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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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16 pages, 9511 KiB  
Article
Materials and Technique: The First Look at Saturnino Gatti
by Letizia Bonizzoni, Simone Caglio, Anna Galli, Luca Lanteri and Claudia Pelosi
Appl. Sci. 2023, 13(11), 6842; https://doi.org/10.3390/app13116842 - 05 Jun 2023
Cited by 8 | Viewed by 1540
Abstract
As part of the study project of the pictorial cycle, attributed to Saturnino Gatti, in the church of San Panfilo at Villagrande di Tornimparte (AQ), image analyses were performed in order to document the general conservation conditions of the surfaces, and to map [...] Read more.
As part of the study project of the pictorial cycle, attributed to Saturnino Gatti, in the church of San Panfilo at Villagrande di Tornimparte (AQ), image analyses were performed in order to document the general conservation conditions of the surfaces, and to map the different painting materials to be subsequently examined using spectroscopic techniques. To acquire the images, radiation sources, ranging from ultraviolet to near infrared, were used; analyses of ultraviolet fluorescence (UVF), infrared reflectography (IRR), infrared false colors (IRFC), and optical microscopy in visible light (OM) were carried out on all the panels of the mural painting of the apsidal conch. The Hypercolorimetric Multispectral Imaging (HMI) technique was also applied in selected areas of two panels. Due to the accurate calibration system, this technique is able to obtain high-precision colorimetric and reflectance measurements, which can be repeated for proper surface monitoring. The integrated analysis of the different wavelengths’ images—in particular, the ones processed in false colors—made it possible to distinguish the portions affected by retouching or repainting and to recover the legibility of some figures that showed chromatic alterations of the original pictorial layers. The IR reflectography, in addition to highlighting the portions that lost materials and were subject to non-original interventions, emphasized the presence of the underdrawing, which was detected using the spolvero technique. UVF photography led to a preliminary mapping of the organic and inorganic materials that exhibited characteristic induced fluorescence, such as a binder in correspondence with the original azurite painting or the wide use of white zinc in the retouched areas. The collected data made it possible to form a better iconographic interpretation. Moreover, it also enabled us to accurately select the areas to be investigated using spectroscopic analyses, both in situ and on micro-samples, in order to deepen our knowledge of the techniques used by the artist to create the original painting, and to detect subsequent interventions. Full article
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20 pages, 1537 KiB  
Review
Use of Machine Learning and Remote Sensing Techniques for Shoreline Monitoring: A Review of Recent Literature
by Chrysovalantis-Antonios D. Tsiakos and Christos Chalkias
Appl. Sci. 2023, 13(5), 3268; https://doi.org/10.3390/app13053268 - 03 Mar 2023
Cited by 15 | Viewed by 3631
Abstract
Climate change and its effects (i.e., sea level rise, extreme weather events) as well as anthropogenic activities, determine pressures to the coastal environments and contribute to shoreline retreat and coastal erosion phenomena. Coastal zones are dynamic and complex environments consisting of heterogeneous and [...] Read more.
Climate change and its effects (i.e., sea level rise, extreme weather events) as well as anthropogenic activities, determine pressures to the coastal environments and contribute to shoreline retreat and coastal erosion phenomena. Coastal zones are dynamic and complex environments consisting of heterogeneous and different geomorphological features, while exhibiting different scales and spectral responses. Thus, the monitoring of changes in the coastal land classes and the extraction of coastlines/shorelines can be a challenging task. Earth Observation data and the application of spatiotemporal analysis methods can facilitate shoreline change analysis and detection. Apart from remote sensing methods, the advent of machine learning-based techniques presents an emerging trend, being capable of supporting the monitoring and modeling of coastal ecosystems at large scales. In this context, this study aims to provide a review of the relevant literature falling within the period of 2015–2022, where different machine learning approaches were applied for cases of coast-line/shoreline extraction and change analysis, and/or coastal dynamic monitoring. Particular emphasis is given on the analysis of the selected studies, including details about their performances, as well as their advantages and weaknesses, and information about the different environmental data employed. Full article
(This article belongs to the Special Issue GIS and Spatial Planning for Natural Hazards Mitigation)
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26 pages, 6738 KiB  
Article
Tannin Extraction from Chestnut Wood Waste: From Lab Scale to Semi-Industrial Plant
by Clelia Aimone, Giorgio Grillo, Luisa Boffa, Samuele Giovando and Giancarlo Cravotto
Appl. Sci. 2023, 13(4), 2494; https://doi.org/10.3390/app13042494 - 15 Feb 2023
Cited by 10 | Viewed by 3824
Abstract
The chestnut tree (Castanea sativa, Mill.) is a widespread plant in Europe whose fruits and wood has a relevant economic impact. Chestnut wood (CW) is rich in high-value compounds that exhibit various biological activities, such as antioxidant as well as anticarcinogenic [...] Read more.
The chestnut tree (Castanea sativa, Mill.) is a widespread plant in Europe whose fruits and wood has a relevant economic impact. Chestnut wood (CW) is rich in high-value compounds that exhibit various biological activities, such as antioxidant as well as anticarcinogenic and antimicrobial properties. These metabolites can be mainly divided into monomeric polyphenols and tannins. In this piece of work, we investigated a sustainable protocol to isolate enriched fractions of the above-mentioned compounds from CW residues. Specifically, a sequential extraction protocol, using subcritical water, was used as a pre-fractionation step, recovering approximately 88% of tannins and 40% of monomeric polyphenols in the first and second steps, respectively. The optimized protocol was also tested at pre-industrial levels, treating up to 13.5 kg CW and 160 L of solution with encouraging results. Ultra- and nanofiltrations were used to further enrich the recovered fractions, achieving more than 98% of the tannin content in the heavy fraction, whilst the removed permeate achieved up to 752.71 mg GAE/gext after the concentration (75.3%). Samples were characterized by means of total phenolic content (TPC), antioxidant activity (DPPH· and ABTS·), and tannin composition (hydrolysable and condensed). In addition, LC-MS-DAD was used for semiqualitative purposes to detect vescalagin/castalagin and vescalin/castalin, as well as gallic acid and ellagic acid. The developed valorization protocol allows the efficient fractionation and recovery of the major polyphenolic components of CW with a sustainable approach that also evaluates pre-industrial scaling-up. Full article
(This article belongs to the Section Green Sustainable Science and Technology)
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22 pages, 33375 KiB  
Article
Using UAS-Aided Photogrammetry to Monitor and Quantify the Geomorphic Effects of Extreme Weather Events in Tectonically Active Mass Waste-Prone Areas: The Case of Medicane Ianos
by Evelina Kotsi, Emmanuel Vassilakis, Michalis Diakakis, Spyridon Mavroulis, Aliki Konsolaki, Christos Filis, Stylianos Lozios and Efthymis Lekkas
Appl. Sci. 2023, 13(2), 812; https://doi.org/10.3390/app13020812 - 06 Jan 2023
Cited by 6 | Viewed by 1421
Abstract
Extreme weather events can trigger various hydrogeomorphic phenomena and processes including slope failures. These shallow instabilities are difficult to monitor and measure due to the spatial and temporal scales in which they occur. New technologies such as unmanned aerial systems (UAS), photogrammetry and [...] Read more.
Extreme weather events can trigger various hydrogeomorphic phenomena and processes including slope failures. These shallow instabilities are difficult to monitor and measure due to the spatial and temporal scales in which they occur. New technologies such as unmanned aerial systems (UAS), photogrammetry and the structure-from-motion (SfM) technique have recently demonstrated capabilities useful in performing accurate terrain observations that have the potential to provide insights into these geomorphic processes. This study explores the use of UAS-aided photogrammetry and change detection, using specialized techniques such as the digital elevation model (DEM) of differences (DoD) and cloud-to-cloud distance (C2C) to monitor and quantify geomorphic changes before and after an extreme medicane event in Myrtos, a highly visited touristic site on Cephalonia Island, Greece. The application demonstrates that the combination of UAS with photogrammetry allows accurate delineation of instabilities, volumetric estimates of morphometric changes, insights into erosion and deposition processes and the delineation of higher-risk areas in a rapid, safe and practical way. Overall, the study illustrates that the combination of tools facilitates continuous monitoring and provides key insights into geomorphic processes that are otherwise difficult to observe. Through this deeper understanding, this approach can be a stepping stone to risk management of this type of highly-visited sites, which in turn is a key ingredient to sustainable development in high-risk areas. Full article
(This article belongs to the Section Earth Sciences)
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18 pages, 7267 KiB  
Article
Machine Learning-Assisted Prediction of Oil Production and CO2 Storage Effect in CO2-Water-Alternating-Gas Injection (CO2-WAG)
by Hangyu Li, Changping Gong, Shuyang Liu, Jianchun Xu and Gloire Imani
Appl. Sci. 2022, 12(21), 10958; https://doi.org/10.3390/app122110958 - 29 Oct 2022
Cited by 8 | Viewed by 2355
Abstract
In recent years, CO2 flooding has emerged as an efficient method for improving oil recovery. It also has the advantage of storing CO2 underground. As one of the promising types of CO2 enhanced oil recovery (CO2-EOR), CO2 [...] Read more.
In recent years, CO2 flooding has emerged as an efficient method for improving oil recovery. It also has the advantage of storing CO2 underground. As one of the promising types of CO2 enhanced oil recovery (CO2-EOR), CO2 water-alternating-gas injection (CO2-WAG) can suppress CO2 fingering and early breakthrough problems that occur during oil recovery by CO2 flooding. However, the evaluation of CO2-WAG is strongly dependent on the injection parameters, which in turn renders numerical simulations computationally expensive. So, in this work, machine learning is used to help predict how well CO2-WAG will work when different injection parameters are used. A total of 216 models were built by using CMG numerical simulation software to represent CO2-WAG development scenarios of various injection parameters where 70% of them were used as training sets and 30% as testing sets. A random forest regression algorithm was used to predict CO2-WAG performance in terms of oil production, CO2 storage amount, and CO2 storage efficiency. The CO2-WAG period, CO2 injection rate, and water–gas ratio were chosen as the three main characteristics of injection parameters. The prediction results showed that the predicted value of the test set was very close to the true value. The average absolute prediction deviations of cumulative oil production, CO2 storage amount, and CO2 storage efficiency were 1.10%, 3.04%, and 2.24%, respectively. Furthermore, it only takes about 10 s to predict the results of all 216 scenarios by using machine learning methods, while the CMG simulation method spends about 108 min. It demonstrated that the proposed machine-learning method can rapidly predict CO2-WAG performance with high accuracy and high computational efficiency under conditions of various injection parameters. This work gives more insights into the optimization of the injection parameters for CO2-EOR. Full article
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17 pages, 4661 KiB  
Article
Forecast of Airblast Vibrations Induced by Blasting Using Support Vector Regression Optimized by the Grasshopper Optimization (SVR-GO) Technique
by Lihua Chen, Panagiotis G. Asteris, Markos Z. Tsoukalas, Danial Jahed Armaghani, Dmitrii Vladimirovich Ulrikh and Mojtaba Yari
Appl. Sci. 2022, 12(19), 9805; https://doi.org/10.3390/app12199805 - 29 Sep 2022
Cited by 13 | Viewed by 1543
Abstract
Air overpressure (AOp) is an undesirable environmental effect of blasting. To date, a variety of empirical equations have been developed to forecast this phenomenon and prevent its negative impacts with accuracy. However, the accuracy of these methods is not sufficient. In addition, they [...] Read more.
Air overpressure (AOp) is an undesirable environmental effect of blasting. To date, a variety of empirical equations have been developed to forecast this phenomenon and prevent its negative impacts with accuracy. However, the accuracy of these methods is not sufficient. In addition, they are resource-consuming. This study employed support vector regression (SVR) optimized with the grasshopper optimizer (GO) algorithm to forecast AOp resulting from blasting. Additionally, a novel input selection technique, the Boruta algorithm (BFS), was applied. A new algorithm, the SVR-GA-BFS7, was developed by combining the models mentioned above. The findings showed that the SVR-GO-BFS7 model was the best technique (R2 = 0.983, RMSE = 1.332). The superiority of this model means that using the seven most important inputs was enough to forecast the AOp in the present investigation. Furthermore, the performance of SVR-GO-BFS7 was compared with various machine learning techniques, and the model outperformed the base models. The GO was compared with some other optimization techniques, and the superiority of this algorithm over the others was confirmed. Therefore, the suggested method presents a framework for accurate AOp prediction that supports the resource-saving forecasting methods. Full article
(This article belongs to the Special Issue Blast and Impact Engineering on Structures and Materials)
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22 pages, 1132 KiB  
Review
Where Are Smart Cities Heading? A Meta-Review and Guidelines for Future Research
by João Reis, Pedro Alexandre Marques and Pedro Carmona Marques
Appl. Sci. 2022, 12(16), 8328; https://doi.org/10.3390/app12168328 - 20 Aug 2022
Cited by 25 | Viewed by 2809
Abstract
(1) Background: Smart cities have been gaining attention in the community, both among researchers and professionals. Although this field of study is gaining some maturity, no academic manuscript yet offers a unique holistic view of the phenomenon. In fact, the existing systematic reviews [...] Read more.
(1) Background: Smart cities have been gaining attention in the community, both among researchers and professionals. Although this field of study is gaining some maturity, no academic manuscript yet offers a unique holistic view of the phenomenon. In fact, the existing systematic reviews make it possible to gather solid and relevant knowledge, but still dispersed; (2) Method: through a meta-review it was possible to provide a set of data, which allows the dissemination of the main theoretical and managerial contributions to enthusiasts and critics of the area; (3) Results: this research identified the most relevant topics for smart cities, namely, smart city dimensions, digital transformation, sustainability and resilience. In addition, this research emphasizes that the natural sciences have dominated scientific production, with greater attention being paid to megacities of developed nations. Recent empirical research also suggests that it is crucial to overcome key cybersecurity and privacy challenges in smart cities; (4) Conclusions: research on smart cities can be performed as multidisciplinary studies of small and medium-sized cities in developed or underdeveloped countries. Furthermore, future research should highlight the role played by cybersecurity in the development of smart cities and analyze the impact of smart city development on the link between the city and its stakeholders. Full article
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41 pages, 4861 KiB  
Review
Analysis of Technologies for Carbon Dioxide Capture from the Air
by Grazia Leonzio, Paul S. Fennell and Nilay Shah
Appl. Sci. 2022, 12(16), 8321; https://doi.org/10.3390/app12168321 - 19 Aug 2022
Cited by 18 | Viewed by 5072
Abstract
The increase in CO2 concentration in the atmosphere has prompted the research community to find solutions for this environmental problem, which causes climate change and global warming. CO2 removal through the use of negative emissions technologies could lead to global emission [...] Read more.
The increase in CO2 concentration in the atmosphere has prompted the research community to find solutions for this environmental problem, which causes climate change and global warming. CO2 removal through the use of negative emissions technologies could lead to global emission levels becoming net negative towards the end of this century. Among these negative emissions technologies, direct air capture (DAC), in which CO2 is captured directly from the atmosphere, could play an important role. The captured CO2 can be removed in the long term and through its storage can be used for chemical processes, allowing closed carbon cycles in the short term. For DAC, different technologies have been suggested in the literature, and an overview of these is proposed in this work. Absorption and adsorption are the most studied and mature technologies, but others are also under investigation. An analysis of the main key performance indicators is also presented here and it is suggested that more efforts should be made to develop DAC at a large scale by reducing costs and improving efficiency. An additional discussion, addressing the social concern, is indicated as well. Full article
(This article belongs to the Special Issue Advances in Carbon Dioxide Removal Technologies)
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40 pages, 42877 KiB  
Review
Metal–Organic Frameworks as Powerful Heterogeneous Catalysts in Advanced Oxidation Processes for Wastewater Treatment
by Antía Fdez-Sanromán, Emilio Rosales, Marta Pazos and Angeles Sanroman
Appl. Sci. 2022, 12(16), 8240; https://doi.org/10.3390/app12168240 - 17 Aug 2022
Cited by 8 | Viewed by 2489
Abstract
Nowadays, the contamination of wastewater by organic persistent pollutants is a reality. These pollutants are difficult to remove from wastewater with conventional techniques; hence, it is necessary to go on the hunt for new, innovative and environmentally sustainable ones. In this context, advanced [...] Read more.
Nowadays, the contamination of wastewater by organic persistent pollutants is a reality. These pollutants are difficult to remove from wastewater with conventional techniques; hence, it is necessary to go on the hunt for new, innovative and environmentally sustainable ones. In this context, advanced oxidation processes have attracted great attention and have developed rapidly in recent years as promising technologies. The cornerstone of advanced oxidation processes is the selection of heterogeneous catalysts. In this sense, the possibility of using metal–organic frameworks as catalysts has been opened up given their countless physical–chemical characteristics, which can overcome several disadvantages of traditional catalysts. Thus, this review provides a brief review of recent progress in the research and practical application of metal–organic frameworks to advanced oxidation processes, with a special emphasis on the potential of Fe-based metal–organic frameworks to reduce the pollutants present in wastewater or to render them harmless. To do that, the work starts with a brief overview of the different types and pathways of synthesis. Moreover, the mechanisms of the generation of radicals, as well as their action on the organic pollutants and stability, are analysed. Finally, the challenges of this technology to open up new avenues of wastewater treatment in the future are sketched out. Full article
(This article belongs to the Section Environmental Sciences)
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32 pages, 14207 KiB  
Article
On the Patterns and Scaling Properties of the 2021–2022 Arkalochori Earthquake Sequence (Central Crete, Greece) Based on Seismological, Geophysical and Satellite Observations
by Filippos Vallianatos, Andreas Karakonstantis, Georgios Michas, Kyriaki Pavlou, Maria Kouli and Vassilis Sakkas
Appl. Sci. 2022, 12(15), 7716; https://doi.org/10.3390/app12157716 - 31 Jul 2022
Cited by 9 | Viewed by 1827
Abstract
The 27 September 2021 damaging mainshock (Mw6.0) close to Arkalochori village is the strongest earthquake that was recorded during the instrumental period of seismicity in Central Crete (Greece). The mainshock was preceded by a significant number of foreshocks that lasted nearly four months. [...] Read more.
The 27 September 2021 damaging mainshock (Mw6.0) close to Arkalochori village is the strongest earthquake that was recorded during the instrumental period of seismicity in Central Crete (Greece). The mainshock was preceded by a significant number of foreshocks that lasted nearly four months. Maximum ground subsidence of about 18 cm was estimated from InSAR processing. The aftershock sequence is located in an almost NE-SW direction and divided into two main clusters, the southern and the northern ones. The foreshock activity, the deformation area, and the strongest aftershocks are located within the southern cluster. Based on body-wave travel times, a 3-D velocity model was developed, while using combined space and ground-based geodetic techniques, the co-seismic ground deformation is presented. Moreover, we examined the co-seismic static stress changes with respect to the aftershocks’ spatial distribution during the major events of the foreshocks, the Mw = 6.0 main event as well as the largest aftershock. Both the foreshock and the aftershock sequences obey the scaling law for the frequency-magnitude distribution as derived from the framework of non-extensive statistical physics (NESP). The aftershock production rate decays according to the modified Omori scaling law, exhibiting various Omori regimes due to the generation of secondary aftershock sequences. The analysis of the inter-event time distribution, based on NESP, further indicates asymptotic power-law scaling and long-range correlations among the events. The spatiotemporal evolution of the aftershock sequence indicates triggering by co-seismic stress transfer, while its slow migration towards the outer edges of the area of the aftershocks, related to the logarithm of time, further indicates a possible afterslip. Full article
(This article belongs to the Special Issue Geographic Visualization: Evaluation and Monitoring of Geohazards)
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21 pages, 7008 KiB  
Article
An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM
by Nikolaos I. Papandrianos, Anna Feleki, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Ioannis D. Apostolopoulos and Dimitris J. Apostolopoulos
Appl. Sci. 2022, 12(15), 7592; https://doi.org/10.3390/app12157592 - 28 Jul 2022
Cited by 13 | Viewed by 3082
Abstract
Background: This study targets the development of an explainable deep learning methodology for the automatic classification of coronary artery disease, utilizing SPECT MPI images. Deep learning is currently judged as non-transparent due to the model’s complex non-linear structure, and thus, it is considered [...] Read more.
Background: This study targets the development of an explainable deep learning methodology for the automatic classification of coronary artery disease, utilizing SPECT MPI images. Deep learning is currently judged as non-transparent due to the model’s complex non-linear structure, and thus, it is considered a «black box», making it hard to gain a comprehensive understanding of its internal processes and explain its behavior. Existing explainable artificial intelligence tools can provide insights into the internal functionality of deep learning and especially of convolutional neural networks, allowing transparency and interpretation. Methods: This study seeks to address the identification of patients’ CAD status (infarction, ischemia or normal) by developing an explainable deep learning pipeline in the form of a handcrafted convolutional neural network. The proposed RGB-CNN model utilizes various pre- and post-processing tools and deploys a state-of-the-art explainability tool to produce more interpretable predictions in decision making. The dataset includes cases from 625 patients as stress and rest representations, comprising 127 infarction, 241 ischemic, and 257 normal cases previously classified by a doctor. The imaging dataset was split into 20% for testing and 80% for training, of which 15% was further used for validation purposes. Data augmentation was employed to increase generalization. The efficacy of the well-known Grad-CAM-based color visualization approach was also evaluated in this research to provide predictions with interpretability in the detection of infarction and ischemia in SPECT MPI images, counterbalancing any lack of rationale in the results extracted by the CNNs. Results: The proposed model achieved 93.3% accuracy and 94.58% AUC, demonstrating efficient performance and stability. Grad-CAM has shown to be a valuable tool for explaining CNN-based judgments in SPECT MPI images, allowing nuclear physicians to make fast and confident judgments by using the visual explanations offered. Conclusions: Prediction results indicate a robust and efficient model based on the deep learning methodology which is proposed for CAD diagnosis in nuclear medicine. Full article
(This article belongs to the Special Issue Information Processing in Medical Imaging)
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18 pages, 1832 KiB  
Review
Halophytes as Medicinal Plants against Human Infectious Diseases
by Maria João Ferreira, Diana C. G. A. Pinto, Ângela Cunha and Helena Silva
Appl. Sci. 2022, 12(15), 7493; https://doi.org/10.3390/app12157493 - 26 Jul 2022
Cited by 14 | Viewed by 2675
Abstract
Halophytes have long been used for medicinal purposes. However, for many decades, their use was entirely empirical, with virtually no knowledge of the bioactive compounds underlying the different applications. In recent decades, the growing problem of antibiotic resistance triggered the research on alternative [...] Read more.
Halophytes have long been used for medicinal purposes. However, for many decades, their use was entirely empirical, with virtually no knowledge of the bioactive compounds underlying the different applications. In recent decades, the growing problem of antibiotic resistance triggered the research on alternative antimicrobial approaches, and halophytes, along with other medicinal plants, regained attention as an underexplored pharmacological vein. Furthermore, the high nutritional/nutraceutical/pharmacological value of some halophytic species may represent added value to the emerging activity of saline agriculture and targeted modification of the rhizosphere, with plant-growth-promoting bacteria being attempted to be used as a tool to modulate the plant metabolome and enhance the expression of interesting metabolites. The objective of this review is to highlight the potential of halophytes as a valuable, and still unexplored, source of antimicrobial compounds for clinical applications. For that, we provide a critical perspective on the empirical use of halophytes in traditional medicine and a state-or-the-art overview of the most relevant plant species and metabolites related with antiviral, antifungal and antibacterial activities. Full article
(This article belongs to the Special Issue Recent Advances in Halophytes Plants)
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13 pages, 1167 KiB  
Article
An Innovative, Green Cascade Protocol for Grape Stalk Valorization with Process Intensification Technologies
by Manuel Salgado-Ramos, Silvia Tabasso, Emanuela Calcio Gaudino, Andrés Moreno, Francesco Mariatti and Giancarlo Cravotto
Appl. Sci. 2022, 12(15), 7417; https://doi.org/10.3390/app12157417 - 23 Jul 2022
Cited by 6 | Viewed by 1550
Abstract
Valorization of agri-food residues to produce bio-based platform chemicals will enhance the transition to the bio-economy era. To this end, a sustainable process has been developed for the overall valorization of grape stalks (GS) according to a circular approach, starting from the [...] Read more.
Valorization of agri-food residues to produce bio-based platform chemicals will enhance the transition to the bio-economy era. To this end, a sustainable process has been developed for the overall valorization of grape stalks (GS) according to a circular approach, starting from the lignin fraction to further deal with the cellulose-rich residue. This non-conventional protocol fully adheres to green chemistry principles, exploiting the so-called enabling technologies—mainly ultrasound and microwaves—for energy-saving innovative processes. Firstly, ultrasound-assisted extraction (UAE, 40 kHz, 200 W) demonstrated to be an excellent technique for GS delignification combined with natural deep eutectic solvents (NaDESs). Delignification enables isolation of the pertinent lignin framework and the potential to obtain a polyphenol-rich liquid fraction, focusing on the valorization of GS as source of bioactive compounds (BACs). Among the NaDESs employed, the combination of choline chloride (ChCl) and levulinic acid (LevA) (ChLevA) presented noteworthy results, enabling a delignification higher than 70%. LevA is one of the top-value biobased platform chemicals. In this work, a flash microwave (MW)-assisted process was subsequently applied to the cellulose-rich fraction remained after delignification, yielding 85% LevA. The regeneration of this starting compound to produce ChLevA can lead to a further biomass delignification cycle, thus developing a new cascade protocol for a full valorization of GS. Full article
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13 pages, 3732 KiB  
Review
Principle and Implementation of Stokes Vector Polarization Imaging Technology
by Yong Wang, Yuqing Su, Xiangyu Sun, Xiaorui Hao, Yanping Liu, Xiaolong Zhao, Hongsheng Li, Xiushuo Zhang, Jing Xu, Jingjing Tian, Xiaofei Kong, Zhiwei Wang and Jie Yang
Appl. Sci. 2022, 12(13), 6613; https://doi.org/10.3390/app12136613 - 29 Jun 2022
Cited by 13 | Viewed by 2729
Abstract
Compared with traditional imaging methods, polarization imaging has its unique advantages in many directions and has great development prospects. It is one of the hot spots of research and development at home and abroad. Based on the polarization imaging principle of Stokes vector, [...] Read more.
Compared with traditional imaging methods, polarization imaging has its unique advantages in many directions and has great development prospects. It is one of the hot spots of research and development at home and abroad. Based on the polarization imaging principle of Stokes vector, the realization methods of non-simultaneous polarization imaging and simultaneous polarization imaging are introduced, respectively according to the different polarization modulation methods of Stokes vector acquisition. Non-simultaneous polarization imaging is mainly introduced in two ways: rotary polarization imaging, electrically controlled polarization imaging, and the simultaneous polarization imaging is mainly introduced in three ways: divided amplitude polarization imaging, divided aperture polarization imaging, and divided focal plane polarization imaging. In this paper, the principle and realization of polarization imaging based on Stokes vector are introduced to boost the application of polarization imaging and promote the research and development of polarization imaging technology. Full article
(This article belongs to the Special Issue Novel Biophotonics Technologies and Applications)
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19 pages, 6235 KiB  
Article
A Hybrid Early Warning Method for the Landslide Acceleration Process Based on Automated Monitoring Data
by Dongxin Bai, Guangyin Lu, Ziqiang Zhu, Xudong Zhu, Chuanyi Tao and Ji Fang
Appl. Sci. 2022, 12(13), 6478; https://doi.org/10.3390/app12136478 - 26 Jun 2022
Cited by 8 | Viewed by 1618
Abstract
The data collection in the automated monitoring of landslides is often characterized by large amounts of data, periodic fluctuations, many outliers, and different collection intervals. The traditional method of calculating velocity and acceleration using the differential algorithm for landslide acceleration relies on experience [...] Read more.
The data collection in the automated monitoring of landslides is often characterized by large amounts of data, periodic fluctuations, many outliers, and different collection intervals. The traditional method of calculating velocity and acceleration using the differential algorithm for landslide acceleration relies on experience to select thresholds and produces a large number of false early warnings. A hybrid early warning method for the landslide acceleration process based on automated monitoring data is proposed to solve this problem. The method combines the conventional warning method, based on cumulative displacement, velocity, and acceleration, and the critical sliding warning method based on normalized tangent angle according to different strategies. On the one hand, the least-squares fitting of monitoring data inside a given time window is used to calculate various early warning parameters, improving data usage and lowering calculation error. On the other hand, a dynamic semi-quantitative and semi-empirical method is provided for the determination of the thresholds, which is more reliable than the purely empirical method. The validation experiments at the Lishanyuan landslide in southern China show that the hybrid method can accurately identify the accelerating deformation of the landslide and gives very few false warnings. The proposed method is practical and effective for systems that require automated monitoring and warnings for a large number of landslides. Full article
(This article belongs to the Special Issue Structural Analysis and Evaluation of Rocks and Rock Masses)
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11 pages, 2019 KiB  
Article
O-Band Multimode Interference Coupler Power Combiner Using Slot-Waveguide Structures
by Salman Khateeb, Netanel Katash and Dror Malka
Appl. Sci. 2022, 12(13), 6444; https://doi.org/10.3390/app12136444 - 24 Jun 2022
Cited by 8 | Viewed by 2262
Abstract
Photonic transmitters that operate with a high data transfer rate (over 150 Gb/s) at the O-band range (1260–1360 nm) require at least 100 milliwatts of power to overcome the power losses that are caused by using high-speed modulators. A laser with higher power [...] Read more.
Photonic transmitters that operate with a high data transfer rate (over 150 Gb/s) at the O-band range (1260–1360 nm) require at least 100 milliwatts of power to overcome the power losses that are caused by using high-speed modulators. A laser with higher power can probably handle this requirement; however, for the transmitter system, this solution can be problematic due to the nonlinear effects that can happen, which may lead to high noise in the transmitter system. Thus, to solve this issue, we propose a new design of a 2 × 1 multimode interference (MMI) power combiner using silicon nitride (SiN) slot waveguide structures. The MMI power combiner and the SiN slot waveguide structures were optimized using the full-vectorial beam propagation method (FV-BPM) and the finite difference time domain (FDTD) method. After combining two sources, high efficiency was obtained of 94.8–97.6% from the total power after a short coupling length of 109.81 µm over the O-band range with a low back reflection of 44.94 dB. Thus, the proposed device can be very useful for combining two O-band sources to gain a higher power level, which can be utilized to improve performances in transmitter systems. Full article
(This article belongs to the Special Issue Recent Advances in Silicon Photonics Design)
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14 pages, 2227 KiB  
Review
A Review of Optical Neural Networks
by Danni Zhang and Zhongwei Tan
Appl. Sci. 2022, 12(11), 5338; https://doi.org/10.3390/app12115338 - 25 May 2022
Cited by 13 | Viewed by 6965
Abstract
With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and constraining the application of deep learning. Optical neuromorphic computing presents various [...] Read more.
With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and constraining the application of deep learning. Optical neuromorphic computing presents various opportunities and challenges compared with the realm of electronics. Algorithms running on optical hardware have the potential to meet the growing computational demands of deep learning and artificial intelligence. Here, we review the development of optical neural networks and compare various research proposals. We focus on fiber-based neural networks. Finally, we describe some new research directions and challenges. Full article
(This article belongs to the Collection New Trends in Optical Networks)
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14 pages, 2370 KiB  
Article
Estimation of Cosmic-Ray-Induced Atmospheric Ionization and Radiation at Commercial Aviation Flight Altitudes
by Panagiota Makrantoni, Anastasia Tezari, Argyris N. Stassinakis, Pavlos Paschalis, Maria Gerontidou, Pantelis Karaiskos, Alexandros G. Georgakilas, Helen Mavromichalaki, Ilya G. Usoskin, Norma Crosby and Mark Dierckxsens
Appl. Sci. 2022, 12(11), 5297; https://doi.org/10.3390/app12115297 - 24 May 2022
Cited by 8 | Viewed by 2331
Abstract
The main source of the ionization of the Earth’s atmosphere is the cosmic radiation that depends on solar activity as well as geomagnetic activity. Galactic cosmic rays constitute a permanent radiation background and contribute significantly to the radiation exposure inside the atmosphere. In [...] Read more.
The main source of the ionization of the Earth’s atmosphere is the cosmic radiation that depends on solar activity as well as geomagnetic activity. Galactic cosmic rays constitute a permanent radiation background and contribute significantly to the radiation exposure inside the atmosphere. In this work, the cosmic-ray-induced ionization of the Earth’s atmosphere, due to both solar and galactic cosmic radiation during the recent solar cycles 23 (1996–2008) and 24 (2008–2019), was studied globally. Estimations of the ionization were based on the CRAC:CRII model by the University of Oulu. The use of this model allowed for extensive calculations from the Earth’s surface (atmospheric depth 1033 g/cm2) to the upper limit of the atmosphere (atmospheric depth 0 g/cm2). Monte Carlo simulations were performed for the estimation quantities of radiobiological interest with the validated software DYASTIMA/DYASTIMA-R. This study was focused on specific altitudes of interest, such as the common flight levels used by commercial aviation. Full article
(This article belongs to the Special Issue Advances in Environmental Applied Physics)
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13 pages, 10605 KiB  
Article
Applications of Decision Tree and Random Forest as Tree-Based Machine Learning Techniques for Analyzing the Ultimate Strain of Spliced and Non-Spliced Reinforcement Bars
by Hamed Dabiri, Visar Farhangi, Mohammad Javad Moradi, Mehdi Zadehmohamad and Moses Karakouzian
Appl. Sci. 2022, 12(10), 4851; https://doi.org/10.3390/app12104851 - 11 May 2022
Cited by 37 | Viewed by 2541
Abstract
The performance of both non-spliced and spliced steel bars significantly affects the overall performance of structural reinforced concrete elements. In this context, the mechanical properties of reinforcement bars (i.e., their ultimate strength and strain) should be determined in order to evaluate their reliability [...] Read more.
The performance of both non-spliced and spliced steel bars significantly affects the overall performance of structural reinforced concrete elements. In this context, the mechanical properties of reinforcement bars (i.e., their ultimate strength and strain) should be determined in order to evaluate their reliability prior to the construction procedure. In this study, the application of Tree-Based machine learning techniques is implemented to analyze the ultimate strain of non-spliced and spliced steel reinforcements. In this regard, a database containing the results of 225 experimental tests was collected based on the research investigations available in peer-reviewed international publications. The database included the mechanical properties of both non-spliced and mechanically spliced bars. For better accuracy, the databases of other splicing methods such as lap and welded-spliced methods were excluded from this research. The database was categorized as two sub-databases: training (85%) and testing (15%) of the developed models. Various effective parameters such as splice technique, steel grade of the bar, diameter of the steel bar, coupler geometry—including length and outer diameter along with the testing temperatures—were defined as the input variables for analyzing the ultimate strain using tree-based approaches including Decision Trees and Random Forest. The predicted outcomes were compared to the actual values and the precision of the prediction models was assessed via performance metrics, along with a Taylor diagram. Based on the reported results, the reliability of the proposed ML-based methods was acceptable (with an R2 ≥ 85%) and they were time-saving and cost-effective compared to more complicated, time-consuming, and expensive experimental examinations. More importantly, the models proposed in this study can be further considered as a part of a comprehensive prediction model for estimating the stress-strain behavior of steel bars. Full article
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19 pages, 2035 KiB  
Article
Waste Management in a Sustainable Circular Economy as a Part of Design of Construction
by Marcela Spišáková, Tomáš Mandičák, Peter Mésároš and Matej Špak
Appl. Sci. 2022, 12(9), 4553; https://doi.org/10.3390/app12094553 - 30 Apr 2022
Cited by 14 | Viewed by 5291
Abstract
The Architecture, Engineering, and Construction (AEC) industries are the producers of the most significant waste stream in the European Union. Known EU initiatives propose to deal with the issue of construction and demolition waste (CDW) according to the principles of a circular economy: [...] Read more.
The Architecture, Engineering, and Construction (AEC) industries are the producers of the most significant waste stream in the European Union. Known EU initiatives propose to deal with the issue of construction and demolition waste (CDW) according to the principles of a circular economy: the 3Rs (reduce, reuse, and recycle). CDW is generated during the whole life cycle of construction. The lack of information about the quantity of CDW during the design phase of building needed for sustainable design of construction was identified as a research gap. The aim of our research is to quantify construction and demolition waste during the construction design phase in a circular economy. The proposed method is based on the generation rate calculation method. This paper describes the proposed methodology for quantifying selected types of construction waste: excavated soil, concrete, and masonry. This information is essential from the point of view of a sustainable circular economy. The main contributions of the paper were identified during the decision-making process of sustainable building design, during the audit of CDW management, and during building information modelling as a support tool for CDW management. As early as the construction design phase, there is the possibility of choosing technologies, construction processes, and materials that have a higher degree of circularity in the economy. Full article
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13 pages, 6182 KiB  
Article
Wear Resistance Comparison Research of High-Alloy Protective Coatings for Power Industry Prepared by Means of CMT Cladding
by Paweł Kołodziejczak, Mariusz Bober and Tomasz Chmielewski
Appl. Sci. 2022, 12(9), 4568; https://doi.org/10.3390/app12094568 - 30 Apr 2022
Cited by 19 | Viewed by 1793
Abstract
In this study, four protective coating materials: Inconel 718, Inconel 625, Alloy 33 and Stellite 6 were deposited on 16Mo3 steel tubes by means of CMT (Cold Metal Transfer), as an advanced version of MAG (Metal Active Gas) welding method. In the next [...] Read more.
In this study, four protective coating materials: Inconel 718, Inconel 625, Alloy 33 and Stellite 6 were deposited on 16Mo3 steel tubes by means of CMT (Cold Metal Transfer), as an advanced version of MAG (Metal Active Gas) welding method. In the next step, the surface of the deposited coating was remelted by means of TIG (Tungsten Inert Gas) welding method. SEM microstructure of coatings–substrate has been reported, and an EDX-researched chemical composition of the coatings was compared to the nominal chemical composition. The hardness distribution in the cross-section was performed, which revealed that among investigated coatings, Stellite 6 layer is the hardest, at about 500 HV0.2. Other materials such as Inconel 625, Inconel 718 and Alloy 33 represented a cladded zone hardness about 250 HV0.2. Stellite 6 layer had the lowest wear resistance in the dry sand/rubber wheel test, and Stellite 6 layer had the highest wear resistance in the erosive blasting test. This proved the existence of different wear mechanisms in the two test methods used. In the dry sand/rubber wheel test, the Alloy 33 and Inconel 718 only represented higher wear resistance than substrate 16Mo3 steel. In abrasive blasting tests all coatings had higher wear resistance than 16Mo3 steel; however, Stellite 6 coatings represented an approximately 5 times higher durability than other investigated (Inconel 625, Inconel 718, and Alloy 33) coatings. Full article
(This article belongs to the Special Issue Advances in Surface Modification of the Materials)
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15 pages, 2755 KiB  
Review
Characteristics and Applications of Biochar in Soil–Plant Systems: A Short Review of Benefits and Potential Drawbacks
by Tamás Kocsis, Marianna Ringer and Borbála Biró
Appl. Sci. 2022, 12(8), 4051; https://doi.org/10.3390/app12084051 - 16 Apr 2022
Cited by 28 | Viewed by 7058
Abstract
The available literary data suggest the general applicability and benefits of different biochar products in various soil–plant–environment systems. Due to its high porosity, biochar might generally improve the physicochemical and biological properties of supplemented soils. Among the direct and indirect effects are (i) [...] Read more.
The available literary data suggest the general applicability and benefits of different biochar products in various soil–plant–environment systems. Due to its high porosity, biochar might generally improve the physicochemical and biological properties of supplemented soils. Among the direct and indirect effects are (i) improved water-retention capacity, (ii) enhanced soil organic matter content, (iii) pH increase, (iv) better N and P availability, and (v) greater potential uptake of meso- and micronutrients. These are connected to the advantage of an enhanced soil oxygen content. The large porous surface area of biochar might indirectly protect the survival of microorganisms, while the adsorbed organic materials may improve the growth of both bacteria and fungi. On the other hand, N2-fixing Rhizobium bacteria and P-mobilizing mycorrhiza fungi might respond negatively to biochar’s application. In arid circumstances with limited water and nutrient availability, a synergistic positive effect was found in biochar–microbial combined applications. Biochar seems to be a valuable soil supplement if its application is connected with optimized soil–plant–environment conditions. This work aims to give a general review of the potential benefits and drawbacks of biochar application to soil, highlighting its impacts on the soil–plant–microbe system. Full article
(This article belongs to the Special Issue Biochar: Preparation and Surface Adsorption Applications)
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16 pages, 2298 KiB  
Review
Orthopedics-Related Applications of Ultrafast Laser and Its Recent Advances
by Celina L. Li, Carl J. Fisher, Ray Burke and Stefan Andersson-Engels
Appl. Sci. 2022, 12(8), 3957; https://doi.org/10.3390/app12083957 - 14 Apr 2022
Cited by 14 | Viewed by 3032
Abstract
The potential of ultrafast lasers (pico- to femtosecond) in orthopedics-related procedures has been studied extensively for clinical adoption. As compared to conventional laser systems with continuous wave or longer wave pulse, ultrafast lasers provide advantages such as higher precision and minimal collateral thermal [...] Read more.
The potential of ultrafast lasers (pico- to femtosecond) in orthopedics-related procedures has been studied extensively for clinical adoption. As compared to conventional laser systems with continuous wave or longer wave pulse, ultrafast lasers provide advantages such as higher precision and minimal collateral thermal damages. Translation to surgical applications in the clinic has been restrained by limitations of material removal rate and pulse average power, whereas the use in surface texturing of implants has become more refined to greatly improve bioactivation and osteointegration within bone matrices. With recent advances, we review the advantages and limitations of ultrafast lasers, specifically in orthopedic bone ablation as well as bone implant laser texturing, and consider the difficulties encountered within orthopedic surgical applications where ultrafast lasers could provide a benefit. We conclude by proposing our perspectives on applications where ultrafast lasers could be of advantage, specifically due to the non-thermal nature of ablation and control of cutting. Full article
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11 pages, 2735 KiB  
Review
An Overview of Terahertz Imaging with Resonant Tunneling Diodes
by Jue Wang, Mira Naftaly and Edward Wasige
Appl. Sci. 2022, 12(8), 3822; https://doi.org/10.3390/app12083822 - 10 Apr 2022
Cited by 11 | Viewed by 3306
Abstract
Terahertz (THz) imaging is a rapidly growing application motivated by industrial demands including harmless (non-ionizing) security imaging, multilayer paint quality control within the automotive industry, insulating foam non-invasive testing in aerospace, and biomedical diagnostics. One of the key components in the imaging system [...] Read more.
Terahertz (THz) imaging is a rapidly growing application motivated by industrial demands including harmless (non-ionizing) security imaging, multilayer paint quality control within the automotive industry, insulating foam non-invasive testing in aerospace, and biomedical diagnostics. One of the key components in the imaging system is the source and detector. This paper gives a brief overview of room temperature THz transceiver technology for imaging applications based on the emerging resonant tunneling diode (RTD) devices. The reported results demonstrate that RTD technology is a very promising candidate to realize compact, low-cost THz imaging systems. Full article
(This article belongs to the Special Issue Terahertz Applications for Nondestructive Testing)
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18 pages, 3347 KiB  
Article
THz Time-Domain Ellipsometer for Material Characterization and Paint Quality Control with More Than 5 THz Bandwidth
by Helge Ketelsen, Rüdiger Mästle, Lars Liebermeister, Robert Kohlhaas and Björn Globisch
Appl. Sci. 2022, 12(8), 3744; https://doi.org/10.3390/app12083744 - 08 Apr 2022
Cited by 7 | Viewed by 2053
Abstract
Quality control of car body paint in the automotive industry is a promising industrial application of terahertz technology. Terahertz time-domain spectroscopy in reflection geometry enables accurate, fast, and nondestructive measurement of individual layer thicknesses of multi-layer coatings. For high precision thickness measurements, the [...] Read more.
Quality control of car body paint in the automotive industry is a promising industrial application of terahertz technology. Terahertz time-domain spectroscopy in reflection geometry enables accurate, fast, and nondestructive measurement of individual layer thicknesses of multi-layer coatings. For high precision thickness measurements, the frequency dependent complex refractive index of all layers must be calibrated very accurately. THz time-domain ellipsometry is self-referencing and provides reliable, frequency resolved material properties with high signal-to-noise ratio. The method is characterized by a high sensitivity to optical material properties and layer thicknesses. We present characterization results in the frequency range 0.1–6 THz for typical automotive paints and different substrates such as polypropylene (PP), which features a high material anisotropy. We demonstrate that the broadband material properties derived from ellipsometry allow for inline thickness measurements of multi-layer car body paints with high accuracy. Full article
(This article belongs to the Special Issue Terahertz Applications for Nondestructive Testing)
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14 pages, 1153 KiB  
Article
Polymer Pellet Fabrication for Accurate THz-TDS Measurements
by Keir N. Murphy, Mira Naftaly, Alison Nordon and Daniel Markl
Appl. Sci. 2022, 12(7), 3475; https://doi.org/10.3390/app12073475 - 29 Mar 2022
Cited by 9 | Viewed by 2329
Abstract
We investigate fabrication of compacts using polytetrafluoroethylene (PTFE) and polyethylene (PE), and the effect of compaction conditions on their terahertz transmission properties. The conditions used to fabricate compressed powder samples for terahertz time-domain spectroscopy (THz-TDS) can impact the accuracy of the measurements and [...] Read more.
We investigate fabrication of compacts using polytetrafluoroethylene (PTFE) and polyethylene (PE), and the effect of compaction conditions on their terahertz transmission properties. The conditions used to fabricate compressed powder samples for terahertz time-domain spectroscopy (THz-TDS) can impact the accuracy of the measurements and hence the interpretation of results. This study investigated the effect of compaction conditions on the accuracy of the THz-TDS analysis. Two polymers that are commonly used as matrix materials in terahertz spectroscopy studies were explored using a compaction simulator and a hydraulic press for sample preparation. THz-TDS was used to determine the refractive index and loss coefficient to compare the powder compacts (pellets) to the values of solid material. Sample porosity, axial relaxation and tensile strength were measured to assess the material’s suitability for terahertz spectroscopy. It was found that PTFE is the preferable material for creating THz-TDS samples due to its low porosity and high tensile strength. PE was found to show significant porosity at all compaction pressures, making it an unsuitable material for the accurate determination of optical parameters from THz-TDS spectroscopy measurements. The larger particle sizes of PE resulted in compacts that exhibited significantly lower tensile strength than those made from PTFE making handling and storage difficult. Full article
(This article belongs to the Special Issue Terahertz Applications for Nondestructive Testing)
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20 pages, 16739 KiB  
Article
Fire Risk Probability Mapping Using Machine Learning Tools and Multi-Criteria Decision Analysis in the GIS Environment: A Case Study in the National Park Forest Dadia-Lefkimi-Soufli, Greece
by Yannis Maniatis, Athanasios Doganis and Minas Chatzigeorgiadis
Appl. Sci. 2022, 12(6), 2938; https://doi.org/10.3390/app12062938 - 13 Mar 2022
Cited by 12 | Viewed by 4600
Abstract
Fire risk will increase in the upcoming years due to climate change. In this context, GIS analysis for fire risk mapping is an important tool to identify high risk areas and allocate resources. In the present study, we aimed to create a fire [...] Read more.
Fire risk will increase in the upcoming years due to climate change. In this context, GIS analysis for fire risk mapping is an important tool to identify high risk areas and allocate resources. In the present study, we aimed to create a fire risk estimation model that incorporates recent land cover changes, along with other important risk factors. As a study area, we selected Dadia-Lefkimi-Soufli National Forest Park and the surrounding area since it is one of the most important protected areas in Greece. The area selected for the case study is a typical Mediterranean landscape. As a result, the outcome model is generic and can be applied to other areas. In order to incorporate land cover changes in our model, we used a support vector machine (SVM) algorithm to classify a satellite image captured in September 2021 and an image of the same period two years ago to obtain comparable results. Next, two fire risk maps were created with a combination of land cover and six other factors, using the analytic hierarchy process (AHP) on a GIS platform. The results of our model revealed noticeable clusters of extreme high risk areas, while the overall fire risk in the National Park Forest of Dadia-Lefkimi-Soufli was classified as high. The wildfires of 1st October 2020 and 9th July 2021 confirmed our model and contributed to quantification of their impact on fire risk due to land cover change. Full article
(This article belongs to the Special Issue GIS Applications in Green Development)
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24 pages, 11419 KiB  
Article
The 27 September 2021 Earthquake in Central Crete (Greece)—Detailed Analysis of the Earthquake Sequence and Indications for Contemporary Arc-Parallel Extension to the Hellenic Arc
by Emmanuel Vassilakis, George Kaviris, Vasilis Kapetanidis, Elena Papageorgiou, Michael Foumelis, Aliki Konsolaki, Stelios Petrakis, Christos P. Evangelidis, John Alexopoulos, Vassilios Karastathis, Nicholas Voulgaris and Gerassimos-Akis Tselentis
Appl. Sci. 2022, 12(6), 2815; https://doi.org/10.3390/app12062815 - 09 Mar 2022
Cited by 15 | Viewed by 3121
Abstract
The Arkalochori village in central Crete was hit by a large earthquake (Mw = 6.0) on 27 September 2021, causing casualties, injuries, and severe damage to the infrastructure. Due to the absence of apparent surface rupture and the initial focal mechanism [...] Read more.
The Arkalochori village in central Crete was hit by a large earthquake (Mw = 6.0) on 27 September 2021, causing casualties, injuries, and severe damage to the infrastructure. Due to the absence of apparent surface rupture and the initial focal mechanism solution of the seismic event, we initiated complementary, multi-disciplinary research by combining seismological and remote sensing data processing, followed by extensive field validation. Detailed geological mapping, fault surface measuring accompanied with tectonic analysis, fault photorealistic model creation by unmanned aerial system data processing, post-seismic surface deformation analysis by DInSAR image interpretation coupled with accurately relocated epicenters recorded by locally established seismographs have been carried out. The combination of the results obtained from these techniques led to the determination of the contemporary tectonic stress regime that caused the earthquake in central Crete, which was found compatible with extensional processes parallel to the Hellenic arc. Full article
(This article belongs to the Special Issue Mapping, Monitoring and Assessing Disasters)
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27 pages, 651 KiB  
Review
Development and Characterization of Bioadsorbents Derived from Different Agricultural Wastes for Water Reclamation: A Review
by Julián Aguilar-Rosero, María E. Urbina-López, Blanca E. Rodríguez-González, Sol X. León-Villegas, Itza E. Luna-Cruz and Diana L. Cárdenas-Chávez
Appl. Sci. 2022, 12(5), 2740; https://doi.org/10.3390/app12052740 - 07 Mar 2022
Cited by 14 | Viewed by 4001
Abstract
The presence of dangerous pollutants in different water sources has restricted the availability of this natural resource. Thus, the development of new low-cost and environmentally-friendly technologies is currently required to ensure access to clean water. Various approaches to the recovery of contaminated water [...] Read more.
The presence of dangerous pollutants in different water sources has restricted the availability of this natural resource. Thus, the development of new low-cost and environmentally-friendly technologies is currently required to ensure access to clean water. Various approaches to the recovery of contaminated water have been considered, including the generation of biomaterials with adsorption capacity for dangerous compounds. Research on bioadsorbents has boomed in recent years, as they constitute one of the most sustainable options for water treatment thanks to their abundance and high cellulose content. Thanks to the vast amount of information published to date, the present review addresses the current status of different biosorbents and the principal processes and characterization methods involved, focusing on base biomaterials such as fruits and vegetables, grains and seeds, and herbage and forage. In comparison to other reviews, this work reports more than 60 adsorbents obtained from agricultural wastes. The removal efficiencies and/or maximum adsorption capacities for heavy metals, industrial contaminants, nutrients and pharmaceuticals are presented as well. In addition to the valuable information provided in the literature investigation, challenges and perspectives concerning the implementation of bioadsorbents are discussed in order to comprehensively guide selection of the most suitable biomaterials according to the target contaminant and the available biowastes. Full article
(This article belongs to the Special Issue Biowaste Treatment and Valorization)
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18 pages, 448 KiB  
Review
Biodegradable Solvents: A Promising Tool to Recover Proteins from Microalgae
by David Moldes, Elena M. Rojo, Silvia Bolado, Pedro A. García-Encina and Bibiana Comesaña-Gándara
Appl. Sci. 2022, 12(5), 2391; https://doi.org/10.3390/app12052391 - 25 Feb 2022
Cited by 9 | Viewed by 3422
Abstract
The world will face a significant protein demand in the next few decades, and due to the environmental concerns linked to animal protein, new sustainable protein sources must be found. In this regard, microalgae stand as an outstanding high-quality protein source. However, different [...] Read more.
The world will face a significant protein demand in the next few decades, and due to the environmental concerns linked to animal protein, new sustainable protein sources must be found. In this regard, microalgae stand as an outstanding high-quality protein source. However, different steps are needed to separate the proteins from the microalgae biomass and other biocompounds. The protein recovery from the disrupted biomass is usually the bottleneck of the process, and it typically employs organic solvents or harsh conditions, which are both detrimental to protein stability and planet health. Different techniques and methods are applied for protein recovery from various matrices, such as precipitation, filtration, chromatography, electrophoresis, and solvent extraction. Those methods will be reviewed in this work, discussing their advantages, drawbacks, and applicability to the microalgae biorefinery process. Special attention will be paid to solvent extraction performed with ionic liquids (ILs) and deep eutectic solvents (DESs), which stand as promising solvents to perform efficient protein separations with reduced environmental costs compared to classical alternatives. Finally, several solvent recovery options will be analyzed to reuse the solvent employed and isolate the proteins from the solvent phase. Full article
(This article belongs to the Special Issue Biowaste Treatment and Valorization)
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26 pages, 4898 KiB  
Article
The Behavior of Hybrid Fiber-Reinforced Concrete Elements: A New Stress-Strain Model Using an Evolutionary Approach
by Ali A. Abdulhameed, Alaa Hussein Al-Zuhairi, Salah R. Al Zaidee, Ammar N. Hanoon, Ahmed W. Al Zand, Mahir M. Hason and Haider A. Abdulhameed
Appl. Sci. 2022, 12(4), 2245; https://doi.org/10.3390/app12042245 - 21 Feb 2022
Cited by 22 | Viewed by 3853
Abstract
Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of [...] Read more.
Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the particle swarm optimization (PSO) technique. It was discovered in this investigation that the new stress-strain model predictions are consistent with the remaining 20% of the experimental stress-strain curves obtained. Case studies of hybrid–fiber–reinforced concrete constructions were investigated in order to better understand the behavior of such elements. The data revealed that the proposed model has the highest absolute relative error (ARE) frequencies (ARE 10%) and the lowest absolute relative error (ARE > 15%) frequencies (ARE > 15%). Full article
(This article belongs to the Special Issue Structural Application of Advanced Concrete Materials)
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19 pages, 268 KiB  
Review
Internet of Things Platforms for Academic Research and Development: A Critical Review
by Luca De Nardis, Alireza Mohammadpour, Giuseppe Caso, Usman Ali and Maria-Gabriella Di Benedetto
Appl. Sci. 2022, 12(4), 2172; https://doi.org/10.3390/app12042172 - 19 Feb 2022
Cited by 10 | Viewed by 3259
Abstract
Tens of different IoT platforms are currently available on the market as a result of the high interest in IoT, characterized by very different characteristics in terms of utilization models, features and availability. This paper provides a review of existing platforms, both adopting [...] Read more.
Tens of different IoT platforms are currently available on the market as a result of the high interest in IoT, characterized by very different characteristics in terms of utilization models, features and availability. This paper provides a review of existing platforms, both adopting a closed source and an open source access model, focusing on five evaluation criteria: communication protocols, data visualization, data processing, integration with external services and security. Afterward, the paper focuses on ten open source platforms, that are deemed more suitable for research and development activities in academia, and provides an evaluation of such platforms according to the five criteria previously defined, combined with two criteria specific to open source platforms: installation procedure and documentation. The evaluation indicates that the FIWARE platform is the best suited platform when taking into account the combination of the seven criteria; other platforms might, however, be preferred, depending on the context, thanks to specific features such as native support for a programming language, or ease and flexibility in the installation procedure. Full article
(This article belongs to the Special Issue Internet of Things (IoT) in Smart Cities)
17 pages, 1234 KiB  
Review
A Review of Treatment Techniques for Short-Chain Perfluoroalkyl Substances
by Yang Liu, Tingyu Li, Jia Bao, Xiaomin Hu, Xin Zhao, Lixin Shao, Chenglong Li and Mengyuan Lu
Appl. Sci. 2022, 12(4), 1941; https://doi.org/10.3390/app12041941 - 12 Feb 2022
Cited by 12 | Viewed by 4245
Abstract
In recent years, an increasing amount of short-chain perfluoroalkyl substance (PFAS) alternatives has been used in industrial and commercial products. However, short-chain PFASs remain persistent, potentially toxic, and extremely mobile, posing potential threats to human health because of their widespread pollution and accumulation [...] Read more.
In recent years, an increasing amount of short-chain perfluoroalkyl substance (PFAS) alternatives has been used in industrial and commercial products. However, short-chain PFASs remain persistent, potentially toxic, and extremely mobile, posing potential threats to human health because of their widespread pollution and accumulation in the water cycle. This study systematically summarized the removal effect, operation conditions, treating time, and removal mechanism of various low carbon treatment techniques for short-chain PFASs, involving adsorption, advanced oxidation, and other practices. By the comparison of applicability, pros, and cons, as well as bottlenecks and development trends, the most widely used and effective method was adsorption, which could eliminate short-chain PFASs with a broad range of concentrations and meet the low-carbon policy, although the adsorbent regeneration was undesirable. In addition, advanced oxidation techniques could degrade short-chain PFASs with low energy consumption but unsatisfied mineralization rates. Therefore, combined with the actual situation, it is urgent to enhance and upgrade the water treatment techniques to improve the treatment efficiency of short-chain PFASs, for providing a scientific basis for the effective treatment of PFASs pollution in water bodies globally. Full article
(This article belongs to the Special Issue Low Carbon Water Treatment and Energy Recovery)
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9 pages, 965 KiB  
Article
High-Efficiency Quantum Dot Lasers as Comb Sources for DWDM Applications
by Mario Dumont, Songtao Liu, M. J. Kennedy and John Bowers
Appl. Sci. 2022, 12(4), 1836; https://doi.org/10.3390/app12041836 - 10 Feb 2022
Cited by 12 | Viewed by 2391
Abstract
The trend of data center transceivers is to increase bandwidth while simultaneously decreasing their size, power consumption, and cost. While data center links have previously relied on vertical-cavity surface-emitting lasers (VCSELs) or in-plane lasers using coarse wavelength division multiplexing (WDM) to encode data, [...] Read more.
The trend of data center transceivers is to increase bandwidth while simultaneously decreasing their size, power consumption, and cost. While data center links have previously relied on vertical-cavity surface-emitting lasers (VCSELs) or in-plane lasers using coarse wavelength division multiplexing (WDM) to encode data, recently, dense WDM (DWDM) has moved to the forefront for next-generation links. Several approaches exist as light sources for DWDM links; DFB arrays, nonlinear microcombs, and semiconductor mode-locked lasers (MLLs). This paper focuses on quantum dot MLLs (QDMLLs), which currently offer the best efficiency, simplicity, and size. The efficiency of optical combs generated by QDMLLs is analyzed in depth in this study. Full article
(This article belongs to the Special Issue Quantum Dot Lasers and Laser Dynamics)
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14 pages, 5182 KiB  
Article
Effects of Adding Alkali Metals and Organic Cations to Cu-Based Perovskite Solar Cells
by Riku Okumura, Takeo Oku, Atsushi Suzuki, Masanobu Okita, Sakiko Fukunishi, Tomoharu Tachikawa and Tomoya Hasegawa
Appl. Sci. 2022, 12(3), 1710; https://doi.org/10.3390/app12031710 - 07 Feb 2022
Cited by 25 | Viewed by 2679
Abstract
First-principles electronic band calculations were used to investigate the effects of alkali metals and organic cations added to Cu-based perovskite solar cells. The copper d-orbital band was slightly above the valence-band maximum and functioned as an acceptor level for carrier generation. Excitation from [...] Read more.
First-principles electronic band calculations were used to investigate the effects of alkali metals and organic cations added to Cu-based perovskite solar cells. The copper d-orbital band was slightly above the valence-band maximum and functioned as an acceptor level for carrier generation. Excitation from iodine p-orbitals and copper d-orbitals to alkali metal s-orbitals could suppress carrier recombination and promote carrier transport. Experimental solar conversion efficiencies increased after adding both Cu and Na, in agreement with the calculations. Total-energy calculations indicated that the perovskite crystal stability increased with the addition of ethyl ammonium, although the total energy decreased with the addition of Cu and Na. Full article
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23 pages, 4808 KiB  
Article
Dynamic Characteristics of Unsteady Aerodynamic Pressure on an Enclosed Housing for Sound Emission Alleviation Caused by a Passing High-Speed Train
by Haiquan Jing, Xiaoyu Ji, Xuhui He, Shifeng Zhang, Jichao Zhou and Haiyu Zhang
Appl. Sci. 2022, 12(3), 1545; https://doi.org/10.3390/app12031545 - 31 Jan 2022
Cited by 5 | Viewed by 1920
Abstract
Train speed is increasing due to the development of high-speed railway technology. However, high-speed trains generate more noise and discomfort for residents, enclosed housing for sound emission alleviation is needed to further reduce noise. Because these enclosed housings for sound emission alleviation restrain [...] Read more.
Train speed is increasing due to the development of high-speed railway technology. However, high-speed trains generate more noise and discomfort for residents, enclosed housing for sound emission alleviation is needed to further reduce noise. Because these enclosed housings for sound emission alleviation restrain the air flow, strong and complicated aerodynamic pressures are generated inside the housing for sound emission alleviation when a train passes through at a high speed. This train-induced aerodynamic pressure, particularly its dynamic characteristics, is a key parameter in structural design. In the present study, the train-induced unsteady aerodynamic pressure in an enclosed housing for sound emission alleviation is simulated using the dynamic mesh method, and the dynamic characteristics of the aerodynamic pressure are investigated. The simulation results show that when the train is running in the enclosed housing for sound emission alleviation, the unsteady aerodynamic pressure is complicated and aperiodic, and after the train leaves the housing for sound emission alleviation, the aerodynamic pressure reverts to periodic decay curves. Two new terms, the duration of the extreme aerodynamic pressure and the pressure change rate, are proposed to evaluate the dynamic characteristics when the train passes through the barrier. The dominant frequency and decay rate are adopted to express the dynamic characteristics after the train exits. When the train runs in the enclosed housing for sound emission alleviation, the longest durations of the positive and negative extreme aerodynamic pressures are in the middle section, and the maximum change rate of aerodynamic pressure occurs at the entrance area. After the train exits the housing for sound emission alleviation, the pressure amplitude at the central region is always higher than those close to the entrance/exit. The dominant frequency of the aerodynamic pressure is identified and explained using wave propagation theory, the decay rate of the aerodynamic pressure at all sections is close. Full article
(This article belongs to the Special Issue New Advances in Fluid Structure Interaction)
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30 pages, 4566 KiB  
Article
Sustainability in the Circular Economy: Insights and Dynamics of Designing Circular Business Models
by Usama Awan and Robert Sroufe
Appl. Sci. 2022, 12(3), 1521; https://doi.org/10.3390/app12031521 - 30 Jan 2022
Cited by 123 | Viewed by 16991
Abstract
The integration of sustainability in the circular economy is an emerging paradigm that can offer a long term vision to achieve environmental and social sustainability targets in line with the United Nation’s Sustainable Development Goals. Developing scalable and sustainable impacts in circular economy [...] Read more.
The integration of sustainability in the circular economy is an emerging paradigm that can offer a long term vision to achieve environmental and social sustainability targets in line with the United Nation’s Sustainable Development Goals. Developing scalable and sustainable impacts in circular economy business models (CEBMs) has many challenges. While many advanced technology manufacturing firms start as small enterprises, remarkably little is known about how material reuse firms in sociotechnical systems transition towards circular business models. Research into CEBMs integrating sustainability and environmental conservation is still in its early stages. There has been increased interest in sustainability and circular economy research, but current research is fragmented. The innovation surrounding CEBMs eludes some firms with relatively limited evidence of the transitional perspective necessary to integrate aspects of sustainability. This lack of evidence is especially applicable to the context of circular economy practices in small and medium enterprises in the United States regarding capabilities, operations obstacles, and elements of success in designing circular business models. Based on a qualitative, interview-based inductive study of a material reuse firm, our research develops a conceptual model of the critical success factors and obstacles that are part of implementing circular economy practices. Firms must first manage strategic enablers and monitor tactical enablers to achieve sustainability goals. In this study, we identify the underlying enablers of how these capabilities affect the transition to a CEBM that integrates sustainability. The framework emerging from our findings highlights the interplay of CEBM, innovation success factors, and obstacles at a micro-level. The investigation of a material reuse firm serves as the foundation for developing a framework for how managers can alter a company and revise the business model to transition towards a more innovative circular economy. Full article
(This article belongs to the Special Issue Manufacturing Sustainability in a Circular Economy)
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7 pages, 2403 KiB  
Article
In-Target Proton–Boron Nuclear Fusion Using a PW-Class Laser
by Daniele Margarone, Julien Bonvalet, Lorenzo Giuffrida, Alessio Morace, Vasiliki Kantarelou, Marco Tosca, Didier Raffestin, Philippe Nicolai, Antonino Picciotto, Yuki Abe, Yasunobu Arikawa, Shinsuke Fujioka, Yuji Fukuda, Yasuhiro Kuramitsu, Hideaki Habara and Dimitri Batani
Appl. Sci. 2022, 12(3), 1444; https://doi.org/10.3390/app12031444 - 28 Jan 2022
Cited by 31 | Viewed by 22703
Abstract
Nuclear reactions between protons and boron-11 nuclei (p–B fusion) that were used to yield energetic α-particles were initiated in a plasma that was generated by the interaction between a PW-class laser operating at relativistic intensities (~3 × 1019 W/cm2) and [...] Read more.
Nuclear reactions between protons and boron-11 nuclei (p–B fusion) that were used to yield energetic α-particles were initiated in a plasma that was generated by the interaction between a PW-class laser operating at relativistic intensities (~3 × 1019 W/cm2) and a 0.2-mm thick boron nitride (BN) target. A high p–B fusion reaction rate and hence, a large α-particle flux was generated and measured, thanks to a proton stream accelerated at the target’s front surface. This was the first proof of principle experiment to demonstrate the efficient generation of α-particles (~1010/sr) through p–B fusion reactions using a PW-class laser in the “in-target” geometry. Full article
(This article belongs to the Special Issue Laser-Driven Accelerators, Radiations, and Their Applications)
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16 pages, 6030 KiB  
Review
Time-Lapse Electrical Resistivity Tomography (TL-ERT) for Landslide Monitoring: Recent Advances and Future Directions
by Vincenzo Lapenna and Angela Perrone
Appl. Sci. 2022, 12(3), 1425; https://doi.org/10.3390/app12031425 - 28 Jan 2022
Cited by 21 | Viewed by 4950
Abstract
To date, there is a growing interest for challenging applications of time-lapse electrical resistivity tomography (TL-ERT) in Earth sciences. Tomographic algorithms for resistivity data inversion and innovative technologies for sensor networks have rapidly transformed the TL-ERT method in a powerful tool for the [...] Read more.
To date, there is a growing interest for challenging applications of time-lapse electrical resistivity tomography (TL-ERT) in Earth sciences. Tomographic algorithms for resistivity data inversion and innovative technologies for sensor networks have rapidly transformed the TL-ERT method in a powerful tool for the geophysical time-lapse imaging. In this paper, we focus our attention on the application of this method in landslide monitoring. Firstly, an overview of recent methodological advances in TL-ERT data processing and inversion is presented. In a second step, a critical analysis of the main results obtained in different field experiments and lab-scale simulations are discussed. The TL-ERT appears to be a robust and cost-effective method for mapping the water-saturated zones, and for the identification of the groundwater preferential pathways in landslide bodies. Furthermore, it can make a valuable contribution to following time-dependent changes in top-soil moisture, and the spatio-temporal dynamics of wetting fronts during extreme rainfall events. The critical review emphasizes the limits and the advantages of this geophysical method and discloses a way to identify future research activities to improve the use of the TL-ERT method in landslide monitoring. Full article
(This article belongs to the Special Issue Advances in Applied Geophysics)
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14 pages, 4497 KiB  
Article
Implementing a GIS-Based Digital Atlas of Agricultural Plastics to Reduce Their Environmental Footprint; Part I: A Deductive Approach
by Giuseppe Cillis, Dina Statuto, Evelia Schettini, Giuliano Vox and Pietro Picuno
Appl. Sci. 2022, 12(3), 1330; https://doi.org/10.3390/app12031330 - 26 Jan 2022
Cited by 6 | Viewed by 3164
Abstract
The agricultural sector has benefitted over the last century from several factors that have led to an exponential increase in its productive efficiency. The increasing use of new materials, such as plastics, has been one of the most important factors, as they have [...] Read more.
The agricultural sector has benefitted over the last century from several factors that have led to an exponential increase in its productive efficiency. The increasing use of new materials, such as plastics, has been one of the most important factors, as they have allowed for increased production in a simpler and more economical way. Various polymer types are used in different phases of the agricultural production cycle, but when their use is incorrectly managed, it can lead to different environmental impacts. In this study, an applied and simplified methodology to manage agricultural plastics monitoring and planning is proposed. The techniques used are based on quantification through the use of different datasets (orthophotos and satellite images) of the areas covered by plastics used for crop protection. The study area chosen is a part of the Ionian Coast of Southern Italy, which includes the most important municipalities of the Basilicata Region for fruit and vegetable production. The use of geographical techniques and observation methodologies, developed in an open-source GIS environment, enabled accurate location of about 2000 hectares of agricultural land covered by plastics, as well as identification of the areas most susceptible to the accumulation of plastic waste. The techniques and the model implemented, due to its simplicity of use and reliability, can be applied by different local authorities in order to realize an Atlas of agricultural plastics, which would be applied for continuous monitoring, thereby enabling the upscaling of future social and ecological impact assessments, identification of new policy impacts, market searches, etc. Full article
(This article belongs to the Special Issue Reducing the Plastic Footprint of Agriculture)
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16 pages, 1687 KiB  
Review
The Role of Plant Growth-Promoting Rhizobacteria (PGPR) in Mitigating Plant’s Environmental Stresses
by Marco Vocciante, Martina Grifoni, Danilo Fusini, Gianniantonio Petruzzelli and Elisabetta Franchi
Appl. Sci. 2022, 12(3), 1231; https://doi.org/10.3390/app12031231 - 25 Jan 2022
Cited by 88 | Viewed by 14709
Abstract
Phytoremediation is a cost-effective and sustainable technology used to clean up pollutants from soils and waters through the use of plant species. Indeed, plants are naturally capable of absorbing metals and degrading organic molecules. However, in several cases, the presence of contaminants causes [...] Read more.
Phytoremediation is a cost-effective and sustainable technology used to clean up pollutants from soils and waters through the use of plant species. Indeed, plants are naturally capable of absorbing metals and degrading organic molecules. However, in several cases, the presence of contaminants causes plant suffering and limited growth. In such situations, thanks to the production of specific root exudates, plants can engage the most suitable bacteria able to support their growth according to the particular environmental stress. These plant growth-promoting rhizobacteria (PGPR) may facilitate plant growth and development with several beneficial effects, even more evident when plants are grown in critical environmental conditions, such as the presence of toxic contaminants. For instance, PGPR may alleviate metal phytotoxicity by altering metal bioavailability in soil and increasing metal translocation within the plant. Since many of the PGPR are also hydrocarbon oxidizers, they are also able to support and enhance plant biodegradation activity. Besides, PGPR in agriculture can be an excellent support to counter the devastating effects of abiotic stress, such as excessive salinity and drought, replacing expensive inorganic fertilizers that hurt the environment. A better and in-depth understanding of the function and interactions of plants and associated microorganisms directly in the matrix of interest, especially in the presence of persistent contamination, could provide new opportunities for phytoremediation. Full article
(This article belongs to the Special Issue Green Technologies for a Cleaner Environment)
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17 pages, 4000 KiB  
Article
Quantifying the Occurrence of Multi-Hazards Due to Climate Change
by Diamando Vlachogiannis, Athanasios Sfetsos, Iason Markantonis, Nadia Politi, Stelios Karozis and Nikolaos Gounaris
Appl. Sci. 2022, 12(3), 1218; https://doi.org/10.3390/app12031218 - 24 Jan 2022
Cited by 9 | Viewed by 2617
Abstract
This paper introduces a climatic multi-hazard risk assessment for Greece, as the first-ever attempt to enhance scientific knowledge for the identification and definition of hazards, a critical element of risk-informed decision making. Building on an extensively validated climate database with a very high [...] Read more.
This paper introduces a climatic multi-hazard risk assessment for Greece, as the first-ever attempt to enhance scientific knowledge for the identification and definition of hazards, a critical element of risk-informed decision making. Building on an extensively validated climate database with a very high spatial resolution (5 × 5 km2), a detailed assessment of key climatic hazards is performed that allows for: (a) the analysis of hazard dynamics and their evolution due to climate change and (b) direct comparisons and spatial prioritization across Greece. The high geographical complexity of Greece requires that a large number of diverse hazards (heatwaves—TX, cold spells—TN, torrential rainfall—RR, snowstorms, and windstorms), need to be considered in order to correctly capture the country’s susceptibility to climate extremes. The current key findings include the dominance of cold-temperature extremes in mountainous regions and warm extremes over the coasts and plains. Extreme rainfall has been observed in the eastern mainland coasts and windstorms over Crete and the Aegean and Ionian Seas. Projections of the near future reveal more warm extremes in northern areas becoming more dominant all over the country by the end of the century. Full article
(This article belongs to the Special Issue Natural-Hazards Risk Assessment for Disaster Mitigation)
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22 pages, 930 KiB  
Perspective
Making Sense of Light: The Use of Optical Spectroscopy Techniques in Plant Sciences and Agriculture
by Ana M. Cavaco, Andrei B. Utkin, Jorge Marques da Silva and Rui Guerra
Appl. Sci. 2022, 12(3), 997; https://doi.org/10.3390/app12030997 - 19 Jan 2022
Cited by 15 | Viewed by 3697
Abstract
As a result of the development of non-invasive optical spectroscopy, the number of prospective technologies of plant monitoring is growing. Being implemented in devices with different functions and hardware, these technologies are increasingly using the most advanced data processing algorithms, including machine learning [...] Read more.
As a result of the development of non-invasive optical spectroscopy, the number of prospective technologies of plant monitoring is growing. Being implemented in devices with different functions and hardware, these technologies are increasingly using the most advanced data processing algorithms, including machine learning and more available computing power each time. Optical spectroscopy is widely used to evaluate plant tissues, diagnose crops, and study the response of plants to biotic and abiotic stress. Spectral methods can also assist in remote and non-invasive assessment of the physiology of photosynthetic biofilms and the impact of plant species on biodiversity and ecosystem stability. The emergence of high-throughput technologies for plant phenotyping and the accompanying need for methods for rapid and non-contact assessment of plant productivity has generated renewed interest in the application of optical spectroscopy in fundamental plant sciences and agriculture. In this perspective paper, starting with a brief overview of the scientific and technological backgrounds of optical spectroscopy and current mainstream techniques and applications, we foresee the future development of this family of optical spectroscopic methodologies. Full article
(This article belongs to the Special Issue Applications of Optical Spectroscopy in Plant Sciences)
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17 pages, 5434 KiB  
Review
Recent Progress of the PAL-XFEL
by Intae Eom, Sae Hwan Chun, Jae Hyuk Lee, Daewoong Nam, Rory Ma, Jaehyun Park, Sehan Park, Sang Han Park, Haeryong Yang, Inhyuk Nam, Myung Hoon Cho, Chi Hyun Shim, Gyujin Kim, Chang-Ki Min, Hoon Heo, Heung-Sik Kang and Changbum Kim
Appl. Sci. 2022, 12(3), 1010; https://doi.org/10.3390/app12031010 - 19 Jan 2022
Cited by 10 | Viewed by 2926
Abstract
The X-ray free-electron laser of the Pohang Accelerator Laboratory (PAL-XFEL) was opened to users in 2017. Since then, significant progress has been made in PAL-XFEL operation and beamline experiments. This includes increasing the FEL pulse energy, increasing the FEL photon energy, generating self-seeding [...] Read more.
The X-ray free-electron laser of the Pohang Accelerator Laboratory (PAL-XFEL) was opened to users in 2017. Since then, significant progress has been made in PAL-XFEL operation and beamline experiments. This includes increasing the FEL pulse energy, increasing the FEL photon energy, generating self-seeding FEL, and trials of two-color operation. In the beamline, new instruments or endstations have been added or are being prepared. Overall, beamline operation has been stabilized since its initiation, which has enabled excellent scientific results through efficient user experiments. In this paper, we describe details of the recent progress of the PAL-XFEL. Full article
(This article belongs to the Special Issue Latest Trends in Free Electron Lasers)
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20 pages, 653 KiB  
Article
Efficient Decomposition of Unitary Matrices in Quantum Circuit Compilers
by Anna M. Krol, Aritra Sarkar, Imran Ashraf, Zaid Al-Ars and Koen Bertels
Appl. Sci. 2022, 12(2), 759; https://doi.org/10.3390/app12020759 - 12 Jan 2022
Cited by 15 | Viewed by 3758
Abstract
Unitary decomposition is a widely used method to map quantum algorithms to an arbitrary set of quantum gates. Efficient implementation of this decomposition allows for the translation of bigger unitary gates into elementary quantum operations, which is key to executing these algorithms on [...] Read more.
Unitary decomposition is a widely used method to map quantum algorithms to an arbitrary set of quantum gates. Efficient implementation of this decomposition allows for the translation of bigger unitary gates into elementary quantum operations, which is key to executing these algorithms on existing quantum computers. The decomposition can be used as an aggressive optimization method for the whole circuit, as well as to test part of an algorithm on a quantum accelerator. For the selection and implementation of the decomposition algorithm, perfect qubits are assumed. We base our decomposition technique on Quantum Shannon Decomposition, which generates O(344n) controlled-not gates for an n-qubit input gate. In addition, we implement optimizations to take advantage of the potential underlying structure in the input or intermediate matrices, as well as to minimize the execution time of the decomposition. Comparing our implementation to Qubiter and the UniversalQCompiler (UQC), we show that our implementation generates circuits that are much shorter than those of Qubiter and not much longer than the UQC. At the same time, it is also up to 10 times as fast as Qubiter and about 500 times as fast as the UQC. Full article
(This article belongs to the Special Issue Quantum Software Engineering and Programming)
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17 pages, 9051 KiB  
Article
Ultrasonic Inspection for Welds with Irregular Curvature Geometry Using Flexible Phased Array Probes and Semi-Auto Scanners: A Feasibility Study
by Seong Jin Lim, Young Lae Kim, Sungjong Cho and Ik Keun Park
Appl. Sci. 2022, 12(2), 748; https://doi.org/10.3390/app12020748 - 12 Jan 2022
Cited by 9 | Viewed by 3860
Abstract
Pipes of various shapes constitute pipelines utilized in industrial sites. These pipes are coupled through welding, wherein complex curvatures such as a flange, an elbow, a reducer, and a branch pipe are often found. Using phased array ultrasonic testing (PAUT) to inspect weld [...] Read more.
Pipes of various shapes constitute pipelines utilized in industrial sites. These pipes are coupled through welding, wherein complex curvatures such as a flange, an elbow, a reducer, and a branch pipe are often found. Using phased array ultrasonic testing (PAUT) to inspect weld zones with complex curvatures is faced with different challenges due to parts that are difficult to contact with probes, small-diameter pipes, spatial limitations due to adjacent pipes, nozzles, and sloped shapes. In this study, we developed a flexible PAUT probe (FPAPr) and a semi-automatic scanner that was improved to enable stable FPAPr scanning for securing its inspection data consistency and reproducibility. A mock-up test specimen was created for a flange, an elbow, a reducer, and a branch pipe. Artificial flaws were inserted into the specimen through notch and hole processing, and simulations and verification experiments were performed to verify the performance and field applicability of the FPAPr and semi-automatic scanner. Full article
(This article belongs to the Special Issue Applications on Ultrasonic Wave ‖)
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16 pages, 9335 KiB  
Article
Cold Atmospheric Pressure Plasma Jet Operated in Ar and He: From Basic Plasma Properties to Vacuum Ultraviolet, Electric Field and Safety Thresholds Measurements in Plasma Medicine
by Andrei Vasile Nastuta and Torsten Gerling
Appl. Sci. 2022, 12(2), 644; https://doi.org/10.3390/app12020644 - 10 Jan 2022
Cited by 19 | Viewed by 3846
Abstract
Application desired functionality as well as operation expenses of cold atmospheric pressure plasma (CAP) devices scale with properties like gas selection. The present contribution provides a comparative investigation for a CAP system operated in argon or helium at different operation voltages and distance [...] Read more.
Application desired functionality as well as operation expenses of cold atmospheric pressure plasma (CAP) devices scale with properties like gas selection. The present contribution provides a comparative investigation for a CAP system operated in argon or helium at different operation voltages and distance to the surface. Comparison of power dissipation, electrical field strength and optical emission spectroscopy from vacuum ultraviolet over visible up to near infrared ((V)UV-VIS-NIR) spectral range is carried out. This study is extended to safety relevant investigation of patient leakage current, induced surface temperature and species density for ozone (O3) and nitrogen oxides (NOx). It is found that in identical operation conditions (applied voltage, distance to surface and gas flow rate) the dissipated plasma power is about equal (up to 10 W), but the electrical field strength differs, having peak values of 320 kV/m for Ar and up to 300 kV/m for He. However, only for Ar CAP could we measure O3 up to 2 ppm and NOx up to 7 ppm. The surface temperature and leakage values of both systems showed different slopes, with the biggest surprise being a constant leakage current over distance for argon. These findings may open a new direction in the plasma source development for Plasma Medicine. Full article
(This article belongs to the Special Issue Frontiers in Atmospheric Pressure Plasma Technology)
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22 pages, 3094 KiB  
Article
Spatial Connections between Microplastics and Heavy Metal Pollution within Floodplain Soils
by Collin J. Weber, Jens Hahn and Christian Opp
Appl. Sci. 2022, 12(2), 595; https://doi.org/10.3390/app12020595 - 08 Jan 2022
Cited by 14 | Viewed by 2461
Abstract
Soils contain an increasing number of different pollutants, which are often released into the environment by human activity. Among the “new” potential pollutants are plastics and microplastics. “Recognized” pollutants such as heavy metals, of geogenic and anthropogenic origin, now meet purely anthropogenic contaminants [...] Read more.
Soils contain an increasing number of different pollutants, which are often released into the environment by human activity. Among the “new” potential pollutants are plastics and microplastics. “Recognized” pollutants such as heavy metals, of geogenic and anthropogenic origin, now meet purely anthropogenic contaminants such as plastic particles. Those can meet especially in floodplain landscapes and floodplain soils, because of their function as a temporary sink for sediments, nutrients, and pollutants. Based on a geospatial sampling approach, we analyzed the soil properties and heavy metal contents (ICP-MS) in soil material and macroplastic particles, and calculated total plastic concentrations (Ptot) from preliminary studies. Those data were used to investigate spatial connections between both groups of pollutants. Our results from the example of the Lahn river catchment show a low-to-moderate contamination of the floodplain soils with heavy metals and a wide distribution of plastic contents up to a depth of two meters. Furthermore, we were able to document heavy metal contents in macroplastic particles. Spatial and statistical correlations between both pollutants were found. Those correlations are mainly expressed by a comparable variability in concentrations across the catchment and in a common accumulation in topsoil and upper soil or sediment layers (0–50 cm). The results indicate comparable deposition conditions of both pollutants in the floodplain system. Full article
(This article belongs to the Special Issue Floodplains and Reservoirs as Sinks and Sources for Pollutants)
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17 pages, 3830 KiB  
Article
A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas
by Alessandro Rocchi, Andrea Chiozzi, Marco Nale, Zeljana Nikolic, Fabrizio Riguzzi, Luana Mantovan, Alessandro Gilli and Elena Benvenuti
Appl. Sci. 2022, 12(2), 583; https://doi.org/10.3390/app12020583 - 07 Jan 2022
Cited by 8 | Viewed by 3182
Abstract
Communities are confronted with the rapidly growing impact of disasters, due to many factors that cause an increase in the vulnerability of society combined with an increase in hazardous events such as earthquakes and floods. The possible impacts of such events are large, [...] Read more.
Communities are confronted with the rapidly growing impact of disasters, due to many factors that cause an increase in the vulnerability of society combined with an increase in hazardous events such as earthquakes and floods. The possible impacts of such events are large, also in developed countries, and governments and stakeholders must adopt risk reduction strategies at different levels of management stages of the communities. This study is aimed at proposing a sound qualitative multi-hazard risk analysis methodology for the assessment of combined seismic and hydraulic risk at the regional scale, which can assist governments and stakeholders in decision making and prioritization of interventions. The method is based on the use of machine learning techniques to aggregate large datasets made of many variables different in nature each of which carries information related to specific risk components and clusterize observations. The framework is applied to the case study of the Emilia Romagna region, for which the different municipalities are grouped into four homogeneous clusters ranked in terms of relative levels of combined risk. The proposed approach proves to be robust and delivers a very useful tool for hazard management and disaster mitigation, particularly for multi-hazard modeling at the regional scale. Full article
(This article belongs to the Special Issue Natural-Hazards Risk Assessment for Disaster Mitigation)
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17 pages, 5622 KiB  
Article
Effect of Rice Straw on Tensile Properties of Tailings Cemented Paste Backfill
by Zeyu Li, Xiuzhi Shi and Xin Chen
Appl. Sci. 2022, 12(1), 526; https://doi.org/10.3390/app12010526 - 05 Jan 2022
Cited by 6 | Viewed by 2665
Abstract
It is important and difficult to improve the tensile strength of backfill material to ensure the stability of goafs. In this study, rice straw (RS) in fiber form is used to improve the tensile properties of cemented paste backfill (CPB). An orthogonal experiment [...] Read more.
It is important and difficult to improve the tensile strength of backfill material to ensure the stability of goafs. In this study, rice straw (RS) in fiber form is used to improve the tensile properties of cemented paste backfill (CPB). An orthogonal experiment was designed, Brazilian indirect tensile strength tests were conducted to test the tensile performance of RS fiber-reinforced cemented paste backfill (RSCPB) under different fiber content (1, 2, 3 kg/m3) and fiber length (0.8~1, 1~3, 3~5 cm), and the microstructure of RSCPB was analyzed with scanning electron microscopy (SEM). The results showed that, compared with the conventional cemented paste backfill (CCPB), the increase in tensile strength of RSCPB ranged from 115.38% to 300.00% at 3 days curing age, 40.91% to 346.15% at 7 days, and −38.10% to 28.00% at 28 days, and the strain was slightly reduced during the curing period. The tensile strength, strain, and percentage increase of the RSCPB compared to the CCBP did not show a monotonic pattern of variation with the RS fiber content and length during the curing period. The RSCPB samples fractured under peak stress, showing obvious brittle failure. In addition, sulfate generated from S2− in the tailings inhibits the hydration reaction, and generates swelling products that form weak structural surfaces, which, in turn, lead to a 28-day tensile strength and strain of RSCPB lower than those at 7 days. Full article
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