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Molecular sieving and adsorption of uremic toxins by a dual-layer hollow fiber mixed matrix membrane (DLHF
No full textA large amount of purified water is used in conventional hemodialysis (HD) for treating end-stage kidney disease (ESKD). To minimize the water demand and waste generation, the regeneration of dialysate is considered to be the most efficient control strategy. In this study, an innovative dual-layer hollow fiber (DLHF) mixed matrix membrane (MMM) incorporated with amine-functionalized mesoporous silica nanoparticles (MPS-NPs) was developed to regenerate spent dialysate. The fabricated DLHF-MMM configuration enabled the continuous removal of small, medium, and large weight uremic toxins (UTs) through dual mechanisms. The inner layer composed of polyethersulfone (PES) and polyethylene glycol (PEG) rejected large molecular weight UTs (i.e., MW > 500 Da) via the molecular sieving. Meanwhile, the outer layer containing amine-functionalized MPS-NPs effectively removed small weight UTs such as urea, creatinine, and hippuric acid. The DLHF-MMM with 6 wt% of amine-functionalized MPS-NPs demonstrated the most favorable characteristics, i.e., high water permeability (298.6 ± 3.2 mL/m2.h. mmHg) and adsorption capacity of urea (523.5 mg/g), creatinine (28.1 mg/g), and hippuric acid (3.1 mg/g). Notably, the optimal membrane (DLHF-4) also achieved favorable removal rates from the actual patient’s spent dialysate, i.e., urea (74.4%), creatinine (56%), hippuric acid (16.1%), and lysozyme (58.7%, additionally spiked as a mimicking for β-2 microglobulin). These results indicate that the fabricated DLHF-MMM in this study can effectively overcome the challenges posed by the complex matrix components. Overall, the results of this study demonstrate that the DLHF- MMM incorporated with amine-functionalized MPS-NPs is a promising potential tool for the regeneration of dialysate. Furthermore, this approach could potentially contribute to water conservation and reduce the burden on wastewater treatment processes associated with conventional HD wastewater. Keywords: Water consumption, amine-functionalized mesoporous silica nanoparticles, hemodialysis, spent dialysate, uremic toxins, dual-layer hollow fiber membraneMaste
Assessment of Stem Cell Viability through Visual Analysis Coupled with Teachable Machine
No full textCell viability is an indispensable aspect of cells in the field of drug discovery, cell biology, and biomedical research to assess the physiological conditions of cells such as healthiness, functionality, survivability, etc. Recently, there have been several methods for determining the cell viability through either cell staining with trypan blue and acridine orange, propidium iodide, calcein-AM, etc., or colorimetric assays such as cell counting kit-8 assay. However, these methods have some limitations like time-consuming, expensive, unstable, individual variability, etc. Even present artificial intelligence software such as QuPath, ImageJ, etc., can only determine the cell viability after cell staining. Therefore, we attempted to determine whether cells are alive or not depending on the visual characteristics of an individual cell using Teachable Machine, a web-based artificial intelligence tool provided by Google. Labeling work to assign correct answers to learning data consumes a lot of time and human costs because it is usually done manually. To solve this problem, labeling was automated by recognizing and extracting only individual cells from the image using the contour function to increase time efficiency. In addition, many datasets were created to evaluate and compare the performances of models. Based on the results, the model that showed the best performance showed an accuracy of more than 80%. In conclusion, this model could minimize analysis time, expenses, individual variability, etc., enhancing the efficacy and reproducibility of biological experiments in the fields of drug discovery, drug development, and biological research.TRUEsciescopu
Eddy-Resolving Simulation Coupled with Stability Analysis for Turbulent Transition in Compressible Boundary Layer
No full textAn efficient and high-fidelity approach is proposed for laminar-to-turbulent transition in compressible boundary layer flows. The proposed method combines eddy-resolving simulations, such as direct-numerical simulation (DNS) and large-eddy simulation (LES), with stability analysis. The combined approach provides (1) high fidelity for simulating transitional flow and (2) cost efficiency for capturing major instabilities in the pre-turbulent region. Coupling between stability analysis and eddy-resolving simulation is pursued via unsteady inlet condition for eddy-resolving simulation; instability modes from stability analysis are introduced at the inlet with the undisturbed laminar solution. The feasibility of the coupled framework is assessed for turbulent transition in both supersonic and hypersonic boundary layer flows because this framework has been rarely used in such high-speed flows. Detailed flow features associated with the transition are well captured, including the growth of instability modes in the pre-turbulent regime and the skin friction in the overall transitional flows. This study demonstrates that the proposed approach provides high fidelity for transitional boundary layers with a fraction of the computational cost of a full-scale DNS computation. It is recognized that artificial dissipation needs to be adequately controlled inside transitional boundary layer, particularly for the hypersonic case, because a common shock sensor is activated unexpectedly in the viscous boundary layer. A modified shock sensor is investigated in the current study of hypersonic boundary layer.FALSEsciescopu
A Lightweight Neural Network for Denoising Wrapped-Phase Images Generated with Full-Field Optical Interferometry
No full textPhase wrapping is a common phenomenon in optical full-field imaging or measurement systems. It arises from large phase retardations and results in wrapped-phase maps that contain essential information about surface roughness and topology. However, these maps are often degraded by noise, such as speckle and Gaussian, which reduces the measurement accuracy and complicates phase reconstruction. Denoising such data is a fundamental problem in computer vision and plays a critical role in biomedical imaging modalities like Full-Field Optical Interferometry. In this paper, we propose WPD-Net (Wrapped-Phase Denoising Network), a lightweight deep learning-based neural network specifically designed to restore phase images corrupted by high noise levels. The network architecture integrates a shallow feature extraction module, a series of Residual Dense Attention Blocks (RDABs), and a dense feature fusion module. The RDABs incorporate attention mechanisms that help the network focus on critical features and suppress irrelevant noise, especially in high-frequency or complex regions. Additionally, WPD-Net employs a growth-rate-based feature expansion strategy to enhance multi-scale feature representation and improve phase continuity. We evaluate the model’s performance on both synthetic and experimentally acquired datasets and compare it with other state-of-the-art deep learning-based denoising methods. The results demonstrate that WPD-Net achieves superior noise suppression while preserving fine structural details even with mixed speckle and Gaussian noises. The proposed method is expected to enable fast image processing, allowing unwrapped biomedical images to be retrieved in real time. © 2025 by the authors.TRUEsciescopu
Corrigendum to “Enhancement of Power Quality based on Dynamic Voltage Restorer Matrix Inverter - Sliding Mode Control Scheme” [Electric Power Systems Research volume 241 (2025) 111408](S037877962500001X)(10.1016/j.epsr.2025.111408)
No full textThe authors regret that the Acknowledgement that we used in the current form of the paper is no longer available for supporting the article processing charge. So, we kindly ask the editorial board to change the Acknowledgement as follow: This work was supported by a Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korean government (MOTIE) (No. RS-2023-00237679). Also, the authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number “NBU-FFR 2025-2448-20”. The authors would like to apologise for any inconvenience caused. Sincerely, Yun-su Kim © 2025 The AuthorsTRUEsciescopu
Femtosecond Laser-Induced Terahertz Emission in Spintronic Multilayers and the Role of Hot Phonons
No full textSpintronic devices have emerged as a promising next-generation technology, as they can utilize spin current―defined as spin-polarized electron flow without a net electric current―thereby avoiding Joule heating. This technology is aimed at energy-efficient and high-speed signal processing, where low power consumption and sub-picosecond response times are essential. In this context, terahertz (THz) spintronics has recently attracted significant attention.
In this study, we investigated spintronic THz emission from ferromagnetic (FM) and nonmagnetic (NM) multilayer structures, focusing on FM/NM bilayers and NM/FM/NM trilayers, which were excited by femtosecond laser pulses. The samples were fabricated with optimized thicknesses for each structure, and the emission efficiency was examined as a function of laser fluence, with slight variations observed between the structures. To gain deeper insight into the emission mechanism, THz time-domain spectroscopy was used to extract the charge currents that govern the THz emission process. Through this apporach, we observed a laser-fluence-dependent temporal delay in the THz emission process, which was attributed to hot phonon effects. Our findings highlight the importance of mulilayer design and phonon engineering in spintronic THz emission and are expected to provide useful insights for future research and design of ultrafast spintronic THz device
Copper Tantalate by a Sodium-Driven Flux-Mediated Synthesis for Photoelectrochemical CO2 Reduction
No full textCopper-tantalate, Cu2Ta4O11 (CTO), shows significant promise as an efficient photocathode for multi-carbon compounds (C2+) production through photoelectrochemical (PEC) CO2 reduction, owing to its suitable energy bands and catalytic surface. However, synthesizing CTO poses a significant challenge due to its metastable nature and thermal instability. In this study, this challenge is addressed by employing a flux-mediated synthesis technique using a sodium-based flux to create sodium-doped CTO (Na-CTO) thin films, providing enhanced nucleation and stabilization for the CTO phase. To evaluate the PEC performance and catalytic properties of the films, copper(II) oxide (CuO) at the Na-CTO surface is selectively etched. The etched Na-CTO shows a lower dark current, with decreased contribution from photocorrosion, unlike the non-etched Na-CTO which has remaining CuO on the surface. Furthermore, Na-CTO exhibits 7.3-fold ethylene selectivity over hydrogen, thus highlighting its promising potential as a photocathode for C2+ production through PEC CO2 reduction. © 2025 The Author(s). Small Methods published by Wiley-VCH GmbH.TRUEsciescopu
Fire-exposed polypropylene as a potential source of nanoplastics in aquatic environments
No full textWorldwide, mismanaged plastic waste from developing countries is increasing, with a significant proportion of this waste being exposed to fire. As a result, fire-exposed plastics are increasingly entering natural environments. This study aims to enhance the understanding of nanoplastics (NPs) leaching from fire-exposed plastics in water. We selected polypropylene (PP), a widely used polymer that can contaminate the water environment. PP was exposed to fire with a torch at temperatures between 950 and 1150 degrees C for varying durations (10-30 s). An electronic balance, vernier calipers, Raman spectroscopy, XPS, SEM, and HRTEM were used to analyze the characteristics of plastics exposed to fire. A shaking incubator was used to simulate the physical impacts of water flow in a water environment. The NPs concentration was analyzed using DLS and TOC. After 24 h of shaking, no NPs were detected for pristine PP. However, the 30 s of fire-exposed PP released NPs with 1.33 x 1012 +/- 3.64 x 1011 particle count kg-1 within just 1 h. This study also found that stronger physical conditions (fire exposure time, shaking time, shaking rate) led to an increase in NPs release. Likewise, as the pH increased from 5 to 9, the absolute zeta potential increased, resulting in a gradual rise in NPs release. These findings underscore the urgent need to assess and manage the environmental risks posed by plastic residues resulting from campfire, wildfire, open burning, or container ship burning, as these residues have the potential to act as sources of NPs water.FALSEsciescopu
APPLICATION OF ENTROPY FIX TO COMPUTATIONS OF HYPERSONIC LAMINAR AND TURBULENT BOUNDARY LAYERS ON HIFIRE-1
No full textThis study presents a case study of hypersonic laminar and turbulent boundary layers on the HIFiRE-1 model, proposed as a benchmark in the 2024 High-Fidelity CFD Verification Workshop. Computations were initially performed with the Roe flux-differencing scheme, but non-physical carbuncle phenomena appeared near the cone nose. To improve numerical stability, an entropy fix was applied by modifying the eigenvalues comprising the dissi- pation term. The improved simulation captured key shock structures and showed good agreement with reference data including surface pressure and heat flux. The turbulent heat flux is up to four times higher than in the laminar one, highlighting the impact of the boundary layer state on the aerothermodynamics of a high-speed vehicle.TRUEkc