This study was conducted to investigate the integration of a Hydraulic Variable Valve Actuation (HVVA) system into a Lifan 177F single-cylinder gasoline engine to enhance performance, fuel efficiency, and emissions control. Unlike conventional valve mechanisms, HVVA systems are designed to dynamically adjust valve timing and lift through hydraulic actuation, allowing combustion to be optimized across a range of engine loads and speeds. MATLAB and GT-Suite simulations were used to model and evaluate the behavior of various valve spring configurations, including single-valve, dual-valve, and double-spring pendulum designs under dynamic operating conditions. It was found that engine power output was increased by 10%, fuel consumption was reduced by 5.64%, and torque delivery was significantly improved at mid to high RPM ranges. Among the configurations examined, the double-spring pendulum mechanism was shown to be the most effective in minimizing hydraulic oscillations, improving valve stability, and enabling smoother operation at higher speeds. These results highlight the practical potential of HVVA systems for use in compact and cost-sensitive engine platforms, where compliance with stringent emissions regulations and improved efficiency are increasingly demanded. Through precise and adaptive valve control, the proposed HVVA approach is shown to support cleaner combustion and align with broader sustainability objectives. In future work, efforts will be directed toward overcoming integration challenges and refining control strategies to further optimize HVVA system performance in practical automotive applications.
{"title":"Performance enhancement of a single-cylinder gasoline engine through hydraulic variable valve actuation (HVVA) system integration","authors":"Dimamu Biru, kumlachew Yeneneh, Bisrat Yoseph, Tatek Mamo","doi":"10.1016/j.sciaf.2026.e03196","DOIUrl":"10.1016/j.sciaf.2026.e03196","url":null,"abstract":"<div><div>This study was conducted to investigate the integration of a Hydraulic Variable Valve Actuation (HVVA) system into a Lifan 177F single-cylinder gasoline engine to enhance performance, fuel efficiency, and emissions control. Unlike conventional valve mechanisms, HVVA systems are designed to dynamically adjust valve timing and lift through hydraulic actuation, allowing combustion to be optimized across a range of engine loads and speeds. MATLAB and GT-Suite simulations were used to model and evaluate the behavior of various valve spring configurations, including single-valve, dual-valve, and double-spring pendulum designs under dynamic operating conditions. It was found that engine power output was increased by 10%, fuel consumption was reduced by 5.64%, and torque delivery was significantly improved at mid to high RPM ranges. Among the configurations examined, the double-spring pendulum mechanism was shown to be the most effective in minimizing hydraulic oscillations, improving valve stability, and enabling smoother operation at higher speeds. These results highlight the practical potential of HVVA systems for use in compact and cost-sensitive engine platforms, where compliance with stringent emissions regulations and improved efficiency are increasingly demanded. Through precise and adaptive valve control, the proposed HVVA approach is shown to support cleaner combustion and align with broader sustainability objectives. In future work, efforts will be directed toward overcoming integration challenges and refining control strategies to further optimize HVVA system performance in practical automotive applications.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03196"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077792","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 : 2026-03-01Epub Date: 2025-12-02DOI: 10.1016/j.sciaf.2025.e03120
F.A. Al-Marhaby , Ahmed Abdelkarim , Roshdi Seoudi
Silver nanoparticles (AgNPs) were chemically synthesized and incorporated into a polyvinyl alcohol–polyvinylpyrrolidone (PVA–PVP) polymer blend using a solution casting method to create PVA–PVP/AgNPs nanocomposite films. Transmission electron microscopy (TEM) revealed uniformly dispersed spherical AgNPs with diameters ranging from 10 to 30 nm, which strongly depend on precursor concentration. X-ray diffraction (XRD) confirmed the semi-crystalline structure of the (PVA–PVP) blend, while Fourier Transform Infrared (FTIR) indicated specific interactions between the silver species and the (PVA–PVP) matrices. UV–Vis spectroscopy showed a surface plasmon resonance (SPR) band between 380 and 400 nm, confirming the successful incorporation of nanoparticles. The position and width of this band correlated with particle size and dispersion. The optical band gap, estimated from Tauc plots, decreased from 5.28 eV for the pure PVA–PVP matrix to 5.18 eV upon AgNPs addition, suggesting improved electronic transition characteristics. Broadband dielectric spectroscopy (0.1 Hz–20 MHz) indicated enhanced dielectric constant and loss at low-frequency attributable to interfacial and space-charge polarization effects. PVA–PVP/AgNPs interfaces introduced varying properties, while the conductivity spectra revealed frequency-dependent hopping processes.
{"title":"Exploring the impact of silver nanoparticles on the structure, optical properties, and dielectric response of PVA–PVP blends","authors":"F.A. Al-Marhaby , Ahmed Abdelkarim , Roshdi Seoudi","doi":"10.1016/j.sciaf.2025.e03120","DOIUrl":"10.1016/j.sciaf.2025.e03120","url":null,"abstract":"<div><div>Silver nanoparticles (AgNPs) were chemically synthesized and incorporated into a polyvinyl alcohol–polyvinylpyrrolidone (PVA–PVP) polymer blend using a solution casting method to create PVA–PVP/AgNPs nanocomposite films. Transmission electron microscopy (TEM) revealed uniformly dispersed spherical AgNPs with diameters ranging from 10 to 30 nm, which strongly depend on precursor concentration. X-ray diffraction (XRD) confirmed the semi-crystalline structure of the (PVA–PVP) blend, while Fourier Transform Infrared (FTIR) indicated specific interactions between the silver species and the (PVA–PVP) matrices. UV–Vis spectroscopy showed a surface plasmon resonance (SPR) band between 380 and 400 nm, confirming the successful incorporation of nanoparticles. The position and width of this band correlated with particle size and dispersion. The optical band gap, estimated from Tauc plots, decreased from 5.28 eV for the pure PVA–PVP matrix to 5.18 eV upon AgNPs addition, suggesting improved electronic transition characteristics. Broadband dielectric spectroscopy (0.1 Hz–20 MHz) indicated enhanced dielectric constant and loss at low-frequency attributable to interfacial and space-charge polarization effects. PVA–PVP/AgNPs interfaces introduced varying properties, while the conductivity spectra revealed frequency-dependent hopping processes.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03120"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145683068","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 : 2026-03-01Epub Date: 2025-11-26DOI: 10.1016/j.sciaf.2025.e03110
Benjamin Kwakye , Alexander Sasu , Stephen Ameyaw , Frank Gyamfi-Yeboah
Previous studies have concluded that models that account for nonlinear relationships outperform their linear counterparts. However, while this is evident in advanced economies, the same cannot be inferred in Sub-Saharan Africa. This paper seeks to show how house prices are responsive to the nonlinear shocks of selected macroeconomic indicators, while controlling for the effects of interest rate and population in the Kenyan housing market. We employed the Nonlinear Autoregressive Distributed Lag (NARDL) model on a quarterly dataset from 2004Q1 to 2021Q4. In the long run, we showed that house prices respond to some nonlinear shocks of macroeconomic indicators, particularly shocks of the exchange rate and the shock of the market index, but not inflationary rate. Moreover, we established a significant negative effect of interest rate and population on house prices. In the short run, we also noted that a decrease in the exchange rate influences house prices negatively. Interest rate, including its lag terms, also impacts house prices negatively. These findings call for prudent macro-prudential policies, more importantly: (a) management of exchange rate and interest rate; (b) give property investment insight and (c) offer effective policy direction in the development and sustenance of the Kenyan property market.
{"title":"From linear to nonlinear models: Responsiveness of house prices to shocks from macroeconomic indicators in Kenya","authors":"Benjamin Kwakye , Alexander Sasu , Stephen Ameyaw , Frank Gyamfi-Yeboah","doi":"10.1016/j.sciaf.2025.e03110","DOIUrl":"10.1016/j.sciaf.2025.e03110","url":null,"abstract":"<div><div>Previous studies have concluded that models that account for nonlinear relationships outperform their linear counterparts. However, while this is evident in advanced economies, the same cannot be inferred in Sub-Saharan Africa. This paper seeks to show how house prices are responsive to the nonlinear shocks of selected macroeconomic indicators, while controlling for the effects of interest rate and population in the Kenyan housing market. We employed the Nonlinear Autoregressive Distributed Lag (NARDL) model on a quarterly dataset from 2004Q1 to 2021Q4. In the long run, we showed that house prices respond to some nonlinear shocks of macroeconomic indicators, particularly shocks of the exchange rate and the shock of the market index, but not inflationary rate. Moreover, we established a significant negative effect of interest rate and population on house prices. In the short run, we also noted that a decrease in the exchange rate influences house prices negatively. Interest rate, including its lag terms, also impacts house prices negatively. These findings call for prudent macro-prudential policies, more importantly: (a) management of exchange rate and interest rate; (b) give property investment insight and (c) offer effective policy direction in the development and sustenance of the Kenyan property market.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03110"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145683115","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 : 2026-03-01Epub Date: 2026-01-05DOI: 10.1016/j.sciaf.2025.e03140
M.E. Sobh , Ammar M. Sarhan
Accurate modeling of data restricted to the unit interval is essential across many applied disciplines. This paper proposes two new single-parameter probability distributions tailored for variables supported on . The models are mathematically tractable and exhibit notable flexibility, with analytical expressions derived for their survival and hazard functions, moments, and parameter-driven behavior. Their single-parameter structure enables closed-form maximum likelihood and Bayesian estimators, avoiding the heavy numerical optimization typically required by existing unit-interval models. The maximum likelihood estimators are shown to be global solutions, and the Bayesian framework benefits from the conjugacy of the gamma prior, allowing for efficient posterior inference. The performance of the proposed distributions is assessed through extensive simulations and applications to four real datasets. These datasets were selected to encompass both positively and negatively skewed structures, allowing for an evaluation of model performance across diverse distributional shapes. The empirical results demonstrate that the proposed models provide an excellent fit for all skewness patterns and consistently outperform ten established benchmark models based on standard goodness-of-fit criteria.
{"title":"Two new unit-interval distributions with applications to COVID-19 and reservoir capacity data","authors":"M.E. Sobh , Ammar M. Sarhan","doi":"10.1016/j.sciaf.2025.e03140","DOIUrl":"10.1016/j.sciaf.2025.e03140","url":null,"abstract":"<div><div>Accurate modeling of data restricted to the unit interval is essential across many applied disciplines. This paper proposes two new single-parameter probability distributions tailored for variables supported on <span><math><mrow><mo>(</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>)</mo></mrow></math></span>. The models are mathematically tractable and exhibit notable flexibility, with analytical expressions derived for their survival and hazard functions, moments, and parameter-driven behavior. Their single-parameter structure enables closed-form maximum likelihood and Bayesian estimators, avoiding the heavy numerical optimization typically required by existing unit-interval models. The maximum likelihood estimators are shown to be global solutions, and the Bayesian framework benefits from the conjugacy of the gamma prior, allowing for efficient posterior inference. The performance of the proposed distributions is assessed through extensive simulations and applications to four real datasets. These datasets were selected to encompass both positively and negatively skewed structures, allowing for an evaluation of model performance across diverse distributional shapes. The empirical results demonstrate that the proposed models provide an excellent fit for all skewness patterns and consistently outperform ten established benchmark models based on standard goodness-of-fit criteria.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03140"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924884","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 : 2026-03-01Epub Date: 2025-12-19DOI: 10.1016/j.sciaf.2025.e03150
Gamil Gamal , Naglaa Zanaty , Pavol Nejedlik
Fine particulate matter (PM₂.₅) pollution poses significant environmental and health risks in urban areas, such as Greater Cairo (GC). To provide the first high-resolution, two-decade assessment (2000–2020) of chronic exposure, this study integrates 1 km satellite-derived PM₂.₅ concentrations with comprehensive population distribution dynamics (LandScan Global). Trends were assessed using the Mann–Kendall test, and Sen’s slope was also calculated. We utilized advanced exposure metrics: the Population-Weighted Mean Concentration (PWMC) and Total Exposure (TE). A multi-level classification based on the five World Health Organization (WHO) Interim Targets and Guideline Value (IT-1, IT-2, IT-3, IT-4, and the Guideline of 5 µg/m³) was used to quantify the health significance of exposure evolution rigorously. PWMC consistently violated strict international health standards, remaining 7 to 10 times higher than the WHO Guideline (5 µg/m³) over the entire period, indicating a 100% population exposure risk. Concentrations exhibited a non-linear temporal pattern, peaking around 2010 (domain-averaged peak at 45.6 µg/m³) before showing a decline through 2020. Crucially, analysis revealed that high population growth increased the overall health burden (TE), actively counteracting localized improvements in pollution intensity (PWMC). Robust K-means clustering confirmed that the highest exposure burdens persisted in dense urban cores and industrial corridors. These findings provide quantitative evidence essential for targeted air quality management, demonstrating the urgent need for integrated urban planning and localized policies to reduce the cumulative health burden in this megacity.
{"title":"Long-term spatiotemporal trends and population-weighted exposure to PM2.5 in Greater Cairo (2000–2020)","authors":"Gamil Gamal , Naglaa Zanaty , Pavol Nejedlik","doi":"10.1016/j.sciaf.2025.e03150","DOIUrl":"10.1016/j.sciaf.2025.e03150","url":null,"abstract":"<div><div>Fine particulate matter (PM₂.₅) pollution poses significant environmental and health risks in urban areas, such as Greater Cairo (GC). To provide the first high-resolution, two-decade assessment (2000–2020) of chronic exposure, this study integrates 1 km satellite-derived PM₂.₅ concentrations with comprehensive population distribution dynamics (LandScan Global). Trends were assessed using the Mann–Kendall test, and Sen’s slope was also calculated. We utilized advanced exposure metrics: the Population-Weighted Mean Concentration (PWMC) and Total Exposure (TE). A multi-level classification based on the five World Health Organization (WHO) Interim Targets and Guideline Value (IT-1, IT-2, IT-3, IT-4, and the Guideline of 5 µg/m³) was used to quantify the health significance of exposure evolution rigorously. PWMC consistently violated strict international health standards, remaining 7 to 10 times higher than the WHO Guideline (5 µg/m³) over the entire period, indicating a 100% population exposure risk. Concentrations exhibited a non-linear temporal pattern, peaking around 2010 (domain-averaged peak at 45.6 µg/m³) before showing a decline through 2020. Crucially, analysis revealed that high population growth increased the overall health burden (TE), actively counteracting localized improvements in pollution intensity (PWMC). Robust K-means clustering confirmed that the highest exposure burdens persisted in dense urban cores and industrial corridors. These findings provide quantitative evidence essential for targeted air quality management, demonstrating the urgent need for integrated urban planning and localized policies to reduce the cumulative health burden in this megacity.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03150"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924991","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":"2026-03-01","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}
Pub Date : 2026-03-01Epub Date: 2026-01-13DOI: 10.1016/j.sciaf.2026.e03183
Chelea Matchawe , Célestin Godwe , Clarisse Engowei Mbah , Tata B. Ndakoh , Mélanie F.K. Gondam , Henriette A. Essomba , Fadimatou Ahmadou , Manuela A. Baomog , Mélissa Wangue , Séverin Loul , Marie-Chantal Ngondé , Bonglaisin J. Nsawir , Lucy M. Ndip , Marco Galeotti , Edi Piasentier
Salmonella contamination of beef carcasses remains a major public health concern, particularly in low- and middle-income countries where abattoir hygiene and traceability systems are often inadequate. This study aimed to generate context-specific data on Salmonella contamination along the cattle slaughter chain at the Yaoundé abattoir using real-time PCR, and to evaluate the influence of zootechnical factors of slaughtered cattle within a One Health framework. A total of 705 swab samples were collected from live cattle (n = 145), carcasses (n = 310), butchers’ hands (n = 145), and meat contact surfaces (n = 105). Salmonella detection was performed using TaqMan probe-based real-time PCR. Overall, 14.9% (95% CI: 12.4%–17.6%) of samples were positive for Salmonella, with prevalence rates of 5.20% (95% CI: 2.4%–10.6%) in live cattle, 17.73% (95% CI: 13.89%–22.38%) in carcasses, 1.9% (95% CI: 0.52% – 6.68%) in contact surfaces, and 5.52% (95% CI: 2.8% – 10.5%) in butchers’ hand swabs. Salmonella occurrence differed significantly among sample categories (p < 0.05). However, multivariate logistic regression revealed that none of the assessed zootechnical factors (sex, age, breed, transport, origin, cleanliness, body condition, and production system) were independently associated with contamination (p > 0.05). These findings suggest that Salmonella contamination in slaughtered cattle is driven by systemic hygiene and biosecurity shortcomings rather than individual animal-related factors. Overall, the moderate prevalence observed reflects gaps in slaughter hygiene and biosecurity. Strengthening sanitation practices, enforcing Hazard Analysis and Critical Control Point (HACCP) measures, and adopting molecular surveillance tools such as real-time PCR are essential to reduce contamination risks and protect public health.
{"title":"Impacts of zootechnical factors on Salmonella contamination in swab samples using real-time PCR at the Yaounde slaughterhouse","authors":"Chelea Matchawe , Célestin Godwe , Clarisse Engowei Mbah , Tata B. Ndakoh , Mélanie F.K. Gondam , Henriette A. Essomba , Fadimatou Ahmadou , Manuela A. Baomog , Mélissa Wangue , Séverin Loul , Marie-Chantal Ngondé , Bonglaisin J. Nsawir , Lucy M. Ndip , Marco Galeotti , Edi Piasentier","doi":"10.1016/j.sciaf.2026.e03183","DOIUrl":"10.1016/j.sciaf.2026.e03183","url":null,"abstract":"<div><div><em>Salmonella</em> contamination of beef carcasses remains a major public health concern, particularly in low- and middle-income countries where abattoir hygiene and traceability systems are often inadequate. This study aimed to generate context-specific data on Salmonella contamination along the cattle slaughter chain at the Yaoundé abattoir using real-time PCR, and to evaluate the influence of zootechnical factors of slaughtered cattle within a One Health framework. A total of 705 swab samples were collected from live cattle (<em>n</em> = 145), carcasses (<em>n</em> = 310), butchers’ hands (<em>n</em> = 145), and meat contact surfaces (<em>n</em> = 105). <em>Salmonella</em> detection was performed using TaqMan probe-based real-time PCR. Overall, 14.9% (95% CI: 12.4%–17.6%) of samples were positive for <em>Salmonella</em>, with prevalence rates of 5.20% (95% CI: 2.4%–10.6%) in live cattle, 17.73% (95% CI: 13.89%–22.38%) in carcasses, 1.9% (95% CI: 0.52% – 6.68%) in contact surfaces, and 5.52% (95% CI: 2.8% – 10.5%) in butchers’ hand swabs. <em>Salmonella</em> occurrence differed significantly among sample categories (<em>p</em> < 0.05). However, multivariate logistic regression revealed that none of the assessed zootechnical factors (sex, age, breed, transport, origin, cleanliness, body condition, and production system) were independently associated with contamination (<em>p</em> > 0.05). These findings suggest that <em>Salmonella</em> contamination in slaughtered cattle is driven by systemic hygiene and biosecurity shortcomings rather than individual animal-related factors. Overall, the moderate prevalence observed reflects gaps in slaughter hygiene and biosecurity. Strengthening sanitation practices, enforcing Hazard Analysis and Critical Control Point (HACCP) measures, and adopting molecular surveillance tools such as real-time PCR are essential to reduce contamination risks and protect public health.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03183"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077844","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 : 2026-03-01Epub Date: 2026-01-28DOI: 10.1016/j.sciaf.2026.e03203
Kevin Otieno , Linda Chaba , Evans Omondi , Collins Odhiambo , Bernard Omolo
In dependence modeling, choosing the right copula is crucial, as different copula models can yield distinct interpretations of the relationship between variables. However, real-world applications are often constrained by the limitations of existing copula selection methods, which lack consistency and robustness across datasets. The selection methods in the literature that includes goodness-of-fit (GoF) tests and selection criteria, often yield conflicting results, thereby misrepresenting the dependence structure and leading to misleading conclusions. This study developed an integrated copula selection framework that combines GOF tests with cross-validation techniques. We integrated block-based cross-validation with GoF tests, where data was partitioned into blocks of different sizes . A copula was fitted on the training set, and its performance was validated on the test set using GoF measures. The selection process was repeated across multiple folds, and an aggregation method was applied to determine the most suitable copula. The approach was tested through Monte Carlo simulations and an empirical study was tested on weather variables in Kenya. The findings show that Kendall-based Kolmogorov–Smirnov (KendallKS) and Cramér–von Mises (KendallCvM) test statistics integrated with stratified cross-validation, when , perform better when the Benjamini–Hochberg (BH) procedure was used for aggregation. The proposed tests successfully identified the true copula and consistently rejected incorrect alternatives, with performance improving as sample size and dependence level increased. The empirical application further demonstrates the method’s robustness in real-world settings. These findings demonstrate that the proposed approach enhances the reliability and stability of copula selection.
在依赖建模中，选择正确的联结模型是至关重要的，因为不同的联结模型可以对变量之间的关系产生不同的解释。然而，现实世界的应用经常受到现有的copula选择方法的限制，这些方法缺乏跨数据集的一致性和鲁棒性。文献中的选择方法包括拟合优度（GoF）检验和选择标准，往往产生相互矛盾的结果，从而歪曲了依赖结构并导致误导性结论。本研究开发了一个综合的copula选择框架，将GOF测试与交叉验证技术相结合。我们将基于块的交叉验证与GoF测试相结合，其中数据被划分为不同大小(K)的块。在训练集上拟合了一个copula，并使用GoF度量在测试集上验证了其性能。选择过程在多个折叠中重复进行，并采用聚集法确定最合适的copula。通过蒙特卡洛模拟对该方法进行了测试，并对肯尼亚的天气变量进行了实证研究。结果表明，当K=5时，使用Benjamini-Hochberg （BH）程序进行聚合时，Kendall-based Kolmogorov-Smirnov （KendallKS）和cram - von Mises （KendallCvM）检验统计量与分层交叉验证相结合，表现更好。所提出的测试成功地识别了真正的联结，并始终拒绝不正确的替代方案，随着样本量和依赖程度的增加，性能也在提高。实证应用进一步证明了该方法在现实世界中的鲁棒性。这些结果表明，该方法提高了交配体选择的可靠性和稳定性。
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Pub Date : 2026-03-01Epub Date: 2026-01-24DOI: 10.1016/j.sciaf.2026.e03190
Rachid Haloui , Amine Ballari , Khadija Khaddam Allah , Ayoub El-Mrabet , Abdelmoula El Abbouchi , Samir Chtita , Ahmed Mazzah , Amal Haoudi , Souad Elkhattabi
Human dihydroorotate dehydrogenase (DHODH) is a therapeutic target for the treatment of rheumatoid arthritis (RA). The development of new DHODH inhibitors could facilitate the discovery of a drug for RA therapy and contribute to sustainable health by promoting the design of safer and more efficient treatments. Using 3D-QSAR modeling techniques, we established a quantitative relationship between the DHODH inhibitory activity of 35 acrylamide derivatives (M1-M35) and their molecular fields. This model guided the design of 22 new acrylamide-based molecules (P1-P22) predicted to exhibit higher activity than M35, the most active in the initial database. The designed molecules were then docked into the DHODH active site, and the resulting complexes were evaluated using MM-GBSA free binding energy calculations. These analyses identified P4, P11, and P18 as the most DHODH inhibitors with docking scores and binding free energies superior to those of M35. The ADMET properties of the P4, P11, and P18 molecules were also predicted. The results show that they have good pharmacokinetic properties and are non-toxic. The molecular dynamics simulations of both free DHODH and its complexes with the best candidates confirmed the stability and validity of the obtained results. Finally, molecules P4, P11, and P18 show excellent capacity to inhibit the DHODH protein for the treatment of RA.
{"title":"Structure-based design and computational evaluation of new acrylamide derivatives as potent inhibitors of human dihydroorotate dehydrogenase for the treatment of rheumatoid arthritis","authors":"Rachid Haloui , Amine Ballari , Khadija Khaddam Allah , Ayoub El-Mrabet , Abdelmoula El Abbouchi , Samir Chtita , Ahmed Mazzah , Amal Haoudi , Souad Elkhattabi","doi":"10.1016/j.sciaf.2026.e03190","DOIUrl":"10.1016/j.sciaf.2026.e03190","url":null,"abstract":"<div><div>Human dihydroorotate dehydrogenase (DHODH) is a therapeutic target for the treatment of rheumatoid arthritis (RA). The development of new DHODH inhibitors could facilitate the discovery of a drug for RA therapy and contribute to sustainable health by promoting the design of safer and more efficient treatments. Using 3D-QSAR modeling techniques, we established a quantitative relationship between the DHODH inhibitory activity of 35 acrylamide derivatives (M1-M35) and their molecular fields. This model guided the design of 22 new acrylamide-based molecules (P1-P22) predicted to exhibit higher activity than M35, the most active in the initial database. The designed molecules were then docked into the DHODH active site, and the resulting complexes were evaluated using MM-GBSA free binding energy calculations. These analyses identified P4, P11, and P18 as the most DHODH inhibitors with docking scores and binding free energies superior to those of M35. The ADMET properties of the P4, P11, and P18 molecules were also predicted. The results show that they have good pharmacokinetic properties and are non-toxic. The molecular dynamics simulations of both free DHODH and its complexes with the best candidates confirmed the stability and validity of the obtained results. Finally, molecules P4, P11, and P18 show excellent capacity to inhibit the DHODH protein for the treatment of RA.</div></div>","PeriodicalId":21690,"journal":{"name":"Scientific African","volume":"31 ","pages":"Article e03190"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077789","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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