bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial Activities against Opportunistic Pathogenic Bacteria Using Green Synthesized Silver Nanoparticles in Plant and Lichen Enzyme-Assisted Extracts
Authors: Balčiūnaitienė Aistė , Štreimikytė Paulina , Puzerytė Viktorija , Viškelis Jonas , Štreimikytė-Mockeliūnė Žaneta , Maželienė Žaneta , Sakalauskienė Vaidė , Viškelis Pranas
Published: July 2022

Enzyme-assisted extraction is a valuable tool for mild and environmentally-friendly extraction conditions to release bioactive compounds and sugars, essential for silver nanoparticle (AgNP) green synthesis as capping and reducing agents. In this research, plant and fungal kingdoms were selected to obtain the enzyme-assisted extracts, using green synthesized AgNPs. For the synthesis, pseudo-cereal Fagopyrum esculentum (F. esculentum) and lichen Certaria islandica (C. islandica) extracts were used as environmentally-friendly agents under heating in an aqueous solution. Raw and enzyme-assisted extracts of AgNPs were characterized by physicochemical, phytochemical, and morphological characteristics through scanning and transmission electron microscopy (SEM and TEM), as well as Fourier transform infrared spectroscopy (FTIR). The synthesized nanoparticles were spherical in shape and well dispersed, with average sizes ranging from 10 to 50 nm. This study determined the total phenolic content (TPC) and in vitro antioxidant activity in both materials by applying standard methods. The results showed that TPC, ABTS•+, FRAP, and DPPH• radical scavenging activities varied greatly in samples. The AgNPs derived from enzymatic hydrolyzed aqueous extracts C. islandica and F. esculentum exhibited higher antibacterial activity against the tested bacterial pathogens than their respective crude extracts. Results indicate that the extracts’ biomolecules covering the AgNPs may enhance the biological activity of silver nanoparticles and enzyme assistance as a sustainable additive to technological processes to achieve higher yields and necessary media components.
Agave Fructans in Oaxaca’s Emblematic Specimens: Agave angustifolia Haw. and Agave potatorum Zucc.
Authors: Márquez-López Ruth E. , Santiago-García Patricia Araceli , López Mercedes G.
Published: July 2022

Despite the recognition of Agave tequilana Weber var. Azul as raw material for producing tequila and obtaining prebiotics, there are other highly relevant Agave species in Mexico. Oaxaca contains a startlingly diverse range of Agave species; Agave angustifolia Haw. and Agave potatorum Zucc. are two classic specimens with great commercial potential. In this study, we examined the fructan fluctuation in these two species during their lifetime in the field (from 1 to 6 years old). First, we analyzed their morphological diversity based on vegetative characteristics. Subsequently, fructan extracts were analyzed by TLC, FT-IR, and HPAEC-PAD to identify carbohydrates. Multivariate analyses of the morphological parameters indicated a morphological divergence between the two species. Furthermore, we found that the concentration of simple carbohydrates and fructans, as well as the fructan DP, changed during plant development. Glucose, fructose, and fructooligosaccharides (FOS) were more abundant in A. potatorum, while A. angustifolia showed a greater amount of sucrose and fructans with a high DP. Fructan DP heatmaps were constructed using HPAEC-PAD profiles—the heatmaps were very helpful for establishing an easy correlation between age and the carbohydrate types present in the fructan extracts. This study is an important contribution to the agave fructan knowledge of the Mexican agave diversity.
Visible Foliar Injury and Ecophysiological Responses to Ozone and Drought in Oak Seedlings
Authors: Moura Barbara Baesso , Paoletti Elena , Badea Ovidiu , Ferrini Francesco , Hoshika Yasutomo
Published: July 2022

To verify the responses of visible foliar injury (VFI), we exposed seedlings of three oak species for 4.5 months in an open air facility, using differing ozone (O3) and drought treatments: O3 (three levels from ambient to ×1.4 ambient), and drought (three levels of irrigation from 40% to 100% field capacity). We related the accumulated phytotoxic O3 dose (POD1) and cumulative drought index (CDI) to the O3 and drought VFI and assessed growth increment (height, diameter, leaf number), biomass (of all organs), and physiological parameters: net photosynthesis per plant (Pn), photosynthetic nitrogen (PNUE) and phosphorus use efficiency (PPUE)). The results indicated that an increase in POD1 promoted O3 VFI in Quercus robur and Quercus pubescens, while Quercus ilex was asymptomatic. The POD1-based critical level at the onset of O3 VFI was lower for Q. robur than for Q. pubescens (12.2 vs. 15.6 mmol m−2 POD1). Interestingly, drought reduced O3 VFI in Q. robur but increased it in Q. pubescens. Both O3 and drought were detrimental to the plant biomass. However, Q. robur and Q. pubescens invested more in shoots than in roots, while Q. ilex invested more in roots, which might be related to a hormetic mechanism. Pn, PNUE and PPUE decreased in all species under drought, and only in the sensitive Q. robur (PPUE) and Q. pubescens (PNUE) under O3. This study confirms that POD1 is a good indicator to explain the development of O3 VFI and helps a differential diagnosis of co-occurring drought and O3 VFI in oak forests.
Development of Ethyl Methanesulfonate Mutant Edamame Soybean (Glycine max (L.) Merr.) Populations and Forward and Reverse Genetic Screening for Early-Flowering Mutants
Authors: Koshika Natsume , Shioya Naohiro , Fujimura Takashi , Oguchi Rina , Ota Chie , Kato Emi , Takahashi Reiko , Kimura Shuichi , Furuno Shinsuke , Saito Koichi , Okabe Kazuhiro , Watanabe Masanori , Hoshino Tomoki
Published: July 2022

Induced mutation is a viable breeding strategy that is widely utilized in the development of elite plant varieties. We aimed to improve a variety of edamame by constructing novel mutant populations using the ethyl methanesulfonate in soybeans (Glycine max (L.) Merr.). In the M2 population, the flowering stage showed a considerable standard deviation compared to the wild type, confirming that the mutant populations had the expected DNA mutations. To identify the DNA mutations in the mutant populations, we used the targeting induced local lesions in genomes (TILLING) method, which is a reverse genetic method, to search for soybean flowering-related gene mutants. A total of 30 mutants from E1, E3, E4, and PhyA1 genes, which are known to be highly effective genes, or their homologous gene for flowering and maturation found in soybean quantitative trait locus analyses were isolated from our TILLING screening. Among these mutants, there were eleven nonsynonymous substitution mutants, one nonsense mutant, and two single nucleotide deletion mutants that could be expected to reduce or eliminate gene function. The e1, e3, and e4 mutants obtained in this study flowered considerably earlier than the wild type. In particular, the e1 mutant with a nonsynonymous substitution flowered approximately 1 month after sowing regardless of the sowing date, and its harvest date was approximately 1 month earlier than that of the wild type. Mutations identified using the TILLING method could not only be used as gel-based DNA markers with the same manipulation method, but the mutations could also be detected as DNA markers by the high-resolution melting method. These results indicate that mutations achieved without chromosome modification by crossbreeding are effective for early and practical improvement of superior varieties and that efficient selection of mutants by reverse genetics is an effective method for the identification of genetic modifications. The edamame mutant populations developed in this study are believed to possess various useful alleles which may be applicable in the search for mutations that lead to improved edamame yield and eating quality beyond the flowering stage.
Adapting Agriculture to Climate Change: A Synopsis of Coordinated National Crop Wild Relative Seed Collecting Programs across Five Continents
Authors: Eastwood Ruth J. , Tambam Beri B. , Aboagye Lawrence M. , Akparov Zeynal I. , Aladele Sunday E. , Allen Richard , Amri Ahmed , Anglin Noelle L. , Araya Rodolfo , Arrieta-Espinoza Griselda , Asgerov Aydin , Awang Khadijah , Awas Tesfaye , Barata Ana Maria , Boateng Samuel Kwasi , Magos Brehm Joana , Breidy Joelle , Breman Elinor , Brenes Angulo Arturo , Burle Marília L. , Castañeda-Álvarez Nora P. , Casimiro Pedro , Chaves Néstor F. , Clemente Adelaide S. , Cockel Christopher P. , Davey Alexandra , De la Rosa Lucía , Debouck Daniel G. , Dempewolf Hannes , Dokmak Hiba , Ellis David , Faruk Aisyah , Freitas Cátia , Galstyan Sona , García Rosa M. , Ghimire Krishna H. , Guarino Luigi , Harker Ruth , Hope Roberta , Humphries Alan W. , Jamora Nelissa , Jatoi Shakeel Ahmad , Khutsishvili Manana , Kikodze David , Kyratzis Angelos C. , León-Lobos Pedro , Liu Udayangani , Mainali Ram P. , Mammadov Afig T. , Manrique-Carpintero Norma C. , Manzella Daniele , Mat Ali Mohd Shukri , Medeiros Marcelo B. , Mérida Guzmán María A. , Mikatadze-Pantsulaia Tsira , Mohamed El Tahir Ibrahim , Monteros-Altamirano Álvaro , Morales Aura , Müller Jonas V. , Mulumba John W. , Nersesyan Anush , Nóbrega Humberto , Nyamongo Desterio O. , Obreza Matija , Okere Anthony U. , Orsenigo Simone , Ortega-Klose Fernando , Papikyan Astghik , Pearce Timothy R. , Pinheiro de Carvalho Miguel A. A. , Prohens Jaime , Rossi Graziano , Salas Alberto , Singh Shrestha Deepa , Siddiqui Sadar Uddin , Smith Paul P. , Sotomayor Diego A. , Tacán Marcelo , Tapia César , Toledo Álvaro , Toll Jane , Vu Dang Toan , Vu Tuong Dang , Way Michael J. , Yazbek Mariana , Zorrilla Cinthya , Kilian Benjamin
Published: July 2022

The Adapting Agriculture to Climate Change Project set out to improve the diversity, quantity, and accessibility of germplasm collections of crop wild relatives (CWR). Between 2013 and 2018, partners in 25 countries, heirs to the globetrotting legacy of Nikolai Vavilov, undertook seed collecting expeditions targeting CWR of 28 crops of global significance for agriculture. Here, we describe the implementation of the 25 national collecting programs and present the key results. A total of 4587 unique seed samples from at least 355 CWR taxa were collected, conserved ex situ, safety duplicated in national and international genebanks, and made available through the Multilateral System (MLS) of the International Treaty on Plant Genetic Resources for Food and Agriculture (Plant Treaty). Collections of CWR were made for all 28 targeted crops. Potato and eggplant were the most collected genepools, although the greatest number of primary genepool collections were made for rice. Overall, alfalfa, Bambara groundnut, grass pea and wheat were the genepools for which targets were best achieved. Several of the newly collected samples have already been used in pre-breeding programs to adapt crops to future challenges.
Cassava Frogskin Disease: Current Knowledge on a Re-Emerging Disease in the Americas
Authors: Pardo Juan Manuel , Alvarez Elizabeth , Becerra Lopez-Lavalle Luis Augusto , Olaya Cristian , Leiva Ana Maria , Cuellar Wilmer Jose
Published: July 2022

Cassava frogskin disease (CFSD) is a graft-transmissible disease of cassava reported for the first time in the 1970s, in Colombia. The disease is characterized by the formation of longitudinal lip-like fissures on the peel of the cassava storage roots and a progressive reduction in fresh weight and starch content. Since its first report, different pathogens have been identified in CFSD-affected plants and improved sequencing technologies have unraveled complex mixed infections building up in plants with severe root symptoms. The re-emergence of the disease in Colombia during 2019–2020 is again threatening the food security of low-income farmers and the growing local cassava starch industry. Here, we review some results obtained over several years of CFSD pathology research at CIAT, and provide insights on the biology of the disease coming from works on symptoms’ characterization, associated pathogens, means of transmission, carbohydrate accumulation, and management. We expect this work will contribute to a better understanding of the disease, which will reflect on lowering its impact in the Americas and minimize the risk of its spread elsewhere.
Recent Advances in the Interfacial Shear and Dilational Rheology of Polymer Systems: From Fundamentals to Applications
Authors: El Omari Younes , Yousfi Mohamed , Duchet-Rumeau Jannick , Maazouz Abderrahim
Published: July 2022

The study of the viscoelastic properties of polymer systems containing huge internal two-dimensional interfacial areas, such as blends, foams and multilayer films, is of growing interest and plays a significant role in a variety of industrial fields. Hence, interfacial rheology can represent a powerful tool to directly investigate these complex polymer–polymer interfaces. First, the current review summarizes the theoretical basics and fundamentals of interfacial shear rheology. Particular attention has been devoted to the double-wall ring (DWR), bicone, Du Noüy ring and oscillating needle (ISR) systems. The measurement of surface and interfacial rheological properties requires a consideration of the relative contributions of the surface stress arising from the bulk sub-phases. Here, the experimental procedures and methodologies used to correct the numerical data are described considering the viscoelastic nature of the interface. Second, the interfacial dilational rheology is discussed, starting with the theory and underlying principles. In particular, the Langmuir trough method, the oscillating spinning drop technique and the oscillating pendant drop technique are investigated. The major pioneering studies and latest innovations dedicated to interfacial rheology in both shear and dilatation–compression are highlighted. Finally, the major challenges and limits related to the development of high-temperature interfacial rheology at the molten state are presented. The latter shows great potential for assessing the interfaces of polymer systems encountered in many high-value applications.
Starch-Based Hydrogel Nanoparticles Loaded with Polyphenolic Compounds of Moringa Oleifera Leaf Extract Have Hepatoprotective Activity in Bisphenol A-Induced Animal Models
Authors: Abou El-Naga Hend Mohamed Hasanin , El-Hashash Samah A. , Yasen Ensaf Mokhtar , Leporatti Stefano , Hanafy Nemany A. N.
Published: July 2022

Bisphenol A (BPA) is an xenoestrogenic chemical used extensively in the fabrication of baby bottles, reusable plastic water bottles and polycarbonate plastic containers. The current study aims to investigate the hepatoprotective activity of Moringa oleifera Lam leaf extract (MOLE) and hydrogel NPs made of starch-MOLE-Bovine Serum Albumin (BSA) against Bisphenol A-induced liver toxicity in male rats. Fabrication and characterization of hydrogel NPs formed of starch-MOLE-BSA were investigated using FTIR, TEM, zeta potential, UV-visible spectroscopy and fluorescence spectrophotometer. The potential efficacy of hydrogel NPs was studied. Compared to the results of control, the level of liver function, oxidative stress markers and lipid profile status were remodulated in the groups treated with MOLE and hydrogel NPs (Encap. MOLE). Meanwhile, the administration of MOLE and Encap MOLE significantly increased antioxidant activity and decreased the level of apoptotic pathways. Heme oxygenase (HO)-1 and growth arrest -DNA damage-inducible gene 45b (Gadd45b) were also regulated in the groups treated with MOLE and Encap. MOLE compared to the group which received BPA alone. In the present study, MOLE and hydrogel NPs led to remarkable alterations in histological changes during BPA administration. Overall, MOLE has a potential antioxidant activity which can be used in the treatment of liver disorders.
Free-Radical Photopolymerization for Curing Products for Refinish Coatings Market
Authors: Ribas-Massonis Aina , Cicujano Magalí , Duran Josep , Besalú Emili , Poater Albert
Published: July 2022

Even though there are many photocurable compositions that are cured by cationic photopolymerization mechanisms, UV curing generally consists of the formation of cross-linking covalent bonds between a resin and monomers via a photoinitiated free radical polymerization reaction, obtaining a three-dimensional polymer network. One of its many applications is in the refinish coatings market, where putties, primers and clear coats can be cured faster and more efficiently than with traditional curing. All these products contain the same essential components, which are resin, monomers and photoinitiators, the latter being the source of free radicals. They may also include additives used to achieve a certain consistency, but always taking into account the avoidance of damage to the UV curing—for example, by removing light from the innermost layers. Surface curing also has its challenges since it can be easily inhibited by oxygen, although this can be solved by adding scavengers such as amines or thiols, able to react with the otherwise inactive peroxy radicals and continue the propagation of the polymerization reaction. In this review article, we cover a broad analysis from the organic point of view to the industrial applications of this line of research, with a wide current and future range of uses.
Anion Exchange Membranes for Fuel Cells Based on Quaternized Polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene Triblock Copolymers with Spacer-Sidechain Design
Authors: Chen Qun-Gao , Lee Ming-Tsung
Published: July 2022

This work studied the polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS) triblock copolymers functionalized by butyl quaternary ammonium (C4Q) groups and alkyl side chains of different chain lengths (Cn, n = 0 to 24). The hydrated membrane morphology was modeled by dissipative particle dynamics simulation at hydration levels from 10 to 30. A hydroxide model was devised to characterize the diffusivity of anions under the coarse-grained framework. In general, the ionomers with alkyl side chains provided ion conductivity of a similar level at a lower ion exchange capacity. All hydrated SEBS–C4Q–Cn ionomers showed clear phase separation of the hydrophobic and hydrophilic domains, featuring 18.6 mS/cm to 36.8 mS/cm ion conductivity. The hydrophilic channels expanded as the water content increased, forming more effective ion conductive pathways. Introducing excess alkyl side chains enhanced the nano-segregation, leading to more ordered structures and longer correlation lengths of the aqueous phase. The membrane morphology was controlled by the length of alkyl side-chains as well as their tethering positions. Ionomers with functionalized side chains tethered on the same block resulted in well-connective water networks and higher conductivities. The detailed structural analysis provides synthesis guidelines to fabricate anion exchange membranes with improved performances.
Sustainable Development Processes for Renewable Energy Technology
Authors: Zhironkin Sergey , Rybár Radim
Published: July 2022

Currently, the production of energy from traditional fossil sources is beginning to give way to renewable energy technologies [...]
Ergonomic Risk Minimization in the Portuguese Wine Industry: A Task Scheduling Optimization Method Based on the Ant Colony Optimization Algorithm
Authors: Freitas António Agrela , Lima Tânia Miranda , Gaspar Pedro Dinis
Published: July 2022

In the wine industry, task planning is based on decision-making processes that are influenced by technical and organizational constraints as well as regulatory limitations. A characteristic constraint inherent to this sector concerns occupational risks, in which companies must reduce and mitigate work-related accidents, resulting in lower operating costs and a gain in human, financial, and material efficiency. This work proposes a task scheduling optimization model using a methodology based on the ant colony optimization approach to mitigate the ergonomic risks identified in general winery production processes by estimating the metabolic energy expenditure during the execution of tasks. The results show that the tasks were reorganized according to their degree of ergonomic risk, preserving an acceptable priority sequence of tasks with operational affinity and satisfactory efficiency from the point of view of the operationalization of processes, while the potential ergonomic risks are simultaneously minimized by the rotation and alternation of operative teams between those tasks with higher and lower values of metabolic energy required. We also verified that tasks with lower ergonomic-load requirements influence the reorganization of the task sequence by lowering the overall value of metabolic energy, which is reflected in the reduction of the ergonomic load.
Post-Tridentine Mass Attendance as Devotion to the Suffering Christ
Authors: von Achen Henrik
Published: July 2022

Continuing the long tradition of the allegorical interpretation of the Mass, the seventeenth- and eighteenth century ideal of proper mass attendance was devotion to the suffering Christ, inextricably linked to each step of the liturgy. In this article, post-Tridentine mass books, booklets, or chapters on the mass in devotional books for lay people, are investigated to understand the praxis pietatis in which they were embedded. These texts served devotional and educational purposes outside mass as well, but primarily they reveal a concerted effort to promote active participation of lay people at mass. In the post-Tridentine era, the mass books for lay people became a kind of Passional, serving active participation of the faithful at mass as a devotional practice configured to the actions of the priest as mass progressed. Joining Ordo and Passion, the mass books combined two dimensions of the one sacrifice with the main objective being to support a heartfelt, attentive focus on both. Based on the mass books and other devotional texts investigated, no sharp distinction can be made between attending the formal liturgy and engaging in a devotional practice as the Passion narrative unfolded in, and by, the actions of the priest.
Studying Jewish Meditative Techniques: A Phenomenological Typology and an Interdisciplinary View
Authors: Persico Tomer
Published: July 2022

The field of mystical and meditative research lacks a basic typology delineating the varied genres and characteristics of the mystical experience and of the meditative practices that may be correlated to those. Such a state hinders the comparative study of mysticism and meditation through different philosophical, religious and spiritual traditions, or along the chronological development in a single tradition. In this article, I introduce phenomenological typological tools developed in a previous monograph dealing with the Jewish meditative tradition and illustrate how these can be used to analyze the adjustments and the variations between previous and contemporary Jewish mystics, through examining the four different types of mystical experience and five different characteristics of meditative techniques.
Neighborhood-Scale Urban Water Reclamation with Integrated Resource Recovery for Establishing Nexus City in Munich, Germany: Pipe Dream or Reality?
Authors: Al-Azzawi Mohammed S. M. , Gondhalekar Daphne , Drewes Jörg E.
Published: July 2022

With the rapid expansion of cities due to population growth and urbanization, conventional centralized wastewater collection and treatment systems are slowly becoming a burden; expensive maintenance is required for aging plants and piping infrastructure, the cost of expanding the capacity to cover demand from population growth, and new regulations for tighter control over certain pollutants such as micropollutants. As an alternative to this system, this study discusses the feasibility of decentralized treatment systems at the neighborhood scale. Taking a Water-Energy-Food (WEF) Nexus approach, such systems can support water and energy conservation, recovery of water, energy, and nutrients as well as generation of energy from wastewater, be customized to individual water and energy requirements, and eliminate the need for lengthy pipe networks. The method employed in this study is comparing the economic feasibility of the status quo to a proposed decentralized solution. The study finds that the costs of implementing a hypothetical decentralized water reclamation with an integrated resource recovery system using an anaerobic membrane bioreactor (AnMBR) in a downtown high-density neighborhood of the city of Munich, Germany, can theoretically be recuperated within two years. This alternative system may cost 60% of what it costs to run the centralized system. By linking the AnMBR to a biogas digestor and using systematically harvested organic waste as a co-substrate, the decentralized system can generate enough energy to run itself and even feed some energy to the grid. This study is highly hypothetical, yet generating evidence such as this can support a systemic socio-technical transition towards a more circular economy with optimal resource recovery.
A New Systematic Framework for Optimization of Multi-Temporal Terrestrial LiDAR Surveys over Complex Gully Morphology
Authors: Domazetović Fran , Šiljeg Ante , Marić Ivan , Panđa Lovre
Published: July 2022

Terrestrial LiDAR scanning (TLS) has in preceding years emerged as one of the most accurate and reliable geospatial methods for the creation of very-high resolution (VHR) models over gullies and other complex geomorphic features. Rough terrain morphology and rapid erosion induced spatio-temporal changes (STCs) can lead to significant challenges in multi-temporal field TLS surveys. In this study, we present a newly developed systematic framework for the optimization of multi-temporal terrestrial LiDAR surveys through the implementation of thorough systematic pre-survey planning and field preparation phases. The developed systematic framework is aimed at increase of accuracy and repeatability of multi-temporal TLS surveys, where optimal TLS positions are determined based on visibility analysis. The whole process of selection of optimal TLS positions was automated with the developed TLS positioning tool (TPT), which allows the user to adjust the parameters of visibility analysis to local terrain characteristics and the specifications of available terrestrial laser scanners. Application and validation of the developed framework were carried out over the gully Santiš (1226.97 m2), located at Pag Island (Croatia). Eight optimal TLS positions were determined by the TPT tool, from which planned coverage included almost 97% of the whole gully area and 99.10% of complex gully headcut morphology. In order to validate the performance of the applied framework, multi-temporal TLS surveys were carried out over the gully Santiš in December 2019 and 2020 using the Faro Focus M70 TLS. Field multi-temporal TLS surveys have confirmed the accuracy and reliability of the developed systematic framework, where very-high coverage (>95%) was achieved. Shadowing effects within the complex overhangs in the gully headcut and deeply incised sub-channels were successfully minimalized, thus allowing accurate detection and quantification of erosion induced STCs. Detection of intensive erosion induced STCs within the observed one-year period was carried out for the chosen part of the gully headcut. Most of the detected STCs were related to the mass collapse and gradual uphill retreat of the headcut, where in total 2.42 m2 of soil has been eroded. The developed optimization framework has significantly facilitated the implementation of multi-temporal TLS surveys, raising both their accuracy and repeatability. Therefore, it has great potential for further application over gullies and other complex geomorphic features where accurate multi-temporal TLS surveys are required for monitoring and detection of different STCs.
Cloud Removal with SAR-Optical Data Fusion and Graph-Based Feature Aggregation Network
Authors: Chen Shanjing , Zhang Wenjuan , Li Zhen , Wang Yuxi , Zhang Bing
Published: July 2022

In observations of Earth, the existence of clouds affects the quality and usability of optical remote sensing images in practical applications. Many cloud removal methods have been proposed to solve this issue. Among these methods, synthetic aperture radar (SAR)-based methods have more potential than others because SAR imaging is hardly affected by clouds, and can reflect ground information differences and changes. While SAR images used as auxiliary information for cloud removal may be blurred and noisy, the similar non-local information of spectral and electromagnetic features cannot be effectively utilized by traditional cloud removal methods. To overcome these weaknesses, we propose a novel cloud removal method using SAR-optical data fusion and a graph-based feature aggregation network (G-FAN). First, cloudy optical images and contemporary SAR images are concatenated and transformed into hyper-feature maps by pre-convolution. Second, the hyper-feature maps are inputted into the G-FAN to reconstruct the missing data of the cloud-covered area by aggregating the electromagnetic backscattering information of the SAR image, and the spectral information of neighborhood and non-neighborhood pixels in the optical image. Finally, post-convolution and a long skip connection are adopted to reconstruct the final predicted cloud-free images. Both the qualitative and quantitative experimental results from the simulated data and real data experiments show that our proposed method outperforms traditional deep learning methods for cloud removal.
Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC
Authors: Hall Kashawn , Daley Alton , Whitehall Shanice , Sandiford Sanola , Gentemann Chelle L.
Published: July 2022

The 2020 ‘Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere’ (EUREC4A-OA) and the ‘Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign’ (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.
Column-Spatial Correction Network for Remote Sensing Image Destriping
Authors: Li Jia , Zeng Dan , Zhang Junjie , Han Jungong , Mei Tao
Published: July 2022

The stripe noise in the multispectral remote sensing images, possibly resulting from the instrument instability, slit contamination, and light interference, significantly degrades the imaging quality and impairs high-level visual tasks. The local consistency of homogeneous region in striped images is damaged because of the different gains and offsets of adjacent sensors regarding the same ground object, which leads to the structural characteristics of stripe noise. This can be characterized by the increased differences between columns in the remote sensing image. Therefore, the destriping can be viewed as a process of improving the local consistency of homogeneous region and the global uniformity of whole image. In recent years, convolutional neural network (CNN)-based models have been introduced to destriping tasks, and have achieved advanced results, relying on their powerful representation ability. Therefore, to effectively leverage both CNNs and the structural characteristics of stripe noise, we propose a multi-scaled column-spatial correction network (CSCNet) for remote sensing image destriping, in which the local structural characteristic of stripe noise and the global contextual information of the image are both explored at multiple feature scales. More specifically, the column-based correction module (CCM) and spatial-based correction module (SCM) were designed to improve the local consistency and global uniformity from the perspectives of column correction and full image correction, respectively. Moreover, a feature fusion module based on the channel attention mechanism was created to obtain discriminative features derived from different modules and scales. We compared the proposed model against both traditional and deep learning methods on simulated and real remote sensing images. The promising results indicate that CSCNet effectively removes image stripes and outperforms state-of-the-art methods in terms of qualitative and quantitative assessments.
Empowering People with a User-Friendly Wearable Platform for Unobtrusive Monitoring of Vital Physiological Parameters
Authors: Krizea Maria , Gialelis John , Protopsaltis Grigoris , Mountzouris Christos , Theodorou Gerasimos
Published: July 2022

Elderly people feel vulnerable especially after they are dismissed from health care facilities and return home. The purpose of this work was to alleviate this sense of vulnerability and empower these people by giving them the opportunity to unobtrusively record their vital physiological parameters. Bearing in mind all the parameters involved, we developed a user-friendly wrist-wearable device combined with a web-based application, to adequately address this need. The proposed compilation obtains the photoplethysmogram (PPG) from the subject’s wrist and simultaneously extracts, in real time, the physiological parameters of heart rate (HR), blood oxygen saturation (SpO2) and respiratory rate (RR), based on algorithms embedded on the wearable device. The described process is conducted solely within the device, favoring the optimal use of the available resources. The aggregated data are transmitted via Wi-Fi to a cloud environment and stored in a database. A corresponding web-based application serves as a visualization and analytics tool, allowing the individuals to catch a glimpse of their physiological parameters on a screen and share their digital information with health professionals who can perform further processing and obtain valuable health information.
A New Conformal Map for Polynomial Chaos Applied to Direction-of-Arrival Estimation via UCA Root-MUSIC
Authors: Van Brandt Seppe , Verhaevert Jo , Van Hecke Tanja , Rogier Hendrik
Published: July 2022

The effects of random array deformations on Direction-of-Arrival (DOA) estimation with root-Multiple Signal Classification for uniform circular arrays (UCA root-MUSIC) are characterized by a conformally mapped generalized Polynomial Chaos (gPC) algorithm. The studied random deformations of the array are elliptical and are described by different Beta distributions. To successfully capture the erratic deviations in DOA estimates that occur at larger deformations, specifically at the edges of the distributions, a novel conformal map is introduced, based on the hyperbolic tangent function. The application of this new map is compared to regular gPC and Monte Carlo sampling as a reference. A significant increase in convergence rate is observed. The numerical experiments show that the UCA root-MUSIC algorithm is robust to the considered array deformations, since the resulting errors on the DOA estimates are limited to only 2 to 3 degrees in most cases.
Measurement and Control of Radially Polarized THz Radiation from DC-Biased Laser Plasma Filaments in Air
Authors: Han Bonan , Chen Yanping , Xia Tianhao , Wang Linzheng , Wang Chen , Sheng Zhengming
Published: July 2022

Detection and manipulation of radially polarized terahertz (THz) radiation is essential for many applications. A new measurement scheme is proposed for the diagnosis of radially polarized THz radiation from a longitudinal dc-biased plasma filament, by introducing a movable metal mask. The amplitude and spectrum of the radially polarized THz beam was measured with a <110>-cut ZnTe crystal, where the THz beam pattern was modulated by the mask. Based on this measurement scheme, it was demonstrated that the amplitude and spectrum of the radially polarized THz radiation from the longitudinal dc-biased filament could be manipulated by controlling the strength and the location of the dc-biased field.
TactCube: An Intelligent Device to ‘converse’ with Smart Environments
Authors: Battistoni Pietro , Di Gregorio Marianna , Romano Marco , Sebillo Monica , Vitiello Giuliana
Published: July 2022

Ambient Intelligence is a vision of daily life in which intelligent devices interact with humans to make their lives easier, and the technology is invisible. Artificial Intelligence (AI) governs this smart environment and must interact with humans to best meet their needs and demands. Although voice assistants are very popular and efficient as conversational AI, under some conditions they cannot be used. Therefore, this work proposed a complementary tactile and tangible interface to converse with AI, creating new Tactile Signs. A prototype of TactCube, a wireless cube-shaped device that can interact with AI using only the tactile sense, is presented. The hypothesis is that TactCube can be manipulated with one hand and generate a sequence of numbers that can be interpreted as a new tactile language by a neural network solution. The paper describes the initial research made to define how these sequences can be generated and demonstrates how TactCube is able to do it.
On the Prediction of In Vitro Arginine Glycation of Short Peptides Using Artificial Neural Networks
Authors: Que-Salinas Ulices , Martinez-Peon Dulce , Reyes-Figueroa Angel D. , Ibarra Ivonne , Scheckhuber Christian Quintus
Published: July 2022

One of the hallmarks of diabetes is an increased modification of cellular proteins. The most prominent type of modification stems from the reaction of methylglyoxal with arginine and lysine residues, leading to structural and functional impairments of target proteins. For lysine glycation, several algorithms allow a prediction of occurrence; thus, making it possible to pinpoint likely targets. However, according to our knowledge, no approaches have been published for predicting the likelihood of arginine glycation. There are indications that arginine and not lysine is the most prominent target for the toxic dialdehyde. One of the reasons why there is no arginine glycation predictor is the limited availability of quantitative data. Here, we used a recently published high–quality dataset of arginine modification probabilities to employ an artificial neural network strategy. Despite the limited data availability, our results achieve an accuracy of about 75% of correctly predicting the exact value of the glycation probability of an arginine–containing peptide without setting thresholds upon whether it is decided if a given arginine is modified or not. This contribution suggests a solution for predicting arginine glycation of short peptides.
Modeling Subjective Affect Annotations with Multi-Task Learning
Authors: Hayat Hassan , Ventura Carles , Lapedriza Agata
Published: July 2022

In supervised learning, the generalization capabilities of trained models are based on the available annotations. Usually, multiple annotators are asked to annotate the dataset samples and, then, the common practice is to aggregate the different annotations by computing average scores or majority voting, and train and test models on these aggregated annotations. However, this practice is not suitable for all types of problems, especially when the subjective information of each annotator matters for the task modeling. For example, emotions experienced while watching a video or evoked by other sources of content, such as news headlines, are subjective: different individuals might perceive or experience different emotions. The aggregated annotations in emotion modeling may lose the subjective information and actually represent an annotation bias. In this paper, we highlight the weaknesses of models that are trained on aggregated annotations for modeling tasks related to affect. More concretely, we compare two generic Deep Learning architectures: a Single-Task (ST) architecture and a Multi-Task (MT) architecture. While the ST architecture models single emotional perception each time, the MT architecture jointly models every single annotation and the aggregated annotations at once. Our results show that the MT approach can more accurately model every single annotation and the aggregated annotations when compared to methods that are directly trained on the aggregated annotations. Furthermore, the MT approach achieves state-of-the-art results on the COGNIMUSE, IEMOCAP, and SemEval_2007 benchmarks.
An Ensemble Approach to Predict Early-Stage Diabetes Risk Using Machine Learning: An Empirical Study
Authors: Laila Umm e , Mahboob Khalid , Khan Abdul Wahid , Khan Faheem , Taekeun Whangbo
Published: July 2022

Diabetes is a long-lasting disease triggered by expanded sugar levels in human blood and can affect various organs if left untreated. It contributes to heart disease, kidney issues, damaged nerves, damaged blood vessels, and blindness. Timely disease prediction can save precious lives and enable healthcare advisors to take care of the conditions. Most diabetic patients know little about the risk factors they face before diagnosis. Nowadays, hospitals deploy basic information systems, which generate vast amounts of data that cannot be converted into proper/useful information and cannot be used to support decision making for clinical purposes. There are different automated techniques available for the earlier prediction of disease. Ensemble learning is a data analysis technique that combines multiple techniques into a single optimal predictive system to evaluate bias and variation, and to improve predictions. Diabetes data, which included 17 variables, were gathered from the UCI repository of various datasets. The predictive models used in this study include AdaBoost, Bagging, and Random Forest, to compare the precision, recall, classification accuracy, and F1-score. Finally, the Random Forest Ensemble Method had the best accuracy (97%), whereas the AdaBoost and Bagging algorithms had lower accuracy, precision, recall, and F1-scores.
A Bio-Inspired Endogenous Attention-Based Architecture for a Social Robot
Authors: Marques-Villarroya Sara , Castillo Jose Carlos , Gamboa-Montero Juan José , Sevilla-Salcedo Javier , Salichs Miguel Angel
Published: July 2022

A robust perception system is crucial for natural human–robot interaction. An essential capability of these systems is to provide a rich representation of the robot’s environment, typically using multiple sensory sources. Moreover, this information allows the robot to react to both external stimuli and user responses. The novel contribution of this paper is the development of a perception architecture, which was based on the bio-inspired concept of endogenous attention being integrated into a real social robot. In this paper, the architecture is defined at a theoretical level to provide insights into the underlying bio-inspired mechanisms and at a practical level to integrate and test the architecture within the complete architecture of a robot. We also defined mechanisms to establish the most salient stimulus for the detection or task in question. Furthermore, the attention-based architecture uses information from the robot’s decision-making system to produce user responses and robot decisions. Finally, this paper also presents the preliminary test results from the integration of this architecture into a real social robot.
Electrochemical Synthesis of Reduced Graphene Oxide/Gold Nanoparticles in a Single Step for Carbaryl Detection in Water
Authors: Albalawi Ibtihaj , Alatawi Hanan , Alsefri Samia , Moore Eric
Published: July 2022

In this study, an in situ synthesis approach based on electrochemical reduction and ion exchange was employed to detect carbaryl species using a disposable, screen-printed carbon electrode fabricated with nanocomposite materials. Reduced graphene oxide (rGO) was used to create a larger electrode surface and more active sites. Gold nanoparticles (AuNPs,) were incorporated to accelerate electron transfer and enhance sensitivity. A cation exchange Nafion polymer was used to enable the adhesion of rGO and AuNPs to the electrode surface and speed up ion exchange. Cyclic voltammetry (CV), energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), electrical impedance spectroscopy (EIS), atomic force microscopy (AFM) and scanning electron microscopy (SEM) were performed to study the electrochemical and physical properties of the modified sensor. In the presence of differential pulse voltammetry (DPV), an rGO/AuNP/Nafion-modified electrode was effectively used to measure the carbaryl concentration in river and tap water samples. The developed sensor exhibited superior electrochemical performance in terms of reproducibility, stability, efficiency and selectivity for carbaryl detection with a detection limit of 0.2 µM and a concentration range between 0.5µM and 250 µM. The proposed approach was compared to capillary electrophoresis with ultraviolet detection (CE-UV).
The Real Deal: A Qualitative Investigation of Authentic Leadership in Irish Primary School Leaders
Authors: Lynch Jemma , Daly Dympna , Lafferty Niamh , Mannix McNamara Patricia
Published: July 2022

Recognition of the importance of authentic leadership is growing in popularity amonleadership scholars. However, little remains known about how it is valued or received among practicing school leaders. The purpose of this research was to explore the perspectives and experiences of school leaders with reference to authentic leadership in Irish primary school leaders. As this is a scoping study, a qualitative research design was adopted, using semi-structured interviews with school leaders. Core traits of self-awareness, balanced processing, relational transparency and internalized perspectives, that are associated with authentic leadership emerged as important for those interviewed. Barriers and facilitators of authentic leadership were also identified including educational policy, procedures and school culture.