Search

This paper proposes a performance-based microstructure design methodology specifically tailored for gas diffusion layers (GDLs). The generative machine learning denoising diffusion probabilistic model (DDPM) is trained and used for performance-based microstructure design. This study demonstrates significant progress in performance-based design by incorporating DDPM into the microstructure design process, offering a promising approach for GDL microstructure design. This methodology provides the advantage of generating 2D microstructures with desired permeability and volume fractions. Moreover, it is not limited to a specific performance criterion, making it adaptable to target other metrics. To train the DDPM, a 2D GDL microstructure dataset is constructed using the Lattice Boltzmann Method (LBM) for permeability estimation. Subsequently, we employ the DDPM with U-net architecture, which leverages positional encoding to learn the microstructure's volume fraction and permeability effectively. The input label pair of permeability and volume fraction is generated considering the inherent relationship between these two parameters to ensure the generation of meaningful microstructures. This relationship is supposed to ensure that the resulting microstructures align with realistic and physically meaningful characteristics. The simulated performance results obtained from the generated microstructures using the proposed methodology demonstrate a strong consistency with the targeted performance objectives. [ABSTRACT FROM AUTHOR]

Background: Infusion pumps are critical in delivering fluids, including medications and blood products, in controlled amounts. However, conventional pumps can cause hemolysis and other issues such as flow variations and infection risks, especially during blood transfusions. To address these limitations, a novel cylinder-type infusion pump, the Anyfusion H-100, was developed, which includes a specialized blood transfusion cartridge set that combines syringe and peristaltic infusion methods. This study evaluates the accuracy and hemolysis rates of the Anyfusion H-100 compared to conventional pumps, aiming to confirm its viability as a safe and effective medical device for blood transfusions. Methods: This study evaluated six different infusion rates (10–180 cc/hr) and conducted 57 transfusion trials, 20 of which used a 1:1 blood–saline dilution. Blood transfusion accuracy was measured using research-grade packed red blood cells, and hemolysis rates were assessed before and after transfusion by chi-square tests and independent sample t-tests. Results: Anyfusion demonstrated an average transfusion error rate of 3.77%, compared to 4.00% for the Terufusion, with no statistically significant difference in hemolysis rates (p = 0.697). Bland–Altman plots confirmed their equivalent performance, with hemolysis rates of 0.566 ± 0.095% for Anyfusion and 0.518 ± 0.126% for Terufusion. Conclusions: Anyfusion provides an accurate and reliable blood transfusion performance comparable to that of Terufusion, with no significant difference in hemolysis rates; its integration of syringe and infusion methods shows a potential for safer and more efficient transfusion practices, especially in pediatric and emergency settings. [ABSTRACT FROM AUTHOR]

This paper proposes a microstructure reconstruction framework with denoising diffusion models for the first time. The novelty and strength of the proposed model lie in its universality and generality for the microstructure characterization and reconstruction (MCR) that can be applied to various types of composite materials. The applicability of the diffusion-based models is validated with several types of microstructures (e.g., polycrystalline alloy, carbonate, ceramics, copolymer, fiber composite, etc.) that have different morphological characteristics. Moreover, an implicit probabilistic model (which yields non-Markovian diffusion processes) is formulated to accelerate the sampling process, thereby controlling the computational cost considering the practicability and reliability. [ABSTRACT FROM AUTHOR]

Cardiovascular disease is a major global health concern, with early detection being critical. This study assesses the effectiveness of a portable ECG device, based on Internet of Medical Things (IoMT) technology, for remote cardiovascular monitoring during daily activities. We conducted a clinical trial involving 2000 participants who wore the HiCardi device while engaging in hiking activities. The device monitored their ECG, heart rate, respiration, and body temperature in real-time. If an abnormal signal was detected while a physician was remotely monitoring the ECG at the IoMT monitoring center, he notified the clinical research coordinator (CRC) at the empirical research site, and the CRC advised the participant to visit a hospital. Follow-up calls were made to determine compliance and outcomes. Of the 2000 participants, 318 showed abnormal signals, and 182 were advised to visit a hospital. The follow-up revealed that 139 (76.37%) responded, and 30 (21.58% of those who responded) sought further medical examination. Most visits (80.00%) occurred within one month. Diagnostic approaches included ECG (56.67%), ECG and ultrasound (20.00%), ultrasound alone (16.67%), ECG and X-ray (3.33%), and general treatment (3.33%). Seven participants (23.33% of those who visited) were diagnosed with cardiovascular disease, including conditions such as arrhythmia, atrial fibrillation, and stent requirements. The portable ECG device using the patch-type electrocardiograph detected abnormal cardiovascular signals, leading to timely diagnoses and interventions, demonstrating its potential for broad applications in preventative healthcare. [ABSTRACT FROM AUTHOR]

Quantifying the formation and decomposition of amyloid is a crucial issue in the development of new drugs and therapies for treating amyloidosis. The current technologies for grasping amyloid formation and decomposition include fluorescence analysis using thioflavin-T, secondary structure analysis using circular dichroism, and image analysis using atomic force microscopy or transmission electron microscopy. These technologies typically require spectroscopic devices or expensive nanoscale imaging equipment and involve lengthy analysis, which limits the rapid screening of amyloid-degrading drugs. In this study, we introduce a technology for rapidly assessing amyloid decomposition using capillary flow-based paper (CFP). Amyloid solutions exhibit gel-like physical properties due to insoluble denatured polymers, resulting in a shorter flow distance on CFP compared to pure water. Experimental conditions were established to consistently control the flow distance based on a hen-egg-white lysozyme amyloid solution. It was confirmed that as amyloid is decomposed by trypsin, the flow distance increases on the CFP. Our method is highly useful for detecting changes in the gel properties of amyloid solutions within a minute, and we anticipate its use in the rapid, large-scale screening of anti-amyloid agents in the future. [ABSTRACT FROM AUTHOR]

Brown algae are gaining traction as biorefinery feedstocks due to their advantages such as rapid growth and carbon dioxide sequestration. Saccharina japonica has high potential due to its high carbohydrate content, especially mannitol (26.7%). In this study, a biorefinery process for S. japonica was designed, with focusing on sugar conversion and bioconversion into lactic acid, a valuable platform chemical utilized in various industries. The existing sugar conversion process of S. japonica has been investigated by focusing on enzymatic or acid‐catalyzed hydrolysis, but not hot water extraction although mannitol can be easily recovered using water. The effect of temperature (60–120°C) on the mannitol yield from S. japonica was investigated, and a mannitol yield of 208 g/kg biomass was achieved at the optimal temperature of 100°C (about 78% of the theoretical maximum yield). This study emphasizes that this simple process has considerable potential for application as over 80% of the fermentable carbohydrates in S. japonica were mannitol. Then, S. japonica extract was applied to lactic acid production. First, lactic acid production of four bacterial strains was tested in a mannitol medium, and Lacticaseibacillus rhamnosus was selected as the superior producer, showing 1.93 to 2.92 times better lactic acid titer than others. Next, the optimal feeding concentration of mannitol was determined to be 20 g/L, which was all consumed by L. rhamnosus. Finally, S. japonica extract was applied to lactic acid production by L. rhamnosus, and the results showed similar fermentation profiles with the control medium: lactic acid production, 18.81 g/L (control: 18.97 g/L); lactic acid conversion, 95.1% (control: 95.9%); cell growth (OD600 nm), 8.9 (control: 7.4). The lactic acid yield in the designed biorefinery process was estimated to be 195.6 g/kg biomass, thus S. japonica has high potential as a biorefinery feedstock to produce valuable bioproducts, including lactic acid. [ABSTRACT FROM AUTHOR]

Sea buckthorn berries (SBB) are well known for being rich in natural bioactive compounds with high pharmacological activity. In this study, the optimization of extraction parameters was performed to recover phenolic compounds with high antioxidant activity from SBB. This study involved a systematic optimization approach, including screening for a variety of parameters, including temperature, time, ethanol concentration, agitation, and solid loading. On the basis of Plackett–Burman design (PBD) model, the two most significant parameters (agitation and solid loading) were selected, and the correlation model between those parameters and multiple responses was derived via response surface methodology (RSM). As a result, the optimal extraction condition for maximizing phenolic content and antioxidant activity was determined to be agitation at 109.54 rpm and a solid loading of 172.67 g/L. Under optimal conditions, SBB extract showed a total phenolic content of 0.21 mg/mL and ABTS and DPPH activities of 27.27% and 58.16%, respectively. The SBB extract prepared under optimal conditions was found to contain caffeic acid, vanillic acid, rutin, and vitamin B1 (thiamine). This work is the first challenge to design an optimization model for the efficient recovery of antioxidants from SBB and is significant in that the model can be applied simply and economically to conventional extraction processes. [ABSTRACT FROM AUTHOR]