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Shape-Memory Property Acting as a Switch to Change the Surface Property of the Film
Image-Based Musculoskeletal Models to Accurately Reproduce a Maximum Voluntary Isometric Contraction Test In Silico
PFAS: The Journey from Wonder Chemicals to Environmental Nightmares and the Search for Solutions
The Use of Electric Vehicles to Support the Needs of the Electricity Grid: A Systematic Literature Review
1D-CLANet: A Novel Network for NLoS Classification in UWB Indoor Positioning System

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 - Q1 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.8 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the first half of 2024).
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: 2.5 (2023); 5-Year Impact Factor: 2.7 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2076-3417

Latest Articles

16 pages, 3290 KiB

Open AccessArticle

Cmpk2 Gene and Protein Expression in Saliva or Salivary Glands of Dyslipidemic Mice

by Baiyan Zhang, Akiyo Kawamoto, Masato Nakagawa, Yoshitomo Honda and Kazuya Takahashi

Appl. Sci. 2024, 14(24), 12004; https://doi.org/10.3390/app142412004 (registering DOI) - 21 Dec 2024

Salivary biomarkers are promising molecules for diagnosing systemic diseases. Cytidine/uridine monophosphate kinase 2 (CMPK2) is associated with various systemic diseases. However, little is known about the role of the CMPK2 gene in saliva and dyslipidemia. This study investigated the relationship between serum lipid [...] Read more.

Salivary biomarkers are promising molecules for diagnosing systemic diseases. Cytidine/uridine monophosphate kinase 2 (CMPK2) is associated with various systemic diseases. However, little is known about the role of the CMPK2 gene in saliva and dyslipidemia. This study investigated the relationship between serum lipid levels and Cmpk2 mRNA expression in the saliva of dyslipidemic mice. Additionally, immunofluorescence staining was employed to assess the localization of the CMPK2 protein in the submandibular gland. Two types of dyslipidemic mice were utilized: mice fed a high-fat and high-cholesterol (HFHC) diet and genetically dyslipidemic ApoE-deficient mice. The mice at 9 to 46 weeks were analyzed for serum lipid levels, Cmpk2 mRNA expression in saliva, and CMPK2 protein localization in the submandibular glands. Both dyslipidemic mice displayed elevated low-density lipoprotein cholesterol and total cholesterol in serum. ApoE-deficient mice apparently exhibited increased Cmpk2 expression in saliva. Immunofluorescence staining indicated that CMPK2 proteins were primarily localized in the serous acini, potentially associated with the secretion of Cmpk2 mRNA in saliva. These findings suggest that Cmpk2 mRNA increases and is detectable in the saliva of dyslipidemic mice, providing a viable experimental model to assess the potential use of CMPK2 as a biomarker for dyslipidemia. Full article

(This article belongs to the Special Issue Recent Advancements in Biomarkers for Noncommunicable Diseases)

15 pages, 10271 KiB

Open AccessArticle

Flow-Induced Fatigue Damage of Large Francis Turbines Under Multiple Operating Loads

by Pinghu Liu, Xingxing Huang, Tianyu Yang and Zhengwei Wang

Appl. Sci. 2024, 14(24), 12003; https://doi.org/10.3390/app142412003 (registering DOI) - 21 Dec 2024

The Francis runner is a critical component of the Francis turbine generator unit, playing a central role in converting water energy into rotating mechanical energy that drives the generator in hydropower stations. In-depth analyses of the flow characteristics of the Francis runner under [...] Read more.

The Francis runner is a critical component of the Francis turbine generator unit, playing a central role in converting water energy into rotating mechanical energy that drives the generator in hydropower stations. In-depth analyses of the flow characteristics of the Francis runner under various operating conditions and avoiding fatigue damage of the Francis runner are crucial to the reliability and efficiency of hydropower operation. In this paper, the flow dynamics of a large Francis turbine runner are analyzed under three representative loading conditions—low partial load, high partial load, and full load—and the flow-induced stress of the runner is analyzed under these loading conditions. It was found that the maximum static and dynamics stresses of the runner at three representative loading conditions are located at the chamfered surface where the blade trailing edge connects to the runner crown. The maximum static stresses of the Francis runner are 284 MPa, 352 MPa, and 381 MPa at low partial load, high partial load, and full load, respectively, and they are above the allowable stress limits, as half of the yield stress of the runner material of 550 MPa. The peak-to-peak values of runner dynamic stress at low partial load, high partial load, and full load are 15 MPa, 25 MPa, and 14.6 MPa, respectively. The high stress invoked by the unsteady flow under various loading conditions in this runner was the cause of the fatigue breakage of the runner blades. The results of this investigation have important reference values for mitigating fatigue damage in similar Francis runners and optimizing unit operation. Full article

(This article belongs to the Special Issue Advanced Technologies in Rotating Machinery: Design, Modeling, Manufacturing, Testing, and Operation)

19 pages, 1643 KiB

Open AccessArticle

Analysis of Selected IT Tools for Environmental Product Assessment

by Damian Grajewski, Anna Dudkowiak, Miłosz Wiśniewski and Ewa Dostatni

Appl. Sci. 2024, 14(24), 12002; https://doi.org/10.3390/app142412002 (registering DOI) - 21 Dec 2024

This article discusses the subject of the environmental assessment of products based on specific methods (LCA, ReCiPe, and SM2013) and tools (GaBi, SimaPro, and Sustainable Minds). The aim of this work was to analyze selected IT tools for supporting such an assessment. Assumptions [...] Read more.

This article discusses the subject of the environmental assessment of products based on specific methods (LCA, ReCiPe, and SM2013) and tools (GaBi, SimaPro, and Sustainable Minds). The aim of this work was to analyze selected IT tools for supporting such an assessment. Assumptions and criteria were adopted, based on which specific IT tools were selected for a comparative analysis. Then, an environmental assessment of reference products was carried out using three different IT tools. The structure of the products was prepared in such a way that the parts and subassemblies met two basic requirements. First, they were made of construction materials that are generally available and used in industry. The second requirement was that the technologies for manufacturing these parts included as many frequently used technological processes as possible. This allowed for a comparison of the results of estimated environmental assessments generated by selected IT tools. As a result, the strengths and weaknesses of each of the IT tools were identified. Full article

(This article belongs to the Section Environmental Sciences)

14 pages, 5606 KiB

Open AccessArticle

Artificial Heart Valve Scaffold Based on Electrospun PCL/PU Three-Layer Composite Fibers

by Xu Gao, Zhong Liu, Zhiwei Zhang, Yuan Gao, Jun Zhang and Yunze Long

Appl. Sci. 2024, 14(24), 12001; https://doi.org/10.3390/app142412001 (registering DOI) - 21 Dec 2024

Abnormal heart valve function is a major cause of heart disease and is often associated with high rates of morbidity and mortality from heart disease. Focusing on the field of valve replacement, tissue-engineered heart valves are becoming popular and attracting more attention. In [...] Read more.

Abnormal heart valve function is a major cause of heart disease and is often associated with high rates of morbidity and mortality from heart disease. Focusing on the field of valve replacement, tissue-engineered heart valves are becoming popular and attracting more attention. In this work, an artificial heart valve scaffold based on polycaprolactone/polyurethane (PCL/PU) three-layer composite fibers was prepared by 3D printing and electrospinning, including an inner PCL layer, a middle PCL/PU layer, and an outer PCL layer. The obtained valve scaffold had strong circumferential mechanical properties when PCL/PU = 1:2, and its elastic modulus was 14.7 MPa, similar to that of natural valve. The heart valve scaffold had good cytocompatibility, and the final cell survival rate was 99.8% after 14 days of cell culture. The layered structure makes the artificial heart valve more similar to the natural structure of the mammalian heart, which is conducive to cell proliferation and differentiation, and provides a reference solution for interventional treatment of heart valves. Full article

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18 pages, 7089 KiB

Open AccessArticle

Analysis of Vegetation Coverage Changes and Influencing Factors in Aksu, Xinjiang, China (2000–2020): A Comparative Study of Climate Factors and Urban Development

by Zhimin Feng, Haiqiang Xin, Hairong Liu, Yong Wang and Junhai Wang

Appl. Sci. 2024, 14(24), 12000; https://doi.org/10.3390/app142412000 (registering DOI) - 21 Dec 2024

The ecological environment is fundamental to human survival and development, and China has seen a historical shift from localized to widespread improvements in its ecological conditions. Aksu, a typical ecologically sensitive region in Xinjiang, China, is significant for the study of vegetation dynamics [...] Read more.

The ecological environment is fundamental to human survival and development, and China has seen a historical shift from localized to widespread improvements in its ecological conditions. Aksu, a typical ecologically sensitive region in Xinjiang, China, is significant for the study of vegetation dynamics and their driving factors, which is crucial for ecological conservation. This study evaluates the spatiotemporal changes in vegetation coverage in Aksu from 2000 to 2020 using long-term Normalized Difference Vegetation Index (NDVI) data and trend analysis. Additionally, this study explores key factors influencing vegetation changes through correlation analysis with temperature, precipitation, and nighttime light data. The results indicate the following: (1) vegetation coverage in Aksu exhibits significant spatial heterogeneity, with annual NDVI increasing at a rate of 0.83% per year (p < 0.05); (2) the influence of temperature and precipitation on NDVI was weakly correlated from 2000 to 2020; and (3) a strong positive correlation was found between nighttime light intensity and NDVI, suggesting that urban development plays a dominant role in vegetation change, while temperature and precipitation have comparatively minor impacts. The findings provide a scientific basis for ecological conservation and sustainable development in the region. Full article

(This article belongs to the Special Issue Geographic Information System and Remote Sensing Applications in Digital Earth)

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15 pages, 3475 KiB

Open AccessArticle

NMR and LC-MS-Based Metabolomics to Study the Effect of Surfactin on the Metabolome of Flax

by Omar Abdelaziz Benamar, Mathie Craquelin, Damien Herfurth, Roland Molinié, Jean-Xavier Fontaine, Akeapot Srifa, Marc Ongena, François Mesnard and Ophélie Fliniaux

Appl. Sci. 2024, 14(24), 11999; https://doi.org/10.3390/app142411999 (registering DOI) - 21 Dec 2024

Flax (Linum usitatissimum) is a versatile plant used in a range of applications, from textiles to nutrition. Surfactin, a cyclic lipopeptide biosurfactant produced by bacteria such as Bacillus subtilis, has potential as a biocontrol agent or as a plant defense inducer [...] Read more.

Flax (Linum usitatissimum) is a versatile plant used in a range of applications, from textiles to nutrition. Surfactin, a cyclic lipopeptide biosurfactant produced by bacteria such as Bacillus subtilis, has potential as a biocontrol agent or as a plant defense inducer in agriculture. This work aims to determine the effects of surfactin treatment at two kinetic points on the metabolism of flax hydroponic cultures, using advanced metabolomic techniques, including ¹H NMR and LC-MS analyses. Surfactin, detected in the roots, has a significant local impact on the metabolic profiles of flax roots, leading mainly to a higher content of cyanogenic compounds and amino acids and a lower content of carbohydrates. Surfactin, which is not detected in the aerial parts, also induces contrasted changes in amino acids, sugars, and secondary metabolite accumulation between stems and leaves. Surfactin treatment of flax leads to both a local and systemic effect on flax metabolism. These changes suggest that plant response to surfactin treatment could induce an enhanced plant defense. This could suggest potential applications of surfactin in the agricultural field as a biostimulant or biocontrol agent, to limit the use of chemical compounds in culture, and to limit their negative impact on both health and the environment. Full article

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16 pages, 1643 KiB

Open AccessArticle

A Case Study of Frequency Analysis of the Contribution of a Single Number Quantity to the Introduction of Rubber Ball Impact Sound and Changes in Assessment Methods

by Hee-Mo Goo, Soon-Seong Moon and Jun-Oh Yeon

Appl. Sci. 2024, 14(24), 11998; https://doi.org/10.3390/app142411998 (registering DOI) - 21 Dec 2024

This study analyzed the effects of changes in the inter-floor noise assessment system in multi-family housing in Korea on heavy-weight impact sound performance assessment. By comparing the existing pre-approval system with the newly introduced post-verification system, we focused on the effects of the [...] Read more.

This study analyzed the effects of changes in the inter-floor noise assessment system in multi-family housing in Korea on heavy-weight impact sound performance assessment. By comparing the existing pre-approval system with the newly introduced post-verification system, we focused on the effects of the evaluation criteria, impact sources, and frequency band considerations on the single numerical evaluation quantities (L’_i,Fmax,AW and L’_iA,Fmax) and contribution rates by frequency band. For the analysis, impact sounds were measured using a bang machine used in the existing pre-approval system and a rubber ball used in the post-verification system, and the performance of the floor structure was evaluated in the 1/1 and 1/3 octave bands. As a result, the pre-approval system showed a high contribution rate mainly in the 63 Hz band, but the post-verification system expanded the contribution rate to the mid-low frequency band of 63–160 Hz. In particular, the evaluation method using the A-weighted maximum floor impact sound level (L’_iA,Fmax) of the post-verification system was found to reflect the performance in the mid- and high-frequency band of 125–250 Hz more effectively. The post-verification system enables a more accurate evaluation of the performance of high-frequency bands that were overlooked in the existing system, thereby enabling a realistic response to the mitigation of inter-floor noise. Accordingly, construction companies must meet stricter performance standards in floor structure design and resilient materials development, in accordance with the new regulations. For example, designs utilizing sound-absorbing ceiling structures and high-performance resilient materials are expected to be effective in reducing heavy-impact noise. This study provides important basic data for tracking the performance of floor structures according to changes in the system, and selecting key frequency bands for reducing heavy-impact noise. In addition, it emphasizes the need to continuously monitor the performance of multi-family housing constructed under the new system and to derive effective design strategies for solving inter-floor noise problems. In the future, it will be necessary to expand the usability of the results of this study through additional studies targeting more diverse floor plans and floor structures. Full article

(This article belongs to the Special Issue New Design Approaches of Acoustical Environments)

20 pages, 3109 KiB

Open AccessArticle

Galvanic Skin Response and Photoplethysmography for Stress Recognition Using Machine Learning and Wearable Sensors

by Alina Nechyporenko, Marcus Frohme, Yaroslav Strelchuk, Vladyslav Omelchenko, Vitaliy Gargin, Liudmyla Ishchenko and Victoriia Alekseeva

Appl. Sci. 2024, 14(24), 11997; https://doi.org/10.3390/app142411997 (registering DOI) - 21 Dec 2024

This study investigates stress recognition using galvanic skin response (GSR) and photoplethysmography (PPG) data and machine learning, with a new focus on air raid sirens as a stressor. It bridges laboratory and real-world conditions and highlights the reliability of wearable sensors in dynamic, [...] Read more.

This study investigates stress recognition using galvanic skin response (GSR) and photoplethysmography (PPG) data and machine learning, with a new focus on air raid sirens as a stressor. It bridges laboratory and real-world conditions and highlights the reliability of wearable sensors in dynamic, high-stress environments such as war and conflict zones. The study involves 37 participants (20 men, 17 women), aged 20–30, who had not previously heard an air raid siren. A 70 dB “S-40 electric siren” (400–450 Hz) was delivered via headphones. The protocol included a 5 min resting period, followed by 3 min “no-stress” phase, followed by 3 min “stress” phase, and finally a 3 min recovery phase. GSR and PPG signals were recorded using Shimmer 3 GSR+ sensors on the fingers and earlobes. A single session was conducted to avoid sensitization. The workflow includes signal preprocessing to remove artifacts, feature extraction, feature selection, and application of different machine learning models to classify the “stress “and “no-stress” states. As a result, the best classification performance was shown by the k-Nearest Neighbors model, achieving 0.833 accuracy. This was achieved by using a particular combination of heart rate variability (HRV) and GSR features, which can be considered as new indicators of siren-induced stress. Full article

(This article belongs to the Section Biomedical Engineering)

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26 pages, 3396 KiB

Open AccessArticle

Carbon Quota Allocation Prediction for Power Grids Using PSO-Optimized Neural Networks

by Yixin Xu, Yanli Sun, Yina Teng, Shanglai Liu, Shiyu Ji, Zhen Zou and Yang Yu

Appl. Sci. 2024, 14(24), 11996; https://doi.org/10.3390/app142411996 (registering DOI) - 21 Dec 2024

Formulating a scientifically sound and efficient approach to allocating carbon quota aligned with the carbon peaking goal is a fundamental theoretical and practical challenge within the context of climate-oriented trading in the power sector. Given the highly irrational allocation of carbon allowances in [...] Read more.

Formulating a scientifically sound and efficient approach to allocating carbon quota aligned with the carbon peaking goal is a fundamental theoretical and practical challenge within the context of climate-oriented trading in the power sector. Given the highly irrational allocation of carbon allowances in China’s power sector, as well as the expanding role of renewable energy, it is essential to rationalize the use of green energy in the development of carbon reduction in the power sector. This study addresses the risk of “carbon transfer” within the power industry and develops a predictive model for CO₂ emission based on multiple influential factors, thereby proposing a carbon quota distribution scheme adapted to green energy growth. The proposed model employs a hybrid of the gray forecasting model-particle swarm optimization-enhanced back-propagation neural network (GM-PSO-BPNN) for forecasting and allocating the total carbon quota. Assuming consistent total volume control through 2030, carbon quota is distributed to regional power grids in proportion to actual production allocation. Results indicate that the PSO algorithm mitigates local optimization constraints of the standard BP algorithm; the prediction error of carbon emissions by the combined model is significantly smaller than that of the single model, while its identification accuracy reaches 99.46%. With the total national carbon emissions remaining unchanged in 2030, in the end, the regional grids received the following quota values: 873.29 million tons in North China, 522.69 million tons in Northwest China, 194.15 million tons in Northeast China, 1283.16 million tons in East China, 1556.40 million tons in Central China, and 1085.37 million tons in the Southern Power Grid. The power sector can refer to this carbon allowance allocation standard to control carbon emissions in order to meet the industry’s emission reduction standards. Full article

(This article belongs to the Special Issue Artificial Intelligence Applications in Smart Energy Systems)

19 pages, 5621 KiB

Open AccessArticle

Modified Kapok Fibers (Ceiba pentandra (L.) Gaerth) for Oil Spill Remediation

by Leonardo M. T. M. Oliveira, Eduardo J. S. Fonseca, Vanderson B. Bernardo, Carmem L. P. S. Zanta, Laís F. A. M. Oliveira, Jennifer N. S. R. de Oliveira, Samuel T. de Souza and José Leandro da Silva Duarte

Appl. Sci. 2024, 14(24), 11995; https://doi.org/10.3390/app142411995 (registering DOI) - 21 Dec 2024

The search for efficient oil spill remediation techniques leads to the use of physical, chemical, and biological methods, featuring both natural and modified lipophilic materials. Kapok fibers (Ceiba pentandra (L.) Gaerth) have been studied as a result of their unusual natural oil [...] Read more.

The search for efficient oil spill remediation techniques leads to the use of physical, chemical, and biological methods, featuring both natural and modified lipophilic materials. Kapok fibers (Ceiba pentandra (L.) Gaerth) have been studied as a result of their unusual natural oil sorption capacity, which can be improved even further through physical or chemical treatments that augment their rugosity and alter their functional properties. Furthermore, the exact role of fiber morphology is not completely clear regarding the sorption process. Hence, this study investigated the efficacy of kapok fibers using different treatments, based on chemical and physical approaches, and characterized using advanced techniques (FTIR, SEM, AFM), aiming to improve the understanding of application possibilities in oil contamination scenarios. The results indicate that treatments using a low thermal intensity and low concentration do not lead to variation in sorption properties nor in surface structural features. Fiber rugosity varied from 4.40 to 12.35 nm, whereas an excessive increase in roughness was observed when the material was subject to more extreme conditions, such as a temperature of 120 °C and high concentrations (2.0 M) of both acid or alkali, accompanied by a loss in functionality and affecting the material sorption capacity. Thus, the study provides conditions to suggest that these treatments are not necessary for this type of material when inserted into sorption processes. Full article

(This article belongs to the Special Issue New Approaches to Water Treatment: Challenges and Trends)

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22 pages, 893 KiB

Open AccessArticle

Joint Design of Transmitter Precoding and Optical Intelligent Reflecting Surface Configuration for Photon-Counting MIMO Systems Under Poisson Shot Noise

by Jian Wang, Xiaolin Zhou, Fanghua Li, Yongkang Chen, Chaoyi Cai and Haoze Xu

Appl. Sci. 2024, 14(24), 11994; https://doi.org/10.3390/app142411994 (registering DOI) - 21 Dec 2024

Intelligent reflecting surfaces (IRSs) have emerged as a promising technology to enhance link reliability in a cost-effective manner, especially for line-of-sight (LOS) link blocking caused by obstacles. In this paper, we investigate an IRS-assisted single-cell photon-counting communication system in the presence of building [...] Read more.

Intelligent reflecting surfaces (IRSs) have emerged as a promising technology to enhance link reliability in a cost-effective manner, especially for line-of-sight (LOS) link blocking caused by obstacles. In this paper, we investigate an IRS-assisted single-cell photon-counting communication system in the presence of building shadows, where one IRS is deployed to assist the communication between a multi-antenna base station (BS) and multiple single-antenna users. Photon counting has been widely adopted in sixth-generation (6G) optical communications due to its exceptional detection capability for low-power optical signals. However, the correlation between signal and noise complicates analyses. To this end, we first derive the channel gain of the IRS-assisted MIMO system, followed by the derivation of the mean square error (MSE) of the system using probabilistic methods. Given the constraints of the transmit power and IRS configuration, we propose an optimization problem aimed at minimizing the MSE of the system. Next, we present an alternating optimization (AO) algorithm that transforms the original problem into two convex subproblems and analyze its convergence and complexity. Finally, numerical results demonstrate that the IRS-assisted scheme significantly reduces the MSE and bit error rate (BER) of the system, outperforming other baseline schemes. Full article

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12 pages, 286 KiB

Open AccessArticle

Predictive Factors of Inpatient Rehabilitation Stay and Post-Discharge Burden of Care After Joint Replacement for Hip and Knee Osteoarthritis: A Retrospective Study on 1678 Patients

by Federico Pennestrì, Valentina Tosto, Catia Pelosi, Dario Grippa, Stefano Negrini, Carlotte Kiekens, Elisabetta Sarasso, Giuseppe Banfi, Claudio Cordani and the PREPARE Project Group

Appl. Sci. 2024, 14(24), 11993; https://doi.org/10.3390/app142411993 (registering DOI) - 21 Dec 2024

The global demand for end-stage hip and knee osteoarthritis surgical treatment is rising, as is the need of optimal postoperative rehabilitation. Patient stratification is key to provide rehabilitation professionals and policy makers with real-life data in support of early discharge planning and continuous [...] Read more.

The global demand for end-stage hip and knee osteoarthritis surgical treatment is rising, as is the need of optimal postoperative rehabilitation. Patient stratification is key to provide rehabilitation professionals and policy makers with real-life data in support of early discharge planning and continuous care provision. The aim of this retrospective, observational study was to investigate which factors can predict the burden of care at discharge (BCD) and the inpatient rehabilitation length of stay (LOS) based on a set of demographic, societal, clinical and organizational data collected from a high-volume orthopedic hospital. We included 45.306 variables from 1678 patients. All variables were initially tested individually using a linear regression model for inpatient rehabilitation LOS and a logistic regression model for BCD. Variables that resulted significant (p < 0.05) were subsequently considered in a single, comprehensive linear regression model, or a single, logistic regression model, respectively. Age, living with a family, occupational status, baseline Barthel Index and duration of surgery were predictors of inpatient rehabilitation LOS and BCD. Sex, primary or secondary osteoarthritis, American Society of Anesthesiologists score, body mass index, transfusion, biological risk, type of anesthesia, day of surgery, numeric pain rating scale and baseline cognitive function at baseline were not. Including specific patient comorbidities, surgical access technique and chronic use of pharmacological therapy can improve the predictive power of the model. Full article

(This article belongs to the Special Issue Rehabilitation Sciences and Physiotherapy: Latest Advances and Prospects)

15 pages, 6325 KiB

Open AccessArticle

A Space-Borne Ka-Band Tile-Type Phased Array Transmitter Module Based on HTCC Technology

by Hui Xu, Kaixue Ma, Shuantao Li and Gaojian Liu

Appl. Sci. 2024, 14(24), 11992; https://doi.org/10.3390/app142411992 (registering DOI) - 21 Dec 2024

We propose a double-sided layout design method with high reliability for multi-beam phased array transmitter modules based on high-temperature co-fired ceramic technology. Efficient transmission of microwave signals and low-frequency signals is realized by using multi-layer wiring and an inter-layer transition. The proposed Ka-band [...] Read more.

We propose a double-sided layout design method with high reliability for multi-beam phased array transmitter modules based on high-temperature co-fired ceramic technology. Efficient transmission of microwave signals and low-frequency signals is realized by using multi-layer wiring and an inter-layer transition. The proposed Ka-band transmitter module exhibits a gain of ≥26 dB, an output power of ≥21 dBm, and an overall efficiency of the component of ≥40%. The RMS accuracy of phase shift and attenuation is better than 3° and 0.5 dB, respectively. The proposed design method addresses the problems of high integration, lightness, and miniaturization in transmit/receive module design, and shows a good performance of heat dissipation performance and sealing capability. It can be easily expanded to large-scale phased arrays. Full article

(This article belongs to the Special Issue Millimeter-Wave and THz Integrated Technologies and Applications)

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20 pages, 862 KiB

Open AccessArticle

Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD

by Xiaowei Fan, Ruimiao Wang, Yi Yang and Jingang Wang

Appl. Sci. 2024, 14(24), 11991; https://doi.org/10.3390/app142411991 (registering DOI) - 21 Dec 2024

In order to solve the difficulties that the uncertain characteristics of PV output, such as volatility and intermittency, will bring to the development of microgrid scheduling plans, this paper proposes a Transformer–Bidirectional Long Short-Term Memory (BiLSTM) neural network PV power generation forecasting fusion [...] Read more.

In order to solve the difficulties that the uncertain characteristics of PV output, such as volatility and intermittency, will bring to the development of microgrid scheduling plans, this paper proposes a Transformer–Bidirectional Long Short-Term Memory (BiLSTM) neural network PV power generation forecasting fusion model based on the Newton–Raphson optimization algorithm (NRBO) and Variational Modal Decomposition (VMD). Firstly, the principle of the VMD technique and the Gray Wolf Optimization (GWO) algorithm’s key parameter optimization method for VMD are introduced. Then, the Transformer decoder partially fuses the BiLSTM network and retains the encoder to obtain the body of the prediction model, followed by explaining the principle of the NRBO algorithm. And finally, the VMD-NRBO-Transformer-BiLSTM prediction model and hyperparameter selection are evaluated by the NRBO algorithm. The algorithm sets up a multi-model comparison experiment, and the results show that the prediction model proposed in this paper has the best prediction accuracy and the optimal evaluation index. Full article

(This article belongs to the Section Energy Science and Technology)

16 pages, 7286 KiB

Open AccessArticle

The Design and Analysis of a Proportional Solenoid with Experimental Validation of Static and Dynamic Behavior

by Ercan Düzgün and Gürsel Şefkat

Appl. Sci. 2024, 14(24), 11990; https://doi.org/10.3390/app142411990 (registering DOI) - 21 Dec 2024

This study presents the design and analysis of a proportional solenoid used in electro-pneumatic brake systems for heavy vehicles. The solenoid was designed using a traditional method, and its static and dynamic characteristics were investigated both theoretically and experimentally. ANSYS 2024 R1 Maxwell [...] Read more.

This study presents the design and analysis of a proportional solenoid used in electro-pneumatic brake systems for heavy vehicles. The solenoid was designed using a traditional method, and its static and dynamic characteristics were investigated both theoretically and experimentally. ANSYS 2024 R1 Maxwell was employed for theoretical static analysis, focusing on the effects of the geometric dimension parameters in the fixed and moving pole contact regions on the force–displacement characteristics. The optimal dimensions for proportionality were determined under constraint parameters. The static analysis results provided the magnetization curve data, which were used to create Look-Up Tables for a dynamic model in MATLAB R2024b-Simulink, and this method reduced the simulation time and increased the dynamic simulation accuracy. Following static analysis, a prototype electromagnet was manufactured and tested. The solenoid achieved a constant magnetic force of 45 ± 3 N with a current of 1.3 A over a working range of 1–3 mm. The dynamic model, incorporating data from ANSYS, yielded results that closely matched the experimental findings. Full article

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14 pages, 1403 KiB

Open AccessArticle

Validity of the Enode Sensor and My Jump 3 App for Assessing Countermovement Jump Performance

by Davor Puljić, Christos Karavas, Athanasios Mandroukas and Andreas Stafylidis

Appl. Sci. 2024, 14(24), 11989; https://doi.org/10.3390/app142411989 (registering DOI) - 21 Dec 2024

Countermovement jump (CMJ) performance analysis is vital in sports science for assessing lower-body strength and neuromuscular efficiency. This study evaluated the validity of the Enode Sensor and My Jump 3 App for measuring vertical jump heights, comparing them to those measured using the [...] Read more.

Countermovement jump (CMJ) performance analysis is vital in sports science for assessing lower-body strength and neuromuscular efficiency. This study evaluated the validity of the Enode Sensor and My Jump 3 App for measuring vertical jump heights, comparing them to those measured using the established Force Plate. Twenty-nine participants performed CMJs measured using each device. Descriptive statistics indicated mean jump heights of 48.4 ± 4.18 cm (for the Enode Sensor), 47.3 ± 4.05 cm (for My Jump 3), and 46.1 ± 4.03 cm (for the Force Plate). Reliability was confirmed via Intraclass Correlation Coefficients (ICCs), with the Enode Sensor at 0.914 and My Jump 3 at 0.968, demonstrating excellent reliability. Bland–Altman analysis showed mean biases of 2.281 cm (for the Enode Sensor) and 1.297 cm (for My Jump 3) against the Force Plate, with limits of agreement suggesting close alignment. Strong positive correlations were observed (for the Enode Sensor, r = 0.972 and for My Jump 3, r = 0.987; p < 0.001), and linear regression analysis produced R² values of 0.945 and 0.973, respectively, confirming both tools’ accuracy for vertical jump measurement. These findings indicate that although both tools are suitable for CMJ assessment, My Jump 3 demonstrated slightly superior accuracy, underscoring the potential for accessible, reliable performance monitoring in sports contexts. Full article

(This article belongs to the Special Issue Advances in Sport and Exercise Biomechanics)

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14 pages, 10981 KiB

Open AccessArticle

Enhancement of Sentinel-2A Images for Ship Detection via Real-ESRGAN Model

by Cemre Fazilet Aldoğan, Koray Aksu and Hande Demirel

Appl. Sci. 2024, 14(24), 11988; https://doi.org/10.3390/app142411988 (registering DOI) - 21 Dec 2024

Ship detection holds great value regarding port management, logistics operations, ship security, and other crucial issues concerning surveillance and safety. Recently, ship detection from optical satellite imagery has gained popularity among the research community because optical images are easily accessible with little or [...] Read more.

Ship detection holds great value regarding port management, logistics operations, ship security, and other crucial issues concerning surveillance and safety. Recently, ship detection from optical satellite imagery has gained popularity among the research community because optical images are easily accessible with little or no cost. However, these images’ quality and quantity of feature details are bound to their spatial resolution, which often comes in medium-low spatial resolution. Accurately detecting ships requires images with richer texture and resolution. Super-resolution is used to recover features in medium-low resolution images, which can help leverage accuracy in ship detection. In this regard, this paper quantitatively and visually investigates the effectiveness of super-resolution in enabling more accurate ship detection in medium spatial resolution images by comparing Sentinel-2A images and enhanced Sentinel-2A images. A collection of Sentinel-2A images was enhanced four times with a Real-ESRGAN model that trained PlanetScope images with high spatial resolution. Separate ship detections with YOLOv10 were implemented for Sentinel-2A images and enhanced Sentinel-2A images. The visual and metric results of both detections were compared to demonstrate the contributory effect of enhancement on the ships’ detection accuracy. Ship detection on enhanced Sentinel-2A images has a mAP50 and mAP50-95 value of 87.5% and 68.5%. These results outperformed the training process on Sentinel-2A images with a mAP value increase of 2.6% for both mAP50 and mAP50-95, demonstrating the positive contribution of super-resolution. Full article

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17 pages, 1210 KiB

Open AccessArticle

Two-Stage Stochastic Programming for Precast Module Water Transportation: A Case Study in Hong Kong

by Huiwen Wang, Ying Terk Lim, Shenming Xie and Wen Yi

Appl. Sci. 2024, 14(24), 11987; https://doi.org/10.3390/app142411987 (registering DOI) - 21 Dec 2024

Transporting precast modules via water is a vital component of multimodal transportation systems, increasingly utilized in large-scale Modular integrated Construction (MiC) projects where modules are prefabricated in remote factories. The effectiveness of module transportation planning significantly impacts the overall costs and productivity of [...] Read more.

Transporting precast modules via water is a vital component of multimodal transportation systems, increasingly utilized in large-scale Modular integrated Construction (MiC) projects where modules are prefabricated in remote factories. The effectiveness of module transportation planning significantly impacts the overall costs and productivity of MiC projects. However, existing studies on module transportation planning neglect the uncertainty inherent in MiC projects, thereby resulting in increased costs. This study proposes a two-stage stochastic programming model to optimize transportation planning through water, addressing this uncertainty. A real Hong Kong case study with 418 modules is employed to assess the effectiveness of the proposed model in comparison with three deterministic models. The optimal transportation plan of modules solved by the proposed model costs HKD 148,951, comprising 21% from temporary rentals and 79% from advance bookings. The results show that the three deterministic models, without considering the uncertainty in module demand, will incur additional transportation costs that are 25% higher on average than the results of the developed two-stage stochastic model. Additionally, this paper conducts a sensitivity analysis on the price ratio of pre-booked barges to on-demand barges to evaluate its impact on total transportation costs. The two-stage programming model developed in this paper can effectively help transport planners reduce the costs associated with module water transportation. Full article

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17 pages, 27765 KiB

Open AccessArticle

Influence of Graphene Oxide on Printability, Rheological and Mechanical Properties of Highly Filled Alumina Filaments and Sintered Parts Produced by FFF

by Ekaterina Kuznetsova, Anton Smirnov, Andrey V. Gusarov, Nestor Washington Solís Pinargote, Tatiana V. Tarasova and Sergey N. Grigoriev

Appl. Sci. 2024, 14(24), 11986; https://doi.org/10.3390/app142411986 (registering DOI) - 21 Dec 2024

The aim of the study was to investigate the effect of the addition of graphene oxide (GO) on the rheological and mechanical properties of extruded polyamide 12 (PA12) filaments with high aluminum oxide (Al₂O₃) content used for 3D printing [...] Read more.

The aim of the study was to investigate the effect of the addition of graphene oxide (GO) on the rheological and mechanical properties of extruded polyamide 12 (PA12) filaments with high aluminum oxide (Al₂O₃) content used for 3D printing using the fused filament fabrication (FFF) method. Firstly, Al₂O₃-based mixtures with 0.10, 0.25 and 0.50 vol.% GO content were prepared. These mixtures were dried and subsequently combined with paraffin wax (PW), stearic acid (SA) and polyamide 12 (PA12) in an organic solvent. After drying in a vacuum oven and sifting, powder compositions of 74 wt.% (Al₂O₃ + GO)/26 wt.% (PA12 + PW + SA) with different GO content were obtained. All compositions were successfully extruded into filaments for 3D printing. Rheological, microstructural and mechanical studies of the compositions and filaments were carried out. X-ray diffraction phase analysis and Raman spectroscopy were also performed. It was shown that 0.10 and 0.25% vol. GO proved to be a universal additive that resulted in an increase in the rheological and mechanical properties of the highly filled polymer and also improved its 3D printability, which ultimately helped obtain a ceramic product with complex shape using the FFF method. Full article

(This article belongs to the Special Issue Additive Manufacturing in Material Processing)

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10 pages, 1581 KiB

Open AccessArticle

Aflatoxin Inactivation in Gamma-Ray-Irradiated Almonds

by Eleni Bozinou, Vassilis Athanasiadis, Iordanis Samanidis, Maria Govari, Alexander Govaris, Konstantinos Sflomos and Stavros I. Lalas

Appl. Sci. 2024, 14(24), 11985; https://doi.org/10.3390/app142411985 (registering DOI) - 21 Dec 2024

Aflatoxins are foodborne toxins that occur naturally in various crops because of fungal contamination, particularly from two strains, namely Aspergillus flavus and Aspergillus parasiticus. Given their adverse properties, which are teratogenic, mutagenic, and carcinogenic, aflatoxins present a significant public health concern. Consequently, [...] Read more.

Aflatoxins are foodborne toxins that occur naturally in various crops because of fungal contamination, particularly from two strains, namely Aspergillus flavus and Aspergillus parasiticus. Given their adverse properties, which are teratogenic, mutagenic, and carcinogenic, aflatoxins present a significant public health concern. Consequently, efforts are underway to inactivate aflatoxins and inhibit the growth of these fungi to prevent toxin formation. Since chemical treatments for food products are undesirable or even restricted in some countries, alternative approaches are also implemented. This study investigated gamma-ray (γ-ray) irradiation as a potential method for reducing aflatoxin levels. Specifically, solutions of aflatoxins B1, B2, G1, and G2 were irradiated with doses of 1, 2, 4, and 8 kGy using a cobalt-60 irradiation source. Following γ-irradiation, a notable reduction in aflatoxin levels was observed, particularly for types B1 and G1, which process higher toxicity. This finding suggests γ-irradiation as a feasible method for aflatoxin deactivation. Additionally, as a proof of concept, almond samples spiked with aflatoxins and A. flavus were irradiated. The results showed a decrease in both aflatoxin levels and microbial load in these samples. Overall, these findings indicate that γ-irradiation is a promising approach to aflatoxin reduction, microbial decontamination, and the potential extension of almonds’ shelf life. Full article

(This article belongs to the Special Issue Research and Analysis on Microbial Food Quality and Safety)

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