26800 research outputs found
Sort by
Challenges and Future Prospects in the Development of Biomimetic Materials for Tissue Engineering and Regenerative Medicine
No full textBiomimetic materials, crafted to replicate natural biological systems, have transformed tissue engineering and regenerative medicine by providing promising solutions for repairing and regenerating damaged tissues. This mini-review addresses the primary challenges encountered in the development of these materials and outlines potential future directions to overcome these obstacles. Key aspects of focus include the materials’ biocompatibility, scalability, functionalization, and integration with biological systems. By examining recent advancements and identifying research gaps, this review seeks to guide future innovations in biomimetic materials to achieve improved therapeutic outcomes
Advancing Health Literacy Through Generative AI: The Utilization of Open-Source LLMs for Text Simplification and Readability
No full textAs health-related digital platforms and their accessibility continue to expand for users, it is crucial to ensure accessible and comprehensible online information for audiences with limited literacy levels. This research focuses on the evaluation of large language models (LLMs) like ChatGPT and Llama-2 for text simplification tasks, specifically within the healthcare domain. We assessed these models using the Flesch-Kincaid Grade scale to determine their effectiveness in generating simplified responses. The results displayed a significant gap in providing adequate text simplification responses to users, leading us to develop an improved LLM model. Our approach involved instruction and fine-tuning an open-source LLM (Llama-2-7B) with a custom dataset containing the correct Flesch-Kincaid grade scale formula. A calculator function was implemented to guide our developed merged-model in generating responses appropriate to the user’s true reading grade level. Key findings indicate that the fine-tuned model consistently produced responses at or below the user’s reading grade level, significantly enhancing readability and accessibility of information, including the subject of health. This study contributes to the refinement of text simplification methodologies, aiming to improve health literacy and patient outcomes
Photocurable and 3D Printable Functional Polyesters to Engineer Elastomeric Scaffolds for Biomedical Applications
No full textPhotocurable functional block copolyesters are reported to engineer elastomeric scaffolds for biomedical applications. The polymer backbone is organized by soft and stiff blocks. The functional prepolymer is readily crosslinked by thiol-yne click chemistry under ulraviolet light in the presence of a photo-initiator to form a robust elastomer. The elastomers bear both chemical crosslinks and crystal-domain crosslinks to simultaneously tune the materials\u27 properties, such as mechanical properties and degradation rates. The dual crosslinks can more efficiently tune the mechanical properties compared to the chemical crosslink alone. More importantly, the functional prepolymer is photo-printable to construct elastomeric scaffolds with precise control of pore sizes using the state-of-the-art digital light processing technique. With hydroxyls pendant on the backbone, human umbilical vein endothelial cells prefer to grow on the elastomer surface compared to that of a poly(caprolactone) film. It is believed that these functional photo-polyesters will be useful to construct medical devices for bioengineering research
Data supporting the paper Enhancing turbulent mixing and microphysical uniformity in a tall convection-cloud chamber through idealized heterogeneity of boundaries
No full textA large convection cloud chamber has been proposed for exploring aerosol–cloud–drizzle interactions under well-controlled turbulent conditions. Recent theoretical and numerical studies suggest that a convection cloud chamber with two heated and two cooled sidewalls can significantly enhance the liquid water content and thus benefit drizzle initiation. However, a chamber with such a sidewall configuration develops stable stratification and extremely weak turbulence therein. In this study, we conduct large-eddy simulations of a tall convection chamber with five different sidewall configurations consisting of alternating warm and cold patches. For each configuration, the total surface area of warm patches equals that of cold patches, resulting in the same expected cloud-free supersaturation based on a flux budget model. Results show that changing the sidewall configuration, while keeping all other factors constant, can substantially enhance turbulent mixing and improve the uniformity of thermodynamic and cloud microphysical properties in the bulk region of the chamber. In addition, turbulence strength is positively correlated with liquid water content and negatively correlated with cloud droplet number concentration, consistent with theoretical predictions. Our results highlight the advantage of building a large cloud chamber using modular patches with individually controllable temperature and humidity to achieve well-mixed conditions
Data-augmented explainable AI for pavement roughness prediction
No full textEffective pavement management systems rely on accurate predictions of pavement conditions to guide strategic decisions about maintenance and rehabilitation projects. Although recent studies have explored various artificial intelligence-based methods for predicting pavement roughness, notable gaps remain in the literature. Existing studies often use homogeneous data from similar climates and pavement types and overlook imbalances in historical pavement condition data. They also treat machine learning models as black boxes, relying on static feature rankings that miss complex relationships between inputs and predictions. This paper bridges these gaps by applying an explainable AI framework, enhanced with data augmentation, to a diverse and comprehensive dataset of pavement conditions. The proposed approach enhanced performance across a comprehensive set of metrics, reducing RMSE by 28.28 %, RSR by 36.92 %, and WMAP by 33.74 %, while increasing R-squared by 7.28 % and VAF by 6.61 %. Explainable AI analysis provided practical insights, enhancing model applicability and supporting informed maintenance decisions
Commercial Fishing Influences the Life Histories of Fish in the World\u27s Largest Desert Lake
No full textLake Turkana, the world\u27s largest permanent desert lake, is an important source of fish for both local consumption and international trade. The growth of Lake Turkana\u27s commercial fishery has increased the risk of overexploiting the lake\u27s fish stocks. Selection pressure from overexploitation of fish stocks often drives shifts in fish life-history traits, including mean length (Lmean), maximum length (Lmax) and size at maturity (Lmat). To assess the life-history indicators of overexploitation in Lake Turkana, we compared the life-history traits of six of Lake Turkana\u27s major commercial fish species from three time periods (1930-1953, 1972-1975, 2010-2022) that represent distinct levels of fishing pressure. These focal species were the African butter catfish Schilbe uranoscopus Rüppell 1832, the elongate tigerfish Hydrocynus forskahlii (Cuvier 1819), Nile perch Lates niloticus (L. 1758), Nile tilapia Oreochromis niloticus (L. 1758), silversides Alestes baremose (Joannis 1835) and wahrindi Synodontis schall (Bloch and Schneider 1801). Heavily exploited species exhibited notable decreases in Lmat as fishing pressure increased, and include A. baremose (29.7% decrease), H. forskahlii (16.4% decrease), L. niloticus (56.1% decrease) and O. niloticus (45.3% decrease). In contrast, lightly exploited species, including S. uranoscopus and S. schall, did not exhibit large declines in life-history traits. Additionally, we used current catch length frequency data for L. niloticus to infer that L. niloticus are currently experiencing overfishing and exhibit signs of the depletion of large \u27mega-spawners\u27. These results suggest that heavy commercial fishing likely drives the observed life-history responses. We suggest that the management of sustainable fisheries in Lake Turkana should focus on gear size restrictions as well as on reducing fishing effort on commercial-sized fish to decrease the probability of overfishing and potential declines of stocks
Accumulation of Nitrogen Species from Industrial Wastewater by Vetiver Grass (Chrysopogon zizanioides)
Full text linkIndustrial munition facilities are increasingly manufacturing insensitive high explosives (IHEs) to improve safety. The explosive residues in wastewater from these facilities are treated to meet regulatory standards. However, the resulting effluent contains elevated levels of mineralized nitrogen species. This study evaluated the potential of vetiver grass (Chrysopogon zizanioides), a non-invasive perennial species, to remove high concentrations of nitrate, nitrite, and ammonium from munition plant wastewater. Vetiver was grown hydroponically in synthetic wastewater containing high levels of nitrogen compounds simulating munitions plant effluents. Vetiver plants were treated with one nitrogen species at a time, with concentrations ranging from 165 to 24,700 mg N/L of nitrate, 100 to 4000 mg N/L of nitrite, and 260 to 39,000 mg N/L of ammonium. Nitrogen concentrations in the media and plant responses were monitored over time. The results showed significant nitrogen removal at lower concentration ranges. When concentrations exceeded 3800 mg N/L of nitrate, 800 mg N/L of nitrite, and 2600 mg N/L of ammonium, the removal rates declined after 7 days. At higher nitrogen levels, vetiver exhibited stress symptoms such as chlorosis and elevated antioxidant enzyme activity. Our study demonstrates the potential of vetiver grass in treating nitrogen-rich wastewater from the munition industry and provides a baseline for future large-scale studies to optimize the technology
Explicit Ehrenpreis–Palamodov–Fokas Representations for the Sobolev–Barenblatt Model and the Rubinshtein–Aifantis System on Semi-Strips and Quarter-Planes
No full textAbstract: Explicit integral representations consistent with the fundamentalEhrenpreis–Palamodov principle are herein constructed for thenovel solution formulae, recently obtained in closed form viarigorous implementation of the Fokas unified transform method, forthe Sobolev–Barenblatt pseudo-parabolic model of seepage inporous media and for the Rubinshtein–Aifantis double-diffusionsystem formulated on semi-bounded domains
Surface properties of oak wood (Quercus castaneifolia) coated with polyester reinforced with ceramic nanoparticles using a plasma deposition technique
No full textThe surface performance and weathering resistance of wood products often depend on the applied coating and reinforcing additives. In this paper, polyester film with the contribution of ceramic nanoparticles (contains zinc oxide, ZnO) was deposited on the oak wood (Quercus castaneifolia) surfaces via atmospheric pressure plasma jet (APPJ) technology. The polyester coating applied with an applicator and uncoated wood samples served as controls. The surface properties such as surface roughness, contact angle, wear index, wear depth and hardness values of the samples were analyzed before and after 720-h exposure to the artificial accelerated weathering test. The results demonstrated that the surface properties of oak samples were considerably improved after coating, and superior performances were observed in the plasma-deposited coating layer, particularly the ones reinforced with ceramic nanoparticles. This indicates a potential for using the plasma deposition method for coating and enhancing the surface properties of wood
Stockmayer fluid simulations for viscosity and glass transition temperature of ionic liquids
No full textWe develop a Stockmayer fluid model for molecular dynamics simulations of ionic liquids that captures molecular polarization, ionic conductivity, viscosity, and glass transition temperature, using ethylammonium nitrate (EAN) as an example. The ions in EAN are treated as spheres interacting via the Lennard-Jones potential with an embedded point charge and a permanent dipole moment. We show that our simulation results for EAN are consistent with experimental data and then explore the effects of the molecular parameters on the viscosity of ionic liquids. Our results indicate that viscosity monotonically increases with ionic charge and dipole moment but non-monotonically changes with ionic diameter (or molar volume). This non-monotonic trend arises from the competition among the electrostatic interactions, molecular packing, and size asymmetry between the cation and anion. Our model also shows that long-lived ion pairs result in higher viscosities