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 many other databases.
- Journal Rank: JCR - Q2 (Engineering, Multidisciplinary) / CiteScore - Q2 (General Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 13.8 days after submission; acceptance to publication is undertaken in 3.5 days (median values for papers published in this journal in the first half of 2021).
- 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.
- Companion journals for Applied Sciences include: Applied Nano, Osteology, Nutraceuticals, AppliedChem and Applied Biosciences.
Impact Factor:
2.679 (2020)
;
5-Year Impact Factor:
2.736 (2020)
Latest Articles
Probabilistic and Semi-Probabilistic Analysis of Slender Columns Frequently Used in Structural Engineering
Appl. Sci. 2021, 11(17), 8009; https://doi.org/10.3390/app11178009 (registering DOI) - 30 Aug 2021
Abstract
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The stability of slender columns is a topic that has been dealt with in research and practice for many years. The importance of this topic also increases with the possibility of using non-linear modeling approaches to determine the stability and with the increasingly
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The stability of slender columns is a topic that has been dealt with in research and practice for many years. The importance of this topic also increases with the possibility of using non-linear modeling approaches to determine the stability and with the increasingly complex safety formats. In order to show the complexity and the variability associated with the non-linear models, two previous contributions discussed and compared (a) the results of the Round Robin Non-Linear Modeling, and (b) the existing international associated standard specifications and safety concepts with respect to experimental results. The aim herein is to determine the reliability level (safety index) on the basis of these investigations and findings and to examine the existing safety formats of classical and extended probabilistic analyses and to derive any necessary adjustments. In addition, the method of the safety format Estimation of Coefficient of Variance of resistance (ECOV) is used for the determination of the global safety resistance factors based on the non-linear analyses’ findings of the Round Robin modeling partners.
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Open AccessArticle
Piezoelectric Silicon Micropump for Drug Delivery Applications
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, , , , , and
Appl. Sci. 2021, 11(17), 8008; https://doi.org/10.3390/app11178008 (registering DOI) - 30 Aug 2021
Abstract
Subcutaneous injection is crucial for the treatment of many diseases. Especially for regular or continuous injections, automated dosing is beneficial. However, existing devices are large, uncomfortable, visible under clothing, or interfere with physical activity. Thus, the development of small, energy efficient and reliable
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Subcutaneous injection is crucial for the treatment of many diseases. Especially for regular or continuous injections, automated dosing is beneficial. However, existing devices are large, uncomfortable, visible under clothing, or interfere with physical activity. Thus, the development of small, energy efficient and reliable patch pumps or implantable systems is necessary and research on microelectromechanical system (MEMS) based drug delivery devices has gained increasing interest. However, the requirements of medical applications are challenging and especially the dosing precision and reliability of MEMS pumps are not yet sufficiently evaluated. To enable further miniaturization, we propose a precise 5 × 5 mm2 silicon micropump. Detailed experimental evaluation of ten pumps proves a backpressure capability with air of 12.5 ± 0.8 kPa, which indicates the ability to transport bubbles. The maximal water flow rate is 74 ± 6 µL/min and the pumps’ average blocking pressure is 51 kPa. The evaluation of the dosing precision for bolus deliveries with water and insulin shows a high repeatability of dosed package volumes. The pumps show a mean standard deviation of only 0.02 mg for 0.5 mg packages, and therefore, stay below the generally accepted 5% deviation, even for this extremely small amount. The high precision enables the combination with higher concentrated medication and is the foundation for the development of an extremely miniaturized patch pump.
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(This article belongs to the Special Issue Development of Microfluidic Devices for Medical Applications)
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Open AccessArticle
Analysis of Harassment Complaints to Detect Witness Intervention by Machine Learning and Soft Computing Techniques
Appl. Sci. 2021, 11(17), 8007; https://doi.org/10.3390/app11178007 - 29 Aug 2021
Abstract
This research is aimed to analyze textual descriptions of harassment situations collected anonymously by the Hollaback! project. Hollaback! is an international movement created to end harassment in all of its forms. Its goal is to collect stories of harassment through the web and
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This research is aimed to analyze textual descriptions of harassment situations collected anonymously by the Hollaback! project. Hollaback! is an international movement created to end harassment in all of its forms. Its goal is to collect stories of harassment through the web and a free app all around the world to elevate victims’ individual voices to find a societal solution. Hollaback! pretends to analyze the impact of a bystander during a harassment in order to launch a public awareness-raising campaign to equip everyday people with tools to undo harassment. Thus, the analysis presented in this paper is a first step in Hollaback!’s purpose: the automatic detection of a witness intervention inferred from the victim’s own report. In a first step, natural language processing techniques were used to analyze the victim’s free-text descriptions. For this part, we used the whole dataset with all its countries and locations. In addition, classification models, based on machine learning and soft computing techniques, were developed in the second part of this study to classify the descriptions into those that have bystander presence and those that do not. For this machine learning part, we selected the city of Madrid as an example, in order to establish a criterion of the witness behavior procedure.
Full article
(This article belongs to the Special Issue Current Technologies in Fairness, Transparency, Security and Safety: Methods, Applications and Challenges)
Open AccessArticle
Hybrid Structure of a ZnO Nanowire Array on a PVDF Nanofiber Membrane/Nylon Mesh for use in Smart Filters: Photoconductive PM Filters
Appl. Sci. 2021, 11(17), 8006; https://doi.org/10.3390/app11178006 - 29 Aug 2021
Abstract
A nanofiber membrane with a high surface-to-volume ratio has advantages in applications such as those used for particulate matter filtration and gas detection. To maximize the potentials of the membrane structure, recent research has been attempted to control nanofiber geometries. In this paper,
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A nanofiber membrane with a high surface-to-volume ratio has advantages in applications such as those used for particulate matter filtration and gas detection. To maximize the potentials of the membrane structure, recent research has been attempted to control nanofiber geometries. In this paper, surface modification of a nanofiber membrane with a metal/ceramic nanostructure is performed to improve multi-functional filter performance, enhancing fine particle filtration and toxic gas absorption. Here, a smart filter is fabricated by electrospinning polyvinylidene difluoride (PVDF) nanofiber onto a nylon mesh and hydrothermal synthesis of ZnO nanoparticles onto a nanowire array on a PVDF nanofiber surface. On the ZnO nanowires–PVDF nanofiber layer filter, the pressure difference (ΔP = 4.13 kPa) is higher than the pure PVDF nanofiber layer. However, the filtration efficiency is 94.3% for a 0.3 μm particle size, which is higher than that of other sizes. Additionally, a ZnO nanowire array with high density on a PVDF nanofiber layer affects sensitivity (S = 39.37), with high resolution. The photocurrent characteristics of a smart filter have the potential for a photo-assisted redox reaction to detect toxic polar molecules in continuous airflow in real-time in indoor environments.
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(This article belongs to the Special Issue Advances of Electrospun Nanofibers, Nanocomposites and Microparticles)
Open AccessFeature PaperArticle
High Strain Rate Properties of Various Forms of Ti6Al4V(ELI) Produced by Direct Metal Laser Sintering
Appl. Sci. 2021, 11(17), 8005; https://doi.org/10.3390/app11178005 - 29 Aug 2021
Abstract
For analysis of engineering structural materials to withstand harsh environmental conditions, accurate knowledge of properties such as flow stress and failure over conditions of high strain rate and temperature plays an essential role. Such properties of additively manufactured Ti6Al4V(ELI) are not adequately studied.
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For analysis of engineering structural materials to withstand harsh environmental conditions, accurate knowledge of properties such as flow stress and failure over conditions of high strain rate and temperature plays an essential role. Such properties of additively manufactured Ti6Al4V(ELI) are not adequately studied. This paper documents an investigation of the high strain rate and temperature properties of different forms of heat-treated Ti6Al4V(ELI) samples produced by the direct metal laser sintering (DMLS). The microstructure and texture of the heat-treated samples were analysed using a scanning electron microscope (SEM) equipped with an electron backscatter diffraction detector for electron backscatter diffraction (EBSD) analysis. The split Hopkinson pressure bar (SHPB) equipment was used to carry out tests at strain rates of 750, 1500 and 2450 s−1, and temperatures of 25, 200 and 500 °C. The heat-treated samples of DMLS Ti6Al4V(ELI) alloys tested here were found to be sensitive to strain rate and temperature. At most strain rates and temperatures, the samples with finer microstructure exhibited higher dynamic strength and lower strain, while the dynamic strength and strain were lower and higher, respectively, for samples with coarse microstructure. The cut surfaces of the samples tested were characterised by a network of well-formed adiabatic shear bands (ASBs) with cracks propagating along them. The thickness of these ASBs varied with the strain rate, temperature, and various alloy forms.
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(This article belongs to the Special Issue Metal Plasticity at High Strain Rate)
Open AccessArticle
Implications of Permanent Teeth Dimensions and Arch Lengths on Dental Crowding during the Mixed Dentition Period
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, , , , , , and
Appl. Sci. 2021, 11(17), 8004; https://doi.org/10.3390/app11178004 - 29 Aug 2021
Abstract
Dento-alveolar disharmony with crowding is a common reason for orthodontic treatment with not fully understood or unequivocally demonstrated causes. This study investigated the correlations between teeth dimensions, arch lengths, and crowding during the mixed dentition period. A cross-sectional study on 100 dental casts
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Dento-alveolar disharmony with crowding is a common reason for orthodontic treatment with not fully understood or unequivocally demonstrated causes. This study investigated the correlations between teeth dimensions, arch lengths, and crowding during the mixed dentition period. A cross-sectional study on 100 dental casts of patients with class I malocclusions was performed. Dental arches were classified as non-crowded, moderately crowded, severely crowded, and spaced. The mesio-distal widths, bucco-lingual sizes, and crown proportions of permanent teeth were assessed. The results indicated that arch length measurements showed smaller values in crowded arches. The mesio-distal dimensions of upper central incisors and lower lateral incisors were larger in patients with crowding. The bucco-lingual dimensions of upper incisors were decreased, the bucco-lingual dimensions of lower central incisors and permanent first molars were increased in crowded arches. Upper incisors and lower lateral incisors presented larger crown proportions in crowding cases. Low negative correlations were found between mesio-distal diameters of maxillary central incisors, lower lateral incisors, lower permanent first molars, and the values of arch space discrepancies. In conclusion, crowding in the mixed dentition could be associated with reduced arch lengths, increase in mesio-distal sizes of incisors and lower permanent first molars, and variations of bucco-lingual dimensions and crown proportions of incisors and lower permanent first molars.
Full article
(This article belongs to the Section Applied Dentistry)
Open AccessArticle
Defrosting of Air-Source Heat Pumps: Effect of Real Temperature Data on Seasonal Energy Performance for Different Locations in Italy
Appl. Sci. 2021, 11(17), 8003; https://doi.org/10.3390/app11178003 - 29 Aug 2021
Abstract
In this paper, dynamic simulations of the seasonal coefficient of performance (SCOP) of Air-Source Heat Pumps will be presented by considering three different heat pump systems coupled with the same building located in three different Italian municipalities: S. Benedetto del Tronto (42°58′ North,
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In this paper, dynamic simulations of the seasonal coefficient of performance (SCOP) of Air-Source Heat Pumps will be presented by considering three different heat pump systems coupled with the same building located in three different Italian municipalities: S. Benedetto del Tronto (42°58′ North, 13°53′ East), Milan (45°28′ North, 9°10′ East), and Livigno (46°28′ North, 10°8′ East). Dynamic simulations were conducted by employing the software package TRNSYS and by considering real weather data (i.e., outdoor air temperature and humidity as well as solar radiation) referring to the three abovementioned cities for a period of 8 years (2013–2020) and collected from on-site weather stations. Attention has been paid to the modeling of the heat pump defrost cycles in order to evaluate their influence on the unit’s seasonal performance. Results show that, when referring to different years, the thermal energy demand displays huge variations (in some cases it can even double its value), while the effective SCOP is characterized by scarce variability. Sensible variations in SCOP values are achieved for Livigno.
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Open AccessArticle
Optimization of Neural Network-Based Self-Tuning PID Controllers for Second Order Mechanical Systems
by
and
Appl. Sci. 2021, 11(17), 8002; https://doi.org/10.3390/app11178002 - 29 Aug 2021
Abstract
The feasibility of a neural network method was discussed in terms of a self-tuning proportional–integral–derivative (PID) controller. The proposed method was configured with two neural networks to dramatically reduce the number of tuning attempts with a practically achievable small amount of data acquisition.
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The feasibility of a neural network method was discussed in terms of a self-tuning proportional–integral–derivative (PID) controller. The proposed method was configured with two neural networks to dramatically reduce the number of tuning attempts with a practically achievable small amount of data acquisition. The first network identified the target system from response data, previous PID parameters, and response characteristics. The second network recommended PID parameters based on the results of the first network. The results showed that it could recommend PID parameters within 2 s of observing responses. When the number of trained data was as low as 1000, the performance efficiency of these methods was 92.9%, and the tuning was completed in an average of 2.94 attempts. Additionally, the robustness of these methods was determined by considering a system with noise or a situation when the target position was modified. These methods are also applicable for traditional PID controllers, thus enabling conservative industries to continue using PID controllers.
Full article
(This article belongs to the Section Mechanical Engineering)
Open AccessArticle
Reducing Forecast Errors of a Regional Climate Model Using Adaptive Filters
Appl. Sci. 2021, 11(17), 8001; https://doi.org/10.3390/app11178001 - 29 Aug 2021
Abstract
In this work, the use of adaptive filters for reducing forecast errors produced by a Regional Climate Model (RCM) is investigated. Seasonal forecasts are compared against the reanalysis data provided by the National Centers for Environmental Prediction. The reanalysis is used to train
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In this work, the use of adaptive filters for reducing forecast errors produced by a Regional Climate Model (RCM) is investigated. Seasonal forecasts are compared against the reanalysis data provided by the National Centers for Environmental Prediction. The reanalysis is used to train adaptive filters based on the Recursive Least Squares algorithm in order to reduce the forecast error. The K-means unsupervised learning algorithm is used to obtain the number of filters to employ from the climate variables. The proposed approach is applied to some climate variables such as the meridional wind, zonal wind, and the geopotential height. The forecast is produced by the Eta RCM at 40-km resolution in a domain covering most of Brazil. Results show that the proposed approach is capable of reducing the forecast errors, according to evaluation metrics such as normalized mean square error, maximum absolute error, and maximum normalized absolute error, thus improving the seasonal climate forecasts.
Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessArticle
pH Measurement of Cement-Based Materials: The Effect of Particle Size
Appl. Sci. 2021, 11(17), 8000; https://doi.org/10.3390/app11178000 - 29 Aug 2021
Abstract
Healthy reinforced concrete should be highly alkaline to safeguard the passive protective film for reinforcement of steel bars against corrosion. pH measurement is gaining importance in research of cement-based materials (CBMs), such as paste, mortar and concrete, as well as in structural health
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Healthy reinforced concrete should be highly alkaline to safeguard the passive protective film for reinforcement of steel bars against corrosion. pH measurement is gaining importance in research of cement-based materials (CBMs), such as paste, mortar and concrete, as well as in structural health monitoring and forensic engineering applications. However, insufficient information is available regarding the most practical, economical and applicable quantitative pH measurement method for CBMs from the sampling to measurement stage. Existing recommended methods for measuring pH have many variables that need to be investigated to determine how they influence the pH value. Samples were recommended to be ground into very fine particles for pH measurement. Preparing very fine particles of CBMs is costly and time consuming, while larger particles, with sizes similar to sand particles, are easier to obtain, without needing special equipment. This study aims to investigate the effect of different particle sizes on the pH of cement mortar. Mortar specimens were crushed and sieved to obtain different ranges of particle sizes to measure the pH values. Results showed that specimens with large particle sizes (between 600 µm and 4.75 mm) can produce similar results to specimens with very fine particle sizes (<600 µm) by increasing the solid-to-solvent ratio or the leaching time.
Full article
(This article belongs to the Special Issue Advanced Structural Health Monitoring: From Theory to Applications)
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Open AccessCommunication
Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status
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, , , , , and
Appl. Sci. 2021, 11(17), 7999; https://doi.org/10.3390/app11177999 - 29 Aug 2021
Abstract
Patients with chronic obstructive pulmonary disease (COPD) suffer from voice changes with respect to the healthy population. However, two issues remain to be studied: how long-term speech elements such as prosody are affected; and whether physical effort and medication also affect the speech
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Patients with chronic obstructive pulmonary disease (COPD) suffer from voice changes with respect to the healthy population. However, two issues remain to be studied: how long-term speech elements such as prosody are affected; and whether physical effort and medication also affect the speech of patients with COPD, and if so, how an automatic speech-based detection system of COPD measurements can be influenced by these changes. The aim of the current study is to address both issues. To this end, long read speech from COPD and control groups was recorded, and the following experiments were performed: (a) a statistical analysis over the study and control groups to analyse the effects of physical effort and medication on speech; and (b) an automatic classification experiment to analyse how different recording conditions can affect the performance of a COPD detection system. The results obtained show that speech—especially prosodic features—is affected by physical effort and inhaled medication in both groups, though in opposite ways; and that the recording condition has a relevant role when designing an automatic COPD detection system. The current work takes a step forward in the understanding of speech in patients with COPD, and in turn, in the research on its automatic detection to help professionals supervising patient status.
Full article
(This article belongs to the Special Issue Applications of Speech and Language Technologies in Healthcare)
Open AccessArticle
Adaptative Cover to Achieve Thermal Comfort in Open Spaces of Buildings: Experimental Assessment and Modelling
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, , , , and
Appl. Sci. 2021, 11(17), 7998; https://doi.org/10.3390/app11177998 - 29 Aug 2021
Abstract
The global need for healthy and safe open spaces faces continuous temperature rise due to the heat island phenomenon and climate change. This problem requires new strategies for improving the habitability of open spaces (indoor and outdoor conditions in buildings). These techniques include
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The global need for healthy and safe open spaces faces continuous temperature rise due to the heat island phenomenon and climate change. This problem requires new strategies for improving the habitability of open spaces (indoor and outdoor conditions in buildings). These techniques include reducing solar radiation, reducing the temperature of surrounding surfaces, and reducing the air temperature. The radiant solutions are essential for outdoor comfort, both in summer and in winter. They are easy to integrate into open spaces. This study explores a new concept of radiant solutions adapted for outdoor spaces. The solution was evaluated in a test cell to obtain its thermal behaviour in different operation conditions. Solutions were optimised for operating in a cooling regimen since it has been identified that the demands for comfort in open spaces in hot climates during the most severe summer months are more pronounced. Experimental results have allowed getting an inverse model to analyse the thermal behaviour of the solution. The inverse model achieved high precision in its estimations. Also, it facilitated knowing the radiant and convective effects. Only the radiant heat flux is relevant in open spaces with a low level of air confinement. Finally, the discussion describes the application of the proposed model. The model allows the replicability of the solution—creating new designs (integration) or evaluating into different operating conditions of the system. This discussion demonstrates the high level of knowledge acquired in the characterisation of the solution studied.
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(This article belongs to the Section Energy)
Open AccessArticle
Ellipsoidal Path Planning for Unmanned Aerial Vehicles
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, , , , and
Appl. Sci. 2021, 11(17), 7997; https://doi.org/10.3390/app11177997 - 29 Aug 2021
Abstract
The research in path planning for unmanned aerial vehicles (UAV) is an active topic nowadays. The path planning strategy highly depends on the map abstraction available. In a previous work, we presented an ellipsoidal mapping algorithm (EMA) that was designed using covariance ellipsoids
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The research in path planning for unmanned aerial vehicles (UAV) is an active topic nowadays. The path planning strategy highly depends on the map abstraction available. In a previous work, we presented an ellipsoidal mapping algorithm (EMA) that was designed using covariance ellipsoids and clustering algorithms. The EMA computes compact in-memory maps, but still with enough information to accurately represent the environment and to be useful for robot navigation algorithms. In this work, we develop a novel path planning algorithm based on a bio-inspired algorithm for navigation in the ellipsoidal map. Our approach overcomes the problem that there is no closed formula to calculate the distance between two ellipsoidal surfaces, so it was approximated using a trained neural network. The presented path planning algorithm takes advantage of ellipsoid entities to represent obstacles and compute paths for small UAVs regardless of the concavity of these obstacles, in a very geometrically explicit way. Furthermore, our method can also be used to plan routes in dynamical environments without adding any computational cost.
Full article
(This article belongs to the Special Issue Applied Machine Learning Ⅱ)
Open AccessSystematic Review
Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches
Appl. Sci. 2021, 11(17), 7996; https://doi.org/10.3390/app11177996 - 29 Aug 2021
Abstract
The Shared Mobility Problems (SMP) with the rideshare concept based on sharing a vehicle are fast becoming a trend in many urban cities around the world. Examples of these problems are like ridesharing, carpooling, taxisharing, buspooling, vanpooling, and multi-modal ridesharing. This is the
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The Shared Mobility Problems (SMP) with the rideshare concept based on sharing a vehicle are fast becoming a trend in many urban cities around the world. Examples of these problems are like ridesharing, carpooling, taxisharing, buspooling, vanpooling, and multi-modal ridesharing. This is the new way to access transportation services by those who are propelling the sharing economy, where access rather than ownership is the new norm. This paper provides a systematic review of SMP using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method. A total of 110 papers from the last decade are selected from 12 abstracts and citation databases to be reviewed and classified. This is done based on the problem types, variants, characteristics, and solution approaches. The current trends and analysis of the survey findings are also summarised. From this systematic review, it is observed that both the time window and multi-objective problems are popular among the researchers, while the minimisation of the total cost is the main concern in the literature of the SMP. Both static and dynamic cases of the SMP are the most researched where heuristic and metaheuristic approaches are widely adopted by the researchers in the literature. Finally, challenges and suggestions for future work are discussed and highlighted.
Full article
(This article belongs to the Collection Intelligent Transportation Systems Ⅱ: Beyond Intelligent Vehicles)
Open AccessFeature PaperArticle
Unveiling the Invisible in Uffizi Gallery’s Drawing 8P by Leonardo with Non-Invasive Optical Techniques
Appl. Sci. 2021, 11(17), 7995; https://doi.org/10.3390/app11177995 - 29 Aug 2021
Abstract
Until recently, the study of drawings by old masters has been confined to the art history conservation field. More specifically, scientific investigations of Leonardo’s drawings are still very few, possibly due to the latter’s extreme fragility and artistic value. However, analytical data are
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Until recently, the study of drawings by old masters has been confined to the art history conservation field. More specifically, scientific investigations of Leonardo’s drawings are still very few, possibly due to the latter’s extreme fragility and artistic value. However, analytical data are crucial to develop a solid knowledge base of the drawing materials and techniques used by artists in the past. In this work, we report on the application of non-invasive optical techniques on a double-sided drawing by Leonardo belonging to the Uffizi Gallery (8P). We used multispectral reflectography in the visible (Vis) and near-infrared (NIR) regions to obtain a spectral mapping of the drawing materials, to be subsequently integrated with technical information provided by art historians and conservators. Morphological analysis by microprofilometry allowed for the identification of the typical wave-like texture impressed in the paper during the sheet’s manufacture, as well as of further paper-impressed traits attributable to the drawing transfer method used by Leonardo. Optical coherence tomography revealed a set of micrometric engraved details in the blank background, which lack any trace of colored material, nor display any apparent relation to the drawn landscape. The disclosure of hidden technical features allowed us to offer new insights into Leonardo’s still under-investigated graphic practices.
Full article
(This article belongs to the Special Issue Application of Materials Science in the Study of Cultural Heritage)
Open AccessReview
Protective Effects of Tocotrienols in Cerebral and Myocardial Ischemia-Reperfusion Injury: A Systematic Review
Appl. Sci. 2021, 11(17), 7994; https://doi.org/10.3390/app11177994 - 29 Aug 2021
Abstract
Although the current treatments for stroke and myocardial infarction contribute to an improvement in mortality rates, the consequences of reperfusion therapy have remained a challenge. Tocotrienols have been shown to exert beneficial effects on the brain and heart. This review aimed to determine
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Although the current treatments for stroke and myocardial infarction contribute to an improvement in mortality rates, the consequences of reperfusion therapy have remained a challenge. Tocotrienols have been shown to exert beneficial effects on the brain and heart. This review aimed to determine the effects of tocotrienols in cerebral and myocardial ischemia-reperfusion (I/R) injury. We retrieved articles from Scopus, MEDLINE and PubMed from inception to June 2021, and included any studies using tocotrienols as a treatment for cerebral or myocardial I/R injury therapy. Observational studies and review articles were excluded, and the risk of bias was conducted using a specific tool for animal study (SYRCLE). The data were analyzed qualitatively. Twelve articles met the eligibility criteria. Tocotrienols significantly improved the structural, functional, and biochemical parameters in both cerebral and myocardial I/R injury models. In contrast, oxidative stress, inflammation, and apoptosis were markedly attenuated by tocotrienol treatment. Limitations to the analysis included marked differences in animal models, disease inductions, forms of tocotrienols, and an unclear risk of bias in certain types of bias. However, tocotrienols have the potential to serve as a supplement for reducing the impact of reperfusion injury.
Full article
(This article belongs to the Special Issue Plant-Derived Functional Foods, Nutraceuticals, and Cosmeceuticals: From Basic to Applied Science)
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Open AccessArticle
Virtual Machine Migration Strategy Based on Multi-Agent Deep Reinforcement Learning
Appl. Sci. 2021, 11(17), 7993; https://doi.org/10.3390/app11177993 - 29 Aug 2021
Abstract
Mobile edge computing is a new computing model, which pushes cloud computing power from centralized cloud to network edge. However, with the sinking of computing power, user mobility brings new challenges: since it is usually unstable, services should be dynamically migrated between multiple
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Mobile edge computing is a new computing model, which pushes cloud computing power from centralized cloud to network edge. However, with the sinking of computing power, user mobility brings new challenges: since it is usually unstable, services should be dynamically migrated between multiple edge servers to maintain service performance, that is, user-perceived latency. Considering that Mobile Edge Computing is a highly distributed computing environment and it is difficult to synchronize information between servers, in order to ensure the real-time performance of the migration strategy, a virtual machine migration strategy based on Multi-Agent Deep Reinforcement Learning is proposed in this paper. The method of centralized training and distributed execution is adopted, that is, the transfer action is guided by the global information during training, and only the local observation information is needed to obtain the transfer action. Compared with the centralized control method, the proposed method alleviates communication bottleneck. Compared with other distributed control methods, this method only needs local information, does not need communication between servers, and speeds up the perception of the current environment. Migration strategies can be generated faster. Simulation results show that the proposed strategy is better than the contrast strategy in terms of convergence and energy consumption.
Full article
Open AccessArticle
Analysis of Nanoindentation Test Results of Asphalt Mixture with Different Gradations
Appl. Sci. 2021, 11(17), 7992; https://doi.org/10.3390/app11177992 - 29 Aug 2021
Abstract
Nanoindentation has been applied in the field of asphalt mixtures, but, at the nano-scale, changes in the composition of the mixture and material properties can have a significant impact on the results. Therefore, it is necessary to investigate the feasibility of nanoindentation tests
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Nanoindentation has been applied in the field of asphalt mixtures, but, at the nano-scale, changes in the composition of the mixture and material properties can have a significant impact on the results. Therefore, it is necessary to investigate the feasibility of nanoindentation tests on different types of asphalt mixtures with different gradations and the influence of material properties and test methods on nanoindentation results. In this paper, the nanoindentation test results on three kinds of asphalt mixture (AC-13, SMA-13, and OGFC-13) with different aggregate gradations were investigated. The load-displacement curves and moduli obtained from the nanoindentation tests were analyzed. In addition, nanoindentation tests were carried out before and after polishing with different ratios of filler and asphalt (RFA) (0.8–1.6). On this basis, the morphology of asphalt specimens with different RFAs is observed by scanning electron microscopy (SEM) imaging. The results indicate that using the nanoindentation test to characterize the mechanical behavior of asphalt mixture, the confidence level of the dense-graded mixture is low, and non-dense-graded mixtures are used as much as possible. Moreover, results illustrate that the nanoindentation modulus tends to increase as the RFA increases. and the SEM chart shows that the higher the mineral powder content in the mastic, the more complex the bitumen and mineral powder interaction surface, confirming the influence of mineral powder content on the nanoindentation test results. Furthermore, the effect of polishing is almost insignificant.
Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
Open AccessFeature PaperArticle
Optimization of the Electrical Demand of an Existing Building with Storage Management through Machine Learning Techniques
Appl. Sci. 2021, 11(17), 7991; https://doi.org/10.3390/app11177991 - 29 Aug 2021
Abstract
Accurate prediction from electricity demand models is helpful in controlling and optimizing building energy performance. The application of machine learning techniques to adjust the electrical consumption of buildings has been a growing trend in recent years. Battery management systems through the machine learning
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Accurate prediction from electricity demand models is helpful in controlling and optimizing building energy performance. The application of machine learning techniques to adjust the electrical consumption of buildings has been a growing trend in recent years. Battery management systems through the machine learning models allow a control of the supply, adapting the building demand to the possible changes that take place during the day, increasing the users’ comfort, and ensuring greenhouse gas emission reduction and an economic benefit. Thus, an intelligent system that defines whether the storage system should be charged according to the electrical needs of that moment and the prediction of the subsequent periods of time is defined. Favoring consumption in the building in periods when energy prices are cheaper or the renewable origin is preferable. The aim of this study was to obtain a building electrical energy demand model in order to be combined with storage devices with the purpose of reducing electricity expenses. Specifically, multilayer perceptron neural network models were applied, and the battery usage optimization is obtained through mathematical modelling. This approach was applied to a public office building located in Bangkok, Thailand.
Full article
(This article belongs to the Special Issue 5th Anniversary of Energy Section—Recent Advances in Energy)
Open AccessArticle
Numerical Simulation on Reflective Cracking Behavior of Asphalt Pavement
Appl. Sci. 2021, 11(17), 7990; https://doi.org/10.3390/app11177990 - 29 Aug 2021
Abstract
Cracks are one of the main problems that plague road workers. A correct understanding of the internal crack propagation mechanism of asphalt pavement will help road workers evaluate the road’s working status more comprehensively and make more reasonable decisions in design, construction, and
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Cracks are one of the main problems that plague road workers. A correct understanding of the internal crack propagation mechanism of asphalt pavement will help road workers evaluate the road’s working status more comprehensively and make more reasonable decisions in design, construction, and maintenance work. This paper established a three-dimensional asphalt pavement layered model using the software ABAQUS and fracture mechanics theory and the extended finite element method were used to explore the mechanical response of the pavement base layer’s preset reflective cracks. This paper investigated the influence of the modulus of each layer, vehicle load on the principal stress, shear stress, J-integral, and two stress intensity factors (K1, K2) during the predetermined crack propagation process of the pavement base layer, and the entropy method was used to analyze the above-mentioned mechanical response. The results show that the main factor affecting the propagation of reflective cracks on asphalt pavements is the modulus of the bottom surface layer. However, from a modeling perspective, the effect of increasing load on crack growth is obvious. Therefore, in terms of technical feasibility, the prevention of reflective cracks should still be achieved by controlling the driving load and prohibiting overloading.
Full article
(This article belongs to the Special Issue Advances in Asphalt Pavement Technologies and Practices)
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