Search Results (20,646)

Background: Occupational exposure to aerosol particles can pose a substantial health risk. The study aimed to characterise the deposition of occupationally relevant aerosols in a 3D anatomical adult nasal cavity model under steady and unsteady flows. Materials: The deposition of aerosolised wheat flour, pine wood sanding dust, carbon black, and Arizona Test Dust A3 was quantified under steady flows (5, 7.5, and 20 L/min per nostril) and an unsteady breathing pattern generated by the commercial breathing simulator. Image analysis with custom software quantified the area covered by deposited particles. The Downstream Penetration Index (DPI) was determined from the outlet mass. Results: The highest segmental deposition occurred in the anterior segment of the lateral wall (WA) and septum (SA), with moderate values in the middle lateral wall (WM) and the lowest in the posterior lateral wall (WP, nasopharynx) and septum (SP). Arizona Test Dust A3 and carbon black demonstrated higher middle-posterior deposition and DPI, consistent with finer particle size distributions (PSD) and greater sub-10 µm fractions. In contrast, wheat flour and pine wood dust, with larger median particle sizes and lower sub-10 µm fractions, showed stronger anterior filtration and lower DPI. Increased flow enhanced anterior filtration of coarse particles and shifted deposition forward, aligning with increased inertial impaction, but elevated DPI for fine particles. Under unsteady flow, deposition was intermediate between 7.5 and 20 L/min. Conclusions: This study shows that PSD, morphology, and flow conditions influence nasal deposition. Coarse aerosols were filtered in the anterior nose, while fine-rich aerosols showed relatively greater middle-posterior deposition and higher DPI. These findings are essential for assessing occupational exposure and developing interventions and prevention strategies. Full article

A dew-point evaporative air cooler incorporating a novel segmented heat exchange design, demarcated according to the humidity state of moist air, is proposed. The system employs a porous fibrous material to create a wetted evaporative surface, which is continuously maintained in a moistened condition through a self-wicking water supply mechanism to enhance latent heat transfer. Circular fins are installed on the heat exchanger’s partition surface once the moist air reaches saturation, thereby improving sensible heat exchange between the dry and wet channels. The performance of a prototype was evaluated under controlled conditions in a standard enthalpy chamber. Experimental results indicate that, under typical summer conditions (inlet dry-bulb and wet-bulb temperatures of 33.8 °C and 25.4 °C, respectively), with an air mass flow ratio of 0.7 and an air velocity of 1.5 m/s, the wet-bulb effectiveness reaches 114.4% and the dew-point effectiveness achieves 84.8%. The maximum temperature reduction occurs in the sensible heat exchange section, reaching up to 6.1 °C, demonstrating its substantial sensible heat recovery capability. The device exhibits an energy efficiency ratio (EER) ranging from 9.1 to 31.8. The proposed compact configuration not only enhances energy efficiency but also reduces material costs by approximately 15.4%, providing a valuable reference for the future development of dew-point evaporative cooling systems in residential buildings. Full article

Slag entrainment within the mold is a significant cause of surface defects in continuously cast slabs. As a key component for controlling molten steel flow, the structure of the submerged entry nozzle directly influences the flow field characteristics and slag entrainment behavior within the mold. This paper employs a 1:4-scale water–oil physical model combined with numerical simulation to investigate the effects of elliptical and circular submerged entry nozzles on slag entrainment behavior in a wide slab mold under different casting speeds and immersion depths. High-speed cameras were used to visualize meniscus fluctuations and oil droplet entrainment processes. An alternating control variable method was employed to quantitatively delineate a slag-free “safe zone” and a “slag entrainment zone” where oil droplets fall, determining the critical casting speed and critical immersion depth under different operating conditions. The results show that, given the nozzle immersion depth and slag viscosity, the maximum permissible casting speed range without slag entrainment can be obtained, providing a reference for industrial production parameter control. The root mean square (RMS) of surface fluctuations was introduced to characterize the activity of the meniscus flow. It was found that the RMS value decreases with increasing nozzle immersion depth and increases with increasing casting speed, showing a good correlation with the frequency of slag entrainment. Numerical simulation results show that compared with elliptical nozzles, circular nozzles form a more symmetrical flow field structure in the upper recirculation zone, with a left–right vortex center deviation of less than 5%, resulting in higher flow stability near the meniscus and thus reducing the risk of slag entrainment. Full article

Coronary artery disease (CAD) remains the leading cause of cardiovascular mortality worldwide. Accurate and non-invasive quantification of coronary hemodynamics, namely in the right coronary artery (RCA), is essential for clinical decision-making but remains challenging due to the complex interaction among vessel geometry, pulsatile flow, and blood rheology. This study presents and validates a transparent computational framework for non-invasive fractional flow reserve (FFR) estimation using patient-specific RCA geometries reconstructed from coronary computed tomography angiography (CCTA) using SimVascular 27-03-2023. The proposed workflow integrates realistic boundary conditions through a Womersley velocity profile and a three-element Windkessel outlet model, coupled with a viscoelastic blood rheology formulation (sPTT) implemented via user-defined functions (UDFs). This work integrates all clinically relevant conditions of invasive FFR assessment into a single patient-specific computational framework, while delivering results within a time frame compatible with clinical practice, representing a meaningful methodological advance. The methodology was applied to seven patient-specific cases, and the resulting non-invasive FFR values were compared with both invasive wire-based measurements and commercial HeartFlow^® outputs (Mountain View, CA, USA). Under hyperemic conditions, the computed FFR values showed strong agreement with invasive references, with a mean relative error of 8.4% ± 6.3%, showing diagnostic consistency similar to that of HeartFlow^® (8.3% ± 8.1%) for the selected dataset. These findings demonstrate the ability of the proposed CFD-based pipeline to accurately replicate physiological coronary behavior under hyperemia. This novel workflow provides a fully on-site, open-source, reproducible, and cost-effective framework. Ultimately, this study advances the clinical applicability of non-invasive CFD tools for the functional assessment of CAD, particularly in the RCA. Full article

Triply periodic minimal surface (TPMS) structures provide high surface area to volume ratios and tunable conduction pathways, but predicting their thermal behavior across different metallic materials remains challenging because multi-material experimentation is costly and full-scale simulations require extremely fine meshes to resolve the complex geometry. This study develops a physics-informed neural network (PINN) that reconstructs steady-state temperature fields in TPMS Gyroid structures using only two experimentally measured materials, Aluminum and Silver, which were tested under identical heat flux and flow conditions. The model incorporates conductivity ratio physics, Fourier-based thermal scaling, and complete spatial temperature profiles directly into the learning process to maintain physical consistency. Validation using the complete Aluminum and Silver datasets confirms excellent agreement for Aluminum and strong accuracy for Silver despite its larger temperature gradients. Once trained, the PINN can generalize the learned behavior to nine additional metals using only their conductivity ratios, without requiring new experiments or numerical simulations. A detailed heat transfer analysis is also performed for Magnesium, a lightweight material that is increasingly considered for thermal management applications. Since no published TPMS measurements for Magnesium currently exist, the predicted Nusselt numbers obtained from the PINN-generated temperature fields represent the first model-based evaluation of its convective performance. The results demonstrate that the proposed PINN provides an efficient, accurate, and scalable surrogate model for predicting thermal behavior across multiple metallic TPMS structures and supports the design and selection of materials for advanced porous heat technologies. Full article

Sickle cell disease is an autosomal recessive hemoglobin disorder affecting about 100,000 people in the United States, predominantly those of African descent. A point mutation in the β-globin gene in red blood cells causes these cells to sickle under hypoxemic conditions, reducing blood flow and oxygen delivery to tissues. This manifests in the form of painful vaso-occlusive episodes, acute chest syndrome, and acute infarction of various organs, including the spleen, bone, and lung. While sickle cell disease complications such as hemolytic anemia, tissue hypoxia, and chronic organ damage are well studied, attention to the unique reproductive challenges faced by patients with sickle cell disease remains underrecognized and underappreciated. This review aims to explore key reproductive health issues in patients with sickle cell disease, including diminished ovarian reserve, infertility, and obstetric and perinatal risk. Secondly, this review aims to identify key counseling and care opportunities for providers to support patients with sickle cell disease in meeting their reproductive goals. Full article

Mobile air cleaners have emerged as a practical solution for reducing indoor aerosol concentrations, particularly in the absence of HVAC systems. Their efficiency is typically assessed under standardised conditions, but how turbulence influences the effective air exchange rate indoors is not well understood. In this study, we present a systematic investigation of the impact of enhanced turbulence on aerosol decay in two room sizes (50 m³ and 200 m³) using a mobile air cleaner combined with different fan configurations. Particle counter measurements were conducted simultaneously with particle image velocimetry ($PIV$), enabling direct comparison of air exchange rates and flow field properties. Our results show that specific fan arrangements significantly modify turbulent kinetic energy ($TKE$) distributions and, in turn, alter the effective air exchange rate. In the smaller room, configurations generating higher $TKE$ brought the measured exchange rates closer to theoretical predictions, while in large rooms other arrangements led to noticeable deviations. We anticipate that these findings provide a reference framework for understanding the role of turbulence in indoor air cleaning performance, with implications for optimizing the operation and placement of mobile air cleaners in practical environments. Full article

Ischemic heart disease (IHD) remains a leading cause of morbidity and mortality worldwide. Myocardial ischemia–reperfusion injury (MIRI) is a significant contributor to cardiac tissue damage, resulting from an abrupt reduction in blood flow that leads to a reduction in the supply of oxygen and nutrients. The resulting hypoxia triggers severe cellular injury and impairs organ function. Hypoxia-inducible factors (HIFs) play a central role in maintaining oxygen homeostasis in mammalian tissues. As primary oxygen sensors, HIFs trigger the transcriptional activation of a wide range of genes that facilitate cellular adaptation to reduced oxygen availability and assist in minimizing ischemic damage. Mitochondria are particularly vulnerable to hypoxic stress and are a major source of reactive oxygen species (ROS) during I/R injury. Stabilization of HIFs has been shown to reduce loss of cardiomyocytes under these conditions, highlighting the importance of HIF-dependent pathways in preserving mitochondrial integrity and promoting cell survival. Collectively, these observations suggest that hypoxia, HIF signaling, and mitochondrial dysfunction are tightly interconnected processes in the pathogenesis of IHD. This review, therefore, focuses on the interaction between hypoxia-driven HIF responses and mitochondrial regulation, emphasizing their implications for therapeutic strategies in managing IHD. Full article

The high penetration of renewable energy brings significant power fluctuations and operational uncertainties to distribution networks. Traditional power allocation methods for hybrid energy storage systems (HESSs) exhibit strong parameter dependency, limited frequency-domain recognition accuracy, and poor dynamic coordination capability. To overcome these limitations, this study proposes an adaptive power allocation strategy for HESSs under renewable energy integration scenarios. The proposed method employs the Grey Wolf Optimizer (GWO) to jointly optimize the mode number and penalty factor of the Variational Mode Decomposition (VMD), thereby enhancing the accuracy and stability of power signal decomposition. In conjunction with the Hilbert transform, the instantaneous frequency of each mode is extracted to achieve a natural allocation of low-frequency components to the battery and high-frequency components to the supercapacitor. Furthermore, a multi-objective power flow optimization model is formulated, using the power commands of the two storage units as optimization variables and aiming to minimize voltage deviation and network loss cost. The model is solved through the Particle Swarm Optimization (PSO) algorithm to realize coordinated optimization between storage control and system operation. Case studies on the IEEE 33-bus distribution system under both steady-state and dynamic conditions verify that the proposed strategy significantly improves power decomposition accuracy, enhances coordination between storage units, reduces voltage deviation and network loss cost, and provides excellent adaptability and robustness. Full article

Low gas recovery in the Sebei-2 gas field is linked to residual gas trapping under water encroachment. This study investigates the pore-scale trapping behaviour of residual gas in three types of layer: conventional, low-resistivity, and low-acoustic high-resistivity. High-fidelity pore structures were reconstructed by integrating mercury intrusion porosimetry with thin-section data and microfluidic models were designed using the Quartet Structure Generation Set method and fabricated by wet etching. Visualized displacement experiments were performed under different wettability conditions and water invasion rates, and image analysis was used to quantify the distribution of trapped gas. Results show that the low-resistivity gas layer exhibits the highest residual gas saturation (30.57%), followed by the low-acoustic high-resistivity gas layer (20.20%), while the conventional gas layer has the lowest (15.29%). These values correspond to apparent pore-scale gas recoveries of about 48.95%, 65.01%, and 72.14% for the low-resistivity, low-acoustic high-resistivity and conventional gas layers, respectively. In hydrophilic systems, wetting-film thickening and flow diversion are the main trapping processes, whereas in hydrophobic systems, flow diversion dominates and residual gas decreases markedly. Increasing the water invasion rate reduces trapped gas in the conventional and low-resistivity layers, whereas in the strongly heterogeneous low-acoustic high-resistivity layer, higher invasion intensity strengthens preferential channelling/viscous fingering, leading to a non-monotonic residual gas response. These findings clarify the differentiated pore-scale trapping mechanisms of gas under water encroachment and highlight that mitigating water film-controlled trapping in low-resistivity layers and flow diversion trapping in low-acoustic high-resistivity layers is essential for mobilizing trapped gas, improving dynamic reserves, and ultimately enhancing the economic recovery of water-bearing gas reservoirs similar to the Sebei-2 gas field. Full article

Modern power grids are crucial infrastructures underpinning societal stability, yet their complexity and dynamic nature pose significant challenges for traditional analytical methods. Graph Neural Networks (GNNs) have recently emerged as powerful tools for modeling complex relationships in graph-structured data, making them especially suitable for analyzing power systems. However, existing GNN methods typically focus on static or simplified network models, failing to adequately address dynamic topological changes and suffering from the over-smoothing issue. To overcome these limitations, we propose a novel GNN framework incorporating dynamic message-passing mechanisms, comprising Dynamic Topological Learning (DTL) and Adaptive Message-Passing (AMP) modules. Specifically, DTL captures dynamic changes in the power grid topology conditioned on the current state of the system, while AMP dynamically adjusts the message-passing process to effectively preserve local node information according to the updated topology. This framework is model-agnostic, allowing it to be integrated with various GNN architectures. Extensive experiments on multiple benchmark power grid datasets demonstrate that our proposed framework significantly enhances existing GNN methods in power flow and optimal power flow analysis, consistently achieving lower mean absolute error and higher R-squared scores. Full article

Objective: Cerebral ischemia–reperfusion injury (IRI) is a distinct pathological phase that differs from permanent ischemia (IR) in that it triggers secondary damage despite the restoration of blood flow. The primary objective of this study is to comprehensively characterize and compare the molecular signatures—such as differential gene expression, protein activation, and metabolic alterations—between IRI and IR. By doing so, we aim to identify key pathways and biomarkers that specifically drive IRI and IR pathology, thereby providing novel therapeutic targets to mitigate reperfusion-induced damage in stroke and related neurological conditions. Methods: We employed an integrated transcriptomic and proteomic approach to compare a permanent ischemia model (IR, 24 h ischemia) with a reperfusion model (IRI, 1 h ischemia + 24 h reperfusion), using SHAM-operated animals as controls. Results: Our results demonstrate a profound decoupling between the transcriptome and proteome in IRI. While IRI induced extensive proteomic alterations (160 changed proteins in IRI vs. IR), transcriptional changes were minimal (3 genes), indicating dominant post-transcriptional regulation. Both IR and IRI activated shared inflammatory responses (e.g., Saa3, upregulated 14.33-fold in IRI/SHAM) and metabolic shifts (Gapdh, downregulated 4.03-fold). However, IRI uniquely upregulated neuroprotective genes (Arc, Npas4), activated a specific set of reperfusion-related pathways (72 proteins), and exhibited distinct extracellular matrix remodeling (Mmp3, upregulated 11.24-fold in IR/SHAM). The overall correlation between transcriptomic and proteomic dynamics was remarkably low (r = 0.014), underscoring the importance of translation and protein decay mechanisms. Conclusions: This study redefines IRI not merely as an exacerbation of ischemic damage but as a unique adaptive molecular trajectory. We identify Pisd-ps3 and Saa3 as potential therapeutic targets and show that proteomic signatures can stratify injury phases. These findings advance the prospects of precision therapeutics aimed at neuroprotection and immunomodulation in ischemic stroke. Full article

With the increasing number of highly airtight residences, concerns have risen that the negative pressure formed indoors during kitchen hood operation can reduce capture performance and cause unintended infiltration. This study experimentally and numerically (via CFD simulations) examined whether installing an air supply unit on the cooktop beneath a hood can stabilize hood performance and suppress infiltration in small residential spaces. Two cases were established depending on whether air was supplied: Case 1 (hood operation only) and Case 2 (simultaneous operation of the hood and the air supply unit). In the experimental setup, the hood exhaust flow rate, supply airflow rate, sink-drain infiltration rate, and temperature/humidity were measured. The period during which variations in measured values remained within 10% was defined as the steady state. In the CFD analysis, winter conditions were assumed, and the measured values were applied to the wall boundary, after which the temperature and velocity field were analyzed. In Case 2, by supplying 24.11 CMH of air, the hood flow rate remained stable at 75.72 CMH (98.8% of the initial level) throughout the test, and no infiltration was detected. The CFD analysis revealed that the air supply unit generated an “air curtain” effect, enabling rapid capture of hot airflow and reducing the high-temperature region. In conclusion, the interconnected operation of supply and exhaust systems was shown to be effective in enhancing hood exhaust stability, suppressing unintended infiltration, and improving capture reliability in highly airtight small residential buildings. Future studies should include further analyses, such as the effects of actual cooking behaviors and leakage path distributions. Full article

Large language models (LLM) have achieved remarkable advances in natural-language understanding and content generation, and LLM-based agents demonstrate strong adaptability, flexibility, and robustness in handling complex tasks and enabling automated decision-making. Determining the operating mode of a power system requires repeated adjustments of boundary conditions to address violations. Conventional approaches include expert-driven power flow calculations and optimal power flow methods, the latter of which often lack clear physical interpretability during the iterative optimization process. This study proposes a novel paradigm for automated computation and adjustment of power system operating modes based on LLM-driven multi-agent systems. The approach leverages the reasoning capabilities of LLMs to enhance the adaptability of power flow adjustment strategies, while multi-agent coordination with power flow calculation modules ensures computational accuracy, enabling a natural-language-guided adaptive operational computation and adjustment process. The framework also incorporates retrieval-augmented generation techniques to access external knowledge bases and databases, further improving the agents’ understanding of system operational patterns and the accuracy of decision-making. This method constitutes an exploratory application of LLMs and multi-agent technologies in power system computational analysis, highlighting the considerable potential of LLMs to extend and enhance traditional power system analysis methodologies. Full article

Microglia play a key role in the development of neuroinflammation induced by cerebral ischemia. On the other hand, these cells participate in neurorepair processes. This dual role of microglia stems from the ability to shift their phenotype from pro-inflammatory M1 to protective M2. Histone deacetylase inhibitors (HDACis) are a group of agents that exhibit neuroprotective effects in some models of ischemia, among others, by modulation of signaling pathways that regulate microglial activation. This study aimed to examine the effect of HDACis—sodium butyrate and Givinostat—on polarization of microglia and their potential mechanism of action in a model of ischemia in vitro (oxygen and glucose deprivation, OGD). We examined the expression of pro- and anti-inflammatory markers in the BV2 microglial cell line after OGD and HDACis treatment by qPCR; polarization of microglia by flow cytometry; and the activation/phosphorylation of ERK and AKT in BV2 cells by Western blot and ELISA. Our findings demonstrate a divergent impact of HDACis on the phenotype of microglial cells. Sodium butyrate significantly suppressed the mRNA expression of pro-inflammatory markers (IL-1β, TNF-α, CD86) and increased the level of anti-inflammatory factors in BV2 microglial cells after OGD, whereas Givinostat failed to attenuate these inflammatory responses. Our findings demonstrate that sodium butyrate, but not Givinostat, promotes a shift in microglia toward an anti-inflammatory M2 phenotype under ischemic conditions. This effect is associated with suppression of pro-inflammatory gene expression and activation of the PI3K/AKT signaling pathway. These results identify sodium butyrate as a potential modulator of microglial responses following ischemic injury. Full article