Next Issue
Volume 10, September-1
Previous Issue
Volume 10, August-1

Table of Contents

Appl. Sci., Volume 10, Issue 16 (August-2 2020) – 330 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Cover Story (view full-size image) This paper presents a methodological approach to the time-series analysis of movement monitoring [...] Read more.
Order results
Result details
Select all
Export citation of selected articles as:
Open AccessArticle
Weibull S-N Fatigue Strength Curve Analysis for A572 Gr. 50 Steel, Based on the True Stress—True Strain Approach
Appl. Sci. 2020, 10(16), 5725; https://doi.org/10.3390/app10165725 - 18 Aug 2020
Viewed by 326
Abstract
In this paper a Weibull methodology to determine the probabilistic percentiles for the S-N curve of the A572 Gr. 50 steel is formulated. The given Weibull/S-N formulation is based on the true stress and true strain values, which are both determined from the [...] Read more.
In this paper a Weibull methodology to determine the probabilistic percentiles for the S-N curve of the A572 Gr. 50 steel is formulated. The given Weibull/S-N formulation is based on the true stress and true strain values, which are both determined from the stress-strain analysis. For the analysis, the Weibull β and η parameters are both determined directly from the maximum and minimum addressed stresses values. The S-N curve parameters are determined for 103 and 106 cycles. In the application, published experimental data for the CSA G40.21 Gr. 350W steel is used to derive the true stress and true strain parameters of the A572 Gr. 50 steel. Additionally, the application of the S-N curve, its probabilistic percentiles and the Weibull parameters that represent these percentiles are all determined step by step. Since the proposed method is flexible, then it can be applied to determine the probabilistic percentiles of any other material. Full article
Show Figures

Figure 1

Open AccessArticle
State-Constrained Sub-Optimal Tracking Controller for Continuous-Time Linear Time-Invariant (CT-LTI) Systems and Its Application for DC Motor Servo Systems
Appl. Sci. 2020, 10(16), 5724; https://doi.org/10.3390/app10165724 - 18 Aug 2020
Viewed by 281
Abstract
In this paper, we propose an analytic solution of state-constrained optimal tracking control problems for continuous-time linear time-invariant (CT-LTI) systems that are based on model-based prediction, the quadratic penalty function, and the variational approach. Model-based prediction is a concept taken from model-predictive control [...] Read more.
In this paper, we propose an analytic solution of state-constrained optimal tracking control problems for continuous-time linear time-invariant (CT-LTI) systems that are based on model-based prediction, the quadratic penalty function, and the variational approach. Model-based prediction is a concept taken from model-predictive control (MPC) and this is essential to change the direction of calculation for the solution from backward to forward. The quadratic penalty function plays an important role in deriving the analytic solution since it can transform the problem into a form that does not have inequality constraints. For computational convenience, we also propose a sub-optimal controller derived from the steady-state approximation of the analytic solution and show that the proposed controller satisfies the Lyapunov stability. The main advantage of the proposed controller is that it can be implemented in real time with a lower computational load compared to the implicit MPC. Finally, the simulation results for a DC motor servo system are shown and compared with the results of the direct multi-shooting method and the implicit MPC to verify the effectiveness of the proposed controller. Full article
(This article belongs to the Special Issue New Trends in the Control of Robots and Mechatronic Systems)
Show Figures

Graphical abstract

Open AccessArticle
Modeling the Formation of Urea-Water Sprays from an Air-Assisted Nozzle
Appl. Sci. 2020, 10(16), 5723; https://doi.org/10.3390/app10165723 - 18 Aug 2020
Viewed by 270
Abstract
Ammonia preparation from urea-water solutions is a key feature to ensure an effective reduction of nitrogen oxides in selective catalytic reduction (SCR) systems. Thereby, air-assisted nozzles provide fine sprays, which enhance ammonia homogenization. In the present study, a methodology was developed to model [...] Read more.
Ammonia preparation from urea-water solutions is a key feature to ensure an effective reduction of nitrogen oxides in selective catalytic reduction (SCR) systems. Thereby, air-assisted nozzles provide fine sprays, which enhance ammonia homogenization. In the present study, a methodology was developed to model the spray formation by means of computational fluid dynamics (CFD) for this type of atomizer. Experimental validation data was generated in an optically accessible hot gas test bench using a shadowgraphy setup providing droplet velocities and size distributions at designated positions inside the duct. An adaption of the turbulence model was performed in order to correct the dispersion of the turbulent gas jet. The spray modeling in the near nozzle region is based on an experimentally determined droplet spectrum in combination with the WAVE breakup model. This methodology was applied due to the fact that the emerging two-phase flow will immediately disintegrate into a fine spray downstream the nozzle exit, which is also known from cavitating diesel nozzles. The suitability of this approach was validated against the radial velocity and droplet size distributions at the first measurement position downstream the nozzle. In addition, the simulation results serve as a basis for the investigation of turbulent dispersion phenomena and evaporation inside the spray. Full article
(This article belongs to the Special Issue Progress in Spray Science and Technology)
Show Figures

Figure 1

Open AccessArticle
Proximal Policy Optimization Through a Deep Reinforcement Learning Framework for Multiple Autonomous Vehicles at a Non-Signalized Intersection
Appl. Sci. 2020, 10(16), 5722; https://doi.org/10.3390/app10165722 - 18 Aug 2020
Viewed by 289
Abstract
Advanced deep reinforcement learning shows promise as an approach to addressing continuous control tasks, especially in mixed-autonomy traffic. In this study, we present a deep reinforcement-learning-based model that considers the effectiveness of leading autonomous vehicles in mixed-autonomy traffic at a non-signalized intersection. This [...] Read more.
Advanced deep reinforcement learning shows promise as an approach to addressing continuous control tasks, especially in mixed-autonomy traffic. In this study, we present a deep reinforcement-learning-based model that considers the effectiveness of leading autonomous vehicles in mixed-autonomy traffic at a non-signalized intersection. This model integrates the Flow framework, the simulation of urban mobility simulator, and a reinforcement learning library. We also propose a set of proximal policy optimization hyperparameters to obtain reliable simulation performance. First, the leading autonomous vehicles at the non-signalized intersection are considered with varying autonomous vehicle penetration rates that range from 10% to 100% in 10% increments. Second, the proximal policy optimization hyperparameters are input into the multiple perceptron algorithm for the leading autonomous vehicle experiment. Finally, the superiority of the proposed model is evaluated using all human-driven vehicle and leading human-driven vehicle experiments. We demonstrate that full-autonomy traffic can improve the average speed and delay time by 1.38 times and 2.55 times, respectively, compared with all human-driven vehicle experiments. Our proposed method generates more positive effects when the autonomous vehicle penetration rate increases. Additionally, the leading autonomous vehicle experiment can be used to dissipate the stop-and-go waves at a non-signalized intersection. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Show Figures

Figure 1

Open AccessCommunication
Optimization of Management Processes in Assessing the Quality of Stored Grain Using Vision Techniques and Artificial Neural Networks
Appl. Sci. 2020, 10(16), 5721; https://doi.org/10.3390/app10165721 - 18 Aug 2020
Viewed by 250
Abstract
The paper presents the method of using vision techniques and artificial neural networks to assess the degree of contamination of cereal during grain reception. The aim of the work is to optimize the management of the contaminant evaluation process of grain mass in [...] Read more.
The paper presents the method of using vision techniques and artificial neural networks to assess the degree of contamination of cereal during grain reception. The aim of the work is to optimize the management of the contaminant evaluation process of grain mass in warehouse and during purchase using vision techniques based on computer image analysis in order to expedite laboratory work. The obtained photographs of wheat seed samples were analyzed using the “Agropol V06” computer application and neural analysis of the obtained empirical results was performed. The application of computer image analysis reduced the time necessary for the quality assessment of the examined material compared to traditional methods. The generated models were characterized by good parameters and high quality, obtaining a high R2 coefficient at the level of 0.999. As part of the investment project, savings resulting from the time of goods receipt and further production process were made. Profitability was estimated at 191.43% per day. The analysis was made without taking into account other costs related to the business activity. The straight payback period is 3 years. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Show Figures

Figure 1

Open AccessArticle
Theoretical Optimization of Trapped-Bubble-Based Acoustic Metamaterial Performance
Appl. Sci. 2020, 10(16), 5720; https://doi.org/10.3390/app10165720 - 18 Aug 2020
Viewed by 256
Abstract
Acoustic metamaterials have proven to be a versatile tool for the precise control and manipulation of sound waves. One of the promising designs of acoustic metamaterials employ the arrays of bubbles and find applications for soundproofing, blast mitigation, and many others. An obvious [...] Read more.
Acoustic metamaterials have proven to be a versatile tool for the precise control and manipulation of sound waves. One of the promising designs of acoustic metamaterials employ the arrays of bubbles and find applications for soundproofing, blast mitigation, and many others. An obvious advantage of bubble-based metamaterials is their ability to be relatively thin while absorbing low-frequency sound waves. The vast majority of theories developed to predict resonant behavior of bubble-based metamaterials capitalize on Minnaert frequency. Here, we propose a novel theoretical approach to characterize bubble-based metamaterials that are based on our previous findings for a single bubble trapped in circular cavity modeled as a thin clamped plate. We obtain analytical expressions for resonant frequencies of bubble metascreens using self-consistent approximation. Two geometry factors, distance between bubble centers and distance between bubble center and interface of acoustic impedance change, are taken into account. We demonstrate the existence of multiple bandgaps and possibility of switching between them via adjustment of geometry parameters and reflector properties. Full article
(This article belongs to the Section Acoustics and Vibrations)
Show Figures

Figure 1

Open AccessArticle
The Optomechanical Response of a Cubic Anharmonic Oscillator
Appl. Sci. 2020, 10(16), 5719; https://doi.org/10.3390/app10165719 - 18 Aug 2020
Viewed by 203
Abstract
The nonlinearity of a mechanical oscillator may lead to the generation of the macroscopic quantum states, which are useful for precision measurement. Measuring the nonlinearity of a mechanical oscillator becomes important in order to effectively assess its performance. In this paper, we study [...] Read more.
The nonlinearity of a mechanical oscillator may lead to the generation of the macroscopic quantum states, which are useful for precision measurement. Measuring the nonlinearity of a mechanical oscillator becomes important in order to effectively assess its performance. In this paper, we study the electromagnetically induced transparency (EIT) in an optomechanical system with a cubic nonlinear movable mirror. In the presence of the nonlinearity of the movable mirror, we show that the intensity of the output probe field exhibits an asymmetric shape with the transparency peak shifted to a frequency lower than the cavity resonance frequency. This shift can be used to measure the nonlinearity strength of the movable mirror. We also show that the mechanical nonlinearity gives rise to the enhancement of the intensity of the second-order upper sideband generation. Full article
(This article belongs to the Section Optics and Lasers)
Show Figures

Figure 1

Open AccessArticle
Experimental and Numerical Investigation of the Internal Temperature of an Oil-Immersed Power Transformer with DOFS
Appl. Sci. 2020, 10(16), 5718; https://doi.org/10.3390/app10165718 - 18 Aug 2020
Viewed by 214
Abstract
To accurately detect and monitor the internal temperature of an operating power transformer, the distributed optical fiber sensor (DOFS) was creatively applied inside an oil-immersed 35 kV transformer through high integration with the winding wire. On the former basis, the power transformer prototype [...] Read more.
To accurately detect and monitor the internal temperature of an operating power transformer, the distributed optical fiber sensor (DOFS) was creatively applied inside an oil-immersed 35 kV transformer through high integration with the winding wire. On the former basis, the power transformer prototype with a completely global internal temperature sensing capability was successfully developed and it was also qualified for power grid operation through the ex-factory type tests. The internal spatially continuous temperature distribution of the operating transformer was then revealed through a heat-run test and the numerical simulation was also applied for further analysis. Hotspots of windings were continuously located and monitored (emerging at about 89%/90% height of low/high voltage winding), which were furtherly compared with the IEC calculation results. This new nondestructive internal sensing method shows a broad application prospect in the electrical equipment field. Also, the revelation of transformer internal distributed temperature can offer a solid reference for both researchers and field operation staff. Full article
Show Figures

Figure 1

Open AccessArticle
A High Manganese-Tolerant Pseudomonas sp. Strain Isolated from Metallurgical Waste Heap Can Be a Tool for Enhancing Manganese Removal from Contaminated Soil
Appl. Sci. 2020, 10(16), 5717; https://doi.org/10.3390/app10165717 - 18 Aug 2020
Viewed by 246
Abstract
Manganese (Mn) is widely used in industry. However, its extensive applications have generated a great amount of manganese waste, which has become an ecological problem and has led to a decrease in natural resources. The use of microorganisms capable of accumulating Mn ions [...] Read more.
Manganese (Mn) is widely used in industry. However, its extensive applications have generated a great amount of manganese waste, which has become an ecological problem and has led to a decrease in natural resources. The use of microorganisms capable of accumulating Mn ions from contaminated ecosystems offers a potential alternative for the removal and recovery of this metal. The main aim of this work was an investigation of removal potential of Mn from soil by isolated bacterial. For this purpose, eleven bacterial strains were isolated from the soil from metallurgical waste heap in Upper Silesia, Poland. Strain named 2De with the highest Mn removal potential was selected and characterized taking into account its ability for Mn sorption and bioaccumulation from soil and medium containing manganese dioxide. Moreover, the protein profile of 2De strain before and after exposition to Mn was analyzed using SDS/PAGE technique. The 2De strain was identified as a Pseudomonas sp. The results revealed that this strain has an ability to grow at high Mn concentration and possesses an enhanced ability to remove it from the solution enriched with the soil or manganese dioxide via a biosorption mechanism. Moreover, changes in cellular protein expression of the isolated strain were observed. This study demonstrated that autochthonous 2De strain can be an effective tool to remove and recover Mn from contaminated soil. Full article
Show Figures

Figure 1

Open AccessArticle
High-Efficiency All-Dielectric Metasurfaces for the Generation and Detection of Focused Optical Vortex for the Ultraviolet Domain
Appl. Sci. 2020, 10(16), 5716; https://doi.org/10.3390/app10165716 - 18 Aug 2020
Viewed by 236
Abstract
The optical vortex (OV) has drawn considerable attention owing to its tremendous advanced applications, such as optical communication, quantum entanglement, and on-chip detectors. However, traditional OV generators suffer from a bulky configuration and limited performance, especially in the ultraviolet range. In this paper, [...] Read more.
The optical vortex (OV) has drawn considerable attention owing to its tremendous advanced applications, such as optical communication, quantum entanglement, and on-chip detectors. However, traditional OV generators suffer from a bulky configuration and limited performance, especially in the ultraviolet range. In this paper, we utilize a large bandgap dielectric material, niobium pentoxide (Nb2O5), to construct ultra-thin and compact transmission-type metasurfaces to generate and detect the OV at a wavelength of 355 nm. The meta-atom, which operates as a miniature half-wave plate and demonstrates a large tolerance to fabrication error, manipulates the phase of an incident right-handed circular polarized wave with high cross-polarized conversion efficiency (around 86.9%). The phase delay of π between the orthogonal electric field component is attributed to the anti-parallel magnetic dipoles induced in the nanobar. Besides, focused vortex generation (topological charge l from 1 to 3) and multichannel detection (l from −2 to 2) are demonstrated with high efficiency, up to 79.2%. We envision that our devices of high flexibility may have potential applications in high-performance micron-scale integrated ultraviolet nanophotonics and meta-optics. Full article
(This article belongs to the Special Issue New Materials for Nanophotonics)
Show Figures

Figure 1

Open AccessArticle
Towards the Discovery of Influencers to Follow in Micro-Blogs (Twitter) by Detecting Topics in Posted Messages (Tweets)
Appl. Sci. 2020, 10(16), 5715; https://doi.org/10.3390/app10165715 - 18 Aug 2020
Viewed by 388
Abstract
Micro-blogs, such as Twitter, have become important tools to share opinions and information among users. Messages concerning any topic are daily posted. A message posted by a given user reaches all the users that decided to follow her/him. Some users post many messages, [...] Read more.
Micro-blogs, such as Twitter, have become important tools to share opinions and information among users. Messages concerning any topic are daily posted. A message posted by a given user reaches all the users that decided to follow her/him. Some users post many messages, because they aim at being recognized as influencers, typically on specific topics. How a user can discover influencers concerned with her/his interest? Micro-blog apps and web sites lack a functionality to recommend users with influencers, on the basis of the content of posted messages. In this paper, we envision such a scenario and we identify the problem that constitutes the basic brick for developing a recommender of (possibly influencer) users: training a classification model by exploiting messages labeled with topical classes, so as this model can be used to classify unlabeled messages, to let the hidden topic they talk about emerge. Specifically, the paper reports the investigation activity we performed to demonstrate the suitability of our idea. To perform the investigation, we developed an investigation framework that exploits various patterns for extracting features from within messages (labeled with topical classes) in conjunction with the mostly-used classifiers for text classification problems. By means of the investigation framework, we were able to perform a large pool of experiments, that allowed us to evaluate all the combinations of feature patterns with classifiers. By means of a cost-benefit function called “Suitability”, that combines accuracy with execution time, we were able to demonstrate that a technique for discovering topics from within messages suitable for the application context is available. Full article
(This article belongs to the Special Issue Applied Machine Learning)
Show Figures

Figure 1

Open AccessArticle
Glass-Ceramic Foams from Alkali-Activated Vitrified Bottom Ash and Waste Glasses
Appl. Sci. 2020, 10(16), 5714; https://doi.org/10.3390/app10165714 - 18 Aug 2020
Viewed by 220
Abstract
Both vitrified bottom ashes (VBAs) and waste glasses are forms of inorganic waste material that are widely landfilled, despite having some economic potential. Building on previous studies, we prepared glass-ceramic foams by the combination of VBA with either soda-lime glass (SLG) or borosilicate [...] Read more.
Both vitrified bottom ashes (VBAs) and waste glasses are forms of inorganic waste material that are widely landfilled, despite having some economic potential. Building on previous studies, we prepared glass-ceramic foams by the combination of VBA with either soda-lime glass (SLG) or borosilicate glass (BSG). Suspensions of fine powders in weakly alkaline solution underwent gelation, followed by frothing at nearly room temperature. Hardened “green” foams were sintered, with concurrent crystallization, at 850–1000 °C. All foams were highly porous (>70%), with mostly open porosity. The glass addition was fundamental in both gelation (promoting the formation of carbonate and silicate hydrated phases) and firing steps. While SLG addition enhanced the viscous flow sintering, without a significant impact on the crystallization of gehlenite, the main crystalline phase from the devitrification of VBA, BSG addition caused a reactive sintering, with remarkable changes in the phase assemblage. The glass addition generally also allowed lower sintering temperatures and yielded products with excellent crushing strength. However, only specific conditions resulted in the complete immobilization of pollutants (e.g., Cr3+ ions). Full article
(This article belongs to the Special Issue Sustainable Construction Materials)
Show Figures

Figure 1

Open AccessArticle
Thermomechanically Induced Precipitation in High-Performance Ferritic (HiperFer) Stainless Steels
Appl. Sci. 2020, 10(16), 5713; https://doi.org/10.3390/app10165713 - 18 Aug 2020
Cited by 1 | Viewed by 228
Abstract
Novel high-performance fully ferritic (HiperFer) stainless steels were developed to meet the demands of next-generation thermal power-conversion equipment and to feature a uniquely balanced combination of resistance to fatigue, creep, and corrosion. Typical conventional multistep processing and heat treatment were applied to achieve [...] Read more.
Novel high-performance fully ferritic (HiperFer) stainless steels were developed to meet the demands of next-generation thermal power-conversion equipment and to feature a uniquely balanced combination of resistance to fatigue, creep, and corrosion. Typical conventional multistep processing and heat treatment were applied to achieve optimized mechanical properties for this alloy. This paper outlines the feasibility of thermomechanical processing for goal-oriented alteration of the mechanical properties of this new type of steel, applying an economically more efficient approach. The impact of treatment parameter variation on alloy microstructure and the resulting mechanical properties were investigated in detail. Furthermore, initial optimization steps were undertaken. Full article
(This article belongs to the Special Issue Thermomechanical Properties of Steel)
Show Figures

Figure 1

Open AccessArticle
Acoustic Improvements of Aircraft Headrests Based on Electrospun Mats Evaluated Through Boundary Element Method
Appl. Sci. 2020, 10(16), 5712; https://doi.org/10.3390/app10165712 - 18 Aug 2020
Viewed by 223
Abstract
This work illustrates the development of passive noise control (PNC) improvements of aircraft headrests to enhance the acoustic comfort for passengers. Two PNC improvements were studied with the aim of reducing the noise perceived by passengers during flight. Two headrest configurations, with and [...] Read more.
This work illustrates the development of passive noise control (PNC) improvements of aircraft headrests to enhance the acoustic comfort for passengers. Two PNC improvements were studied with the aim of reducing the noise perceived by passengers during flight. Two headrest configurations, with and without the lateral caps, and two different materials, a traditional foam and an innovative Silica/Polyvinylpyrrolidone (PVP) woven non-woven mat, were considered, and compared in terms of sound pressure level (SPL) perceived by passengers. Boundary element method (BEM) models were built up to evaluate the acoustic performances of different headrest configurations, varying in terms of shape and textile. A spherical distribution of monopole sources surrounding the headrests was considered as acoustic load, in such a way as to recreate a diffuse acoustic field simulating the cabin noise perceived by passengers during cruise conditions. The impact of the two PNC improvements was analyzed to envisage some general guidelines useful to design advanced headrests from the acoustic viewpoint. Full article
Show Figures

Figure 1

Open AccessArticle
An ERNIE-Based Joint Model for Chinese Named Entity Recognition
Appl. Sci. 2020, 10(16), 5711; https://doi.org/10.3390/app10165711 - 18 Aug 2020
Viewed by 263
Abstract
Named Entity Recognition (NER) is the fundamental task for Natural Language Processing (NLP) and the initial step in building a Knowledge Graph (KG). Recently, BERT (Bidirectional Encoder Representations from Transformers), which is a pre-training model, has achieved state-of-the-art (SOTA) results in various NLP [...] Read more.
Named Entity Recognition (NER) is the fundamental task for Natural Language Processing (NLP) and the initial step in building a Knowledge Graph (KG). Recently, BERT (Bidirectional Encoder Representations from Transformers), which is a pre-training model, has achieved state-of-the-art (SOTA) results in various NLP tasks, including the NER. However, Chinese NER is still a more challenging task for BERT because there are no physical separations between Chinese words, and BERT can only obtain the representations of Chinese characters. Nevertheless, the Chinese NER cannot be well handled with character-level representations, because the meaning of a Chinese word is quite different from that of the characters, which make up the word. ERNIE (Enhanced Representation through kNowledge IntEgration), which is an improved pre-training model of BERT, is more suitable for Chinese NER because it is designed to learn language representations enhanced by the knowledge masking strategy. However, the potential of ERNIE has not been fully explored. ERNIE only utilizes the token-level features and ignores the sentence-level feature when performing the NER task. In this paper, we propose the ERNIE-Joint, which is a joint model based on ERNIE. The ERNIE-Joint can utilize both the sentence-level and token-level features by joint training the NER and text classification tasks. In order to use the raw NER datasets for joint training and avoid additional annotations, we perform the text classification task according to the number of entities in the sentences. The experiments are conducted on two datasets: MSRA-NER and Weibo. These datasets contain Chinese news data and Chinese social media data, respectively. The results demonstrate that the ERNIE-Joint not only outperforms BERT and ERNIE but also achieves the SOTA results on both datasets. Full article
(This article belongs to the Special Issue Machine Learning and Natural Language Processing)
Show Figures

Figure 1

Open AccessArticle
Dynamic Load Modelling within Combined Transport Trains during Transportation on a Railway Ferry
Appl. Sci. 2020, 10(16), 5710; https://doi.org/10.3390/app10165710 - 18 Aug 2020
Viewed by 265
Abstract
The development of foreign economic activity of the Eurasian states led to the introduction of rail and ferry transportation. It is important to note that the current normative documentation does not fully cover the issues of transporting combined trains by sea. This can [...] Read more.
The development of foreign economic activity of the Eurasian states led to the introduction of rail and ferry transportation. It is important to note that the current normative documentation does not fully cover the issues of transporting combined trains by sea. This can lead to a violation of the traffic safety of both the railway ferry and the transport of containers as part of combined trains by sea. In this connection, we investigated the dynamic loading of a container as part of a combined train when transported by a railway ferry. To ensure the stability of the container relative to the frame, we suggested an improvement of the load-bearing structure of a flat wagon. Additionally, we suggested the use of a viscous linkage between containers with the aim of reducing their dynamic load. To justify the suggested solutions, we carried out a mathematical modelling of the container dynamic load. The calculation was performed in MathCad. Due to the fact that the container has its own degree of freedom when transported by sea, the accelerations were separately determined for the supporting structure of the flat wagon and for the container. We found that the total amount of acceleration that acted on the container was 3.57 m/s2 (0.36 g) and on the load-bearing structure of the wagon was 2.47 m/s2 (0.25 g) which were, respectively, 38% and 23% less than the acceleration values in the typical scheme of their interaction. To determine the fields of acceleration distribution relative to the load-bearing structure of a flat wagon with containers, we carried out computer modelling of their dynamic load. The maximum percentage of discrepancy between the accelerations obtained by mathematical and computer modelling was 17.7%. The study will contribute to the creation of recommendations for the safe transport of combined trains by sea, as well as to increasing the efficiency of combined transport through international transport corridors. Full article
Show Figures

Figure 1

Open AccessArticle
Things2People Interaction toward Energy Savings in Shared Spaces Using BIM
Appl. Sci. 2020, 10(16), 5709; https://doi.org/10.3390/app10165709 - 18 Aug 2020
Viewed by 268
Abstract
People in shared building space have an important role in energy consumption because they can turn on/off equipment and heat/cooling systems. This behaviour can be influenced by giving then locally tailored context information (energy consumption, temperature, luminosity) and information about the cost of [...] Read more.
People in shared building space have an important role in energy consumption because they can turn on/off equipment and heat/cooling systems. This behaviour can be influenced by giving then locally tailored context information (energy consumption, temperature, luminosity) and information about the cost of their actions. This paper presents an approach to create personalized local energy consumption predictions in a building using past sensor data, correlated with external conditions to create local context predictions. This prediction is sent in real-time to people’s mobile devices in order to influence their behaviour when increasing or decreasing temperature using heating or cooling systems. This information is essential for sustainability actions in shared spaces, where this information can have an important role. Also, the data (temperature) representation in the building information model (BIM) module can help the user understand environment conditions and, together with the user sharing their thermal feelings, can be used to change behaviour. This approach using BIM’s representation models allows Things2People interaction to improve energy savings in these shared spaces. Full article
(This article belongs to the Special Issue Human Factors in the Digital Society)
Show Figures

Figure 1

Open AccessArticle
Surface Morphology of Three-Dimensionally Printed Replicas of Upper Dental Arches
Appl. Sci. 2020, 10(16), 5708; https://doi.org/10.3390/app10165708 - 17 Aug 2020
Viewed by 332
Abstract
The aim of our study was to analyze the precision of fused-deposition modeling (FDM), polyjet technology (PJ), stereolithography (SLA) and selective laser sintering (SLS) and to evaluate some interesting indications of these methods in clinical practice. Forty upper dental arches were scanned using [...] Read more.
The aim of our study was to analyze the precision of fused-deposition modeling (FDM), polyjet technology (PJ), stereolithography (SLA) and selective laser sintering (SLS) and to evaluate some interesting indications of these methods in clinical practice. Forty upper dental arches were scanned using a 3Shape Trios 3R optical scanner system and 3D models were made. An Atos II 400 optical 3D scanner was used for calculating the coordinates of points by optical triangulation, photogrammetry and fringe projection. Each model was scanned from a minimum of 56 positions to evaluate global coordinates. Surface morphology was evaluated with an Alpha Step IQ profilometer and a JSM 5510 LV scanning electron microscope. From the measurements in cross-sections it was evident that the deviation shifted by approximately 0.1 mm. The smoothest and most homogeneous sample was SLA. SLS and SLA samples showed the most similar results in comparison of perpendicular directions (homogeneity). FDM and PJ materials exhibited significantly greater roughness in the printing direction than in the perpendicular one, which is most likely caused by the technology selected and/or print parameters. Clinical applications have demonstrated unusual treatment options for patients with rare diseases. Full article
(This article belongs to the Section Applied Dentistry)
Show Figures

Figure 1

Open AccessArticle
Performance In-Live of Marine Engines: A Tool for Its Evaluation
Appl. Sci. 2020, 10(16), 5707; https://doi.org/10.3390/app10165707 - 17 Aug 2020
Viewed by 305
Abstract
Currently, most ships use internal combustion engines (ICEs) either as propulsion engines or generator sets. The growing concern in environmental protection along with the consequent international rule framework motivated shipowners and designers to replace conventional power systems in order to mitigate pollutant emissions. [...] Read more.
Currently, most ships use internal combustion engines (ICEs) either as propulsion engines or generator sets. The growing concern in environmental protection along with the consequent international rule framework motivated shipowners and designers to replace conventional power systems in order to mitigate pollutant emissions. Therefore, manufacturers have made available on the market many technological solutions to use alternative fuels (Liquefied Natural Gas or LNG, methanol, etc.). However, the main energy source is still fossil fuel, so almost all the ICEs are made up of turbocharged diesel engines (TDEs). TDEs have still the potential to improve their efficiency and reduce fuel consumption and pollutant emissions. In particular, the interpretation of Industry 4.0 given by manufacturers enabled the installation of a robust network of sensors on TDEs, which is able to allow reliable power management systems and make ships much more efficient regarding operating costs (fuel consumption and maintenance) and environmental footprint. In this paper, a software tool that is capable of processing the in-live performance of TDEs is described. The great novelty consists in the ability to process all the information detected by the sensor network in-live and dynamically optimize TDEs’ operation, whereas the common practice involves the collection of performance data and their off-line processing. Full article
(This article belongs to the Special Issue Ship Energy Systems)
Show Figures

Figure 1

Open AccessArticle
Antihypertensive Effect of Amaranth Hydrolysate Is Comparable to the Effect of Low-Intensity Physical Activity
Appl. Sci. 2020, 10(16), 5706; https://doi.org/10.3390/app10165706 - 17 Aug 2020
Viewed by 271
Abstract
Background and objectives: Both antihypertensive peptide intake and physical activity help to control blood pressure. Our aim was to evaluate the impact of consuming amaranth antihypertensive peptides on systolic blood pressure (SBP) in normotensive rats and the magnitude and relevance of the peptide-induced [...] Read more.
Background and objectives: Both antihypertensive peptide intake and physical activity help to control blood pressure. Our aim was to evaluate the impact of consuming amaranth antihypertensive peptides on systolic blood pressure (SBP) in normotensive rats and the magnitude and relevance of the peptide-induced antihypertensive effect in spontaneously hypertensive rats (SHR). Materials and Methods: Treatments (alcalase-generated amaranth protein hydrolysate, captopril, or water) were given by gavage and the SBP measured by the tail-cuff method. Physical activity was performed five days/week (for twenty weeks). Results: The normotensive rats’ SBP (mmHg, average/group) remained unaffected after amaranth antihypertensive peptide supplementation (121.8) (p > 0.05 vs controls). In SHR, the SBP was lowered by 24.6 (sedentary/supplemented at two weeks), 42.0 (sedentary/supplemented at eight weeks), and 31.5 (exercised/non-supplemented at eight weeks) (p < 0.05 vs sedentary/non-supplemented). The combination of supplementation and physical activity lowered the SBP by 36.2 and 42.7 (supplemented/exercised at two weeks and eight weeks, respectively) (p < 0.05 vs sedentary/non-supplemented), but it did not have additional antihypertensive benefits (p > 0.05 vs sedentary/supplemented at eight weeks or exercised/non-supplemented at eight weeks). Conclusions: Amaranth antihypertensive peptide supplementation has no impact on SBP in normotensive rats. This supplementation develops sustained antihypertensive benefits in SHR, which are similar to the antihypertensive effect developed after eight- or twenty-week low-intensity physical activity. These findings have implications for developing safe and effective peptide-based functional foods. Full article
(This article belongs to the Special Issue Research of Bioactive Peptides in Foods)
Show Figures

Figure 1

Open AccessArticle
Analyzing Zone-Based Registration Using a Three Zone System: A Semi-Markov Process Approach
Appl. Sci. 2020, 10(16), 5705; https://doi.org/10.3390/app10165705 - 17 Aug 2020
Viewed by 267
Abstract
The location of user equipment (UE) should always be maintained in order to connect any incoming calls within a mobile network. While several methods of location registration have been proposed, most mobile networks have adopted zone-based registration due to its superior performance. Even [...] Read more.
The location of user equipment (UE) should always be maintained in order to connect any incoming calls within a mobile network. While several methods of location registration have been proposed, most mobile networks have adopted zone-based registration due to its superior performance. Even though recommendations from research on these zone-based systems state that multiple zones can be stored in a zone-based registration system, actual current mobile networks only employ a zone-based registration system that stores a single zone. Therefore, some studies have been conducted on zone-based registration using multiple zones. However, most of these studies consider only two zones. In this study, through the development of a semi-Markov process approach, we present a simple but accurate mathematical model for zone-based registration using three zones. In addition, our research results in zone-based registration systems where one, two and three zones are used to suggest the optimal management scheme for zone-based registration. Given that most mobile networks have already adopted some kind of zone-based registration, these results are able to directly enhance the performance of the actual mobile network in the near future with the minimum of effort required for implementation. Full article
(This article belongs to the Special Issue Big Data Analysis and Visualization Ⅱ)
Show Figures

Figure 1

Open AccessReview
Two Decades of TB Drug Discovery Efforts—What Have We Learned?
Appl. Sci. 2020, 10(16), 5704; https://doi.org/10.3390/app10165704 - 17 Aug 2020
Cited by 1 | Viewed by 529
Abstract
After several years of limited success, an effective regimen for the treatment of both drug-sensitive and multiple-drug-resistant tuberculosis is in place. However, this success is still incomplete, as we need several more novel combinations to treat extensively drug-resistant tuberculosis, as well newer emerging [...] Read more.
After several years of limited success, an effective regimen for the treatment of both drug-sensitive and multiple-drug-resistant tuberculosis is in place. However, this success is still incomplete, as we need several more novel combinations to treat extensively drug-resistant tuberculosis, as well newer emerging resistance. Additionally, the goal of a shortened therapy continues to evade us. A systematic analysis of the tuberculosis drug discovery approaches employed over the last two decades shows that the lead identification path has been largely influenced by the improved understanding of the biology of the pathogen Mycobacterium tuberculosis. Interestingly, the drug discovery efforts can be grouped into a few defined approaches that predominated over a period of time. This review delineates the key drivers during each of these periods. While doing so, the author’s experiences at AstraZeneca R&D, Bangalore, India, on the discovery of new antimycobacterial candidate drugs are used to exemplify the concept. Finally, the review also discusses the value of validated targets, promiscuous targets, the current anti-TB pipeline, the gaps in it, and the possible way forward. Full article
(This article belongs to the Special Issue Tuberculosis Drug Discovery and Development 2019)
Show Figures

Figure 1

Open AccessArticle
Comparison of Capillary Flow Porometry (CFP) and Liquid Extrusion Porometry (LEP) Techniques for the Characterization of Porous and Face Mask Membranes
Appl. Sci. 2020, 10(16), 5703; https://doi.org/10.3390/app10165703 - 17 Aug 2020
Viewed by 230
Abstract
This work aims to study the characterization of several membrane filters by using capillary flow porometry (CFP) and liquid extrusion porometry (LEP) to obtain their pore size distributions (PSD) and mean pore diameters (davg). Three polymeric membranes of different materials namely, [...] Read more.
This work aims to study the characterization of several membrane filters by using capillary flow porometry (CFP) and liquid extrusion porometry (LEP) to obtain their pore size distributions (PSD) and mean pore diameters (davg). Three polymeric membranes of different materials namely, polyethylene (PET), cellulose nitrate (CN), and FM (face mask), and one inorganic (namely, alumina Al2O3) from ultrafiltration (UF)/microfiltration (MF) and particle separation were analyzed using a pressure constant fluid/liquid extrusion porometer, developed at institute de la filtration et techniques séparatives (IFTS). Several porosimetric fluids have been used to wet and penetrate into the porous/fiber structure. The results show the accuracy of the setup on characterizing membranes in the UF/MF range by CFP, with reasonable agreement with nominal data of the filters. Additionally, LEP extension of the equipment obtained good agreement with nominal data and the CFP results, while filters presenting a microstructure of highly interconnected pores (face mask) resulted in clear differences in terms of resulting PSD and average sizes when CFP and LEP results are compared. Full article
(This article belongs to the Special Issue Preparation, Characterization and Modelling of Advanced Membranes)
Show Figures

Figure 1

Open AccessArticle
Modern Aspects of Cyber-Security Training and Continuous Adaptation of Programmes to Trainees
Appl. Sci. 2020, 10(16), 5702; https://doi.org/10.3390/app10165702 - 17 Aug 2020
Viewed by 251
Abstract
Nowadays, more-and-more cyber-security training is emerging as an essential process for the lifelong personnel education in organizations, especially for those which operate critical infrastructures. This is due to security breaches on popular services that become publicly known and raise people’s security awareness. Except [...] Read more.
Nowadays, more-and-more cyber-security training is emerging as an essential process for the lifelong personnel education in organizations, especially for those which operate critical infrastructures. This is due to security breaches on popular services that become publicly known and raise people’s security awareness. Except from large organizations, small-to-medium enterprises and individuals need to keep their knowledge on the related topics up-to-date as a means to protect their business operation or to obtain professional skills. Therefore, the potential target-group may range from simple users, who require basic knowledge on the current threat landscape and how to operate the related defense mechanisms, to security experts, who require hands-on experience in responding to security incidents. This high diversity makes training and certification quite a challenging task. This study combines pedagogical practices and cyber-security modelling in an attempt to support dynamically adaptive training procedures. The training programme is initially tailored to the trainee’s needs, promoting the continuous adaptation to his/her performance afterwards. As the trainee accomplishes the basic evaluation tasks, the assessment starts involving more advanced features that demand a higher level of understanding. The overall method is integrated in a modern cyber-ranges platform, and a pilot training programme for smart shipping employees is presented. Full article
(This article belongs to the Special Issue Cyber Security of Critical Infrastructures)
Show Figures

Figure 1

Open AccessArticle
Automatic Segmentation of Macular Edema in Retinal OCT Images Using Improved U-Net++
Appl. Sci. 2020, 10(16), 5701; https://doi.org/10.3390/app10165701 - 17 Aug 2020
Viewed by 245
Abstract
The number and volume of retinal macular edemas are important indicators for screening and diagnosing retinopathy. Aiming at the problem that the segmentation method of macular edemas in a retinal optical coherence tomography (OCT) image is not ideal in segmentation of diverse edemas, [...] Read more.
The number and volume of retinal macular edemas are important indicators for screening and diagnosing retinopathy. Aiming at the problem that the segmentation method of macular edemas in a retinal optical coherence tomography (OCT) image is not ideal in segmentation of diverse edemas, this paper proposes a new method of automatic segmentation of macular edema regions in retinal OCT images using the improved U-Net++. The proposed method makes full use of the U-Net++ re-designed skip pathways and dense convolution block; reduces the semantic gap of the feature maps in the encoder/decoder sub-network; and adds the improved Resnet network as the backbone, which make the extraction of features in the edema regions more accurate and improves the segmentation effect. The proposed method was trained and validated on the public dataset of Duke University, and the experiments demonstrated the proposed method can not only improve the overall segmentation effect, but also can significantly improve the segmented precision for diverse edema in multi-regions, as well as reducing the error of the number of edema regions. Full article
(This article belongs to the Special Issue Image Processing Techniques for Biomedical Applications)
Show Figures

Figure 1

Open AccessArticle
A Novel Hybrid Decomposition—Ensemble Prediction Model for Dam Deformation
Appl. Sci. 2020, 10(16), 5700; https://doi.org/10.3390/app10165700 - 17 Aug 2020
Viewed by 265
Abstract
Accurate and reliable prediction of dam deformation (DD) is of great significance to the safe and stable operation of dams. In order to deal with the fluctuation characteristics in DD for more accurate prediction results, a new hybrid model based on a decomposition-ensemble [...] Read more.
Accurate and reliable prediction of dam deformation (DD) is of great significance to the safe and stable operation of dams. In order to deal with the fluctuation characteristics in DD for more accurate prediction results, a new hybrid model based on a decomposition-ensemble model named VMD-SE-ER-PACF-ELM is proposed. First, the time series data are decomposed into subsequences with different frequencies and an error sequence (ER) by variational mode decomposition (VMD), and then the secondary decomposition method is introduced into the prediction of ER. In these two decomposition processes, the sample entropy (SE) method is innovatively utilized to determine the decomposition modulus. Then, the input variables of the subsequences are selected by partial autocorrelation analysis (PACF). Finally, the parameter-optimization-based extreme learning machine (ELM) models are used to predict the subsequences, and the outputs are reconstructed to obtain the final prediction results. The case analysis shows that the VMD-SE-ER-PACF-ELM model has strong prediction ability for DD. The model is then compared with other nonlinear and time series models, and its performance under different prediction periods is also analyzed. The results show that the proposed model is able to adequately describe the original DD. It performs well in both training and testing stages. It is a preferred data-driven model for DD prediction and can provide a priori knowledge for health monitoring of dams. Full article
(This article belongs to the Section Civil Engineering)
Show Figures

Figure 1

Open AccessArticle
Microscopic Characteristic Analysis on Sandstone under Coupling Effect of Freeze–Thaw and Acidic Treatment: From Nuclear Magnetic Resonance Perspective
Appl. Sci. 2020, 10(16), 5699; https://doi.org/10.3390/app10165699 - 17 Aug 2020
Viewed by 225
Abstract
Microscopic characteristics greatly affect mechanical and physical properties as they exert vital impact on the stability and durability of materials. In this paper, widely distributed sandstone was chosen as the research object. Sandstone was treated with a coupled effect of Freeze–Thaw (F–T) weathering [...] Read more.
Microscopic characteristics greatly affect mechanical and physical properties as they exert vital impact on the stability and durability of materials. In this paper, widely distributed sandstone was chosen as the research object. Sandstone was treated with a coupled effect of Freeze–Thaw (F–T) weathering and acid solution, where freeze–thaw cycles were set as 0, 10, 20, 30 and 40 cycles, and the pH of the acid solution were set as 2.8, 4.2, 5.6 and 7.0, respectively. Then, nuclear magnetic resonance was applied to measure the microscopic characteristics of sandstone, then porosity, pore size distribution and permeability before the fractal dimensions were obtained and calculated. Results show that porosity increases when F–T cycles increase, and its increase grows with the pH of acid solution decrease during the first 10 F–T cycles. Macro porosity, meso porosity and micro porosity account for the largest, second largest and smallest ratio of porosity growth. Meso porosity, micro porosity and macro porosity account for the largest, second largest and smallest ratio of total porosity. Permeability increases obviously with F–T cycle increase, while acid erosion exerts little influence on permeability increment overall. Fractal dimensions of meso pores and macro pores increase with F–T cycle increase overall, and they increase with pH decrease overall. Porosity has strong exponentially correlation with permeability. Fractal dimensions of meso pores and macro pores have good linearly correlation with permeability, while correlation between porosity and fractal dimensions are not that obvious. Full article
Show Figures

Figure 1

Open AccessArticle
A Methodology for Increasing Convergence Speed of Traffic Assignment Algorithms Based on the Use of a Generalised Averaging Function
Appl. Sci. 2020, 10(16), 5698; https://doi.org/10.3390/app10165698 - 17 Aug 2020
Viewed by 246
Abstract
In this paper, we propose a generalisation of the Method of Successive Averages (MSA) for solving traffic assignment problems. The generalisation consists in proposing a different step sequence within the general MSA framework to reduce computing times. The proposed step sequence is based [...] Read more.
In this paper, we propose a generalisation of the Method of Successive Averages (MSA) for solving traffic assignment problems. The generalisation consists in proposing a different step sequence within the general MSA framework to reduce computing times. The proposed step sequence is based on the modification of the classic 1/k sequence for improving the convergence speed of the algorithm. The reduction in computing times is useful if the assignment problems are subroutines of algorithms for solving Network Design Problems—such algorithms require estimation of the equilibrium traffic flows at each iteration, hence, many thousands of times for real-scale cases. The proposed algorithm is tested with different parameter values and compared with the classic MSA algorithm on a small and on two real-scale networks. A test inside a Network Design Problem is also reported. Numerical results show that the proposed algorithm outperforms the classic MSA with reductions in computing times, reaching up to 79%. Finally, the theoretical properties are studied for stating the convergence of the proposed algorithm. Full article
Show Figures

Figure 1

Open AccessCase Report
3D-Printed Surgical Guide for Crown Lengthening Based on Cone Beam Computed Tomography Measurements: A Clinical Report with 6 Months Follow Up
Appl. Sci. 2020, 10(16), 5697; https://doi.org/10.3390/app10165697 - 17 Aug 2020
Viewed by 238
Abstract
Excessive gingival display is a common clinical presentation that often requires surgical intervention. This report is for a patient for whom esthetic crown lengthening is indicated due to altered passive eruption. Cone beam computed tomography (CBCT) scan and an intraoral scan were used [...] Read more.
Excessive gingival display is a common clinical presentation that often requires surgical intervention. This report is for a patient for whom esthetic crown lengthening is indicated due to altered passive eruption. Cone beam computed tomography (CBCT) scan and an intraoral scan were used to design and print a single surgical guide which provided a reference for both gingivectomy and osteoectomy. A satisfactory outcome was obtained 6 months after surgery. The present technique provided a simplified method of generating a surgical guide with predictable results by relying on the existing tooth anatomy rather than diagnostic waxing. This technique is particularly useful when crowns or veneers are not indicated. Full article
(This article belongs to the Special Issue Application of CAD/CAM and 3D Printing Technologies in Dentistry)
Show Figures

Figure 1

Open AccessArticle
Partially versus Purely Data-Driven Approaches in SARS-CoV-2 Prediction
Appl. Sci. 2020, 10(16), 5696; https://doi.org/10.3390/app10165696 - 17 Aug 2020
Viewed by 269
Abstract
Prediction models of coronavirus disease utilizing machine learning algorithms range from forecasting future suspect cases, predicting mortality rates, to building a pattern for country-specific pandemic end date. To predict the future suspect infection and death cases, we categorized the approaches found in the [...] Read more.
Prediction models of coronavirus disease utilizing machine learning algorithms range from forecasting future suspect cases, predicting mortality rates, to building a pattern for country-specific pandemic end date. To predict the future suspect infection and death cases, we categorized the approaches found in the literature into: first, a purely data-driven approach, whose goal is to build a mathematical model that relates the data variables including outputs with inputs to detect general patterns. The discovered patterns can then be used to predict the future infected cases without any expert input. The second approach is partially data-driven; it uses historical data, but allows expert input such as the SIR epidemic algorithm. This approach assumes that the epidemic will end according to medical reasoning. In this paper, we compare the purely data-driven and partially-data driven approaches by applying them to data from three countries having different past pattern behavior. The countries are the US, Jordan, and Italy. It is found that those two prediction approaches yield significantly different results. Purely data-driven approach depends totally on the past behavior and does not show any decline in the number of the infected cases if the country did not experience any decline in the number of cases. On the other hand, a partially data-driven approach guarantees a timely decline of the infected curve to reach zero. Using the two approaches highlights the importance of human intervention in pandemic prediction to guide the learning process as opposed to the purely data-driven approach that predicts future cases based on the pattern detected in the data. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
Show Figures

Figure 1

Previous Issue
Back to TopTop