Search Results (29,707)

This study is the first to investigate the performance of ultraviolet germicidal irradiation (UVGI) in underfloor air distribution (UFAD) systems. A simplified mathematical model is developed to predict airborne pathogen transport and inactivation by upper room UVGI in UFAD spaces. The proposed model is substantiated for the SARS-CoV-2 virus as a simulated pathogen through a comprehensive computational fluid dynamics methodology validated against published experimental data of upper room UVGI and UFAD flows. Simulations show an 11% decrease in viral concentration within the upper irradiated zone when a 15 W louvered germicidal lamp is utilized. Finally, a case study on Mycobacterium tuberculosis (M. tuberculosis) bacteria is carried out using the validated simplified model to optimize the use of return air and UVGI implementation, ensuring acceptable indoor air quality and enhanced energy efficiency. Results reveal that the UFAD-UVGI system may consume up to 13.6% less energy while keeping the occupants at acceptable levels of M. tuberculosis concentration and UV irradiance when operated with 26% return air and a UVGI output of 72 W. Full article

Acute lymphoblastic leukemia (ALL) is a heterogeneous hematologic malignancy defined by the uncontrolled proliferation of lymphoid precursors. Accurate diagnosis and effective therapeutic strategies hinge on a comprehensive understanding of the genetic and molecular landscape of ALL. This review synthesizes the latest updates in cytogenetic and molecular classifications, emphasizing the 2022 World Health Organization (WHO) and International Consensus Classification (ICC) revisions. Key chromosomal alterations such as BCR::ABL1 and ETV6::RUNX1 and emerging subtypes including Ph-like ALL, DUX4, and MEF2D rearrangements are examined for their prognostic significance. Furthermore, we assess novel diagnostic tools, notably next-generation sequencing (NGS) and optical genome mapping (OGM). While NGS excels at identifying point mutations and small indels, OGM offers high-resolution structural variant detection with 100% sensitivity in multiple validation studies. These advancements enhance our grasp of leukemogenesis and pave the way for precision medicine in both B- and T-cell ALL. Ultimately, integrating these innovations into routine diagnostics is crucial for personalized patient management and improving clinical outcomes. Full article

Background/Objectives: This study examines how seasonality, pollution, and sample type (water and sediment) influence the presence and distribution of antibiotic resistance genes (ARGs), with a focus on antibiotic resistance genes (ARGs) located on plasmids (the complete set of plasmid-derived sequences, including ARGs) in a tropical urban river. Methods: Samples were collected from three sites along a pollution gradient in the Virilla River, Costa Rica, during three seasonal campaigns (wet 2021, dry 2022, and wet 2022). ARGs in water and sediment were quantified by qPCR, and metagenomic sequencing was applied to analyze chromosomal and plasmid-associated resistance profiles in sediments. Tobit and linear regression models, along with multivariate ordination, were used to assess spatial and seasonal trends. Results: During the wet season of 2021, the abundance of antibiotic resistance genes (ARGs) such as sul-1, intI-1, and tetA in water samples decreased significantly, likely due to dilution, while intI-1 and tetQ increased in sediments, suggesting particle-bound accumulation. In the wet season 2022, intI-1 remained low in water, qnrS increased, and sediments showed significant increases in tetQ, tetA, and qnrS, along with decreases in sul-1 and sul-2. Metagenomic analysis revealed spatial differences in plasmid-associated ARGs, with the highest abundance at the most polluted site (Site 3). Bacterial taxa also showed spatial differences, with greater plasmidome diversity and a higher representation of potential pathogens in the most contaminated site. Conclusions: Seasonality and pollution gradients jointly shape ARG dynamics in this tropical river. Plasmid-mediated resistance responds rapidly to environmental change and is enriched at polluted sites, while sediments serve as long-term reservoirs. These findings support the use of plasmid-based monitoring for antimicrobial resistance surveillance in aquatic systems. Full article

E-Learning is an emerging dominant phenomenon in education, making the development of robust models that can accurately represent the dynamic behavior of learners in MOOCs even more critical. In this article, we propose the Temporal Sparse Attention-Gated Recurrent Unit (TSA-GRU), a novel deep learning framework that combines TSA with a sequential encoder based on the GRU. This hybrid model effectively reconstructs student response times and learning trajectories with high fidelity by leveraging tthe emporal embeddings of instructional and feedback activities. By dynamically filtering noise from student interactions, TSA-GRU generates context-aware representations that seamlessly integrate both short-term fluctuations and long-term learning patterns. Empirical evaluation on the 2009–2010 ASSISTments dataset demonstrates that TSA-GRU achieved a test accuracy of 95.60% and a test loss of 0.0209, outperforming Modular Sparse Attention-Gated Recurrent Unit (MSA-GRU), Bayesian Knowledge Tracing (BKT), Performance Factors Analysis (PFA), and TSA in the same experimental design. TSA-GRU converged in five training epochs; thus, while TSA-GRU is demonstrated to have strong predictive performance for knowledge tracing tasks, these findings are specific to the conducted dataset and should not be implicitly regarded as conclusive for all data. More statistical validation through five-fold cross-validation, confidence intervals, and paired t-tests have confirmed the robustness, consistency, and statistically significant superiority of TSA-GRU over the baseline model MSA-GRU. TSA-GRU’s scalability and capacity to incorporate a temporal dimension of knowledge can make it acceptably well-positioned to analyze complex learner behaviors and plan interventions for adaptive learning in computerized learning systems. Full article

In this paper, we study the conformal symmetry for locally rotationally symmetric Bianchi type I space-time. New exact conformal solutions of Einstein’s field equations for this space-time were obtained. The space-time geometry of these solutions is found to be non-vacuum, conformally flat, and shear-free. We show that in order for LRS Bianchi type I space-time to admit a conformal vector field it must reduce to the FRW space-time. Some physical and kinematic properties of the obtained conformal solutions are also discussed. Full article

Geographical Indication labels are an increasingly popular alternative among producers and governments seeking to protect the products and producers of their countries. This trend has grown due to the opening of markets and consumers’ increasing desire to know the origin of the products they purchase. A bibliographic review was conducted, including studies on the feasibility of applying quality labels, the associated challenges, and examples. This review identifies the processes involved in obtaining Designation of Origin and presents a positive perspective on their application. It was concluded that obtaining a differentiated quality label can improve production and quality of life, provided that it is the result of an evaluation of the area’s context and the main actors in production chains. Full article

Understanding the factors that drive green buying intentions has become critical, as environmental issues continue to rise globally. The study investigates the influence of environmental commitment and green motivation on environmental identity and green purchasing intentions. Additionally, it assesses the mediating role of environmental identity in the relationships between environmental commitment, green motivation, and green purchasing intentions. Moreover, it examines the moderating effect of eco-conscious behaviour on the relationships between environmental commitment, green motivation, green identity, and green purchasing intentions. A total of 440 participants, who stayed in high-rate hotels in Sharm el-Sheikh, were asked to fill out the survey distributed. (PLS-SEM) was used to analyze data. The study outcomes confirmed that environmental commitment and green motivation significantly affect green identity and purchasing behavior. Besides, the results showed the essential mediator contribution of the environmental identity between environmental commitment and green motivation. In addition, it explains eco-conscious behavior as a moderator between the previously mentioned variables. The study contributes to the existing tourism literature by demonstrating the impact of green commitment and environmental motivation on making choices to buy eco-friendly products. Moreover, the results hold significant implications for researchers, policymakers, and tourism stakeholders. Full article

In remote alpaca breeding regions, access to advanced sperm analysis laboratories is limited. This study validates a practical cytometric method for evaluating sperm viability and acrosomal integrity in epididymal alpaca sperm using early fluorochrome staining, formaldehyde fixation, and intermediate storage. Thirty-two testes were transported at 5 °C, and spermatozoa were collected from the cauda epididymis. After morphometric screening, 26 samples were included. Aliquots were stained with Zombie Green (viability) and FITC–PSA (acrosomal integrity), at time zero. Each aliquot was divided for cytometric analysis at T0 (immediately), T24 (24 h after formaldehyde fixation) and T1w (1 week post-fixation). Fixed samples showed higher viability and acrosomal integrity values (T24: 70.75%, 97.24%; T1w: 71.80%, 97.21%) than T0 (67.63%, 95.89%). This may reflect fluorescence alterations associated with fixation. Strong correlations and Bland–Altman analysis confirmed consistency across time points. This method enables accurate sperm quality evaluation up to one week after collection, offering a useful tool for reproductive monitoring in field conditions without immediate analysis. Further research on ejaculated semen and field protocols is recommended. Full article

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

This study aims to characterize for the first time the insect assemblage associated with sown, introduced guayule (Parthenium argentatum A. Gray, Asteraceae) in Castilla-La Mancha, Spain, and identify potential relationships with the crop. Insect sampling was conducted using nets and pan traps during spring and early summer, coinciding with the flowering period of the plant. A total of 352 insect species/morphospecies across 12 orders were identified. Diptera, Coleoptera, Hemiptera, and Hymenoptera were the most species-rich and abundant orders. Within these orders, Muscidae, Syrphidae, Tenebrionidae, Dermestidae, Miridae, Halictidae, and Apidae were the most numerous families. Guayule flowering intensity increased gradually until mid-June, aligning with the peak activity of pollinating Diptera. The majority of the identified insects (74.4%) were potential pollinators, while nearly 50% were detritivores and approximately 30% were herbivorous. The similarity in insect families and functional roles observed in this study to previous studies in the USA and Mexico suggest that guayule may serve as a similar trophic resource for insects in Spain, despite being a non-native species. Full article

This paper proposes an intelligent power adaptation framework for Free-Space Optics (FSO) communication systems operating under different weather conditions exploiting a deep learning (DL) analysis of received eye diagram images. The system incorporates two Convolutional Neural Network (CNN) architectures, LeNet and Wide Residual Network (Wide ResNet) algorithms to perform regression tasks that predict received signal quality metrics such as the Quality Factor (Q-factor) and Bit Error Rate (BER) from the received eye diagram. These models are evaluated using Mean Squared Error (MSE) and the coefficient of determination (${\mathrm{R}}^2$ score) to assess prediction accuracy. Additionally, a custom CNN-based classifier is trained to determine whether the BER reading from the eye diagram exceeds a critical threshold of ${10}^{-4}$; this classifier achieves an overall accuracy of 99%, correctly detecting 194/195 “acceptable” and 4/5 “unacceptable” instances. Based on the predicted signal quality, the framework activates a dual-amplifier configuration comprising a pre-channel amplifier with a maximum gain of 25 dB and a post-channel amplifier with a maximum gain of 10 dB. The total gain of the amplifiers is adjusted to support the operation of the FSO system under all-weather conditions. The FSO system uses a 15 dBm laser source at 1550 nm. The DL models are tested on both internal and external datasets to validate their generalization capability. The results show that the regression models achieve strong predictive performance, and the classifier reliably detects degraded signal conditions, enabling the real-time gain control of the amplifiers to achieve the quality of transmission. The proposed solution supports robust FSO communication under challenging atmospheric conditions including dry snow, making it suitable for deployment in regions like Northern Europe, Canada, and Northern Japan. Full article

With the rapid pace of urbanization, cities are increasingly facing severe challenges related to environmental pollution, ecological degradation, and climate change. Extreme climate events—such as heatwaves, droughts, heavy rainfall, and wildfires—have intensified public concern about sustainability, environmental protection, and low-carbon development. Ensuring environmental preservation while maintaining residents’ quality of life has become a central focus of urban governance. In this context, evaluating green indicators and predicting urban greenness is both necessary and urgent. This study incorporates international frameworks such as the EU Green City Index, the European Green Capital Award, and the United Nations Sustainable Development Goals to assess urban sustainability. The Extreme Gradient Boosting (XGBoost) algorithm is employed to predict the green level of cities and to develop multiple optimized models. Comparative analysis with traditional models demonstrates that XGBoost achieves superior performance, with an accuracy of 0.84 and an F1-score of 0.81. Case study findings identify “Greenhouse Gas Emissions per Person” and “Per Capita Emissions from Transport” as the most critical indicators. These results provide practical guidance for policymakers, suggesting that targeted regulations based on these key factors can effectively support emission reduction and urban sustainability goals. Full article

This study investigates the influence of façade-design parameters on daylighting performance in hot arid climates, with a particular focus on Egypt. A total of nine façade configurations of a residential building were modeled and simulated using Autodesk Revit and Insight 360, varying three critical variables: glazing type (clear, blue, and dark), Window-to-Wall Ratio (WWR) of 15%, 50%, 75%, and indoor wall finish (light, moderate, dark) colors. These were compared to the Leadership in Energy and Environmental Design (LEED) daylighting quality thresholds. The results revealed that clear glazing paired with high WWR (75%) achieved the highest Spatial Daylight Autonomy (sDA), reaching up to 92% in living spaces. However, this also led to elevated Annual Sunlight Exposure (ASE), with peak values of 53%, exceeding the LEED discomfort threshold of 10%. Blue and dark glazing types successfully reduced ASE to as low as 0–13%, yet often resulted in underlit spaces, especially in private rooms such as bedrooms and bathrooms, with sDA values falling below 20%. A 50% WWR emerged as the optimal balance, providing consistent daylight distribution while maintaining ASE within acceptable limits (≤33%). Similarly, moderate color wall finishes delivered the most balanced lighting performance, enhancing sDA by up to 30% while controlling reflective glare. Statistical analysis using Pearson correlation revealed a strong positive relationship between sDA and ASE (r = 0.84) in highly glazed, clear glass scenarios. Sensitivity analysis further indicated that low WWR configurations of 15% were highly influenced by glazing and finishing types, leading to variability in daylight metrics reaching ±40%. The study concludes that moderate glazing (blue), medium WWR (50%), and moderate color indoor finishes provide the most robust daylighting performance across diverse room types. These findings support an evidence-based approach to façade design, promoting visual comfort, daylight quality, and sustainable building practices. Full article

The demand for functional beverages is increasing as consumers seek options that offer health benefits, and plant-based beverages are gaining popularity for their associated advantages. The objective of this study was to optimize the formulation of a chickpea and hibiscus beverage to maximize flavor sensory acceptance, antioxidant capacity, and anthocyanin content using a mixture design and characterize the optimal formulation. An extreme vertices mixture design was employed, with fixed proportions of chickpea beverage (66.5%) and inulin (2%), while varying the proportions of hibiscus decoction, monk fruit, and cinnamon powder. Additionally, the Kano model was used to classify the beverage’s attributes. The optimized formulation consisted of 31.41% hibiscus decoction, 0.48% monk fruit, and 0.61% cinnamon powder, achieving 329.2 µmol ET/100 mL (antioxidant capacity), 3.567 mg C3GE/100 mL (anthocyanin content), and a flavor rating of 6.2. The Kano model classified good taste, functional properties, monk fruit sweetening, and chickpeas as attractive attributes, with functional properties obtaining the highest satisfaction index (0.88). These results demonstrate that employing a mixture design is an effective tool to enhance health-related aspects and consumer acceptance. Additionally, the incorporation of the Kano model provides a broader perspective on the development of functional beverages by identifying key attributes that influence product acceptance and market success. Full article