Journal Description
Applied Sciences
Applied Sciences
is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our authors say about Applied Sciences.
- Companion journals for Applied Sciences include: Applied Nano, AppliedChem, Applied Biosciences, Virtual Worlds, Spectroscopy Journal and JETA.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
A Ship Trajectory Prediction Method Based on an Optuna–BILSTM Model
Appl. Sci. 2024, 14(9), 3719; https://doi.org/10.3390/app14093719 (registering DOI) - 27 Apr 2024
Abstract
In the field of maritime traffic management, overcoming the challenges of low prediction accuracy and computational inefficiency in ship trajectory prediction is crucial for collision avoidance. This paper presents an advanced solution using a deep bidirectional long- and short-term memory network (BILSTM) and
[...] Read more.
In the field of maritime traffic management, overcoming the challenges of low prediction accuracy and computational inefficiency in ship trajectory prediction is crucial for collision avoidance. This paper presents an advanced solution using a deep bidirectional long- and short-term memory network (BILSTM) and the Optuna hyperparameter automatic optimized framework. Utilizing automatic identification system (AIS) data to analyze ship navigation patterns, the study applies Optuna to fine-tune the hyperparameters of the BILSTM network to improve prediction accuracy and efficiency. The developed Optuna–BILSTM model shows a remarkable 7% increase in prediction accuracy over traditional back propagation (BP) neural networks and standard BILSTM models. These results not only improve ship navigation and safety but also have significant implications for the development of autonomous ship collision avoidance systems, marking a significant step toward safer and more efficient maritime traffic management.
Full article
(This article belongs to the Section Marine Science and Engineering)
►
Show Figures
Open AccessArticle
The Association between Countermovement Rebound Jump Metrics and Independent Measures of Athletic Performance
by
Jiaqing Xu, Anthony Turner, Thomas M. Comyns, Shyam Chavda and Chris Bishop
Appl. Sci. 2024, 14(9), 3718; https://doi.org/10.3390/app14093718 (registering DOI) - 26 Apr 2024
Abstract
This study investigates the associations between countermovement rebound jump (CMRJ) performance metrics and various independent measures of athletic performance, including the isometric mid-thigh pull (IMTP), 20 m linear sprint, and 505 change-of-direction (COD) speed tests. Pearson’s correlations were used to analyse the relationship
[...] Read more.
This study investigates the associations between countermovement rebound jump (CMRJ) performance metrics and various independent measures of athletic performance, including the isometric mid-thigh pull (IMTP), 20 m linear sprint, and 505 change-of-direction (COD) speed tests. Pearson’s correlations were used to analyse the relationship between the CMRJ measures with athletic performance, with significance being set at p ≤ 0.006. Results showed large significant positive relationships between IMTP peak force and force at 300 milliseconds with the first jump height of the CMRJ (JH-1, r = 0.54 to 0.55, p ≤ 0.002). Additionally, inverse relationships were observed between reactive strength index modified (RSImod) and reactive strength index (RSI) with 20 m sprint total and split times (r = −0.55 to −0.66, p ≤ 0.001), and the 10 m and total sprint times were significantly correlated with JH-1 (r = −0.54, p = 0.003), indicating that greater vertical explosive power and reactive strength are associated with faster sprint performance. Finally, a significant inverse relationship was identified between CMRJ metrics (two JH values and RSImod) and 505 COD times in both the left and right sides (r = −0.51 to −0.68, p ≤ 0.006). These findings suggest that CMRJ performance metrics are valuable indicators of lower-limb explosive force production, with a strong link to both linear sprint and COD performance. The finding underscores the importance of including CMRJ assessments in athletic performance evaluations due to their dual assessment capacity of slow and fast stretch–shortening cycle mechanics.
Full article
Open AccessArticle
Gas–Liquid Two-Phase Flow Measurement Based on Optical Flow Method with Machine Learning Optimization Model
by
Junxian Wang, Zhenwei Huang, Ya Xu and Dailiang Xie
Appl. Sci. 2024, 14(9), 3717; https://doi.org/10.3390/app14093717 (registering DOI) - 26 Apr 2024
Abstract
Gas–Liquid two-phase flows are a common flow in industrial production processes. Since these flows inherently consist of discrete phases, it is challenging to accurately measure the flow parameters. In this context, a novel approach is proposed that combines the pyramidal Lucas-Kanade (L–K) optical
[...] Read more.
Gas–Liquid two-phase flows are a common flow in industrial production processes. Since these flows inherently consist of discrete phases, it is challenging to accurately measure the flow parameters. In this context, a novel approach is proposed that combines the pyramidal Lucas-Kanade (L–K) optical flow method with the Split Comparison (SC) model measurement method. In the proposed approach, videos of gas–liquid two-phase flows are captured using a camera, and optical flow data are acquired from the flow videos using the pyramid L–K optical flow detection method. To address the issue of data clutter in optical flow extraction, a dynamic median value screening method is introduced to optimize the corner point for optical flow calculations. Machine learning algorithms are employed for the prediction model, yielding high flow prediction accuracy in experimental tests. Results demonstrate that the gradient boosted regression (GBR) model is the most effective among the five preset models, and the optimized SC model significantly improves measurement accuracy compared to the GBR model, achieving an R2 value of 0.97, RMSE of 0.74 m3/h, MAE of 0.52 m3/h, and MAPE of 8.0%. This method offers a new approach for monitoring flows in industrial production processes such as oil and gas.
Full article
(This article belongs to the Special Issue Advanced Heat and Mass Transfer Techniques in Power and Energy Systems)
Open AccessArticle
Fast Rail Fastener Screw Detection for Vision-Based Fastener Screw Maintenance Robot Using Deep Learning
by
Yijie Cai, Ming He, Qi Tao, Junyong Xia, Fei Zhong and Hongdi Zhou
Appl. Sci. 2024, 14(9), 3716; https://doi.org/10.3390/app14093716 (registering DOI) - 26 Apr 2024
Abstract
Fastener screws are critical components of rail fasteners. For the fastener screw maintenance robot, an image-based fast fastener screw detection method is urgently needed. In this paper, we propose a light-weight model named FSS-YOLO based on YOLOv5n for rail fastener screw detection. The
[...] Read more.
Fastener screws are critical components of rail fasteners. For the fastener screw maintenance robot, an image-based fast fastener screw detection method is urgently needed. In this paper, we propose a light-weight model named FSS-YOLO based on YOLOv5n for rail fastener screw detection. The C3Fast module is presented to replace the C3 module in the backbone and neck to reduce Params and FLOPs. Then, the SIoU loss is introduced to enhance the convergence speed and recognition accuracy. Finally, for the enhancement of the screw detail feature fusion, the shuffle attention (SA) is incorporated into the bottom-up process in the neck part. Experiment results concerning CIoU and DIoU for loss, MobileNetv3 and GhostNet for light-weight improvement, simple attention mechanism (SimAM), and squeeze-and-excitation (SE) attention for the attention module, and YOLO series methods for performance comparison are listed, demonstrating that the proposed FSS-YOLO significantly improves the performance, with higher accuracy and lower computation cost. It is demonstrated that the FSS-YOLO is 7.3% faster than the baseline model in FPS, 17.4% and 19.5% lower in Params and FLOPs, respectively, and the P, mAP@50, Recall, and F1 scores are increased by 10.6% and 6.4, 13.4%, and 12.2%, respectively.
Full article
(This article belongs to the Section Applied Industrial Technologies)
Open AccessArticle
Indole-3-Acetic Acid Action in Outdoor and Indoor Cultures of Spirulina in Open Raceway Reactors
by
Jéssica Teixeira da Silveira, Ana Priscila Centeno da Rosa, Michele Greque de Morais and Jorge Alberto Vieira Costa
Appl. Sci. 2024, 14(9), 3715; https://doi.org/10.3390/app14093715 (registering DOI) - 26 Apr 2024
Abstract
A significant research gap exists in investigating large-scale microalgae cultures exposed to outdoor conditions, with the addition of phytohormones using non-sterile growth media. Implementing these conditions is crucial for verifying the industrial viability of this strategy. This study aimed to evaluate the effect
[...] Read more.
A significant research gap exists in investigating large-scale microalgae cultures exposed to outdoor conditions, with the addition of phytohormones using non-sterile growth media. Implementing these conditions is crucial for verifying the industrial viability of this strategy. This study aimed to evaluate the effect of indole-3-acetic acid (IAA) supplementation on Spirulina sp. LEB 18 cultures conducted indoors and outdoors in raceway bioreactors. The outdoor experiments were performed under uncontrolled environmental conditions. The indoor cultures were maintained within a thermostat-controlled chamber at a consistent temperature and lighting intensity. The outdoor experiments supplemented with IAA achieved a biomass concentration of 5.43 g L−1 and productivity of 173.9 mg L−1 d−1. These values increased 122.5% and 130.9% in biomass concentration and productivity, respectively, compared to the indoor experiments with the same supplementation. Moreover, roughly half of the biomass generated from outdoor cultivation with IAA consisted of carbohydrates (45%). Compared to indoor cultivation, this approach reduced production costs for biomass (55%) and lowered production costs for carbohydrates, proteins, and lipids by 86%, 44%, and 50%, respectively. The successful application of phytohormones in microalgae cultures, particularly under larger scale, nonsterile, and outdoor conditions, represents a significant advancement toward industrial implementation.
Full article
(This article belongs to the Special Issue New Insights into Microalgae Cultivation and Downstream Processes, 3rd Edition)
Open AccessArticle
Radar Error Correction Method Based on Improved Sparrow Search Algorithm
by
Yifei Liu, Zhangsong Shi, Bing Fu and Huihui Xu
Appl. Sci. 2024, 14(9), 3714; https://doi.org/10.3390/app14093714 (registering DOI) - 26 Apr 2024
Abstract
Aiming at the problem of the limited application range and low accuracy of existing radar calibration methods, this paper studies the radar calibration method based on cooperative targets, and establishes the integrated radar measurement error model. Then, the improved sparrow search algorithm (ISSA)
[...] Read more.
Aiming at the problem of the limited application range and low accuracy of existing radar calibration methods, this paper studies the radar calibration method based on cooperative targets, and establishes the integrated radar measurement error model. Then, the improved sparrow search algorithm (ISSA) is used to estimate the systematic error, so as to avoid the loss of partial accuracy caused by the process of approximating the nonlinear equation to the linear equation, thus improving the radar calibration effect. The sparrow search algorithm (SSA) is improved through integrating various strategies, and the convergence speed and stability of the algorithm are also improved. The simulation results show that the ISSA can solve radar systematic errors more accurately than the generalized least square method, Kalman filter, and SSA. It takes less time the than SSA and has a certain stability and real-time performance. The radar measurement error after correction is obviously smaller than that before correction, indicating that the proposed method is feasible and effective.
Full article
(This article belongs to the Topic Radar Signal and Data Processing with Applications)
Open AccessArticle
Joint Hybrid Beamforming Design for Millimeter Wave Amplify-and-Forward Relay Communication Systems
by
Jinxian Zhao, Dongfang Jiang, Heng Wei, Bingjie Liu, Yifeng Zhao, Yi Zhang, Haoyuan Yu and Xuewei Liu
Appl. Sci. 2024, 14(9), 3713; https://doi.org/10.3390/app14093713 (registering DOI) - 26 Apr 2024
Abstract
Hybrid beamforming (HBF) has been regarded as one of the most promising technologies in millimeter Wave (mmWave) communication systems. In order to guarantee the communication quality in non-line-of-sight (NLOS) scenarios, joint HBF design for the mmWave amplify-and-forward (AF) relay communication system is studied
[...] Read more.
Hybrid beamforming (HBF) has been regarded as one of the most promising technologies in millimeter Wave (mmWave) communication systems. In order to guarantee the communication quality in non-line-of-sight (NLOS) scenarios, joint HBF design for the mmWave amplify-and-forward (AF) relay communication system is studied in this paper. The ideal case is first considered where the mmWave half-duplex (HD) AF relay system operates with channel state information (CSI) accurately known. In order to tackle the non-convex problem, a manifold optimization (MO)-based alternating optimization algorithm is proposed, where an optimization problem containing only constant modulus constraints in Euclidean space can be converted to an unconstrained optimization problem in a Riemann manifold. Furthermore, considering more practical cases with estimation errors of CSI, we investigate the robust joint HBF design with the system operating in full-duplex (FD) mode to obtain higher spectral efficiency (SE). A null-space projection (NP) based self-interference cancellation (SIC) algorithm is developed to attenuate the self-interference (SI). Different from the traditional SI suppression algorithm, there’s no limit on the number of RF chains. Numerical results reveal that our proposed algorithms has a good convergence and can effectively deal with the influence of different CSI estimation errors. A significant performance improvement can be achieved in contrast with other approaches.
Full article
(This article belongs to the Special Issue Novel Advances in Internet of Vehicles)
Open AccessArticle
Semantic Segmentation of Aerial Imagery Using U-Net with Self-Attention and Separable Convolutions
by
Bakht Alam Khan and Jin-Woo Jung
Appl. Sci. 2024, 14(9), 3712; https://doi.org/10.3390/app14093712 - 26 Apr 2024
Abstract
This research addresses the crucial task of improving accuracy in the semantic segmentation of aerial imagery, essential for applications such as urban planning and environmental monitoring. This study emphasizes the significance of maintaining the Intersection over Union (IOU) score as a metric and
[...] Read more.
This research addresses the crucial task of improving accuracy in the semantic segmentation of aerial imagery, essential for applications such as urban planning and environmental monitoring. This study emphasizes the significance of maintaining the Intersection over Union (IOU) score as a metric and employs data augmentation with the Patchify library, using a patch size of 256, to effectively augment the dataset, which is subsequently split into training and testing sets. The core of this investigation lies in a novel architecture that combines a U-Net framework with self-attention mechanisms and separable convolutions. The introduction of self-attention mechanisms enhances the model’s understanding of image context, while separable convolutions expedite the training process, contributing to overall efficiency. The proposed model demonstrates a substantial accuracy improvement, surpassing the previous state-of-the-art Dense Plus U-Net, achieving an accuracy of 91% compared to the former’s 86%. Visual representations, including original patch images, original masked patches, and predicted patch masks, showcase the model’s proficiency in semantic segmentation, marking a significant advancement in aerial image analysis and underscoring the importance of innovative architectural elements for enhanced accuracy and efficiency in such tasks.
Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessArticle
Which Are the Needs of People with Learning Disorders for Inclusive Museums? Design of OLOS®—An Innovative Audio-Visual Technology
by
Michele Materazzini, Alessia Melis, Andrea Zingoni, Daniele Baldacci, Giuseppe Calabrò and Juri Taborri
Appl. Sci. 2024, 14(9), 3711; https://doi.org/10.3390/app14093711 - 26 Apr 2024
Abstract
This paper proposes an innovative methodology for enhancing museum accessibility and inclusivity for visitors with specific learning disorders (SLDs) using audio-visual interfaces based on patented technology. The approach involves analyzing user preferences and dyslexic students’ self-assessments through two questionnaires. This study gathered 126
[...] Read more.
This paper proposes an innovative methodology for enhancing museum accessibility and inclusivity for visitors with specific learning disorders (SLDs) using audio-visual interfaces based on patented technology. The approach involves analyzing user preferences and dyslexic students’ self-assessments through two questionnaires. This study gathered 126 responses from both SLD-certified individuals and those without intellectual disabilities for the first questionnaire and over 1300 responses exclusively from SLD-certified individuals for the second. Results suggest practical solutions such as new visual effects, gamification methods, and user-friendly informational materials linked to an AI system. These findings serve as guidelines for developing technology to improve museum accessibility, particularly for individuals with SLDs.
Full article
(This article belongs to the Special Issue Cross Applications of Interactive System and Extended Reality)
Open AccessSystematic Review
Antibacterial Agents Used in Modifications of Dental Resin Composites: A Systematic Review
by
Maja Zalega and Kinga Bociong
Appl. Sci. 2024, 14(9), 3710; https://doi.org/10.3390/app14093710 - 26 Apr 2024
Abstract
Introduction: Resin-based composites (RBCs) are very common and often applicable in dentistry. Their disadvantage is susceptibility to secondary caries due to the formation of bacterial biofilm at the interface with the patient’s tissues. Antimicrobial additive incorporation into RBCs seems to be a justified
[...] Read more.
Introduction: Resin-based composites (RBCs) are very common and often applicable in dentistry. Their disadvantage is susceptibility to secondary caries due to the formation of bacterial biofilm at the interface with the patient’s tissues. Antimicrobial additive incorporation into RBCs seems to be a justified method to alleviate the above-mentioned negative phenomenon. The aim of this review is to provide a juxtaposition of strategies and results on the topic of antimicrobial composites. It also provides insights into future research and prospects for clinical applications. Methods: This review summarizes the literature from 2017 to 2024, describing potential antimicrobial agents incorporated into dental composites. The research methodology involved a systematic search using the Population/Intervention/Comparison/Outcome (PICO) structure and selecting articles from databases such as Pubmed, ScienceDirect, and Elsevier, which allowed for an in-depth review of substances utilized for the antibacterial modification of RBCs. Results: A total of 159 articles were identified, 43 of which met the inclusion criteria. Conclusions: This review is a summary of novel approaches in the field of dental materials science. The results show the variety of approaches to modifying composites for antimicrobial efficacy. It is worth underlining that there is a significant difficulty in comparing the studies selected for this review. This is related to the different modifiers used and the modification of composites with different compositions. Unfortunately, there is still a lack of a standardized approach to the modification of dental materials to give them a biocidal character and simultaneously maintain the stability of their mechanical and chemical properties.
Full article
(This article belongs to the Special Issue Dental Materials: Latest Advances and Prospects, Third Edition)
Open AccessArticle
Nutritional Profiling of Underutilised Citrullus Lanatus Mucosospermus Seed Flour
by
Olakunbi Olubi, Joseline Veronica Felix-Minnaar and Victoria A. Jideani
Appl. Sci. 2024, 14(9), 3709; https://doi.org/10.3390/app14093709 - 26 Apr 2024
Abstract
The seed of Citrullus lanatus mucosospermus, known as egusi, is versatile and explored for its oil and flour functionality. Raw flour can be used as a raw material in a nutritional program due to its oil-rich, remarkably high protein content, and richness in
[...] Read more.
The seed of Citrullus lanatus mucosospermus, known as egusi, is versatile and explored for its oil and flour functionality. Raw flour can be used as a raw material in a nutritional program due to its oil-rich, remarkably high protein content, and richness in omega-6 fatty acids. There is a need to explore eco-friendly defatting methods using the supercritical CO2 extraction method (SFECO2) to preserve this seed’s generic richness and to control the flour–oil ratio in processing formulations. The supercritical fluid extraction method uses temperature, pressure, and CO2 flow rate to determine the best yield and extraction parameters. Defatted egusi flour (DEF) was extracted using three runs. Firstly, at 60 °C, 30 g/h, and 450 bar (DEF1); secondly, at 55 °C, 30 g/h, and 600 bar (DEF2); and thirdly, extraction was performed at 75 °C, 30 g/h and 600 bar (DEF3). Trace and major elements were analysed using Agilent 7700 quadruple ICP-MS (Agilent Technologies Network, Palo Alto, CA, USA) and Thermo Cap 6200 ICP-AES (Thermo Scientific, Waltham, MA, USA), respectively. The sugar was separated on a gas chromatograph coupled to a Mass Selective Detector (MSD). The fundamental pasting property measurements were performed using a Rapid Visco Analyser RVA 4500 Perten instrument Sin 214 31208-45 Australia. Data analysis was conducted using IBM SPSS version 29 software (v. 2022). The protein content of defatted egusi flour ranged from 48.4 for DEF2 to 60.4% w/w for DEF1 and differed significantly, with a rich amino acid high in glutamine ranging from 9.8 to 12.9 g/100 g). DEF2 (512.0 cP) showed the highest peak viscosity and was the most viscous among the samples. Defatted flour with lower temperature and lower pressure (60 °C and 450 bar) offered the best nutritional properties, proffering defatted egusi flour from SFECO2, a novel flour for dietary programs.
Full article
(This article belongs to the Special Issue Novel Extraction Methods and Applications)
Open AccessArticle
Identifying Users’ Needs to Design and Manufacture 3D-Printed Upper Limb Sockets: A Survey-Based Study
by
Alba Roda-Sales and Immaculada Llop-Harillo
Appl. Sci. 2024, 14(9), 3708; https://doi.org/10.3390/app14093708 - 26 Apr 2024
Abstract
The development of prosthetic arms has increased in recent years, particularly with the growth of 3D printing technologies. However, one of the main weaknesses of 3D-printed prosthetics is the prosthetic socket, which commonly presents a generic adjustable design that may produce discomfort. In
[...] Read more.
The development of prosthetic arms has increased in recent years, particularly with the growth of 3D printing technologies. However, one of the main weaknesses of 3D-printed prosthetics is the prosthetic socket, which commonly presents a generic adjustable design that may produce discomfort. In fact, the socket has always been a part that has frequently caused discomfort in traditionally manufactured prosthetics and, consequently, high rejection rates. Studies about improving the socket component in traditional and 3D-printed upper limb prostheses are scarce. Advancements in 3D printing and 3D scanning will offer a high potential to improve the design and manufacturing of 3D-printed sockets. Thus, to propose better designs and manufacturing protocols, this paper presents a questionnaire to assess the needs of upper limb prosthetics users or potential users, as well as a survey-based study with 18 respondents. The results reveal that users prioritize breathability and low cost, a stable fixing system, products without the need for shape adjustments, a light weight and comfort regarding the products they require. The results of this study provide insights into the key characteristics that sockets should accomplish according to users’ needs that are applicable to 3D-printed sockets and traditionally manufactured sockets, and they contribute to improving their design and manufacturing.
Full article
(This article belongs to the Section Biomedical Engineering)
►▼
Show Figures
Figure 1
Open AccessArticle
Reconstruction of the Subsurface of Al-Hassa Oasis Using Gravity Geophysical Data
by
Abid Khogali, Konstantinos Chavanidis, Panagiotis Kirmizakis, Alexandros Stampolidis and Pantelis Soupios
Appl. Sci. 2024, 14(9), 3707; https://doi.org/10.3390/app14093707 - 26 Apr 2024
Abstract
Al-Hassa city, located in Eastern Saudi Arabia, boasts the world’s largest oasis and the most expansive naturally irrigated lands. Historically, a total of 280 natural springs facilitated significant groundwater discharge and irrigation of agricultural land. Furthermore, the water in certain springs formerly had
[...] Read more.
Al-Hassa city, located in Eastern Saudi Arabia, boasts the world’s largest oasis and the most expansive naturally irrigated lands. Historically, a total of 280 natural springs facilitated significant groundwater discharge and irrigation of agricultural land. Furthermore, the water in certain springs formerly had a high temperature. The spatial variability of the water quality was evident. At the same time, Al-Hassa Oasis is situated on the northeastern side of the Ghawar field, which is the largest conventional onshore oil field in the world in terms of both reserves and daily output (approximately 3.8 mmb/d). The aforementioned traits suggest an intricate subsurface that has not yet been publicly and thoroughly characterized. Due to the presence of significant cultural noise caused by agricultural and nearby industrial activities, a robust, easy-to-use, and accurate geophysical method (gravity) was used to cover an area of 350 km2, producing the 3D subsurface model of the study area. A total of 571 gravity stations were collected, covering the whole Al-Hassa Oasis and parts of the nearby semi-urban areas. The gravity data were corrected and processed, and a 3D inversion was applied. The resulting 3D geophysical subsurface modeling unveiled an intricate subterranean configuration and revealed lateral variations in density, indicating the presence of a potential salt dome structure, as well as fracture zones that serve as conduits or obstacles to the flow of the subsurface fluids. This comprehensive modeling approach offers valuable insights into the subsurface dynamics of the broader study area, enhancing our understanding of its qualitative tectonic and hydraulic features and their impacts on the area’s natural resources, such as groundwater and hydrocarbons.
Full article
(This article belongs to the Section Earth Sciences)
Open AccessArticle
Precise Calculation of Inverse Kinematics of the Center of Gravity for Bipedal Walking Robots
by
İsmail Hakkı Şanlıtürk and Hikmet Kocabaş
Appl. Sci. 2024, 14(9), 3706; https://doi.org/10.3390/app14093706 - 26 Apr 2024
Abstract
The walking of humanoid robots is dependent on the precise tracking of their center of gravity and foot trajectories. Trajectory tracking is achieved by mobilizing their joints to achieve the correct trajectory. Errors occur because of assumptions on tracking the center of gravity
[...] Read more.
The walking of humanoid robots is dependent on the precise tracking of their center of gravity and foot trajectories. Trajectory tracking is achieved by mobilizing their joints to achieve the correct trajectory. Errors occur because of assumptions on tracking the center of gravity and the foot trajectories. In this study, a numerical algorithm was developed that produces an exact and single kinematic solution in which the center of gravity and foot trajectories can be tracked with the desired precision. The effectiveness of this algorithm was examined with a dynamic simulation and compared with a method given in the literature. The main highlight of this study, using the presented algorithm, is that the robot could walk even if the position of its center of gravity was lower than its hips, resulting in a tracking error that was smaller than that reported in the literature.
Full article
Open AccessArticle
Impulsive Control Discrete Fractional Neural Networks in Product Form Design: Practical Mittag-Leffler Stability Criteria
by
Trayan Stamov
Appl. Sci. 2024, 14(9), 3705; https://doi.org/10.3390/app14093705 - 26 Apr 2024
Abstract
The planning, regulation and effectiveness of the product design process depend on various characteristics. Recently, bio-inspired collective intelligence approaches have been applied in this process in order to create more appealing product forms and optimize the design process. In fact, the use of
[...] Read more.
The planning, regulation and effectiveness of the product design process depend on various characteristics. Recently, bio-inspired collective intelligence approaches have been applied in this process in order to create more appealing product forms and optimize the design process. In fact, the use of neural network models in product form design analysis is a complex process, in which the type of network has to be determined, as well as the structure of the network layers and the neurons in them; the connection coefficients, inputs and outputs have to be explored; and the data have to be collected. In this paper, an impulsive discrete fractional neural network modeling approach is introduced for product design analysis. The proposed model extends and complements several existing integer-order neural network models to the generalized impulsive discrete fractional-order setting, which is a more flexible mechanism to study product form design. Since control and stability methods are fundamental in the construction and practical significance of a neural network model, appropriate impulsive controllers are designed, and practical Mittag-Leffler stability criteria are proposed. The Lyapunov function strategy is applied in providing the stability criteria and their efficiency is demonstrated via examples and a discussion. The established examples also illustrate the role of impulsive controllers in stabilizing the behavior of the neuronal states. The proposed modeling approach and the stability results are applicable to numerous industrial design tasks in which multi-agent systems are implemented.
Full article
(This article belongs to the Special Issue Bio-Inspired Collective Intelligence in Multi-Agent Systems)
Open AccessArticle
Elite Genotypes of Water Yam (Dioscorea alata) Yield Food Product Quality Comparable to White Yam (Dioscorea rotundata)
by
Michael Adesokan, Emmanuel Oladeji Alamu, Segun Fawole, Asrat Asfaw and Busie Maziya-Dixon
Appl. Sci. 2024, 14(9), 3704; https://doi.org/10.3390/app14093704 (registering DOI) - 26 Apr 2024
Abstract
Water yam (Dioscorea alata), also known as winged yam, is one of the most economically significant yam species, serving as a staple food crop in tropical and subtropical regions. Its widespread cultivation is due to its favorable agronomic characteristics, including high
[...] Read more.
Water yam (Dioscorea alata), also known as winged yam, is one of the most economically significant yam species, serving as a staple food crop in tropical and subtropical regions. Its widespread cultivation is due to its favorable agronomic characteristics, including high yield, improved tuber storability, and significant nutritional and health benefits. Despite these advantages, water yam often remains underutilized due to consumer biases towards its traditional food product quality, particularly for pounded yam preparations. In this study, we evaluated fifty-eight improved genotypes of water yams grown across three locations to assess their potential to produce superior food qualities comparable to the widely consumed white yams (D.rotundata). Seven white yams, including popular landraces, were used to set thresholds for desirable food quality. Through standardized analysis, yam samples were assessed for their biochemical composition and culinary and sensory texture attributes. The results revealed varying ranges of dry matter (DM), starch, sugar, protein, crude fiber (CF), fat, and amylose, spanning from 20.35 to 35.95 g/100 g, 42.81 to 83.31 g/100 g, 4.76 to 6.95 g/100 g, 4.33 to 6.62 g/100 g, 1.55 to 3.89 g/100 g, 0.32 to 0.53 g/100 g, and 29.27 to 38.52 g/100 g, respectively. The mean values (± SD) were found to be 29.85 ± 4.0 g/100 g (DM), 67.90 ± 44g/100 g (starch), 5.82 ± 0.64 g/100 g (sugar), 6.31 ± 1.31 g/100 g (protein), 2.14 ± 0.57 g/100 g (crude fiber), 0.44 ± 0.08 (fat), and 33 ± 16.43 g/100 g (amylose). Significant effects (p < 0.001) of the planting environments and genotypes on the biochemical composition of the yam samples were observed, except for the sugar content. Furthermore, specific water yam genotypes, such as TDa 0900354, TDa 9801174, TDa 1401619, TDa 1400301, TDa 140091, TDa 0100029, TDa 1100793, TDa 1401249, TDa 1100242, and TDa 1401276, exhibited biochemical properties and culinary and sensory textural attributes akin to the improved white yam genotypes and their landrace counterparts. These findings underscore the potential for promoting selected water yam genotypes to diversify food options and reduce reliance on a limited array of crops, particularly in traditional food-insecure regions of tropical Africa.
Full article
Open AccessArticle
Swarm of Drones in a Simulation Environment—Efficiency and Adaptation
by
Dariusz Marek, Marcin Paszkuta, Jakub Szyguła, Piotr Biernacki, Adam Domański, Marta Szczygieł, Marcel Król and Konrad Wojciechowski
Appl. Sci. 2024, 14(9), 3703; https://doi.org/10.3390/app14093703 - 26 Apr 2024
Abstract
In the swiftly advancing field of swarm robotics and unmanned aerial vehicles, precise and effective testing methods are essential. This article explores the crucial role of software-in-the-loop (SITL) simulations in developing, testing, and validating drone swarm control algorithms. Such simulations play a crucial
[...] Read more.
In the swiftly advancing field of swarm robotics and unmanned aerial vehicles, precise and effective testing methods are essential. This article explores the crucial role of software-in-the-loop (SITL) simulations in developing, testing, and validating drone swarm control algorithms. Such simulations play a crucial role in reproducing real-world operational scenarios. Additionally, they can (regardless of the type of application) accelerate the development process, reduce operational risks, and ensure the consistent performance of drone swarms. Our study demonstrates that different geometrical arrangements of drone swarms require flexible control strategies. The leader-based control model facilitates coherent movement and enhanced coordination. Addressing various issues such as communication delays and inaccuracies in positioning is essential here. These shortcomings underscore the value of improved approaches to collision avoidance. The research described in this article focused on the dynamics of drone swarms in a simulated context and emphasized their operational efficiency and adaptability in various scenarios. Advanced simulation tools were utilized to analyze the interaction, communication, and adaptability of autonomous units. The presented results indicate that the arrangement of drones significantly affects their coordination and collision avoidance capabilities. They also underscore the importance of control systems that can adapt to various situations. The impact of communication delays and errors in positioning systems on the required distance between drones in a grid structure is also presented. This article assesses the impact of different levels of GPS accuracy and communication delays on the coordination of group movement and collision avoidance capabilities.
Full article
Open AccessReview
Recent Advances in the Strategies of Simultaneous Enzyme Immobilization Accompanied by Nanocarrier Synthesis
by
Xinrui Hao, Pengfu Liu and Xiaohe Chu
Appl. Sci. 2024, 14(9), 3702; https://doi.org/10.3390/app14093702 - 26 Apr 2024
Abstract
In recent years, with advancements in nanotechnology and materials science, new enzyme immobilization strategies based on nanomaterials have continuously emerged. These strategies have shown significant effects on enhancing enzyme catalytic performance and stability due to their high surface area, good chemical stability, and
[...] Read more.
In recent years, with advancements in nanotechnology and materials science, new enzyme immobilization strategies based on nanomaterials have continuously emerged. These strategies have shown significant effects on enhancing enzyme catalytic performance and stability due to their high surface area, good chemical stability, and ease of enzyme binding, demonstrating tremendous potential for industrial applications. Those methods that can rapidly synthesize nanocarriers under mild conditions allow for the one-step synthesis of nanocarriers and enzyme complexes, thereby exhibiting advantages such as simplicity of process, minimal enzyme damage, short processing times, and environmental friendliness. This paper provides an overview of simultaneous enzyme immobilization strategies accompanied by nanocarrier synthesis, including organic–inorganic hybrid nano-flowers (HNFs), metal–organic frameworks (MOFs), and conductive polymers (CPs). It covers their preparation principles, post-immobilization performance, applications, and existing challenges.
Full article
(This article belongs to the Special Issue Recent Advances in Nanoparticles for Biomedical Applications)
Open AccessArticle
Instrument Detection and Descriptive Gesture Segmentation on a Robotic Surgical Maneuvers Dataset
by
Irene Rivas-Blanco, Carmen López-Casado, Juan M. Herrera-López, José Cabrera-Villa and Carlos J. Pérez-del-Pulgar
Appl. Sci. 2024, 14(9), 3701; https://doi.org/10.3390/app14093701 - 26 Apr 2024
Abstract
Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA
[...] Read more.
Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend the ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low-level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tools and the left-handed tools. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. On the other hand, for gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.
Full article
(This article belongs to the Special Issue Advances in Intelligent Minimally Invasive Surgical Robots)
Open AccessArticle
Novel Adamantane Derivatives: Synthesis, Cytotoxicity and Antimicrobial Properties
by
Łukasz Popiołek, Wiktoria Janas, Anna Hordyjewska and Anna Biernasiuk
Appl. Sci. 2024, 14(9), 3700; https://doi.org/10.3390/app14093700 - 26 Apr 2024
Abstract
Seventeen adamantane derivatives were synthesized according to facile condensation reaction protocols. Spectral analysis (1H NMR and 13C NMR) was applied to confirm the chemical structure of the obtained substances. The synthesized compounds were tested for in vitro antimicrobial activity against
[...] Read more.
Seventeen adamantane derivatives were synthesized according to facile condensation reaction protocols. Spectral analysis (1H NMR and 13C NMR) was applied to confirm the chemical structure of the obtained substances. The synthesized compounds were tested for in vitro antimicrobial activity against a panel of Gram-positive and Gram-negative bacterial strains and towards fungi from Candida spp. Among them, four derivatives numbered 9, 14, 15 and 19 showed the highest antibacterial potential with MIC = 62.5–1000 µg/mL with respect to all Gram-positive bacteria. S. epidermidis ATCC 12228 was the most susceptible among the tested bacterial strains and C. albicans ATCC 10231 among fungi. Additionally, the cytotoxicity for three derivatives was measured with the use of the MTT test on A549, T47D, L929 and HeLa cell lines. Our cytotoxicity studies confirmed that the tested substances did not cause statistically significant changes in cell proliferation within the range of the tested doses.
Full article
(This article belongs to the Special Issue Natural and Synthetic Antimicrobial Substances: Novel Advances and Applications)
►▼
Show Figures
Figure 1
Journal Menu
► ▼ Journal Menu-
- Applied Sciences Home
- Aims & Scope
- Editorial Board
- Reviewer Board
- Topical Advisory Panel
- Instructions for Authors
- Special Issues
- Topics
- Sections & Collections
- Article Processing Charge
- Indexing & Archiving
- Editor’s Choice Articles
- Most Cited & Viewed
- Journal Statistics
- Journal History
- Journal Awards
- Society Collaborations
- Conferences
- Editorial Office
Journal Browser
► ▼ Journal BrowserHighly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Applied Sciences, Energies, Materials, Nanoenergy Advances, Nanomaterials
Applications of Nanomaterials in Energy Systems, 2nd Volume
Topic Editors: Eleftheria C. Pyrgioti, Ioannis F. Gonos, Diaa-Eldin A. MansourDeadline: 30 April 2024
Topic in
Materials, Nanomaterials, Photonics, Polymers, Applied Sciences, Sensors
Optical and Optoelectronic Properties of Materials and Their Applications
Topic Editors: Zhiping Luo, Gibin George, Navadeep ShrivastavaDeadline: 20 May 2024
Topic in
Applied Sciences, Energies, Minerals, Mining, Sustainability
Mining Innovation
Topic Editors: Krzysztof Skrzypkowski, René Gómez, Fhatuwani Sengani, Derek B. Apel, Faham Tahmasebinia, Jianhang ChenDeadline: 1 June 2024
Topic in
Applied Sciences, Electricity, Electronics, Energies, Sensors
Power System Protection
Topic Editors: Seyed Morteza Alizadeh, Akhtar KalamDeadline: 20 June 2024
Conferences
Special Issues
Special Issue in
Applied Sciences
Advances in Sustainable Materials for Engineering
Guest Editors: Richard Critchley, Rachael HazaelDeadline: 27 April 2024
Special Issue in
Applied Sciences
Hearing Loss: From Pathophysiology to Therapies and Habilitation
Guest Editors: Ronen Perez, Liat Kishon-RabinDeadline: 30 April 2024
Special Issue in
Applied Sciences
Oral and Systemic Implications of Periodontal Disease – an Integrated Approach
Guest Editor: Petra SurlinDeadline: 25 May 2024
Special Issue in
Applied Sciences
Functional Fermented Food Products II
Guest Editor: Pawel GlibowskiDeadline: 30 May 2024
Topical Collections
Topical Collection in
Applied Sciences
Structural Dynamics and Aeroelasticity
Collection Editors: Sergio Ricci, Paolo Mantegazza, Alessandro De Gaspari, Jonathan E. Cooper, Afzal Suleman, Hector Climent
Topical Collection in
Applied Sciences
Distributed Energy Systems
Collection Editor: Rodolfo Dufo-López
Topical Collection in
Applied Sciences
Intelligent Transportation Systems II: Beyond Intelligent Vehicles
Collection Editors: Javier Alonso Ruiz, Jeroen Ploeg, Angel Llamazares, Carlota Salinas, Rubén Izquierdo, Noelia Hernández Parra
Topical Collection in
Applied Sciences
Optical Design and Engineering
Collection Editors: Zhi-Ting Ye, Pin Han, Chun Hung Lai, Yi Chin Fang