), respectively; however, higher dosages lead to a decrease in strength due to excessive porosity. Sawdust reduces mechanical strength but improves insulation by lowering thermal conductivity from 0.632 W/m.K for the reference brick to 0.145 W/m.K at 10% sawdust. Mixed formulations provided the best compromise: with approximately 0.5–4% sawdust and 0.5–4% straw, they maintained compressive strengths above the minimum requirement of 2.07 MPa established by the Mexican adobe construction standard. A measured dataset (density/porosity, Rc/Rf, λ and Cp) was used to train surrogate models with a 70/15/15 train–validation–test split, 5-fold cross-validation, and grid-search tuning. The machine learning models exhibited distinct predictive capabilities, achieving R² = 0.323–0.566 for compressive strength and R² = 0.794–0.991 for thermal conductivity, and multi-objective optimization (Pareto-based selection) further revealed that hybrid mixtures offer the most balanced solutions. These findings confirm the potential of agricultural waste valorization for the production of eco-friendly building materials and establish a systematic methodology that combines experimental work with artificial intelligence to optimize sustainable adobe bricks.
{"title":"Prediction and optimization of the thermomechanical performance of carbon-free Adobe bricks reinforced with straw and sawdust using machine learning","authors":"Abdelmounaim Alioui , Mohamed-Amine Babay , Mohammed Benfars , Youness Azalam , Samir Idrissi Kaitouni , El Maati Bendada , Mustapha Mabrouki","doi":"10.1016/j.sciaf.2025.e03167","DOIUrl":"10.1016/j.sciaf.2025.e03167","url":null,"abstract":"<div><div>This study proposes and applies a machine-learning-driven optimization framework to predict and enhance the thermomechanical performance of carbon-free adobe bricks reinforced with straw and sawdust. To move beyond trial-and-error mix design under a strength–insulation trade-off, the study establishes reproducible mix-selection rules that reduce experimental iterations. Experimental tests show that adding small amounts of straw (1% and 2%) significantly improves compressive strength, increasing it from 5.41 MPa to 9.62 MPa (+78%) and 7.93 MPa (+46.5%), respectively; however, higher dosages lead to a decrease in strength due to excessive porosity. Sawdust reduces mechanical strength but improves insulation by lowering thermal conductivity from 0.632 W/m.K for the reference brick to 0.145 W/m.K at 10% sawdust. Mixed formulations provided the best compromise: with approximately 0.5–4% sawdust and 0.5–4% straw, they maintained compressive strengths above the minimum requirement of 2.07 MPa established by the Mexican adobe construction standard. A measured dataset (density/porosity, Rc/Rf, λ and Cp) was used to train surrogate models with a 70/15/15 train–validation–test split, 5-fold cross-validation, and grid-search tuning. The machine learning models exhibited distinct predictive capabilities, achieving R² = 0.323–0.566 for compressive strength and R² = 0.794–0.991 for thermal conductivity, and multi-objective optimization (Pareto-based selection) further revealed that hybrid mixtures offer the most balanced solutions. These findings confirm the potential of agricultural waste valorization for the production of eco-friendly building materials and establish a systematic methodology that combines experimental work with artificial intelligence to optimize sustainable adobe bricks.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03167"},"PeriodicalIF":3.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-31DOI: 10.1016/j.sciaf.2025.e03175
Imane Moustati, Noreddine Gherabi
In this study, we present a novel hybrid portfolio‐management framework within an Internet of Behaviors (IoB) ecosystem that brings together rule‐based heuristics, explainable AI (XAI), and reinforcement learning to make robust, risk‐aware trading decisions. Our system harnesses FinBERT to extract daily sentiment scores from social media, fusing these signals with technical indicators in an LSTM forecasting model whose hyperparameters are optimally tuned via random search. Next, we apply TIME and TimeSHAP explainability tools to gauge how much we trust each prediction, and we adjust our entry, stop-loss, and take-profit levels on the fly based on that confidence. At the same time, a Q‐learning agent learns to scale position sizes by observing recent volatility, drawdown, and explainability confidence, maximizing a risk‐aware reward that balances profit against downside exposure. When backtested on Tesla data, our XAI‐driven hybrid system delivered a 60 % total return, with a Sharpe of 2.11, Sortino of 2.98, and Calmar of 17.9—all while keeping drawdowns below 4 %. It beat both a purely rule-based strategy and a buy-and-hold approach, and the integrated CVaR checks and circuit breakers stopped extreme losses, aligning with industry risk standards. Our findings underscore how embedding XAI‐derived confidence into reinforcement‐learned risk policies can yield state‐of‐the‐art risk‐adjusted performance, enhance trust through transparency, and pave the way for behavioral‐data‐driven financial decision‐support in next‐generation IoB platforms.
{"title":"A novel hybrid XAI-RL framework for IoB-driven risk-adjusted portfolio optimization","authors":"Imane Moustati, Noreddine Gherabi","doi":"10.1016/j.sciaf.2025.e03175","DOIUrl":"10.1016/j.sciaf.2025.e03175","url":null,"abstract":"<div><div>In this study, we present a novel hybrid portfolio‐management framework within an Internet of Behaviors (IoB) ecosystem that brings together rule‐based heuristics, explainable AI (XAI), and reinforcement learning to make robust, risk‐aware trading decisions. Our system harnesses FinBERT to extract daily sentiment scores from social media, fusing these signals with technical indicators in an LSTM forecasting model whose hyperparameters are optimally tuned via random search. Next, we apply TIME and TimeSHAP explainability tools to gauge how much we trust each prediction, and we adjust our entry, stop-loss, and take-profit levels on the fly based on that confidence. At the same time, a Q‐learning agent learns to scale position sizes by observing recent volatility, drawdown, and explainability confidence, maximizing a risk‐aware reward that balances profit against downside exposure. When backtested on Tesla data, our XAI‐driven hybrid system delivered a 60 % total return, with a Sharpe of 2.11, Sortino of 2.98, and Calmar of 17.9—all while keeping drawdowns below 4 %. It beat both a purely rule-based strategy and a buy-and-hold approach, and the integrated CVaR checks and circuit breakers stopped extreme losses, aligning with industry risk standards. Our findings underscore how embedding XAI‐derived confidence into reinforcement‐learned risk policies can yield state‐of‐the‐art risk‐adjusted performance, enhance trust through transparency, and pave the way for behavioral‐data‐driven financial decision‐support in next‐generation IoB platforms.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03175"},"PeriodicalIF":3.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.sciaf.2025.e03166
Nihad Sahri , Noura A Hassan , Nadia Hassan , Mona F Mahmoud , Ahmet Buğra Ortaakarsu , Abdellah Ezzanad , Asmae Alaoui , Elhassania Elherradi , Mansour Sobeh
Acute kidney injury (AKI) is a major clinical problem associated with high morbidity and mortality, and current treatment options remain limited. Herine, phytochemical characterization, computational analyses, and the nephroprotective effects of the aqueous extract of Euphorbia echinus aerial parts were investigated, and the underlying mechanisms were explored. The phytochemical components were identified employing LC-MS/MS, and their antioxidant potential was evaluated using the DPPH radical scavenging assay, while in vivo nephroprotection was evaluated using the glycerol-induced AKI model. Rats were given 200 or 400 mg/kg of the extract, and kidney function was assessed based on serum creatinine, blood urea nitrogen, urinary albumin, urinary creatinine, and the albumin/creatinine ratio. Biomarkers of oxidative stress (GSH, catalase), inflammation (IL-1β), and apoptosis (Bcl-2) were also quantified. Molecular docking, molecular dynamics simulations, and deep learning-based affinity prediction (Boltz-2) were used to determine the interactions of the identified phytoconstituents with caspase-1. LC-MS/MS analysis identified 76 phytocomponents, predominantly flavonoids, phenolic acids, and daphnane-type diterpenoids. The extract demonstrated marked antioxidant capacity, as indicated by a DPPH IC50 of 17.15 μg/mL, and its administration significantly restored renal function while attenuating oxidative stress, inflammatory cytokine production, and apoptotic signaling in a dose-dependent manner. Consistent computational analyses revealed resiniferatoxin and eupatorin as strong and stable caspase-1 binders. The findings of this study demonstrate the relevance of E. echinus phytoconstituents as promising candidates for AKI management and encourage plant-derived therapies against inflammasome-associated pathways.
{"title":"Phytochemical characterization and nephroprotective potential of Euphorbia echinus: antioxidant, anti-inflammatory, and anti-apoptotic effects in acute kidney injury","authors":"Nihad Sahri , Noura A Hassan , Nadia Hassan , Mona F Mahmoud , Ahmet Buğra Ortaakarsu , Abdellah Ezzanad , Asmae Alaoui , Elhassania Elherradi , Mansour Sobeh","doi":"10.1016/j.sciaf.2025.e03166","DOIUrl":"10.1016/j.sciaf.2025.e03166","url":null,"abstract":"<div><div>Acute kidney injury (AKI) is a major clinical problem associated with high morbidity and mortality, and current treatment options remain limited. Herine, phytochemical characterization, computational analyses, and the nephroprotective effects of the aqueous extract of <em>Euphorbia echinus</em> aerial parts were investigated, and the underlying mechanisms were explored. The phytochemical components were identified employing LC-MS/MS, and their antioxidant potential was evaluated using the DPPH radical scavenging assay, while <em>in vivo</em> nephroprotection was evaluated using the glycerol-induced AKI model. Rats were given 200 or 400 mg/kg of the extract, and kidney function was assessed based on serum creatinine, blood urea nitrogen, urinary albumin, urinary creatinine, and the albumin/creatinine ratio. Biomarkers of oxidative stress (GSH, catalase), inflammation (IL-1β), and apoptosis (Bcl-2) were also quantified. Molecular docking, molecular dynamics simulations, and deep learning-based affinity prediction (Boltz-2) were used to determine the interactions of the identified phytoconstituents with caspase-1. LC-MS/MS analysis identified 76 phytocomponents, predominantly flavonoids, phenolic acids, and daphnane-type diterpenoids. The extract demonstrated marked antioxidant capacity, as indicated by a DPPH IC<sub>50</sub> of 17.15 μg/mL, and its administration significantly restored renal function while attenuating oxidative stress, inflammatory cytokine production, and apoptotic signaling in a dose-dependent manner. Consistent computational analyses revealed resiniferatoxin and eupatorin as strong and stable caspase-1 binders. The findings of this study demonstrate the relevance of <em>E. echinus</em> phytoconstituents as promising candidates for AKI management and encourage plant-derived therapies against inflammasome-associated pathways.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03166"},"PeriodicalIF":3.3,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.sciaf.2025.e03170
Babangida Mohammed Ahmed , Andy Anderson Bery , Adedibu Sunny Akingboye , Muhammad Khan , Mbuotidem David Dick , Gabriel Abraham Bala , Dharma Arung Laby
The Middle–Upper Benue Trough (MBT–UBT) of Nigeria contains warm springs and felsic intrusions that indicate substantial geothermal potential, yet basin-scale geothermal–structural controls remain poorly constrained. This study integrates magnetic, gravity, and radiometric datasets—previously analysed separately in other studies—into a joint interpretive framework that images intrusive and basement highs, asymmetric sedimentary depocentres, and steep fault-controlled gradient belts, while radiogenic heat production (RHP) delineates radiogenic crustal domains, resolving the coupled heat-source–reservoir–pathway system. The resulting geothermal–structural framework identifies two corridor-scale geothermal targets (Awe–Keana–Akiri–Azara–Ribi and Wase–Kurmi–Pinau) and three first-order tectono-geophysical domains that control geothermal heat and fluid favourability: (i) intrusive and uplifted basement highs expressed as co-located magnetic–gravity highs, (ii) deep sedimentary depocentres locally exceeding 6–6.5 km defined by Bouguer gravity lows and 2-D gravity-depth modelling, and (iii) steep gradient belts interpreted as high-permeability fault corridors. Two continuous radiogenic belts—Keana–Awe–Azara–Akiri–Ribi (>3.0 µW m⁻³) and Wase–Kurmi–Pinau (∼2.3–2.9 µW m⁻³)—align with NE–SW rift-parallel structures segmented by NW–SE to E–W transfer zones. The strongest convergence of intrusive highs, elevated RHP, deep depocentres, and steep structural gradients occurs along the Awe–Keana–Akiri–Azara–Ribi corridor, with Wase–Kurmi–Pinau emerging as a secondary target. These findings establish the MBT–UBT as a structurally governed and radiogenically enhanced geothermal province and provide a transferable framework for geothermal prospect ranking and future drilling in intracontinental rift systems.
尼日利亚中上贝努埃海槽（MBT-UBT）含有温泉和长英质侵入岩，表明地热潜力巨大，但盆地尺度的地热构造控制仍然很差。本研究将磁场、重力和辐射测量数据集（之前在其他研究中分别进行了分析）整合到一个联合解释框架中，该框架对侵入性和基底性高点、不对称沉积沉积中心和陡峭的断层控制梯度带进行了成像，而放射性成因产热（RHP）则描绘了放射性成因的地壳域，解决了热源-储层-通道耦合系统。由此产生的地热构造框架确定了两个走廊尺度的地热目标（Awe-Keana-Akiri-Azara-Ribi和Wase-Kurmi-Pinau）和三个控制地热和流体有利性的一级构造-地球物理域：(i)侵入和隆起的基底高表现为同位磁重高；（ii）由布格重力低和二维重力-深度模型定义的局部超过6-6.5 km的深部沉积中心；（iii）陡峭的梯度带被解释为高渗透断层走廊。两条连续的辐射形成带——keina - awe - azara - akiri - ribi （3.0 μ W m毒毒学）和Wase-Kurmi-Pinau （2.3-2.9 μ W m毒毒学）——与NE-SW平行的裂谷构造相吻合，由NW-SE到E-W转移带分割开来。在Awe-Keana-Akiri-Azara-Ribi走廊上出现了最强的侵入高压辐合、较高的RHP、深沉积中心和陡峭的构造梯度，瓦斯-库尔米-皮瑙是次要目标。这些发现确立了MBT-UBT是一个受构造控制和放射性增强的地热省，并为大陆内裂谷系统的地热前景排序和未来钻探提供了可转移的框架。
{"title":"Basin-scale geothermal–structural mapping of the Nigerian Benue Trough using aeromagnetic, satellite gravity, and aeroradiometric data","authors":"Babangida Mohammed Ahmed , Andy Anderson Bery , Adedibu Sunny Akingboye , Muhammad Khan , Mbuotidem David Dick , Gabriel Abraham Bala , Dharma Arung Laby","doi":"10.1016/j.sciaf.2025.e03170","DOIUrl":"10.1016/j.sciaf.2025.e03170","url":null,"abstract":"<div><div>The Middle–Upper Benue Trough (MBT–UBT) of Nigeria contains warm springs and felsic intrusions that indicate substantial geothermal potential, yet basin-scale geothermal–structural controls remain poorly constrained. This study integrates magnetic, gravity, and radiometric datasets—previously analysed separately in other studies—into a joint interpretive framework that images intrusive and basement highs, asymmetric sedimentary depocentres, and steep fault-controlled gradient belts, while radiogenic heat production (RHP) delineates radiogenic crustal domains, resolving the coupled heat-source–reservoir–pathway system. The resulting geothermal–structural framework identifies two corridor-scale geothermal targets (Awe–Keana–Akiri–Azara–Ribi and Wase–Kurmi–Pinau) and three first-order tectono-geophysical domains that control geothermal heat and fluid favourability: (i) intrusive and uplifted basement highs expressed as co-located magnetic–gravity highs, (ii) deep sedimentary depocentres locally exceeding 6–6.5 km defined by Bouguer gravity lows and 2-D gravity-depth modelling, and (iii) steep gradient belts interpreted as high-permeability fault corridors. Two continuous radiogenic belts—Keana–Awe–Azara–Akiri–Ribi (>3.0 µW m⁻³) and Wase–Kurmi–Pinau (∼2.3–2.9 µW m⁻³)—align with NE–SW rift-parallel structures segmented by NW–SE to E–W transfer zones. The strongest convergence of intrusive highs, elevated RHP, deep depocentres, and steep structural gradients occurs along the Awe–Keana–Akiri–Azara–Ribi corridor, with Wase–Kurmi–Pinau emerging as a secondary target. These findings establish the MBT–UBT as a structurally governed and radiogenically enhanced geothermal province and provide a transferable framework for geothermal prospect ranking and future drilling in intracontinental rift systems.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03170"},"PeriodicalIF":3.3,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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