Applied Sciences

17 pages, 1730 KiB

Open AccessArticle

Fenugreek: New Therapeutic Resource or Emerging Allergen?

by Clara Alessandrello, Serena Sanfilippo, Sebastiano Gangemi, Giovanni Pioggia and Paola Lucia Minciullo

Appl. Sci. 2024, 14(20), 9195; https://doi.org/10.3390/app14209195 (registering DOI) - 10 Oct 2024

Abstract

Background: Fenugreek, or Trigonella foenum greacum, is an ancient medicinal plant native to the eastern Mediterranean that later spread to Asia; it is used as a medicinal herb, spice, or food. It is a component of spice mixes, such as curry, and [...] Read more.

Background: Fenugreek, or Trigonella foenum greacum, is an ancient medicinal plant native to the eastern Mediterranean that later spread to Asia; it is used as a medicinal herb, spice, or food. It is a component of spice mixes, such as curry, and it is also used as a supplement in wheat and corn flour for bread making. Fenugreek appears to have many health benefits and potential medicinal properties; for this reason, it is increasingly being used in nutraceutical formulations. This study aimed to describe patients who visited our operative unit for a suspected adverse reaction after ingestion of fenugreek and to highlight possible cross-reactivity between fenugreek and other legumes or other foods. Methods: A total of 13 patients (5 males and 8 females; mean age: 30.6; range: 20–42 years) visited our outpatient clinic with a clinical history suggestive of an allergic reaction to spices or legumes. They underwent a skin prick test for fenugreek, fresh foods, and food extracts. Results: A total of 6 out of 13 patients positive for fenugreek had experienced allergic symptoms after ingesting foods containing spices, and 10 patients presented polysensitization with other legumes, of which 8 also presented sensitization to pistachios. Conclusions: Given the increasing use of novel spices in Mediterranean cuisine and the possible spread of fenugreek-based nutraceuticals, it is relevant to draw attention to possible allergic reactions. Further studies are also needed to be able to establish its cross-reactivity pattern. Full article

(This article belongs to the Special Issue New Diagnostic and Therapeutic Approaches in Food Allergy)

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16 pages, 5818 KiB

Open AccessArticle

Biomineralization Process Inspired In Situ Growth of Calcium Carbonate Nanocrystals in Chitosan Hydrogels

by Xinyue Zeng, Zheng Zhu, Wei Chang, Bin Wu and Wei Huang

Appl. Sci. 2024, 14(20), 9193; https://doi.org/10.3390/app14209193 (registering DOI) - 10 Oct 2024

Abstract

Biological composites such as bone, nacre, and teeth show excellent mechanical efficiency because of the incorporation of biominerals into the organic matrix at the nanoscale, leading to hierarchical composite structures. Adding a large volume of ceramic nanoparticles into an organic molecular network uniformly [...] Read more.

Biological composites such as bone, nacre, and teeth show excellent mechanical efficiency because of the incorporation of biominerals into the organic matrix at the nanoscale, leading to hierarchical composite structures. Adding a large volume of ceramic nanoparticles into an organic molecular network uniformly has been a challenge in engineering applications. However, in natural organisms, biominerals grow inside organic fibers, such as chitin and collagen, forming perfect ceramic/polymer composites spontaneously via biomineralization processes. Inspired from these processes, the in situ growth of calcium carbonate nanoparticles inside the chitosan network to form ceramic composites was proposed in the current work. The crystal growth of CaCO₃ nanoparticles in the chitosan matrix as a function of time was investigated. A weight percentage of ~35 wt% CaCO₃ composite was realized, resembling the high weight percentage of mineral phase in bones. Scanning and transmission electron microscopy indicated the integration of CaCO₃ nanocrystals with chitosan macromolecules. By growing CaCO₃ minerals inside the chitosan matrix, the elastic modulus and tensile strength increases by ~110% and ~90%, respectively. The in situ crystal growth strategy was also demonstrated in organic frameworks prepared via 3D printing, indicating the potential of fabricating ceramic/polymer composites with complicated structures, and further applications in tissue engineering. Full article

(This article belongs to the Section Chemical and Molecular Sciences)

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12 pages, 253 KiB

Open AccessArticle

Effects of In-Season Velocity-Based vs. Traditional Resistance Training in Elite Youth Male Soccer Players

by Veselin Sekulović, Tatjana Jezdimirović-Stojanović, Nikola Andrić, Andoni Elizondo-Donado, Diego Martin, Mladen Mikić and Marko D. M. Stojanović

Appl. Sci. 2024, 14(20), 9192; https://doi.org/10.3390/app14209192 (registering DOI) - 10 Oct 2024

Abstract

The objectives of this study were to compare the effects of two in-season velocity loss training methods (VBT) on performance outcomes and to evaluate the effects of velocity-based training compared to traditional resistance training (TRT) on performance outcomes in young elite soccer players. [...] Read more.

The objectives of this study were to compare the effects of two in-season velocity loss training methods (VBT) on performance outcomes and to evaluate the effects of velocity-based training compared to traditional resistance training (TRT) on performance outcomes in young elite soccer players. VBT utilized the same relative load but varied in the extent of velocity loss during the set: 15% (VL15%) and 30% (VL30%). Thirty-four players were recruited and randomly distributed into three groups: the VL15% group (n = 12; age = 18.50 ± 0.67 years; stature = 183.41 ± 4.25 cm; body mass = 75.08 ± 5.57 kg), the VL30% group (n = 11; age = 17.91 ± 0.60 years; stature = 181.21 ± 6.56 cm, body mass = 73.58 ± 6.22 kg), and the traditional strength training group TRT (n = 11; age = 18.14 ± 0.74 years; stature = 182.17 ± 5.52 cm; body mass = 74.86 ± 6.68 kg). Alongside regular soccer sessions and matches, the groups underwent a four-week (2 sesions per week) resistance training intervention with back squats involved. Changes in leg strength (SQ1RM), 20 m sprint time (SPR 20 m), countermovement jump height (CMJ), reactive strength index (RSI), and change of direction (COD) from before and after were evaluated using a 3 × 2 ANOVA. While no significant interaction was found for SQ1RM and SPR20, all of the groups showed significant pre to post improvements. Significant interactions were observed for CMJ (F = 38.24, p = 0.000), RSI (F = 8.33; p = 0.001), and change of direction agility test (COD) (F = 3.64; p = 0.038), with a post hoc analysis showing differences between the VL15 (6.0%) and TRT (1.7%) groups (p = 0.034); VL15 (12.2%) and VL30 (3.2%) groups (p = 0.004); VL15 and TRT (0.4%) (p = 0.018); VL15 (2.4%) and VL30 (1.5%) (p = 0.049); and between the VL15 and TRT (0.4%) groups (p = 0.015). Four weeks of VL15% training during the season induced similar strength increases to VL30% and TRT, superior improvements in RSI and COD compared to VL30%, and superior improvements in CMJ, RSI, and COD tests compared to TRT. Thus, incorporating the VL15% training method may be recommended to improve power-related performance metrics in elite young soccer players. Full article

(This article belongs to the Special Issue Innovative Approaches in Sports Science and Sports Training)

30 pages, 10558 KiB

Open AccessArticle

A Numerical Evaluation for Estimating the Consequences on Users and Rescue Teams Due to the Fire of an Electric Bus in a Road Tunnel

by Ciro Caliendo, Isidoro Russo and Gianluca Genovese

Appl. Sci. 2024, 14(20), 9191; https://doi.org/10.3390/app14209191 (registering DOI) - 10 Oct 2024

Abstract

E-mobility is progressively penetrating the European market with the ever-increasing registration of new battery electric vehicles (BEVs). Although BEVs can significantly contribute to achieving the goal of sustainable road transport, they pose new challenges related to the complexity of managing battery fire events, [...] Read more.

E-mobility is progressively penetrating the European market with the ever-increasing registration of new battery electric vehicles (BEVs). Although BEVs can significantly contribute to achieving the goal of sustainable road transport, they pose new challenges related to the complexity of managing battery fire events, especially in confined spaces such as road tunnels. In this regard, while fires of BEVs with small-sized batteries (i.e., cars and vans) have been widely studied, the consequences of fires involving battery electric buses (BEBs), which are equipped with larger-capacity traction batteries, have not yet been sufficiently investigated. In this context, 3D computational fluid dynamics (CFD) simulations were performed to quantitatively assess the threat that a BEB might pose to the safety of users and rescue teams when it catches fire in a bi-directional road tunnel. In this respect, a comparison was also carried out with the consequences of the fire of a similar internal combustion engine bus (ICEB). Since the environmental conditions inside a tunnel, apart from its geometry, depend on both the traffic flow and type of ventilation, the safety of the users and rescue teams in the event of a BEB fire was evaluated by considering the tunnel under conditions of congested traffic, as well as natural or longitudinal mechanical ventilation. The results showed that the fire of the BEB, compared to that of its ICEB counterpart, worsened the environmental conditions inside the tunnel, especially in terms of toxic gas concentrations. This caused a reduction in the safety level of the users when considering the scenarios of both the naturally and mechanically ventilated tunnel. Moreover, in the case of natural ventilation, the BEB fire was found to cause a higher reduction in the safety level of the rescue teams. Full article

(This article belongs to the Section Civil Engineering)

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20 pages, 1748 KiB

Open AccessArticle

Harnessing Unsupervised Insights: Enhancing Black-Box Graph Injection Attacks with Graph Contrastive Learning

by Xiao Liu, Junjie Huang, Zihan Chen, Yi Pan, Maoyi Xiong and Wentao Zhao

Appl. Sci. 2024, 14(20), 9190; https://doi.org/10.3390/app14209190 (registering DOI) - 10 Oct 2024

Abstract

Adversarial attacks on Graph Neural Networks (GNNs) have emerged as a significant threat to the security of graph learning. Compared with Graph Modification Attacks (GMAs), Graph Injection Attacks (GIAs) are considered more realistic attacks, in which attackers perturb GNN models by injecting a [...] Read more.

Adversarial attacks on Graph Neural Networks (GNNs) have emerged as a significant threat to the security of graph learning. Compared with Graph Modification Attacks (GMAs), Graph Injection Attacks (GIAs) are considered more realistic attacks, in which attackers perturb GNN models by injecting a small number of fake nodes. However, most existing black-box GIA methods either require comprehensive knowledge of the dataset and the ground-truth labels or a large number of queries to execute the attack, which is often unfeasible in many scenarios. In this paper, we propose an unsupervised method for leveraging the rich knowledge contained in the graph data themselves to enhance the success rate of graph injection attacks on the initial query. Specifically, we introduce GraphContrastive Learning-based Graph Injection Attack (GCIA), which consists of a node encoder, a reward predictor, and a fake node generator. The Graph Contrastive Learning (GCL)-based node encoder transforms nodes for low-dimensional continuous embedding, the reward predictor acts as a simplified surrogate for the target model, and the fake node generator produces fake nodes and edges based on several carefully designed loss functions, utilizing the node encoder and reward predictor. Extensive results demonstrate that the proposed GCIA method achieves a first query success rate of 91.2% on the Reddit dataset and improves the success rate to over 99.7% after 10 queries. Full article

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24 pages, 3843 KiB

Open AccessArticle

Integration of Isotopic and Nuclear Techniques to Assess Water and Soil Resources’ Degradation: A Critical Review

by José L. Peralta Vital, Lucas E. Calvo Gobbetti, Yanna Llerena Padrón, Francisco Heriberto Martínez Luzardo, Oscar Díaz Rizo and Reinaldo Gil Castillo

Appl. Sci. 2024, 14(20), 9189; https://doi.org/10.3390/app14209189 (registering DOI) - 10 Oct 2024

Abstract

Isotopic and nuclear techniques are indispensable in many fields, including health, industry, food, and agriculture. The techniques discussed, collectively known as fallout radionuclide, fingerprint, and isotope hydrology, are currently being employed to characterize and assess phenomena that could potentially degrade soil and water [...] Read more.

Isotopic and nuclear techniques are indispensable in many fields, including health, industry, food, and agriculture. The techniques discussed, collectively known as fallout radionuclide, fingerprint, and isotope hydrology, are currently being employed to characterize and assess phenomena that could potentially degrade soil and water resources. Given the intricate nature of erosion and sedimentation processes in landscapes and water reservoirs, conducting a comprehensive characterization and evaluation of these phenomena is imperative. A traditional literature review was conducted to obtain the most thorough understanding of both the current state of the art and the subject matter regarding the conception of these techniques’ application and the manner of their use (use combined/integrated or use isolated in search of particular results on a single type of degradation, whether soil or water). There is no evidence that an integrative methodology employing these isotopic and nuclear techniques has previously been utilized (as evidenced by 109 current publications), thereby impeding the analysis of the potential sequential occurrence of soil and water degradation. The findings substantiate the hypothesis that isotopic and nuclear techniques can be integrated sequentially through a synergistic convergence. This represents an emerging methodology for addressing the complex needs of the landscape’s soil and water degradation process. Full article

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11 pages, 8637 KiB

Open AccessArticle

Study of Various Process Parameters on Bead Penetration and Porosity in Wire Arc Additive Manufacturing (WAAM) of Copper Alloy Cu1897

by Abid Shah, Neel Kamal Gupta, Rezo Aliyev and Henning Zeidler

Appl. Sci. 2024, 14(20), 9188; https://doi.org/10.3390/app14209188 (registering DOI) - 10 Oct 2024

Abstract

Copper-based alloys are widely known for their high thermal and electrical conductivity. Although the use of these alloys in powder-based additive manufacturing (AM) shows significant promise, applying this method in wire arc additive manufacturing (WAAM) processes poses various considerable challenges, including porosity, delamination, [...] Read more.

Copper-based alloys are widely known for their high thermal and electrical conductivity. Although the use of these alloys in powder-based additive manufacturing (AM) shows significant promise, applying this method in wire arc additive manufacturing (WAAM) processes poses various considerable challenges, including porosity, delamination, surface oxidation, etc. The limited research on WAAM of copper alloys, especially Cu1897, highlights the need for a more in-depth investigation. This study addresses the effects of process parameters in pulse cold metal transfer (CMT)-based WAAM of Cu1897, i.e., pulse correction (PC) and arc length correction (ALC), on bead penetration and porosity. The results showed that as PC was increased from −5 to +5, weld bead penetration increased from 2.38 mm to 3.87 mm. To further enhance penetration and reduce the porosity, the ALC was varied from +30% to −30% with a step size of 15%. The results showed that weld bead penetration increased to 4.47 mm by altering the ALC from +30% to −30%. Additionally, as the ALC varied within this range, porosity decreased significantly from 3.98% to 0.28%. Overall, it is concluded that a lower value of ALC is recommended to improve bead penetration and reduce porosity in WAAM of Cu1897. Full article

(This article belongs to the Special Issue Recent Advances in 3D Printing and Additive Manufacturing Technology)

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13 pages, 4745 KiB

Open AccessArticle

Effects of Zirconium-Based Crosslinkers with Different Zirconium Contents on Pigment Coating in Paper

by Hyeong-Hun Park, Chul-Hwan Kim, Tae-Gyeong Lee, Ju-Hyun Park, Min-Sik Park and Jae-Sang Lee

Appl. Sci. 2024, 14(20), 9187; https://doi.org/10.3390/app14209187 (registering DOI) - 10 Oct 2024

Abstract

This study investigates the impact of zirconium-based KZC series crosslinkers with varying zirconium contents and the polyamine-based crosslinker (PBC) on the properties of coated paper, focusing on key performance metrics such as viscosity, wet rub and pick resistance, dry pick resistance, gloss, brightness, [...] Read more.

This study investigates the impact of zirconium-based KZC series crosslinkers with varying zirconium contents and the polyamine-based crosslinker (PBC) on the properties of coated paper, focusing on key performance metrics such as viscosity, wet rub and pick resistance, dry pick resistance, gloss, brightness, ink set-off, and print mottle. The findings reveal that crosslinkers’ type and concentration significantly influence the coating colors’ viscosity, with PBC demonstrating lower low shear viscosity at lower concentrations. The KZC series showed stable viscosity across a zirconium content range of 7% to 20%, and both crosslinker types enhanced wet rub resistance at higher concentrations. Notably, the KZC series, particularly KZC7, exhibited superior wet pick resistance at increased concentrations, highlighting its effectiveness in enhancing the durability of the coating layer. All crosslinkers maintained excellent dry pick resistance, ensuring robust coating performance. While gloss and brightness were generally unaffected, KZC20, which had the highest zirconium content, slightly reduced these optical properties. Ink set-off tests indicated that the KZC series performed better at lower concentrations, whereas higher concentrations led to increased ink set-off, potentially due to over-crosslinking. Print mottle remained consistent across all crosslinkers, indicating uniform coating quality. Overall, the zirconium-based KZC series significantly enhances wet resistance and maintains high performance across various properties, though it may slightly reduce gloss and brightness and increase ink set-off at higher concentrations. PBC offers a balanced performance profile, emphasizing the need for careful crosslinker type and concentration optimization to achieve the desired coating properties for specific applications. This comprehensive evaluation provides valuable insights for developing and optimizing high-performance coated papers. Full article

(This article belongs to the Special Issue Advances in Pulp and Paper Technologies 2nd Edition)

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19 pages, 5089 KiB

Open AccessArticle

High-Precision Elastoplastic Four-Node Quadrilateral Shell Element

by Mingjiang Tian and Yongtao Wei

Appl. Sci. 2024, 14(20), 9186; https://doi.org/10.3390/app14209186 (registering DOI) - 10 Oct 2024

Abstract

In order to enhance the accuracy of calculations for four-node quadrilateral shell elements, modifications have to be made to the computation of the membrane strain rate and transverse shear strain rate. For membrane strain rate calculations, the interpolation of the quadratic displacement of [...] Read more.

In order to enhance the accuracy of calculations for four-node quadrilateral shell elements, modifications have to be made to the computation of the membrane strain rate and transverse shear strain rate. For membrane strain rate calculations, the interpolation of the quadratic displacement of the nodes along the edges of the quadrilateral shell element is implemented, along with the introduction of a degree of freedom for rotation around the normal. Additionally, the elimination of the zero-energy mode of additional stiffness is achieved through a penalty function. When computing the transverse shear strain rate, the covariant component is expressed in the tensor of the natural coordinate system, followed by the elimination of shear self-locking in the element coordinate system. The strain-updating calculation and stress-updating calculation for the quadrilateral shell element, utilizing the model and J2 flow theory, respectively, are suitable for small deformations, geometric nonlinearity, and elastic–plastic problems. The improved quadrilateral shell element successfully undergoes in-plane and bending fragment inspections, demonstrating good reliability and calculation accuracy for the dynamic analysis of planar shells, curved shells, and twisted shells. Full article

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19 pages, 2485 KiB

Open AccessArticle

Enhancing Real Estate Valuation in Kazakhstan: Integrating Machine Learning and Adaptive Neuro-Fuzzy Inference System for Improved Precision

by Alibek Barlybayev, Nurzhigit Ongalov, Altynbek Sharipbay and Bakhyt Matkarimov

Appl. Sci. 2024, 14(20), 9185; https://doi.org/10.3390/app14209185 (registering DOI) - 10 Oct 2024

Abstract

The concept of fair value, defined by the valuation of assets and liabilities at their current market worth, remains central to the International Financial Reporting Standards (IFRS) and has persisted despite critiques intensified by the 2008 financial crisis. This valuation method continues to [...] Read more.

The concept of fair value, defined by the valuation of assets and liabilities at their current market worth, remains central to the International Financial Reporting Standards (IFRS) and has persisted despite critiques intensified by the 2008 financial crisis. This valuation method continues to be prevalent under both IFRS and the US Generally Accepted Accounting Principles (GAAP). The adoption of IFRS has notably enhanced the role of accounting in information analysis, vital for owners who prioritize both secure accounting practices and reliable data for strategic management decisions. Real estate, a significant business asset, has long been a focal point in accounting discussions, prompting extensive research into the applicability and effectiveness of various accounting standards. These investigations assess the adaptability of standards based on property type, utility, and valuation techniques. However, the challenge of accurately determining the fair value of real estate remains unresolved, signifying its importance not only in the corporate manufacturing realm but also among development companies striving to manage property values efficiently. This study addresses the challenge of accurately determining the fair market value of real estate in Kazakhstan, leveraging a multi-methodological approach that encompasses statistical models, regression analysis, data visualization, neural networks, and particularly, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The integration of these diverse methodologies not only enhances the robustness of real estate valuation but also introduces new insights into effective asset management. The findings suggest that ANFIS provides superior precision in real estate pricing, demonstrating its potential as a valuable tool for strategic management and investment decision-making. Full article

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

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11 pages, 428 KiB

Open AccessArticle

A Modality-Enhanced Multi-Channel Attention Network for Multi-Modal Dialogue Summarization

by Ming Lu, Yang Liu and Xiaoming Zhang

Appl. Sci. 2024, 14(20), 9184; https://doi.org/10.3390/app14209184 (registering DOI) - 10 Oct 2024

Abstract

Integrating multi-modal data in natural language processing has opened new pathways for the enhancement of dialogue summarization. However, existing models often struggle to effectively synthesize textual, auditory, and visual inputs. This paper introduces a Modality-Enhanced Multi-Channel Attention Network (MEMA), a novel approach designed [...] Read more.

Integrating multi-modal data in natural language processing has opened new pathways for the enhancement of dialogue summarization. However, existing models often struggle to effectively synthesize textual, auditory, and visual inputs. This paper introduces a Modality-Enhanced Multi-Channel Attention Network (MEMA), a novel approach designed to optimize the integration and interaction of diverse modalities for dialogue summarization. MEMA leverages symmetrical embedding strategies to balance the integrity and distinctiveness of each modality, ensuring a harmonious interaction within the unified architecture. By maintaining symmetry in the processing flow, MEMA enhances the contextual richness and coherence of the generated summaries. Our model demonstrates superior performance on the Multi-modal Dialogue Summarization (MDS) dataset, particularly in generating contextually enriched abstract summaries. The results underscore MEMA’s potential to transform dialogue summarization by providing a more symmetrical and integrated understanding of multi-modal interactions, bridging the gap in multi-modal data processing, and setting a new standard for future summarization tasks. Full article

(This article belongs to the Special Issue Artificial Intelligence in Transportation Safety and Traffic Management)

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30 pages, 1223 KiB

Open AccessReview

The Impact of Freeze Drying on Bioactivity and Physical Properties of Food Products

by Nurten Coşkun, Sümeyye Sarıtaş, Yassine Jaouhari, Matteo Bordiga and Sercan Karav

Appl. Sci. 2024, 14(20), 9183; https://doi.org/10.3390/app14209183 (registering DOI) - 10 Oct 2024

Abstract

Freeze drying (FD) is a technique used to preserve the bioactive content and flavor of samples. Foods with a short shelf life due to nature have been preserved via FD in recent years. The success of the drying technique is thanks to the [...] Read more.

Freeze drying (FD) is a technique used to preserve the bioactive content and flavor of samples. Foods with a short shelf life due to nature have been preserved via FD in recent years. The success of the drying technique is thanks to the high retention ability of the bioactive compounds and the flavor of the sample. However, the high cost and energy consumption of FD limit its usage in several fields. Freezing, primary drying, and secondary drying, which take place in the same device, are the stages of FD. In addition, several parameters, including pretreatment, size, temperature, sample species, time, and pressure, affect the FD process. These parameters are controlled to increase the effectiveness of FD on the samples. Moreover, FD has been compared with other drying techniques including hot air drying, microwave drying, vacuum drying, and solar drying to determine its protective capability. It has also been applied to the valorization of waste products, which is a common problem worldwide. For valorization, microencapsulation and powder production have been achieved using FD. In recent years, studies on the effects and use of FD on various materials increased, providing new aspects for the future of science and food industry. Full article

(This article belongs to the Special Issue Advanced Food Processing Technologies and Approaches)

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29 pages, 6572 KiB

Open AccessArticle

Robust Parking Space Recognition Approach Based on Tightly Coupled Polarized Lidar and Pre-Integration IMU

by Jialiang Chen, Fei Li, Xiaohui Liu and Yuelin Yuan

Appl. Sci. 2024, 14(20), 9181; https://doi.org/10.3390/app14209181 (registering DOI) - 10 Oct 2024

Abstract

Improving the accuracy of parking space recognition is crucial in the fields for Automated Valet Parking (AVP) of autonomous driving. In AVP, accurate free space recognition significantly impacts the safety and comfort of both the vehicles and drivers. To enhance parking space recognition [...] Read more.

Improving the accuracy of parking space recognition is crucial in the fields for Automated Valet Parking (AVP) of autonomous driving. In AVP, accurate free space recognition significantly impacts the safety and comfort of both the vehicles and drivers. To enhance parking space recognition and annotation in unknown environments, this paper proposes an automatic parking space annotation approach with tight coupling of Lidar and Inertial Measurement Unit (IMU). First, the pose of the Lidar frame was tightly coupled with high-frequency IMU data to compensate for vehicle motion, reducing its impact on the pose transformation of the Lidar point cloud. Next, simultaneous localization and mapping (SLAM) were performed using the compensated Lidar frame. By extracting two-dimensional polarized edge features and planar features from the three-dimensional Lidar point cloud, a polarized Lidar odometry was constructed. The polarized Lidar odometry factor and loop closure factor were jointly optimized in the iSAM2. Finally, the pitch angle of the constructed local map was evaluated to filter out ground points, and the regions of interest (ROI) were projected onto a grid map. The free space between adjacent vehicle point clouds was assessed on the grid map using convex hull detection and straight-line fitting. The experiments were conducted on both local and open datasets. The proposed method achieved an average precision and recall of 98.89% and 98.79% on the local dataset, respectively; it also achieved 97.08% and 99.40% on the nuScenes dataset. And it reduced storage usage by 48.38% while ensuring running time. Comparative experiments on open datasets show that the proposed method can adapt to various scenarios and exhibits strong robustness. Full article

(This article belongs to the Special Issue Advances and Challenges in the Next-Generation Internet of Things (IoT))

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15 pages, 2145 KiB

Open AccessArticle

Autocorrelation Matrix Knowledge Distillation: A Task-Specific Distillation Method for BERT Models

by Kai Zhang, Jinqiu Li, Bingqian Wang and Haoran Meng

Appl. Sci. 2024, 14(20), 9180; https://doi.org/10.3390/app14209180 (registering DOI) - 10 Oct 2024

Abstract

Pre-trained language models perform well in various natural language processing tasks. However, their large number of parameters poses significant challenges for edge devices with limited resources, greatly limiting their application in practical deployment. This paper introduces a simple and efficient method called Autocorrelation [...] Read more.

Pre-trained language models perform well in various natural language processing tasks. However, their large number of parameters poses significant challenges for edge devices with limited resources, greatly limiting their application in practical deployment. This paper introduces a simple and efficient method called Autocorrelation Matrix Knowledge Distillation (AMKD), aimed at improving the performance of smaller BERT models for specific tasks and making them more applicable in practical deployment scenarios. The AMKD method effectively captures the relationships between features using the autocorrelation matrix, enabling the student model to learn not only the performance of individual features from the teacher model but also the correlations among these features. Additionally, it addresses the issue of dimensional mismatch between the hidden states of the student and teacher models. Even in cases where the dimensions are smaller, AMKD retains the essential features from the teacher model, thereby minimizing information loss. Experimental results demonstrate that BERT_TINY-AMKD outperforms traditional distillation methods and baseline models, achieving an average score of 83.6% on GLUE tasks. This represents a 4.1% improvement over BERT_TINY-KD and exceeds the performance of BERT₄-PKD and DistilBERT₄ by 2.6% and 3.9%, respectively. Moreover, despite having only 13.3% of the parameters of BERT_BASE, the BERT_TINY-AMKD model retains over 96.3% of the performance of the teacher model, BERT_BASE. Full article

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17 pages, 1100 KiB

Open AccessArticle

Harnessing the Power of Natural Mineral Waters in Bread Formulations: Effects on Chemical, Physical, and Physicochemical Properties

by Fernanda Ferreira, Rafaela Guimarães, André Lemos, Catarina Milho, Tayse F. F. da Silveira, Jonata M. Ueda, Márcio Carocho, Sandrina A. Heleno, Lillian Barros, Isabel C. F. R. Ferreira, Manuela Pintado and Maria José Alves

Appl. Sci. 2024, 14(20), 9179; https://doi.org/10.3390/app14209179 (registering DOI) - 10 Oct 2024

Abstract

This study aimed to evaluate the feasibility of incorporating natural mineral waters (NMW), including thermal water (TW) and bottled mineral water (BMW), into bread (‘biju’ type) to enhance its mineral content and explore their impacts on physicochemical, technological, biochemical, and chemical composition. NMW, [...] Read more.

This study aimed to evaluate the feasibility of incorporating natural mineral waters (NMW), including thermal water (TW) and bottled mineral water (BMW), into bread (‘biju’ type) to enhance its mineral content and explore their impacts on physicochemical, technological, biochemical, and chemical composition. NMW, rich in sodium, potassium, and magnesium, resulted in bread formulations with higher contents of these minerals and greater total mineral levels, thus potentially enriching food products. Proximate composition analysis showed no significant differences in moisture, proteins, carbohydrates, and energy, except for lipids and soluble sugars. Texture analysis revealed that water type influenced textural properties, with salt content affecting hardness, springiness, and cohesiveness. Viability analysis of Saccharomyces cerevisiae showed consistent results across formulations, suggesting water pH and mineral content did not significantly affect fermentation. In addition, bread formulations without added salt were developed to assess the potential of sodium-rich NMW as a natural source of salt. For these samples, and considering the parameters assessed, except for salt and sodium content, the differences observed were slight compared to salt-added formulations, highlighting NMW’s potential to produce low-salt bread. These findings not only enhance the value of local resources but also offer an innovative and sustainable strategy for utilizing NMW springs across Europe. Full article

(This article belongs to the Special Issue Bio-Based Products and Co-products Applications)

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10 pages, 3238 KiB

Open AccessArticle

The Effect of Silane Treatment of a Resin-Based Composite on Its Microtensile Bond Strength to a Ceramic Restorative Material

by Akiko Haruyama, Takashi Muramatsu and Atsushi Kameyama

Appl. Sci. 2024, 14(20), 9178; https://doi.org/10.3390/app14209178 (registering DOI) - 10 Oct 2024

Abstract

The purpose of this study was to investigate the effect of silane treatment of a resin-coated resin-based composite (RBC) base material on its microtensile bond strength (μTBS) to a computer aided-design/computer-aided manufacturing (CAD/CAM) ceramic restorative material. RBC blocks (4 mm × 7 mm [...] Read more.

The purpose of this study was to investigate the effect of silane treatment of a resin-coated resin-based composite (RBC) base material on its microtensile bond strength (μTBS) to a computer aided-design/computer-aided manufacturing (CAD/CAM) ceramic restorative material. RBC blocks (4 mm × 7 mm × 10 mm) were prepared, and the adherend surfaces were prepared as follows: no resin coating + no silane treatment (Group I), no resin coating + silane treatment (Group II), resin coating only (Group III), and resin coating + silane treatment (Group IV). The resin coating was applied with Clearfil SE Bond and flowable RBC to the adherend surface. Each treated sample was bonded to a ceramic block using Panavia V5. After storage in 37 °C water for 1 week, microspecimens were fabricated, and the μTBS was tested. The failure mode of each specimen was determined using stereomicroscopy and scanning electron microscopy. The µTBS of Group II (20.2 ± 4.0 MPa) was not significantly different from that of Group I (17.6 ± 5.9 MPa) (p > 0.05), and the µTBS of Group I was significantly smaller than that of Group III (21.3 ± 7.2 MPa) (p < 0.05). The µTBS of Group IV (24.9 ± 3.8 MPa) was significantly greater than that of Group III (p < 0.05). Our findings indicate that silane treatment of the resin-coated surface can enhance the µTBS. Silane treatment of RBC base material was not effective when prepared without resin coating. Full article

(This article belongs to the Special Issue New Materials and Techniques in Restorative Dentistry)

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18 pages, 4800 KiB

Open AccessArticle

Train-Induced Unsteady Airflow in a Metro Tunnel with a Ventilation Shaft

by Fei Wang, Xingsen He, Lin Xu, Shengzhong Zhao and Miaocheng Weng

Appl. Sci. 2024, 14(20), 9177; https://doi.org/10.3390/app14209177 (registering DOI) - 10 Oct 2024

Abstract

To ensure only one train operates in each ventilation section within an extra-long tunnel, a ventilation shaft was typically installed to divide the entire tunnel into multiple sections. Given the crucial role of piston wind in the metro tunnel environment and ventilation, a [...] Read more.

To ensure only one train operates in each ventilation section within an extra-long tunnel, a ventilation shaft was typically installed to divide the entire tunnel into multiple sections. Given the crucial role of piston wind in the metro tunnel environment and ventilation, a deeper understanding of train-induced unsteady airflow in a metro tunnel with a ventilation shaft is desirable. This study uses the unsteady flow theory of the Bernoulli equation to mathematically model piston wind in metro tunnels both with and without ventilation shafts. The influence of various shaft parameters on piston wind development is systematically analyzed. The results indicate that the shaft significantly impacts the piston wind. The maximum piston wind speed and ventilation rate in tunnels with ventilation shafts surpass those in tunnels without them. Moreover, shaft location and the cross-sectional area notably affect the maximum piston wind speed, ventilation rate, and airflow in the shaft, whereas shaft height has no significant effect. It is found that a ventilation shaft with a larger cross-sectional area positioned in the middle of the tunnel enhances the performance of piston ventilation. Full article

(This article belongs to the Special Issue Advances in Tunnel and Underground Engineering)

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20 pages, 3886 KiB

Open AccessArticle

Are There Seven Symbols for the Nucleotide-Based Genetic Code?

by Adam Kłóś, Przemysław M. Płonka and Krzysztof Baczyński

Appl. Sci. 2024, 14(20), 9176; https://doi.org/10.3390/app14209176 (registering DOI) - 10 Oct 2024

Abstract

The common assumption is that genetic information is built on a four-symbol alphabet, i.e., DNA nucleotides, the smallest meaningful blocks of genomes are codon triplets, and the record of genetic information does not contain any asserted symbols playing the role of the space. [...] Read more.

The common assumption is that genetic information is built on a four-symbol alphabet, i.e., DNA nucleotides, the smallest meaningful blocks of genomes are codon triplets, and the record of genetic information does not contain any asserted symbols playing the role of the space. It is, however, well known that some nucleotides in some codons are redundant. Our study, therefore, tests the alternative scenario. As the same nucleotide may play various semiotic roles, the genomic alphabet actually contains seven semiotic symbols. Consequently, the meaningful fragments of genomes (words) can be of different sizes, and there are asserted symbols in the record of genomic information. If this is true, then, similarly to natural languages, the frequency-range of these genomic words should follow the power-law distribution. The presented hypothesis was tested, in comparison to competitive (codon-based and n-tuple) forms of tokenization, on a wide range of genomic texts. Full article

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10 pages, 355 KiB

Open AccessArticle

Partial Path Overlapping Mitigation: An Initial Stage for Joint Detection and Decoding in Multipath Channels Using the Sum–Product Algorithm

by Anoush Mirbadin and Abolfazl Zaraki

Appl. Sci. 2024, 14(20), 9175; https://doi.org/10.3390/app14209175 (registering DOI) - 10 Oct 2024

Abstract

This paper addresses the problem of mitigating unknown partial path overlaps in communication systems. This study demonstrates that by utilizing the front-end insight of communication systems along with the sum–product algorithm applied to factor graphs, it is possible not only to track these [...] Read more.

This paper addresses the problem of mitigating unknown partial path overlaps in communication systems. This study demonstrates that by utilizing the front-end insight of communication systems along with the sum–product algorithm applied to factor graphs, it is possible not only to track these overlapping components accurately, but also to detect all multipath channel impairments simultaneously. The proposed methodology involves discretizing channel parameters, such as channel paths and attenuation coefficients, to ensure the most accurate computation of means of Gaussian observations. These parameters are modeled as Bernoulli random variables with priors set to

0.5

. A notable aspect of the algorithm is its integration of the received signal power into the calculation of noise variance, which is critical for its performance. To further reduce the receiver complexity, a novel implementation strategy, based on provided pre-defined look up tables (LOTs) to the reciver, is introduced. The simulation results, covering both distributed and concentrated pilot scenarios, reveal that the algorithm performs almost equally under both conditions and surpasses the established upper bound in performance. Full article

(This article belongs to the Special Issue Advances in Wireless Communication Technologies)

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17 pages, 4158 KiB

Open AccessArticle

Investigations of the Windage Losses of a High-Speed Shrouded Gear via the Lattice Boltzmann Method

by Yu Dai, Caihua Yang and Xiang Zhu

Appl. Sci. 2024, 14(20), 9174; https://doi.org/10.3390/app14209174 (registering DOI) - 10 Oct 2024

Abstract

To suppress the adverse effect of the gear windage phenomenon in the high-speed aeronautic industry, a shroud as an effective alternative strategy is usually to enclose gears to reduce the windage behaviors of high-speed gears. To deeply understand these no-load power losses, this [...] Read more.

To suppress the adverse effect of the gear windage phenomenon in the high-speed aeronautic industry, a shroud as an effective alternative strategy is usually to enclose gears to reduce the windage behaviors of high-speed gears. To deeply understand these no-load power losses, this paper proposes a new simulation methodology based on the Lattice Boltzmann method to study the windage losses of a shrouded spur gear and conducts a series of numerical studies. The models reproduce a shroud spur gear varying radial and axial clearances to evaluate the influence of casing walls on windage losses. The simulation results were then compared with experimental values, showing a satisfactory agreement. Furthermore, a torque containment factor integrating the air compressibility at high Mach numbers is introduced to represent the reduction in torque (windage power losses) for the shrouded gear compared to the free case, and the theoretical formulae for predicting windage power losses are further improved for better applicability as the tight shroud approaches the gear during the preliminary design stage. Full article

(This article belongs to the Special Issue Mathematical Methods and Simulations in Mechanics and Engineering)

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18 pages, 5296 KiB

Open AccessArticle

A Novel Approach to Monitoring the Performance of Carbon-Fiber-Reinforced Polymer Retrofitting in Reinforced Concrete Beam–Column Joints

by George M. Sapidis, Maria C. Naoum, Nikos A. Papadopoulos, Emmanouil Golias, Chris G. Karayannis and Constantin E. Chalioris

Appl. Sci. 2024, 14(20), 9173; https://doi.org/10.3390/app14209173 (registering DOI) - 10 Oct 2024

Abstract

Due to insufficient transverse reinforcement, the retrofitting of beam–column joints (BCJs) in existing reinforced concrete (RC) frame structures is commonly required to alter their brittle behavior. The construction industry has extensively embraced carbon-fiber-reinforced polymers (C-FRPs) as near-surface-mounted (NSM) reinforcement. Monitoring the performance of [...] Read more.

Due to insufficient transverse reinforcement, the retrofitting of beam–column joints (BCJs) in existing reinforced concrete (RC) frame structures is commonly required to alter their brittle behavior. The construction industry has extensively embraced carbon-fiber-reinforced polymers (C-FRPs) as near-surface-mounted (NSM) reinforcement. Monitoring the performance of C-FRP retrofitting is crucial due to the wide range of factors influencing its effectiveness. A novel methodology has been implemented to assess the efficacy of the C-FRP retrofitting method in this study. This approach was validated through experimental investigation of full-scale BCJs, which were retrofitted with C-FRP ropes and subjected to cyclic loading. Furthermore, piezoelectric lead zirconate titanate (PZT) patches were placed on the NSM C-FRP ropes, and the electro-mechanical impedance (EMI) method was employed to monitor the retrofitting technique’s performance. A combination of the commonly used statistical damage index root mean squared deviation (RMSD) and a hierarchical clustering-based approach (HCA) was used to assess the performance of the C-FRP retrofitting technique. The experimental investigation results strongly indicate the proposed approach’s positive impact on the reliable assessment of C-FRP retrofitting performance. Thus, the proposed approach enhances the safety and resilience of retrofitted BCJs in RC structures. Full article

(This article belongs to the Special Issue High Reliability Building Structures: Retrofits, Designs and Applications, 2nd Edition)

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18 pages, 2439 KiB

Open AccessArticle

Phytochemical and Functional Properties of Fruit and Vegetable Processing By-Products

by Roberto Ciccoritti, Roberto Ciorba, Danilo Ceccarelli, Monica Amoriello and Tiziana Amoriello

Appl. Sci. 2024, 14(20), 9172; https://doi.org/10.3390/app14209172 (registering DOI) - 10 Oct 2024

Abstract

Processing sustainability and the concept of zero waste discharge are of great interest for many industries. Every year, fruit and vegetable processing industries generate huge amounts of by-products, which are often intended for animal feed or discarded as waste, posing a problem to [...] Read more.

Processing sustainability and the concept of zero waste discharge are of great interest for many industries. Every year, fruit and vegetable processing industries generate huge amounts of by-products, which are often intended for animal feed or discarded as waste, posing a problem to both environmental and economic points of view. However, to minimize the waste burden, the valorization of these residues received increased interest. In fact, fruit and vegetable by-products are an excellent source of valuable compounds, such as proteins, dietary fibers, lipids, minerals, vitamins, phenolic acids, flavonoids, anthocyanins, carotenoids, and pigments, which can be recovered and reused, creating new business prospects from a circular economy perspective. Understanding the chemical characteristics of these materials is a key concern for their valorization and the identification of their most appropriate intended use. In this study, the phytochemical and functional properties of fruit and vegetable processing by-products (peel and pomace) were investigated. Samples of different plants (i.e., apple, black and orange carrot, cucumber, kumquat, mango, parsnip, peach, black plum) were analyzed using chemical analytical methods and characterized using Fourier Transform Mid-Infrared spectroscopy (FT-MIR). The results highlighted their high nutritional composition in terms of protein, lipids, fiber, and ash, as well as bioactive and antioxidant profiles. These characteristics make these residues suitable as natural ingredients for the development of high-added-value products in food, cosmetic, and pharmaceutical industries. Full article

(This article belongs to the Special Issue Application of Natural Components in Food Production)

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16 pages, 8870 KiB

Open AccessArticle

Yoga and Swimming—A Symbiotic Approach with Positive Impacts on Health and Athletes’ Performance

by Rocsana Bucea-Manea-Țoniș, Andreea Natalia Jureschi (Gheorghe) and Luciela Vasile

Appl. Sci. 2024, 14(20), 9171; https://doi.org/10.3390/app14209171 (registering DOI) - 10 Oct 2024

Abstract

Yoga enhances acceptance, compassion, physicality, mental and emotional awareness, and spiritual benefits through breath techniques, postures, and body locks, while swimming improves flexibility, strength, and body awareness. The fusion of yoga and swimming, particularly the aqua yoga asana method, offers a balanced lifestyle [...] Read more.

Yoga enhances acceptance, compassion, physicality, mental and emotional awareness, and spiritual benefits through breath techniques, postures, and body locks, while swimming improves flexibility, strength, and body awareness. The fusion of yoga and swimming, particularly the aqua yoga asana method, offers a balanced lifestyle for athletes and non-performers, enhancing their performance. Our study examined the feasibility of incorporating yoga and swimming practice into Romanian subjects’ lifestyles, designing a factor analysis in SmartPLS software, based on an online survey. This study assessed participants’ knowledge of yoga’s theory and philosophy, as well as their perceptions of the benefits of swimming practice for social and health issues. Our 250 young swimming athletes train in Bucharest’s sports clubs. According to our study, Romanian participants practice yoga and swimming as often as possible to reduce stress, improve concentration for work-related tasks, and improve joint elasticity, balance, and muscular tone. The high coefficient of path analysis (0.667) proved that those who practice yoga asanas have a high level of awareness and understand the fundamentals of the practice. The second coefficient of path analysis (0.857) shows that those who understand yoga better are convinced of its positive effects on society and their health. Thus, yoga and swimming are substitutes for other approaches in prevention and therapy, making it a beneficial tool for pre-performance swimming. Full article

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22 pages, 11975 KiB

Open AccessArticle

Fall Risk Classification Using Trunk Movement Patterns from Inertial Measurement Units and Mini-BESTest in Community-Dwelling Older Adults: A Deep Learning Approach

by Diego Robles Cruz, Sebastián Puebla Quiñones, Andrea Lira Belmar, Denisse Quintana Figueroa, María Reyes Hidalgo and Carla Taramasco Toro

Appl. Sci. 2024, 14(20), 9170; https://doi.org/10.3390/app14209170 (registering DOI) - 10 Oct 2024

Abstract

Falls among older adults represent a critical global public health problem, as they are one of the main causes of disability in this age group. We have developed an automated approach to identifying fall risk using low-cost, accessible technology. Trunk movement patterns were [...] Read more.

Falls among older adults represent a critical global public health problem, as they are one of the main causes of disability in this age group. We have developed an automated approach to identifying fall risk using low-cost, accessible technology. Trunk movement patterns were collected from 181 older people, with and without a history of falls, during the execution of the Mini-BESTest. Data were captured using smartphone sensors (an accelerometer, a gyroscope, and a magnetometer) and classified based on fall history using deep learning algorithms (LSTM). The classification model achieved an overall accuracy of 88.55% a precision of 90.14%, a recall of 87.93%, and an F1 score of 89.02% by combining all signals from the Mini-BESTest tasks. The performance outperformed the metrics we obtained from individual tasks, demonstrating that aggregating all cues provides a more complete and robust assessment of fall risk in older adults. The results suggest that combining signals from multiple tasks allowed the model to better capture the complexities of postural control and dynamic gait, leading to better prediction of falls. This highlights the potential of integrating multiple assessment modalities for more effective fall risk monitoring. Full article

(This article belongs to the Special Issue Falls: Risk, Prevention and Rehabilitation (2nd Edition))

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25 pages, 1702 KiB

Open AccessArticle

An Anomaly Detection Method for Oilfield Industrial Control Systems Fine-Tuned Using the Llama3 Model

by Jianming Zhao, Ziwen Jin, Peng Zeng, Chuan Sheng and Tianyu Wang

Appl. Sci. 2024, 14(20), 9169; https://doi.org/10.3390/app14209169 (registering DOI) - 10 Oct 2024

Abstract

The device anomaly detection in an industrial control system (ICS) is essential for identifying devices with abnormal operating states or unauthorized access, aiming to protect the ICS from unauthorized access, malware, operational errors, and hardware failures. This paper addresses the issues of numerous [...] Read more.

The device anomaly detection in an industrial control system (ICS) is essential for identifying devices with abnormal operating states or unauthorized access, aiming to protect the ICS from unauthorized access, malware, operational errors, and hardware failures. This paper addresses the issues of numerous manufacturers, complex models, and incomplete information by proposing a fingerprint extraction method based on ICS protocol communication models, applied to an anomaly detection model fine-tuned using the Llama3 model. By considering both hardware and software characteristics of ICS devices, the paper designs a fingerprint vector that can be extracted in both active and passive network communication environments. Experimental data include real ICS network traffic from an oilfield station and extensive ICS device traffic data obtained through network scanning tools. The results demonstrate that the proposed method outperforms existing methods in terms of accuracy and applicability, especially in differentiating devices from various manufacturers and models, significantly enhancing anomaly detection performance. The innovation lies in using large language models for feature extraction and the anomaly detection of device fingerprints, eliminating dependency on specific ICS scenarios and protocols while substantially improving detection accuracy and applicability. Full article

(This article belongs to the Special Issue Process Control and Optimization)

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15 pages, 4728 KiB

Open AccessArticle

Field Trial and Performance Evaluation of Soybean-Based Bio-Fog Seals for Asphalt Rejuvenation

by Ana Luiza Rodrigues, Caio Falcao, Maxwell Staver, Irvin Pinto, Andrew Becker, Michael Forrester, Austin Hohmann, Baker Kuehl, Nacu Hernandez, Ashley Buss, Eric Cochran and R. Christopher Williams

Appl. Sci. 2024, 14(20), 9168; https://doi.org/10.3390/app14209168 (registering DOI) - 10 Oct 2024

Abstract

Cracked and deteriorated asphalt are common problems on our roads, leading to safety concerns and requiring significant resources for rehabilitation and reconstruction. This study investigates bio-fog seals, a promising eco-friendly solution utilizing bio-based rejuvenators. These treatments penetrate aged asphalt, restoring its flexibility and [...] Read more.

Cracked and deteriorated asphalt are common problems on our roads, leading to safety concerns and requiring significant resources for rehabilitation and reconstruction. This study investigates bio-fog seals, a promising eco-friendly solution utilizing bio-based rejuvenators. These treatments penetrate aged asphalt, restoring its flexibility and resistance to cracking. We assessed the effectiveness of two bio-fog seal formulations—one containing sub-epoxidized soybean oil (SESO) and the other combining SESO with a biopolymer (BioMag). Applied to real pavement sections, the research evaluated how these bio-seals impacted key performance factors, such as stiffness, permeability, and drying time, and safety factors, including skid resistance and pavement marking visibility. The results indicate the bio-seals did not compromise skid resistance and the reflectivity of the markings, eliminating the need for repainting stripes. Additionally, they successfully reduced pavement stiffness, making the asphalt more flexible and crack-resistant. Remarkably, with rapid setting times, under 30 min, these treatments minimize traffic disruption and do not require a blotter material. Overall, this research demonstrates the potential of bio-fog seals as a sustainable solution for extending pavement lifespan and lowering long-term maintenance costs. Full article

(This article belongs to the Special Issue Sustainability in Asphalt Pavement and Road Construction)

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17 pages, 5872 KiB

Open AccessArticle

Prediction Models and Feature Importance Analysis for Service State of Tunnel Sections Based on Machine Learning

by Debo Zhao, Yujia Yang, Chengyong Cao and Bin Liu

Appl. Sci. 2024, 14(20), 9167; https://doi.org/10.3390/app14209167 (registering DOI) - 10 Oct 2024

Abstract

The evaluation of tunnel service conditions is a core problem in the maintenance of tunnel structures during their life cycles. To address this problem, machine learning algorithms were applied to the National Tunnel Inventory (NTI) database of the Federal Highway Administration of the [...] Read more.

The evaluation of tunnel service conditions is a core problem in the maintenance of tunnel structures during their life cycles. To address this problem, machine learning algorithms were applied to the National Tunnel Inventory (NTI) database of the Federal Highway Administration of the United States to predict the service states of the structural, civil, and non-structural sections of a tunnel, respectively. The results indicate that ensemble learning algorithms such as Light Gradient Boosting Machine (LGBM) and Random Forest outperform Support Vector Machine, Multi-Layer Perceptron, Decision Tree, and K-Nearest Neighbor in solving imbalanced classification problems presented in the NTI database. The machine learning models established using the LGBM algorithm exhibited prediction accuracies of 90.9%, 96.4%, and 77.3% for the structural, civil, and non-structural sections, respectively. The importance sorting of features influencing the tunnel’s service state was then performed based on the LGBM model, revealing that the features with a significant impact on the service states of the structural, civil, and non-structural sections are service time, tunnel length and width, geographic position (longitude and latitude), minimum vertical clearance, annual average daily traffic (AADT), and annual average daily truck traffic (AADTT). Data-driven LGBM models identified human factors such as AADT and AADTT as key features influencing the service states of tunnels’ structural sections, and these factors should be taken into consideration in further research to elucidate the potential physical mechanisms. Full article

(This article belongs to the Special Issue The Application of Machine Learning in Geotechnical Engineering, 2nd Edition)

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16 pages, 1927 KiB

Open AccessArticle

Acute Fatigue Impairs Heart Rate Variability and Resting Muscle Oxygen Consumption Kinetics

by Aldo A. Vasquez-Bonilla, Rodrigo Yáñez-Sepúlveda, Marcelo Tuesta, Eduardo Báez-San Martin, Matías Monsalves-Álvarez, Jorge Olivares-Arancibia, Daniel Duclos-Bastías, Catalina Recabarren-Dueñas and Fernando Alacid

Appl. Sci. 2024, 14(20), 9166; https://doi.org/10.3390/app14209166 (registering DOI) - 10 Oct 2024

Abstract

This study evaluated the influence of acute fatigue on heart rate variability (HRV) and muscle oxygen saturation (SmO₂) at rest, as well as the reliability of SmO₂ data measured using near-infrared spectroscopy (NIRS) during a vascular occlusion test (VOT). Twelve [...] Read more.

This study evaluated the influence of acute fatigue on heart rate variability (HRV) and muscle oxygen saturation (SmO₂) at rest, as well as the reliability of SmO₂ data measured using near-infrared spectroscopy (NIRS) during a vascular occlusion test (VOT). Twelve physically active subjects participated. Measurements included perceived muscle soreness using the visual analog scale (VAS pain), HRV parameters, variables of resting SmO₂ (desaturation and resaturation), and reoxygenation kinetics (mean response time, MRT) through a VOT-NIRS located in the vastus lateralis (VL). Measurements were taken at three points: 24 h before, before exhaustive exercise, and 30 min after exhaustive exercise. The results indicated that acute fatigue increased resting muscle oxygen consumption in desaturation (+22 SmO₂) and resaturation (+18 SmO₂), improved MRT (−15 s), and elevated sympathetic nervous system (SNS) activity, as observed in the R-R interval (−262 ms) and SNS index (+0.5). HRV significantly influenced desaturation (r² = 0.69), resaturation (r² = 0.60), and MRT (r² = 0.54). Reliability was established with an ICC of 0.49 and 0.63 for desaturation and resaturation, respectively. Real changes in desaturation and resaturation should be considered ≥ 7% SmO₂ at rest and ≥ 11% SmO₂ to avoid daily fatigue interference. In conclusion, acute fatigue increases resting SmO₂ consumption and is associated with higher SNS activity and increased VAS pain. Full article

(This article belongs to the Special Issue Research of Sports Medicine on Health Care)

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14 pages, 1254 KiB

Open AccessArticle

Relationship between Body Composition and Physical Performance by Sex in Professional Basketball Players

by Jordan Hernandez-Martinez, Joaquín Perez-Carcamo, Bayron Coñapi-Union, Sebastian Canales-Canales, Mario Negron-Molina, Sergio Avila-Valencia, Izham Cid-Calfucura, Tomas Herrera-Valenzuela, Diego Cisterna, Braulio Henrique Magnani Branco and Pablo Valdés-Badilla

Appl. Sci. 2024, 14(20), 9165; https://doi.org/10.3390/app14209165 (registering DOI) - 10 Oct 2024

Abstract

This study aimed to identify the relationship between body composition (fat-free mass and body fat percentage) and physical performance (countermovement jump, CMJ; throwing ball; maximal isometric handgrip strength, MIHS dominant and non-dominant hands; 10-m and 20-m sprints with and without ball) in Chilean [...] Read more.

This study aimed to identify the relationship between body composition (fat-free mass and body fat percentage) and physical performance (countermovement jump, CMJ; throwing ball; maximal isometric handgrip strength, MIHS dominant and non-dominant hands; 10-m and 20-m sprints with and without ball) in Chilean professional basketball players. Its secondary aim was to analyze if there were differences in body composition and physical performance according to sex. This was a cross-sectional study that analyzed 23 professional basketball players with a mean age of 24.0 ± 4.92 years, distributed among male professional basketball players (male professional BPs, n = 12) and female professional basketball players (female professional BPs, n = 14). The main results indicate the correlation presented significant relationships between fat-free mass with CMJ (r = 0.760; p < 0.0001; ES = 1.43), MIHS dominant hand (r = 0.783; p < 0.0001; ES = 1.50) and MIHS non-dominant hand (r = 0.805; p < 0.0001; ES = 1.85), throwing ball (r = 0.586; p = 0.001; ES = 0.56), 10 m sprint with ball (r = −0.510; p = 0.007; ES = 0.35), and 20 m sprint with ball (r = −0.143; p = 0.046; ES = 0.16). As did body fat percentage with CMJ (r = −0.647; p = 0.000; ES = 0.56), throwing the ball (r = −0.657; p = 0.000; ES = 0.58), MIHS dominant hand (r = −0.745; p < 0.0001; ES = 1.17), and MIHS non-dominant hand (r = −0.820; p < 0.0001; ES = 1.50). In conclusion, body composition is related to physical performance in professional basketball players. Meanwhile, male professional BPs had better body composition and physical performance than female professional BPs. Full article

(This article belongs to the Special Issue Sports Performance: Data Measurement, Analysis and Improvement)

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20 pages, 1488 KiB

Open AccessArticle

A Graph Convolutional Network-Based Method for Congested Link Identification

by Jiaqing Song, Xuewen Liao and Jiandong Qiao

Appl. Sci. 2024, 14(20), 9164; https://doi.org/10.3390/app14209164 (registering DOI) - 10 Oct 2024

Abstract

Accurate and efficient congested link identification is crucial in wireless sensor networks (WSNs). However, in some networks with a centralized management architecture, it is often not feasible to monitor large numbers of internal links directly or even impossible in some heterogeneous networks. Network [...] Read more.

Accurate and efficient congested link identification is crucial in wireless sensor networks (WSNs). However, in some networks with a centralized management architecture, it is often not feasible to monitor large numbers of internal links directly or even impossible in some heterogeneous networks. Network tomography, the science of inferring the performance characteristics of a network’s interior by correlating sets of end-to-end measurements, was put forward to solve this problem. Nevertheless, a network always contains more links than end-to-end paths, making it problematic to find a determined solution. To solve this problem, most of the current methods try to use some additional prerequisites, such as the link congestion probability. However, most existing studies have not considered the congestion caused by node factors and the case of multiple congested links on one path. In this paper, we initially model the issue of link congestion as a Bayesian network model (BNM). Subsequently, we introduce a congestion link identification method based on graph convolutional networks (GCNs), novelly converting the intricate Bayesian network solving problem into a graph node classification task. The simulation results validate the feasibility of our proposed algorithm in identifying congested links and underscore its advantages in scenarios involving node congestion and multiple congested links. Full article

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Appl. Sci., Volume 14, Issue 20 (October-2 2024) – 40 articles

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