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Appl. Sci., Volume 11, Issue 13 (July-1 2021) – 481 articles

Cover Story (view full-size image): Renal cell carcinoma (RCC) can present with or without peritumoral collateral vessels. Computed tomography (CT) allows in vivo quantification of the composition of the abdominal adipose compartments, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). In this study, we found a significant decrease in SAT of patients with peritumoral collateral vessels and clear RCC (ccRCC). The presence of peritumoral collateral vessels adjacent to ccRCC might be a subtle and novel diagnostic clue to kidney cancer cachexia. View this paper
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25 pages, 8593 KiB  
Article
Application Study on Fiber Optic Monitoring and Identification of CRTS-II-Slab Ballastless Track Debonding on Viaduct
by Gaoran Guo, Junfang Wang, Bowen Du and Yanliang Du
Appl. Sci. 2021, 11(13), 6239; https://doi.org/10.3390/app11136239 - 5 Jul 2021
Cited by 4 | Viewed by 2672
Abstract
China Railway Track System (CRTS)-II-slab ballastless track is a new type of track structure, and its interlayer connection state is considerably important for the operation safety and ride comfort of high-speed trains. However, the location and multiple influencing factors of interlayer debonding lead [...] Read more.
China Railway Track System (CRTS)-II-slab ballastless track is a new type of track structure, and its interlayer connection state is considerably important for the operation safety and ride comfort of high-speed trains. However, the location and multiple influencing factors of interlayer debonding lead to difficulties in monitoring and identification. Here, the research on the design and application of a monitoring scheme that facilitates interlayer debonding detection of ballastless track and an effective indicator for debonding identification and assessment is proposed. The results show that on-site monitoring can effectively capture the vibration signals caused by train vibration and interlayer debonding. The features of the data acquired in the situations with and without interlayer debonding are compared after instantaneous baseline validation. Some significant features capable of obviously differentiating a debonding state from the normal state are identified. Furthermore, a new indicator, combining multiple debonding-sensitive features by similarity-based weights normalizing the initial difference between mutual instantaneous baselines, is developed to support rational and comprehensive assessment quantitatively. The contribution of this study includes the development and application of an interlay-debonding monitoring scheme, the establishment of an effective-feature pool, and the proposal of the similarity-based indicator, thereby laying a good foundation for debonding identification of ballastless track. Full article
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36 pages, 8379 KiB  
Article
Data-Driven Approach for Rainfall-Runoff Modelling Using Equilibrium Optimizer Coupled Extreme Learning Machine and Deep Neural Network
by Bishwajit Roy, Maheshwari Prasad Singh, Mosbeh R. Kaloop, Deepak Kumar, Jong-Wan Hu, Radhikesh Kumar and Won-Sup Hwang
Appl. Sci. 2021, 11(13), 6238; https://doi.org/10.3390/app11136238 - 5 Jul 2021
Cited by 24 | Viewed by 3441
Abstract
Rainfall-runoff (R-R) modelling is used to study the runoff generation of a catchment. The quantity or rate of change measure of the hydrological variable, called runoff, is important for environmental scientists to accomplish water-related planning and design. This paper proposes (i) an integrated [...] Read more.
Rainfall-runoff (R-R) modelling is used to study the runoff generation of a catchment. The quantity or rate of change measure of the hydrological variable, called runoff, is important for environmental scientists to accomplish water-related planning and design. This paper proposes (i) an integrated model namely EO-ELM (an integration of equilibrium optimizer (EO) and extreme learning machine (ELM)) and (ii) a deep neural network (DNN) for one day-ahead R-R modelling. The proposed R-R models are validated at two different benchmark stations of the catchments, namely river Teifi at Glanteifi and river Fal at Tregony in the UK. Firstly, a partial autocorrelation function (PACF) is used for optimal number of lag inputs to deploy the proposed models. Six other well-known machine learning models, called ELM, kernel ELM (KELM), and particle swarm optimization-based ELM (PSO-ELM), support vector regression (SVR), artificial neural network (ANN) and gradient boosting machine (GBM) are utilized to validate the two proposed models in terms of prediction efficiency. Furthermore, to increase the performance of the proposed models, paper utilizes a discrete wavelet-based data pre-processing technique is applied in rainfall and runoff data. The performance of wavelet-based EO-ELM and DNN are compared with wavelet-based ELM (WELM), KELM (WKELM), PSO-ELM (WPSO-ELM), SVR (WSVR), ANN (WANN) and GBM (WGBM). An uncertainty analysis and two-tailed t-test are carried out to ensure the trustworthiness and efficacy of the proposed models. The experimental results for two different time series datasets show that the EO-ELM performs better in an optimal number of lags than the others. In the case of wavelet-based daily R-R modelling, proposed models performed better and showed robustness compared to other models used. Therefore, this paper shows the efficient applicability of EO-ELM and DNN in R-R modelling that may be used in the hydrological modelling field. Full article
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23 pages, 13973 KiB  
Article
Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources
by Azharul Islam and KyungHi Chang
Appl. Sci. 2021, 11(13), 6237; https://doi.org/10.3390/app11136237 - 5 Jul 2021
Cited by 8 | Viewed by 6801
Abstract
Unstructured data from the internet constitute large sources of information, which need to be formatted in a user-friendly way. This research develops a model that classifies unstructured data from data mining into labeled data, and builds an informational and decision-making support system (DMSS). [...] Read more.
Unstructured data from the internet constitute large sources of information, which need to be formatted in a user-friendly way. This research develops a model that classifies unstructured data from data mining into labeled data, and builds an informational and decision-making support system (DMSS). We often have assortments of information collected by mining data from various sources, where the key challenge is to extract valuable information. We observe substantial classification accuracy enhancement for our datasets with both machine learning and deep learning algorithms. The highest classification accuracy (99% in training, 96% in testing) was achieved from a Covid corpus which is processed by using a long short-term memory (LSTM). Furthermore, we conducted tests on large datasets relevant to the Disaster corpus, with an LSTM classification accuracy of 98%. In addition, random forest (RF), a machine learning algorithm, provides a reasonable 84% accuracy. This research’s main objective is to increase the application’s robustness by integrating intelligence into the developed DMSS, which provides insight into the user’s intent, despite dealing with a noisy dataset. Our designed model selects the random forest and stochastic gradient descent (SGD) algorithms’ F1 score, where the RF method outperforms by improving accuracy by 2% (to 83% from 81%) compared with a conventional method. Full article
(This article belongs to the Special Issue Deep Convolutional Neural Networks)
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18 pages, 1355 KiB  
Article
Diversity and Seasonal Dynamics of Airborne Fungi in Nerja Cave, Spain
by Valme Jurado, Yolanda Del Rosal, Cristina Liñan, Tamara Martin-Pozas, Jose Luis Gonzalez-Pimentel and Cesareo Saiz-Jimenez
Appl. Sci. 2021, 11(13), 6236; https://doi.org/10.3390/app11136236 - 5 Jul 2021
Cited by 13 | Viewed by 3580
Abstract
Nerja Cave, Southern Spain, was revealed as an important biodiversity reservoir from which several novel species of Aspergillus were described. We carried out an aerobiological study in Nerja Cave to assess the origin of airborne fungi. This study quantified the fungi present in [...] Read more.
Nerja Cave, Southern Spain, was revealed as an important biodiversity reservoir from which several novel species of Aspergillus were described. We carried out an aerobiological study in Nerja Cave to assess the origin of airborne fungi. This study quantified the fungi present in the air of ten representative halls covering the three sectors comprising the cave: Touristic Galleries, High Galleries, and New Galleries. Microclimatological monitoring allowed us to understand the dynamic of airborne fungi in two seasons of the year (winter and summer), corresponding to the strongest and the lowest cave ventilation, and to validate the influence that the transport of airborne fungi from outside may have on the cave itself. The data show that cold air enters in winter, as confirmed by the abundant presence of Aspergillus and Penicillium spores inside and outside the cave. In summer, the abundance of some fungi in the air of Nerja Cave, which are not detected outside, indicates a stagnation or low ventilation, and therefore, the concentration of fungal spores is maxima. The high occurrence of Cladosporium outside the cave and the scarce abundance inside support the cave stagnation in this season. Full article
(This article belongs to the Special Issue The Role of Fungi in Biodeterioration of Cultural Heritage: New Insights for Their Control)
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11 pages, 2917 KiB  
Article
Fast Low-Precision Computer-Generated Holography on GPU
by David Blinder and Peter Schelkens
Appl. Sci. 2021, 11(13), 6235; https://doi.org/10.3390/app11136235 - 5 Jul 2021
Cited by 7 | Viewed by 2655
Abstract
Computer-generated holography (CGH) is a notoriously difficult computation problem, simulating numerical diffraction, where every scene point can affect every hologram pixel. To tackle this challenge, specialized software instructions and hardware solutions are developed to significantly reduce calculation time and power consumption. In this [...] Read more.
Computer-generated holography (CGH) is a notoriously difficult computation problem, simulating numerical diffraction, where every scene point can affect every hologram pixel. To tackle this challenge, specialized software instructions and hardware solutions are developed to significantly reduce calculation time and power consumption. In this work, we propose a novel algorithm for high-performance point-based CGH, leveraging fixed-point integer representations, the separability of the Fresnel transform and using new look-up table free cosine representation. We report up to a 3-fold speed up over an optimized floating-point GPU implementation, as well as a 15 dB increase in quality over a state-of-the-art FPGA-based fixed-point integer solution. Full article
(This article belongs to the Special Issue Advanced Digital Holographic Technology: Imaging Methods and Devices Construction)
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17 pages, 4370 KiB  
Article
Demonstration of Phase Change Thermal Energy Storage in Zinc Oxide Microencapsulated Sodium Nitrate
by Ciprian Neagoe, Ioan Albert Tudor, Cristina Florentina Ciobota, Cristian Bogdanescu, Paul Stanciu, Nicoleta Zărnescu-Ivan, Radu Robert Piticescu and Maria Dolores Romero-Sanchez
Appl. Sci. 2021, 11(13), 6234; https://doi.org/10.3390/app11136234 - 5 Jul 2021
Cited by 5 | Viewed by 2997
Abstract
Microencapsulation of sodium nitrate (NaNO3) as phase change material for high temperature thermal energy storage aims to reduce costs related to metal corrosion in storage tanks. The goal of this work was to test in a prototype thermal energy storage tank [...] Read more.
Microencapsulation of sodium nitrate (NaNO3) as phase change material for high temperature thermal energy storage aims to reduce costs related to metal corrosion in storage tanks. The goal of this work was to test in a prototype thermal energy storage tank (16.7 L internal volume) the thermal properties of NaNO3 microencapsulated in zinc oxide shells, and estimate the potential of NaNO3–ZnO microcapsules for thermal storage applications. A fast and scalable microencapsulation procedure was developed, a flow calorimetry method was adapted, and a template document created to perform tank thermal transfer simulation by the finite element method (FEM) was set in Microsoft Excel. Differential scanning calorimetry (DSC) and transient plane source (TPS) methods were used to measure, in small samples, the temperature dependency of melting/solidification heat, specific heat, and thermal conductivity of the NaNO3–ZnO microcapsules. Scanning electron microscopy (SEM) and chemical analysis demonstrated the stability of microcapsules over multiple tank charge–discharge cycles. The energy stored as latent heat is available for a temperature interval from 303 to 285 °C, corresponding to onset–offset for NaNO3 solidification. Charge–self-discharge experiments on the pilot tank showed that the amount of thermal energy stored in this interval largely corresponds to the NaNO3 content of the microcapsules; the high temperature energy density of microcapsules is estimated in the range from 145 to 179 MJ/m3. Comparison between real tank experiments and FEM simulations demonstrated that DSC and TPS laboratory measurements on microcapsule thermal properties may reliably be used to design applications for thermal energy storage. Full article
(This article belongs to the Special Issue Phase Change Materials: Design and Applications)
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15 pages, 36687 KiB  
Article
Multiparametric Analysis of a Gravity Retaining Wall
by Rok Varga, Bojan Žlender and Primož Jelušič
Appl. Sci. 2021, 11(13), 6233; https://doi.org/10.3390/app11136233 - 5 Jul 2021
Cited by 10 | Viewed by 5455
Abstract
The design of a gravity retaining wall should be simple to construct, quick to build and the best economic solution to a problem. This can be achieved by using advanced optimization methods. Since geotechnical engineers are not always able to determine the exact [...] Read more.
The design of a gravity retaining wall should be simple to construct, quick to build and the best economic solution to a problem. This can be achieved by using advanced optimization methods. Since geotechnical engineers are not always able to determine the exact soil properties and other project data, an optimal design of a gravity retaining wall should also be determined for a wide range of input parameters. Therefore, a multiparametric analysis of an optimal designed gravity retaining wall was carried out. Optimum designs of gravity retaining walls were obtained for 567 combinations of different design parameters. Diagrams were developed to help engineers determine the optimum section of the wall, based on construction costs. An exhaustive search was carried out within the available parameters (project data). The parameters were ranked according to which had the most influence on the optimum cost of the gravity retaining wall and the utilization of multiple constraints. The most important parameter for the optimal cost of a gravity retaining wall is the height of the retained ground, followed by the shear angle of the soil, the soil–wall interaction coefficient, the slope angle and the variable surcharge load. The shear angle of the soil is most relevant to the bearing capacity and eccentricity condition, while the soil–wall interaction coefficient is most relevant to the sliding condition. Since European countries apply different load, material and resistance safety factors, the optimization model was developed in a general form, where different design approaches and unit prices could be applied. The case study provides an improved optimization model for selecting the optimal design of gravity walls, for engineers. Full article
(This article belongs to the Special Issue New Frontiers in Buildings and Construction)
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15 pages, 2526 KiB  
Article
Photonic Integrated Reconfigurable Linear Processors as Neural Network Accelerators
by Lorenzo De Marinis, Marco Cococcioni, Odile Liboiron-Ladouceur, Giampiero Contestabile, Piero Castoldi and Nicola Andriolli
Appl. Sci. 2021, 11(13), 6232; https://doi.org/10.3390/app11136232 - 5 Jul 2021
Cited by 24 | Viewed by 3698
Abstract
Reconfigurable linear optical processors can be used to perform linear transformations and are instrumental in effectively computing matrix–vector multiplications required in each neural network layer. In this paper, we characterize and compare two thermally tuned photonic integrated processors realized in silicon-on-insulator and silicon [...] Read more.
Reconfigurable linear optical processors can be used to perform linear transformations and are instrumental in effectively computing matrix–vector multiplications required in each neural network layer. In this paper, we characterize and compare two thermally tuned photonic integrated processors realized in silicon-on-insulator and silicon nitride platforms suited for extracting feature maps in convolutional neural networks. The reduction in bit resolution when crossing the processor is mainly due to optical losses, in the range 2.3–3.3 for the silicon-on-insulator chip and in the range 1.3–2.4 for the silicon nitride chip. However, the lower extinction ratio of Mach–Zehnder elements in the latter platform limits their expressivity (i.e., the capacity to implement any transformation) to 75%, compared to 97% of the former. Finally, the silicon-on-insulator processor outperforms the silicon nitride one in terms of footprint and energy efficiency. Full article
(This article belongs to the Special Issue Photonics for Optical Computing)
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25 pages, 25708 KiB  
Article
Analytic Binary Alloy Volume–Concentration Relations and the Deviation from Zen’s Law
by Alexander Landa, John E. Klepeis, Robert E. Rudd, Kyle J. Caspersen and David A. Young
Appl. Sci. 2021, 11(13), 6231; https://doi.org/10.3390/app11136231 - 5 Jul 2021
Cited by 9 | Viewed by 2856
Abstract
Alloys expand or contract as concentrations change, and the resulting relationship between atomic volume and alloy content is an important property of the solid. While a well-known approximation posits that the atomic volume varies linearly with concentration (Zen’s law), the actual variation is [...] Read more.
Alloys expand or contract as concentrations change, and the resulting relationship between atomic volume and alloy content is an important property of the solid. While a well-known approximation posits that the atomic volume varies linearly with concentration (Zen’s law), the actual variation is more complicated. Here we use the apparent size of the solute (solvent) atom and the elasticity to derive explicit analytical expressions for the atomic volume of binary solid alloys. Two approximations, continuum and terminal, are proposed. Deviations from Zen’s law are studied for 22 binary alloy systems. Full article
(This article belongs to the Special Issue Feature Paper Collection in Section Materials)
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14 pages, 3476 KiB  
Article
Continuous Control Set Predictive Current Control for Induction Machine
by Toni Varga, Tin Benšić, Vedrana Jerković Štil and Marinko Barukčić
Appl. Sci. 2021, 11(13), 6230; https://doi.org/10.3390/app11136230 - 5 Jul 2021
Cited by 4 | Viewed by 2164
Abstract
A speed tracking control method for induction machine is shown in this paper. The method consists of outer speed control loop and inner current control loop. Model predictive current control method without the need for calculation of the weighing factors is utilized for [...] Read more.
A speed tracking control method for induction machine is shown in this paper. The method consists of outer speed control loop and inner current control loop. Model predictive current control method without the need for calculation of the weighing factors is utilized for the inner control loop, which generates a continuous set of voltage reference values that can be modulated and applied by the inverter to the induction machine. Interesting parallels are drawn between the developed method and state feedback principles that helped with the analysis of the stability and controllability. Simple speed and rotor flux estimator is implemented that helps achieve sensorless control. Simulation is conducted and the method shows great performance for speed tracking in a steady state, and during transients as well. Additionally, compared to the finite control set predictive current control, it shows less harmonic content in the generated torque on the rotor shaft. Full article
(This article belongs to the Topic Dynamical Systems: Theory and Applications)
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19 pages, 5338 KiB  
Article
Lane Detection Algorithm Using LRF for Autonomous Navigation of Mobile Robot
by Jong-Ho Han and Hyun-Woo Kim
Appl. Sci. 2021, 11(13), 6229; https://doi.org/10.3390/app11136229 - 5 Jul 2021
Cited by 2 | Viewed by 2801
Abstract
This paper proposes a lane detection algorithm using a laser range finder (LRF) for the autonomous navigation of a mobile robot. There are many technologies for ensuring the safety of vehicles, such as airbags, ABS, and EPS. Further, lane detection is a fundamental [...] Read more.
This paper proposes a lane detection algorithm using a laser range finder (LRF) for the autonomous navigation of a mobile robot. There are many technologies for ensuring the safety of vehicles, such as airbags, ABS, and EPS. Further, lane detection is a fundamental requirement for an automobile system that utilizes the external environment information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. In the case of a vision-based system, the recognition of the environment of a three-dimensional space becomes excellent only in good conditions for capturing images. However, there are so many unexpected barriers, such as bad illumination, occlusions, vibrations, and thick fog, that the vision-based method cannot be used for satisfying the abovementioned fundamental requirement. In this paper, a three-dimensional lane detection algorithm using LRF that is very robust against illumination is proposed. For the three-dimensional lane detection, the laser reflection difference between the asphalt and the lane according to color and distance has been utilized with the extraction of feature points. Further, a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been experimentally verified. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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16 pages, 19005 KiB  
Article
Experimental Investigation of Traditional Clay Brick and Lime Mortar Intended for Restoration of Cultural Heritage Sites
by Gayoon Lee, Jun Hyoung Park, Khoa V. A. Pham, Chan Hee Lee and Kihak Lee
Appl. Sci. 2021, 11(13), 6228; https://doi.org/10.3390/app11136228 - 5 Jul 2021
Cited by 7 | Viewed by 3869
Abstract
To properly restore masonry cultural heritage sites, the materials used for retrofitting can have a critical effect, and this requires standards for traditional Korean brick and lime mortar to be examined. This study experimentally investigated the material characteristics of Korean traditional bricks and [...] Read more.
To properly restore masonry cultural heritage sites, the materials used for retrofitting can have a critical effect, and this requires standards for traditional Korean brick and lime mortar to be examined. This study experimentally investigated the material characteristics of Korean traditional bricks and two types of lime mortar (quicklime lumps and powdered hydrated lime) and the strength of masonry specimens made from those materials. Four different mixing ratios of lime, sand and white cement were considered as material parameters in this study. The experiment included uniaxial compressive testing and flexural testing to examine the mortars’ mechanical properties, and compression tests, triplet shear tests and diagonal compression tests for the masonry specimens. The results found that the strength of the masonry specimens was not necessarily associated with the mortar’s strength, but rather the cohesion between brick and mortar. In the material test, adding white cement had no noticeable effect on mortar strength. Meanwhile, in the masonry specimen, the effect of the added white cement was significant in terms of compressive and shear strength. This suggests that the bonding ratio between mortar and brick, which is an important factor influencing the behavior of bricks, was stronger with the addition of white cement. Furthermore, it was found that quicklime lumps had a lower strength than powdered hydrated lime. The test specimen with white cement added to powdered hydrated lime exhibited the greatest strength. Full article
(This article belongs to the Special Issue Structural Performances of Concrete Composite Members: Experimental, Theoretical, Numerical Approaches II)
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8 pages, 4477 KiB  
Article
Evaluation of Corrosion Behavior on Crept AlSi10MnMg (AA365) Alloy Produced by High-Pressure Die-Casting (HPDC)
by Seonghwan Park, Cheolmin Ahn and Eunkyung Lee
Appl. Sci. 2021, 11(13), 6227; https://doi.org/10.3390/app11136227 - 5 Jul 2021
Cited by 4 | Viewed by 3400
Abstract
High-pressure die-cast AlSi10MnMg (AA365) alloys have been used as a material for automotive components exposed to high temperature and corrosive environments. This work determines the correlation of corrosion resistance with the intermetallic compounds and micro-voids of crept AA365 alloys under temperatures ranging from [...] Read more.
High-pressure die-cast AlSi10MnMg (AA365) alloys have been used as a material for automotive components exposed to high temperature and corrosive environments. This work determines the correlation of corrosion resistance with the intermetallic compounds and micro-voids of crept AA365 alloys under temperatures ranging from 373 K to 573 K with various applied stresses. The results showed that crept AA365 alloy at 473 K possessed a large amount of the intermetallic phases, compared with crept AA365 alloys at 373 K and 573 K due to the non-equilibrium solute atoms in Al matrix. By contrast, crept AA365 alloy at 573 K contained the lowest number of intermetallic precipitates owing to the remelting of the phases. With regard to the corrosion behavior, the corrosion potentials showed −687.0, −684.0, and −673.0 mVSCE of crept AA365 alloys at 373 K, 473 K, and 573 K, respectively, which means the corrosion occurred slowly on the crept AA365 alloy at 573 K, rather than at 373 K, 473 K. The value of the corrosion current density (Icorr) in the crept HPDC AA365 alloy at 473 K has the highest corrosion current density of 13.3 × 10−6 Acm−2, compared with others. It can be inferred that the high amount of intermetallic compounds gave rise to severe corrosion and led to the harmful micro-galvanic corrosion of crept AA365 alloy, rather than the micro-voids. Full article
(This article belongs to the Special Issue Metal Alloys: Fusion of the Cutting Edge Research Tools with Conventional Metal Study)
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18 pages, 4659 KiB  
Article
Energy, Exergy, and Environmental (3E) Analysis of Hydrocarbons as Low GWP Alternatives to R134a in Vapor Compression Refrigeration Configurations
by Morteza Ghanbarpour, Adrián Mota-Babiloni, Bassam E. Badran and Rahmatollah Khodabandeh
Appl. Sci. 2021, 11(13), 6226; https://doi.org/10.3390/app11136226 - 5 Jul 2021
Cited by 15 | Viewed by 2921
Abstract
The phase-down of hydrofluorocarbons and substitution with low global warming potential values are consequences of the awareness about the environmental impacts of greenhouse gases. This theoretical study evaluated the energy and exergy performances and the environmental impact of three vapor compression system configurations [...] Read more.
The phase-down of hydrofluorocarbons and substitution with low global warming potential values are consequences of the awareness about the environmental impacts of greenhouse gases. This theoretical study evaluated the energy and exergy performances and the environmental impact of three vapor compression system configurations operating with the hydrocarbons R290, R600a, and R1270 as alternatives to R134a. The refrigeration cycle configurations investigated in this study include a single-stage cycle, a cycle equipped with an internal heat exchanger, and a two-stage cycle with vapor injection. According to the results, the alternative hydrocarbon refrigerants could provide comparable system performance to R134a. The analysis results also revealed that using an internal heat exchanger or a flash tank vapor injection could improve the system’s efficiency while decreasing the heating capacity. The most efficient configuration was the two-stage refrigeration cycle with vapor injection, as revealed by the exergy analysis. The environmental impact analysis indicated that the utilization of environmentally-friendly refrigerants and improving the refrigeration system’s efficiency could mitigate equivalent CO2 emissions significantly. The utilization of hydrocarbons reduced the carbon footprint by 50%, while a 1% to 8% reduction could be achieved using the internal heat exchanger and flash tank vapor injection. Full article
(This article belongs to the Special Issue 10th Anniversary of Applied Sciences: Invited Papers in Applied Thermal Engineering)
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15 pages, 2036 KiB  
Article
A Study of Predictive Models for Early Outcomes of Post-Prostatectomy Incontinence: Machine Learning Approach vs. Logistic Regression Analysis Approach
by Seongkeun Park and Jieun Byun
Appl. Sci. 2021, 11(13), 6225; https://doi.org/10.3390/app11136225 - 5 Jul 2021
Cited by 7 | Viewed by 2580
Abstract
Background: Post-prostatectomy incontinence (PPI) is a major complication that can significantly decrease quality of life. Approximately 20% of patients experience consistent PPI as long as 1 year after radical prostatectomy (RP). This study develops a preoperative predictive model and compares its diagnostic [...] Read more.
Background: Post-prostatectomy incontinence (PPI) is a major complication that can significantly decrease quality of life. Approximately 20% of patients experience consistent PPI as long as 1 year after radical prostatectomy (RP). This study develops a preoperative predictive model and compares its diagnostic performance with conventional tools. Methods: A total of 166 prostate cancer patients who underwent magnetic resonance imaging (MRI) and RP were evaluated. According to the date of the RP, patients were divided into a development cohort (n = 109) and a test cohort (n = 57). Patients were classified as PPI early-recovery or consistent on the basis of pad usage for incontinence at 3 months after RP. Uni- and multi-variable logistic regression analyses were performed to identify associates of PPI early recovery. Four well-known machine learning algorithms (k-nearest neighbor, decision tree, support-vector machine (SVM), and random forest) and a logistic regression model were used to build prediction models for recovery from PPI using preoperative clinical and imaging data. The performances of the prediction models were assessed internally and externally using sensitivity, specificity, accuracy, and area-under-the-curve values and estimated probabilities and the actual proportion of cases of recovery from PPI within 3 months were compared using a chi-squared test. Results: Clinical and imaging findings revealed that age (70.1 years old for the PPI early-recovery group vs. 72.8 years old for the PPI consistent group), membranous urethral length (MUL; 15.7 mm for the PPI early-recovery group vs. 13.9 mm for the PPI consistent group), and obturator internal muscle (18.2 mm for the PPI early-recovery group vs. 17.5 mm for the PPI consistent group) were significantly different between the PPI early-recovery and consistent groups (all p-values < 0.05). Multivariate analysis confirmed that age (odds ratio = 1.07, 95% confidence interval = 1.02–1.14, p-value = 0.007) and MUL (odds ratio = 0.87, 95% confidence interval = 0.80–0.95, p-value = 0.002) were significant independent factors for early recovery. The prediction model using machine learning algorithms showed superior diagnostic performance compared with conventional logistic regression (AUC = 0.59 ± 0.07), especially SVM (AUC = 0.65 ± 0.07). Moreover, all models showed good calibration between the estimated probability and actual observed proportion of cases of recovery from PPI within 3 months. Conclusions: Preoperative clinical data and anatomic features on preoperative MRI can be used to predict early recovery from PPI after RP, and machine learning algorithms provide greater diagnostic accuracy compared with conventional statistical approaches. Full article
(This article belongs to the Special Issue Artificial Intelligence and Beyond in Medical and Healthcare Engineering)
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15 pages, 2193 KiB  
Article
Visual Tracking Control of Cable-Driven Hyper-Redundant Snake-Like Manipulator
by Qisong Zhou, Jianzhong Tang, Yong Nie, Zheng Chen and Long Qin
Appl. Sci. 2021, 11(13), 6224; https://doi.org/10.3390/app11136224 - 5 Jul 2021
Cited by 5 | Viewed by 2666
Abstract
The cable-driven hyper-redundant snake-like manipulator (CHSM) inspired by the biomimetic structure of vertebrate muscles and tendons, which consists of numerous joint units connected adjacently driven by elastic materials with hyper-redundant DOF, performs flexible kinematic skills and competitive compound capability under complicated working circumstances. [...] Read more.
The cable-driven hyper-redundant snake-like manipulator (CHSM) inspired by the biomimetic structure of vertebrate muscles and tendons, which consists of numerous joint units connected adjacently driven by elastic materials with hyper-redundant DOF, performs flexible kinematic skills and competitive compound capability under complicated working circumstances. Nevertheless, the drawback of lacking the ability to perceive the environment to perform intelligently in complex scenarios leaves a lot to be improved, which is the original intention to introduce visual tracking feedback acting as an instructor. In this paper, a cable-driven snake-like robotic arm combined with a visual tracking technique is introduced. A visual tracking approach based on dual correlation filter is designed to guide the CHSM in detecting the target and tracing after its trajectory. Specifically, it contains an adaptive optimization for the scale variation of the tracking target via pyramid sampling. For the CHSM, an explicit kinematics model is derived from its specific geometry relationships and followed by a simplification for the inverse kinematics based on some assumption or limitation. A control scheme is brought up to combine the kinematics with visual tracking via the processing tracking errors. The experimental results with a practical prototype validate the availability of the proposed compound control method with the derived kinematics model. Full article
(This article belongs to the Section Robotics and Automation)
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17 pages, 4809 KiB  
Article
STEP-NC Compliant Intelligent CNC Milling Machine with an Open Architecture Controller
by Mahanama Dharmawardhana, Asanga Ratnaweera and Gheorghe Oancea
Appl. Sci. 2021, 11(13), 6223; https://doi.org/10.3390/app11136223 - 5 Jul 2021
Cited by 8 | Viewed by 8953
Abstract
A STEP-NC or ISO 14649 compliant machine controller is developed, using Open Architecture Control technology for a three-axis Computer Numerical Control milling machine in this research. The controller is developed on a Raspberry Pi single-board computer, using C++ language. This new development is [...] Read more.
A STEP-NC or ISO 14649 compliant machine controller is developed, using Open Architecture Control technology for a three-axis Computer Numerical Control milling machine in this research. The controller is developed on a Raspberry Pi single-board computer, using C++ language. This new development is proposed as a low-cost alternative to ISO6983 standard, ensuring continuous integration in the CAD/CAM/CNC chain in machining; thus, it broadens the spectrum of problems handled by conventional CNC systems. The new machine controller is intelligent enough to extract geometrical and manufacturing parameters, cutting tool data, and material data from the STEP-NC file. Accordingly, tool paths for machining can be generated in the controller itself. The shop floor level modification of parameters and the possibility of regeneration of new toolpaths is an added advantage of this new controller. The modified or improved version of the STEP-NC file can be sent back to the CAD/CAM system to close the CAD/CAM/CNC chain. Machine condition monitoring can be achieved by connecting sensors through an available slave I/O board. In the present development, the current drawn by each servo motor is fed back to the controller for cutting condition monitoring. A laboratory scale three-axis CNC milling machine is developed to test the performance of the newly developed controller. The accuracy of positioning, perpendicularity of axes and linearity of this machine are experimentally verified through standard tests. The STEP-NC compliance of the controller is tested and verified, using a STEP-NC program derived based on a sample program given in ISO 14649 standard. Full article
(This article belongs to the Section Robotics and Automation)
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26 pages, 5078 KiB  
Article
Improving Bridge Expansion and Contraction Installation Replacement Decision System Using Hybrid Chaotic Whale Optimization Algorithm
by Zian Xu and Minshui Huang
Appl. Sci. 2021, 11(13), 6222; https://doi.org/10.3390/app11136222 - 5 Jul 2021
Cited by 3 | Viewed by 3372
Abstract
Bridge expansion and contraction installation (BECI) has proved to be an essential component of the bridge structure due to its stability, comfort, and durability benefits. At present, traditional replacement technologies for modular type, comb plate type, and seamless type BECIs are widely applied [...] Read more.
Bridge expansion and contraction installation (BECI) has proved to be an essential component of the bridge structure due to its stability, comfort, and durability benefits. At present, traditional replacement technologies for modular type, comb plate type, and seamless type BECIs are widely applied worldwide. Nevertheless, it is unfortunate that the research conducted on decision-making (DM) approaches for the technical condition assessment and the optimal replacement plan selection of existing BECIs remain scarce, which results in the waste of resources and the increase in cost. Therefore, a BECI technical condition assessment approach, which contains specific on-site inspection regulations with both qualitative and quantitative descriptions, is proposed in this research, and a corresponding calculation program has been developed based on the MATLAB platform, which provides the basis for the necessity of replacement. Simultaneously, the hybrid chaotic whale optimization algorithm is designed and performed to improve and automate the process of optimal replacement plan selection under the assistance of the analytic hierarchy process (AHP), where both the achievement in consistency modification and the reservation of initial information are perused, and its superiority and effectiveness are verified via the comparative experimental analysis. The improved BECI replacement decision system is established, and the corresponding case study demonstrates that the proposed system in this research proves reasonable and feasible. The improved system can effectively assist bridge managers in making more informed operation and maintenance (O and M) decisions in actual engineering projects. Full article
(This article belongs to the Special Issue Technology and Management Applied in Construction Engineering Projects)
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13 pages, 3747 KiB  
Article
Estimating Turbulence Distribution over a Heterogeneous Path Using Time-Lapse Imagery from Dual Cameras
by Benjamin Wilson, Santasri Bose-Pillai, Jack McCrae, Kevin Keefer and Steven Fiorino
Appl. Sci. 2021, 11(13), 6221; https://doi.org/10.3390/app11136221 - 5 Jul 2021
Cited by 5 | Viewed by 2011
Abstract
Knowledge of turbulence distribution along an experimental path can help in effective turbulence compensation and mitigation. Although scintillometers are traditionally used to measure the strength of turbulence, they provide a path-integrated measurement and have limited operational ranges. A technique to profile turbulence using [...] Read more.
Knowledge of turbulence distribution along an experimental path can help in effective turbulence compensation and mitigation. Although scintillometers are traditionally used to measure the strength of turbulence, they provide a path-integrated measurement and have limited operational ranges. A technique to profile turbulence using time-lapse imagery of a distant target from spatially separated cameras is presented here. The method uses the turbulence induced differential motion between pairs of point features on a target, sensed at a single camera and between cameras to extract turbulence distribution along the path. The method is successfully demonstrated on a 511 m almost horizontal path going over half concrete and half grass. An array of Light-Emitting Diodes (LEDs) of non-uniform separation is imaged by a pair of cameras, and the extracted turbulence profiles are validated against measurements from 3D sonic anemometers placed along the path. A short-range experiment with a heat source to create local turbulence spike gives good results as well. Because the method is phase-based, it does not suffer from saturation issues and can potentially be applied over long ranges. Although in the present work, a cooperative target has been used, the technique can be used with non-cooperative targets. Application of the technique to images collected over slant paths with elevated targets can aid in understanding the altitude dependence of turbulence in the surface layer. Full article
(This article belongs to the Special Issue Atmospheric Optics Sensing, Mitigation and Exploitation)
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18 pages, 3727 KiB  
Article
Safe Local Aerial Manipulation for the Installation of Devices on Power Lines: AERIAL-CORE First Year Results and Designs
by Jonathan Cacace, Santos M. Orozco-Soto, Alejandro Suarez, Alvaro Caballero, Matko Orsag, Stjepan Bogdan, Goran Vasiljevic, Emad Ebeid, Jose Alberto Acosta Rodriguez and Anibal Ollero
Appl. Sci. 2021, 11(13), 6220; https://doi.org/10.3390/app11136220 - 5 Jul 2021
Cited by 32 | Viewed by 4040
Abstract
The power grid is an essential infrastructure in any country, comprising thousands of kilometers of power lines that require periodic inspection and maintenance, carried out nowadays by human operators in risky conditions. To increase safety and reduce time and cost with respect to [...] Read more.
The power grid is an essential infrastructure in any country, comprising thousands of kilometers of power lines that require periodic inspection and maintenance, carried out nowadays by human operators in risky conditions. To increase safety and reduce time and cost with respect to conventional solutions involving manned helicopters and heavy vehicles, the AERIAL-CORE project proposes the development of aerial robots capable of performing aerial manipulation operations to assist human operators in power lines inspection and maintenance, allowing the installation of devices, such as bird flight diverters or electrical spacers, and the fast delivery and retrieval of tools. This manuscript describes the goals and functionalities to be developed for safe local aerial manipulation, presenting the preliminary designs and experimental results obtained in the first year of the project. Full article
(This article belongs to the Special Issue Aerial Robotics for Inspection and Maintenance)
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16 pages, 5069 KiB  
Article
Packet Optical Transport Network Slicing with Hard and Soft Isolation
by Samier Barguil, Victor Lopez Alvarez, Luis Miguel Contreras Murillo, Oscar Gonzalez de Dios, Alejandro Alcala Alvarez, Carlos Manso, Pol Alemany, Ramon Casellas, Ricardo Martinez, David Gonzalez-Perez, Xufeng Liu, Jose-Miguel Pulido, Juan Pedro Fernandez-Palacios, Raul Muñoz and Ricard Vilalta
Appl. Sci. 2021, 11(13), 6219; https://doi.org/10.3390/app11136219 - 5 Jul 2021
Cited by 4 | Viewed by 3549
Abstract
Network operators have been dealing with the necessity of a dynamic network resources allocation to provide a new generation of customer-tailored applications. In that sense, Telecom providers have to migrate their BSS/OSS systems and network infrastructure to more modern solutions to introduce end-to-end [...] Read more.
Network operators have been dealing with the necessity of a dynamic network resources allocation to provide a new generation of customer-tailored applications. In that sense, Telecom providers have to migrate their BSS/OSS systems and network infrastructure to more modern solutions to introduce end-to-end automation and support the new use cases derived from the 5G adoption and transport network slices. In general, there is a joint agreement on making this transition to an architecture defined by programmable interfaces and standard protocols. Hence, this paper uses the iFusion architecture to control and program the network infrastructure. The work presents an experimental validation of the network slicing instantiation in an IP/Optical environment using a set of standard protocols and interfaces. The work provides results of the creation, modification and deletion of the network slices. Furthermore, it demonstrates the usage of standard communication protocols (Netconf and Restconf) in combination with standard YANG data models. Full article
(This article belongs to the Collection New Trends in Optical Networks)
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18 pages, 6614 KiB  
Article
Thermal and Mechanical Assessment of PLA-SEBS and PLA-SEBS-CNT Biopolymer Blends for 3D Printing
by Balázs Ádám and Zoltán Weltsch
Appl. Sci. 2021, 11(13), 6218; https://doi.org/10.3390/app11136218 - 5 Jul 2021
Cited by 21 | Viewed by 3350
Abstract
Polylactic acid (PLA) is one of the most promising biopolymers often used as a raw material in 3D printing in many industrial areas. It has good mechanical properties, is characterized by high strength and stiffness, but unfortunately, it has some disadvantages; one is [...] Read more.
Polylactic acid (PLA) is one of the most promising biopolymers often used as a raw material in 3D printing in many industrial areas. It has good mechanical properties, is characterized by high strength and stiffness, but unfortunately, it has some disadvantages; one is brittleness, and the other is slow crystallization. Amounts of 1–5% SEBS (styrene-ethylene-butylene-styrene) thermoplastic elastomer were blended into the PLA and the thermal and mechanical properties were investigated. DSC (Differential Scanning Calorimetry) measurements on the filaments have shown that SEBS increases the initial temperature of crystallization, thereby acting as a nucleating agent. The cooling rate of 3D printing, on the other hand, is too fast for PLA, so printed specimens behave almost amorphously. The presence of SEBS increases the impact strength, neck formation appears during the tensile test, and in the bending test, the mixture either suffers partial fracture or only bends without fracture. Samples containing 1% SEBS were selected for further analysis, mixed with 0.06 and 0.1% carbon nanotubes (CNTs), and tested for thermal and mechanical properties. As a result of CNTs, another peak appeared on the DSC curve in addition to the original single-peak crystallization, and the specimens previously completely broken in the mechanical tests suffered partial fractures, and the partially fractured pieces almost completely regained their original shape at the end of the test. Full article
(This article belongs to the Special Issue Biomaterials, Polymers and Tissue Engineering)
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5 pages, 634 KiB  
Article
Comparative Analysis of Derivatization Reagents for Catecholamines and Amino Acids
by Shu Taira, Akari Ikeda, Shoko Kobayashi, Hitomi Shikano, Ryuzoh Ikeda, Yuko Maejima, Shoichiro Horita, Jun Yokoyama and Kenju Shimomura
Appl. Sci. 2021, 11(13), 6217; https://doi.org/10.3390/app11136217 - 5 Jul 2021
Cited by 4 | Viewed by 2997
Abstract
We compared four derivatization reagents to analyze catecholamines and amino acids by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. 2,4,6-Trimethylpyrylium tetrafluoroborate (TMPy), 2,4-diphenyl-pyranylium tetrafluoroborate (DPP-TFB), 4-(anthracen-9-yl)-2-fluoro-1-methylpyridin-1-ium iodide (FMP-10), and triphenyl pyrilium (TPP) were used as derivatization reagents that can specifically modify primary amines or [...] Read more.
We compared four derivatization reagents to analyze catecholamines and amino acids by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. 2,4,6-Trimethylpyrylium tetrafluoroborate (TMPy), 2,4-diphenyl-pyranylium tetrafluoroborate (DPP-TFB), 4-(anthracen-9-yl)-2-fluoro-1-methylpyridin-1-ium iodide (FMP-10), and triphenyl pyrilium (TPP) were used as derivatization reagents that can specifically modify primary amines or hydroxy groups in target molecules. Three derivatization reagents, not including TPP, reacted with all target molecules. The derived catecholamines dopamine and L-DOPA, and the amino acids GABA and glycine, were efficiently ionized in comparison with non-derivatized targets. Comparative analysis indicated that TMPy and FMP-10 produced general increases in signal-to-noise ratios (S/N), whereas DPP and TPP produced specific increases in the S/N of GABA and DA. Notably, TMPy is a small molecule that efficiently reacts with target molecules due to the absence of high bulk and steric hinderance. Full article
(This article belongs to the Special Issue Modern Molecular Imaging: New Frontiers in Biotechnology)
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16 pages, 3450 KiB  
Article
Informative Biomarkers for Autism Spectrum Disorder Diagnosis in Functional Magnetic Resonance Imaging Data on the Default Mode Network
by Aikaterini S. Karampasi, Antonis D. Savva, Vasileios Ch. Korfiatis, Ioannis Kakkos and George K. Matsopoulos
Appl. Sci. 2021, 11(13), 6216; https://doi.org/10.3390/app11136216 - 5 Jul 2021
Cited by 11 | Viewed by 4397
Abstract
Effective detection of autism spectrum disorder (ASD) is a complicated procedure, due to the hundreds of parameters suggested to be implicated in its etiology. As such, machine learning methods have been consistently applied to facilitate diagnosis, although the scarcity of potent autism-related biomarkers [...] Read more.
Effective detection of autism spectrum disorder (ASD) is a complicated procedure, due to the hundreds of parameters suggested to be implicated in its etiology. As such, machine learning methods have been consistently applied to facilitate diagnosis, although the scarcity of potent autism-related biomarkers is a bottleneck. More importantly, the variability of the imported attributes among different sites (e.g., acquisition parameters) and different individuals (e.g., demographics, movement, etc.) pose additional challenges, eluding adequate generalization and universal modeling. The present study focuses on a data-driven approach for the identification of efficacious biomarkers for the classification between typically developed (TD) and ASD individuals utilizing functional magnetic resonance imaging (fMRI) data on the default mode network (DMN) and non-physiological parameters. From the fMRI data, static and dynamic connectivity were calculated and fed to a feature selection and classification framework along with the demographic, acquisition and motion information to obtain the most prominent features in regard to autism discrimination. The acquired results provided high classification accuracy of 76.63%, while revealing static and dynamic connectivity as the most prominent indicators. Subsequent analysis illustrated the bilateral parahippocampal gyrus, right precuneus, midline frontal, and paracingulate as the most significant brain regions, in addition to an overall connectivity increment. Full article
(This article belongs to the Special Issue Advances in Biomedical Signal Processing in Health Care)
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18 pages, 1149 KiB  
Article
Changes in the Biochemical Composition and Physicochemical Properties of Apples Stored in Controlled Atmosphere Conditions
by Aurita Butkeviciute, Jonas Viskelis, Pranas Viskelis, Mindaugas Liaudanskas and Valdimaras Janulis
Appl. Sci. 2021, 11(13), 6215; https://doi.org/10.3390/app11136215 - 5 Jul 2021
Cited by 9 | Viewed by 4309
Abstract
Apples are an important component of the diet and are used in the food industry in the production of food products and beverages. The aim of the study was to determine the changes in the biochemical composition and physicochemical properties of apples stored [...] Read more.
Apples are an important component of the diet and are used in the food industry in the production of food products and beverages. The aim of the study was to determine the changes in the biochemical composition and physicochemical properties of apples stored in a controlled atmosphere. We studied the biochemical composition (sugars, ascorbic acid, soluble solids, and titratable acidity) and physicochemical properties (color coordinates, peel, and flesh firmness) in the apple samples before placing them in the controlled atmosphere chambers and at the end of the experiment 8 months later. The total content of sugars and soluble solids was found to increase in the samples of apples stored in I to VIII conditions. The study showed a decrease in titratable acidity in apple samples of all cultivars stored in I to VIII conditions. The values of C*, L*, a*, and b* co-ordinates of apple colors were evaluated. Apple samples stored in VI conditions were the lightest color, and their lightness was close to that of fresh fruit. The firmness of apple peel samples of the ‘Sampion’ cultivar stored in I and III–VI conditions increased. The study is valuable and proves that, under the studied conditions, it is possible to extend the time of the provision of apples to the consumers with minimal changes in their chemical composition and nutritional value. Full article
(This article belongs to the Special Issue Biochemical Composition of Food)
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14 pages, 2396 KiB  
Article
Asynchrony Drives Plant and Animal Community Stability in Mediterranean Coastal Dunes
by Tania L.F. Bird, Pua Bar (Kutiel), Elli Groner and Amos Bouskila
Appl. Sci. 2021, 11(13), 6214; https://doi.org/10.3390/app11136214 - 5 Jul 2021
Cited by 3 | Viewed by 2673
Abstract
Substantial evidence now suggests that a positive diversity–stability relationship exists. Yet few studies examine the facets of biodiversity that contribute to this relationship, and empirical research is predominantly conducted on grassland communities under controlled conditions. We investigate the roles of species richness, environmental [...] Read more.
Substantial evidence now suggests that a positive diversity–stability relationship exists. Yet few studies examine the facets of biodiversity that contribute to this relationship, and empirical research is predominantly conducted on grassland communities under controlled conditions. We investigate the roles of species richness, environmental condition (vegetation cover), asynchrony, and weighted population stability in driving community stability across multiple taxa. We used data from a Long-term Ecological Research project to investigate temporal stability of annual plants, beetles, reptiles, and rodents in Nizzanim Coastal Sand Dune Nature Reserve in Israel. All four taxa had a strong positive relationship between asynchrony and community stability. Only rodents showed a positive richness–stability relationship. Perennial plant cover had a significant relationship with community stability for three taxa, but the direction of the correlation varied. Asynchrony had a stronger relationship with perennial plant cover than it did with richness for both plants and beetles. We suggest that community stability is driven by asynchrony for flora as well as fauna. Stability appears to be determined by species’ interactions and their responses to the environment, and not always by diversity. This has important consequences for understanding the effects of environmental degradation on ecosystem stability and productivity, which have destabilizing consequences beyond biodiversity loss. Full article
(This article belongs to the Special Issue Soil Erosion: Dust Control and Sand Stabilization, Volume II)
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12 pages, 1365 KiB  
Article
MLUTNet: A Neural Network for Memory Based Reconfigurable Logic Device Architecture
by Xuechen Zang and Shigetoshi Nakatake
Appl. Sci. 2021, 11(13), 6213; https://doi.org/10.3390/app11136213 - 5 Jul 2021
Viewed by 2088
Abstract
Neural networks have been widely used and implemented on various hardware platforms, but high computational costs and low similarity of network structures relative to hardware structures are often obstacles to research. In this paper, we propose a novel neural network in combination with [...] Read more.
Neural networks have been widely used and implemented on various hardware platforms, but high computational costs and low similarity of network structures relative to hardware structures are often obstacles to research. In this paper, we propose a novel neural network in combination with the structural features of a recently proposed memory-based programmable logic device, compare it with the standard structure, and test it on common datasets with full and binary precision, respectively. The experimental results reveal that the new structured network can provide almost consistent full-precision performance and binary-precision performance ranging from 61.0% to 78.8% after using sparser connections and about 50% reduction in the size of the weight matrix. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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19 pages, 4649 KiB  
Article
Advanced Configuration Parameters of Post Processor Influencing Tensile Testing PLA and Add-Mixtures in Polymer Matrix in the Process of FDM Technology
by Jozef Török, Monika Törökova, Darina Duplakova, Zuzana Murcinkova, Jan Duplak, Jakub Kascak and Monika Karkova
Appl. Sci. 2021, 11(13), 6212; https://doi.org/10.3390/app11136212 - 5 Jul 2021
Cited by 9 | Viewed by 2813
Abstract
The present paper focuses on the configuration possibilities of post -processor influencing mechanical properties of a given test sample produced by the FDM printer from different materials. The research consists of assessing the composite material configurations through a static tensile test conducted on [...] Read more.
The present paper focuses on the configuration possibilities of post -processor influencing mechanical properties of a given test sample produced by the FDM printer from different materials. The research consists of assessing the composite material configurations through a static tensile test conducted on 80 samples produced. The samples were produced based on ISO 527-2 standard, type 1A, with a horizontal position and a layer height of 0.2 mm. The individual samples consisted of four basic groups of materials—the pure Polylactic acid (PLA) plastic (reference sample), and three composite samples with admixtures—PLA matrix with a copper admixture, PLA matrix with an iron admixture, and PLA matrix with a steel admixture. The static tensile test was conducted at a test speed of 5 mm/min. During the research, reference samples (pure PLA) were assessed in five orientations. Samples made of the PLA composite materials with admixtures were manufactured, tested, and evaluated only in the 0° orientation. The paper concludes by comparing the results of measurement with the original material, free from additives, and with the researched influence of the orientation of the prints on the resulting mechanical properties of shear samples and their surface structure. In the conducted experiments, the lowest tensile strength has been demonstrated in test samples the orbital transitions and the upper surface layers of which were parallel to the infill. Full article
(This article belongs to the Section Materials Science and Engineering)
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17 pages, 837 KiB  
Review
Regenerative Endodontics as the Future Treatment of Immature Permanent Teeth
by Justyna Zbańska, Katarzyna Herman, Piotr Kuropka and Maciej Dobrzyński
Appl. Sci. 2021, 11(13), 6211; https://doi.org/10.3390/app11136211 - 5 Jul 2021
Cited by 6 | Viewed by 6442
Abstract
The regenerative endodontic procedure (REP) is an alternative solution for endodontic treatment of permanent teeth with incomplete root apex development. It results in angiogenesis, reinnervation, and further root formation. Indications for REP include immature permanent teeth with necrotic pulp and inflammatory lesions of [...] Read more.
The regenerative endodontic procedure (REP) is an alternative solution for endodontic treatment of permanent teeth with incomplete root apex development. It results in angiogenesis, reinnervation, and further root formation. Indications for REP include immature permanent teeth with necrotic pulp and inflammatory lesions of the periapical tissues. The main contraindications comprise significant destruction of the tooth tissues and a lack of patient cooperation. We distinguish the following stages of this procedure: disinfection of the canal, delivery of the REP components, closure of the cavity, and follow-up appointments. For effective canal disinfection, the use of both rinsing agents and intracanal medicaments is suggested. Sodium hypochlorite and triple antibiotic paste are used most commonly. Light-activated disinfection is proposed as an alternative method. The prerequisite for the regeneration process of the pulp is the supply of its essential components: stem cells, growth factors, and scaffolds to the canal lumen. Blood clotting, platelet-rich plasma, and platelet-rich fibrin are used for this purpose. For a proper course of REP, it is also necessary to close the tooth canal tightly. For this purpose, mineral trioxide aggregate (MTA), tricalcium silicate (Biodentine), or types of glass ionomer cement are employed. The patient should attend regularly scheduled follow-up appointments and each time undergo a thorough interview, physical and radiological examination. The most important indicator of a successful REP is the continued growth of the root in length and thickness and the closure of the root apex visible on X-rays. Many different proposals for a management protocol have been published; the following paper proposes the authors’ original scheme. Regenerative endodontics is the future of the endodontic treatment of immature permanent teeth; however, it still requires a lot of research to refine and standardize the treatment protocol. The application of tissue engineering methods seems to be promising, also for mature teeth treatment. Full article
(This article belongs to the Section Materials Science and Engineering)
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13 pages, 4755 KiB  
Review
Application of Gas Foil Bearings in China
by Yu Hou, Qi Zhao, Yu Guo, Xionghao Ren, Tianwei Lai and Shuangtao Chen
Appl. Sci. 2021, 11(13), 6210; https://doi.org/10.3390/app11136210 - 5 Jul 2021
Cited by 24 | Viewed by 5747
Abstract
Gas foil bearing has been widely used in high-speed turbo machinery due to its oil-free, wide temperature range, low cost, high adaptability, high stability and environmental friendliness. In this paper, state-of-the-art investigations of gas foil bearings are reviewed, mainly on the development of [...] Read more.
Gas foil bearing has been widely used in high-speed turbo machinery due to its oil-free, wide temperature range, low cost, high adaptability, high stability and environmental friendliness. In this paper, state-of-the-art investigations of gas foil bearings are reviewed, mainly on the development of the high-speed turbo machinery in China. After decades of development, progress has been achieved in the field of gas foil bearing in China. Small-scale applications of gas foil bearing have been realized in a variety of high-speed turbo machinery. The prospects and markets of high-speed turbo machinery are very broad. Various high-speed turbomachines with gas foil bearings have been developed. Due to the different application occasions, higher reliability requirements are imposed on the foil bearing technology. Therefore, its design principle, theory, and manufacturing technology should be adaptive to new application occasions before mass production. Thus, there are still a number of inherent challenges that must be addressed, for example, thermal management, rotor-dynamic stability and wear-resistant coatings. Full article
(This article belongs to the Special Issue Gas Bearings: Modelling, Design and Applications)
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