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
Solvothermal Treatment of Micron-Sized Commercial SrAl2O4:Eu2+, Dy3+ Phosphors and One-Step Preparation of Nanophosphors for Fingerprint Imaging
Appl. Sci. 2024, 14(9), 3929; https://doi.org/10.3390/app14093929 (registering DOI) - 04 May 2024
Abstract
Preparing submicron and nanoscale phosphors with good optical properties for practical applications is a challenging task for current inorganic long afterglow luminescent materials. This study utilized commercialized SrAl2O4:Eu2+, Dy3+ phosphors (SAOED) as raw materials and employed
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Preparing submicron and nanoscale phosphors with good optical properties for practical applications is a challenging task for current inorganic long afterglow luminescent materials. This study utilized commercialized SrAl2O4:Eu2+, Dy3+ phosphors (SAOED) as raw materials and employed solvents with lower polarity or non-polar solvents for dynamic solvothermal treatment. The commercialized phosphor’s overall average particle size was reduced from 42.3 μm to 23.6 μm while maintaining the fluorescence intensity at 91.39% of the original sample. Additionally, the study demonstrated the applicability of the dynamic solvothermal method to most other commercialized inorganic phosphors. The experiment produced a high-brightness nano-sized phosphor with a yield of 5.64%. The average diameter of the phosphor was 85 nm, with an average thickness of 16 nm. The quantum efficiency of the phosphor was 74.46% of the original sample. The fingerprint imaging results suggest that the nano-sized phosphors have potential for practical applications.
Full article
(This article belongs to the Section Applied Thermal Engineering)
Open AccessArticle
Efficient Crowd Anomaly Detection Using Sparse Feature Tracking and Neural Network
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Sarah Altowairqi, Suhuai Luo, Peter Greer and Shan Chen
Appl. Sci. 2024, 14(9), 3928; https://doi.org/10.3390/app14093928 (registering DOI) - 04 May 2024
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Crowd anomaly detection is crucial in enhancing surveillance and crowd management. This paper proposes an efficient approach that combines spatial and temporal visual descriptors, sparse feature tracking, and neural networks for efficient crowd anomaly detection. The proposed approach utilises diverse local feature extraction
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Crowd anomaly detection is crucial in enhancing surveillance and crowd management. This paper proposes an efficient approach that combines spatial and temporal visual descriptors, sparse feature tracking, and neural networks for efficient crowd anomaly detection. The proposed approach utilises diverse local feature extraction methods, including SIFT, FAST, and AKAZE, with a sparse feature tracking technique to ensure accurate and consistent tracking. Delaunay triangulation is employed to represent the spatial distribution of features in an efficient way. Visual descriptors are categorised into individual behaviour descriptors and interactive descriptors to capture the temporal and spatial characteristics of crowd dynamics and behaviour, respectively. Neural networks are then utilised to classify these descriptors and pinpoint anomalies, making use of their strong learning capabilities. A significant component of our study is the assessment of how dimensionality reduction methods, particularly autoencoders and PCA, affect the feature set’s performance. This assessment aims to balance computational efficiency and detection accuracy. Tests conducted on benchmark crowd datasets highlight the effectiveness of our method in identifying anomalies. Our approach offers a nuanced understanding of crowd movement and patterns by emphasising both individual and collective characteristics. The visual and local descriptors facilitate high-level analysis by closely relating to semantic information and crowd behaviour. The analysis observed shows that this approach offers an efficient framework for crowd anomaly detection, contributing to improved crowd management and public safety. The proposed model achieves accuracy of 99.5 %, 96.1%, 99.0% and 88.5% in the UMN scenes 1, 2, and 3 and violence in crowds datasets, respectively.
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Open AccessArticle
Evaluation of Antimutagenic and Antioxidant Properties in Fomes fomentarius L.: Potential Development as Functional Food
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Chang-Gyun Park and Heung-Bin Lim
Appl. Sci. 2024, 14(9), 3927; https://doi.org/10.3390/app14093927 (registering DOI) - 04 May 2024
Abstract
Numerous studies derived from medicinal herbs have been conducted to explore bioactive compounds as potential alternatives to synthetic drugs, aiming to mitigate harmful side effects and alleviate economic burdens. In this study, we assessed the safety and potential biological activities of extracts from
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Numerous studies derived from medicinal herbs have been conducted to explore bioactive compounds as potential alternatives to synthetic drugs, aiming to mitigate harmful side effects and alleviate economic burdens. In this study, we assessed the safety and potential biological activities of extracts from Fomes fomentarius L. (FFL). The FFL extracts were obtained through various ethanol concentrations, as follows: 0%, 30%, 50%, 70%, and 100%, respectively. All extracts did not induce mutagenicity even up to 5 mg/plate concentration. In the assessment of antioxidant activity, only the hot water extract exhibited weaker antioxidant activity than the other ethanol extracts. Notably, all extracts exhibited significant antimutagenetic effects only with a metabolically active enzyme system (S9 mix). The condition of 70% ethanol extract displayed the most robust antimutagenic activity; thus, the extract was sequentially fractionated with solvents of varying polarities to isolate inhibitory components. After the fractionization, the diethyl ether and butanol fractions effectively suppressed the growth of mutated colonies, suggesting that those such as essential oils, vitamins, alkaloids, and flavonoids can be considered major active compounds. Overall, our study demonstrated that FFL extracts induce potent antioxidant and antimutagenic effects. Further investigations are warranted to verify specific active compounds which induce an antimutagenic effect. Our findings provide valuable insights into FFL as a promising source for potential functional food development.
Full article
(This article belongs to the Special Issue Advances in Biological Activities of Natural Products)
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Open AccessArticle
Transverse Spin Hall Effect and Twisted Polarization Ribbons at the Sharp Focus
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Victor V. Kotlyar, Alexey A. Kovalev, Alexey M. Telegin, Elena S. Kozlova, Sergey S. Stafeev, Alexander Kireev, Kai Guo and Zhongyi Guo
Appl. Sci. 2024, 14(9), 3926; https://doi.org/10.3390/app14093926 (registering DOI) - 04 May 2024
Abstract
In this work, using a Richards-Wolf formalism, we derive explicit analytical relationships to describe vectors of the major and minor axes of polarization ellipses centered in the focal plane when focusing a cylindrical vector beam of integer order n. In these beams, the
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In this work, using a Richards-Wolf formalism, we derive explicit analytical relationships to describe vectors of the major and minor axes of polarization ellipses centered in the focal plane when focusing a cylindrical vector beam of integer order n. In these beams, the major axis of a polarization ellipse is found to lie in the focal plane, with the minor axis being perpendicular to the focal plane. This means that the polarization ellipse is perpendicular to the focal plane, with its polarization vector rotating either clockwise or anticlockwise and forming “photonic wheels”. Considering that the wave vector is also perpendicular to the focal plane, we conclude that the polarization ellipse and the wave vector are in the same plane, so that at some point these can coincide, which is uncharacteristic of transverse electromagnetic oscillations. In a cylindrical vector beam, the spin angular momentum vector lies in the focal plane, so when making a circle centered on the optical axis, at some sections, the handedness of the spin vector and circular motion are the same, being opposite elsewhere. This effect may be called an azimuthal transverse spin Hall effect, unlike the familiar longitudinal spin Hall effect found at the sharp focus. The longitudinal spin Hall effect occurs when opposite-sign longitudinal projections of the spin angular momentum vector are spatially separated in the focal plane. In this work, we show that for the latter, there are always an even number of spatially separated regions and that, when making an axis-centered circle, the major-axis vector of polarization ellipse forms a two-sided twisted surface with an even number of twists.
Full article
(This article belongs to the Section Optics and Lasers)
Open AccessArticle
Hemp Flour as a Functional Ingredient for the Partial Replacement of Nitrites in a Minced Meat Model: Effect on Nutrient Composition, Antioxidant Profile and Sensory Characteristics
by
Georgios Papatzimos, Paraskevi Mitlianga, Zoitsa Basdagianni and Eleni Kasapidou
Appl. Sci. 2024, 14(9), 3925; https://doi.org/10.3390/app14093925 (registering DOI) - 04 May 2024
Abstract
Consumers are becoming increasingly concerned about synthetic preservatives like nitrites in meat, prompting the meat industry to explore alternatives in order to lower nitrite levels. This study investigated the effects of incorporating hemp flour on the chemical and shelf-life characteristics of minced meat
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Consumers are becoming increasingly concerned about synthetic preservatives like nitrites in meat, prompting the meat industry to explore alternatives in order to lower nitrite levels. This study investigated the effects of incorporating hemp flour on the chemical and shelf-life characteristics of minced meat products with reduced nitrite content. Three types of products were prepared: HF0 (control) (0% hemp flour, 30 mg/kg NaNO2), HF4 (4% hemp flour, 15 mg/kg NaNO2), and HF6 (6% hemp flour, 15 mg/kg NaNO2). Analyses were conducted on proximate composition, fatty acid composition, antioxidant properties, lipid oxidation, colour, texture, and sensory characteristics. The addition of hemp flour at 6% reduced moisture content and influenced ash and sodium chloride levels in minced meat products. Despite the favorable fatty acid profile of hemp flour, its inclusion did not significantly alter the composition of the products. However, it did lead to significantly lower levels of lipid oxidation and modified the antioxidant capacity. Colour attributes were affected, with a higher hemp flour content resulting in colour deterioration. Cooking loss increased with a higher hemp flour content, and the minced meat products were significantly harder. Visual and olfactory sensory evaluation indicated that there were no significant differences in most traits, suggesting consumer acceptance of hemp-flour-enriched minced meat products. Overall, this study highlights the potential of hemp as a functional ingredient in minced meat products, also exhibiting the ability to reduce lipid oxidation.
Full article
(This article belongs to the Special Issue Advances in Meat Quality and Processing)
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Open AccessCase Report
The Occurrence of a Rare Mandibular Retromolar Triangle Schwannoma and Its Differentiation from Other Rare and Atypical Oral Cavity Tumours
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Kamil Nelke, Maciej Janeczek, Edyta Pasicka, Krzysztof Żak, Szczepan Barnaś, Jan Nienartowicz, Grzegorz Gogolewski, Irma Maag and Maciej Dobrzyński
Appl. Sci. 2024, 14(9), 3924; https://doi.org/10.3390/app14093924 (registering DOI) - 04 May 2024
Abstract
Cone-beam computed tomography (CBCT) remains the diagnostic modality of choice. The involvement of the cortical bone and adjacent teeth can be easily established via CBCT. Magnetic resonance can be helpful in the estimation of any other soft-tissue tumour spread within this anatomical area.
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Cone-beam computed tomography (CBCT) remains the diagnostic modality of choice. The involvement of the cortical bone and adjacent teeth can be easily established via CBCT. Magnetic resonance can be helpful in the estimation of any other soft-tissue tumour spread within this anatomical area. The soft, hard-tissue, or mixed aetiology of tumours requires a differential diagnosis and accurate evaluation. If such pathologies arise, an adequate biopsy or incisional biopsy is essential to evaluate the type of tumour histopathologically. The occurrence of some neural tumours in the oral cavity is rare. Schwannomas (SCs), like some neuromas and other types of neural tumours, are rare and atypical. During clinical examination, a smooth, sponge-like, elastic mass could indicate other small salivary gland tumours rather than an oral neural tumour. Such pathologies of neural origins are quite rare and are uncommon findings in the oral cavity; therefore, their appearance may be conflated with other more typical benign or malignant tumours in the oral cavity. Establishing the status of bone via CBCT, the tooth involvement and the composition of the cortical bone may be helpful for establishing the best treatment of choice. The presented case report describes a rare schwannoma localised at the mandibular retromolar trigone.
Full article
(This article belongs to the Special Issue Orthodontics and Maxillofacial Surgery)
Open AccessArticle
Exploring Flexural Strength Variation in Polymeric Materials for Provisional Fixed Prosthetic Structures: Comparative Analysis with and without Reinforcement through Laboratory Experimentation and Statistical Evaluation
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Mariana Dimova-Gabrovska, Todor Uzunov, Angela Gusiyska, Dobromira Shopova, Iva Taneva, Ivan Gerdzhikov and Stefan Rangelov
Appl. Sci. 2024, 14(9), 3923; https://doi.org/10.3390/app14093923 (registering DOI) - 04 May 2024
Abstract
Provisional fixed partial dentures represent a critical phase in dental treatment, necessitating heightened mechanical durability, particularly in comprehensive and extended treatment plans. Strengthening these structures with various reinforcing materials offers a method to enhance their resilience. Utilizing a three-point testing methodology on standardized
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Provisional fixed partial dentures represent a critical phase in dental treatment, necessitating heightened mechanical durability, particularly in comprehensive and extended treatment plans. Strengthening these structures with various reinforcing materials offers a method to enhance their resilience. Utilizing a three-point testing methodology on standardized trial specimens allows for a comparative assessment of various materials and reinforcement techniques for pre-prosthetic applications. This study aims to validate and assess the significance of integrating different reinforcing materials into standardized test bodies. The study focuses on test specimens comprising three types of unreinforced laboratory and clinical polymers for provisional constructions (n = 6)—heat-cured PMMA (Superpont C+B, Spofa Dental, Czech Republic), CAD-CAM prefabricated PMMA (DD temp MED, Dental Direkt, Germany), CAD-CAM printing resin (Temporary CB Resin, FormLabs, USA), self-polymerizing PEMA (DENTALON plus, Kulzer, Germany), light-polymerizing composite (Revotek LC, GC, Japan), and dual-polymerizing composite (TempSpan, Pentron, USA). Additionally, laboratory polymers are evaluated in groups with five types of reinforcing filaments (n = 15)—Glass Fiber (Fiber Splint One-Layer, Polydentia, Switzerland), Polyethylene thread (Ribbond Regular 4.0 mm, Ribbond Inc., USA), triple-stranded chrome-cobalt wire for splinting 015″ (Leone S.p.a., Italy), Aesthetic ligature wire 012” (Leone S.p.a., Italy), and Glass Fiber coated with light-cured composite 8.5 × 0.2 mm (Interlig, Angelus, Brazil). Analysis of the data using Generalized Linear Models (GLMs) reveals that the experimental bodies, produced via the subtractive digital method using PMMA (DD temp MED, Dental Direkt GmbH, Germany) as the polymer and glass filaments as the reinforcement, exhibit superior mechanical properties, particularly when pre-wetted with Interlig liquid composite (Angelus, Brazil).
Full article
(This article belongs to the Section Applied Dentistry and Oral Sciences)
Open AccessArticle
Experimental Study on the Relationship between Time-Varying Uplift Displacement and Grout Diffusion in Sand
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Huan-Xiao Hu, Wei Cao, Chao Deng and Yu-Fan Lu
Appl. Sci. 2024, 14(9), 3922; https://doi.org/10.3390/app14093922 (registering DOI) - 04 May 2024
Abstract
Traditional model tests for soil and rock materials face challenges in observing the slurry diffusion within the soil mass, hindering the understanding of the relationship between grouting-induced ground deformation and grout diffusion. This study conducts grouting diffusion model tests using a self-developed experimental
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Traditional model tests for soil and rock materials face challenges in observing the slurry diffusion within the soil mass, hindering the understanding of the relationship between grouting-induced ground deformation and grout diffusion. This study conducts grouting diffusion model tests using a self-developed experimental setup on both ordinary and transparent sand. We investigate cement slurry diffusion patterns, distribution characteristics, and temporal variations in ground uplift displacement during the grouting process. By leveraging a visualization grouting model and non-intrusive displacement measurements, we directly observe and verify the changes in cement slurry diffusion and ground displacement in transparent sand. The results indicate the following: during non-steady grouting in sand, slurry diffusion progresses from low-pressure infiltration to medium-pressure compaction, culminating in high-pressure fracturing; ground uplift displacement curves exhibit a consistent “step-like” increase with grouting time, featuring accelerated growth after each step; and visualization tests reveal a strong correlation between grouting pressure, slurry diffusion, and corresponding uplift displacement. Distinct features in the grouting pressure plot align with the acceleration phases of the displacement; at a water–cement ratio (w/c) of 0.8, the stratum’s vertical deformation shows a symmetric “higher in the middle, lower on the sides” distribution. As the burial depth decreases, the stratum’s uplift displacement tends to flatten horizontally, especially at w/c = 0.8 and 1.2.
Full article
(This article belongs to the Special Issue Recent Advances in Soft Soil Engineering)
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Open AccessArticle
Cardiorespiratory Response to Workload Volume and Ergonomic Risk: Automotive Assembly Line Operators’ Adaptations
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Dania Furk, Luís Silva, Mariana Dias, Carlos Fujão, Phillip Probst, Hui Liu and Hugo Gamboa
Appl. Sci. 2024, 14(9), 3921; https://doi.org/10.3390/app14093921 (registering DOI) - 04 May 2024
Abstract
Repetitive tasks can lead to long-term cardiovascular problems due to continuous strain and inadequate recovery. The automobile operators on the assembly line are exposed to these risks when workload volume changes according to the workstation type. However, the current ergonomic assessments focus primarily
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Repetitive tasks can lead to long-term cardiovascular problems due to continuous strain and inadequate recovery. The automobile operators on the assembly line are exposed to these risks when workload volume changes according to the workstation type. However, the current ergonomic assessments focus primarily on observational and, in some cases, biomechanical methods that are subjective and time-consuming, overlooking cardiorespiratory adaptations. This study aimed to analyze the cardiorespiratory response to distinct workload volumes and ergonomic risk (ER) scores for an automotive assembly line. Sixteen male operators (age = 38 ± 8 years; BMI = 25 ± 3 kg·m2) volunteered from three workstations (H1, H2, and H3) with specific work cycle duration (1, 3, and 5 min respectively). Electrocardiogram (ECG), respiratory inductance plethysmography (RIP), and accelerometer (ACC) data were collected during their shift. The results showed significant differences from the first to the last 10 min, where H3 had its SDRRi reduced (p = 0.014), H1’s phase synchrony and H2’s coordination between thoracic and abdominal movements decreased (p < 0.001, p = 0.039). In terms of ergonomic risk, the moderate-high rank showed a reduction in SDRRi (p = 0.037) and moderate-risk activities had diminished phase synchrony (p = 0.018) and correlation (p = 0.004). Thus, the explored parameters could have the potential to develop personalized workplace adaptation and risk assessment systems.
Full article
(This article belongs to the Special Issue Biomechanics and Motor Control on Human Movement Analysis)
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Open AccessArticle
Dielectric Properties and Magnetoelectric Effect of Bi7Fe3Ti3O21 Ceramic Material Doped with Gadolinium Ions
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Diana Szalbot, Joanna A. Bartkowska, Jolanta Makowska, Maciej Chrunik, Katarzyna Osińska and Małgorzata Adamczyk-Habrajska
Appl. Sci. 2024, 14(9), 3920; https://doi.org/10.3390/app14093920 (registering DOI) - 04 May 2024
Abstract
Pure Bi7Fe3Ti3O21 ceramic material and gadolinium ion (Gd3+)-doped ones were prepared by solid-state reaction method using simple oxides. The findings of the XRD measurements confirmed the initial author’s assumption that the dopant ions substituted
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Pure Bi7Fe3Ti3O21 ceramic material and gadolinium ion (Gd3+)-doped ones were prepared by solid-state reaction method using simple oxides. The findings of the XRD measurements confirmed the initial author’s assumption that the dopant ions substituted in perovskite blocks influenced the dimensions of the unit cell parameters. All obtained materials are single-phase and show an orthorhombic structure with the Fm2m space group. Microstructure studies show that the admixture gadolinium doping changes the microstructure of the base material, changing grain shapes from plate-like to rounded. The temperature dependences of the electric permittivity have shown the existence of a maximum, the temperature location of which depends on both the frequency and the concentration of Gd3+ ions. The highest values of electric permittivity were characteristic of the material with an admixture of Gd3+ ions in the amount of x = 0.6 (f = 1 kHz), and the lowest values were for material with x = 0.2 (f = 1 kHz). Studies of the magnetoelectric effect have shown that the strongest coupling between magnetic and electrical properties was demonstrated by a material doped with Ga3+ ions in the amount of x = 0.2, for which the magnetoelectric coupling coefficient is equal to α = 12.58·10−9 s/m.
Full article
(This article belongs to the Special Issue Novel Ceramic Materials: Processes, Properties and Applications)
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Open AccessArticle
Few-Shot Federated Learning: A Federated Learning Model for Small-Sample Scenarios
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Junfeng Tian, Xinyao Chen and Shuo Wang
Appl. Sci. 2024, 14(9), 3919; https://doi.org/10.3390/app14093919 (registering DOI) - 04 May 2024
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Traditional federated learning relies heavily on mature datasets, which typically consist of large volumes of uniformly distributed data. While acquiring extensive datasets is relatively straightforward in academic research, it becomes prohibitively expensive in practical applications, especially in emerging or specialized medical fields characterized
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Traditional federated learning relies heavily on mature datasets, which typically consist of large volumes of uniformly distributed data. While acquiring extensive datasets is relatively straightforward in academic research, it becomes prohibitively expensive in practical applications, especially in emerging or specialized medical fields characterized by data scarcity. This poses a significant challenge. To address this issue, our study introduces a federated learning model that integrates few-shot learning techniques and is complemented by personalized knowledge distillation to further enhance the model’s classification accuracy. This innovative approach significantly reduces the dependence on large-scale datasets, enabling efficient model training under limited data conditions. Our experimental evaluations conducted on small-scale datasets, including Omniglot, FC100, and mini-ImageNet, indicate that our model surpasses existing state-of-the-art federated learning models in terms of accuracy, achieving a substantial improvement. Specifically, on the FC100 dataset, the classification accuracy of the conventional federated learning algorithm FedAvg was merely 19.6%, whereas the method proposed in this study achieved a classification accuracy of 41%, representing an improvement of more than double. This advancement not only highlights our model’s superiority in alleviating the challenges of limited data availability, but also expands the applicability of federated learning to a broader range of applications.
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Open AccessArticle
Discrete Element Study on the Mechanical Response of Soft Rock Considering Water-Induced Softening Effect
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Chi Liu, Xiaoli Liu, Haoyang Peng, Enzhi Wang and Sijing Wang
Appl. Sci. 2024, 14(9), 3918; https://doi.org/10.3390/app14093918 (registering DOI) - 04 May 2024
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Soft rocks are prone to softening upon contact with water, and their rapid deterioration in mechanical properties is a significant cause of instability and failure soft rock masses. Besides, the macroscopic mechanical response of rocks is closely related to the mineral composition and
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Soft rocks are prone to softening upon contact with water, and their rapid deterioration in mechanical properties is a significant cause of instability and failure soft rock masses. Besides, the macroscopic mechanical response of rocks is closely related to the mineral composition and microstructure. The purpose of this research is to consider the heterogeneity factors and softening effects, and systematically investigate the influence of confining pressure and softening time on the damage and failure characteristics of soft rocks. The Voronoi polygons generated using a built-in Voronoi diagram algorithm and contact elements (the substances with cementing capacity) of UDEC discrete element method are employed to represent the clastic grains and interfacial cemented bonding (ICB) structures in soft rock. Based on the Voronoi probabilistic method, the grain-based discrete element model (GB-DEM) considering the softening effect is established by introducing a meso-scale softening damage factor, along with a detailed calibration method for meso-scale parameters. The damage parameters such as the crack initiation threshold, the crack damage threshold, the damage degree, and the tensile and shear crack ratio are then analyzed. The study results indicate that the simulated strengths of the heterogeneous models under different water immersion time are in good agreement with the experimental results. The thresholds for crack initiation and damage, the proportions of tensile and shear cracks, and the degree of damage are positively correlated with the confining pressure. The attenuation patterns of the crack initiation threshold and damage threshold in the heterogeneous models with water immersion time are highly consistent with the meso-scale softening damage factor. The damage parameters show a trend of increasing first and then decreasing with the extension of water immersion time. The cement–cement contact elements are the main locations for crack initiation and propagation. The research outcomes have significant theoretical and practical implications for understanding and predicting the mechanical behavior of soft rocks under a water–rock interaction.
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Open AccessArticle
Effects of Amyloid Beta (Aβ) Oligomers on Blood–Brain Barrier Using a 3D Microfluidic Vasculature-on-a-Chip Model
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Samuel Chidiebere Uzoechi, Boyce Edwin Collins, Cody Joseph Badeaux, Yan Li, Sang Su Kwak, Doo Yeon Kim, Daniel Todd Laskowitz, Jin-Moo Lee and Yeoheung Yun
Appl. Sci. 2024, 14(9), 3917; https://doi.org/10.3390/app14093917 (registering DOI) - 04 May 2024
Abstract
The disruption of the blood–brain barrier (BBB) in Alzheimer’s Disease (AD) is largely influenced by amyloid beta (Aβ). In this study, we developed a high-throughput microfluidic BBB model devoid of a physical membrane, featuring endothelial cells interacting with an extracellular matrix (ECM). This
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The disruption of the blood–brain barrier (BBB) in Alzheimer’s Disease (AD) is largely influenced by amyloid beta (Aβ). In this study, we developed a high-throughput microfluidic BBB model devoid of a physical membrane, featuring endothelial cells interacting with an extracellular matrix (ECM). This paper focuses on the impact of varying concentrations of Aβ1–42 oligomers on BBB dysfunction by treating them in the luminal. Our findings reveal a pronounced accumulation of Aβ1–42 oligomers at the BBB, resulting in the disruption of tight junctions and subsequent leakage evidenced by a barrier integrity assay. Additionally, cytotoxicity assessments indicate a concentration-dependent increase in cell death in response to Aβ1–42 oligomers (LC50 ~ 1 µM). This study underscores the utility of our membrane-free vascular chip in elucidating the dysfunction induced by Aβ with respect to the BBB.
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(This article belongs to the Collection BioMEMS)
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Open AccessArticle
A Multi-Stance Detection Method by Fusing Sentiment Features
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Weidong Huang and Jinyuan Yang
Appl. Sci. 2024, 14(9), 3916; https://doi.org/10.3390/app14093916 (registering DOI) - 04 May 2024
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Stance information has a significant influence on market strategy, government policy, and public opinion. Users differ not only in their polarity but also in the degree to which they take a stand. The traditional classification of stances is quite simple and cannot fully
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Stance information has a significant influence on market strategy, government policy, and public opinion. Users differ not only in their polarity but also in the degree to which they take a stand. The traditional classification of stances is quite simple and cannot fully depict the diversity of stances. At the same time, traditional approaches ignore user sentiment features when expressing their stances. As a result, this paper develops a multi-stance detection model by fusing sentiment features. First, a five-category stance indicator system is built based on the LDA model, then sentiment features are extracted from the reviews using the sentiment lexicon, and finally, stance detection is implemented using a hybrid neural network model. The experiment shows that the proposed method can classify stances into five categories and perform stance detection more accurately.
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Open AccessArticle
Quarterly Percentual Change in Height, Weight, Body Fat and Muscle Mass in Young Football Players of Different Categories
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Moisés Falces-Prieto, Ricardo Martín-Moya, Gabriel Delgado-García, Rui Miguel Silva, Halil Ibrahim Ceylan and Juan Carlos de la Cruz-Márquez
Appl. Sci. 2024, 14(9), 3915; https://doi.org/10.3390/app14093915 (registering DOI) - 04 May 2024
Abstract
The purpose of this study was to compare the change of Body Composition (BC) (height, weight, body fat percentage and muscle mass) as a function of the trimester and category in a sample of young soccer players. Data collection was performed in five
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The purpose of this study was to compare the change of Body Composition (BC) (height, weight, body fat percentage and muscle mass) as a function of the trimester and category in a sample of young soccer players. Data collection was performed in five consecutive seasons (2016–2021). The sample consisted of 741 young male football players of different categories (Under 14 year old (U14), U15, U16, U17 and U18) belonging to a high-performance football academy. Considering the trimestral change of all the raw anthropometrics variables a set of new variables called the trimestral change in percentage (TC) of each raw variable was computed. Two-way repeated measures ANOVA (including the raw anthropometric variables as dependent and trimester and the age-category as independent) revealed differences for the anthropometric variables (p value < 0.001 in all cases), concluding that the effect of trimester reaches conventional levels of statistical significance. The trimester by age in contrast was significant (p < 0.05) in all raw variables except for the height. Considering the TC variables, the variable height-TC showed an increase (p value < 0.05) while the variable muscle mass-TC was near the significative value (p = 0.09). In this case the interaction trimester by age category was not significative (p > 0.05 in all cases). It seems that height suffers more changes in the first trimester but the weight, body fat percentage and muscle mass changes more in the second and third trimester. It is important to modulate the training load according to the trimester-specific response, although these improvements may vary according to factors such as genetics, diet, sleep and the specific training.
Full article
(This article belongs to the Special Issue New Trends in Training, Performance, Coaching and Health in Sports Science)
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Open AccessArticle
Design and Implementation of an Automated Disaster-Recovery System for a Kubernetes Cluster Using LSTM
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Ji-Beom Kim, Je-Bum Choi and Eun-Sung Jung
Appl. Sci. 2024, 14(9), 3914; https://doi.org/10.3390/app14093914 - 03 May 2024
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With the increasing importance of data in modern business environments, effective data management and protection strategies are gaining increasing research attention. Data protection in a cloud environment is crucial for safeguarding information assets and maintaining sustainable services. This study introduces a system structure
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With the increasing importance of data in modern business environments, effective data management and protection strategies are gaining increasing research attention. Data protection in a cloud environment is crucial for safeguarding information assets and maintaining sustainable services. This study introduces a system structure that integrates Kubernetes management platforms with backup and restoration tools. This system is designed to immediately detect disasters and automatically recover applications from another Kubernetes cluster. The experimental results show that this system executes the restoration process within 15 s without human intervention, enabling rapid recovery. This, in turn, significantly reduces the potential for delays and errors compared to manual recovery processes, thereby enhancing data management and recovery efficiency in cloud environments. Moreover, our research model predicts the CPU utilization of the cluster using Long Short-Term Memory (LSTM). The necessity of scheduling through this predict is made clearer through comparison with experiments without scheduling, demonstrating its ability to prevent performance degradation. This research highlights the efficiency and necessity of automatic recovery systems in cloud environments, setting a new direction for future research.
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Open AccessEditorial
Applied Maritime Engineering and Transportation Problems 2022
by
Lucjan Gucma, Krzysztof Naus, Marko Perkovič and Cezary Specht
Appl. Sci. 2024, 14(9), 3913; https://doi.org/10.3390/app14093913 - 03 May 2024
Abstract
It is probable that the term marine traffic engineering (MTE) was first used by Toyoda and Fuji [...]
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(This article belongs to the Special Issue Applied Maritime Engineering and Transportation Problems 2022)
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Open AccessArticle
Degree of Hamstring Extensibility and Its Relationship with Pelvic Tilt in Professional Cyclists
by
José M. Muyor, Pedro A. López-Miñarro, Fernando Alacid and Daniel López-Plaza
Appl. Sci. 2024, 14(9), 3912; https://doi.org/10.3390/app14093912 - 03 May 2024
Abstract
The cyclist’s posture is typically characterized by a trunk flexion position to reach the handlebar of the bike. The pelvis serves as the base of the spine, and its tilt has been associated with the degree of extensibility of the hamstring, particularly in
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The cyclist’s posture is typically characterized by a trunk flexion position to reach the handlebar of the bike. The pelvis serves as the base of the spine, and its tilt has been associated with the degree of extensibility of the hamstring, particularly in flexion postures of the trunk. The aim of this study was to determine whether, in professional cyclists, the degree of hamstring extensibility influences the pelvic tilt maintained while seated on the bicycle with support from the three handlebar grips of the road bike, as well as in other positions of the bicycle. To evaluate pelvic tilt, all participants were measured using the Spinal Mouse system. The results revealed statistically significant differences in pelvic tilt among the six positions assessed (p ≤ 0.05). Furthermore, the degree of hamstring extensibility of the hamstrings presented a strong and positive correlation with pelvic tilt in standing posture (r = 0.82), Sit-and-Reach (r = 0.76), and Toe-Touch (r = 0.88). However, the degree of hamstring extensibility showed no significant correlations with pelvic tilt in any posture maintained on the bicycle.
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(This article belongs to the Special Issue Research of Sports Medicine on Health Care)
Open AccessArticle
Explainable Artificial Intelligence to Support Work Safety in Forestry: Insights from Two Large Datasets, Open Challenges, and Future Work
by
Ferdinand Hoenigsberger, Anna Saranti, Anahid Jalali, Karl Stampfer and Andreas Holzinger
Appl. Sci. 2024, 14(9), 3911; https://doi.org/10.3390/app14093911 - 03 May 2024
Abstract
Forestry work, which is considered one of the most demanding and dangerous professions in the world, is claiming more and more lives. In a country as small as Austria, more than 50 forestry workers are killed in accidents every year, and the number
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Forestry work, which is considered one of the most demanding and dangerous professions in the world, is claiming more and more lives. In a country as small as Austria, more than 50 forestry workers are killed in accidents every year, and the number is increasing rapidly. This serves as a catalyst for us to implement more stringent measures for workplace safety in order to achieve the sustainability objective of SDG 3, which focuses on health and well-being. This study contributes to the analysis of occupational accidents and focuses on two large real-world datasets from both the Austrian Federal Forests (ÖBf) and the Austrian Workers’ Compensation Board (AUVA). Decision trees, random forests, and fully connected neural networks are used for the analysis. By exploring different interpretation methods, this study sheds light on the decision-making processes ranging from basic association to causal inference and emphasizes the importance of causal inference in providing actionable insights for accident prevention. This paper contributes to the topic of explainable AI, specifically in its application to occupational safety in forestry. As a result, it introduces novel aspects to decision support systems in this application domain.
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(This article belongs to the Section Ecology Science and Engineering)
Open AccessArticle
Perception versus Historical Knowledge in Baccalaureate: A Comparative Study Mediated by Augmented Reality and Historical Thinking
by
Alejandro López-García, Javier J. Maquilón-Sánchez and Pedro Miralles-Sánchez
Appl. Sci. 2024, 14(9), 3910; https://doi.org/10.3390/app14093910 - 03 May 2024
Abstract
Numerous studies have shown that a traditional model persists in the teaching of history, in which students are not allowed to think for themselves and are assigned a passive role based on the mere memorisation of information. This reality is in opposition to
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Numerous studies have shown that a traditional model persists in the teaching of history, in which students are not allowed to think for themselves and are assigned a passive role based on the mere memorisation of information. This reality is in opposition to the technological and technical boom taking place in the current educational context and to the enhancement of innovative strategies and methodologies that mark the role that students must occupy as protagonists of their own learning. This paper aims to compare the perceptions and historical knowledge of 93 baccalaureate students (16–18 years of age) following the implementation of an intervention programme based on active learning situations mediated by augmented reality and historical thinking skills. A quasi-experimental quantitative design with a non-equivalent control group was employed to meet these objectives. The results showed higher scores in the perception and knowledge of students in the experimental group compared with those in the control group. This line of work should be continued in the future with new studies to corroborate these findings, prioritising pedagogical models based on student activity and protagonism via the use of technology and critical thinking.
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(This article belongs to the Special Issue Artificial Intelligence and Information Visualization in Social and Industrial Systems)
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