Applied Sciences

32 pages, 777 KiB

Open AccessArticle

A Comprehensive Approach to Bias Mitigation for Sentiment Analysis of Social Media Data

by Jothi Prakash Venugopal, Arul Antran Vijay Subramanian, Gopikrishnan Sundaram, Marco Rivera and Patrick Wheeler

Appl. Sci. 2024, 14(23), 11471; https://doi.org/10.3390/app142311471 - 9 Dec 2024

Viewed by 1197

Abstract

Sentiment analysis is a vital component of natural language processing (NLP), enabling the classification of text into positive, negative, or neutral sentiments. It is widely used in customer feedback analysis and social media monitoring but faces a significant challenge: bias. Biases, often introduced [...] Read more.

Sentiment analysis is a vital component of natural language processing (NLP), enabling the classification of text into positive, negative, or neutral sentiments. It is widely used in customer feedback analysis and social media monitoring but faces a significant challenge: bias. Biases, often introduced through imbalanced training datasets, can distort model predictions and result in unfair outcomes. To address this, we propose a bias-aware sentiment analysis framework leveraging Bias-BERT (Bidirectional Encoder Representations from Transformers), a customized classifier designed to balance accuracy and fairness. Our approach begins with adapting the Jigsaw Unintended Bias in Toxicity Classification dataset by converting toxicity scores into sentiment labels, making it suitable for sentiment analysis. This process includes data preparation steps like cleaning, tokenization, and feature extraction, all aimed at reducing bias. At the heart of our method is a novel loss function incorporating a bias-aware term based on the Kullback–Leibler (KL) divergence. This term guides the model toward fair predictions by penalizing biased outputs while maintaining robust classification performance. Ethical considerations are integral to our framework, ensuring the responsible deployment of AI models. This methodology highlights a pathway to equitable sentiment analysis by actively mitigating dataset biases and promoting fairness in NLP applications. Full article

(This article belongs to the Special Issue Advancements in Natural Language Processing, Semantic Networks, and Sentiment Analysis)

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23 pages, 12345 KiB

Open AccessArticle

MuIm: Analyzing Music–Image Correlations from an Artistic Perspective

by Ubaid Ullah and Hyun-Chul Choi

Appl. Sci. 2024, 14(23), 11470; https://doi.org/10.3390/app142311470 - 9 Dec 2024

Viewed by 893

Abstract

Cross-modality understanding is essential for AI to tackle complex tasks that require both deterministic and generative capabilities, such as correlating music and visual art. The existing state-of-the-art methods of audio-visual correlation often rely on single-dimension information, focusing either on semantic or emotional attributes, [...] Read more.

Cross-modality understanding is essential for AI to tackle complex tasks that require both deterministic and generative capabilities, such as correlating music and visual art. The existing state-of-the-art methods of audio-visual correlation often rely on single-dimension information, focusing either on semantic or emotional attributes, thus failing to capture the full depth of these inherently complex modalities. Addressing this limitation, we introduce a novel approach that perceives music–image correlation as multilayered rather than as a direct one-to-one correspondence. To this end, we present a pioneering dataset with two segments: an artistic segment that pairs music with art based on both emotional and semantic attributes, and a realistic segment that links music with images through affective–semantic layers. In modeling emotional layers for the artistic segment, we found traditional 2D affective models inadequate, prompting us to propose a more interpretable hybrid-emotional rating system that serves both experts and non-experts. For the realistic segment, we utilize a web-based dataset with tags, dividing tag information into semantic and affective components to ensure a balanced and nuanced representation of music–image correlation. We conducted an in-depth statistical analysis and user study to evaluate our dataset’s effectiveness and applicability for AI-driven understanding. This work provides a foundation for advanced explorations into the complex relationships between auditory and visual art modalities, advancing the development of more sophisticated cross-modal AI systems. Full article

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16 pages, 893 KiB

Open AccessArticle

Effects of Lactic Acid Bacterial Fermentation on the Biochemical Properties and Antimicrobial Activity of Hemp Seeds

by Dalia Čižeikienė, Ieva Gaidė, Daiva Žadeikė and Loreta Bašinskienė

Appl. Sci. 2024, 14(23), 11469; https://doi.org/10.3390/app142311469 - 9 Dec 2024

Viewed by 853

Abstract

Recently, there has been an increase in the application of lactic acid bacteria (LAB) for seed fermentation because of the improved functional, technological, and nutritional properties of the fermented seeds. The purpose of this study was to evaluate the effects of selected LAB [...] Read more.

Recently, there has been an increase in the application of lactic acid bacteria (LAB) for seed fermentation because of the improved functional, technological, and nutritional properties of the fermented seeds. The purpose of this study was to evaluate the effects of selected LAB on the biochemical and antimicrobial features of fermented hemp seeds and their water-, salt-, and ethanol-soluble protein fractions. The results showed that hemp seed medium was suitable for Lactiplantibacillus plantarum, Levilactobacillus brevis, and Lactobacillus acidophilus multiplication (with a LAB count > 10⁹ colony-forming units/g). The biochemical and antimicrobial properties of the fermented hemp seeds strictly depended on the LAB strain used for fermentation. The hemp seeds fermented with L. brevis, which was previously isolated from rye sourdough, presented the highest total phenolic content and phytase, amylase, protease, and antioxidant activities. The hemp seeds fermented with L. acidophilus showed the broadest spectrum of antimicrobial activity against foodborne pathogens. The ethanol-soluble protein fractions from the fermented hemp seeds inhibited the growth of Escherichia coli, Staphylococcus aureus, Salmonella typhimurium, Bacillus subtilis, and Bacillus cereus, while the ethanol-soluble protein fraction from unfermented hemp seeds did not have an antimicrobial effect. The results of ABTS·+ radical scavenging and antimicrobial activity assays by agar well diffusion method confirmed that the tested LAB strains for hemp seed fermentation influenced the antioxidant and antimicrobial activities of protein fractions. Full article

(This article belongs to the Special Issue Advances in Food Safety and Microbial Control)

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23 pages, 26520 KiB

Open AccessArticle

A Study on the Impact of Different Delay Times on Rock Mass Throwing and Movement Characteristics Based on the FEM–SPH Method

by Guoqiang Wang, Hui Chen and Jingkun Zhao

Appl. Sci. 2024, 14(23), 11468; https://doi.org/10.3390/app142311468 - 9 Dec 2024

Viewed by 710

Abstract

Burst morphology is a crucial indicator for evaluating the effectiveness of blasting, as it directly reflects the actual state of the blasting results. The results of rock displacement following blasting partially reflect the effectiveness of throw blasting, while the rock ejection process serves [...] Read more.

Burst morphology is a crucial indicator for evaluating the effectiveness of blasting, as it directly reflects the actual state of the blasting results. The results of rock displacement following blasting partially reflect the effectiveness of throw blasting, while the rock ejection process serves as the macroscopic manifestation of the blasting method. To accurately assess the impact of different delay times on burst formation, this study addressed the issues of rock movement and ejection in underground blasting. Using three-dimensional modeling, we constructed a FEM–SPH model and utilized LS-DYNA numerical simulation software to investigate the movement patterns of rock in precise delayed blasting scenarios underground. This study explored the spatiotemporal evolution characteristics of rock movement post-blasting. Digital electronic detonators were used to set precise inter-row delay times of 25 ms, 50 ms, and 75 ms. The results revealed that the ejection distance of blasted rock in underground mining increased with longer inter-row delay times, while the slope angle of the blasted muck pile decreased as the delay time increased. Furthermore, at a micro level, the study found that a 75 ms delay created new free surfaces, providing effective compensation space for subsequent blasts, thereby improving blasting outcomes. Analysis of the 25 ms and 50 ms delay periods indicated a clamping effect on rock movement. Field comparisons of blasting results were conducted to validate the influence of precise delay times on the movement patterns and spatiotemporal evolution characteristics of blasted rock. Full article

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18 pages, 5548 KiB

Open AccessArticle

Assessing Ammonia (NH₃) Emissions, Precursor Gas (SO₂, NO_x) Concentrations, and Source Contributions to Atmospheric PM_2.5 from a Commercial Manure Composting Facility

by Sang-Ryong Lee and Gyuwon Kim

Appl. Sci. 2024, 14(23), 11467; https://doi.org/10.3390/app142311467 - 9 Dec 2024

Viewed by 650

Abstract

Increased ammonia (NH₃) emissions from intensive agriculture negatively affect environmental and ecosystem health, contributing to formation of particulate matter (PM) and the potent greenhouse gas, N₂O. Better understanding NH₃ emissions from the manure composting process and their behavior [...] Read more.

Increased ammonia (NH₃) emissions from intensive agriculture negatively affect environmental and ecosystem health, contributing to formation of particulate matter (PM) and the potent greenhouse gas, N₂O. Better understanding NH₃ emissions from the manure composting process and their behavior as a constituent of the atmospheric aerosol load is a crucial element in creating better farm management systems, improving public health outcomes, and mitigating the broader environmental and climatic impacts of agriculture. Retarded generation of PM with a major constituent source of NH₃ is a primary mechanism for evaluating the effects of agricultural contribution to PM. This study aimed to quantify NH₃ emissions, examine the influence of environmental factors, and investigate the relationship between precursor gases (SO₂, NO_x, NH₃) and PM_2.5 at a modern manure composting facility in Paju, South Korea. Over 35 days, average internal concentrations of NH₃, SO₂, and NO_x were significantly higher than external levels. NH₃ concentrations reached 3.64 ± 0.06 mg m⁻³ at 3 m height and 2.43 ± 0.16 mg m⁻³ at ground level, while the total NH₃ flux from the facility was 24.47 ± 1.39 NH₃-N kg d⁻¹. Internal PM_2.5 concentrations (36.9 ± 2.6 µg m⁻³) were about 50% higher than external levels (23.7 ± 2 µg m⁻³), with a moderate correlation (r = 0.341) suggesting some contribution of external PM_2.5 to internal levels. Despite large quantities of internal emissions, the facility’s sealed design with a negative pressure ventilation system effectively minimized external emissions. These results suggest that while manure composting facilities are significant sources of NH₃ and PM_2.5, advanced systems like high-volume ventilation and scrubbing technologies can effectively reduce their impact on regional air pollution, contributing to better environmental management in agriculture. Full article

(This article belongs to the Section Environmental Sciences)

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40 pages, 1079 KiB

Open AccessArticle

Context-Adaptable Deployment of FastSLAM 2.0 on Graphic Processing Unit with Unknown Data Association

by Jessica Giovagnola, Manuel Pegalajar Cuéllar and Diego Pedro Morales Santos

Appl. Sci. 2024, 14(23), 11466; https://doi.org/10.3390/app142311466 - 9 Dec 2024

Viewed by 824

Abstract

Simultaneous Localization and Mapping (SLAM) algorithms are crucial for enabling agents to estimate their position in unknown environments. In autonomous navigation systems, these algorithms need to operate in real-time on devices with limited resources, emphasizing the importance of reducing complexity and ensuring efficient [...] Read more.

Simultaneous Localization and Mapping (SLAM) algorithms are crucial for enabling agents to estimate their position in unknown environments. In autonomous navigation systems, these algorithms need to operate in real-time on devices with limited resources, emphasizing the importance of reducing complexity and ensuring efficient performance. While SLAM solutions aim at ensuring accurate and timely localization and mapping, one of their main limitations is their computational complexity. In this scenario, particle filter-based approaches such as FastSLAM 2.0 can significantly benefit from parallel programming due to their modular construction. The parallelization process involves identifying the parameters affecting the computational complexity in order to distribute the computation among single multiprocessors as efficiently as possible. However, the computational complexity of methodologies such as FastSLAM 2.0 can depend on multiple parameters whose values may, in turn, depend on each specific use case scenario ( ingi.e., the context), leading to multiple possible parallelization designs. Furthermore, the features of the hardware architecture in use can significantly influence the performance in terms of latency. Therefore, the selection of the optimal parallelization modality still needs to be empirically determined. This may involve redesigning the parallel algorithm depending on the context and the hardware architecture. In this paper, we propose a CUDA-based adaptable design for FastSLAM 2.0 on GPU, in combination with an evaluation methodology that enables the assessment of the optimal parallelization modality based on the context and the hardware architecture without the need for the creation of separate designs. The proposed implementation includes the parallelization of all the functional blocks of the FastSLAM 2.0 pipeline. Additionally, we contribute a parallelized design of the data association step through the Joint Compatibility Branch and Bound (JCBB) method. Multiple resampling algorithms are also included to accommodate the needs of a wide variety of navigation scenarios. Full article

(This article belongs to the Special Issue Advancements in Multi-Agent Systems and Artificial Intelligence: Methodologies, Applications, and Future Trends)

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20 pages, 6787 KiB

Open AccessArticle

REDUCE—A Tool Supporting Inconsistencies Reduction in the Decision-Making Process

by Paweł Kuraś, Dominik Strzałka, Bartosz Kowal, Patryk Organiściak, Krzysztof Demidowski and Veronika Vanivska

Appl. Sci. 2024, 14(23), 11465; https://doi.org/10.3390/app142311465 - 9 Dec 2024

Viewed by 765

Abstract

This paper presents REDUCE, a free online tool designed to support decision-making processes by addressing inconsistency in multiplicative pairwise comparison (PC) matrices, a key element of many multi-criteria decision-making (MCDM) methods, including the analytic hierarchy process (AHP). AHP relies on pairwise comparisons to [...] Read more.

This paper presents REDUCE, a free online tool designed to support decision-making processes by addressing inconsistency in multiplicative pairwise comparison (PC) matrices, a key element of many multi-criteria decision-making (MCDM) methods, including the analytic hierarchy process (AHP). AHP relies on pairwise comparisons to assign weights to decision criteria or alternatives, but human-generated PC matrices often exhibit inconsistencies. Consistency is evaluated using Saaty’s consistency ratio (

C R

), where a value below 0.10 is considered acceptable. Higher inconsistency levels necessitate matrix corrections, which are challenging if the original expert is unavailable or revision constraints exist. REDUCE autonomously reduces inconsistency in PC matrices using two different algorithms that require no expert intervention. The tool accommodates different PC matrices, enabling users to specify the desired CR threshold (e.g.,

C R \leq 0.10

) and select the algorithm for adjustment. It ensures the resulting matrix is consistent while preserving the original preference structure to the greatest extent possible. Additionally, REDUCE calculates weights for the compared entities, making it a valuable tool for applications of AHP and related methodologies. Quantitative evaluations demonstrate that REDUCE can improve matrices with high inconsistency (e.g.,

C R = 0.25

) to acceptable levels (e.g.,

C R = 0.08

) while retaining up to 95% of the original preference integrity, depending on the chosen algorithm. By addressing the accessibility gap for small and medium enterprises (SMEs) that lack resources for costly decision-making software or expert consultants, REDUCE facilitates broader adoption of MCDM tools. This work highlights the potential of REDUCE to enhance decision-making reliability and accessibility in resource-constrained environments. Full article

(This article belongs to the Special Issue Decision-Making Methods: Applications and Perspectives)

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18 pages, 9183 KiB

Open AccessArticle

Short-Glass-Fiber Aspect Ratios in Polyamide-6 Composites: Homogenization and Deep Learning-Based Scanning Image-Microscope Segmentation Comparison

by Evgenii Kurkin, Vladislava Chertykovtseva, Andry Sedelnikov, Evgenii Minaev, Ekaterina Kurkina and Andrey Gavrilov

Appl. Sci. 2024, 14(23), 11464; https://doi.org/10.3390/app142311464 - 9 Dec 2024

Viewed by 808

Abstract

This paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using [...] Read more.

This paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. This makes it possible to use an electron microscope to image fiber samples corresponding to the sample size using microtomography. Molded samples and pellets of four polyamide-6 short-glass fiber-reinforced composites with mass fractions of 15%, 30%, and 50% were considered. The aspect ratio distribution measured by SEM for the investigated materials was 20.25 with a coefficient of variation of 5.1%. The fiber aspect ratio obtained based on mean field homogenization theory and the tensile curve approximation was underestimated at 13.698 with a coefficient of variation of 5.2%. The deviation between the micro- and macro-estimates can be represented as a mean effective aspect ratio of 68% with a coefficient of variation of 8.5%. The developed technology for preparing samples for SEM and automated image processing can be used to study other short-reinforced polymer composite materials. The obtained estimates can serve as a useful reference when calibrating other models of short-fiber-reinforced polymer materials. Full article

(This article belongs to the Special Issue Advanced Composite Materials and Structures: Innovations and Applications)

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17 pages, 5753 KiB

Open AccessArticle

Vehicle Mass Estimation via Practical Supervisory Artificial Neural Networks Using Perturbed Engine Torque and Acceleration Inputs

by Minsu Kim and Daeyi Jung

Appl. Sci. 2024, 14(23), 11463; https://doi.org/10.3390/app142311463 - 9 Dec 2024

Viewed by 585

Abstract

Various model-based mass estimation approaches have been discussed for a long time. However, estimation performance often deteriorates in some driving situations and, in particular, slow convergence and excessive overshoot of estimates are a major issue for model-based approaches. Meanwhile, mass estimation approaches using [...] Read more.

Various model-based mass estimation approaches have been discussed for a long time. However, estimation performance often deteriorates in some driving situations and, in particular, slow convergence and excessive overshoot of estimates are a major issue for model-based approaches. Meanwhile, mass estimation approaches using ANN models have recently emerged to propose better solutions, but their usefulness has not been fully investigated. Therefore, this paper presents a vehicle mass estimation strategy using practical supervisory artificial neural networks to achieve more accurate results with better convergence. Here, the perturbed engine torque and vehicle longitudinal acceleration are selected as the inputs of the ANN (instead of the original engine torque and vehicle acceleration), which allows for the faster convergence of estimates with high accuracy; these inputs are existing sensor values already available in the vehicle system. The effectiveness of the proposed ANN approach was verified using simulation and software-in-the-loop simulation (SILS) with field test data, and it was found that the convergence speed of the proposed ANN is almost twice as fast as that of the model-based approach, the accuracy is much better, and the estimation quality is constantly stable without any excessive transient responses. This study will provide further insights into mass estimation using the ANN approach. Full article

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29 pages, 8082 KiB

Open AccessArticle

Charting the Growth of Text Summarisation: A Data-Driven Exploration of Research Trends and Technological Advancements

by Anukriti Kaushal, Chia-Chen Lin, Rishabh Chauhan and Rajeev Kumar

Appl. Sci. 2024, 14(23), 11462; https://doi.org/10.3390/app142311462 - 9 Dec 2024

Viewed by 847

Abstract

Text summarisation plays a pivotal role in efficiently processing large volumes of textual data, making it an indispensable tool across diverse domains such as healthcare, legal, education, and journalism. It addresses the challenge of information overload by condensing or generating concise, meaningful summaries [...] Read more.

Text summarisation plays a pivotal role in efficiently processing large volumes of textual data, making it an indispensable tool across diverse domains such as healthcare, legal, education, and journalism. It addresses the challenge of information overload by condensing or generating concise, meaningful summaries that improve decision-making, enhance accessibility, and save valuable time. Advances in artificial intelligence continue to propel the growth of text summarisation research, particularly with the evolution from traditional extractive approaches to cutting-edge abstractive models like BERT and GPT, as well as emerging innovations in multimodal and multilingual summarisation. To trace the development of this field, this study integrates bibliometric analysis and an in-depth survey, leveraging data from the Web of Science database to explore citation trends, uncover influential contributors, and highlight emerging research areas. Furthermore, bibliometric and critical evaluations are employed to outline strategic pathways and propose future directions for the continued advancement of the field. By incorporating sophisticated visualisation tools such as VOSviewer and RawGraphs, the analysis provides an enriched understanding of the field’s trajectory, identifying significant methodologies, landmark contributions, and existing gaps. This comprehensive exploration not only underscores the progress achieved in text summarisation but also serves as an invaluable resource for shaping forthcoming research endeavours and inspiring innovation in this dynamic area of study. Full article

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

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11 pages, 2277 KiB

Open AccessArticle

Investigating an Enhanced Contour Blasting Technique Considering Rock Mass Structural Properties

by Askar Imashev, Aibek Mussin and Amoussou Coffi Adoko

Appl. Sci. 2024, 14(23), 11461; https://doi.org/10.3390/app142311461 - 9 Dec 2024

Viewed by 664

Abstract

When excavating tunnels and underground openings with the drill-and-blast method, minimizing excavation overbreak is vital, as it reduces the costs associated with excavation stability, mucking, and rock support. Overbreak in excavations not only causes safety concerns but also increases the cost of construction [...] Read more.

When excavating tunnels and underground openings with the drill-and-blast method, minimizing excavation overbreak is vital, as it reduces the costs associated with excavation stability, mucking, and rock support. Overbreak in excavations not only causes safety concerns but also increases the cost of construction and completion time. This paper proposes a contour blasting design in which the parameters are optimized based on the rock’s structural properties. Numerical modeling was used to identify the possible damage zones of rock with a change of the seismic load due to blasting. The results were used as input for the design of the proposed contour blasting with a low-brisance explosive. Experimental blasting tests were conducted at the Akbakai mine, located in Kazakhstan, and the performance of the design was examined. The proposed contour blasting was compared with the standard blasting method. The results indicated that the cross-section of excavation with the conventional blasting method varied between 10.5 and 12.1 m², indicating an overbreak between 17 and 34%. However, with the suggested contour blasting, the overbreak was less than 13%. It was concluded that charging contour boreholes with low-brisance explosives is an effective method of reducing overbreak due to excessive explosive loads on the contour massif, which can improve the safety and profitability of mining operations. Full article

(This article belongs to the Special Issue Underground Rock Support and Excavation)

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23 pages, 4842 KiB

Open AccessArticle

Evaluation of Snowboarding Helmets in Mitigation of the Biomechanical Responses of Head Surrogate

by Atul Harmukh and Shailesh G. Ganpule

Appl. Sci. 2024, 14(23), 11460; https://doi.org/10.3390/app142311460 - 9 Dec 2024

Viewed by 812

Abstract

Traumatic brain injury (TBI) during snowboarding sports is a major concern. A robust evaluation of existing snowboarding helmets is desired. Head kinematics (i.e., linear acceleration, angular velocity, angular acceleration) and associated brain responses (brain pressure, equivalent (von Mises) stress, and maximum principal strain) [...] Read more.

Traumatic brain injury (TBI) during snowboarding sports is a major concern. A robust evaluation of existing snowboarding helmets is desired. Head kinematics (i.e., linear acceleration, angular velocity, angular acceleration) and associated brain responses (brain pressure, equivalent (von Mises) stress, and maximum principal strain) of the head are a predominant cause of TBI or concussion. The conventional snowboarding helmet, which mitigates linear acceleration, is typically used in snow sports. However, the role of conventional snowboarding helmets in mitigating angular head kinematics is marginal or insignificant. In recent years, new anti-rotational technologies (e.g., MIPS, WaveCel) have been developed that seek to reduce angular kinematics (i.e., angular velocity, angular acceleration). However, investigations regarding the performance of snowboarding helmets in terms of the mitigation of head kinematics and brain responses are either extremely limited or not available. Toward this end, we have evaluated the performance of snowboarding helmets (conventional and anti-rotational technologies) against blunt impact. We also evaluated the performance of newly developed low-cost, silica-based anti-rotational pads by integrating them with conventional helmets. Helmets were mounted on a head surrogate–Hybrid III neck assembly. The head surrogate consisted of skin, skull, dura mater, and brain. The geometry of the head surrogate was based on the GHBMC head model. Substructures of the head surrogate was manufactured using additive manufacturing and/or molding. A linear impactor system was used to simulate/recreate snowfield hazards (e.g., tree stump, rock, pole) loading. Following the ASTM F2040 standard, an impact velocity of 4.6 ± 0.2 m/s was used. The head kinematics (i.e., linear acceleration, angular velocity, angular acceleration) and brain simulant pressures were measured in the head surrogate. Further, using the concurrent simulation, the brain simulant responses (i.e., pressure, von Mises stress, and maximum principal strain) were computed. The front and side orientations were considered. Our results showed that the helmets with anti-rotation technologies (i.e., MIPS, WaveCel) significantly reduced the angular kinematics and brain responses compared to the conventional helmet. Further, the performance of the silica pad-based anti-rotational helmet was comparable to the existing anti-rotational helmets. Lastly, the effect of a comfort liner on head kinematics was also investigated. The comfort liner further improved the performance of anti-rotational helmets. Overall, these results provide important data and novel insights regarding the performance of various snowboarding helmets. These data have utility in the design and development of futuristic snowboarding helmets and safety protocols. Full article

(This article belongs to the Special Issue Traumatic Injury Towards Enhanced Prevention, Diagnosis, Prognosis, and Treatment)

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16 pages, 1853 KiB

Open AccessArticle

Early Infection for Mass Production of Artificial Single-Stranded DNA with Escherichia coli

by Nathalie Hafner, Nazanin Nematzadeh Somehsaraei, Maximilian N. Honemann, Hendrik Dietz and Dirk Weuster-Botz

Appl. Sci. 2024, 14(23), 11459; https://doi.org/10.3390/app142311459 - 9 Dec 2024

Viewed by 944

Abstract

Large quantities of artificial single-stranded DNA (ssDNA) with user-defined sequences are increasingly required to exploit the potential of DNA nanotechnology. Cross-contamination-free ssDNA production can be achieved using Escherichia coli with an optimized helper plasmid in high-cell-density cultivation via the secretion of phagemid particles [...] Read more.

Large quantities of artificial single-stranded DNA (ssDNA) with user-defined sequences are increasingly required to exploit the potential of DNA nanotechnology. Cross-contamination-free ssDNA production can be achieved using Escherichia coli with an optimized helper plasmid in high-cell-density cultivation via the secretion of phagemid particles containing ssDNA with user-defined sequences. In our study, we aimed to reduce the number of phagemid particles for the initiation of ssDNA production. We tested different infection densities, ranging from a multiplicity of infection (MOI) of 10⁻⁶–10⁻² tfu cfu⁻¹ at the start of the initial batch phase in a 2.5 L stirred tank bioreactor. A MOI of 10⁻³ tfu cfu⁻¹ was the best compromise between process time and ssDNA concentration. Early initiation of ssDNA production with low MOI reduced the number of phagemid particles by a factor of 250,000. The early infection strategy was successfully scaled up to the 25 L scale, resulting in ssDNA concentrations of >100 mg L⁻¹ within a process time of one day. Transferring the infection strategy to a 1000 L scale gained 65 mg L⁻¹ ssDNA because of incomplete initial infection. The versatility of the early infection strategy was further proven with a second prolonged, user-defined ssDNA sequence. Full article

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22 pages, 11079 KiB

Open AccessArticle

Hybrid 3D Convolutional–Transformer Model for Detecting Stereotypical Motor Movements in Autistic Children During Pre-Meltdown Crisis

by Salma Kammoun Jarraya and Marwa Masmoudi

Appl. Sci. 2024, 14(23), 11458; https://doi.org/10.3390/app142311458 - 9 Dec 2024

Viewed by 581

Abstract

Computer vision using deep learning algorithms has served numerous human activity identification applications, particularly those linked to safety and security. However, even though autistic children are frequently exposed to danger as a result of their activities, many computer vision experts have shown little [...] Read more.

Computer vision using deep learning algorithms has served numerous human activity identification applications, particularly those linked to safety and security. However, even though autistic children are frequently exposed to danger as a result of their activities, many computer vision experts have shown little interest in their safety. Several autistic children show severe challenging behaviors such as the Meltdown Crisis which is characterized by hostile behaviors and loss of control. This study aims to introduce a monitoring system capable of predicting the Meltdown Crisis condition early and alerting the children’s parents or caregivers before entering more difficult settings. For this endeavor, the suggested system was constructed using a combination of a pre-trained Vision Transformer (ViT) model (Swin-3D-b) and a Residual Network (ResNet) architecture to extract robust features from video sequences to extract and learn the spatial and temporal features of the Stereotyped Motor Movements (SMMs) made by autistic children at the beginning of the Meltdown Crisis state, which is referred to as the Pre-Meltdown Crisis state. The evaluation was conducted using the MeltdownCrisis dataset, which contains realistic scenarios of autistic children’s behaviors in the Pre-Meltdown Crisis state, with data from the Normal state serving as the negative class. Our proposed model achieved great classification accuracy, at 92%. Full article

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15 pages, 6760 KiB

Open AccessArticle

A Modified Bearing Capacity Model for Inclined Shallow Anchor Cable with Experimental Verification

by Zhenhua Zhang, Guojuan Xu, Liangjun Dai, Tao Cheng, Banglu Xi, Mingliang Chen and Jiaqiang Yang

Appl. Sci. 2024, 14(23), 11457; https://doi.org/10.3390/app142311457 - 9 Dec 2024

Viewed by 628

Abstract

Most theoretical models of shallow anchor cables do not take the effect of anchor inclination into consideration, which is an important factor influencing load distribution, stress concentration, and failure mechanisms. In this paper, a modified bearing capacity was developed for a single anchor [...] Read more.

Most theoretical models of shallow anchor cables do not take the effect of anchor inclination into consideration, which is an important factor influencing load distribution, stress concentration, and failure mechanisms. In this paper, a modified bearing capacity was developed for a single anchor cable, taking the anchor inclination into consideration, based on the principle of limit equilibrium. Then, a series of indoor pull-out tests of single anchors with different inclinations were performed, where the effects of the anchor inclination on the bearing capacity and failure mechanisms were carefully analyzed. The experimental bearing capacities were compared to the predicted data of the proposed modified model, as well as other existing experimental results, aiming to verify the applicability and accuracy. The results show that the bearing capacity increases with decreasing anchor inclination because the vertical component of the force acting on the anchor cable increases. The failure models of the anchor cables, pulled out at different angles, exhibit an asymmetric “inverted trumpet” shape, which is caused by the varying stress distributions around the anchor cable during pull-out. In addition, the bearing capacities of the theory differ very little from the experimental and previous results, with a max error of nearly 10%. This study confirms that the proposed model reliably captures the effects of anchor inclination, providing valuable insights for designing inclined anchors in engineering practice. Full article

(This article belongs to the Special Issue Emerging Trends in Rock Mechanics and Rock Engineering)

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13 pages, 3585 KiB

Open AccessFeature PaperArticle

How Does Induced Deceleration of One Treadmill’s Belt in the Pre-Swing Gait Phase Change Gait Pattern?

by Katarzyna Chodkowska, Michalina Błażkiewicz, Justyna Kędziorek, Dorota Ortenburger and Jacek Wąsik

Appl. Sci. 2024, 14(23), 11456; https://doi.org/10.3390/app142311456 - 9 Dec 2024

Viewed by 666

Abstract

This study aimed to investigate how external perturbations caused by the treadmill belt’s deceleration during the pre-swing phase affect gait kinematics and kinetics in young adults. Twenty-one healthy young females walked on a treadmill in a virtual environment (GRAIL, Motek), where unexpected perturbations [...] Read more.

This study aimed to investigate how external perturbations caused by the treadmill belt’s deceleration during the pre-swing phase affect gait kinematics and kinetics in young adults. Twenty-one healthy young females walked on a treadmill in a virtual environment (GRAIL, Motek), where unexpected perturbations were applied to the left belt, mimicking a ‘trip-like’ effect at toe-off. The spatiotemporal, kinematic, and kinetic parameters were analyzed during two cycles. The first cycle involved the first perturbation and the response to it. The second included a gait cycle without the perturbation (treadmill gait). The perturbation resulted in an increased stride duration for both limbs when compared to the treadmill gait. The perturbed limb had a longer support phase, while the reactive limb had the longest double stance phase. The responding limb exhibited more than double the ankle plantarflexion compared to the normal treadmill gait and the perturbed limb. At the hip joint, both limbs showed significantly higher values, with a 40.8% increase in flexion and a 227% increase in extension for the perturbed limb, and a 24.5% increase in flexion and a 212% increase in extension for the responding limb, compared to the treadmill gait. Muscle torque was generally lower in most joints for both limbs, except for notably higher hip and knee extensor values for the perturbed limb. The responding limb exhibited lower values for the ankle, knee, and hip joints, indicating unexpected muscle activity patterns. Studying treadmill belt deceleration during pre-swing gait can provide valuable insights into biomechanical adaptations and motor control strategies. Full article

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12 pages, 2662 KiB

Open AccessArticle

Determination of Lichens’ Bioaccumulation Capacity for Radioactive Isotopes Under Laboratory Conditions as a Basis for Their Application as Biomonitors

by Michał Saniewski, Michał Hubert Węgrzyn, Patrycja Fałowska, Patrycja Dziurowicz, Karolina Waszkiewicz and Tamara Zalewska

Appl. Sci. 2024, 14(23), 11455; https://doi.org/10.3390/app142311455 - 9 Dec 2024

Viewed by 611

Abstract

This study investigates the bioaccumulation capacity of the lichen Cladonia uncialis for radioactive isotopes, aiming to establish its potential as a biomonitor. Conducted under controlled laboratory conditions, the experiment utilised gamma-emitting isotopes to simulate fallout. The lichens were exposed to varying concentrations of [...] Read more.

This study investigates the bioaccumulation capacity of the lichen Cladonia uncialis for radioactive isotopes, aiming to establish its potential as a biomonitor. Conducted under controlled laboratory conditions, the experiment utilised gamma-emitting isotopes to simulate fallout. The lichens were exposed to varying concentrations of these isotopes in three aquariums. The results demonstrated that the bioaccumulation of ⁵⁴Mn, ⁵⁷Co, ⁶⁰Co, ⁶⁵Zn, ¹³⁷Cs, and ²⁴¹Am by C. uncialis was proportional to their initial deposition levels, and this occurred in the first days of the experiment. Analysis of isotope activity in washed and unwashed lichens showed that retention primarily occurred intracellularly, indicating effective bioaccumulation. The study derived the Aggregated Transfer Coefficient (Tag) for each isotope, which ranged from 0.34 to 0.64, and the absorption capacity of the elements increased in the following order: ⁵⁴Mn < ⁵⁷Co < ⁶⁰Co ≤ ⁶⁵Zn < ²⁴¹Am < ¹³⁷Cs. Absorption efficiency, amounting to approximately 50% for ¹³⁷Cs and ²⁴¹Am, highlights the potential for lichens to serve as reliable biomonitors for environmental monitoring and estimation of deposition when knowing only the activity of the isotopes in lichen. Full article

(This article belongs to the Special Issue Advances in Environmental Applied Physics—2nd Edition)

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15 pages, 7101 KiB

Open AccessArticle

Fatigue Crack Propagation Analysis of Rail Surface Under Mixed Initial Crack Patterns

by Jianhua Liu, Weiqi Yang and Zhongmei Wang

Appl. Sci. 2024, 14(23), 11454; https://doi.org/10.3390/app142311454 - 9 Dec 2024

Viewed by 690

Abstract

Prolonged rolling contact fatigue between wheels and rails results in the formation of surface cracks on the rail and accurately analyzing the crack expansion behavior is essential to ensuring the safe operation of the train. Drawing upon the principles of fracture mechanics and [...] Read more.

Prolonged rolling contact fatigue between wheels and rails results in the formation of surface cracks on the rail and accurately analyzing the crack expansion behavior is essential to ensuring the safe operation of the train. Drawing upon the principles of fracture mechanics and finite element theory, this study establishes a finite element model of wheel–rail rolling contact that incorporates the presence of cracks. The method utilizes an interaction integral to calculate the stress intensity factors at the leading edge of the crack; then, the Paris formula is used to solve the crack spreading rate. It systematically examines the effects of the initial crack angle, the coefficient of friction of wheels to rails, and crack size on the behavior of fatigue crack propagation. The results indicate that the cracks primarily extend in the depth direction of the rail, transforming the semi-circular surface cracks into elliptical cracks with the major axis oriented along the rail’s width. Crack propagation is primarily driven by model II and III composite crack propagation, with their expansion rates influenced by operating conditions. In contrast, mode-I expansion is less sensitive to these conditions. Under single-variable loading conditions, a smaller initial crack angle results in a faster crack growth rate. Increasing crack length accelerates crack growth, while a higher friction coefficient inhibits it. Full article

(This article belongs to the Section Materials Science and Engineering)

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23 pages, 46810 KiB

Open AccessArticle

Investigation of Corrosion Product Distribution and Induced Cracking Patterns in Reinforced Concrete Using Accelerated Corrosion Testing

by Olfa Loukil, Lucas Adelaide, Véronique Bouteiller, Marc Quiertant, Frédéric Ragueneau and Thierry Chaussadent

Appl. Sci. 2024, 14(23), 11453; https://doi.org/10.3390/app142311453 - 9 Dec 2024

Viewed by 692

Abstract

The present study investigates the corrosion development and induced cracks in reinforced concrete specimens submitted to an accelerated corrosion test. The accelerated chloride-induced corrosion test was performed using an impressed current mode. Three current densities (50, 100 and 200 µA/cm² of steel) [...] Read more.

The present study investigates the corrosion development and induced cracks in reinforced concrete specimens submitted to an accelerated corrosion test. The accelerated chloride-induced corrosion test was performed using an impressed current mode. Three current densities (50, 100 and 200 µA/cm² of steel) and different exposure times were considered. The objective of the experiments is to analyse two distinct types of damage: firstly, internal damage near the steel/concrete interface, which can be observed in the distribution of corrosion products, as well as damage within the concrete cover, which manifests as cracking. Secondly, external damage, which can be observed in the form of rust spots and concrete surface cracks. The aim of this analysis is to elucidate the relationship between internal damage and external damage. The study confirmed that the corrosion products are non-uniformly distributed around and along the steel reinforcing bar. It also highlighted that the accelerated corrosion test conditions, such as current density, duration, environmental conditions and the specimen geometry, have a significant influence on the distribution of the corrosion products and their thickness around the steel reinforcement and therefore on the internal and external crack patterns. The data analysis revealed a substantial dispersion and contrast in terms of the data, which precluded the establishment of a definitive correlation between internal and external deterioration. Full article

(This article belongs to the Special Issue Advances in Reinforced Concrete Structural Health Monitoring)

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48 pages, 6986 KiB

Open AccessReview

Fluid Flow-Based Vibration Energy Harvesters: A Critical Review of State-of-the-Art Technologies

by Sadia Bakhtiar, Farid Ullah Khan, Hailing Fu, Amal Z. Hajjaj and Stephanos Theodossiades

Appl. Sci. 2024, 14(23), 11452; https://doi.org/10.3390/app142311452 - 9 Dec 2024

Viewed by 1646

Abstract

Energy harvesting technology plays an important role in converting ambient energy into useful electrical energy to power wireless sensing and system monitoring, especially for systems operating in isolated, abandoned or embedded locations where battery replacement or recharging is not a feasible solution. This [...] Read more.

Energy harvesting technology plays an important role in converting ambient energy into useful electrical energy to power wireless sensing and system monitoring, especially for systems operating in isolated, abandoned or embedded locations where battery replacement or recharging is not a feasible solution. This paper provides an integrative study of the methodologies and technologies of energy harvesting from fluid flow-induced vibration (FIV). The recent research endeavors contributing to flow-based energy harvesting have been reviewed to present the state-of-the-art issues and challenges. Several mechanisms on FIVs including vortex-induced vibrations (VIVs), flutter, galloping and wake galloping are thoroughly discussed in terms of device architecture, operating principles, energy transduction, voltage production and power generation. Additionally, advantages and disadvantages of each FIV energy harvesting mechanism are also talked about. Power enhancement methods, such as induced nonlinearities, optimized harvester’s configuration, hybridization and coupling of aerodynamic instabilities, for boosting the harvester’s output are also elucidated and categorized. Moreover, rotary wind energy harvesters are reviewed and discussed. Finally, the challenges and potential directions related to the flow-based energy harvesters (FBEHs) are also mentioned to provide an insight to researchers on the development of sustainable energy solutions for remote wireless sensing and monitoring systems. Full article

(This article belongs to the Section Mechanical Engineering)

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19 pages, 10315 KiB

Open AccessArticle

Selection of Grid Road Networks Based on Raster Data

by Yilang Shen, Yiqing Zhang and Renzhu Li

Appl. Sci. 2024, 14(23), 11451; https://doi.org/10.3390/app142311451 - 9 Dec 2024

Viewed by 573

Abstract

In cartography, generalization is a key process used to simplify complex geographic information, making it suitable for display at different scales while maintaining its essential meaning. When representing high-density road networks on a fixed screen area, overcrowding and loss of clarity often occur. [...] Read more.

In cartography, generalization is a key process used to simplify complex geographic information, making it suitable for display at different scales while maintaining its essential meaning. When representing high-density road networks on a fixed screen area, overcrowding and loss of clarity often occur. To solve these problems, a road selection operation can be applied. However, traditional methods have primarily focused on structured vector road networks, leaving unstructured raster road networks largely unaddressed. This study introduces a novel technique, Adaptive Road Width Selection (ARWS), designed to improve the multiscale visualization of compact road systems using unstructured raster datasets. The ARWS method begins by segmenting the original raster road network into multilevel superpixels of varying sizes, reflecting the road widths, through neighborhood analysis. Next, road superpixel matching and selection are performed based on the minimum angle and maximum distance rules, alongside shortest-path calculations. Finally, redundant intersection pixels are eliminated to generate the selection results. The proposed ARWS method was evaluated using road network data from Shenzhen, China, producing effective multiscale visualization outcomes. Unlike conventional techniques relying on structured vector data, ARWS excels in preserving the semantic attributes, overall structure, local connectivity, and integrity of road networks. It addresses the challenges of multiscale visualization in dense road networks, offering a robust solution for unstructured raster data. Full article

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28 pages, 10033 KiB

Open AccessArticle

A WENO-Based Upwind Rotated Lattice Boltzmann Flux Solver with Lower Numerical Dissipation for Simulating Compressible Flows with Contact Discontinuities and Strong Shock Waves

by Yunhao Wang, Jiabao Chen, Yan Wang, Yuhang Zeng and Shitang Ke

Appl. Sci. 2024, 14(23), 11450; https://doi.org/10.3390/app142311450 - 9 Dec 2024

Viewed by 643

Abstract

This paper presents a WENO-based upwind rotated lattice Boltzmann flux solver (WENO-URLBFS) in the finite difference framework for simulating compressible flows with contact discontinuities and strong shock waves. In the method, the original rotating lattice Boltzmann flux solver is improved by applying the [...] Read more.

This paper presents a WENO-based upwind rotated lattice Boltzmann flux solver (WENO-URLBFS) in the finite difference framework for simulating compressible flows with contact discontinuities and strong shock waves. In the method, the original rotating lattice Boltzmann flux solver is improved by applying the theoretical solution of the Euler equation in the tangential direction of the cell interface to reconstruct the tangential flux so that the numerical dissipation can be reduced. The fluxes at each interface are evaluated using a weighted summation of lattice Boltzmann solutions in two local perpendicular directions decomposed from the direction vector so that the stability performance can be improved. To achieve high-order accuracy, both fifth and seventh-order WENO reconstructions of the flow variables in the characteristic spaces are carried out. The order accuracy of the WENO-URLBFS is evaluated and compared with the traditional Lax–Friedrichs scheme, Roe scheme, and the LBFS by simulating the advection of the density disturbance problem. It is shown that the fifth and seventh-order accuracy can be achieved by all considered flux-evaluation schemes, and the present WENO-URLBFS has the lowest numerical dissipation. The performance of the WENO-URLBFS is further examined by simulating several 1D and 2D examples, including shock tube problems, Shu–Osher problems, blast wave problems, double Mach reflections, 2D Riemann problems, K-H instability problems, and High Mach number astrophysical jets. Good agreements with published data have been achieved quantitatively. Moreover, complex flow structures, including shock waves and contact discontinuities, are successfully captured. The present WENO-URLBFS scheme seems to present an effective numerical tool with high-order accuracy, lower numerical dissipation, and strong robustness for simulating challenging compressible flow problems. Full article

(This article belongs to the Section Aerospace Science and Engineering)

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18 pages, 2358 KiB

Open AccessArticle

Extracellular Lipases of Yarrowia lipolytica Yeast in Media Containing Plant Oils—Studies Supported by the Design of Experiment Methodology

by Agata Fabiszewska, Bartłomiej Zieniuk, Karina Jasińska, Dorota Nowak, Katarzyna Sasal, Joanna Kobus and Urszula Jankiewicz

Appl. Sci. 2024, 14(23), 11449; https://doi.org/10.3390/app142311449 - 9 Dec 2024

Viewed by 636

Abstract

Lipases are enzymes of great application importance in the food industry, in the cosmetic and detergent industries, in pharmacy and medicine, and in organic chemistry. Among lipases of various origins, those from microorganisms are currently the most commonly used. An excellent producer of [...] Read more.

Lipases are enzymes of great application importance in the food industry, in the cosmetic and detergent industries, in pharmacy and medicine, and in organic chemistry. Among lipases of various origins, those from microorganisms are currently the most commonly used. An excellent producer of lipases seems to be the nonconventional Yarrowia lipolytica yeast, but the biosynthesis of valuable metabolites depends on many factors. This study aimed to investigate the biodiversity of extracellular enzymes produced by four strains of Y. lipolytica, and to determine the optimal conditions of catalysis for the enzymes, according to temperature and pH, in a model hydrolysis reaction. Based on the obtained results, the biodiversity and strain dependence in lipase biosynthesis were observed. Using a Central Composite Design, it was found that temperature is the main factor in determining lipase activity. The enzymes produced by four different strains exhibited other substrate specificity, which was investigated using Latin square design methodology. Only two examined yeast strains, KKP 379 and W29, produced extracellular lipases at a high activity level towards medium- and long-chain fatty acid esters. Moreover, extracellular lipase from wild-type strain KKP 379 was further characterized, followed by exploring the activity of whole-cell biocatalyst and lyophilized enzyme solutions, and it was acknowledged that it was a “true” lipase with the highest affinity to p-nitrophenyl oleate. Full article

(This article belongs to the Special Issue Recent Advances in the Improvement of Food Quality and Safety)

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22 pages, 731 KiB

Open AccessOpinion

Intellectual Property Challenges in the Age of 3D Printing: Navigating the Digital Copycat Dilemma

by Antreas Kantaros

Appl. Sci. 2024, 14(23), 11448; https://doi.org/10.3390/app142311448 - 9 Dec 2024

Viewed by 1246

Abstract

This paper examines the intellectual property (IP) challenges introduced by 3D printing, a transformative technology enabling widespread innovation, but also raising critical legal questions. It focuses on three main areas: (1) IP issues associated with 3D printing hardware, (2) copyright and licensing complexities [...] Read more.

This paper examines the intellectual property (IP) challenges introduced by 3D printing, a transformative technology enabling widespread innovation, but also raising critical legal questions. It focuses on three main areas: (1) IP issues associated with 3D printing hardware, (2) copyright and licensing complexities related to downloadable 3D files, and (3) IP concerns for commercialized 3D printed items. Through a comprehensive review, the paper highlights how existing IP frameworks struggle to keep pace with the flexibility and accessibility inherent in 3D printing. Proposed solutions, such as blockchain for secure design tracking and enhanced digital rights management (DRM), point towards a more controlled future for digital design protection. Additionally, the study underscores the need for international cooperation to harmonize IP laws, facilitating more effective cross-border enforcement. This work aims to contribute to the ongoing dialogue on IP rights in 3D printing, proposing adaptive strategies to support legal clarity while fostering technological advancement. Full article

(This article belongs to the Section Additive Manufacturing Technologies)

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15 pages, 12118 KiB

Open AccessArticle

Effect of Vehicle Vibration on Interior Noise of Railway Vehicles Passing Through Rail Corrugation Sections

by Junhyuk Lee, Yonghyun Park and Dahoon Ahn

Appl. Sci. 2024, 14(23), 11447; https://doi.org/10.3390/app142311447 - 9 Dec 2024

Viewed by 637

Abstract

This study involved experimental research to analyze the effect of rail corrugation on interior noise levels inside railway vehicles. Measurements taken on the Incheon Line 2 light rail indicated that the vehicle’s age and maintenance condition have minimal effects on interior noise. Although [...] Read more.

This study involved experimental research to analyze the effect of rail corrugation on interior noise levels inside railway vehicles. Measurements taken on the Incheon Line 2 light rail indicated that the vehicle’s age and maintenance condition have minimal effects on interior noise. Although wheel wear slightly reduces interior noise, it is insufficient to address the issue of abnormal noise. The analysis of the relationship between vehicle vibrations and interior noise revealed that at 80 km/h and with a 24 mm rail corrugation wavelength, vibrations at 920 Hz in the axle box and car body increase, coinciding with the dominant interior noise frequency of 926.6 Hz. Furthermore, an analysis using a car body sweep confirmed a relative increase in noise in the 920 Hz range. Therefore, abnormal noise in rail corrugation sections is caused by vibrations at 920 Hz due to the corrugation wavelength and train speed, which align with the car body resonance frequency, leading to increased car body vibrations and interior noise. Full article

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23 pages, 5822 KiB

Open AccessArticle

Reverb and Noise as Real-World Effects in Speech Recognition Models: A Study and a Proposal of a Feature Set

by Valerio Cesarini and Giovanni Costantini

Appl. Sci. 2024, 14(23), 11446; https://doi.org/10.3390/app142311446 - 9 Dec 2024

Viewed by 723

Abstract

Reverberation and background noise are common and unavoidable real-world phenomena that hinder automatic speaker recognition systems, particularly because these systems are typically trained on noise-free data. Most models rely on fixed audio feature sets. To evaluate the dependency of features on reverberation and [...] Read more.

Reverberation and background noise are common and unavoidable real-world phenomena that hinder automatic speaker recognition systems, particularly because these systems are typically trained on noise-free data. Most models rely on fixed audio feature sets. To evaluate the dependency of features on reverberation and noise, this study proposes augmenting the commonly used mel-frequency cepstral coefficients (MFCCs) with relative spectral (RASTA) features. The performance of these features was assessed using noisy data generated by applying reverberation and pink noise to the DEMoS dataset, which includes 56 speakers. Verification models were trained on clean data using MFCCs, RASTA features, or their combination as inputs. They validated on augmented data with progressively increasing noise and reverberation levels. The results indicate that MFCCs struggle to identify the main speaker, while the RASTA method has difficulty with the opposite class. The hybrid feature set, derived from their combination, demonstrates the best overall performance as a compromise between the two. Although the MFCC method is the standard and performs well on clean training data, it shows a significant tendency to misclassify the main speaker in real-world scenarios, which is a critical limitation for modern user-centric verification applications. The hybrid feature set, therefore, proves effective as a balanced solution, optimizing both sensitivity and specificity. Full article

(This article belongs to the Special Issue Spatial Audio and Sound Design)

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26 pages, 6029 KiB

Open AccessArticle

Median U-Turn Intersection Critical Parameter Research and Operational Performance Evaluation

by Changxiang Zhao, Xuewen Liu, Tianhao Wu and Weiwei Zhang

Appl. Sci. 2024, 14(23), 11445; https://doi.org/10.3390/app142311445 - 9 Dec 2024

Viewed by 632

Abstract

As one of the unconventional intersection designs, the median U-turn (MUT) intersection design has been confirmed to have the potential to improve intersection efficiency and produce lower vehicle delays, and it has been widely applied to many urban networks. Most existing studies have [...] Read more.

As one of the unconventional intersection designs, the median U-turn (MUT) intersection design has been confirmed to have the potential to improve intersection efficiency and produce lower vehicle delays, and it has been widely applied to many urban networks. Most existing studies have successfully evaluated the operational performance of MUT intersections by analyzing the overall traffic flow, particularly for intersection delay and capacity. However, the impact of the critical parameters and behavior of individual vehicles in MUT intersection operations has not been adequately studied. These limitations cannot provide a complete and objective evaluation of MUT intersections. Therefore, a comprehensive cellular automata model is proposed to simulate vehicle dynamic variations, considering road channelization information and vehicle random movements. This model will be compared to the VISSIM model to validate rationality by using field data, and it shows a good agreement between the simulation results of both models. In addition, sensitive experiments reveal that properly adjusting the elements, including the separation distance, the proportion of left-turn vehicles, and green phase percentage, can improve the operation of MUT intersections to varying degrees. By appropriately improving intersection features and conducting reasonable evaluations, the overall performance and sustainability of the MUT intersections in Xi’an city can be enhanced. Finally, this paper offers a valuable guideline for the evaluation and modeling strategies of MUT intersections. Full article

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12 pages, 1950 KiB

Open AccessArticle

Distance Estimation with a Stereo Camera and Accuracy Determination

by Arnold Zaremba and Szymon Nitkiewicz

Appl. Sci. 2024, 14(23), 11444; https://doi.org/10.3390/app142311444 - 9 Dec 2024

Viewed by 1021

Abstract

Distance measurement plays a key role in many fields of science and technology, including robotics, civil engineering, and navigation systems. This paper focuses on analyzing the precision of a measurement system using stereo camera distance measurement technology in the context of measuring two [...] Read more.

Distance measurement plays a key role in many fields of science and technology, including robotics, civil engineering, and navigation systems. This paper focuses on analyzing the precision of a measurement system using stereo camera distance measurement technology in the context of measuring two objects of different sizes. The first part of the paper presents key information about stereoscopy, followed by a discussion of the process of building a measuring station. The Mask R-CNN algorithm, which is a deep learning model that combines object detection and instance segmentation, was used to identify objects in the images. In the following section, the calibration process of the system and the distance calculation method are presented. The purpose of the study was to determine the precision of the measurement system and to identify the distance ranges where the measurements are most precise. Measurements were made in the range of 20 to 70 cm. The system demonstrated a relative error of 0.95% for larger objects and 1.46% for smaller objects at optimal distances. A detailed analysis showed that for larger objects, the system exhibited higher precision over a wider range of distances, while for smaller objects, the highest accuracy was achieved over a more limited range. These results provide valuable information on the capabilities and limitations of the measurement system used, while pointing out directions for its further optimization. Full article

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16 pages, 1528 KiB

Open AccessArticle

1-Bit Reconfigurable Transmitarray Antenna with Out-of-Band RCS Reduction

by Binchao Zhang, Fan Yang, Shenheng Xu, Maokun Li and Weidong Hu

Appl. Sci. 2024, 14(23), 11443; https://doi.org/10.3390/app142311443 - 9 Dec 2024

Viewed by 686

Abstract

Stealth reconfigurable transmitarray antennas (RTAs) are essential components in wireless communication and radar detection systems. Therefore, in this study, we propose a 1-bit RTA with out-of-band radar cross-section (RCS) reduction. The antenna consists of an absorptive frequency selective transmission (AFST) layer and RTA [...] Read more.

Stealth reconfigurable transmitarray antennas (RTAs) are essential components in wireless communication and radar detection systems. Therefore, in this study, we propose a 1-bit RTA with out-of-band radar cross-section (RCS) reduction. The antenna consists of an absorptive frequency selective transmission (AFST) layer and RTA layer separated by air. Specifically, the AFST layer achieves out-of-band RCS reduction and in-band transmission utilizing the first three resonant modes of a bent metallic strip with a centrally loaded resistor. Meanwhile, the RTA layer adopts a receiver–transmitter structure with an active receiving dipole and a passive orthogonal transmitting dipole. 1-bit phase shift is achieved by alternating two pin diodes integrated on the active dipole to reverse its current direction. To evaluate the proposed design, a 16 × 16-element prototype was designed, fabricated, and measured. For scattering, the bandwidth of 10 dB RCS reduction was about 52.5% and 43.8%, respectively. For radiation, the measured gain was 20.1 dBi at 7.5 GHz, corresponding to an aperture efficiency of 12.7%. The gain loss of beam scans to ±60° was about 5 dB in both two principal planes. Full article

(This article belongs to the Special Issue Recent Advances in Reflectarray and Transmitarray Antennas)

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22 pages, 15728 KiB

Open AccessArticle

A New Methodology for Optimization of Lashing Lines in the Securing Arrangement of Non-Standardized Cargo on Ships

by José M. Pérez-Canosa and José A. Orosa

Appl. Sci. 2024, 14(23), 11442; https://doi.org/10.3390/app142311442 - 9 Dec 2024

Viewed by 638

Abstract

The stowage plan and the securing arrangement of non-standardized cargo are some of the most important aspects in terms of cargo safety and economic costs. For this reason, the optimization of this operation is crucial and a daily challenge for securing planners trying [...] Read more.

The stowage plan and the securing arrangement of non-standardized cargo are some of the most important aspects in terms of cargo safety and economic costs. For this reason, the optimization of this operation is crucial and a daily challenge for securing planners trying to fulfill both requirements. In the present paper, a new methodological optimization is proposed presenting novel mathematical models and new 3D maps useful for the people in charge of stowage and securing arrangement. For this goal, the materials followed were the Code of Safe Practice for Cargo Stowage and Securing (CSS) of the International Maritime Organization (IMO) because many ships’ Cargo Securing Manuals refer to this international standard. Using an initial case study and making use of response surface techniques of design of experiments (DOE), multiple numerical simulations were performed to obtain novel mathematical models, revealing a high precision. Moreover, new 3D maps were presented and are very interesting tools due to their ease of understanding. The obtained results were compared with other simulations carried out where different variables were employed. The presented models of this methodology can predict the best securing arrangement to fulfill the balance forces in any stowage position (vertical and longitudinal) using the minimum securing devices and keeping the standards of safety. These methodological tools offer valuable advice to the shipping industry with responsibilities involved in the securing design of non-standardized cargo items. Full article

(This article belongs to the Section Marine Science and Engineering)

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