Search Results (68)

Ultrasonic impact treatment (UIT) is widely employed as a post-weld treatment to enhance the fatigue performance of welded joints through the introduction of surface plastic deformation and compressive residual stresses. While its beneficial effect on fatigue life when applied at an earlier stage is well established, the influence of UIT on aged structures remains controversial in the literature. This study investigates the effect of UIT on the corrosion performance of S355 steel welded T-joints after accelerated corrosion-induced aging. As-welded (AW) and UIT-treated T-joints were subjected to salt spray exposure, followed by detailed microstructural and surface analyses to assess corrosion morphology and damage evolution. The results show that UIT induces significant surface plastic deformation and microstructural refinement in the weld toe region without promoting preferential corrosion aging or accelerated degradation. The aging behavior of UIT-treated joints, following accelerated environmental exposure, is comparable to that of the AW condition, with corrosion rates decreasing from 3.27 and 3.28 mm/year at 42 days to 1.32 and 1.26 mm/year at 126 days for AW and UIT specimens, respectively. These results indicate that the compressive residual stresses and surface modifications introduced by UIT do not adversely affect material durability. These findings clarify the role of UIT under such exposure conditions and demonstrate that UIT can be applied as a post-weld treatment to improve fatigue properties without compromising the long-term performance of structural steel welded joints. Full article

Despite the importance of wastewater environmental monitoring in disease prevention and response strategies, its use remains poorly documented in Senegal. In addition, there is more onsite sanitation than sewer networks in Dakar, and open drains channel for rainwater are also used as clandestine wastewater discharge into the sea. This study aimed to assess the presence of specific pathogens in wastewater, faecal sludge, and bathing water (the sea). Samples were taken at treatment plants, an open drain, and in the receiving environment (the sea) from June to December 2023. Total nucleic acid was subjected to multiplex qualitative qPCR using SeeGene Allplex™ kits targeting 34 gastrointestinal pathogens. Descriptive statistics, multiple correspondence analysis (MCA) and logistic regression were performed. Considering all matrices, across 51 analysed samples, the results revealed strong bacterial (96.08%, n = 49), parasitic (84.31%, n = 43), and viral (68.63%, n = 35) presence. These results showed high levels of Aeromonas spp. (96.08%), Blastocystis hominis (80.39%), Enterocytozoon (58.82%), and Norovirus GII (74.51%) among bacteria, protozoa, helminths, and viruses, respectively. Moreover, faecal sludge and pumping station samples show more identified pathogen than wastewater treatment plant and seawater samples. The MCA revealed that the dry season is spatially associated with a greater number of pathogens than the rainy season, but the latter showed a greater species diversity. Logistic regression showed that certain physicochemical parameters, including BOD5, turbidity, pH, and suspended solids, influence pathogen detection. However, qualitative detection and sampling period may constitute limitations. These results reveal that wastewater and bathing water can serve as sources of information on the circulation of pathogens of interest with epidemic potential. Therefore, this valuable epidemiological tool could serve as an adjunct to clinical surveillance in order to prevent future epidemics. Full article

Malaria remains a global health threat, with Plasmodium falciparum causing most deaths, especially in sub-Saharan Africa. Although artemisinin-based therapies reduce the burden, drug-resistant parasites threaten control efforts. Mapping the distribution and evolution of molecular resistance markers is vital for evidence-based strategies. This systematic review mapped the global distribution, pooled prevalence, and temporal trends of key P. falciparum antimalarial resistance markers. Following the PRISMA methodology (PROSPERO: CRD4202511098991), databases (PubMed, Web of Science, Scopus, and Google Scholar) and gray sources were searched (July 2005–July 2025). Data were extracted in Rayyan, assessed via the JBI prevalence tool, and analyzed using Python v3.13 for WHO regional distribution, temporal trends, and treatment outcome trends. Of the 1972 records, 261 studies from 64 countries qualified for inclusion in this review. The pooled prevalence was highest for pfdhfr (85.7%), followed by pfcrt (78.0%), pfdhps (73.7%), pfmdr1 (60.5%), and pfk13 (45.0%). High heterogeneity (I² > 95%) and rising pfk13 since 2012 highlight emerging artemisinin resistance, while persistent pfdhfr/pfdhps mutations show that ongoing sulfadoxine–pyrimethamine (SP) pressure on P. falciparum drug resistance, decreased parasite clearance, and treatment failure remain widespread and evolving in Africa. Integrating molecular surveillance into national malaria programs is essential to guide treatment modalities and support progress toward malaria elimination. Full article

Recent advances in vibration-based pavement assessment have enabled the low-cost monitoring of road conditions using inertial sensors and machine learning models. However, most studies focus on isolated tasks, such as roughness classification, without integrating statistical validation, anomaly detection, or maintenance prioritization. This study presents a unified framework for road roughness severity classification and predictive maintenance using multi-axis accelerometer data collected from urban road networks in Pretoria, South Africa. The proposed pipeline integrates ISO-referenced labeling, ensemble and deep classifiers (Random Forest, XGBoost, MLP, and 1D-CNN), McNemar’s test for model agreement validation, feature importance interpretation, and GIS-based anomaly mapping. Stratified cross-validation and hyperparameter tuning ensured robust generalization, with accuracies exceeding 99%. Statistical outlier detection enabled the early identification of deteriorated segments, supporting proactive maintenance planning. The results confirm that vertical acceleration (accel_z) is the most discriminative signal for roughness severity, validating the feasibility of lightweight single-axis sensing. The study concludes that combining supervised learning with statistical anomaly detection can provide an intelligent, scalable, and cost-effective foundation for municipal pavement management systems. The modular design further supports integration with Internet-of-Things (IoT) telematics platforms for near-real-time road condition monitoring and sustainable transport asset management. Full article

Transportation networks are critical lifelines in national infrastructure but are increasingly exposed to risks arising from climate variability, cyber threats, aging assets, and limited resources. This paper presents a scoping review of 58 peer-reviewed studies published between 2015 and 2025 that examine the role of Artificial Intelligence (AI) in strengthening infrastructure resilience, with transportation systems adopted as the strategic case. The review classifies applications along five dimensions: technological approach, infrastructure sector, transportation linkage, resilience/security aspect, and key research gaps. Findings show that AI, machine learning (ML), and the Internet of Things (IoT) dominate current applications, particularly in predictive maintenance, intelligent monitoring, early-warning systems, and optimization. These applications extend beyond transport to energy, water, and agri-food systems that indirectly sustain transport resilience. Persistent challenges include affordability, data scarcity, infrastructural limitations, and limited real-world validation, especially in Sub-Saharan African contexts. The paper synthesizes cross-sector pathways through which AI enhances transport resilience and outlines practical implications for policymakers and practitioners. A targeted research agenda is also proposed to address methodological gaps, enhance deployment in resource-constrained settings, and promote hybrid and explainable AI for trust and scalability. Full article

Unexpected machine failures in industrial environments lead to high maintenance costs, unplanned downtime, and safety risks. This study proposes a proactive predictive model using a hybrid of eXtreme Gradient Boosting (XGBoost) and Neural Networks (NN) to forecast machine failures. A synthetic dataset capturing recent breakdown history and time since last failure was used to simulate industrial scenarios. To address class imbalance, SMOTE and class weighting were applied, alongside a focal loss function to emphasize difficult-to-classify failures. The XGBoost model was tuned via GridSearchCV, while the NN model utilized ReLU-activated hidden layers with dropout. Evaluation using stratified 5-fold cross-validation showed that the NN achieved an F1-score of 0.7199 and a recall of 0.9545 for the minority class. XGBoost attained a higher PR AUC of 0.7126 and a more balanced precision–recall trade-off. Sample predictions demonstrated strong recall (100%) for failures, but also a high false positive rate, with most prediction probabilities clustered between 0.50–0.55. Additional benchmarking against Logistic Regression, Random Forest, and SVM further confirmed the superiority of the proposed hybrid model. Model interpretability was enhanced using SHAP and LIME, confirming that recent breakdowns and time since last failure were key predictors. While the model effectively detects failures, further improvements in feature engineering and threshold tuning are recommended to reduce false alarms and boost decision confidence. Full article

Aluminum Conductors Steel-Reinforced (ACSR) conductors are typically used in overhead transmission lines. Corrosion is an important degradation mechanisms that might affect the lifetime of this essential electricity network component. Considering the complexity of conductors, it is difficult to predict the damage of these conductors in corrosive environments. The objective of this paper is to evaluate the effect of grease and conductor geometry on the mechanical properties of aluminum strand composing the envelope of ASCR conductors. Thus, ACSR wires and strands have been evaluated in corrosion by the mean of accelerated corrosion tests. Tensile, fatigue and torsion test results are presented to examine the effect of corrosion on aluminum strands. The influence of corrosion on mechanical characteristics is established by a decrease in ductility, maximum elongation and tensile strength for the longest exposition (336 days). This significant reduction in the internal layer of ungreased wires confirms the importance of the galvanic corrosion mechanism of aluminum wires. This evolution concerns only aluminum wires of non-greased conductors, confirming the crucial role of grease as protection against corrosion. Full article

Background: Insecticide resistance challenges the vector control efforts towards malaria elimination and proving the development of complementary tools. Targeting the genes that are involved in mosquito fertility and susceptibility to Plasmodium with small molecule inhibitors has been a promising alternative to curb the vector population and drive the transmission down. However, such an approach would require a comprehensive knowledge of the genetic diversity of the targeted genes to ensure the broad efficacy of new tools across the natural vector populations. Methods: Four fertility and parasite susceptibility genes were identified from a systematic review of the literature. The Single Nucleotide Polymorphisms (SNPs) found within the regions spanned by these four genes, genotyped across 2784 wild-caught Anopheles gambiae s.l. from 19 sub-Saharan African (SSA) countries, were extracted from the whole genome SNP data of the Ag1000G project (Ag3.0). The population genetic analysis on gene-specific data included the determination of the population structure, estimation of the differentiation level between the populations, evaluation of the linkage between the non-synonymous SNPs (nsSNPs), and a few statistical tests. Results: As potential targets for small molecule inhibitors to reduce malaria transmission, our set of four genes associated with Anopheles fertility and their susceptibility to Plasmodium comprises the mating-induced stimulator of oogenesis protein (MISO, AGAP002620), Vitellogenin (Vg, AGAP004203), Lipophorin (Lp, AGAP001826), and Haem-peroxidase 15 (HPX15, AGAP013327). The analyses performed on these potential targets of small inhibitor molecules revealed that the genes are conserved within SSA populations of An. gambiae s.l. The overall low Fst values and low clustering of principal component analysis between species indicated low genetic differentiation at all the genes (MISO, Vg, Lp and HPX15). The low nucleotide diversity (>0.10), negative Tajima’s D values, and heterozygosity analysis provided ecological insights into the purifying selection that acts to remove deleterious mutations, maintaining genetic diversity at low levels within the populations. None of MISO nsSNPs were identified in linkage disequilibrium, whereas a few weakly linked nsSNPs with ambiguous haplotyping were detected at other genes. Conclusions: This integrated finding on the genetic features of major malaria vectors’ biological factors across natural populations offer new insights for developing sustainable malaria control tools. These loci were reasonably conserved, allowing for the design of effective targeting with small molecule inhibitors towards controlling vector populations and lowering global malaria transmission. Full article

Integrating local, bio-sourced materials, such as earth and agricultural waste like dwarf hulls, is a sustainable solution to the challenges of climate change and increasing urbanization. The use of bio-based materials such as néré husk (Parkia biglobosa) in the manufacture of compressed earth bricks is a sustainable alternative for improving their thermal performance. This study assesses the impact of adding hulls in different forms (fine powder < 0.08 mm, aggregates from 2 mm to 5 mm, and aqueous maceration) on the thermal conductivity and effusivity of bricks. The tests were carried out using the asymmetric hot plane method, applying a constant heat flux and measuring the temperature variation via a thermocouple. Three samples of each formulation were analyzed to ensure the reliability of the results. The results show that the addition of fine powdered husk reduces the thermal conductivity of the bricks to 0.404 W/m.K and their effusivity to 922.2 W/(Km²) s¹/², compared with 0.557 W/m.K and 1000.32 W/(Km²) s¹/² for the control bricks. The addition of coarser aggregates (2 mm–5 mm) gives intermediate values (0.467 W/m.K and 907.99 W/(Km²) s¹/²). Aqueous maceration, on the other hand, results in an increase in thermal conductivity to 0.614 W/m.K. These results confirm that the shape and method of incorporation of the husk influence the thermal performance of the bricks, with fine powder offering the best thermal insulation. This approach highlights the potential of bio-based materials for eco-responsible construction. Full article

Orthobunyaviruses are a diverse group of segmented RNA viruses with significant but underexplored public and veterinary health implications. This study provides a genomic, phylogenetic, and ecological analysis of neglected Orthobunyaviruses using next-generation sequencing and computational predictions. We identified unique phylogenetic relationships, with Tanga virus forming a distinct lineage linked to zoonotic, human-associated, or non-vertebrate viruses across segments. GC content analysis revealed segment-specific patterns: higher GC content in the S segment suggests genomic stability and immune evasion, while lower GC content in the L segment reflects host-vector adaptation. Phylogenetic ties to well-characterized pathogenic viruses, such as Ilesha virus with Cache Valley virus and Bwamba virus with California encephalitis virus, indicate potential neurotropism. Ingwavuma virus clustered with Oropouche virus, suggesting risks of systemic febrile illnesses. Within the Simbu serogroup, Sango and Sabo viruses show teratogenic risks to livestock. Vector and host predictions implicate rodents, artiodactyls, and primates in Orthobunyavirus transmission, emphasizing complex ecological dynamics and zoonotic potential. These findings advance the understanding of Orthobunyavirus diversity, linking genomic features to pathogenicity and ecological adaptation, while providing a foundation for future surveillance and intervention strategies targeting these neglected viruses. Full article

Background/Objectives: Cowpea is a major source of dietary protein and plays a key role in sustainable agriculture across sub-Saharan Africa (SSA), Asia, and Latin America. Research efforts have focused mainly on enhancing productivity through higher yield and resistance to biotic and abiotic stresses in cowpea. Understanding the genetic basis of yield and associated agronomic traits is crucial for improving crop productivity. This study aims to identify quantitative trait loci (QTL) associated with grain yield and related traits in cowpea under regular rainfed conditions. Methods: We developed a set of 316 F6:7 recombinant inbred lines (RILs) mapping populations derived from a cross between RP270 and CB27 using a single-seed descent breeding method. The RILs and their two parental lines were evaluated in the field for two years, 2022 and 2023, at the International Institute of Tropical Agriculture (IITA) in Ibadan, Nigeria. The cowpea mid-density genotyping panel consisting of 2602 quality DArTag single nucleotide polymorphisms (SNPs) was used to genotype the RIL population. Results: Seven major QTLs, each explaining ≥10% of phenotypic variance, were detected for 100-seed weight, number of days to flower, number of pods per plant, number of branches per plant, and number of peduncles per plant. Putative genes associated with yield and related traits were identified within significant flanking markers. Further efforts to validate these loci will help to better understand their roles in yield and associated traits in cowpea. Full article

Cassava brown streak disease (CBSD) remains the most severe threat to cassava production in the Great Lakes region and Southern Africa. Screening for virus resistance by subjecting cassava to high virus pressure in the epidemic zone (hotspots) is a common but lengthy process because of unpredictable and erratic virus infections requiring multiple seasons for disease evaluation. This study investigated the feasibility of graft-infections to provide a highly controlled infection process that is robust and reproducible to select and eliminate susceptible cassava at the early stages and to predict the resistance of adapted and economically valuable varieties. To achieve this, a collection of cassava germplasm from the Democratic Republic of Congo and a different set of breeding trials comprising two seed nurseries and one preliminary yield trial were established. The cassava varieties OBAMA and NAROCASS 1 infected with CBSD were planted one month after establishment of the main trials in a 50 m² plot to serve as the source of the infection and to provide scions to graft approximately 1 ha. Grafted plants were inspected for virus symptoms and additionally tested by RT-qPCR for sensitive detection of the viruses. The incidence and severity of CBSD and cassava mosaic disease (CMD) symptoms were scored at different stages of plant growth and fresh root yield determined at harvesting. The results from the field experiments proved that graft-infection with infected plants showed rapid symptom development in susceptible cassava plants allowing instant exclusion of those lines from the next breeding cycle. High heritability, with values ranging from 0.63 to 0.97, was further recorded for leaf and root symptoms, respectively. Indeed, only a few cassava progenies were selected while clones DSC260 and two species of M. glaziovii (Glaziovii20210005 and Glaziovii20210006) showed resistance to CBSD. Taken together, grafting scions from infected cassava is a highly efficient and cost-effective method to infect cassava with CBSD even under rugged field conditions. It replaces an erratic infection process with a controlled method to ensure precise screening and selection for virus resistance. The clones identified as resistant could serve as elite donors for introgression, facilitating the transfer of resistance to CBSD. Full article

The cladding process is a cost-effective solution to improve surface properties and obtain additional functionalities. The current paper focuses on the cladding of austenitic 304L stainless steel on aluminum substrate (SS/Al) by diffusion bonding, particularly relevant in the kitchenware field for safety issues. The study investigates the bonding characteristics and the deep drawing formability of the clad material, aiming to improve the understanding of its performance. The main results show a defect-free interface, as observed through microstructural analyzes. This highlights the ability of this process to create a good bond. The SEM/EDS results confirmed the absence of a diffusion layer. Microhardness and adhesion tests revealed non-uniform hardness values and moderate strength values across the interface. Numerical simulation showed the feasibility of deep drawing the SS/Al clad material without failure, proving its suitability in cookware manufacturing. These findings demonstrate the workability of diffusion bonding and suggest the potential for improving mechanical properties. Full article

Hybrid teaching, which integrates traditional in-person learning based on students’ perspectives where online learning offers a flexible approach to education, combines the benefits of technology with face-to-face interactions. Moreover, teaching and learning in a hybrid way met several challenges for both teachers and learners, including technological problems, time management, communication difficulties, and assessment complexities. This systematic review investigates six main research questions: (1) What pedagogical frameworks are used in hybrid teaching and learning? (2) How can we enhance students’ engagement in hybrid teaching and learning? (3) What is the impact of technological integration on hybrid learning scenarios, both for students and teachers? (4) How do training and support measures influence the willingness and ability of university teachers to implement hybrid teaching formats? (5) How do formative assessment and feedback methods in hybrid learning environments enable teachers to effectively monitor student progress and provide tailored support? (6) How does the implementation of hybrid learning affect student learning outcomes? This study identifies the following key themes: technological integration, pedagogical innovation, faculty support, student engagement, assessment practices, and learning outcomes. Our contribution of this literature review is related to teaching and learning by showing teachers the most appropriate way to avoid the challenges encountered when teaching in a hybrid way. These include strong technology integration, innovative pedagogical strategies, strong academic development and support, active student engagement, effective assessment practices, and positive learning outcomes. Full article

Cowpea is one of the most important leguminous crops in Sub-Saharan Africa (SSA), and moisture stress is among the constraints affecting its productivity. This study was conducted to understand the response of cowpea accessions to moisture stress. A total of 255 cowpea accessions from Togo and four checks from the International Institute of Tropical Agriculture (IITA), were assessed. The trials were conducted in the glasshouse and an open field (which was divided into moisture-stressed (MS) and non-moisture-stressed fields (NMS)). In the non-moisture-stressed environment compared to the moisture-stressed environment, there was a greater heritability for agronomic traits such as biomass, seed weight, and pod weight. The accessions with the highest seed weights (yield-related traits), surpassing the checks under both moisture-stressed and non-moisture-stressed conditions in the field, were six viz.: RK173 (49.8 g (MS); 90.4 g (NMS)), RP225 (34.6 g (MS); 119.9 g (NMS)), RP232 (33.4 g (MS); 51.9 g (NMS)), RM357 (27.9 g (MS); 62.9 g (NMS)), RK148 (23.9 g (MS); 63.4 g (NMS)), and Vu081_2_2 (21.8 g (MS); 46.7 g (NMS)). The most promising accession was RK173; this was ranked first under the moisture-stressed condition and ranked second under the non-moisture-stressed condition with a loss in weight of 44.9% due to drought stress. Of the top 20 accessions that recovered after watering resumed in the glasshouse screening, only the following 9 had a recovery percentage higher than 5% viz.: RS029 (34.5%), RK014 (14.2%), RS114 (9.6%), RK121 (8.3%), RS007 (7.6%), RK123 (7.3%), RS037 (7.3%), RS101 (5.6%), and RS108 (5.1%). The best line and those with a higher recovery percentage could be exploited further in order to improve them in future drought breeding programs by crossing them with lines susceptible to drought or using other drought breeding techniques. Full article