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
CycleGAN-Driven MR-Based Pseudo-CT Synthesis for Knee Imaging Studies
Appl. Sci. 2024, 14(11), 4655; https://doi.org/10.3390/app14114655 (registering DOI) - 28 May 2024
Abstract
In the field of knee imaging, the incorporation of MR-based pseudo-CT synthesis holds the potential to mitigate the need for separate CT scans, simplifying workflows, enhancing patient comfort, and reducing radiation exposure. In this work, we present a novel DL framework, grounded in
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In the field of knee imaging, the incorporation of MR-based pseudo-CT synthesis holds the potential to mitigate the need for separate CT scans, simplifying workflows, enhancing patient comfort, and reducing radiation exposure. In this work, we present a novel DL framework, grounded in the development of the Cycle-Consistent Generative Adversarial Network (CycleGAN) method, tailored specifically for the synthesis of pseudo-CT images in knee imaging to surmount the limitations of current methods. Upon visually examining the outcomes, it is evident that the synthesized pseudo-CTs show an excellent quality and high robustness. Despite the limited dataset employed, the method is able to capture the particularities of the bone contours in the resulting image. The experimental Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Zero-Normalized Cross Correlation (ZNCC), Mutual Information (MI), Relative Change (RC), and absolute Relative Change (|RC|) report values of 30.4638 ± 7.4770, 28.1168 ± 1.5245, 0.9230 ± 0.0217, 0.9807 ± 0.0071, 0.8548 ± 0.1019, 0.0055 ± 0.0265, and 0.0302 ± 0.0218 (median ± median absolute deviation), respectively. The voxel-by-voxel correlation plot shows an excellent correlation between pseudo-CT and ground-truth CT Hounsfield units (m = 0.9785; adjusted = 0.9988; = 0.9849; p < 0.001). The Bland–Altman plot shows that the average of the differences is low (( = 0.7199 ± 35.2490; 95% confidence interval [−68.3681, 69.8079]). This study represents the first reported effort in the field of MR-based knee pseudo-CT synthesis, shedding light to significantly advance the field of knee imaging.
Full article
(This article belongs to the Special Issue Biomedical Imaging: From Methods to Applications)
Open AccessArticle
Why Are Explainable AI Methods for Prostate Lesion Detection Rated Poorly by Radiologists?
by
Mehmet A. Gulum, Christopher M. Trombley, Merve Ozen, Enes Esen, Melih Aksamoglu and Mehmed Kantardzic
Appl. Sci. 2024, 14(11), 4654; https://doi.org/10.3390/app14114654 (registering DOI) - 28 May 2024
Abstract
Deep learning offers significant advancements in the accuracy of prostate identification and classification, underscoring its potential for clinical integration. However, the opacity of deep learning models presents interpretability challenges, critical for their acceptance and utility in medical diagnosis and detection. While explanation methods
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Deep learning offers significant advancements in the accuracy of prostate identification and classification, underscoring its potential for clinical integration. However, the opacity of deep learning models presents interpretability challenges, critical for their acceptance and utility in medical diagnosis and detection. While explanation methods have been proposed to demystify these models, enhancing their clinical viability, the efficacy and acceptance of these methods in medical tasks are not well documented. This pilot study investigates the effectiveness of deep learning explanation methods in clinical settings and identifies the attributes that radiologists consider crucial for explainability, aiming to direct future enhancements. This study reveals that while explanation methods can improve clinical task performance by up to 20%, their perceived usefulness varies, with some methods being rated poorly. Radiologists prefer explanation methods that are robust against noise, precise, and consistent. These preferences underscore the need for refining explanation methods to align with clinical expectations, emphasizing clarity, accuracy, and reliability. The findings highlight the importance of developing explanation methods that not only improve performance but also are tailored to meet the stringent requirements of clinical practice, thereby facilitating deeper trust and a broader acceptance of deep learning in medical diagnostics.
Full article
(This article belongs to the Special Issue Artificial Intelligence in Medicine and Healthcare)
Open AccessArticle
ODGNet: Robotic Grasp Detection Network Based on Omni-Dimensional Dynamic Convolution
by
Xinghong Kuang and Bangsheng Tao
Appl. Sci. 2024, 14(11), 4653; https://doi.org/10.3390/app14114653 (registering DOI) - 28 May 2024
Abstract
In this article, to further improve the accuracy and speed of grasp detection for unknown objects, a new omni-dimensional dynamic convolution grasp detection network (ODGNet) is proposed. The ODGNet includes two key designs. Firstly, it integrates omni-dimensional dynamic convolution to enhance the feature
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In this article, to further improve the accuracy and speed of grasp detection for unknown objects, a new omni-dimensional dynamic convolution grasp detection network (ODGNet) is proposed. The ODGNet includes two key designs. Firstly, it integrates omni-dimensional dynamic convolution to enhance the feature extraction of the graspable region. Secondly, it employs a grasping region feature enhancement fusion module to refine the features of the graspable region and promote the separation of the graspable region from the background. The ODGNet attained an accuracy of 98.4% and 97.8% on the image-wise and object-wise subsets of the Cornell dataset, respectively. Moreover, the ODGNet’s detection speed can reach 50 fps. A comparison with previous algorithms shows that the ODGNet not only improves the grasp detection accuracy, but also satisfies the requirement of real-time grasping. The grasping experiments in the simulation environment verify the effectiveness of the proposed algorithm.
Full article
(This article belongs to the Special Issue Computer Vision in Automatic Detection and Identification)
Open AccessArticle
Experimental Parametric Study on Flow Separation Control Mechanisms around NACA0015 Airfoil Using a Plasma Actuator with Burst Actuation over Reynolds Numbers of 105–106
by
Noritsugu Kubo, Sagar Bhandari, Motofumi Tanaka, Taku Nonomura and Hirokazu Kawabata
Appl. Sci. 2024, 14(11), 4652; https://doi.org/10.3390/app14114652 (registering DOI) - 28 May 2024
Abstract
Dielectric barrier discharge plasma actuators (DBD-PAs) have the potential to improve the performance of fluid machineries such as aircrafts and wind turbines by preventing flow separation. In this study, to identify the multiple flow control mechanisms in high Reynolds number flow, parametric experiments
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Dielectric barrier discharge plasma actuators (DBD-PAs) have the potential to improve the performance of fluid machineries such as aircrafts and wind turbines by preventing flow separation. In this study, to identify the multiple flow control mechanisms in high Reynolds number flow, parametric experiments for an actuation parameter F+ with a wide range of Re values (105–106) for NACA0015 airfoil was conducted. We conducted wind tunnel tests by applying a DBD-PA to the flow field around a wing model at the leading edge. Lift characteristics, turbulent kinetic energy in the flow field, shear layer height, and the separation point of the boundary layer were evaluated based on pressure distributions on the wing surface and velocity of the flow field, with the effect of DBD-PA on the post-stall flow around the wing and the mechanism behind the increase in the lift coefficient CL analyzed based on these evaluation results. The following phenomena contributed to the increase in CL: (1) increase in turbulent kinetic energy; (2) increase in circulation; and (3) acceleration of the flow near the leading edge. Thus, this study effectively investigated the dependence of the increase in lift on F+ and the lift-increasing mechanism for a wide range of Re values.
Full article
Open AccessArticle
Validation of Dynamic Natural Ventilation Protocols for Optimal Indoor Air Quality and Thermal Adaptive Comfort during the Winter Season in Subtropical-Climate School Buildings
by
Antonio Sánchez Cordero, Sergio Gómez Melgar and José Manuel Andújar Márquez
Appl. Sci. 2024, 14(11), 4651; https://doi.org/10.3390/app14114651 (registering DOI) - 28 May 2024
Abstract
The need for energy-efficient buildings must be based on strong effective passive-design techniques, which coordinate indoor air quality and thermal comfort. This research describes the principles, simulation, implementation, and monitoring of two different natural cross-ventilation algorithm scenarios applied to a school-building case study
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The need for energy-efficient buildings must be based on strong effective passive-design techniques, which coordinate indoor air quality and thermal comfort. This research describes the principles, simulation, implementation, and monitoring of two different natural cross-ventilation algorithm scenarios applied to a school-building case study affected by a subtropical climate during the winter season. These ventilation protocols, the steady and dynamic versions, can control the carbon dioxide concentration and actuate the window openings according to pre-defined window-to-wall ratios. The implementation of the monitoring process during three non-consecutive days in the winter of 2021 validates the opening strategy to maintain carbon dioxide below 800 ppm, described by the protocol Hygiene Measures Against COVID-19, and the temperature within the comfort ranges suggested by the adaptive UNE-EN 16798. The study shows that a steady opening of 2.16% window-to-wall equivalent ratio can be enough to maintain the requested comfort and carbon dioxide conditions. The use of the dynamic window ratios, from 0.23% to 2.16%, modified according to the measured carbon dioxide concentration, can partially maintain the carbon dioxide below the required limits for ASHRAE 62.1, Hygiene Measures Against COVID-19 and UNE-EN 16798 between 48.28% to 74.14% of the time. However, the carbon dioxide limit proposed by RITE, 500 ppm, is only achieved for 15.52% of the time, which demonstrates the inadequacy of the natural ventilation to fulfil the standard. Further improvements in the dynamic control of the openings in these buildings could lead to lower carbon dioxide concentrations while maintaining the thermal comfort in mild winter climates.
Full article
(This article belongs to the Special Issue Energy Implications of Thermal Comfort in Buildings considering Climate Change)
Open AccessArticle
Visual and Haptic Guidance for Enhancing Target Search Performance in Dual-Task Settings
by
Gang Wang, Hung-Hsiang Wang and Gang Ren
Appl. Sci. 2024, 14(11), 4650; https://doi.org/10.3390/app14114650 (registering DOI) - 28 May 2024
Abstract
In complex environments, users frequently need to manage multiple tasks simultaneously, which poses significant challenges for user interface design. For instance, when driving, users must maintain continuous visual attention on the road ahead while also monitoring rearview mirrors and performing shoulder checks. These
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In complex environments, users frequently need to manage multiple tasks simultaneously, which poses significant challenges for user interface design. For instance, when driving, users must maintain continuous visual attention on the road ahead while also monitoring rearview mirrors and performing shoulder checks. These multitasking scenarios present substantial design challenges in effectively guiding users. To address these challenges, we focus on investigating and designing visual and haptic guidance systems to augment users’ performance. We initially propose the use of visual guidance, specifically employing a dynamic arrow as a guidance technique. Our evaluation shows that dynamic arrows significantly expedite both reaction and selection times. We further introduce and evaluate haptic feedback, which users perceive as more salient than visual guidance, leading to quicker responses when switching from primary to secondary tasks. This allows users to maintain visual attention on the primary task while simultaneously responding effectively to haptic cues. Our findings suggest that multimodal guidance, especially haptic guidance, can enhance both reaction time and user experience in dual-task environments, offering promising practical implications and guidelines for designing more user-friendly interfaces and systems.
Full article
(This article belongs to the Special Issue Human–Computer Interaction and Virtual Environments)
Open AccessArticle
Influence of Kluyveromyces lactis and Enterococcus faecalis on Obtaining Lactic Acid by Cheese Whey Fermentation
by
Carlos Gordillo-Andia, Jonathan Almirón, Jaime E. Barreda-Del-Carpio, Francine Roudet, Danny Tupayachy-Quispe and María Vargas
Appl. Sci. 2024, 14(11), 4649; https://doi.org/10.3390/app14114649 (registering DOI) - 28 May 2024
Abstract
Cheese whey is a byproduct of the cheese industry that causes high levels of pollution in the environment, but its high lactose content means that it can be used as a source to obtain lactic acid. In this study, two strains, one belonging
[...] Read more.
Cheese whey is a byproduct of the cheese industry that causes high levels of pollution in the environment, but its high lactose content means that it can be used as a source to obtain lactic acid. In this study, two strains, one belonging to a yeast and the other one to a bacteria (Kluyveromyces lactis and Enterococcus faecalis), were isolated from cheese whey and molecularly characterized, and the optimal growth conditions were determined. Then, using proteinized and deproteinized cheese whey, batch fermentation was carried out with the strains arranged in suspension and immobilized. The consumption of lactose and the production of lactic acid were measured through Brix degrees and acidity analysis. Afterwards, the lactic acid was purified, and its yield and physical and chemical characteristics were determined. It was proven that there were differences between each of the strains; arranged in free or encapsulated cells, the proteinized and deproteinized cheese wheys, under the same purification conditions, achieved different yields, colors, and densities of lactic acid. Immobilized Enterococcus faecalis had the highest yield (50.61 ± 34.94 g/L) using the deproteinized cheese whey compared to the immobilized Kluyveromyces lactis (35.70 ± 0.15 g/L) using the proteinized cheese whey.
Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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Open AccessArticle
Agroecological Transformation: Implementation of an Agroforestry System in a Construction Debris Area Focusing on Vegetables Development through Microbial Treatments
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Thiago Fernandes Rodrigues, Marina Paes Machado Itkes, Giovanne Brogiato, Victor Augusto Reis Marques, Valdir Martins, Carlos Orlando Villarraga and Elisa Esposito
Appl. Sci. 2024, 14(11), 4648; https://doi.org/10.3390/app14114648 (registering DOI) - 28 May 2024
Abstract
Soil microorganisms play an important role on plant development and the homogenization of soil microbiomes is harmful to agri-environments. It is essential that agricultural practices are carried out by taking soil microbiome preservation in consideration. Agroforestry systems are one of the most environmentally
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Soil microorganisms play an important role on plant development and the homogenization of soil microbiomes is harmful to agri-environments. It is essential that agricultural practices are carried out by taking soil microbiome preservation in consideration. Agroforestry systems are one of the most environmentally friendly agrosystems and its plant diversity directly influences the soil microbiome diversity. In this study, we tested the efficacy of the microbial consortium (MC) obtained from compost and the cyanobacteria Arthrospira platensis (Ap) compared with the application of the vermicompost tea (VT) and bokashi (Bk) in arugula, lettuce, beetroot, and carrot in two seasons in a recently implemented agroforestry system. We aimed to verify if MC and Ap could be new promising sustainable alternatives in vegetables production. The strategy can be broken down into three stages: (1) Green manure management: planting, cutting, griding, and incorporation in the soil, (2) agroforestry system implementation, and (3) treatment application in a completely randomized blocks design. The vegetables yield was measured. Nutritional traits and the plant root system were evaluated for arugula and lettuce. Greater plant yield, nutritional values, and plant root development were observed in the MC-treated plants; Ap and Bk had, in general, similar results. Our data show that both MC and Ap have potential to become a sustainable product for agricultural production.
Full article
(This article belongs to the Special Issue Microbial Diversity as a Driver of Plant Growth and Soil Health)
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Open AccessArticle
Novel Aluminum Alloy Tailored for Additive Manufacturing: Structural Characterization and Qualification Perspectives
by
Maurizio Arena, Bharat Mehta, Tommaso Tirelli, Paolo Ambrogiani, Martina Castaldo, Sven Bengtsson and Lars Nyborg
Appl. Sci. 2024, 14(11), 4647; https://doi.org/10.3390/app14114647 (registering DOI) - 28 May 2024
Abstract
The recent advances achieved in additive manufacturing (AM) technology demonstrate the potential to realize customized metal components, ensuring weight reduction opportunities. These benefits make AM attractive for high-cost aerospace applications, especially where high geometric complexity is required. In the context of an EU
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The recent advances achieved in additive manufacturing (AM) technology demonstrate the potential to realize customized metal components, ensuring weight reduction opportunities. These benefits make AM attractive for high-cost aerospace applications, especially where high geometric complexity is required. In the context of an EU research scenario, the H2020 MANUELA (Additive Manufacturing Using Metal Pilot Line) project promotes the development of new technologies for design optimization by enabling the application of novel materials in AM. This paper illustrates recent advances in a new aluminum alloy (Al-HS1) with high strength emphasizing all of the characterization steps at the coupon level. This material has been employed in the re-engineering of a conventional hydraulic manifold using a powder bed fusion-laser beam (PBF-LB) process. Both the simulations and structural tests allowed for proving its compliance and technological maturity with industrial standards and applicable airworthiness requirements.
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(This article belongs to the Special Issue Additive Manufacturing Technology and Applications for Aerospace)
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Open AccessArticle
Intelligent Transportation System Technologies, Challenges and Security
by
İsa Avcı and Murat Koca
Appl. Sci. 2024, 14(11), 4646; https://doi.org/10.3390/app14114646 (registering DOI) - 28 May 2024
Abstract
Intelligent Transportation Systems (ITS) first appeared in 1868 with traffic lights. With developing technology, the need to bring a smart approach to transportation applications within the scope of speed and environmental protection has emerged. Protecting ITS infrastructure against cyber attacks has become a
[...] Read more.
Intelligent Transportation Systems (ITS) first appeared in 1868 with traffic lights. With developing technology, the need to bring a smart approach to transportation applications within the scope of speed and environmental protection has emerged. Protecting ITS infrastructure against cyber attacks has become a matter of reputation for states. It is essential to provide the necessary technological infrastructure for the integrated operation of the systems used in ITS, especially geographical location, communication, and mapping. These technological developments bring cyber attacks, risks, and many dangers that should be avoided, especially on the systems used. This study examines ITS architecture, applications, communication technologies, and new trend technologies in detail. This study includes contributing to studies in the field of ITS and preventing attacks and incidents that may occur in terms of cyber security. The most important cyber attacks that may occur in ITS applications are included. In addition, the minimum security requirements that can be taken in ITS applications and infrastructures against these attacks are included.
Full article
(This article belongs to the Section Transportation and Future Mobility)
Open AccessArticle
Securing Edge Devices: Malware Classification with Dual-Attention Deep Network
by
Gasim Alandjani
Appl. Sci. 2024, 14(11), 4645; https://doi.org/10.3390/app14114645 (registering DOI) - 28 May 2024
Abstract
Detecting malware is a crucial defense mechanism against potential cyber-attacks. However, current methods illustrate significant limitations in achieving high performance while maintaining faster inference on edge devices. This study proposes a novel deep network with dual-attention feature refinement on a two-branch deep network
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Detecting malware is a crucial defense mechanism against potential cyber-attacks. However, current methods illustrate significant limitations in achieving high performance while maintaining faster inference on edge devices. This study proposes a novel deep network with dual-attention feature refinement on a two-branch deep network to learn real-time malware detection on edge platforms. The proposed method introduces lightweight spatial-asymmetric attention for refining the extracted features of its backbone and multi-head attention to correlate learned features from the network branches. The experimental results show that the proposed method can significantly outperform existing methods in quantitative evaluation. In addition, this study also illustrates the practicability of a lightweight deep network on edge devices by optimizing and deploying the model directly on the actual edge hardware. The proposed optimization strategy achieves a frame rate of over 545 per second on low-power edge devices.
Full article
(This article belongs to the Special Issue Security in Internet of Things (IoT): Challenges, Solutions and Future Directions)
Open AccessArticle
Cross-Domain Person Re-Identification Based on Feature Fusion Invariance
by
Yushi Zhang, Heping Song and Jiawei Wei
Appl. Sci. 2024, 14(11), 4644; https://doi.org/10.3390/app14114644 (registering DOI) - 28 May 2024
Abstract
Cross-domain person re-identification is a technique for identifying the same individual across different cameras or environments that necessitates the overcoming of challenges posed by scene variations, which is a primary challenge in person re-identification and a bottleneck for its practical applications. In this
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Cross-domain person re-identification is a technique for identifying the same individual across different cameras or environments that necessitates the overcoming of challenges posed by scene variations, which is a primary challenge in person re-identification and a bottleneck for its practical applications. In this paper, we learn the invariance model of cross-domain feature fusion in a labeled source domain and an unlabeled target domain. First, our method learns the global and local fusion features of a person in the source domain by means of supervised learning with no component label and only person identification and obtains the fusion features of the person in the source and target domains by means of unsupervised learning. Based on person fusion features, this paper introduces feature memory to store the fused target features and designs a cross-domain invariance loss function to improve the cross-domain adaptability of the person. Finally, this paper carries out cross-domain person re-identification verification experiments between the Market-1501 and DukeMTMC-reID datasets; the experimental results show that the proposed method achieves significant performance improvement in cross-domain person re-identification.
Full article
(This article belongs to the Special Issue Intelligent Data Mining, Analysis and Modeling Based on Machine Learning)
Open AccessReview
The Interaction of Microplastics and Microbioplastics with Soil and a Comparison of their Potential to Spread Pathogens
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Marek Trojan, Marek Koutný, Martin Brtnický, Jiří Holátko, Helena Zlámalová Gargošová, Jakub Fojt, Petra Procházková, Gabriela Kalčíková and Jiří Kučerík
Appl. Sci. 2024, 14(11), 4643; https://doi.org/10.3390/app14114643 (registering DOI) - 28 May 2024
Abstract
Microplastics contribute to various environmental issues and serve as carriers for a wide range of toxic compounds such as pesticides, pharmaceuticals, and metal ions. Consequently, there is a gradual shift towards replacing them with biodegradable plastics (bioplastics). However, biodegradable plastics require specific conditions
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Microplastics contribute to various environmental issues and serve as carriers for a wide range of toxic compounds such as pesticides, pharmaceuticals, and metal ions. Consequently, there is a gradual shift towards replacing them with biodegradable plastics (bioplastics). However, biodegradable plastics require specific conditions for complete biodegradation, and their biodeterioration often leads to the rapid production of smaller fragments, known as microbioplastics. In this review, we summarize selected issues related to the impact of plastic particles on soil properties and the soil microbiome. Findings from numerous studies indicate that both microplastics and microbioplastics induce adverse changes in soil microbiology, potentially increasing the abundance of soil-borne pathogens. Based on these observations, we argue that plastic particles could serve as carriers for colonies of soil-borne pathogens. Furthermore, the use of bioplastics may exacerbate this issue due to their easier and faster formation, increased support for biofilms, and more pronounced adverse effects on soil biota. However, further research is necessary to either substantiate or refute this perspective.
Full article
(This article belongs to the Special Issue Environmental Pollution and Bioremediation Technology)
Open AccessArticle
Improvements in the Wavelet Transform and Its Variations: Concepts and Applications in Diagnosing Gearbox in Non-Stationary Conditions
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Trong-Du Nguyen and Phong-Dien Nguyen
Appl. Sci. 2024, 14(11), 4642; https://doi.org/10.3390/app14114642 (registering DOI) - 28 May 2024
Abstract
Wavelet transform is a powerful time-frequency-based analysis method often used in gear fault diagnostics. The development of wavelet transform is closely linked to the improvement of resolution. When the high-frequency resolution allows for easy observation of different frequency components, it is a symptom
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Wavelet transform is a powerful time-frequency-based analysis method often used in gear fault diagnostics. The development of wavelet transform is closely linked to the improvement of resolution. When the high-frequency resolution allows for easy observation of different frequency components, it is a symptom of damage to an individual part of the machine. This study effectively applied the Wavelet analysis technique to diagnose faulty gearboxes operated in non-stationary conditions. This is a complex problem that usual diagnostic approaches need help to solve due to its non-linear character. This work conducted a simulation and real-world testing to show that the newest wavelet analysis techniques work well, showing that they can accurately find gear faults in gearboxes in non-stationary conditions. A thorough overview of the cutting-edge applications of wavelet transform in diagnosing faults in industrial gearbox systems was also given. This work also explained in detail the mathematical ideas behind the continuous wavelet transform, discrete wavelet transforms, and wavelet packet transform.
Full article
(This article belongs to the Section Applied Physics General)
Open AccessArticle
Research on an Index System for the Earthquake Disaster Resistance Capability of Highway Tunnels
by
Fei Wan, Nian Zhang, Zheng Lu, Yu Zhang, Xuehui Yan and Jiang Yu
Appl. Sci. 2024, 14(11), 4641; https://doi.org/10.3390/app14114641 (registering DOI) - 28 May 2024
Abstract
To evaluate the earthquake disaster resistance capability of highway tunnels, it is necessary to study an index system for the earthquake disaster resistance capability of highway tunnels. This paper uses a literature research method. The damage of highway tunnels in 12 earthquake disasters
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To evaluate the earthquake disaster resistance capability of highway tunnels, it is necessary to study an index system for the earthquake disaster resistance capability of highway tunnels. This paper uses a literature research method. The damage of highway tunnels in 12 earthquake disasters recorded in detail in China and abroad was investigated. According to the types of hazard-beating bodies and damage forms, 17 seismic damage scenes of highway tunnels are classified. According to different damage scenes, the fault tree analysis model is used to identify the damage-causing factors. Combined with the industry standards, norms and research results related to the earthquake resistance of highway tunnels, the evaluation indices are analyzed from three perspectives: engineering geological factors, tunnel structural factors and operation management factors. According to the principle of index system construction, a four-level index system is constructed, which takes the earthquake disaster resistance capability of highway tunnels as the target layer; engineering geological factors, tunnel structural factors and operation management factors as the criterion layer indices; 12 indicators as the index layer and 35 specific indicators. The established index system for the earthquake disaster resistance capability of highway tunnels has strong scientific, rational and application value and can provide a reference for the evaluation of the earthquake disaster resistance capability of highway tunnels and can also provide important support for the safe operation and sustainable development of highway tunnels.
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(This article belongs to the Special Issue Advances in Tunnel and Underground Construction)
Open AccessArticle
Development of Technology for the Bioleaching of Uranium in a Solution of Bacterial Immobilization
by
Bauyrzhan Shiderin, Yerkin Bektay, Gaukhar Turysbekova, Akmurat Altynbek and Maxat Bektayev
Appl. Sci. 2024, 14(11), 4640; https://doi.org/10.3390/app14114640 - 28 May 2024
Abstract
This study presents findings regarding the kinetics of ferrous iron oxidation in solution mediated by Acidithiobacillus ferrooxidans bacteria within a continuous-flow bioreactor employing diverse types of immobilizers. The objective is to augment the rate of ferrous iron oxidation in solutions utilizing an immobilizer
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This study presents findings regarding the kinetics of ferrous iron oxidation in solution mediated by Acidithiobacillus ferrooxidans bacteria within a continuous-flow bioreactor employing diverse types of immobilizers. The objective is to augment the rate of ferrous iron oxidation in solutions utilizing an immobilizer for Acidithiobacillus ferrooxidans strains. Immobilization represents a promising avenue for enhancing the efficiency of Fe2⁺ oxidation via acidophilic ferrooxidizing bacteria, leading to a several-fold increase in oxidation rate. A comparative analysis was conducted to evaluate the efficacy of different types of immobilizer in facilitating iron oxidation within a continuous-flow bioreactor, including the application of wood chips coated with Fe(OH)3. The results indicate that wood chips coated with iron hydroxide serve as effective type of immobilizer, facilitating the robust attachment of Acidithiobacillus ferrooxidans via electrostatic interactions between negatively charged bacteria and positively charged surfaces. Experimental investigations were conducted using novel immobilization matrices in pilot-scale tests simulating the underground borehole leaching (UBL) of uranium. The bioactivation of leaching solutions enhances the efficiency and environmental compatibility of UBL compared to conventional chemical oxidation methods. The relationships between redox potential and ferric iron content in bioactivated solutions during the UBL of uranium were delineated. The significance of this study lies in its elucidating the pivotal role of Fe2⁺ oxidation in uranium extraction processes, particularly in the context of UBL. By employing bioactivation mediated by Acidithiobacillus ferrooxidans, the study demonstrates not only enhanced uranium extraction efficiency, but also markedly improved environmental sustainability compared to traditional chemical oxidation methods. The findings reveal crucial correlations between redox potential and ferric iron concentration in bioactivated solutions.
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(This article belongs to the Special Issue Sustainable Materials and Waste Recovery)
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State of the Art on Relative Permeability Hysteresis in Porous Media: Petroleum Engineering Application
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Yubo Lan, Ping Guo, Yong Liu, Shuoshi Wang, Sheng Cao, Jiang Zhang, Wenjing Sun, Dongyan Qi and Qiang Ji
Appl. Sci. 2024, 14(11), 4639; https://doi.org/10.3390/app14114639 - 28 May 2024
Abstract
This paper delivers an examination of relative permeability hysteresis in porous media in the field of petroleum engineering, encompassing mathematical modeling, experimental studies, and their practical implications. It explores two-phase and three-phase models, elucidating the generation of scanning curves and their applications in
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This paper delivers an examination of relative permeability hysteresis in porous media in the field of petroleum engineering, encompassing mathematical modeling, experimental studies, and their practical implications. It explores two-phase and three-phase models, elucidating the generation of scanning curves and their applications in various porous materials. Building on the research of traditional relative permeability hysteresis models, we have incorporated literature on forward calculations of relative permeability based on digital rock core models. This offers a new perspective for studying the hysteresis effect in relative permeability. Additionally, it compiles insights from direct relative permeability and flow-through experiments, accentuating the methodologies and key findings. With a focus on enhanced oil recovery (EOR), carbon capture, utilization and sequestration (CCUS), and hydrogen storage applications, the paper identifies existing research voids and proposes avenues for future inquiry, laying the groundwork for advancing recovery techniques in oil and gas sectors.
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(This article belongs to the Section Energy Science and Technology)
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Open AccessArticle
Optimizing the Shape of the Spinning Electrode for Needleless Coaxial Electrospinning
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Ondrej Batka, Josef Skrivanek and Jaroslav Beran
Appl. Sci. 2024, 14(11), 4638; https://doi.org/10.3390/app14114638 - 28 May 2024
Abstract
This work deals with designing the optimal shape of the spinning electrode to optimize the distribution of the electric field and suppress the formation of corona discharges on the surface of the electrode during electrospinning using direct current (DC). Some of the solutions
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This work deals with designing the optimal shape of the spinning electrode to optimize the distribution of the electric field and suppress the formation of corona discharges on the surface of the electrode during electrospinning using direct current (DC). Some of the solutions used for electrospinning are solved in flammable solvents, such as PVB; therefore, corona discharges are hazardous, as they cause sparks that can cause fires and explosions. The shape optimization was carried out on a plate weir electrode, which uses the principle of free surface spinning. Using the electric field simulation, an analysis of the plate weir spinner was carried out, and its optimization was aimed at minimizing the occurrence of corona discharges, which negatively affect the spinning process. Based on the simulations’ results, the spinning electrode design parameters were adjusted so that an even distribution of the electric field over the entire active surface of the electrode was ensured, and the incidence of corona discharges was prevented. A laboratory experiment was used to validate the function of the design changes in the spinning electrode.
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(This article belongs to the Section Nanotechnology and Applied Nanosciences)
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Open AccessArticle
Vibration Reduction on Circular Disks with Vibroacoustic Metamaterials
by
Sebastian Rieß, Ron Schmidt, William Kaal, Heiko Atzrodt and Sven Herold
Appl. Sci. 2024, 14(11), 4637; https://doi.org/10.3390/app14114637 - 28 May 2024
Abstract
Vibroacoustic metamaterials represent an innovative technology developed for broadband vibration reduction. They consist of an array of local resonators and are able to reduce vibrations over a wide frequency range, commonly referred to as a stop band. Vibroacoustic metamaterials may be a promising
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Vibroacoustic metamaterials represent an innovative technology developed for broadband vibration reduction. They consist of an array of local resonators and are able to reduce vibrations over a wide frequency range, commonly referred to as a stop band. Vibroacoustic metamaterials may be a promising strategy to reduce out-of-plane vibrations of thin-walled, disk-shaped structures, such as saw blades. However, their behavior in rotating systems has not yet been fully understood. In this study, a vibroacoustic metamaterial integrated into a circular disk for the reduction of out-of-plane vibrations is experimentally investigated in the rotating and non-rotating state. Derived from the predominant frequency range of noise emitted by saw blades, a vibroacoustic metamaterial with a numerically predicted stop band in the frequency range from 2000 Hz to 3000 Hz, suitable for integration into a circular disk, is designed. The resonators of the metamaterial are realized by cutting slots into the disk using a waterjet cutting machine. To experimentally examine the structural dynamic behavior, the disk is excited by an impulse hammer and observed by a stationary optical velocity sensor on a rotor dynamics test stand. The results of the rotating and the non-rotating state are compared. The measurements are carried out at two different radii and at speeds up to 3000 rpm. A distinct stop band characteristic is shown in the desired frequency range from 2000 Hz to 3000 Hz in the rotating and non-rotating state. No significant shift of the stop band frequency range was observed during rotation. However, adjacent modes were observed to propagate into the stop band frequency range. This work contributes to a better understanding of the behavior of vibroacoustic metamaterials in the rotating state and enables future applications of vibroacoustic metamaterials for vibration reduction in rotating, disk-shaped structures such as saw blades, brake disks or gears.
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(This article belongs to the Special Issue New Advances in Acoustic and Mechanical Metamaterials: Design and Applications)
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Open AccessArticle
The Injury Risk Prediction of Firefighters with Biomechanical Parameters during Single- and Double-Leg Jumps
by
Guanzheng Zhang, Pengyu Tao, Jingwen Chen, Ziyao Wang and Rui Xu
Appl. Sci. 2024, 14(11), 4636; https://doi.org/10.3390/app14114636 - 28 May 2024
Abstract
The incidence of knee injuries during firefighter training is high, but there is a lack of research on predictive factors and risk assessment for such injuries. Biomechanical assessments can provide a better understanding of how the body’s load changes during exercise, which may
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The incidence of knee injuries during firefighter training is high, but there is a lack of research on predictive factors and risk assessment for such injuries. Biomechanical assessments can provide a better understanding of how the body’s load changes during exercise, which may alter the risk of injury. Ten firefighters were recruited for our study. Each participant completed the FMS test and the single- and double-leg jump tasks. Motion information was collected and musculoskeletal models of the participants were constructed using OpenSim 4.4 to obtain the joint angle and joint moment. The peak GRF and CoM-CoP angle were also calculated. The findings showed a significantly larger PKFM (p = 0.0195), VAFM (p = 0.0039), and peak AP GRF (p = 0.0039) during the single-leg jump. The opposite performance was observed for KFA (p = 0.0098) and MPA (p = 0.0273). A stepwise multiple linear regression analysis was used to explore the relationship between these parameters and both the FMS score and the times of injuries. The risk of injury is higher in the single-leg jump compared to the double-leg jump. The biomechanical parameters of these two jumps can be used to assess sports injuries and to provide methods and references for injury risk monitoring during firefighter occupational training.
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(This article belongs to the Section Biomedical Engineering)
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