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
Characteristics of Electric Field Induced by Oscillating Metal Underwater Vehicle
Appl. Sci. 2024, 14(7), 2873; https://doi.org/10.3390/app14072873 - 28 Mar 2024
Abstract
To analyze the induced electric field characteristics generated by the rotation and shaking of underwater metal vehicles, a mathematical model of the induced electric field generated by the underwater metal vehicles was derived using Faraday’s electromagnetic induction law. A mathematical model of the
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To analyze the induced electric field characteristics generated by the rotation and shaking of underwater metal vehicles, a mathematical model of the induced electric field generated by the underwater metal vehicles was derived using Faraday’s electromagnetic induction law. A mathematical model of the induced electric field on the electrode pairs of metal vehicles shaking in different coordinate system planes was established through in-depth analysis. Based on this, a three-component output model of the induced electric field output by the three-axis sensor was obtained when the measurement system was shaking at all three angles. At a constant speed, the induced electric field interference output by the measurement system is a static signal. The value of the static electric field is proportional to the vehicle’s speed and the value of the geomagnetic field, and the value of each component is related to the direction of movement and the value of the geomagnetic field component. The simulation results show that when the navigation body is moving at a constant speed, the induced electric field is a static electric field with a magnitude of mV/m. In a stable state, the induced electric field noise generated by changes in pitch, roll, and heading sway is at the nV/m level and does not have a significant impact on detection. The correctness of the theoretical model has been verified through experiments on offshore speedboat platforms, and it is feasible to use metal navigation bodies for ship electric field detection.
Full article
(This article belongs to the Section Marine Science and Engineering)
Open AccessArticle
Terahertz Time-Domain Spectroscopy of Blood Serum for Differentiation of Glioblastoma and Traumatic Brain Injury
by
Denis A. Vrazhnov, Daria A. Ovchinnikova, Tatiana V. Kabanova, Andrey G. Paulish, Yury V. Kistenev, Nazar A. Nikolaev and Olga P. Cherkasova
Appl. Sci. 2024, 14(7), 2872; https://doi.org/10.3390/app14072872 - 28 Mar 2024
Abstract
The possibility of the differentiation of glioblastoma from traumatic brain injury through blood serum analysis by terahertz time-domain spectroscopy and machine learning was studied using a small animal model. Samples of a culture medium and a U87 human glioblastoma cell suspension in the
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The possibility of the differentiation of glioblastoma from traumatic brain injury through blood serum analysis by terahertz time-domain spectroscopy and machine learning was studied using a small animal model. Samples of a culture medium and a U87 human glioblastoma cell suspension in the culture medium were injected into the subcortical brain structures of groups of mice referred to as the culture medium injection groups and glioblastoma groups, accordingly. Blood serum samples were collected in the first, second, and third weeks after the injection, and their terahertz transmission spectra were measured. The injection caused acute inflammation in the brain during the first week, so the culture medium injection group in the first week of the experiment corresponded to a traumatic brain injury state. In the third week of the experiment, acute inflammation practically disappeared in the culture medium injection groups. At the same time, the glioblastoma group subjected to a U87 human glioblastoma cell injection had the largest tumor size. The THz spectra were analyzed using two dimensionality reduction algorithms (principal component analysis and t-distributed Stochastic Neighbor Embedding) and three classification algorithms (Support Vector Machine, Random Forest, and Extreme Gradient Boosting Machine). Constructed prediction data models were verified using 10-fold cross-validation, the receiver operational characteristic curve, and a corresponding area under the curve analysis. The proposed machine learning pipeline allowed for distinguishing the traumatic brain injury group from the glioblastoma group with 95% sensitivity, 100% specificity, and 97% accuracy with the Extreme Gradient Boosting Machine. The most informative features for these groups’ differentiation were 0.37, 0.40, 0.55, 0.60, 0.70, and 0.90 THz. Thus, an analysis of mouse blood serum using terahertz time-domain spectroscopy and machine learning makes it possible to differentiate glioblastoma from traumatic brain injury.
Full article
(This article belongs to the Special Issue Spectroscopy Applications: New Frontiers in Complex Materials, Life Science and Technological Advances)
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Open AccessArticle
Impact of the Pre-Harvest Biocontrol Agent and Post-Harvest Massive Modified Atmosphere Packaging Application on Organic Table Grape (cv. ‘Allison’) Quality during Storage
by
Attilio Matera, Giuseppe Altieri, Francesco Genovese, Luciano Scarano, Giuseppe Genovese, Paola Pinto, Mahdi Rashvand, Hazem S. Elshafie, Antonio Ippolito, Annamaria Mincuzzi and Giovanni Carlo Di Renzo
Appl. Sci. 2024, 14(7), 2871; https://doi.org/10.3390/app14072871 - 28 Mar 2024
Abstract
The marketing value of table grapes is contingent upon several quality requirements, mostly related to microbial decay, sugar/acidity ratio, and colour. This research explores the impact of combining organic-cultured compatible techniques to delay disorders along with organic grape distribution in post-harvest. Aurebasidum pullulans
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The marketing value of table grapes is contingent upon several quality requirements, mostly related to microbial decay, sugar/acidity ratio, and colour. This research explores the impact of combining organic-cultured compatible techniques to delay disorders along with organic grape distribution in post-harvest. Aurebasidum pullulans in-field application on grape bunches at three growing stages as a biocontrol agent against grey mould growth coupled with massive modified atmosphere packaging (MMAP; 20% CO2, 10% O2) equipped with a breathable valve was tested. The in-field treatment had a significant impact on the colour and sugar content of the grapes at harvest and the mould count evolution during storage, whilst the trend of the other parameters was mainly affected by the interaction of the variables tested. The untreated batch experienced the worst behaviour and the packaging was paramount in preserving the moisture content and appearance of the bunches. The findings of this study may contribute to developing novel practices for setting a smart distribution of organic table grapes and reducing food waste.
Full article
(This article belongs to the Special Issue Innovative Technology in Food Analysis and Processing)
Open AccessArticle
Analysis of Underlapped Symmetrically Ported Valve-Controlled Asymmetric Cylinder Drive
by
Huankun Wang, Man Xu and Zijian Cao
Appl. Sci. 2024, 14(7), 2870; https://doi.org/10.3390/app14072870 - 28 Mar 2024
Abstract
The valve-controlled cylinder drive system is the most common type among hydraulic applications. Nonlinear behaviour in such systems is inevitable when the valve spool is around its null position. We utilised the component linking method to investigate the nonlinearities in a Moog valve-controlled
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The valve-controlled cylinder drive system is the most common type among hydraulic applications. Nonlinear behaviour in such systems is inevitable when the valve spool is around its null position. We utilised the component linking method to investigate the nonlinearities in a Moog valve-controlled asymmetric cylinder drive system by simulation in Fortran, in which a generalised concept is introduced and validated by comparing to the experimental results. An X factor is proposed in the generalised concept to describe the asymmetric cylinder state, which is a constant when the cylinder is extending or retracting, but numerically calculated when the valve spool is in the underlap region. This analytical solution is approximately 200 times more computationally efficient than the numerical solution method. This paper utilises the component linking method to simulate the Moog valve-controlled asymmetric cylinder drive system in Matlab Simulink, and proposes an analytical solution for the X factor when the valve spool is in the underlap region. This analytical solution is approximately 200 times more computationally efficient than the numerical solution method.
Full article
(This article belongs to the Special Issue Research Progress on Hydraulic Fluid and Hydraulic Systems)
Open AccessArticle
Unveiling the Biomechanical Insights: Motor Control Shifts Induced by Shoe Friction Adjustments and Their Impact on Defensive Slide, Crossover Dribbling, and Full Approach Jump in Basketball
by
Xiangdong Wang, Kezhun Cao, Yang Bai, Shutao Wei, Zongxiang Hu and Gongbing Shan
Appl. Sci. 2024, 14(7), 2869; https://doi.org/10.3390/app14072869 - 28 Mar 2024
Abstract
This study endeavors to explore the intricate interplay between the fundamental skills of basketball—defensive slide, crossover dribbling, and full approach jump—and the shoe outsole friction coefficient, with the overarching goal of advancing our comprehension regarding the pivotal role of footwear in athlete performance.
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This study endeavors to explore the intricate interplay between the fundamental skills of basketball—defensive slide, crossover dribbling, and full approach jump—and the shoe outsole friction coefficient, with the overarching goal of advancing our comprehension regarding the pivotal role of footwear in athlete performance. Employing a comprehensive methodology that integrates 3D motion capture, force platform dynamometry, and biomechanical modeling, the study seeks to quantify the inherent motor control intricacies associated with these fundamental skills. Data collection involved 12 varsity players, and the research systematically assesses the influence of the shoe friction coefficient on both skill quality and injury risk, utilizing a set of 13 parameters for evaluation. The findings unveil that, with an increased friction coefficient, the following changes occur: for the defensive slide, we observed decreased contact time (p < 0.05), boosted medio–lateral impulse (p < 0.05), and lowered ankle torque (p < 0.01); for crossover dribbling, we observed increased anterior–posterior impulse (p < 0.05) and ankle torque (p < 0.05); for the full approach jump, we observed decreased contact time (p < 0.05) and increased jump height (p < 0.05). Generally, the equal increment in the shoe outsole friction coefficient did not result in equal changes in the selected parameters of motor skill control, indicating a non-linear relationship between the performance quality of essential basketball skills and the shoe friction coefficient. The results suggest the potential existence of an optimal value for skill execution. Notably, the study identifies that, while an augmentation in the friction coefficient enhances specific skill aspects, there is a discernible saturation point, signifying diminishing returns. This investigation makes a substantial contribution to our understanding of the precise impacts of shoe friction coefficients on basketball skills, thereby prompting considerations for the judicious selection of optimal friction coefficients and advocating for possible personalized footwear recommendations based on individual biomechanical profiles.
Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
Open AccessArticle
Optimization Study of Water Interval Charge Structure Based on the Evaluation of Rock Damage Effect in Smooth Blasting
by
Sijie Wang, Min Gong, Haojun Wu, Xiaodong Wu and Xiangyu Liu
Appl. Sci. 2024, 14(7), 2868; https://doi.org/10.3390/app14072868 - 28 Mar 2024
Abstract
In tunnel smooth blasting, optimizing the water interval charging structure of peripheral holes is of great significance in improving the effect of smooth blasting and reducing the unit consumption of explosives. Addressing the issue of a single traditional evaluation standard, this paper proposes
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In tunnel smooth blasting, optimizing the water interval charging structure of peripheral holes is of great significance in improving the effect of smooth blasting and reducing the unit consumption of explosives. Addressing the issue of a single traditional evaluation standard, this paper proposes a composite index evaluation method for rock blasting damage in different zones, and the best charging structure is optimized according to the evaluation results. Taking Liyue Road Tunnel Light Smooth Blasting Project in Chongqing as the Research Background, the numeric models were established with ten kinds of charge structures, the charge structures and explosive quantity were optimized according to the evaluation results, and then the field tests were conducted. The results show that when the length of the water medium at the bottom of the hole is 20 cm, the damage range of the retained rock mass can be controlled while ensuring rock fragmentation. If the length of the water medium at the orifice and in the center of the hole is more than 30 cm, it will affect the superposition effect of the blast stress wave, resulting in under-excavation; in the preferred charge structure, the ratio of the length of the upper and lower explosives reaches 1:3, and the ratio of the length of the water medium is 2:2:1, which achieves a better rock-breaking effect in the field test.
Full article
(This article belongs to the Special Issue Smart Geotechnical Engineering)
Open AccessArticle
A Performance Evaluation Approach for Satellite Attitude Control System in Tracking Mode
by
Yanhua Zhang, Lei Yang, Yuehua Cheng and Kaixin Ying
Appl. Sci. 2024, 14(7), 2867; https://doi.org/10.3390/app14072867 - 28 Mar 2024
Abstract
The study of satellite performance evaluation can reveal the ability of satellite systems to fulfil corresponding tasks in the space environment, and provide information support for the resource allocation and mission scheduling of in-orbit satellites. In this paper, we took the satellite attitude
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The study of satellite performance evaluation can reveal the ability of satellite systems to fulfil corresponding tasks in the space environment, and provide information support for the resource allocation and mission scheduling of in-orbit satellites. In this paper, we took the satellite attitude control system in attitude tracking mode as the research object. In accordance with the system’s mission requirements, the control performance evaluation indicator set, characterized by a generalized grey number, is constructed to tackle the uncertainty and inadequacy of information contained in flight status data resulting from the complex space operating environment and sensor measurement noise. An improved principal component analysis method based on generalized grey number is proposed to solve the weight amplification caused by the correlation between performance indicators and realize the weight allocation of the indicators. Finally, the grey-target decision model is established to determine the weights of the performance indicators, and the performance evaluation model is established under the tracking mode. The feasibility of the grey-target decision-evaluation model based on the improved principal component is confirmed through comparative experiments.
Full article
(This article belongs to the Collection Space Applications)
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Open AccessArticle
Numerically Optimized Fourier Transform-Based Beamforming Accelerated by Neural Networks
by
Keivan Kaboutari, Abdelghafour Abraray and Stanislav Maslovski
Appl. Sci. 2024, 14(7), 2866; https://doi.org/10.3390/app14072866 - 28 Mar 2024
Abstract
Conventional beamforming methods for reconfigurable reflector antennas assume full control over the amplitude and phase of the reflected field. Here, we develop a novel beamforming methodology for reflecting Programmable Metasurfaces (PMS) with capacitive memory. Although utilizing such fully reactive PMS simplifies antenna design
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Conventional beamforming methods for reconfigurable reflector antennas assume full control over the amplitude and phase of the reflected field. Here, we develop a novel beamforming methodology for reflecting Programmable Metasurfaces (PMS) with capacitive memory. Although utilizing such fully reactive PMS simplifies antenna design and reduces energy consumption, the PMS reflection magnitude is unity and thus a global optimization of the reflection phases over the PMS unit cells is required in each beamforming scenario. We propose an implementation of such an optimization method rooted in the traditional Fourier transform-based beamforming and evaluate its performance. Additionally, we show that a pair of trained feed-forward neural networks (FFNN) with one input, one hidden, and one output layer can replace time-consuming global optimizations in the case of a PMS comprising unit cells. We train the FFNNs on a dataset obtained for typical single- and dual-beam beamforming scenarios. After training, the FFNNs perform requested beamforming tasks within a fraction of second and with about the same accuracy as the original optimization algorithm. The proposed methodology may find applications in future mobile telecommunication systems that require real-time beamforming on low-end hardware. The same beamforming methodology can be also employed in short-range wireless power transfer systems.
Full article
(This article belongs to the Special Issue New Trends in Antennas and Propagation: Theory, Material, Technology, and Applications for Future Systems)
Open AccessArticle
Hybrid-Margin Softmax for the Detection of Trademark Image Similarity
by
Chenyang Wang, Guangyuan Zheng and Hongtao Shan
Appl. Sci. 2024, 14(7), 2865; https://doi.org/10.3390/app14072865 - 28 Mar 2024
Abstract
The detection of image similarity is critical to trademark (TM) legal registration and court judgment on infringement cases. Meanwhile, there are great challenges regarding the annotation of similar pairs and model generalization on rapidly growing data when deep learning is introduced into the
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The detection of image similarity is critical to trademark (TM) legal registration and court judgment on infringement cases. Meanwhile, there are great challenges regarding the annotation of similar pairs and model generalization on rapidly growing data when deep learning is introduced into the task. The research idea of metric learning is naturally suited for the task where similarity of input is given instead of classification, but current methods are not targeted at the task and should be upgraded. To address these issues, loss-driven model training is introduced, and a hybrid-margin softmax (HMS) is proposed exactly based on the peculiarity of TM images. Two additive penalty margins are attached to the softmax to expand the decision boundary and develop greater tolerance for slight differences between similar TM images. With the HMS, a Siamese neural network (SNN) as the feature extractor is further penalized and the discrimination ability is improved. Experiments demonstrate that the detection model trained on HMS can make full use of small numbers of training data and has great discrimination ability on bigger quantities of test data. Meanwhile, the model can reach high performance with less depth of SNN. Extensive experiments indicate that the HMS-driven model trained completely on TM data generalized well on the face recognition (FR) task, which involves another type of image data.
Full article
(This article belongs to the Topic Computer Vision and Image Processing, 2nd Edition)
Open AccessArticle
Comparative Analysis of Local Differential Privacy Schemes in Healthcare Datasets
by
Andres Hernandez-Matamoros and Hiroaki Kikuchi
Appl. Sci. 2024, 14(7), 2864; https://doi.org/10.3390/app14072864 - 28 Mar 2024
Abstract
In the rapidly evolving landscape of healthcare technology, the critical need for robust privacy safeguards is undeniable. Local Differential Privacy (LDP) offers a potential solution to address privacy concerns in data-rich industries. However, challenges such as the curse of dimensionality arise when dealing
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In the rapidly evolving landscape of healthcare technology, the critical need for robust privacy safeguards is undeniable. Local Differential Privacy (LDP) offers a potential solution to address privacy concerns in data-rich industries. However, challenges such as the curse of dimensionality arise when dealing with multidimensional data. This is particularly pronounced in k-way joint probability estimation, where higher values of k lead to decreased accuracy. To overcome these challenges, we propose the integration of Bayesian Ridge Regression (BRR), known for its effectiveness in handling multicollinearity. Our approach demonstrates robustness, manifesting a noteworthy reduction in average variant distance when compared to baseline algorithms such as LOPUB and LOCOP. Additionally, we leverage the R-squared metric to highlight BRR’s advantages, illustrating its performance relative to LASSO, as LOPUB and LOCOP are based on it. This paper addresses a relevant concern related to datasets exhibiting high correlation between attributes, potentially allowing the extraction of information from one attribute to another. We convincingly show the superior performance of BRR over LOPUB and LOCOP across 15 datasets with varying average correlation attributes. Healthcare takes center stage in this collection of datasets. Moreover, the datasets explore diverse fields such as finance, travel, and social science. In summary, our proposed approach consistently outperforms the LOPUB and LOCOP algorithms, particularly when operating under smaller privacy budgets and with datasets characterized by lower average correlation attributes. This signifies the efficacy of Bayesian Ridge Regression in enhancing privacy safeguards in healthcare technology.
Full article
(This article belongs to the Special Issue Data Privacy and Security for Information Engineering)
Open AccessArticle
Determining Steady-State Operation Criteria Using Transient Performance Modelling and Steady-State Diagnostics
by
Konstantinos Mathioudakis, Nikolaos Aretakis and Alexios Alexiou
Appl. Sci. 2024, 14(7), 2863; https://doi.org/10.3390/app14072863 - 28 Mar 2024
Abstract
Data from the steady-state operation of gas turbine engines are used in gas path diagnostic procedures. A method to identify steady-state operation is thus required. This paper initially explains and demonstrates the factors that cause a deviation in engine health when transient data
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Data from the steady-state operation of gas turbine engines are used in gas path diagnostic procedures. A method to identify steady-state operation is thus required. This paper initially explains and demonstrates the factors that cause a deviation in engine health when transient data are used for diagnosis and shows that there is a threshold in the slope of time traces, below which the variation in engine health parameters is acceptable. A methodology for deriving a criterion for steady-state operation based on actual flight data is then presented. The slope of the exhaust gas temperature variation with time and the size of its time-series window, from which this slope is determined, are the required parameters that must be specified when applying this criterion. It is found that the values of these parameters must be selected so that a sufficient number of steady-state points are available without compromising the accuracy of the diagnostic procedure.
Full article
(This article belongs to the Special Issue Advanced Technologies in Rotating Machinery: Design, Modeling, Manufacturing, Testing, and Operation)
Open AccessArticle
The Efficacy of a Cosmetic Preparation Containing Sheep Colostrum on Mature Skin: A Randomized Placebo-Controlled Double-Blind Study
by
Kinga Kazimierska, Anna Erkiert-Polguj and Urszula Kalinowska-Lis
Appl. Sci. 2024, 14(7), 2862; https://doi.org/10.3390/app14072862 - 28 Mar 2024
Abstract
Colostrum, the first milk produced by mammals, is rich in various bioactive components that provide numerous health benefits to newborns, such as growth factors, hormones, immunoglobulins, cytokines, and enzymes. Topical application of bovine or equine colostrum has been found to improve regeneration, accelerate
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Colostrum, the first milk produced by mammals, is rich in various bioactive components that provide numerous health benefits to newborns, such as growth factors, hormones, immunoglobulins, cytokines, and enzymes. Topical application of bovine or equine colostrum has been found to improve regeneration, accelerate cutaneous wound healing, and have moisturizing, protective, and anti-aging properties. The aim of this study was to examine the effect of a cosmetic preparation containing sheep colostrum on skin with signs of aging in mature women. Fifty-two women, aged 40–70, were randomized into two groups to receive either colostrum or placebo cream. The participants applied the cream for eight weeks. Skin hydration, TEWL, sebum, erythema, and tone were measured using a standardized Courage + Khazaka electronic GmbH Multi Probe Adapter; skin elasticity was measured with a cutometer, and images were taken by FotoMedicus. The treatment increased skin moisture, reduced TEWL, and improved skin firmness. These findings were confirmed by the subjective survey. The participants reported, inter alia, improved skin softness and less redness and hypersensitivity. Sheep colostrum cream was more effective at improving skin conditions than placebo cream. Colostrum creams can improve certain aspects of skin quality, especially the hydrolipid barrier, and overall rejuvenation.
Full article
(This article belongs to the Special Issue Development of Innovative Cosmetics)
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Open AccessArticle
External Workload Evolution and Comparison across a Pre-Season in Belgian Professional Football Players: A Pilot Study
by
Moisés Falces-Prieto, Luis Manuel Martínez-Aranda, Javier Iglesias-García, Samuel López-Mariscal and Javier Raya-González
Appl. Sci. 2024, 14(7), 2861; https://doi.org/10.3390/app14072861 - 28 Mar 2024
Abstract
The pre-season plays a crucial role in the preparation of professional football players, as it allows for an extensive focus on training sessions compared to the more congested schedules during the in-season period, especially in professional football leagues. This study aimed to describe
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The pre-season plays a crucial role in the preparation of professional football players, as it allows for an extensive focus on training sessions compared to the more congested schedules during the in-season period, especially in professional football leagues. This study aimed to describe the workload during a 6-week pre-season in Belgian professional football players and to analyse and compare the workloads for players in each microcycle according to several variables of external workload (e.g., distance covered at some velocities). Seventeen male Belgian professional football players competing in the second division of the Belgian league system participated in the study. Throughout the 6 weeks, the players were closely monitored during both training sessions and friendly matches using Global Positioning System (GPS) devices. Several parameters, including total distance covered and distance at different velocities, were recorded. Accelerating and decelerating distances, as well as the number of sprints, were also captured. Statistical analysis was based on a repeated measures ANOVA, percentage dynamics, and effect size calculations. The results obtained showed a progressive increase in the distance travelled at different intensities from week 1 (i.e., lower values) to week 3 (i.e., higher values), with reductions in these values in week 6, prior to the start of the official competition. Similarly, the peak of accelerations and decelerations were observed in week 2 and week 3, with decrements at the end of the pre-season period. This comprehensive investigation attempts to shed light on the effects and dynamic changes in external workload during the crucial pre-season, contributing valuable insights for coaches and practitioners in football conditioning and training programs, especially concerning optimal preparation for the beginning of the league’s season.
Full article
(This article belongs to the Special Issue Assessment, Control and Monitoring of Physical Activity and Sports Training)
Open AccessArticle
Field Reconnaissance and Earthquake Vulnerability of the RC Buildings in Adıyaman during 2023 Türkiye Earthquakes
by
Ercan Işık, Fatih Avcil, Rabia İzol, Aydın Büyüksaraç, Hüseyin Bilgin, Ehsan Harirchian and Enes Arkan
Appl. Sci. 2024, 14(7), 2860; https://doi.org/10.3390/app14072860 - 28 Mar 2024
Abstract
The 6th February 2023 Pazarcık and Elbistan earthquakes (Mw = 7.7 and Mw = 7.6) caused great destruction in many cities and were the disaster of the century for Türkiye. The greatest destruction was caused in the provinces of Hatay, Kahramanmaraş,
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The 6th February 2023 Pazarcık and Elbistan earthquakes (Mw = 7.7 and Mw = 7.6) caused great destruction in many cities and were the disaster of the century for Türkiye. The greatest destruction was caused in the provinces of Hatay, Kahramanmaraş, and Adıyaman during these earthquakes, which were independent of each other and occurred on the same day. Information about earthquakes and strong ground motion records is given within the scope of this study. Reinforced concrete (RC) structures which constitute a large part of the urban building stock in the earthquake region were exposed to structural damage at different levels. The structural damage in the RC structures in the city center, Gölbaşı, and Kahta districts of the province of Adıyaman was evaluated within the scope of earthquake and civil engineering after field investigations. Insufficient RC, low-strength concrete reinforcement problems, RC frame failure, heavy overhang, short columns, soft story, and pounding effect are the main causes of the earthquake damage. The presence of these factors that reduce the earthquake resistance of RC structures increased the damage level. In addition, the fact that the earthquakes occurred nine hours apart and the continuation of aftershocks during that period negatively affected the damage levels. It has been observed that structures that receive the necessary engineering services during the construction and project phases ensure the safety of life and property, even if the structure is slightly damaged. In this study, we also tried to reveal whether the target displacements were satisfactorily represented by numerical analysis for a sample RC structure.
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(This article belongs to the Special Issue Earthquake Engineering and Seismic Risk)
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Open AccessArticle
Time of Flight Distance Sensor–Based Construction Equipment Activity Detection Method
by
Young-Jun Park and Chang-Yong Yi
Appl. Sci. 2024, 14(7), 2859; https://doi.org/10.3390/app14072859 - 28 Mar 2024
Abstract
In this study, we delve into a novel approach by employing a sensor-based pattern recognition model to address the automation of construction equipment activity analysis. The model integrates time of flight (ToF) sensors with deep convolutional neural networks (DCNNs) to accurately classify the
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In this study, we delve into a novel approach by employing a sensor-based pattern recognition model to address the automation of construction equipment activity analysis. The model integrates time of flight (ToF) sensors with deep convolutional neural networks (DCNNs) to accurately classify the operational activities of construction equipment, focusing on piston movements. The research utilized a one-twelfth-scale excavator model, processing the displacement ratios of its pistons into a unified dataset for analysis. Methodologically, the study outlines the setup of the sensor modules and their integration with a controller, emphasizing the precision in capturing equipment dynamics. The DCNN model, characterized by its four-layered convolutional blocks, was meticulously tuned within the MATLAB environment, demonstrating the model’s learning capabilities through hyperparameter optimization. An analysis of 2070 samples representing six distinct excavator activities yielded an impressive average precision of 95.51% and a recall of 95.31%, with an overall model accuracy of 95.19%. When compared against other vision-based and accelerometer-based methods, the proposed model showcases enhanced performance and reliability under controlled experimental conditions. This substantiates its potential for practical application in real-world construction scenarios, marking a significant advancement in the field of construction equipment monitoring.
Full article
(This article belongs to the Topic Applications in Image Analysis and Pattern Recognition)
Open AccessArticle
Corn Cropping Systems in Agricultural Soils from the Bajio Region of Guanajuato: Soil Quality Indexes (SQIs)
by
Alejandra Sánchez-Guzmán, Héctor Iván Bedolla-Rivera, Eloy Conde-Barajas, María de la Luz Xochilt Negrete-Rodríguez, Marcos Alfonso Lastiri-Hernández, Francisco Paúl Gámez-Vázquez and Dioselina Álvarez-Bernal
Appl. Sci. 2024, 14(7), 2858; https://doi.org/10.3390/app14072858 - 28 Mar 2024
Abstract
Agriculture is a sector of great importance for Mexico’s economy, generating employment and contributing significantly to the country’s gross domestic product. The Bajio stands out as one of the most productive agricultural regions in Mexico. However, intensive agricultural practices in this area have
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Agriculture is a sector of great importance for Mexico’s economy, generating employment and contributing significantly to the country’s gross domestic product. The Bajio stands out as one of the most productive agricultural regions in Mexico. However, intensive agricultural practices in this area have caused a progressive deterioration and loss of soil fertility. This study focused on evaluating the quality of soils used for agriculture in the Bajio region of the State of Guanajuato, Mexico. This evaluation, utilised soil quality indexes (SQIs) based on a total of 27 physicochemical, biological and enzymatic indicators. These indicators were selected by means of a principal component analysis (PCA), which allowed for the identification of a minimum set of data. The SQIs developed in this study categorised soils into different quality levels, ranging from low to high, mainly based on the values observed in the biological indicators (SMR and qCO2), which comprised the established SQIs. The inclusion of these biological indicators provides the developed SQIs with greater sensitivity to detect minor disturbances in agricultural soils due to human activity, compared with SQIs consisting only of physicochemical indicators. The developed SQIs can be used to ensure high-quality food production in soils used for corn cultivation under similar conditions, both nationally and internationally.
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(This article belongs to the Section Environmental Sciences)
Open AccessArticle
How Pseudomonas nitroreducens Passivates Cadmium to Inhibit Plant Uptake
by
Yakui Chen, Yongquan Yu, Xiaoyu Fang, Yinhuan Zhou and Diannan Lu
Appl. Sci. 2024, 14(7), 2857; https://doi.org/10.3390/app14072857 - 28 Mar 2024
Abstract
Cadmium (Cd) has been widely used in industry applications, leading to water and soil contamination. This study investigated the potential ability of Pseudomonas nitroreducens (11830) to perform the biosorption of cadmium from aqueous solution and soil. The biosorption characteristics were described using equilibrium
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Cadmium (Cd) has been widely used in industry applications, leading to water and soil contamination. This study investigated the potential ability of Pseudomonas nitroreducens (11830) to perform the biosorption of cadmium from aqueous solution and soil. The biosorption characteristics were described using equilibrium isotherm and kinetic studies. The Langmuir adsorption isotherm indicated a better fit with the experimental data (R2 = 0.980), with a maximum capacity of 160.51 mg/g at 30 °C in an initial aqueous solution of 300 mg/L Cd2+. The experiments followed a pseudo-second-order kinetics model (R2 > 0.99), especially at a low initial concentration. The biosorption mechanisms involved were determined through scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive spectroscopy (EDS) and protein analysis. The SEM and TEM figures showed that the morphology of cells changed before and after the adsorption of Cd, and the EDS confirmed that Cd was absorbed on the surface of the cell. The analysis of proteins indicated that the protein species increased after the stimulation of Cd, which further confirmed the biosorption mechanism. A pot experiment confirmed that 11830 could passivate the cadmium in soil and reduce its uptake and utilization by Houttuynia cordata Thunb (H. cordata). This work demonstrates the potential application of microorganisms in inhibiting the accumulation of Cd in crops.
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(This article belongs to the Special Issue Environmental Pollution and Bioremediation Technology)
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Using Integrated Multi-Omics to Explore the Differences in the Three Developmental Stages of Thelephora ganbajun Zang
by
Zihan Zhang, Hongzhen Gai and Tao Sha
Appl. Sci. 2024, 14(7), 2856; https://doi.org/10.3390/app14072856 - 28 Mar 2024
Abstract
Thelephora ganbajun Zang, a rare wild macrofungus, has significant culinary and medicinal value. However, it also has a high cost attributed to its inability to achieve artificial cultivation and its strict environmental requirements. To reveal the intricacies of its development, we conducted a
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Thelephora ganbajun Zang, a rare wild macrofungus, has significant culinary and medicinal value. However, it also has a high cost attributed to its inability to achieve artificial cultivation and its strict environmental requirements. To reveal the intricacies of its development, we conducted a comprehensive analysis of the proteome and metabolome in three pivotal developmental stages: the mycelium, the primordium, and the fruiting body. In our investigation, genes exhibiting various expression levels across multi-omics analyses were identified as potential candidates implicated in growth, development, or metabolic regulation. The aim of this study was to provide a clearer direction for understanding the fundamental metabolic activities and growth stages of this species. Label-free proteomic sequencing revealed a critical juncture in ectomycorrhiza formation, particularly during the transition from the mycelium to the primordium. Secreted proteins, signaling proteins, membrane proteins, and proteins with unidentified functions were rapidly synthesized, with certain amino acids contributing to the synthesis of proteins involved in signaling pathways or hormone precursor substances. In the metabolomics analysis, the classification of secondary metabolites revealed a noteworthy increase in lipid substances and organic acids, contributing to cell activity. The early mycelial development stage exhibited vigorous cell metabolism, contrasting with a decline in cell division activity during fruiting body formation. In our findings, the integration of metabolomic and transcriptomic data highlighted the potential key role of folate biosynthesis in regulating early ectomycorrhiza development. Notably, the expression of alkaline phosphatase and dihydrofolate synthase genes within this pathway was significantly up-regulated in the mycelium and fruiting body stages but down-regulated in the primordium stage. This regulation primarily influences dihydrofolate reductase activity and B vitamin synthesis.
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Open AccessArticle
An Extremely Close Vibration Frequency Signal Recognition Using Deep Neural Networks
by
Mentari Putri Jati, Muhammad Irfan Luthfi, Cheng-Kai Yao, Amare Mulatie Dehnaw, Yibeltal Chanie Manie and Peng-Chun Peng
Appl. Sci. 2024, 14(7), 2855; https://doi.org/10.3390/app14072855 - 28 Mar 2024
Abstract
This study proposes the utilization of an optical fiber vibration sensor for detecting the superposition of extremely close frequencies in vibration signals. Integration of deep neural networks (DNN) proves to be meaningful and efficient, eliminating the need for signal analysis methods involving complex
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This study proposes the utilization of an optical fiber vibration sensor for detecting the superposition of extremely close frequencies in vibration signals. Integration of deep neural networks (DNN) proves to be meaningful and efficient, eliminating the need for signal analysis methods involving complex mathematical calculations and longer computation times. Simulation results of the proposed model demonstrate the remarkable capability to accurately distinguish frequencies below 1 Hz. This underscores the effectiveness of the proposed image-based vibration signal recognition system embedded in DNN as a streamlined yet highly accurate method for vibration signal detection, applicable across various vibration sensors. Both simulation and experimental evaluations substantiate the practical applicability of this integrated approach, thereby enhancing electric motor vibration monitoring techniques.
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(This article belongs to the Special Issue Machine Learning in Vibration and Acoustics 2.0)
Open AccessArticle
A Numerical Bio-Geotechnical Model of Pressure-Responsive Microbially Induced Calcium Carbonate Precipitation
by
Jianye Wang, Helen Mitrani, Anil Wipat, Polly Moreland, Jamie Haystead, Meng Zhang and Martyn Dade Robertson
Appl. Sci. 2024, 14(7), 2854; https://doi.org/10.3390/app14072854 - 28 Mar 2024
Abstract
The employment of Microbially Induced Calcium Carbonate Precipitation (MICP) is of increasing interest as a technique for environmentally sustainable soil stabilisation. Recent advancements in synthetic biology have allowed for the conception of a pressure-responsive MICP process, wherein bacteria are engineered to sense environmental
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The employment of Microbially Induced Calcium Carbonate Precipitation (MICP) is of increasing interest as a technique for environmentally sustainable soil stabilisation. Recent advancements in synthetic biology have allowed for the conception of a pressure-responsive MICP process, wherein bacteria are engineered to sense environmental loads, thereby offering the potential to stabilise specific soil regions selectively. In this study, a 2D smart bio-geotechnical model is proposed based on a pressure-responsive MICP system. Experimentally obtained pressure-responsive genes and hypothetical genes with different pressure responses were applied in the model and two soil profiles were evaluated. The resulting model bridges scales from gene expression within bacteria cells to geotechnical simulations. The results show that both strata and gene expression–pressure relationships have a significant influence on the distribution pattern of calcium carbonate precipitation within the soil matrix. Among the evaluated experimental genes, Gene A demonstrates the best performance in both of the two soil profiles due to the effective stabilisation in the centre area beneath the load, while Genes B and C are more effective in reinforcing peripheral regions. Furthermore, when the hypothetical genes are utilised, there is an increasing stabilisation area with a decreased threshold value. The results show that the technique can be used for soil reinforcement in specific areas.
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(This article belongs to the Special Issue Smart Geotechnical Engineering)
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