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Appl. Sci., Volume 14, Issue 11 (June-1 2024) – 623 articles

Cover Story (view full-size image): Droplet impact on heated plates is widespread in nature and industrial applications. This study compares the impact dynamics of ethanol/propanol and ethanol/water binary droplets, which have similar differences in boiling points but exhibit significantly different impact behaviors due to the high surface tension and latent heat of water. Notably, a novel bubble shrinkage phenomenon is observed for the 25 vol.% ethanol/water binary droplet. It is proposed to be relevant to the increasing surface tension and saturation temperature of the bubble liquid film with decreasing ethanol content, as well as the decreasing ambient temperature above the top surface of the bubble during its growth. Consequently, the vapor condensation inside the bubble leads to a decrease in the bubble’s internal pressure. Finally, an imbalance in the forces inside and outside the bubble results in bubble shrinkage. View this paper
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19 pages, 8473 KiB  
Article
Synthesis and Characterization of Iron-Based Catalysts for Carbon Dioxide Valorization
by Alexandra Bakratsa, Vasiliki Zacharopoulou, George Karagiannakis, Vasileios Zaspalis and Georgia Kastrinaki
Appl. Sci. 2024, 14(11), 4959; https://doi.org/10.3390/app14114959 - 6 Jun 2024
Viewed by 519
Abstract
The extensive release of carbon dioxide (CO2) into the atmosphere is associated with the detrimental impacts of the global environmental crisis. Consequently, the valorization of CO2 from industrial processes holds great significance. Transforming CO2 into high added-value products (e.g., [...] Read more.
The extensive release of carbon dioxide (CO2) into the atmosphere is associated with the detrimental impacts of the global environmental crisis. Consequently, the valorization of CO2 from industrial processes holds great significance. Transforming CO2 into high added-value products (e.g., CH4, C1-C3 deoxygenated products) has attracted considerable attention. This is feasible through the reverse water–gas shift (RWGS) and Fischer–Tropsch synthesis (FTS) reactions; CO is initially formed and then hydrogenated, resulting in the production of hydrocarbons. Iron-based materials have a remarkable ability to catalyze both RWGS and FTS reactions, enhancing the olefinic nature of the resulting products. Within this context, iron-based nanoparticles, unsupported and supported on zeolite, were synthesized and physico-chemically evaluated, applying multiple techniques (e.g., BET, XRD, FT-IR, Raman, SEM/TEM, DLS, NH3-TPD, CO2-TPD). Preliminary experiments show the potential for the production of C2+ deoxygenated products. Among the tested samples, supported Fe3O4 and Na-Fe3O4 (A) nanoparticles on HZSM-5 are the most promising for promoting CO2 valorization into products with more than two carbon atoms. Results demonstrate that product distribution is highly affected by the presence of acid sites, as low-medium acid sites and medium acidity values enable the formation of C2+ hydrocarbons. Full article
(This article belongs to the Special Issue CCUS: Paving the Way to Net Zero Emissions Technologies)
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14 pages, 2812 KiB  
Article
Quantitative Analysis of Influencing Factors on Changzhou Ship Lock Capacity
by Quanbo Xin, Yong Wang, Ming Zhang, Ruixi Wang and Yongchao Wang
Appl. Sci. 2024, 14(11), 4958; https://doi.org/10.3390/app14114958 - 6 Jun 2024
Viewed by 310
Abstract
The Changzhou ship lock is approaching its capacity limit. In order to quantitatively analyze the influencing factors that restrict the capacity of the Changzhou ship lock, this study proposes an influencing factor analysis method based on principal component analysis (PCA). This method estimates [...] Read more.
The Changzhou ship lock is approaching its capacity limit. In order to quantitatively analyze the influencing factors that restrict the capacity of the Changzhou ship lock, this study proposes an influencing factor analysis method based on principal component analysis (PCA). This method estimates the confidence interval of ship passing time by fitting a lognormal distribution curve, eliminates redundancy in navigability data by combining the hydrological data and cargo load data, and quantitatively analyzes the influencing factors of ship lock capacity under saturated operating conditions. The results show that the influencing factors of Changzhou ship lock capacity are classified according to their influence contribution rate as minimum water depth above the lock sill, operation direction, ship dimensions, draft, loading capacity, and actual load. The research results can provide a theoretical basis for improving the ship lock capacity and have application value for lock scheduling management. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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12 pages, 1119 KiB  
Article
Techno-Economic Assessment of Anaerobic Digestion Technology for Small- and Medium-Sized Animal Husbandry Enterprises
by Alexandros Eftaxias, Iliana Kolokotroni, Christos Michailidis, Panagiotis Charitidis and Vasileios Diamantis
Appl. Sci. 2024, 14(11), 4957; https://doi.org/10.3390/app14114957 - 6 Jun 2024
Viewed by 315
Abstract
Investments in small and medium-sized anaerobic digestion facilities have the potential to boost biogas production in Greece and other EU countries. This study aimed to evaluate the economic feasibility of anaerobic digestion facilities equipped with combined heat and power (CHP) units ranging from [...] Read more.
Investments in small and medium-sized anaerobic digestion facilities have the potential to boost biogas production in Greece and other EU countries. This study aimed to evaluate the economic feasibility of anaerobic digestion facilities equipped with combined heat and power (CHP) units ranging from 50 to 400 kW, while treating livestock waste. For this purpose, data were gathered from various livestock operations (dairy cattle, poultry, swine, dairy sheep and goats) regarding their annual production, revenues, electricity and fuel usage, and waste generation. Waste samples were then collected and analyzed to assess their biochemical methane production potential. The capital and operational costs of anaerobic digestion facilities, from 50 and 400 kW, were calculated using the equations developed within the “eMT cluster” project. Findings indicate that current feed-in tariffs (FITs) of 0.21 € kWh−1 are insufficient to incentivize investment in anaerobic digestion facilities with capacities below 250 kW, highlighting the need for increased FIT rates or capital expenditure subsidies. Recommendations include shifting towards simplified technology and business models with reduced farmer involvement, coupled with supportive legislative framework and long-term electricity price guarantees. These measures are expected to foster the implementation of anaerobic digestion projects in the animal husbandry sector. Full article
(This article belongs to the Section Environmental Sciences)
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15 pages, 1330 KiB  
Systematic Review
Fluoride Release by Restorative Materials after the Application of Surface Coating Agents: A Systematic Review
by Dominik Tokarczuk, Oskar Tokarczuk, Jan Kiryk, Julia Kensy, Magdalena Szablińska, Tomasz Dyl, Wojciech Dobrzyński, Jacek Matys and Maciej Dobrzyński
Appl. Sci. 2024, 14(11), 4956; https://doi.org/10.3390/app14114956 - 6 Jun 2024
Viewed by 501
Abstract
Background: Fluoride is vital in dentistry for caries prevention, enhancing remineralization, and inhibiting bacteria. Incorporating fluoride into restorative materials like glass-ionomer cements, compomers, and giomers has significantly increased fluoride availability in the oral cavity. This review assesses how surface coatings influence fluoride release [...] Read more.
Background: Fluoride is vital in dentistry for caries prevention, enhancing remineralization, and inhibiting bacteria. Incorporating fluoride into restorative materials like glass-ionomer cements, compomers, and giomers has significantly increased fluoride availability in the oral cavity. This review assesses how surface coatings influence fluoride release from various dental restorative materials. Methods: In December 2023, we conducted electronic searches in PubMed, Scopus, and Web of Science (WoS) databases. In the Scopus database, the results were refined to titles, abstracts, and keywords, while in PubMed, they were narrowed down to titles and abstracts. In WoS, the results were refined only to abstracts. The search criteria were based on the terms fluoride AND release AND (coating OR glaze OR layer OR film OR varnish) AND (composite OR glass OR compomer), following PRISMA guidelines and the PICO framework. Twenty-three studies were rigorously selected and analyzed for fluoride release from coated versus uncoated materials. Results: Surface coatings typically reduce the rate of fluoride release. Glass-ionomer cements had the highest release, followed by giomers and compomers. The initial release was greater in uncoated materials but stabilized over time, influenced by variables like artificial saliva and deionized water. Conclusions: Surface coatings generally decrease fluoride release rates from dental materials. Although initial rates are high, contributing to caries prevention, more standardized research is needed to better understand the impact of coatings and optimize materials for maximum preventive benefits. Full article
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11 pages, 1054 KiB  
Article
Influence of Technological Parameters on Sourdough Starter Obtained from Different Flours
by Alina Alexandra Dobre, Elena Mirela Cucu and Nastasia Belc
Appl. Sci. 2024, 14(11), 4955; https://doi.org/10.3390/app14114955 - 6 Jun 2024
Viewed by 290
Abstract
One of the oldest biotechnological processes used in bread manufacture is sourdough production which relies on wild yeast and lactobacillus cultures naturally present in flour. The aim of this paper was to evaluate the influence of selected flours of different cereal grains (ancient [...] Read more.
One of the oldest biotechnological processes used in bread manufacture is sourdough production which relies on wild yeast and lactobacillus cultures naturally present in flour. The aim of this paper was to evaluate the influence of selected flours of different cereal grains (ancient wheat, corn, and rye), different dough variations, and temperature of fermentation on the quality of spontaneous sourdough. Two values of fermentation temperatures were tested (25 °C and 35 °C), and for each temperature analyzed, three backslopping steps were carried out to obtain mature doughs according to the traditional type I sourdough scheme. In total, 14 different sourdoughs were produced, and microbiology, pH, and total titration acidity for 96 h were determined. Optimal pH values for the samples determined that the optimal fermentation period was 48 h. The acidification rate of the dough was faster at 35 °C than at 25 °C. This fact became evident via the pH values obtained in the first 24 h. However, from this point, the pH values were lower in the samples kept at 25 °C, showing that a cooler fermentation temperature allows the acidification activity of the microorganisms to be prolonged for a longer time. In the study carried out, the ideal fermentation time for the population of LAB and yeasts is 72 h at a temperature of 25 °C, and the most productive sourdoughs were the dough with 100% Einkorn wheat flour and the dough obtained from the 1:1 combination of flour rye and corn flours. Full article
(This article belongs to the Special Issue Trends in Grain Processing for Food Industry)
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12 pages, 1432 KiB  
Article
Vibrational Rarefaction Waves Excited by Laser-Induced Bubble within Confined Cuvettes and Their Feedback on Cavitation Dynamics: Influence of Wall and Liquid
by Lei Fu, Ziyao Peng, Xiaofan Du, Zhenxi Zhang, Jing Wang and Cuiping Yao
Appl. Sci. 2024, 14(11), 4954; https://doi.org/10.3390/app14114954 - 6 Jun 2024
Viewed by 384
Abstract
In this work, within finite liquid spaces confined by elastic walls and the free surface, we investigated the influence of wall and liquid on laser bubble-excited vibrational rarefaction waves, via the dynamics of the laser-induced plasma-mediated bubble and its accompanying small secondary bubble [...] Read more.
In this work, within finite liquid spaces confined by elastic walls and the free surface, we investigated the influence of wall and liquid on laser bubble-excited vibrational rarefaction waves, via the dynamics of the laser-induced plasma-mediated bubble and its accompanying small secondary bubble clouds. We observed the modulation of the rebound maximum radius (Rmax2) relative to the first oscillation period (Tosc1) for the laser bubble and the periodic appearance of secondary bubble clouds, which were caused by extra rarefaction waves. We found an approximate constant modulation period of Rmax2 (Tosc1) and increased time intervals between the adjacent secondary bubble clouds with increasing liquid height in the same cuvette, while both of them were remarkably increased with increasing inner size of cuvettes within the same liquid height. This indicated that the cuvette geometry and liquid volume alter the key characteristics of the vibrational rarefaction waves. It was further confirmed that extra rarefaction waves within the liquid are excited by wall vibrations linked to laser bubble expansion and its induced liquid-mass oscillations. Our study provides a better understanding of the interactions of laser-induced cavitation with liquid and elastic walls in confined geometry, which is essential for intraluminal laser surgery. Full article
(This article belongs to the Section Fluid Science and Technology)
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16 pages, 3117 KiB  
Article
Impact of Visual Disturbances on the Trend Changes of COP Displacement Courses Using Stock Exchange Indices
by Piotr Wodarski, Marta Chmura and Jacek Jurkojć
Appl. Sci. 2024, 14(11), 4953; https://doi.org/10.3390/app14114953 - 6 Jun 2024
Viewed by 297
Abstract
This work aims to define a strategy for maintaining a vertical posture of the human body under conditions of conflicting sensory stimuli using a method of trend change analysis. The investigations involved 28 healthy individuals (13 females, 15 males, average age = 21, [...] Read more.
This work aims to define a strategy for maintaining a vertical posture of the human body under conditions of conflicting sensory stimuli using a method of trend change analysis. The investigations involved 28 healthy individuals (13 females, 15 males, average age = 21, SD = 1.3 years). Measurements were conducted with eyes opened and closed and in the virtual environment with two sceneries oscillating at two frequencies. Values in the time domain were calculated—the mean center of pressure (COP) velocity and movement range in the AP direction—as well as values based on the moving average convergence divergence (MACD) computational algorithm—the trend change index (TCI), MACD_dT, MACD_dS, and MACD_dV. After dividing the analysis into distinct time periods, an increase in TCI values was identified in the oscillating scenery at 0.7 and 1.4 Hz during the 0.5–1 and 0.2–0.5 s time periods, respectively. Statistically significant differences were observed between measurements with an oscillation frequency of 0.7 Hz and those with an oscillation frequency of 1.4 Hz during the 0.2–0.5 s and 0.5–1 s periods. The use of stock exchange indices in the assessment of the ability to keep a stable body posture supplements and extends standard analyses in the time and frequency domains. Full article
(This article belongs to the Special Issue Human–Computer Interaction and Virtual Environments)
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15 pages, 2710 KiB  
Article
Research on Longitudinal Thermoelastic Waves in an Orthotropic Anisotropic Hollow Cylinder Based on the Thermoelastic Theory of Green–Naghdi
by Jinjie Zhou, Xingwang Zhang, Yang Zheng, Xingquan Shen and Yuanxin Li
Appl. Sci. 2024, 14(11), 4952; https://doi.org/10.3390/app14114952 - 6 Jun 2024
Viewed by 355
Abstract
At present, many high-temperature pipelines need to carry out non-stop detection under high-temperature conditions, and an ultrasonic guided wave is undoubtedly one of the solutions with the highest potential to solve the problem. However, there is a lack of research on the propagation [...] Read more.
At present, many high-temperature pipelines need to carry out non-stop detection under high-temperature conditions, and an ultrasonic guided wave is undoubtedly one of the solutions with the highest potential to solve the problem. However, there is a lack of research on the propagation characteristics of longitudinal guided wave modes in high-temperature pipelines. Based on the Green–Naghdi (GN) generalized thermoelastic theory, a theoretical model of thermoelastic guided waves in an orthotropic hollow cylinder with a temperature field is established by using the Legendre polynomial series expansion method. Firstly, based on the GN thermoelastic theory, the coupling equations expressed by displacement and temperature are established by introducing the rectangular window function. The curves of dispersion, displacement, and temperature of the guided wave are numerically solved by using this equation. Subsequently, the influence of the diameter-to-thickness ratio on the dispersion of the longitudinal thermoelastic guided wave is analyzed at the same temperature. Finally, the effect of temperature field variation on the phase velocity dispersion is discussed, which provides a theoretical basis for the study of the dispersion characteristics of hollow cylindrical pipes containing temperature fields. Full article
(This article belongs to the Section Mechanical Engineering)
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24 pages, 4686 KiB  
Article
User-Centric Internet of Things and Controlled Service Scheduling Scheme for a Software-Defined Network
by Mohd Anjum, Hong Min and Zubair Ahmed
Appl. Sci. 2024, 14(11), 4951; https://doi.org/10.3390/app14114951 - 6 Jun 2024
Viewed by 318
Abstract
Mobile users can access vital real-time services through wireless paradigms like software-defined network (SDN) topologies and the Internet of Things. Point-of-contact-based infrastructures and dynamic user densities increase resource access and service-sharing concurrency. Thus, controlling power consumption and network and device congestion becomes a [...] Read more.
Mobile users can access vital real-time services through wireless paradigms like software-defined network (SDN) topologies and the Internet of Things. Point-of-contact-based infrastructures and dynamic user densities increase resource access and service-sharing concurrency. Thus, controlling power consumption and network and device congestion becomes a major issue for SDN-based IoT applications. This paper uses the Controlled Service Scheduling Scheme (CS3) to address the challenge of simultaneous scheduling and power allocation. The suggested approach uses deep recurrent learning and probabilistic balancing for power allocation and service distribution during user-centric concurrent sharing intervals. The SDN control plane decides how much power to use for service delivery while forecasting user service demands directs the scheduling interval allocation. Power management is under the control plane of the SDN, whereas service distribution is under the data plane. Power-to-service requirements are evaluated probabilistically, and updates for both aircraft are obtained via the deep learning model. This allocation serves as the basis for training the learning model to alleviate power deficits across succeeding intervals. The simulation experiments are modeled using the Contiki Cooja simulator, where 200 mobile users are placed. The proposed plan delivers a 14.9% high-service distribution for various users, 18.29% less delay, 13.34% less failure, 5.54% less downtime, and 18.68% less power consumption. Full article
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10 pages, 855 KiB  
Article
Reliability Analysis of Small-Sample Failure Data for Random Truncation High-Voltage Relay
by Yingzhi Zhang, Feng Han, Fang Yang, Xiaofeng Wang and Yutong Zhou
Appl. Sci. 2024, 14(11), 4950; https://doi.org/10.3390/app14114950 - 6 Jun 2024
Viewed by 328
Abstract
In order to model and evaluate the reliability of long-life high-voltage relays with small-sample fault data characteristics, a reliability analysis method integrating average rank, the minimum mean square distance empirical distribution function, and total least squares estimation is proposed. In the random truncation [...] Read more.
In order to model and evaluate the reliability of long-life high-voltage relays with small-sample fault data characteristics, a reliability analysis method integrating average rank, the minimum mean square distance empirical distribution function, and total least squares estimation is proposed. In the random truncation experiment, considering the influence of random truncation data, the average rank method is used to correct the rank of small-sample fault data; then, the optimal empirical distribution function for small-sample fault data is obtained through the minimum average square distance, which can overcome the impact of small-sample fault data randomness. Under the assumption of the Weibull distribution model, the total least squares estimation method is used for reliability model parameter estimations, and the linear correlation coefficient and d-test method are used for model hypothesis testing. If two or more distribution models pass the linear correlation coefficient test and the d-test simultaneously, the root mean square error and relative root mean square error are applied to determine the optimal reliability model. The effectiveness of this method is verified by comparing it with the maximum likelihood estimation method. Full article
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21 pages, 36012 KiB  
Article
DFD-SLAM: Visual SLAM with Deep Features in Dynamic Environment
by Wei Qian, Jiansheng Peng and Hongyu Zhang
Appl. Sci. 2024, 14(11), 4949; https://doi.org/10.3390/app14114949 - 6 Jun 2024
Viewed by 383
Abstract
Visual SLAM technology is one of the important technologies for mobile robots. Existing feature-based visual SLAM techniques suffer from tracking and loop closure performance degradation in complex environments. We propose the DFD-SLAM system to ensure outstanding accuracy and robustness across diverse environments. Initially, [...] Read more.
Visual SLAM technology is one of the important technologies for mobile robots. Existing feature-based visual SLAM techniques suffer from tracking and loop closure performance degradation in complex environments. We propose the DFD-SLAM system to ensure outstanding accuracy and robustness across diverse environments. Initially, building on the ORB-SLAM3 system, we replace the original feature extraction component with the HFNet network and introduce a frame rotation estimation method. This method determines the rotation angles between consecutive frames to select superior local descriptors. Furthermore, we utilize CNN-extracted global descriptors to replace the bag-of-words approach. Subsequently, we develop a precise removal strategy, combining semantic information from YOLOv8 to accurately eliminate dynamic feature points. In the TUM-VI dataset, DFD-SLAM shows an improvement over ORB-SLAM3 of 29.24% in the corridor sequences, 40.07% in the magistrale sequences, 28.75% in the room sequences, and 35.26% in the slides sequences. In the TUM-RGBD dataset, DFD-SLAM demonstrates a 91.57% improvement over ORB-SLAM3 in highly dynamic scenarios. This demonstrates the effectiveness of our approach. Full article
(This article belongs to the Special Issue Intelligent Control and Robotics II)
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16 pages, 8909 KiB  
Article
Establishment and Accuracy Analysis of Measurement Control Network Based on Length–Angle Mixed Intersection Adjustment Model
by Zhi Xiong, Chunsen Li, Hao Zhang, Chenxiaopeng Zhong, Zhongsheng Zhai and Ziyue Zhao
Appl. Sci. 2024, 14(11), 4948; https://doi.org/10.3390/app14114948 - 6 Jun 2024
Viewed by 292
Abstract
To achieve high-precision measurements of target points on long straight tracks, a multi-level measurement method based on length–angle mixed intersection techniques was explored. Firstly, a control network with graded measurement levels was proposed, based on the spatial error characteristics of different measuring devices [...] Read more.
To achieve high-precision measurements of target points on long straight tracks, a multi-level measurement method based on length–angle mixed intersection techniques was explored. Firstly, a control network with graded measurement levels was proposed, based on the spatial error characteristics of different measuring devices and the principle of nonlinear least squares, and a method for adjustment calculation based on length–angle mixed intersection was studied. Secondly, numerical simulation was conducted to assess the impact of instrument placement on measurement accuracy, and the results indicated that central positioning within the measurement range can effectively minimize the overall point location errors. Finally, the methodology was validated in a practical setting at a rocket sled test site. Experimental results demonstrated that, within a measurement range of approximately 669 m, when target points were located on one side of the track and distance measurements were used as benchmark values, the measurement control network achieved a distance standard deviation of 0.20 mm. The range of distance deviations was between −0.85 mm and 0.98 mm. This approach offers substantial reference value for high-precision coordinate measurements over extended distances. Full article
(This article belongs to the Special Issue Advances in Optical Instrument and Measurement Technology)
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19 pages, 9230 KiB  
Article
Evaluation of Urban Transportation Resilience under Extreme Weather Events
by Yuepeng Cui, Zijian Liu, Huiming Wu, Pengju Sun and Fubin Zhou
Appl. Sci. 2024, 14(11), 4947; https://doi.org/10.3390/app14114947 - 6 Jun 2024
Viewed by 236
Abstract
The frequent occurrence of extreme weather events (EWEs) in recent years has posed major hazards to urban transportation as well as socioeconomic impacts. A quantitative evaluation of the urban transportation resilience to minimize the impact caused by EWEs becomes critical to the rapid [...] Read more.
The frequent occurrence of extreme weather events (EWEs) in recent years has posed major hazards to urban transportation as well as socioeconomic impacts. A quantitative evaluation of the urban transportation resilience to minimize the impact caused by EWEs becomes critical to the rapid recovery of urban transportation after disasters. However, there is, generally, a lack of reliable data sources to monitor urban transportation performance under EWEs. This empirical study proposes a performance indicator (displacement) and quantitative method for evaluating the urban transportation performance under EWEs based on bus GPS trajectory datasets. Furthermore, the transportation resilience of it is quantified, and the variation is compared across temporal and spatial dimensions. The method is applied in a case study of Fuzhou, China, under rainstorm events. The results show that the Gulou and Jinan subareas have the highest transportation resilience during the yellow and red rainstorm warnings. By formulating an emergency plan and taking mitigation measures, the transportation performance in the Jinan subarea during the red rainstorm warning was improved by 36% compared to the yellow rainstorm warning. The empirical study not only fills the knowledge gap for quantifying the transportation resilience across the geographical boundary under rainstorm events, but also estimates the operation status of the road network. The results will help policymakers prioritize the resource distribution and develop effective policies or measures to further improve transportation resilience in the city. Full article
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16 pages, 608 KiB  
Article
A Spectral Clustering Algorithm for Non-Linear Graph Embedding in Information Networks
by Li Ni, Peng Manman and Wu Qiang
Appl. Sci. 2024, 14(11), 4946; https://doi.org/10.3390/app14114946 - 6 Jun 2024
Viewed by 240
Abstract
With the development of network technology, information networks have become one of the most important means for people to understand society. As the scale of information networks expands, the construction of network graphs and high-dimensional feature representation will become major factors affecting the [...] Read more.
With the development of network technology, information networks have become one of the most important means for people to understand society. As the scale of information networks expands, the construction of network graphs and high-dimensional feature representation will become major factors affecting the performance of spectral clustering algorithms. To address this issue, in this paper, we propose a spectral clustering algorithm based on similarity graphs and non-linear deep embedding, named SEG_SC. This algorithm introduces a new spectral clustering model that explores the underlying structure of graphs through sparse similarity graphs and deep graph representation learning, thereby enhancing graph clustering performance. Experimental analysis with multiple types of real datasets shows that the performance of this model surpasses several advanced benchmark algorithms and performs well in clustering on medium- to large-scale information networks. Full article
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14 pages, 658 KiB  
Article
Using Machine Learning to Predict Pedestrian Compliance at Crosswalks in Jordan
by Madhar M. Taamneh, Ahmad H. Alomari and Salah M. Taamneh
Appl. Sci. 2024, 14(11), 4945; https://doi.org/10.3390/app14114945 - 6 Jun 2024
Viewed by 350
Abstract
This study employs machine learning (ML) techniques to predict pedestrian compliance at crosswalks in urban settings in Jordan, aiming to enhance pedestrian safety and traffic management. Utilizing data from 2437 pedestrians at signalized intersections in Amman, Irbid, and Zarqa, four models based on [...] Read more.
This study employs machine learning (ML) techniques to predict pedestrian compliance at crosswalks in urban settings in Jordan, aiming to enhance pedestrian safety and traffic management. Utilizing data from 2437 pedestrians at signalized intersections in Amman, Irbid, and Zarqa, four models based on different ML algorithms were developed: an artificial neural network (ANN), a support vector machine (SVM), a decision tree (ID3), and a random forest (RF). The results have shown that local infrastructure and traffic conditions influence pedestrian behavior. The RF model, with its excellent accuracy and precision, has proven to be an excellent choice for accurately predicting pedestrian behavior. This research provides valuable insights into the demographic and spatial aspects that influence pedestrian compliance with laws and regulations in the local environment. Additionally, this work highlights the ability of ML algorithms to improve urban traffic dynamics. Policymakers and urban planners, particularly with the rise of theories and trends toward the humanization of urban roads, should firmly establish this understanding among themselves to create environments that make pedestrians safer. This strategy could be a measurable solution for international urban situations if future research focuses on integrating these prediction models with real-time traffic management systems to improve pedestrian safety dynamically. Full article
(This article belongs to the Special Issue Optimization and Simulation Techniques for Transportation)
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18 pages, 5034 KiB  
Article
Influence of Vehicle Wake on the Control of Towed Systems
by Jinjing Gu and Zhibo Wang
Appl. Sci. 2024, 14(11), 4944; https://doi.org/10.3390/app14114944 - 6 Jun 2024
Viewed by 302
Abstract
The hydrodynamic wake generated by the underwater vehicle’s motion has a considerable impact on the movement of the towed system underwater. This paper utilizes the lumped mass method to model the towed cable in order to improve the accuracy of predicting its position [...] Read more.
The hydrodynamic wake generated by the underwater vehicle’s motion has a considerable impact on the movement of the towed system underwater. This paper utilizes the lumped mass method to model the towed cable in order to improve the accuracy of predicting its position and attitude in the wake, and to determine the suitable cable-towed position. Velocity is transferred from the flow field to the cable dynamic model in an innovative way to imitate the motion of the cable. Several iterations are conducted to enhance the dynamic reactivity of the cable system. Numerical simulations are used to model both the straight towed and turning movements. The numerical calculation provides the characteristics of vorticity in the flow field formed by the energy exchange between the vorticity and the cable, as well as the gradually dissipating vorticity and momentum exchange characteristics at the trailing edge of the enclosure. The results indicate that the best location for the cable towed is where its motion does not cause any adhesion. On the other hand, the disadvantageous scenario for cable-towed systems occurs when the cable’s movement causes substantial adhesion. This paper innovatively establishes a model of mechanical energy exchange, describes the characteristics of energy exchange between the cable and fluid dynamics, and divides the four regions of cable motion. In the manipulation state, the dynamic energy exchange between the cable and the wake results in the transient vibration response of the cable. The fluid structure coupling method can accurately determine the separation region of the towed point of the vehicle based on its compatibility (non-adhesive) and incompatibility (adhesive). The boundary of the region is defined to distinguish a free tow point from a wall-attached tow point. A transition zone has the possibility to change the pattern from a free tow to a wall-attached tow. The wake can be divided into free tow region, transition zone, and adjacent wall tow region by this fluid structure interaction assessment method. Full article
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23 pages, 11021 KiB  
Article
A Trajectory Optimisation-Based Incremental Learning Strategy for Learning from Demonstration
by Yuqi Wang, Weidong Li and Yuchen Liang
Appl. Sci. 2024, 14(11), 4943; https://doi.org/10.3390/app14114943 - 6 Jun 2024
Viewed by 309
Abstract
The insufficient generalisation capability of the conventional learning from demonstration (LfD) model necessitates redemonstrations. In addition, retraining the model can overwrite existing knowledge, making it impossible to perform previously acquired skills in new application scenarios. These are not economical and efficient. To address [...] Read more.
The insufficient generalisation capability of the conventional learning from demonstration (LfD) model necessitates redemonstrations. In addition, retraining the model can overwrite existing knowledge, making it impossible to perform previously acquired skills in new application scenarios. These are not economical and efficient. To address the issues, in this study, a broad learning system (BLS) and probabilistic roadmap (PRM) are integrated with dynamic movement primitive (DMP)-based LfD. Three key innovations are proposed in this paper: (1) segmentation and extended demonstration: a 1D-based topology trajectory segmentation algorithm (1D-SEG) is designed to divide the original demonstration into several segments. Following the segmentation, a Gaussian probabilistic roadmap (G-PRM) is proposed to generate an extended demonstration that retains the geometric features of the original demonstration. (2) DMP modelling and incremental learning updating: BLS-based incremental learning for DMP (Bi-DMP) is performed based on the constructed DMP and extended demonstration. With this incremental learning approach, the DMP is capable of self-updating in response to task demands, preserving previously acquired skills and updating them without training from scratch. (3) Electric vehicle (EV) battery disassembly case study: this study developed a solution suitable for EV battery disassembly and established a decommissioned battery disassembly experimental platform. Unscrewing nuts and battery cell removal are selected to verify the effectiveness of the proposed algorithms based on the battery disassembly experimental platform. In this study, the effectiveness of the algorithms designed in this paper is measured by the success rate and error of the task execution. In the task of unscrewing nuts, the success rate of the classical DMP is 57.14% and the maximum error is 2.760 mm. After the optimisation of 1D-SEG, G-PRM, and Bi-DMP, the success rate of the task is increased to 100% and the maximum error is reduced to 1.477 mm. Full article
(This article belongs to the Section Robotics and Automation)
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19 pages, 12293 KiB  
Article
Disturbance Propagation Model of Luggage Drifting Motion Based on Nonlinear Pressure in Typical Passenger Corridors of Transportation Hubs
by Bingyu Wei, Rongyong Zhao, Cuiling Li, Miyuan Li, Yunlong Ma and Eric S. W. Wong
Appl. Sci. 2024, 14(11), 4942; https://doi.org/10.3390/app14114942 - 6 Jun 2024
Viewed by 270
Abstract
In current transportation hubs, passengers travelling with wheeled luggage or suitcases is a common phenomenon. Due to the fact that most luggage occupies a certain space in dense passenger crowds with high mass inertia, its abnormal motion, such as drifting, can frequently trigger [...] Read more.
In current transportation hubs, passengers travelling with wheeled luggage or suitcases is a common phenomenon. Due to the fact that most luggage occupies a certain space in dense passenger crowds with high mass inertia, its abnormal motion, such as drifting, can frequently trigger unavoidable local disturbances and turbulence in the surrounding pedestrian flows, further increasing congestion risk. Meanwhile, there still is a lack of quantitative disturbance propagation analysis, since most state-of-the-art achievements rely on either scenario-based experiments or the spatial characteristics of crowd distribution assessed qualitatively. Therefore, this study considers the luggage-laden passenger as a deformable particle. The resulting disturbance on surrounding non-luggage-carrying passengers is analyzed and quantified into a nonlinear pressure term. Subsequently, the disturbance propagation model of passenger-owned luggage is developed by adapting the classical Aw–Rascle traffic flow model with a pressure term. Simulation experiments of disturbances caused by luggage drifting and retrograding were conducted in Pathfinder 2022 Software. Experimental results showed that the disturbing force of a left-sided crowd can reach a peak of 238 N with a passenger density of 3.0 p/m2, and the maximum force difference between the left- and right-sided disturbing force can reach 153 N, as confirmed by a case study in an L-shaped corridor of a transportation hub. Furthermore, it is recommended that the proposed model can be applied in crowd flow analysis and intelligent decision-making for passenger management in transportation hubs. Full article
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10 pages, 4747 KiB  
Article
Combustion and Emission Characteristics of a Diesel Engine with a Variable Injection Rate
by Jun Chen, Guanyu Shi, Jinzhe Wu, Chenghao Cao, Lei Zhou, Wu Xu, Sheng Wang and Xiaofeng Li
Appl. Sci. 2024, 14(11), 4941; https://doi.org/10.3390/app14114941 - 6 Jun 2024
Viewed by 284
Abstract
Diesel engine combustion is dependent mainly on the fuel injection characteristics, particularly the injection pressure and rate, which directly affect the engine efficiency and emissions. Herein, an electrically controlled supercharger is added to a traditional high-pressure common rail system to form an ultrahigh-pressure [...] Read more.
Diesel engine combustion is dependent mainly on the fuel injection characteristics, particularly the injection pressure and rate, which directly affect the engine efficiency and emissions. Herein, an electrically controlled supercharger is added to a traditional high-pressure common rail system to form an ultrahigh-pressure common rail system. Then, the variations in the spray, combustion, and emission characteristics of a diesel engine with a variable fuel injection rate are analyzed. Moreover, a simulation model for a diesel engine combustion chamber is built and verified by experimental results for numerical analysis. The results reveal that the injection rate can be flexibly adjusted via regulation when the solenoid valves are opened on the electrically controlled supercharger. Specifically, (1) the boot-shaped injection rate has greater potential than the traditional rectangular injection rate in terms of combustion and emission; (2) the main injection advance angle at the boot-shaped injection rate can be properly increased to improve combustion; and (3) the pilot injection quantity and advance angle are strongly coupled with the boot-shaped injection rate, potentially enhancing the mixing efficiency of fuel and air in the cylinder to achieve favorable emission results. This paper provides good guidance for the reliable design and optimization of noble-metal-based diesel engines. Full article
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26 pages, 3626 KiB  
Review
Bioactive Compounds, Health Benefits and Food Applications of Artichoke (Cynara scolymus L.) and Artichoke By-Products: A Review
by Pablo Ayuso, Jhazmin Quizhpe, María de los Ángeles Rosell, Rocío Peñalver and Gema Nieto
Appl. Sci. 2024, 14(11), 4940; https://doi.org/10.3390/app14114940 - 6 Jun 2024
Viewed by 410
Abstract
Cynara scolymus L. is an herbaceous plant originally from the western Mediterranean area, with Italy, Spain and France the main being producers. Both the edible flowering head and the by-products generated during processing (outer bracts, leaves and stem) are characterized by a high [...] Read more.
Cynara scolymus L. is an herbaceous plant originally from the western Mediterranean area, with Italy, Spain and France the main being producers. Both the edible flowering head and the by-products generated during processing (outer bracts, leaves and stem) are characterized by a high content of essential vitamins, minerals and bioactive compounds. In particular, the leaves represent a great source of phenolic acids derived from caffeoylquinic acid or flavonoids such as luteonin and apigenin, while the head and stem contain a high content of soluble and insoluble dietary fiber, especially inulin and pectins. Its high content of bioactive compounds provides artichoke a high antioxidant power due to the modulation effect of the transcription factor Nrf2, which may lead to protection against cardiovascular, hepatic and neurological disorders. The potential use of artichoke as a functional ingredient in the food industry may be promising in terms of improving the nutritional value of products, as well as preventing oxidation and extending the shelf-life of processed foods due to its antimicrobial activity. This review aims to provide an overview of the nutritional qualities of Cynara scolymus L. and its by-products, focusing on the possible health effects and potential applications in food products as a higher-value-added alternative ingredient. Full article
(This article belongs to the Special Issue Antioxidant Compounds in Food Processing)
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15 pages, 5025 KiB  
Article
Estimation of Critical Fatigue Conditions Based on the Accelerated Fatigue Locati Method by Mean of Net Damage
by Isidro A. Carrascal, Soraya Diego, Jose A. Casado, Jose A. Sainz-Aja and Diego Ferreño
Appl. Sci. 2024, 14(11), 4939; https://doi.org/10.3390/app14114939 - 6 Jun 2024
Viewed by 264
Abstract
The increasing utilization of short fiber-reinforced thermoplastics, due to their advantageous mechanical properties and manufacturing convenience, has led to their application in areas traditionally dominated by metals. This shift underscores the importance of understanding the fatigue behavior of these materials. This study evaluates [...] Read more.
The increasing utilization of short fiber-reinforced thermoplastics, due to their advantageous mechanical properties and manufacturing convenience, has led to their application in areas traditionally dominated by metals. This shift underscores the importance of understanding the fatigue behavior of these materials. This study evaluates the fatigue behavior of short fiber-reinforced thermoplastics through three characterization methods: continuous fatigue, interrupted fatigue, and the Locati method, with the latter serving as a novel approach for estimating critical fatigue conditions from a single specimen. Continuous fatigue testing provides the baseline for comparison. The effect of load interruption is explored through the interrupted fatigue method. The Locati method, characterized by incrementally increasing load steps until failure, offers a significant benefit by enabling the estimation of critical fatigue conditions efficiently. This research aims to provide a comprehensive understanding of the fatigue behavior of short fiber-reinforced thermoplastics, contributing to the optimization of their use in engineering applications. Full article
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8 pages, 21672 KiB  
Article
Effect of Near Ultraviolet Radiation on Varroa Destructor Using Digital Holographic Interferometry
by José Luis Silva-Acosta, Tonatiuh Saucedo-Anaya, Fernando Mendoza-Santoyo, María Del Socorro Hernández-Montes, Carlos Guerrero-Mendez, Daniel Gaytán-Saldaña and Bruno Saucedo-Orozco
Appl. Sci. 2024, 14(11), 4938; https://doi.org/10.3390/app14114938 - 6 Jun 2024
Viewed by 311
Abstract
The incessant threat posed by the Varroa destructor mite to bee colonies has spurred extensive research into control strategies. One of these strategies involves ultraviolet radiation, aiming to harness the damaging effects that this type of radiation induces in arthropods. This study focuses [...] Read more.
The incessant threat posed by the Varroa destructor mite to bee colonies has spurred extensive research into control strategies. One of these strategies involves ultraviolet radiation, aiming to harness the damaging effects that this type of radiation induces in arthropods. This study focuses on investigating the potential influence of near ultraviolet (UVA) radiation on the surface damage incurred by Varroa destructor. To address this inquiry, multiple specimens were continuously irradiated with UVA while digital holograms were recorded. To assess surface damage, these holographic records were processed and analyzed. It was found that exposure to radiation induces subtle swelling, around a few tenths of micrometers, which is more pronounced around the anal shield and genital shield of the mite. These alterations could impact the health and viability of this parasitic mite. This is the first time that the measurement and quantification of this superficial damage is reported, contributing to the understanding of the impact of UVA irradiation on the external structure of the mite. Full article
(This article belongs to the Special Issue Digital Holography: Advancements, Applications, and Challenges)
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15 pages, 4373 KiB  
Article
Application Strategy of Unmanned Aerial Vehicle Swarms in Forest Fire Detection Based on the Fusion of Particle Swarm Optimization and Artificial Bee Colony Algorithm
by Xiaohong Yan and Renwen Chen
Appl. Sci. 2024, 14(11), 4937; https://doi.org/10.3390/app14114937 - 6 Jun 2024
Viewed by 224
Abstract
Unmanned aerial vehicle (UAV) swarm intelligence technology has shown unique advantages in agricultural and forestry disaster detection, early warning, and prevention with its efficient and precise cooperative operation capability. In this paper, a systematic application strategy of UAV swarms in forest fire detection [...] Read more.
Unmanned aerial vehicle (UAV) swarm intelligence technology has shown unique advantages in agricultural and forestry disaster detection, early warning, and prevention with its efficient and precise cooperative operation capability. In this paper, a systematic application strategy of UAV swarms in forest fire detection is proposed, including fire point detection, fire assessment, and control measures, based on the fusion of particle swarm optimization (PSO) and the artificial bee colony (ABC) algorithm. The UAV swarm application strategy provides optimized paths to quickly locate multiple mountain forest fire points in 3D forest modeling environments and control measures based on the analysis of the fire situation. This work lays a research foundation for studying the precise application of UAV swarm technology in real-world forest fire detection and prevention. Full article
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17 pages, 1685 KiB  
Article
Active Collision Avoidance for Robotic Arm Based on Artificial Potential Field and Deep Reinforcement Learning
by Qiaoyu Xu, Tianle Zhang, Kunpeng Zhou, Yansong Lin and Wenhao Ju
Appl. Sci. 2024, 14(11), 4936; https://doi.org/10.3390/app14114936 - 6 Jun 2024
Viewed by 241
Abstract
To address the local minimum issue commonly encountered in active collision avoidance using artificial potential field (APF), this paper presents a novel algorithm that integrates APF with deep reinforcement learning (DRL) for robotic arms. Firstly, to improve the training efficiency of DRL for [...] Read more.
To address the local minimum issue commonly encountered in active collision avoidance using artificial potential field (APF), this paper presents a novel algorithm that integrates APF with deep reinforcement learning (DRL) for robotic arms. Firstly, to improve the training efficiency of DRL for the collision avoidance problem, Hindsight Experience Replay (HER) was enhanced by adjusting the positions of obstacles, resulting in Hindsight Experience Replay for Collision Avoidance (HER-CA). Subsequently, A robotic arm collision avoidance action network model was trained based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) and HER-CA methods. Further, a full-body collision avoidance potential field model of the robotic arm was established based on the artificial potential field. Lastly, the trained action network model was used to guide APF in real-time collision avoidance planning. Comparative experiments between HER and HER-CA were conducted. The model trained with HER-CA improves the average success rate of the collision avoidance task by about 10% compared to the model trained with HER. And a collision avoidance simulation was conducted on the rock drilling robotic arm, confirming the effectiveness of the guided APF method. Full article
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27 pages, 20444 KiB  
Article
Investigating User Experience of an Immersive Virtual Reality Simulation Based on a Gesture-Based User Interface
by Teemu H. Laine and Hae Jung Suk
Appl. Sci. 2024, 14(11), 4935; https://doi.org/10.3390/app14114935 - 6 Jun 2024
Viewed by 384
Abstract
The affordability of equipment and availability of development tools have made immersive virtual reality (VR) popular across research fields. Gesture-based user interface has emerged as an alternative method to handheld controllers to interact with the virtual world using hand gestures. Moreover, a common [...] Read more.
The affordability of equipment and availability of development tools have made immersive virtual reality (VR) popular across research fields. Gesture-based user interface has emerged as an alternative method to handheld controllers to interact with the virtual world using hand gestures. Moreover, a common goal for many VR applications is to elicit a sense of presence in users. Previous research has identified many factors that facilitate the evocation of presence in users of immersive VR applications. We investigated the user experience of Four Seasons, an immersive virtual reality simulation where the user interacts with a natural environment and animals with their hands using a gesture-based user interface (UI). We conducted a mixed-method user experience evaluation with 21 Korean adults (14 males, 7 females) who played Four Seasons. The participants filled in a questionnaire and answered interview questions regarding presence and experience with the gesture-based UI. The questionnaire results indicated high ratings for presence and gesture-based UI, with some issues related to the realism of interaction and lack of sensory feedback. By analyzing the interview responses, we identified 23 potential presence factors and proposed a classification for organizing presence factors based on the internal–external and dynamic–static dimensions. Finally, we derived a set of design principles based on the potential presence factors and demonstrated their usefulness for the heuristic evaluation of existing gesture-based immersive VR experiences. The results of this study can be used for designing and evaluating presence-evoking gesture-based VR experiences. Full article
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19 pages, 6295 KiB  
Article
A CNN-LSTM-Attention Model for Near-Crash Event Identification on Mountainous Roads
by Jing Zhao, Wenchen Yang and Feng Zhu
Appl. Sci. 2024, 14(11), 4934; https://doi.org/10.3390/app14114934 - 6 Jun 2024
Viewed by 260
Abstract
To enhance traffic safety on mountainous roads, this study proposes an innovative CNN-LSTM-Attention model designed for the identification of near-crash events, utilizing naturalistic driving data from the challenging terrains in Yunnan, China. A combination of a threshold method complemented by manual verification is [...] Read more.
To enhance traffic safety on mountainous roads, this study proposes an innovative CNN-LSTM-Attention model designed for the identification of near-crash events, utilizing naturalistic driving data from the challenging terrains in Yunnan, China. A combination of a threshold method complemented by manual verification is used to label and annotate near-crash events within the dataset. The importance of vehicle motion features is evaluated using the random forest algorithm, revealing that specific variables, including x-axis acceleration, y-axis acceleration, y-axis angular velocity, heading angle, and vehicle speed, are particularly crucial for identifying near-crash events. Addressing the limitations of existing models in accurately detecting near-crash scenarios, this study combines the strengths of convolutional neural networks (CNN), long short-term memory (LSTM) networks, and an attention mechanism to enhance model sensitivity to crucial temporal and spatial features in naturalistic driving data. Specifically, the CNN-LSTM-Attention model leverages CNN to extract local features from the driving data, employs LSTM to track temporal dependencies among feature variables, and uses the attention mechanism to dynamically fine-tune the network weights of feature parameters. The efficacy of the proposed model is extensively evaluated against six comparative models: CNN, LSTM, Attention, CNN-LSTM, CNN-Attention, and LSTM-Attention. In comparison to the benchmark models, the CNN-LSTM-Attention model achieves superior overall accuracy at 98.8%. Moreover, it reaches a precision rate of 90.1% in detecting near-crash events, marking an improvement of 31.6%, 14.8%, 63.5%, 8%, 23.5%, and 22.6% compared to the other six comparative models, respectively. Full article
(This article belongs to the Special Issue Traffic Emergency: Forecasting, Control and Planning)
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19 pages, 6054 KiB  
Article
Smart Electric Three-Wheeled Unit for the Manufacturing Industry
by Juraj Kováč, Peter Malega and Jozef Svetlík
Appl. Sci. 2024, 14(11), 4933; https://doi.org/10.3390/app14114933 - 6 Jun 2024
Viewed by 299
Abstract
This article presents the design of a smart three-wheeled unit for the manufacturing industry with the aim of optimizing and automating internal logistical processes. It presents an innovative solution that combines the advantages of mobility, intelligent transportation technology, and smart devices to ensure [...] Read more.
This article presents the design of a smart three-wheeled unit for the manufacturing industry with the aim of optimizing and automating internal logistical processes. It presents an innovative solution that combines the advantages of mobility, intelligent transportation technology, and smart devices to ensure the efficient movement of materials and raw materials in manufacturing facilities. The article describes the design, production, and testing of the tricycle in a real manufacturing environment of the production system and the testing of the proposed smart devices. It evaluates the advantages of the electric smart tricycle, including increased efficiency, reduced costs, and more flexible production processes. The results of this study suggest that the intelligent three-wheeled unit represents a promising technological innovation with the potential to increase competitiveness and productivity in manufacturing enterprises. Full article
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17 pages, 15456 KiB  
Article
New Design of Personal Protective Equipment for Handling Contagious Viruses: Evaluation of Comfort and Physiological Responses
by Totong Totong, Herman Rahadian Soetisna, Titis Wijayanto and Hardianto Iridiastadi
Appl. Sci. 2024, 14(11), 4932; https://doi.org/10.3390/app14114932 - 6 Jun 2024
Viewed by 271
Abstract
The use of personal protective equipment (PPE) for virus handling has the side effect of heat stress, which requires intervention to improve. This study aimed to evaluate the comfort of a newly designed PPE ensemble for virus handling. Three types of PPE ensembles [...] Read more.
The use of personal protective equipment (PPE) for virus handling has the side effect of heat stress, which requires intervention to improve. This study aimed to evaluate the comfort of a newly designed PPE ensemble for virus handling. Three types of PPE ensembles were tested: reg-ular PPE as a control, PPE plus breathable cooling wear (cooling wear), and PPE plus a portable airflow cooling device (cooling device). Twelve participants simulated six activities, including physical activities, activities requiring concentration, and manual dexterity activities, for one hour. The microclimate conditions, perceived discomfort, and physiological responses were measured after each experimental activity. The results show that the use of cooling wear and a cooling device had a significant effect on the microclimate conditions, perceived comfort, and physiological responses of users, proving superior to the use of regular PPE. A cooling device can improve the microclimate more than cooling wear, thereby directly increasing perceived comfort and decreasing physiological responses. It can be concluded that the use of cooling wear and a cooling device effectively increases the comfort of wearing PPE. The cooling device is more suitable for use in tropical climates with hot and humid characteristics, so it is a better choice than cooling wear. Full article
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18 pages, 5680 KiB  
Article
Sustainable and Inflatable Aeroponics Smart Farm System for Water Efficiency and High-Value Crop Production
by Junhui Kim, Haeyoung Park, Chungmo Seo, Hyunjin Kim, Gyuseung Choi, Minho Kim, Byungjoo Kim and Wonhyong Lee
Appl. Sci. 2024, 14(11), 4931; https://doi.org/10.3390/app14114931 - 6 Jun 2024
Viewed by 351
Abstract
Existing smart farming technology faces sustainability challenges due to high costs and environmental pollution. This study introduces a novel, sealed smart farming system utilizing misting technology to address these limitations. The system is designed to efficiently use water and nutrients, making it particularly [...] Read more.
Existing smart farming technology faces sustainability challenges due to high costs and environmental pollution. This study introduces a novel, sealed smart farming system utilizing misting technology to address these limitations. The system is designed to efficiently use water and nutrients, making it particularly suitable for high-value crop cultivation in urban environments with architectural constraints. Over a one-month experimental period, we monitored the system’s performance in a controlled environment. The methodology included setting up the system and regularly measuring water usage, nutrient delivery, and plant growth metrics. The experimental results showed a significant reduction in water usage compared to traditional methods, with precise control of micronutrient delivery. Additionally, the system’s ability to maintain a consistent sealed environment was demonstrated, which is crucial for optimal plant growth. The system’s portability and space utilization efficiency were also highlighted as major advantages. Furthermore, the system demonstrated potential for cultivation in extreme environments, such as water-scarce regions, by maintaining optimal indoor conditions for crop growth. Challenges such as nozzle clogging and uneven mist distribution were identified, indicating the need for further research in cartridge design and misting methods. Overall, this smart farming technology shows significant promise for enhancing global food security and contributing to sustainable agricultural development by minimizing water usage and optimizing nutrient management. Full article
(This article belongs to the Special Issue New Development in Smart Farming for Sustainable Agriculture)
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13 pages, 472 KiB  
Article
Examining Memory Performance in Senior Adults: A Comparative Cross-Sectional Study
by Noelia Lago-Priego, Iván Otero-González, Moisés Pacheco-Lorenzo, Manuel J. Fernández-Iglesias, Carlos Dosil-Díaz, César Bugallo-Carrera, Manuel Gandoy-Crego and Luis Anido-Rifón
Appl. Sci. 2024, 14(11), 4930; https://doi.org/10.3390/app14114930 - 6 Jun 2024
Viewed by 263
Abstract
This study investigates memory performance among 73 adults over 60 years old, utilising Memory Impairment Screening (MIS) and self-reported memory failures assessed by the Memory Failures in Everyday questionnaire (MFE-28). Participants were divided into four groups: individuals with depressive symptoms, healthy individuals, individuals [...] Read more.
This study investigates memory performance among 73 adults over 60 years old, utilising Memory Impairment Screening (MIS) and self-reported memory failures assessed by the Memory Failures in Everyday questionnaire (MFE-28). Participants were divided into four groups: individuals with depressive symptoms, healthy individuals, individuals with depressive symptoms and mild cognitive impairment, and individuals with mild cognitive impairment only. Groups were organised according to their Montreal Cognitive Assessment (MoCA) and the 15-item Geriatric Depression Scale (GDS-15) scores. The study aims to analyse MIS scores and self-reported memory failures across these groups as measured with the 28-item Memory Failures Everyday (MFE-28) scale. Correlation analyses were conducted for the complete sample, while variance analyses were carried out for the four classification groups above. Bivariate linear regression analysis was carried out to explore how the combination of cognitive and depressive symptoms status influenced memory performance. Results show that subjective memory complaints and memory performance are related to depressive symptoms, and the latter is associated with worse cognitive performance. Lastly, our study highlights that individuals with mild cognitive impairment and depressive symptoms exhibit worse performance in recall tasks and report more subjective memory complaints compared to those with mild cognitive impairment alone. Full article
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