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Appl. Sci., Volume 11, Issue 9 (May-1 2021) – 531 articles

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Open AccessFeature PaperReview
Percutaneous Electrical Nerve Stimulation (PENS) as a Rehabilitation Approach for Reducing Mixed Chronic Pain in Patients with Musculoskeletal Disorders
by , , , , and
Appl. Sci. 2021, 11(9), 4257; https://doi.org/10.3390/app11094257 (registering DOI) - 08 May 2021
Abstract
“Mixed pain” is a term recently introduced to define the overlapping of nociceptive, neuropathic and nociplastic pain. To date, it has been reported that pharmacological treatments might have a modest effectiveness on patients affected by mixed chronic pain, with detrimental consequences in terms [...] Read more.
“Mixed pain” is a term recently introduced to define the overlapping of nociceptive, neuropathic and nociplastic pain. To date, it has been reported that pharmacological treatments might have a modest effectiveness on patients affected by mixed chronic pain, with detrimental consequences in terms of disability, physical function and health-related quality of life. In this scenario, Percutaneous Electrical Nerve Stimulation (PENS), a mini-invasive neuromodulation technique, has been recently suggested as a promising approach for the complex management of mixed pain in musculoskeletal disorders. Albeit PENS showed to be effective in reducing unspecified pain in several chronic pain conditions, there is still a lack of evidence in the literature about its role in the management of neuropathic or mixed pain not responsive to pharmacological treatments. Therefore, by the present scoping review, we portray the potential effects of PENS in the multidisciplinary and multidimensional management of mixed chronic pain in patients with musculoskeletal disorders. Full article
(This article belongs to the Special Issue Musculoskeletal Rehabilitation)
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Open AccessArticle
Hot Resistance of Spores from the Thermophilic Bacillus horneckiae SBP3 of Shallow Hydrothermal Vent Origin Elucidated by Spectroscopic Analyses
by , , , , and
Appl. Sci. 2021, 11(9), 4256; https://doi.org/10.3390/app11094256 (registering DOI) - 08 May 2021
Abstract
Spores from Bacillus horneckiae SBP3 (SBP3) of shallow hydrothermal vent origin have recently been reported to survive extreme conditions more often than their close phylogenetic relatives B. horneckiae DSM 23495T (BHO) and B. subtilis 168 (BSU) used in biodosimetry and the space [...] Read more.
Spores from Bacillus horneckiae SBP3 (SBP3) of shallow hydrothermal vent origin have recently been reported to survive extreme conditions more often than their close phylogenetic relatives B. horneckiae DSM 23495T (BHO) and B. subtilis 168 (BSU) used in biodosimetry and the space microbiology model. To investigate the structures of unheated spores, Fourier-transform infrared spectroscopy (FTIR) analysis was used. The FTIR spectra of the spores from the strains SBP3, BHO and BSU mainly differed in the region that referred to lipids and amino acids or polypeptides, indicating that the SBP3 spores were richer in saturated fatty acids, and the protein structures of SBP3 and BHO spores were more aggregated and complex than those of BSU. SBP3 spores were more resistant (LD90 = 4.2 ± 0.3 min) to wet heat treatment (98 °C) than BHO (LD90 = 1.8 ± 0.2 min) and BSU (LD90 = 2.9 ± 0.5 min) spores were. In comparison to the untreated spores, the Raman spectra of the wet-heat-treated SBP3 spores showed minor variations in the bands that referred to proteins, whereas major changes were observed in the bands that referred to lipids and amide I in the heated BSU spores and to both lipids and proteins bands in the treated BHO spores. These results suggest that the major stability of SBP3 spore proteins could explain their greater resistance to wet heat compared to BHO and BSU. Our findings provide basic information for further comparative studies into spore responses to natural and laboratory stresses, which are useful in several different fields, such as astrobiology. Full article
(This article belongs to the Special Issue Applications and Advancements of Spectroscopy)
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Open AccessArticle
Non-Contact SpO2 Prediction System Based on a Digital Camera
by , , and
Appl. Sci. 2021, 11(9), 4255; https://doi.org/10.3390/app11094255 (registering DOI) - 07 May 2021
Abstract
Patients with the COVID-19 condition require frequent and accurate blood oxygen saturation (SpO2) monitoring. The existing pulse oximeters, however, require contact-based measurement using clips or otherwise fixed sensor units or need dedicated hardware which may cause inconvenience and involve additional appointments with the [...] Read more.
Patients with the COVID-19 condition require frequent and accurate blood oxygen saturation (SpO2) monitoring. The existing pulse oximeters, however, require contact-based measurement using clips or otherwise fixed sensor units or need dedicated hardware which may cause inconvenience and involve additional appointments with the patient. This study proposes a computer vision-based system using a digital camera to measure SpO2 on the basis of the imaging photoplethysmography (iPPG) signal extracted from the human’s forehead without the need for restricting the subject or physical contact. The proposed camera-based system decomposes the iPPG obtained from the red and green channels into different signals with different frequencies using a signal decomposition technique based on a complete Ensemble Empirical Mode Decomposition (EEMD) technique and Independent Component Analysis (ICA) technique to obtain the optical properties from these wavelengths and frequency channels. The proposed system is convenient, contactless, safe and cost-effective. The preliminary results for 70 videos obtained from 14 subjects of different ages and with different skin tones showed that the red and green wavelengths could be used to estimate SpO2 with good agreement and low error ratio compared to the gold standard of pulse oximetry (SA210) with a fixed measurement position. Full article
(This article belongs to the Special Issue Novel Advances of Image and Signal Processing)
Open AccessArticle
Sharing Soil and Building Geophysical Data for Seismic Characterization of Cities Using CLARA WebGIS: A Case Study of Matera (Southern Italy)
by , , , , , , and
Appl. Sci. 2021, 11(9), 4254; https://doi.org/10.3390/app11094254 (registering DOI) - 07 May 2021
Abstract
In the context of seismic risk, studying the characteristics of urban soils and of the built environment means adopting a holistic vision of the city, taking a step forward compared to the current microzonation approach. Based on this principle, CLARA WebGIS aims to [...] Read more.
In the context of seismic risk, studying the characteristics of urban soils and of the built environment means adopting a holistic vision of the city, taking a step forward compared to the current microzonation approach. Based on this principle, CLARA WebGIS aims to collect, organize, and disseminate the available information on soils and buildings in the urban area of Matera. The geodatabase is populated with (i) 488 downloadable geological, geotechnical, and geophysical surveys; (ii) geological, geomorphological, and seismic homogeneous microzone maps; and (iii) a new Digital Surface Model. The CLARA WebGIS is the first publicly available database that reports for the whole urban area the spatial distribution of the fundamental frequencies for soils and the overlying 4043 buildings, along with probability levels of soil-building resonance. The WebGIS is aimed at a broad range of end users (local government, engineers, geologists, etc.) as a support to the implementation of seismic risk mitigation strategies in terms of urban planning, seismic retrofitting, and management of post-earthquake crises. We recommend that the database be managed by local administrators, who would also have the task of deciding on future developments and continuous updating as new data becomes available. Full article
Open AccessArticle
Development and Characterization of 3D Printed Multifunctional Bioscaffolds Based on PLA/PCL/HAp/BaTiO3 Composites
by , and
Appl. Sci. 2021, 11(9), 4253; https://doi.org/10.3390/app11094253 (registering DOI) - 07 May 2021
Abstract
Bone substitute materials are placed in bone defects and play an important role in bone regeneration and fracture healing. The main objective of the present research is fabrication through the technique of 3D printing and the characterization of innovative composite bone scaffolds composed [...] Read more.
Bone substitute materials are placed in bone defects and play an important role in bone regeneration and fracture healing. The main objective of the present research is fabrication through the technique of 3D printing and the characterization of innovative composite bone scaffolds composed of polylactic acid (PLA), poly (ε-caprolactone) (PCL) while hydroxyapatite (HAp), and/or barium titanate (BaTiO3—BT) used as fillers. Composite filaments were prepared using a single screw melt extruder, and finally, 3D composite scaffolds were fabricated using the fused deposition modeling (FDM) technique. Scanning electron microscopy (SEM) images showed a satisfactory distribution of the fillers into the filaments and the printed objects. Furthermore, differential scanning calorimetry (DSC) measurements revealed that PLA/PCL filaments exhibit lower glass transition and melting point temperatures than the pure PLA filaments. Finally, piezoelectric and dielectric measurements of the 3D objects showed that composite PLA/PCL scaffolds containing HAp and BT exhibited piezoelectric coefficient (d33) values close to the human bone and high dielectric permittivity values. Full article
(This article belongs to the Special Issue Biomaterial Synthesis and Application)
Open AccessArticle
Underwater Excavation Records Using Underwater Acoustic Survey: A Case Study in South Korea
by , , and
Appl. Sci. 2021, 11(9), 4252; https://doi.org/10.3390/app11094252 (registering DOI) - 07 May 2021
Abstract
The most effective method for surveying underwater archeological sites is visually identifying areas with relics or remains through diving surveys. However, during underwater excavations, it is difficult to obtain images in turbid water. Furthermore, on-site diving is costly and time-consuming. Marine acoustic geophysical [...] Read more.
The most effective method for surveying underwater archeological sites is visually identifying areas with relics or remains through diving surveys. However, during underwater excavations, it is difficult to obtain images in turbid water. Furthermore, on-site diving is costly and time-consuming. Marine acoustic geophysical survey equipment is not significantly affected by underwater turbidity, and underwater excavations often rely on geophysical equipment for surface inspections. This study aimed to improve existing underwater excavation imaging through the application of acoustic survey methods. Underwater surveys were conducted via acoustic marine geophysical survey devices at three historically significant underwater sites in South Korea: Dangampo, Nakwoldo Island, and the Battle of Myeongnyang. At the Dangampo site, surveys were conducted using three different sonar devices—side scan sonar, multibeam echo sounder, and scanning sonar—and the results were compared; scanning sonar was the most effective. The methodology was further refined during excavations at the Nakwoldo and Myeongnyang sites. Results show that the scanning sonar can produce images that are more accurate than on-site drawings produced during underwater excavations, even in turbid underwater environments. Moreover, applied in conjunction with high-frequency geophysical exploration techniques, scanning sonar can significantly increase the reliability of investigations of buried underwater remains and relics. Full article
(This article belongs to the Section Marine Science and Engineering)
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Open AccessArticle
Machine Learning Model of Dimensionless Numbers to Predict Flow Patterns and Droplet Characteristics for Two-Phase Digital Flows
by , , and
Appl. Sci. 2021, 11(9), 4251; https://doi.org/10.3390/app11094251 - 07 May 2021
Abstract
In the digital microfluidic experiments, the droplet characteristics and flow patterns are generally identified and predicted by the empirical methods, which are difficult to process a large amount of data mining. In addition, due to the existence of inevitable human invention, the inconsistent [...] Read more.
In the digital microfluidic experiments, the droplet characteristics and flow patterns are generally identified and predicted by the empirical methods, which are difficult to process a large amount of data mining. In addition, due to the existence of inevitable human invention, the inconsistent judgment standards make the comparison between different experiments cumbersome and almost impossible. In this paper, we tried to use machine learning to build algorithms that could automatically identify, judge, and predict flow patterns and droplet characteristics, so that the empirical judgment was transferred to be an intelligent process. The difference on the usual machine learning algorithms, a generalized variable system was introduced to describe the different geometry configurations of the digital microfluidics. Specifically, Buckingham’s theorem had been adopted to obtain multiple groups of dimensionless numbers as the input variables of machine learning algorithms. Through the verification of the algorithms, the SVM and BPNN algorithms had classified and predicted the different flow patterns and droplet characteristics (the length and frequency) successfully. By comparing with the primitive parameters system, the dimensionless numbers system was superior in the predictive capability. The traditional dimensionless numbers selected for the machine learning algorithms should have physical meanings strongly rather than mathematical meanings. The machine learning algorithms applying the dimensionless numbers had declined the dimensionality of the system and the amount of computation and not lose the information of primitive parameters. Full article
(This article belongs to the Section Fluid)
Open AccessArticle
Analytical Modeling of Current-Voltage Photovoltaic Performance: An Easy Approach to Solar Panel Behavior
by , , , , , , , and
Appl. Sci. 2021, 11(9), 4250; https://doi.org/10.3390/app11094250 - 07 May 2021
Abstract
In this paper, we propose very simple analytical methodologies for modeling the behavior of photovoltaic (solar cells/panels) using a one-diode/two-resistor (1-D/2-R) equivalent circuit. A value of a = 1 for the ideality factor is shown to be very reasonable for the different photovoltaic [...] Read more.
In this paper, we propose very simple analytical methodologies for modeling the behavior of photovoltaic (solar cells/panels) using a one-diode/two-resistor (1-D/2-R) equivalent circuit. A value of a = 1 for the ideality factor is shown to be very reasonable for the different photovoltaic technologies studied here. The solutions to the analytical equations of this model are simplified using easy mathematical expressions defined for the Lambert W-function. The definition of these mathematical expressions was based on a large dataset related to solar cells and panels obtained from the available academic literature. These simplified approaches were successfully used to extract the parameters from explicit methods for analyzing the behavior of solar cells/panels, where the exact solutions depend on the Lambert W-function. Finally, a case study was carried out that consisted of fitting the aforementioned models to the behavior (that is, the I-V curve) of two solar panels from the UPMSat-1 satellite. The results show a fairly high level of accuracy for the proposed methodologies. Full article
Open AccessArticle
Carotenoid Accumulation and the Expression of Carotenoid Metabolic Genes in Mango during Fruit Development and Ripening
by , , , , , , , and
Appl. Sci. 2021, 11(9), 4249; https://doi.org/10.3390/app11094249 - 07 May 2021
Abstract
Carotenoids are considered to be important components in mango fruits. However, there is a lack of understanding about the regulation of carotenoids in mango. To gain an insight into the carotenoid metabolism pathway, carotenoid content and the expression of carotenoid metabolic genes were [...] Read more.
Carotenoids are considered to be important components in mango fruits. However, there is a lack of understanding about the regulation of carotenoids in mango. To gain an insight into the carotenoid metabolism pathway, carotenoid content and the expression of carotenoid metabolic genes were investigated in the peel and pulp of mango during fruit development and ripening in three cultivars, ‘Kaituk’, ‘Nam Dok Mai No.4′, and ‘Nam Dok Mai Sithong’, which are different in color. The highest carotenoid content was observed in ‘Kaituk’, followed by ‘Nam Dok Mai No.4′ and ‘Nam Dok Mai Sithong’, with the major carotenoid being β-carotene. The gene expression analysis found that carotenoid metabolism in mango fruit was primarily regulated at the transcriptional level. The changing patterns of carotenoid biosynthetic gene expression (MiPSY, MiPDS, MiZDS, MiCRTISO, MiLCYb, MiLCYe, MiHYb, and MiZEP) were similar to carotenoid accumulation, and ‘Kaituk’ exhibited a higher expression level than the other two cultivars. In addition, the differential regulation of carotenoid catabolic genes was found to be a mechanism responsible for variability in carotenoid content among the three mango cultivars. The expression of carotenoid catabolic genes (MiCCD1, MiNCED2, and MiNCED3) more rapidly decreased in ‘Kaituk’, resulting in a larger amount of carotenoids in ‘Kaituk’ than the other two cultivars. Full article
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Open AccessArticle
Accurate Instance-Based Segmentation for Boundary Detection in Robot Grasping Application
by and
Appl. Sci. 2021, 11(9), 4248; https://doi.org/10.3390/app11094248 - 07 May 2021
Abstract
With the rapid development of cameras and deep learning technologies, computer vision tasks such as object detection, object segmentation and object tracking are being widely applied in many fields of life. For robot grasping tasks, object segmentation aims to classify and localize objects, [...] Read more.
With the rapid development of cameras and deep learning technologies, computer vision tasks such as object detection, object segmentation and object tracking are being widely applied in many fields of life. For robot grasping tasks, object segmentation aims to classify and localize objects, which helps robots to be able to pick objects accurately. The state-of-the-art instance segmentation network framework, Mask Region-Convolution Neural Network (Mask R-CNN), does not always perform an excellent accurate segmentation at the edge or border of objects. The approach using 3D camera, however, is able to extract the entire (foreground) objects easily but can be difficult or require a large amount of computation effort to classify it. We propose a novel approach, in which we combine Mask R-CNN with 3D algorithms by adding a 3D process branch for instance segmentation. Both outcomes of two branches are contemporaneously used to classify the pixels at the edge objects by dealing with the spatial relationship between edge region and mask region. We analyze the effectiveness of the method by testing with harsh cases of object positions, for example, objects are closed, overlapped or obscured by each other to focus on edge and border segmentation. Our proposed method is about 4 to 7% higher and more stable in IoU (intersection of union). This leads to a reach of 46% of mAP (mean Average Precision), which is a higher accuracy than its counterpart. The feasibility experiment shows that our method could be a remarkable promoting for the research of the grasping robot. Full article
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Open AccessArticle
Multi-Task Learning for Medical Image Inpainting Based on Organ Boundary Awareness
by , , and
Appl. Sci. 2021, 11(9), 4247; https://doi.org/10.3390/app11094247 - 07 May 2021
Abstract
Distorted medical images can significantly hamper medical diagnosis, notably in the analysis of Computer Tomography (CT) images and organ segmentation specifics. Therefore, improving diagnostic imagery accuracy and reconstructing damaged portions are important for medical diagnosis. Recently, these issues have been studied extensively in [...] Read more.
Distorted medical images can significantly hamper medical diagnosis, notably in the analysis of Computer Tomography (CT) images and organ segmentation specifics. Therefore, improving diagnostic imagery accuracy and reconstructing damaged portions are important for medical diagnosis. Recently, these issues have been studied extensively in the field of medical image inpainting. Inpainting techniques are emerging in medical image analysis since local deformations in medical modalities are common because of various factors such as metallic implants, foreign objects or specular reflections during the image captures. The completion of such missing or distorted regions is important for the enhancement of post-processing tasks such as segmentation or classification. In this paper, a novel framework for medical image inpainting is presented by using a multi-task learning model for CT images targeting the learning of the shape and structure of the organs of interest. This novelty has been accomplished through simultaneous training for the prediction of edges and organ boundaries with the image inpainting, while state-of-the-art methods still focus only on the inpainting area without considering the global structure of the target organ. Therefore, our model reproduces medical images with sharp contours and exact organ locations. Consequently, our technique generates more realistic and believable images compared to other approaches. Additionally, in quantitative evaluation, the proposed method achieved the best results in the literature so far, which include a PSNR value of 43.44 dB and SSIM of 0.9818 for the square-shaped regions; a PSNR value of 38.06 dB and SSIM of 0.9746 for the arbitrary-shaped regions. The proposed model generates the sharp and clear images for inpainting by learning the detailed structure of organs. Our method was able to show how promising the method is when applying it in medical image analysis, where the completion of missing or distorted regions is still a challenging task. Full article
(This article belongs to the Special Issue Artificial Intelligence for Computer Vision)
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Open AccessArticle
Evaluation of Design Provisions for Horizontal Shear Strength in Composite Precast Concrete Beams with Different Interface Conditions
by and
Appl. Sci. 2021, 11(9), 4246; https://doi.org/10.3390/app11094246 - 07 May 2021
Abstract
In a precast concrete (PC) composite beam, the horizontal interface between the PC beam and the cast-in-place (CIP) slab is located either on the compression side or on the tensile side of the cross-section. If the CIP slab is on the compression side, [...] Read more.
In a precast concrete (PC) composite beam, the horizontal interface between the PC beam and the cast-in-place (CIP) slab is located either on the compression side or on the tensile side of the cross-section. If the CIP slab is on the compression side, it becomes C-type interface, and if it is on the tensile side, it becomes T-type interface. Tensile cracks in the CIP slab may cause the horizontal shear strength of composite beams to decrease because of the reduced anchorage performance of shear reinforcements as well as the sliding on the interface. Such a tendency can be found from previous test results of specimens having T-type interface. In this study, the results of the push-off test and the beam flexure test were collected and analyzed to evaluate effects on the horizontal shear strength depending on the interface conditions, such as the interface location, surface roughness, concrete compressive strength, and clamping stress by shear connectors. The horizontal shear strength equations of ACI, PCI, AASHTO LRFD, and MC 2010 were evaluated with a database composed of 84 push-off tests and 95 beam tests from previous studies. According to the evaluation, evaluation results show that the design codes predict the horizontal shear strength conservatively for conditions other than the interface location. The horizontal shear strength deviated largely depending on the interface locations. The design codes conservatively estimate the horizontal shear strength for C-type interface, but the horizontal shear strength of T-type interface is overestimated. Based on current studies, it is recommended to use a friction coefficient of 0.7 as MC 2010 when calculating the horizontal shear strength of a composite beam with roughened T-type interface. Full article
Open AccessArticle
Proteins as Hair Styling Agents
by , , , , and
Appl. Sci. 2021, 11(9), 4245; https://doi.org/10.3390/app11094245 (registering DOI) - 07 May 2021
Abstract
The perming of hair is a common styling procedure with negative impact on the overall properties of the hair fibers. Usually, this process uses harsh chemicals to promote the disruption of disulfide bonds and the formation of new bonds to change the shape [...] Read more.
The perming of hair is a common styling procedure with negative impact on the overall properties of the hair fibers. Usually, this process uses harsh chemicals to promote the disruption of disulfide bonds and the formation of new bonds to change the shape of hair. Here, we explored bovine serum albumin (BSA), silk fibroin (SF), keratin and two fusion recombinant proteins (KP-UM and KP-Cryst) as new perming agents. A phosphate buffer prepared at different pH values (5, 7 and 9) was used to apply the proteins to virgin Asian hair, and a hot BaByliss was used to curl the hair fibers. To assess the potential of the protein formulations for hair styling, the perming efficiency and the perming resistance to wash were measured. Furthermore, the fiber water content was evaluated to assess if the proteins protected the hair during the styling process. Despite all of the proteins being able to assist in the curling of Asian hair, the best perming efficiency and perming resistance to wash results were observed for BSA and keratin. These proteins showed perming efficiency values close to that measured for a commercial perming product (chemical method), particularly at pH 5 and 9. The increase in the hair’s internal and external water contents revealed a protective effect provided by the proteins during the application of heat in the styling procedure. This study shows the potential of proteins to be used in the development of new eco-friendly hair styling products. Full article
(This article belongs to the Special Issue Recent Advances in Hair Science)
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Open AccessArticle
Imaging Top of Volcanic Mounds Using Seismic Time- and Depth-Domain Data Processing
by , , and
Appl. Sci. 2021, 11(9), 4244; https://doi.org/10.3390/app11094244 - 07 May 2021
Abstract
A seismic survey identified a basalt flow that could consist of cap rock of CO2 storage beneath saline aquifer sediment in the Southern Continental Shelf of Korea. To determine the precise depth of the basalt flow, specific depth-domain data processing of migration [...] Read more.
A seismic survey identified a basalt flow that could consist of cap rock of CO2 storage beneath saline aquifer sediment in the Southern Continental Shelf of Korea. To determine the precise depth of the basalt flow, specific depth-domain data processing of migration velocity analysis (MVA) was applied to the seismic survey data. The accurate depth measurement of a target structure provides crucial information when storing and stabilizing injected CO2 beneath basalt cap rock. Strong reflections of seismic amplitude at the volcanic mounds were adjusted from the time domain to the exact depth domain by the iterated velocity using MVA. The confidence of the updated velocity was verified by the horizontal alignment of seismic events sorted according to their common reflection point (CRP). The depth difference in volcanic mounds before and after MVA application ranged from 32.5 to 60 m along the vertical axis, showing the eruption shape on the strong-amplitude contour map in detail. The eruption shape of the top of volcanic mounds was verified with spatial continuity in 3D geological interpretation. The presented results provide suitable information that can be used to locate drilling sites and to prepare CO2 injection. The geological model obtained from both time- and depth-domain processing can significantly influence the calculation of the storage volume and can be useful for history matching studies. Full article
(This article belongs to the Special Issue Data Processing and Modeling on Volcanic and Seismic Areas)
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Open AccessArticle
A Two-Stage Neural Network-Based Cold Start Item Recommender
by , and
Appl. Sci. 2021, 11(9), 4243; https://doi.org/10.3390/app11094243 - 07 May 2021
Abstract
Nowadays, recommendation systems have been successfully adopted in variant online services such as e-commerce, news, and social media. The recommenders provide users a convenient and efficient way to find their exciting items and increase service providers’ revenue. However, it is found that many [...] Read more.
Nowadays, recommendation systems have been successfully adopted in variant online services such as e-commerce, news, and social media. The recommenders provide users a convenient and efficient way to find their exciting items and increase service providers’ revenue. However, it is found that many recommenders suffered from the cold start (CS) problem where only a small number of ratings are available for some new items. To conquer the difficulties, this research proposes a two-stage neural network-based CS item recommendation system. The proposed system includes two major components, which are the denoising autoencoder (DAE)-based CS item rating (DACR) generator and the neural network-based collaborative filtering (NNCF) predictor. In the DACR generator, a textual description of an item is used as auxiliary content information to represent the item. Then, the DAE is applied to extract the content features from high-dimensional textual vectors. With the compact content features, a CS item’s rating can be efficiently derived based on the ratings of similar non-CS items. Second, the NNCF predictor is developed to predict the ratings in the sparse user–item matrix. In the predictor, both spare binary user and item vectors are projected to dense latent vectors in the embedding layer. Next, latent vectors are fed into multilayer perceptron (MLP) layers for user–item matrix learning. Finally, appropriate item suggestions can be accurately obtained. The extensive experiments show that the DAE can significantly reduce the computational time for item similarity evaluations while keeping the original features’ characteristics. Besides, the experiments show that the proposed NNCF predictor outperforms several popular recommendation algorithms. We also demonstrate that the proposed CS item recommender can achieve up to 8% MAE improvement compared to adding no CS item rating. Full article
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Open AccessReview
Recent Developments in Lignin- and Tannin-Based Non-Isocyanate Polyurethane Resins for Wood Adhesives—A Review
by , , , , , , , and
Appl. Sci. 2021, 11(9), 4242; https://doi.org/10.3390/app11094242 - 07 May 2021
Abstract
This review article aims to summarize the potential of using renewable natural resources, such as lignin and tannin, in the preparation of NIPUs for wood adhesives. Polyurethanes (PUs) are extremely versatile polymeric materials, which have been widely used in numerous applications, e.g., packaging, [...] Read more.
This review article aims to summarize the potential of using renewable natural resources, such as lignin and tannin, in the preparation of NIPUs for wood adhesives. Polyurethanes (PUs) are extremely versatile polymeric materials, which have been widely used in numerous applications, e.g., packaging, footwear, construction, the automotive industry, the lighting industry, insulation panels, bedding, furniture, metallurgy, sealants, coatings, foams, and wood adhesives. The isocyanate-based PUs exhibit strong adhesion properties, excellent flexibility, and durability, but they lack renewability. Therefore, this study focused on the development of non-isocyanate polyurethane lignin and tannin resins for wood adhesives. PUs are commercially synthesized using polyols and polyisocyanates. Isocyanates are toxic, costly, and not renewable; thus, a search of suitable alternatives in the synthesis of polyurethane resins is needed. The reaction with diamine compounds could result in NIPUs based on lignin and tannin. The research on bio-based components for PU synthesis confirmed that they have good characteristics as an alternative for the petroleum-based adhesives. The advantages of improved strength, low curing temperatures, shorter pressing times, and isocyanate-free properties were demonstrated by lignin- and tannin-based NIPUs. The elimination of isocyanate, associated with environmental and human health hazards, NIPU synthesis, and its properties and applications, including wood adhesives, are reported comprehensively in this paper. The future perspectives of NIPUs’ production and application were also outlined. Full article
(This article belongs to the Special Issue Advanced Technologies in Wood Science)
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Open AccessArticle
A New Multi-Person Pose Estimation Method Using the Partitioned CenterPose Network
by and
Appl. Sci. 2021, 11(9), 4241; https://doi.org/10.3390/app11094241 (registering DOI) - 07 May 2021
Abstract
In bottom-up multi-person pose estimation, grouping joint candidates into the appropriately structured corresponding instance of a person is challenging. In this paper, a new bottom-up method, the Partitioned CenterPose (PCP) Network, is proposed to better cluster the detected joints. To achieve this goal, [...] Read more.
In bottom-up multi-person pose estimation, grouping joint candidates into the appropriately structured corresponding instance of a person is challenging. In this paper, a new bottom-up method, the Partitioned CenterPose (PCP) Network, is proposed to better cluster the detected joints. To achieve this goal, we propose a novel approach called Partition Pose Representation (PPR) which integrates the instance of a person and its body joints based on joint offset. PPR leverages information about the center of the human body and the offsets between that center point and the positions of the body’s joints to encode human poses accurately. To enhance the relationships between body joints, we divide the human body into five parts, and then, we generate a sub-PPR for each part. Based on this PPR, the PCP Network can detect people and their body joints simultaneously, then group all body joints according to joint offset. Moreover, an improved l1 loss is designed to more accurately measure joint offset. Using the COCO keypoints and CrowdPose datasets for testing, it was found that the performance of the proposed method is on par with that of existing state-of-the-art bottom-up methods in terms of accuracy and speed. Full article
(This article belongs to the Special Issue Deep Learning-Based Action Recognition)
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Open AccessArticle
Influence of Soil Heterogeneity on the Contact Problems in Geotechnical Engineering
by and
Appl. Sci. 2021, 11(9), 4240; https://doi.org/10.3390/app11094240 - 07 May 2021
Abstract
Contact problems are widely encountered in geotechnical engineering, such as the contact between soils and concrete used in earth and rockfill dams, tunnels and coastal levees. Due to the unknown contact region and contact forces, the contact problems have strong boundary nonlinearity. In [...] Read more.
Contact problems are widely encountered in geotechnical engineering, such as the contact between soils and concrete used in earth and rockfill dams, tunnels and coastal levees. Due to the unknown contact region and contact forces, the contact problems have strong boundary nonlinearity. In addition, soils have been recognized as heterogeneous materials in geotechnical engineering. The existence of the soil heterogeneity increases the nonlinearity of the contact problems. Currently, the contact problems are mostly analysed without considering the soil heterogeneity, which may not reflect the contact behavior well. In order to investigate the influence of soil heterogeneity on the contact problems, in this paper, a simple plane-strain contact problem is analysed as an example. In this example, Young’s modulus is taken to be a spatially variable. The local average subdivision (LAS) is used to model the heterogeneity of Young’s modulus. The penalty method is utilised to determine the contact behavior. By the first use of linking the penalty method with the LAS, the proposed approach can be used to analyse the contact problems considering soil heterogeneity. The results show that the influence of soil heterogeneity on the elastic contact problems is significant. The contact forces of the heterogeneous case present apparent variation compared to the results of the homogeneous case. The distribution of the contact force at a specific point is also normal when Young’s modulus is normally distributed, moreover, the coefficient of variation (COV) and the horizontal scale of fluctuation of Young’s modulus affect the extent of variation of the normal contact forces. The standard deviation of the normal contact force increases with the increase of the COV and decreases with the increase of the horizontal scale of fluctuation of Young’s modulus. From the analyses, to better predict the deformation/stress in the contact problems, heterogeneity needs to be considered. Full article
(This article belongs to the Section Earth Sciences and Geography)
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Open AccessArticle
Antimycotoxigenic Activity of Beetroot Extracts against Altenaria alternata Mycotoxins on Potato Crop
by , , , , , , , , and
Appl. Sci. 2021, 11(9), 4239; https://doi.org/10.3390/app11094239 - 07 May 2021
Abstract
Alternaria species, mainly air-borne fungi, affect potato plants, causing black spots symptoms. Morphological identification, pathogenicity assessment, and internal transcribed spacer (ITS) molecular identification confirmed that all isolates were Alternaria alternata. The annotated sequences were deposited in GenBank under accession numbers MN592771–MN592777. HPLC analysis [...] Read more.
Alternaria species, mainly air-borne fungi, affect potato plants, causing black spots symptoms. Morphological identification, pathogenicity assessment, and internal transcribed spacer (ITS) molecular identification confirmed that all isolates were Alternaria alternata. The annotated sequences were deposited in GenBank under accession numbers MN592771–MN592777. HPLC analysis revealed that the fungal isolates KH3 (133,200 ng/g) and NO3 (212,000 ng/g) produced higher levels of tenuazonic acid (TeA) and alternariol monomethyl ether (AME), respectively. Beet ethanol extract (BEE) and beet methanol extract (BME) at different concentrations were used as antimycotoxins. BME decreased the production of mycotoxins by 66.99–99.79%. The highest TeA reduction rate (99.39%) was reported in the KH3 isolate with 150 µg/mL BME treatment. In comparison, the most effective AME reduction rate (99.79%) was shown in the NO3 isolate with 150 µg/mL BME treatment. In the same way, BEE application resulted in 95.60–99.91% mycotoxin reduction. The highest TeA reduction rate (99.91%) was reported in the KH3 isolate with 150 µg/mL BEE treatment, while the greatest AME reduction rate (99.68%) was shown in the Alam1 isolate with 75 µg/mL BEE treatment. GC-MS analysis showed that the main constituent in BME was the antioxidant compound 1-dodecanamine, n,n-dimethyl with a peak area of 43.75%. In contrast, oxirane, methyl- (23.22%); hexadecanoic acid, methyl ester (10.72%); and n-hexadecanoic acid (7.32%) were the main components in BEE found by GC-MS. They are probably antimicrobial molecules and have an effect on the mycotoxin in general. To our knowledge, this is the first study describing the antimycotoxigenic activity of beet extracts against A. alternata mycotoxins-contaminated potato crops in Egypt, aimed to manage and save the environment. Full article
(This article belongs to the Special Issue Application of Plant Natural Compounds)
Open AccessArticle
SVM Performance for Predicting the Effect of Horizontal Screen Diameters on the Hydraulic Parameters of a Vertical Drop
by , , , and
Appl. Sci. 2021, 11(9), 4238; https://doi.org/10.3390/app11094238 - 07 May 2021
Abstract
The present study investigated the application of support vector machine algorithms for predicting hydraulic parameters of a vertical drop equipped with horizontal screens. The study incorporated varying sizes of a rectangular channel. Horizontal screens, in addition to being able to dissipate the destructive [...] Read more.
The present study investigated the application of support vector machine algorithms for predicting hydraulic parameters of a vertical drop equipped with horizontal screens. The study incorporated varying sizes of a rectangular channel. Horizontal screens, in addition to being able to dissipate the destructive energy of the flow, cause turbulence. The turbulence in turn supplies oxygen to the system through the promotion of air–water mixing. To achieve the objectives of the present study, 164 experiments were analyzed under the same experimental conditions using a support vector machine. The approach utilized dimensionless terms that included scenario 1: the relative energy consumption and scenario 2: the relative pool depth. The performance of the models was evaluated with statistical criteria (RMSE, R2 and KGE) and the best model was introduced for each of the parameters. RMSE is the root mean square error, R2 is the correlation coefficient and KGE is the Kling–Gupta criterion. The results of the support vector machine showed that for the first scenario, the third combination with R2 = 0.991, RMSE = 0.00565 and KGE = 0.998 for the training mode and R2 = 0.991, RMSE = 0.00489 and KGE = 0.991 for the testing mode were optimal. For the second scenario, the third combination with R2 = 0.988, RMSE = 0.0395 and KGE = 0.998 for the training mode and R2 = 0.988, RMSE = 0.0389 and KGE = 0.993 for the testing mode were selected. Finally, a sensitivity analysis was performed that showed that the yc/H and D/H parameters are the most effective parameters for predicting relative energy dissipation and relative pool depth, respectively. Full article
(This article belongs to the Special Issue Machine Learning Algorithms for Hydraulic Engineering)
Open AccessArticle
Orbit Decomposition Method for Rotordynamic Coefficients Identification of Annular Seals
by , , and
Appl. Sci. 2021, 11(9), 4237; https://doi.org/10.3390/app11094237 - 07 May 2021
Abstract
The elliptical orbit whirl model is widely used to identify the frequency-dependent rotordynamic coefficients of annular seals. The existing solution technique of an elliptical orbit whirl model is the transient computational fluid dynamics (CFD) method. Its computational time is very long. For rapid [...] Read more.
The elliptical orbit whirl model is widely used to identify the frequency-dependent rotordynamic coefficients of annular seals. The existing solution technique of an elliptical orbit whirl model is the transient computational fluid dynamics (CFD) method. Its computational time is very long. For rapid computation, this paper proposes the orbit decomposition method. The elliptical whirl orbit is decomposed into the forward and backward circular whirl orbits. Under small perturbation circumstances, the fluid-induced forces of the elliptical orbit model can be obtained by the linear superposition of the fluid-induced forces arising from the two decomposed circular orbit models. Due to that the fluid-induced forces of circular orbit, the model can be calculated with the steady CFD method, and the transient computations can be replaced with steady ones when calculating the elliptical orbit whirl model. The computational time is significantly reduced. To validate the present method, its rotordynamic results are compared with those of the transient CFD method and experimental data. Comparisons show that the present method can accurately calculate the rotordynamic coefficients. Elliptical orbit parameter analysis reveals that the present method is valid when the whirl amplitude is less than 20% of seal clearance. The effect of ellipticity on rotordynamic coefficients can be ignored. Full article
(This article belongs to the Section Mechanical Engineering)
Open AccessArticle
Low Doses of Gamma Irradiation Stimulate Synthesis of Bioactive Compounds with Antioxidant Activity in Fomes fomentarius Living Mycelium
by , , and
Appl. Sci. 2021, 11(9), 4236; https://doi.org/10.3390/app11094236 - 07 May 2021
Abstract
Environmental changes generate free radicals and reactive oxygen species (ROS), resulting in abiotic stress in plants and fungi. Gamma ionizing radiation generates a significant amount of free radicals and ROS, thereby simulating natural environmental stressors. We used a 60Co source of radiation [...] Read more.
Environmental changes generate free radicals and reactive oxygen species (ROS), resulting in abiotic stress in plants and fungi. Gamma ionizing radiation generates a significant amount of free radicals and ROS, thereby simulating natural environmental stressors. We used a 60Co source of radiation to experimentally induce oxidative stress in living mycelium mass of the medicinal fungus Fomes fomentarius, in order to obtain a late response of stress tolerance by means of bioactive compounds synthesis. We measured the response at 24, 48, and 72 h after the irradiation. The highest improvement was found 24 h after exposure for antioxidant activity and for total phenolic compounds of methanolic extract, with a 1.89- and 1.64-fold increase, respectively. The total flavonoids in methanolic extract increased 1.68 times after 48 h from treatment and presented a more stable raising in the assessed time-lapse. For the three analyzed parameters, 300 Gy was the optimum absorbed dose to trigger a beneficial response, with potentially applications in pharmaceutics and nutraceutics. Gamma irradiation can be used as a biotechnological tool to direct the secondary metabolites synthesis upregulation in medicinal mushroom living mycelium. Full article
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Open AccessArticle
SLLB-DEVS: An Approach for DEVS Based Modeling of Semiconductor Lithography Load Balance
by , , and
Appl. Sci. 2021, 11(9), 4235; https://doi.org/10.3390/app11094235 - 07 May 2021
Abstract
In industrial applications, software related to computational lithography using a DP system method, which refers to how efficiently hardware resources are used, has a significant impact on performance. Because the amount of data to be processed per unit of time is comparatively large [...] Read more.
In industrial applications, software related to computational lithography using a DP system method, which refers to how efficiently hardware resources are used, has a significant impact on performance. Because the amount of data to be processed per unit of time is comparatively large in the current semiconductor industry, the efficiency of hardware should be increased through job 12 scheduling by using the most efficient load balancing techniques possible. For efficient scheduling of the load balancer, these are necessary to predict the end time of a given job; this is calculated based on the performance of computing resources and the development of effective traffic distribution algorithms. Due to the high integration of semiconductor chips, the volume of mask exposure data has increased exponentially, the number of slave nodes is increasing, and most EDA tools require one license per DP node to perform a simulation. In this paper, in order to improve efficiency and reduce cost through more efficient load balancing scheduling, a new type of DEVS load balancing method was studied based on the existing industrial E-beam cluster model. The designed DEVS model showed up to four times the throughput of the existing legacy model for medium and large clusters when the BSF policy was applied. Full article
(This article belongs to the Section Applied Industrial Technologies)
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Open AccessArticle
Exposure to Phthalates and Alternative Plasticizers Is Associated with Methylation Changes of ESR1 and PGR in Uterine Leiomyoma: The ELENA Study
by , , , , , , , , , , and
Appl. Sci. 2021, 11(9), 4234; https://doi.org/10.3390/app11094234 - 07 May 2021
Abstract
Uterine leiomyomas are estrogen-dependent benign tumors with unknown etiologies. Phthalates are endocrine-disrupting chemicals and ubiquitous in the environment; thus, it has been suggested that they play a role in the development of uterine leiomyoma. We aimed to investigate whether the pathogenesis of uterine [...] Read more.
Uterine leiomyomas are estrogen-dependent benign tumors with unknown etiologies. Phthalates are endocrine-disrupting chemicals and ubiquitous in the environment; thus, it has been suggested that they play a role in the development of uterine leiomyoma. We aimed to investigate whether the pathogenesis of uterine leiomyoma is related to methylation changes in promoter regions of estrogen receptor α (ESR1) and progesterone receptor (PGR) genes in response to phthalates and alternative plasticizers exposure. Urinary concentrations of 20 phthalate metabolites and seven metabolites of di-2-ethylhexyl terephthalate (DEHTP) and di (isononyl) cyclohexane-1,2-dicarboxylate (DINCH) were measured by UHPLC-MS/MS in thirty leiomyoma patients, who provided both paired leiomyoma and myometrium tissues. Methylation levels of ESR1 and PGR were analyzed by pyrosequencing assay. A total of 12 phthalate metabolites and 5 alternative metabolites (3 DEHTP and 2 DINCH) were detected >70% among study participants. The methylation of ESR1 and PGR were significantly lower in leiomyoma tissues compared to those in myometrium (18.10 ± 4.41 vs. 28.72 ± 4.95; 2.32 ± 0.81 vs. 3.27 ± 0.56, respectively). ESR1 methylation in leiomyoma was negatively associated with mono-2-carboxylmethyl-hexyl phthalate (2cx-MMHP) and mono-3-carbocyl-propyl phthalate (MCPP) after adjusting for confounding factors. However, 1-mono-2-ethyl-5-oxohexyl-benzene-1,4-dicarboxylate (5OXO-MEHTP), one of the alternatives, showed positive association with ESR1 methylation in leiomyoma. PGR methylation in leiomyoma was significantly associated with mono butyl phthalate (MnBP), but negatively associated with cyclohexane-1,2-dicarboxylate-mono-7-hydroxy-4-methyl-heptyl ester (cx-MINCH). Our results suggest that phthalates exposure may contribute to leiomyoma pathogenesis via ESR1 and PGR methylation changes. Full article
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Open AccessArticle
Vulnerability in Deep Transfer Learning Models to Adversarial Fast Gradient Sign Attack for COVID-19 Prediction from Chest Radiography Images
by , , , and
Appl. Sci. 2021, 11(9), 4233; https://doi.org/10.3390/app11094233 - 07 May 2021
Abstract
The COVID-19 pandemic requires the rapid isolation of infected patients. Thus, high-sensitivity radiology images could be a key technique to diagnose patients besides the polymerase chain reaction approach. Deep learning algorithms are proposed in several studies to detect COVID-19 symptoms due to the [...] Read more.
The COVID-19 pandemic requires the rapid isolation of infected patients. Thus, high-sensitivity radiology images could be a key technique to diagnose patients besides the polymerase chain reaction approach. Deep learning algorithms are proposed in several studies to detect COVID-19 symptoms due to the success in chest radiography image classification, cost efficiency, lack of expert radiologists, and the need for faster processing in the pandemic area. Most of the promising algorithms proposed in different studies are based on pre-trained deep learning models. Such open-source models and lack of variation in the radiology image-capturing environment make the diagnosis system vulnerable to adversarial attacks such as fast gradient sign method (FGSM) attack. This study therefore explored the potential vulnerability of pre-trained convolutional neural network algorithms to the FGSM attack in terms of two frequently used models, VGG16 and Inception-v3. Firstly, we developed two transfer learning models for X-ray and CT image-based COVID-19 classification and analyzed the performance extensively in terms of accuracy, precision, recall, and AUC. Secondly, our study illustrates that misclassification can occur with a very minor perturbation magnitude, such as 0.009 and 0.003 for the FGSM attack in these models for X-ray and CT images, respectively, without any effect on the visual perceptibility of the perturbation. In addition, we demonstrated that successful FGSM attack can decrease the classification performance to 16.67% and 55.56% for X-ray images, as well as 36% and 40% in the case of CT images for VGG16 and Inception-v3, respectively, without any human-recognizable perturbation effects in the adversarial images. Finally, we analyzed that correct class probability of any test image which is supposed to be 1, can drop for both considered models and with increased perturbation; it can drop to 0.24 and 0.17 for the VGG16 model in cases of X-ray and CT images, respectively. Thus, despite the need for data sharing and automated diagnosis, practical deployment of such program requires more robustness. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
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Open AccessFeature PaperArticle
Neuro-Inspired Computing with Spin-VCSELs
by , and
Appl. Sci. 2021, 11(9), 4232; https://doi.org/10.3390/app11094232 - 07 May 2021
Viewed by 106
Abstract
Delay-based reservoir computing (RC), a neuromorphic computing technique, has gathered lots of interest, as it promises compact and high-speed RC implementations. To further boost the computing speeds, we introduce and study an RC setup based on spin-VCSELs, thereby exploiting the high polarization modulation [...] Read more.
Delay-based reservoir computing (RC), a neuromorphic computing technique, has gathered lots of interest, as it promises compact and high-speed RC implementations. To further boost the computing speeds, we introduce and study an RC setup based on spin-VCSELs, thereby exploiting the high polarization modulation speed inherent to these lasers. Based on numerical simulations, we benchmarked this setup against state-of-the-art delay-based RC systems and its parameter space was analyzed for optimal performance. The high modulation speed enabled us to have more virtual nodes in a shorter time interval. However, we found that at these short time scales, the delay time and feedback rate heavily influence the nonlinear dynamics. Therefore, and contrary to other laser-based RC systems, the delay time has to be optimized in order to obtain good RC performances. We achieved state-of-the-art performances on a benchmark timeseries prediction task. This spin-VCSEL-based RC system shows a ten-fold improvement in processing speed, which can further be enhanced in a straightforward way by increasing the birefringence of the VCSEL chip. Full article
(This article belongs to the Special Issue Photonics for Optical Computing)
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Open AccessArticle
The Ability to Normalise Energy Metabolism in Advanced COVID-19 Disease Seems to Be One of the Key Factors Determining the Disease Progression—A Metabolomic NMR Study on Blood Plasma
by , , , , , and
Appl. Sci. 2021, 11(9), 4231; https://doi.org/10.3390/app11094231 - 07 May 2021
Viewed by 118
Abstract
Background: COVID-19 represents a severe inflammatory condition. Our work was designed to monitor the longitudinal dynamics of the metabolomic response of blood plasma and to reveal presumable discrimination in patients with positive and negative outcomes of COVID-19 respiratory symptoms. Methods: Blood plasma from [...] Read more.
Background: COVID-19 represents a severe inflammatory condition. Our work was designed to monitor the longitudinal dynamics of the metabolomic response of blood plasma and to reveal presumable discrimination in patients with positive and negative outcomes of COVID-19 respiratory symptoms. Methods: Blood plasma from patients, divided into subgroups with positive (survivors) and negative (worsening condition, non-survivors) outcomes, on Days 1, 3, and 7 after admission to hospital, was measured by NMR spectroscopy. Results: We observed changes in energy metabolism in both groups of COVID-19 patients; initial hyperglycaemia, indicating lowered glucose utilisation, was balanced with increased production of 3-hydroxybutyrate as an alternative energy source and accompanied by accelerated protein catabolism manifested by an increase in BCAA levels. These changes were normalised in patients with positive outcome by the seventh day, but still persisted one week after hospitalisation in patients with negative outcome. The initially decreased glutamine plasma level normalised faster in patients with positive outcome. Patients with negative outcome showed a more pronounced Phe/Tyr ratio, which is related to exacerbated and generalised inflammatory processes. Almost ideal discrimination from controls was proved. Conclusions: Distinct metabolomic responses to severe inflammation initiated by SARS-CoV-2 infection may serve towards complementary personalised pharmacological and nutritional support to improve patient outcomes. Full article
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Open AccessEditorial
Applied Biomechanics: Sport Performance and Injury Prevention
by , , and
Appl. Sci. 2021, 11(9), 4230; https://doi.org/10.3390/app11094230 - 07 May 2021
Viewed by 168
Abstract
This Special Issue had, as its main objective, the compilation of studies on sports performance and its relationship with musculoskeletal injuries [...] Full article
(This article belongs to the Special Issue Applied Biomechanics: Sport Performance and Injury Prevention)
Open AccessArticle
Effectiveness of an App-Based Mobile Intervention for Precision Oral Self-Care in Patients with Periodontitis from Initial Therapy to Re-Evaluation
by , , and
Appl. Sci. 2021, 11(9), 4229; https://doi.org/10.3390/app11094229 - 07 May 2021
Viewed by 171
Abstract
Good oral hygiene is essential to oral health and oral disease prevention. Strengthening the adherence of patients with periodontitis to oral hygiene behaviors (OHBs) is crucial for the success of periodontal treatment. This study aims to investigate the intervention effectiveness of a novel [...] Read more.
Good oral hygiene is essential to oral health and oral disease prevention. Strengthening the adherence of patients with periodontitis to oral hygiene behaviors (OHBs) is crucial for the success of periodontal treatment. This study aims to investigate the intervention effectiveness of a novel mobile app for precision oral self-care, which was developed to help patients with periodontitis improving their oral hygiene through daily oral self-care. One-hundred and fifty eligible patients were recruited into this study and randomly allocated to the control (n = 75) or intervention group (n = 75), and their oral hygiene status (OHS) and OHBs were recorded at baseline and re-evaluation. The participants in the intervention group were required to perform daily oral self-care using our oral self-care app (OSCA) and the functional preferences and overall likeability of the OSCA were evaluated through a questionnaire survey. In total, 39 patients from the control group and 49 from the intervention group completed clinical examinations at baseline and re-evaluation. The results demonstrated that there was no significant difference in OHS improvement between the two groups. However, OHS improvement significantly differed between low-, moderate-, and high-frequency users, with frequency of use being positively correlated to the likeability of the app. Further investigation of the effectiveness of the OSCA intervention revealed that behavioral change in oral hygiene, frequency of OSCA use, and smoking affected OHS improvement. These outcomes indicate that our app-based mobile intervention may be of value for precision oral self-care in patients with periodontitis. Full article
(This article belongs to the Special Issue Clinical Applications for Dentistry and Oral Health)
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Open AccessArticle
Wrench-Closure Condition of Cable-Driven Parallel Manipulators
Appl. Sci. 2021, 11(9), 4228; https://doi.org/10.3390/app11094228 - 06 May 2021
Viewed by 161
Abstract
Cable-driven parallel manipulators (CDPM) have parallel structures that consist of moving platforms connected to the fixed platform through many flexible cables. The moving platform is driven by many winches, and because of the unidirectional property of cables (cables can only pull and not [...] Read more.
Cable-driven parallel manipulators (CDPM) have parallel structures that consist of moving platforms connected to the fixed platform through many flexible cables. The moving platform is driven by many winches, and because of the unidirectional property of cables (cables can only pull and not push in the moving platform), some specific workspaces of CDPM are limited and often do not exist (Gouttefarde and Gosselin 2006). Therefore, determining workspaces for CDPM become an important task, in order to easily plan the trajectory or control the robot. In this paper, we are interested in a set of poses of moving platforms, in which CDPM is always able to generate wrenches that balance any given external wrench exerted on the moving platform. This set of poses is also called wrench-closure workspace (WCW). In this work, we propose a novel procedure used to determine whether a pose of moving platform belongs to WCW. The condition used to check the feasibility of a certain pose in WCW is also called wrench closure condition (WCC). The proposed WCC is able to apply to completely or redundantly restrained CDPM. By analyzing the geometric properties of CDPM and applying the method used to check the feasibility of a system of inequalities, the algorithm used to check the presence of a given pose in WCW is established. To verify the performance of the proposed WCC, the test has been done in two different CDPMs that are clearly described in the introduction section. Full article
(This article belongs to the Section Mechanical Engineering)
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