Search Results (21,285)

Processing tubers such as potato, sweet potato, cassava, and yam, as well as legumes such as soybean, pea, chickpea, bean, and lentil, generates substantial quantities of peels, pulps, husks, and press cakes that retain considerable nutritional and functional value despite often being discarded. Microbial fermentation has emerged as a low-cost and scalable approach for valorising these residues into functional ingredients with improved digestibility and enhanced bioactive-compound content. This study synthesises the composition of major tuber and legume by-products, the solid-state and submerged fermentation systems employed for their bioconversion, and the biochemical and functional transformations achieved through fermentation, including improvements in antioxidant activity, prebiotic potential, antihyperglycaemic properties, and protein quality. The emerging applications of these fermented by-products in bakery products, dairy alternatives, snacks, nutraceuticals, and the conceptually related field of gut-microbiome-guided precision nutrition are also examined. Persistent challenges, including compositional variability, safety monitoring, and regulatory classification, are critically evaluated alongside strategies for addressing these limitations. Overall, fermentation-based valorisation of tuber and legume residues represents a scientifically credible and environmentally sustainable strategy for transforming agri-food waste streams into value-added, functional nutrition ingredients. Full article

Interactions between soil bacteria and free-living bacterivorous nematodes influence nutrient cycling, microbial community dynamics, and rhizosphere processes, yet the behavioural responses of nematodes to bacterial traits remain poorly understood. This study investigated the relationship between bacterial phenotypic traits and the behavioural responses of Metarhabditis rainai isolated from ginger rhizosphere soil in Limpopo Province, South Africa. Three bacterial isolates (Stenotrophomonas chelatiphaga, Bacillus sp., and Aeromonas sp.) were characterized for hemolytic activity, motility, biofilm formation, and gentamicin susceptibility. Molecular analyses of 18S and 16S rDNA confirmed the identities of the nematode and bacterial isolates. Nematode attraction was evaluated using an in vitro feeding preference assay. Significant effects of bacterial isolate, time, and their interaction were detected (p < 0.0001), indicating distinct behavioural responses among treatments. Aeromonas sp. elicited the strongest attraction, followed by Bacillus sp., whereas S. chelatiphaga induced a weaker response. Bacterial phenotypic traits varied among isolates, with Bacillus sp. exhibiting the highest hemolytic activity, motility, and gentamicin resistance. Overall, M. rainai displayed selective attraction toward different bacterial isolates, and these responses coincided with variation in bacterial traits. However, no direct causal relationship between individual bacterial traits and nematode behaviour was established. Full article

Cloacal swabs were collected from 12 Eurasian goshawk chicks during routine veterinary inspections to evaluate the gut-associated virome of goshawks used for falconry. The material was used for metagenomic screening with high-throughput sequencing. Sequences belonging to several viral families (Poxviridae, Circoviridae, Anelloviridae, Retroviridae, Parvoviridae and Astroviridae) were detected and their occurrence differed across samples G1-G12. Most of the identified sequences were highly similar to those of viruses that infect poultry, suggesting a probable alimentary transmission route. Two complete genomes of closely related chicken astroviruses, most likely strains belonging to subgroup Biii, were identified. Their ORF2 proteins shared 98.78% amino acid identity. Another complete genome was identified as that of pigeon circovirus with 98.96% nucleotide identity to a strain previously reported from China. A parvovirus genome sequence, distinct from those of known members of the genus Aveparvovirus genus was also identified. This parvovirus genome sequence represents approximately 86% of the average aveparvovirus genome length (5422 bp) and contains three open reading frames. The sequence lacks the 3′ region of the capsid gene is missing and the 3′ UTR. The NS1 protein sequence of this virus shares 52.42% amino acid identity with that of its closest relative, the nonstructural protein of silver pheasant parvovirus. These findings suggest that parvovirus infection may occur in birds of prey and that the detected virus may represent a novel member of the genus Aveparvovirus. The infected bird showed no clinical symptoms during sampling; thus, the role of this parvovirus in raptor pathology as well as the possibility that it was of dietary origin remains unknown and requires further investigation. Full article

The increasing sophistication of cyber threats and severe class imbalance in network traffic continue to challenge traditional intrusion detection systems. This study proposes a hybrid framework that integrates SMOTE and CTGAN for minority-class augmentation, a Bidirectional Long Short-Term Memory (Bi-LSTM) network for supervised traffic classification, and a benign-trained Variational Autoencoder (VAE) for validating low-confidence predictions. The framework was evaluated on the CSE-CIC-IDS2018 dataset. On a final holdout test partition of 2,759,227 network flows, it achieved a binary accuracy of 98.51%, an F1-score of 92.59%, and a ROC-AUC of 0.9935. In the 15-class evaluation, it achieved 98.50% accuracy and a weighted F1-score of 98.42%, while stratified 10-fold cross-validation yielded a mean accuracy of 98.79%. The VAE was activated for 519,389 low-confidence flows, representing 18.82% of the complete holdout test partition, and primarily reduced false-positive predictions, although this improvement was accompanied by a measurable reduction in attack recall. SHAP analysis was applied to the supervised Bi-LSTM component to provide feature-level interpretability. The framework also achieved a mean inference latency of 0.5195 ms per network flow. These findings demonstrate strong aggregate detection performance, stable generalisation, effective false-alarm reduction, and low inference latency, while highlighting continuing challenges in rare-class and open-set detection. Full article

The efficient utilization of underexploited biomass resources for renewable energy production requires reliable engineering data on their mechanical behaviour during processing. However, information on the compressive mechanical properties of Canarium schweinfurthii seeds, a promising oil-bearing biomass resource, remains scarce. This study investigated the effects of moisture content (3.89–25.65%, db) and loading orientation (horizontal and vertical) on the compressive mechanical properties of the seeds using a universal testing machine. Measured parameters included rupture force, rupture energy, bio-yield force, bio-yield energy, deformation at rupture point, and hardness. Moisture content significantly influenced the measured mechanical properties under both horizontal and vertical loading orientations (<!-- MathType@Translator@5@5@MathML2 (no namespace).tdl@MathML 2.0 (no namespace)@ --> Full article

Precise prediction of pressure drop and drag-reduction performance is essential for improving the hydraulic efficiency and reducing the energy demand of crude-oil pipeline transportations. Therefore, this study aims to develop an integrated computational fluid dynamics (CFD)–machine learning (ML) framework for predicting pressure drop (∆p), drag reduction (DR), pumping power reduction (PPR), energy savings (ES), and flow-rate enhancement (Q) in turbulent crude-oil pipeline flow containing drag-reducing agents (DRAs). The investigated system considers the effect of pipeline length (L), diameter (D), surface roughness (ε), operating temperature (T), and DRA concentration (25–200 ppm). The Reynolds-average Navier–Stokes equations (RANS) were solved using the shear stress transport (SST) k-ω turbulence model approaching near-wall resolution of y⁺ ≈ 1 for DRA3 at 20 ppm. The CFD modelling was first used to validate an experimental benchmark and subsequently used to expand the available dataset over the investigated operating conditions. The combined experimental–CFD dataset was then employed to develop a multi-output Kolmogorov–Arnold network (KAN) surrogate model. The proposed framework predicted DR up to 44.2%, PPR of approximately 55 W, ES of 30%, and flow-rate enhancement up to 5–10(${\displaystyle \frac{\mathrm{L}}{\mathrm{d}\mathrm{a}\mathrm{y}}}$). The KAN model effectively captured the nonlinear relationships among DRA characteristics, pipeline geometry, and operating conditions, achieving R² = 0.9318 for PPR prediction. The novelty of the proposed work lies in integrating a validated, near-wall-resolved SST k-ω CFD model with a multi-output KAN surrogate model, combining physics-based flow analysis with rapid data-driven prediction of hydraulic and energy-performance indicators. Full article

Closely related Aspergillus section Nigri species are difficult to resolve taxonomically, while short-read comparisons may be influenced by reference-genome choice. We applied reciprocal genome projection to 31 whole-genome sequencing libraries representing South African clinical section-Nigri isolates, Japanese and USA A. niger-labeled isolates, and A. welwitschiae-labeled isolates. Reads were aligned independently to A. niger ATCC 1015 and A. welwitschiae Aspwel1, followed by reference-specific differential-representation and KEGG analyses. Species-level classification showed substantial overlap between A. niger and A. welwitschiae. The A. welwitschiae–South African comparison identified 44 and 59 effect-qualified features under the respective projections, including 20 reciprocal feature pairs defining a reference-robust A. welwitschiae-associated core. The clinical Japanese–South African comparison identified 116 and 127 features, with 14 concordant KEGG orthologs involving sterol modification, protein prenylation, cofactor metabolism, redox processing, cell-wall turnover and ribosome maturation. No pathway remained significant after false discovery-rate correction; nominal pathway signals were reference-sensitive. Reciprocal projection, therefore, recovered localized cohort-associated genomic differentiation while identifying reference-conditioned effects. These findings represent differential genomic-read representation and do not independently establish copy-number variation, pathway activity, virulence or antifungal resistance. Full article

The cultic practices of ancient Israel, specifically with respect to ritual eating and sex, serve jointly as a unifying motif for 1 Corinthians 8–11. Eating and sexual intercourse are viewed as sacred acts because of their generative capacity. Sex and food were highly regulated in ancient Israel, yet eating was an essential part of Israelite ritual, while sex was forbidden. Paul’s discussion of various issues in 1 Corinthians 8–11 is linked in his discourse by the common thread of the generative and communicative power of food and sex. Full article

This qualitative study addresses a significant gap in existing literature concerning the emotional, psychological, and academic consequences of gender-based violence (GBV) among high school learners in Eswatini, a context where culturally embedded norms and systemic challenges may shape how GBV is experienced, disclosed, and addressed. While prior research underscores the detrimental effects of GBV, limited attention has been given to learners’ accounts within Eswatini’s socio-cultural landscape. Employing a qualitative descriptive design, data were collected from 36 learners (18 girls and 18 boys) across six high schools. Thirty learners participated in six focus group discussions, with five learners in each group, while an additional six learners participated in individual semi-structured interviews. No participant participated in both methods. Data were analysed using Braun and Clarke’s reflexive thematic analysis. Three overarching themes were developed inductively: (1) emotional trauma and demotivation, characterised by feelings of worthlessness, fear, anxiety, and withdrawal; (2) psychological effects, including anxiety, shame, isolation, and psychological distress; and (3) a decline in academic performance and engagement, reflected in perceived difficulties with concentration, attendance, participation, motivation, and academic performance. Bronfenbrenner’s Ecological Model was subsequently used as an interpretive lens to examine how individual, interpersonal, institutional, community, and broader societal contexts shaped participants’ accounts. The study also considers similarities, differences, and contradictions in girls’ and boys’ accounts and recognises that participants occupy different positions in relation to GBV, including experiences of victimisation, witnessing, and acknowledgement of harmful behaviour. Because the study is qualitative and cross-sectional, the findings describe participants’ perceived relationships between GBV and educational and psychosocial experiences rather than establishing causal effects. The study highlights the importance of trauma-informed school environments, accessible psychosocial support, effective safeguarding and referral mechanisms, gender-responsive prevention, and coordinated interventions across ecological levels. Full article

High-dimensional gene expression datasets in chemometric and biomedical research present significant challenges for machine learning because the number of genes greatly exceeds the number of available samples, increasing the risk of overfitting and reducing classification reliability. Existing gene selection methods are often sensitive to noise and outliers, leading to unstable feature subsets and degraded classification performance. To address these limitations, this study proposes a Robust Masked Painter (RMP) framework that integrates robust measures of location and dispersion, namely the Median and the Rousseeuw & Croux statistic ($Q_n$), for reliable gene selection. The proposed framework operates in two stages. First, we identify informative genes using a round-robin strategy with a greedy search algorithm and robust core intervals to reduce the influence of noise and outliers. Second, Dominant Class (DC) analysis and Overlapping Scores (OS) further refine the selected gene subset by minimizing class overlap. We evaluate the proposed method on four publicly available gene expression datasets and compare it with several established feature selection methods using Random Forest, K-Nearest Neighbors, and Support Vector Machine classifiers. We assess classification performance using the Classification Error Rate. Experimental results and simulation studies demonstrate that the proposed RMP framework consistently outperforms competing methods by selecting highly informative genes that improve classification accuracy, robustness, and generalization. Full article

Dry anaerobic digestion (DAD) is increasingly recognized as a promising waste-to-energy pathway for treating high-solids organic wastes. However, the extent to which the contemporary peer-reviewed literature addresses conditions relevant to scalable implementation remains unclear. This systematic review synthesizes evidence from 148 studies on technological performance, process stability, scalability readiness, and deployment conditions. The evidence base was geographically and methodologically concentrated, with a predominance of laboratory-scale, batch-operated, and mesophilic systems. Co-digestion, pretreatment, operating-condition optimization, and recirculation were frequently investigated strategies. Methane performance varied substantially, reflecting differences in feedstock characteristics, solids content, reactor configurations, and operating conditions. Process stability remained a central concern, with pH, volatile fatty acids, and ammonia-related parameters the most frequently reported indicators, consistent with challenges associated with acidification, ammonia inhibition, and mass-transfer limitations. The scalability assessment showed that most studies provided limited evidence on advanced deployment maturity and enabling conditions, while commercial-scale implementation, financing, stakeholder engagement, and policy support were infrequently represented in the reviewed literature. The 2010–2025 peer-reviewed evidence base remains more strongly oriented toward technological and experimental optimization than integrated deployment-oriented assessment. Greater integration of long-term operational validation with techno-economic, institutional, and implementation-related evidence is needed to understand conditions for reliable and scalable DAD deployment. Full article

Introduction: Hepatitis B virus (HBV) genotypes exhibit distinct geographic distributions and may differ in virological expression. In low-endemic settings such as Canada, where chronic HBV burden is largely migration-driven, clinical cohorts provide a unique opportunity to characterize genotype diversity and its relationship with sociodemographic and baseline virological markers. Methods: We conducted a retrospective cohort study of patients with chronic HBV infection and available genotype results followed in The Ottawa Hospital Viral Hepatitis Program (TOHVHP) between 2001 and 2025. Results: Among 778 patients (median age 42.5 years; 52.3% male), 94.3% were born outside Canada, representing 78 countries and predominantly Asian (51.4%) and Black (34.8%). Six genotypes were identified: A (19.8%), B (25.6%), C (21.0%), D (17.4%), E (15.9%), and F (0.4%). Distribution reflected global migration patterns, with B/C predominating in East and Southeast Asia, E in West Africa, A in East Africa and the Caribbean, and D across the Middle East and North Africa, South Asia, and Europe/Central Asia. Younger age was observed among African-associated genotypes and among Black and Arab/MENA populations. Genotype-ethnicity patterns were concordant (A/E predominantly Black; B/C > 95% Asian; D heterogeneous). Genotypes B and C were independently associated with higher HBV DNA compared with genotype A. Overall, 10.7% of patients were HBeAg-positive, with genotype C showing the highest prevalence (23.7%) and an independent association with HBeAg positivity (aOR 8.3, 95% CI 2.0–34.9). Younger age and male sex were associated with higher HBV DNA and HBeAg positivity. Conclusions: In this immigration-rich Canadian cohort, HBV genotype distribution closely reflected global epidemiology and was strongly structured by country and region of birth. Baseline virological activity also differed by genotype and host factors, supporting integration of HBV genotype with sociodemographic context when characterizing chronic HBV in diverse migrant-receiving populations. Full article

Although expression-based omics has greatly contributed to biological research, the biochemical state of cells or tissues cannot be fully explained by transcript or gene expression data alone. This systematic review investigated when matrix-assisted laser desorption/ionisation (MALDI)-based approaches can support the integration of multiple molecular layers and when they remain limited to single-class molecular mapping. PubMed was searched between 1 February and 8 June 2026. English-language peer-reviewed publications relevant to the principles, methods, molecular classes, or biomedical applications of matrix-assisted laser desorption/ionisation-based multiomics were eligible. Publications outside this scope were excluded. Records were independently screened by two reviewers, and disagreements were resolved through discussion. The findings were narratively synthesised based on the analytical platform, molecular layer, integrated spatial multiomics, spatial application, and biomedical use. The methodological quality and risk of bias were not formally assessed, which limits the certainty and strength of the conclusions drawn from this narrative synthesis. Following the reapplication of the relevance criteria, 111 publications from 1633 identified records were included in the final review. The evidence was reclassified and presented separately as true multilayer MALDI studies, MALDI integrated with orthogonal modalities, and background uniomics or spatial molecular profiling studies. These publications included human, animal, cellular, tissue-based, and methodological studies. These publications cover many molecular classes and biomedical applications. As many publications did not involve human participants, a single pooled participant total was not applicable to this study. Matrix-assisted laser desorption/ionisation-based techniques were used to analyse metabolites, lipids, glycans, peptides, and intact proteins in the reviewed literature. The literature also shows that spatial information can be retained using matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI-IMS). Its ability to map molecular signals back to specific tissue regions or areas associated with disease supports its potential clinical utility. Specific areas of application, such as cancer, neurological, and infectious disease research, are also reviewed. The use of matrix-assisted laser desorption/ionisation-based techniques for biomarker discovery has been evaluated. Small sample sizes, proof-of-concept designs, inconsistent outcome reporting, and limited external validation have limited the evidence. Technical limitations include ion suppression, limited quantification, sample preparation variability, and differing analyte sensitivity. Emerging developments, such as single-cell imaging and AI analysis, have also been explored. Matrix-assisted laser desorption/ionisation enables multiomics when two or more complementary molecular layers are analysed and integrated within the same biological system. When only a single molecular class is analysed, the approach remains spatial molecular mapping rather than multiomic analysis. However, before matrix-assisted laser desorption/ionisation-based approaches can be applied in routine clinical practice, standardised workflows and better quantitative methods are needed. This review received no external funding and was not registered. Full article

Personal health management and clinical health systems are increasingly being transformed by data-driven smart technologies that enable remote monitoring, predictive analytics, and digitally mediated care. Wearable technologies contribute to this transformation by continuously generating wearable health data (WHD), but integrating such data into routine and clinical health management raises governance requirements beyond those for traditional health data. This study examines perceptions of WHD governance among wearable users and health professionals in South Africa. A mixed-methods approach was adopted, with quantitative and qualitative data collected through questionnaires and interviews. The findings show that wearable users are generally confident in WHD governance regarding access, reliability, trust, accuracy, and sharing. Privacy and third-party data practices raised comparatively less concern, though with less certainty, while perceptions of security and the adequacy of current South African laws were less definite and marked more by uncertainty. Health professionals viewed WHD governance more cautiously, emphasising regulatory adequacy, data quality, security, accountability, and the conditions required for meaningful use of WHD in health management. The study concludes that effective WHD governance requires more than formal regulation and must also support intelligibility, credibility, quality assurance, and practical oversight to support the responsible integration of WHD into health management. Full article

In South Africa, the culture and creative industry still faces structural constraints and rapid technological change. While digital infrastructure has opened new paths for creative production, distribution, and commercialisation, the extent to which digital connectivity and innovation translate into tangible, measurable performance in the creative economy remains a question. In this paper, the study investigates the short- and long-run relationships among technological innovation, telecommunications infrastructure, digital services intensity, and the performance of South Africa’s creative economy over the period 1999–2023 using an Autoregressive Distributed Lag (ARDL) model. The study uses patent applications as an indicator of formal innovation, as well as of fixed telecommunications infrastructure, digital services exports, and overall economic activity. The negative and marginally significant long-run association of digital services exports is also observed, while overall GDP is insignificant. The error-correction mechanism is negative and statistically significant, although its small magnitude suggests a slow recovery toward the long-run equilibrium. The study’s results show that the development of the creative economy is not only about increasing overall digital connectivity but also about innovation capacity and technological infrastructure within the creative innovation ecosystem. The study further observes that technological access alone is insufficient to achieve sector-level benefits and that it must be accompanied by stronger innovation support, commercialisation capabilities, and institutional support for creative companies. From a policy perspective, the findings call for greater attention to intellectual property development, innovation capabilities, digital production capacity, and infrastructure to help creative companies translate their technology into business. The study provides time-series evidence on the link between technological innovation, digital infrastructure, and creative economy performance in an African emerging-market context, and it offers policy-relevant insights for developing innovation-led creative sector development in South Africa amid uneven digital and economic development. Full article