bluuebunny/crossref_metadata_2025 huggingface dataset:
Exposure of the Basophilic Cell Line KU812 to Liposomes Reveals Activation Profiles Associated with Potential Anaphylactic Responses Linked to Physico-Chemical Characteristics
Authors: Plant-Hately Alexander J. , Eryilmaz Burcu , David Christopher A. W. , Brain Danielle E. , Heaton Bethany J. , Perrie Yvonne , Liptrott Neill J.
Published: November 2022

Lipidic nanoparticles (LNP), particularly liposomes, have been proven to be a successful and versatile platform for intracellular drug delivery for decades. Whilst primarily developed for small molecule delivery, liposomes have recently undergone a renaissance due to their success in vaccination strategies, delivering nucleic acids, in the COVID-19 pandemic. As such, liposomes are increasingly being investigated for the delivery of nucleic acids, beyond mRNA, as non-viral gene delivery vectors. Although not generally considered toxic, liposomes are increasingly shown to not be immunologically inert, which may have advantages in vaccine applications but may limit their use in other conditions where immunological responses may lead to adverse events, particularly those associated with complement activation. We sought to assess a small panel of liposomes varying in a number of physico-chemical characteristics associated with complement activation and inflammatory responses, and examine how basophil-like cells may respond to them. Basophils, as well as other cell types, are involved in the anaphylactic responses to liposomes but are difficult to isolate in sufficient numbers to conduct large scale analysis. Here, we report the use of the human KU812 cell line as a surrogate for primary basophils. Multiple phenotypic markers of activation were assessed, as well as the release of histamine and inflammasome activity within the cells. We found that larger liposomes were more likely to result in KU812 activation, and that non-PEGylated liposomes were potent stimulators of inflammasome activity (four-fold greater IL-1β secretion than untreated controls), and a lower ratio of cholesterol to lipid was also associated with greater IL-1β secretion ([Cholesterol:DSPC ratio] 1:10; 0.35 pg/mL IL-1β vs. 5:10; 0.1 pg/mL). Additionally, PEGylation appeared to be associated with direct KU812 activation. These results suggest possible mechanisms related to the consequences of complement activation that may be underpinned by basophilic cells, in addition to other immune cell types. Investigation of the mechanisms behind these responses, and their impact on use in vivo, are now warranted.
Non-Viral Gene Therapy in Trabecular Meshwork Cells to Prevent Fibrosis in Minimally Invasive Glaucoma Surgery
Authors: Luo Jinyuan , Tan Greymi , Thong Kai Xin , Kafetzis Konstantinos N. , Vallabh Neeru , Sheridan Carl M. , Sato Yusuke , Harashima Hideyoshi , Tagalakis Aristides D. , Yu-Wai-Man Cynthia
Published: November 2022

The primary cause of failure for minimally invasive glaucoma surgery (MIGS) is fibrosis in the trabecular meshwork (TM) that regulates the outflow of aqueous humour, and no anti-fibrotic drug is available for intraocular use in MIGS. The myocardin-related transcription factor/serum response factor (MRTF/SRF) pathway is a promising anti-fibrotic target. This study aims to utilise a novel lipid nanoparticle (LNP) to deliver MRTF-B siRNA into human TM cells and to compare its effects with those observed in human conjunctival fibroblasts (FF). Two LNP formulations were prepared with and without the targeting peptide cΥ, and with an siRNA concentration of 50 nM. We examined the biophysical properties and encapsulation efficiencies of the LNPs, and evaluated the effects of MRTF-B silencing on cell viability, key fibrotic genes expression and cell contractility. Both LNP formulations efficiently silenced MRTF-B gene and were non-cytotoxic in TM and FF cells. The presence of cΥ made the LNPs smaller and more cationic, but had no significant effect on encapsulation efficiency. Both TM and FF cells also showed significantly reduced contractibility after transfection with MRTF-B siRNA LNPs. In TM cells, LNPs with cΥ achieved a greater decrease in contractility compared to LNPs without cΥ. In conclusion, we demonstrate that the novel CL4H6-LNPs are able to safely and effectively deliver MRTF-B siRNA into human TM cells. LNPs can serve as a promising non-viral gene therapy to prevent fibrosis in MIGS.
Terahertz Generation by Optical Rectification of 780 nm Laser Pulses in Pure and Sc-Doped ZnGeP2 Crystals
Authors: Voevodin Vladimir , Bereznaya Svetlana , Sarkisov Yury S. , Yudin Nikolay N. , Sarkisov Sergey Yu.
Published: November 2022

Terahertz wave generation through the optical rectification of 780 nm femtosecond laser pulses in ZnGeP2 crystals has been studied. All of the possible interactions of types I and II were analyzed by modeling and experimentally. We demonstrate the possibility of broadband “low-frequency” terahertz generation by an ee–e interaction (with two pumping waves and a generated terahertz wave; all of these had extraordinary polarization in the crystal) and “high-frequency” terahertz generation by an oe–e interaction. The arising possibility of achieving the narrowing of the terahertz generation bandwidth at the oe–e interaction using thicker ZnGeP2 crystals is experimentally confirmed. It has been found that the thermal annealing of as-grown ZnGeP2 crystals and their doping with a 0.01 mass % of Sc reduces the absorption in the “anomalous absorption” region (λ = 0.62–3 μm). The terahertz generation by the oo–e interaction in (110) ZnGeP2:Sc and the as-grown ZnGeP2 crystals of equal thicknesses was compared. It has been found that ZnGeP2:Sc is more efficient for 780 nm femtosecond laser pulses optical rectification.
Characterization and In Vivo Anti-Inflammatory Efficacy of Copal (Dacryodes peruviana (Loes.) H.J. Lam) Essential Oil
Authors: Espinoza Lupe Carolina , Valarezo Eduardo , Fábrega María José , Rodríguez-Lagunas María José , Sosa Lilian , Calpena Ana Cristina , Mallandrich Mireia
Published: November 2022

Essential oils are natural aromatic substances that contain complex mixtures of many volatile compounds frequently used in pharmaceutical and cosmetic industries. Dacryodes peruviana (Loes.) H.J. Lam is a native species from Ecuador whose anti-inflammatory activity has not been previously reported, thus the aim of this study was to evaluate the anti-inflammatory activity of D. peruviana essential oil. To that end, essential oil from D. peruviana fruits was isolated by hydrodistillation and characterized physically and chemically. The tolerance of the essential oil was analyzed by cytotoxicity studies using human keratinocytes. The anti-inflammatory activity was evaluated by an arachidonic acid-induced edema model in mouse ear. The predominant compounds in D. peruviana essential oil were α-phellandrene, limonene, and α-pinene, with the three compounds reaching approximately 83% of the total composition. Tolerance studies showed high biocompatibility of this essential oil with human keratinocytes. In vivo studies demonstrated a moisturizing effect and an alleviation of several events occurred during the inflammatory process after topical treatment with D. peruviana essential oil such as decline in skin edema; reduction in leukocytic infiltrate; and decrease in inflammatory cytokines TNFα, IL-8, IL-17A, and IL-23. Therefore, this essential oil could be an attractive treatment for skin inflammation.
Plant Growth Promoting Rhizobacteria and Silica Nanoparticles Stimulate Sugar Beet Resilience to Irrigation with Saline Water in Salt-Affected Soils
Authors: Alharbi Khadiga , Hafez Emad , Omara Alaa El-Dien , Awadalla Abdelmoniem , Nehela Yasser
Published: November 2022

Combined stressors (high soil salinity and saline water irrigation) severely reduce plant growth and sugar beet yield. Seed inoculation with plant growth-promoting rhizobacteria (PGPR) and/or foliar spraying with silica nanoparticles (Si-NP) is deemed one of the most promising new strategies that have the potential to inhibit abiotic stress. Herein, sugar beet (Beta vulgaris) plants were treated with two PGPR (Pseudomonas koreensis MG209738 and Bacillus coagulans NCAIM B.01123) and/or Si-NP, during two successive seasons 2019/2020 and 2020/2021 to examine the vital role of PGPR, Si-NP, and their combination in improving growth characteristics, and production in sugar beet plants exposed to two watering treatments (fresh water and saline water) in salt-affected soil. The results revealed that combined stressors (high soil salinity and saline water irrigation) increased ion imbalance (K+/Na+ ratio; from 1.54 ± 0.11 to 1.00 ± 0.15) and declined the relative water content (RWC; from 86.76 ± 4.70 to 74.30 ± 3.20%), relative membrane stability index (RMSI), stomatal conductance (gs), and chlorophyll content, which negatively affected on the crop productivity. Nevertheless, the application of combined PGPR and Si-NP decreased oxidative stress indicators (hydrogen peroxide and lipid peroxidation) and sodium ions while increasing activities of superoxide dismutase (SOD; up to 1.9-folds), catalase (CAT; up to 1.4-folds), and peroxidase (POX; up to 2.5-folds) enzymes, and potassium ions resulting in physiological processes, root yield, and sugar yield compared to non-treated controls under combined stressors (high soil salinity and saline water irrigation). It is worth mentioning that the singular application of PGPR improved root length, diameter, and yield greater than Si-NP alone and it was comparable to the combined treatment (PGPR+Si-NP). It was concluded that the combined application of PGPR and Si-NP has valuable impacts on the growth and yield of sugar beet growing under combined stressors of high soil salinity and saline water irrigation.
Bioinformatics in Plant Breeding and Research on Disease Resistance
Authors: Mu Huiying , Wang Baoshan , Yuan Fang
Published: November 2022

In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance.
Hidden Diversity within Tetralophozia filiformis (Marchantiophyta, Anastrophyllaceae) in East Asia
Authors: Bakalin Vadim A. , Vilnet Anna A. , Maltseva Yulia D. , Klimova Ksenia G. , Bakalin Daniil A. , Choi Seung Se
Published: November 2022

Tetralophozia filiformis s.l. is known from a number of localities mostly in amphi-oceanic areas in Northern Hemisphere, including Atlantic Europe, amphi-Pacific Asia, South Siberia, and western North America. The newly obtained collections of this ‘species’ show strong variation in morphology of the taxon across amphi-Pacific Asia although connected by some ‘intergrading’ modifications. This implies the genetic diversity within this unit earlier recognized as a single taxon. Authors used molecular-genetic, morphological, and chorological methods to understand if the geographically correlated morphological variation also correlates with genetic differences and if it is possible to distinguish some additional taxa within the series of specimens originating from the various areas in amphi-Pacific Asia. It was found that Tetralophozia filiformis is a complex of at least three morphologically similar species, including one long forgotten name (Chandonanthus pusillus) that should be reinstated as separate species and one taxon (Tetralophozia sibirica) that should be described as new. Tetralophozia filiformis and Chandonanthus pusillus are lectotypified, and the new combination is provided for the latter. The three accepted taxa distinctly differ one from another in distribution patterns, preferable climate characteristics, and genetic distances, besides minor differentiations in morphology. The main morphological distinguishing features are the leaf cell size, height of undivided part in leaf lamina, and leaf dentation characteristics. Taking into account the robust correlation between the climate-based and molecular-genetic-based clusters, one more (fourth) taxon could be probably segregated from Tetralophozia filiformis.
A New Approach for Controlling Agrobacterium tumefaciens Post Transformation Using Lytic Bacteriophage
Authors: Ramadhan Fiqih , Alfiko Yuzer , Purwantomo Sigit , Mubarok Andhika Faisal , Budinarta Widyah , Suwanto Antonius , Budiarti Sri
Published: November 2022

Overgrowth of Agrobacterium tumefaciens has frequently been found in Agrobacterium-mediated plant transformation. This overgrowth can reduce transformation efficiency and even lead to explant death. Therefore, this research investigates an alternative way to mitigate or eliminate Agrobacterium after transformation using a bacteriophage. To develop this alternative method, we conducted effectiveness studies of two lytic bacteriophages (ΦK2 and ΦK4) and performed an application test to control Agrobacterium growth after transformation. According to plaque morphological characterization and molecular analysis, the two bacteriophages used in this experiment were distinct. Moreover, some stability physicochemical and growth kinetics, such as adsorption time and susceptibility test, also showed that both bacteriophages differed. On the other hand, the optimum temperature and pH of both phages were the same at 28–30 °C and pH 7. Further investigation showed that both ΦK2 and ΦK4 were able to reduce the overgrowth of A. tumefaciens post transformation. Moreover, applying the cocktail (mixture of ΦK2 and ΦK4) with antibiotic application eradicated A. tumefaciens (0% overgrowth percentage). This result indicates that the application of bacteriophage could be used as an alternative way to eradicate the overgrowth of A. tumefaciens subsequent to transformation.
Synergistic Effects of Some Methoxyflavones Extracted from Rhizome of Kaempferia parviflora Combined with Gentamicin against Carbapenem-Resistant Strains of Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii
Authors: Sookkhee Siriwoot , Sakonwasun Choompone , Mungkornasawakul Pitchaya , Khamnoi Phadungkiat , Wikan Nitwara , Nimlamool Wutigri
Published: November 2022

The present study aimed to investigate the antibacterial activity of ethanolic Kaempferia parviflora extracts and the combined effects of the plant’s specific compounds with gentamicin against clinical strains of carbapenem-resistant Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. The minimal inhibitory concentrations (MIC) of gentamicin and Kaempferia parviflora extracts against the tested bacterial strains were determined by using broth microdilution. The combined effects of Kaempferia parviflora extract and gentamicin were investigated by using a checkerboard assay and expressed as a fractional inhibitory concentration index (FICI). Crude ethanolic extract of Kaempferia parviflora showed the lowest median values of MIC towards the tested isolates (n = 10) of these tested bacteria at doses of 64 µg/mL, compared to those of other Kaempferia extracts. Among the isolated compounds, only three compounds, namely 3,5,7-trimethoxyflavone, 3,5,7,3′4′-pentamethoxyflavone, and 5,7,4′-trimethoxyflavone, were identified by NMR structural analysis. According to their FICIs, the synergistic effects of gentamicin combined with 3,5,7,3′4′-pentamethoxyflavone were approximately 90%, 90%, and 80% of tested carbapenem-resistant Klebsiella pneumoniae (CRKP), Pseudomonas aeruginosa (CRPA), and Acinetobacter baumannii (CRAB), respectively. The present study concluded that 3,5,7,3′4′-pentamethoxyflavone extracted from Kaempferia parviflora potentiated the antibacterial action of gentamicin to combat bacterial resistance against the tested bacteria.
Improving the Thermal Stability and Flame Retardancy of Epoxy Resins by Lamellar Cobalt Potassium Pyrophosphate
Authors: Kong Qinghong , Li Lan , Zhang Manman , Chai Huiyu , Li Weixi , Zhu Fang , Zhang Junhao
Published: November 2022

In order to improve the fire retardancy of epoxy resin (EP), lamellar cobalt potassium pyrophosphate (LCPP) nanocrystal whiskers with a length of 100–300 nm were designed and synthesized by a liquid technique. LCPP with high thermal stability was blended into EP to prepare the EP/LCPP composites. The results show that the EP/LCPP composites have higher thermal stability and produce more residues compared to pure EP. The combustion results display that the LOI value of the EP/10wt%LCPP composites was significantly improved to 35.9%, and the EP/6wt%LCPP composite can reach a UL-94 V-1 rating. Additionally, the peak heat release rate and peak smoke production rate of the EP/10wt%LCPP composites dramatically decreased by 43.8% and 48.5%, respectively. The improved flame retardancy and smoke suppression are mainly attributed to the inherent physical barrier of LCPP and the excellent catalytic carbonization ability of LCPP.
Methods of Analyses for Biodegradable Polymers: A Review
Authors: Baidurah Siti
Published: November 2022

Biodegradable polymers are materials that can decompose through the action of various environmental microorganisms, such as bacteria and fungi, to form water and carbon dioxide. The biodegradability characteristics have led to a growing demand for the accurate and precise determination of the degraded polymer composition. With the advancements in analytical product development, various analytical methods are available and touted as practical and preferable methods of bioanalytical techniques, which enable the understanding of the complex composition of biopolymers such as polyhydroxyalkanoates and poly(lactic acid). The former part of this review discusses the definition and examples of biopolymers, followed by the theory and instrumentation of analytical methods applicable to the analysis of biopolymers, such as physical methods (SEM, TEM, weighing analytical balance, etc.), chromatographic methods (GC, THM-GC, SEC/GPC), spectroscopic methods (NMR, FTIR, XRD, XRF), respirometric methods, thermal methods (DSC, DTA, TGA), and meta-analysis. Special focus is given to the chromatographic methods, because this is the routine method of polymer analysis. The aim of this review is to focus on the recent developments in the field of biopolymer analysis and instrument application to analyse the various types of biopolymers.
Polyurethane Foam Waste Upcycling into an Efficient and Low Pollutant Gasification Syngas
Authors: Hasanzadeh Rezgar , Mojaver Parisa , Khalilarya Shahram , Azdast Taher , Chitsaz Ata , Mojaver Mehran
Published: November 2022

Waste treatment has attracted much attention and, in this regard, gasification processes offer an efficient thermochemical technique that can produce a syngas rich in hydrogen. This technique has been well developed for solid waste and biomass while investigations on gasification of polymeric foam are rare. Therefore, this study explores the treatment of polyurethane foam waste with different gasifying agents, based on thermodynamic modeling. The polymeric foam gasification was developed using the best model for estimating higher heating value (gross calorific value). As the results indicated, models based on both ultimate and proximate analyses had better performance in predicting higher heating value. As one of the main objectives and novelties, the steam and air gasification performance of flexible and rigid polyurethane foam wastes was investigated and compared from efficiency and CO2 emission viewpoints. Polyurethane foam gasification by steam resulted in higher hydrogen efficiency, led to lower energy efficiency and produced lower CO2 emissions compared to gasification by air. A hydrogen efficiency of 41.4% was obtained for gasification of waste flexible polyurethane foam by steam. An energy efficiency of 76.6% and CO2 emission of 7.43 g per mole of feedstock were attained for waste flexible polyurethane foam gasified by air.
Mechanical Performance of Recycled Reinforced Polyamide from Rejected Railway Fastenings Flanged Plates
Authors: Diego Soraya , Casado Jose , Carrascal Isidro , Sainz-Aja Jose , Ferreño Diego
Published: November 2022

The superstructure of modern railway lines uses tons of technical polymeric material spread along the track with mechanical, insulating and damping functions. Many of these parts are rejected because they do not pass the quality controls, generating a large accumulation of plastic waste of high economic value. Therefore, this study is aimed at determining the optimum degree of recyclability by mechanical crushing of geometrically defective (and so rejected) railway fastenings flanged plates injected with short fiberglass-reinforced polyamide. After recycling, the material must guarantee its physical and mechanical properties required to ensure the future in-service conditions of the highly responsible components that guarantee the maintenance of the railway gauge. Viscosity, mechanical properties (tensile test), Charpy and fracture toughness as well as fatigue performance were determined for ten successive recyclings. It has been found that the drop of viscosity is the most restrictive limitation, allowing three recyclings of the material. All the properties measured have experienced a noticeable reduction after 10 recyclings. Specifically, viscosity is reduced by 15%, ultimate strength by 70%, yield stress by 41% strain under maximum load lost by 70%, Young’s modulus lost by 38%, Charpy impact strength by 70%, fatigue resistance by 69% and fracture toughness lost by 80%. With the development of this study and taking into account that the market price of the flanged plates is valued at approximately 8 k€/km, of which around 5 k€/km corresponds to the raw material, the recovery of this material not only represents a great environmental benefit but also an economic one.
The Functionalization of a Honeycomb Polystyrene Pattern by Excimer Treatment in Liquid
Authors: Slepička Petr , Siegel Jakub , Šlouf Miroslav , Fajstavr Dominik , Fajstavrová Klára , Kolská Zdeňka , Švorčík Václav
Published: November 2022

In this article, we present a unique combination of techniques focusing on the immobilization of noble metal nanoparticles into a honeycomb polystyrene pattern prepared with the improved phase-separation technique. The procedure consists of two main steps: the preparation of the honeycomb pattern (HCP) on a perfluoroethylenepropylene substrate (FEP), followed by an immobilization procedure realized by the honeycomb pattern’s exposure to an excimer laser in a noble metal nanoparticle solution. The surface physico-chemical properties, mainly the surface morphology and chemistry, are characterized in detail in the study. The two-step procedure represents the unique architecture of the surface immobilization process, which reveals a wide range of potential applications, mainly in tissue engineering, but also as substrates for analytical use.
Influence of the Type of Binder Used in the Treatment of Cotton Fabric with Montmorillonite Particles on the Release of Negative Ions
Authors: Carette Margaux , Gisbert-Payá Jaime , Capablanca Lucía , Bou-Belda Eva
Published: November 2022

Throughout history, mineral clays have had a multitude of applications. With recent developments in the textile industry, they have been used for their antimicrobial properties. As a promising phyllosilicate with a negative layer charge, montmorillonite (MMT) was used in this work to treat cotton fabric to evaluate its ability to generate negative air ions (NAIs). The MMT was dispersed with varying binder concentrations. Resins of different composition (polyurethane or acrylic) was applied to cotton fabric by padding, and the negative ion count was measured. Two types of MMT with different characteristics were tested. Electronic microscopy (SEM) was used to study the presence of MMT particles on the cotton fabric surface, and the colors of the samples were tested. It was observed that the composition of the binder used had a significant influence on the number of negative ions released by the treated sample.
The Applications of Ferulic-Acid-Loaded Fibrous Films for Fruit Preservation
Authors: Huang Xinyi , Jiang Wenlai , Zhou Jianfeng , Yu Deng-Guang , Liu Hui
Published: November 2022

The aim of this study was to develop a novel ultrathin fibrous membrane with a core–sheath structure as an antioxidant food packaging membrane. The core–sheath structure was prepared by coaxial electrospinning, and the release of active substances was regulated by its special structure. Ferulic acid (FA) was incorporated into the electrospun zein/polyethylene oxide ultrathin fibers to ensure their synergistic antioxidant properties. We found that the prepared ultrathin fibers had a good morphology and smooth surface. The internal structure of the fibers was stable, and the three materials that we used were compatible. For the different loading positions, it was observed that the core layer ferulic-acid-loaded fibers had a sustained action, while the sheath layer ferulic-acid-loaded fibers had a pre-burst action. Finally, apples were selected for packaging using fibrous membranes to simulate practical applications. The fibrous membrane was effective in reducing water loss and apple quality loss, as well as extending the shelf life. According to these experiments, the FA-loaded zein/PEO coaxial electrospinning fiber can be used as antioxidant food packaging and will also undergo more improvements in the future.
Smart Greenhouse Based on ANN and IOT
Authors: Tawfeek Medhat A. , Alanazi Saad , El-Aziz A. A. Abd
Published: November 2022

The effective exploitation of smart technology in applications helps farmers make better decisions without increasing costs. Agricultural Research Centers (ARCs) are continually updating and producing new datasets from applied research, so the smart model should dynamically address all surrounding agricultural variables and improve its expertise from all available datasets. This research concentrates on sustainable agriculture using Adaptive Particle Swarm Optimization (PSO) and Artificial Neural Networks (ANNs). Therefore, if a new related dataset is created, this new incoming dataset is merged with the existing dataset. The proposed PSO then bypasses the summarization of the dataset. It deletes the least essential and speculative records and keeps the records that are the most influential in the classification process. The summarized dataset is interposed in the training process without re-establishing the system again by modifying the classical ANN. The proposed ANN comprises an adaptive input layer and an adaptive output layer to handle the process of continuously updating the datasets. A comparative study between the proposed adaptive PSO-ANN and other known and used methods on different datasets has been applied. The results prove the quality of the proposed Adaptive PSO-ANN from various standard measurements. The proposed PSO-ANN achieved an accuracy of 94.8%, precision of 91.15%, recall of 97.93%, and F1-score of 94.42%. The smart olive cultivation case study is accomplished with the proposed adaptive PSO-ANN and technological tools from the Internet of Things (IoT). The advanced tools from IoT technology are established and analyzed to control all the required procedures of olive cultivation. This case study addresses the necessary fertilizers and irrigation water to adapt to the changes in climate. Empirical results show that smart olive cultivation using the proposed adaptive PSO-ANN and IoT has high quality and efficiency. The quality and efficiency are measured by diversified metrics such as crop production and consumed water, which confirm the success of the proposed smart olive agriculture method.
Special Issue on Recent Advances in Machine Learning and Applications
Authors: Wang Chien-Chih
Published: November 2022

Digital technologies for cyber-physical systems are rapidly advancing, and the ubiquity of the Internet of Things (IoT) has created significant challenges for academic, industrial, and service applications due to high dimensionality, noise contamination, incompleteness, inconsistency, and massive amounts of data [...]
Spiritual Experience and Parishioners Satisfaction in the Online Eucharist: A Latin American Case Study
Authors: Areiza-Padilla Jose Andres , Veas-González Iván , Galindo-Becerra Tatiana
Published: November 2022

This research contributes to the scarce literature that exists on the perception that Catholics have about the Eucharist online, which was continued through various digital platforms, but once the emergence of the COVID-19. In this way, the perception of Catholics is identified, regarding their spiritual experience, their satisfaction, and their intention to continue attending this type of religious practice in the future, but online. For this, a quantitative study was carried out through the PLS program with a sample of 1423 parishioners in the city of Bogotá, Colombia. Bearing in mind that Latin America has the largest number of Catholics in the world, the results of this study help the Catholic Church to generate possible strategies that can be developed in various parts of the world, to combine this type of religious services with the various virtual platforms.
Warrior Gods and Otherworldly Lands: Daoist Icons and Practices in Late Chosŏn Korea
Authors: Stiller Maya
Published: November 2022

This article brings Chosŏn dynasty (1392–1910) Korea into the discussion about the various roles of Daoism in East Asian cultures in which it has, unfortunately, all too often been absent. Based primarily on art-historical methodology and literary analysis, the article offers an overview of the many sorts of sources and materials that determine the perspectives we have of Daoism-related beliefs and concepts during the late Chosŏn. In contrast to earlier interpretations of Daoist practices as exclusively expressing a desire to retreat from public life, the materials discussed in this article advance a more subtle understanding of the pervasiveness of Daoism in late Chosŏn society, ranging from Daoist divination texts and rituals at religious shrines to the construction of artificial mountains for theater performances and the establishment of government office gardens that served as conduits for spiritual rejuvenation and display of cultural cachet.
From Positive to Idealistic: A Methodological Critique of Positive Psychology for Better Research on Idealistic Mentalities in Chinese Spiritual Traditions
Authors: Liu Yuchun , Dong Xintong , Zhao Haohao , Zhou Jingyi , Zeng Xianglong
Published: November 2022

Chinese spiritual traditions such as Buddhism, Confucianism, and Taoism all emphasize the cultivation of idealistic mentalities (IMs) which are (1) not yet achieved, (2) clear in value judgment, (3) systematic and stable, and (4) cultivated with systematic training. While IMs are of interest to positive psychology, the methodology of positive psychology limits research on IMs. Fundamentally, positive psychology focuses on widely existing positive concepts and emphasizes being value-free, which conflicts with the features of IMs. Positive psychological studies relevant to IMs also suffer from methodological limitations: (1) recruiting samples without a spiritual background (realistic assumption); (2) ignoring qualitative differences between levels of actualization of IMs (linear assumption); (3) dividing systematic mental patterns into separate elements (reductionism); and (4) lacking value clarification during interventions. In summary, this article illustrates the methodological limitations of positive psychology in research on IMs. It encourages further research on IMs and supports the necessity of developing a new idealistic psychology for better research on IMs.
A Review on the Use of Mobile Service Robots in Elderly Care
Authors: Asgharian Pouyan , Panchea Adina M. , Ferland François
Published: November 2022

Global demographics trend toward an aging population. Hence, there will be an increased social demand for elderly care. Recently, assistive technologies such as service robots have emerged and can help older adults to live independently. This paper reports a review starting from 1999 of the existing mobile service robots used for older adults to grow old at home. We describe each robot from the viewpoint of applications, platforms, and empirical studies. Studies reported that mobile social robots could assist older adults throughout their daily activities such as reminding, household tasks, safety, or health monitoring. Moreover, some of the reported studies indicate that mobile service robots can enhance the well-being of older adults and decrease the workload for their caregivers.
BoxPaste: An Effective Data Augmentation Method for SAR Ship Detection
Authors: Suo Zhiling , Zhao Yongbo , Chen Sheng , Hu Yili
Published: November 2022

Data augmentation is a crucial technique for convolutional neural network (CNN)-based object detection. Thus, this work proposes BoxPaste, a simple but powerful data augmentation method appropriate for ship detection in Synthetic Aperture Radar (SAR) imagery. BoxPaste crops ship objects from one SAR image using bounding box annotations and pastes them on another SAR image to artificially increase the object density in each training image. Furthermore, we dive deep into the characteristics of the SAR ship detection task and draw a principle for designing a SAR ship detector—light models may perform better. Our proposed data augmentation method and modified ship detector attain a 95.5% Average Precision (AP) and 96.6% recall on the SAR Ship Detection Dataset (SSDD), 4.7% and 5.5% higher than the fully convolutional one-stage (FCOS) object detection baseline method. Furthermore, we also combine our data augmentation scheme with two current detectors, RetinaNet and adaptive training sample selection (ATSS), to validate its effectiveness. The experimental results demonstrate that our newly proposed SAR-ATSS architecture achieves 96.3% AP, employing ResNet-50 as the backbone. The experimental results show that the method can significantly improve detection performance.
A 20-Year Climatology of Sea Ice Leads Detected in Infrared Satellite Imagery Using a Convolutional Neural Network
Authors: Hoffman Jay P. , Ackerman Steven A. , Liu Yinghui , Key Jeffrey R.
Published: November 2022

Sea ice leads, or fractures account for a small proportion of the Arctic Ocean surface area, but play a critical role in the energy and moisture exchanges between the ocean and atmosphere. As the sea ice area and volume in the Arctic has declined over the past few decades, changes in sea ice leads have not been studied as extensively. A recently developed approach uses artificial intelligence (AI) and satellite thermal infrared window data to build a twenty-year archive of sea ice lead detects with Moderate Resolution Imaging Spectroradiometer (MODIS) and later, an archive from Visible Infrared Imaging Radiometer Suite (VIIRS). The results are now available and show significant improvement over previously published methods. The AI method results have higher detection rates and a high level detection agreement between MODIS and VIIRS. Analysis over the winter season from 2002–2003 through to the 2021–2022 archive reveals lead detections have a small decreasing trend in lead area that can be attributed to increasing cloud cover in the Arctic. This work reveals that leads are becoming increasingly difficult to detect rather than less likely to occur. Although the trend is small and on the same order of magnitude as the uncertainty, leads are likely increasing at a rate of 3700 km2 per year with a range of uncertainty of 3500 km2 after the impact of cloud cover changes are removed.
Monitoring and Integrating the Changes in Vegetated Areas with the Rate of Groundwater Use in Arid Regions
Authors: Morsy Mona , Michaelides Silas , Scholten Thomas , Dietrich Peter
Published: November 2022

Frequent water table measurements are crucial for sustainable groundwater management in arid regions. Such monitoring is more important in areas that are already facing an acute problem with excessive groundwater withdrawal. In the majority of these locations, continuous readings of groundwater levels are lacking. Therefore, an approximate estimate of the rate of increase or decrease in water consumption over time may serve as a proxy for the missing data. This could be achieved by tracking the changes in vegetated areas that generally correlate with changes in the rate of water use. The technique proposed in this paper is based on two remote sensing datasets: Landsat 7 and 8 from 2001 to 2021, and Sentinel 2A from 2015 to 2021, as well as five vegetation indices: Normalized Difference Vegetation Index (NDVI), Renormalized Difference Vegetation Index (RDVI), Soil Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), and Transformed Vegetation Index (TVI). The findings have shown that the datasets chosen performed best for small-scale land farms at the research location, which was chosen to be the El-Qaa plain, in the southwestern corner of the Sinai Peninsula in Egypt. Landsat 7 data with a resolution of 30 m revealed a substantial increase in land farms from 2.9 km2 in 2001 to 23.3 km2 in 2021. By using the five indices based on Sentinel 2A data, vegetated areas were categorized as heavy, moderate, or light. In addition, the expansion of each class area from 2015 to 2021 was tracked. Additionally, the NDVI index was modified to better reflect the arid environment (subsequently naming this new index as the Arid Vegetation Index: AVI). Rough scenarios of the increase in water consumption rate at the research site were generated by observing the increase in vegetated areas and collecting rough information from the farmers regarding the crop types.
A Robust Track Error Estimation Method for Airborne SAR Based on Accuracy Analysis Model
Authors: Gao Ming , Qiu Xiaolan , Cheng Yao , Lv Junwei , Ding Chibiao
Published: November 2022

With the development of miniaturization technology, Synthetic Aperture Radar (SAR) can be equipped on small carriers such as small Unmanned Aerial Vehicles (UAVs). In order to lower the cost, the accuracy of navigation equipment carried by UAV SAR is usually limited, so it is challenging to meet the requirements of SAR imaging and locating accuracy. Therefore, accurately estimating SAR tracks becomes a crucial issue. So, for the motion error estimation model widely used in current literature, this paper derives the accuracy limits of the model for the first time. The derived Cramer–Rao Lower Bound (CRLB) specifies the factors affecting the estimation accuracy, which provides new insights into the estimation model. The in-depth analysis of how the factors affect CRLB can guide the setting of the parameters while using the estimation method. Moreover, based on the accuracy analysis model, this paper improves the WTLS-based autofocus method (WTA) by selecting the appropriate estimation kernel step. The proposed method can suppress noise more effectively and further ensure estimation accuracy compared to WTA. Airborne SAR data experiments in the high-resolution condition obtain trajectory estimation results of 0.02 m.
Reconstruction of Near-Surface Air Temperature over the Greenland Ice Sheet Based on MODIS Data and Machine Learning Approaches
Authors: Che Jiahang , Ding Minghu , Zhang Qinglin , Wang Yetang , Sun Weijun , Wang Yuzhe , Wang Lei , Huai Baojuan
Published: November 2022

High spatial and temporal resolution products of near-surface air temperature (T2m) over the Greenland Ice Sheet (GrIS) are required as baseline information in a variety of research disciplines. Due to the sparse network of in situ data on the GrIS, remote sensing data and machine learning methods provide great advantages, due to their capacity and accessibility. The Land Surface Temperature (LST) at 780 m resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) and T2m observation from 25 Automatic Weather Stations (AWSs) are used to establish a relationship over the GrIS by comparing multiple machine learning approaches. Four machine learning methods—neural network (NN), gaussian process regression (GPR), support vector machine (SVM), and random forest (RF)—are used to reconstruct the T2m at daily and monthly scales. We develop a reliable T2m reconstruction model based on key meteorological parameters, such as albedo, wind speed, and specific humidity. The reconstructions daily and monthly products are generated on a 780 m × 780 m spatial grid spanning from 2007 to 2019. When compared with in situ observations, the NN method presents the highest accuracy, with R of 0.96, RMSE of 2.67 °C, and BIAS of −0.36 °C. Similar to the regional climate model (RACMO2.3p2), the reconstructed T2m can better reflect the spatial pattern in term of latitude, longitude, and altitude effects.
Oceanic Eddy Detection and Analysis from Satellite-Derived SSH and SST Fields in the Kuroshio Extension
Authors: Cui Wei , Yang Jungang , Jia Yongjun , Zhang Jie
Published: November 2022

Vigorous mesoscale eddies are broadly distributed in the Kuroshio Extension and can generally be identified from sea surface height (SSH) and sea surface temperature (SST) fields. Nevertheless, the changes in SSH and SST caused by mesoscale eddies and their seasonal correlation in the Kuroshio Extension are not clear, as well as the difference between identified eddy results from the two data. Combining in situ Argo float profiles data, the correlation between SSH anomaly (SSHA) and SST anomaly (SSTA) signals in mesoscale eddies are analyzed. The result shows that SSTA–SSHA signals inside eddies are generally more correlated in winter than in summer. Argo subsurface temperature anomalies θ′ and SSHA signals inside eddies show a high correlation, with a regression coefficient θ′/SSHA of about 7 °C·m−1, while correlations of Argo θ′–SSTA inside eddies are low. Generally, the lifetime and propagation distance of SSTA-based eddies are shorter and smaller than those of SSHA-based eddies, which may be related to the rapid changes in SSTA field and the interference of small-scale oceanic signal in the SST field. Comparing with SSHA-based eddies, which exist primarily around the region of the Kuroshio mainstream (33°–36°N), SSTA-based eddies are concentrated in the Oyashio Extension (39°–42°N), where SST gradient is large, and changes in SST fields caused by mesoscale eddies are more obvious and more likely to be captured by satellites there. In addition, the geographical distributions of SSHA- and SSTA-based eddy amplitudes are consistent with the absolute dynamic topography and SST gradient.
Development of YOLOv5-Based Real-Time Smart Monitoring System for Increasing Lab Safety Awareness in Educational Institutions
Authors: Ali Luqman , Alnajjar Fady , Parambil Medha Mohan Ambali , Younes Mohammad Issam , Abdelhalim Ziad Ismail , Aljassmi Hamad
Published: November 2022

The term “smart lab” refers to a system that provides a novel and flexible approach to automating and connecting current laboratory processes. In education, laboratory safety is an essential component of undergraduate laboratory classes. The institution provides formal training for the students working in the labs that involve potential exposure to a wide range of hazards, including chemical, biological, and physical agents. During the laboratory safety lessons, the instructor explains the lab safety protocols and the use of personal protective equipment (PPE) to prevent unwanted accidents. However, it is not always guaranteed that students follow safety procedures throughout all lab sessions. Currently, the lab supervisors monitor the use of PPE, which is time consuming, laborious, and impossible to see each student. Consequently, students may unintentionally commit unrecognizable unsafe acts, which can lead to unwanted situations. Therefore, the aim of the research article was to propose a real-time smart vision-based lab-safety monitoring system to verify the PPE compliance of students, i.e., whether the student is wearing a mask, gloves, lab coat, and goggles, from image/video in real time. The YOLOv5 (YOLOv5l, YOLOv5m, YOLOv5n, YOLOv5s, and YOLOv5x) and YOLOv7 models were trained using a self-created novel dataset named SLS (Students Lab Safety). The dataset comprises four classes, namely, gloves, helmets, masks, and goggles, and 481 images, having a resolution of 835 × 1000, acquired from various research laboratories of the United Arab Emirates University. The performance of the different YOLOv5 and YOLOv7 versions is compared based on instances’ size using evaluation metrics such as precision, F1 score, recall, and mAP (mean average precision). The experimental results demonstrated that all the models showed promising performance in detecting PPE in educational labs. The YOLOv5n approach achieved the highest mAP of 77.40% for small and large instances, followed by the YOLOv5m model having a mAP of 75.30%. A report detailing each student’s PPE compliance in the lab can be prepared based on data collected in real time and stored in the proposed system. Overall, the proposed approach can be utilized to make laboratories smarter by enhancing the efficacy of safety in research settings; this, in turn, will aid the students in establishing a health and safety culture among students.
Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors
Authors: Wilson Aaron J. , Warmack Bruce R. J. , Ekti Ali Riza , Liu Yilu
Published: November 2022

The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.