Search Results (10,306)

Polycyclic aromatic hydrocarbons (PAHs) are toxic air pollutants mainly released through vehicular emissions and can accumulate on edible plants, posing health risks to humans. This study aimed to isolate and identify endophytic fungi from Allium ampeloprasum and Brassica oleracea var. capitata, which are widely cultivated along roadside areas in the upcountry region of Sri Lanka. Sampling sites included Nuwara Eliya town, Nanu Oya, St. Clair’s, and Meepilimana (control), where above-ground parts of the selected vegetables were collected in six replicates. Fungal isolates were obtained through surface sterilization, and their ability to degrade PAHs (naphthalene, phenanthrene, anthracene, and pyrene) was evaluated using plate assays, spectrophotometric analysis, and high-performance liquid chromatography (HPLC). Phyllosphere PAH concentrations were also measured using HPLC. It revealed significantly higher concentrations of all four PAHs in the phyllosphere of both vegetables at polluted sites, with the highest levels recorded in A. ampeloprasum from Nuwara Eliya town: naphthalene (145.92 ng/g), phenanthrene (97.67 ng/g), anthracene (88.71 ng/g), and pyrene (63.82 ng/g). Most endophytic fungal strains isolated from both vegetables were able to grow on Bacto Bushnell–Haas (BBH) medium supplemented with PAHs, producing colonies exceeding 20 mm in diameter. Spectrophotometric analysis showed that Fusarium liriodendri SP2 (PV400499.1) and Trichoderma atroviride SP1 (PV400486.1) achieved approximately 75% degradation of selected PAHs. Furthermore, HPLC analysis confirmed that these isolates effectively degraded all tested PAHs, with degradation rates of approximately 70%. F. liriodendri was the most efficient degrader, achieving degradation rates of 68.50 ± 2.34% for naphthalene, 65.26 ± 1.21% for phenanthrene, 69.21 ± 1.45% for pyrene, and 66.89 ± 1.98% for anthracene. The PAH degradation byproducts of the selected fungal isolates were non-toxic to Artemia salina, confirming their environmental safety. These results highlight the bioremediation potential of endophytic fungi isolated from A. ampeloprasum and B. oleracea var. capitata in PAH-contaminated environments. Full article

Task scheduling in cloud computing environments is a complex NP-hard problem that requires maximizing resource utilization while satisfying quality-of-service (QoS) constraints. Traditional meta-heuristic algorithms often become stuck in local optima, while single deep reinforcement learning (DRL) models exhibit instability when exploring large-scale solution spaces. To address this, this paper proposes a hybrid scheduling algorithm based on multi-objective sand cat colony optimization (MoSCO). This algorithm utilizes a D3QN network to extract task features and guide population initialization, followed by a multi-objective Sand Cat Swarm Optimization (SCSO) algorithm for refined local search. Results from 50 independent replicate experiments conducted in a simulated cloud environment, coupled with an analysis of the dynamic convergence process, demonstrate that MoSCO exhibits significant superiority and robustness. Scatter plot convergence analysis further confirms that MoSCO’s knowledge injection mechanism effectively overcomes the blind exploration phase of traditional algorithms and successfully breaks through the local optimum bottleneck in the late iteration stages of single reinforcement learning, achieving higher-quality, denser, and more stable convergence. Furthermore, 3D and 2D Pareto front analyses show that MoSCO generates highly competitive, well-distributed non-dominated solutions, offering flexible trade-off options for conflicting objectives. Compared to PureD3QN, H-SCSO, and NSGA-II, MoSCO exhibits the smallest performance fluctuations in box plots. Specifically, MoSCO elevates the average resource utilization of clusters to 92.20%, while reducing the average maximum Makespan and Tardiness to 528 and 4187, respectively. Experimental data confirm that MoSCO effectively balances global exploration with local exploitation, delivering stable, high-quality solutions for dynamic cloud task scheduling. Full article

This study examines how UNHCR’s administrative category of the “person of concern” functions as a governance mechanism in refugee education policy, stripping refugees of political agency and positioning them as subjects of institutional control rather than rights-bearing actors. Employing Fairclough’s three-dimensional Critical Discourse Analysis alongside Quijano’s coloniality of power, the paper analyzes five key policy documents: four UNHCR education strategies spanning 2010 to 2020 and the World Bank’s INSPIRE Guide to Refugee Inclusion in National Education Systems (2025). The analysis identifies four dominant discursive themes: education as a mechanism of control, dehumanization and the passive subject, the neoliberalization of refugee education, and colonial legacies in knowledge production. The INSPIRE Guide is examined as a paradigmatic text crystallizing the shift from humanitarian parallel systems to developmental inclusion, revealing how the language of inclusion, efficiency, and sustainability reconfigures refugee education as economic governance while leaving the “person of concern” category uninterrogated. The study argues that UNHCR education policies reproduce colonial governance patterns in which education actively produces particular refugee subjects who can be governed, surveilled, and integrated into host-state frameworks on institutional terms. Findings challenge the assumed neutrality of humanitarian education frameworks and call for decolonial approaches centering refugee agency, epistemic sovereignty, and self-determined educational futures. Full article

The effective control of foodborne salmonellosis relies on the rapid and reliable detection and identification of the pathogen. Reliable detection tools for identifying the most common Salmonella serovars should translate to a considerable alleviation of the health burden attributed to Salmonella. We have developed a PCR assay for the rapid identification of colonies of Salmonella enterica serovar Thompson, a common serovar. Genomic analyses of publicly available sequences of Salmonella Thompson revealed the presence of a unique, Thompson-specific fragment, which we have used to design a pair of oligonucleotides, STho-F and STho-R, for the PCR amplification of an 808 bp DNA fragment. Using crude DNA extracts, the 808 bp fragment was detected in 77 out of 78 isolates of S. Thompson (sensitivity = 98.7% n = 78 isolates) but not in any of the non-Salmonella organisms tested (n = 100; 100% specificity) nor in non-Thompson Salmonella serovars (n = 100; 100% specificity). The sensitivity (inclusivity) and specificity (exclusivity) indices of the PCR assay for S. Thompson met the standard regulatory requirements. The Thompson primer pair was compatible with other primers pairs in a multiplex PCR designed for three other common Salmonella serovars. Colonies belonging to the Enteritidis serovar (n = 100), Heidelberg serovar (n = 100), Typhimurium serovar (n = 100), and Thompson serovar (n = 77) were correctly designated, indicating excellent inclusivity and exclusivity scores for all four Salmonella serovars tested in a single multiplex PCR. Full article

Outbreaks of crown-of-thorns sea stars (CoTS) threaten coral reef integrity and biodiversity, yet local dynamics and short-term responses to control remain insufficiently described. This study characterised an outbreaking Acanthaster population in two specific sites of the coast of Khor Fakkan (Gulf of Oman, United Arab Emirates) to resolve species identity, population composition, prey selection and the effects of targeted removals. All sequenced individuals clustered in two related haplotypes belonging to the species Acanthaster planci. Benthic surveys showed moderate live-coral cover, dominated by massive Porites sp. colonies. Moreover, the observations of 139 preyed colonies revealed pronounced genus-level selectivity, with branching and complex morphologies suffering disproportionately and massive forms largely avoided. However, the selection of massive Plesiastrea and Favites genera as preferred coral prey might suggest a shift towards less preferred coral in the CoTS diet, posing a severe threat to coral reefs’ integrity. Intensive removal reduced the local density, up to 86%, and provided substantial short-term relief, but continued monitoring is required to secure long-term reef resilience. Full article

Watermelon juice is a nutritious yet highly perishable beverage. Conventional thermal pasteurization ensures safety but degrades heat-sensitive nutrients, color, and flavor. Induced electric field (IEF) is an emerging technology that inactivates microorganisms while better preserving quality. However, its effects on the comprehensive quality retention of watermelon juice during storage remain underexplored. This study investigated the efficacy of IEF treatment on the microbial inactivation and quality preservation of watermelon juice during 25 days of storage at 4 °C. Freshly extracted watermelon juice was subjected to low-temperature IEF at 65 °C (IEF1) for 101 s and 60 °C (IEF2) for 88 s, with conventional pasteurization (65 °C, 30 min) as a control. The results showed that no colonies were detected in the IEF2 group throughout the 25-day storage period. Both IEF treatment and pasteurization effectively inhibited juice acidification. Soluble solids content and electrical conductivity remained stable under refrigeration, and the IEF group showed slower and more controllable acidity on day 25. Notably, the IEF1 group retained the highest lycopene content at the end of storage, while the IEF2 group maintained the highest total phenolic content (TPC). Furthermore, IEF treatment effectively mitigated color deterioration and preserved carbohydrate stability during refrigeration. Flavor analysis revealed that the taste profile of the IEF2 group at the initial storage stage closely resembled that of fresh watermelon juice. Over the 25-day period, the relative content of key volatile compounds characteristic of fresh watermelon decreased by only 3.64% in the IEF2 group. Full article

In precision apiculture, the portable digital camera is a cost-effective sensor for capturing hive images or videos used to quantify different colony variables. Openly accessible, well-annotated, interoperable cell-level image datasets are still the exception rather than the norm. This shortage constitutes a major barrier to AI-driven approaches aimed at automating image-based comb analysis. In this article, we present FAIRHiveFrames-1K, a publicly available dataset of 1265 annotated hive frame images (1920 × 1080 PNG) designed to facilitate research in AI-intensive image-based comb analysis automation. The dataset, derived from a 2013-2022 U.S. Department of Agriculture–Agricultural Research Service multi-sensor research reservoir, includes 124,669 annotated regions of interest for seven biologically meaningful categories consistent with comb analysis literature and standard hive inspection protocols. FAIRHiveFrames-1K is curated according to FAIR principles (Findable, Accessible, Interoperable, Reusable) and distributed under CC-BY 4.0 with standard annotation formats, fixed training and validation splits, and reproducible benchmarking artifacts. To establish preliminary baseline performance, we iteratively tuned four YOLO architectures (YOLOv8n, YOLOv8s, YOLOv11n, YOLOv11s) under a shared tuning protocol over the period of dataset growth. Full article

Background/Objectives: High-grade serous ovarian cancer (HGSOC) is usually discovered in advanced stages and often relapses shortly after initial conventional therapy. Survival in HGSOC patients might be improved with the use of novel immune therapies, which potentiate autologous anti-tumor responses. Dendritic cells (DCs) are potent antigen-presenting cells that can initiate immune responses, activate cytotoxic T cells and drive T-cell differentiation. This pilot trial evaluated the safety and efficacy of a unique DC vaccine (α-DC-1) in relapsed, advanced HGSOC patients with minimal tumor burden. Methods: Monocytes from patient leukaphereses were used to propagate a unique autologous DC, the α-DC-1, generated with granulocyte–macrophage colony-stimulating factor and interleukin-4, pulsed with keyhole limpet hemocyanin (KLH) and tumor lysate (from debulking surgery) on day 5, and matured with a cocktail of cytokines and chemokines on day 6. Mature α-DC-1 were harvested on day 7 and administered intranodally (inguinal nodes) every other week for three doses/cycle for up to three DC vaccine cycles (nine vaccines). The primary endpoints were progression-free survival (PFS) and overall survival (OS). Results: In 19 patients treated, the median PFS was 9.7 months (95% CI: (5, NA)) and the median OS was 42.2 months (95% CI: (31.2, 68.3)). In 5/19 (26.3%) patients, OS exceeded five years. Administration of six or more vaccines was associated with a significant improvement in PFS. No grade 2 or higher toxicities were noted. Conclusions: Our α-DC-1 vaccine was safe, and 94.2% elicited an immune response to KLH. The long OS, exceeding 5 years in some patients, suggests this DC vaccine may improve survival for some with relapsed HGSOC. Full article

For over a decade, non-integrating Sendai virus vectors have been the gold standard for induced pluripotent stem cell (iPSC) reprogramming. However, as the field shifts toward regenerative and precision medicine and large-scale biorepositories, Sendai virus workflow necessitates dedicated viral-clearance testing, specialized manufacturing controls, and heightened regulatory oversight, leading to increased cost. While mRNA-based reprogramming offers a non-viral alternative, traditional mRNA delivery methods like electroporation are often physiologically disruptive. This study evaluates an mRNA-reprogramming platform that delivers lipid nanoparticles (mRNA-LNPs) via receptor-mediated endocytosis. By utilizing both Sendai virus and mRNA-LNP approaches to reprogram PBMCs from the same donor, we established a genetically identical starting point. Results demonstrate that mRNA-LNP-reprogrammed iPSCs maintain genomic integrity, retain the donor KCNH2 c.2398+5G>T variant, and exhibit characteristic colony morphology, pluripotency markers, and trilineage differentiation capacity consistent with the Sendai-reprogrammed counterparts. The mRNA-LNP-reprogrammed iPSCs differentiate into iPSC-derived cardiomyocytes presenting sarcomeric structures and electrophysiological activity, recapitulating a disease-specific phenotype. Notably, the mRNA-LNP workflow reached these milestones in significantly fewer passages than the Sendai virus workflow, markedly shortening timelines and reducing costs. These findings highlight mRNA-LNP reprogramming as a potentially attractive and effective, virus-independent platform to support future regenerative and precision medicine initiatives and scalable biobanking. Full article

Accurate identification of cariogenic bacteria is crucial for understanding caries development in children. Classical culture methods often underestimate microbial diversity, while polymerase chain reaction (PCR) can detect species that are difficult to cultivate. The aim of this study was to compare culture-based and PCR-based methods for detecting key cariogenic microorganisms in the carious dentin of pediatric patients. Thirty dentin samples were collected from the permanent teeth of children aged 8–14 years. Parallel analyses were performed using standard culture techniques and PCR targeting the gtfB gene of S. mutans and the 16S rRNA gene of Lactobacillus spp. Culture results were quantified as colony-forming units, while PCR results were classified as negative, low-positive, or positive. The results show that culture-based methods identified S. mutans in 16.7% of the samples and Lactobacillus spp. in 3.3%, while PCR identified a signal for S. mutans in 43.3% and Lactobacillus spp. in 100% of the samples. PCR-based methods provide higher sensitivity for detecting key cariogenic bacteria, including S. mutans and Lactobacillus spp. However, PCR detects bacterial DNA and does not indicate bacterial viability or activity. Combining molecular and culture-based approaches allows a more comprehensive assessment of the cariogenic microbiota, supporting accurate microbiological evaluation in pediatric caries research. Full article

This paper reconstructs the archive of Islamic humanism as a cultural resource for Critical Psychologists, addressing the geopolitical double-bind of the global Muslim population caught between Islamophobia and fundamentalism. This living archive spans intellectual contributions to falsafa (rationalism) and tasawwuf (mysticism), from medieval thinkers like Ibn Rushd and al-Ghazali to modern figures like Mourad Wahba and Ali Shariʿati. While primarily philosophical, these contributions offer practical implications for psychosocial liberation. Utilizing a methodology of deconstructive unsilencing, the archive is positioned as both pluriversal and metaphorical. By analyzing the ideological mechanism of virtual internment, the paper proposes a praxis of learned ignorance and decolonial resistance to subvert the panoptic look of anti-humanism through the Real Gaze of Islamic humanism. This retrieval offers a materialist praxis seeking to overturn the (post)colonial triad of fundamentalism, parasitic capitalism, and postmodernism. In sum, the article argues that a genealogical consignation of Islamic humanism facilitates a transmodernity that integrates Totality with Exteriority, effectively negating both coloniality and antimodernity. Full article

Background: Lung cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due to late diagnosis. Although machine learning (ML) techniques have been widely applied for lung cancer classification, many studies lack a fully optimized end-to-end pipeline using routine clinical data. This study proposes an optimized ML framework that integrates demographic, lifestyle, and clinical features with systematic hyperparameter tuning to improve classification performance. Methods: A dataset of 309 patient records containing demographic, lifestyle, and clinical attributes was used. The data were preprocessed and split into training and testing sets in an 80:20 ratio. Feature selection was performed using metaheuristic algorithms, including Red Deer Optimization, Binary Grasshopper Optimization, Gray Wolf Optimization, and Bee Colony Optimization. Six ML classifiers—Logistic Regression, Support Vector Classifier, Gradient Boosting, Random Forest, K-Nearest Neighbors, and Gaussian Naive Bayes—were trained with optimized hyperparameters. Model performance was evaluated using accuracy, precision, recall, F1-score, and ROC–AUC. Results: The optimized pipeline significantly improved classification performance. Logistic Regression achieved the highest accuracy of 91.07% with an AUC of 0.91, outperforming more complex ensemble models. Gradient Boosting and Random Forest both achieved an accuracy of 87.5%, while other classifiers demonstrated moderate performance. Conclusions: The proposed optimized ML pipeline enhances lung cancer classification accuracy using routine clinical data. The results highlight that simpler, well-optimized models can outperform complex approaches on structured datasets. This framework shows strong potential for early lung cancer risk screening and clinical decision support, although further validation on larger datasets is recommended. Full article

Due to their characteristics of a high power-to-weight ratio, stringent lightweight requirements, and harsh working environments, straight face gears are prone to issues such as tooth fracture and inadequate fatigue strength. Meanwhile, because of the lack of fatigue information and weak fatigue life prediction method, the fatigue life of face gears cannot be effectively evaluated. In this study, the key technologies involved in the hot rolling forming process, fatigue experiments, and numerical modeling of straight face gears are studied. A technical foundation for straight face gears formed by hot rolling processing is established, and a fatigue experiment of the hot rolling forming of straight face gears is carried out. Due to the lack of information on fatigue experiments, a numerical prediction model is constructed. Sample expansion is carried out using a BP neural network–Bootstrap model to calculate the reliable lifespan of hot-rolled straight face gears, and fatigue life prediction for hot-rolled straight face gears is completed via the improved GM(1,1,λ) model based on the artificial bee colony algorithm, and thus the accurate evaluation of the fatigue life of rolling forming face gears is realized. The feasibility and superiority of the improved fatigue life prediction model are demonstrated by comparing it with the traditional prediction model and experimental results. The theoretical basis and technical support for the research of the fatigue resistance and installation application of face gears are provided. Full article

Achnanthidium catenatum exhibits both epiphytic and planktonic ecological types and forms multiple large-scale diatom blooms in different drinking water reservoirs. This study determined its growth and physiological characteristics under different nitrogen (N) or phosphorus (P) conditions. The study found that N ≤ 2.5 mg/L promoted its growth, while the promoting effect weakened at ≥5 mg/L. The lag phase of the growth cycle was shorter, taking only 6 days to reach peak density; meanwhile, it showed strong adaptability to P (0.5–3.5 mg/L), with peak density occurring by approximately 12 days. It was found that N-induced blooms formed earlier and lasted longer, whereas P-induced blooms were relatively delayed, more intense, and shorter in duration. Low and high concentrations of N, as well as P concentrations (≥0.1 mg/L), significantly promoted the formation of multicellular chain colonies (p < 0.05). The percentage of chain colonies was relatively higher during the lag phase and tended to exist as single cells during the stationary phase, at which time the colloidal extracellular polymeric substance (CEPS) content was higher and significantly correlated with changes in cell density. Alkaline phosphatase activity (APA) and malondialdehyde (MDA) content varied markedly under different N or P concentrations (p < 0.05). These results reveal the potential impact of N or P variations on the bloom-forming capacity of A. catenatum. Full article

To address the high labor intensity of weight handling and the low accuracy of testing outcomes in the 125% rated-load down-running braking test for high-speed elevators, this study proposes a numerical-model-driven evaluation method for elevator braking capability based on Dynamic Ant Colony Optimization–eXtreme Gradient Boosting (DACO-XGBoost). Firstly, to overcome the limited prediction accuracy caused by insufficient measured samples during braking analysis, vibration and noise effects are both considered, and thus an equivalent dynamic analysis is conducted for no-load up-running and 125% load down-running conditions. Based on this, a simulation-data generation approach was developed to produce loaded down-running braking samples from the no-load up-running operating condition. Secondly, by combining the simulated samples generated by the above model with a limited set of measured samples, an XGBoost model optimized by a dynamic ant colony algorithm was constructed, improving the model’s ability to fit the complex nonlinear relationships in the elevator braking process. This mitigates the constraints imposed by sample scarcity and enables accurate prediction of key braking-performance parameters. Experimental results demonstrate that the proposed DACO-XGBoost substantially improves prediction accuracy. For braking distance, it decreased from 7.5453 to 0.5661 (RMSE) and from 2.7452 to 0.0370 (MAE). For slip amount, it decreased from 60.0307 to 1.2200 (RMSE) and from 7.7401 to 0.8146 (MAE), respectively. Furthermore, after comparisons with RF, GA-RF, and PSO-RF, the effectiveness of the proposed method for quantitative evaluation of braking performance in high-speed elevators was verified. Full article