Applied Sciences

13 pages, 2731 KiB

Open AccessArticle

EPR Spectroscopy Coupled with Spin Trapping as an Alternative Tool to Assess and Compare the Oxidative Stability of Vegetable Oils for Cosmetics

by Giulia Di Prima, Viviana De Caro, Cinzia Cardamone, Giuseppa Oliveri and Maria Cristina D’Oca

Appl. Sci. 2024, 14(22), 10766; https://doi.org/10.3390/app142210766 - 20 Nov 2024

Viewed by 264

Abstract

Antioxidants are the most popular active ingredients in anti-aging cosmetics as they can restore the physiological radical balance and counteract the photoaging process. Instead of adding pure compounds into the formulations, some “precious” vegetable oils could be used due to their content of [...] Read more.

Antioxidants are the most popular active ingredients in anti-aging cosmetics as they can restore the physiological radical balance and counteract the photoaging process. Instead of adding pure compounds into the formulations, some “precious” vegetable oils could be used due to their content of tocopherols, phenols, vitamins, etc., constituting a powerful antioxidant unsaponifiable fraction. Here, electron paramagnetic resonance (EPR) spectroscopy coupled with spin trapping was proven to provide a valid method for evaluating the antioxidant properties and the oxidative resistance of vegetable oils which, following UV irradiation, produce highly reactive radical species although hardly detectable. Extra virgin olive oil, sweet almond oil, apricot kernel oil, and jojoba oil were then evaluated by using N-t-butyl-α-phenylnitrone as a spin trapper and testing different UV irradiation times followed by incubation for 5 to 180 min at 70 °C. The EPR spectra were manipulated to obtain quantitative information useful for comparing the different tested samples. As a result, the knowledge acquired via the EPR analyses demonstrated jojoba oil as the best of the four considered oils in terms of both starting antioxidant ability and oxidative stability overtime. The obtained results confirmed the usefulness of the EPR spin trapping technique for the main proposed purpose. Full article

(This article belongs to the Special Issue New Insights in Functional Cosmetic Materials and Industrial Manufacture)

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21 pages, 2088 KiB

Open AccessArticle

Study of the Applicability of Thermochemical Processes for Solid Recovered Fuel

by Juan Jesús de la Torre-Bayo, Montserrat Zamorano, Juan Carlos Torres-Rojo, Noemí Gil-Lalaguna, Gloria Gea, Isabel Fonts and Jaime Martín-Pascual

Appl. Sci. 2024, 14(22), 10765; https://doi.org/10.3390/app142210765 - 20 Nov 2024

Viewed by 306

Abstract

Within the context of the new circular model for wastewater treatment aimed at achieving zero waste, this research seeks an alternative to landfill disposal of waste screenings. It examines the feasibility of thermochemical processes—combustion and gasification—for the valorisation of solid recovered fuel (SRF) [...] Read more.

Within the context of the new circular model for wastewater treatment aimed at achieving zero waste, this research seeks an alternative to landfill disposal of waste screenings. It examines the feasibility of thermochemical processes—combustion and gasification—for the valorisation of solid recovered fuel (SRF) derived from screening wastes, which are the only waste in wastewater treatment plants (WWTPs) that typically have an absence of existing recycling or valorisation processes. Laboratory-scale experiments assessed the technical viability of gasification, and energy balances were calculated for both combustion and the syngas obtained from gasification experiments. Results indicate that both processes are feasible for SRF valorisation. Combustion demonstrated the highest energy efficiency, yielding up to 1.6 MJ per kg of raw SRF, compared to gasification’s maximum of 1.4 MJ. The moisture content in SRF feedstock influences both processes, underscoring the need to optimise moisture levels. Additionally, combustion showed a higher conversion efficiency due to the complete oxidation of the feedstock, whereas gasification produced valuable syngas that can be further utilised for energy production or as a chemical feedstock. The study concludes that, from a purely energetic perspective, combustion is the most efficient process for SRF valorisation. However, gasification offers significant environmental and sustainability advantages, including lower greenhouse gas emissions and the potential for integrating with renewable energy systems, making it a more attractive option for long-term sustainability goals. Full article

(This article belongs to the Special Issue Application of Municipal/Industrial Solid and Liquid Waste in Energy Area, 2nd Edition)

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13 pages, 46604 KiB

Open AccessArticle

Human Activity Recognition Based on Point Clouds from Millimeter-Wave Radar

by Seungchan Lim, Chaewoon Park, Seongjoo Lee and Yunho Jung

Appl. Sci. 2024, 14(22), 10764; https://doi.org/10.3390/app142210764 - 20 Nov 2024

Viewed by 263

Abstract

Human activity recognition (HAR) technology is related to human safety and convenience, making it crucial for it to infer human activity accurately. Furthermore, it must consume low power at all times when detecting human activity and be inexpensive to operate. For this purpose, [...] Read more.

Human activity recognition (HAR) technology is related to human safety and convenience, making it crucial for it to infer human activity accurately. Furthermore, it must consume low power at all times when detecting human activity and be inexpensive to operate. For this purpose, a low-power and lightweight design of the HAR system is essential. In this paper, we propose a low-power and lightweight HAR system using point-cloud data collected by radar. The proposed HAR system uses a pillar feature encoder that converts 3D point-cloud data into a 2D image and a classification network based on depth-wise separable convolution for lightweighting. The proposed classification network achieved an accuracy of 95.54%, with 25.77 M multiply–accumulate operations and 22.28 K network parameters implemented in a 32 bit floating-point format. This network achieved 94.79% accuracy with 4 bit quantization, which reduced memory usage to 12.5% compared to existing 32 bit format networks. In addition, we implemented a lightweight HAR system optimized for low-power design on a heterogeneous computing platform, a Zynq UltraScale+ ZCU104 device, through hardware–software implementation. It took 2.43 ms of execution time to perform one frame of HAR on the device and the system consumed 3.479 W of power when running. Full article

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13 pages, 1236 KiB

Open AccessArticle

Comparative Analysis of Chemical Composition and Radical-Scavenging Activities in Two Wheat Cultivars

by Nari Yoon, Sung-Hwan Jeong, Jong-Suk Park, Woo Jung Kim and Sanghyun Lee

Appl. Sci. 2024, 14(22), 10763; https://doi.org/10.3390/app142210763 - 20 Nov 2024

Viewed by 285

Abstract

Triticum aestivum (wheat) is one of the most significant crops worldwide. This study compares the chemical composition and radical-scavenging activities of two cultivars of T. aestivum, Saekeumkang wheat (SW) and Baekkang wheat (BW). Sprouted wheatgrass extracts of SW and BW were analyzed [...] Read more.

Triticum aestivum (wheat) is one of the most significant crops worldwide. This study compares the chemical composition and radical-scavenging activities of two cultivars of T. aestivum, Saekeumkang wheat (SW) and Baekkang wheat (BW). Sprouted wheatgrass extracts of SW and BW were analyzed using assessments of total polyphenol and flavonoid contents, liquid chromatography–electrospray ionization/mass spectrometry (LC-ESI/MS), and high-performance liquid chromatography with a photodiode array (HPLC-PDA). Radical-scavenging activities were evaluated using 2,2-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS·⁺) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. The results indicated that SW had a higher total polyphenol content than BW, while no significant differences were observed regarding total flavonoid content. HPLC-PDA analysis, guided by LC-ESI/MS, identified four compounds—saponarin, schaftoside, isoorientin, and isovitexin—with isoorientin (3.02 mg/g extract) and schaftoside (4.23 mg/g extract) present in higher concentrations in SW compared to BW. In the ABTS·⁺ assay, the two samples did not show noticeable differences, with SW displaying a scavenging ability with an IC₅₀ of 3.36 mg/mL, and BW with an IC₅₀ of 3.19 mg/mL. Contrarily, the DPPH assay results showed an inverse trend, suggesting that the radical-scavenging behavior may be influenced by the synergistic and antagonistic interactions of the compounds in SW and BW extracts. Full article

(This article belongs to the Special Issue Advances in Bioactive Compounds from Plants and Their Applications)

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19 pages, 6034 KiB

Open AccessArticle

GMN+: A Binary Homologous Vulnerability Detection Method Based on Graph Matching Neural Network with Enhanced Attention

by Zheng Zhao, Tianhao Zhang, Xiaoya Fan, Qian Mao, Dafeng Wang and Qi Zhao

Appl. Sci. 2024, 14(22), 10762; https://doi.org/10.3390/app142210762 - 20 Nov 2024

Viewed by 342

Abstract

The widespread reuse of code in the open-source community has led to the proliferation of homologous vulnerabilities, which are security flaws propagated across diverse software systems through the reuse of vulnerable code. Such vulnerabilities pose serious cybersecurity risks, as attackers can exploit the [...] Read more.

The widespread reuse of code in the open-source community has led to the proliferation of homologous vulnerabilities, which are security flaws propagated across diverse software systems through the reuse of vulnerable code. Such vulnerabilities pose serious cybersecurity risks, as attackers can exploit the same weaknesses across multiple platforms. Deep learning has emerged as a promising approach for detecting homologous vulnerabilities in binary code due to their automated feature extraction and high efficiency. However, existing deep learning methods often struggle to capture deep semantic features in binary code, limiting their effectiveness. To address this limitation, this paper presents GMN+, which is a novel graph matching neural network with enhanced attention for detecting homologous vulnerabilities. This method comprehensively considers the information contained in instructions and incorporates types of input instruction. Masked Language Modeling and Instruction Type Prediction are developed as pre-training tasks to enhance the ability of GMN+ in extracting semantic information from basic blocks. GMN+ utilizes an attention mechanism to focus concurrently on the critical semantic information within functions and differences between them, generating robust function embeddings. Experimental results indicate that GMN+ outperforms state-of-the-art methods in various tasks and achieves notable performance in real-world vulnerability detection scenarios. Full article

(This article belongs to the Special Issue Artificial Intelligence for Cybersecurity: Latest Advances and Prospects)

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22 pages, 1159 KiB

Open AccessArticle

Energetic Analysis of Passive Solar Strategies for Residential Buildings with Extreme Summer Conditions

by Stephanny Nogueira, Ana I. Palmero-Marrero, David Borge-Diez, Emin Açikkalp and Armando C. Oliveira

Appl. Sci. 2024, 14(22), 10761; https://doi.org/10.3390/app142210761 - 20 Nov 2024

Viewed by 316

Abstract

This study investigates the implementation of passive design strategies to improve the thermal environment in the extremely hot climates of Brazil, Portugal, and Turkey. Given the rising cooling demands due to climate change, optimizing energy efficiency in buildings is essential. Using the Trace [...] Read more.

This study investigates the implementation of passive design strategies to improve the thermal environment in the extremely hot climates of Brazil, Portugal, and Turkey. Given the rising cooling demands due to climate change, optimizing energy efficiency in buildings is essential. Using the Trace 3D Plus v6.00.106 software, typical residential buildings for each country were simulated to assess various passive solutions, such as building orientation, wall and roof modifications, glazing optimization options, window-to-wall ratio (WTWR) reduction, shading, and natural ventilation. The findings highlight that Brazil experienced the higher discomfort temperatures compared to Mediterranean climates, with indoor air temperatures exceeding 28 °C all year round and remaining between 34 °C and 37 °C for nearly 40% of the time. Building orientation had a minimal impact near the equator, while Mediterranean climates benefited from an up to 10% variation in energy demand. Thermal insulation combined with white exterior paint resulted in Şanlıurfa experiencing annual energy savings of up to 26%. Optimal roof solutions yielded a 19% demand reduction in Évora, while WTWR reduction and double-colored glazing achieved up to a 35% reduction in Évora and 19% in other regions. Combined strategies achieved energy demand reductions of 44% for Évora, 40% for Şanlıurfa, and 32% for Teresina. The study emphasizes the need for integrated, climate-specific passive solutions, showing their potential to enhance both energy efficiency and the thermal environment in residential buildings across diverse hot climates. Full article

(This article belongs to the Special Issue Energy Efficiency and Thermal Comfort in Buildings)

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23 pages, 6823 KiB

Open AccessArticle

Construction of Green Space Ecological Network in Xiongan New Area Based on the MSPA–InVEST–MCR Model

by Xiaoqi Feng, Zhiyu Du, Peiyuan Tao, Huaqiu Liang, Yangzi Wang and Xin Wang

Appl. Sci. 2024, 14(22), 10760; https://doi.org/10.3390/app142210760 - 20 Nov 2024

Viewed by 436

Abstract

With the rapid pace of urbanization, the integrity and connectivity of ecosystems are under serious threat, making biodiversity conservation a top priority. We use the Xiongan New Area in China as a case study to explore the significance and application of constructing urban [...] Read more.

With the rapid pace of urbanization, the integrity and connectivity of ecosystems are under serious threat, making biodiversity conservation a top priority. We use the Xiongan New Area in China as a case study to explore the significance and application of constructing urban ecological networks in the development of new cities. This study systematically applied the categorization of green space systems using remote sensing technology; MSPA was used to identify key landscape patches; InVEST was employed to assess habitat quality; and potential ecological corridors were established using the minimum cumulative resistance model (MCR). Moreover, targeted recommendations for optimizing ecological green spaces were put forward. The findings demonstrate that the Xiongan New Area has significant potential and needs for ecological network construction, and it faces the issue of ecological network fragmentation. This research highlights the significance of developing ecological networks within urban planning and proposes optimization strategies tailored to these networks. The objective is to offer scientific guidance for the design and development of emerging cities, such as the Xiongan New Area, to facilitate the alignment and integration of ecological preservation efforts with urban expansion, ultimately achieving the sustainable development goal of harmonious coexistence between the environment and urban areas. Full article

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12 pages, 276 KiB

Open AccessArticle

Quantum Private Comparison Based on Four-Particle Cluster State

by Min Hou and Yue Wu

Appl. Sci. 2024, 14(22), 10759; https://doi.org/10.3390/app142210759 - 20 Nov 2024

Viewed by 307

Abstract

A quantum private comparison (QPC) protocol enables two parties to securely compare their private data without disclosing the actual values to one another, utilizing quantum mechanics to maintain confidentiality. Many current QPC protocols mainly concentrate on comparing the equality of private information between [...] Read more.

A quantum private comparison (QPC) protocol enables two parties to securely compare their private data without disclosing the actual values to one another, utilizing quantum mechanics to maintain confidentiality. Many current QPC protocols mainly concentrate on comparing the equality of private information between two users during a single execution, which restricts their scalability. To overcome this limitation, we present an efficient QPC protocol aimed at evaluating the equality of private information between two groups of users in one execution. This is achieved by leveraging the entanglement correlations present in each particle of a four-particle cluster state. In our approach, users encode their private data using bit flip or phase shift operators on the quantum sequence they receive, which is then sent back to a semi-trusted party which then determines whether the secrets of the two groups are equal and communicates the results to the users. By employing this method and facilitating the distributed transmission of the quantum sequence, our protocol achieves a qubit efficiency of 50%. Security analyses reveal that neither external attacks nor insider threats can successfully compromise the confidentiality of private data. Full article

(This article belongs to the Special Issue Quantum Communication and Applications)

16 pages, 5966 KiB

Open AccessArticle

Assessment of Hoisting Conveyance Guiding Forces Based on Field Acceleration Measurements and Numerical Simulation

by Przemysław Fiołek and Jacek Jakubowski

Appl. Sci. 2024, 14(22), 10758; https://doi.org/10.3390/app142210758 - 20 Nov 2024

Viewed by 290

Abstract

Shafts play a key role in the operation of mining plants. They connect underground excavations with the surface and provide the ability to transport people, equipment, and raw materials. The nature of the dynamic interaction of a conveyance moving at a significant speed [...] Read more.

Shafts play a key role in the operation of mining plants. They connect underground excavations with the surface and provide the ability to transport people, equipment, and raw materials. The nature of the dynamic interaction of a conveyance moving at a significant speed along deformed guide rails is complex, and the method of assessing the interaction of hoisting conveyances with shaft steelwork, despite ongoing research, still requires further understanding and improvement. Misalignments of the guide rails and conveyance movements transverse to the shaft axis induce impact (guiding) forces, which are the key design parameters of shaft steelwork. The reliable assessment of guiding forces allows the design of safe and economical steelworks and the assessment of their structural safety during operation under deformations and corrosive deterioration. Determining the value of guiding forces requires their field measurements or the use of approximate empirical formulas. Both methods have their limitations—measurement is expensive and interferes with normal shaft operation, while empirical formulas are subject to high error due to the lack of consideration of many structural details specific to each shaft that significantly affect the behavior of the system. This study presents a new method for using a relatively simple-to-implement measurement of hoisting conveyance acceleration to assess guiding forces. A finite element model of the skip and steelwork was built, and simulations of the conveyance interaction with the structure were carried out. A strong relationship between the sliding plate’s impact point location and the guiding force was found. Extreme values of the guiding force were observed in the vicinity of the bunton connection. The study showed that reducing the skip load mass does not affect the force value. Simplified methods of calculating the moments of inertia of the hoisting conveyance significantly overestimate the code-based values of the guiding forces. The presented method considers the actual stiffness and mass distribution of hoisting conveyance and, therefore, allows for a more accurate estimation of the guiding forces and the transport of larger loads. This data-driven approach allows for the continuous monitoring of the guiding forces, the adjustments of the hoisting parameters, the rational planning of repairs, and a reduction in the replacement of corroded shaft steelwork. Full article

(This article belongs to the Special Issue Recent Advances in Mining Technology and Geotechnical Engineering)

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29 pages, 4068 KiB

Open AccessArticle

Multidimensional User Experience Analysis of Chinese Battery Electric Vehicles’ Competition: An Integrated Association Mining Framework

by Quan Gu, Jie Zhang, Shengqing Huang, Yuchao Cai, Chenlu Wang and Jiaoman Liu

Appl. Sci. 2024, 14(22), 10757; https://doi.org/10.3390/app142210757 - 20 Nov 2024

Viewed by 305

Abstract

This study introduces an integrative framework for association mining within the Chinese battery electric vehicle market, aiming to reveal key user experience (UX) factors and their interrelationships through multidimensional analysis. Utilizing latent Dirichlet allocation (LDA), the study discerned primary themes from user-generated content [...] Read more.

This study introduces an integrative framework for association mining within the Chinese battery electric vehicle market, aiming to reveal key user experience (UX) factors and their interrelationships through multidimensional analysis. Utilizing latent Dirichlet allocation (LDA), the study discerned primary themes from user-generated content (UGC). The entropy weight method categorized level 2 factors, while domain-adaptive sentiment analysis quantified emotional responses to BEV user experience dimensions, highlighting significant sentiment disparities among competitors. Co-occurrence network analysis deepened insights into the emotional fabric of UX by exploring tertiary factor associations. Theoretically, this study advances a novel framework informed by Norman’s UX theory, integrating analytical techniques to capture the complexity of UX. Practically, it delivers strategic guidance for BEV manufacturers by analyzing emotional polarities and attribute associations, guiding product innovation and responding to market dynamics. The empirical evidence corroborates the framework’s efficacy in revealing the emotional associations within BEVUX factors, offering valuable implications for both theoretical development and practical application. Full article

(This article belongs to the Special Issue Advanced Technologies for User-Centered Design and User Experience)

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21 pages, 6228 KiB

Open AccessArticle

DC-DC Buck Converters with Quasi-Online Estimation of Filter Capacitor Equivalent Parameters

by Dadiana-Valeria Căiman, Corneliu Bărbulescu, Sorin Nanu and Toma-Leonida Dragomir

Appl. Sci. 2024, 14(22), 10756; https://doi.org/10.3390/app142210756 - 20 Nov 2024

Viewed by 309

Abstract

The article focuses on devising solutions for monitoring the condition of the filter capacitors of DC-DC converters. The article introduces two novel DC-DC buck converter designs that monitor the equivalent series resistance (ESR) and the capacitance of capacitors using a parameter observer (PO) [...] Read more.

The article focuses on devising solutions for monitoring the condition of the filter capacitors of DC-DC converters. The article introduces two novel DC-DC buck converter designs that monitor the equivalent series resistance (ESR) and the capacitance of capacitors using a parameter observer (PO) and simple variable electrical networks (VEN). For the first scheme, the PO processes in real time the voltage at the capacitor terminals during a discharge-charge cycle. For the second scheme, the filtering is performed with two or more capacitors in parallel, and the PO processes the voltage at the terminals of each capacitor during two discharge processes without interrupting the filtering operation of the converter. The paper presents the principles and theoretical support on which the two schemes of DC-DC buck converters are based, design details regarding PO and VEN, as well as experiments performed with each of the schemes. In the experimental schemes, the PO is implemented with a microcontroller, and the parameters of some aluminum electrolytic filter capacitors are calculated in a real-time manner of about

40 m s

. The calculation accuracy of the equivalent capacity is very good. Regarding the calculation accuracy of the ESR, it is shown that it depends on the fulfillment of certain ratios between the VEN resistances, on the one hand, as well as between them and the ESR, on the other hand. Full article

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39 pages, 1531 KiB

Open AccessReview

Omics-Integrated Approach (Metabolomics, Proteomics and Lipidomics) to Assess the Quality Control of Aquatic and Seafood Products

by Marianthi Sidira, Sofia Agriopoulou, Slim Smaoui and Theodoros Varzakas

Appl. Sci. 2024, 14(22), 10755; https://doi.org/10.3390/app142210755 - 20 Nov 2024

Viewed by 285

Abstract

Since the demand for seafood products is growing and aquaculture provides more than fifty percent of the aquatic food as reported by FAO, the development of more accurate and sensitive analytical techniques in order to screen and evaluate the safety and quality of [...] Read more.

Since the demand for seafood products is growing and aquaculture provides more than fifty percent of the aquatic food as reported by FAO, the development of more accurate and sensitive analytical techniques in order to screen and evaluate the safety and quality of seafood products is needed. At this point, several omic techniques like proteomics, lipidomics, and metabolomics, or combinations of them, are used for integration into seafood processing and quality control. Moreover, according to the literature, using the respective techniques can prevent, control, and treat diseases in fish as well as address several issues in aquaculture. Proteomic techniques are used for the expression of proteins and their modifications. Metabolomic techniques are used for accurate identification of species, while lipidomics techniques are used for the identification of different or specific lipid molecules in fish species, as well as fatty acid composition and location distribution. This review is to cover the recent proteomics, metabolomics, and lipidomics studies on aquatic and seafood products in the areas of quality, safety, processing, and breeding of fish. Full article

(This article belongs to the Special Issue Advances in Food Metabolomics)

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15 pages, 4362 KiB

Open AccessArticle

Detection of Defects in Warp Knitted Fabrics Based on Local Feature Scale Adaptive Comparison

by Yongchao Zhang, Weimin Shi and Jindou Zhang

Appl. Sci. 2024, 14(22), 10754; https://doi.org/10.3390/app142210754 - 20 Nov 2024

Viewed by 266

Abstract

In order to improve the accuracy and detection effect of fabric defect detection, a fabric defect detection method based on local similarity comparison is proposed in this paper. This method first takes each pixel in the image as the central pixel, selects a [...] Read more.

In order to improve the accuracy and detection effect of fabric defect detection, a fabric defect detection method based on local similarity comparison is proposed in this paper. This method first takes each pixel in the image as the central pixel, selects a specific window as the region size, and then uses the similarity between the central region and the surrounding neighborhood to find the neighborhood most similar to the central region to complete the estimation of the central pixel. Finally, the target image is obtained by the principle of background difference, so as to detect fabric defects. The results show that this method is superior to the traditional detection method, which can not only detect the defect image under the complex background, but also have good detection results for the fabric defect image under the influence of different organization and lighting factors. The detection accuracy rate under factory conditions can reach 98.45%, which has a high applicability and detection rate, and also demonstrates certain anti-interference performance. Full article

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19 pages, 3743 KiB

Open AccessArticle

Optimized Detection Algorithm for Vertical Irregularities in Vertical Curve Segments

by Rong Xie and Chunjun Chen

Appl. Sci. 2024, 14(22), 10753; https://doi.org/10.3390/app142210753 - 20 Nov 2024

Viewed by 243

Abstract

The vertical curve is designed to smooth sudden gradient changes in the longitudinal profile, enhancing train operational safety and passenger comfort. However, dynamic detection in these segments has consistently encountered issues with long-wavelength vertical irregularities exceeding tolerance limits. To investigate the root causes [...] Read more.

The vertical curve is designed to smooth sudden gradient changes in the longitudinal profile, enhancing train operational safety and passenger comfort. However, dynamic detection in these segments has consistently encountered issues with long-wavelength vertical irregularities exceeding tolerance limits. To investigate the root causes of this phenomenon and develop a targeted solution, a comprehensive vehicle-track dynamics simulation model was first constructed, based on the design principles for intercity railway vertical curves. The inertial reference method was then applied to process the acceleration and relative displacement data between the detection beam and the track, yielding virtual irregularities. These were compared with excitation irregularities to identify key factors affecting detection accuracy in vertical curve segments. Through further analysis of abnormal exceedances in detection data, the reference cancellation method was proposed. By employing smoothing filters and orthogonal least squares fitting, this method effectively removes track alignment components from the acceleration integration results. Detection errors under various conditions were then compared between the two methods to evaluate the feasibility and effectiveness of the reference cancellation approach. Results indicate that regions with increased longitudinal profile detection errors are primarily located at and near gradient transition points. The vertical curve radius was found to be the primary factor influencing the accuracy of long-wavelength irregularity detection. The proposed reference cancellation method effectively reduces detection errors in areas near gradient transition points to levels comparable to other track sections. Compared to the inertial reference method, the reference cancellation method reduces the maximum detection error by up to 71.77% and the root mean square error by up to 86.61%, effectively mitigating the abnormal exceedances associated with vertical curves. Full article

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22 pages, 10049 KiB

Open AccessArticle

Failure Probability Analysis of the Transmission Line Considering Uncertainty Under Combined Ice and Wind Loads

by Jiaxiang Li, Chao Zhang, Jian Zhang, Xuesheng Zhang and Wenrui Wang

Appl. Sci. 2024, 14(22), 10752; https://doi.org/10.3390/app142210752 - 20 Nov 2024

Viewed by 266

Abstract

The probability of accidents, including conductor breakage and tower collapse, for the transmission tower-line system significantly increases under combined ice and wind loads. The existing research on the failure probability of the tower-line system under combined ice and wind loads is limited to [...] Read more.

The probability of accidents, including conductor breakage and tower collapse, for the transmission tower-line system significantly increases under combined ice and wind loads. The existing research on the failure probability of the tower-line system under combined ice and wind loads is limited to static calculation, ignoring the fluctuating effect of wind. In addition, uncertainty in the material strength and geometric dimensions of the structure due to the production process and other pertinent factors could affect the bearing capacity of the tower. To accurately assess the failure probability of transmission lines under combined ice and wind loads, this paper first established numerical models of the transmission tower-line system considering structural uncertainty based on the Latin Hypercube Sampling method. And then, the limit performance indexes of the uncertain models were determined by Pushover analysis. Subsequently, considering the joint probability distributions of ice thickness–wind speed and wind speed–wind direction, the failure probability of the tower-line system under ice and wind loads was calculated. Finally, the influence of structural uncertainty and fluctuating wind on the failure probability was discussed. The results showed that, compared with structural uncertainty, the fluctuating effect of wind had a more significant influence on the failure probability of the tower-line system under combined ice and wind loads. After considering the fluctuating effect of wind, the smaller ice loads can potentially lead to the failure of the transmission tower-line system. Full article

(This article belongs to the Special Issue Structural Dynamics and Risk Assessment of Structures)

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18 pages, 582 KiB

Open AccessArticle

Analysis of the Severity of Heavy Truck Traffic Accidents Under Different Road Conditions

by Ziqun Tian, Facheng Chen, Sheqiang Ma and Mengzhu Guo

Appl. Sci. 2024, 14(22), 10751; https://doi.org/10.3390/app142210751 - 20 Nov 2024

Viewed by 289

Abstract

The rising frequency of heavy truck accidents in China poses a significant public safety risk, endangering lives and property. However, current research based on data from heavy truck accidents in China remains limited, making it challenging to support the formulation of traffic management [...] Read more.

The rising frequency of heavy truck accidents in China poses a significant public safety risk, endangering lives and property. However, current research based on data from heavy truck accidents in China remains limited, making it challenging to support the formulation of traffic management measures. To mitigate the severity of these accidents, this study analyzed five years of heavy truck accident data from a specific region in China and developed logistic regression models for different road conditions. The aim was to identify the key factors influencing accident severity and understand the underlying mechanisms. The findings revealed that, under urban road conditions, the severity of heavy truck accidents is significantly impacted by factors such as lighting conditions, road safety attributes, driver age, and vehicle driving status. On highways, accident severity is largely influenced by visibility, roadside protection measures, intersection and section types, vehicle driving status, inter-vehicle accident types, and road safety features. On expressways, critical factors include inter-vehicle accident types, driver violations, visibility, and road alignment. In conclusion, the factors contributing to the severity of heavy truck accidents vary according to road conditions, which necessitates tailored traffic management strategies. The study’s findings offer theoretical support for more targeted approaches to preventing and controlling heavy truck traffic accident severity under different road conditions in China. Full article

(This article belongs to the Special Issue Traffic Safety Measures and Assessment)

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18 pages, 7440 KiB

Open AccessArticle

Energy Consumption Prediction for Drilling Pumps Based on a Long Short-Term Memory Attention Method

by Chengcheng Wang, Zhi Yan, Qifeng Li, Zhaopeng Zhu and Chengkai Zhang

Appl. Sci. 2024, 14(22), 10750; https://doi.org/10.3390/app142210750 - 20 Nov 2024

Viewed by 276

Abstract

In the context of carbon neutrality and emission reduction goals, energy consumption optimization in the oil and gas industry is crucial for reducing carbon emissions and improving energy efficiency. As a key component in drilling operations, optimizing the energy consumption of drilling pumps [...] Read more.

In the context of carbon neutrality and emission reduction goals, energy consumption optimization in the oil and gas industry is crucial for reducing carbon emissions and improving energy efficiency. As a key component in drilling operations, optimizing the energy consumption of drilling pumps has significant potential for energy savings. However, due to the complex and variable geological conditions, diverse operational parameters, and inherent nonlinear relationships in the drilling process, accurately predicting energy consumption presents considerable challenges. This study proposes a novel Long Short-Term Memory Attention model for precise prediction of drilling pump energy consumption. By integrating Long Short-Term Memory (LSTM) networks with the Attention mechanism, the model effectively captures complex nonlinear relationships and long-term dependencies in energy consumption data. Comparative experiments with traditional LSTM and Convolutional Neural Network (CNN) models demonstrate that the LSTM-Attention model outperforms these models across multiple evaluation metrics, significantly reducing prediction errors and enhancing robustness and adaptability. The proposed model achieved Mean Absolute Error (MAE) values ranging from 5.19 to 10.20 and R² values close to one (0.95 to 0.98) in four test scenarios, demonstrating excellent predictive performance under complex conditions. The high-precision prediction of drilling pump energy consumption based on this method can support energy optimization and provide guidance for field operations. Full article

(This article belongs to the Special Issue Development and Application of Intelligent Drilling Technology)

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11 pages, 8283 KiB

Open AccessArticle

Repair Composite Adhesion Strength: A Comparison of Testing Methods

by Khrystyna Moskalova, Serhii Hedulian, Nadiia Antoniuk and Mario Šercer

Appl. Sci. 2024, 14(22), 10749; https://doi.org/10.3390/app142210749 - 20 Nov 2024

Viewed by 292

Abstract

The adhesive strength of repair composites to concrete substrates was assessed through both Ukrainian and European standard test methods. The types of adhesion loss observed included adhesive failure along the contact layer (AF-S), and cohesion failure along the substrate (CF-S). The Ukrainian method [...] Read more.

The adhesive strength of repair composites to concrete substrates was assessed through both Ukrainian and European standard test methods. The types of adhesion loss observed included adhesive failure along the contact layer (AF-S), and cohesion failure along the substrate (CF-S). The Ukrainian method showed adhesive bond loss in 90.5% of samples (181 out of 200), while the European method showed loss in 76% (152 out of 200). However, under identical conditions, the EU standard showed greater consistency (standard deviation 0.25) than the Ukrainian standard (standard deviation 0.42 and 0.32). The effect of pull-off techniques on failure models varied depending on the epoxy thickness and the mechanical testing performed. Repair composites meeting the highest Ukrainian structural class criteria (PM1) were classified as R3 materials according to the European standard. This research highlights that statistical analysis shows a significant improvement in reliability with an increased number of pull-off tests. Full article

(This article belongs to the Special Issue Mechanical Properties and Characterization Technologies of Composite Materials)

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27 pages, 2383 KiB

Open AccessArticle

Integrating a Virtual Assistant by Using the RAG Method and VERTEX AI Framework at Algebra University

by Zlatan Morić, Leo Mršić, Mario Filjak and Goran Đambić

Appl. Sci. 2024, 14(22), 10748; https://doi.org/10.3390/app142210748 - 20 Nov 2024

Viewed by 307

Abstract

The development and testing of a virtual assistant (VA) designed to enhance information retrieval and support in an academic environment are presented in this paper, with the Retrieval-Augmented Generation (RAG) approach being utilized alongside Google’s VERTEX AI Palm-2 model. A novel integration of [...] Read more.

The development and testing of a virtual assistant (VA) designed to enhance information retrieval and support in an academic environment are presented in this paper, with the Retrieval-Augmented Generation (RAG) approach being utilized alongside Google’s VERTEX AI Palm-2 model. A novel integration of RAG with contextual learning is introduced in this study, specifically for applications in university contact centers, where accuracy and relevance are considered paramount. The effectiveness of the VA was evaluated through user testing, focusing on two primary hypotheses: first, that the VA can achieve accurate interpretation and response to queries with context-based information, and second, that the VA minimizes potential harm from erroneous responses. In total, 187 participants were involved in the testing, and a diverse set of inquiries was utilized, resulting in 561 query–response interactions that were analyzed. It was shown that contextual data significantly reduced hallucinations and increased response accuracy, thereby underscoring the value of the RAG method in applications requiring high levels of specificity. Furthermore, the study provides empirical insights into the impact of AI-generated hallucinations and response inconsistencies, particularly about structured or procedural data. A framework for mitigating these challenges in future implementations is also offered. The scalability and adaptability of the RAG method in specialized academic contexts are demonstrated in this work, with broader implications for integrating AI-driven VAs across educational and professional domains being highlighted. Full article

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13 pages, 275 KiB

Open AccessArticle

Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System

by Woncheol Park, Seungmin Oh and Seonghyun Park

Appl. Sci. 2024, 14(22), 10747; https://doi.org/10.3390/app142210747 - 20 Nov 2024

Viewed by 305

Abstract

This study proposes a system for analyzing non-face-to-face counseling data using text-mining techniques to assess psychological states and automatically classify them into predefined categories. The system addresses the challenge of understanding internal issues that may be difficult to express in traditional face-to-face counseling. [...] Read more.

This study proposes a system for analyzing non-face-to-face counseling data using text-mining techniques to assess psychological states and automatically classify them into predefined categories. The system addresses the challenge of understanding internal issues that may be difficult to express in traditional face-to-face counseling. To solve this problem, a counseling management system based on text mining was developed. In the experiment, we combined TF-IDF and Word Embedding techniques to process and classify client counseling data into five major categories: school, friends, personality, appearance, and family. The classification performance achieved high accuracy and F1-Score, demonstrating the system’s effectiveness in understanding and categorizing clients’ emotions and psychological states. This system offers a structured approach to analyzing counseling data, providing counselors with a foundation for recommending personalized counseling treatments. The findings of this study suggest that in-depth analysis and classification of counseling data can enhance the quality of counseling, even in non-face-to-face environments, offering more efficient and tailored solutions. Full article

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15 pages, 4979 KiB

Open AccessArticle

Experimental Study on Fluid Dissipation Effects in Core Samples by NMR Measurement

by Zhongshu Liao, Gong Zhang and Yingying Ma

Appl. Sci. 2024, 14(22), 10746; https://doi.org/10.3390/app142210746 - 20 Nov 2024

Viewed by 281

Abstract

Laboratory core nuclear magnetic resonance (NMR) relaxation measurements offer geological information, including rock porosity and oil saturation, relevant to logging. When core samples drilled from wells are exposed to air, the fluids within their pores inevitably dissipate. This phenomenon may lead to discrepancies [...] Read more.

Laboratory core nuclear magnetic resonance (NMR) relaxation measurements offer geological information, including rock porosity and oil saturation, relevant to logging. When core samples drilled from wells are exposed to air, the fluids within their pores inevitably dissipate. This phenomenon may lead to discrepancies between the results of nuclear magnetic resonance relaxation experiments and the actual situation underground. To deeply explore the impact of fluid dissipation on NMR core analysis experimental results, a series of simulated dissipation experiments were designed under constant temperature and humidity conditions. Variations in one-dimensional and two-dimensional NMR measurement results of oil-saturated samples were examined under varying crude oil viscosities and dissipation times. The experimental results indicate that as exposure time increases, the T₂ distribution of oil-saturated cores decreases, and the amplitude of the T₂ distribution peaks decreases. Both oil and water relaxation components show a decreasing trend; however, the dissipation rate of the bounding water component significantly exceeds that of the crude oil component. By employing two-dimensional NMR relaxation time distribution fluid quantitative analysis technology, the relationship between the dissipation rates of various phase fluids and exposure time during the stable dissipation stage was analyzed. This offers a reference for adjusting the oil saturation of exposed cores based on NMR measurements. Full article

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15 pages, 2747 KiB

Open AccessArticle

A Short-Circuit Current Calculation Model for Renewable Power Plants Considering Internal Topology

by Po Li, Ying Huang, Guoteng Wang, Jianhua Li and Jianyu Lu

Appl. Sci. 2024, 14(22), 10745; https://doi.org/10.3390/app142210745 - 20 Nov 2024

Viewed by 314

Abstract

With the large-scale integration of renewable energy into the grid, traditional short-circuit current (SCC) calculation methods for synchronous generators are no longer applicable to inverter-based non-synchronous machine sources (N-SMSs). Current SCC calculation methods for N-SMSs often use a single-machine multiplication method, which tends [...] Read more.

With the large-scale integration of renewable energy into the grid, traditional short-circuit current (SCC) calculation methods for synchronous generators are no longer applicable to inverter-based non-synchronous machine sources (N-SMSs). Current SCC calculation methods for N-SMSs often use a single-machine multiplication method, which tends to overlook the internal variability of N-SMSs within power plants, leading to low calculation accuracy. To address this issue, this paper first derives an analytical expression for SCC in grid-connected inverters under low voltage ride through (LVRT) control strategies. Then, a single-machine steady-state SCC calculation model is proposed. Based on the classification of N-SMSs, a practical SCC calculation model for renewable power plants is introduced, balancing accuracy and computational speed. The feasibility of the model is validated through simulations. The proposed method enables simple calculations to obtain the steady-state voltage and SCC at the machine terminal, offering strong engineering practicality. Full article

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21 pages, 3958 KiB

Open AccessArticle

PHR-NFT: Decentralized Blockchain Framework with Hyperledger and NFTs for Secure and Transparent Patient Health Records

by Huwida E. Said, Nedaa B. Al Barghuthi, Sulafa M. Badi, Faiza Hashim and Shini Girija

Appl. Sci. 2024, 14(22), 10744; https://doi.org/10.3390/app142210744 - 20 Nov 2024

Viewed by 333

Abstract

Blockchain technology holds significant promise for healthcare by enhancing the security and integrity of patient health records (PHRs) through decentralized storage and transparent access. However, it has substantial limitations, including problems with scalability, high transaction costs, privacy concerns, and intricate stakeholder access management. [...] Read more.

Blockchain technology holds significant promise for healthcare by enhancing the security and integrity of patient health records (PHRs) through decentralized storage and transparent access. However, it has substantial limitations, including problems with scalability, high transaction costs, privacy concerns, and intricate stakeholder access management. This study presents PHR-NFT, a novel framework that strengthens PHR privacy by utilizing Hyperledger Fabric and non-fungible tokens (NFTs) to address these issues. PHR-NFT improves privacy and communication by letting patients keep control of their medical records while permitting temporary, permission-based access by medical professionals. PHR-NFT offers a transparent solution that increases trust among healthcare stakeholders through the robust and decentralized architecture of the Hyperledger Fabric. This study demonstrates the viability and effectiveness of the PHR-NFT framework through performance evaluations focused on transaction latency, throughput, and security. This research has valuable implications for enhancing data privacy and security in healthcare practices and insightful information about blockchain-based healthcare systems. Full article

(This article belongs to the Special Issue Future Security of NFT-Blockchain)

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22 pages, 6230 KiB

Open AccessArticle

FEA-Based Design Procedure for IPMSM and IM for a Hybrid Electric Vehicle

by Emad Roshandel, Amin Mahmoudi, Wen L. Soong, Solmaz Kahourzade and Nathan Kalisch

Appl. Sci. 2024, 14(22), 10743; https://doi.org/10.3390/app142210743 - 20 Nov 2024

Viewed by 270

Abstract

This paper describes the detailed design procedure of electric machines using finite element analysis (FEA). The proposed method uses the available findings from the literature and FEA results for the design procedure. In addition to electromagnetic analysis, thermal analysis is executed to examine [...] Read more.

This paper describes the detailed design procedure of electric machines using finite element analysis (FEA). The proposed method uses the available findings from the literature and FEA results for the design procedure. In addition to electromagnetic analysis, thermal analysis is executed to examine the capability of the designed machines for handling the load in terms of thermal limits. It allows for considering the normal and overload performance of the electric machines during design. The proposed design procedure is used for designing a 100 kW induction machine (IM) and interior permanent magnet synchronous machine (IPMSM) for a parallel hybrid electric vehicle (HEV). The differences between the performance parameters of the studied machines are discussed, and the advantages and disadvantages of each design are highlighted. The designed machines are compared with commercially available electrical machines in terms of performance and power density. The comparison demonstrates that the developed machines can offer comparable performance to other designs. Full article

(This article belongs to the Special Issue Recent Developments in Electric Vehicles)

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18 pages, 3720 KiB

Open AccessArticle

Packaging Design Image Segmentation Based on Improved Full Convolutional Networks

by Chunxiao Zhang, Mengmeng Han, Jingjing Jia and Chulsoo Kim

Appl. Sci. 2024, 14(22), 10742; https://doi.org/10.3390/app142210742 - 20 Nov 2024

Viewed by 263

Abstract

Packaging design plays a critical role in brand recognition and cultural dissemination, yet the traditional design process is time-consuming and dependent on the designer’s technical skills, making it difficult to quickly respond to market changes and consumer demands. In recent years, advancements in [...] Read more.

Packaging design plays a critical role in brand recognition and cultural dissemination, yet the traditional design process is time-consuming and dependent on the designer’s technical skills, making it difficult to quickly respond to market changes and consumer demands. In recent years, advancements in machine learning, particularly in the field of natural language processing (NLP), have paved the way for novel methods in other areas, such as image processing and packaging design. This study draws inspiration from advanced NLP techniques and proposes an improved fully convolutional network (FCN) model for image semantic segmentation, which is applied to packaging design. The model integrates superpixel technology, multi-branch networks, dual-attention mechanisms, and edge knowledge distillation in a manner analogous to the approach taken by NLP models in the context of semantic segmentation and context understanding. The experimental results showed that the model achieved significant improvements in accuracy, inference efficiency, and memory usage, with an average accuracy of 96.84% and a false-alarm rate of only 2.78%. Compared to traditional methods, the proposed model achieved over 96% accuracy across 50 packaging design images, with an average segmentation error rate of only 1.42%. By incorporating machine learning techniques from NLP into image processing, this study enhances the overall quality and efficiency of packaging design and provides new directions for the application of advanced technologies across different fields. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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23 pages, 3012 KiB

Open AccessArticle

Novel In Silico Strategies to Model the In Vivo Nerve Scarring Around Implanted Parylene C Devices

by Pier Nicola Sergi, Jaume del Valle, Thomas Stieglitz, Xavier Navarro and Silvestro Micera

Appl. Sci. 2024, 14(22), 10741; https://doi.org/10.3390/app142210741 - 20 Nov 2024

Viewed by 273

Abstract

The implantation of materials into in vivo peripheral nerves triggers the production of scar tissue. A scar capsule progressively incorporates foreign bodies, which become insulated from the surrounding environment. This phenomenon is particularly detrimental in the case of electrical active sites enveloped within [...] Read more.

The implantation of materials into in vivo peripheral nerves triggers the production of scar tissue. A scar capsule progressively incorporates foreign bodies, which become insulated from the surrounding environment. This phenomenon is particularly detrimental in the case of electrical active sites enveloped within scar sheets, since the loss of contact with axons highly decreases the effectiveness of neural interfaces. As a consequence, the in silico modelling of scar capsule evolution may lead to improvements in the design of intraneural structures and enhancing their reliability over time. In this work, a novel theoretical framework is proposed to model the evolution of capsule thickness over time together with an improved optimisation procedure able to avoid apparently suitable choices resulting from standard procedures. This framework provides a fast, simple, and accurate modelling of experimental data (

R^{2} = 0.97

), definitely improving on previous approaches. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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18 pages, 4410 KiB

Open AccessArticle

Evaluating Environmental Impacts of Urban Development Strategies: A Case Study of the Fontaine d’Ouche District

by Mohamad Achour, Mohamad Toufaily, Ludovic Avril, Gilles Betis and Nisrine Makhoul

Appl. Sci. 2024, 14(22), 10740; https://doi.org/10.3390/app142210740 - 20 Nov 2024

Viewed by 330

Abstract

Life cycle assessment (LCA) is a methodology used to analyze the environmental impacts of a product. Initially, it was applied to buildings only, but recently, it has also been applied to entire neighborhood. This expansion from individual buildings to the neighborhood scale requires [...] Read more.

Life cycle assessment (LCA) is a methodology used to analyze the environmental impacts of a product. Initially, it was applied to buildings only, but recently, it has also been applied to entire neighborhood. This expansion from individual buildings to the neighborhood scale requires additional inputs, such as the impacts of public spaces, transportation, public network systems, and roads. Additionally, conducting an LCA for a neighborhood requires software tools to simulate the neighborhood and databases to store the environmental impacts of all the components integrated into the neighborhood. This paper presents an LCA case study of a neighborhood in Dijon, France. The study aims to analyze the thermal impacts of buildings and the neighborhood with single-, double-, and triple-pane windows. The second part of the study involves two LCA studies using the 1996 version of ecoinvent. The first study is a continuation of the thermal simulation analysis, while the second study compares concrete, masonry, and timber-based construction designs for the neighborhoods. The results show that the heating demands inside the buildings are substantially reduced when transitioning from single- to triple-pane, while the cooling demands show the opposite effect. Furthermore, doubling the width of double-pane windows resulted in less profound environmental damage for the construction, use, and demolition phases compared to single-pane windows, with only the renovation phase being more damaging. Additionally, the comparison between different construction scenarios shows that the timber-based variant is slightly advantageous from an environmental point of view compared to the concrete and masonry designs. Full article

(This article belongs to the Special Issue Enhancing Structural Sustainability: Data-Based Adaptive Solutions for the Built Environment)

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15 pages, 2098 KiB

Open AccessArticle

The Value of Using Green Extraction Techniques to Enhance Polyphenol Content and Antioxidant Activity in Nasturtium officinale Leaves

by Eva Naoum, Aikaterini Xynopoulou, Konstantina Kotsou, Theodoros Chatzimitakos, Vassilis Athanasiadis, Eleni Bozinou and Stavros I. Lalas

Appl. Sci. 2024, 14(22), 10739; https://doi.org/10.3390/app142210739 - 20 Nov 2024

Viewed by 429

Abstract

Increasing research is being directed toward the production of value-added products using plant extracts that are super-fortified with antioxidants. In this study, the extraction parameters for bioactive compounds (such as polyphenols) from Nasturtium officinale leaves and their antioxidant properties were optimized using response [...] Read more.

Increasing research is being directed toward the production of value-added products using plant extracts that are super-fortified with antioxidants. In this study, the extraction parameters for bioactive compounds (such as polyphenols) from Nasturtium officinale leaves and their antioxidant properties were optimized using response surface methodology. The optimization procedure examined the effects of the extraction temperature, time, and solvent composition on conventional magnetic stirring (ST). In addition, the impacts of two green techniques—pulsed electric field (PEF) and ultrasound (US)—were evaluated individually and in combination to assess their potential to enhance the extraction of the compounds. According to our findings, under the proposed extraction conditions (a combination of PEF, US, and ST as a extraction technique, 50% ethanolic solvent, for 30 min at 80 °C). N. officinale leaf extract proved to be an excellent source of bioactive compounds, with extracts containing rosmarinic acid (3.42 mg/g dried weight (dw)), chlorogenic acid (3.13 mg/g dw), total polyphenol content (28.82 mg of gallic acid equivalents (GAE)/g dw), and strong antioxidant properties. The FRAP method measured 57.15 μmol ascorbic acid equivalents (AAE)/g dw, while the DPPH radical scavenging activity method measured 47.55 μmol AAE/g dw. This study was carried out to evaluate and improve the concentration of bioactive compounds in N. officinale leaf extract, resulting in a product with multiple applications across the food, cosmetic, and pharmaceutical industries. Full article

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

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15 pages, 3765 KiB

Open AccessArticle

Drainage Troughs as a Protective Measure in Subway–Pedestrian Collisions: A Multibody Model Evaluation

by Daniel Hall, Kevin Gildea and Ciaran Simms

Appl. Sci. 2024, 14(22), 10738; https://doi.org/10.3390/app142210738 - 20 Nov 2024

Viewed by 219

Abstract

Introduction: Subway–pedestrian collisions are a significant and growing problem, but they are poorly understood. This study presents the first subway–pedestrian collision model with the aim of evaluating the baseline safety performance of an R160 NYC train and track combination and the potential safety [...] Read more.

Introduction: Subway–pedestrian collisions are a significant and growing problem, but they are poorly understood. This study presents the first subway–pedestrian collision model with the aim of evaluating the baseline safety performance of an R160 NYC train and track combination and the potential safety effects of drainage trough depth. Methods: A baseline simulation test sample of 384 unique impacts (8 velocities (2–16 m/s), 24 positions (standing jumping and lying), and 2 track types (flat and crossties)) was created in MADYMO. The full simulation test sample (N = 1920) included with various depth drainage troughs (0–1 m). Head injuries and wheel and third rail contacts were evaluated. Results: Limb–wheel contact occurred in 60% of scenarios. Primary and secondary contact HIC₁₅ showed similar high severity, with an HIC₁₅ < 2000 (88% risk of AIS 4+) in 29% of results for both train and ground contact. Impact velocity strongly influences primary contact HIC₁₅ with limited effect on secondary contact. Impact velocities between 6 and 16 m/s showed little change in wheel contact. Increasing the trough depth up to 0.5 m showed a decrease in wheel contact probability with little increase in secondary contact. No further benefits were found above 0.5 m. Conclusions: A subway–pedestrian collision model is presented which predicts that wheel–pedestrian contact risk can be reduced with a 0.5 m drainage trough. The model suggests that slower impact velocities may reduce head injury risk for primary contact; however, this will have less effect on injuries caused by secondary and wheel contact. Full article

(This article belongs to the Special Issue Railway Dynamic Simulation: Recent Advances and Perspective, 2nd Edition)

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17 pages, 8959 KiB

Open AccessReview

Laboratory Assessment of Manual Wheelchair Propulsion

by Bartosz Wieczorek and Maciej Sydor

Appl. Sci. 2024, 14(22), 10737; https://doi.org/10.3390/app142210737 - 20 Nov 2024

Viewed by 198

Abstract

Self-propelled manual wheelchairs offer several advantages over electric wheelchairs, including promoting physical activity and requiring less maintenance due to their simple design. While theoretical analyses provide valuable insights, laboratory testing remains the most reliable method for evaluating and improving the efficiency of manual [...] Read more.

Self-propelled manual wheelchairs offer several advantages over electric wheelchairs, including promoting physical activity and requiring less maintenance due to their simple design. While theoretical analyses provide valuable insights, laboratory testing remains the most reliable method for evaluating and improving the efficiency of manual wheelchair drives. This article reviews and analyzes the laboratory methods for assessing the efficiency of wheelchair propulsion documented in the scientific literature: (1) A wheelchair dynamometer that replicates real-world driving scenarios, quantifies the wheelchair’s motion characteristics, and evaluates the physical exertion required for propulsion. (2) Simultaneous measurements of body position, motion, and upper limb EMG data to analyze biomechanics. (3) A method for determining the wheelchair’s trajectory based on data from the dynamometer. (4) Measurements of the dynamic center of mass (COM) of the human–wheelchair system to assess stability and efficiency; and (5) data analysis techniques for parameterizing large datasets and determining the COM. The key takeaways include the following: (1) manual wheelchairs offer benefits over electric ones but require customization to suit individual user biomechanics; (2) the necessity of laboratory-based ergometer testing for optimizing propulsion efficiency and safety; (3) the feasibility of replicating real-world driving scenarios in laboratory settings; and (4) the importance of efficient data analysis techniques for interpreting biomechanical studies. Full article

(This article belongs to the Section Biomedical Engineering)

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