Applied Sciences

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EISSN : 2076-3417
Current Publisher: MDPI AG (10.3390)
Total articles ≅ 20,300
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Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020828

Abstract:
Recently, there has been a growing interest in research on nanofibrous scaffolds developed by electrospinning bioactive plant extracts. In this study, the extract material obtained from the medicinal plant Inula graveolens (L.) was loaded on polycaprolactone (PCL) electrospun polymeric nanofibers. The combined mixture was prepared by 5% of I. graveolens at 8% (PCL) concentration and electrospun under optimal conditions. The chemical analysis, morphology, and crystallization of polymeric nanofibers were carried out by (FT-IR) spectrometer, scanning electron microscopy (SEM), and XRD diffraction. Hydrophilicity was determined by a contact angle experiment. The strength was characterized, and the toxicity of scaffolds on the cell line of fibroblasts was finally investigated. The efficiency of nanofibers to enhance the proliferation of fibroblasts was evaluated in vitro using the optimal I. graveolens/PCL solutions. The results show that I. graveolens/PCL polymeric scaffolds exhibited dispersion in homogeneous nanofibers around 72 ± 963 nm in the ratio 70/30 (V:V), with no toxicity for cells, meaning that they can be used for biomedical applications.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020822

Abstract:
Objective: Calibrated horizontal measurements (e.g., mm) from endoscopic procedures could be utilized for advancement of evidence-based practice and personalized medicine. However, the size of an object in endoscopic images is not readily calibrated and depends on multiple factors, including the distance between the endoscope and the target surface. Additionally, acquired images may have significant non-linear distortion that would further complicate calibrated measurements. This study used a recently developed in vivo laser-projection fiberoptic laryngoscope and proposes a method for calibrated spatial measurements. Method: A set of circular grids was recorded at multiple working distances. A statistical model was trained that would map from pixel length of the object, the working distance, and the spatial location of the target object into its mm length. Result: A detailed analysis of the performance of the proposed method is presented. The analyses have shown that the accuracy of the proposed method does not depend on the working distance and length of the target object. The estimated average magnitude of error was 0.27 mm, which is three times lower than the existing alternative. Conclusion: The presented method can achieve sub-millimeter accuracy in horizontal measurement. Significance: Evidence-based practice and personalized medicine could significantly benefit from the proposed method. Implications of the findings for other endoscopic procedures are also discussed.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020837

Abstract:
For high-fidelity quantum operations in ion traps, it is important to maintain the secular frequency of the trapped ions at a constant value. The radial secular frequency is proportional to the amplitude of the radio frequency (RF) signal applied to ion traps. Owing to the changes in the ambient temperature of a helical resonator and the minute vibration of the optical table, the amplitude can vary. Recently, a method for reducing the fluctuation in the RF signal amplitude, using a commercial universal proportional-plus-integral (PI) controller, has been introduced, which, in turn, reduces the secular frequency drift of the trapped ions. The method improves the capability to maintain the secular frequency at a constant value. However, the structure of the controller is fixed; thus, the control method cannot be changed to suit different experimental conditions, and the different feedback configuration cannot be implemented to increase the resolution. In this paper, we develop a field-programmable gate array (FPGA)-based feedback controller that allows the implementation of various automatic control methods and feedback configurations. In our experiments, the fluctuation in the amplitude of the RF signal was 1.806% using a commercial universal PI controller. The fluctuation was reduced to 0.099% using the developed FPGA-based PI controller, and to 0.102% using the developed FPGA-based lag compensator. By employing the developed FPGA control method, many other automating control methods can be applied to achieve a stable and high-performance control of the secular frequency.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020824

Abstract:
Autoclaved aerated concrete (AAC) and its hygric parameters are a highly important issue in the field of building physics. There are several methods currently available to determine the equilibrium moisture content of building materials. Beside the conventional ones, new methods are constantly being introduced. This study explores the sorption/desorption properties of of three types of commercially produced AACs with three different bulk densities and demonstrates the application of the relevant methods available to characterize these parameters. The reliable characterization of the studied material was done through the conventional static approach, using the desiccator and an environmental chamber, and a new automated method of dynamic vapor sorption is implemented. The goal is to compare and identify the reliability of all methods used with respect to the efficiency of the data measurement process. Sound consistency between the results of the conventional methods and the experimental data obtained indicates the dynamic vapor sorption technique is highly reliable when measuring the equilibrium moisture content—particularly exemplified during the AAC sample testing. Therefore, the methodology developed in this study is expected to provide the reference for measuring the sorption/desorption isotherms of building materials with both static and automated techniques.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020830

Abstract:
The main assumption of eco-efficient High-Performance Concrete (HPC) design is the reduction of Portland cement clinker content without negatively affecting the composite’s mechanical and durability properties. In this paper, three low-clinker HPC mixtures incorporating slag cement (CEM III/B as per EN 197-1) and Supplementary Cementitious Materials (SCMs)—Ground Granulated Blast Furnace Slag (GGBFS), Siliceous Fly Ash (SFA) and Silica Fume (SF)—were designed. The maximum amount of Portland cement clinker from CEM III/B varied from 64 to 116 kg in 1 m3 of concrete mix. The compressive strength of HPC at 2, 7, 14, 28, 56, 90 days, and 2 years after casting, as well as the modulus of elasticity on 2-year-old specimens, was tested. The depth of water penetration under pressure and internal frost resistance in freeze–thaw tests were evaluated after 56 days of curing. Additionally, the concrete pH value tests were performed. The microstructure of 2-year-old HPC specimens was analyzed using Scanning Electron Microscopy (SEM). The research proved that it is possible to obtain low-clinker High-Performance Concretes that reach compressive strength of 76–92 MPa after 28 days of curing, show high values of modulus of elasticity (49–52 GPa) as well as increased resistance to frost and water penetration under pressure.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020833

Abstract:
A literature search and systematic review were conducted to present and discuss the most recent research studies for the past twenty years on the application of non-thermal methods for ensuring the microbiological safety and quality of fish and seafood. This review presents the principles and reveals the potential benefits of high hydrostatic pressure processing (HHP), ultrasounds (US), non-thermal atmospheric plasma (NTAP), pulsed electric fields (PEF), and electrolyzed water (EW) as alternative methods to conventional heat treatments. Some of these methods have already been adopted by the seafood industry, while others show promising results in inactivating microbial contaminants or spoilage bacteria from solid or liquid seafood products without affecting the biochemical or sensory quality. The main applications and mechanisms of action for each emerging technology are being discussed. Each of these technologies has a specific mode of microbial inactivation and a specific range of use. Thus, their knowledge is important to design a practical application plan focusing on producing safer, qualitative seafood products with added value following today’s consumers’ needs.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020834

Abstract:
Measuring knee biomechanics provides valuable clinical information for defining patient-specific treatment options, including patient-oriented physical exercise programs. It can be done by a knee kinesiography test measuring the three-dimensional rotation angles (3D kinematics) during walking, thus providing objective knowledge about knee function in dynamic and weight-bearing conditions. The purpose of this study was to assess whether 3D kinematics can be efficiently used to predict the impact of a physical exercise program on the condition of knee osteoarthritis (OA) patients. The prediction was based on 3D knee kinematic data, namely flexion/extension, adduction/abduction and external/internal rotation angles collected during a treadmill walking session at baseline. These measurements are quantifiable information suitable to develop automatic and objective methods for personalized computer-aided treatment systems. The dataset included 221 patients who followed a personalized therapeutic physical exercise program for 6 months and were then assigned to one of two classes, Improved condition (I) and not-Improved condition (nI). A 10% improvement in pain was needed at the 6-month follow-up compared to baseline to be in the improved group. The developed model was able to predict I and nI with 84.4% accuracy for men and 75.5% for women using a decision tree classifier trained with 3D knee kinematic data taken at baseline and a 10-fold validation procedure. The models showed that men with an impaired control of their varus thrust and a higher pain level at baseline, and women with a greater amplitude of internal tibia rotation were more likely to report improvements in their pain level after 6 months of exercises. Results support the effectiveness of decision trees and the relevance of 3D kinematic data to objectively predict knee OA patients’ response to a treatment consisting of a physical exercise program.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020826

Abstract:
Over the last several years, in parallel with the general global advancement in mobile technology and a rise in social media network content consumption, multimedia content production and reproduction has increased exponentially. Therefore, enabled by the rapid recent advancements in deep learning technology, research on scene graph generation is being actively conducted to more efficiently search for and classify images desired by users within a large amount of content. This approach lets users accurately find images they are searching for by expressing meaningful information on image content as nodes and edges of a graph. In this study, we propose a scene graph generation method based on using the Resource Description Framework (RDF) model to clarify semantic relations. Furthermore, we also use convolutional neural network (CNN) and recurrent neural network (RNN) deep learning models to generate a scene graph expressed in a controlled vocabulary of the RDF model to understand the relations between image object tags. Finally, we experimentally demonstrate through testing that our proposed technique can express semantic content more effectively than existing approaches.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020835

Abstract:
Asphalt mixture proportion design is one of the most important steps in asphalt pavement design and application. This study proposes a novel multi-objective particle swarm optimization (MOPSO) algorithm employing the Gaussian process regression (GPR)-based machine learning (ML) method for multi-variable, multi-level optimization problems with multiple constraints. First, the GPR-based ML method is proposed to model the objective and constraint functions without the explicit relationships between variables and objectives. In the optimization step, the metaheuristic algorithm based on adaptive weight multi-objective particle swarm optimization (AWMOPSO) is used to achieve the global optimal solution, which is very efficient for the objectives and constraints without mathematical relationships. The results showed that the optimal GPR model could describe the relationship between variables and objectives well in terms of root-mean-square error (RMSE) and R2. After the optimization by the proposed GPR-AWMOPSO algorithm, the comprehensive pavement performances were enhanced in terms of the permanent deformation resistance at high temperature, crack resistance at low temperature as well as moisture stability. Therefore, the proposed GPR-AWMOPSO algorithm is the best option and efficient for maximizing the performances of composite modified asphalt mixture. The GPR-AWMOPSO algorithm has advantages of less computational time and fewer samples, higher accuracy, etc. over traditional laboratory-based experimental methods, which can serve as guidance for the proportion optimization design of asphalt pavement.
Published: 17 January 2021
Applied Sciences, Volume 11; doi:10.3390/app11020831

Abstract:
Methylglyoxal (MGO) is recognized as being the bioactive component responsible for the antibacterial activity of mānuka honey. MGO content was investigated by high-performance liquid chromatography (HPLC-UV), in isocratic elution, to assess the occurrence of this compound in mono- and multi-floral honey samples representative of different botanical and geographic origins in Italy. Specifically, 110 honey samples from sweet cherry tree (Prunus avium L.), thyme (Thymus vulgaris L.), almond tree (Prunus amygdalus L.), eucalyptus (Eucalyptus camaldulensis L.), coriander (Coriandrum sativum L.), cornflower (Centaurea cyanus L.), thistle (Silybum marianum L.), acacia (Robinia pseudoacacia L.), citrus, honeydew and multifloral honey were considered. The amount of MGO found in different types of honey was ranging from 0.4 to 24.1 mg/kg. This study provides, for the first time, data on MGO levels in Italian cherry and almond honey, which showed higher concentrations of MGO compared to honeys from other botanical species.
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