Applied Sciences

13 pages, 1858 KiB

Open AccessArticle

Enhancement of Phenylpropanoid Accumulation and Antioxidant Activities of Agastache rugosa Transgenic Hairy Root Cultures by Overexpressing the Maize Lc Transcription Factor

by Bao Van Nguyen, Jae Kwang Kim, Jinsu Lim, Kihyun Kim, Ramaraj Sathasivam, Dong Ha Cho and Sang Un Park

Appl. Sci. 2024, 14(20), 9617; https://doi.org/10.3390/app14209617 - 21 Oct 2024

Viewed by 1103

Abstract

Agastache rugosa is also known as Korean mint, and it has numerous health benefits due to its rich source of phenolic compounds. The main objective of this study was to produce a ZmLC-overexpressing transgenic hairy root line via Agrobacterium rhizogenes-mediated transformation. [...] Read more.

Agastache rugosa is also known as Korean mint, and it has numerous health benefits due to its rich source of phenolic compounds. The main objective of this study was to produce a ZmLC-overexpressing transgenic hairy root line via Agrobacterium rhizogenes-mediated transformation. The overexpressing transgenic lines were screened using qRT-PCR after exposure to light conditions. The best hairy root line was selected, and the expression levels of phenylpropanoid biosynthetic pathway genes and phenylpropanoid compound accumulation were analysed using qRT-PCR and HPLC, respectively. In addition, antioxidant activities (RPA, ABTS, and DPPH), total phenolic content, and total flavonoid content were analysed. The ZmLC-overexpressing transgenic line upregulated all the phenylpropanoid pathway genes, which led to the higher accumulation of phenylpropanoid compounds in the transgenic line than in the control line. In addition, the total phenolic and flavonoid content was significantly higher in the transgenic line. The antioxidant activity assay showed that the transgenic hairy root line had significantly higher activity than that of the control lines. Thus, ZmLC positively enhances the phenylpropanoid biosynthetic pathway and antioxidant activities in A. rugosa. The results show that ZmLC can be used to enhance phenylpropanoid compounds and antioxidant activities in transgenic A. rugosa hairy root lines via the genetic engineering approach. Full article

(This article belongs to the Special Issue Phytochemical Compounds and Antioxidant Activity)

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14 pages, 1586 KiB

Open AccessArticle

An Analysis Comparing the Taguchi Method for Optimizing the Process Parameters of AA5083/Silicon Carbide and AA5083/Coal Composites That Are Fabricated via Friction Stir Processing

by Oritonda Muribwathoho, Velaphi Msomi and Sipokazi Mabuwa

Appl. Sci. 2024, 14(20), 9616; https://doi.org/10.3390/app14209616 - 21 Oct 2024

Viewed by 876

Abstract

Aluminium metal matrix composites are widely used in automotive, aerospace, marine, and structural engineering due to their high strength-to-weight ratio and superior mechanical properties. Optimizing friction stir process parameters is critical to enhancing the performance of these materials. This study investigates the effects [...] Read more.

Aluminium metal matrix composites are widely used in automotive, aerospace, marine, and structural engineering due to their high strength-to-weight ratio and superior mechanical properties. Optimizing friction stir process parameters is critical to enhancing the performance of these materials. This study investigates the effects of FSP parameters such as rotational speed, tilt angle, and traverse speed, on the mechanical properties of AA5083/Silicon carbide and AA5083/Coal composites. Using a Taguchi L9 design of experiments, signal-to-noise ratio, and analysis of variance, this study identifies the optimal process settings for maximizing ultimate tensile strength, microhardness, and elongation. From the results, the study revealed that for AA5083/Silicon carbide composites, rotational speed was the most significant factor affecting tensile strength, while for AA5083/Coal composites, tilt angle played a more critical role. Rotational speed consistently influenced microhardness and elongation for both materials. The signal-to-noise ratio analysis indicates that optimal FSP parameters vary depending on the reinforcement material used. This study highlights the importance of tailoring FSP settings to specific reinforcements to achieve optimal mechanical properties. These findings contribute to the advancement of friction stir processing techniques for fabricating high-performance aluminium metal matrix composites, particularly for applications in industries requiring strong, lightweight, and corrosion-resistant materials. Full article

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18 pages, 39985 KiB

Open AccessArticle

Research on the Evolutionary Law of Fracture Formation in Loose Seams Under High-Intensity Mining with Shallow Depth

by Linshuang Zhao, Daming Yang, Lihui Sun, Jiabo Xu and Yun Sun

Appl. Sci. 2024, 14(20), 9615; https://doi.org/10.3390/app14209615 - 21 Oct 2024

Viewed by 802

Abstract

The western mining regions of China, known for shallow-buried and high-intensity mining activities, face significant ecological threats due to damage to loose strata and the surface. The evolution of fissures within the loose layer is a critical issue for surface ecological environment protection [...] Read more.

The western mining regions of China, known for shallow-buried and high-intensity mining activities, face significant ecological threats due to damage to loose strata and the surface. The evolution of fissures within the loose layer is a critical issue for surface ecological environment protection in coal mining areas. The study employed field measurements, mechanical experiments, numerical simulations, and theoretical analysis, using the ‘triaxial consolidation without drainage’ experiment to assess the physical and mechanical properties of various strata in the loose layer. Additionally, the PFC^2D numerical simulation software was employed to construct a numerical model that elucidates the damage mechanisms and reveals the evolution of loose layer fissures and the development of ground cracks. The research findings indicate that during shallow-buried high-intensity mining loose layer fissures undergo a dynamic evolution process characterized by “vertical extension-continuous penetration-lateral expansion”. As the working face advances, these fissures eventually propagate to the surface, forming ground cracks. The strong force chains within the overlying rock (or soil) layers develop in the form of an “inverted catenary arch”. As the arch foot and the middle of the arch overlap, fissures propagate along these strong force chains to the surface, resulting in ground cracks. The study elucidates the surface damage patterns in shallow-buried, high-intensity mining, offering theoretical insights for harmonizing coal mining safety with ecological conservation in fragile regions. Full article

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15 pages, 3552 KiB

Open AccessFeature PaperArticle

Multifunctional 3D-Printed Thermoplastic Polyurethane (TPU)/Multiwalled Carbon Nanotube (MWCNT) Nanocomposites for Thermal Management Applications

by Daniele Rigotti, Andrea Dorigato and Alessandro Pegoretti

Appl. Sci. 2024, 14(20), 9614; https://doi.org/10.3390/app14209614 - 21 Oct 2024

Viewed by 1032

Abstract

In this work, multiwalled carbon nanotubes (MWCNTs) were melt-compounded into a novel thermal energy storage system consisting of a microencapsulated paraffin, with a melting temperature of 6 °C (M6D), dispersed within a flexible thermoplastic polyurethane (TPU) matrix. The resulting materials were then processed [...] Read more.

In this work, multiwalled carbon nanotubes (MWCNTs) were melt-compounded into a novel thermal energy storage system consisting of a microencapsulated paraffin, with a melting temperature of 6 °C (M6D), dispersed within a flexible thermoplastic polyurethane (TPU) matrix. The resulting materials were then processed via Fused Filament Fabrication (FFF), and their thermo-mechanical properties were comprehensively evaluated. After an optimization of the processing parameters, good adhesion between the polymeric layers was obtained. Field-Emission Scanning Electron Microscopy (FESEM) images of the 3D-printed samples highlighted a uniform distribution of the microcapsules within the polymer matrix, without an evident MWCNT agglomeration. The thermal energy storage/release capability provided by the paraffin microcapsules, evaluated through Differential Scanning Calorimetry (DSC), was slightly lowered by the FFF process but remained at an acceptable level (i.e., >80% with respect to the neat M6D capsules). The novelty of this work lies in the successful integration of MWCNTs and PCMs into a TPU matrix, followed by 3D printing via FFF technology. This approach combines the high thermal conductivity of MWCNTs with the thermal energy storage capabilities of PCMs, creating a multifunctional nanocomposite material with unique thermal management properties. Full article

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

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10 pages, 596 KiB

Open AccessArticle

In Vitro Antitumor, Antioxidant, and Hemolytic Activities of Chlorella sorokiniana Methanol Extracts and Collective Fractions

by Maribel Domínguez-Gámez, César I. Romo-Sáenz, Ricardo Gomez-Flores, Guadalupe González-Ochoa, Andrés García-Romero, Alonso A. Orozco-Flores, Cristina Rodríguez-Padilla and Patricia Tamez-Guerra

Appl. Sci. 2024, 14(20), 9613; https://doi.org/10.3390/app14209613 - 21 Oct 2024

Viewed by 895

Abstract

Chlorella species are fast-growing microalgae with significant industrial applications. The aim of the present study was to investigate the antitumor, antioxidant, and hemolytic activities of Chlorella sorokiniana UTEX 1230 crude methanol extracts and fractions. Ch. sorokiniana crude methanol extracts and collective fractions (CFs) [...] Read more.

Chlorella species are fast-growing microalgae with significant industrial applications. The aim of the present study was to investigate the antitumor, antioxidant, and hemolytic activities of Chlorella sorokiniana UTEX 1230 crude methanol extracts and fractions. Ch. sorokiniana crude methanol extracts and collective fractions (CFs) were obtained from lyophilized biomass by maceration and column chromatography. Antitumor assays against murine lymphoma L5178Y-R and human breast cancer MCF-7 cells were performed by the colorimetric 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) reduction technique, using human peripheral blood mononuclear cells (PBMC) as the control group. Antioxidant and hemolytic activities were evaluated using the 2,2-diphenyl-1-picrylhydrazyl radical scavenging assay (DPPH) and erythrocyte hemolysis, respectively. We showed that crude methanol extracts (IC₅₀) increased L5178Y-R and MCF-7 cell growth inhibition, without affecting PBMC. In addition, all evaluated CFs showed significantly higher antioxidant activity than the positive control (ascorbic acid). CF3 and CF4 showed the highest cytotoxicity against L5178Y-R, whereas CF3, CF4, and CF5 caused the highest antitumor activity against MCF-7 cells. CF3, CF4, and CF5 induced significantly higher hemolytic activity compared with all other fractions. CF characterization revealed loliolide, cinnamic acid, methyl dihydrojasmonate, salsalvamide A, 1-monolinolenin, cryptophycin 29, costunolide, riboflavin lumicrome, and germicidin B, which have been related to antitumor and antioxidant activities. In conclusion, we demonstrated that Ch. sorokiniana extracts and fractions possess antitumor and antioxidant potential, without affecting human erythrocytes and PBMC. Full article

(This article belongs to the Special Issue Microorganisms and their Use in Biotechnological Production)

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19 pages, 7133 KiB

Open AccessArticle

Fatigue Crack Growth Monitoring and Investigation on G20Mn5QT Cast Steel and Welds via Acoustic Emission

by Qingyang Liu, Zhenli Zhang, Giuseppe Lacidogna, Yantao Xu and Jie Xu

Appl. Sci. 2024, 14(20), 9612; https://doi.org/10.3390/app14209612 - 21 Oct 2024

Viewed by 700

Abstract

The fatigue crack growth properties of G20Mn5QT cast steel and corresponding butt welds, using compact tension specimens, were monitored and investigated via acoustic emission (AE) techniques. Fatigue crack growth is a combination of cyclic plastic deformations before the crack tip, tensile crack fractures, [...] Read more.

The fatigue crack growth properties of G20Mn5QT cast steel and corresponding butt welds, using compact tension specimens, were monitored and investigated via acoustic emission (AE) techniques. Fatigue crack growth is a combination of cyclic plastic deformations before the crack tip, tensile crack fractures, and shear crack fractures. The cyclic plastic deformations release the maximum amount of energy, which accounts for half of the total energy, and the second-largest number of AE signals, which are of the continuous-wave type. The tensile crack fractures release the second-largest amount of energy and the largest number of AE signals, which are of the burst-wave type. The shear crack fractures release the least amount of energy and the lowest number of AE signals, which are similar to the burst type, albeit with a relatively longer rise time and duration. Crack tip advancement can be regarded as a discontinuous process. The critical area before the crack tip brittlely ruptures when the fatigue damage caused by cyclic plastic deformations reaches critical status. The ruptures produce a large number of tensile crack fractures and rare shear crack fractures. Through fractography observation, the shear crack fractures occur probabilistically around defects caused by casting or welding, which lead to stress and strain in the local complex. Full article

(This article belongs to the Collection Nondestructive Testing (NDT))

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18 pages, 4078 KiB

Open AccessArticle

Equivalent Simulation Study of Delta-Rotor Engine

by Yaoyao Shi, Liangyu Li, Ye Tian and Run Zou

Appl. Sci. 2024, 14(20), 9611; https://doi.org/10.3390/app14209611 - 21 Oct 2024

Viewed by 494

Abstract

The mechanical structure, movement mode, and combustion process of a triangular rotor engine differ from those of a conventional engine with a crank connecting rod mechanism as the core. This makes it impossible to directly use existing simulation software to simulate the performance [...] Read more.

The mechanical structure, movement mode, and combustion process of a triangular rotor engine differ from those of a conventional engine with a crank connecting rod mechanism as the core. This makes it impossible to directly use existing simulation software to simulate the performance of the entire engine, rendering it difficult to conduct structural evaluation and performance prediction during the engine development stage. Therefore, using existing performance simulation software to establish a performance-equivalent model for a triangular rotor engine is crucial. To solve the above problems, this study proposes a performance-equivalent simulation modelling method for a triangular rotor engine based on a three-dimensional simulation model and the operating principles of the triangular rotor and four-stroke engines. Compared to various performance indicators obtained from the three-dimensional simulation model, the results show that the equivalent model established in this study has sufficient accuracy for key indicators such as the cylinder pressure, cylinder temperature, and in-cylinder quality under various working conditions. This can satisfy the requirements of the complete machine-performance simulation of a triangular rotor engine. Full article

(This article belongs to the Section Mechanical Engineering)

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46 pages, 10581 KiB

Open AccessArticle

An Efficient and Fast Hybrid GWO-JAYA Algorithm for Design Optimization

by Chiara Furio, Luciano Lamberti and Catalin I. Pruncu

Appl. Sci. 2024, 14(20), 9610; https://doi.org/10.3390/app14209610 - 21 Oct 2024

Viewed by 990

Abstract

Metaheuristic algorithms (MHAs) are widely used in engineering applications in view of their global optimization capability. Researchers continuously develop new MHAs trying to improve the computational efficiency of optimization search. However, most of the newly proposed algorithms rapidly lost their attractiveness right after [...] Read more.

Metaheuristic algorithms (MHAs) are widely used in engineering applications in view of their global optimization capability. Researchers continuously develop new MHAs trying to improve the computational efficiency of optimization search. However, most of the newly proposed algorithms rapidly lost their attractiveness right after their release. In the present study, two classical and powerful MHAs, namely the grey wolf optimizer (GWO) and the JAYA algorithm, which still attract the attention of optimization experts, were combined into a new hybrid algorithm called FHGWJA (Fast Hybrid Grey Wolf JAYA). FHGWJA utilized elitist strategies and repairing schemes to generate high-quality new trial solutions that may always improve the current best record or at least the old population. The proposed FHGWJA algorithm was successfully tested in seven engineering optimization problems formulated in the fields of robotics, hydraulics, and mechanical and civil engineering. Design examples included up to 29 optimization variables and 1200 nonlinear constraints. The optimization results proved that FHGWJA always was superior or very competitive with the other state-of-the-art MHAs including other GWO and JAYA variants. In fact, FHGWJA always converged to the global optimum and very often achieved 0 or nearly 0 standard deviation, with all optimization runs practically converging to the target design. Furthermore, FHGWJA always ranked 1st or 2nd in terms of average computational speed, and its fastest optimization runs were better or highly competitive with those of the best MHA taken for comparison. Full article

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11 pages, 515 KiB

Open AccessCommunication

A Novel Artificial General Intelligence Security Evaluation Scheme Based on an Analytic Hierarchy Process Model with a Generic Algorithm

by Guangyong Chen, Yiqun Zhang and Rui Jiang

Appl. Sci. 2024, 14(20), 9609; https://doi.org/10.3390/app14209609 - 21 Oct 2024

Viewed by 689

Abstract

The rapid development of Artificial General Intelligence (AGI) in recent years has provided many new opportunities and challenges for human social production. However, recent evaluation methods have some problems with regard to consistency, subjectivity and comprehensiveness. In order to solve the above problems, [...] Read more.

The rapid development of Artificial General Intelligence (AGI) in recent years has provided many new opportunities and challenges for human social production. However, recent evaluation methods have some problems with regard to consistency, subjectivity and comprehensiveness. In order to solve the above problems, in this paper, we propose an Artificial General Intelligence Security Evaluation scheme (AGISE), which is based on analytic hierarchy process (AHP) technology with a genetic algorithm, to comprehensively evaluate the AGI security based on multiple security risk styles and complex indicators. Firstly, our AGISE combines AHP technology with a genetic algorithm to realize reliable, consistent and objective evaluation for AGI security. Secondly, in our AGISE, we propose implementing more effective AGI security evaluation classification and indicator settings. Finally, we demonstrate the effectiveness of our AGISE through experiments. Full article

(This article belongs to the Special Issue Privacy and Security in Machine Learning and Artificial Intelligence)

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19 pages, 16637 KiB

Open AccessArticle

Study on the Bearing Structure of Key Strata and the Linkage Evolution Mechanism of Surface Subsidence in Shallow Coal Seam Mining

by Yifeng He, Jie Zhang, Tao Yang, Jianjun Wu, Shoushi Gao and Jianping Sun

Appl. Sci. 2024, 14(20), 9608; https://doi.org/10.3390/app14209608 - 21 Oct 2024

Viewed by 641

Abstract

Shallow coal seam mining results in the formation of various bearing structures in key strata, leading to varying degrees of surface subsidence and severe disruption to the surface ecological environment. To investigate the coupled evolution characteristics of key strata fracture-bearing structures and surface [...] Read more.

Shallow coal seam mining results in the formation of various bearing structures in key strata, leading to varying degrees of surface subsidence and severe disruption to the surface ecological environment. To investigate the coupled evolution characteristics of key strata fracture-bearing structures and surface subsidence in shallow coal seam mining, with a focus on the 1–2 coal seam mining at Longhua Coal Mine in northern Shaanxi as the research background, this study employed physical similarity simulation to establish the correlation between key strata fracture-bearing structures and surface subsidence. The study also utilized theoretical calculations to develop models for the trapezoidal hinged arch structure and the coupling between key strata-bearing structures and surface subsidence. Mechanical properties of bearing structures and the coupled evolution characteristics of surface subsidence were examined, and the scientific validity of the models was verified through field monitoring. The research reveals that the inclined section of the working face in shallow coal seam mining forms a trapezoidal hinged arch structure, where stress transmission actually resembles an arch shape. Based on the fracture characteristics of rock strata, this structure can be categorized into three types: a full-trapezoidal hinged arch structure, a semi-trapezoidal hinged arch structure, and a trapezoidal-like hinged arch structure. A mechanical calculation model for the trapezoidal hinged arch structure was constructed, and the mechanical calculation formula for this structure was derived based on mechanical equilibrium conditions. Using a masonry beam mechanical model, the formula for calculating the subsidence of key blocks in the key strata fracture was obtained. Based on the “masonry beam” mechanical model, a formula was derived to calculate the subsidence of key blocks in fractured key strata. The relationship between key strata-bearing structures and surface subsidence curves was analyzed, leading to the development of a calculation model for both. This model reveals the coupled evolution between rock movement and surface subsidence. Field measurements indicate a maximum surface subsidence of 1.93 m, with a subsidence coefficient of 0.65, showing that the surface helps suppress and reduce the overall subsidence. Full article

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13 pages, 14375 KiB

Open AccessArticle

Spiking Neural Networks for Object Detection Based on Integrating Neuronal Variants and Self-Attention Mechanisms

by Weixuan Li, Jinxiu Zhao, Li Su, Na Jiang and Quan Hu

Appl. Sci. 2024, 14(20), 9607; https://doi.org/10.3390/app14209607 - 21 Oct 2024

Viewed by 857

Abstract

Thanks to their event-driven asynchronous computing capabilities and low power consumption advantages, spiking neural networks (SNNs) show significant potential for computer vision tasks, especially in object detection. However, effective training methods and optimization mechanisms for SNNs remain underexplored. This study proposes two high [...] Read more.

Thanks to their event-driven asynchronous computing capabilities and low power consumption advantages, spiking neural networks (SNNs) show significant potential for computer vision tasks, especially in object detection. However, effective training methods and optimization mechanisms for SNNs remain underexplored. This study proposes two high accuracy SNNs for object detection, AMS_YOLO and AMSpiking_VGG, integrating neuronal variants and attention mechanisms. To enhance these proposed networks, we explore the impact of incorporating different neuronal variants.The results show that the optimization in the SNN’s structure with neuronal variants outperforms that in the attention mechanism for object detection. Compared to the state-of-the-art in the current SNNs, AMS_YOLO improved by 6.7% in accuracy on the static dataset COCO2017, and AMS_Spiking has improved by 11.4% on the dynamic dataset GEN1. Full article

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21 pages, 713 KiB

Open AccessArticle

Construction Quality Evaluation of Concrete Structures in Hydraulic Tunnels Based on CWM-UM Modeling

by Liang Zhao, Changhai He, Zhuangzhuang Luo and Qingfu Li

Appl. Sci. 2024, 14(20), 9606; https://doi.org/10.3390/app14209606 - 21 Oct 2024

Viewed by 763

Abstract

The construction time of concrete structures in hydraulic tunnels is long, the construction environment is complex, and there are many influencing factors. The requirements for construction quality are high not only to meet the strength requirements but also to meet the design requirements [...] Read more.

The construction time of concrete structures in hydraulic tunnels is long, the construction environment is complex, and there are many influencing factors. The requirements for construction quality are high not only to meet the strength requirements but also to meet the design requirements of erosion resistance, crack resistance, and seepage resistance according to its specific operating environment. Therefore, evaluating the construction quality of concrete structures in hydraulic tunnels is of great significance. Considering the randomness and fuzziness of factors affecting the construction quality of concrete structures in hydraulic tunnels, this paper proposes a comprehensive evaluation model based on combined weighting (CWM) and uncertainty measurement theory (UM). The improved analytic hierarchy process (IAHP) and the CRITIC method are used to determine the subjective and objective weights of evaluation indicators. Combined weighting is based on the principle of minimum entropy, and the UM method is used to evaluate the construction quality level. Finally, taking a hydraulic tunnel as an example, its construction quality grade is calculated to be III, according to the evaluation model proposed in this paper, which matches the engineering reality, and a comparative study is made with the mixture element topology theory at the same time. It is verified that the evaluation model can scientifically and reasonably evaluate the construction quality level of concrete structures in hydraulic tunnels. Full article

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

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18 pages, 4562 KiB

Open AccessArticle

Immobilization of Levocetirizine on Mesoporous Silica for Antiallergenic Gel Formulation

by Klára Szentmihályi, Szilvia Klébert, Krisztina Móricz, Antal Balázs Szenes-Nagy, Zoltán May, Eszter Bódis, Miklós Mohai, László Trif, Mirella Mirankó, Tivadar Feczkó and Zoltán Károly

Appl. Sci. 2024, 14(20), 9605; https://doi.org/10.3390/app14209605 - 21 Oct 2024

Viewed by 594

Abstract

Levocetirizine dihydrochloride is an effective antiallergenic drug applied mostly orally; however, developing a topical formulation for localized treatment could be beneficial. To achieve this, a modified formulation technique is necessary to enhance bioavailability efficiency and minimize possible side effects. Therefore, levocetirizine particles were [...] Read more.

Levocetirizine dihydrochloride is an effective antiallergenic drug applied mostly orally; however, developing a topical formulation for localized treatment could be beneficial. To achieve this, a modified formulation technique is necessary to enhance bioavailability efficiency and minimize possible side effects. Therefore, levocetirizine particles were prepared by immobilization on mesoporous silica material. Both the dihydrochloride form and its free base of levocetirizine were fixed on a silica-type Syloid support. Immobilization of the active ingredient levocetirizine in a free base form on a Syloid support by mixing in a dichloromethane solution provides better surface coverage (65.5%) than immobilization in the dihydrochloride form in water or methanol (24.5% for both). The successful binding of levocetirizine was confirmed by X-ray photoelectron spectroscopy and infrared measurements. The active ingredient in the form of hydrochloride is more likely to be in the pores, while the free base is bound to the surface in larger quantities. The time-dependent levocetirizine release showed that the liberation of the active ingredient from the Syloid is slower than the dissolution of the starting active ingredient itself, so it may be suitable for exerting a more reliable and prolonged local effect. A gel containing a Syloid-fixed levocetirizine free base was tested in vivo in a croton oil-induced ear edema mouse model. When compared to a reference gel, the half-dose formulation containing levocetirizine free base demonstrated a similar efficacy to Fenistil gel, indicating that the new formulation may offer superior effectiveness at lower doses. Full article

(This article belongs to the Special Issue Pharmaceutical Development and Drug Delivery)

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15 pages, 304 KiB

Open AccessArticle

Physiological Response and Sports Injury Risk Relevant Biomechanics in Endurance Obstacle Course Races

by Jorge Rey-Mota, David Martín-Caro Álvarez, Ana Onate-Figuérez, Rodrigo Yañez-Sepúlveda and Vicente Javier Clemente-Suárez

Appl. Sci. 2024, 14(20), 9604; https://doi.org/10.3390/app14209604 - 21 Oct 2024

Viewed by 813

Abstract

Obstacle course races (OCR) have experienced significant growth in recent years, with millions of participants worldwide. However, there is limited research on the specific physiological demands and injury prevention strategies required for these events. This study aimed to analyze the physiological responses and [...] Read more.

Obstacle course races (OCR) have experienced significant growth in recent years, with millions of participants worldwide. However, there is limited research on the specific physiological demands and injury prevention strategies required for these events. This study aimed to analyze the physiological responses and injury risks in participants of a 5 km (Sprint) and 13 km (Super) OCR. Sixty-eight participants were assessed for cortical arousal, leg strength, isometric handgrip strength, blood lactate, heart rate, blood oxygen saturation, body temperature, urine composition, spirometry values, hamstring flexibility, lower limb stability, foot biomechanics, and scapular kinematics, one hour before and immediately after the races. The results showed a significant decrease in leg strength (Sprint: r = −0.56, p < 0.01; Super: r = −0.54, p = 0.01) and urine pH (Sprint: r = −0.70, p = 0.03; Super: r = −0.67, p = 0.01) in both distances, with increases in urine colour, protein, and glucose (Sprint: p < 0.04). In the 13 km race, lower limb stability decreased significantly post-race (r = −0.53, p = 0.01). Positive correlations were found between performance and pre-race handgrip strength (Sprint: r = 0.71, p = 0.001; Super: r = 0.72, p = 0.01) and spirometry values (FVC, FEF 25–75%, FEV1) (Sprint: r = 0.52, p = 0.031; Super: r = 0.48, p = 0.035). Thermoregulation capacity, reflected in a higher pre-race body temperature and lower post-race body temperature, also correlated with improved performance (r = 0.49, p = 0.046). Injury risk increased post-race, with a significant decline in lower limb stability (p < 0.05). These findings highlight the importance of targeted training programs, focusing on grip strength, leg strength, respiratory muscle training, and hydration strategies to optimize performance and reduce injury risk in OCR athletes. Full article

(This article belongs to the Special Issue Sports Biomechanics and Injury Prevention)

16 pages, 5192 KiB

Open AccessArticle

A Deep Learning Model for Predicting the Laminar Burning Velocity of NH₃/H₂/Air

by Wanying Yue, Bin Zhang, Siqi Zhang, Boqiao Wang, Yuanchen Xia and Zhuohui Liang

Appl. Sci. 2024, 14(20), 9603; https://doi.org/10.3390/app14209603 - 21 Oct 2024

Viewed by 675

Abstract

Both NH₃ and H₂ are considered to be carbon-free fuels, and their mixed combustion has excellent performance. Considering the laminar burning velocity as a key characteristic of fuels, accurately predicting the laminar burning velocity of NH₃/H₂/Air is [...] Read more.

Both NH₃ and H₂ are considered to be carbon-free fuels, and their mixed combustion has excellent performance. Considering the laminar burning velocity as a key characteristic of fuels, accurately predicting the laminar burning velocity of NH₃/H₂/Air is crucial for its combustion applications. The study made improvements to the XGBoost model and developed NH₃/H₂/Air Laminar Burning Velocity Net (NHLBVNet), which adopts a composite hierarchical structure to connect the functions of feature extraction, feature combination, and model prediction. The dataset consists of 487 sets of experimental data after the exclusion of outliers. The correlation coefficient (

R^{2}

> 0.99) of NHLBVNet is higher than that of the XGBoost model (

R^{2}

> 0.93). Robustness experiment results indicate that this model can obtain more accurate prediction results than other models even under small sample datasets. Full article

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

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18 pages, 2990 KiB

Open AccessArticle

Identification of Risk Factors for Bus Operation Based on Bayesian Network

by Hongyi Li, Shijun Yu, Shejun Deng, Tao Ji, Jun Zhang, Jian Mi, Yue Xu and Lu Liu

Appl. Sci. 2024, 14(20), 9602; https://doi.org/10.3390/app14209602 - 21 Oct 2024

Viewed by 723

Abstract

Public transit has been continuously developing because of advocacy for low-carbon living, and concerns about its safety have gained prominence. The various factors that constitute the bus operating environment are extremely complex. Although existing research on operational security is crucial, previous studies often [...] Read more.

Public transit has been continuously developing because of advocacy for low-carbon living, and concerns about its safety have gained prominence. The various factors that constitute the bus operating environment are extremely complex. Although existing research on operational security is crucial, previous studies often fail to fully represent this complexity. In this study, a novel method was proposed to identify the risk factors for bus operations based on a Bayesian network. Our research was based on monitoring data from the public transit system. First, the Tabu Search algorithm was applied to identify the optimal structure of the Bayesian network with the Bayesian Information Criterion. Second, the network parameters were calculated using bus monitoring data based on Bayesian Parameter Estimation. Finally, reasoning was conducted through prediction and diagnosis in the network. Additionally, the most probable explanation of bus operation spatial risk was identified. The results indicated that factors such as speed, traffic volume, isolation measures, intersections, bus stops, and lanes had a significant effect on the spatial risk of bus operation. In conclusion, the study findings can help avert dangers and support decision-making for the operation and management of public transit in metropolitan areas to enhance daily public transit safety. Full article

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14 pages, 1722 KiB

Open AccessArticle

Research on an Equivalent Algorithm for Predicting Gas Content in Deep Coal Seams

by Hongbao Chai, Jianguo Wu, Lei Zhang, Yanlin Zhao and Kangxu Cai

Appl. Sci. 2024, 14(20), 9601; https://doi.org/10.3390/app14209601 - 21 Oct 2024

Viewed by 589

Abstract

This document introduces a novel equivalent algorithm for forecasting gas content within deep coal seams, which is subject to constraints stemming from the advancements and precision achieved in well and roadway engineering endeavors. This algorithm meticulously acknowledges that coal seam gas content comprises [...] Read more.

This document introduces a novel equivalent algorithm for forecasting gas content within deep coal seams, which is subject to constraints stemming from the advancements and precision achieved in well and roadway engineering endeavors. This algorithm meticulously acknowledges that coal seam gas content comprises three fundamental components: the inherent gas emission rate of the equivalent stratum, the residual gas content retained within the coal seam itself, and the influence imparted by the gas content within the coal seam. Furthermore, the approach thoroughly considers variations in the level of porosity development within the coal seam and its surrounding rock formations, as well as the occurrence of gas within these structures. The equivalent layer is classified into two distinct groups: the sandstone zone and the clay zone. The sandstone zone utilizes pertinent parameters pertaining to fine sandstone, whereas the clay zone distinguishes between clay rock and thick mudstone. The influencing factor considerations solely encompass natural elements, such as the coal seam’s occurrence and geological structure. The residual gas content employs either existing measured parameters or acknowledged experimental parameters specific to the coal seam. Based on this predictive approach, an intelligent auxiliary software (V1.0) for mine gas forecasting was devised. The software calculates the gas content of deep coal seams within the mine at intervals of 100 m × 100 m, subsequently fitting the contour lines of gas content across the entire area. The gas content predictions derived from this equivalent algorithm demonstrate robust adaptability to variations in gas content caused by construction activities, and the prediction results exhibit an acceptable level of error on-site. Notably, the prediction process is not constrained by the progress of tunnel engineering, ensuring that the prediction outcomes can accurately represent the distribution characteristics of deep coal seam gas content. After a year of application, the prediction results have consistently met on-site requirements, providing a scientific foundation for the implementation of effective gas prevention and control measures in the mining area. Furthermore, this approach can effectively guide the formulation of medium- and long-term gas prevention and control plans for mines. Full article

(This article belongs to the Special Issue Recent Research on Tunneling and Underground Engineering)

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17 pages, 1651 KiB

Open AccessArticle

Node Importance Evaluation of Urban Rail Transit Based on Signaling System Failure: A Case Study of the Nanjing Metro

by Junhong Hu, Mingshu Yang, Yunzhu Zhen and Wenling Fu

Appl. Sci. 2024, 14(20), 9600; https://doi.org/10.3390/app14209600 - 21 Oct 2024

Viewed by 617

Abstract

Assessing the importance of nodes in urban rail transit systems helps enhance their ability to respond to emergencies and improve reliability in view of the fact that most of the existing methods for evaluating the importance of rail transit nodes ignore the disturbance [...] Read more.

Assessing the importance of nodes in urban rail transit systems helps enhance their ability to respond to emergencies and improve reliability in view of the fact that most of the existing methods for evaluating the importance of rail transit nodes ignore the disturbance effect of signaling system failures and are unable to objectively identify critical stations in specific disturbance scenarios. Therefore, this paper proposed a method for evaluating the importance of urban rail transit nodes in signaling system failure scenarios. The method was based on the research background of the signaling system failure that occurs most frequently and analyzed the network failure mechanism after the occurrence of a disturbance. The node importance evaluation indices were selected from the network topology and network operation performance in two aspects. The variation coefficient–VIKOR method was employed to comprehensively assess the significance of urban rail transit stations during signaling system failures. The Nanjing Metro network was also used as an example to evaluate the importance of network stations. The results showed that under the attack method of signaling system failure, most ECC and interlocking stations experienced significantly higher network performance losses compared to the original attack method, and a few interchange stations showed smaller performance losses. The critical stations identified based on the proposed method are mainly distributed in the passenger flow backbone of the Nanjing Metro and were constructed in the early stage; of these, 85% are ECC stations or interlocking stations, which are easily neglected in daily management, in contrast to interchange stations with heavy passenger flow. The results of this study can provide an important reference for the stable operation and sustainable construction of urban rail transit. Full article

(This article belongs to the Topic Smart Cities: Infrastructure, Innovation, Technology, Governance and Citizenship)

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32 pages, 2679 KiB

Open AccessArticle

UPI-LT: Enhancing Information Propagation Predictions in Social Networks Through User Influence and Temporal Dynamics

by Zexia Huang, Xu Gu, Jinsong Hu and Xiaoliang Chen

Appl. Sci. 2024, 14(20), 9599; https://doi.org/10.3390/app14209599 - 21 Oct 2024

Viewed by 618

Abstract

The TEST pervasive use of social media has highlighted the importance of developing sophisticated models for early information warning systems within online communities. Despite the advancements that have been made, existing models often fail to adequately consider the pivotal role of network topology [...] Read more.

The TEST pervasive use of social media has highlighted the importance of developing sophisticated models for early information warning systems within online communities. Despite the advancements that have been made, existing models often fail to adequately consider the pivotal role of network topology and temporal dynamics in information dissemination. This results in suboptimal predictions of content propagation patterns. This study introduces the User Propagation Influence-based Linear Threshold (UPI-LT) model, which represents a novel approach to the simulation of information spread. The UPI-LT model introduces an innovative approach to consider the number of active neighboring nodes, incorporating a time decay factor to account for the evolving influence of information over time. The model’s technical innovations include the incorporation of a homophily ratio, which assesses the similarity between users, and a dynamic adjustment of activation thresholds, which reflect a deeper understanding of social influence mechanisms. Empirical results on real-world datasets validate the UPI-LT model’s enhanced predictive capabilities for information spread. Full article

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15 pages, 2946 KiB

Open AccessArticle

Research on the Optimization Method of Bus Travel Safety Considering Drivers’ Risk Characteristics

by Yue Dou, Shejun Deng, Hongru Yu, Tingting Li, Shijun Yu and Jun Zhang

Appl. Sci. 2024, 14(20), 9598; https://doi.org/10.3390/app14209598 - 21 Oct 2024

Viewed by 696

Abstract

Bus drivers have an important role in ensuring road safety, as their driving circumstances fluctuate due to the combined influence of physiological, psychological, and environmental dynamics, which can cause complex and varied driving dangers. Quantifying and assessing drivers’ risk characteristics under various scenarios, [...] Read more.

Bus drivers have an important role in ensuring road safety, as their driving circumstances fluctuate due to the combined influence of physiological, psychological, and environmental dynamics, which can cause complex and varied driving dangers. Quantifying and assessing drivers’ risk characteristics under various scenarios, as well as finding the best fit with their work schedules, is critical for enhancing bus safety. This research first uses the entropy weight method, which is based on historical warning data, to examine the risk characteristics of bus drivers in various complicated contexts. It then creates an objective function targeted at minimizing the operational risk for a specific bus route. This function uses the quasi-Vogel approach and an improved simulated annealing algorithm to optimize and restructure the scheduling table, taking individual driver risk characteristics into account. Finally, the analysis is confirmed and examined with actual operational data from the Zhenjiang Bus Line 3. The data show that enhanced bus operations resulted in a 7.22% gain in overall safety and a 33.76% improvement in balancing levels. These insights provide valuable theoretical guidance as well as practical references for the safe operation and administration of public buses. Full article

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18 pages, 2907 KiB

Open AccessArticle

The Environmental Stake of Bitcoin Mining: Present and Future Challenges

by Francesco Arfelli, Irene Coralli, Daniele Cespi, Luca Ciacci, Daniele Fabbri, Fabrizio Passarini and Lorenzo Spada

Appl. Sci. 2024, 14(20), 9597; https://doi.org/10.3390/app14209597 - 21 Oct 2024

Viewed by 1383

Abstract

The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and [...] Read more.

The environmental impact of Bitcoin mining has raised severe concerns considering the expected growth of 30% by 2030. This study aimed to develop a Life Cycle Assessment model to determine the carbon dioxide equivalent emissions associated with Bitcoin mining, considering material requirements and energy demand. By applying the impact assessment method IPCC 2021 GWP (100 years), the GHG emissions associated with electricity consumption were estimated at 51.7 Mt CO₂ eq/year in 2022 and calculated by modelling real national mixes referring to the geographical area where mining takes place, allowing for the determination of the environmental impacts in a site-specific way. The estimated impacts were then adjusted to future energy projections (2030 and 2050), by modelling electricity mixes coherently with the spatial distribution of mining activities, the related national targeted goals, the increasing demand for electricity for hashrate and the capability of the systems to recover the heat generated in the mining phase. Further projections for 2030, based on two extrapolated energy consumption models, were also determined. The outcomes reveal that, in relation to the considered scenarios and their associated assumptions, breakeven points where the increase in energy consumption associated with mining nullifies the increase in the renewable energy share within the energy mix exist. The amount of amine-based sorbents hypothetically needed to capture the total CO₂ equivalent emitted directly and indirectly for Bitcoin mining reaches up to almost 12 Bt. Further developments of the present work would rely on more reliable data related to future energy projections and the geographical distribution of miners, as well as an extension of the environmental categories analyzed. The Life Cycle Assessment methodology represents a valid tool to support policies and decision makers. Full article

(This article belongs to the Special Issue CCUS: Paving the Way to Net Zero Emissions Technologies)

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18 pages, 9623 KiB

Open AccessArticle

Study on Multi-Crack Damage Evolution and Fatigue Life of Corroded Steel Wires Inside In-Service Bridge Suspenders

by Luming Deng and Yulin Deng

Appl. Sci. 2024, 14(20), 9596; https://doi.org/10.3390/app14209596 - 21 Oct 2024

Viewed by 693

Abstract

The parallel steel wires used in arch bridge suspenders experience random corrosion damage on their surfaces during service. Corrosion damage, including micro-cracks, pitting, and a combination of both, leads to significant stress concentration under axial loading, which affects the performance of the steel [...] Read more.

The parallel steel wires used in arch bridge suspenders experience random corrosion damage on their surfaces during service. Corrosion damage, including micro-cracks, pitting, and a combination of both, leads to significant stress concentration under axial loading, which affects the performance of the steel wires. The change in the stress field caused by surface damage alters the stress intensity factor at the crack tip, and the presence of adjacent crack tips significantly amplifies the stress intensity factor, thereby accelerating crack propagation. The development of small surface damages in the steel wires is difficult to control and observe through experiments. By utilizing finite element methods for simulation, it is possible to intuitively analyze the crack propagation process, the trend of stress changes at the crack tip, and the interaction between damages. Numerical simulation results based on Paris’ law indicate that corrosion pits have a certain impact on the stress intensity factor at the crack tip. The propagation process of coplanar double cracks is highly sensitive to the initial crack size and the distance between adjacent crack tips. When the crack spacing is less than the crack depth, the stress intensity factor at the adjacent crack tips exhibits significant amplification. Based on this phenomenon, the coplanar double-crack system can be simplified to a complete single crack for analysis. By comparing the fatigue life of the double-crack system with that of the equivalent single crack, the effectiveness of the simplification rule has been validated. Full article

(This article belongs to the Special Issue Construction Materials: Characterization, Structure and Durability)

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12 pages, 1117 KiB

Open AccessArticle

CycleDiffusion: Voice Conversion Using Cycle-Consistent Diffusion Models

by Dongsuk Yook, Geonhee Han, Hyung-Pil Chang and In-Chul Yoo

Appl. Sci. 2024, 14(20), 9595; https://doi.org/10.3390/app14209595 - 21 Oct 2024

Viewed by 881

Abstract

Voice conversion (VC) refers to the technique of modifying one speaker’s voice to mimic another’s while retaining the original linguistic content. This technology finds its applications in fields such as speech synthesis, accent modification, medicine, security, privacy, and entertainment. Among the various deep [...] Read more.

Voice conversion (VC) refers to the technique of modifying one speaker’s voice to mimic another’s while retaining the original linguistic content. This technology finds its applications in fields such as speech synthesis, accent modification, medicine, security, privacy, and entertainment. Among the various deep generative models used for voice conversion, including variational autoencoders (VAEs) and generative adversarial networks (GANs), diffusion models (DMs) have recently gained attention as promising methods due to their training stability and strong performance in data generation. Nevertheless, traditional DMs focus mainly on learning reconstruction paths like VAEs, rather than conversion paths as GANs do, thereby restricting the quality of the converted speech. To overcome this limitation and enhance voice conversion performance, we propose a cycle-consistent diffusion (CycleDiffusion) model, which comprises two DMs: one for converting the source speaker’s voice to the target speaker’s voice and the other for converting it back to the source speaker’s voice. By employing two DMs and enforcing a cycle consistency loss, the CycleDiffusion model effectively learns both reconstruction and conversion paths, producing high-quality converted speech. The effectiveness of the proposed model in voice conversion is validated through experiments using the VCTK (Voice Cloning Toolkit) dataset. Full article

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

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9 pages, 263 KiB

Open AccessArticle

Characterization of Beer Produced with the Addition of Brown Macroalgae Fucus virsoides

by Kristina Habschied, Zdenko Lončarić, Stela Jokić, Krunoslav Aladić, Vinko Krstanović and Krešimir Mastanjević

Appl. Sci. 2024, 14(20), 9594; https://doi.org/10.3390/app14209594 - 21 Oct 2024

Viewed by 971

Abstract

Marine macroalgae are organisms rich in bioactive compounds such as polysaccharides, polyphenols, and various minerals. Macroalgae are increasingly being added to the human diet precisely because they contain useful compounds that can also be used in the pharmaceutical industry. Previous research describes their [...] Read more.

Marine macroalgae are organisms rich in bioactive compounds such as polysaccharides, polyphenols, and various minerals. Macroalgae are increasingly being added to the human diet precisely because they contain useful compounds that can also be used in the pharmaceutical industry. Previous research describes their addition to meat products, yogurt, bread, and baby food. However, data on the addition of algae to beer have been scarce. The goal of this work was to produce beer with the addition of brown macroalgae (Fucus virsoides) from the Adriatic Sea. In addition, the basic physical–chemical parameters (color, pH, ethanol, extract, and polyphenols) were determined. The most important premise is the transfer of selenium (Se) to beer, since Se is deficient in human food chain. The transfer of different metals, namely, S (sulfur), Mg (magnesium), P (phosphorus), K (potassium), Ca (calcium), Cr (chromium), Mn (manganese), Fe (iron), Co (cobalt), Ni (nickel), Cu (copper), Zn (zinc), As (arsenic), Se (selenium), Mo (molybdenum), Cd (cadmium), Hg (mercury), and Pb (lead), from algae to beer was determined using inductively coupled plasma–mass spectrometry (ICP−MS). The results, however, were not satisfactory regarding metal transfer. In particular, Se was detected in beer, but other metals such as As, Cd, and Pb were not. Alga addition contributed to extract values, and the original extract reached 14.3 °P in wort with alga addition, as opposed to 12.8 °P in the control sample. Such high extract content, however, resulted in beer with low alcohol content, <4% v/v for both beers. This could be explained by the high levels of unfermentable extract. pH values showed statistical difference between samples, meaning that the addition of algae significantly affected the pH value of beer, reducing acidity by almost 5%. Full article

(This article belongs to the Special Issue Applications of Algae and Their Metabolites in Industry and Agriculture)

12 pages, 3087 KiB

Open AccessArticle

Torsional Fatigue Performance of a Spot-Welded Structure: An XFEM Analysis

by Murat Demiral and Ertugrul Tolga Duran

Appl. Sci. 2024, 14(20), 9593; https://doi.org/10.3390/app14209593 - 21 Oct 2024

Viewed by 739

Abstract

This study delves into the exploration of the fatigue performance of a structure that has been spot-welded and is being loaded with torsional fatigue. The extended finite element method (XFEM) was applied to simulate the intricate interaction of spot welds in response to [...] Read more.

This study delves into the exploration of the fatigue performance of a structure that has been spot-welded and is being loaded with torsional fatigue. The extended finite element method (XFEM) was applied to simulate the intricate interaction of spot welds in response to cyclic loading. The developed model was validated through experiments. The influences of different parameters, such as the number of spot welds used to join the adherends, the diameters of the spot welds, and the load ratio applied, on the fatigue performance of the box were investigated. The first two parameters studied had a significant influence on the extent of the fatigue failure-affected spot welds, where the crack propagation rate can be decreased by more than 700%. Full article

(This article belongs to the Special Issue Fatigue Damage Behavior and Mechanisms: Latest Advances and Prospects)

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19 pages, 4589 KiB

Open AccessArticle

A Novel Robust Hybrid Control Strategy for a Quadrotor Trajectory Tracking Aided with Bioinspired Neural Dynamics

by Jianqi Li, Xin Li, Jianquan Lu, Binfang Cao and Jian Sun

Appl. Sci. 2024, 14(20), 9592; https://doi.org/10.3390/app14209592 - 21 Oct 2024

Viewed by 707

Abstract

This paper introduces a novel hybrid control strategy for quadrotor UAVs inspired by neural dynamics. Our approach effectively addresses two common issues: the velocity jump problem in traditional backstepping control and the control signal chattering in conventional sliding mode control. The proposed system [...] Read more.

This paper introduces a novel hybrid control strategy for quadrotor UAVs inspired by neural dynamics. Our approach effectively addresses two common issues: the velocity jump problem in traditional backstepping control and the control signal chattering in conventional sliding mode control. The proposed system combines an outer-loop bioinspired backstepping controller with an inner-loop bioinspired sliding mode controller, ensuring smooth trajectory tracking even under external disturbances. We rigorously analyzed the system’s stability using Lyapunov stability theory. To validate our algorithm’s effectiveness, we conducted trajectory tracking experiments in both disturbance-free and step-disturbance conditions, comparing it with the traditional backstepping control, conventional sliding mode control, and saturated sliding mode control. The results demonstrate that our algorithm not only tracks trajectories more effectively but also significantly outperforms these methods in suppressing velocity jumps and signal chattering. Full article

(This article belongs to the Special Issue Data-Driven Control System: Methods and Applications)

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16 pages, 2793 KiB

Open AccessArticle

Design of a Lower Limb Prosthesis for Ballet Practice

by Blanca Monge Pérez, Cristina Alía García and Juan David Cano-Moreno

Appl. Sci. 2024, 14(20), 9591; https://doi.org/10.3390/app14209591 - 21 Oct 2024

Viewed by 587

Abstract

Ballet is a discipline that combines art and sport in a harmonious way. It is a practice that has high physical and mental demands to achieve the proper body precision. During this activity, numerous muscles, including those in the legs, need to be [...] Read more.

Ballet is a discipline that combines art and sport in a harmonious way. It is a practice that has high physical and mental demands to achieve the proper body precision. During this activity, numerous muscles, including those in the legs, need to be exercised. Therefore, individuals who have lost part of their lower limb due to amputation face numerous significant challenges when it comes to practicing ballet. Throughout this article, the key aspects that influence the design of a lower limb prosthesis specifically adapted for ballet practice will be analyzed. New materials will be explored with the goal of designing an optimal model that ensures maximum performance and comfort for the users. Additionally, the prosthesis will be customized using 3D-printing technology, and a prototype will be presented. This study will merge biomechanics, ergonomics, and design. Its goal is to find a solution that improves the quality of life for lower limb amputees whose passion is ballet. The aim is to overcome physical and emotional barriers and provide a way to reintegrate amputee dancers into the world of dance. It is important to highlight the novelty of this work: combining different disciplines to provide a solution for individuals who engage in dance as a hobby rather than professionally. The proposed methodology aims to enable users with disabilities to access a personalized, complex, and potentially costly product. Full article

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16 pages, 6520 KiB

Open AccessArticle

Classification of Faults in Power System Transmission Lines Using Deep Learning Methods with Real, Synthetic, and Public Datasets

by Ozan Turanlı and Yurdagül Benteşen Yakut

Appl. Sci. 2024, 14(20), 9590; https://doi.org/10.3390/app14209590 - 21 Oct 2024

Viewed by 1070

Abstract

Every part of society relies on energy systems due to the growing population and the constant demand for energy. Because of the high energy demands of transportation, industry, and daily life, energy systems are crucial to every part of society. Electrical transmission lines [...] Read more.

Every part of society relies on energy systems due to the growing population and the constant demand for energy. Because of the high energy demands of transportation, industry, and daily life, energy systems are crucial to every part of society. Electrical transmission lines are a crucial component of the electrical power system. Therefore, in order to determine the power system’s protection plan and increase its reliability, it is critical to foresee and classify fault types. With this motivation, the main goal of this paper is to design a deep network model to classify faults in transmission lines based on real, generated, and publicly available datasets. A deep learning architecture that was based on a one-dimensional convolutional neural network (CNN) was utilized in this study. Accuracy, specificity, recall, precision, F1 score, ROC curves, and AUC were employed as performance criteria for the suggested model. Not only synthetic but also real data were used in this study. It has been seen that the created model can be used successfully for both real data and synthetic data. In order to measure the robustness of the network, it was tested with three different datasets consisting of real, generated, and publicly available datasets. In the paper, 1D CNN, one of the machine learning methods, was used on three different power systems, and it was observed that the machine learning method was successful in all three power systems. Full article

(This article belongs to the Special Issue Analysis, Modelling and Simulation in Electrical Power Systems)

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20 pages, 6118 KiB

Open AccessReview

Progress of Capillary Flow-Related Hydrovoltaic Technology: Mechanisms and Device Applications

by Wenluan Zhang, Runru Tristan Liu and Yumin Huang

Appl. Sci. 2024, 14(20), 9589; https://doi.org/10.3390/app14209589 - 21 Oct 2024

Viewed by 862

Abstract

Capillary flow-related hydrovoltaic technology is an emerging research field for sustainable electricity generation. Despite great progress in the last decade, the mechanisms behind electricity generation remain unclear. In this review, we provide an overview of the current proposed mechanisms for electricity generation induced [...] Read more.

Capillary flow-related hydrovoltaic technology is an emerging research field for sustainable electricity generation. Despite great progress in the last decade, the mechanisms behind electricity generation remain unclear. In this review, we provide an overview of the current proposed mechanisms for electricity generation induced by water evaporation and moisture absorption. We explore key mechanisms, including streaming potential, ion concentration gradient, microbial electricity, ionovoltaic effect, pseudo-streaming, evaporating potential, and upstream proton diffusion. Each offers distinct insights and faces specific challenges that require further study. Unlike previous reviews, we focus specifically on the detailed mechanistic understanding of capillary flow-related electricity generation and highlight the interplay of different mechanisms. Additionally, we identify critical gaps in current research, particularly the need for empirical validation through advanced characterization techniques, such as spectroscopy, microscopy, and electrochemical analysis. Moreover, we discuss the practical applications of capillary flow-related hydrovoltaic technology in energy harvesting systems and self-powered sensors, highlighting its potential to convert water evaporation and environmental moisture into sustainable energy. We believe this review can serve as a starting point for further efforts aimed at addressing these challenges, thus paving the way for the commercialization of this technology and its contribution to sustainable development goals. Full article

(This article belongs to the Special Issue Advances in New Energy Power Technology)

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15 pages, 2191 KiB

Open AccessArticle

YOLO-ESL: An Enhanced Pedestrian Recognition Network Based on YOLO

by Feilong Wang, Xiaobing Yang and Juan Wei

Appl. Sci. 2024, 14(20), 9588; https://doi.org/10.3390/app14209588 - 21 Oct 2024

Viewed by 741

Abstract

Pedestrian detection is a critical task in computer vision; however, mainstream algorithms often struggle to achieve high detection accuracy in complex scenarios, particularly due to target occlusion and the presence of small objects. This paper introduces a novel pedestrian detection algorithm, YOLO-ESL, based [...] Read more.

Pedestrian detection is a critical task in computer vision; however, mainstream algorithms often struggle to achieve high detection accuracy in complex scenarios, particularly due to target occlusion and the presence of small objects. This paper introduces a novel pedestrian detection algorithm, YOLO-ESL, based on the YOLOv7 framework. YOLO-ESL integrates the ELAN-SA module, designed to enhance feature extraction, with the LGA module, which improves feature fusion. The ELAN-SA module optimizes the flexibility and efficiency of small object feature extraction, while the LGA module effectively integrates multi-scale features through local and global attention mechanisms. Additionally, the CIOUNMS algorithm addresses the issue of target loss in cases of high overlap, improving boundary box filtering. Evaluated on the VOC2012 pedestrian dataset, YOLO-ESL achieved an accuracy of 93.7%, surpassing the baseline model by 3.0%. Compared to existing methods, this model not only demonstrates strong performance in handling occluded and small object detection but also remarkable robustness and efficiency. Full article

(This article belongs to the Special Issue Applications of Artificial Intelligence in Industrial Engineering)

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