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In this study, a numerical simulation method was used to explore the impact of changes in riverine runoff input flow variations on the marine environmental dynamics in the northern Yellow Sea of China. Based on the depth-averaged two-dimensional shallow water equations, a hydrodynamic and water quality coupling model was established to simulate the changes of the water environmental indicators under five conditions. Validation against filed-measured data confirmed the model’s great accuracy and stability. The findings show that interception activities had a relatively small impact on hydrodynamic conditions, and the changes in velocity did not exceed 10 cm/s; however, the salinity changed significantly. As the interception rate increased, the moving distance of the isohaline with a value of 5 towards the estuary gradually increased, with a maximum distance of 3420 m. Meanwhile, the amount of reduction of the area of the envelope curve with a salinity of 26.8 gradually increased, with a peak areal reduction rate of 10.7%. The amount of changes in nutrient concentration was related to the interception rate and the distance of a station from the estuary. The maximum percentages of changes in inorganic nitrogen and inorganic phosphorus contents were 5.39% and 6.34%, respectively. This study provides a technical methodology for evaluating the impacts of analogous riverine runoff variations on estuarine and adjacent ecosystems. Full article

(This article belongs to the Section Marine Environmental Science)

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9 pages, 1633 KiB

Open AccessCommunication

Identification and Visualization Textile Fibers by Raman Imaging

by Kaili Liu and Huacai Chen

Materials 2025, 18(7), 1682; https://doi.org/10.3390/ma18071682 (registering DOI) - 7 Apr 2025

Abstract

Textile fibers are an essential component of daily necessities and are often used as forensic evidence, making their characterization crucial in forensic science. Different types of textile fibers can be identified using their unique Raman spectral characteristic peaks. In this study, we achieved the visualization of single-component, multi-component, and dyed blended fibers through Raman spectral imaging, demonstrating the spatial distribution of different types of textile fibers within the same area. Furthermore, by merging Raman images of fibers from non-confocal planes, we achieved accurate visual identification, providing more possibilities for characterizing fibers with special morphological features using Raman spectral imaging. In conclusion, Raman spectral imaging enables the successful visualization and identification of different types of fibers. Full article

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4 pages, 1609 KiB

Open AccessCorrection

Correction: Yuan et al. Identification of Protein Hydrolysates from Sesame Meal and In Vivo Study of Their Gastric Mucosal Protective Effects. Foods 2024, 13, 4178

by Yutong Yuan, Xinyi Wang, Nan Ling, Jingxuan Zhou, Lei Zhao, Baoping Ji, Feng Zhou and Liang Zhao

Foods 2025, 14(7), 1281; https://doi.org/10.3390/foods14071281 (registering DOI) - 7 Apr 2025

Abstract

In the original publication, there were mistakes in Figures 1, 2 and 4 as published [...] Full article

(This article belongs to the Special Issue Bioactive Peptides: Preparation, Characterization and Properties)

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19 pages, 7175 KiB

Open AccessArticle

MFFSNet: A Lightweight Multi-Scale Shuffle CNN Network for Wheat Disease Identification in Complex Contexts

by Mingjin Xie, Jiening Wu, Jie Sun, Lei Xiao, Zhenqi Liu, Rui Yuan, Shukai Duan and Lidan Wang

Agronomy 2025, 15(4), 910; https://doi.org/10.3390/agronomy15040910 (registering DOI) - 7 Apr 2025

Abstract

Wheat is one of the most essential food crops globally, but diseases significantly threaten its yield and quality, resulting in considerable economic losses. The identification of wheat diseases faces challenges, such as interference from complex environments in the field, the inefficiency of traditional machine learning methods, and difficulty in deploying the existing deep learning models. To address these challenges, this study proposes a multi-scale feature fusion shuffle network model (MFFSNet) for wheat disease identification from complex environments in the field. MFFSNet incorporates a multi-scale feature extraction and fusion module (MFEF), utilizing inflated convolution to efficiently capture diverse features, and its main constituent units are improved by ShuffleNetV2 units. A dual-branch shuffle attention mechanism (DSA) is also integrated to enhance the model’s focus on critical features, reducing interference from complex backgrounds. The model is characterized by its smaller size and fast operation speed. The experimental results demonstrate that the proposed DSA attention mechanism outperforms the best-performing Squeeze-and-Excitation (SE) block by approximately 1% in accuracy, with the final model achieving 97.38% accuracy and 97.96% recall on the test set, which are higher than classical models such as GoogleNet, MobileNetV3, and Swin Transformer. In addition, the number of parameters of this model is only 0.45 M, one-third that of MobileNetV3 Small, which is very suitable for deploying on devices with limited memory resources, demonstrating great potential for practical applications in agricultural production. Full article

(This article belongs to the Section Pest and Disease Management)

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19 pages, 5177 KiB

Open AccessArticle

Comparison of LiDAR Operation Methods for Forest Inventory in Korean Pine Forests

by Lan Thi Ngoc Tran, Myeongjun Kim, Hongseok Bang, Byung Bae Park and Sung-Min Choi

Forests 2025, 16(4), 643; https://doi.org/10.3390/f16040643 (registering DOI) - 7 Apr 2025

Abstract

Precise forest inventory is the key to sustainable forest management. LiDAR technology is widely applied to tree attribute extraction. Therefore, this study compared DBH and tree height derived from Handheld Mobile Laser Scanning (HMLS), Airborne Laser Scanning (ALS), and Integrated ALS and HMLS and determined the applicability of integrating HMLS and ALS scanning methods to estimate individual tree attributes such as diameter at breast height (DBH) and tree height in pine forests of South Korea. There were strong correlations for DBH at the individual tree level (r > 0.95; p < 0.001). HMLS and Integrated ALS-HMLS achieved high accuracy for DBH estimations, showing Root Mean Squared Error (RMSE) of 1.46 cm (rRMSE 3.7%) and 1.38 cm (rRMSE 3.5%), respectively. In contrast, tree height obtained from HMLS was lower than expected, showing an RMSE of 2.85 m (12.74%) along with a bias of −2.34 m. ALS data enhanced the precision of tree height estimations, achieving a RMSE of 1.81 m and a bias of −1.24 m. However, integrating ALS and HMLS data resulted in the most precise tree height estimations resulted in a reduced RMSE to 1.43 m and biases to −0.3 m. Integrated ALS and HMLS and its advantages are a beneficial solution for accurate forest inventory, which in turn supports forest management and planning. Full article

(This article belongs to the Special Issue Application of Remote Sensing and Geographic Information Systems for Natural Resource Management of Forest Ecosystems)

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15 pages, 3937 KiB

Open AccessArticle

Probiotic Supplementation Improves Lipid Metabolism Disorders and Immune Suppression Induced by High-Fat Diets in Coilia nasus Liver

by Jun Gao, Qi Mang, Yi Sun and Gangchun Xu

Biology 2025, 14(4), 381; https://doi.org/10.3390/biology14040381 (registering DOI) - 7 Apr 2025

Abstract

High-fat diets (HFDs) usually trigger disruptions in lipid metabolic processes and immune suppression in fish. As an eco-friendly and potent additive, the inclusion of probiotics in fish diets ameliorates dysregulations in lipid metabolism, mitigates oxidative stress, and reduces inflammatory reactions triggered by HFDs. However, little current research has focused on the improvement of the hazards of HFDs in fish by probiotics. Therefore, we employed 4-dimensional data-independent (4D-DIA) proteomic analysis to investigate the mechanism of the protective impact of probiotics against HFD-induced hepatic injury in Coilia nasus between the HFD group and the probiotic supplementation in HFD (PHFD) group. Additionally, lipid accumulation and antioxidant indicators in the liver were also measured via Oil Red O staining and activity detection. Administration of probiotics markedly attenuated the hepatic concentrations of triglycerides (TG), cholesterol (CHO), and low-density lipoprotein cholesterol (LDL-C) in C. nasus subjected to HFDs. Furthermore, it significantly upregulated the expression of the differentially expressed proteins (DEPs) implicated in cholesterol metabolism and fatty acid oxidation, while concurrently downregulating the DEPs associated with fatty acid synthesis. Additionally, probiotic supplementation significantly reduced the aspartate aminotransferase (AST), alanine aminotransferase (ALT), and malondialdehyde (MDA) levels induced by HFDs. It also upregulated the activities of catalase (CAT) and superoxide dismutase (SOD). Probiotic supplementation significantly upregulated the DEPs related to antioxidants, while significantly downregulating the DEPs associated with inflammatory responses and autophagy. These findings suggested that probiotics ameliorated HFD-induced hepatic lipid accumulation in C. nasus by enhancing cholesterol metabolism and fatty acid oxidation, concomitantly with the suppression of fatty acid synthesis pathways. Additionally, probiotics protected against HFD-induced hepatic injury by enhancing antioxidant defenses and suppressing inflammation in C. nasus. Full article

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19 pages, 4368 KiB

Open AccessReview

Drought–Rewatering Dynamics in Chinese Cropping Systems: A Meta-Analysis of Yield Loss Mitigation, Water Use Efficiency, and Compensatory Physiological Response

by Zhitao Li, Zhen Liu, Jinyong Zhu, Weilu Wang, Chengwei Gao, Jiangpeng Qi, Xiaoqiang Qiu, Minmin Bao, Hongyu Luo, Yuanming Li and Yuhui Liu

Agronomy 2025, 15(4), 911; https://doi.org/10.3390/agronomy15040911 (registering DOI) - 7 Apr 2025

Abstract

Drought stress, being a crucial abiotic stress factor, and its recovery mechanism after rehydration are important in regulating crop production. This meta-analysis investigates the effects of drought stress followed by rewatering (DSRW) on crop productivity and water use efficiency (WUE) in Chinese cropping systems, synthesizing data from 90 studies (1997–2023) encompassing 2606 experimental observations. Results indicate that DSRW significantly reduced crop yield (CY) across plant types, with monocots (20.31% decline) outperforming dicots (23.64%) and woody plants (19.98% decline) showing greater resilience than herbaceous species (21.52%). WUE improved in woody plants (+7.81%) but declined in herbaceous crops (−9.44%), with notable increases in Chenopodiaceae (+59.39%) and Malvaceae (+11.35%). Mild drought stress (>65% field capacity) followed by short-term rewatering during early growth stages minimized CY losses (−19.60%) and WUE reduction (−6.89%), outperforming moderate or severe stress. Physiological analyses revealed DSRW-induced declines in photosynthetic parameters (e.g., net photosynthetic rate: −11.54%) but enhanced antioxidant enzyme activities (CAT: +18.21%, SOD: +10.23%) and osmoregulatory substance accumulation (proline: +16.22%). The study highlights the compensatory potential of strategic rewatering timing and intensity, advocating for early-stage, mild drought interventions to mitigate yield losses, which provide a practical value for promoting the sustainable development of water-saving agriculture. Future research should address regional climatic variability and crop quality responses to DSRW, advancing climate-resilient agricultural practices. Full article

(This article belongs to the Special Issue Optimizing Crop Water Use: Advances and Applications in Deficit Irrigation Strategies)

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15 pages, 1067 KiB

Open AccessArticle

Multi-Analytical Characterisation of an Alcoholic Beverage Obtained by Blending of White Wine and Organic Kiwifruit Wine

by Lorenzo Marsili, Fabio Pietrangeli, Claudio Brilli, Martina Foschi, Alessandra Biancolillo, Angelo Antonio D’Archivio and Guerino Pescara

Beverages 2025, 11(2), 48; https://doi.org/10.3390/beverages11020048 (registering DOI) - 7 Apr 2025

Abstract

While studies on the co-fermentation of fruits and grapes are reported in the literature, blends of wine and fruit wine have never been investigated before. We characterised a blend (80:20 v/v) of Trebbiano Abruzzese white wine, organic kiwifruit wine, and the sparkling beverage obtained by its successive refermentation in a bottle. A persimmon/kiwifruit wine (50:50 v/v), after and before alcoholic fermentation, was also analysed. The buffer capacity, redox potential, concentration of selected polyphenols, total polyphenol content, antioxidant activity, and volatile profile were evaluated. The addition of kiwifruit wine to Trebbiano Abruzzese confers, to the final beverage, an appreciable improvement in terms of antioxidant activity, related to the content of polyphenols and ascorbic acid, which is substantially preserved in the sparkling product. Appreciable differences in the aroma of the blend compared to pure wine are mainly associated with the increased content of norisoprenoids, terpenes, methyl esters, and sulphur compounds, arising from the kiwifruit wine. The innovative beverages here proposed exhibit distinctive compositional and sensorial attributes that can be appreciated by consumers. Full article

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1 pages, 116 KiB

Open AccessCorrection

Correction: Ferreira Lima dos Santos et al. Riding into Danger: Predictive Modeling for ATV-Related Injuries and Seasonal Patterns. Forecasting 2024, 6, 266–278

by Fernando Ferreira Lima dos Santos, Farzaneh Khorsandi and Guilherme De Moura Araujo

Forecasting 2025, 7(2), 17; https://doi.org/10.3390/forecast7020017 (registering DOI) - 7 Apr 2025

Abstract

Addition of an Author [...] Full article

20 pages, 6644 KiB

Open AccessArticle

Safe Path for the Transformation of the Polish Energy System Leading to Its Decarbonization and Reliable Operation

by Andrzej Rusin and Adam Wojaczek

Energies 2025, 18(7), 1856; https://doi.org/10.3390/en18071856 (registering DOI) - 7 Apr 2025

Abstract

The European Union’s energy policy, which aims to achieve climate neutrality by 2050, requires substantial changes in the structure of the energy sources used for power generation. The paper considers the possibilities of increasing the pace of the Polish energy system transformation by replacing coal sources with renewable energy sources using energy storage. It is demonstrated that in the analyzed period until 2040 it will be possible to ensure the required level of the system’s energy supply reliability by supporting the system with energy storage. The assessment of the system reliability was carried out based on the LOLE and LOLP indicators, selecting the system structure in such a way that for the hourly energy demand characteristic adopted in the analyzed year, the LOLE was less than 3 h. The required capacity and power of the storage systems depend on the level of the demand for energy and power. The results of the analyses indicate that for the linear trend in the growth in the demand for energy, nuclear power plants with the total power of 8.8 GW have to be installed in the energy system. However, with a significant rise in the power demand and the decommissioning of coal units, balancing the system using other sources with a dominant share of renewable sources will be insufficient. It will therefore be necessary to use the energy storage with a capacity above 11 GWh and a total power above 2 GW. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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23 pages, 724 KiB

Open AccessArticle

GBsim: A Robust GCN-BERT Approach for Cross-Architecture Binary Code Similarity Analysis

by Jiang Du, Qiang Wei, Yisen Wang and Xingyu Bai

Entropy 2025, 27(4), 392; https://doi.org/10.3390/e27040392 (registering DOI) - 7 Apr 2025

Abstract

Recent advances in graph neural networks have transformed structural pattern learning in domains ranging from social network analysis to biomolecular modeling. Nevertheless, practical deployments in mission-critical scenarios such as binary code similarity detection face two fundamental obstacles: first, the inherent noise in graph construction processes exemplified by incomplete control flow edges during binary function recovery; second, the substantial distribution discrepancies caused by cross-architecture instruction set variations. Conventional GNN architectures demonstrate severe performance degradation under such low signal-to-noise ratio conditions and cross-domain operational environments, particularly in security-sensitive vulnerability identification tasks where feature instability or domain shifts could trigger critical false judgments. To address these challenges, we propose GBsim, a novel approach that combines graph neural networks with natural language processing. GBsim employs a cross-architecture language model to transform binary functions into semantic graphs, leverages a multilayer GCN for structural feature extraction, and employs a Transformer layer to integrate semantic information, generates robust cross-architecture embeddings that maintain high performance despite significant distribution shifts. Extensive experiments on a large-scale cross-architecture dataset show that GBsim achieves an MRR of 0.901 and a Recall@1 of 0.831, outperforming state-of-the-art methods. In real-world vulnerability detection tasks, GBsim achieves an average recall rate of 81.3% on a 1-day vulnerability dataset, demonstrating its practical effectiveness in identifying security threats and outperforming existing methods by 2.1%. This performance advantage stems from GBsim’s ability to maximize information preservation across architectural boundaries, enhancing model robustness in the presence of noise and distribution shifts. Full article

(This article belongs to the Special Issue Robustness of Graph Neural Networks)

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11 pages, 1339 KiB

Open AccessArticle

Innovative Use of Bleomycin Electrosclerotherapy (BEST) for High-Flow Arteriovenous Malformations in the Head District: Preliminary Results of Two Cases

by Linda Latini, Sandra Bracco, Samuele Cioni, Sara Leonini, Flavia Cascino and Paolo Gennaro

J. Clin. Med. 2025, 14(7), 2516; https://doi.org/10.3390/jcm14072516 (registering DOI) - 7 Apr 2025

Abstract

Background: According to the ISSVA 2018 classification, arteriovenous malformations (AVMs) are high-flow vascular malformations, distinct from low-flow lesions. About 60% of extracranial AVMs occur in the head and neck, making their management a focus of maxillofacial surgery. Due to their complexity, precise diagnosis and careful treatment planning are crucial for optimal aesthetics and structural preservation. The standard approach combines embolization with surgical resection, though Bleomycin electrosclerotherapy (BEST) has recently gained recognition. Methods: From July 2023 to December 2024, a total of 16 patients with vascular malformations were treated with bleomycin electrosclerotherapy at the Azienda Ospedaliera Universitaria Senese (AOUS). Among them, two patients were affected by arteriovenous malformations. These two patients underwent this treatment to avoid more invasive and demolitive procedures, considering the anatomical region involved. Both patients had previously been treated at other hospitals, experiencing subsequent lesion recurrence. Preoperative evaluation included angiographic and ultrasound studies. The patients underwent electrosclerotherapy sessions and were closely monitored during follow-up. The uniqueness of this innovative approach lies in the use of fractionated doses of bleomycin for each treatment session, compared to the standard protocols described in the literature. Results: BEST has demonstrated efficacy in the treatment of high-flow AVMs by delivering bleomycin into the interstitial tissue and subsequently applying electroporation so the drug’s effects can be precisely localized and amplified. The macroscopically evident results, patient satisfaction, and, most importantly, the objective ultrasound flow data demonstrate the effectiveness of this treatment. Conclusions: Arteriovenous malformations (AVMs) pose treatment challenges due to their variability and lack of standardized guidelines. This study explores electrosclerotherapy with bleomycin in two head and neck AVM cases, using fractionated doses to enhance safety and efficacy. The findings support its potential as a minimally invasive alternative, warranting further research on broader applications. Full article

(This article belongs to the Special Issue Vascular Surgery: Current Advances and Future Directions)

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21 pages, 4531 KiB

Open AccessArticle

Flavor Characteristics of Sun-Dried Green Tea in Different Regions of Yunnan: Metabolite Basis and Soil Influencing Factors

by Miao Zhou, Xiujuan Deng, Qiaomei Wang, Zhenzhen Wei, Xinhua Wang, Wenxia Yuan, Limei Li, Man Zou, Weihao Liu, Shijie Lu, Yubo Sheng and Baijuan Wang

Foods 2025, 14(7), 1280; https://doi.org/10.3390/foods14071280 (registering DOI) - 7 Apr 2025

Abstract

To elucidate the regional flavor characteristics of sun-dried green tea (SDT) and their underlying influencing factors, a comprehensive analysis was conducted using metabolomics and flavoromics approaches. This study systematically examined SDT samples and their corresponding tea garden soils from 13 distinct regions in Yunnan Province. The results revealed that the SDT samples could be classified into two distinct groups based on their flavor profiles. Compared to the regions of Pa Sha (PS), Bang Dong (BD), Dong Ban Shan (DBS), Dong Guo (DG), Su Hu (SH), Gua Feng Zhai (GFZ), and Wu Liang Shan (WLS), the regions of Xin Nong (XN), Ba Ka Nuan (BKN), Mang Ang (MA), Man Nuan (MN), Bing Dao (BDao), and Bin Shan (BS) exhibited a significant upregulation of the tea polyphenols (TP)/free amino acids (FAA) ratio. The former group was characterized by a sweet mellow taste, while the latter displayed a stronger taste profile. Furthermore, the analysis of volatile compounds demonstrated that geraniol and linalool were significantly upregulated in the PS, BD, DBS, DG, BS, and BDao regions, which were associated with tender and floral aromas. In contrast, isophorone, 2-pentyl furan, 1-octanol, D-limonene, and benzaldehyde were markedly enriched in the XN, BKN, MA, MN, SH, GFZ, and WLS regions, contributing to sweet and honey-like aromatic profiles. Altitude and mineral element phosphorus are potential key factors affecting the regional flavor differences in SDT. Specifically, SDT cultivated at higher altitudes and in soils with elevated available phosphorus content exhibited a greater likelihood of accumulating sweet mellow and floral compounds. This study provides scientific evidence for understanding the characteristic flavor profiles of SDT across different regions, offering valuable insights into the factors contributing to regional flavor differentiation in tea production. Full article

(This article belongs to the Special Issue Production, Quality, Flavor Characteristics and Health Benefits of Tea)

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Graphical abstract

30 pages, 31096 KiB

Open AccessArticle

Decadal Trends and Drivers of Dust Emissions in East Asia: Integrating Statistical and SHAP-Based Interpretability Approaches

by Ziwei Yi, Yaqiang Wang, Zhaoliang Zeng, Weijie Li, Huizheng Che and Xiaoye Zhang

Remote Sens. 2025, 17(7), 1313; https://doi.org/10.3390/rs17071313 (registering DOI) - 7 Apr 2025

Abstract

Dust emissions significantly impact the radiation balance, ecosystems, human health, and global climate change through long-range transport. However, their spatiotemporal characteristics and driving mechanisms in East Asia remain poorly understood. This study integrates multi-source reanalysis and remote sensing data (1980–2023) to analyze dust emissions across East Asian source regions using statistical methods and SHapley Additive exPlanations (SHAP) interpretability. The results show significant spatial and seasonal variations, with peak emissions occurring in spring (March–May). The Taklamakan Desert (S4) accounts for 38.1% of total emissions and is the largest source region. Meteorological factors are the main drivers (49.4–68.8% contribution), while climate indices contribute the least (2.9–8.0%). Wind speed is the most critical factor driving dust emissions, showing a significant positive correlation and interacting with 850 hPa geopotential height and boundary layer height. The driving factors of dust emissions vary across regions. In Mongolia (S1), dust emissions are mainly influenced by wind speed and atmospheric circulation, while in S4, near-surface meteorological conditions play a dominant role. In the Tsaidam Basin and Kumutage Desert (S5), as well as the Badain Jaran, Tengger, and Ulan Buh Deserts (S6), dust emissions are primarily driven by wind speed and boundary layer height, with atmospheric circulation also playing a certain role. Relative humidity shows a significant negative correlation with dust emissions in S5 and S6, while snowmelt and soil temperature have significant impacts on S4 and S5. The negative phases of the Arctic Oscillation and North Atlantic Oscillation enhance cold air activity and wind speed, significantly promoting dust emissions in S1 and S6. This study quantifies the mechanisms of dust emissions in East Asia and offers scientific support for improving climate models and developing disaster mitigation strategies. Full article

(This article belongs to the Topic Machine Learning and Big Data Analytics for Natural Disaster Reduction and Resilience)

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8 pages, 1582 KiB

Open AccessProceeding Paper

Psychophysiological Analysis of Correction Calculation for as Turbine Engine Gas Turbine Engine Noise Tonality

by Volodymir M. Zhuravlev, Igor F. Kravchenko and Sergiy V. Dmytriyev

Eng. Proc. 2025, 90(1), 90; https://doi.org/10.3390/engproc2025090090 (registering DOI) - 7 Apr 2025

Abstract

In this paper, we duct a psychophysiological and methodological analysis of the calculation of tonality correction during bench tests of aircraft gas turbine engines for compliance with environmental noise requirements. It is proven that the noise characteristics of a signal are influenced by the modulation law of its tonal components. It is shown that the application of the spectral analysis method for gas turbine engine acoustic signals, for which the stationarity parameters are not determined, leads to an uncertain systematic error. The calculation of the tonality parameter value, which determines the correction of deterioration of the environmental impact assessment of the engine, is not substantiated and has a random character. This paper presents a methodology for the psychophysiological ranking of gas turbine engine noise signals, which offers an intelligent algorithm for signal processing that corresponds with that corresponds with the speech zones of the human central nervous system. Full article

(This article belongs to the Proceedings of The 14th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)

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