Search Results (105)

The geometric design of flow channels in bipolar plates is one of the critical features of proton exchange membrane fuel cells (PEMFCs), as it determines the power output of the fuel cell and has a significant impact on its performance and durability. The function of the bipolar plate is to guide the transfer of reactant gases to the gas diffusion layer and catalytic layer inside the PEMFC, while removing unreacted gases and gas–liquid byproducts. Therefore, the design of the bipolar plate flow channel is directly related to the water and thermal management of the PEMFC. In order to improve the comprehensive performance of PEMFCs and ensure their safe and stable operation, it is necessary to design the flow channels in bipolar plates rationally and effectively. This study addresses the limitations of existing bipolar plate flow channels by proposing a new coupling of serpentine and radial channels. The distribution of oxygen, water concentrations, and temperature inside the channel is simulated using the multi-physics simulation software COMSOL Multiphysics 6.0. The performance of this novel design is compared with conventional flow channels, with a particular focus on the pressure drop and current density to evaluate changes in the output performance of the PEMFC. The results show that the maximum current density of this novel design is increased by 67.36% and 10.43% compared to straight channel and single serpentine channels, respectively. The main contribution of this research is the innovative design of a new coupling of serpentine and radial channels in bipolar plates, which improves the overall performance of the PEMFC. This study provides theoretical support for the design of bipolar plate flow channels in PEMFCs and holds significant importance for the green development of energy. Full article

Holothuria scabra has long been acknowledged in traditional medicine for its therapeutic properties. The transforming growth factor-beta (TGF-β) superfamily is crucial in regulating cellular processes, including differentiation, proliferation, and immune responses. This study marks the first exploration of the gene expression localization, sequence conservation, and functional roles of H. scabra TGF-β proteins, specifically activin (HolscActivin), inhibin (HolscInhibin), and the TGF-β receptor (HolscTGFBR), across various organs. In situ hybridization indicated that HolscActivin and HolscInhibin are expressed in the intestine, respiratory tree, ovary, testis, and inner body wall. This suggests their roles in nutrient absorption, gas exchange, reproduction, and extracellular matrix remodeling. Notably, HolscTGFBR demonstrated a similar tissue-specific expression pattern, except for its absence in the respiratory tree. Bioinformatics analysis reveals that HolscTGFBR shares significant sequence similarity with HomsaTGFBR, especially in regions essential for signal transduction and inhibition. Molecular docking results indicate that HolscActivin may promote receptor activation, while HolscInhibin functions as a natural antagonist, reflecting the signaling mechanisms of human TGF-β proteins. Interestingly, cross-species ternary complex docking with human TGF-β receptors further supports these findings, showing that HolscActivin moderately engages the receptors, whereas HolscInhibin exhibits strong binding, suggestive of competitive inhibition. These results indicate that H. scabra TGF-β proteins retain the structural and functional features of vertebrate TGF-β ligands, supporting their potential applications as natural modulators in therapeutic and functional food development. Full article

The horizontal tube falling film heat exchangers (HTFFHEs), which exhibit remarkable advantages such as high efficiency in heat and mass transfer, low resistance, and a relatively simple structural configuration, have found extensive applications. Complex flow phenomena and the coupled processes of heat and mass transfer take place within it. Given that the heat and mass transfer predominantly occur at the gas-liquid interface, the flow characteristics therein emerge as a significant factor governing the performance of heat and mass transfer. This article elaborates on the progress of experimental and simulation research approaches with respect to flow characteristics. It systematically reviews the influence patterns of various operating parameters, namely parameters of gas, solution and internal medium, as well as structural parameters like tube diameter and tube spacing, on the flow characteristics, such as the flow regime between tubes, liquid film thickness, and wettability. This review serves to furnish theoretical underpinnings for optimizing the heat and mass transfer performance of the horizontal tube falling film heat exchanger. It is further indicated that the multi-dimensional flow characteristics and their quantitative characterizations under the impacts of different airflow features will constitute the focal research directions for horizontal tube falling film heat exchangers in the foreseeable future. Full article

Particulate matter affects both the light environment and air quality in greenhouses, obstructing normal gas exchange and hindering efficient physiological activities such as photosynthesis. This study focused on young Chinese cabbage (Brassica rapa L. Chinensis Group) in a greenhouse at harvest time, monitoring and comparing hyperspectral information, net photosynthetic rate, and microscopic leaf structure under two conditions: a quantitative artificial particulate matter environment and a healthy environment. Based on microscopic results combined with spectral responses and changes in photosynthetic physiological information, it is believed that particulate matter enters plant cells through stomata. Through retention and transport pathways, it disrupts the membrane structure, organelles, and other components of plant cells, resulting in adverse effects on the plant’s physiological functions. The study analyzed the mechanisms by which particulate matter influences the photosynthesis, spectral characteristics, and physiological responses of young Chinese cabbage. Physiological Reflectance Index (PRI), Modified Chlorophyll Absorption Ratio Index (MCARI), spectral red-edge position (λr), and spectral sensitive bands were used as spectral feature variables. Through cubic polynomial and 24 combinations of spectral preprocessing and modeling methods, an inversion model of spectral features and net photosynthetic rate was established. The optimal combination of spectral preprocessing and modeling methods was finally selected as SG + SD + PLS + MSC, which consists of Savitzky-Golay smooth (SG), second derivative (SD), partial least squares (PLS), and multiplicative scatter correction (MSC). The coefficient of determination (R²) of the model is 0.9513. The results indicate that particulate matter affects plant photosynthesis. The SG + SD + PLS + MSC combination method is relatively advantageous for processing the photosynthetic spectral physiological information of plants under the influence of particulate matter. The results of this study will deepen the understanding of the mechanisms by which particulate matter affects plants and provide a reference for the physiological information inversion of greenhouse vegetables under particulate matter pollution. Full article

As a new form of economic activity driven by data resources and digital technologies, the digital economy underscores the strategic significance of data as a core production factor. This growing importance necessitates accurate and robust valuation methods. Data valuation poses core modeling challenges due to its nonlinear nature and the instability of neural networks, including gradient vanishing, parameter sensitivity, and slow convergence. To overcome these challenges, this study proposes a genetic algorithm-optimized BP (GA-BP) model, enhancing the efficiency and accuracy of data valuation. The BP neural network employs a symmetrical architecture, with neurons organized in layers and information transmitted symmetrically during both forward and backward propagation. Similarly, the genetic algorithm maintains a symmetric evolutionary process, featuring symmetric operations in both crossover and mutation. The empirical data used in this study are sourced from the Shanghai Data Exchange, comprising 519 data samples. Based on this dataset, the model incorporates 9 primary indicators and 21 secondary indicators to comprehensively assess data value, optimizing network weights and thresholds through the genetic algorithm. Experimental results show that the GA-BP model outperforms the traditional BP network in terms of mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R²), achieving a 47.6% improvement in prediction accuracy. Furthermore, GA-BP exhibits faster convergence and greater stability. When compared to other models such as long short-term memory (LSTM), convolutional neural networks (CNNs), and optimization-based BP variants like particle swarm optimization BP (PSO-BP) and whale optimization algorithm BP (WOA-BP), GA-BP demonstrates superior generalization and robustness. This approach provides valuable insights into the commercialization of data assets. Full article

Accurate segmentation of soil pore structure is crucial for studying soil water migration, nutrient cycling, and gas exchange. However, the low-contrast and high-noise CT images in complex soil environments cause the traditional segmentation methods to have obvious deficiencies in accuracy and robustness. This paper proposes a hybrid model combining a Multi-Modal Low-Frequency Reconstruction algorithm (MMLFR) and UNet (MMLFR-UNet). MMLFR enhances the key feature expression by extracting the image low-frequency signals and suppressing the noise interference through the multi-scale spectral decomposition, whereas UNet excels in the segmentation detail restoration and complexity boundary processing by virtue of its coding-decoding structure and the hopping connection mechanism. In this paper, an undisturbed soil column was collected in Hainan Province, China, which was classified as Ferralsols (FAO/UNESCO), and CT scans were utilized to acquire high-resolution images and generate high-quality datasets suitable for deep learning through preprocessing operations such as fixed-layer sampling, cropping, and enhancement. The results show that MMLFR-UNet outperforms UNet and traditional methods (e.g., Otsu and Fuzzy C-Means (FCM)) in terms of Intersection over Union (IoU), Dice Similarity Coefficients (DSC), Pixel Accuracy (PA), and boundary similarity. Notably, this model exhibits exceptional robustness and precision in segmentation tasks involving complex pore structures and low-contrast images. Full article

The hospital-at-home (HaH) model offers hospital-level care within patients’ homes and has proven effective for managing conditions such as pneumonia. The point-of-care ultrasonography (PoCUS) is a key diagnostic tool in this model, especially when traditional imaging modalities are unavailable. This review explores how PoCUS can be optimized to manage pneumonia in HaH settings, focusing on its diagnostic accuracy in patients with comorbidities, differentiation from mimickers, and role in assessing disease severity. Pulmonary comorbidities, such as heart failure and interstitial lung disease (ILD), can complicate lung ultrasound (LUS) interpretation. In heart failure, combining lung, cardiac, and venous assessments (e.g., IVC collapsibility, VExUS score) improves diagnostic clarity. In ILD, distinguishing chronic changes from acute infections requires attention to B-line patterns and pleural abnormalities. PoCUS must differentiate pneumonia from conditions such as atelectasis, lung contusion, cryptogenic organizing pneumonia, eosinophilic pneumonia, and neoplastic lesions—many of which present with similar sonographic features. Serial LUS scoring provides useful information on pneumonia severity and disease progression. Studies, particularly during the COVID-19 pandemic, show correlations between worsening LUS scores and poor outcomes, including increased ventilator dependency and mortality. Furthermore, LUS scores correlate with inflammatory markers and gas exchange metrics, supporting their prognostic value. In conclusion, PoCUS in HaH care requires clinicians to integrate multi-organ ultrasound findings, clinical context, and serial monitoring to enhance diagnostic accuracy and patient outcomes. Mastery of LUS interpretation in complex scenarios is crucial to delivering personalized, high-quality care in the home setting. Full article

The air–sea transfer of gases is important within climate physics, biogeochemistry and the control of pollutants. A two-layer model of transfer directly across the sea surface underpins most discourse, but an expanding literature also features transfer mediated by “suspended fragments”, either bubbles in the upper ocean or drops and aerosol in the lower atmosphere. In this study, we describe a categorization of process that elucidates departures from two-layer theory and is a starting point for quantification. On counting the distinct phenomena and their application to gases of various solubility, a total of eight categories are identified. Each category has a distinct scaling with respect to the properties of the gas and this is key to the relative importance of different categories and processes. Transfer through sea spray can be an exchange process, but the evaporation of sea spray is more effective and is an ejection process. The reactivity of carbon dioxide in aqueous solution enhances the effect of spray. Exceptional levels of sea spray generation and evaporation are required to be significant for most gases, but moderate levels are sufficient for carbon dioxide and the most soluble pollutants. Full article

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by the fibrotic thickening of the alveolar walls, resulting in compromised gas exchange, restricted ventilation, and respiratory failure. It has been indicated that elastase inhibitors reduced the severity of IPF by neutralizing excessive elastase levels in the lungs. ShSPI is an elastase inhibitor derived from centipede toxin. The present study evaluates the therapeutic effects of ShSPI in a bleomycin-induced idiopathic pulmonary fibrosis model. According to the results, ShSPI markedly reduced the weight loss, showing the improvement of health status in bleomycin-induced mice. Its robust antifibrotic effects were evidenced by the mitigation of alveolar structural damage, reduction in inflammatory cell infiltration, inhibition of collagen deposition, and suppression of fibrotic nodule formation. ShSPI effectively attenuated inflammatory responses by downregulating pro-inflammatory factors (IL-6, IL-1β, and MCP-1) and upregulating the anti-inflammatory factor interleukin-10 (IL-10). After delivered via inhalation, ShSPI exhibited favorable pharmacokinetic properties. It could be detected at 8 h at doses of 1 mg/kg and achieved maximum plasma concentrations (Cmax) of 188.00 ± 64.40 ng/mL in vivo. At high doses (160 mg/kg), ShSPI maintained a strong safety profile, with no detectable toxicity observed. This feature shows the therapeutic potential of ShSPI in the treatment of idiopathic pulmonary fibrosis and provides valuable evidence for its development as a novel peptide-based therapy. Full article

The performance and durability of proton-exchange membrane fuel cells (PEMFCs) are dependent on fuel flow, humidifying water, and outgoing water management. Unlike conventional flow fields with linear channels, the complex 3D flow field—featuring repeating baffles along the channel, known as the baffle design—induces a micro-scale interface flux between the gas diffusion layer (GDL) and the flow fields. Thus, an intensive oxygen flow is created that removes excess water from the GDL, thereby improving the fuel cell efficiency. Another approach for channel design is the Turing flow field, which resembles the organization of fluid flows in natural objects such as leaves, lungs, and the blood system. This design enhances the distribution of inlet flow significantly compared with traditional designs. The present study aims to combine the advantages of both Turing and baffle flow field designs and to provide model investigations on the influence of the mixed flow field design on the efficiency of PEMFCs. It was established that the mixed design achieves the highest electrode current density of 1.2 A/cm², outperforming the other designs. Specifically, it achieves 20% improvement over the Turing design, reaching 1.0 A/cm² and generating three times more current than the baffle design, which delivers 0.4 A/cm². In contrast, the conventional serpentine designs exhibit the lowest current density. The mixed flow field design provides better oxygen utilization in the electrochemical reaction, offers optimal membrane hydration, and contributes to superior electrode current density performance. These data illustrate how flow field structure directly impacts fuel cell efficiency through enhancement of current density. Full article

Postharvest preservation of fruits is one of the key issues in the current agriculture and food processing industry. Surface coating treatment, a promising technology for postharvest fruit preservation, has gathered significant attention due to its ability to reduce water loss, regulate gas exchange, and inhibit respiration, thereby achieving postharvest fruit preservation. Among them, chitosan-based coating has a wide application prospect due to its superior film-forming capability, high biosecurity, wide range of sources, etc. This review summarizes the structural features, physicochemical properties, modification strategies, and preservation mechanisms of chitosan-based coatings, focusing on their applications in postharvest fruit storage. Unlike prior works, it highlights advanced modifications (e.g., nanocomposite, multifunctional grafting) that enhance antimicrobial activity, mechanical strength, and environmental adaptability. Challenges in fruit preservation—such as microbial resistance and stability—are analyzed, with solutions proposed via material innovation. The discussion on industrial scalability emphasizes chitosan’s biodegradability, cost-effectiveness, and alignment with sustainable agriculture, while addressing technical bottlenecks. This work bridges fundamental research and practical use, advancing chitosan-based coatings toward greener, safer, and scalable postharvest solutions. Full article

Interstitial lung diseases (ILDs) are a heterogeneous group of pulmonary disorders characterised by variable degrees of inflammation, interstitial thickening, and fibrosis leading to distortion of the pulmonary architecture and gas exchange impairment. There are approximately 200 different entities in this category. ILDs are commonly classified based on several criteria, including causes, clinical features, and radiological patterns. Chest HRCT is the gold standard for the recognition of lung alteration patterns underlying interstitial lung diseases (ILDs), diagnosing specific patterns, and evaluating radiologic progression. Methods based on artificial intelligence (AI) may be used in computational medicine, especially in image-based specialties such as radiology. The evolving field of radiomics offers a unique and non-invasive approach to extracting quantitative information from medical images, particularly high-resolution computed tomography (HRCT) scans. This comprehensive review explores the burgeoning role of radiomics in unravelling the intricacies of interstitial lung disease. It focuses on its potential applications in diagnosis, prognostication, and treatment response evaluation. Full article

Heat exchangers play an important role in offshore oil and gas production and offshore low-temperature waste heat power generation. Heat exchanger health management mainly relies on performance parameter monitoring; however, accurate fault mode identification remains a challenge and the diagnostic results are difficult to interpret. This paper proposed an interpretable intelligent diagnosis method for heat exchangers based on Shapley Additive exPlanation and eXtreme Gradient Boosting. Firstly, secondary parameters characterizing the health state of heat exchangers are constructed based on online monitored data such as pressure and temperature. Then, the multi-dimensional feature vector is constructed by integrating the online monitored data and secondary parameters. The XGBoost fault diagnosis model for leakage and scaling faults is established with the multi-dimensional feature vector as the input. To improve the model performance on diagnosis, a grid search optimization algorithm is adopted. After the fault diagnosis of a heat exchanger is completed, the SHAP method is introduced to analyze the contribution of features by quantifying their influence on the fault diagnosis results. Finally, the effectiveness of the proposed method is verified by the heat exchanger fault simulation experiment. The proposed method achieved a diagnosis accuracy of 99.79%, which has better performance than the traditional fault diagnosis method. Full article

Drought is a detrimental abiotic stress that severely limits wheat growth and productivity worldwide by altering several physiological processes. Thus, understanding the mechanisms of drought tolerance is essential for the selection of drought-resilient features and drought-tolerant cultivars for wheat breeding programs. This exploratory study evaluated 14 wheat genotypes (13 relatively tolerant, one susceptible) for drought endurance based on flag leaf physiological and biochemical traits during the critical grain-filling stage in the field conditions. Measurements included six physiological, seven gas exchange, six photosystem II, six stomatal, three reactive species, seven metabolomic solutes, and two biomass traits. All parameters were significantly influenced by drought, with varying genotypic responses. Hierarchical cluster analysis (HCA) categorized genotypes into three drought tolerance groups based on trait performance. Seven genotypes in Cluster 2 (BARI Gom 26, BARI Gom 33, BD-631, BD-600, BD-9910, BD-9889, BD-637) exhibited superior drought tolerance, characterized by minimal changes in physiological traits and biomass accumulation, reduced oxidative stress markers, and increased accumulation of osmoprotectants. The innovative multi-trait genotype-ideotype distance index (MGIDI) further ranked wheat genotypes in regard to drought tolerance, identifying BARI Gom 33, BARI Gom 26, BD-9889, and BD-600 as top performers. Notably, all these top-ranking genotypes belonged to Cluster 2, previously identified as the highest-performing group in the HCA. The identified genotypes with superior drought tolerance offer valuable genetic resources for enhancing wheat productivity in water-limiting environments. Traits related to photosynthetic activity, biomass gain, leaf conductance, water stress, and osmoprotection showed high selection differentials and heritability in MGIDI analysis, indicating their potential as selection targets for drought-tolerant wheat. Overall, the strategic approaches have yielded novel insights into genotype screening that can be directly applied to deepen our understanding of drought tolerance mechanisms in wheat. Full article

Acute lung injury (ALI), diagnosed clinically as acute respiratory distress syndrome (ARDS), refers to a spectrum of acute inflammatory processes culminating in increased permeability of the pulmonary alveolar–capillary barrier and impaired gas exchange. The pandemic caused by the novel coronavirus, SARS-CoV-2, has raised questions as to the similarities and differences between COVID-19 lung injury and ALI of other etiologies. This review summarizes current knowledge regarding the pathophysiology of ALI and COVID-19 lung injury and draws comparisons between the latter and other infectious etiologies of ALI. Indeed, severe COVID-19 is characterized by a unique array of disease mechanisms including suppression of interferon responses, widespread inflammasome activation, altered leukocyte phenotypes, and hyperactive thrombotic activity. Moreover, these mechanisms manifest as a unique clinical progression, which further differentiates COVID-19 from other viral respiratory pathogens such as SARS, MERS, and influenza. These unique features of COVID-19 pathophysiology bear important implications for current and future therapeutic strategies. Full article