Journal Description
Applied Sciences
Applied Sciences
is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our authors say about Applied Sciences.
- Companion journals for Applied Sciences include: Applied Nano, AppliedChem, Applied Biosciences, Virtual Worlds, Spectroscopy Journal and JETA.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
Exploring the Effectiveness of the Phase Features on Double Compressed AMR Speech Detection
Appl. Sci. 2024, 14(11), 4573; https://doi.org/10.3390/app14114573 (registering DOI) - 26 May 2024
Abstract
Determining whether an audio signal is single compressed (SC) or double compressed (DC) is a crucial task in audio forensics, as it is closely linked to the integrity of the recording. In this paper, we propose the utilization of phase spectrum-based features for
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Determining whether an audio signal is single compressed (SC) or double compressed (DC) is a crucial task in audio forensics, as it is closely linked to the integrity of the recording. In this paper, we propose the utilization of phase spectrum-based features for detecting DC narrowband and wideband adaptive multi-rate (AMR-NB and AMR-WB) speech. To the best of our knowledge, phase spectrum features have not been previously explored for DC audio detection. In addition to introducing phase spectrum features, we propose a novel parallel LSTM system that simultaneously learns the most representative features from both the magnitude and phase spectrum of the speech signal and integrates both sets of information to further enhance its performance. Analyses demonstrate significant differences between the phase spectra of SC and DC speech signals, suggesting their potential as representative features for DC AMR speech detection. The proposed phase spectrum features are found to perform as well as magnitude spectrum features for the AMR-NB codec, while outperforming the magnitude spectrum in detecting AMR-WB speech. The proposed phase spectrum features yield 8% performance improvement in terms of true positive rate over the magnitude spectrogram features. The proposed parallel LSTM system further improves DC AMR-WB speech detection.
Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessArticle
Synthesis of Non-Linguistic Utterances for Sound Design Support Using a Genetic Algorithm
by
Ahmed Khota, Eric W. Cooper and Yu Yan
Appl. Sci. 2024, 14(11), 4572; https://doi.org/10.3390/app14114572 (registering DOI) - 26 May 2024
Abstract
As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of
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As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of non-speech sounds that can convey emotions has been limited. To enable social robots to use a large amount of non-speech sounds in a natural and dynamic way, while expressing a wide range of emotions effectively, this work proposes an automatic method of sound generation using a genetic algorithm, coupled with a random forest model trained on representative non-speech sounds to validate each produced sound’s ability to express emotion. The sounds were tested in an experiment wherein subjects rated the perceived valence and arousal. Statistically significant clusters of sounds in the valence arousal space corresponded to different emotions, showing that the proposed method generates sounds that can readily be used in social robots.
Full article
(This article belongs to the Special Issue Intelligent Robotics: Design and Applications)
Open AccessArticle
Influence of Non-Ionic Surfactant and Silver on the Photocatalytic Activity of TiO2 Films for Degradation of Dyes in Distilled and Tap Water
by
Dobrina Ivanova, Elisaveta Mladenova and Nina Kaneva
Appl. Sci. 2024, 14(11), 4571; https://doi.org/10.3390/app14114571 (registering DOI) - 26 May 2024
Abstract
This study describes the impact of surfactant molecular weights (PEG 2000 and PEG 4000) on the photocatalytic activity of TiO2 films, deposited via dip-coating from a PEG-stabilized suspension and silver-functionalized photo-fixation of Ag+ under UV illumination. The photocatalytic activity of pure
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This study describes the impact of surfactant molecular weights (PEG 2000 and PEG 4000) on the photocatalytic activity of TiO2 films, deposited via dip-coating from a PEG-stabilized suspension and silver-functionalized photo-fixation of Ag+ under UV illumination. The photocatalytic activity of pure and Ag/TiO2 films is assessed in the aqueous-phase degradation of Malachite green and Methylene blue in distilled and tap water under UV and visible illumination. The results indicate a positive effect of both the higher-molecular-weight non-ionic surfactant and Ag-functionalization yield higher photocatalytic efficiency. Notably, films photo-fixed with 10−2 M Ag+ show the highest degradation percentages in all experimental conditions. A direct correlation between the concentration of Ag+ ions and the enhancement of the photocatalytic activity is revealed: pure TiO2 < Ag, 10−4/TiO2 < Ag, 10−3/TiO2 < Ag, 10−2/TiO2. Flame atomic absorption spectrometry is used to study the Ag+ leeching from the Ag/TiO2 films. The structural properties of the nanostructures are investigated through scanning electron microscopy, Brunauer–Emmett–Teller analysis, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Additionally, after three cycles of operation, Ag, 10−2/TiO2 (PEG 4000) films can maintain their photocatalytic activity, suggesting a potential application in the treatment of dye wastewater.
Full article
(This article belongs to the Special Issue Environmental Catalysis and Green Chemistry)
Open AccessArticle
Implementation of a Generative AI Algorithm for Virtually Increasing the Sample Size of Clinical Studies
by
Anastasios Nikolopoulos and Vangelis D. Karalis
Appl. Sci. 2024, 14(11), 4570; https://doi.org/10.3390/app14114570 (registering DOI) - 26 May 2024
Abstract
Determining the appropriate sample size is crucial in clinical studies due to the potential limitations of small sample sizes in detecting true effects. This work introduces the use of Wasserstein Generative Adversarial Networks (WGANs) to create virtual subjects and reduce the need for
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Determining the appropriate sample size is crucial in clinical studies due to the potential limitations of small sample sizes in detecting true effects. This work introduces the use of Wasserstein Generative Adversarial Networks (WGANs) to create virtual subjects and reduce the need for recruiting actual human volunteers. The proposed idea suggests that only a small subset (“sample”) of the true population can be used along with WGANs to create a virtual population (“generated” dataset). To demonstrate the suitability of the WGAN-based approach, a new methodological procedure was also required to be established and applied. Monte Carlo simulations of clinical studies were performed to compare the performance of the WGAN-synthesized virtual subjects (i.e., the “generated” dataset) against both the entire population (the so-called “original” dataset) and a subset of it, the “sample”. After training and tuning the WGAN, various scenarios were explored, and the comparative performance of the three datasets was evaluated, as well as the similarity in the results against the population data. Across all scenarios tested, integrating WGANs and their corresponding generated populations consistently exhibited superior performance compared with those from samples alone. The generated datasets also exhibited quite similar performance compared with the “original” (i.e., population) data. By introducing virtual patients, WGANs effectively augment sample size, reducing the risk of type II errors. The proposed WGAN approach has the potential to decrease costs, time, and ethical concerns associated with human participation in clinical trials.
Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Biomedical Data Analysis)
Open AccessArticle
Research on the Construction of a Blockchain-Based Industrial Product Full Life Cycle Information Traceability System
by
Leifeng Xiao, Wenlei Sun, Saike Chang, Cheng Lu and Renben Jiang
Appl. Sci. 2024, 14(11), 4569; https://doi.org/10.3390/app14114569 (registering DOI) - 26 May 2024
Abstract
The application of blockchain technology in industrial product quality traceability is analyzed to construct a new model of product quality traceability that is mainly based on blockchain technology and supplemented by an identity system. The blockchain-enabled overall technical architecture of an industrial product
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The application of blockchain technology in industrial product quality traceability is analyzed to construct a new model of product quality traceability that is mainly based on blockchain technology and supplemented by an identity system. The blockchain-enabled overall technical architecture of an industrial product quality traceability system is explored, and a blockchain-based industrial product full life cycle information traceability system is constructed. First, the weights of the information indicators of different links of the industrial equipment information traceability system were calculated using the EAHP hierarchical analysis method. The manufacturing link had the largest weight, with a value of 18.8%. Second, the system’s functional module design is based on the weights. We designed and developed the industrial product information traceability platform based on the hybrid blockchain chain structure of private chain + alliance chain. Finally, a manufacturing enterprise in the Xinjiang region is taken as the research object, query validation is carried out for the products produced by the enterprise, and the average query time of the system is measured to be 65.376 ms. It can meet the traceability needs of consumers and enterprise users. The research can provide theoretical support and reference for the whole life cycle information traceability of industrial products.
Full article
Open AccessArticle
Removal of Color-Document Image Show-Through Based on Self-Supervised Learning
by
Mengying Ni, Zongbao Liang and Jindong Xu
Appl. Sci. 2024, 14(11), 4568; https://doi.org/10.3390/app14114568 (registering DOI) - 26 May 2024
Abstract
Show-through phenomena have always been a challenging issue in color-document image processing, which is widely used in various fields such as finance, education, and administration. Existing methods for processing color-document images face challenges, including dealing with double-sided documents with show-through effects, accurately distinguishing
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Show-through phenomena have always been a challenging issue in color-document image processing, which is widely used in various fields such as finance, education, and administration. Existing methods for processing color-document images face challenges, including dealing with double-sided documents with show-through effects, accurately distinguishing between foreground and show-through parts, and addressing the issue of insufficient real image data for supervised training. To overcome these challenges, this paper proposes a self-supervised-learning-based method for removing show-through effects in color-document images. The proposed method utilizes a two-stage-structured show-through-removal network that incorporates a double-cycle consistency loss and a pseudo-similarity loss to effectively constrain the process of show-through removal. Moreover, we constructed two datasets consisting of different show-through mixing ratios and conducted extensive experiments to verify the effectiveness of the proposed method. Experimental results demonstrate that the proposed method achieves competitive performance compared to state-of-the-art methods and can effectively perform show-through removal without the need for paired datasets. Specifically, the proposed method achieves an average PSNR of 33.85 dB on our datasets, outperforming comparable methods by a margin of 0.89 dB.
Full article
(This article belongs to the Special Issue AI-Based Image Processing: 2nd Edition)
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Open AccessArticle
A Quantitative and Qualitative Analysis of the Lubricity of Used Lubricating Oil Diluted with Diesel Oil
by
Leszek Chybowski, Marcin Szczepanek, Robert Sztangierski and Piotr Brożek
Appl. Sci. 2024, 14(11), 4567; https://doi.org/10.3390/app14114567 (registering DOI) - 26 May 2024
Abstract
Experience shows that dilution of lubricating oil with diesel oil is unfavorable to the engine, causing issues including deterioration of engine performance, shortening of oil life, and reduction in engine reliability and safety. This paper presents the verification of the hypothesis that the
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Experience shows that dilution of lubricating oil with diesel oil is unfavorable to the engine, causing issues including deterioration of engine performance, shortening of oil life, and reduction in engine reliability and safety. This paper presents the verification of the hypothesis that the changes in lubricity, friction coefficient, and decreasing oil film thickness (using a relative approach, given as a percentage) are similar for lubricating oil and diesel mixtures prepared from fresh lubricating oil and used lubricating oil. To validate this hypothesis, an experiment is conducted using a high-frequency reciprocating rig (HFFR), in which the lubricity is determined by the corrected average wear scar WS1.4, the coefficient of friction μ, and the percentage relative decrease in oil film thickness r. A qualitative visual assessment of the wear scars on the test specimens is also performed after the HFFR tests. The testing covers mixtures of SAE 30 grade Marinol CB-30 RG1230 lubricating oil with Orlen Efecta Diesel Biodiesel. The used lubricating oil is extracted from the circulating lubrication system of a supercharged, trunk-piston, four-stroke ZUT Zgoda Sulzer 5 BAH 22 engine installed in the laboratory of ship power plants of the Maritime University of Szczecin. Mixtures for the experiment are prepared for fresh lubricating oil with diesel oil and used lubricating oil with diesel oil. Mixtures of these lubricating oils with diesel oil are examined for diesel oil concentrations in the mixture equal to 1, 2, 5, 10, 15, and 20% m/m. The results of the experiment confirm the hypothesis, proving that, for up to 20% m/m diesel oil concentration in lubricating oil, the changes in the lubricity of used lubricating oil diluted with diesel oil can be evaluated based on reference data prepared for mixtures of diesel oil with fresh lubricating oil. The linear approximation of μ and r trends is made with a certain margin of error we estimated. The experiment also confirms the results of previous studies which state that oil aging products in small quantities contribute to improved lubricity.
Full article
(This article belongs to the Special Issue Digital and Computational Tribology)
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Open AccessArticle
Small-Cell Combs Offer as Favorable Conditions of Rearing Worker Bees as Standard-Cell Combs in the Temperate Climate in Spring
by
Piotr Dziechciarz, Aneta Strachecka, Grzegorz Borsuk and Krzysztof Olszewski
Appl. Sci. 2024, 14(11), 4566; https://doi.org/10.3390/app14114566 (registering DOI) - 26 May 2024
Abstract
During the spring development of bee colonies, small-cell combs were found to create equally favorable conditions for worker bee rearing as standard-cell combs, since the workers reared in the small-cell combs did not differ significantly in the majority of morphometric traits, including the
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During the spring development of bee colonies, small-cell combs were found to create equally favorable conditions for worker bee rearing as standard-cell combs, since the workers reared in the small-cell combs did not differ significantly in the majority of morphometric traits, including the length of wings and the sum of the widths of the third and fourth tergites, from those reared in standard-cell combs. Moreover, they had a significantly longer and wider thorax. It can be assumed that the workers reared in small-cell combs collect nectar as effectively as those reared in standard-cell combs, as both groups did not differ in the proboscis length. It was confirmed that the body size of workers is relatively constant and is less influenced by the width of comb cells than was assumed previously, as the values of their morphometric parameters did not increase proportionally with the increasing cell width. The colony kept on small-cell combs provided worse rearing conditions for workers reared in standard-cell combs than the colony kept on standard-cell combs, which may have been related to the less abundant feeding of larvae by workers reared in small-cell combs.
Full article
(This article belongs to the Special Issue Apiculture: Challenges and Opportunities)
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Open AccessArticle
The Effect of the Initial Phase of a Tightly Focused Laser Pulse on the Emission Characteristics of High-Energy Electrons
by
Yiwei Zhou, Erhan Li and Youwei Tian
Appl. Sci. 2024, 14(11), 4565; https://doi.org/10.3390/app14114565 (registering DOI) - 26 May 2024
Abstract
Abstract: Based on the classical theory of nonlinear Thomson scattering and the single electron model, we performed extensive numerical simulations in MATLAB R2022b to comprehensively investigate how the initial phase of a tightly focused, circularly polarized laser pulse affects the radiation characteristics of
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Abstract: Based on the classical theory of nonlinear Thomson scattering and the single electron model, we performed extensive numerical simulations in MATLAB R2022b to comprehensively investigate how the initial phase of a tightly focused, circularly polarized laser pulse affects the radiation characteristics of high-energy electrons at different energy levels. Our findings indicate that the polar angle corresponding to the maximum radiation energy remains constant as the initial phase of the laser changes from 0 to 2π, while the azimuth angle correspondingly moves from 0 to 2π. Moreover, as the initial phase changes, the pulse width of the electron radiation peak displays a quasi-periodic oscillation with a period of π. Notably, an increase in the initial energy of the electrons results in a significant enhancement in both the peak radiation value and the collimation of the radiation. These results demonstrate that manipulating the initial phase of the driving laser pulse enables effective control over the spatial distribution of radiation light.
Full article
(This article belongs to the Section Optics and Lasers)
Open AccessArticle
Impact of Augmented Reality on Assistance and Training in Industry 4.0: Qualitative Evaluation and Meta-Analysis
by
Ginés Morales Méndez and Francisco del Cerro Velázquez
Appl. Sci. 2024, 14(11), 4564; https://doi.org/10.3390/app14114564 (registering DOI) - 26 May 2024
Abstract
In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies.
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In the context of Industry 4.0, industrial environments are at a crossroads, facing the challenge of greater flexibility and significant technical skills gaps. In this situs, Augmented Reality (AR) emerges as a transformative tool, enhancing the synergy between technical staff and emerging technologies. This article focuses on exploring the integration of AR in Industry 4.0, with a particular emphasis on its role in improving technical assistance and training. The research addresses the ways in which AR not only facilitates more efficient processes but also acts as an essential bridge for training and skills development in constantly changing technological environments. It investigates the significant impact of AR on both optimising work processes and training workers to meet the emerging challenges of Industry 4.0. Through a qualitative analysis, the studies are categorised according to their application domains, grouping them into specific thematic areas. Subsequently, a meta-analysis is conducted to determine the actual impact of AR in the sector. The findings reveal a positive and significant correlation between the implementation of AR and its effectiveness in assistance and training in the framework of Industry 4.0. Finally, the article delves into an analysis of current limitations and challenges, providing insights into possible developments and trends in the use of AR for assistance and training in Industry 4.0.
Full article
(This article belongs to the Special Issue Virtual/Augmented Reality and Its Applications)
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Open AccessArticle
Machine Learning-Based Fatigue Level Prediction for Exoskeleton-Assisted Trunk Flexion Tasks Using Wearable Sensors
by
Pranav Madhav Kuber, Abhineet Rajendra Kulkarni and Ehsan Rashedi
Appl. Sci. 2024, 14(11), 4563; https://doi.org/10.3390/app14114563 (registering DOI) - 26 May 2024
Abstract
Monitoring physical demands during task execution with exoskeletons can be instrumental in understanding their suitability for industrial tasks. This study aimed at developing a fatigue level prediction model for Back-Support Industrial Exoskeletons (BSIEs) using wearable sensors. Fourteen participants performed a set of intermittent
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Monitoring physical demands during task execution with exoskeletons can be instrumental in understanding their suitability for industrial tasks. This study aimed at developing a fatigue level prediction model for Back-Support Industrial Exoskeletons (BSIEs) using wearable sensors. Fourteen participants performed a set of intermittent trunk-flexion task cycles consisting of static, sustained, and dynamic activities, until they reached medium-high fatigue levels, while wearing BSIEs. Three classification algorithms, Support Vector Machine (SVM), Random Forest (RF), and XGBoost (XGB), were implemented to predict perceived fatigue level in the back and leg regions using features from four wearable wireless Electromyography (EMG) sensors with integrated Inertial Measurement Units (IMUs). We examined the best grouping and sensor combinations by comparing prediction performance. The findings showed best performance in binary classification of leg and back fatigue with 95% (2 EMG + IMU sensors) and 82% (single IMU sensor) accuracy, respectively. Tertiary classification for back and leg fatigue level prediction required four sensor setups with both EMG and IMU measures to perform at 79% and 67% accuracy, respectively. The efforts presented in our article demonstrate the feasibility of an accessible fatigue level detection system, which can be beneficial for objective fatigue assessment, design selection, and implementation of BSIEs in real-world scenarios.
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(This article belongs to the Special Issue Advances in Digital Technology Assisted Industrial Design)
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Open AccessArticle
Harnessing Heritage BIM for Enhanced Architectural Documentation of Ad Deir in Petra
by
Ahmad Baik and Yahya Alshawabkeh
Appl. Sci. 2024, 14(11), 4562; https://doi.org/10.3390/app14114562 (registering DOI) - 26 May 2024
Abstract
This paper investigates the utilisation of heritage building information modelling (BIM) in order to improve the architectural heritage documentation process at Ad Deir, a significant historical building within the UNESCO World Heritage site of Petra, Jordan. Ad Deir, also known as ‘The Monastery’,
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This paper investigates the utilisation of heritage building information modelling (BIM) in order to improve the architectural heritage documentation process at Ad Deir, a significant historical building within the UNESCO World Heritage site of Petra, Jordan. Ad Deir, also known as ‘The Monastery’, requires accurate and complete documentation for its preservation and effective management. Traditional documentation methods, such as manual surveys and 2D drawings, frequently fail to obtain the intricate details and complexity of heritage structures. This study proposes the use of heritage BIM, which involves creating a digital representation of Ad Deir by combining various data types such as geometric, material, and historical information. Laser scanning technology is used to capture the site in three dimensions, providing a precise representation of its current state. The point clouds are exported to the BIM workflow once they have been processed. The longitudinal and cross-sections of the point clouds revealed the dimensions of regular and irregular elements, which were then traced and modelled accurately. This digital model serves as a platform for future data integration, which may include historical documentation, architectural plans, and construction details. Creating accurate heritage BIM, which involves various levels of knowledge, improves quality control during conservation work and aids in informed decision-making.
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(This article belongs to the Special Issue Advances in BIM-Based Architecture and Civil Infrastructure Systems)
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Open AccessArticle
The Impact of Pulsed Electric Field Treatment and Shelf Temperature on Quality of Freeze-Dried Pumpkin
by
Oleksii Rastorhuiev, Aleksandra Matys, Artur Wiktor, Katarzyna Rybak, Alica Lammerskitten, Stefan Toepfl, Wolfram Schnäckel, Ewa Gondek and Oleksii Parniakov
Appl. Sci. 2024, 14(11), 4561; https://doi.org/10.3390/app14114561 (registering DOI) - 26 May 2024
Abstract
Pulsed electric field (PEF) treatment is known as a method that can intensify heat- and mass-transfer-based processes such as osmotic dehydration, drying, or freeze-drying. However, the literature about its impact on quality of freeze-dried products is limited to a few raw materials. The
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Pulsed electric field (PEF) treatment is known as a method that can intensify heat- and mass-transfer-based processes such as osmotic dehydration, drying, or freeze-drying. However, the literature about its impact on quality of freeze-dried products is limited to a few raw materials. The aim of this study was to analyze the effect of PEF on the cell disintegration index, selected bioactive compounds, and physical quality parameters of freeze-dried pumpkin. The final quality of the freeze-dried product was evaluated by residual moisture content, color analysis, total phenolic content, total carotenoid content, sugars content, and hygroscopic properties. The application of PEF treatment induced the disintegration of pumpkin cells even at low energy input (0.11 kJ/kg), and the saturation level of electroporation was reached after 4 kJ/kg. PEF treatment at 2 kJ/kg allowed 40% more total carotenoids to be retained in comparison to the untreated sample. Furthermore, all PEF-treated freeze-dried pumpkin samples exhibited lower sucrose content but had higher glucose and fructose contents in comparison to the reference samples. However, this effect was more pronounced when the shelf temperature was equal to 40 °C.
Full article
(This article belongs to the Special Issue Characterization of Bioactive Compounds and Antioxidants in Natural Products)
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Open AccessArticle
Numerical Study on the Mechanical Behavior of Sand–Rubber Mixtures under True Triaxial Tests
by
Yiming Liu, Xiang Gao, Huiru Dou, Liu Yang and Zhangshuaihang Cao
Appl. Sci. 2024, 14(11), 4560; https://doi.org/10.3390/app14114560 (registering DOI) - 25 May 2024
Abstract
A series of numerical true triaxial compression tests were carried out on rubber–sand mixtures (RSMs) by means of the 3D discrete element method to study the effect of the intermediate principal stress ratio b on the failure properties of RSMs with different rubber
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A series of numerical true triaxial compression tests were carried out on rubber–sand mixtures (RSMs) by means of the 3D discrete element method to study the effect of the intermediate principal stress ratio b on the failure properties of RSMs with different rubber contents (RCs), and to explore the effect mechanism from a microscopic point of view. The numerical simulation results show that as the intermediate principal stress ratio b increases and the peak deviator stress qpeak gradually increases, while the peak internal friction angle φb first increases and then decreases. The numerical simulation results were compared with four common strength criteria, including the modified Lade–Duncan criterion, the SMP criterion, the FKZ criterion and the DP criterion. The comparative analysis showed that the existing common criteria cannot accurately predict the damage state of RSMs, suggesting the necessity for further research. At the micro level, the combined effects of the intermediate principal stress ratio b values and RC on the micro-parameters, such as the coordination number, average normal stress between particles, probability density and anisotropy, were investigated.
Full article
(This article belongs to the Section Additive Manufacturing Technologies)
Open AccessArticle
Multidisciplinary Design Optimization of Cooling Turbine Blade: An Integrated Approach with R/ICSM
by
Wenjun Wang, Lan Xiang, Enzi Kang, Jiahao Xia, Shanguang Shi, Cunfu Wang and Cheng Yan
Appl. Sci. 2024, 14(11), 4559; https://doi.org/10.3390/app14114559 (registering DOI) - 25 May 2024
Abstract
This paper presents an efficient integrated multidisciplinary design optimization method for shaping a high-pressure cooling turbine blade in aero engines. This approach utilizes a novel regression/interpolation combination surrogate model (R/ICSM), facilitating comprehensive design optimization through collaborative coupling feature parameterization modeling and numerical simulation
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This paper presents an efficient integrated multidisciplinary design optimization method for shaping a high-pressure cooling turbine blade in aero engines. This approach utilizes a novel regression/interpolation combination surrogate model (R/ICSM), facilitating comprehensive design optimization through collaborative coupling feature parameterization modeling and numerical simulation analysis across various disciplines. The optimized blade adjusts the load distribution on its surface, effectively eliminating flow separation at the tip and trailing edge. Notably, the optimized blade achieves a 0.69% increase in isentropic efficiency while satisfying aerodynamic, strength, and structural constraints. This highlights the effectiveness and progressiveness of the multidisciplinary design optimization method for a cooling turbine blade based on the R/ICSM in enhancing overall performance. It offers a novel and feasible approach for turbine blade design optimization and provides valuable insights for future research and applications.
Full article
(This article belongs to the Section Aerospace Science and Engineering)
Open AccessArticle
Syn2Real Detection in the Sky: Generation and Adaptation of Synthetic Aerial Ship Images
by
Yaoyuan Wu, Weijie Guo, Zhuoyue Tan, Yifei Zhao, Quanxing Zhu, Liaoni Wu and Zhiming Guo
Appl. Sci. 2024, 14(11), 4558; https://doi.org/10.3390/app14114558 (registering DOI) - 25 May 2024
Abstract
Object detection in computer vision requires a sufficient amount of training data to produce an accurate and general model. However, aerial images are difficult to acquire, so the collection of aerial image datasets is a priority issue. Building on the existing research on
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Object detection in computer vision requires a sufficient amount of training data to produce an accurate and general model. However, aerial images are difficult to acquire, so the collection of aerial image datasets is a priority issue. Building on the existing research on image generation, the goal of this work is to create synthetic aerial image datasets that can be used to solve the problem of insufficient data. We generated three independent datasets for ship detection using engine and generative model. These synthetic datasets are rich in virtual scenes, ship categories, weather conditions, and other features. Moreover, we implemented domain-adaptive algorithms to address the issue of domain shift from synthetic data to real data. To investigate the application of synthetic datasets, we validated the synthetic data using six different object detection algorithms and three existing real-world, ship detection datasets. The experimental results demonstrate that the methods for generating synthetic aerial image datasets can complete the insufficient data in aerial remote sensing. Additionally, domain-adaptive algorithms could further mitigate the discrepancy from synthetic data to real data, highlighting the potential and value of synthetic data in aerial image recognition and comprehension tasks in the real world.
Full article
(This article belongs to the Special Issue AI-Based Image Processing: 2nd Edition)
Open AccessArticle
Research on the Capillary Filling Behavior of Liquid Solder Al-12Si under the Action of Electromagnetic Ultrasonic Wave
by
Guijuan Chen, Qianqian Gao, Mingxuan Zhang and Haonan Yu
Appl. Sci. 2024, 14(11), 4557; https://doi.org/10.3390/app14114557 (registering DOI) - 25 May 2024
Abstract
To address the issues of high cost, low welding efficiency, and complex processes in vacuum brazing, we proposed a method of electromagnetic ultrasonic (EU)-assisted brazing with Al-12Si solder to join SiC ceramic and TC4 alloy. The results showed that the maximum magnetic induction
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To address the issues of high cost, low welding efficiency, and complex processes in vacuum brazing, we proposed a method of electromagnetic ultrasonic (EU)-assisted brazing with Al-12Si solder to join SiC ceramic and TC4 alloy. The results showed that the maximum magnetic induction strength (MIS) on the surface of the liquid solder was 0.629 T when subjected to a static and alternating magnetic field (MF). Additionally, the combined action of MF and eddy current generated a downward Lorentz force (LF) in the liquid solder, with the maximum LF in the horizontal and vertical directions being 48.91 kN m−3 and 60.93 kN m−3, respectively. Under the influence of an EU wave, the liquid solder exhibited capillary filling (CF) behavior. At 26 ms, the maximum length of CF was 12.21 mm.
Full article
(This article belongs to the Special Issue Advanced Welding and Soldering Technologies for Metals and Alloys)
Open AccessArticle
Fixed-Point Iteration Method for Uncertain Parameters in Dynamic Response of Systems with Viscoelastic Elements
by
Magdalena Łasecka-Plura
Appl. Sci. 2024, 14(11), 4556; https://doi.org/10.3390/app14114556 (registering DOI) - 25 May 2024
Abstract
The paper presents a method for determining the dynamic response of systems containing viscoelastic damping elements with uncertain design parameters. A viscoelastic material is characterized using classical and fractional rheological models. The assumption is made that the lower and upper bounds of the
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The paper presents a method for determining the dynamic response of systems containing viscoelastic damping elements with uncertain design parameters. A viscoelastic material is characterized using classical and fractional rheological models. The assumption is made that the lower and upper bounds of the uncertain parameters are known and represented as interval values, which are then subjected to interval arithmetic operations. The equations of motion are transformed into the frequency domain using Laplace transformation. To evaluate the uncertain dynamic response, the frequency response function is determined by transforming the equations of motion into a system of linear interval equations. Nevertheless, direct interval arithmetic often leads to significant overestimation. To address this issue, this paper employs the element-by-element technique along with a specific transformation to minimize redundancy. The system of interval equations obtained is solved iteratively using the fixed-point iteration method. As demonstrated in the examples, this method, which combines the iterative solving of interval equations with the proposed technique of equation formulation, enables a solution to be found rapidly and significantly reduces overestimation. Notably, this approach has been applied to systems containing viscoelastic elements for the first time. Additionally, the proposed notation accommodates both parallel and series configurations of damping elements and springs within rheological models.
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Open AccessArticle
ADLBiLSTM: A Semantic Generation Algorithm for Multi-Grammar Network Access Control Policies
by
Jing Zhang and Xiaoyan Liang
Appl. Sci. 2024, 14(11), 4555; https://doi.org/10.3390/app14114555 (registering DOI) - 25 May 2024
Abstract
Abstract: Semantic generation of network access control policies can help network administrators accurately implement policies to achieve desired security objectives. Current semantic generation research mainly focuses on semantic generation of single grammar and lacks work on automatically generating semantics for different grammatical
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Abstract: Semantic generation of network access control policies can help network administrators accurately implement policies to achieve desired security objectives. Current semantic generation research mainly focuses on semantic generation of single grammar and lacks work on automatically generating semantics for different grammatical strategies. Generating semantics for different grammars is a tedious, inefficient, and non-scalable task. Inspired by sequence labeling in the field of natural language processing, this article models automatic semantic generation as a sequence labeling task. We propose a semantic generation algorithm named ADLBiLSTM. The algorithm uses a self-attention mechanism and double-layer BiLSTM to extract the features of security policies from different aspects, so that the algorithm can flexibly adapt to policies of different complexity without frequent modification. Experimental results showed that the algorithm has good performance and can achieve high accuracy in semantic generation of access control list (ACL) and firewall data and can accurately understand and generate the semantics of network access control policies.
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Open AccessArticle
Dynamic Land-Use Patterns and the Associated Impacts on Ecosystem Services Value in Putian City, China
by
Qingxia Peng, Dongqing Wu, Wenxiong Lin, Shuisheng Fan and Kai Su
Appl. Sci. 2024, 14(11), 4554; https://doi.org/10.3390/app14114554 (registering DOI) - 25 May 2024
Abstract
Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of
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Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of Landsat satellite images from 2000 to 2020, which allowed us to obtain land-use data for Putian City, China. Next, the geo-informatic Tupu model and the revised valuation model were used to explore the spatial attributes and ecological effects of land-use changes (LUCs). Subsequently, EEH (eco-economic harmony), ESTD (ecosystem services tradeoffs and synergies degree index), and ESDA (exploratory spatial data analysis) methods were employed to further analyze the coordination level, trade-offs, synergies, and spatial patterns of ecological-economic system development. The findings revealed that: (1) The land-use composition in Putian City was predominantly cultivated land and forest land, with other types of land intermixed. Concurrently, there was an ongoing trend of expansion in urban areas. (2) ESV in Putian City exhibited an upward trend, increasing from 15.4 billion CNY to 23.1 billion CNY from 2000 to 2020. (3) ESV exhibited an imbalance in spatial distribution, with high-high agglomeration areas concentrated in the central part of Putian City and the coastal region of Hanjiang District, while low-low agglomeration areas were prevalent in Xianyou County in the southwest, Xiuyu District along the coast, and Licheng District in the urban center. (4) Synergistic relationships among ESs predominated, though the trade-off relationship showed a tendency to expand. (5) The ecological environment and economic progress in Putian City collectively faced a region of potential risk. The findings of this study are intended to serve as a guide for improving the distribution of land resources and for developing strategies that ensure the sustainable development of the region’s socio-economic framework.
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(This article belongs to the Special Issue Ecosystems and Landscape Ecology)
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